EMISSIONS MODELING

Overview

In support of the WRAP Regional Haze air qualit y modeling efforts, the RMC developed annual emissions inventories for a 2002 actual emissions base case, a planning case to represent the 2000-04 regional haze baseline period using averages for key emissions categories, and a 2018 base case of projected emissions determined using factors known at the end of 2005. All emission inventories were developed using the Sparse Matrix Operator Kernel Emissions (SMOKE) modeling system. Each of these invent ories has undergone a number of revisions throughout the development process to arrive at the final versions used in CMAQ and CAMx air quality modeling. The WRAP emission i nventories developed by the RMC include:

 The 2002 base case emissions scenario, referred to as “2002 Base Case” or “Base02”. The purpose of the Base02 inventory is to repr esent the actual conditions in calendar year 2002 with respect to ambient air quality and the associat ed sources of criteria and particulate matter air pollutants. The Base02 emissions inventories are used to validate the air quality model and associated databa ses and to demonstrate acceptable model performance with respect to replicating observed particulate matter air quality.

 The 2000-04 baseline period planning case emissions scenario, is referred to as “Plan02”. The purpose of the Plan02 inventory is to represent baseline emission patterns based on average, or “typical”, conditions. This inventory provides a basis for comparison with the future year 2018 projected emissions, as well as to gauge reasonable progress with respect to future year visibility.

 The 2018 future-year base case emissions scenar io, referred to as “2018 Base Case” or “Base18”. These emissions are used to re present conditions in future year 2018 with respect to sources of criter ia and particulate matter air pollutants, taking into consideration growth and cont rols. Modeling results based on this emission inventory are used to define the future year ambien t air quality and visibility metrics.

Emission inventory development and modeling in ge neral is discussed below. Specifics with respect to the development each of these inventor ies, as well as a discussion of the various revisions and enhancements for each are provid ed separately for each of these emission scenarios.

Source categories

Emissions inventories are typically divided into area, on-road mob ile, point, and biogenic source categories. These divisions arise from differing methods for prepar ing the inventories, different characteristics and attributes of the categories, and how the emissions are modeled. Generally, emissions inventories are divided in to the following source categories:

 Stationary Area Sources: Sources that are treated as be ing spread over a spatial extent (usually a county or air distri ct) and that are not movable (a s compared to nonroad mobile and on-road mobile sources). Because it is not possible to collect the emissions at eachpoint of emission, they are estimated over la rger regions. Examples of stationary area sources are residential heating and architectural coatings. Nu merous sources, such as dry cleaning facilities, may be treated either as st ationary area sources or as point sources.

 Mobile Sources: Vehicular sources that travel on roadways. These sources can be computed either as being spread over a spatial extent or as be ing assigned to a line location (called a link). Data in on-road inventories can be either emissions or activity data. Activity data consist of vehicle miles tr aveled (VMT) and, optionally, vehicle speed. Examples of on-road mobile sources include light-duty gasoline vehi cles and heavy-duty diesel vehicles.

 Point Sources: These are sources that are identifie d by point locations, typically because they are regulated and their locations are available in regulator y reports. In addition, elevated point sources will have their emissions allocated vertically through the model layers, as opposed to being emitted into only the first model layer. Point sources can be further subdivided into electric genera ting unit (EGU) sources and non-EGU sources, particularly in criteria inventories in which EGUs are a primary source of NO x and SO 2
. Examples of non-EGU point sources include chemical manufacturers and furniture refinishers.

 Biogenic Land Use Data: Biogenic land use data characteri ze the types of vegetation that exist in either county-total or grid cell values. The biogenic land use data in North America are available using two different sets of land use cate gories: the Biogenic Emissions Landcover Database (BELD) vers ion 2 (BELD2), and the BELD version 3 (BELD3) (CEP, 2004b).

In addition to these standard source categorie s, the inventory devel opment efforts included additional categories either to represent specific emissions processes more accurately or to integrate emissions data that are not compatib le with SMOKE. Examples of emissions sectors that fall outside of the standard SMOKE proce ssing categories include emissions generated from process-based models for representing windblown dust and agricultural ammonia (NH 3 ) sources. An emissions category with data that are not compatible with SMOKE is one with gridded emissions data sets, such as commercial marine sources. Other source cat egories treated outside the standard SMOKE processing in clude emissions from oil and gas operations and fires.

Emission source categories were furt her refined to include more e xplicit emissions sectors. The advantage of using more detailed definitions of the source categor ies is that it leads to more flexibility in designing control st rategies, substituting new invent ory or profile data into the modeling, and managing the inpu t and output data from SMOKE. The major drawback to defining more emissions source cate gories is the increased level of complexity that results from having a larger number of input data sets. Another motivation behind separating the various emissions categories is related to the size and flexibility of th e input data. Additional details regarding the development of each of the source sectors, including emissions inventories and ancillary data for modeling are described in later sections of this documentation. Table 1 summarizes the primary source se ctors defining the WRAP emissi on inventories. Some minor modifications to this list were made for each of specific scenarios and inventory versions, as discussed below.The development and modeling of each emissions source sector is documented in separate subsections of this document. For each, a de scription in terms of the SMOKE processing category, the year covered by the inventory and i nventory version, and the source(s) of the data are discussed. Additional details about the inventories are also provided, including any modifications that we made to prepare them for input into SMOKE.

