WRAP Regional Modeling Center - Simulation Specifications

Scenario Name: 2018 Preliminary Reasonable Progress Simulation version B

RMC Code: “PRP18b”

Date Specifications Prepared: 4/29/2009, revised August 11, 2009

Time Window for Modeling/Analysis:

 Emissions modeling April 27 to May 15, 2009

 Air quality modeling May 15 to June 15, 2009

 Analysis results June 24, 2009

 All PRP18b files to TSS July 2009

Description: 2018 Annual 36-km CMAQ air quality model simulation using PRP18b future year emissions, consisting of selected updates from PRP18a.

Purpose/Objective: Evaluate the regional haze air quality for future year 2018 conditions with all known and expected controls on land-based emissions sources as of March 2009. Provide predicted 2018 future year air quality and visibility conditi ons in the Western Class I areas for 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 modeli ng results and analyses a nd aid in summarizing and interpreting the simulation results. For the present simulation these would include:

 Standard displays of spatial distribution of concentr ations of relevant polluta nts (Sulfate, Nitrate, PM, OC, EC, etc..) for various temporal periods (daily, monthly, seas onal and annual totals)

 Spatial plots of differences between 2002 Plan Vers ion D and PRP18b, as well as between PRP18a and PRP18b model predictions

 Stacked-bar charts of contributions to light extinc tion 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://newpah.cert.ucr.edu/aqm/308/qa_prp18b36.shtml

The following 2009 updates for PRP18b include:

 Update of California 2018 on-road and non-road emission inventories PDF

 Update of 2018 locomotive emissions PDF

 Update of WRAP 2018 stationa ry point source emissions PDF

 Update of WRAP 2018 area source emissions PDF

 Mexico 2018 projections PDF2 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 NH 3 from WRAP NH 3 model

o Ontario, Canada point fires

 From Plan02a

o WRAP baseline wildfires

o WRAP baseline wildland fire use

o Offshore commercial shipping: no change (see Plan02a) The effect of changing the Eastern Pacific emissions to 2018 projections will be an alyzed in the PRP18cmv sensitivity modeling scenario

 From Base18a:

o WRAP (except California) non-road mobile (annua l and seasonal)

 From Base18b:

o CENRAP on-road mobile

o WRAP baseline prescribed fire s (natural and anthropogenic)

o WRAP baseline agricultural fires

o WRAP baseline non-feder al rangeland fires

 From PRP18a:

o Non-WRAP stationary area

o Non-WRAP stationary point

o Non-WRAP mobile sources (on-road & off-road)

o WRAP Oil & Gas

o Fugitive dust

o CENRAP & VISTAS point fires

o Offshore Area, Gulf of Mexico

o Gridded Offshore Shipping (Gulf of Mexico and Atlantic: Corbet /ENVIRON inventory)

o Canada - 2020 inventory

o Mexico – Road dust extracted from Phase II area inventory and had tran sport factors applied.

The following emission updates we re included in simulation P RP18b:

 Stationary Area

o WRAP: Updated 2018 inventory

o Mexico: Phase III inventory a nd updates to gridding data

 Non-road Mobile

o WRAP: Updated 2018 inventory for California

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

 On-road Mobile

o WRAP: Updated 2018 inventory for California

o Mexico: Phase III inventory a nd updates to gridding data

 Fugitive Dust

o WRAP: Extracted from Updated 2018 st ationary area source inventory

o Mexico: Extracted from Phase III inventory

 Stationary Point

o WRAP: Updated 2018 inventory

o VISTAS: Updated 2018 Best & Final inventory3 o Mexico: Phase III inventory

 Documentation on input data, mode l settings, and modeling/QA pro cedures provided through standard reporting products: PRP18b_Inventory_summary_v{mmddyy}.xls

o Simulation schedule and input files

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

Other Inputs and Model Settings

 Initial and Boundary Conditions base d on natural GEOS-CHEM simulation

 Model version, settings and confi guration same as for 2002 Plan B

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

Results:

Summary tables and maps
Table 1. PRP18b annual emissions summary by regions (tons/yr)

