This Is My Presentation - Nc State University€¦ · Low-Carb Land Presentation Outline • Background • Overview: motivation and tool purpose • Tool description • Tool menu

Low-Carb Land:Informing Your Land Use Decisions to Consider Travel and CO2 Impacts

620000-4081

Song Bai, Douglas Eisinger, Jason Amador, Lyle Chinkin (STI)Joyce Phillips, Washington State Department of Commerce

Thera Black, Thurston Regional Planning CouncilMia Waters, Washington State Department of Transportation

Presented toSouthern Transportation and Air Quality Summit

Raleigh, North Carolina, July 20, 2011

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Low-Carb Land Presentation Outline

• Background• Overview: motivation and tool purpose• Tool description• Tool menu overview (Beta v4.0)• Case studies (hypothetical)

– Thurston County, Washington– Marin County, California

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Background

• Representative greenhouse gas (GHG) reduction goals– By 2050, reduce to 50-80% below 1990 levels

NRC, 2010: America’s Climate Choices

• Vehicle controls: fuel economy, fuel type, activity– By 2050, smart growth could reduce CO2 < 1% up to 11%

NRC, 2009: Driving and the Built Environment

• Smaller agency needs– “…to analyze smart growth strategies… training is

needed… [for] local jurisdictions and smaller MPOs.”Caltrans, 2007: Assessment of Local Models and Tools for Analyzing Smart-Growth Strategies

Overview: Motivation

Land Use• Density• Diversity• Destination• Distance• Design

Travel• Vehicle miles traveled (VMT)• Vehicle trips started (VT)

GHG• CO2 emissions

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• Helps small- to medium-sized regions– Reduce analysis barriers for agencies with few resources

• Informs decision making processes– Provide easily used tool for policy or public settings

Examine interactions among land use patterns,travel activities, and CO2 emissions.

Growth• Population• Jobs

Overview: Tool Purpose

• Lets users test growth planning scenarios– Future growth and spatial allocation of population/jobs

• Compares CO2 impacts– High-level directional insights for CO2 emissions changes

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Sample CO2 emissions results from Low-Carb Land (tonnes/day).

Tool Description: Overview

Web-based graphical user interface• Interactive maps and spatial analysis functions• Data query and management functions

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Data Modeling Scenarios “D” Variables CO2

Tool Description: Data

• Pre-loaded census tract-level data– Most U.S. areas (45 of 50 states)– Households, jobs, travel activities (2002-2006)– Sources

• U.S. Census Bureau• U.S. Bureau of Transportation Statistics• Oak Ridge National Laboratory

– Managed in SQL Server database

• Interactive GIS maps– State, county, census tract– Managed in open source platform with

OpenLayers and MapServer

Data

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Tool Description: Scenarios

Modeling Scenarios• Baseline

– Sub-regions and area types– Aggregation of pre-loaded

census tract-level data

• Alternatives– Future growth patterns– Land use strategies and options

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Tool Description: “D” Variables

“D” Variables • Definitions and metrics– Density: degree of compactness– Diversity: degree of multiple land uses– Destination: level of regional accessibility– Distance: level of transit service– Design: street network characteristics

• Elasticities– From EPA’s literature review – Quantified impacts on travel activities

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Tool Description: Emissions

CO2

• Emission factors– Derived from EPA’s MOVES model– Running and start exhaust for on-road traffic– Vary by area type and speed range

• Total emissions– Aggregated for sub-regions– Summarized results by scenario

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Tool Menu OverviewHome

Log in Tool background

About

DefinitionsCreate and review projects

Define sub-regions by area type

Create scenario for a base year

Create future growth scenarios

Comparison Summary

Outputs: travel activity and CO2 emissions

My Scenarios

Select Region

Base Case

Alternatives

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Thurston County (WA) Case Study

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Fast population growth: ~ 2% per year

255,000 in 2010 → 373,000 in 2030

Source: Thurston Regional Planning Council

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Embedded data: D variable elasticities

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Embedded data: trips, VMT, speeds

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Embedded data: emission factors

Output: base case emissions

Thurston County Hypothetical Scenarios

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Scenario Year Land Use Pattern

Base Case 2005 Existing baseline

BAU 2030 “Business as usual”

Compact 2030 Compact, urbanized growth

Sprawl 2030 Sprawl growth in suburbs

Illustrations assume 50% growth in population and jobs over 25 years.

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Output: emissions by scenario

Thurston County Results

• Future scenarios (2030) vs. base case (2005)– 50% pop./job growth about 35–42% CO2 increase

• Compact vs. BAU or Sprawl– shift to urban about 4–5% CO2 reduction

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Marin County (CA) Case Study

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Slow population growth: ~ 0.5% per year

251,000 in 2010 281,000 in 2030

Source: County of Marin, http://www.co.marin.ca.us

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User-created scenarios

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Output: emissions by scenario

Marin County Results

• Future scenarios (2030) vs. base case (2005)– ~14% CO2 increase

• Shift to urban vs. shift to suburban– ~1% CO2 reduction

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Summary

• Assists policy-level land use analyses – Screening resource; high-level directional insights

• Helps small- to mid-sized agencies– Easy to use; requires minimal inputs– Complements models requiring more expertise, funds– Could be used in public settings to facilitate dialogue

• Enables quick sensitivity testing– Scenarios take a few hours to develop and run

Future improvements– Map functions, data updates, further validation work

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AcknowledgmentsThe tool development team wishes to thank the following individuals for their support:

Jason Beloso, WSDOTMike Claggett, FHWA Jeff Houk, FHWA Karin Landsberg, WSDOTSteve Ludewig, STIBharath Paladugu, TRPC Steve Reid, STIJohn Thomas, EPASupin Yoder, FHWA

Points of Contact: 707-665-9900

Song Bai or Doug [email protected] [email protected]

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Question and Answer Discussion

Sample Forecasted CO2 Reductions

Source: NRC, 2009: “Driving and the Built Environment,” Report in Brief.

U.S. National Research Council: 1-11% by 2050(land use packaged with TCMs)

“… the reduction in vehicle miles traveled (VMT), energy use, and CO2 emissions resulting from more compact, mixed-use development would be in the range of less than 1 percent to 11 percent by 2050…”

Sample Forecasted CO2e Reductions

Source: EPA-ICF, 2011: “Potential Changes in Emissions Due to Improvements in Travel Efficiency,” Final Report.

U.S. EPA: 3% by 2030, 9% by 2050(land use packaged with TCMs)