WRAP Regional Modeling Center - Simulation Specific ations

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 usin g PRP18b future year emissions, consisting of selected updates from PRP18a.

Purpose/Objective: Evaluate the regional haze air quality for future y ear 2018 conditions with all known and expected controls on land-based emissions sources a s of March 2009. Provide predicted 2018 future yea r air quality and visibility conditions in the Western Cl ass I areas for regional haze plans.

Expected Analysis Methods: Specific analysis methods will generally be deter mined based on the nature of the simulation and the stated purpose and objective s. These typically involve a number of standard po stprocessing products used to elucidate relevant mode ling results and analyses and aid in summarizing an d interpreting the simulation results. For the prese nt simulation these would include:

• Standard displays of spatial distribution of concen trations 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 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 qualit y 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.shtm l

The following 2009 updates for PRP18b include:

• Update of California 2018 on-road and non-road emis sion inventories PDF

• Update of 2018 locomotive emissions PDF

• Update of WRAP 2018 stationary point source emissio ns PDF

• Update of WRAP 2018 area source emissions PDF

• Mexico 2018 projections PDF2

The following emissions data did not change from pr evious simulations:

• From Base02a

o BEIS3 biogenic emissions (includes soil NO)

o Windblown fugitive PM dust emissions – all componen ts 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 Plan02 a) The effect of changing the Eastern Pacific emissions to 2018 projections will be analy zed in the PRP18cmv sensitivity modeling

scenario

• From Base18a:

o WRAP (except California) non-road mobile (annual an d seasonal)

• From Base18b:

o CENRAP on-road mobile

o WRAP baseline prescribed fires (natural and anthrop ogenic)

o WRAP baseline agricultural fires

o WRAP baseline non-federal 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 Atlan tic: Corbet/ENVIRON inventory)

o Canada - 2020 inventory

o Mexico – Road dust extracted from Phase II area inv entory and had transport factors applied.

The following emission updates were included in sim ulation PRP18b:

• Stationary Area

o WRAP: Updated 2018 inventory

o Mexico: Phase III inventory and updates to gridding data

• Non-road Mobile

o WRAP: Updated 2018 inventory for California

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

• On-road Mobile

o WRAP: Updated 2018 inventory for California

o Mexico: Phase III inventory and updates to gridding data

• Fugitive Dust

o WRAP: Extracted from Updated 2018 stationary area s ource 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, model settings, and mo deling/QA procedures provided through standard reporting products: PRP18b_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 GE OS-CHEM simulation

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

• Time period simulated – annual, typical year, meteo rology 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 sect or (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 33931684 Discussion:

Emissions Summary

The objective of emissions simulation PRP18b was to incorporate emissions inventory updates completed during 2009 by WRAP contractors to create a new fut ure year, annual 36-km grid resolution emissions da taset for air quality modeling. As summarized in the Inpu t Data/Emissions section of this specification shee t, we received updated 2018 PRP inventories (for selected source categories – see above) for the WRAP states . We also obtained updated 2018 inventories for the VIST AS states, year 2020 inventories for Canada and new 2018 national inventories for Mexico (Phase III). We com bined these updated inventory data with existing em issions data from the PRP18a emissions scenario to develop the PRP18b emissions. We will summarize simulation PRP18b by RPO, Canada, and Mexico in terms of new i nventories, emissions data and modeling corrections

, and emissions that we reused from previous simulati ons. 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, respectively. This section will conclude with a discussion of the overall impa cts of these changes on the emissions modeling results.

The RMC received new data for the WRAP states and t ribes that included 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 inventor y using the list of sources consistent with simulat ion PRP18a (originally developed during Base18b modeling). The changes to the WRAP stationary area inventory impa cted only some of the states in the region. The states impacted by this inventory update included Californ ia, Idaho, Nevada, South Dakota, and Washington. The WRAP sta tionary point inventory update impacted all 13 stat es and some of the Tribes. The on-road mobile updates only impacted California and the non-road mobile up dates impacted all of the states in the WRAP region. The rest of the inventory sectors in the WRAP region re mained unchanged in simulation PRP18b relative to PRP18a. We also updated the emissions data for the VISTAS R PO

in simulation PRP18b.

We incorporated an updated 2018 stationary point in ventory for the VISTAS states in simulation PRP18b. We used the 2018 best & final inventory from the VISTA S RPO as a replacement to the 2018 point inventory that we used in simulation PRP18a. We did not make chang es to any of the other U.S. inventories outside of the WRAP and VISTAS regions in simulation PRP18b. In ad dition to the WRAP and VISTAS updates, we

included new 2018 Mexican inventories in simulation PRP18b.