Region CO NOX VOC NH3 SO2 PM10 PM2

_ 5 PMC
US 90741069 12745979 66309558 5368193 7845370 15989089 5029158 11015336 WRAP 23948636 2873849 22257586 943731 683989 4981494 1620019 3392036 CENRAP 20167299 3713812 16034674 2423559 2232321 7157076 1783387 3551486 VISTAS 23246332 2828046 18784889 792822 2165368 2309828 917211 1325749 MWRPO 11298046 1704809 4716975 789173 1794155 664226 343924 201263 MANE-VU 11917915 1285561 4402945 418907 925065 871886 360126 493440 Canada 12346108 2175237 21050573 428767 2173766 3475854 887462 2588666 Mexico 9793174 2209114 15252537 814815 3244297 1337612 751393 590409 Pacific Shipping 40868 524797 367468 149 280561 36352 35220 1132 Atlantic/Gulf Shipping 30158 571769 12587 108 229651 63726 62756 971
Total 203529605 30632973 169189793 11980224 21574544 36887143 11790656 23160487

Table 2. PRP18b WRAP total annual emissions by sector (tons/yr)
Sector CO NOX VOC NH3 SO2 PM10 PM2

_ 5 PMC
Fires 8928013 202217 436714 45263 53856 726518 627618 119796 Area 1386853 290874 1830236 25387 108274 233469 205202 28306 Point 714163 811324 300509 11564 512467 196677 59046 147229 Non Road 4520104 557423 332659 922 3186 35095 31673 3442 Onroad 5706430 533287 410149 43339 6116 38603 25509 13094 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 1099367 166474 932901 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 **23989504 3398646**  **22625055 943880**  **964550 5017846**  **1655240 3393168** 4 Discussion:

Emissions Summary

The objective of emissions simulatio n PRP18b was to incorporate emi ssions inventory updates completed during 2009 by WRAP contractors to crea te a new future year, annual 36-km grid resolution emissions dataset for air quality modeling. As summarized in the Input Data/Emissions secti on of this specification sheet, we received updated 2018 PRP inventories (for selected source categories – s ee above) for the WRAP states. We also obtained updated 2018 inventories for the VISTAS states, year 2020 inventorie s for Canada and new 2018 national inventories for Mexico (Phase III). We combin ed these updated inventory data with existing emissions data from the PRP18a emissions scenario to deve lop the PRP18b emissions. We will summarize simulation PRP18b by RPO, Canada, and Mexico in terms of new inventories, emissi ons data and modeling corrections, and emissions that we reused from previous simulations . Tables 1 and 2 summarize the annual emissions totals for simulation PRP18b for the different regions of the modeling domain and for the different inventory sectors within the WRAP region, resp ectively. 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 in cluded 2018 PRP inventories for the stationary area, stationary point, on -road mobile, and non-road mobile sectors. We extracted fugitive dust PM emissions sources from the stationary area inventory using the lis t of sources consistent with simulation PRP18a (originally developed during Base18b modeling). The changes to the WRAP stationary area inventory impacted only some of the states in the region. The states imp acted by this inventory update included California, Idaho, Nevada, South Dakota, and Washington. The WRAP stationary point invent ory update impacted all 13 states and some of the Tribes. The on-road mobile updates only impacted Califo rnia and the non-road mobile updates impacted all of the states in the WR AP region. The rest of the inventory sectors in the WRAP region remained unchanged in simulation PRP18b relative to PRP18a. We also updated the emissions data for the VISTAS RPO in simulation PRP18b.

We incorporated an updated 2018 stati onary point inventory for the VISTAS states in simulation PRP18b. We used the 2018 best & final inventory from the VISTAS RPO as a replacement to th e 2018 point inventory that we used in simulation PRP18a. We did not make changes to any of the other U.S. inventories outside of the WRAP and VISTAS regions in si mulation PRP18b. In addition to the WRAP and VISTAS updates, we included new 2018 Mexican invent ories in simulation PRP18b.

We updated the Mexico inventories in simulation PRP 18b with the Phase III 2018 inventory produced by ERG, Inc. The Phase III 2018 Mexico invent ory replaced the 1999 Mexican inventor ies that we used in simulation PRP18a. The Phase III inventories cover the entire country for all emissions se ctors. We worked with ERG, Inc. to reconcile state/county coding chan ges in the 2018 Phase III inventory wi th the spatial surrogates that we developed for Mexico during the PRP18a modeling. In stead of including new muni cipalities in the 2018 Phase III inventory, ERG added the emissions for these new areas back into the municipali ties used in the Phase III 1999 inventory. We prepared the fugitive dust inventor ies from Mexico through the application of revised PM 10 /PM 2.5 ratios and vegetative s cavenging reduction factors in a manner c onsistent with the U.S. inventories. As the 2018 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 inventory sources for Canada, as well as the domain-wide biogenic emissions did not change in simulation PRP18b.

