Ben Map Manual Oct 2012

October 2012

Prepared forOffice of Air Quality Planning and Standards

U.S. Environmental Protection Agency Research Triangle Park, NCNeal Fann, Project Manager

Prepared byAbt Associates Inc.

User's Manual

October 20122

BenMAP User's Manual

Table of Contents

1 Welcome to BenMAP 6

................................................................................................................................... 81.1 Overview of BenMAP & Benefits Assessment

................................................................................................................................... 101.2 How to Use this Manual

................................................................................................................................... 111.3 Computer Requirements

................................................................................................................................... 121.4 Installing BenMAP

.......................................................................................................................................................... 14Upgrading to a new version of BenMAP 1.4.1

................................................................................................................................... 141.5 Uninstalling BenMAP

................................................................................................................................... 151.6 Contacts for Comments, Questions & Bug Reporting

................................................................................................................................... 161.7 Sources for More Information

................................................................................................................................... 171.8 Frequently Asked Questions (General)

2 Terminology and File Types 22

................................................................................................................................... 232.1 Common Terms

................................................................................................................................... 312.2 File Types

3 Overview of BenMAP Components 33

................................................................................................................................... 353.1 One-Step Analysis

.......................................................................................................................................................... 36One-Step Reports 3.1.1

.......................................................................................................................................................... 39Questions Regarding the One-Step Analysis 3.1.2

................................................................................................................................... 433.2 Custom Analysis

.......................................................................................................................................................... 43Create Air Quality Grids 3.2.1

.......................................................................................................................................................... 44Create and Run Configuration 3.2.2

.......................................................................................................................................................... 46Aggregation, Pooling, and Valuation 3.2.3

.......................................................................................................................................................... 49Generate Reports 3.2.4

................................................................................................................................... 523.3 Menus

.......................................................................................................................................................... 52Tools 3.3.1

4 Loading Data 55

................................................................................................................................... 564.1 Add, Modify, and Delete Setups

.......................................................................................................................................................... 58Grid Definitions 4.1.1

......................................................................................................................................................... 60Regular Grid

......................................................................................................................................................... 62Shapefile Grid

.......................................................................................................................................................... 63Pollutants 4.1.2

......................................................................................................................................................... 66Hourly Metrics

......................................................................................................................................................... 70Seasonal Metrics

......................................................................................................................................................... 72Advanced Pollutant Options

.......................................................................................................................................................... 73Monitor Data 4.1.3

......................................................................................................................................................... 76Format Monitor Data

.......................................................................................................................................................... 79Incidence/Prevalence Data 4.1.4

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October 20123


......................................................................................................................................................... 82Format Incidence/Prevalence Data

.......................................................................................................................................................... 83Population Data 4.1.5

......................................................................................................................................................... 90Format Population Data

.......................................................................................................................................................... 91Health Impact Functions 4.1.6

......................................................................................................................................................... 95Format Health Impact Functions

.......................................................................................................................................................... 97Variable Data 4.1.7

......................................................................................................................................................... 102Format Variable Data

.......................................................................................................................................................... 103Inflation Data 4.1.8

......................................................................................................................................................... 104Format Inflation Data

.......................................................................................................................................................... 105Valuation Data 4.1.9

......................................................................................................................................................... 108Format Valuation Data

.......................................................................................................................................................... 109Income Growth Data 4.1.10

......................................................................................................................................................... 113Format Income Grow th Data

.......................................................................................................................................................... 114QALY Data 4.1.11

......................................................................................................................................................... 116Format QALY Data

................................................................................................................................... 1174.2 Export and Import Setups

.......................................................................................................................................................... 117Export Setups 4.2.1

.......................................................................................................................................................... 120Import Setups 4.2.2

................................................................................................................................... 1214.3 Questions Regarding Loading Data

5 Air Quality Grid Creation 123

................................................................................................................................... 1255.1 Model Direct

................................................................................................................................... 1275.2 Monitor Direct

.......................................................................................................................................................... 129Closest Monitor for Monitor Direct 5.2.1

.......................................................................................................................................................... 129Voronoi Neighbor Averaging (VNA) for Monitor Direct 5.2.2

.......................................................................................................................................................... 132Fixed Radius for Monitor Direct 5.2.3

.......................................................................................................................................................... 132Custom Monitor Filtering for EPA Standard Monitors 5.2.4

................................................................................................................................... 1375.3 Monitor and Model Relative

.......................................................................................................................................................... 138Spatial Scaling 5.3.1

.......................................................................................................................................................... 139Temporal Scaling 5.3.2

.......................................................................................................................................................... 139Spatial and Temporal Scaling 5.3.3

.......................................................................................................................................................... 140Examples 5.3.4

................................................................................................................................... 1425.4 Monitor Rollback

.......................................................................................................................................................... 146Example: Combining Three Rollback Approaches in Different Regions 5.4.1

................................................................................................................................... 1505.5 Questions Regarding Creating Air Quality Grids

6 Incidence Estimation 152

................................................................................................................................... 1536.1 Introduction to Estimating Health Incidence

................................................................................................................................... 1546.2 Create Health Impact Configuration

.......................................................................................................................................................... 154Configuration Settings 6.2.1

.......................................................................................................................................................... 156Select Health Impact Functions 6.2.2

................................................................................................................................... 1596.3 Run Health Impact Configuration

................................................................................................................................... 1606.4 Open & Modify Existing Health Impact Configuration

................................................................................................................................... 1606.5 Questions Regarding Health Impact Configurations

7 Aggregation, Pooling, and Valuation 162

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................................................................................................................................... 1637.1 Introduction to Valuation, Discounting, and Pooling

.......................................................................................................................................................... 163Overview of Valuation 7.1.1

......................................................................................................................................................... 165Valuing Reductions in Premature Mortality

.......................................................................................................................................................... 165Overview of Discounting 7.1.2

.......................................................................................................................................................... 170Overview of Pooling 7.1.3

................................................................................................................................... 1707.2 Create Aggregation, Pooling, and Valuation (APV) Configuration

.......................................................................................................................................................... 171Pooling Incidence Results 7.2.1

......................................................................................................................................................... 177Example: Simple Sorting & Pooling

......................................................................................................................................................... 180Example: Multiple Pooling Window s

.......................................................................................................................................................... 181Valuing Pooled Incidence Results 7.2.2

.......................................................................................................................................................... 186Using QALYs Weights 7.2.3

.......................................................................................................................................................... 190APV Configuration Advanced Settings 7.2.4

......................................................................................................................................................... 191Aggregation & Pooling

......................................................................................................................................................... 193Currency & Income

................................................................................................................................... 1957.3 Run APV Configuration

................................................................................................................................... 1957.4 Open & Modify Existing APV Configuration

................................................................................................................................... 1967.5 Questions Regarding APV Configurations

8 Reports 198

................................................................................................................................... 2008.1 One-Step Reports

................................................................................................................................... 2028.2 Incidence, Valuation, & QALY - from APVR file

.......................................................................................................................................................... 204Incidence Results 8.2.1

.......................................................................................................................................................... 206Aggregated Incidence Results 8.2.2

.......................................................................................................................................................... 207Pooled Incidence Results 8.2.3

.......................................................................................................................................................... 208Valuation Results 8.2.4

......................................................................................................................................................... 209Add Sums Button

.......................................................................................................................................................... 210Aggregated Valuation Results 8.2.5

.......................................................................................................................................................... 211Pooled Valuation Results 8.2.6

.......................................................................................................................................................... 212QALY Results 8.2.7

.......................................................................................................................................................... 213Aggregated QALY Results 8.2.8

.......................................................................................................................................................... 214Pooled QALY Results 8.2.9

.......................................................................................................................................................... 215Export Incidence, Valuation, & QALY Reports 8.2.10

................................................................................................................................... 2168.3 Raw Incidence - from CFGR file

.......................................................................................................................................................... 217Export Raw Incidence 8.3.1

................................................................................................................................... 2188.4 Audit Trail Reports - from all BenMAP files

.......................................................................................................................................................... 219Export Audit Trail 8.4.1

................................................................................................................................... 2208.5 Questions Regarding Creating Reports

9 GIS/Mapping 222

................................................................................................................................... 2239.1 Overview of Mapping

.......................................................................................................................................................... 224Display Options 9.1.1

.......................................................................................................................................................... 226Taskbar Buttons 9.1.2

................................................................................................................................... 2289.2 Mapping from the Tools Menu

.......................................................................................................................................................... 230Air Quality Grids 9.2.1

.......................................................................................................................................................... 232APV Configuration Results 9.2.2

.......................................................................................................................................................... 236Configuration Results 9.2.3

.......................................................................................................................................................... 240Modeling Data 9.2.4

Contents

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.......................................................................................................................................................... 241Monitoring Data 9.2.5

.......................................................................................................................................................... 245Population Data 9.2.6

.......................................................................................................................................................... 246Mapping Multiple Layers of Data 9.2.7

................................................................................................................................... 2489.3 Viewing Maps in a BenMAP Analysis

.......................................................................................................................................................... 249Mapping Air Quality Deltas 9.3.1

.......................................................................................................................................................... 250Mapping Monitor Direct Air Quality Grids 9.3.2

.......................................................................................................................................................... 252Mapping Air Quality Monitors from the Advanced Monitor Filter 9.3.3

.......................................................................................................................................................... 255Mapping Monitor Rollback Inputs & Outputs 9.3.4

................................................................................................................................... 2579.4 Questions Regarding Mapping

10 Tools Menu 259

................................................................................................................................... 26110.1 Air Quality Grid Aggregator

................................................................................................................................... 26310.2 Model File Concatenator

................................................................................................................................... 26710.3 Export Air Quality Grid

................................................................................................................................... 26910.4 Neighbor File Creator

................................................................................................................................... 27110.5 One-Step Setup

Welcome to BenMAP

October 20126BenMAP User's Manual

CHAPTER 1

Welcome toBenMAP

In this chapter...

Find an overview of the model.

Find installation instructions.

Find contacts, sources for more information andanswers to frequently asked general questions.

Welcome to BenMAP


BenMAP is a powerful, yet easy-to-use program that helps you estimate human health benefitsresulting from changes in air quality. The U.S. Environmental Protection Agency (U.S. EPA)originally developed this tool to analyze national-scale air quality regulations, including theNational Ambient Air Quality Standards for Particulate Matter (2006) and Ozone (2008) as wellas the Locomotive Marine Engine Rule (2008). To accommodate a wider range of potentialusers interested in simplified analyses, local/regional analyses, or international analyses, EPAdeveloped a more flexible version of BenMAP that includes options for a one-step analysis or acustom analysis.

A wide range of users, including scientists, policy analysts, and decision makers, can utilizeBenMAP to answer many policy questions, such as estimating the benefits from previousreductions in air pollution emissions or the benefits of new requirements to control air pollution.

Welcome to BenMAP


Advanced users can explore a wide range of options in the custom analysis, such as adding newhealth impact and valuation functions, mapping results, and performing sensitivity analyses. Beginning users can take advantage of EPA’s pre-programmed settings and reports in the one-step analysis.

1.1 Overview of BenMAP & Benefits Assessment

The BenMAP program estimates the human health impacts and economic value of air qualitychanges; it is principally a tool that characterizes the benefits of changes in air quality policy. Thatis — BenMAP relates air quality changes to human health benefits. Such analyses are a criticalcomponent of air quality policy assessments, and a variety of Federal, State and Local airpollution officials have used BenMAP to inform air quality management decisions.

BenMAP estimates benefits from improvements in human health, such as reductions in prematuremortality, heart attacks, chronic respiratory illnesses, and other adverse health effects. Otherbenefits of reducing air pollution (i.e., visibility and ecosystem effects) are not quantified in thecurrent version of BenMAP. After estimating the reductions in adverse health effects, BenMAPcalculates the monetary benefits associated with those reductions.

How does BenMAP estimate human health effects?

First, BenMAP determines the change in ambient air pollution using user-specified air qualitydata. Because BenMAP does not include an air quality model, this data must be input intoBenMAP as modeling data or generated from air pollution monitoring data pre-loaded inBenMAP. Next, BenMAP calculates the relationship between the pollution and certain healtheffects (also known as health endpoints). This step is often referred to as the health impactfunction or the concentration-response (C-R) function in epidemiology studies. Finally, BenMAPapplies that relationship to the exposed population.

A simplified example is shown below.

Health Effect = Air Quality Change * Health Effect Estimate * Exposed Population * HealthBaseline Incidence

Air Quality Change. The air quality change is the difference between the starting air pollutionlevel, (i.e., the baseline), and the air pollution level after some change, such as a new regulation(i.e., the control).

Health Effect Estimate. The health effect estimate is an estimate of the percentage change in anadverse health effect due to a one unit change in ambient air pollution. Epidemiological studiesprovide a good source for effect estimates.

Exposed Population. The exposed population is the number of people affected by the airpollution reduction. The government census office is a good source for this information. Inaddition, private companies may collect this information and offer it for sale.

Welcome to BenMAP


Health Baseline Incidence. The health incidence rate is an estimate of the average number ofpeople that die (or suffer from some adverse health effect) in a given population over a givenperiod of time. For example, the health incidence rate might be the probability that a personwill die in a given year. Health incidence rates and other health data are typically collected bythe government. In addition the World Health Organization is a good source for this. SeeWorld Health Organization

How does BenMAP estimate the economic value of human health effects?

BenMAP also calculates the economic value of avoided health effects (see Section 7 for details).After calculating the health changes, you can estimate the economic value by multiplying thereduction of the health effect by an estimate of the economic value per case:

Economic Value = Health Effect * Value of Health Effect

There are several different ways of calculating the value of the health effect. For example, thevalue of an avoided premature mortality is generally calculated using the Value of Statistical Life(VSL). The value of a statistical life is the monetary value that people are willing to pay to slightlyreduce the risk of premature death. For other health effects, the medical costs of the illness maybe the only valuation data available. The BenMAP database includes several different functionsfor VSL and valuation functions for other health effects for you to choose, or you can rely onEPA’s preloaded selections.

Figure 1-1 summarizes the basic steps in BenMAP. This figure shows the types of choices thatyou make regarding the modeling of population exposure, the types of health effects to model,and how to place an economic value on these health effects. Please note that BenMAP does nothave air modeling capabilities, and instead relies on modeling and monitoring inputs.

http://www.who.int/research/en

http://www.who.int/research/en

Welcome to BenMAP


Figure 1-1. BenMAP Flow Diagram Census

Population

Data

Air Quality

Monitoring

Health

Functions

Valuation

Functions

Population

Projections

Air Quality

Modeling

Incidence and Prevalence

Rates

Population

Estimates

Population

Exposure

Adverse

Health Effects

Economic

Costs

Black text represents user input

Blue text represents result from inputs

What else can BenMAP do?

BenMAP incorporates a Geographic Information System (GIS), allowing users to create, utilize,and visualize maps of air pollution, population, incidence rates, incidence rate changes, economicvaluations, and other types of data.

BenMAP can thus be used for a variety of purposes, including:

Generating population/community level ambient pollution exposure maps;

Comparing benefits associated with various regulatory programs;

Characterizing the distribution of health impacts among population sub-groups;

Estimating health impacts and economic value of existing air pollution concentrations;

Estimating health benefits of alternative ambient air quality standards; and

Performing sensitivity analyses of health or valuation functions, or of other inputs.

1.2 How to Use this Manual

Chapters 2 through 9 of this manual provide step-by-step instructions on how to use BenMAP.

New users should start with Chapters 2 and 3, which are both very short, but provide a good

Welcome to BenMAP


overview of the model and how it works, and explain some potentially confusing terminology. Use the rest of the manual to answer any specific questions you may have, or to walk you step-by-step through the various model functions. Chapter 4 discusses how to enter data intoBenMAP, Chapters 5 through 8 cover each of the four main buttons, and Chapter 9 coversmapping.

Each chapter is introduced by a short section which describes what you can find within thechapter, and provides an outline of the chapter’s contents. This is a good place to go if the Tableof Contents does not provide enough detail for you to find the section you need. The end ofmost chapters has a series of “Frequently Asked Questions,” which may also be helpful inanswering specific questions. In sections that provide instructions on navigating the model, thefollowing conventions are observed: menu items, buttons, and tab and selection box labels are inbold type; prompts and messages are enclosed in quotation marks; and drop-down menu items,options to click or check, and items that need to be filled in or selected by the user are italicized. Throughout the chapters you will also see boxes presenting common mistakes and importantthings to remember when working with BenMAP.

There is also a set of Technical Appendices to provide more detailed information on modelfunctions, data, and underlying assumptions.

Appendix A: Monitor Rollback Algorithms

Appendix B: Air Pollution Exposure Estimation Algorithms

Appendix C: Deriving Health Impact Functions

Appendix D: Health Incidence & Prevalence Data in U.S. Setup

Appendix E: Particulate Matter Health Impact Functions in U.S. Setup

Appendix F: Ozone Health Impact Functions in U.S. Setup

Appendix G: Nitrogen Dioxide Health Impact Functions in U.S. Setup

Appendix H: Sulfur Dioxide Health Impact Functions in U.S. Setup

Appendix I: Health Valuation Functions in U.S. Setup

Appendix J: Population & Other Data in U.S. Setup

Appendix K: Uncertainty & Pooling

Appendix L: Command Line BenMAP

Appendix M: Function Editor

References

1.3 Computer Requirements

The computer hardware requirements for BenMAP are typically modest, though this will againvary depending on the complexity of the analysis. BenMAP requires a Windows platform, andcan be used on machines running Windows 2000, as well as more recent versions of Windows. In particular, BenMAP requires a computer with:

Windows 2000 or greater.

Adobe Acrobat Reader

Welcome to BenMAP


128 megabytes of RAM or greater. In general, the amount of RAM required depends on thescope of the Grid Definitions defined for the model (specifically, the number of cells within theGrid Definitions). If the largest grid contains hundreds of cells, 128 MB is required. If thelargest grid contains thousands of cells, 256-512 MB is required. If the largest grid contains tensof thousands of cells, 1 GB is required.

Intel® or compatible processor, Pentium 166 MHz or higher. 1 GHz processor or greaterrecommended for optimum performance.

A CD-ROM drive for CD based installation. Alternatively, an internet connection might be usedto download the (~350 MB) installer.

At least 3.5 GB free space is recommended for the installation of BenMAP U.S. version.

1.4 Installing BenMAP

The Installation of BenMAP 4.0 is very simple. Double click the Setup.exe in your installationdirectory to bring up the setup wizard. Then follow the setup wizard by clicking 'Next' or 'OK'to complete the installation.

Welcome to BenMAP


Welcome to BenMAP


1.4.1 Upgrading to a new version of BenMAP

Periodically, new versions of BenMAP will be made available and posted to the BenMAPwebsite: http://www.epa.gov/air/benmap/. The upgrade just requires replacing the executable ("BenMap 4.0.exe") located in the BenMAP directory, which is typically located at C:\ProgramFiles\BenMAP 4.0. The executable is a relatively small file, about 8 megabytes, so the upgradeprocess is generally very fast.

For upgrades that require replacing or otherwise updating the underlying BenMAP databases,then it might be necessary to completely uninstall BenMAP and then reinstall BenMAP with anew installer package. A new installer package can be relatively large, about 400 megabytes forthe U.S. version. Luckily a complete reinstallation is generally not necessary. Simply replacingthe executable or importing new databases (discussed here in the Load Data chapter) is usuallyall that is necessary.

1.5 Uninstalling BenMAP

To uninstall BenMAP, go to Control Panel, Add/Remove Programs and remove BenMAP4.0. Note that uninstalling BenMAP does not also remove any files that you have created withBenMAP.

When choosing to remove BenMAP 4.0, the Add or Remove Programs window should looksomething like the following:

http://www.epa.gov/air/benmap/

Welcome to BenMAP


1.6 Contacts for Comments, Questions & Bug Reporting

For comments and questions, please contact Neal Fann at the United States EnvironmentalProtection Agency.

Address: C539-07, U.S. EPA Mailroom, Research Triangle Park, NC 27711

Email: [email protected]

Telephone: 919-541-0209

mailto:[email protected]

Welcome to BenMAP


Alternatively, you can send a message at the BenMAP website: http://www.epa.gov/air/benmap/contact.html, or by simply emailing [email protected].

To report programming bugs in BenMAP:

Community Modeling and Analysis System (CMAS) Center at the University of NorthCarolina at Chapel Hill, BenMAP Bugzilla website. Available at: http://benmap-model.org/

1.7 Sources for More Information

For files that you can use in BenMAP:

U.S. Environmental Protection Agency, Office of Air Quality Planning and Standards(OAQPS), BenMAP website. Available at: http://www.epa.gov/air/benmap/

For more information on conducting benefit analysis, see the following documents:

U.S. EPA (1999). OAQPS Economic Analysis Resource Document. Office of Air QualityPlanning and Standards, Innovative Strategies and Economics Group. Available at: http://www.epa.gov/ttn/ecas/analguid.html

U.S. EPA (various years). Costs and Benefits of the Clean Air Act. Available at: http://www.epa.gov/oar/sect812/

U.S. EPA (2004). Final Regulatory Analysis: Control of Emissions from Nonroad DieselEngines. EPA420-R-04-007. May. See: Chapter 9. Available at: http://www.epa.gov/nonroad-diesel/2004fr/420r04007a.pdf

U.S. EPA (2006). Final Regulatory Impact Analysis: 2006 National Ambient Air QualityStandards for Particulate Matter. Office of Air Quality Planning and Standards. See: Chapter5. Available at: http://www.epa.gov/ttn/ecas/regdata/RIAs/Chapter%205--Benefits.pdf

U.S. EPA (2008). Final Ozone NAAQS Regulatory Impact Analysis. Office of Air QualityPlanning and Standards. March. See: Chapter 6. Available at: http://www.epa.gov/ttn/ecas/regdata/RIAs/6-ozoneriachapter6.pdf

U.S. EPA (2008). Regulatory Impact Analysis: Control of Emissions of Air Pollution fromLocomotive Engines and Marine Compression Ignition Engines Less than 30 Liters PerCylinder. Office of Transportation and Air Quality. EPA420-R-08-001a. May. See: Chapter6. Available at: http://www.epa.gov/otaq/regs/nonroad/420r08001a.pdf U.S. EPA (2010). Final Regulatory Impact Analysis (RIA) for the SO2 National Ambient AirQuality Standards (NAAQS). Office of Air Quality Planning and Standards. June. See:Chapter 5. Available at: http://www.epa.gov/ttn/ecas/regdata/RIAs/fso2ria100602ch5.pdfU.S. EPA (2010). Final Regulatory Impact Analysis (RIA) for the NO2 National Ambient AirQuality Standards (NAAQS). Office of Air Quality Planning and Standards. June. See:Chapter 4. Available at: http://www.epa.gov/ttn/ecas/regdata/RIAs/FinalNO2RIACh41-20-10.pdf

http://www.epa.gov/air/benmap/contact.html

http://www.epa.gov/air/benmap/contact.html


http://benmap-model.org/


http://www.epa.gov/ttn/ecas/analguid.html

http://www.epa.gov/ttn/ecas/analguid.html

http://www.epa.gov/oar/sect812/

http://www.epa.gov/oar/sect812/

http://www.epa.gov/nonroad-diesel/2004fr/420r04007a.pdf

http://www.epa.gov/nonroad-diesel/2004fr/420r04007a.pdf

http://www.epa.gov/ttn/ecas/regdata/RIAs/Chapter%205--Benefits.pdf

http://www.epa.gov/ttn/ecas/regdata/RIAs/6-ozoneriachapter6.pdf

http://www.epa.gov/ttn/ecas/regdata/RIAs/6-ozoneriachapter6.pdf

http://www.epa.gov/otaq/regs/nonroad/420r08001a.pdf

http://www.epa.gov/ttn/ecas/regdata/RIAs/fso2ria100602ch5.pdf

http://www.epa.gov/ttn/ecas/regdata/RIAs/FinalNO2RIACh41-20-10.pdf

http://www.epa.gov/ttn/ecas/regdata/RIAs/FinalNO2RIACh41-20-10.pdf

Welcome to BenMAP


U.S. EPA (2010). Guidelines for Preparing Economic Analyses. Office of the Administrator,National Center for Environmental Economics. EPA 240-R-10-001. December. Available at: http://yosemite.epa.gov/ee/epa/eed.nsf/pages/Guidelines.htmlU.S. EPA (2011). Regulatory Impact Analysis (RIA) for the Final Transport Rule. Office ofAir and Radiation. June. See: Chapter 5. Available at: http://www.epa.gov/airtransport/pdfs/FinalRIA.pdfU.S. EPA (2011). Regulatory Impact Analysis for the Final Mercury and Air ToxicsStandards. Office of Air Quality Planning and Standards. December. See: Chapter 5.Available at: http://www.epa.gov/ttnecas1/regdata/RIAs/matsriafinal.pdf

To get email updates about BenMAP:

U.S. EPA, Office of Air Quality Planning and Standards, BenMAP website - Get EmailUpdates. Available at http://www.epa.gov/air/benmap/regis.html

1.8 Frequently Asked Questions (General)

Why do I get different results than someone else?

There are a lot of possible reasons why your results might differ from someone else's results. One good place to start is the Audit Trail reporting option. With the Audit Trail you canexamine the assumptions that you have made to generate your results and compare yourassumptions with those made in another analysis.

How do I know which version of BenMAP I am using? How do I know if I have themost current version of BenMAP? How do I get the most current version?

You can identify the version of BenMAP you are using by going to the Help menu andchoosing About. Here you will see the version number and contact information. To determinewhether you have the most recent version of BenMAP, you can check the BenMAP website (http://www.epa.gov/air/benmap/), which should have the latest version that is publiclyavailable. Alternatively, you can use the contact information to inquire about any upcomingversions of the model.

http://yosemite.epa.gov/ee/epa/eed.nsf/pages/Guidelines.html

http://www.epa.gov/airtransport/pdfs/FinalRIA.pdf

http://www.epa.gov/airtransport/pdfs/FinalRIA.pdf

http://www.epa.gov/ttnecas1/regdata/RIAs/matsriafinal.pdf

http://www.epa.gov/air/benmap/regis.html


Welcome to BenMAP


Why are my pop-up windows too small? Why are buttons missing?

You need to check the display properties for your computer. If you right-click on the desktop,you will get the Display Properties window.

Welcome to BenMAP


At the Settings tab, click on the Advanced button and try a different DPI setting. If this doesnot resolve the problem, try different Screen resolution and Color quality options back on theSettings tab.

Welcome to BenMAP


What do I need to be aware of if I use BenMAP for a local scale analysis?

Perhaps the most important issue is to make sure that you have identified the resolution of youranalysis and have the appropriate grid definitions loaded into BenMAP. See here about loadinggrid definitions. The next key step, which is closely connected to the grid definitions, is todetermine the data that you want to use. Data such as air quality modeling, incidence data, andpopulation data need to match the grid definitions that you are using. You also need to be carefulabout the formatting of your data when loading it into BenMAP. The chapter describing how to Load Data goes into this in detail.

How can I get training for BenMAP?

Contact [email protected] for the latest information on training options.


Welcome to BenMAP


Is BenMAP free? Is there a Terms of Use agreement? Are there any restrictions onusing BenMAP?

BenMAP is free. There is no Terms of Use agreement and there are no restrictions on usingBenMAP. Feel free to share it with others.

Does BenMAP estimate effects of air pollution that are not related to human health (i.e., ecological effects)?

No. BenMAP does not currently have impact functions to estimate other than human healtheffects. In principle it would be possible to estimate ecological effects, as BenMAP is designedto combine different types of geographically variable data. To do so, you would need to developand load data and impact functions appropriate to estimating ecological effects of interest.

Why don't my files created with an older version of BenMAP work with the newerversion of BenMAP?

Files created with an older version of BenMAP will not, in some cases, work with a newerversion of BenMAP because of changes to the program. For example, later versions ofBenMAP have the capability to handle population data differentiated by ethnicity. For thisreason, after completing an analysis with BenMAP, it is always good to archive the BenMAPinstaller along with the files used in your analysis, so that you will always be able to reproduceyour work in the future.

Terminology and File Types


CHAPTER 2

Terminology andFile Types

In this chapter...

Find definitions for terms used in the model and in thismanual that may be confusing.

Find descriptions of the various types of files used inBenMAP.



The first section of this chapter explains common terms used in this user’s manual and in themodel. The second section describes in detail the necessary format for externally-generated model and monitor data files that can be read into BenMAP and used to generate the air qualitygrid files.

2.1 Common Terms

Active Layer. In the GIS window, the active layer is the top-most data layer. All queries orstatistical analysis of the map will act upon this top-most layer.

Aggregation. The summing of grid cell level results to the county, state and national levels.

Aggregation, Pooling, and Valuation (APV) Configuration. APV Configurations store theaggregation levels, pooling options, and valuation methods used in the analysis. In particular, youmay specify the aggregation level for incidence estimates, how to pool incidence estimates, thevaluation estimates to use, the aggregation level for the valuation estimates, and how to pool thevaluation estimates. APV Configurations are stored in files with an “.apv” file extension. Theresults derived from an APV Configuration have an “.apvr” file extension. APV files aretypically stored in the Configurations folder, and APV Results files are typically stored in theConfiguration Results folder.

Air Quality Grid. An air quality grid contains air pollution data. BenMAP uses one air qualitygrid for the baseline scenario and a second for the control scenario, in order to estimate thechange in the number of adverse health effects between the two scenarios. Air Quality Gridsare stored in files with an “.aqg” file extension. AQG files are typically stored in the Air QualityGrids folder.

Air Quality Metric. One of the measures typically used for air pollution. These are daily valuescalculated directly from daily observations, or through various mathematical manipulations ofhourly observations. Typical ozone metrics include the highest hourly observations during thecourse of each day, such as the average of all twenty four hourly observations. These dailyvalues may be summarized to characterize seasonal and annual values.

Air Quality Model. Air quality models are valuable air quality management tools. Models aremathematical descriptions of pollution transport, dispersion, and related physical and chemicalprocesses in the atmosphere. Air quality models estimate the air pollutant concentration at manylocations, which are referred to as receptors, or over a spatial area that has been divided intouniform grid squares. The number of receptors or grid-cells in a model far exceeds the number ofmonitors one could typically afford to deploy in a monitoring study. Therefore, models provide acost-effective way to analyze pollutant impacts over a wide spatial area where factors such asmeteorology, topography, and emissions from both local and remote sources could be important.Some examples include CMAQ and CAMx.



APV Configuration. See Aggregation, Pooling, and Valuation (APV) Configuration.

Attainment. The state of meeting the National Ambient Air Quality Standard (NAAQS) for apollutant. A geographical area that meets the NAAQS is called an “attainment area.”

Audit Trail. This is a report that contains a record of all the choices involved in creating aparticular file. Audit trails can be created for any file that BenMAP creates.

Background Concentration. The concentration of a pollutant irrespective of local,anthropogenic sources. In other words, the background concentration is the level of the pollutantdue to long-range transport, natural sources, and unidentified sources.

Background Incidence. The incidence of a given adverse effect due to all causes including airpollution.

Baseline Scenario. The base air quality conditions where emissions are not adjusted orcontrolled. The baseline scenario is usually considered to be the reference scenario against whichto compare a potential “control scenario”, in which emissions levels are changed from thebaseline levels through the application of various control measures.

Beta. The coefficient for the health impact function. The value of beta (ß) typically representsthe percent change in a given adverse health impact per unit of pollution.

Binning. The process of summarizing data by sorting the data values from low to high, dividingthe sorted data into a pre-determined number of groups, and then choosing a representative valuefor each group, by either averaging the values in each group, or picking the mid-point of eachgroup.

