Excerpt from: http://vista.cira.colostate.edu/TSS/Results/Emissions.aspx

Emissions Methods: Area Source Emissions

Stationary Area Source Emissions

The stationary area source emission category includes those sources that are treated as being 

spread over a spatial extent (usually a county or air district) and that are not movable (as 

compared to off-road mobile and on-road mobile sources). Because it is not possible to collect 

the emissions at each point of emission, they are estimated over larger regions. Examples of 

stationary area sources are residential heating and architectural coatings. Numerous sources, such 

as dry cleaning facilities and oil and gas production facilities, may be treated either as stationary 

area sources or as point sources, or a combination of both. 

Stationary area source emissions data for SMOKE modeling consist of IDA-formatted inventory 

files and ancillary data for allocating the inventories in space, time, and to the Carbon Bond-IV 

chemistry mechanism used in CMAQ and CAMx. The development of the area source emission 

inventory is described in this section. 

Source Categories

In addition to the typical area source emission categories, the WRAP RMC included the 

following emission source categories in the development of the inventories for this sector:

 Stationary area sources

 Agricultural and natural ammonia emission sources

 Oil and gas production operations

 Biogenic emissions

The development of each of these sectors is described below. The discussion focuses on the 

development of the 2002 Base inventory; emissions modeling for the 2002 Planning inventory 

and the 2018 base year inventory use the same processing approach. Variations to the modeling 

approach and specific revisions and enhancements incorporated into the final modeling versions 

of the inventories have been described previously (refer to the Emission Overview 

Documentation). Specific revisions are noted with respect to data sources and source categories 

for the Plan02 and Base18 emissions inventories. 

Data sources

The data sources used in the development of the area sources emissions inventory for the WRAP 

modeling efforts are documented below.

Stationary Area Sources
The Base02 stationary area source inventories used actual 2002 data developed by the RPOs for 

the U.S., version 2 of the year 2000 Canadian inventory, and the BRAVO 1999 Mexican 

inventory. The WRAP stationary area inventory consists of annual county-level and tribal data 

provided by ERG, Inc. (2005), however, due to the small contribution of the WRAP tribal 

inventories to the total domain emissions and the lack of readily available spatial allocation data 

for these parts of the domain, the WRAP tribal data was not incorporated into the final modeling 

inventories. The CENRAP (E.H. Pechan et al., 2005) and VISTAS Phase II (Stella, 2005) 

stationary area inventories also consisted of an annual data set and were provided by these RPOs. 

The MANE-VU and MRPO 2002 stationary area inventories were obtained from the MANE-VU 

and LADCO websites, respectively. 

For Mexico, the same BRAVO 1999 inventory that was used in the preliminary 2002 modeling 

(Tonnesen et al., 2005), was used in the development of the Base02 inventories. Entirely new 

inventories for the six northern states of Mexico for stationary area, as well as stationary point, 

on-road mobile, and off-road mobile sources, were incorporated into the 2002 Planning 

inventories. These data were provided by ERG, Inc., who completed an updated 1999 emissions 

inventory for northern Mexico (Fields et al., 2006) and delivered these data in early 2006 For 

Canada, the Canadian 2000 inventory version 2, obtained from the U.S. EPA EFIG (U.S. EPA, 

2005) was used. 

The 2018 area source emission inventories for WRAP, MANE-VU, and VISTAS were

developed from county-level input data processed outside SMOKE. For the MRPO and 

CENRAP regions, 2018 projection factors (growth and control) were applied to the Plan02 

inventories; Mexico and Canada data were held constant at 2002 levels.