Overall the WRAP emissions on an annua l basis (annual totals for all WRAP states) decreased for all inventory pollutants, with the exception of CO, for simulati on PRP18b relative to simula tion PRP18a. The largest reductions for the PM pollutants came from the non-road mobile and fugitive dust/stationary area sectors. Increases in PM emissions from the on-road mobile a nd stationary point sectors slightly offset the PM5 emissions reductions in PRP18b. The NO x emissions reductions in simulati on PRP18b relative to PRP18a were driven by the stationary poi nt sector, with smaller reductions from non-road mobile and stationary area. The only sector that exhibited NO x increases in comparing these two simula tions was the on-road mobile sector. The SO 2 reductions in simulation PRP18b rela tive to PRP18a were driven primar ily by the stationary point sector with smaller reductions in the stationary area and non-road mobile sectors. There was a small offsetting increase in SO 2 emissions from the on-road mobile sector. S imulation PRP18b included only reductions in NH 3 emissions relative to simulation PRP18a and these were the result of changes primar ily in the on-road mobile sector. Smaller NH 3 reductions occurred in the st ationary point, non-road mobile, and stationary area sectors. The stationary area sector contri buted the only VOC reduction, which was offset by smaller increases in VOC emissions from the on-road mobile, non-road mobile, and st ationary point sectors. A relatively large increase in CO emissions from non-road mobile sources was offset by smaller decreases in the stationary area, stationary point, and on-road mobile sectors.

Relative to simulation Plan02d, the PRP 18b WRAP emissions decreased for PM 2.5 , NO x , SO 2 , NH 3 and CO and increased for PMC, PM 10 , and VOC. The PM 2.5 reductions were driven by the on-road mobile, non-road mobile, and stationary point sectors and offset by increases in the stationary area, road dust and fugitive dust sectors. The largest increase in PM 2.5 is from the fugitive dust sector and reflects the expanded list of dust sources that we applied after simulation Plan02d. The NO x emissions decreased as a result of the on-road mobile, non-road mobile, and stationary point sectors. Th ese decreases were offset slightly by NO x increases in the stationary area and oil and gas sectors. The SO 2 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, non-road mobile, and oil and gas sectors. PMC and PM 10 increased in simulation PRP18b relative to Plan02d primarily because of the fugitive dust and road dust sector s. The only major offset to these increases were reductions in PMC and PM 10 emissions from non-road mobile sources. Decreases in NH 3 emissions were driven by the on-road mobile sector. La rge increases in VOC emissions from the oil and gas and stationary area sectors were offset by smaller decreases in the on-ro ad and non-road mobile sectors.

Visibility Modeling Results

The objective of the PRP18b simulation was to evaluate the regional haze air qua lity 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 PRP18b case includes new updates to the emissions comple ted after the PRP18a simulation, as described above. The PRP18b case is designed to be compared to the 2002 Plan Case Version D (Plan02d) to evaluate changes in model simulated visibility from 2002 to 2018. The PR P18b case will also be compared to the PRP18cmv simulation.

Relevant Output Products

Analysis products for the comparison of the PRP18b simulation to the Plan02d si mulation can be found at: http://pah.cert.ucr.edu/aqm/308/cmaq.shtml# prp18bvsplan02d

 Relevant model output products include daily and monthly 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 b een compared with and 2002 Planni ng (Plan02d) simulation to evaluate changes in model simulated visibi lity using both spatial plots of the differences between the two simulations for each PM species;, and

 On the WRAP TSS , the Visibility Projections tool displays the model-based projected 2018 visibility results using Relative Response Factors from IM PROVE monitoring data. To use this tool, 1) Click the6 TSS link above, 2) Select a site(s), 3) Click th e "Modeling" button below th e map, and 4) Select the "Visibility Projections" link.

Summary of Key Findings

To evaluate seasonal differences in the comparison of PRP18b to Plan02d, we pr epared plots of monthly average changes in concentrations fo r ozone and each of the PM species. Pl ots for all 12 months are available on the RMC webpage (see: http://pah.cert.ucr.edu/aqm/30 8/cmaq.shtml#prp18bvsplan02d ) but we present summary results here for the months of January and Ju ly. These months were sele cted because the largest variation in model results is typi cally between the winter and summer months. Figures 1 through 4 show the monthly average model concentrations of the PM species for the PRP18b case relative to the Plan02d case.