Table 1. WRAP emission inventory source sectors.

Emissions Sector Abbreviation* Stationary area, including VISTAS county-level fires ar

CENRAP county-level fires arf WRAP point-source fires awf Biogenic bg Ontario, Canada, point-source fires bsf Fugitive dust fd
WRAP on-road mobile mb
CENRAP on-road mobile mbvcen
Other US on-road mobile mbv
Non-US on-road mobile nusm CENRAP/MRPO anthropogenic NH 3 nh3 WRAP anthropogenic NH 3 nh3wrap Seasonal/monthly nonroad mobile nrm Annual nonroad mobile nry Non-WRAP point-source fires nwf
Offshore area ofsar Offshore point ofspt Commercial marine shipping ofsmar Stationary point pt
Road dust rd
Windblown dust wbd WRAP oil and gas wog

*These abbreviations are used in the file na ming of the SMOKE output files for each sector.
SMOKE Modeling

Emissions models such as SMOKE are computer programs that convert a nnual or daily estimates of emissions at the state or c ounty level to hourly emissions fluxe s on a uniform spatial grid that are formatted for input to an air quality mode l. Emission inventories were prepared for CMAQversion 4.4 using SMOKE version 2.1 on the WR AP RMC Linux computing cluster. SMOKE integrates annual county-level em issions inventories with source- based temporal, spatial, and chemical allocation profiles to create hourly em issions fluxes on a predefined model grid. For elevated sources that require allocation of the emissions to the vertic al model layers, SMOKE integrates meteorology data to derive dynamic vert ical profiles. In additio n to its capacity to represent the standard emissions processing ca tegories, SMOKE is also incorporates the Biogenic Emissions Inventory System, versi on 3 (BEIS3) model for estimating biogenic emissions fluxes (U.S. EPA, 2004) and the MO BILE6 model for estimating on-road mobile emissions fluxes from county-level vehi cle activity data (U.S. EPA, 2005a).

SMOKE uses C-Shell scripts as user interfaces to set configuration options and call executables. SMOKE includes flexible QA capabilities to genera te standard and custom reports for checking the emissions modeling process. After modeling all of the source ca tegories individually, including those categories generated outside of SMOKE, the model is used to merge all of the categories together to create a single CMAQ input file per simulation day. Also, for use in the CAMx modeling, we converted the CMAQ-ready emissions estimates to CAMx-ready files using a combination of SMOKE and stand-alone Perl scripts devel oped by ENVIRON. SMOKE was also used to generate CAMx inputs for al l low-level emissions (i ncluding low-level point sources) and the CMAQ2CAMX converter to creat e the CAMx inputs for the elevated sources (including fires).

SMOKE Ancillary Data

The development of emission inventories using SMOKE requires a number of ancillary datasets. SMOKE ancillary modeling data include

 temporal and chemical allocation factors by state, county, and sour ce classification code (SCC)

 spatial surrogates and cross-reference files fo r allocating county-level emissions to the model grid

 hourly, gridded meteorology data

 stack defaults for elevated point sources

 MOBILE6 configuration files

 Federal Implementation Standards (FIPS) codes (i.e., country/state/county codes) definition file

 SCC definition file

 pollutant definition file

All WRAP emission inventories were prepared using a common set of ancillary data with specific revisions and enhancements, as noted below. Default data sets provided by EPA formed the basis for these data except for the meteorological data and the MOBILE6 configuration files. The WRAP RMC provided the meteorology data at 36-km and 12-km grid resolutions (Tonnesen et al., 2005) . MOBILE6 configuration files were provided to the RMC by mobile source emissions contractor.Minor modifications were made to the ch emical allocation, pollutant definition, and country/state/county codes files for new sources, pollutants, or counties contained in the WRAP inventories that we had not pr eviously modeled. The temporal and spatial allocation inputs incorporated major modifications, as described below.

Temporal allocation data

Temporally allocating annual, daily, or hour ly emissions inventories in SMOKE involves combining a temporal cross-reference file and a temporal profiles file.

 Temporal cross-reference files associate m onthly, weekly, and diurnal temporal profile codes with specific inventory source s, through a combination of a FIPS (country/state/county) code, an SCC, and sometimes for point sources, facility and unit identification codes.

 Temporal profiles files contain coded monthly, weekly, and diur nal profiles in terms of a percentage of emissions allocated to each te mporal unit (e.g., percentage of emissions per month, weekday, or hour).

The temporal allocation data from the WR AP preliminary 2002 modeling (Tonnesen et al., 2005), which originated from EPA (2005b) form ed the basis for all modeling inventories developed fro WRAP. Based on guidance from the developers of some of the inventory files, enhancements were made to the temporal profil es and assignments for some source categories.

