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

Emissions M ethods : 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 d ry 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
file s and ancillary data for allocating the inventories in space, time, and to the Carbon Bond

- IV chemistry mechanism used in CMAQ and CAMx. Th e development of the area source emission inventory is described i n 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

 Agricultu r al and natural ammonia emission sources

 Oil and gas produ ction 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 us e 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). Sp ecific 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 a re documented below.

Stationary Area SourcesThe 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 ar ea inventory consist s of annual county

- level and tribal data provided by ERG, Inc. (2005), however, d ue to the small contribution of the WRAP tribal inventories to the total domain emissions and the lack of readily available spatial allocation data
for the se 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 provid ed by these RPOs.
T he 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
inven tories. 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. E PA 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 contr ol) 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 ( lives tock operations and fertilizer application)
and natural so urces ( 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 NH 3 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 OperationsThe 2002 Base year emission inventory included a number of emissions sectors that WRAP had

ne ver 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 model ing 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, 200 5a ). ENVIRON provided th e 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, 200 5 ). For California, oil and gas
inventories were extrac ted 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 emis sions 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 differe d from the preliminary 2002 modeling in the use of improved 2002 meteorology data we developed in 2005 (Kemball

Cook et al., 2005). Biogenic emissions are held constant for the 2018 future year modeling
inventories.

Emissions Modeling

To prepare the stati onary 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 E PA (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 (see the Fugitive Dust Emissions documentation ). T he stage II refue ling 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. T he stage II refueling emissions in the WRAP

st ationary 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 treat ment

, confirming that there is no overlap between the anthropogenic NH 3 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 invent ory 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 modelin g; the rest of the ancillary data for modeling stationary area sources remained unchanged from the preliminary 2002 modeling (Tonnesen et al., 2005). E nhanced spatial
allocation data with additional area

- based surrogates were incorporated for Canada, and

a dd itional 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 target ed mainly fire and agricultural NH 3 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 g raphical 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/

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Ammonia Emission Source s

Ammonia (NH 3 ) 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 i n the stationary

- area

source 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 NH 3 emissions model to estimate NH 3 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.

T he WRAP NH 3 emissions were prepared outside of SMOKE using the WRAP NH 3 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, w e had to discard the emissions from this

sector. The WRAP NH 3 model emissions estimates were combined with data provided by the other RPOs to represent agricultural NH 3 emissions in Base02 modeling inventories. CENRAP and MRPO provided monthly IDA

- formatte d, county

- level NH 3 inventories that they developed with their own process

- based models. T hese emissions were modeled as area sources with SMOKE, applying the temporal profiles and the spatial cross

- referencing received from these RPOs. The agricultural NH 3 emissions for the rest of the RPOs, Canada, and Mexico are

co ntained within their stationary area inventories. T he SMOKE default temporal profiles and spatial surrogates were applied to all non

- process

- based NH 3 emissions

.
The quality assurance of the am monia emissions followed the WRAP emissions modeling QA protocol (Adelman, 2004) and a suite of graphical summaries. Tabulated summaries of the inputdata 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://p ah.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 proces ses 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 th e 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 t hat 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 r egion 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 i mplement a uniform procedure for estimating area source emissions from oil and gas production operations across the western region ( R ussell 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 in tegrating 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 emiss ions, 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
th is 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 thoseemission control strategies that have already been adopted are considered. Oil and gas

p roduction 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 separ ate report (ERG, 2005b).

Inventoried Sources

The WRAP Oil and Gas inventory was developed for a number of specific processes and equipment not pre viously inventoried. Emissions were estimated and modeled as both stationary point and distributed area so urces. 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 i nclude 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 revise d 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 appropriat e 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 opera tion 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 pum

p 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

to tal 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 w ere reformatted to comply with the SMOKE emissions processor AGPRO file format and a n 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 repres ent 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

- refe rence. 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 2 310010200 686
000000 2310010300 686
000000 2310020600 686
000000 2310021100 685000000 2310021300 685

000000 2310021400 685
000000 2310021500 685
000000 2310023000 687
000000 2310030210 685
000000 2310030220 685

2018 Projection Methodology

Th e 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 an d 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.

T here 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 d iscussion s of
each of the projection method s, 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 (Adelm an, 2004) and a suite of graphical summaries. C ompar isons of the spatial plots produced from SMOKE output with spatial plots provided by ENVIRON were reviewed to ensure these data were modeled correctly. T abulated summaries of the input data and SMOKE
scri pt 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
hour ly, 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 Bas e02 modeling, the gridded land use data and vegetation emissions factors prepared for the preliminary simulations were used. The major difference in the emissions processing betweenthe preliminary 2002 and Base02 modeling was in the integration of improve d 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 we re 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 Bas e18b
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: Refinem ent 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_E I_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.vistas

sesarm.org/documents/VISTASJointWorkGroupMeeting09052005/2_Stella

IPM2018Results22Sept2005.ppt
Tonnesen, G. et al., 2005: Final Report for the WRAP RMC for the Project Period March 1, 2004 through February 28, 2005, Prepar ed 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

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