Closest Monitor. The procedure by which data from a nearest monitor are used to representair pollutant levels in a population grid cell. BenMAP can also scale the data from the nearestmonitor with air pollution modeling data. BenMAP includes two types of scaling – “temporal” and“spatial”. See “Scaling” for additional explanation.

Community Multi-scale Air Quality (CMAQ) Model. The CMAQ modeling system is theU.S. EPA 3rd generation air quality model that has been designed to approach air quality as awhole by including state-of-the science capabilities for modeling multiple air quality issues,including tropospheric ozone, fine particles, toxics, acid deposition, and visibility degradation.

Concentration-Response (C-R) Function. A C-R function estimates the relationshipbetween adverse health effects and ambient air pollution, and is used to derive health impactfunctions (defined below). You will often see that the term C-R function and health impactfunction are used interchangeably.

Configuration. A Configuration stores the health impact functions and model options used toestimate adverse health effects. Configurations are stored in files with a “.cfg” file extension.CFG files are typically stored in the Configurations folder. The results derived from aConfiguration have a “.cfgr” file extension. CFGR files are typically stored in the Configuration



Results folder.

Contingent valuation. A survey-based economic technique for the valuation of non-marketresources, such as environmental preservation or avoidance of air pollution health risk.

Control scenario. In a modeling study, this is a sensitivity scenario in which emissions from oneor more source sectors are changed (increased or decreased), from a given “baseline scenario”.The subsequent modified emissions are then used within an air quality model to derive newambient concentrations. Control scenarios are used to assess the efficacy of proposed emissionscontrols for sources of pollution.

Cost of Illness (COI). The cost of illness includes the direct medical costs and lost earningsassociated with illness. These estimates generally understate the true value of reductions in riskof a health effect, as they include just the direct expenditures related to treatment and lostearnings, but not the value of avoided pain and suffering from the health effect.

C-R Function. See Concentration-Response (C-R) Function.

Currency year. The value of the dollar based on the year specified. Typically, you would adjustthe valuation estimate to a consistent currency year. For example, you might want to report thevaluation estimate in 2000 dollars to make it easier to compare with your cost analysis, whichuses that same currency year.

Custom analysis. This type of BenMAP analysis allows you to perform each part of an analysisseparately: air quality estimation; calculation of health impact functions; aggregation, pooling, andvaluation; and reporting.

Deltas. The difference between two pieces of data. As used in BenMAP, mapping the deltasshows the reduction in air pollution from the baseline air quality grid to the control air quality grid.

Discount Rate. In this context, the discount rate is a quantitative method to account for the factthat people generally value future benefits and costs less than current costs and benefits.Typically, if a benefit occurs over multiple years, the benefit should be discounted.

Endpoint. An endpoint is a subset of an endpoint group, and represents a more specific class ofadverse health effects. For example, within the endpoint group Mortality, there might be theendpoints Mortality, Long Term, All Cause and Mortality, Long Term, Cardiopulmonary.

Endpoint Group. A endpoint group represents a broad class of adverse health effects, such aspremature mortality, chronic bronchitis, and hospital admissions. BenMAP only allows pooling ofadverse health effects to occur within a given endpoint group, as it generally does not make senseto sum together the number of cases of disparate health effects, such as premature mortality andchronic bronchitis.

Epidemiology. The study of factors affecting the health and illness of populations.Epidemiological studies cannot prove that a specific risk factor actually causes the disease beingstudied, and instead can only show that a risk factor is associated (correlated) with a higher



incidence of disease in the population exposed to that risk factor. The higher the correlation themore certain the association, but it cannot prove the causation.

FIPS Code . Federal Information Processing Standard codes. Each state in the U.S. is assigneda 2-digit code. For example, “01” refers to Alaska, “37” refers to North Carolina, and “56” refersto Wyoming.

Fixed Effects Pooling. Fixed effects pooling is used to combine two or more distributions(represented by Latin Hypercube points) into a single new distribution. Fixed effects poolingassumes that there is a single true underlying relationship between these component distributions,and that differences among estimated parameters are the result of sampling error. Weights forthe pooling are generated via inverse variance weighting, thus giving more weight to the inputdistributions with lower variance and less weight to the input distributions with higher variance.

Fixed Radius . An air quality monitor interpolation option that uses all monitors within a fixedradius (or distance) of a given point of interest. All monitors are used and weighted by theirrelative distance.

GIS. Geographic Information System. A GIS is a system of hardware and software used forstorage, retrieval, mapping, and analysis of geographic data.

Grid Cell. One of the many geographic, or spatial components within Grid Definition.

Grid Definition. A BenMAP Grid Definition provides a method of breaking a geographicregion into areas of interest (Grid Cells) in conducting an analysis. This can be done in two ways- by loading a Shapefile (a particular type of Geographic Information System file) or byspecifying a regularly shaped grid pattern. These are referred to as Shapefile Grid Definitionsand Regular Grid Definitions, respectively. Typically a Shapefile Grid Definition is used whenthe areas of interest are political boundaries with irregularly shaped borders, while a Regular GridDefinition is used when the areas of interest are uniformly shaped rectangles.

Growth Income Adjustment. See Income Growth Adjustment.

Health Impact Function. A health impact function calculates the change in adverse healtheffects associated with a change in exposure to air pollution. Based on a C-R function, a typicalhealth impact function has inputs specifying the air quality metric and pollutant, the age, race andethnicity of the population affected, and the incidence rate of the adverse health effect.

Incidence. The total number of adverse health effects in a geographic region in a given unittime. In BenMAP, this is the total number of adverse health effects avoided due to a change inair pollution.

Incidence Rate. The background rate of a health effect per person in a given geographic region(a.k.a. background incidence rate). The average number of adverse health effects per personper unit of time, typically a day or a year.

Income Growth Adjustment. Adjusting certain valuation functions to reflect increases in real



income. Generally, an increase in real income implies an increase in the willingness to pay(WTP).

Interpolation. The process of estimating the air quality level in an unmonitored area by usingone or more nearby air quality monitors. BenMAP uses two types of interpolation procedures:one is to simply choose the closest monitor, the other is to use a technique called VoronoiNeighbor Averaging. These interpolation methods are discussed in more detail in Appendix B.

Lat/Long. Latitude and longitude information to specify the geographic coordinates of a spatiallocation. The CMAQ model data are usually provided for each grid cell identified by the latitudeand longitude of the grid cell’s center point. Latitude identifies the north-to-south location of apoint on the Earth. Latitude can be defined precisely as the angle between the vertical at alocation, and the equatorial plane of the Earth. Longitude identifies the east to west location of apoint on the Earth, by measuring the angular distance from the Greenwich meridian (or Primemeridian, where longitude is 0), along the equator.

Latin Hypercube. A series of points generated by using specified percentiles in a givendistribution, such as that of a health impact coefficient. It is a short-cut method designed torepresent a distribution, while at the same time saving on computation time. For example, when

using 20 Latin Hypercube points, BenMAP would use the 2.5th, 7.5th, 12.5th, ..., and 97.5th pointsfrom the distribution. The Latin Hypercube points are used when combining the results ofdifferent health impact functions (discussed in Chapter 7), and in presenting confidence intervalsfor the incidence estimates (discussed in Chapter 8).

Layer. In geographic information systems (GIS), a layer represents a logical separation ofmapped data usually representing a theme, such as political boundaries, roads, ozone data,number of mortalities avoided, etc. In BenMAP, “active layer” refers to the top-most layer withwhich the user is currently working.

Layer Statistics. The summary statistics that correspond to the active layer in BenMAP. Forexample, "mean", "standard deviation" or "max" of PM

2.5 air quality grid.

Micrograms per Cubic Meter (µg/m3). The unit of measure for particulate matter in theNAAQS. This unit represents the mass of PM found in a cubic meter of air.

Model Data. Pollutant concentration data that are generated by running an air quality modelsuch as CMAQ. This is different from “monitor data,” which are based upon measurements.

Model Delta. Differences in pollutant concentrations from applying an air quality model (e.g.CMAQ) for two different emissions scenarios – a baseline scenario and an emissions controlscenario.

Modeling. Estimating air pollution levels using air quality models. The EPA website discusses awide range of air quality models: http://www.epa.gov/scram001/aqmindex.htm and at http://www.epa.gov/ttn/scram/.

Monetize . In the context of human health benefits assessment, this is the practice of expressing

http://www.epa.gov/scram001/aqmindex.htm

http://www.epa.gov/ttn/scram/




society’s preferences for avoiding certain health effects as a dollar value. In BenMAP weestimate monetized benefits by using either Willingness-to-Pay or Cost-of-Illness valuationfunctions (see above and below).

Monitor Data. Pollutant concentration data that are based upon measurements. “Raw” monitordata usually refers to data that are taken directly from measurement networks, with no additionalprocessing of the data. Monitor data are different from “model data,” which are based uponnumerical predictions.

Monitoring. Actual measurements of air pollution levels. The U.S. Environmental ProtectionAgency has monitoring data, as well as other information related to monitoring, available throughits Air Quality System (AQS): http://www.epa.gov/air/data/aqsdb.html.

Morbidity. A measure of being diseased or afflicted by an illness (non-fatal).

Mortality. A measure of the number of deaths in a given population.

National Ambient Air Quality Standards (NAAQS). The U.S. EPA establishes levels forpollutants that are considered harmful to public health and the environment. The Clean Air Actestablished two types of national air quality standards. Primary standards set limits to protectpublic health, including the health of "sensitive" populations such as asthmatics, children, and theelderly. Secondary standards set limits to protect public welfare, including protection againstdecreased visibility and against damage to animals, crops, vegetation, and buildings. The U.S.EPA has set NAAQS for six principal pollutants, which are called "criteria" pollutants. (CarbonMonoxide, Lead, Nitrogen Dioxide, Ozone, Particulate Matter (PM

2.5, PM

10), and Sulfur

Dioxide).

One-Step Analysis. An easier and shorter approach to performing analyses with BenMAP,targeted for beginning users. This combines all three major steps of BenMAP, i.e., a) calculatechanges in pollutant concentrations, b) use concentration-response (C-R) function to estimatehealth incidences, and c) calculate economic benefits due to changes in morbidity and mortalityinto a single process. However, the choices of analyses are limited. For example, the healthincidences and valuation functions are predefined, and the user cannot change them.

Ordinality. In relation to AQ monitors, ordinality refers to the number of monitor values in theseason that can exceed your standard. For example, if we had set the ordinality to 4, then amonitor can have as many as three daily averages (assuming that we are using the daily averagemetric to define our standard) greater than your standard without violating the standard. In termsof rollback, if it has more than 3 daily averages in exceedance of the standard, then the rollbacktechnique will be applied to that monitor.

Ozone (O3). A gas composed of three oxygen atoms. It is not usually emitted directly into the

air, but at ground-level is created by a chemical reaction between oxides of nitrogen (NOx) andvolatile organic compounds (VOC) in the presence of sunlight. Ozone has the same chemicalstructure whether it occurs miles above the earth (in what is sometimes referred to as “the ozonelayer”) or at ground-level, and can be "good" or "bad," depending on its location in theatmosphere. For the purposes of BenMAP, the focus is on ground-level ozone, which can be

http://www.epa.gov/air/data/aqsdb.html



breathed in. Breathing ozone can trigger a variety of health problems, including chest pain,coughing, throat irritation, and congestion. It can worsen bronchitis, emphysema, and asthma.Ground-level ozone also can reduce lung function and inflame the linings of the lungs. Repeatedexposure may permanently scar lung tissue.

Particulate Matter. "Particulate matter," also known as particle pollution or PM, is a complexmixture of extremely small particles and liquid droplets. Particle pollution is made up of a numberof components, including acids (such as nitrates and sulfates), organic chemicals, metals, and soilor dust particles. Once inhaled, these particles can affect the heart and lungs and cause serioushealth effects. Includes PM

2.5 (particles less than 2.5 microns in aerodynamic diameter), PM

10

(particles less than 10 microns in aerodynamic diameter), and PMC (particles between 2.5 and 10microns in aerodynamic diameter).

Parts per Million (ppm). This unit represents the concentration of the pollutant in a million partsof air. Carbon monoxide is often measured in units of ppm.

Parts per Billion (ppb). This unit represents the concentration of the pollutant in a billion partsof air. Ozone concentrations in BenMAP are reported in units of ppb.

Pooling. The combining of different sets of data. BenMAP has several pooling methods,including fixed effects, fixed/random effects, and subjective weighting. Appendix K discussesthe pooling approaches available in BenMAP.

Point Mode. When defining the configuration, you may choose to either estimate adversehealth effects in point mode or using a Latin Hypercube. The point mode simply means thatBenMAP will use the mean value of the coefficient in the health impact function.

Population Exposure versus Personal Exposure. Population (or ambient) exposure refersto the average air pollution level measured in a grid cell. In contrast, personal exposure keepstrack over the course of a day the exposure individuals encounter in different micro-environments, such as the freeway, outdoors and indoors. BenMAP only keeps track ofpopulation exposure.

Post-processing. Additional data modification steps that are undertaken to prepare either rawmonitor data or raw model data for subsequent import into BenMAP. Postprocessing may be assimple as reformatting the data, or it may involve more complex operations such as performingadditional numerical calculations to aggregate or disaggregate data temporally or spatially.

Prevalence Rate. The percentage of individuals in a given population who already have a givenadverse health condition. Used to calculate changes in health conditions among those whoalready have a health condition, such as asthmatics.

Quality Adjusted Life Years (QALYs). The number of "healthy" life years gained or lost dueto changes in air quality. The QALY weights each life year gained according to the severity ofthe health effect.

Random Effects Pooling. Random effects pooling is an alternative to the fixed effects pooling



(see Fixed Effects Pooling, above), and allows the possibility that the estimated parameter fromdifferent studies may in fact be estimates of different parameters, rather than just differentestimates of a single underlying parameter.

Regulatory Impact Analysis (RIA). A policy tool used to assess the likely effects of aproposed regulation or regulatory change. It usually involves detailed analyses to quantify thecosts and benefits of the regulation.

Relative Risk. Relative risk typically is used as a measure of the change in risk of an adversehealth effect associated with an increase in air pollution levels. More specifically, it is the ratio ofthe risk of illness with higher pollution to the risk of illness with a lower pollution level, where the“risk” is defined as the probability that an individual will become ill.

Rollback. The process by which monitor data are reduced to a different level. BenMAPfacilitates three different types of monitor data rollback. Percentage rollback reduces all monitorobservations by the same percentage. Incremental rollback reduces all observations by the sameincrement. Rollback to a standard reduces monitor observations so that they just meet a specifiedstandard.

Scaling. The process in which monitor data are used in conjunction with model data to improveinterpolation and/or forecast future air quality trends. BenMAP has 3 types of scaling – temporalonly, spatial only, temporal and spatial scaling.

Setup. A BenMAP Setup encapsulates all of the data needed to run analyses for a particulargeographic area - a city, an entire country, etc. These data consist of grid definitions, pollutants,monitor data, incidence and prevalence rates, population data, health impact functions, variables,inflation rates, and valuation functions.

Shapefile. A shapefile is a particular type of Geographic Information System (GIS) file, and hasa .shp extension. These files are accompanied by companion files with .shx and .dbf extensions,and can be used to create Shapefile Grid Definitions. See http://www.esri.com/library/whitepapers/pdfs/shapefile.pdf for more information.

Subjective Weighting Pooling. Subjective weights let you specify the weights that you wantto use when combining two or more distributions of results. The weights should sum to one. Ifnot, BenMAP normalizes the weights so that they do.

Sum Dependent Pooling. Summing two or more incidence or valuation results, assuming theunderlying functions are correlated.

Sum Independent Pooling. Summing two or more incidence or valuation results, assuming theunderlying functions are independent (uncorrelated).

Threshold. An air quality level below which benefits are not calculated. For example, if the

threshold is 10 µg/m3, then only areas with PM2.5

concentrations equal to or greater than 10 µg/m3

will be included in estimating health incidence results.

http://www.esri.com/library/whitepapers/pdfs/shapefile.pdf

http://www.esri.com/library/whitepapers/pdfs/shapefile.pdf



Unit Value. A unit value is the estimated mean value of avoiding a single case of a particularhealth effect.

Valuation Function. Valuation functions are used by BenMAP to estimate the economic valuesof changes in the incidence of health effects. These are selected within an Aggregation, Pooling,and Valuation Configuration (APV Configuration).

VNA (Voronoi Neighbor Averaging). An algorithm used by BenMAP to interpolate airquality monitoring data to an unmonitored location. BenMAP first identifies the set of monitorsthat best “surround” the center of the population grid cell, and then takes an inverse-distanceweighted average of the monitoring values. This is discussed in detail in Appendix B.

WTP (Willingness to Pay). The willingness of individuals to pay for a good, such as areduction in the risk of illness. In general, economists tend to view an individual’s WTP for aimprovement in environmental quality as the appropriate measure of the value of a risk reduction. An individual’s willingness-to-accept (WTA) compensation for not receiving an improvement isalso a valid measure. However, WTP is generally considered to be a more readily available andconservative measure of benefits.

2.2 File Types

BenMAP has a number of file types that you can use to store the settings used in a BenMAPanalysis, the results of an analysis, as well as maps and reports. Table 2-1 presents the names ofthe different file types, their functions, and their default folder locations.

Table 2-1. File Types Generated by BenMAP

File Extension Description Default Folder Location

*.aqg Air quality grid. Air Quality Grids

*.cfg Configuration specifying the health impact functions andother options used to generate incidence estimates.

Configurations

*.cfgr Configuration results, containing incidence results at the grid cell level.

Configuration Results

*.apv Aggregation, Pooling, and Valuation configurationspecifying the aggregation levels, pooling options, andvaluation methods used to generate aggregated incidenceestimates, pooled incidence estimates, valuation estimates,aggregated valuation estimates, and pooled valuationestimates.

Configurations



File Extension Description Default Folder Location

*.apvr Aggregation, Pooling, and Valuation configuration results,containing incidence results at the grid cell level, aggregatedincidence results, valuation results, aggregated valuationresults, and pooled valuation results.

Configuration Results

*.shp Shape files generated by BenMAP’s geographic informationsystem. These files can be viewed within BenMAP or withinshape file viewers, such as ArcView.

Maps

*.csv Reports are exported as *.csv files, which may be viewed in atext editor, or in programs such as Excel.

Reports

Overview of BenMAP Components


CHAPTER 3

Overview ofBenMAP

Components

In this chapter...

Learn about the One-Step Analysis.

Get an overview of the functions available with theCustom Analysis.

Learn about the Tools and Help menu options.



Upon starting BenMAP for the first time, you will see the following main window.

The opening screen is broken into two sections. On the left hand slide is the One-Step Analysisbutton. This feature enables you to perform a quick benefit analysis while selecting a minimum ofanalysis options. On the right hand side is the Custom Analysis section, which contains four largebuttons. This feature allows you to perform a highly customized benefit analysis. The Tools menuat the top of the screen is for less frequently used functions, such as importing and exporting dataand mapping.

The first section in this Chapter describes the One Step Analysis. The second section describesthe Custom Analysis. And the final section describes the functions found in the Tools and Helpmenu options. All of these topics are covered in greater detail in subsequent chapters of thismanual.



3.1 One-Step Analysis

The One-Step Analysis allows you to run a BenMAP analysis quickly. This option can be usefulwhen you are time constrained, when you don't have a strong preference regarding the benefitanalysis options, or if you are new to the program. This feature uses an EPA-developed benefitanalysis configuration to estimate the human health benefits of the air quality scenario that youspecify in the model.

The One-Step Analysis requires a minimal number of inputs. At minimum, you should:

Give your run a name. Very descriptive titles can help you remember more about your runwhen you want to review your results in the future.

Choose an output directory. The output directory is the location on your computer in whichyou will save your results. (The default is to put the output in the Configuration Results folder.)

Select air quality grids. BenMAP estimates the benefits of some change in air quality for aparticular area of the country. Here, you're telling BenMAP which air quality files to use tocalculate benefits. You can either import an air quality file that has already been created, or youcan generate your own. If you want to create your own air quality file, you will want hit the"create" button and follow the instructions under the custom analysis page below. Foradditional details on air quality grid creation, see the chapter on Air Quality Grid Creation.

Choose your aggregation level. Select the geographic level at which you want to summarizeyour results.



After you have selected these options, just hit the "Go!" button, and BenMAP will run theanalysis in a single step. The One-Step run time generally depends on the complexity of the airquality data. More complex air quality data requires more time to run.

3.1.1 One-Step Reports

When BenMAP completes its run a new window will appear that gives you an array of graphicaland tabular reporting options. The top part of this window provides incidence report options, themiddle part of the window contains options for creating valuation reports and in the bottom partof the window is the audit trail report button. (For more details on One-Step reports, see the chapter on Reports.)





BenMAP will report an "audit trail" that reports all of your data inputs and analysis options. Thisreport can be very useful when someone wants to replicate your analysis, or when you wouldsimply like to remember all of the data and options you used in your analysis. The audit trail isdiscussed in further under "generate reports" in the Custom Analysis section below.



3.1.2 Questions Regarding the One-Step Analysis

How do I know what currency year is used in the One-Step Analysis?

You can find the answer in the Audit trail for the APVR file that you generated. Alternatively,go to the Tools menu and choose One-Step Setup. Then choose a Pollutant (e.g., PM

2.5) to

determine the currency year.





How do I know what population year is used in the One-Step Analysis?

You can find this answer in the Audit Trail.



How do I change the .cfg or .apv files used in the One-Step Analysis?

Go to the Tools menu and choose One-Step Setup. At the One Step Setup Parameterswindow, you can browse for alternative .cfg and .apv files.

How do I find out which functions are used in the One-Step Analysis?

You can identify the functions used in the One-Step Analysis at least two ways. First, you canuse the Audit Trail option to identify the functions used in an existing set of One-Step results. Alternatively, if you want to look at the functions prior to the analysis, then you might want tolook at the .cfg and .apv files using the Audit Trail available with the Report options under theCustom Analysis.

How do I create the Air Quality Grids needed for the One-Step Analysis?

There are several ways to create Air Quality Grids needed for a One-Step Analysis, usingmonitor data, model data, or both monitor and model data. These options are brieflydiscussed in the Create Air Quality Grids section of this Overview chapter and in detail in the



Air Quality Grid Creation chapter.

Why are the aggregation levels limited in the One-Step Analysis?

The aggregation levels are limited in the One-Step Analysis in order to simplify the analysis andto make the results compatible with the pre-made tables and graphs.

3.2 Custom Analysis

Returning to the main BenMAP window, you can choose the Setup you want to use for ananalysis by selecting it from the Active Setup drop-down list. You are then ready to begin usingthe functions available through the four main buttons.

These four buttons take you through the steps of an analysis. The first button allows you tocreate air quality grids which contain estimates of population-level exposure to air pollution. Thesecond button lets you choose the air quality grids for a particular analysis, and then to choosethe health impact functions to estimate the incidence of adverse health effects. The third buttongives you different options for combining the health effects estimates and choosing economic valuation functions. Using the fourth button, you can generate several different kinds of reports.

3.2.1 Create Air Quality Grids

BenMAP is not an air quality model, nor can it generate air quality data independently. Instead itrelies on the air quality inputs given to it. To estimate population exposure to air pollution,BenMAP combines population data with an Air Quality Grid, which it generates using somecombination of air quality modeling and/or monitoring data. The Create Air Quality Gridsbutton allows you to put your air quality data into the format that is used by BenMAP, the firststep in conducting an analysis within BenMAP.

Grid Definitions

Air quality grids contain air pollution exposure estimates for a particular Grid Definition, asdefined in the Setup Manager window. Grid Definitions are typically comprised of eitherregularly shaped rectangles covering the region of analysis, or irregularly shaped polygonscorresponding to political boundaries.

Modeling and Monitoring Data

To generate air quality grids, you can use air quality modeling data and air quality monitoring datain three different ways, as discussed below. However, once generated, all air quality grids havethe same structure, and have the same .aqg extension that BenMAP uses to designate these filetypes.

Model Direct. Model Direct grid creation simply takes raw model data and converts it into afile that BenMAP recognizes as an air quality grid. This type of grid definition allows you to



directly specify the air pollution values for each grid cell in a Grid Definition.

Monitor Direct. Monitor Direct grid creation uses air pollution monitoring data to estimate airpollution levels for each grid cell in the selected Grid Definition. This may be done using one oftwo interpolation procedures – Closest Monitor, or Voronoi Neighbor Averaging (VNA). Withclosest monitor, BenMAP simply uses the data of the monitor closest to each grid cell's centroid.With VNA, BenMAP first identifies the set of monitors that most closely “surround” each gridcell, and then calculates an inverse-distance weighted average of the data from these neighboringmonitors.

Monitor and Model Relative. Monitor and Model Relative grid creation allows you tocombine information from both monitor and modeling data files. BenMAP uses the modeling datato scale the monitoring data, to compensate for incomplete monitoring data coverage, and theinability of monitor data to predict future conditions. Like the Monitor Direct approach, youchoose an interpolation method (Closest Monitor or VNA), but a scaling approach is also chosen,either temporal, spatial, or both. This approach is described in more detail in the Air Quality GridCreation chapter, as well as in the appendix on Air Pollution Exposure Estimation Algorithms.

Monitor Rollback. Monitor Rollback grid creation allows you to reduce, or roll back, monitordata using three methods: percentage rollback, incremental rollback, and rollback to a standard. Percentage rollback reduces all monitor observations by the same percentage. Incrementalrollback reduces all observations by the same increment. Rollback to a standard reduces monitorobservations so that they just meet a specified standard. After the monitor data is rolled back, itmay be directly interpolated (as in Monitor Direct grid creation) or combined with modeling data(as in Monitor and Model Relative grid creation). This approach is described in more detail inthe Air Quality Grid Creation chapter, as well as in the appendix on Monitor Rollback Algorithms.

3.2.2 Create and Run Configuration

The Create and Run Configuration button allows you to calculate the change in the incidenceof adverse health effects associated with changes in air quality. There are several steps in theprocess.



Step 1. Specify the baseline and control air quality grids that you created using the Create AirQuality Grids button.

Step 2. Specify whether BenMAP should make a “point estimate”, or a set of “LatinHypercube” points. The point estimate is the change in incidence, generated using the meanvalue of the coefficient in the health impact function. The Latin Hypercube points are a series ofpoints generated by using evenly spaced percentiles in the distribution of the health impactcoefficient – these points represent the distribution of incidence values. (The Latin Hypercubepoints can later be used when combining the results of different health impact functions, and inpresenting confidence intervals for the incidence estimates.)

Step 3. Specify the threshold, or a lowest value for air quality data. Any observations which fallbelow this threshold will be replaced with the threshold value in all calculations.



Step 4. Choose the health impact functions that will be used in the estimation, and hit the Go!button to start estimating the change in incidence.

BenMAP can store configuration choices in a user-named file with a .cfg extension, and canstore incidence change estimates in a user-named file with a .cfgr extension.

3.2.3 Aggregation, Pooling, and Valuation

The Aggregation, Pooling, and Valuation button allows you to specify an aggregation level forpreviously calculated incidence estimates, pool these aggregated incidence estimates, place aneconomic value on these pooled and aggregated incidence estimates, aggregate these economicvalues, and finally pool these aggregated economic values. There are several steps in thisprocess.

Step 1. Choose whether to create a new .apv configuration or use an existing .apvconfiguration. (For this description we will choose to create a new .apv configuration.)



Step 2. Choose a set of incidence estimates to use. These will be loaded from a configurationresults file made with the Create and Run Configuration button, which is stored by BenMAPwith a .cfgr extension.

Step 3. Choose the desired pooling and aggregation options for the incidence results.



Step 4. Choose the economic valuation functions to apply to the pooled and aggregatedincidence results.



Step 5. Choose the desired pooling and aggregation options for the economic valuations, and hitthe Next button. If the Skip QALY Valuation box is checked, then BenMAP is ready to saveyour APV Configuration and generate results.

Step 6. If desired, you can uncheck the Skip QALY Valuation box and proceed to choosingyour desired QALY functions. Why have Skip QALY Valuation box? It takes a bit of time forthe QALY functions to load, and since QALY functions are not always used, this box is intendedto speed up the time it takes to develop the APV Configuration.

BenMAP can store APV Configuration choices in a user-named file with an “.apv” extension, andcan store APV Configuration results in a user-named file with an “.apvr” extension. As needed,you can access both files for later use.

3.2.4 Generate Reports

The Generate Reports button allows you to generate several types of reports.



Incidence and Valuation Results reports use an Aggregation, Pooling, and ValuationResults file (with the “.apvr” extension) to create reports for incidence, aggregated incidence,pooled incidence, valuation, aggregated valuation, or pooled valuation results. These reportsare comma separated values (CSV) files (*.csv) which can be read using a text editor, or byvarious spreadsheet and database programs, such as Microsoft Excel.

Raw Incidence Results use a Configuration Results file (with the “.cfgr” extension) to create reports for incidence results. These reports are CSV files.



Audit Trail Reports provide a summaries of the assumptions underlying each of five types offiles generated by BenMAP: Air Quality Grid (“.aqg”), Configuration (“.cfg”), ConfigurationResults ( “.cfgr”), Aggregation, Pooling, and Valuation (“.apv”), and Aggregation,Pooling, and Valuation Results (“.apvr”). These reports can be viewed within BenMAP in anexpandable tree structure, or can be exported to text files.



3.3 Menus

There are two menu options found at the top of the main window: Tools and Help. The Toolsmenu provides access to data import and export functionality and mapping. The Help menuprovides access to information about BenMAP - the version, contact information, and asuggested citation.

3.3.1 Tools

The Tools menu has several options: Database Export, Database Import, GIS / Mapping,andModify Setup.



Air Quality Grid Aggregation. Create a new air quality for a new grid definition (e.g., State)from an existing air quality grid created with a different grid definition (e.g., County).

Model File Concatenator. Combine model files for use in the creation of air quality grids.

Database Export. Export all or part of BenMAP’s internal database to a file which can later beused (on another computer, for example) with the Database Import tool. Manually loading datainto BenMAP can be time and labor intensive, so this tool can be quite useful in sharing data withother users or computers.

Database Import. Import data exported using the Database Import tool.

Export Air Quality Grid. Generate a text file (.csv) with all of the data in air quality grid,including summary statistics such as mean, median, minimum, and maximum.

GIS / Mapping. Generate a wide variety of maps, including maps of monitor data, air qualitygrids, population data, incidence rates, and both incidence and valuation results. In addition, you



can export the maps you have generated and view them in a shapefile viewer, such as ArcView.Note that BenMAP also has context specific mapping capabilities in various parts of theapplication. See the GIS/Mapping chapter for details on BenMAP's mapping capabilities.

Modify Setup. View, edit, add, and delete data from BenMAP’s internal database. For detailssee the Load Data chapter.

Neighbor File Creator. Create a text file (.txt) identifying "neighbor" monitors and associatedinterpolation weights for each grid cell in an air quality grid.

One-Step Setup. Specify the CFG and APV Configuration files and currency year for the One-Step Analysis.

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CHAPTER 4

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In this chapter...

Create new data setups to load and store your inputdata.

Find details on the file structures for data inputs.

Learn how to export and import setups.

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BenMAP encapsulates in a single dataset all of the data needed to run analyses for a particulargeographic area, such as a city, region, or nation. This dataset is called a “Setup” and consistsof grid definitions, pollutants, monitor data, incidence and prevalence rates, population data,health impact functions, variables, inflation rates, valuation functions, income growth data, andQALY data. Grouping the data in this way has a number of advantages. It makes it easy toorganize and view the data, export the data (either a whole setup or a portion of a setup), andimport setups generated by others.