Agricultural and Natural Ammonia Emissions

Ammonia emissions from agricultural sources (livestock operations and fertilizer application)

and natural sources (soil ammonia emissions), were derived from 2002 data and used in the 

WRAP RMC GIS-based NH3 emissions model. The development of emission inventories from 

this source sector, and specific data sources used, is described in more detail below and also in 

Mansell (2005) 

CENRAP and MRPO provided monthly IDA-formatted inventories produced from process-based 

models of their own, along with temporal profiles and spatial cross-reference information for 

these sources. The rest of the U.S., Canada, and Mexico had agricultural NH3 emissions 

contained within their annual stationary area source inventories

The 2018 ammonia source emission inventories for WRAP, MANE-VU, and VISTAS were held 

constant at 2002 levels. For the MRPO and CENRAP regions, 2018 projection factors (growth 

and control) applied to the Plan02 inventories. Mexican and Canadian data were held constant at 

2002 levels.

Oil and Gas Production Operations
The 2002 Base year emission inventory included a number of emissions sectors that WRAP had 

never modeled before, including oil and gas production operations. Emissions from oil and gas 

production operations have been sporadically reported by some states in their stationary area 

source inventories, but for the most part were missing from the modeling inventories. In the 

Base02 inventories, oil and gas production emissions were represented explicitly as both area and 

point sources in a handful of states across the WRAP region.

The oil and gas production emissions inventories for the WRAP states and for tribal lands in the 

WRAP region were provided as stationary area source and stationary point source IDA-formatted 

inventories. ERG, Inc. provided the point-source inventories with the rest of the stationary-point 

data (ERG, 2005a). ENVIRON provided the area source oil and gas inventories for non-CA 

WRAP states and for tribal lands in the WRAP region, along with spatial surrogates for 

allocating these data to the model grid (Russell and Pollack, 2005). For California, oil and gas 

inventories were extracted from the stationary area source data used in the preliminary 2002 

modeling. Oil and gas production emissions data for outside of the WRAP region, if they exist, 

are contained in the stationary area inventories received from the other RPOs. 

For 2018, ENVIRON and ERG provided projected inventory data for oil and gas operations for 

the WRAP states. Projection factors were used for all other RPOs. 

Biogenic Emissions 

For Base02 biogenic emissions inventories, the BELD3 land use data and biogenic emissions 

factors collected during the WRAP preliminary 2002 modeling (Tonnesen et al., 2005) were 

used. These data included BELD3 1-km resolution land use estimates and version 0.98 of the 

BELD emissions factors. The Base02 biogenic emissions modeling differed from the preliminary 

2002 modeling in the use of improved 2002 meteorology data we developed in 2005 (KemballCook et al., 2005). Biogenic emissions are held constant for the 2018 future year modeling 

inventories.

Emissions Modeling 

To prepare the stationary area inventories for modeling, several modifications to the inventory 

files were made by removing selected sources either to model them as separate source categories 

or to omit them from the Base02 inventories completely. Using guidance provided by EPA (U.S. 

EPA, 2004b) fugitive and road dust sources were extracted from all stationary area source 

inventories for adjustment by transport factors and modeling as separate source categories (seethe 

Fugitive Dust Emissions documentation). The stage II refueling sources were also extracted and 

discarded from the non-WRAP U.S. inventories; these sources were modeled with MOBILE6 as 

part of the on-road mobile-source emissions. The stage II refueling emissions in the WRAP 

stationary area inventory were retained because the on-road mobile inventory for this region did 

not contain these emissions. 

Additional steps performed to prepare the area source inventories included moving oil and gas 

sources from the California inventory to a separate file for explicit treatment, confirming that 

there is no overlap between the anthropogenic NH3 inventory and stationary area sources, 

moving several off-road mobile SCCs from the Mexico inventory to the off-road mobile sector, 
and moving area source fires in each regional inventory to separate files. In addition to these 

inventory modifications, a few changes to the ancillary data files for the Base02 inventories were 

made. 

Base02 used improved temporal and spatial allocation information relative to the preliminary 

2002 modeling; the rest of the ancillary data for modeling stationary area sources remained 

unchanged from the preliminary 2002 modeling (Tonnesen et al., 2005). Enhanced spatial 

allocation data with additional area-based surrogates were incorporated for Canada, and 

additional surrogates for Broomfield County in Colorado were used. 