The WRAP nonroad mobile-source inventories included weekday/weekend split factors to allocate these data to the various days of the week (Pollack, 2005). These split factors were used to modify the standard EPA temporal profiles for a series of nonroad SCCs specified by the inventory contractor. Specific de tails regarding these modifications are described in the section on mobile source emissions inventory development.

Other additions to temporal allocation data in cluded updates made for some WRAP sources and updates made by other RPOs that are applicable to their inventories. These other updates to the temporal allocation files included

 VISTAS continuous emissions monitoring (C EM)-specific profiles for EGUs in the VISTAS states

 VISTAS agricultural burning profiles

 Wildfire and prescribed fire profiles developed by VISTAS for the entire U.S.

 MANE-VU on-road mobile profiles

 WRAP weekly and diurnal road dust profiles

 WRAP diurnal wildfire, agricultural fire, and prescribed fire profiles

 WRAP on-road mobile weekly and diurnal profiles

 CENRAP non-Federal rangeland fire profilesFinally, for all of the monthly and seasonal emissi ons inventories, temporal cross-reference files were modified to apply uniform monthly profiles to the sources contained in these inventories. The monthly variability is inhere nt in monthly and seasonal invent ories and does not need to be reapplied through the temporal al location process in SMOKE. The inventories to which uniform monthly temporal profiles were applied included:

 WRAP, CENRAP, and MRPO nonroad mobile sources

 WRAP on-road mobile sources

 WRAP road dust

Spatial allocation data

SMOKE uses spatial surrogates and SCC cross-refe rence files to allocate county-level emissions inventories to model grid cells . Geographic information system (GIS)-calculated fractional land use values define the percentage of a grid cell that is covere d by standard sets of land use categories. In addition to land use categories, spatial surrogates can also be defined by demographic or industrial units, such as populati on or commercial area. Similar to the temporal allocation data, an accompanying spatial cross-reference file a ssociates the spatial surrogates (indexed with a numeric code) to SCCs. Spatial a llocation with surrogates is applicable only to area and mobile sources. Point sources are loca ted in the model grid cells by SMOKE based on the latitude-longitude coordinates of each source. Biogenic emissions are estimated based on 1-km 2 gridded land use information that is mapped to the model grid using a processing program such as the Multimedia Integrated Modeling System (MIMS) Spatia l Allocator (CEP, 2005).

Various sources of spatial surrogate information for the U.S., Canada, and Mexico were used in the development of the WRAP inventories. For the U.S. and Canadian sources, the EPA unified surrogates available through the EFIG web site (EPA, 2005c) were used. For the 36-km grid, EPA provides these data already formatted fo r SMOKE on the RPO Unified 36-km domain. Spatial surrogates for Canada on the RPO Un ified 36-km domain were modified by adding several surrogate categories whic h were lacking in the EPA data set. For Mexico, GIS shapefiles developed for the Big Bend Regional Aerosol and Visibility Observ ations Study (BRAVO) modeling were used to create surrogates for Mexico on the RPO Unified 36-km domain (U.S. EPA, 2005c).

2002 BASE CASE INVENTORY

The developm ent of the 2002 Base Case emissi on inventory for WRAP has undergone a number of revisions throughout the development process to arrive at the final versions used in CMAQ and CAMx air quality modeling. A brief description of these revisi ons is presented below. More detail with respect to the development of each sp ecific version is provided separately as part of the discussion of each emission source category.

Base02aVersion “a” of the 2002 base cas e inventory, Base02a, was developed based on preliminary 2002 modeling (Tonnesen et al., 2005). Improved 2002 em issions data for the United States, Mexico, and Canada were used to create a final base 2002 annual emissions database for use in the CMAQ and CAMx model performance evaluati ons. Sources for emissions inventory and ancillary modeling data included WRAP emissions inventory contractors, other RPOs, and EPA. Building from the WRAP preliminary 2002 modeling cases completed earlier, several updates to the inventories and ancillary data were incorpor ated to create final 2002 emissions input files for the 2002 base case A, or Base02a. SMOKE vers ion 2.1 (CEP, 2004) was used to prepare the inventories for input to the air quality modeling systems. More detailed documentation of the SMOKE emissions modeling ca n be found in Adelman, 2004.

Base02b

2000-04 BASELINE PERIOD PLANNING INVENTORY

This “Plan02” series of invent ories was developed to represen t baseline period em ission patterns based on average, or “typical”, conditions. This inventory series (cas es Plan02a, b, c) were performed in sequence to diagnose emissions is sues and true up the representativeness and accuracy of the emissions for planning purposes, provides a basis for comparison with the future year 2018 projected emissions, as well as to ga uge reasonable progress with respect to future year visibility. As with the Base02 inventorie s, the WRAP planning inventory has undergone a number of revisions and enhancem ents to arrive at the final ve rsions used in CMAQ and CAMx air quality modeling. A brief descri ption of these revisions is presented below. More detail with respect to the development of each specific vers ion is provided separately as part of the discussion of each emission source category. Th e Plan02 emissions inve ntory was developed from the Base02 emissions modeling scenarios by incorporating two major modifications; the inclusion of baseline, rather than actual-year, fire emissions data, and the application of averaged temporal profiles for stationary point sources.