In this Chapter we discuss how to add, modify, and delete setups, as well as how to export andimport existing setups. There are a number of steps involved in loading the data, particularly inthe formatting of the data, so it is important to carefully review the steps in this Chapter. Also, itis important to keep in mind that if you delete one part of a setup, you may be affecting otherparts of the setup. We discuss this further below.

Finally, it's worth noting that many users will never need to modify the setup. If you areperforming an analysis with the U.S. setup, you may find that BenMAP contains all of the datayou need to perform your analysis, and no additional modifications are necessary.

4.1 Add, Modify, and Delete Setups

To add a new setup, modify an existing setup, or delete a setup, go to the Tools drop-downmenu, and choose the Modify Setup option. This will bring up the Manage Setups window. TheUnited States setup, which comes preinstalled with BenMAP comes with a variety of datasetsand might look something like this:

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Add a Setup. To add a setup, click the Add button. The New Setup window will appear,where you can type the name of the setup.

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After naming a new setup, you can then define anew the elements that comprise a setup: GridDefinitions, Pollutants, Monitor DataSets, Incidence and Prevalence DataSets,Population DataSets, C-R Function DataSets, Variable DataSets, Inflation DataSets,Valuation DataSets, Income Growth Adjustments, and QALY Distribution DataSets.

Some of the elements of a setup are fundamental and should be entered before the others,namely Grid Definitions and Pollutants. The Incidence and Prevalence, Population, andVariable DataSets depend on the Grid Definitions, and the Monitor and C-R FunctionDataSets depend on the Pollutants that you have defined. As a result, it is best to start bydefining your Grid Definitions and Pollutants, and then defining the other elements of the setup.

Modify a Setup. To modify a setup, start by choosing the setup for modification from the drop-down menu in Available Setups. Click on the Edit button under one of the eleven componentscomprising a setup. The sections below describe each of these components.

Delete a Setup. To delete a setup, choose the setup for deletion from the drop-down menu inAvailable Setups. Click the Delete button. You will then be asked to confirm your decision.

4.1.1 Grid Definitions

A BenMAP Grid Definition provides a method of breaking a geographic region into areas ofinterest (Grid Cells) in conducting an analysis. This can be done in two ways: by loading aShapefile (a particular type of Geographic Information System file) or by specifying a regularlyshaped grid pattern. These are referred to as Shapefile Grid Definitions and Regular GridDefinitions, respectively. Typically a Shapefile Grid Definition is used when the areas ofinterest are political boundaries with irregularly shaped borders, while a Regular Grid

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Definition is used when the areas of interest are uniformly shaped rectangles.

Ideally, one Shapefile Grid Definition will be created using a shapefile containing an outline ofthe area of interest (a city boundary, for example). Additional grid definitions will then be createdfor each subdivision of that area for which (a) data is available (see the Air Monitoring,Population, Incidence and Prevalence, and Variables sections below), or (b) reports or maps aredesired.

For example, to conduct analyses for the United States, one might use the following griddefinitions:

Nation - this Shapefile Grid Definition contains an outline of the United States (just the lowerforty-eight states), defining an overall area of interest.

County - this Shapefile Grid Definition contains county borders, for use with county-basedpopulation and incidence rate data.

CMAQ 12km Nation - this Shapefile Grid Definition contains grid cells that are roughly 12kilometers on each side, for use with air quality modeling data.

State - this Shapefile Grid Definition contains state borders, for use in generating reports andmaps with results aggregated to the state level.

To start adding or modifying grid definitions, click on the Edit button below the GridDefinitions box. The Manage Grid Definitions window will appear.

Click on the Add button below the Available Grid Definitions box,. The Grid Definitionwindow will appear, with two tabs showing the two main types of grid definitions that you mayuse in BenMAP: Shapefile Grid or Regular Grid.

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4.1.1.1 Regular Grid

Regular Grid Definitions are defined by a lower left corner (specified as decimal degreelatitude and longitude, with West and South having negative values and East and North havingpositive values), a total number of columns and rows, a number of columns per degree longitude,and a number of rows per degree latitude. Individual cells within the resultant grid are numberedin sequential order (columns from left to right, rows from bottom to top) starting at (1, 1). Thesefield values will be used to link the Regular Grid Definition with other sources of data, asdiscussed in more detail below.

To define a Regular Grid, start by typing the name of the grid definition in the Grid ID box, andthen defining the number of Columns and Rows in the grid. To locate this grid geographically,provide the decimal degree coordinates for the lower left-hand corner of the grid in the Minimum Longitude and Minimum Latitude boxes.

To give the overall geographic size of the grid, provide the number of Columns Per Longitudeand Rows Per Latitude. For example, if there are 16 columns and 2 columns per degreelongitude, then the grid will span 8 degrees longitude. And if there are 25 rows and 4 rows perdegree latitude, then the grid will span 6.25 degrees of latitude.

Combining the numbers in this example, if the minimum longitude and latitude are -81 and 38 andthe grid spans 8 degrees longitude and 6 degrees latitude, then the grid will run between -81 and-73 degrees longitude and between 38 and 44.25 degrees latitude.

After defining the grid, click the Preview button to see what the grid looks like. You may change

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the parameters and click the Preview again to see how the grid changes. When you are satisfiedwith the grid definition, click the OK button.

The name of your newly defined grid will then appear in the Manage Grid Definitions window. You may click Edit to change the grid definition, Delete to permanently remove the grid thatyou just defined, Add to define a new grid definition, or OK to get back to the Manage Setupswindow.

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4.1.1.2 Shapefile Grid

Shapefiles used to create Shapefile Grid Definitions should be of the ESRI® Shapefile format. Details on this format can be found at http://downloads.esri.com/support/whitepapers/other_/shapefile.pdf. Shapefiles used must be unprojected - that is, they should store their geographicinformation as decimal degree latitude and longitude values. If your shapefile is already projected,you will want to use a program like ArcGIS® to reproject the shapefile using the NAD 1983datum. Finally, any shapefiles used must contain integer fields named Column (or Col) and Row, and each shape within the shapefile must contain a unique combination of values for these twofields. These column and row values are used, just as the Column and Row field values inRegular Grid Definitions, to link the Shapefile Grid Definition with other sources of data, asdiscussed in more detail below.

To add a Shapefile Grid, click on the Add button in the Manage Grid Definitions window,choose the Shapefile Grid tab, name the grid in the Grid ID, and browse for the correctshapefile by clicking on the small open-file icon just to the right of the Load Shapefile box.

After locating the file in the Browse for a Shapefile window, click Open. This will choose thefile, and bring you back to the Grid Definition window. To view the shapefile, choose Preview.

When you are satisfied that the shapefile looks correct, click OK. This will bring you back toManage Grid Definitions window. Note that the Grid Type box displays the type of grid foreach of your grid definitions.

Click OK when you are finished loading grid definitions. The Manage Setups screen will nowlist the Grid Definitions that you have just created. At any time, you may click the Edit button

http://downloads.esri.com/support/whitepapers/other_/shapefile.pdf

http://downloads.esri.com/support/whitepapers/other_/shapefile.pdf

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to add, modify, or delete grid definitions.

Note that if you delete a Grid Definition you will delete any data that is dependent on it, such asany Incidence, Prevalence, Population, and Variable DataSets that use this particular GridDefinition. As we discuss below each of these other elements of a setup, we will describe howthis might happen.

4.1.2 Pollutants

The Pollutants section of a setup specifies the pollutants that BenMAP will analyze and definesthe air quality metrics to be used by BenMAP. You are not importing air pollution data, butrather naming your pollutants and defining the measures or metrics BenMAP will use whenperforming a benefit analysis for each pollutant. You may include any pollutant, though typicallyair pollutants such as particulate matter, ozone, sulfur dioxide, and carbon monoxide are used in aBenMAP analysis.

A key concept for pollutants is the Metric. Air quality metrics are daily values calculateddirectly from daily observations, or through various mathematical manipulations of hourlyobservations. Typical ozone metrics include the highest hourly observations during the course ofeach day, the average of all twenty four hourly observations, etc. In a benefit analysis, the airquality change must be expressed in a metric that matches the metric used by the health impactfunction; this concept is discussed further below.

In general, air pollution data in BenMAP is hierarchical – a pollutant can have multiple Metrics,each of which has multiple Statistics (these are automatically calculated by BenMAP) and whichcan have multiple Seasonal Metrics. Similarly, Seasonal Metrics have multiple Statistics.Furthermore, air pollution data can be provided to BenMAP at any of these levels, in addition tothe daily/hourly observation level, as described in more detail in Section 4.3.

To start adding pollutant definitions to BenMAP, click on the Edit button below the Pollutantsbox of the Manage Setups window. The Manage Pollutants window will appear. Here youmay click Add to add a new Pollutant, Delete to remove a previously defined pollutant, or Editto modify an existing pollutant.

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Add a Pollutant

Air pollution data in BenMAP is of two types - point source monitoring data, and GridDefinition based modeling data. For both types, the data must be associated with a particularpollutant. Table 4-1 describes these variables used to define a pollutant in BenMAP.

Table 4-1. BenMAP Pollutant Definitions

Pollutant Field Name Notes

Pollutant IDUnique name for the pollutant which will be referenced in health impact functions,

associated with monitoring and modeling data, etc.

Observation Type

Pollutants may have hourly observations or daily observations. In the UnitedStates, Ozone has hourly observations, while PM

10 and PM

2.5 have daily

observations.

Metrics

Daily values calculated directly from daily observations, or through variousmathematical manipulations of hourly observations. Typical ozone metrics include

the highest hourly observations during the course of each day, the mean of alltwenty four hourly observations, etc.

Seasonal MetricsSeasonal values calculated from metric values. In the United States, for example,

quarterly means are calculated for PM2.5

from daily means.

To start defining a pollutant, click the Add button and the Pollutant Definition window willappear. In the Pollutant ID box, you give a unique name for the pollutant (e.g., PM

2.5), and then

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define the characteristics of this pollutant – the Observation Type and Metrics.

The Observation Type identifies whether a pollutant is measured hourly or daily. In the UnitedStates, ozone, sulfur dioxide, carbon monoxide, and others have hourly observations, whileparticulate matter has daily observations. Use the Observation Type drop-down menu tochoose either the Hourly or Daily observation type.

Next you need to define a pollutant’s Metrics. A pollutant has to have one or more metrics,which are daily values calculated directly from daily observations, or through variousmathematical manipulations of hourly observations.

To add a Metric, click on the Add button below the Metrics box. A default name Metric 0will appear in the box. Since the default name is not very descriptive of a metric, it is best tochange the name. Typical names used for metrics given in Table 4-2. These are provided just asan example, and you may use any names that you like. However, keep in mind that the namesthat you use for your metrics need to be consistent with the metric names that you include in yourair pollution monitoring and modeling data, as well as your health impact functions. (We willdiscuss this further below.) Additionally, metric names are used to display pollutantconcentrations in BenMAP’s mapping window. As such, they must be consistent with GISnaming conventions, meaning they must begin with a letter, and may only contain letters, numbers,and underscores.

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Table 4-2. Examples of Metric Names

Name Description

D1HourMax Highest hourly value from 12:00 A.M. through 11:59 P.M.

D24HourMean Average of hours from 12:00 A.M. through 11:59 P.M.

D8HourMax Highest eight-hour average calculated between 12:00 A.M. and 11:59 P.M.

4.1.2.1 Hourly Metrics

Pollutants that are measured hourly (Observation Type = Hourly), such as ozone, sulfurdioxide, carbon monoxide, and others, must be characterized by a daily metric, whichmathematically summarizes the hourly observations.

Table 4-2 lists some of the ways that metrics can be generated from hourly values. Note thatthese metrics are not arbitrarily chosen, and instead match the metrics used in epidemiologicalstudies.

The Hourly Metric Generation portion of the Pollutant Definition window lets you define themetrics that you want to use. There are three tabs that you may choose: Fixed Window,Moving Window, and Custom.

The Fixed Window tab lets you define simple metrics which are calculated as statistics over afixed window of hours (Start Hour and End Hour) within each day. The Start Hour should beless than or equal to the End Hour, and both can range from 0 to 23, where 0 stands for theperiod 12:00 am to 12:59 am, and 23 stands for 11:00 pm to 11:59 pm. The Statistic includesthe Mean, Median, Max, Min, and Sum. Some examples follow:

D24HourMean: The mean of the observations from 12:00 am through 11:59 pm.Start Hour = 0. End Hour = 23. Statistic = Mean.

D1HourMax: The highest hourly value of the observations from 12:00 am through11:59 pm. Start Hour = 0. End Hour = 23. Statistic = Max.

D12HourMean: The mean of the daylight observations, defined as the period from8:00 am through 7:59 pm. Start Hour = 8. End Hour = 19. Statistic = Mean.

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The Moving Window tab lets you consider metrics that are not based on the same set of hourseach day. The Window Size defines the number of hours that will be considered together. TheWindow Statistic defines how the hours in the Window Size will be characterized. And theDaily Statistic defines how BenMAP will use the statistics generated for each window.

For example, consider the highest eight-hour mean (D8HourMax) over the course of a day. Youwould have the following settings: Window Size = 8. Window Statistic = Mean. DailyStatistic = Max. BenMAP would calculate every possible eight-hour mean, starting with theeight-hour mean from 12:00 am through 7:59 am, and ending with the eight-hour mean from 4:00pm through 11:59 pm. This would generate 17 possible eight-hour means. BenMAP would thenchoose the eight-hour mean that has the highest value.

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The Custom tab lets you define Metrics using customized functions. These functions caninclude measures such as the sum of the number of hours of ozone exposure about 60 parts perbillion. The possibilities are quite diverse, as evidenced by the range of functions and variablesavailable for use in Table 4-3. However, the syntax for using these functions is somewhatinvolved, so we have reserved discussion of this for the Function Editor appendix.

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Table 4-3. Available Functions and Variables for Custom Metrics

AvailableFunctions Description Available Variables Description

ABS(x) Returns the absolute valueof x.

Observations[i] All hourly observations for theyear (index begins at zero,typically ranging to 8,760).

EXP(x) Returns e the power x, wheree is the base of the natural

logarithm.

DailyObservations[i] All hourly observations for theday (indexed zero to twenty-

three).

IPower(x,y) Returns x to the power y (yan integer value).

SortedObservations[i] All hourly observations for theday, sorted from low to high

(indexed zero to twenty-three).

LN(x) Returns the natural logarithmof x.

Day Index of the day whose metricvalue is being generated (index

begins at zero).

POWER(x,y) Returns x to the power y (y afloating point value).

Mean Mean of the daily observations.

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AvailableFunctions Description Available Variables Description

SQR(x) Returns the square of x. Median Median of the dailyobservations.

SQRT(x) Returns the positive squareroot of x.

Min Minimum of the dailyobservations.

Max Maximum of the dailyobservations.

Sum Sum of the daily observations.

NoObservation Flag value indicating a missingobservation (-345)

4.1.2.2 Seasonal Metrics

Seasonal Metrics allow users to aggregate daily Metric values. This has a number of uses.For example, if pollutant values vary greatly by season, you can calculate separate pollutantmeasures for each season of interest. You might be interested in dry season versus wet season,or differences between Winter, Spring, Summer, and Fall.

To add seasonal metrics, click on the Edit button below the Seasonal Metrics box. TheManage Seasonal Metrics window will appear.

To add a Seasonal Metric, click on the Add button below the Seasonal Metrics box. Adefault name Seasonal Metric will appear in the box. Since the default name is not verydescriptive, it is best to change the name to something more informative such as the QuarterlyMean. As with the Metric names, keep in mind that the Seasonal Metric namesthat you use need to be consistent with the metric names that you include in your air pollutionmonitoring and modeling data, as well as your health impact functions.

The next step is to define the seasons that you want associated with your Seasonal Metricname. For example, in the case of a Quarterly Mean, you would want to define four seasons.To start this process, click on the Add button below the Seasons box. Then, in the far right sideof the window under Selected Season Details, give the Start Date and End Date for eachseason.

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Next, you need to choose the Statistic tab or the Custom tab to determine how the dailyMetrics will be combined in each season. For example, you might choose the Mean from thedrop-down list on the Statistics tab. This would calculate the mean of the daily metrics in eachseason. The Custom tab allows seasonal metric values to be calculated using customizedfunctions, similar to those used to calculate daily metric values from hourly observations. See the Function Editor appendix for more detail on this topic.

Once you have finished defining the Seasonal Metrics, click OK to return to the PollutantDefinition window.

Click OK after defining each Pollutant - this will return you to the Manage Pollutants window.

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4.1.2.3 Advanced Pollutant Options

The Advanced Pollutant Options button allows you to associate Seasons with a Pollutant.These seasons differ somewhat from the Seasonal Metrics discussed above. They are used todefine:

The portion of the year for which benefits are calculated for a Pollutant. Forexample, in the United States ozone benefits are only calculated for the ozoneseason, which is assumed to be May 1 through September 30.

The portion(s) of the year for which missing pollutant concentrations are filled in byBenMAP. That is, in order to calculate benefits, BenMAP in certain cases needs togenerate complete sets of metric values by estimating concentrations for those dayswhich have missing observations. This can be important if certain seasons tend tohave more missing values than others.

The portion(s) of the year for which monitor data is scaled by modeling data whencreating Monitor Model Relative air quality grids (discussed in the Air Quality GridCreation chapter).

To define Seasons for a Pollutant, click the Advanced Pollutant Options button. This willbring up the Define Seasons window. For each season desired, click the Add button, selectthe appropriate Start Date and End Date, which define the days included in the season; theappropriate Start Hour and End Hour, which define the hours included in Monitor ModelRelative scaling; and the appropriate Number of Bins, which define the number of bins used inMonitor Model Relative scaling. The advanced options for PM

2.5 look like the following:

Once you have finished defining the Seasons, click OK to return to the Pollutant Definitionwindow.

If you later wish to View or Edit a particular Pollutant definition, simply select the appropriate

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Pollutant within the Available Pollutants box and click the Edit button. When you are done,click OK to return to the Manage Setups window.

After defining all of the pollutants that you want to consider, click OK. This will return you tothe Manage Setups window.

4.1.3 Monitor Data

The Monitor DataSets section of the Manage Setups window allows to you to add airpollution monitoring data to your setup. Air pollution monitoring data may be used alone, or inconjunction with air pollution modeling data, to estimate ambient pollution levels in each grid celldefined by a Grid Definition. BenMAP uses a variety of procedures (such as VoronoiNeighbor Averaging, discussed later) to interpolate the monitor data points across the area ofinterest.

NOTE: Air pollution data in BenMAP is of two types - point source monitoring data, and GridDefinition based modeling data. Both types of data must be associated with a particularpollutant that you have defined. Only the point source monitoring data is stored in the setupdatabase. The modeling data are loaded into BenMAP as you need them for a particularanalysis.

To start, click on the Edit button below the Monitor DataSets box. The Manage MonitorDataSets window will appear. From this window you may Add monitoring data, view and Editexisting datasets, as well as Delete them. The section on the left under Available DataSets liststhe monitor datasets that are currently in the setup. The section on the right under the DataSetContents identifies the number of monitors in each dataset by pollutant and by year.

To start adding data, click the Add button. This will bring up the Monitor DataSet Definitionwindow. Give the dataset a name in the DataSet Name box, choose the appropriate pollutantfrom the Pollutant drop-down menu, and then type the year of the data in the Year box.

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NOTE: The DataSet that you define can have one or more pollutants and multiple years of data. If your data come from a single source, for simplicity it probably makes sense to combine thesedata into a single DataSet.

Now choose one of the three tabs (Database, Columns; Database, Rows; or Text File) thatmatches the format of your data. Monitor data may be formatted in three different ways: (1) intwo database files/tables, with monitor definition information in rows in one file/table and monitorvalues in a single column in the other file/table (Database, Columns format), (2) in a databasefile, with monitor definition information and monitor values in a single line (Database, Rowsformat), and (3) in a text file, with monitor definition information and monitor values in a single line(Text File format). There is no preferred approach, and instead use the approach with which youare most comfortable. (We define these formats in detail below.)

Click on the Browse button next to the Monitor Data File box. This will bring up a windowfrom which you can browse the BenMAP Data directory to find the desired data file. The Filesof type drop-down menu allows you to choose from a variety of file types.

Click Open. This will choose the file, and bring you back to the Monitor DataSet Definitionwindow. If you are using the Database, Columns format, you will need to repeat thisprocedure with the Monitor Definition File. To add monitors from the selected file(s), clickLoad Monitor Data.

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Follow this same procedure to load all of your monitoring data. Select the pollutant from the Pollutant drop-down menu, edit the Year box, choose the tab that matches the database formatthat you are using, and select the appropriate file(s) by clicking the Browse button(s). When youhave clicked Load Monitor Data for your final dataset, click OK. This will bring you back tothe Manage Monitor DataSets window.

To see the years of data and the number of monitors each year, use the scrollbars on the bottomand on the right of the DataSet Contents box.

If desired you can add additional monitor datasets (click the Add button), delete existing datasets(select the dataset in the Available DataSets list and click the Delete button), or edit existingdatasets (select the dataset in the Available DataSets list and click the Edit button).

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When you have finished loading your monitor data, click OK in the Manage MonitorDataSets window. This will take you back to the Manage Setups window, which will show thename of the DataSet(s) that you just entered.

4.1.3.1 Format Monitor Data

Monitor data may be formatted in three different ways. There is no preferred option. Simply usewhichever method seems most appropriate.

Database, Columns format. Two database files/tables, with monitor definition information in rowsin one file/table and monitor values in a single column in the other file/table.

Database, Rows format. One database file, with monitor definition information and monitor values in a single line.

Text File format. One text file, with monitor definition information and monitor values in a singleline.

Tables 4-4a through 4-4d present the variables in each of the datasets when using the columnsformat and a sample of what the files might look like. Tables 4-5a and 4-5b present the variablesin the dataset when using the rows format and a sample of what a data file might look like.

NOTE: The monitor data files do not specify the pollutant with which the data is associated - thisis specified by the user when loading the monitor data into BenMAP.

Table 4-4a. Column Format, Air Monitor Definition Variables

Variable Type Required Notes

MonitorName

text yes Unique name for the monitor.

Description text no Description of the Monitor.

Longitude numeric(double)

yes Values should be in decimal degree format. Values in the easternhemisphere are positive, and those in the western hemisphereare negative.

Latitude numeric(double)

yes Values should be in decimal degree format. Values in thenorthern hemisphere are positive, and those in the southernhemisphere are negative.

Table 4-4b. Column Format, Sample Air Monitor Definition File

Monitor Name Description Latitude Longitude

Monitor1 City Park 40.107222 -74.882222

Monitor2 Industrial Site 39.835556 -75.3725

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Monitor Name Description Latitude Longitude

Monitor3 Suburban 40.112222 -75.309167

Monitor4 Rural 39.94 -75.6

Table 4-4c. Column Format, Air Monitoring Data Set Variables


Metric text no This variable is either blank (signifying that the Values areObservations, rather than Metric values), or must reference an

already defined Metric for the appropriate Pollutant.

SeasonalMetric

text no This variable is either blank (signifying that the Values are notSeasonal Metric values) or must reference an already defined

Seasonal Metric for the Metric.

Statistic text no This is an annual metric, which is either blank (signifying that thevalues are not annual statistics) or must be one of: None, Mean,

Median, Max, Min, Sum.

Monitor Name(s)

numeric(double)

yes Each of these field names should match up with a value in theMonitor Name field in the Definitions file. The values will be

observations, metric, seasonal metric, or annual metric values, asdetermined by the values of the other fields.

Table 4-4d. Column Format, Sample Air Monitoring Data File

Table 4-5a. Row Format, Air Monitoring Data File Variables


Monitor Name text yes Unique name for each monitor in a particular location.

Description text no Description of the Monitor.

Longitude numeric(double)

yes Values should be in decimal degree format. Values in the easternhemisphere are positive, and those in the western hemisphere are

negative.

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Latitude numeric(double)

yes Values should be in decimal degree format. Values in the northernhemisphere are positive, and those in the southern hemisphere are

negative.

Metric text no This variable is either blank (signifying that the Values areObservations, rather than Metric values), or must reference an

already defined Metric (e.g., 1-hour daily maximum) for theappropriate Pollutant.

SeasonalMetric

text no This variable is either blank (signifying that the Values are notSeasonal Metric values) or must reference an already defined

Seasonal Metric for the Metric (e.g., mean of the 1-hour maximumfor the months of June through August).

Statistic text no This is an annual metric, which is either blank (signifying that thevalues are not annual statistics) or must be one of: None, Mean,

Median, Max, Min, Sum. (e.g., mean of the 1-hour maximum for theyear)

Values commaseparated

values(text)

yes If Metric is blank, either 365 or 8,760 comma separatedobservations (depending on whether the Pollutant has daily orhourly observations). If Metric is defined, but Seasonal Metricand Statistic are blank, 365 metric values. If Seasonal Metric is

defined, but Statistic is blank, n seasonal metric values. If Statisticis defined, one annual statistic value (for either the Metric (if

Seasonal Metric is blank) or the Seasonal Metric. Missing valuesare signified with a period ('.').

Table 4-5b. Row Format, Sample Air Monitoring Data File

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4.1.4 Incidence/Prevalence Data

Most health impact functions, such as those developed from log-linear or logistic health impactfunctions, estimate the percent change in a health effect associated with a pollutant change. Inorder to estimate the absolute change in incidence using these functions, the baseline incidencerate (and in some cases the prevalence rate) of the adverse health effect are needed.

The incidence rate is the number of health effects per person in the population per unit of time,and the prevalence rate is the percentage of people that suffer from a particular chronic illness. For example, the incidence rate for asthma attacks may be 25 cases per asthmatic individual peryear, and the prevalence rate (measuring the percentage of the population that is asthmatic) mightbe six percent.

NOTE: For both incidence and prevalence rates, BenMAP allows the user to have rates thatvary by race, ethnicity, gender, and age group. BenMAP can support multiple sets of incidenceand prevalence rates, if the rates differ by year or by grid definition.

To start adding incidence and prevalence data files, click on the Edit button below theIncidence/Prevalence DataSets box. The Manage Incidence DataSets window willappear.

In this window you may Add, Edit, and Delete datasets. The section on the left underAvailable DataSets lists the incidence/prevalence datasets that are currently in the setup. Thesection on the right under the DataSet Incidence Rates identifies the rates in the selecteddataset.

To add a dataset, click the Add button. This will bring up the Incidence DataSet Definition.Give a name to the dataset that you are creating by typing a name in DataSet Name box.

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NOTE: If you have multiple incidence/prevalence datasets that vary by, say, year and griddefinition, then use the name to provide a reference to the year and grid definition.

Click the Load From Database button. In the Grid Definition drop-down list choose the griddefinition that matches the grid definition used to develop the incidence/prevalence dataset. Thenclick on the Browse button, to browse for the dataset file. (The format for the dataset is detailedin the next sub-section.)

After finding the file, click OK. The Incidence DataSet Definition window will appear,displaying the rates in the data file that you just loaded.

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If the data look correct, click OK. This will return you to the Manage Incidence DataSetswindow.

Follow the same procedure for any additional incidence/prevalence datasets that you want to addto the setup database. When you have finished adding data, click OK in the ManageIncidence DataSets window. The Incidence/Prevalence DataSets box in the Manage

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Setups window will show the datasets that you have entered.

4.1.4.1 Format Incidence/Prevalence Data

Table 4-6a presents the variables that can be used in incidence and prevalence datasets, andTable 4-6b presents a sample dataset that follows this format.

Table 4-6a. Health Incidence and Prevalence Data Set Variables

Field Name Type Required Notes

Endpoint Group text yes If this does not reference an already defined Endpoint Group,one will be added.

Endpoint text yes If this does not reference an already defined Endpoint for theEndpoint Group, one will be added.

Race text no Should either be blank (signifying All Races) or reference adefined Race, such as "Black" (from one or more Population

Configurations).

Ethnicity text no Should either be blank (signifying All Ethnicities) or referencea defined Ethnicity, such as "Hispanic" (from one or more

Population Configurations).

Gender text no Should either be blank (signifying All Genders) or reference adefined Gender (from one or more Population Configurations).

Start Age integer yes Specifies the low and high ages, inclusive. For example, StartAge of “0" and End Age of “1" includes infants through the

first 12 months of life and all one-year old infants.End Age integer yes

Column integer yesThe column and the row link the incidence/prevalence data

with cells from a Grid Definition. Row integer yes

Value numeric(double)

yes The incidence/prevalence rate for the specified demographicgroup for this location.

Type text no If value is a prevalence rate, then “Prevalence” should bespecified. Otherwise BenMAP assumes that the value is an

incidence rate.

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Table 4-6b. Sample Health Incidence and Prevalence Data Set

4.1.5 Population Data

The population data is used to estimate population exposure and in turn any adverse healtheffects associated with a change in air pollution. BenMAP allows the user to specify race,ethnicity, gender, and age of the population, as well as the year of the population estimate.

Population data loaded into BenMAP must be associated with a Population Configuration,which defines the races, ethnicities, genders, and age ranges present in the data. Race, ethnicity,and gender are unique text values representing population subgroups. Age ranges are defined byinteger values for starting age and ending age (inclusive), and a unique text value representing thename of the age range. For example, “0TO1” might be used as a name for the age range definedby a start age of zero and an end age of one, thus consisting of infants through the first twelvemonths of life and all one-year old infants. The population data provided to BenMAP shouldthen contain population values for all combinations of race, ethnicity, gender, and age range. Thepopulation values may be real numbers (e.g., non-integer values).

Population data must also be associated with a Grid Definition which specifies the geographicareas for which the data is available (see for more details the section on Grid Definitions). Ifpopulation data is available for multiple grid definitions (cities and neighborhoods, for example),users can have the option of using different sets of population data for different analyses. BenMAP can also estimate populations for Grid Definitions for which no population data isavailable by calculating spatial overlap percentages with Grid Definitions for which data isavailable.

To add population data to BenMAP, click on the Edit button below the Population DataSetsbox in the Manage Setups window. The Manage Population DataSets window will appear.

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Click on the Add button.

This brings up the Load Population DataSet window, which has a number of importantfeatures. The Population DataSet Name box allows you to name the dataset.

The Population Configuration Definition window allows you to define the variables that are inthe population data file to be loaded into BenMAP. Use the drop-down list to choose an existingpopulation configuration and then view it by clicking the View button, or you may click the Addbutton and define a new population configuration.

The Grid Definition drop-down list provides the list of existing grid definitions, and you need tochoose the grid definition that matches that in the population dataset. The Browse button to theright of the Database box allows to find the datafile that you want to load into BenMAP.

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The Use Population Growth Weights checkbox should be checked when using populationdata generated by the PopGrid software application. The population weights file assists inforecasting population levels. This topic is fairly involved, so we have deferred discussion untilthe appendix.

Defining a Population Configuration

The Population Configuration defines the age range, race, and gender of the variables in yourpopulation database. It is critical that the definitions in the population configuration match thoseused in the development of the database. If they do not match exactly, BenMAP will fail to loadthe population data. (If this occurs, you need to go back and either develop a new populationconfiguration to match your data, or you need to revise your population database so that itmatches the population configuration.)

To add a population configuration, click the Add button in the Load Population DataSetwindow.

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In the Population Configuration Name, replace "PopulationConfiguration 0" with a name of yourchoosing. Under the Races box click on New and type in the name for any races present in yourpopulation data. The names appear in both the Races list box and the Available Races listbox. (If you later create alternative population configurations, you can simply drag the relevantnames from the Available Races list box into the Races list box.) Similarly, under theAvailable Genders and Available Ethnicity list boxes click on New and type in the name forany ethnicity and gender identifiers present in your population data.

