WRAP Regional Modeling Center - Simulation Specifications 

Scenario Name: 2018 Preliminary Reasonable Progress Simulation version A 

RMC Code: “PRP18a” 

Date Specifications Prepared: 4/2/2007; Last revised 11/3/2008

Time Window for Modeling/Analysis: 

• Emissions modeling April 2 to May 18, 2007 

• Air quality modeling May 18 to June 1, 2007 

• Analysis results June7, 2007 

• All PRP18a files to TSS June 7, 2007 – critical date

Description: 2018 Annual 36-km CMAQ air quality model simulation using PRP18a future year emissions. 

Purpose/Objective: Evaluate the regional haze air quality for future year 2018 conditions with all known and 

expected controls as of March 2007. Provide predicted 2018 future year air quality and visibility conditions in 

the Western Class I areas for December 2007 regional haze plans.

Expected Analysis Methods: Specific analysis methods will generally be determined based on the nature of 

the simulation and the stated purpose and objectives. These typically involve a number of standard postprocessing products used to elucidate relevant modeling results and analyses and aid in summarizing and 

interpreting the simulation results. For the present simulation these would include: 

• Standard displays of spatial distribution of concentrations of relevant pollutants (Sulfate, Nitrate, PM, 

OC, EC, etc..) for various temporal periods (daily, monthly, seasonal and annual totals) 

• Spatial plots of differences between 2002 Plan Version D and model predictions 

• Stacked-bar charts of contributions to light extinction for the 20% best and 20% worst days at each 

IMPROVE site 

• Output files of SMOKE emissions and CMAQ air quality results to TSS 

• SMOKE reports processed and uploaded to TSS 

Input Data: 

Emissions – emission data and QA found at: http://pah.cert.ucr.edu/aqm/308/qa_prp18a36.shtml

The following emissions data did not change from previous simulations:

• From Base02a 

o BEIS3 biogenic emissions (includes soil NO) 

o Windblown fugitive PM dust emissions – all components from WRAP WB Dust model 

o WRAP NH3 from WRAP NH3 model 

o Ontario, Canada point fires 

o Mexico road dust 

• From Plan02a 
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o Eastern Pacific commercial shipping lanes 

o WRAP baseline wildfires 

o WRAP baseline wildland fire use 

• From Base18a: 

o WRAP non-road mobile (annual and seasonal) 

• From Base18b: 

o CENRAP on-road mobile 

o WRAP baseline prescribed fires (natural and anthropogenic) 

o WRAP baseline agricultural fires 

o WRAP baseline non-federal rangeland fires 

The following emission updates were included in simulation PRP18a:

• Stationary Area 

o WRAP: PRP2018 inventory 

o CENRAP: 2018 inventory version October 16, 2006; included the area fire emissions in the 

stationary area sector (eliminated the area fire sector), using fire inventory data from the 

stationary area inventory, not the area fire inventory; updates to temporal and gridding data for 

fire sources 

o VISTAS: included the area fire emissions in the stationary area sector (eliminated the area fire 

sector); 2018 version G inventory 

o MWRPO: 2018 version K inventory 

o MANE-VU: 2018 version 3 inventory 

o Mexico: Phase III inventory and updates to gridding data 

o Canada: 2020 inventory 

• Non-road Mobile 

o WRAP: no change (see Base18a) 

o CENRAP: new inventories (annual and monthly) 

o VISTAS: 2018 version G inventory (annual) 

o MWRPO: 2018 version K inventory (monthly) 

o MANE-VU: 2018 version 3 inventory (annual) 

o Mexico: Phase III inventory and updates to gridding data (annual) 

o Canada: 2020 inventory (annual) 