Improvements to the temporal allocation data for the Base02 inventories included the addition of 

several FIPS-specific profiles provided by VISTAS and CENRAP. These temporal profiles 

targeted mainly fire and agricultural NH3 sources in these regions, such as open burning and 

livestock operations, respectively. 

The quality assurance of the area source emissions followed the WRAP emissions modeling QA 

protocol (Adelman, 2004) and a suite of graphical summaries. Tabulated summaries of the input 

data and SMOKE script settings were used to document the data and configuration of SMOKE. 

The graphical QA summaries include, for all emissions output species, daily time-series plots, 

annual time-series plots, and daily vertical profiles. These QA graphics are available on the 

RMC web site at http://pah.cert.ucr.edu/aqm/308/QA_base02a36.plots/ar/plots/.

Ammonia Emission Sources

Ammonia (NH3) emissions from agricultural activities are a major source of ammonia and are 

dependent on many different environmental parameters, such as meteorology, crop and soil 

types, and land use. Traditionally these emissions have been represented in the stationary-areasource inventory as annual, county-level estimates. These estimates did not consider 

meteorology, and may have used different land use assumptions than were used in the air quality 

model simulations to which they were input. The WRAP funded development of a process-based 

agricultural NH3 emissions model to estimate NH3 emissions from several different agricultural 

sources (such as soils, livestock, and fertilizer application) that uses the same meteorology and 

land use assumptions that are used in CMAQ and CAMx. 

The WRAP NH3 emissions were prepared outside of SMOKE using the WRAP NH3 model; 

details of this modeling are available in Mansell (2005). Due to an incorrect assumption in the 

soil emission factor used in the model, however, we had to discard the emissions from this 

sector. The WRAP NH3 model emissions estimates were combined with data provided by the 

other RPOs to represent agricultural NH3 emissions in Base02 modeling inventories. CENRAP 

and MRPO provided monthly IDA-formatted, county-level NH3 inventories that they developed 

with their own process-based models. These emissions were modeled as area sources with 

SMOKE, applying the temporal profiles and the spatial cross-referencing received from these 

RPOs. The agricultural NH3 emissions for the rest of the RPOs, Canada, and Mexico are 

contained within their stationary area inventories. The SMOKE default temporal profiles and 

spatial surrogates were applied to all non-process-based NH3 emissions.

The quality assurance of the ammonia emissions followed the WRAP emissions modeling QA 

protocol (Adelman, 2004) and a suite of graphical summaries. Tabulated summaries of the input 
data and SMOKE script settings were used to document the data and configuration of SMOKE. 

The graphical QA summaries include, for all emissions output species, daily time-series plots, 

annual time-series plots, and daily vertical profiles. These QA graphics are available at 

http://pah.cert.ucr.edu/aqm/308/QA_base02a36.plots/nh3/plots/.

Oil and Gas Emissions

The oil and gas production industry includes a large number of processes and equipment types 

that stretch from the wellhead to fuel distribution networks. Many of these processes emit 

significant quantities of nitrous oxides (NOx), volatile organic compounds (VOC) and other 

pollutants. Past emission inventories have estimated emissions from specific pieces of 

equipment, for limited geographic areas and for other segments of the industry. The largest oil 

and gas production facilities, gas plants and major compressor stations, have been previously 

inventoried as stationary sources. All states in the western region had previously compiled 

emission inventories for the year 2002 that included the major “point” emission sources in the oil 

and gas production industry. However, what was included in these emission inventories varied 

from state to state, depending on the permitting and/or reporting thresholds. 