To create the Plan02a emissions inventory, only two changes were anticipated: (1) replacement of actual 2002 fire emissions inve ntories with the baseline typical fire emissions inventories and (2) replacement of the temporal profiles for large stationary point sources with profiles developed from an average of several y ears surrounding 2002. Based on the QA performed on the Base02a inventory, however, several errors and issues were discovered which required corrections. As a result, the Plan02a inventory cont ained not just the originally planned inventory changes but also corrections to the off-road mobile, on-road mobile, offshore Pacific shipping lane, and WRAP oil and gas inventories. Additiona l issues with the development of the Plan02a inventory were also addressed a nd incorporated into the version “b” of the planning inventories. A final version “c” planning inventory was devel oped which incorporated a number of additionalminor revisions to the “b” version of the invent ory. These revisions and corrections are briefly described below, while more details are provided under sour ce category-specific documentation presented in later sections.

Plan02a

The Plan02a emission inventory was developed from a combinati on of the WRAP baseline fire inventories, actual 2002 EGU invent ories with historically averag ed temporal profiles, typicalyear inventories from other RPOs, and Base02 emissions for the remaining emission sectors. After completing the Base02a inventory (Tonnesen et al., 2006), several updates to the 2002 base inventories that affected most regions of the modeling domain were collected. Although they were considered components of the Base02 inve ntories, we applied these updated inventories initially in simulation Plan02a.

The RMC implemented the following changes to the Base02 inventories to develop the Plan02a emission inventory:

 Stationary Area Sources: Revised inventories for Califor nia, Washington, North Dakota, Oregon, Utah, Mexico, and non-fire sources in the VISTAS states. Additional dust sources extracted from the area-source inventory to be modeled explicitly as fugitive dust.

 Fugitive Dust Sources: Revised inventories for Califor nia, Washington, North Dakota, Oregon, Utah, Mexico, and non-fire sources in the VISTAS states. Expansion of the fugitive dust list of sources to include a broader definition of dust.

 Road Dust Sources: Revised inventory for Californi a and VISTAS states. Note: We extracted the California data from the revised stationary-a rea-source inventory.

 On-road Mobile Sources: Revised inventories for Calif ornia, Montana, Colorado, and Mexico.

 Non-road Mobile Sources: Revised inventories for Califor nia, Mexico, and the VISTAS states. Updated temporal profiles for all non-WRAP states, as developed from the NONROAD2004 model by Alpine Geophysics, LLC.

 Oil and Gas Sources: Revised inventory for stationa ry area California oil and gas sources. Note: We extracted the California da ta from the revised stationary-area-source inventory.

 Stationary Point Sources: Revised inventories for California, Alaska, Arizona, Montana, New Mexico, Oregon, Utah, Washington, Wy oming, WRAP Tribes, Mexico, MANEVU, and VISTAS states. Updated temporal pr ofiles for all non-WRAP EGU sources, as developed from the Integrated Pla nning Model (IPM) for 2018 emissions.

 Pacific Commercial Marine Sources: Revised inventories for Pacific shipping lanes and California on- and near-shore sources

 Broomfield County, CO: Revised the 36-km spatial surr ogates to include Broomfield County, CO, and applied these to the stationary area, road dust, fugitive, oil and gas, andon-road mobile inventories. As these invent ories all explicitly contain emissions for Broomfield County, we revised our spatial al location approach to include surrogates for this county, as opposed to including these emissions in the surrounding counties. As the nonroad mobile inventories still contain Br oomfield County emissions folded into the surrounding counties, we did not change th e spatial surrogates for allocating these emissions to the model grid.

These updates were combined with the previously described revisions to th e fire inventories and EGU temporal profiles to cr eate simulation Plan02a.

Plan02b

The RMC developed the Plan02b inve ntory to correct errors discove red in the Plan02a emissions and to include inventory updates received af ter commencement of the Plan02a inventory development efforts. To create Plan02b from Plan02a, updates were made to the non-WRAP stationary point source emissions, domain-wide fugitive dust and road dust emissions, and Gulf of Mexico offshore area source invent ories. Errors were also correct ed in the configuration of the WRAP non-Federal rangeland prescribed fire emissions, Pacific shipping emissions, and omissions of sources in the fugitive dust inventories used in simulation Plan02a.

The RMC implemented the following changes to the Base02 and Plan02a i nventories to develop the Plan02b emission inventory:

 Updates to non-WRAP stati onary point source emissions: As part of the QA process for new emissions simulations, qualitative a nd quantitative comparisons are made to sequential inventories to confirm that the re sults show the expected changes based on the incremental updates that are made between inve ntories. Observed differences in the nonWRAP stationary point sources these emissions were much larger than anticipated considering that only updates to the temporal profiles were made for these sources. It was discovered that the IPM-derived temporal prof iles used in the Plan02a inventory for the non-WRAP stationary point sources were in tended for use only with IPM-projected 2018 inventories, not with the 2002 inventories. The use of these profiles caused the 2002 emissions for non-WRAP EGUs to increase dr amatically in the Pl an02a inventory. The IPM-derived temporal profiles were theref ore replaced with baseline CEM temporal profiles calculated as 2000-2003 activity averages for the VISTAS states and with actual 2002 CEM-derived temporal profiles for th e CENRAP, MANE-VU, and MRPO states.

