## TSD-1e



# CM AQ Model Performance and A ssessment 8-Hr OTC O zone Modeling

Bureau of

Air Qualit y Anal ysis a nd Research Division o f Air Reso urces Ne w York State Depart me nt o f Environ me ntal Con servation

Alba ny , NY 12233

February 23, 2006

1

## Air q uality m od el evaluation and as sess me nt One of the tasks that is required as part of demonstra ting attain me nt for the 8-hr ozone N AA QS is the evaluation and as sessment of the air qualit y mode ling sys tem that has been utilized to predict future air qualit y over the region of interest. As part of the attain me nt demonstrat ion, the S MOKE/CMA Q mode ling s ys tem wa s applied to simula te the pollutant

concentra tion fields for the base ye ar 2002 em issions with the corresponding me teorolog ical informa tion. The mode ling databases for met eorolog y u sing M M5 (TSD1a), the em issions using SM OKE (TSD-1b and TSD-1c), and application of C MAQ (TSD-1d) provides simul ated pollutant fields that are comp ared to measure me nts, in order to establish the credibil it y of the simula tion. In the following sections a comparison between the measured

and predicted

concentrat ions is performed and results are presented, demonstra ting on an overall basis the utili t y of the modeling sy ste m in this applica tion. The results presented here should serve a s an illustration of s ome of the evaluat ion and asses sm ent perform ed on the base 2002 CM AQ simula tion. A dditional inform ation can be made availab le b y request from the Ne w York State Departm ent of Environ ment al Conservation. Su m m ar y of

me as ured data The ambi ent air

qualit y data, both gaseous and aerosol species, for the simula tion period of May through Septe mber 2002 were obtained from the following sources:

• EPA A ir Q ualit y S y st em (A QS) • EPA fine particulate S peciation T rends N etwork (STN) • EPA C lean A ir S tatus & T rends N etwork (C ASTNet) • I nteragenc y M onitoring of PR Otected V isual E nvironmen ts (I MPRO VE) • Pinnacle State Park, NY operated by Atmospheric Science Research Center, Universit y at Alban y, Albany , N Y • Harvard Forest, Petersha m, MA operated by Harvard University , Boston, MA • A tmospheric I nvestigation, R egional M odeling, A nal ys is and P rediction (AIRM AP) operated b y

Universit y of Ne w Hampshire, D urha m, NH • N orth E ast O zone & F ine P articl e S tud y ( NE- O PS), led b y Penn State Universit y and other research group s in Philadelphia, P A • Aircraft data obtained b y the U niversit y of Mar yl and, College Park M D • Wet deposition data from the N ational A tmospher ic D eposition P rogram/ N ational T rends N etwork ( NAD P/NTN), A tmospheric I ntegrated R esearch M o nitoring N etwork (AIR MoN), and the N ew Y ork S tate D epart men t of E nvironmen tal C onservation (N YSDEC) Measured data from sites within the Ozone Transport Region (OTR) plus the rest of Virginia were included here. The model- ba sed data w ere obtained at the grid-cell corresponding to the monitor location; no interpolation wa s perform ed.

2

## Ozone (O 3 

## ) Hourly O 3 

## is measured at a large number of State, Local, and National Air Monitoring Stations ( SLAMS/N AMS) across the US on a routine basis, and the data from 208 sites w ere extracted

from the AQ S database ( http:// w w w . ep a. gov/ttn/airs/ai rsaqs/aqs we b/aq s we bho me .ht ml ). Hourly O 3 

## concentrat ions from the Harvard Forest Environ menta l Managem ent Site in Petersham, MA ( htt p://w w w . as .h arvard.edu/data/nigec- data.ht ml ); Pinnacle State Park in Addison, N Y ( http://

w w w . a src.cest m. alban y.ed u ); and the four Universit y of New Hampshire A IRMAP sites (http://a irm ap.unh.edu) were also included in this database. The EPA C ASTNet program collects hourly O 3 