Oil and gas production facilities that are geographically distributed and have lesser emissions 

than the point source threshold are considered area sources. Previously, there had not been a 

comprehensive emission inventory of oil and gas production operations in the western region that 

covered both point and area sources. Nor had there been a methodology developed to produce an 

inventory of this scope. The current WRAP inventory of oil and gas emissions was developed by 

ENVIRON as part of a WRAP-funded study to develop and implement a uniform procedure for 

estimating area source emissions from oil and gas production operations across the western 

region (Russell and Pollack, 2005). The emphasis of this study was placed on estimating 

emissions of pollutants with the potential to impair visibility near Class I areas in the west, in 

particular NOx emissions. In developing the emission estimation methodology, considerable 

resources were devoted to incorporating the insights and guidance of a variety of stakeholders, as 

well as integrating the point source emissions estimates developed in previous inventory efforts. 

The 2002 oil and gas point source emissions have been adopted from the state inventories (ERG, 

2005a). The level of coverage in those inventories was evaluated and the point source emissions 

have been reconciled with emissions estimated using the newly developed area source inventory 

methodology.

Oil and gas point source emission inventories include location parameters. For the current oil 

and gas area source emissions, a new spatial allocation scheme was developed to facilitate the 

integration of these emissions sources into the WRAP regional haze modeling. New spatial 

surrogates were developed for each of the non-point oil and gas emission sources addressed by 

this inventory. These surrogates, which are based on the geographic locations of oil and gas 

production, will enable the appropriate spatial distribution of emissions from oil and gas 

production operations in the air quality modeling.

Finally, a procedure was formulated and implemented to project the emissions from oil and gas 

production operations to future year 2018. For the WRAP 2018 base case modeling, only those 
emission control strategies that have already been adopted are considered. Oil and gas 

production forecasts were drawn from several sources and combined with the emissions 

estimates produced for the 2002 inventory and information on future controls to arrive at the 

2018 inventory. Oil and gas point source projections are described in a separate report (ERG, 

2005b).

Inventoried Sources 

The WRAP Oil and Gas inventory was developed for a number of specific processes and 

equipment not previously inventoried. Emissions were estimated and modeled as both stationary 

point and distributed area sources. Major sources of NOx and VOC emission were the focus of 

the inventory. 

Major sources of NOx emissions include the following processes and equipment types:

 Compressor engines

 Drill rigs

 Wellheads

 CBM pump engines

Major sources of VOC emissions include the following processes and equipment types:

 Oil well tanks

 Oil well pneumatic devices

 Gas well pneumatic devices

 Gas well dehydrators

 Gas well flaring and venting

 Condensate tanks

For each of these equipment types and processes, new and/or revised estimation methodologies 

were developed and applied. A detailed discussion of these methodologies can be found in 

Russell and Pollack, 2005.

Spatial Allocation

For air quality modeling, the EPA default spatial allocation surrogates were not 

appropriate for the area source oil and gas production emissions. ENVIRON therefore developed 

a new set of spatial allocation surrogates to be used in SMOKE to allocate the county-level area 

source emissions to the appropriate oil and gas fields. Oil and gas operation emissions estimated 

as stationary point sources are allocated based on geographic coordinates. 

A total of four different surrogate categories were designed to allocate emissions from the twelve 

oil and gas emission source categories listed in Table 1. The oil, gas and water production 

surrogates were based on production data at known well locations, while the drill rig surrogate 

was based solely on the number and location of wells drilled.
Table 1. Emission sources and surrogate categories.

Source SCC Allocation Surrogate Surrogate Code

Drill rigs 2310000220 Drill Rigs 688

Oil well - heaters 2310010100 Oil Production 686

Oil well - tanks 2310010200 Oil Production 686

Oil well - pneumatic devices 2310010300 Oil Production 686

Compressor engines 2310020600 Gas Production 685

Gas well - heaters 2310021100 Gas Production 685

Gas well - pneumatic devices 2310021300 Gas Production 685

Gas well - dehydration 2310021400 Gas Production 685

Gas well - completion 2310021500 Gas Production 685

CBM pump engines 2310023000 Water production at CBM wells 687

Gas well - tanks, uncontrolled 2310030210 Gas Production 685

Gas well - tanks, controlled 2310030220 Gas Production 685

Once the well locations were known, creation of the surrogates took place in several steps, and 

relied on the use of ArcINFO GIS software.