Figure 1 (top) shows the changes in sulfate for January and July. The largest change was caused by updates to the Mexican SOx emissions inventory, with large reductions in sulfate in the Baja California area and large increases in sulfate in northern Mexi co and southern Texas. Overall, there was a mixed response in sulfate concentration in the WRAP states in January, and there was a reduction in sulfate in the WRAP states in July. The annual average change in sulfat e in Figure 5 shows that there was a reduction in sulfate in the PRP18b simulation compared to Plan02d.

Figure 1 (bottom) shows the change in nitrate for January and July. There we re reductions in nitrate in most of the WRAP region throughout the year, due largely to la rge reductions in NOx emissions in the PRP18b mobile source inventory. The PRP18b point inve ntory had reductions in NOx emissions in some areas and increases in other areas, and Figure 2 shows small increases for PRP18b compared to Plan02d nitrate in parts of Nevada and Arizona in January. The reductions in nitrate in PRP18b were largest in the winter months because nitrate concentrations are much larger in th e winter than in the summer months.

Figure 2 (top) shows that there were mostly reducti ons in ammonium concentra tion in PRP18b compared to Plan02d, consistent with the large reduc tions in nitrate. There were some areas, mostly in Mexico and Texas, where ammonium increased in PRP18b because of the increases in sulfate in PROP18b compared to Plan02d.

Figure 2 (bottom) shows the change in ozone in PR P18b compared to Plan02d for January and July. During January, PRP18b had higher ozone concentration in ur ban influenced areas because of the reduced NOx emissions in PRP18b. During winter months, high NOx concentrations mostly acts to titrate ozone, so reductions in NOx cause increases in ozone in winter months. However, th e ozone concentrations are usually low during the winter and exceedences of the oz one NAAQS are rare. During July, the PRP18b NOx reductions cause significant reductions of ozone in the WRAP region with the largest reductions, up to 8 ppb for the monthly average, occurring in California’s central valley.

Figure 3 (top) shows the change in elemental carbon (E C) in PRP18b compared to Plan02d for January and July. EC concentrations were reduced in the WRAP region throughout the year in PRP18b, in part due to reductions in mobile source emissions. Reductions were larger in the winter months, as much a 2 ug/m3 in December compared with smaller reductions of up to 1 ug/ m3 in July, because of less vertical mixing in the winter months. Figure 3 (bottom) shows changes in organic carbon (OC) in PRP18b compared to Plan02d for January and July. There were mostly reductions in OC in PRP18b compared to Plan 02d, with the exception of increases in OC in both the Seat tle and Phoenix areas in PRP18b.

Figure 4 (top) shows the change in total PM2.5 in PRP18b compared to Pl an02d for January and July. PM2.5 represents the sum of the changes in the speciated PM results shown in Figure 1 through 3. The largest reductions in PM2.5 were in January in California, as large as 6 ug/m 3 , because of large reductions there in nitrate, ammonium and EC from the updated mobile s ource inventory in PRP18b. The magnitude of the reductions in PM2.5 for PRP18b were smaller in the summ er months in California, but reduction extended over7 a much larger area, including the mountain states, because of reductions in sulfate, ammonium and EC in those areas for the PRP18b simulation.

Figure 4 (bottom) shows the change in total coarse matter (CM) in PRP18b compared to Plan02d for January and July. There were mostly increases in CM associat ed with urban areas in PR P18b, with the exception of Clark County, NV, were there were large reductions in CM.Figure 1. Top panels shows change in monthly average sulfate concentration for th e PRP18b compared to the Plan02d CMAQ simulations for January (left) and July (ri ght). Bottom panels show change nitrate for the same periods.

8Figure 2. Top panels shows change in monthly average ammonium (NH4) concentration for the PRP18b compared to the Plan02d CMAQ simulations for January (lef t) and July (right). Bottom panels show change in ozone for the same periods.

9Figure 3. Top panels shows change in monthly averag e elemental carbon (EC) c oncentration for the PRP18b compared to the Plan02d CMAQ simulations for January (lef t) and July (right). Bottom panels show change in organic carbon aerosols.

10Figure 4. Top panels shows change in monthly averag e total PM2.5 concentration fo r the PRP18b compared to the Plan02d CMAQ simulations for January (l eft) and July (right). Bottom pane ls show change in coarse matter.

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