If you want to remove a category in Races, Genders, and Ethnicity list boxes, then highlightthe entry that you want to remove and click the Remove button. (It is not possible to removeentries from either the Available Races, Available Genders, or Available Ethnicity listboxes.)

The next step is to create the age groups that match the age groups in your population file. To

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start click on the Add button below the Age Ranges list box. The AgeRange Definitionwindow will appear. Type in the name of the age variable in the Age Range ID box and theupper bound of the age range in the High Age box. (BenMAP automatically fills in the value forthe Low Age box.) For example, the age range names (with corresponding low and high ages)might include the following: 0to0, 1to4, 5to9, 10to14, 15to19, 20to24, 25to29, 30to34,35to39, 40to44, 45to49, 50to54, 55to59, 60to64, 65to69, 70to74, 75to79, 80to84, and85up. The choice of the names is up to you. However, you must be sure that the names exactlymatch those in your population datafile.

Click OK when you have defined the age range. If you make a mistake and want to delete anage definition after you have entered it, click on the Delete button. This will remove the last agegroup that you have entered. (Click on it twice if you want to remove the last two age groupsthat you entered.) The population configurations can be quite detailed as in the case of theUnited States Census population configuration that comes loaded with BenMAP.

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Or the population configuration can be somewhat simpler as in the case of the populationconfiguration for CityOne -- also pre-loaded with BenMAP:

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Click OK to return to the Load Population DataSet window. From the Grid Definitiondrop-down list choose the grid definition (e.g., Tract). Then click on the Browse button to theright of the Database box to choose the population data file to be loaded into BenMAP.

To finish loading the population datafile, click OK. The Manage Population DataSetswindow will appear displaying the characteristics of the available population datafile that you justloaded and any other datasets that have already been loaded into BenMAP.

Click OK. In the Population DataSets box of the Manage Setups window you should see anentry for the population dataset that you just loaded.

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4.1.5.1 Format Population Data

Table 4-7 presents the variables that can be used in population datasets. Note that the namesused for the age ranges do not need to follow this same pattern, and instead should be based onwhat seems most appropriate for you.

Table 4-7. Population Data Set Variables


Age Range text yes References a defined age range in the associatedPopulation Configuration.

Column integer yesThe column and the row link the population data with cells

in a Grid Definition.Row integer yes

Year integer yes The year of the data. Note that this may include historicalpopulation estimates (such as from a census), as well as

population forecasts.

Population numeric (double) yes Population estimate. Note that the estimate is notrestricted to integers.

Race text yes References a defined race in the associated PopulationConfiguration.

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Ethnicity text no References a defined ethnicity in the associated PopulationConfiguration.

Gender text yes References a defined gender in the associated PopulationConfiguration.

4.1.6 Health Impact Functions

Health impact functions calculate the change in the number of adverse health effects among acertain population associated with a change in exposure to air pollution. A typical health impactfunction has inputs specifying the pollutant; the metric (daily, seasonal, and/or annual); the age,race, ethnicity, and gender of the population affected; and the incidence rate of the adverse healtheffect.

Health impact functions are subdivided by user-specified types of adverse health effects. Thebroadest category is the Endpoint Group, which represents a broad class of adverse healtheffects, such as premature mortality, cardiovascular-related hospital admissions, and respiratory-related hospital admissions, among other categories. (BenMAP only allows pooling of adversehealth effects to occur within a given endpoint group, as it generally does not make sense to sumor average together the number of cases of disparate health effects, such as premature mortalityand chronic bronchitis.) The Endpoint Group may then be subdivided by user-specifiedEndpoints. For example, the respiratory-related hospital admission Endpoint Group, may haveseparate Endpoints for Asthma-related hospital admissions and chronic bronchitis-relatedhospital admissions.

There are a wide range of variables that can be included in a health impact function, to specify theparameters of the function and to identify its source, such as the author, year, and location of thestudy, as well as other pollutants used in the study. The bibliographic reference for the study maybe included, as well as any additional information needed to identify a particular impact function. (The Reference and Qualifier variables are useful for this.) A number of health impactfunctions have been developed based on epidemiological studies in the United States andEurope. However, researchers have conducted an increasing number of epidemiological studiesin Asia and Latin America that can be used to develop more location-specific impact functions.

There are a number of issues that arise when deriving and choosing between health impactfunctions that go well beyond this user manual. Hence, it is important to have a trained healthresearcher assist in developing the impact function data file.

To add health impact functions to BenMAP, click on the Edit button below the C-R FunctionsDataSets box in the Manage Setups window. The Manage C-R Functions DataSetswindow will appear.

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In this window you may Add, Edit, and Delete datasets. The section on the left underAvailable DataSets lists the health impact function datasets that are currently in the setupdatabase. The section on the right under the C-R Functions in DataSet lets you view thefunctions in a selected dataset.

To add a new dataset, click the Add button. The C-R Function DataSet Definition windowwill appear. Type the name that you want to use for the dataset in the C-R Function DataSetName box.

You may then enter functions into this dataset through an externally created database by clickingthe Load From Database button. Alternatively, you may Add, Delete, and Edit individualsfunctions within BenMAP.

To add a database click the Load From Database button. In the Load a C-R FunctionDatabase window, click the Browse button and then find and select the health impact functiondatabase that you want to load into your setup.

The C-R Function DataSet Definition window will reappear, and you can then view the healthimpact functions that you have loaded into your dataset. Note that the central boxed area in thiswindow has two parts. On the left is the Tree and on the right is the Data.

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The columns within each of the list boxes can be rearranged in order to provide the most usefuldisplay. By clicking and holding the cursor on a column, you may move it within either the Treeor Data boxes, or you may move columns between boxes. For example, by clicking and holdingon the Pollutant column and then dragging it to the far left of the tree, you can sort all of thehealth impact functions by Pollutant. (Note rearranging the columns is only for display and has noeffect on the underlying health impact function database.)

Clicking OK brings you back to the Manage C-R Function DataSets window. Here youhave the opportunity to view the functions in your dataset. If you have more than one dataset,you can choose the dataset that you want to view in the Available DataSets in the left-handsection of the window. In the C-R Functions in DataSet in the right-hand section of thewindow, you have the same Tree and Data structure that you have in the C-R FunctionDataSet Definition window.

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You may edit this dataset by clicking the Edit button. This will bring up the C-R FunctionDataSet Definition window. You may load an additional database to your dataset, or youmay Add, Edit, and Delete individual functions directly in BenMAP.

To edit an existing function, highlight a particular function in the C-R Function DataSetDefinition window, and then click the Edit button. The C-R Function Definition windowappears, and you may change any of the values in the boxes and the drop-down lists. When youare finished click OK.

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From the C-R Function DataSet Definition window you can also add health impact functionsto the ones that are already in your dataset. Click the Add button and a blank C-R FunctionDefinition window will appear, and you can then create new health impact functions. (We willdiscuss this in more detail in subsequent examples.)

After defining the new health impact function, click OK. This will take you back to the C-RFunction DataSet Definition window. When you are finished with any editing or adding ofhealth impact functions click OK. The Manage Setups window will appear. Here in the C-RFunction DataSets box you should see an entry for any health impact function datasets that youhave loaded.

4.1.6.1 Format Health Impact Functions

Table 4-8 presents the variables that can be used in health impact function datasets.

Table 4-8. Health Impact Function Data Set Variables


Endpoint Group text yes If this does not reference an already defined Endpoint Group,one will be added.

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Endpoint text yes If this does not reference an already defined Endpoint for theEndpoint Group, one will be added.

Pollutant text yes Should reference an already defined Pollutant.

Metric text yes Should reference an already defined Metric for the Pollutant.

Seasonal Metric text no Should either be blank (signifying no Seasonal Metric value)or reference an already defined Seasonal Metric for the Metric.

Statistic text no Should either be blank (signifying no annual metric value) orbe one of: None, Mean, Median, Min, Max, Sum.

Race text no Should either be blank (signifying All Races) or reference adefined Race.

Ethnicity text no Should either be blank (signifying All Ethnicities) or referencea defined Ethnicity.

Gender text no Should either be blank (signifying All Genders) or reference adefined Gender.

Start Age

End Age

integer yes Specifies the low and high ages, inclusive. For example, StartAge of “0" and End Age of “1" includes infants through the

first 12 months of life and all one-year old infants

Author text no The author(s) of the study from which the function is derived.

Year integer no The year of publication of the study.

Location text no The location of the study.

Qualifier text no Provides additional information to identify a particular healthimpact function, such as when a particular study has multiple

functions.

OtherPollutants

text no Identifies other pollutants that were included simultaneouslyin the estimation equation for the pollutant of interest.

Reference text no Bibliographic reference, included to identify the source in thehealth literature.

Function text yes The functional form, interpreted (executed) by BenMAP whenrunning an analysis to estimate air pollution-related health

impacts. For example, the log-linear form is as follows: “(1-(1/EXP(Beta*DELTAQ)))*Incidence*POP”.

BaselineIncidenceFunction

text no The functional form, interpreted (executed) by BenMAP toestimate health impacts due to all causes. This typically has

the form: "Incidence*POP".

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Beta numeric(double)

no Mean value of the Beta distribution.

DistributionBeta

text no If the Beta has no distribution, any value is acceptable. Otherwise, should be one of: Normal, Triangular, Poisson,

Binomial, LogNormal, Uniform, Exponential, Geometric,Weibull, Gamma, Logistic, Beta, Pareto, Cauchy, Custom.

Parameter 1Beta

numeric(double)

no Parameter 1 of the Beta distribution (meaning depends on thedistribution - for Normal distributions this represents the

standard deviation).

Parameter 2Beta

numeric(double)

no Parameter 2 of the Beta distribution (meaning depends on thedistribution - for Normal distributions this is not required).

Name A text no Description of variable A.

A numeric(double)

no A constant value which can be referenced by the Function(see below).

Name B text no Description of variable B.

B numeric(double)

no A constant value which can be referenced by the Function(see below).

Name C text no Description of variable C.

C numeric(double)

no A constant value which can be referenced by the Function.

IncidenceDataSet

text no Specifies the dataset from which incidence data will bederived. The user may choose from multiple datasets.

(Initially this field may be left blank.)

PrevalenceDataSet

text no Specifies the dataset from which prevalence data will bederived. The user may choose from multiple datasets.

(Initially this field may be left blank.)

VariableDataSet

text no Specifies the dataset from which "variable" data (e.g., income data) will be derived. The user may choose from multiple

datasets. (Initially this field may be left blank.)

4.1.7 Variable Data

Health Impact functions and/or Valuation functions may sometimes refer to variables other thanthose for which BenMAP automatically calculates values. For example, some valuation functionsreference the median income within each area of analysis. To facilitate this, BenMAP allows youto load datasets of variables, which may either be global values or may vary geographically(meaning they are associated with a Grid Definition).

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To add variables to BenMAP (such as income and other miscellaneous variables that might beneeded in the analysis), click on the Edit button below the Variables DataSets box in theManage Setups window. The Manage Setup Variables DataSets window will appear.

In this window you may Add, Edit, and Delete datasets. The section on the left underAvailable DataSets lists the variables datasets that are currently in the setup database. Thesection on the right under the DataSet Variables lets you view the variables in a selecteddataset.

To add variables click the Add button. This will take you to the Setup Variable DataSetDefinition window. In this window you may add externally created variables through the LoadFrom Data button for any of your predefined grid definitions. Alternatively, by clicking the Addbutton you may create global variables to your dataset that are not tied to a specific geographicregion.

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To start, type the name that you want to use for the dataset in the DataSet Name box. (This isa name that is internal to BenMAP and used just for identification.)

To add an externally created variable database, click the Load From Database button. Thiswill bring up the Load Variable Database window choose. Here you need to choose the griddefinition from the Grid Definition drop-down list that matches the level of aggregation in yourvariable database. Then you may use the Browse button to find and select the desired data file.

After choosing the database, click OK. This takes you back to the Setup Variable DataSetDefinition window. This allows you to see the variables in the dataset and their values.

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You may also add Global variables to the dataset by clicking on the Add button in the SetupVariable DataSet Definition window. After clicking Add, type the name of the variable whereit says Setup Variable 0 in the DataSet Variables list box, and then in Value box type thevalue of the global variable.

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When finished adding variables, click OK. This will take you to the Manage Setup VariableDataSets window. In the Available DataSets list box there is an entry for the dataset that youjust added. And in the DataSet Variables list box are the variables in the highlighted dataset.

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At this point you may click Add to load an additional dataset, click Edit to edit the selecteddataset, click Delete to delete the selected dataset, or complete this variable management stepby clicking OK.

Clicking OK returns you to the Manage Setups window, where in the Variable DataSetsbox, you should see an entry for the variable dataset that you just created.

4.1.7.1 Format Variable Data

Table 4-9a presents the variables that can be used in variable datasets, and Table 4-9b presentsa sample of what a dataset might look like.

Table 4-9a. Variable Data Set Variables


Column integer yesThe column and the row link the population data with cells

in a Grid Definition.Row integer yes

Variable Name numeric(double)

no

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Table 4-9b. Sample Variable Data Set

COL ROW median_income42 17 39871.1942 29 43760.3142 45 38186.7742 91 42298.4942 101 31261.07

4.1.8 Inflation Data

It may be desirable for the dollar values generated by Valuation functions to account for inflation,and generate economic benefits for years other than the year initially specified by your valuationdata. To do this, you can load inflation data into BenMAP, and then include a reference to yourinflation data when developing valuation functions. (We give an example of this below.)

The valuation functions should have a consistent dollar year, and this dollar year has to be kept inmind when developing the inflation datasets. That is, whichever dollar year is used for yourvaluation functions, then the inflation values for that year should be set to 1. For example, in theU.S. setup, the valuation functions have a dollar year of 2000, so the inflation datasets have avalue of 1 for the year 2000. (Values for years earlier than 2000 are less than 1, and values foryears after 2000 are greater than 1, because inflation has increased from one year to the next.)

The U.S. setup in BenMAP provides inflation factors for three different types of values:

All Goods Index can be used to adjust the value of generic goods.

Medical Cost Index can be used to adjust the value of medical expenses.

Wage Index can be used to adjust the value of wages.

If a valuation function includes an estimate of wage income, for example, this value could bemultiplied by the Wage Index adjustment factor to get the specified currency year. Forexample, in valuing workloss days, the U.S. setup uses a function like the following:DailyWage*WageIndex, where the DailyWage is specified in year 2000 dollars. TheWageIndex scales this DailyWage value up or down depending on the currency year you havechosen. (The choice of currency year can be made with the One-Step Setup, discussed here,and with the Advanced button when creating an APV file, discussed here.) If the currency yearis 2000, then the WageIndex has a value of 1 and no change is made to the DailyWage. If thecurrency year is specified to, say, 2005, then the WageIndex will have a value greater than 1because of the inflation that has occurred between 2000 and 2005.

To add inflation data to BenMAP, click on the Edit button below the Inflation DataSets box inthe Manage Setups window. The Inflation DataSet Manager window will appear. In thiswindow you may Add, Edit, and Delete datasets. The section on the left under AvailableDataSets lists the inflation datasets that are currently in the setup database. The section on theright presents the inflation factors in a selected dataset.

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Click on the Add button. In the Load Inflation DataSet window, type in the name of thedataset in the Inflation DataSetName box, and then click on the Browse button to the right ofthe Database box to choose the dataset that you want to import. Click OK. The InflationDataSet Manager window will appear. Here you may view the data that you just loaded.

At this point you may add more data by clicking Add, or you may complete this step by clickingOK. Clicking OK takes you to the Manage Setups window, where in the Inflation DataSetsbox, you should see an entry for the inflation dataset that you just loaded.

4.1.8.1 Format Inflation Data

Table 4-10a presents the variables that can be used in inflation datasets, and Table 4-10bpresents a sample of what a dataset might look like. Note that if you are loading your owninflation data, you can use different names than the ones specified below. Instead of specifying"AllGoodsIndex" you could have a variable called "General Index" -- this is fine so long as youmake sure that your valuation functions properly reference these inflation variables.

Table 4-10a. Inflation Data Set Variables in U.S. Setup


Year integer yes The year of the data. Note that this will typically onlyinclude historical estimates.

AllGoodsIndex integer no All goods inflation index value.

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MedicalCostIndex integer no Medical cost inflation index value.

WageIndex integer no Wage inflation index value.

< variable name > integer no Additional indices can be specified.

Table 4-10b. Sample Inflation Data Set

YEAR AllGoodsIndex MedicalCostIndex WageIndex1995 0.75 0.62 0.711996 0.79 0.67 0.741997 0.81 0.72 0.761998 0.83 0.77 0.781999 0.86 0.8 0.812000 0.88 0.84 0.832001 0.91 0.87 0.862002 0.93 0.89 0.892003 0.94 0.92 0.922004 0.96 0.96 0.962005 1 1 12006 1.02 1.04 1.03

4.1.9 Valuation Data

BenMAP allows the valuation estimates to vary by Endpoint Group, Endpoint, and Age (notethat multiple estimates may be provided for a particular combination). BenMAP allows the valuation function to be quite detailed, and allows an uncertain parameter (A) with a user-specified distribution. The user can modify the valuation function with a number of constantvalues (B, C, and D) that might represent an adjustment for inflation, income growth, incomeelasticity, or, say, purchasing power parity. Finally, BenMAP has two fields to more clearlyidentify the valuation function (i.e., Qualifier and Reference).

When reviewing the economic literature to develop a valuation database or simply add additionalvaluation functions to an existing database, it is important to have an economist assist. For anoverview of valuation, see the Overview of Valuation section in the chapter on Aggregation,Pooling, and Valuation.

To add valuation functions to BenMAP, click on the Edit button below the Valuation DataSetsbox in the Manage Setups window. The Manage Valuation Function DataSets windowwill appear.

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In this window you may Add, Edit, and Delete datasets. The section on the left underAvailable DataSets lists the valuation datasets that are currently in the setup database. Thesection on the right under the Valuation Functions in DataSet lets you view the valuationfactors in a selected dataset.

To add a dataset click on Add. In the Valuation Function DataSet Name type the name ofthe dataset that will be added.

You may load valuation data with an externally-created database, or you may add individualvaluation functions from within BenMAP. To load an externally-created valuation database, clickon the Load From Database button. This will bring you to the Load a Valuation FunctionDatabase window.

In the Load a Valuation Function Database window use the File of Type drop-down list tochoose the type of file (e.g., MS Access Database). Choose the valuation database and click Open. This will bring you back to the Valuation Function DataSet Definition window. Hereyou can view the valuation functions that you have in your database.

Note that the large box is divided in two. On the left is the Tree and on the right is the Data.The tree can be expanded by clicking on the “+” sign, or contracted by clicking on the “-“ sign.

The columns within each of the list boxes can be rearranged in order to provide the most usefuldisplay. By clicking and holding the cursor on a column, you may move it within either the Treeor Data boxes, or you may move columns between boxes. (Note that rearranging the columns isonly for display and has no effect on the underlying Valuation function dataset.)

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In the Valuation Function DataSet Definition window you can also edit the functions alreadyexisting in your data set by highlighting a particular Valuation function and then clicking the Editbutton.

The Valuation Function Definition window allows you to change any of the values in the boxesand the drop-down lists. When you are finished click OK.

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From the Valuation Function DataSet Definition window you can also add Valuationfunctions to the ones that are already in your dataset. Click the Add button and a blankValuation Function Definition window will appear, and you can then create a new Valuationfunction.

After defining the new Valuation function, click OK. This will take you back to the ValuationFunction DataSet Definition window. When you are finished with any editing or adding ofvaluation functions click OK. The Manage Setups window will appear. Here in the ValuationFunction DataSets box you should see an entry for the valuation function dataset that you justloaded.

4.1.9.1 Format Valuation Data

Table 4-11 presents the variables that can be used in valuation datasets.

Table 4-11. Valuation Data Set Variables


Endpoint Group text yes If this doesn't reference an already defined Endpoint Group, onewill be added.

Endpoint text yes If this doesn't reference an already defined Endpoint for theEndpoint Group, one will be added.

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Qualifier text no Provides additional information to identify a particular valuationfunction.

Reference text no Bibliographic reference, included to identify the source in theeconomic literature.

Start Age integer no Specifies the low and high ages, inclusive. For example, StartAge of “0" and End Age of “1" includes infants through the

first 12 months of life and all one-year old infants.End Age integer no

Point Estimate numeric(double)

yes Central estimate of the unit value.

Function text yes The functional form, interpreted (executed) by BenMAP whenrunning an analysis. The BenMAP User Manual will contain

more information on the format of this field.

A Description text no Description of variable A.

A numeric(double)

no Mean of the A distribution.

A Distribution text no If A has no distribution, any value is acceptable. Otherwise,should be one of: Normal, Triangular, Poisson, Binomial,

LogNormal, Uniform, Exponential, Geometric, Weibull, Gamma,Logistic, Beta, Pareto, Cauchy, Custom.

A Parameter 1 numeric(double)

no Parameter 1 of the A distribution (meaning depends on thedistribution - for Normal distributions this represents the

standard deviation).

A Parameter 2 numeric(double)

no Parameter 2 of the A distribution (meaning depends on thedistribution - for Normal distributions this is not required).

ConstantDescription

text no Description of variables, B, C, and D.

Constant Value numeric(double)

NO A constant value (denoted by B, C, and/or D) which can bereferenced by the Function.

4.1.10 Income Growth Data

As real income increases, willingness-to-pay (WTP) to avoid air-pollution related morbidityeffects and premature mortality should grow. BenMAP allows users to adjust the WTP estimatesto account for the growth in income over time. This adjustment is a combination of data onincome growth and estimated income elasticity of demand, which measures the responsiveness ofthe quantity demanded of a good to the change in the income of the people demanding the good;this is distinct from elasticity of demand, which quantifies the change in demand for goods andservices as a result of changes in price for those goods and services. This section describes howto load the data adjusting for income growth and how EPA developed these adjustment factors.

Loading Data


Note that the WTP estimates in the default valuation functions in the U.S. setup are assumed tobe based on 1990 income, so the income growth adjustments are all relative to 1990. That is,the income growth data has a value of 1 in 1990, and because income has generally increasedover time in the U.S., the income growth values are typically greater than 1 after 1990. (Anexception is 1991, when incomes declined slightly in the U.S.)

If you load in your own valuation functions and/or income growth adjustment factors, be sure thatyou have carefully considered the income year. For example, if your valuation functions arebased on income in the year 2005, then the income growth adjustment should have a value of 1.0in 2005, because no adjustment is necessary. As you forecast into the future, under theassumption that incomes go up over time, then your income growth adjustment factors wouldhave values greater than 1.0 for years past 2005, and would have values less than 1.0 for yearsprior to 2005.

To add income growth data to BenMAP, click on the Edit button below the Income GrowthAdjustments box in the Manage Setups window. The Income Growth AdjustmentDataSet Manager window will appear.

In this window you may Add and Delete datasets. The section on the left under AvailableDataSets lists the income growth datasets that are currently in the setup database. The sectionon the right presents the income growth adjustment factors in a selected dataset.

Click on the Add button. In the Load Income Growth Adjustment Factors DataSetwindow, type in the name of the dataset in the Income Growth Adjustment DataSetNamebox, and then click on the Browse button to the right of the Database box to choose the datasetthat you want to import.

Loading Data


Click OK. The Income Growth Adjustment DataSet Manager window will appear. Hereyou may view the data that you just loaded.

Developing Income Growth Adjustment Factors

Adjusting WTP to reflect growth in real income requires three steps:

1. Identify relevant income elasticity estimates from the peer-reviewed literature2. Calculate changes in future income3. Calculate adjustments to WTP based on changes in future income and income

elasticity estimates

1. Identifying income elasticity estimates

Income elasticity estimates relate changes in demand for goods to changes in income. Positiveincome elasticity suggests that as income rises, demand for the good also rises. Negative incomeelasticity suggests that as income rises, demand for the good falls. BenMAP does not adjustCost-of-Illness (COI) estimates according to changes in income elasticity due to the fact thatCOI estimates the direct cost of a health outcome; instead we adjust this metric using inflationfactors described above. BenMAP includes income elasticity estimates specific to the type ofhealth endpoint associated with the WTP estimate. BenMAP contains elasticity estimates forthree types of health effects: minor, severe and premature mortality. Minor health effects arethose of short duration. Severe, or chronic, health effects are of longer duration. Consistent witheconomic theory, the peer reviewed literature indicates that income elasticity varies according tothe severity of the health effect. Below we summarize the health endpoints considered minor andsevere within BenMAP.

Minor

Asthma exacerbationAcute bronchitisAcute respiratory symptoms (minor restricted activity days)Lower respiratory symptomsUpper respiratory symptoms

Severe

Chronic bronchitisChronic asthma

A review of the literature revealed a range of income elasticity estimates that varied across thestudies and according to the severity of health endpoint. Table 4-12 summarizes the incomeelasticity estimates found in BenMAP to adjust minor health effects, severe health effects andpremature mortality. Here we have provided a lower-, upper- and central-estimate for each typeof health endpoint.

Loading Data


Table 4-12. Income Elasticity Estimates

Health Endpoint Lower Bound Central Estimate Upper Bound

Minor Health Effect 0.04 0.15 0.30

Severe and ChronicHealth Effects

0.25 0.45 0.60

Premature Mortality 0.08 0.40 1.00

2. Calculating changes in future income

The next input to the WTP adjustment is annual changes in future income. To estimate changes infuture income, EPA used the Standard & Poor’s projections of future changes in Gross DomesticProduct (GDP) occurring after the year 2010. EPA then divided the projected change in GDP bythe Woods & Poole projected change in total US population to produce an estimate of the futureGDP per capita.

3. Calculating changes in WTP

The income elasticity estimates from Table 4-12 and the estimated changes in future income maythen be used to estimate changes in future WTP for each health endpoint. The adjustment formulafollows four steps:

Table 4-13 below summarizes the income-based WTP adjustments used within BenMAP for

Loading Data


minor health endpoints, severe health endpoints, and premature mortality.

Table 4-13. Income-Based WTP Adjustments by Health Effect and Year

4.1.10.1Format Income Growth Data

Table 4-14a presents the variables that can be used in income growth adjustment datasets, andTable 4-14b presents a sample of what a dataset might look like.

Loading Data


Table 4-14a. Income Growth Data Set Variables


Year integer yes The year of the data. Note that this will includehistorical estimates as well as forecasts.

Mean integer yes Mean income growth adjustment factor.

EndPoint Group text yes

Table 4-14b. Sample Income Growth Data Set

Year Mean EndpointGroup

1990 1.0000 Acute Bronchitis
















4.1.11 QALY Data

To add QALY data to BenMAP, click on the Edit button below the QALY DistributionDataSets box in the Manage Setups window. The QALY DataSet Manager window willappear.

Loading Data


In this window you may Add and Delete datasets. The section on the left under AvailableDataSets lists the QALY datasets that are currently in the setup database. The sections onabove and to the right describe the data and let you view the QALY factors in a selecteddataset.

To add a dataset click on Add. This will bring up the Load QALY Dataset window.

Loading Data


In the QALY DataSet Name type the name of the dataset that will be added. Then click theBrowse button to find the QALY database that you want to load. This will bring up the Openwindow. Use the File of Type drop-down list to choose the type of file (e.g., MS AccessDatabase). Choose the QALY database and click Open. This will bring you back to the LoadQALY DataSet window.

Each QALY dataset is assumed to be specific to an Endpoint Group and Endpoint, so use the Endpoint Group and Endpoint drop-down menus to identify the appropriate selections.

Next use the Qualifier box to provide a brief description of the datafile. When creating an APVConfiguration, you will see this Qualifier description, so choose a description that adequatelycaptures what you have in your QALY datafile. There can be multiple QALY datafiles, in whichcase the Qualifier can be quite useful.

Finally, include a detailed description in the Description box. This is not required, but can beuseful when comparing different QALY datasets.

4.1.11.1Format QALY Data

Table 4-15a presents the variables that can be used in QALY datasets, and Table 4-15bpresents a sample of what a dataset might look like.

Loading Data


Table 4-15a. QALY Data Set Variables


Start Age

End Age

integer yes Specifies the low and high ages, inclusive. Forexample, Start Age of “0" and End Age of “1" includesinfants through the first 12 months of life and all one-

year old infants

QALY integer yes QALY value

Table 4-15b. Sample QALY Data Set

StartAge EndAge QALY

18 24 5.666993

18 24 2.758569

18 24 5.485653

18 24 3.647018

18 24 4.196073

18 24 3.501245

18 24 6.018638

18 24 2.057168

4.2 Export and Import Setups

BenMAP allows you to export and import entire databases (all Setups), individual Setups, andparts of individual Setups (e.g. all GridDefinitions, or individual health impact Function DataSets). This functionality can be used to share data with other BenMAP users, as well as to allow you tomove databases between computers. In particular, all of the steps involved in creating a Setupcan be done just once, after which the data can be exported and then imported on othercomputers.

4.2.1 Export Setups

To export part or all of an existing setup, go to the Tools drop-down menu, and choose theDatabase Export option.

Loading Data


This will bring up the DatabaseExportForm window. Initially, all of the setups are in a datatree, which is initially collapsed into the dataset Available Setups. To view the available Setups,click on the “+” sign to the left of Available Setups. This will expand the data tree. To contractthe tree simply click on the “-“ sign.

Choose an dataset to export by clicking on it. In the screenshot below, we are have chosen toexport EPA Standard Monitors.

Loading Data


You may choose all available Setups, individual Setups, the various collections within a Setup (allGridDefinitions, all Pollutants, all Population DataSets, etc.), and individual datasets within thevarious collections within a Setup. Click OK when you have selected the dataset to export.

This will bring up the Export Database Objects To File window. From here you may namethe dataset and choose the folder into which to export it. Type the dataset name the Filenamebox, and in the Save in drop-down menu locate the folder that you want to use.

Loading Data


NOTE: Exported BenMAP database files have a .bdb extension, and are a binary format notsuitable for viewing in external applications.

4.2.2 Import Setups

To import part or all of an existing setup, go to the Tools drop-down menu, and choose theDatabase Import option. This will bring up the Import Object Into Database window.

Loading Data


The Database Object File box identifies the file that you want to import. Click on the Browsebutton to locate the file to import. This will bring up the Import Database Object From Filewindow.

Select the file that you want to import, and then click Open. This will bring you back to theImport Object Into Database window. Click OK to finish the import process.

If the file contains a sub-Setup item, such as a collection (e.g., a set of grid definitions) or anindividual item (e.g., a single grid definition from among many available), select the Setup intowhich it should be imported. Select the Setup from the drop-down list below Target Setup.Click OK to finish.

NOTE: Duplicates of datasets (typically identified by their names - e.g. “Population CityOne”)will overwrite existing data in a Setup. New datasets (i.e., non-duplicated) will be added to theSetup.

4.3 Questions Regarding Loading Data

I've loaded new baseline incidence data, but BenMAP won't let me select it in theconfiguration stage

When formatting these data for importation to BenMAP, take special care to ensure that you

Loading Data


have specified the health endpoints correctly. The baseline incidence rate must be associatedwith a specific health endpoint and endpoint group in BenMAP. Be sure that you haverecorded the endpoint group and endpoint exactly as it is recorded in BenMAP. For example,if the baseline incidence rate is for asthma-related hospital admissions, be sure you haverecorded the endpoint group as "Hospital Admissions, Asthma" and the endpoint as "HA,Asthma".