1. All wells and drill rigs were labeled with the appropriate grid cell IJ values for the 36-km 

domain. 

2. For each individual well, the oil, gas and water production values were divided by the 

total oil, gas and water production values corresponding to the county in which the well 

was located. This division resulted in determination of the fraction of a county’s total 

production taking place at each well. In the case of drill rigs, the number of drills, rather 

than the production values, were used.

3. For each unique grid cell / county combination with wells, each well’s production 

fractions were summed to create the surrogate value. 

The surrogate values for each grid cell / county combination were reformatted to comply with the 

SMOKE emissions processor AGPRO file format and an accompanying SMOKE AGREF file 

was created. The purpose of the AGREF file, presented in Table 2, is to define the relationship 

between the 3-digit codes chosen to represent each of the four surrogate categories in the 

AGPRO file and the SCC codes for the twelve oil and gas emission categories to be allocated 

with these surrogates. This file also specifies which county/state/county (COSTCY) should use 

the given cross-reference. In this case, COSTCY is set to 000000 to indicate that all states and 

counties can use these cross-references.

Table 2. SMOKE gridding surrogate cross-reference (AGREF) file.

COSTCY SCC CODE

000000 2310000220 686

000000 2310010100 688

000000 2310010200 686

000000 2310010300 686

000000 2310020600 686

000000 2310021100 685
000000 2310021300 685

000000 2310021400 685

000000 2310021500 685

000000 2310023000 687

000000 2310030210 685

000000 2310030220 685

2018 Projection Methodology 

The 2018 emission estimates from oil and gas production operations reflect the anticipated 2018 

emission levels with the future controls currently defined by state and federal regulation. The 

2018 oil and gas point source emissions inventory was prepared and reported separately by 

Eastern Research Group (ERG, 2005b). A detailed discussion of the development of the 2018 oil 

and gas inventory, including those sources modeled as area sources can be found in Russell and 

Pollack, 2005. 

There were two primary basic methods used to estimate 2018 county-level oil and gas emissions. 

The first and by far the dominant method was to develop growth factors that were then used to 

project from the 2002 oil and gas emissions. A second method was necessary to estimate 

emissions in the handful of counties that had no 2002 oil and gas emissions but are anticipated to 

see oil and gas development by 2018. The decision of which method was used to estimate 2018 

emissions was based on the existence of oil and gas emissions in 2002. Detailed discussions of 

each of the projection methods, data sources and methodologies for both cases are presented in 

Russell and Pollack, 2005. 

To QA the oil and gas production emissions, we used the WRAP emissions modeling QA 

protocol (Adelman, 2004) and a suite of graphical summaries. Comparisons of the spatial plots 

produced from SMOKE output with spatial plots provided by ENVIRON were reviewed to 

ensure these data were modeled correctly. Tabulated summaries of the input data and SMOKE 

script settings were used to document the data and configuration of SMOKE. The graphical QA 

summaries include, for all emissions output species, daily spatial plots, daily time-series plots, 

and annual time-series plots are available at 

http://pah.cert.ucr.edu/aqm/308/QA_base02a36.plots/wog/plots/.

Biogenic Emissions

The BEIS3.12 model, integrated in SMOKE, was used to prepare biogenic emissions for the 

Base02 modeling inventories. BEIS3 is a system integrated into SMOKE for deriving emissions 

estimates of biogenic gas-phase pollutants from land use information, emissions factors for 

different plant species, and hourly, gridded meteorology data. The results of BEIS3 modeling are 

hourly, gridded emissions fluxes formatted for input to CMAQ or CAMx. 