## at generall y rural locations acros s the U S ( http:// w w w . ep a. gov/castnet ); data from 22 sites, including two from West Virginia, were used in the mode l evaluation. Fine particulate mat ter

(PM 2 .5 

## ) The 24-hour average Federal Reference Method (FRM) P M 2. 5 

## mass data collect ed routinel y at SLAM S/NAM S sites acros s the US were extracted from A QS (257 sites). Hourly PM 2 .5 

## mass wa s also included in this database, pri maril y extracted from A QS (54 sites). H ourl y P M 2 .5 

## mass were also taken from the Thompson Farm, N H AIR MAP site, Pinnacle State Park, and the NE-OP S site in Philadelphi a, PA ( htt p://lidar1.e e.psu.edu ). Fine particulate speciation The 24-hour average P M 2. 5 

## and fine particula te speciation (sulfate ( SO 4 

## ), nitrate (NO 3 

## ), elem enta l carbon (EC), organic carbon/organic m ass (OC/OM), and soil/crustal ma tter) from Class I areas across the U S, collec ted ever y 3 rd 

## day , were obtained from the IMPR OVE web site ( htt p://vista.cira. colostate.edu/IMPRO VE /Default.htm ). In addition to these para met ers, the EPA STN ( http:// w w w . ep a. gov/ttn/am tic/speciepg.htm l ) also reports amm on ium (NH 4 

## ) to AQ S; data from this network are collected every 3 rd 

## or 6 th 

## da y. D ata from 49 STN sites, generall y in urban areas and often collocated with FR M moni tors, and 21 IMPR OVE sites (including D oll y Sods, W V) were u sed in this anal y sis. O rganic mass is assumed to equal 1.8× OC, and s oil/crusta l ma tter is as sumed to consist of oxides of Al, Ca, Fe, Si, and Ti. The STN O C data are blank-corrected b y re moving a monitor- s pecific, constant blank, and these values are available from http:// w w w . ep a. gov/airtrends/aqtrnd03/pdf s/2_chem spec0 fp m2 5. pdf ; the IMPR OVE OC blanks are as sumed to equal zero. Criteria gaseous pollutants Hourly carbon monoxide (C O; 97 sites), nitric oxide ( NO; 75 sites), nitrogen dioxide (NO 2 

## ; 97 sites) and s ulfur dioxide ( SO 2 

## ; 134 sites) are also included in this model evaluat ion database. A large majorit y of these sites are SLAMS/N AMS monitors located prim aril y in urban in s uburban areas, but data from the Harvard Forest, Pinnacle State Park, and A IRMA P sites are also included here.

3

## Non-meth ane h yd rocarbons While there are several dozen h yd rocarbon s pecies measured routinel y, for this mode l evaluation database the focu s was on Carbon Bond IV species groups that consist of a single prim ar y species. For this reason only ethene (C 2 

## H 4 

## ), isoprene (C 5 

## H 8 

## ), and forma ldeh yd e ( HCHO) concentrations were extracted from A QS. H ourl y C 2 

## H 4 

## and C 5 

## H 8 

## data from 19 Photoche mic al A sse ssmen t Monitoring Stations (PA MS) sites and 24-hour average HCH O from 18 air toxics sites are included in this database. Universit y of Mary la nd aircraft data The University of Mar yl and performed 144 aircraft spirals at 41 regional airport locations over 26 day s from May

- Augu st 2002 ( http:// w w w . a t mo s. u md .ed u/~RAMMPP ). Spirals are approxima tel y 20-45 minutes in duration, over which time the atmosphere from about 0-3 km is sampled. The concentrat ions of O 3 

## , C O, and S O 2 

## from these spirals were included in this database, and help provide a semi- quantita tive evaluation of CMA Q perfor mance above the ground surface. Minute average aircraft data w ere compared to the nearest instantaneous 3- dim ensional C MAQ output. Wet deposition The N ADP (http://nadp.sws.uiuc.edu) collec ts wet deposition samples across the US, through the NT N and the AIR MoN. Weekl y wet deposition sampl es are collec ted b y the NTN, w hile dail y or event- based samples w ere collected by the AIRMo N. The NY SDEC ( http://

w w w . d ec. state.ny .us ) also collects weekl y wet deposition samples independent l y from the N ADP. The wet deposition of S O 4 2- 