 Updates to domain-wide fugi tive dust and road dust emissions: Recent information about dust emissions led to a revision in the appro ach that the RMC uses to model fugitive and road dust emissions. Implementing these updates in simulation Plan02b impacted the fugitive dust, road dust, and stationary-ar ea-source inventories. In May 2006 the EPA Emissions Factors and Inventory Group (EFIG) revised the transport factors that they recommend for scaling dust emissions downward to account for scavenging by vegetation (U.S. EPA, 2006). In implementing these updated factors, an expanded list of source classification codes (SCCs) was used to define the dust sources extracted from the stationary area inventory. This change impacts both the fugitive dust inventory, by increasing the number of sources contained in this sector, and the stationary area sourceinventory, by removing fugitive dust sources from this sector that previously were modeled as area sources.
An additional update to the dust emissions evolved from recommendations made by MRI (2005) regarding a revision to the fine fracti on of PM from dust sources. Based on these recommendations, the PM 2.5 /PM 10 ratios in all of the road dust and fugitive dust inventories were updated prior to SMOKE modeling the Plan02b inventory.

 Updates to Gulf of Mexico o ffshore area source inventories: The RMC also received an updated Gulf of Mexico offshore area sour ce inventory from the U.S. Minerals Management Service during the Plan02a modeli ng. These data were used to replace the previous inventory data for this region of the modeling domain.

 Errors in the Pacific shipping emissions, and omissions of sources in the fugitive dust inventories: Corrections to the Plan02a modeling i nventory were incorporated for these source categories. QA of the Pacific shipping emissions revealed an error in converting the pre-speciated VOC emissions from tons to moles. These emissions were corrected with the appropriate conversion factors for the affected pollutants. During the preparation of the fugitive dust inventor ies, construction and mining dus t sources were inadvertently omitted from Arizona, Colorado, Montana, Nevada, New Mexico, South Dakota, and Wyoming. These data were included in the Plan02b inventory. The above updates and revisions were combined with the unaffect ed sources from Plan02a to produce the Plan02b emission inventory.

Plan02c

The RMC developed the Plan02c emission inventory to correct one error discovered in the Plan02b emissions. To create the Plan02c i nventory from Plan02b, the WRAP non-Federal rangeland prescribed fire emissions were update d. When these data were added to the WRAP modeling, updates to the speciation and temporal cross-reference files were omitted. The result was that the default diurna l temporal profile and PM 2.5 speciation profile were in correctly applied to these emissions. Although these fire sources a ccount for only 0.5% of the total annual WRAP PM 2.5 emissions, this change was made because th eir episodic and localized nature concentrate the emissions in a few grid cells in short time periods, leading to a magnification of the impacts from these sources.

Plan02 Inventory Data Collection and Preparation

The data collection procedures for the devel opm ent of the Plan02 emission inventories are described in this section. A disc ussion of the sources of all in ventory and ancillary data that changed between the Base02a emissions simu lation and the Plan02a, Plan02b, and Plan02c emissions inventories is provided. The RMC worked with emissions inventory contractors, other RPOs, and EPA to collect all of the data that used in updating the Base02a emissions to create the Plan02 emissions.

For the WRAP state and tribal inventories, Air Sc iences, Inc., provided all fire inventories; ERG, Inc., provided all stationary area and stationary point inventories and temporal profiles; and ENVIRON provided all mobile, oil and gas, and Pacific shipping i nventories used in the Plan02scenario emissions inventories. Alpine Geophysics, LLC, provided all inventories and temporal profiles for the non-WRAP U.S. data. ERG, Inc. provided all updated Mexican inventory data. All emissions data were received electronically; the inventories as SMOKE-ready IDA-format data, and the temporal profiles as SMOKE-ready ASCII files.

The RMC received corrected U.S. data for only the updated portions of the Base02 inventories. The previous inventory data for the affected st ates were removed from the files used in the Base02a modeling and combined the remaining data with the updated information to build revised Base02 inventories. This substitution of on ly the revised portions of the inventories was a general approach applied to several emissions s ectors. More specific approaches for preparing the fire, EGU, Pacific shipping, dust, and Mexico inventories were also developed and applied.

 Fires: Air Sciences, Inc., provided annual Baselin e Phase III fire inventories for each of the five fire categories (wildfires, agricu ltural fires, prescribed fires, non-Federal rangeland prescribed fires, and wildland fire use) as three-file sets for each category. Consistent with the fire inventories for Phases I and II, each fire category consisted of an annual IDA file with physical fire event info rmation, a daily IDA file with daily emissions by criteria pollutant, and an hourly IDA file with hourly pre-computed plume rise values. Upon receiving these data, annual i nventories were split into monthly files to avoid computer memory problems related to processing very larg e inventories with SMOKE. For additional information on the developm ent of these fire inventories, refer to WRAP-FEJF (2006).

