Emissions Modeling Platform Collaborative: 2016 Version 1 Biogenic Sources 1 October 15, 2019 SPECIFICATION SHEET: BEIS Biogenics 2016 Version 1 Platform Description: Biogenic emissions estimated from the Biogenic Emission Inventory System version 3.61 (BEIS3.61) model for simulating 2016 and future year U.S. air quality. 1. Executive Summary 1 2. Introduction 2 3. Inventory Development Methods 2 4. Ancillary Data 4 Gridded land use 4 Environment Canada BELD4 landuse 5 Meteorology (including BIOSEASON) 7 Chemical Speciation 9 Spatial allocation (for generating reports) 9 5. Emissions Projection Methods 9 6. Emissions Processing Requirements 9 7. Emissions Summaries 10 1. EXECUTIVE SUMMARY Biogenic emissions are generated with the Biogenic Emissions Inventory System (BEIS) model, which is internal to the Sparse Matrix Operating Kernel Emissions (SMOKE) modeling system version 4.7. SMOKE creates emissions in a format that can be input into air quality models. BEIS uses gridded hourly meteorology, gridded land use, emission factors, and a speciation profile to generate hourly biogenic emissions for use in air quality modeling. National and state-level emission summaries for key pollutants are provided.
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Emissions Modeling Platform Collaborative: 2016 Version 1 Biogenic Sources
1
October 15, 2019
SPECIFICATION SHEET: BEIS Biogenics 2016 Version 1 Platform
Description: Biogenic emissions estimated from the Biogenic Emission Inventory System version 3.61 (BEIS3.61) model for simulating 2016 and future year U.S. air quality.
1. Executive Summary 1
2. Introduction 2
3. Inventory Development Methods 2
4. Ancillary Data 4
Gridded land use 4
Environment Canada BELD4 landuse 5
Meteorology (including BIOSEASON) 7
Chemical Speciation 9
Spatial allocation (for generating reports) 9
5. Emissions Projection Methods 9
6. Emissions Processing Requirements 9
7. Emissions Summaries 10
1. EXECUTIVE SUMMARY
Biogenic emissions are generated with the Biogenic Emissions Inventory System (BEIS) model,
which is internal to the Sparse Matrix Operating Kernel Emissions (SMOKE) modeling system
version 4.7. SMOKE creates emissions in a format that can be input into air quality models. BEIS
uses gridded hourly meteorology, gridded land use, emission factors, and a speciation profile to
generate hourly biogenic emissions for use in air quality modeling. National and state-level
emission summaries for key pollutants are provided.
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2. INTRODUCTION
This document details the approach and data sources to be used for developing 2016 biogenic
emissions using the BEIS model.
Biogenic emissions can be computed either within CMAQ itself (inline option) or using the
Biogenic Emission Inventory System version 3.61 (BEIS3.61) within SMOKE. The BEIS3.61
creates gridded, hourly, model-species emissions from vegetation and soils. It estimates CO,
VOC (most notably isoprene, terpene, and sesquiterpene), and NO emissions for the contiguous
U.S. and for portions of Mexico and Canada. Even when using the CMAQ inline option, it is still
necessary to run the SMOKE program Normbeis, as described in Section 6 of this document.
3. INVENTORY DEVELOPMENT METHODS
Biogenic emissions for the entire year 2016 were developed using the Biogenic Emission
Inventory System version 3.61 (BEIS3.61) within SMOKE. The landuse input into BEIS3.61 is the
Biogenic Emissions Landuse Dataset (BELD) version 4.1 which is based on an updated version of
the USDA-USFS Forest Inventory and Analysis (FIA) vegetation speciation-based data from 2001
to 2014 from the FIA version 5.1.
BEIS3.61 has some important updates from BEIS 3.14. These include the incorporation of
Version 4.1 of the Biogenic Emissions Landuse Database (BELD4), and the incorporation of a
canopy model to estimate leaf-level temperatures (Pouliot and Bash, 2015). BEIS3.61 includes
a two-layer canopy model. Layer structure varies with light intensity and solar zenith angle.
Both layers of the canopy model include estimates of sunlit and shaded leaf area based on solar
zenith angle and light intensity, direct and diffuse solar radiation, and leaf temperature (Bash et
al., 2015). The new algorithm requires additional meteorological variables over previous
versions of BEIS. The variables output from the Meteorology-Chemistry Interface Processor
(MCIP) that are used for BEIS3.61 processing are shown in Table 1. The 2016 version 1 of the
BEIS3 modeling for year 2016 included processing for both a 36km (36US3) and 12km domain
(12US1) (see Figure 1). The 12US2 modeling domain can also be supported by taking a subset
or window of the 12US1 BEIS3 emissions dataset.
Emissions Modeling Platform Collaborative: 2016 Version 1 Biogenic Sources
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Figure 1. Various EPA modeling domains including 36US3 (36km) and 12US2 (12km).
SMOKE-BEIS3 modeling system consists of two programs named: 1) Normbeis3 and 2)
Tmpbeis3. Normbeis3 uses emissions factors and BELD4 landuse to compute gridded
normalized emissions for chosen model domain (see Figure 2). The emissions factor file
specific leaf weight, and normalized emission fluxes for 35 different species/compounds. The
BELD4 file is the gridded landuse for 276 different landuse types. The output gridded domain
is the same as the input domain for the land use data. Output emission fluxes (B3GRD) are
normalized to 30 °C, and isoprene and methyl-butenol fluxes are also normalized to a
photosynthetic active radiation (PAR) of 1000 µmol/m2s.
Figure 2. Normbeis3 data flows
The normalized emissions output from Normbeis3 (B3GRD) are input into Tmpbeis3 along with
the MCIP meteorological data, chemical speciation profile to use for desired chemical
mechanism, and BIOSEASON file used to indicate how each day in year 2016 should be treated,
Emissions Modeling Platform Collaborative: 2016 Version 1 Biogenic Sources
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either as summer or winter. Figure 3 illustrates the data flows for the Tmpbeis3 program. The
output from Tmpbeis includes gridded, speciated, hourly emissions both in moles/second
(B3GTS_L) and tons/hour (B3GTS_S).
Figure 3. Tmpbeis3 data flow diagram.
Biogenic emissions do not use an emissions inventory and do not have SCCs. The gridded land
use data, gridded meteorology, an emissions factor file, and a speciation profile are further
described in the next section.
4. ANCILLARY DATA
Gridded land use
The BELD version 4.1 land use is based on an updated version of the USDA-USFS Forest
Inventory and Analysis (FIA) vegetation speciation based data from 2001 to 2014 from the FIA
version 5.1. Canopy coverage is based on the Landsat satellite National Land Cover Database
(NLCD) product from 2011. The FIA includes approximately 250,000 representative plots of
species fraction data that are within approximately 75 km of one another in areas identified as
forest by the NLCD canopy coverage. The 2011 NLCD provides land cover information with a
native data grid spacing of 30 meters. For land areas outside the conterminous United States,
500 meter grid spacing land cover data from the Moderate Resolution Imaging
Spectroradiometer (MODIS) is used. This area outside of the United States where MODIS is
used includes most of Canada and all of Mexico as shown in Figure 1. BELDv4.1 also
incorporates the following:
• 30 meter NASA's Shuttle Radar Topography Mission (SRTM) elevation data (http://www2.jpl.nasa.gov/srtm/) to more accurately define the elevation ranges of the vegetation species than in previous versions; and
• 2011 30 meter USDA Cropland Data Layer (CDL) data (https://www.nass.usda.gov/Research_and_Science/Cropland/Release/).