We updated the Mexico inventories in simulation PRP 18b with the Phase III 2018 inventory produced by E RG, Inc. The Phase III 2018 Mexico inventory replaced t he 1999 Mexican inventories that we used in simulat ion

PRP18a. The Phase III inventories cover the entire country for all emissions sectors. We worked with E RG, Inc. to reconcile state/county coding changes in the 201 8 Phase III inventory with the spatial surrogates t hat we developed for Mexico during the PRP18a modeling. I nstead of including new municipalities in the 2018 Phase III inventory, ERG added the emissions for these ne w areas back into the municipalities used in the Ph ase III 1999 inventory. We prepared the fugitive dust inve ntories from Mexico through the application of revi sed

PM 10 /PM 2.5 ratios and vegetative scavenging reduction factors in a manner consistent with the U.S. inventories. As the 2018 Phase III Mexican inventory did not con tain road dust estimates, we used the same Mexican road dust inventory that we used in all previous modelin g runs. The inventory sources for Canada, as well a s the domain-wide biogenic emissions did not change in si mulation PRP18b.

Overall the WRAP emissions on an annual basis (annu al totals for all WRAP states) decreased for all in ventory pollutants, with the exception of CO, for simulatio n PRP18b relative to simulation PRP18a. The largest reductions for the PM pollutants came from the non- road mobile and fugitive dust/stationary area secto rs. 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 simulation PRP18b relative to PRP18a were driven by the stationary point sector, with smaller reductions from non-road mobile and stationary are a. The only sector that exhibited NO

x increases in comparing these two simulations was t he on-road mobile sector. The

SO 2 reductions in simulation PRP18b relative to PRP18a were driven primarily by the stationary point sect or with smaller reductions in the stationary area and non-road mobile sectors. There was a small offsett ing

increase in SO 2 emissions from the on-road mobile sector. Simulati on PRP18b included only reductions in NH 3 emissions relative to simulation PRP18a and these w ere the result of changes primarily in the on-road mobile

sector. Smaller NH 3 reductions occurred in the stationary point, non-r oad mobile, and stationary area sectors. The stationary area sector contributed the only VOC reduction, which was offset by smaller increases i n VOC emissions from the on-road mobile, non-road mobile, and stationary point sectors. A relatively large i ncrease in

CO emissions from non-road mobile sources was offse t by smaller decreases in the stationary area, stat ionary point, and on-road mobile sectors.

Relative to simulation Plan02d, the PRP18b WRAP emi ssions 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 increase s in the stationary area, road dust and fugitive du st 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 mob ile, non-road mobile, and stationary point sectors. These decreas es 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-roa d mobile, and non-road mobile sectors. A large CO reduction in the on-road mobile sector was offset by increases in the stati onary 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 fugiti ve dust and road dust sectors. The only major offse t 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. Large increases in VOC emissions from the oil and gas and stationary area sectors were offset by smaller decr eases in the on-road and non-road mobile sectors.

Visibility Modeling Results

The objective of the PRP18b simulation was to eval uate 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 Wester n Class I areas for December 2007 regional haze pla ns. The PRP18b case includes new updates to the emissions c ompleted after the PRP18a simulation, as described above. The PRP18b case is designed to be compared to the 2 002 Plan Case Version D (Plan02d) to evaluate chang es in model simulated visibility from 2002 to 2018. The P RP18b case will also be compared to the PRP18cmv

simulation.

Relevant Output Products

Analysis products for the comparison of the PRP18b simulation to the Plan02d simulation can be found a t: http://pah.cert.ucr.edu/aqm/308/cmaq.shtml#prp18bvs plan02d

• Relevant model output products include daily and mo nthly spatial distributions of Regional Haze contributing pollutants;

• Model output concentrations will serve as indicatio n of future year 2018 baseline visibility condition s;

• Results of this simulation have been compared with and 2002 Planning (Plan02d) simulation to evaluate changes in model simulated visibility using both sp atial plots of the differences between the two simulations for each PM species;, and

• On the WRAP TSS , the Visibility Projections tool displays the mode l-based projected 2018 visibility results using Relative Response Factors from IMPROV E monitoring data. To use this tool, 1) Click the6

TSS link above, 2) Select a site(s), 3) Click the " Modeling" button below the map, and 4) Select the "Visibility Projections" link.