Most of the preparation for the biogenic emissions processing was completed during the 

preliminary 2002 modeling. As the modeling domains did not change from the preliminary 2002 

to the Base02 modeling, the gridded land use data and vegetation emissions factors prepared for 

the preliminary simulations were used. The major difference in the emissions processing between 
the preliminary 2002 and Base02 modeling was in the integration of improved meteorology in 

the Base02 inventories.

The quality assurance of the biogenic emissions followed the WRAP emissions modeling QA 

protocol (Adelman, 2004) and a suite of graphical summaries. Tabulated summaries of the input 

data and SMOKE script settings were used to document the data and configuration of SMOKE. 

The graphical QA summaries include, for all emissions output species, daily time-series plots, 

annual time-series plots, and daily vertical profiles. These QA graphics are available at 

http://pah.cert.ucr.edu/aqm/308/QA_base02a36.plots/b3/plots/.

Gridded Area Source Emission Inventory Summaries

Summaries of the gridded area source emissions for the Base02b, Plan02c and Base18b 

inventories by state and county, annual and seasonal periods, can be found on the TSS at: 

http://vista.cira.colostate.edu/tss/Results/Emissions.aspx. 

References

Adelman, Z. 2004: Quality Assurance Protocol – WRAP RMC Emissions Modeling with SMOKE, 

Prepared for the WRAP Modeling Forum by the WRAP Regional Modeling Center, Riverside, CA.

E.H. Pechan & Associates and Carolina Environmental Program, 2005: Final Report: Refinement of 

CENRAP’s 2002 Emissions Inventories, Prepared for the Central Regional Air Planning Association 

by E.H. Pechan & Associates, Inc., Durham, NC and the Carolina Environmental Program, Chapel 

Hill, NC, 

http://projects.pechan.com/CENRAP/Deliverables/2002%20Inventory%20Revisions/Report%20and

%20Supporting%20Files/Final/CENRAP_Base%20B_EI_Rpt_Final_Aug3105.doc

ERG. 2005a. "Quality Assurance of the 2002 WRAP Stationary Sources Emissions Inventory," 

Draft, December 5, 2005.

ERG. 2005b. "WRAP Point and Area Source Emissions Projections for the 2018 Base Case 

Inventory," Draft, December 21, 2005.

Kemball-Cook, S. et al., 2005: Draft Final Report, Annual 2002 MM5 Meteorological Modeling 

to Support Regional Haze Modeling of the Western United States, prepared for the WRAP by 

ENVIRON International Corporation, Novato, CA and the University of California at 

Riverside, Riverside, CA. 

http://pah.cert.ucr.edu/aqm/308/reports/mm5/DrftFnl_2002MM5_FinalWRAP_Eval.pdf

Mansell, G., 2005: Final Report Volume I: An Improved Ammonia Inventory for the WRAP 

Domain, Prepared for the Western Regional Air Partnership by ENVIRON International 

Corporation, Novato, CA. 

http://pah.cert.ucr.edu/aqm/308/ppt_files/emissions/nh3/Volume_I_FinalReport.3-07.pdf

Russell, J. and A. Pollack. 2005. “Oil and Gas Emissions Inventories for the Western States” 

Final Report. Prepared for the Western Governors’ Association. December 27.
Stella, G., 2005: Base F Emissions Inventories by State and RPO, Prepared for the VISTAS Joint 

Work Group Meeting by Alpine Geophysics, LLC. http://www.vistassesarm.org/documents/VISTASJointWorkGroupMeeting09052005/2_StellaIPM2018Results22Sept2005.ppt

Tonnesen, G. et al., 2005: Final Report for the WRAP RMC for the Project Period March 1, 

2004 through February 28, 2005, Prepared for the Western Governors Association by 

ENVIRON International Corporation, Novato, CA. 

http://pah.cert.ucr.edu/aqm/308/ppt_files/emissions/nh3/Volume_I_FinalReport.3-07.pdf

U.S. EPA (U.S. Environmental Protection Agency), 2005d: North American Emission Inventories –

Canada, http://www.epa.gov/ttn/chief/net/canada.html.