I've loaded a new grid and new population data into BenMAP but I can't seem to usethese new data

Be sure to load the new grid definition first. Next, load the population dataset and be sure toselect your new grid definition.

How do I generate a population dataset for a new grid definition?

You can generate a population dataset using a variety of approaches. The key is that youneed to have a shapefile of your area of interest (e.g., census tracts in a city) and you havecensus data matching your area of interest. One source for both a shapefile and theassociated population data is the U.S. Census Bureau. (A variety of other agencies havecensus data, and you need to check around for your area of interest.) Another option for U.S.population data is to use the PopGrid software application, described in appendix on Population Data for U.S. Setup. Using PopGrid, you still need to have a shapefile for yourarea of interest.

Can I edit a population configuration?

No, you cannot edit a population configuration. You can only view a population configuration. If the population configuration does not match your data, then you need to either create a newpopulation configuration to match your data, or reshape your data so that it matches thepopulation configuration.

Air Quality Grid Creation


CHAPTER 5

Air Quality GridCreation

In this chapter...

Create air quality grids using different methods.

Find details on the file structures for data inputs.

Interpolate with Closest Monitor or Voronoi NeighborAveraging.

Scale monitor data with modeling data.

Learn about the Monitor Rollback feature.



BenMAP is not an air quality model, nor can it generate air quality data independently. Instead itrelies on the air quality inputs given to it. To estimate population exposure to air pollution,BenMAP uses air quality grids that it generates from input air quality data (modeling and ormonitoring data).

BenMAP creates air quality grids to estimate the average exposure to ambient air pollution ofpeople living in some regularly-shaped area, or domain, such as that delineated by air qualitymodels, as well as more irregular shapes, such as cities or nations. However, BenMAP does notestimate personal exposure. Instead, the air quality grids provide the average populationexposure for each grid cell that BenMAP can then use in health impact functions.

To create air quality grids, BenMAP uses a number of inputs, including modeling data, monitoringdata, or both. You may enter your own modeling and monitoring data, provided that the data arein a format recognized by BenMAP.

To start the grid creation process, click on the Create Air Quality Grids button. BenMAP willthen ask which of the following types of air quality data you wish to use:

Model Direct. Choose this option if you have air quality modeling data that you wish to usedirectly. Table 5-1 below describes the input format for modeling data.

Monitor Direct. Choose this option if you wish to use monitoring data, without additionalmodeling data.

Monitor and Model Relative. Choose this option if you wish to use a combination of monitorand model data.

Monitor Rollback. Choose this option if you want to reduce monitor levels by a specifiedamount.

Select your option and then click Go!. BenMAP will direct you through the necessary steps foreach option.



5.1 Model Direct

After choosing the Model Direct option, you need to specify the grid definition to which the datafile corresponds (Grid Type), the pollutant that the data is modeling (Pollutant), and the locationof your data file (Model Database).

The Model File specifies the location of the air quality model results that you want to import.Table 5-1 presents the structure that these files must have, and Table 5-2 presents a sample datafile with a variety of metrics. (For more information on air quality models, the EPA website hasdetailed descriptions of a variety of models: http://www.epa.gov/ttn/scram/.)




Table 5-1. Air Modeling Data File Variables


Column integer yes The column and the row uniquely identify each set of modeling values, and link the modeling data with cells in a

Grid Definition.Row integer yes

Metric text no This variable is either blank (signifying that the Values areObservations, rather than Metric values), or must referencean already defined Metric (e.g., 1-hour daily maximum) for

the appropriate Pollutant.

Seasonal Metric text no This variable is either blank (signifying that the Values arenot Seasonal Metric values) or must reference an already

defined Seasonal Metric for the Metric (e.g., mean of the 1-hour maximum for the months of June through August).

Statistic text no This variable is either blank (signifying that the values arenot an annual metric) or must be one of: None, Mean,

Median, Max, Min, Sum. (e.g., mean of the 1-hour maximumfor the year)

Values commaseparated

values (text)

yes If Metric is blank, either 365 or 8,760 comma separatedobservations. If Metric is defined, but Seasonal Metric andStatistic are blank, 365 metric values. If Seasonal Metric isdefined, but Statistic is blank, n seasonal metric values. IfStatistic is defined, one annual metric value (for either the

Metric (if Seasonal Metric is blank) or the Seasonal Metric. Missing values are signified with a period ('.').



Table 5-2. Sample Air Modeling Data File

5.2 Monitor Direct

Using the Monitor Direct grid creation option, you create an air quality grid directly from airpollution monitoring data. At the top left of the Monitor Direct Settings window, you areasked to select a previously defined grid definition from the Grid Type drop-down list, and apreviously-defined pollutant from the Pollutant drop-down list. And at the top right of theMonitor Direct Settings window, you are asked to select an interpolation method. Theinterpolation method is used to move from point-based monitor data to grid cell based air qualitydata. That is, some grid cells will have many monitors in them, some will have just one, and somewill have none. BenMAP uses the interpolation methods to generate representative air qualitymetric values for each grid cell from monitor data for all of these cases.



BenMAP includes three interpolation methods. The Closest Monitor method simply uses themonitor closest to a grid cell’s center as its representative value. The Voronoi NeighborAveraging method takes an inverse-distance weighted average of a set of the monitorssurrounding a grid cell’s center as its representative value. The Fixed Radius method averages allof the monitors within a fixed radius. Each method is described below. For more detail, alsosee the appendix on Air Pollution Exposure Estimation Algorithms.

In the middle of the Monitor Direct Settings window, you can choose the rest of the options tocreate your air quality grid. You need to specify the Grid Type and the Pollutant. The choicesfor Grid Type include only those that you have previously defined for the particular Setup inwhich you are working. Similarly, the choices for Pollutant include only those that you havealready defined in your Setup. And you need to specify a source for your monitor data. In theLibrary tab you may select data that you have already loaded into BenMAP.

You can also input your own monitor data file rather than use monitor data already existing in adataset, so long as it is in the format that BenMAP recognizes (see the Load Data chapter fordetails on the format for monitor datasets). Click on the tab that matches one of the threepossible formats for your data: (1) in a database file, with monitor definition information andmonitor values in a single row (Database, Rows), (2) in a text file, with monitor definitioninformation and monitor values in a single line (Text File), and (3) in two database files/tables,with monitor definition information in rows in one file/table and monitor values in a single columnin the other file/table (Database, Columns). There is no preferred approach; you should use theapproach with which you are most comfortable.



5.2.1 Closest Monitor for Monitor Direct

If you choose the Closest Monitor option, BenMAP identifies the monitor closest to each gridcell's center, and then assigns that monitor's data to the grid cell. Closest Monitor interpolationcan be modified by clicking on the Advanced button at the bottom of the window and typing ina Maximum Neighbor Distance (in km).

The Maximum Neighbor Distance specifies the maximum distance (measured in kilometers) that amonitor may be from a grid cell (distances are calculated using the grid cell centroid). Cellswithout any monitors within this distance will not be included in the resultant air quality grid. Thedefault setting is infinite (i.e. no limit to the distance between a monitor and a grid cell).

Note: Both the Maximum Relative Neighbor Distance and the Weighting Approach options areirrelevant, since BenMAP is only choosing a single monitor to assign to any given grid cell.

5.2.2 Voronoi Neighbor Averaging (VNA) for Monitor Direct

If you choose the VNA option, BenMAP first identifies the set of monitors that “surround” eachgrid cell’s center (these monitors are referred to as the grid cell’s neighbors), and then BenMAPcalculates an inverse-distance weighted average of these neighboring monitors. In this section,we provide some examples of the different ways that BenMAP calculates the average of theneighbor monitors. See the appendix on Air Pollution Exposure Estimation Algorithms. for anexpanded discussion of VNA, including how the VNA algorithm actually chooses the neighbormonitors, as well as the different ways that it may be used.

VNA interpolation has three advanced interpolation options, which can be modified by clickingon the Advanced button at the bottom of the window:

Maximum Neighbor Distance (in km) specifies the maximum distance that a monitor may befrom a grid cell, and still be included in the set of neighbor monitors used to calculate air pollutionexposure at a particular grid cell. The default setting is infinite (i.e., no limit to the distance



between a monitor and the grid cell).

Maximum Relative Neighbor Distance specifies the maximum ratio for the distance of eachmonitor to the distance of the closest monitor. The default setting is infinite.

Weighting Approach specifies whether BenMAP should use inverse-distance weighting for themonitors, or inverse-distance-squared weighting of the monitors. The default setting is inverse-distance weighting.

The following examples illustrate how varying these options affects the final average concentrationestimate.

Example 1: Monitor Direct VNA method

Default options

Consider the following example at an hypothetical rural grid cell, where there are relatively fewmonitors, and where the distance from a monitor to the grid cell can be fairly large. With VNA,BenMAP first identifies the set of “neighbor” monitors for each grid cell. The number ofneighbors is usually in the range of about three to eight. In this case, assume that there are fivemonitors at distances of 25, 50, 100, 200, and 400 miles from the grid cell, with annual PM

2.5

levels of 8, 13, 12, 18, and 15 µg/m3, respectively. BenMAP would calculate an inverse-distance weighted average of the monitor values as follows:

PM average2 5

1

258

1

5013

1

10012

1

20018

1

40015

1

25

1

50

1

100

1

200

1

400

10 68. .


Maximum Neighbor Distance = 75

Using the same example that we used above, let us say you have specified a MaximumNeighbor Distance of 75 miles, and left unchanged the default options (infinite value) forMaximum Relative Neighbor Distance. BenMAP would only consider the first twomonitors, and would calculate an inverse-distance weighted average of the monitor values asfollows:



PM average2 5

1

258

1

5013

1

25

1

50

9 67. .


Maximum Relative Distance = 10

Alternatively, if you have specified that the Maximum Neighbor Distance is infinite, but theMaximum Relative Neighbor Distance should have a value of, say, 10, then BenMAP wouldcalculate the ratio of the distance for each monitor to distance of the closest monitor. In this case,the ratios would be 1 (=25/25), 2 (=50/25), 4 (=100/25), 8 (=200/25), and 16 (=400/25), andBenMAP would drop the monitor with a ratio of 16. BenMAP would then calculate an inverse-distance weighted average of the monitor values as follows:

PM average2 5

1

258

1

5013

1

10012

1

20018

1

25

1

50

1

100

1

200

1053. .


Inverse-distance squared neighbor scaling

In addition, you can specify the an inverse-distance-squared weighting of the monitors. Let ussay that you have left unchanged the defaults (infinite values) for Maximum Neighbor Distanceand Maximum Relative Neighbor Distance, and specified that the Weighting Approach isinverse-distance-squared. BenMAP would then calculate an inverse-distance-squared weightedaverage of the monitor values as follows:

PM average2 5

1

6258

1

2 50013

1

10 00012

1

40 00018

1

160 00015

1

625

1

2 500

1

10 000

1

40 000

1

160 000

9 26.

, , , ,

, , , ,

.


Maximum Neighbor Distance = 75

Maximum Relative Neighbor Distance = 10

Inverse-distance squared Weighting Approach



Finally, you could specify changes to all three options: a Maximum Neighbor Distance of 75miles, a Maximum Relative Neighbor Distance of 10, and a Weighting Approach ofinverse-distance-squared weighting. BenMAP would then calculate the following average:

PM average2 5

1

6258

1

2 50013

1

625

1

2 500

9 00.

,

,

.

5.2.3 Fixed Radius for Monitor Direct

The Fixed Radius method averages all of the monitors within a fixed radius (measured inkilometers) that you specify. The the way that the monitors are averaged depends on the Weighting Approach that you choose after clicking the Advanced button. You can chooseeither Inverse Distance or Inverse Distance Squared weighting.

Note that the default option with the Fixed Radius approach is that BenMAP will not calculate anaverage for a grid cell if there are no monitors within the fixed radius (distance) that you specify. In the Advanced Options window, if you click Get Closest if None within Radius, thenBenMAP will calculate an average for those grid cells without any monitors within the fixedradius, by reaching out and choosing the nearest monitor regardless of distance.

5.2.4 Custom Monitor Filtering for EPA Standard Monitors

The Custom Filtering option only applies to EPA Standard Monitors library. This option allowsyou to filter, map, and export your monitor data. You can reach the Custom Filtering option byfirst choosing your pollutant, data source (e.g., monitor library) and year.



Click the Advanced button. This will take you to the Advanced Options window.

Click the Custom Monitor Filtering button. This will take you to the Filter Monitorswindow. Note that the first six options are essentially the same for each pollutant, and theseventh option depends on the pollutant.

1. Include specific monitors. Here you can specify particular monitor IDs that you want toinclude in your analysis. If this is left blank, then BenMAP will include all monitors that meet therest of the selection criteria.



2. Exclude specific monitors. Here you can exclude any particular monitor IDs from youranalysis. Here again, if this option is left blank then BenMAP will include all monitors that meetthe rest of the selection criteria.

3. Restrict to particular states and/or latitude/longitude. You can choose monitors toinclude from particular states, by listing the two-character state abbreviation (e.g., CA =California). You can also choose monitors within particular latitude and longitude ranges. Thedefault values for latitude (20 to 50) and longitude (-130 to -65) completely includes thecontinental U.S. Here again, if this option is left blank then BenMAP will include all monitors thatmeet the rest of the selection criteria.

4. POC code. The Maximum POC specifies the highest POC value allowed in the data. Thedefault is a value of 4. And to choose one monitor when more than one monitor is in the samelocation, the POC Preference Order specifies the preferred ordering of POC codes.

5. Methods. The Method codes listed depend on the pollutant. In the case of O3 and PM

10, all

methods are checked by default. And in the case of PM2.5

, only so-called federal-reference

methods (FRM) are chosen by default -- specifically numbers 116 through 120.

6. Monitor Objectives. The default is to choose all monitors regardless of monitor objective.

7. Parameters Specific to the Pollutant. The default options vary by pollutant. Below, wehave listed the windows that appear with PM

2.5, PM

10, and ozone.

PM10 Monitor Filter

The Number of Valid Observations Required Per Quarter specifies the number of days ofdata needed. The default is to require 11 observation per quarter. The Data Types to Useoption specifies whether to use Local data (parameter code 85101), Standard data (parametercode 81102), or Both. The default for PM

10 is to use both local and standard data. When

standard and local data are available at the same monitor location, the Preferred Type allowsyou to choose which to use -- the default is Local. The Output Type option is designed to allowyou to make the data reasonably consistent when both local and standard data are used. Thedefault is to use the local output type, so standard data will converted to local.



PM2.5

Monitor Filter

The default for PM2.5

is to also require 11 observations per quarter. A key difference with 0, is

that only local PM2.5

data is used by default.



Ozone Monitor Filter

The ozone specific options differ from PM10

and PM2.5

in large part because ozone is an hourly

pollutant. The Number of Valid Hours specifies the number of hours needed for a particularday of monitor to be considered "valid." BenMAP counts the number of non-missing hourlyvalues from the Start Hour through the End Hour and compare this number with that specifiedin the Number of Valid Hours.

The Percent of Valid Days specifies the percent of days between the Start Date and the EndDate that need to be valid for the monitor itself to be considered valid. The default is 50 percentof the days between May 1 and September 30.



5.3 Monitor and Model Relative

The Monitor and Model Relative option lets you scale interpolated monitor values with modeldata. As with the Monitor Direct option, you can choose Closest Monitor or VoronoiNeighbor Averaging (VNA). In addition, you can scale the monitor values with three differentapproaches: Spatial Only, Temporal Only, and Spatial and Temporal. As discussed below,these approaches let you combine the advantage of the actual monitor observations with theinformation provided by the models.

Monitor and Model Relative air quality grid creation is exactly the same as Monitor Direct airquality grid creation with the exception of scaling. The concept of scaling is to use modeling datato improve interpolation and/or forecast future air quality trends.



Identify and load your modeling data into BenMAP using the Base Year Model File box. Iftemporal scaling is used, load your modeling forecasts using the Future Year Model File box.The base year file should be created with modeling data which closely reflects the historicalconditions of the monitor data to be used. Typically multiple future year files will be used tocreate multiple air quality grids for use in an analysis. That is, one future year file might representa future projection of current trends, while another might represent the results of implementing aregulatory program.

5.3.1 Spatial Scaling

Spatial scaling involves only a Base Year Model File, and scales the concentrations of each



neighboring monitor by the ratio of the modeled concentration at the grid cell to the modeledconcentration at the grid cell containing the monitor. This approach takes into account what theair quality modeling reveals about spatial heterogeneity in pollution levels. For example, if themonitors are in relatively polluted urban areas, and the grid cell is in a relatively unpolluted ruralarea, then the scaling will result in multiplying the monitor values with ratios less than one, and thusproduce lower values at the rural grid cell than would be estimated with interpolation of theunscaled monitor data.

Spatial scaling, then, is useful because, while monitors provide invaluable information abouthistorical conditions, there are only a limited number of monitors. Many areas, particularly ruralareas, do not have close monitors. Model data can provide additional information that improvesthe interpolated concentration estimates, and provides a more accurate picture of air quality.

5.3.2 Temporal Scaling

Temporal scaling involves both a Base Year Model File and a Future Year Model File, andscales the concentrations of each neighboring monitor by the ratio of the modeled concentrationat the grid cell containing the monitor in the future year to the modeled concentration at the gridcell containing the monitor in the base year. This approach takes into account what the air qualitymodeling reveals about the changes in pollution levels over time at the monitor sites. Forexample, if the modeling forecasts that in the future, pollution levels will decrease, then the scalingwill result in multiplying the monitor values with a ratio less than one, and thus produce lowerforecasts at the grid cell than would be obtained with the unscaled monitor data.

Temporal scaling, then, is useful because monitors cannot provide any information about futureconditions. Model data can provide this information, which can then be used to project futuremonitor concentrations.

5.3.3 Spatial and Temporal Scaling

Using both spatial and temporal scaling involves both a Base Year Model File and a FutureYear Model File, and is simply a combination of spatial scaling and temporal scaling, except thatthe future year data is used for the spatial scaling. That is, it scales the concentrations of eachneighboring monitor first by the ratio of the modeled concentration at the grid cell in the futureyear to the modeled concentration at the grid cell containing the monitor in the future year (spatialscaling), and then by the ratio of the modeled concentration at the grid cell containing the monitorin the future year to the modeled concentration at the grid cell containing the monitor in the baseyear (temporal scaling). Notice, however, that the two future year concentrations at the grid cellcontaining the monitor cancel out, allowing the ratio used to be simply the modeled concentrationat the grid cell in the future year to the modeled concentration at the grid cell containing themonitor in the base year.

Using both spatial and temporal scaling gives the benefits of both approaches - it both improvesthe interpolated estimates of air quality, and provides a future forecast of air quality.



5.3.4 Examples

The first example presented is a Monitor Direct example, which will provide a foundation for thefollowing Monitor and Model Relative examples. Recall that Monitor and Model Relative airquality grid creation is exactly the same as Monitor Direct grid creation with the exception ofscaling. For additional examples with more detail, see Appendix B.

Example 1: Monitor Direct VNA Method

Default options

Consider the example at an hypothetical rural grid cell, from Section 5.2.2, where there are fivemonitors at a distance of 25, 50, 100, 200, and 400 miles from the grid cell. Further, let us say

that the monitors have annual PM2.5

levels of 8, 13, 12, 18, and 15 µg/m3. Without any model-

based scaling, BenMAP would calculate an inverse-distance weighted average of the monitorvalues as follows:

Example 2: Monitor and Model Relative VNA Method

Default options

Spatial Only scaling

Assume the same monitors and monitor concentrations as above. Additionally, assume that the

grid cell model value in the base-year is 6 µg/m3, and the model values at the monitors in the

base-year are: 10, 14, 11, 17, and 15 µg/m3. (This modeling suggests that the grid cell is a less-polluted area than the area around the monitors.) Incorporating Spatial Only scaling, BenMAPwould calculate an inverse-distance weighted average of the monitor values using the sameapproach as before, with the difference being that the monitor values are scaled with the modelingvalues:



Example 3: Monitor and Model Relative Closest Monitor Method

Default options

Spatial Only scaling

Assume the same monitors and monitor concentrations as above. Additionally, assume the samemodel values as above. The Closest Monitor interpolation of these same values using SpatialOnly scaling would be calculated as follows:


Default options

Temporal Only scaling

Again, assume the same monitors and monitor concentrations as above. Additionally, assume

that the model values at the monitors in the future-year are: 8, 11, 9, 14, and 11 µg/m3, and that

base-year model values at the monitors are: 10, 14, 11, 17, and 15 µg/m3. (This modelingsuggests that the future-year model values are generally lower.) Incorporating the TemporalOnly scaling, BenMAP would calculate an inverse-distance weighted average of the monitorvalues as follows:


Default options

Spatial and Temporal scaling

Again, assume the same monitors and monitor concentrations as above. Additionally, assume

that the future-year model value at the grid cell is 4 µg/m3, and that base-year model values at the

monitors are: 10, 14, 11, 17, and 15 µg/m3. (This modeling suggests that the future-year modelvalue at the grid cell is significantly lower than the base-year model values at the monitor.) Incorporating the Spatial and Temporal scaling, BenMAP would calculate an inverse-distanceweighted average of the monitor values as follows:



5.4 Monitor Rollback

The Monitor Rollback option allows you quickly test what the benefits would be from reducinghistorical monitor levels. BenMAP has three methods to reduce, or “roll back,” monitor data:percentage rollback, incremental rollback, or rollback to a standard. Each of these methods aredepiocted below. Note that with each of these methods you can use the same two interpolationalgorithms (closest monitor, and VNA) as you can use with Monitor Direct and Monitor andModel Relative.

Percentage rollback reduces all monitor observations by the same percentage.

Incremental rollback reduces all observations by the same increment.

Rollback to a standard lets you choose a standard, and then reduces monitor observations sothat they just meet the standard.



To apply a monitor rollback, first click the Create Air Quality Grids button. On the AirQuality Grid Creation Method window, choose Monitor Rollback.

There are three steps to the Monitor Rollback method.

1. Monitor Rollback Settings: (1) Select Monitors. Choose the Pollutant for the monitordata. If you use data from an existing dataset, then choose the Library tab, and from the drop-down list choose the Monitor DataSet and the Monitor Library Year.

If you want to use your own data, then choose the format tab that matches the data that you wantto load: Database, Columns; Database, Rows; or Text File. The file should have the monitordata format specified in Load Data chapter.

Then choose the Rollback Grid Type from the drop-down list. This allows you to determine



how detailed the rollback scenario may be. If the whole region (e.g., United States) will have thesame type of rollback then you may simply choose a grid outlining the area of interest. If you areinterested in different rollbacks within a region, then you should choose a more finely detailed griddefinition (e.g., states).

When you have finished making your choices, click Next.

2. Monitor Rollback Settings: Select Rollback Regions and Settings. In this section, youcan specify the type of the rollback method(s) that you would like to use, as well as the locationof the monitors that you want to rollback.

Choosing the Add Region button brings up the three rollback methods: Percentage Rollback,Incremental Rollback, and Rollback to a Standard.



After choosing the rollback type, you then need to specify the amount of the rollback and theregion to which you want to apply it. In this example, we specified a 10 percent reduction, abackground of 0 ppb, and applied it to all monitors in all states by clicking the Select All. So,BenMAP will reduce all observations for all monitors in all states by 10 percent.

Note that just above the map of the states there are four buttons, typically seen in mappingprograms, that allow you to zoom in and zoom out, and to focus on the particular groups of gridcells that interest you.

At any time you can change the grid cells that you have selected. This particular example is quitesimple, so we will use a more complicated example below. After choosing the counties whereyou want to rollback monitors, click on the Next button. BenMAP will then perform the



rollback you specified on the monitors in the grid cells that you have chosen.

3. Monitor Rollback Settings: Additional Grid Settings.

The third stage is similar to the Monitor Direct grid creation method. As in Monitor Direct, youneed to specify the Interpolation Method (Closest Monitor or VNA) and the Grid Type.You may select a Scaling Method (None or Spatial Only). If you choose spatial scaling, itworks exactly as described in the Monitor and Model Relative section, where the modeling datais used to provide information in those areas that are unmonitored.

By checking the Make Baseline Grid (in addition to Control Grid) you may create a baselinegrid at the same time as the control grid. The baseline grid uses the same parameters as thecontrol grid, with the exception of the rollback. That is, the baseline uses the same monitor data,interpolation method, scaling (if any), and the same grid type. The two resultant grids can thenserve as both baseline and control scenarios in later stages of an analysis.

Note that there is an Advanced button that lets you select the Maximum Neighbor Distance,Maximum Relative Neighbor Distance, and Weighting Approach. The specific availability ofadvanced features depends on the interpolation method that you choose. You may also click the Map button to view the inputs to the rollback grids that you are creating, as well as to view thegrids themselves. The chapter on GIS/Mapping discusses the mapping of grids in more detail.

5.4.1 Example: Combining Three Rollback Approaches in Different Regions

BenMAP allows you to have different rollback approaches in different regions. In this example,we combine the three rollback types: Percentage Rollback, Incremental Rollback, and



Rollback to a Standard. Start by clicking on the Create Air Quality Grids button, andchoosing Monitor Rollback. On the Monitor Rollback Settings: (1) Select Monitorswindow, select your pollutant (Ozone) and year (2000), and click Next. On the next window,click the Add Region button and enter 10 for the Percent. In the previous example, we usedthe Select All button to include all states in the rollback region. In this example we want tocreate three regions instead, so just click on the three western-most states to add them to theregion. The states you have added to the region will turn yellow, as in the picture below.

To add states with a second type of rollback, click on the Add Region button, choose therollback type, and then click on the counties to include in this second region, which BenMAPdenotes as Region 2. In this example, we have chosen an Incremental Rollback of 5 and abackground of 20, and applied it to the 14 next western-most states.

The map now depicts two rollback regions. We can toggle back and forth between each regionby clicking on the legend on the left side of the map. Any counties that have not yet beenincluded in a region may be added to an existing region, or we may create one or more regionsfor these remaining counties. Note that once counties have been included in a rollback region,they cannot be included in a different rollback region. In our example, the three western-moststates are highlighted in gray.



To add a third rollback type covering the rest of the counties, click again on the Add Regionbutton, and then choose the rollback type. However, instead of choosing individually the states,simply click the Select All button. This will select all of the states that are not yet included in aregion, and these remaining counties will now become Region 3.

In this third region, we have chosen a Rollback to a Standard, which involves two groups ofparameters - those associated with the Attainment Test, which determines whether a monitor isin attainment (meets the standard), and those associated with the Rollback Methods, which areused to bring out-of-attainment monitors into attainment.

The Attainment Test parameters are Metric, Seasonal Metric, Statistic, Ordinality, and

Standard. A monitor is considered in attainment if the nth highest value of a daily metricspecified by Metric is at or below the value specified by Standard, where n is the valuespecified by Ordinality. For example, if Metric is D8HourMax, Ordinality is 4, andStandard is 85, a monitor will be considered in attainment if the fourth highest value of the eight-hour daily maximum is at or below 85 ppb. In this step BenMAP calculates the metric to beused to determine whether a monitor’s values must be rolled back and, if so, how much (e.g., if Metric is D8HourMax, BenMAP calculates the 8-hour daily maximum for each day at eachmonitor).



The Attainment Test can also be used for seasonal metrics (by choosing previously definedseasonal metrics from the drop-down list below Seasonal Metric), as well as for annual metrics(by using the drop-down list below Statistic). For example, if you want the annual mean ozonelevel to go stay below 60 ppb, then you would choose the daily 24 hour mean (D24HourMean)from the drop-down list below Metric, choose Mean from the drop-down list below Statistic,and set the Standard to 60. (Note that in this case Ordinality cannot be chosen because thereis only a single annual value.)

The Rollback Method parameters are Interday Rollback Method, Interday BackgroundLevel, Intraday Rollback Method, and Intraday Background Level. These fourparameters determine the rollback procedures used to simulate out-of-attainment monitorscoming into attainment. The Interday Rollback Method and Background Level are used togenerate target values for the metric specified by the Attainment Test. The Intraday RollbackMethod and Background Level are used to adjust hourly observations to meet the targetmetric values generated in the previous step.

BenMAP provides several types of Interday Rollback Methods (Percentage, Incremental,Quadratic, and Peak Shaving) and several types of Intraday Rollback Methods (Percentage, Incremental, and Quadratic). The methods involved for each can be somewhatcomplicated, so we have included a section in the Monitor Rollback Algorithms appendix goesthrough several examples.



5.5 Questions Regarding Creating Air Quality Grids

How can I generate a map of an air quality grid and export it?

You need to choose the GIS/Mapping option from the Tools drop-down menu available in theupper left-hand corner of the main BenMAP window. The GIS/Mapping option, as described inthe GIS/Mapping chapter, provides the option to map and then save air quality grids.

For the Rollback to a Standard option, why are there Interday and Intraday rollbackoptions?

The Interday Rollback Method option identifies the approach (e.g., Percentage) to reducedaily air pollution levels, in order to meet the specified standard. (In other words, there is morethan one way to reduce daily pollution levels so as to meet the standard you have chosen, andBenMAP lets you choose from among several approaches.) The Background level associatedwith the Interday Rollback specifies the bound, below which, BenMAP will not makeadjustments to daily levels.

The Intraday Rollback Method option is only relevant for hourly pollutants, like ozone. Thisoption specifies the approach (e.g., Percentage) used by BenMAP to reduce hourly air pollutionlevels to reach is only relevant for hourly air pollution data. That is, once you have chosen theapproach to reduce daily air pollution levels, on any given day there is more than one way toreduce the hourly air pollution values to meet the targeted pollution level for that day. TheBackground level associated with the Intraday Rollback specifies the bound, below which,BenMAP will not make adjustments to hourly levels.

The Interday and Intraday options are complicated. The appendix on Monitor RollbackAlgorithms explains these options in more detail and gives some numerical examples.

Can I use air quality grids based on different Grid Types in the baseline and controlscenarios?

No. In any given analysis, you need to use the same Grid Type in the baseline and controlscenarios.

Can I use air quality grids of the same Grid Type but based on different Grid CreationMethods?

Yes. In any given analysis, you may use air quality grids made with different methods. Air



quality grids made with Model Direct, Monitor Direct, and Monitor and Model Relative maybe used interchangeably, if desired. Similarly, air quality grids made with different interpolationmethods may be compared. However, it generally is not recommended to create grids withdifferent methods and use them in the same analysis.

Can I do an analysis with multiple pollutants?

You can only estimate impacts one pollutant at a time, however, BenMAP allows you toaggregate the results of more than one pollutant. This is discussed in the chapter onAggregation, Pooling, and Valuation.

Why does it take so long to generate an Ozone Air Quality grid if there are a lot of gridcells?

It can take a long time to create an air quality grid because the file being generated can be quitelarge. In some cases, air quality grids can be several hundred megabytes in size. (One reasonthe ozone files are large is that the definition of ozone has, by default, four metrics. If you do notneed all of the default metrics for the health impact functions in your database, then delete theunneeded metrics and BenMAP will run faster and will generate smaller air quality grids. This isan advanced step, so do not do it if you are unsure.)

How do I access data in an Air Quality grid?

You can access the data in an air quality grid by going to the Tools drop-down menu andchoosing the Export Air Quality Grid option. (The Tools drop-down menu is available in theupper left-hand corner of the main BenMAP window.) You then locate the air quality gridfrom which you want to export air quality data and then give a name to your exported file. BenMAP will generate a text file that you can then examine. This is discussed in detail in the Tools Menu chapter.

How do I create Air Quality grids for a One-Step Analysis?

Follow the same steps outlined.