 EGUs: ERG, Inc., provided SMOKE-ready temporal profiles and cross-reference files for representing baseline EGU activities in the WRAP states. The RMC worked closely with ERG to refine the cross-references that a ssociate the profiles with actual inventory sources. For additional information on the deve lopment and application of these profiles, refer to Fields et al. (20 05). Alpine Geophysics, LLC, pr ovided SMOKE-ready temporal profiles and cross-reference files for representing baseline EGU activities for non-WRAP EGUs.

 Pacific shipping: To prepare the new Pacific sh ipping inventories for the Plan02 scenario, these data were converted direc tly to the CMAQ-ready format outside of SMOKE. Inventory data were received as a nnual estimates of criteria pollutants in gridded ASCII files on the WRAP 36-k m model grid. A FORTRAN program was developed to convert these f iles to the SMOKE netCDF format and then apply speciation and temporal adjustments using SMOKE chemical and temporal profiles, respectively, to create gridded, hourly emissions with volatile organic compound (VOC) and PM 2.5 speciation consistent with the rest of the Plan02 emissions. Because SMOKE is not set up to process pre-gridded data, FORTRAN progr ams were developed in -house at the RMC to prepare these data for merging with the rest of the source categories.

 Dust: The fugitive dust inventory for the entire modeling domain was developed by extracting these sources, based on SCCs, from the stationary-area inventories. A list of the sources defined as fugitive dust is provi ded in U.S. EPA (2004b). Explicit road dust inventories were received for most of th e WRAP states; for California, the non-WRAP states, and the non-U.S. sources, the road dus t inventory was built by extracting the paved and unpaved road dust SCCs from the sta tionary-area inventor y. After building thefugitive and road dust inventories, these data were prepared for the Plan02 emissions modeling by applying transport factors to these data and re-adj usting the inventory PM 2.5 /PM 10 ratios. To apply the transport factors recommended by EPA (2006), a SMOKE control file (GCNTL) that contains scalars by SCC and location codes was used. The new, adjusted dust invent ories with the factors in the GCNTL file were developed using the SMOKE programs Cntlmat and Grwinven. The RMC developed a Fortran program to reapportion the PM i nventories using the revised PM 2.5 /PM 10 ratios.

 Mexico: Entirely new inventories for the six northe rn states of Mexico for stationary area, stationary point, on-road mobile, and nonroa d mobile sources became available at the conclusion of the Plan02a modeling. ERG, Inc., completed an updated 1999 emissions inventory for northern Mexico (Fields et al., 2006) and delivered these data in early 2006.

Quality Assurance

The quality assurance of the Plan02 emissi ons followed the WRAP emissions modeling QA protocol (Adelman, 2004) and a su ite of graphical summaries. Ta bulated summaries of the input data and SMOKE script settings were used to document the data and configuration of SMOKE for all three Plan02 cases. The graphical QA summar ies include, for all emissions output species that changed from Base02a to Plan02, daily spat ial plots summed across all model layers, daily time-series plots, annual time-se ries plots, and daily vertical profiles. The Plan02a, Plan02b, and Plan02c QA graphics are available on the RMC web site at http://pah.cert.ucr.edu/aqm/308/Plan02a_36.shtml

, http://pah.cert.ucr.edu/aqm/308/qa_plan02b36.shtml , and http://pah.cert.ucr.edu/aqm/308/qa_plan02c36.shtml , respectively.

2018 BASE CASE INVENTORY

The Base18 em ission inventory, which represents emissions forecasted to 2018, was developed to represent baseline future-year emissions pa tterns for use in developing emissions control strategies and then evaluating thei r effects on future-year air quality. The first step in this process is to compare the Base18 future emissions with the Plan02 typical-year em issions. To facilitate direct comparison, the SMOKE configuration be tween the Base18 and Plan02 inventories was normalized as much as possible, varying only the i nventories and ancillary input data. In contrast to the Plan02 cases, the Base18 cases used inve ntories and SMOKE ancillary data that had not previously been used. WRAP inventory cont ractors provided 2018 inve ntories and temporal profiles in SMOKE-ready formats.

The RMC completed two iterations (cases Base18a, b) of the Base18 inventory before settling on a final version for input to CM AQ for visibility modeling. B ecause version A of the Base18 emissions (case Base18a) was developed using da tasets that had never been modeled through SMOKE, encountering multiple errors in the data and incompatibilities between the data and SMOKE was anticipated. As expected, during th e QA of the Base18a emi ssion inventories, the RMC was notified about errors in the 2018 invent ories and other problems in the modeling ofthese data were also discovered. After receiving co rrected inventories and fixing the errors in the modeling, version B of the Base 2018 emissi on inventory (Base18b) was developed.