Summary of Key Findings

To evaluate seasonal differences in the comparison of PRP18b to Plan02d, we prepared plots of monthly average changes in concentrations for ozone and eac h of the PM species. Plots for all 12 months are av ailable on the RMC webpage (see: http://pah.cert.ucr.edu/aqm/308/cmaq.shtml#prp18bvs plan02d ) but we present summary results here for the months of January and July. These months were selected because the larges t variation in model results is typically between the winter and summer months. Figures 1 through 4 show the monthly average model concentrations of the PM spec ies for the PRP18b case relative to the Plan02d cas e.

Figure 1 (top) shows the changes in sulfate for Jan uary and July. The largest change was caused by up dates to the Mexican SOx emissions inventory, with large red uctions in sulfate in the Baja California area and large

increases in sulfate in northern Mexico and souther n Texas. Overall, there was a mixed response in su lfate concentration in the WRAP states in January, and th ere was a reduction in sulfate in the WRAP states i n July. The annual average change in sulfate in Figure 5 sh ows that there was a reduction in sulfate in the PR P18b simulation compared to Plan02d.

Figure 1 (bottom) shows the change in nitrate for J anuary and July. There were reductions in nitrate in most of the WRAP region throughout the year, due largely to large reductions in NOx emissions in the PRP18b mo bile source inventory. The PRP18b point inventory had r eductions in NOx emissions in some areas and increa ses in other areas, and Figure 2 shows small increases for PRP18b compared to Plan02d nitrate in parts of Nev ada and Arizona in January. The reductions in nitrate in PR P18b were largest in the winter months because nitr ate concentrations are much larger in the winter than i n the summer months.

Figure 2 (top) shows that there were mostly reduct ions in ammonium concentration in PRP18b compared t o Plan02d, consistent with the large reductions in ni trate. There were some areas, mostly in Mexico and Texas,

where ammonium increased in PRP18b because of the i ncreases in sulfate in PROP18b compared to Plan02d.

Figure 2 (bottom) shows the change in ozone in PRP1 8b compared to Plan02d for January and July. During January, PRP18b had higher ozone concentration in u rban influenced areas because of the reduced NOx emissions in PRP18b. During winter months, high NO x concentrations mostly acts to titrate ozone, so

reductions in NOx cause increases in ozone in winte r months. However, the ozone concentrations are usu ally low during the winter and exceedences of the ozone 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 cent ral valley.

Figure 3 (top) shows the change in elemental carbon (EC) in PRP18b compared to Plan02d for January and July. EC concentrations were reduced in the WRAP re gion 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 O C in PRP18b compared to Plan02d, with the exception of

increases in OC in both the Seattle and Phoenix are as in PRP18b.

Figure 4 (top) shows the change in total PM2.5 in P RP18b compared to Plan02d for January and July. PM 2.5 represents the sum of the changes in the speciated PM results shown in Figure 1 through 3. The large st 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 so urce inventory in PRP18b. The magnitude of the

reductions in PM2.5 for PRP18b were smaller in the summer months in California, but reduction extended over7 a much larger area, including the mountain states, because of reductions in sulfate, ammonium and EC i n those

areas for the PRP18b simulation.

Figure 4 (bottom) shows the change in total coarse matter (CM) in PRP18b compared to Plan02d for Janua ry and July. There were mostly increases in CM associ ated with urban areas in PRP18b, with the exception of Clark County, NV, were there were large reductions in CM.8 Figure 1. Top panels shows change in monthly avera ge sulfate concentration for the PRP18b compared to the Plan02d CMAQ simulations for January (left) and Jul y (right). Bottom panels show change nitrate for th e same periods.9 Figure 2. Top panels shows change in monthly avera ge ammonium (NH4) concentration for the PRP18b compared to the Plan02d CMAQ simulations for Januar y (left) and July (right). Bottom panels show chang e in ozone for the same periods.10 Figure 3. Top panels shows change in monthly avera ge elemental carbon (EC) concentration for the PRP1 8b compared to the Plan02d CMAQ simulations for Januar y (left) and July (right). Bottom panels show chang e in organic carbon aerosols.11 Figure 4. Top panels shows change in monthly avera ge total PM2.5 concentration for the PRP18b compare d to the Plan02d CMAQ simulations for January (left) and July (right). Bottom panels show change in coarse matter.