## , N O 3 - 

## , and N H 4 + 

## from 43 NA DP/NTN sites, 7 NA DP/AIRMo N sites, and 19 N YSDEC sites are included in this mode l evaluation database. Evaluation of

CMAQ predictions The following s ections provide model evaluation inform ation for the above referenced pollutants over the OTR portion of the 12-km mode ling dom ain. The statistic al formu lations that have been computed for each species are as follows: P i 

## and O i 

## are the individual (dail y maxi mu m 8-hour O 3 

## or dail y average for the other species) predicted and observed concentrat ions, respectivel y ; P and O are the average concentrat ions, respectivel y , and N is the sample size. Observed average, in ppb: O N O i 

## = 

# ∑ 1
Predicted average, in ppb (only use P i 

## when O i 

## is valid):

4

## P N P i 

## = 

# ∑ 1
Correlation coefficient, R 2 

## : 

# [ ] R P P O O P P O O i i
i i 2 2
2 2 

## = − −

− − 

# ∑ ∑ ∑ ( ) ( ) ( ) ( ) Normal ized mean error ( NME), in %:
N M E P O

O i i i 

## = − × 

# ∑ ∑ | | 1 0 0 %
Root mean

square error (RM SE), in ppb:

R M S E N P O

i i 

## = −    

  

# ∑ 1 2 1 2 

## ( ) /



## Fractional error (FE), in %: F E N P O

P O i i i i 

## = −

+ × 

# ∑ 2 1 0 0 %
Mean absolute gross error (M AGE), in ppb: M A G E N P O

i i 

## = − 

# ∑ 1

Mean norm aliz ed gross error ( MNGE), in %: M N G E N P O

O i i i 

## = − × 

# ∑ 1 1 0 0 %
Mean bias ( MB), in ppb: M B N P O

i i 

## = − 

# ∑ 1 ( )
Mean norm aliz ed bias (MNB), in %: M N B N P O

O i i i 

## = − × 

# ∑ 1 1 0 0 % ( )

Mean fractiona liz ed bias (MFB), in %: M F B N P O

P O i i i i 

## = −

+       × 

# ∑ 2 1 0 0 %

5

## Normal ized mean bias ( NMB), in %: N M B P O

O i i i 

## = − × 

# ∑ ∑ ( ) 1 0 0 % Dail y maxi mu m 8-hour O 3 

## concentrat ions Model evaluation statistics, based on dail y maxim um 8-hour average O 3 

## levels on those day s having (1) at least 18 valid observations, or (2) fewer than 18 valid observations but the ob served dail y maxi mu m O 3 

## concentrat ion was at least 85 ppb, are presented here for all sites across the OTR and all of VA. The data coverthe periodMay 15 through September

29, excluding July 6-9, when man y sites across the eastern U S were affected by large forest fires in Quebec. There are 208 SLAM S/NAM S sites and 28 special sites. These model evaluation statistics were computed using two different threshold values for ob served dail y maxi mu m 8-hour O 3 

## . First, the statistics were compu ted using onl y those day s w hen the observed dail y max im um 8-hour O 3 

## concentration exceeded 40 ppb. Second, the statistics were co mputed u sing only those da ys when the ob served dail y max im um 8-hour O 3 