• On-road Mobile 

o WRAP: corrected double counting of primary elemental and organic carbon by removing 

process-specific emissions from inventory; otherwise inventory same as in Base18a 

o CENRAP: no change (see Base18b) 

o VISTAS: new 2018 activities and M6 scenario inputs 

o MWRPO: new 2018 activities and M6 scenario inputs 

o MANE-VU: new 2018 activities and M6 scenario inputs 

o Mexico: Phase III inventory and updates to gridding data 

o Canada: 2020 inventory 

• Road Dust (extracted from stationary area inventories) 

o PM2.5/PM10 ratio adjustments and county-level (US)/state-level (Mexico)/provincelevel(Canada) vegetative cover transport factors applied to all dust sources 

o WRAP: corrected dropped PM2.5 from Base18b; affects all PM, including PMC 

o CENRAP: new inventories 

o VISTAS: 2018 version G inventory 

o MWRPO: 2018 version K inventory 
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o MANE-VU: 2018 version 3 inventory 

o Mexico: no change (See Base02a) 

o Canada: 2020 inventory 

• Fugitive Dust 

o PM2.5/PM10 ratio adjustments and county-level (US)/state-level (Mexico)/provincelevel(Canada) vegetative cover transport factors applied to all dust sources 

o WRAP: PRP2018 inventory 

o CENRAP: new inventories 

o VISTAS: 2018 version G inventory 

o MWRPO: 2018 version K inventory 

o MANE-VU: 2018 version 3 inventory 

o Mexico: Phase III inventory and updates to gridding data 

o Canada: 2020 inventory 

• Offshore Area, Gulf of Mexico 

o Removed shipping lane portion of the inventory to keep from double counting with the gridding 

shipping inventory 

o non-shipping emissions the same as Base18b 

• Gridded Offshore Shipping 

o Eastern Pacific: no change (see Plan02a) 

o Gulf of Mexico and Atlantic: Corbet/ENVIRON inventory 

• Point Fires 

o CENRAP: inventories same as Base02a, corrections to speciation profiles 

o VISTAS: 2018 version Base G2 inventory 

• WRAP Oil & Gas 

o PRP2018 inventory 

• Stationary Point 

o WRAP: PRP2018 inventory 

o CENRAP: new inventory 

o VISTAS: 2018 version G inventory 

o MWRPO: 2018 version K inventory 

o MANE-VU: 2018 version 3 inventory 

o Mexico: Phase III inventory 

o Canada: 2020 inventory 

• Documentation on input data, model settings, and modeling/QA procedures provided through standard 

reporting products: PRP18_Inventory_summary_v{mmddyy}.xls

o Simulation schedule and input files 

o Summary of inventory inputs to the simulation with descriptions of the changes to each input 

Other Inputs and Model Settings

• Initial and Boundary Conditions based on natural GEOS-CHEM simulation 

• Model version, settings and configuration same as for 2002 Plan B 

• Time period simulated – annual, typical year, meteorology for 2002 used 

Results: 

Summary tables and maps
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Table 1. PRP18a annual emissions summary by regions 

Region CO NOX VOC NH3 SO2 PM10 PM2_5 PMC 

US 90799132 13963994 66757755 5399684 8563099 16143203 5156474 11032520

Total WRAP 23936606 3535119 22640603 974946 990341 5049001 1666017 3403931 

CENRAP 20167299 3713812 16034674 2423559 2232321 7157086 1783387 3551497 

VISTAS 23286267 2813022 18837483 792990 2347095 2332697 935773 1330056 

MWRPO 11298046 1704809 4716975 789173 1794155 664227 343924 201263 

MANE-VU 11917915 1285561 4402945 418907 925065 871886 360126 493441 

Canada 12346108 2175237 21050573 428767 2173766 3479869 887462 2592703 

Mexico 9742629 1501699 14281680 1438928 1223375 972148 523137 449011 

Pacific 

Shipping 40868 524797 367468 149 280561 36352 35220 1132 

Atlantic/Gulf 

Shipping 30158 571769 12587 108 229651 63726 62756 971 

Total 203565028 31789819 169102744 12667211 20759429 36770194 11754276 23056524

Table 2. PRP18a WRAP total annual emissions by sector 

Sector CO NOX VOC NH3 SO2 PM10 PM2_5 PMC 

Fires 8928013 202217 436714 45263 53856 726518 627618 119796 

Area 1446307 320345 1860528 25430 110772 240738 211012 29765 

Point 752028 895549 299700 14031 535055 190862 58607 132255 

Non Road 4367813 594397 328247 1409 4074 43367 39320 4047 

Onroad 5708505 519090 400626 71408 5933 36368 23618 12749 

Biogenic 2624814 286996 18197340 0 0 0 0 0 

WOG 68260 191728 749979 0 89 0 0 0 

Road Dust 0 0 0 0 0 689599 72821 616779 

Fugitive Dust 0 0 0 0 0 1123032 166125 956919 

Wind-Blown 

Dust 0 0 0 0 0 1962165 431676 1530489 

Offshore 

Platforms 0 0 0 0 0 0 0 0 

Offshore 

Shipping 40868 524797 367468 149 280561 36352 35220 1132 

Ag Ammonia 0 0 0 817256 0 0 0 0 

Total 23936606 3535119 22640603 974946 990341 5049001 1666017 3403931 

Discussion: 