The Base18 emissions were derived from invent ory data projected fr om 2002 to 2018 by WRAP inventory contractors, the RMC, and WRAP and other RPOs. For most inventory sectors, the Base18 input datasets were developed by combining (1) 2018 inventories from inventory contractors both within and outsi de of the WRAP region and (2 ) 2018 inventories developed at the WRAP RMC by applying projecti on factors to the Plan02 inventories. Exceptions to this procedure were the fire inventories, non-U.S. sources, WRAP ammonia, Pacific shipping, and most of the MRPO sources; these were all kept the same as in the Plan02 inventories. The majority of the emissions sectors used temporal, sp atial, and chemical prof iles that are consistent with the Plan02 scenario. Details on the diffe rences between the two Base18 cases follow.

Base18a

The RMC created case B ase18a from a combination of U.S. baseline fire inventories; 2018 stationary area, point, and mob ile inventories; and 2002 inventor ies for MRPO sources, non-U.S. sources, NH 3 emissions in the WRAP region, and P acific shipping emissions. For the WRAP, VISTAS, and MANE-VU states, 20 18 inventories were received for stationary area, point, onroad mobile and off-road mobile sources. For th e CENRAP states, projection factors to “grow” the Plan02 inventories to 2018 were provide d. Although a few emission source categories constant with respect to the Plan02 emissions —primarily due to the lack of either 2018 inventories or projection information for th ese sources—most of the inventories used for Base18a emissions simulation were new and developed by th e RPOs specifically for 2018 modeling.

The following data, by source category, were us ed to develop the case Base18a simulation:

 Stationary Area Sources: 2018 inventories for WRAP, MANE-VU, and VISTAS; 2018 projection factors (growth and control) applied to the Pla n02 inventories for MRPO and CENRAP; Mexico and Canada he ld constant with Plan02a.

 Fugitive and Road Dust Sources: 2018 inventories for WRAP, MANE-VU, and VISTAS; 2018 growth factors applied to the Plan02 inventories for CENRAP; MRPO, Mexico, and Canada held constant with Plan02a.

 Windblown Dust Sources: The entire domain held constant with Plan02a.

 Agricultural and Animal Ammonia Sources: WRAP, MANE-VU, VISTAS, Mexico, and Canada held constant with Plan02a; 2018 growth factors applied to the Plan02a inventories for CENRAP and MRPO.

 Stationary Point Sources: 2018 inventories for WRAP, MANE-VU, and VISTAS; 2018 projection factors (growth and control) applied to the Pl an02 inventories for CENRAP; MRPO, Mexico, and Canada held constant wi th Plan02a; updated temporal profiles for all non-WRAP EGU sources, as developed from the IPM for 2018 emissions. Fire Sources: Baseline inventories for WRAP, CE NRAP, and VISTAS; these emissions were held constant with Plan02a.

 On-road Mobile Sources: 2018 inventories for WRAP, CENRAP, VISTAS, and MANEVU; MRPO, Mexico, and Canada held constant with Plan02a. As with the Base02 and Plan02 inventories, WRAP, Mexico, and Canada use pre-computed emissions inventories; the rest of th e U.S. sources use on-road mobile activity inventories.

 Non-road Mobile Sources: 2018 inventories for WRAP , CENRAP, VISTAS, and MANE-VU; MRPO, Mexico, and Canada held constant with Plan02a.

 Oil and Gas Sources: 2018 inventories for WRAP states only.

 Pacific Marine Shipping Sources: Held constant with Plan02a.

 Gulf of Mexico Offshore Area and Point Sources: 2018 growth factors applied to the Plan02a inventories.

The inventory updates were combined with the Pl an02a emission inventories for the sources that did not change to create case Base18a.

Base18b

The RMC created case B ase18b to correct errors discovered in the Base18a emissions and to include inventory updates that we re received after beginning th e Base18a emissions simulation. These updates affected emissions both within and outside of the WRAP region. The WRAP updates included corrections to the stationary point inve ntory, revisions to the PM 2.5 emissions from fugitive and road dust sources, and upda tes to the fire emissions. The non-WRAP updates included the creation of new 2018 inventories fo r CENRAP and MRPO states with revised projection factors; fixing an erro r in the on-road mobile emissions for non-WRAP U.S. sources; replacing the temporal profiles for EGU sources in the VISTAS, MANE-VU, and MRPO states; and revisions to the PM 2.5 emissions from fugitive and road dust sources throughout the entire 36-km modeling domain. These revisi ons are all discussed below.

For the WRAP states and tribal la nds, four major correct ions were applied to the inventories and emissions inputs for modeling sour ces to create case Base18b:

 ERG, Inc., the WRAP inventory contractor that prepared the WRAP 2018 stationary point inventory, noted corrections to appl y to the Base18a inventory. They provided incremental updates to apply to a group of sources in the WRAP 2018 inventory.

 The expanded list of dust sources, descri bed in Mansell, 2006, and also under the documentation regarding fugitive dust sources, was used to develop the Base18b dust inventories. This change impacted both the dus t and stationary-area-source inventories.