Incidence Estimation


CHAPTER 6

IncidenceEstimation

In this chapter...

Get an overview of health incidence estimation.

Use the Create and Run Configuration button to specifyvarious options for calculating incidence results.

Learn about baseline and control scenarios.

Learn the difference between Point Mode and the LatinHypercube option.

Select health impact functions.

Run, save and reopen a configuration.



A configuration is a record of the choices you make in estimating the change in adverse healtheffects between a baseline and control scenario. The choices include the following:

The air quality grids for the baseline and control scenarios;

The year for the analysis;

The threshold for the analysis;

Whether the analysis will focus on a single “point” estimate (Point Mode), or a range of resultsthat mirror the variability in the inputs to the health impact functions (Latin Hypercube Points);and,

The health impact functions to be used in estimating adverse health effects.

Once these choices are made, they can be saved in a configuration file for future reuse. BenMAPgives you flexibility in the creation, editing, and saving of configuration files. You can open analready existing configuration, and proceed directly to the estimation of incidence. Or, you cancreate a new one, and proceed with the incidence estimation. In addition, you may save anyedits made to existing or new configuration files. BenMAP saves configuration files with a “.cfg”extension. After calculating the change in adverse health effects, BenMAP saves the results in a“configuration results” file with a “.cfgr” extension.

After clicking the Create and Run Configuration button, you will be asked if you want tocreate a new configuration, or open an existing one, if you have already created one that youwould like to use again. Select the desired option and click Go!. Below, we discuss thesubsequent steps for each option.

6.1 Introduction to Estimating Health Incidence

Health impact functions relate a change in the concentration of a pollutant to a change in theincidence of a health endpoint (i.e., premature mortality or work loss days). It is typically derivedfrom the estimated relationship between the concentration of a pollutant and the adverse healtheffects suffered by a given population. This relationship is called the concentration-response (C-R) function. For example, the concentration of the pollutant may be particulate matter (PM

10),

and the population response may be daily premature deaths. For the purposes of estimatingbenefits, we are not interested in the C-R function itself, but rather the relationship between the change in concentration of the pollutant, and the corresponding change in the population health



response. We want to know, for example, if the concentration of PM10

is reduced by 10

micrograms per meter cubed, how many premature deaths will be avoided?

To produce health incidence results, the first step is to calculate the change in pollutionconcentrations that would be produced by the application of a given set of emissions controls.The concentration change in a pollutant is the increment between the control scenario and thebaseline scenario. This increment and a gridded population dataset are then used in health impactfunctions to calculate the change in health incidence that would result from this change in pollution. These functions are based on epidemiological studies and can be selected by the user. Typically,these health incidence results show the decrease in health incidence (e.g. the decrease in asthma,bronchitis, mortality, etc) due to a decrease in pollution.

In BenMAP, the selected health impact functions are stored in configurations, which can be re-used over and over again.

6.2 Create Health Impact Configuration

If you choose to create a new configuration, there are two steps. First, fill out the ConfigurationSettings form with the following options: the air quality grids for the Baseline File and theControl File, the Population DataSet, Population Year, Threshold, and whether BenMAPwill run in Point Mode or use the Latin Hypercube Points option. In the second step, specifythe health impact functions that you want to use in your analysis.

6.2.1 Configuration Settings

The Configuration Settings window opens after you select Create New Configuration andclick Go!. In this window, you first specify the air quality grids for the Baseline File andControl File. The baseline file contains the air quality metrics for the scenario assumed to occurwithout any change in policy. The control file specifies the air quality metrics assuming that sometype of policy or change has been implemented. The air quality grids should be of the samepollutant, and should also be based on the same grid-type. If you choose a particular grid type(e.g., County) for the baseline file, then the same grid type must be used in the control file.Conversely, it would not possible to use County grid-type in the baseline and a Tract grid typein the control file.

You may choose existing air quality grids, by clicking the Open button, and selecting an airquality grid, which is designated with an “.aqg” extension. You may also create a new air qualitygrid by clicking the New button. This will take you to window for Air Quality Grid CreationMethod, where you follow the same steps outlined in the chapter on air quality grid creation.

The Pollutant specified in the air quality grids determines the suite of health impact functionsavailable for the configuration. Only functions associated with the specified pollutant will beavailable for the configuration. Furthermore, if only certain Metrics associated with the pollutantare present in one (or both) of the air quality grids (this see the information on monitor and modeldata formats above for more information on how this can occur) only those health impact



functions associated with those metrics will be available.

In choosing the Population DataSet and Population Year, you specify the population data thatwill be used in the health impact function. The values in the menu for the Population Yeardepend on the range of values in your Population DataSet.

The Threshold indicates the minimum air quality value that BenMAP will use to quantify healthimpacts. That is, air quality metrics below the threshold will be replaced with the threshold value. With a threshold of zero, there is no impact on the estimates generated by the health impactfunctions. However, as the threshold increases, then it will have a progressively larger impact onthe incidence estimation. For most analyses, a threshold of zero is appropriate, as there is littleevidence suggesting the existence of a threshold. Nevertheless, the Threshold option allows youto explore the impact of any given threshold on the incidence estimation. This is also useful forscenarios where you might want to know the incidence associated with changes in air qualityoccurring above a standard.

The Point Mode and Latin Hypercube Points options allow you to generate an averageincidence estimate, or a range of results that mirror the variability in the inputs to the health impactfunctions. With the Point Mode option, BenMAP uses the mean values of the inputs to thehealth impact functions, and generates a single “point estimate” of the change in adverse health



effects.

With the Latin Hypercube Points option, you can generate a number of estimates that mirrorthe variability in the inputs to the health impact functions. The Latin Hypercube Points optionallows you to generate specific percentiles along the estimated incidence distribution. For

example, if you specify 20 points, then BenMAP will generate estimates of the 2.5th percentile,

7.5th percentile, and so on, up through the 97.5th percentile. The number of points suggested inthe drop down menu varies between 10 and 100. In addition, you can simply type in the desirednumber of points. The greater the number of chosen points, the greater the time needed byBenMAP to process the results. The relationship between the number of points and time neededis essentially linear, so a doubling of the number of points would double the processing time.

If Point Mode is chosen, the number of Latin Hypercube Points cannot be modified and willbe ignored (treated as zero). However, with the Latin Hypercube Points option, a pointestimate will still be generated. As discussed in the chapter on Aggregation, Pooling, andValuation, by choosing the Point Mode, you have fewer pooling options. You cannot conductfixed/random effects pooling, nor any other procedure that depends on knowing the distribution,or the range of variability of the incidence estimates.

6.2.2 Select Health Impact Functions

The second step in creating a configuration is to select the health impact functions. After filling inboth the Select Air Quality Grids and Settings of the Configuration Settings window, clickNext to select the health impact functions.



The Configuration Settings window is split into two display boxes. The upper box presentsthe Available C-R Functions which you may select and the lower box the Selected C-RFunctions that you have already selected. Both boxes have a tree structure and the ability tochange the order of the fields for easy viewing of the functions.

To add studies to your configuration, simply highlight the health impact functions of interest anddrag them over to the lower portion of the window. You can do this for blocks of health impactfunctions by dragging over an endpoint group or an endpoint, or drill down and drag individualfunctions.



If you want to delete some of the health impact functions that you added to your configuration,just highlight the studies of interest and hit the Delete key on your keyboard.

When you drag over a study, BenMAP displays the study’s information in two broad categories: Function Identification and Function Parameters. The Function Identification includesinformation such as the Endpoint Group, Endpoint, Metric, Location, and other variables.This identification information is useful when distinguishing between multiple health impactfunctions. The Function Parameters include those variables that you may directly edit: Race,Ethnicity, Gender, Start Age, End Age, Incidence DataSet, Prevalence DataSet, andVariable DataSet..

You can drag over the same study multiple times, and then make edits, in order to be able tocalculate the impact of changes in these variables. To edit Start Age and End Age, just highlightthe appropriate cell and type in the desired age values. Keep in mind that these age representinclusive age bounds, so if you type in 10 and 12 this will include all children ages ten, eleven, andtwelve years old. If you want just a single age year, then type the same year in both the StartAge and the End Age. Note that the accuracy of the populations calculated for these age rangeswill depend on the specificity of the population data present in your selected population dataset.



At the same time you can edit the Race, Ethnicity, and Gender variables, by clicking on theappropriate cell, and then scrolling through the drop-down menu. Similarly, if you have multipledatasets to choose from, you can change the source of the incidence and prevalence data that isused for each function. Use the drop-down lists in the Incidence DataSet, PrevalenceDataSet, and Variable DataSet fields.

6.3 Run Health Impact Configuration

To begin the calculation of incidence for the health impact functions in the configuration, you clickthe Run button on the bottom right-hand corner of the Configuration Window that has the listof chosen health impact functions. After clicking Run, BenMAP allows you to save theconfiguration, or begin the calculation. If you wish to save the configuration for future use, clickSave and specify a file with a “.cfg” extension.



When ready to generate incidence estimates, click on the OK button. BenMAP then requiresthat you specify a file in which to save the results, with a “.cfgr” extension.

6.4 Open & Modify Existing Health Impact Configuration

To use the same settings as a previous BenMAP run, you can choose to open an existing configuration. After clicking the Create and Run Configuration button, you simply chooseOpen Configuration and click the Go! button. Once an existing configuration is open,, you cando all the things with it that you would do with a newly created configuration - modify settings,add and delete health impact functions, save it to a configuration file, generate results, etc.

6.5 Questions Regarding Health Impact Configurations

I got an error message the "specified Baseline file does not exist." What does thatmean and how do I fix it?

The path and/or the file that you have specified do not exist. Go back and ensure that the pathand file are correctly identified.

How do I know which health impact functions to use? Which functions does EPA use?

One option regarding the choice of health impact functions is to work with someone, say



another BenMAP user, who is familiar with the epidemiological literature and develop yourown set of health impact functions. Reviewing the epidemiological literature can be time-consuming, though in some situations, this might be the best option, such as if you want toestimate the health impacts of carbon monoxide exposure, for which BenMAP does not havepre-installed health impact functions.

Another option is to use the ozone and PM2.5

configurations used by EPA that come installed

with BenMAP. You will find them in the Configurations folder. If desired you can edit thisconfiguration and then save it under a different file name -- it is always a good idea to keep theoriginal version, so you can go back to it if needed!

How do I edit or add other health impact functions?

To edit or add health impact functions you need to go to Modify Setup option in the Toolsdrop-down menu available in the upper left-hand corner of the main BenMAP window. Seethe health impact function section in the chapter on Loading Data for details on how to do this.

How do I learn more about the population data in BenMAP?

The appendix on Population Data for U.S. Setup describes the population data in detail.

Why did I not get results for a given geographic area that I wanted in my analysis?

Check to see if your air quality grids mapped properly.

Why does BenMAP give me a range check error when I try to run the configurationstep?

If you get a "range check" error, it usually means that you are using files that are incompatiblewith your current version of BenMAP. Make sure that the files you are currently using weregenerated with the version of BenMAP that you have installed. If the problem persists,contact: [email protected].


Aggregation, Pooling, and Valuation


CHAPTER 7

Aggregation,Pooling, and

Valuation

In this chapter...Get an overview of valuation, discounting, and pooling.

Use the Aggregation, Pooling, and Valuation (APV)button to create an APV configuration.

Sort and pool incidence results.

Learn the differences between the pooling methods.

Assign economic values to incidence results.

Aggregate incidence results and valuations.

Run, save and re-open an APV configuration.



Once you have created a configuration results file with incidence results based on your two airquality grids (using the Create and Run Configuration button), you can use the Aggregation,Pooling, and Valuation button to combine the incidence results and place an economic valueon the combined results. You have two options.

Create a New Configuration for Aggregation, Pooling, and Valuation. You can create anew type of configuration, termed an Aggregation, Pooling, and Valuation (APV) Configuration.This allows you to specify whether to aggregate incidence results at the county, state or nationallevel, or whether to leave them at the grid cell level. In addition, you can specify how you mightwant to combine or “pool” the incidence results, using a variety of pooling options. Given theaggregated and pooled incidence results, you then can specify how you might want to value them– typically there are multiple valuations. These valuation results can then be further aggregated,and these aggregated valuation results can be pooled. Having made all of your selections, youmay save this APV Configuration file (“.apv”) for future use, and then proceed to calculating theresults, which are stored in an APV Results file (“.apvr).

Open Existing Configuration for Aggregation, Pooling, and Valuation. You can load anexisting APV Configuration file, edit the configuration, save it with the same or a different name,and then proceed to calculating the results.

7.1 Introduction to Valuation, Discounting, and Pooling

This section presents an introduction to valuation, discounting, and pooling. Valuation generallyrefers to placing a dollar value on estimated health incidence. In BenMAP, you might also thinkof valuation as including the assignment of quality adjust life year (QALY) weights, in the sensethat the placement of dollar values and QALY weights both occur in the APV configuration. We discuss both dollar values and QALY weights here. In addition, we provide a brief introductionto discounting, which has to do with placing less weight on things occurring in the future than wedo for things today. Finally, we discuss pooling, which has to do with combining comparableresults.

7.1.1 Overview of Valuation

Improvements in ambient air quality generally lower the risk of developing an adverse healtheffect by a fairly small amount for a large population. A lower risk for everyone means that fewercases of the adverse health effect are expected, although we cannot predict which people wouldbe spared. Therefore, the health benefits conferred on individuals by a reduction in pollution areactually reductions in the risk of having to endure certain health problems. Monetizing thebenefits of a reduction in air pollution involves estimating society’s willingness to pay (WTP) forthese reductions in risk and is typically referred to as valuation. BenMAP uses valuationfunctions to estimate the benefits of reducing air pollution.

These benefits (reductions in risk) may not be the same for all individuals (and could be zero forsome individuals). Likewise, the WTP for a given benefit is likely to vary from one individual to



another. In theory, the total social value associated with the decrease in risk of a given healthproblem resulting from a given reduction in pollution concentrations is generally taken to be thesum of everyone’s WTP for the benefits they receive.

Epidemiological studies allow us to estimate the number of cases of an adverse health effect thatwould be avoided by a given reduction in pollutant concentrations. If we have an estimate of theaverage individual’s WTP for the risk reduction conferred upon him, we can derive from that anestimate of the value of a statistical case avoided. Suppose, for example, that a given reduction inpollutant concentrations results in a decrease in mortality risk of 1/10,000. Then for every10,000 individuals, one individual would be expected to die in the absence of the reduction inpollutant concentrations (who would not be expected to die in the presence of the reduction inpollutant concentrations). If the average individual’s WTP for this 1/10,000 decrease in mortalityrisk is $100, then the value of a statistical life is 10,000 x $100, or $1 million. In general, the exante WTP for a risk reduction of x can be converted into an ex post value of a statistical caseavoided by dividing the average individual’s WTP for the risk reduction of x by x (e.g.$100/0.0001 = $1,000,000). The same type of calculation can produce values for statisticalincidences of other health endpoints.

Sometimes those values come from contingent valuation studies, in which study participants arequeried about their WTP to avoid a specific adverse health effect. When WTP estimates are notavailable, it can be approximated by other measures, most notably cost of illness measures.

An individual’s WTP to avoid an adverse health effect will include, at a minimum, the amount ofmoney he or she would have to pay for medical expenses associated with the illness. Becausemedical expenditures are to a significant extent shared by society, via medical insurance,Medicare, etc., the medical expenditures actually incurred by the individual are likely to be lessthan the total medical cost to society. The total value to society of an individual’s avoidance of anadverse health effect, then, might be thought of as having two components: (1) the cost of theillness (COI) to society, including the total value of the medical resources used (some portion ofwhich will be paid by the individual), plus the value of the lost productivity, as well as (2) theWTP of the individual, as well as that of others, to avoid the pain and suffering resulting from theillness.

The COI approach attempts to estimate the total value of the medical resources used up as wellas the value of the individual’s time lost as a result of the illness. Because this method does notinclude the value of avoiding the pain and suffering resulting from the illness (a potentially largecomponent), it is generally believed to underestimate the total value of avoiding the illness,perhaps substantially.

The contingent valuation method attempts to elicit from people what they would be willing to payto avoid the illness. Because of the distortion in the market for medical goods and services,whereby individuals generally do not pay the full value of the medical care, this method too islikely to understate the total value of avoiding the illness.

Although the COI and contingent valuation are the two most common methods, other methodshave been used in certain circumstances. The method the benefit analyst chooses to value a



particular health endpoint will depend in part on what is available. The unit values currentlyavailable for use in BenMAP are data or estimates that have been collected or generated byresearchers and can be readily obtained in publicly available databases or in the open literature. When reviewing the economic literature to determine the appropriate valuation functions to use, itis important to have an economist assist.

7.1.1.1 Valuing Reductions in Premature Mortality

The economics literature discussing the value of changes in fatality risks is extensive and providesa basis for monetizing benefits when the number of deaths avoided as a result of a regulatoryaction can be calculated, but the literature on certain issues regarding the appropriate method forvaluing reductions in premature mortality risk is still developing. Issues such as the appropriatediscount rate and whether there are factors, such as age or the quality of life, that should be takeninto consideration when estimating the value of avoided premature mortality are still underdiscussion. BenMAP currently offers a variety of options reflecting the uncertainty surroundingthe unit value for premature mortality. See the appendix on Economic Value of Health Effects formore detail on the valuation functions available in BenMAP.

Monetary estimates of changes in fatality risk are often expressed in terms of the Value of aStatistical Life (VSL). This term is easily misinterpreted and should be carefully described whenused in benefit analysis. In particular, VSL refers to the WTP for reductions in the risk ofpremature death aggregated over the population experiencing the risk reduction; that is, VSLrefers to the sum of many small reductions in fatality risks. The basic assumption underlying theVSL approach is that equal increments in fatality risks are valued equally. For similar reasons,the VSL approach is only appropriate for marginal changes in the risk of death and should not beused to value more significant changes. Because changes in individual fatality risks resulting fromenvironmental regulation are typically very small, the VSL approach is usually acceptable forthese types of benefit analyses.

7.1.2 Overview of Discounting

What is discounting?

In general, people prefer current consumption to future consumption. In other words, a $1today is worth more today than a $1 tomorrow is worth today, and that dollar continues todecrease in value as you go further out into the future. (This concept is also referred to as thesocial rate of time preference or the time value of money. This is a different concept thaninflation, which is a general increase in the price level of goods and services.) Discounting is theprocess of converting that future dollar into a value that can be compared to the value of a dollartoday. The discount rate expresses this process in quantitative terms. The higher the discountrate, the faster value decreases over time. For example, $1 twenty years from now is worth$0.55 today at a 3% annual discount rate, but worth only $0.26 at a 7% annual discount rate.

A basic discounting function is as follows:

Present Value = Future Value / (1+r)t



where r is the discount rate and t is the time period (usually years).

Example: $1 twenty years from now at a 3% annual discount rate is worth $0.55 today

Present Value = $1.00 / (1 + 0.03)20 = 1 / (1.03)20 = 1 / 1.806111 = 0.553676 = $0.55

Why do we discount benefits?

The benefits of reductions in air pollution may need to be discounted for several reasons.

1. Today’s society values benefits that occur today more than benefits in the future. Therefore,we must discount in order to compare those future benefits with current benefits.

2. For a cost-benefit analysis, benefits estimates need to be comparable to the cost estimates.Discounting can be used to compare the future streams of benefits and costs.

3. BenMAP only estimates changes in adverse health effects based on changes in air quality forone specified analysis year, even though certain health benefits may occur after the analysis year. Discounting can be used to compare the future benefits with benefits occurring during the analysisyear.

Under which scenarios would I need to discount benefits?

Health benefits may occur three different ways after the analysis year specified in BenMAP.

1. Certain health endpoints accrue medical expenses or lost earnings for multiple years. Thefuture medical expenses would need to be discounted to compare with expenses occurring in theanalysis year.

2. Pollution exposure and the resulting health effects do not occur within the same year (a.k.a. acession lag). The monetized benefits of future health effects would need to be discounted tocompare with the benefits of health effects that occur during the analysis year.

3. In some analyses, you may want to estimate a stream of benefits occurring over multipleanalysis years instead of just one analysis year. In this scenario, you would need to discount thefuture benefits occurring in each year analyzed back to the present year in order to present thecumulative total estimate of benefits (i.e., the net present value of a stream of benefits).

When would we not discount benefits?

In many instances, it is not necessary to discount the benefits estimates generated by BenMAP. If the health effect and the monetized value of all the medical expenses, lost earnings, andsuffering occur entirely in the analysis year, then you may not need to discount your benefits. Forexample, school loss days occur within the analysis year, and all monetized expenses occur within



the analysis year. It is important that you understand the assumptions within the health andvaluation functions before you decide whether you need to discount. (If your analysis year foryour benefits estimates does not match the analysis year for your costs estimates, you may needto discount in order to compare your benefits with your costs even if you meet the criteria listedabove.)

Which discount rate should I choose?

Selecting a discount rate is challenging and is one of the most contentious methodological issuesencountered in economic analyses of environmental policies. Because environmental regulationsfrequently have differing streams of costs and benefits over time, the selected discount rate maydetermine whether the benefits of a regulatory action exceed the costs. In addition, selecting ahigher discount rate may result in a smaller benefits estimate because the future benefits are worthmuch less than they would be if a lower discount rate was selected. For benefits that occur wellinto the future, the issue of intergenerational equity further complicates the selection of thediscount rate. (In the context of environmental policy, intergenerational equity refers to thefairness of the distribution of the costs and benefits of a long-lived policy when those costs andbenefits are borne by different generations. Most criteria pollutants are not considered to haveintergenerational equity issues, but the issue frequently arises in analyses of climate and mercury.)

There are various economic arguments in support of and in opposition to various discount rates.(For more details see EPA [1999; 2000] listed in the section on Sources for More Information.)To comply with OMB and EPA’s recommendations, EPA currently uses discount rates of 3%and 7% for benefit analyses.

Which health endpoints accrue medical expenses or lost earnings for multiple years, andhow do I discount them?

BenMAP includes health and valuation functions for several chronic health effects, including PM2.5

–related chronic bronchitis and non-fatal acute myocardial infarctions (AMIs, or heart attacks). Technically, AMIs are discrete, acute events, not chronic conditions. However, heart attackscause chronic follow-up health effects that accrue medical expenses over time, similar to chronicconditions. You can discount the economic value of these chronic effects through the valuationfunction in BenMAP. Chronic bronchitis is assumed to last from the initial onset of the illnessthroughout the rest of the individual’s life. BenMAP currently includes one WTP function as wellas two COI functions representing the two discount rates for chronic bronchitis. AMIs areassumed to accrue costs over five years. Although WTP functions for AMIs are not available,BenMAP currently includes several COI functions that incorporate the direct medical costs andthe opportunity cost (lost earnings) for specific age groups at two discount rates. See Appendix Ifor details on the discounting assumptions within the valuation functions.



Should I discount the health incidence as well as the valuation?

You should not discount the health incidence for any of the scenarios mentioned above. Changesin the lag assumptions do not change the total number of estimated deaths, for example, butrather the timing of those deaths. If you discounted the health incidence along with valuation, youwould essentially be discounting twice. In contrast, the process for conducting cost-effectivenessanalyses and calculating QALYs involves discounting life years. See Appendix G of the PM RIAfor more information on cost-effectiveness analyses (http://www.epa.gov/ttn/ecas/regdata/RIAs/Appendix%20G--Health%20Based%20Cost%20Effectiveness%20Analysis.pdf).

Which health endpoints do not occur in the same year as exposure?

In many cases, the health effect from exposure to air pollution occurs shortly after exposure, butthere can be a significant lag between exposure and the health effect. The cession lag can be amatter of hours or days in duration, but some health effects may lag exposure by much longer. Ifexposure and the health effect do not occur within the same year, it is necessary to discount thosebenefits back to the analysis year. The only health function currently in BenMAP that falls intothis category is PM

2.5–related premature mortality. Discounting PM-related premature mortality

is controversial because the lag structure is unknown, but scientific literature on similar adversehealth effects and new intervention studies suggest that premature mortality probably would notoccur in the same year as the exposure. (See: Roosli M, Kunzli N, Braun-Fahrlander C, EggerM. 2005. “Years of life lost attributable to air pollution in Switzerland: dynamic exposure-response model.” International Journal of Epidemiology 34[5]:1029-35.)

EPA’s Science Advisory Board recommends future research to support the development ofdefensible lag structures and provided a lag structure that could be assumed until additionalresearch has been completed. See Chapter 5 of the PM RIA for more detail on assumed lagstructures for PM

2.5-related premature mortality (http://www.epa.gov/ttn/ecas/regdata/RIAs/

Chapter%205--Benefits.pdf). Some example lag structures from the PM RIA are shown inFigures 6-1 and 6-2 below. Currently, BenMAP does not have the capability to do this type ofdiscounting, so you must discount outside of BenMAP.

Note: Discounting is not necessary for ozone-related premature mortality because it occurswithin the analysis year.

http://www.epa.gov/ttn/ecas/regdata/RIAs/Appendix%20G--Health%20Based%20Cost%20Effectiveness%20Analysis.pdf

http://www.epa.gov/ttn/ecas/regdata/RIAs/Appendix%20G--Health%20Based%20Cost%20Effectiveness%20Analysis.pdf





Figure 6-1. Graphical representation of assumed lag structures analyzed in EPA’s PMRIA as sensitivity analyses

Assumed Lag Structures for PM2.5 Premature Mortality

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Figure 6-2. Graphical representation of cumulative assumed lag structures analyzed inEPA’s PM RIA as sensitivity analyses

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7.1.3 Overview of Pooling

For many of the health endpoints (e.g., mortality), BenMAP contains many different functionsfrom different studies that you could choose to include in your configuration. Combining datafrom several comparable studies in order to analyze them together is often referred to as meta-analysis. For a number of reasons, it is often impractical or impossible to combine the originaldata sets. Combining the results of studies provides a second-best way to synthesizeinformation. This is referred to as pooling.

BenMAP allows the pooling of incidence changes predicted by several studies for the samepollutant-health endpoint group combination. It also allows the pooling of the correspondingstudy-specific estimates of monetary benefits. See the appendix on Uncertainty & Pooling formore detail on the pooling options available in BenMAP.

7.2 Create Aggregation, Pooling, and Valuation (APV) Configuration

To start you need to choose a configuration results file that contains incidence estimates at the grid cell level (created by clicking the Create and Run Configuration button, see Chapter 6).These incidence results are in files with a *.cfgr extension, and typically stored in the Configuration Results folder.



Once you open this file, you can begin creating your APV configuration. You will start withselecting and pooling your incidence results, then move on to valuation. These processes aredescribed in detail below. Advanced functions, including aggregation, are described below.

7.2.1 Pooling Incidence Results

After opening the configuration results file, you will find a list of Available Incidence Results onthe left-hand side of the window. The results are represented by the health impact functions fromwhich they were created, and are displayed in a tree-structure with three levels, similar to thetree-structure found in the Configuration Settings Window. Endpoint Groups occupy thetop-most level, followed by Endpoints, and then individual health impact Function identifiers.You will also see a pooling window at the right, where you can select pooling options.

There are several steps to pooling your incidence results:

Step 1. Add incidence results to the pooling window

In the Incidence and Pooling window, you will see all the incidence results generated from yourconfiguration in the left hand column. You can drag individual incidence results, or groups of



results at any level of the tree and drag them over to the pooling window. Note that once youdrag a result or group of results into the pooling window it will still be displayed on the left side. You do not have to drag all of your incidence results over into the pooling window, but note thatonly those results showing in the pooling window will be included in the pooled incidence orvaluation results.

Incidence results are displayed in the pooling window in a tree structure determined by (1) theorder of the columns, and (2) the values of the identifying variables of the health impact Functionsfrom which the incidence results were generated (Endpoint Group, Endpoint, etc.).

Each line in the pooling window represents a node in the tree structure, with each noderepresenting either an individual incidence result or a collection of incidence results which havecommon values for their leftmost identifying variables. The tree structure is generated bycomparing the leftmost values of the incidence result’s identifying variables. High level nodes inthe tree are formed when results have common values for identifying variables, and branches inthe tree occur when the values differ.



In the above example, four incidence results have been dragged into the pooling window. Eachof the four health impact Functions has Endpoint Group Asthma Exacerbation. Thus, the topline, or root of the tree structure, represents all four incidence results. A branch then occurs inthe tree structure, because two studies have Endpoint Asthma Exacerbation, Cough, whiletwo others have Endpoint Asthma Exacerbation, Wheeze and Endpoint AsthmaExacerbation, Shortness of Breath. A further branch occurs within Endpoint AsthmaExacerbation, Cough when Author of the two incidence results differs. Once a node has onlya single incidence result, no further branching can occur.

Step 2. Sort results

After dragging incidence results into the Pooling Window, you can rearrange the order of thecolumns (variables), and thus change the tree structure. To do this, click on a column and holdthe button down as you drag it to its new location. Note that Endpoint Group is always the firstcolumn, and Pooling Method is always the last column. All the other columns can be moved.To see how the order of the columns in the pooling window affects the tree structure, considerthe following example:



This example uses exactly the same incidence results as the previous example, but with the Author column (variable) immediately after the Endpoint Group column.

Step 3. Select pooling methods

Once the tree structure is set up in the Pooling Window, you are ready to select your poolingmethods. Essentially each pooling method involves a different method of combining inputincidence results to generate new incidence results. Results can be pooled any time a branchoccurs in the tree structure - that is, any time two or more results share common values for theirleftmost variables. BenMAP helps you to identify these spots by inserting a value of None in the Pooling Method column at each spot where pooling is possible.

Table 7-1 summarizes the different types of pooling approaches, and Appendix K provides adetailed discussion of the approaches. Note that some pooling methods are only available inLatin Hypercube mode. This is because these pooling methods attempt to combine distributionsof results into new distributions, and no distributional information is available in Point Mode. The Pooling Method column will thus have different values in its drop down list depending on themode used to generate the incidence results being pooled.



Table 7-1. Pooling Approaches for Incidence and Valuation Results

PoolingApproach

Description of Pooling Approach

Availability

PointMode

LatinHypercube

None No pooling performed. Yes Yes

Sum(Dependent)

Results are summed assuming they are perfectly correlated. InPoint Mode, this is just a simple sum. In Latin Hypercube mode,BenMAP chooses the first point from each result in the poolingand does a simple sum to generate the first point in the pooled

result, and so on for all of the points in the distribution ofresults.

Yes Yes

Sum(Independent)

Results are summed assuming that they are independent. AMonte Carlo simulation is used. At each iteration, a random

point is chosen from the Latin Hypercube of each result, and thesum of these values is put in a holding container. After some

number of iterations, the holding container is sorted low to highand binned down to the appropriate number of Latin Hypercube

points.

No Yes

Subtraction(Dependent)

Results are subtracted assuming they are perfectly correlated. All subsequent results are subtracted from the first result (the

highest result in the display - to reorder results, simply click andhold a result and then drag it to its new position). In Point

Mode, this is a simple subtraction. In Latin Hypercube mode,BenMAP chooses the first point from each result in the poolingand does a simple subtraction to generate the first point in thepooled result, and so on for all of the points in the distribution

of results.

Yes Yes

Subtraction(Independent)

Results are subtracted assuming that they are independent. AMonte Carlo simulation is used. At each iteration, a random

point is chosen from the Latin Hypercube of the first result, andthen random points are chosen from the Latin Hypercube of

each subsequent result and subtracted from the first. The resultis put into a holding container. After some number of iterations,the holding container is sorted low to high and binned down to

the appropriate number of Latin Hypercube points.