Emissions Summary

The objective of emissions simulation PRP18a was to incorporate new emissions data and corrections to errors 

discovered during the QA/QC of previous WRAP-RMC emissions simulations to create a new future year, 

annual 36-km grid resolution emissions dataset for air quality modeling. As summarized in the Input Data Æ

Emissions section of this specification sheet, we received 2018 PRP inventories for the WRAP states and 

collected updated 2018 inventories for the rest of the U.S. We also obtained year 2020 inventories for Canada 
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and new 1999 national inventories for Mexico. We combined these updated inventory data with both corrected 

and existing emissions data to develop the PRP18a emissions. We will summarize simulation PRP18a by RPO, 

Canada, and Mexico in terms of new inventories, emissions data and modeling corrections, and emissions that 

we reused from previous simulations. This section will conclude with a discussion of the overall impacts of 

these changes on the emissions modeling results. 

The RMC received new data for the WRAP states and tribes that included 2018 PRP inventories for the 

stationary area, stationary point, and oil and gas sectors. We extracted fugitive dust PM emissions sources from 

the stationary area inventory using the list of sources consistent with simulation Base18b. We expanded the list 

of sources in the stationary area inventory that we categorize as fugitive dust between the Plan02b/c series and 

Base18b simulations. The reason for categorizing these emissions as fugitive dust rather than leaving them as 

stationary area sources is to apply revised PM10/PM2.5 ratios and vegetative scavenging reduction factors to the 

PM emissions from dust sources. The result of using the expanded list of fugitive dust emissions sources was an 

increase in the PM emissions in the fugitive dust sector and a decrease in the PM emissions in the stationary 

area sector in simulation PRP18a relative to simulation Plan02c. The net result of the expanded dust list is an 

overall reduction of PM2.5 emissions through the application of scavenging factors to a larger number of 

sources. As with previous simulations the updated oil and gas inventories consisted of both area and point 

sources. The explicit WRAP oil and gas emissions sector contains only the area source oil and gas inventories. 

The point oil and gas sources are contained in the stationary point inventory. The rest of the changes to the 

WRAP emissions in simulation PRP18a resulted from corrections to modeling and data errors discovered since 

the completion of simulation Base18b. 

We corrected errors in the WRAP on-road mobile and road dust sectors that we discovered during the QA of 

simulation Base18b. We found that we were double counting primary elemental and organic carbon emissions 

from brake wear, tire wear, and resting-exhaust on-road mobile emissions processes. The net result of this 

correction was to decrease the PM2.5 emissions, specifically in the form of elemental and organic carbon, from 

the WRAP on-road mobile sources in simulation PRP18a relative to Base18b. We also discovered that we 

inadvertently dropped all PM2.5 from WRAP road dust sources in simulation Base18b. Although the road dust 

inventory technically was not updated for simulation PRP18a, we did experience a net increase in PM2.5

emissions and a decrease in PMC emissions from road dust relative to simulation Base18b after correcting this 

error. The rest of the inventory sectors in the WRAP region remained unchanged in simulation PRP18a relative 

to Base18b and Plan02b/c. We also made several updates and corrections to the emissions data for the other 

RPOs in simulation PRP18a. 

We incorporated updated 2018 inventories and some corrections for all of the other RPOs in simulation 

PRP18a. We updated the stationary area, stationary point, and non-road mobile inventories for all non-WRAP 

RPO’s; we also updated the on-road mobile inventories for all RPOs except CENRAP. As the fugitive dust and 

road dust inventories are derived from the stationary area inventory, the updates to the stationary area 

inventories also impacted these emissions sectors. As with the WRAP inventories, we treated the fugitive and 

road dust inventories explicitly in order to apply revised PM10/PM2.5 ratios and vegetative scavenging reduction 

factors. We selected the fugitive dust sources from the stationary area inventory using the expanded list of 

sources that we applied for the WRAP states. We also eliminated the non-WRAP area-source fire sector, which 

included CENRAP and VISTAS fires that are inventoried at the county-level and get modeled as area sources. 