 On-shore and near-shore ma rine shipping sources were added for Washington and Oregon in case Base18b to correct the omission of these sources in Base18a. The WRAP inventories for prescribed and ag ricultural fires were updated, and errors corrected in the application of temporal and speciation pr ofiles for non-Federal rangeland prescribed fires.

o Air Sciences, Inc., provided revisions to the Phase III prescribed and agricultural fire inventories to estimate the emissions reductions from applying fire emissions reduction techniques (ERTs) to controllable fire emissions (Randall, 2006). They based the revised emissions on the same data that the RMC used in case Plan02b to illustrate the changes that resulted fr om controlling prescribed and agricultural fires between the Plan02b and Base18b cases.

o The temporal and speciation profiles th at applied to the non-Federal rangeland prescribed fires were corrected. By not adding the SCC for this source to the input cross-reference files in the Plan 02 scenario and Base18a case, default temporal and speciation profiles were mist akenly applied to these emissions.
For the non-WRAP areas of the modeling domain, f our major corrections to the inventories and emissions inputs for modeling sources were a pplied to prepare the case Base18b emissions inventories:

 Updated projection factors for the CENR AP and MRPO inventories to correct inconsistencies in their file formats with the IDA-formatted inventories were incorporated in the SMOKE modeling. Corrected projection da ta was received from CENRAP to apply to the CENRAP and MRPO stationary area, fugitive and road dust, agricultural and animal ammonia, and stati onary point inventories.

 An error discovered in modeling of the 2018 on-road mobile activity inventories was corrected. By not resetting the SMOKE em issions factor year from 2002 to 2018, the correct emissions factors were not applie d to the non-WRAP U.S. on-road mobile emissions. This problem was corrected by setting up SMOKE to use 2018 emissions factors.

 Similar to the problems encountered in the Plan02 modeling, it was discovered that the IPM-derived temporal profiles used in case Base18a for the non-WRAP stationary point sources produced emissions estimates that appeared unreasonably high, relative to the Plan02b emissions. The IPM-derived temporal profiles were replaced with baseline CEM temporal profiles calculated as 2000-2003 activity averages for the VISTAS states, and with actual 2002 CEM-derived temporal pr ofiles for the CENRAP, MANE-VU, and MRPO states.

 The expanded list of fugitive dust sources was used to develop the Base18b dust inventories. As with the WRAP states, this change impacted both th e dust and stationaryarea-source inventories.

These inventory updates were combined with th e unaffected sources from Base18a to produce case Base18b.

Base18 Inventory Data Collection and PreparationThe data collection procedures for the devel opment of the Plan02 emission inventories are described in this section. A disc ussion of the sources of all in ventory and ancillary data that changed between the Plan02 scenario and the Ba se18 inventories is provided. The RMC worked with emissions inventory contract ors, WRAP and other RPOs, and EP A to collect all of the data used to create the Base18 emissions inputs for SMOKE.

For the WRAP state and tribal inventories, Air Sc iences, Inc., provided all fire inventories; ERG, Inc., provided all stationary area and stationary point inventories and temporal profiles; and ENVIRON provided all mobile, oil a nd gas, and Pacific shipping inve ntories that we used in the Base18 scenario. Alpine Geophysic s, LLC, provided all inventorie s and ancillary data for the VISTAS states and tribes. CE NRAP provided the 2018 projection factors for the CENRAP and MRPO states and tribes. The Mid-Atlantic Re gional Air Management Association (MARAMA) provided 2018 inventories for the MANE-VU states and tribes. Data from the Plan02 inventory were used for Mexico and Canada emissions. A ll emissions data were received electronically; the inventories in SMOKE-ready IDA format and the ancillary data as SMOKE-ready ASCII files.

To prepare the 2018 emissions data for SMOKE, th ese inventories were reorganized to conform to the list of sources modeled in the Plan02 scen ario. Most of this reorganization affected the stationary-area-source in ventory. 2018 inventories were prep ared for SMOKE modeling in the following ways:

 Apply projection factors to applicab le CENRAP and MRPO inventories.

 Extract fugitive and road dust sources from the stationary-area inve ntories to separate inventory files. Apply tran sport factors and revised PM 2.5 /PM 10 splits to these sources.

 Extract WRAP oil and gas sources from the stationary-area invent ories to separate inventory files.

 Extract refueling emissions from the non-WR AP U.S. off-road mobile inventory and discard; these sources are covered in the on-road mobile emissions.

 Split the fire inventories from annual to monthly files.

 For case Base18b, update the stationary-point inventories based on information provided by ERG, Inc.

Quality Assurance

The quality assurance of the Base18 emissi ons followed the WRAP emissions modeling QA protocol (Adelman, 2004) and a su ite of graphical summaries. Ta bulated summaries of the input data and SMOKE script settings were used to document the data and configuration of SMOKE for Base18a and Base18b. The graphical QA summarie s include, for all emissions output species that changed from Plan02a to Base18, daily sp atial plots summed across all model layers, daily time-series plots, annual time-se ries plots, and daily vertical profiles. The Base18a and Base18b QA graphics are available on the RMC web site athttp://pah.cert.ucr.edu/aqm/308/Base18a_36.shtml and http://pah.cert.ucr.edu/aqm/308/qa_base18b36.shtml , respectively.