No Yes

SubjectiveWeights

Weights are specified by the user (see Step 5, below). In PointMode, the new result is generated by a simple weighted sum of

the input results. In Latin Hypercube mode, the results arecombined using the user specified weights with the “Round

Weights to Two Digits” Advanced Pooling Method. Note thatthe weights you enter need not add up to one - BenMAP will

normalize them internally. Also note that BenMAP initializes allthe weights to 1/n, where n is the number of results being

pooled.

Yes Yes



PoolingApproach

Description of Pooling Approach

Availability

PointMode

LatinHypercube

Fixed Effects Pooling weights are generated automatically based on theinverse variance of each input result, with the weights

normalized to sum to one. Results with a larger absolutevariance get smaller weights. Results are then combined

according to the chosen Advanced Pooling Method.

No Yes

Random / FixedEffects

BenMAP first tests if random weights should be used. If not,BenMAP uses fixed effects weights. If yes, the weights take

into account both the variance within each set of results and thevariance between sets of results. Results are then combined

according to the chosen Advanced Pooling Method.

No Yes

Step 4. Create additional pooling windows if needed

Within a given pooling window, you can have only one ordering of the columns (variables). Aswe have seen, however, the ordering of the columns determines the structure of the tree used topool results. It may thus sometimes be necessary for analyses to have multiple tree structures tohandle the various pooling trees they require. To facilitate this, BenMAP allows additionalpooling windows to be added and deleted. To open a new pooling window, simply click on the Add button. You may do this as many times as needed to accommodate different sort orders.You can add the same incidence results to as many different pooling windows as you like.

As needed you can also delete a pooling window by using the “-- Window to Delete --” drop-down menu to identify the pooling window, and then hitting the Delete button.



7.2.1.1 Example: Simple Sorting & Pooling

If you add a single incidence result to the right-hand window, you will see just one line, andtherefore no opportunities to pool. This shown in the example below.



If you add a second incidence result to the window whose health impact Function has the sameEndpoint Group, but a different Author, you will then have a tree with two items in it. The treebranches at the point where the two health impact Functions vary - at the Author column.

Note that a pooling method can now be selected for the two incidence results, since a branch hasappeared. If we desired to pool these two incidence results, we would end up with a pooledresult representing two Hospital Admissions (HA), Respiratory incidence results.

If you now add four more incidence results to the window whose health impact Functions have



the same Endpoint Group, you will see the following:

Now you have many pooling options. Setting aside the issue of which pooling method to choose,there are four different pooling options at this point (including doing nothing), since we have twoplaces where we can choose to pool or not to pool.

If you choose to pool at the spot corresponding to Endpoint (HA, Chronic Lung Disease) youwould end up with three results (one pooled and two unpooled) instead of four individualincidence results.

If you choose to pool at the first place where the Pooling Method field says None, the spotcorresponding to the Endpoint Group (Hospital Admissions, Respiratory), you will end up with asingle result representing all four of the original incidence results.



If you pool at both spots:

First, the HA, Chronic Lung Disease results are pooled to a give a single HA, Chronic LungDisease result.

Next, the three separate Endpoint results are pooled to give a single Hospital Admissions,Respiratory result.

These same principles apply no matter how many incidence results are being pooled, andregardless of which pooling methods are selected.

7.2.1.2 Example: Multiple Pooling Windows

There are many different ways to pool your incidence results. Sometimes you may want to lookat the same results in different ways, or you may just have many results that need to be sorted bydifferent variables. In these cases, you can open up multiple pooling windows by clicking on the Add button.



For example, you might want to pool all results of health impact Functions by a particular author,rather than pooling all results of health impact functions of a particular endpoint. The examplesbelow show the same set of incidence results, first sorted by Author, then sorted by Endpoint.As you can see, the pooling options are very different.

If you use two different pooling windows, each sorted as shown above, you can create resultspooled by Author, and results pooled by Endpoint.

7.2.2 Valuing Pooled Incidence Results

After you have specified your incidence pooling options you can hit the Next button and selectvaluations and valuation pooling options. The Select Valuation Methods, Pooling andAggregation window appears after you click Next on the Incidence Pooling andAggregation window. This window should look quite similar to the Incidence Pooling andAggregation window, with tree views on the left side representing the valuation databases



available, and various pooling windows on the right side representing the selected valuations andpooling options.

There will be one pooling window in the Select Valuation Methods, Pooling, andAggregation screen for each pooling window Incidence Pooling and Aggregation screen. Ineach pooling window, there will be one result present for each incidence result left over after allincidence pooling has occurred. Each of these results will be represented by a “-- Select --”value in the Valuation Method column.

The columns present in the Select Valuation Methods, Pooling, and Aggregation windoware determined by the incidence results left after all incidence pooling has occurred. There will beexactly enough columns in each pooling window to represent the “least” pooled incidence result. That is, the columns will be in the same order they were in the Incidence Pooling andAggregation window, but the only columns present will be those up to the level of the pooledincidence result with the most columns left over after all pooling has occurred. Here is anexample:

There are several steps to take in the Select Valuation Methods, Pooling, and Aggregationwindow:



Step 1. Select your valuation methods

Valuation methods are specific to endpoint groups, and sometimes to endpoints as well. Theonly valuation methods which appear in the left side tree views are those which have the sameendpoint group values as the pooled incidence results which are available to be valued. To selecta valuation method, select it in the left side tree views and drag and drop it onto the appropriateincidence result in the pooling window. Note that BenMAP will only allow you to drop valuationmethods onto incidence results which have the same endpoint group value. For example,BenMAP will not allow you to drop a Mortality valuation on a Hospital Admissions incidenceresult. Note also that you can only drag and drop individual valuation methods, not entire groupsof them. For explanations of the various valuations, see the appendix on the Economic Value ofHealth Effects.

If you have added any of your own valuation methods, as described in the Valuation Data sectionof the Loading Data chapter, you can drag and drop them in the same way as the EPA Standardvaluations.

When BenMAP runs the APV Configuration, it will generate a valuation result for eachvaluation method you select by running the valuation method’s valuation functions on theincidence results for which they were selected. You do not need to select valuation methods forevery incidence result - incidence results without any valuation methods will simply be ignoredwhen valuation results are generated, aggregated, and pooled.

Because valuation functions have uncertainty associated with them, generating valuation results isfairly complicated. The procedure used depends on whether the incidence results being usedwere generated in Point Mode or with Latin Hypercube Points (see the chapter on Incidence



Estimation for details on Point Mode and Latin Hypercube Points).

In Point Mode, BenMAP simply runs the valuation functions once using the point estimate of theincidence result and the mean of the valuation function as inputs.

With Latin Hypercube Points, on the other hand, BenMAP generates one hundred percentilepoints (from the 0.5th percentile to the 99.5th percentile) to represent the distribution of theinputs to the valuation function. To get the value of the health incidence, BenMAP multiplies eachcombination of values from the incidence result, Latin Hypercube, with each of the hundredvaluation points, and puts the results into a holding container. (For example, if the incidenceresult has 10 Latin Hypercube Points and there are 100 valuation points, then the holdingcontainer will have 1,000 values.) Finally, the holding container is sorted low to high and binnedback down to 100 Latin Hypercube points (representing the 0.5th percentile to the 99.5thpercentile of the economic value of the incidence).


Depending on how your incidence results were pooled, the columns in the valuation poolingwindows can be resorted in the same way as the incidence pooling window columns. Thisresorting will have the same sort of impact on the tree structure of valuation results that it had onthe tree structure of incidence results. (See Step 2 in the section on Pooling Incidence Results.)


The same pooling methods are available for valuation results which were available for incidenceresults. (See Step 2 in the section on Pooling Incidence Results.) You should note that whenmore than one valuation method is selected for a particular pooled incidence result, it is possibleto pool the generated valuation results.



Step 4. Select Variable DataSet

In order to proceed to the next step, you must select a Variable DataSet from the drop-downmenu. The files in the Variable DataSet can include a variety of data, such as income andpoverty data that might be used in health or valuation functions. For the default EPA health andvaluation functions, you just need to select the EPA Standard Variables.

If you have developed your own setup, then you need to make sure that you also load a Variable DataSet. This is necessary even if you do not need the extra variables that canincluded in this dataset.



7.2.3 Using QALYs Weights

After you have specified your incidence and valuation pooling options, you can select QALYsand pooling options. By default, the Skip QALY Weights box is checked in the SelectValuation Methods, Pooling, and Aggregation window. This is done to save time, as it takesBenMAP a few moments to load the QALY datafiles. If you want to use QALY weights, thenuncheck this box, and then click Next.

The Select QALY Methods, Pooling and Aggregation window appears after you click Nexton the Select Valuation Methods, Pooling and Aggregation window. This window shouldlook quite similar to the Incidence Pooling and Aggregation and Select Valuation Methods,Pooling and Aggregation windows, with tree views on the left side representing the valuationdatabases available, and various pooling windows on the right side representing the selectedvaluations and pooling options.

There will be one pooling window in the Select QALY Methods, Pooling, and Aggregationscreen for each pooling window Incidence Pooling and Aggregation screen. In each poolingwindow, there will be one result present for each incidence result left over after all incidencepooling has occurred. Each of these results will be represented by a “-- Select --” value in the QALY Method column.



As with the Select Valuation Methods, Pooling, and Aggregation window, the columnspresent in the Select QALY Methods, Pooling, and Aggregation window are determined bythe incidence results left after all incidence pooling has occurred. There will be exactly enoughcolumns in each pooling window to represent the “least” pooled incidence result. That is, thecolumns will be in the same order they were in the Incidence Pooling and Aggregationwindow, but the only columns present will be those up to the level of the pooled incidence resultwith the most columns left over after all pooling has occurred. Here is an example:

There are several steps to take in the Select QALY Methods, Pooling, and Aggregationwindow:

Step 1. Select your QALY methods

The QALY datasets that come installed with the U.S. setup have only a limited number of QALYmethods -- mortality, myocardial infarction (heart attack) and chronic bronchitis. And, as withvaluation methods, the QALY methods are specific to endpoint groups. The only QALYmethods which appear in the left side tree views are those which have the same endpoint groupvalues as the pooled incidence results which are available to be valued. For example, in thestandard APV Configuration for PM

2.5 used by EPA, the available QALY methods appear in the

left side tree.



On the other hand, in the case of the Endpoint Group Hospital Admissions, Respiratory, thereare no QALY methods from which to choose in the data that comes loaded with BenMAP, asseen in the following screenshot:

To select a QALY method, select it in the left side tree views and drag and drop it onto the



appropriate incidence result in the pooling window. Note that BenMAP will only allow you todrop QALY methods onto incidence results which have the same endpoint group value. Forexample, BenMAP will not allow you to drop a Mortality QALY method on a AcuteMyocardial Infarction incidence result. Note also that you can only drag and drop individualQALY methods, not entire groups of them.

If you have added any of your own QALY methods, as described in the QALY Data section ofthe Loading Data chapter, you can drag and drop them in the same way as the EPA Standardvaluations.

When BenMAP runs the APV Configuration, it will generate a QALY result for each QALYmethod you select. You do not need to select QALY methods for every incidence result -incidence results without any QALY methods will simply be ignored when QALY results aregenerated, aggregated, and pooled.

Because QALY method databases have uncertainty associated with them, generating QALYresults is fairly complicated. The procedure used depends on whether the incidence results beingused were generated in Point Mode or with Latin Hypercube Points (see the chapter onIncidence Estimation for details on Point Mode and Latin Hypercube Points).

In Point Mode, BenMAP simply runs the QALY functions once using the point estimate of theincidence result and the mean of the valuation function as inputs.

With Latin Hypercube Points, on the other hand, BenMAP uses a 5,000 draw Monte Carloapproach to estimate QALYs. That is, BenMAP draws once from the QALY database andonce from the incidence Latin Hypercube, and multiplies the two draws together, repeating thisprocess 5,000 times and putting the results into a holding container. Finally, the holding containeris sorted low to high and binned back down to 100 Latin Hypercube points (representing the0.5th percentile to the 99.5th percentile of the estimated QALY distribution).


Depending on how your incidence results were pooled, the columns in the QALY poolingwindows can be resorted in the same way as the incidence and valuation pooling windowcolumns. This resorting will have the same sort of impact on the tree structure of valuation resultsthat it had on the tree structure of incidence results. (See Step 2 in the section on PoolingIncidence Results.)


The same pooling methods are available for QALY results which were available for incidenceand valuation results. (See Step 2 in the section on Pooling Incidence Results.) You should notethat when more than one QALY method is selected for a particular pooled incidence result, it ispossible to pool the generated QALY results.



7.2.4 APV Configuration Advanced Settings

At any point when specifying the incidence and valuation pooling options, you may click on theAdvanced button on the bottom-left of either the window for Incidence Pooling andAggregation, Select Valuation Methods, Pooling and Aggregation, or Select QALYMethods, Pooling and Aggregation. This button will open the APV ConfigurationAdvanced Settings window.

The APV Configuration Advanced Settings window has three advanced option tabs for thefollowing:

Aggregation and Pooling. This lets you choose the level of aggregation for the incidence,valuation, and QALY results. You can also specify details on the pooling procedure, such aswhether to use a Monte Carlo or Latin Hypercube approach.

Currency and Income. You can choose the currency year, how to adjust for inflation, andhow to adjust for income growth.



7.2.4.1 Aggregation & Pooling

The Aggegation & Pooling tab lets you choose the level of aggregation for the incidence,valuation, and QALY results. You can also specify details on the pooling procedure, such aswhether to use a Monte Carlo or Latin Hypercube approach.



Default Advanced Pooling Method

The relative contribution of any one study in the pooling process depends on the weight assignedto that study. A key component of the pooling process, then, is the determination of the weightgiven to each study. BenMAP lets users assign "subjective" weights and it assign weights using afixed effects or a random effects approach. There are three options for using weights available inthe Default Advanced Pooling Method drop-down menu:

Round weights to two digits. BenMAP rounds each weight to two digits (e.g. 0.73), andthen multiplies these weights by 100 to get two digit integers. Each entire distribution (set ofLatin Hypercube points) is then put into a holding container an integral number of times,according to its integral weight. This holding container is then sorted low to high and binneddown to the appropriate number of Latin Hypercube points.

Round weights to three digits. BenMAP rounds each weight to three digits (e.g. 0.732), andthen multiplies these weights by 1000 to get three digit integers. Each entire distribution (set ofLatin Hypercube points) is then put into a holding container an integral number of times,according to its integral weight. This holding container is then sorted low to high and binneddown to the appropriate number of Latin Hypercube points.

Use exact weights for Monte Carlo. BenMAP uses exact weights and a Monte Carlosimulation. On each iteration of the procedure, a particular result is chosen with a probabilityequal to its weight. Once a result is chosen, one of its Latin Hypercube points is chosen atrandom and put into a holding container. This is done some number of times (see Monte



Carlo Iterations, below), and the holding container is then sorted low to high and binned downto the appropriate number of Latin Hypercube points.

Default Monte Carlo Iterations

This drop down list is only enabled when Use exact weights for Monte Carlo is selected as theAdvanced Pooling Method. It specifies the number of iterations the Monte Carlo simulationshould be run (see above). Its initial value is set by the Default Monte Carlo Iterations valuefrom the APV Advanced Settings window (see Step 1, above).

Random Seed

The APV Configuration Advanced Settings window allows the specification of a RandomSeed. As mentioned at the beginning of this chapter (see Open an APV Results File, above)many of the pooling methods require the generation of sequences of random numbers (e.g.choosing a random Latin Hypercube point during a Monte Carlo simulation). Providing aspecific Random Seed value allows you to ensure that the same sequence of random numbers isgenerated as in a previous analysis, thus allowing exact results to be reproduced.

If you do not set the Random Seed for a particular run, one will be generated automatically fromthe system clock (the number generated will depend on the date and time, and should changeevery minute). Normally, you should not set the Random Seed value. If you need to reproducea specific set of results, however, the random seed used to generate previous APVConfiguration Results can be obtained from an APV Configuration Result file (*.apvr) AuditTrail Report.

Sort Incidence Results

The Sort Incidence Results should generally be always checked. This setting ensures that theincidence Latin Hypercube results are sorted low to high.

7.2.4.2 Currency & Income

The Currency & Income tab allows you to specify an Inflation DataSet and a CurrencyYear, which in combination allow you to change the year of the valuation dollars. The IncomeGrowth Adjustment panel allows you to adjust the valuation estimates to account for the growthin income over time.



Inflation Adjustment

The inflation adjustment needs to be carefully considered in relation to the valuation database thatyou are using. (This is discussed in detail in the section on loading inflation data.) The defaultvaluation database in the U.S. Setup has a currency year of 2000, so the inflation dataset has avalue of 1 for the year 2000.

Income Growth Adjustment

Willingness to pay (WTP) estimates are believed to be tied to the income of individuals. Asincome rises over time, WTP estimates are likely to increase as well. The income growthadjustment is designed to take this phenomenon into account, allowing you to account for incomegrowth between the time when WTP estimates were calculated and the year of your analysis.

As with the inflation adjustment, the income growth adjustment has a close connection to thevaluation estimates. For example, the valuation estimates in the default version of BenMAP areassumed to be based on income levels from 1990, so the income growth adjustment databasehas a value of 1 for the year 1990. (This is discussed in detail in the section on loading incomegrowth data.)

To use the income growth adjustment, you need to choose a dataset and then choose the incomeyear that you want to use. It is common to set the "Year" variable to the year of the population



forecast in your analysis. Of course, you can only choose from the available data. If the incomegrowth adjustment data only goes to 2024 and the population data in your analysis are for 2030,then there will be some, unavoidable mismatch.

7.3 Run APV Configuration

After having specified the various aggregation, pooling, and valuation/QALY options, you havethe opportunity to save your APV Configuration for future use. The file that you save has an“apv” extension. The configuration that you have specified is similar in idea to the configurationthat you developed for choosing health impact functions. (That configuration has a “cfg”extension.) Both files allow you to save choices that you have made, and re-run them at a latertime.

You can save your APV configuration when you have finished making your valuation poolingchoices. Click the Run button, and then choose Save.

You then need to name your configuration (*.apv) file. We suggest that you save this in theConfigurations folder. When ready to generate APV Configuration results, click the OK button.BenMAP then requires that you specify a file in which to save the results, with an “.apvr”extension.

7.4 Open & Modify Existing APV Configuration

If you have an existing configuration (*.apv) file, you can open, and then edit it.



If you have only a few changes to make to an existing configuration, it is typically much quicker toopen the previous configuration, rather than entering all of your choices again. Note that thevarious parts of an APV Configuration are quite interdependent, so modifying part of theconfiguration may cause other parts to be reset. For example, modifying the tree structure forincidence pooling will cause the valuation method selection and valuation pooling tree structure tobe cleared and reset. Changing the Configuration Results Filename in the Incidence Pooling andAggregation window will not reset the incidence or valuation pooling trees as long as the new filecontains incidence results generated from the same health impact Functions as the old file. Thiscan be quite helpful for generating new APV Configuration Results from several differentConfiguration Results files which were generated from different baseline / control scenarios, butwith the same set of health impact functions.

7.5 Questions Regarding APV Configurations

I am at the BenMAP valuation window and cannot proceed. What should I do?

In order to proceed to the next step, you must select a Variable DataSet from the drop-down menu in the Select Valuation Methods, Pooling, and Aggregation window. Thefiles in the Variable DataSet can include a variety of data, such as income and poverty datathat might be used in health or valuation functions. For the default EPA health and valuationfunctions, you just need to select the EPA Standard Variables.

If you have developed your own setup, then you need to make sure that you also load a Variable DataSet. This is necessary even if you do not need the extra variables that can beincluded in this dataset.

How do I edit or add other valuation functions?

To edit or add valuation functions you need to go to Modify Setup option in the Tools drop-down menu available in the upper left-hand corner of the main BenMAP window. See the valuation function section in the chapter on Loading Data for details on how to do this.



How do I get to the QALY selection window?

By default, the Skip QALY Weights box is checked in the Select Valuation Methods,Pooling, and Aggregation window. This is done to save time, as it takes BenMAP a fewmoments to load the QALY datafiles. If you want to use QALY weights, then uncheck thisbox, and then click Next.

The Select QALY Methods, Pooling and Aggregation window appears after you clickNext on the Select Valuation Methods, Pooling and Aggregation window.

How do I know what year dollars were used?

You can find the answer in the Audit trail for the APVR file that you generated.

Do the currency year and year of the population data have to match?

No. The currency year and the year of the population data do not need to match.

Reports


CHAPTER 8

Reports

In this chapter...

Use the Create Reports button to create incidence,valuation, and QALY reports.

Find the file formats, including variable definitions andprogram compatibility, for each report type.

Find out about using an Audit Trail report to keep trackof the options and assumptions underlying eachanalysis.

Reports


If you are interested in merely exporting results or merely viewing them, there are three types ofreports that you can access by clicking on the Create Reports button. You will be asked whichtype of report you wish to create:

Incidence, Valuation, & QALY Results: Raw, Aggregated, and Pooled use anAggregation, Pooling, and Valuation Results file (with the “.apvr” extension) to create report for incidence, aggregated incidence, pooled incidence, valuation, aggregated valuation, pooledvaluation, QALY, aggregated QALY, or pooled QALY results. These reports are commaseparated values (CSV) files (*.csv) which can be read into various spreadsheet and databaseprograms, such as Microsoft Excel.

Raw Incidence Results use a Configuration Results file (with the “.cfgr” extension) to createreports for incidence results. These reports are CSV files.

Audit Trail Reports provide a summary of the assumptions underlying each of five types offiles generated by BenMAP: Air Quality Grids (with the “.aqg” extension), IncidenceConfigurations (with the “.cfg” extension), Configuration Results (with the “.cfgr”extension), Aggregation, Pooling, and Valuation Configurations (with the “.apv” extension),and Aggregation, Pooling, and Valuation Results (with the “.apvr” extension). Thesereports can be viewed within BenMAP in an expandable tree structure, or can be exported totab-delimited text files.

Reports


8.1 One-Step Reports

trail report button.

The report module for one-step analysis is the same as custom analysis (see Section 8.2).

Alternatively, you can load in a data file and create reports at the One Step Analysis window.

Reports


Click on the Open Results button. This will bring up the One Step Results window.

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Click on the Load APVR button, and browse for the APVR file that you want to load. Makesure that the file you load has the results needed for the reports that you will be generating. Ifyou find that the tables, box plot, or bar charts look incomplete, misformatted, or otherwise odd,check that the CFG and APV files are reasonably similar to the default files that come withBenMAP. To the extent that there are divergences, then it is likely that these pre-defined reports(which depend on the output looking a certain way) will not look right.

8.2 Incidence, Valuation, & QALY - from APVR file

Using the results in the Aggregation, Pooling, and Valuation Results file (“.apvr” extension), youcan create nine types of reports: raw incidence, aggregated incidence, pooled incidence, valuation(of the pooled incidence), aggregated valuation, and pooled valuation. After you click on the Create Reports button, you need to specify the APV Configuration Results File that youwant to use.

Reports


After choosing your APVR file and clicking the Open button, you then need to choose a ResultType.

Table 8-1 describes the results contained in each type of report.

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Table 8-1. Summary of the Reports Generated from APVR Files

Result Type Description

Incidence Results Incidence results for each health impact function at the grid-cell level oraggregated at the county, state, or national level.

Aggregated IncidenceResults

Incidence results for each health impact function aggregated to the level youspecified in the Aggregation, Pooling, and Valuation configuration file.

Pooled Incidence Results Incidence results aggregated and pooled as you specified in the Aggregation,Pooling, and Valuation configuration file.

Valuation Results Valuation results for the pooled and aggregated incidence results.

Aggregated ValuationResults

Valuation results aggregated to the level you specified in the Aggregation,Pooling, and Valuation configuration file.

Pooled Valuation Results Valuation results aggregated and pooled as you specified in the Aggregation,Pooling, and Valuation configuration file.

QALY Results QALY results for the pooled and aggregated incidence results.

Aggregated QALYResults

QALY results aggregated to the level you specified in the Aggregation,Pooling, and Valuation configuration file.

Pooled QALY Results QALY results aggregated and pooled as you specified in the Aggregation,Pooling, and Valuation configuration file.

8.2.1 Incidence Results

The Incidence Results report gives you the opportunity to examine the results of each healthimpact function at the grid-cell level, or aggregate them to, say, the state or national level.Simply select the options that you desire from the four main sections of the ConfigurationResults Report window: Column Selection (these include Grid Fields, C-R Function Fields, and Result Fields), Grouping Options, Display Options, and Advanced Options. As youmodify your choices, the Preview section will be updated accordingly.

The Column Selection section allows you to choose the field names (and values) which willappear in the report. The Grid Fields section allows the inclusion of Col and Row fields, whichcan be helpful in identifying the grid-cell of a particular line in the report. These will not always benecessary, however - for example, when results have been aggregated to the national level. The C-R Function Fields section allows the inclusion of various fields which can be helpful inidentifying the health impact function of a particular line in the report. Almost all of the field

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names have appeared previously in the preparation of a Aggregation, Pooling, and ValuationResults file. Finally, the Result Fields section allows the inclusion of various types of results.

In the Grouping Options section, you can change the sorting of the results, by clicking the radiobuttons Group by Gridcell, then by C-R function and Group by C-R function, then byGridcell.

In the Display Options section, you may set the number of digits that appear after the decimalpoint, and you can set the number of rows that appear in the preview window.

In the Advanced Options, you can set the level of aggregation at the grid cell (none), county,state, and national levels. You can also choose to generate Population Weighted Deltas, whichBenMAP calculates at the national level for each health impact function by weighting the changein the pollution metric at each grid cell with the population of the grid cell. For example, if thereare large changes in highly populated urban grid cells and relatively small changes in lightlypopulation rural grid cells, then the population-weighted change would reflect the large urbanchanges and be relatively large.

As noted above, most of these fields have been seen previously; Table 8-2 provides a summaryof the fields that are new to this report format. (See the section on Health Impact Functions dataformat in the Loading Data chapter for a description of the C-R Function Fields).

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Table 8-2. Selected Variables in the Reports Based on the APVR file

Variable Description

Col The column of the grid cell of the result. For grid cell level results, this is the columnof the grid cell. For county and state level results, this is the state FIPS code. For

national results, this is always 1.

Row The row of the grid cell of the result. For grid cell level results, this is the row of thegrid cell. For county results, this is the county FIPS code. For state and national

results, this is always 1.

DataSet Specifies the dataset from which a health impact function was chosen.

Population Population provides the number of persons used in the health impact functioncalculation.

Delta The difference between the baseline and control scenarios for the metric used in thehealth impact function. Calculated by subtracting the metric value in the control

scenario from the metric value in the baseline scenario.

Point Estimate The point estimate for the result from the health impact function. The point estimate isgenerally based on the mean estimate of the "Beta" from the health impact function.

Mean Mean of the points in the Latin Hypercube for this result. The mean is set to missing ifthe Point Mode option is chosen.

Baseline Estimate based on the baseline function, which typically estimates health impacts dueto all causes (not just air pollution-related causes).

Percent of Baseline Estimates the percentage change in health impacts (e.g., hospital admissions) due tothe change in air quality from the baseline to the control scenario. Calculated by

dividing the Point Estimate by the Baseline.

Std Dev Standard deviation calculated based on the points in the Latin Hypercube for thisresult.

Latin HypercubePoints

The number of percentiles depends on the number of points in the Latin Hypercubefor this result.

8.2.2 Aggregated Incidence Results

The Aggregated Incidence Results report presents the incidence results at the aggregationlevel that you have previously specified in the Aggregation, Pooling, and Valuation Configurationfile. If you want to change the level of aggregation, you need to revise your choices in the APVConfiguration Advanced Settings window (see the section on advanced APV options).

The Column Selection section looks largely the same as in the Incidence Results Report.

Reports


The Grouping Options section and Display Options section are exactly the same, as is theAdvanced Options section.

8.2.3 Pooled Incidence Results

The Pooled Incidence Results report provides results aggregated and pooled to the level thatyou previously specified in the Aggregation, Pooling, and Valuation Configuration file. Thisreport has fewer health impact Function Fields than the Aggregated Incidence ResultsReport, and values for others will be blank. This is because after pooling, only enough fields areretained to uniquely identify individual results. In addition, the Advanced Options section(available for Incidence Results and Aggregated Incidence Results reports) no longer exists, asthe options in it do not apply to aggregated incidence results.

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8.2.4 Valuation Results

The Valuation Results report gives you the opportunity to examine the valuation results for thepooled and aggregated incidence results. In the example below, the incidence results wereaggregated to the state level, so in the Column field, you can see the value changing from , so thevalues in the Column field vary (e.g., 1=Alabama, 4=Arizona).

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8.2.4.1 Add Sums Button

To calculate the total value of different groups of effects, click on the Add Sums button in theAPV Configuration Results Report window. In the next window you can specify the effectsyou want to sum and how you want to sum them. In the Include in Total field, simply check theeffects that you want to sum together, and then name the sum in the Valuation Sum Identifierfield. You also need to specify whether you are going to use the Dependent or Independent sumapproach. (See Chapter 7 for a discussion of these two summing approaches.) In theSummation Type use the drop-down menu, choose the approach that you want to use. If youchoose the Independent sum, then you also need to specify the number of Monte Carlo drawsthat you want BenMAP to use. The default is 5,000. You may repeat this procedure togenerate as many totals as you like.

Note that the Add Sums button is only enabled for reports involving monetary valuations, notthose involving incidence estimates. Typically, incidence estimates should not be summed across endpoint groups (for example, Mortality and Hospital Admissions, Respiratory). Within endpointgroups, incidence estimates can be summed - you may do this in Aggregation, Pooling and

Reports


Valuation Configurations. Once results are in monetary values, however, summing acrossendpoint groups can be useful in calculating aggregate benefits.

8.2.5 Aggregated Valuation Results

The Aggregated Valuation Results report presents valuation results aggregated to the levelyou specified at the Advanced button when creating the APV configuration file. Note that theaggregation level specified for the valuation does not need to be same as that for the incidenceaggregation. In the example below, the valuation results are aggregated to the three so-called"report regions," so in the Row field, you can see the value changing from 1 (East), 2 (Westminus California), and 3 (California). (The underlying incidence data in this example wereaggregated to the state level.).

As with the Valuation Results Report, you can use the Add Sums button to create totals withvarious valuation results.

Reports


8.2.6 Pooled Valuation Results

The Pooled Valuation Results report presents valuation results aggregated and pooled to thelevel you specified at the Advanced button when creating the APV configuration file. As withthe Pooled Incidence Results Report, fewer Pooled Valuation Method Fields are available,because only enough fields are retained to uniquely identify individual results. As with the Valuation Results Report, you can use the Add Sums button to create totals with variousvaluation results.

Reports


8.2.7 QALY Results

The QALY Results report gives you the opportunity to examine the QALY results for thepooled and aggregated incidence results. In the example below, the incidence results wereaggregated to the state level, so in the Column field, you can see the value changing from , so thevalues in the Column field vary (e.g., 1=Alabama, 4=Arizona). You can use the Add Sumsbutton to create totals with various QALY results.

Reports


8.2.8 Aggregated QALY Results

The Aggregated QALY Results report presents QALY results aggregated to the level youspecified at the Advanced button when creating the APV configuration file. (Recall that you canaggregate incidence, valuation, and QALY results to different levels.) In the example below, theQALY results are aggregated at the national level, so the values in the Column and Row fieldsare set to 1. As with the Valuation Results Report, you can use the Add Sums button tocreate totals with various QALY results.