We folded this category into the stationary area sector for simulation PRP18a. The impetus for this change was 

the discovery that we double counted the area source fire category for the CENRAP states in all previous 

simulations. To maintain consistency with the updated CENRAP 2018 inventories, we discarded the previous 

set of area fire inventories and used the estimates contained in the updated 2018 stationary area inventory for 

these sources. For the point fire category we updated the VISTAS data to a new 2018 inventory and corrected 

errors in the application of speciation profiles to the fires in the CENRAP region. In addition to these updates 

and corrections to sources in the continental U.S., we also included updated the offshore, Canadian, and 

Mexican emissions in simulation PRP18a. 
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We added a new source in commercial shipping lane emissions in the Gulf of Mexico and the Atlantic Ocean 

and updated the Mexico and Canadian inventories in simulation PRP18a. We received a new gridded 

commercial shipping inventory that contained emissions for the Pacific, Gulf of Mexico, and Atlantic. We 

discarded the Pacific shipping lane emissions in this new inventory and combined the Pacific shipping lane 

emissions that we used in the Plan02b/c and Base18b simulations with the Gulf of Mexico and Atlantic 

emissions from the new inventory. With the addition of the shipping lane inventory for the Gulf of Mexico, we 

modified the offshore area source inventory for this region by removing the shipping sources to keep from 

double counting these emissions. Otherwise the Gulf of Mexico area and point source inventories remained 

unchanged. We also removed some shipping sources from the Canadian inventory to keep from double counting 

the offshore shipping emissions in the Pacific. We used new 2020 Canadian inventories for all emissions 

sectors. The Canadian inventories included pre-processed elevated point source emissions prepared by the U.S. 

EPA for the RPO 36-km modeling grid. Finally we used updated Phase III 1999 Mexican inventories that 

covered the entire country for all emissions sectors. Along with the updated inventories we used revised spatial 

surrogates developed from Shapefiles provided by Mexico’s Instituto Nacional de Ecología. We prepared the 

fugitive dust inventories from Canada and Mexico through the application of revised PM10/PM2.5 ratios and 

vegetative scavenging reduction factors in a manner consistent with the U.S. inventories. As the Phase III 

Mexican inventory did not contain road dust estimates, we used the same Mexican road dust inventory that we 

used in all previous modeling runs. The rest of the sources for Mexico and Canada, as well as the domain-wide 

biogenic emissions did not change in simulation PRP18a. 

Overall the WRAP emissions on an annual basis (annual totals for all WRAP states) decreased for all inventory 

pollutants for simulation PRP18a relative to simulation Base18b. The largest reductions for the PM pollutants 

came from the fugitive dust, on-road mobile, and stationary point sectors. The addition of PM2.5 emissions in 

the road dust sector that resulted from correcting the dropped emissions in simulation Base18b was the only 

major offset to the PM2.5 emissions reductions in PRP18a. The NOx emissions reductions in simulation PRP18a 

relative to Base18b were driven by large emissions reductions in the oil and gas sector and smaller reductions in 

the stationary point sector. The only sector that exhibited NOx increases in comparing these two simulations 

was the stationary area sector. The SO2 reductions in simulation PRP18a relative to Base18b were driven 

primarily by the stationary point sector with smaller reductions in the stationary area sector. A small reduction 

in NH3 emissions was the result of changes in the stationary point sector. The oil and gas sector contributed the 

largest VOC reductions, while the reduction of VOC from stationary point sources was all but offset by 

increases in the stationary point sector. Large CO reductions from stationary point sources were offset by 

smaller increases in the stationary area and oil and gas sectors. 

Relative to simulation Plan02c, the PRP18a WRAP emissions decreased for PM2.5, NOx, SO2, and CO and 

increased for PMC, PM10, and VOC. The PM2.5 reductions were driven by the on-road mobile, non-road mobile, 

and stationary area sectors and offset by increases in the stationary point, road dust and fugitive dust sectors. 

The largest increase in PM2.5 is from the fugitive dust sector and reflects the expanded list of dust sources that 

we applied after simulation Plan02c. The NOx emissions decreased as a result of the on-road mobile, non-road 

mobile, and stationary point sectors. These decreases were offset slightly by NOx increases in the stationary area 

and oil and gas sectors. The SO2 reductions were driven by stationary point, on-road mobile, and non-road 

mobile sectors. A large CO reduction in the on-road mobile sector was offset by increases in the stationary area, 

stationary point, on-road mobile, and oil and gas sectors. PMC and PM10 increased in simulation PRP18a 

relative to Plan02c primarily because of the fugitive dust and road dust sectors. The only major offset to these 

increases were reductions in PMC and PM10 emissions from stationary area sources. Increases in NH3 emissions 

were driven by the on-road mobile and stationary point sectors. Large increases in VOC emissions from the oil 

and gas and stationary area sectors were offset by smaller decreases in the on-road and non-road mobile sectors. 
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Visibility Modeling Results 

The objective of the PRP18a simulation was to evaluate the regional haze air quality for future year 2018 

conditions with all known and expected controls as of March 2007 and to provide predicted 2018 future year 

air quality and visibility conditions in the Western Class I areas for December 2007 regional haze plans. The 

PRP18a case should be compared to the 2002 Plan Case Version D (Plan02d) to evaluate changes in model 

simulated visibility from 2002 to 2018.

Relevant Output Products 

Analysis products for the PRP18a simulation can be found at: 

http://pah.cert.ucr.edu/aqm/308/cmaq.shtml#prp18avsplan02d 

• Relevant model output products include daily, seasonal and annual spatial distributions of Regional 

Haze contributing pollutants. 

• Model output concentrations will serve as indication of future year 2018 baseline visibility conditions 

• Results of this simulation have been compared with and 2002 Planning (Plan02d) simulation to evaluate 

changes in model simulated visibility using both spatial plots of the differences between the two 

simulations for each PM species, and as the bar plots of the change in visibility from each PM 

component at the individual monitoring sites Comparisons with other simulations as appropriate 

Summary of Key Findings

Figures 1 through 4 show the annual average model concentrations of the PM species for the PRP18a case in 

the left panels, and the change in concentrations relative to the Plan02d case are shown in the right panels. 

There were small reductions in sulfate in PRP19a and larger reductions in nitrate, ammonium and elemental 

carbon throughout large regions in the WRAP states. Figure 2 shows that there were small reductions in ozone 

of about 1 to 3 ppb though much of the WRAP domain, excluding some major urban areas were low ozone 

levels increased because of reduced NOx emissions and reduced titration of ozone by NO. While the annual 

average plots are useful for summarizing the trends in PM concentrations, there is substantial seasonal 

variability in the results, and monthly average results are also available at the RMC webpage at this ink: 

http://pah.cert.ucr.edu/aqm/308/cmaq.shtml#prp18avsplan02d 

Figure 5 shows an example of a stacked bar plot of the modeled contribution of individual PM species to 

visibility impairment at Rocky Mountain National Park for each day during the PRP18a simulation. Complete 

results for all IMPROVE sites are available at this link: 

http://pah.cert.ucr.edu/aqm/308/results_prp18a_vs_plan02d/visibility/wrap.prp18a_vs_plan02d.IMPRO

VE.aero_bext.pdf

 
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Figure 1. Left panel shows annual average sulfate (top) and nitrate (bottom) CMAQ simulated concentrations 

for Plan02d. Right panel shows the change in concentration for Plan02d minus Plan02c. 
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Figure 2. Left panel shows annual average ammonium (top) and ozone (bottom) CMAQ simulated 

concentrations for Plan02d. Right panel shows the change in concentration for Plan02d minus Plan02c. 
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Figure 3. Left panel shows annual average elemental carbon (top) and organic carbon (bottom) CMAQ 

simulated concentrations for Plan02d. Right panel shows the change in concentration for Plan02d minus 

Plan02c. 
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Figure 4. Left panel shows annual average coarse matter (top) and total PM2.5 (bottom) CMAQ simulated 

concentrations for Plan02d. Right panel shows the change in concentration for Plan02d minus Plan02c. 
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Figure 5. Stacked bar plot showing modeled contribution of individual PM species to visibility impairment at 

Rocky Mountain National Park for each day during the 2018 Preliminary Reasonable Progress simulation.