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8.2.9 Pooled QALY Results

The Pooled QALY Results report presents QALY results aggregated and pooled to the levelyou specified in the Aggregation, Pooling, and Valuation configuration file. As with the othervaluation reports, you can use the Add Sums button to create totals with various valuationresults.

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8.2.10 Export Incidence, Valuation, & QALY Reports

To export an Incidence, Valuation, & QALY Results report, first choose the GroupingOptions, Display Options, and Advanced Options that you want to see in your report. Thenchoose the variables that you want to see in your report. Finally, choose the Save option fromthe File drop-down menu.

This will bring up a window allowing you to name the file you want to save. Note that by defaultBenMAP will export the file to the Reports folder. Carefully name the file that you are generatingso that you will recognize it in the future!

Reports


8.3 Raw Incidence - from CFGR file

The Raw Incidence Results report gives you the opportunity to examine the results of eachhealth impact function at the grid-cell level, county, state, or national level. It is based on theConfiguration Results file (with the *.cfgr extension), and is otherwise identical to the IncidenceResults Report generated from the Aggregation, Pooling, and Valuation results file (with the *.apvr extension). BenMAP includes both versions to increase the reporting flexibility for users. (See the section on Incidence Results reports for a description of the options available for thisreport type.)

Reports


8.3.1 Export Raw Incidence

To export the Raw Incidence Results report, first choose the Grouping Options, DisplayOptions, and Advanced Options that you want to see in your report. Then choose the variablesthat you want to see in your report. Finally, choose the Save option from the File drop-downmenu.

This will bring up a window allowing you to name the file you want to save. Note that by defaultBenMAP will export the file to the Reports folder. Carefully name the file that you are generatingso that you will recognize it in the future!

Reports


8.4 Audit Trail Reports - from all BenMAP files

The Audit Trail Reports provide a summary of the assumptions underlying the various parts ofthe analysis. You may generate an audit trail with any of the file types used in BenMAP: AirQuality Grids (with the “.aqg” extension), Incidence Configurations (with the “.cfg” extension),Configuration Results (with the “.cfgr” extension), Aggregation, Pooling, and ValuationConfigurations (with the “.apv” extension), and Aggregation, Pooling, and Valuation Results (withthe “.apvr” extension). The report itself has a tree structure that lets you easily find theinformation that you are seeking. Below is an example of an Audit Trail Report for aAggregation, Pooling, and Valuation Results file.

Note that each successive step in an analysis contains a summary of its assumptions, and those ofeach previous step in the analysis. For example, in the below report the assumptions of the Configuration Results file used to generate the APV Results are present in the ConfigurationResults node. Similarly, the assumptions of both the baseline and control air quality grids arepresent under the Configuration Results node.

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8.4.1 Export Audit Trail

Note that you can export Audit Trail as a text file . Each branch in the tree structure will beconverted to a tab in the exported file, allowing for easy viewing in Excel, WordPad, and avariety of other programs. Simply click on the Export button, name the file, and click Save.

Note that by default BenMAP will export the file to the Reports folder. Carefully name the filethat you are generating so that you will recognize it in the future!

Reports


8.5 Questions Regarding Creating Reports

When creating reports from *.cfgr and *.apvr files, why do some of the variables that Ihave checked appear as blanks?

When results are pooled together, some of the identifying information for individual health impactfunctions gets lost. For example, when pooling together endpoints within the same endpointgroup, such as “HA, Pneumonia” and “HA, Chronic Lung Disease” (both within “HospitalAdmissions, Respiratory”), there is no longer a unique endpoint name for the pooled result. So,BenMAP would leave the endpoint name blank.

How do I export my results?

Identify the type of report that you want to create, then refer to the sections in this chapter onexporting reports.

How do I determine what the Column and Row refer to?

The Column and Row are variables designed to uniquely identify each grid cell in the griddefinition. In the case of the County grid definition, the Column refers to the state FIPS code

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and the row refers to the county FIPS code. One way to get a good sense of the Column andRow variables is to create a map (discussed in the next chapter) and then view whetherparticular Column and Row variables occur in the map.

In the report step, why is it that when I click the Done button the report is not saved?

You have to go to File menu and choose Save.

GIS/Mapping


CHAPTER 9

GIS/Mapping

In this chapter...

Learn about BenMAP’s mapping functions.

Map configuration inputs like air quality grids.

Map incidence and valuation results.

Map different variables and modify the map display.

GIS/Mapping


Mapping can be quite useful to check the quality of your work, and, of course, mapping providesa useful platform for presenting your results. BenMAP features powerful, integrated mappingcapabilities which you can access at several points in the model. The main Mapping / GIS tool,available via the Tools drop-down menu in the main window, allows you to map various typesof files and data associated with an analysis, including air quality grid files, monitor data,population data, and valuation results.

In addition, at several points from within the program, you can view data being used in ananalysis. You can view maps when filtering monitor data, creating air quality grids, and whencreating configuration files (with the *.cfg extension). In particular, when creating a configurationfile, you have the option to map your baseline and control air quality grids, as well as to map thedifference between the two (the "delta"), which is used in health impact functions. The "delta" istypically a key input to your calculations, and this is the only way to map it -- mapping of thedelta is not available from the Tools menu.

9.1 Overview of Mapping

You can access the some of the mapping capabilities in BenMAP by going to the Tools drop-down menu, and choosing the GIS/Mapping.

GIS/Mapping


In addition to the Tools menu, BenMAP provides several places where you can map the inputdata that you are using for a particular analysis. Below, we provide examples of both types ofmapping. First, we discuss the display options and taskbar buttons which can be used in bothcases.

9.1.1 Display Options

After choosing the file or data type that you want to map, you must select the variable you wantto map, and how you want it displayed. Double-click on the layer name on the left-hand side ofthe window. A small box will appear with the Display Options for the layer.

GIS/Mapping


This box allows you to set the following options:

Variable. The drop-down menu lists all of the variables contained in the layer you chose. Selectthe variable that you want to view. Note that each layer can only show one variable at a time.

Start Color and End Color. These are the colors that represent the gradations in the selectedvariable. BenMAP uses 10 equal-sized increments for the variable, with a gradual transitionbetween the Start Color and the End Color. To change either color, click on the coloredsquare and select a new color.

Default Color. This is the color is used for values that fall outside of the range of the MinValue and the Max Value.

Min Value and the Max Value. These options define the range of the selected variable and areautomatically set to the minimum and maximum of the variable. However, you may wish to enterother minimum and maximum values, such as in the case where there is one outlier that isdominating the color scale. For example, some urban grid-cells such as those in Los Angeleshave extremely large values. Since BenMAP creates 10 equal-sized increments between theminimum and the maximum, it is not uncommon to have most of the grid values in just a few of theincrements. If you change the minimum and/or maximum values to exclude outliers from the colorscale, the outliers will then appear in the Default color.

Decimal Digits. This specifies the number of digits used in displaying the results. The default istwo decimal points. However, for variables with values much smaller than one, you will want toincrease the number of digits that you display.

Grid Outline. This appears as a fine white line around the border of each grid cell. For somegrid types, this outline can make the map too complicated, and you may want to uncheck thisoption. An alternative is to use the Reference Layer drop-down window (described in theTaskbar Buttons section), which lets you add a blue outline for the nation, states, or counties.

Note that if you have specified point data, such as monitors, the Display Options window

GIS/Mapping


includes the ability to set the size of the points on the map. The Start Size, End Size, andDefault Size have a default value of 75, 150, and 120, respectively, which you can then edit, ifdesired. For example, if you want smaller values to be all the same size, you might set all of thevalues to 100.

9.1.2 Taskbar Buttons

There are a number of standard buttons used in most map viewing programs which you can useto navigate and customize the map view.

Open a file. Use this to open maps for viewing.

Save active layer to file. Creates a shape file for use in other map-viewingprograms. The active layer is the topmost visible layer.

Zoom to full extent. Allows you to view the whole map that you are viewing.

GIS/Mapping


Increase zoom. Allows you to zoom in.

Decrease zoom. Allows you to zoom out.

Select a region for zooming. Allows you to select a region to view.

Drag mode. Allows you to manually move the map by clicking and dragging.

Click to display info for the cell under the mouse. Allows you to displayinformation (all the variable values) for individual cells or points by clicking on them.

Build Query. Allows you to view grid-cells that satisfy certain criteria. Hitting theExecute button will produce a map of the cells that meet the criteria that you havespecified. Below is an example of how you might use this function.

GIS/Mapping


Layer Statistics. Provides information about the active layer. In the Fields sectionsimply choose the variable of interest, and BenMAP will display statistics andsample values for that variable.

The drop-down menu provides alternative projections for displaying the data, with the default setto Albers Equal Area Conic.

9.2 Mapping from the Tools Menu

To access the main mapping capabilities within BenMAP, go to the Tools drop-down menu, andchoose the GIS/Mapping option. A blank window will appear, with buttons at the top for

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managing files and navigating the map. To see the name of each button, simply hold the cursorover it.

Use the Open a file button in the top-left corner to choose the file (or other type of data) thatyou want to view. All of the options are straightforward, though some require a few more stepsthan others. Below we give some step-by-step examples. See Table 9-1 for a brief descriptionof each type.

Table 9-1. Description of Mapping File Types

File Type Description Source File Used

Air Quality Grid Annual summary values (e.g., daily average, dailymaximum, or other metric where available) within each

grid cell.

Air quality grids created byBenMAP (*.aqg)

APVConfiguration

Results

Presents the full range of incidence, valuation, andQALY results. The results are available at the levelof aggregation of the air quality grids. In additionaggregated results are available, as well as both

aggregated and pooled results.

Aggregation, Pooling andValuation Results files (*.apvr)

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File Type Description Source File Used

ConfigurationResults

Presents the incidence estimate, change in airpollution, and population used in the health impact

calculation.

Configuration Results files (*.cfgr)

Modeling Data

Monitors Annual summary values (average, median or othermetric where available) for each monitor.

Select monitors from theBenMAP library or use your

own by loading a file.

Population Total population, and cross-tabulations of age andgender with race/hispanic origin within each grid cell

(for the Year and GridType you specify).

Internal BenMAP populationfiles and projections, based on

Census block-level data.

Each map that you select and load into the GIS viewer will appear on the left-hand side of thewindow as a layer. All of the options to create maps are straightforward, though some require afew more steps than others. Below we give some step-by-step examples of each type.

9.2.1 Air Quality Grids

Air quality grid maps present annual summary values of air pollution metrics (e.g., daily average,daily maximum, or other metric where available) within each grid cell. After choosing the airquality grid that you want to map, double-click on the layer name on the left-hand side of thewindow. A small box will appear with the Display Options for the layer. Choose the metricthat you want to map. When mapping an air quality grid with county-level PM

2.5 values, the

available default metrics are D24HourMean and QuarterlyMean.

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If you keep the default display options, the maps can often look a little complicated or busy. Forexample, when mapping county-level level PM

2.5 levels with the default display options you might

get a map looking like the following:

Unchecking the Grid Outline box, reducing the Decimal Digits from 2 to 0, and using a StateReference Layer can simplify the map, as follows:

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9.2.2 APV Configuration Results

When mapping APV Configuration results, you can generate nine different types of maps: (1)Incidence, (2) Aggregated Incidence, (3) Pooled Incidence, (4) Valuation, (5) AggregatedValuation, (6) Pooled Valuation, and (7) QALY Results, (8) Aggregated QALY Results, and(9) Pooled QALY Results. All of the options use the information contained in the Aggregation,Pooling and Valuation Results files (*.apvr), which you can create using the Aggregation,Pooling, and Valuation button on the main window.

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After you have chosen the results you want to map, a window will appear with identifiers for eachof the variables. On the right-hand side is the GIS Field Name. Mapping programs typicallyhave a default length of 10 characters for variable names, so it is necessary to specify your ownnames or to use the default name given in the GIS Field Name column.

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Note that if you used more than one pooling window (described in Aggregation, Pooling, andValuation chapter), then BenMAP will create one layer for each pooling window. Also, note thatthe "aggregated" results are aggregated to the level specified in the APVR file. If results wereaggregated to the national level, the US map will only show one color.

For each of the three valuation options (Valuation, Aggregated Valuation, and PooledValuation) and for each of the three QALY options (QALY, Aggregated QALY, and PooledQALY), a second window appears that allows you to specify variables that you want to addtogether. (If you have selected Incidence, Pooled Incidence, or Aggregated Incidence,BenMAP will go directly to loading the new layer.)

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Click on the Add Sum button. Then in the far-right column, Include in Total, check thevariables that you want to include in the total. In the lower-left corner, give a name (no longerthan 10 characters) for the total in the Valuation Sum Identifier, and then choose whether touse a Dependent or Independent sum. If you choose the latter, then you also need to choosethe number of Monte Carlo draws. To finish, click OK. You may repeat this step as many timesas desired.

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9.2.3 Configuration Results

The Configuration Results (*.cfgr file) are a subset of the APV Configuration Results (*.apvr file). Specifically, they capture incidence results calculated at each grid cell. In those instances whenyou have not yet generated an APV Configuration Results file, mapping your ConfigurationResults file may be useful, particularly as a quick check that your results seem reasonable.

As in the case with mapping APV Configuration Results, after choosing the file you want to view,you then need to name your variables. The layer will then be displayed, where you can thenchoose particular variables to map by double-clicking on the layer name on the left-hand side ofthe window. (It is not uncommon to have many variables to choose from, so you may need totake some care in developing a variable naming convention that makes sense to you!)

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After choosing the rest of your display options, you can then view your map. Note that it is fairlycommon for maps of Configuration Results to be dominated by a few regions, such as southernCalifornia, with many other parts of the country indistinguishable from each other.

By changing the Max Value, End Color, and Default Color, as follows, you can develop amap that provides more information regarding impacts in other parts of the country, aside fromthose with the largest impacts.

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In this example, the areas with the largest impacts appear in bright red (i.e., southern California,Phoenix, Houston, Chicago, and a handful of other locations). The areas with the next largestimpacts appear in dark green.

You might also use the Create a Query button to focus on your results of interest. Forexample, if wanted to focus on those areas (in this instance counties) with at least one hundreddeaths as calculated with our "Laden" function, then we would first click the Create a Query

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button and build the following query.

Clicking OK will complete the query.

Running the query again on this hypothetical, we might to focus on just those areas with at least200 deaths. The exact type of map that you want generate will of course depend on yourparticular set of results and analytical goals. The point is that mapping capabilities in BenMAPcan provide some interesting, easy-to-use options.

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9.2.4 Modeling Data

You can map any modeling data that you planning to use to create an air quality grid (*.aqg file),as long as you have a grid definition and a pollutant definition that matches your data. Choose Modeling Data from the Open a file drop-down menu on the BenMAP GIS window. Thiswill bring up the Select Model Data to Map window. Click the Browse button to find the fileyou want to map, and then choose the appropriate Grid Type and Pollutant from the drop-down menus.

Click OK, and then you will be ready to map. Double-click on the layer in the left panel, and thiswill bring up the Display Options window, so you can choose the variable you want to map andhow you want it to look. In this example, the Grid Outline has been unchecked and theDecimal Digits has been set to 0.

To add context to the map (because the Grid Outline is unchecked), you will likely want to use aReference Layer from the drop-down list.

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9.2.5 Monitoring Data

You can map monitor locations and concentration levels using the Monitors option. Click the Open a file button and select Monitors from the drop-down menu. The Select Monitorswindow will appear in which you select the Pollutant and then load monitor data for thatpollutant from either an existing library (in which case you choose the Library tab) or from adataset outside of BenMAP (in which case you would use either the Database Columns,Database Rows, or Text File tabs, depending on the file format). The same monitor data canbe used many times, so it is generally a good idea to create a library -- see the Loading Datachapter for how to do this.

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If you map data from the BenMAP library, you need to specify the Monitor DataSet and theMonitor Library Year. In addition, you can change the default monitor filter options.Generally speaking, this is not necessary. However, if desired, click the Advanced button. Thiswill bring up Filter Monitors window, where you can make whatever adjustments are deemednecessary to the default options. (Note that the filtering is hardcoded into BenMAP, so whateverfilter options you choose will not persist to any future mapping or use of monitor data.)

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Click Go! after you have made your selections. This will bring you back to the Select Monitorswindow. Click OK again, and BenMAP will generate a monitor layer that you can view.

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In this map, each red square is a monitor location. To see the monitor values displayed withcolors varying by the level of the monitor, double-click on the layer on the left side of the map,and follow the steps outlined above for setting the display options. Values shown using the

Monitors mapping option are annual average values (µg/m3 for PM and ppb for ozone).

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9.2.6 Population Data

You can map the population data that you have already loaded into BenMAP. Choose Population from the Open a file drop-down menu on the BenMAP GIS window. This willbring up the Select Population Data window. Choose the Population DataSet that you wantto map and the particular year from the Population Year from the drop-down menus.

Click OK, and then you will be ready to map. Double-click on the layer in the left panel, and thiswill bring up the Display Options window, so you can choose the variable you want to map andhow you want it to look. In the example below, the Grid Outline has been unchecked and theDecimal Digits has been set to 0.

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To add context to the map (because the Grid Outline is unchecked), you will likely want to use aReference Layer from the drop-down list.

9.2.7 Mapping Multiple Layers of Data

It is possible to map multiple layers simultaneously. The layer that you have opened mostrecently appears on the top of the list, and in the map its values lie on top of the other layers. By

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right-clicking on any given layer, you can move its position within the list (select Move Up orMove Down). For example in the following screenshot, we move the Control Grid layer to thetop by right-clicking on the Control Grid layer and choose Move Up (or you can right-click onthe Delta layer and choose Move Down).

By checking the box to the left of the layer name, you can turn a layer’s visibility off and on. Forinstance, if you want to see the second layer in the list, simply un-check the box next to the firstlayer in the list. The second layer will then be on top and be visible, as in the example below.

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9.3 Viewing Maps in a BenMAP Analysis

In addition to the Tools menu, BenMAP provides several places where you can map the inputdata that you are using for a particular analysis. We provide examples of these mapping optionsbelow.

Air Quality Deltas. When creating your Configuration (*.cfg file), you can map the baselineminus the control scenario to get a sense of where the major impacts are occurring in youranalysis.

Air Quality Grids. When creating an air quality grid (*.aqg file), you can map what the airquality grid will look like. And in the case of air quality grids based on monitor data, you canmap the monitors as well.

Air Quality Monitors from the Advanced Monitor Filter. When filtering monitors, you canmap the monitors to see the impact of the filtering.

Monitor Rollback Inputs & Outputs. When creating a monitor rollback air quality grid (*.aqgfile), you can map both the baseline and control air quality grids and the monitor data used.

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9.3.1 Mapping Air Quality Deltas

When developing a Configuration file (with the *.cfg extension), you can map the baseline andcontrol air quality grids, as well as the difference between the two. In the Configuration Settingswindow, after choosing the grids that you want to use, click on the Map Grids button.

This will generate layers with the delta (baseline minus control), baseline, and control values foreach grid cell. You can then double-click on the layers in the left panel to set your displaysettings.

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9.3.2 Mapping Monitor Direct Air Quality Grids

When generating air quality grids there is an option to map the grid and the data used to create it.For example, when generating a Monitor Direct grid, click on the Map button on the MonitorDirect Settings page.

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BenMAP will then generate the grid, generate a map with both the monitors and the monitor datainterpolated to the grid cells. You can then use the display options to generate the map youdesire.

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9.3.3 Mapping Air Quality Monitors from the Advanced Monitor Filter

You can access mapping through the advanced monitor filter when generating air quality grids. Click on the Create Air Quality Grids button and choose either Monitor Direct, Monitor andModel Relative, or Monitor Rollback. On the Settings page, click on the Advanced button,which brings up the Advanced Options page.

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Then click on the Custom Monitor Filtering button, which will bring up the Filter Monitorswindow.

Choose your filtering options and click Go! Then click the Map button. An initial map appears

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with each monitor location identified by a red square. To immediately provide some context, youmay want to choose, say, the States reference layer.

Double-click on the layer to the left of the map. Choose the display options that you would like,and then click OK.

A map with your display options will then appear. You may then use the various mappingoptions available, such as zooming in to an area of interest, getting information on particularmonitors, querying the map to display monitors with certain characteristics, and saving the map asa shapefile and viewing it in another map viewer.

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9.3.4 Mapping Monitor Rollback Inputs & Outputs

When using the Monitor Rollback option, you can generate two types of maps. First, you canmap the inputs to the rollback – the monitor data and any spatial adjustment file that you mayhave used. Second, you can map the inputs and at the same time map the grid based on theseinputs. Start to create a monitor rollback grid, and when you get to the Monitor RollbackSettings: (3) Additional Grid Settings, make your selections for the Select Interpolation Method,Select Scaling Method, Grid Type, and whether you want to Make Baseline Grid (in additionto Cotnrol Grid).

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In this example, BenMAP will produce a map with both the inputs, as well as the baseline andcontrol grids. (The baseline grid gets created because we checked the box for Make BaselineGrid (in addition to Control Grid). Click on the Map button. This will bring up the BenMAPGIS window.

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As before, you may use the various display options to generate the map that you desire. Recallthat the topmost layer lies on top of the other mapped layers. To change the ordering of thelayers, simply right-click on the layer that you want to move (up or down).

9.4 Questions Regarding Mapping

Why is the Open a File menu button disabled?

This happened because you did not use the Tools button and choose Mapping / GIS. Whenviewing maps while generating air quality grids, filtering monitor data, and other activities withinBenMAP you do not have access to other types of maps. This is to avoid too many competingactivities.

All of the mapped values have the same color. How do I avoid this?

This can happen when the values are extremely small and you have not specified a sufficientnumber of decimal points. Go to the Display Options window, and change the Decimal Points. This can also happen when one of the grid cells is an outlier, with either a very low or verysmall value. You can go to the Display Options window, and change either the Min Value orthe Max Value. Finally, this can happen if you have mapped national data. In this instance, youshould expect all areas to have the same color, since there is only a single national number fordisplay, such as when mapping national results, or mapping incidence rates that do not vary byregion (e.g., MRAD incidence rate).

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Can I map air quality for individual days?

No. BenMAP only maps annual averages. In the case of hourly metrics, such as the one-hourdaily maximum for ozone, BenMAP will map the average of the metric for the available days.

Can I print maps in BenMAP?

No. BenMAP does not currently allow printing directly from the program. However, you canexport shapefiles, and then read these shapefiles into a program that does support printing, suchas ArcView.

Why is my map all grey or all black?

You may need to select a variable or uncheck the grid outlines checkbox. You can do this bydouble-clicking on the layer name.

How do I clear a query?

When using a query, you limit the areas that get displayed. That is, after using a query, someareas will be white and other areas will have colors that you have specified. If you want to beable to display all areas simply run a query that includes all areas. For example, if you run aquery such as choose all areas with population greater than or equal to zero, then you will get acomplete set of results.

What are the units?

The units that get displayed depend on the particular map that you are creating. For example, ifyou are mapping PM

2.5 levels, then the units will be in micrograms per meter cubed. If you are

mapping ozone, the units will be in parts per billion. If you are mapping mortality or some othertype of health effect, then the units will be numbers of cases. If you are mapping valuationresults, then the results will be in dollars.

How do I change which layer is on top?

When mapping multiple layers, the top-most layer is the active layer. To change the position of alayer, simply right-click on it, and you can move it up or down. This is discussed in the section Mapping Multiple Layers of Data.

Tools Menu


CHAPTER 10

Tools Menu

In this chapter...

Learn about the options in the Tools menu.

Tools Menu


The Tools menu, available on the main BenMAP screen, provides access to a number ofspecialized applications. We list them below and give a brief description. Note that othersections of the manual have already covered several of them, such as GIS/Mapping, so wemerely list them here and point you to the appropriate section.

Air Quality Grid Aggregator. You can change an air quality grid based on one grid definitionto another grid definition, using a simple spatially-weighted average approach. This option isdescribed below.

Model File Concatenator. This is a highly specialized option that allows you to combine airquality modeling data text files and produce a smaller, more efficient, binary file. This option isdescribed below.

Tools Menu


Database Export. Export entire databases (all Setups), individual Setups, and parts of individualSetups (e.g. all GridDefinitions, or individual health impact Function DataSets). This functionalitycan be used to share your data with other users, as well as to allow you to move databasesbetween computers. This is described in the Export Setups section of the Loading Data chapter.

Database Import. Import entire Setups or parts of individual Setups. This option is describedin the Import Setups section of the Loading Data chapter.

Export Air Quality Grid. Generate a data file with all of the data in an air quality grid. Thisoption is described below.

GIS/Mapping. Map various types of files and data associated with an analysis, including airquality grid files, monitor data, population data, and valuation results. See the GIS/Mappingchapter for details.

Modify Setup. BenMAP encapsulates in a single dataset, called a "Setup," all of the dataneeded to run analyses for a particular geographic area. Using the Modify Setup option, you addto, modify, and delete setups. See the Loading Data chapter for details.

Neighbor File Creator. Identify the monitors and weights used in the interpolation processwhen creating air quality grids. This option is described below.

One-Step Setup. Allows you to set the CFG and APV files, as well as currency year, for theOne-Step analysis. This option is described below.

10.1 Air Quality Grid Aggregator

Using the Air Quality Grid Aggregator you can change an air quality grid based on one griddefinition to another grid definition, using a simple spatially-weighted average approach.

To start, choose Air Quality Grid Aggregator from the Tools drop-down menu. This will bringup the Air Quality Grid Aggregator window. Click the Browse button to find the air qualitygrid that you want to change and then use the drop-down menu in the Aggregation Grid panel toidentify the new grid definition that you want to use. (For example, you might want to aggregate acounty-level air quality gird to state-level.) Click OK when done.

This will bring up the Save Aggregated Air Quality Grid window, where you specify the name of

Tools Menu


the file you are creating and its location. After the file is created, BenMAP will take you back tothe main BenMAP screen. You can then use the new file just as you would any other air qualitygrid.

Below is an example of going from a county-level PM2.5

air quality grid to a state-level PM2.5

air

quality grid. The county-level file looks as follows:

The state-level file looks as follows:

Tools Menu


The scale in the left panel is set to the same values, so you can compare the two maps moreeasily. One key thing to note is that there is more variation in the county-level file. For example,in California the county-level file has colors ranging from yellow to dark red, while in the state-level file, California is a solid orange color. This pattern is expected, because BenMAP is justtaking a simple spatially-weighted average of the data.

10.2 Model File Concatenator

The Model File Concatenator is a specialized tool that allows you to combine air qualitymodeling data text files and produce a smaller, more efficient, binary file. For example, ozonemodeling files often are generated one day at a time and split between eastern and westernmodeling domains, so the input modeling files to BenMAP might consist of dozens of files. The Model File Concatenator combines these files into a single file that can then be easily used inBenMAP.

You can use this tool if you have data for both a western and eastern domain. In case you wantto use this tool for a single modeling domain, then just fill in the options for the western domain,and ignore the eastern domain.

To start, choose Model File Concatenator from the Tools drop-down menu, the Model FileConcatenator window will appear. There are a number of options that need to be specified.We describe each below.

Tools Menu


The Input Files options are Row/Column and Column/Row. The choice depends on how thedata files are formatted. Below is an example of what a typical datafile looks like. In thisexample, the first column specifies the Row and the second column specified the Column. (Inother cases, this might be reversed.)

Tools Menu


The Column Delimiter options are White Space and Comma. In the example above, WhiteSpace is the correct choice.

The BenMAP health impact functions for ozone generally assume that the data is in parts perbillion (ppb). If your model data happens to be in parts per million (ppm) then check the box Convert model values from parts per million to parts per billion.

Click on the Select Western Domain Files button and choose the files that you want to load.Note that each file represents a different day of modeling, and there can be any number of days. After selecting the files for the western domain, then specify the number of Columns and Rowsin each file by filling in the Lower Bound and Upper Bound boxes. For example, if the file has122 columns and 188 rows in the western domain, and 213 columns and 192 rows in the easterndomain, then boxes would be filled out as follows:

Tools Menu


In this example, BenMAP will renumber the eastern domain so that it follows the numbering in thewestern domain. There will be 335 columns and 380 rows numbered consecutively.

When you have completed filling in the options, then click the Go! button. BenMAP will beginprocessing the files. When the processing is complete, the Specify an Output File window willappear. Provide a name for the file in the File Name box. Note that BenMAP automaticallyuses a *.model extension for this type of file.

Tools Menu


After the file is saved, BenMAP brings you back to the Model File Concatenator window. Youcan reuse the tool by choosing a new set of western and eastern domain model files and makingthe other appropriate selections. When you are done using this tool, you can just click the Donebutton.

10.3 Export Air Quality Grid

The Export Air Quality Grid tool generates a data file (*.csv) with all of the data in an airquality grid. After choosing Export Air Quality Grid from the Tools drop-down menu, theExport Air Quality Grid window will appear. Click the Browse button to choose the airquality grid that you want to examine.

Tools Menu


Click OK after you have selected your file. This will bring up the Reports window. Use theSave in drop-down menu to choose the director where you want to save your file. And in theFile name box, type in the name of the file.

To help keep track of what you are doing, you might want to name the file the same thing as yourair quality grid, or something very similar. (If you name it the same as your air quality grid, youcan always distinguish the two files with the extension. An air quality grid has a *.aqg extensionand the file you are generating here has a *.csv extension.)

When done click the Save button. You can view the files you have created with any databaseviewer. For each Metric and Seasonal Metric, you can see the actual values. In addition, youcan see the Statistics calculated for each. In the example below for a county-level PM

2.5 air

Tools Menu


quality grid, you can see in the first county (Column = 1, Row = 1) that the Mean of theD24HourMean metric is 17.24, with a Median of 15.1, a Maximum of 52.1, a Minimum of0.4, and finally the Sum of the D24HourMean values is 6292.

Note that the files may well be quite large, with more lines than can be completely read by aprogram like Excel, which can read only the first 65,000, or so, lines of data. With large files,you might want to use a database program like SAS. Alternatively, these files can also be readby simple text editors, which do not have the 65,000 line limitation of Excel.

10.4 Neighbor File Creator

The Neighbor File Creator tool generates a file that specifies the monitors used to estimate airquality in each grid cell of a Monitor Direct, Monitor and Model Relative, or Monitor Rollbackair quality grid.

To start, choose Neighbor File Creator from the Tools drop-down menu. This will bring up

Tools Menu


the Create Neighbor File window. Click on the Browse button, and find the air quality you wantto analyze.

After finding the file, click the OK button. BenMAP will then ask you to provide a name for thefile you want to create. BenMAP will then save the file as a text file that can be easily viewed in avariety of programs, including WordPad. An example is as follows:

The first two columns specify the Column and Row variables for each grid cell. In the exampleabove, you will see that Column = 110 and Row = 60 are repeated seven times, indicating thatseven different monitors were used to estimate air quality at this grid cell. The third column givesthe monitor identifier. The fourth column the weight used in the air quality calculation (e.g., Voronoi Neighbor Averaging). And the fifth column gives the distance (in kilometers) from themonitor to the center of the grid cell.

Note that if an air quality grid was created using the Closest Monitor option, then only a singlemonitor is used for any given grid cell. As a result the resulting neighbor file only has three

Tools Menu


columns, the Column and Row identifier and the monitor used.

10.5 One-Step Setup

The One-Step Setup tool lets you specify the CFG and APV files (and currency year) for theOne-Step Analysis.

To start, choose One-Step Setup from the Tools drop-down menu. This brings up the One-Step Setup Parameters window. From the Pollutant drop-down menu, choose one of thepollutants that you have already specified. The U.S. setup that comes with BenMAP already hasdefaults for PM

2.5 and Ozone. If desired, you can change the defaults.

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Ben Map Manual Oct 2012

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