## exceeded 60 ppb. This latter method focuses on the highest O 3 

## da ys . Figures 1-4 displa y tim e series of observed and predicted dail y maxi mu m 8-hour O 3 

## concentrations averaged over all sites across the OTR, at SLA MS/NA MS and special sites and for the dail y max im um two thresholds. These averages were co mputed for each da y con sidering all sites that m et the corresponding threshold criteria. In general the observed and predicted

composi te average O 3 

## concentrations track each other

rather well, although there was fairl y s ubstantial underprediction during the m id- Augu st period. Also, the model perfor mance tends to be better w hen the lower

cutoff (40 ppb) was considered. Figures 5-8 displa y spatial maps of fractiona l error and mean fractiona lized bias for the two threshold levels. At each site the statistics were computed over the entire mode ling s eason. Both the SLAM S/NAMS and s pecial monitors are displa ye d here. In general, the model performanc e was better in the vicinit y of urban areas and along the northeastern corridor, compar ed to the performan ce in rural areas w here the mode l tended to underpredict

dail y maxi mu m concentrations. The other statistic al m etrics yi el ded simi lar re sults to FE and MFB. Table 1 lists the med ian and range in fractional error, and the m ean fractiona lized bias of daily m axim

um 8-hour O 3 

## calculat ed at each site over the season, for both observed thresholds (40 and 60 ppb), as well as all sites ver sus ju st the SLA MS/NAM S sites. Con sidering ju st SLAMS/N AMS sites, FE was alway s less than 32% for the 40 ppb threshold, and less than 40% for the 60 ppb threshold. Simil arl y, the MF B at SLAM S/NAMS sites ranged from -29 to +23% for the 40 ppb threshold, and ranged from -40 to + 22% for the 60 ppb threshold. Adding the special sites did not affect the statistics substantiall y .

6

## Diurnal variations of gases Figures 9-17 displa y the co mposite diurnal variations of the species reported hourl y – O 3 

## (SLAM S/NAMS and other/special sites, displa ye d separatel y) , continuous PM 2 .5 

## , C O, NO, N O 2 

## , SO 2 

## , ethene, and isoprene. The average diurnal variations are for the period of Ma y

15-Septe mber

30 – again excluding J ul y 6-9 – con sidering all sites in the OTR. Note that the O 3 

## diurnal variations were computed from running 8-hour averages, with hours denoting the start of the 8-hour block. The number of mon itors used to compute each composite diurnal variation is sho wn in each figure. For O 3 

## , the composi te diurnal pattern predicted b y CM AQ is fairl y simil ar to that observed, especial l y at the more urban SLAM S/NAM S mon itors. Ho wever, on average CMA Q predicts the dail y maxi mu m about an hour earlier than observed. For most of the other species presented here, C MAQ tends to predict two dail y peaks, one morning and one late afternoon. F or some s pecies, such as P M 2. 5 

## mass the ob served concentration on a composi te basis has ver y little diurnal variation. On the other hand, primar

y pollutants like CO, N O, and ethane, C MAQ exhibits qualita tive agreem ent with the observations. Dail y average concentrations of co-pollutant trace gases Composit e dail y average predicted and ob served concentrations of C O, NO, N O 2 

## , SO 2 

## , C 2 

## H 4 

## , HCH O, and C 5 

## H 8 

## across the OTR are displa ye d in Figures 18-24. Dail y average concentrat ions of the criteriagases, C 2 

## H 4 

## and C 5 

## H 8 

## were comput ed from hourl y averages, and onl y those day s having at least 12 hour s of valid observed data were considered here. The HC HO data sho wn here are based on 24-hour average values every 6 th 

## da y. The criteria gas data cover the period Ma y 15 – Septe mber

30, whereas the NM HC data onl y

coverthe J une 1 – August 31 period, since these data are predomin antl y PA MS data; however, excluded from this anal y sis is the July 6-9 period when man y sites across the eastern US were affected b y large forest fires in Quebec. Table 2 lists the med ian and range in mean fractiona liz ed bias calcula ted at each site over the season u sed in this anal ys is. The values listed in Table 2 were compu ted at each site over the entire sea son. While the range in MF B is rather large for each species across all sites, the medi an MF B was below 50% for all species except C 2 

## H 4 

## , which is substantiall y overpredicted b y CMA Q. It s hould be noted that these species can vary substantiall y from da y

to day , and da ys with ver y low modeled or observed values can contribute to high MFB. PM 2 .5 

## mass and speciation Composit e dail y average predicted and ob served concentrations of P M 2. 5 

## mass (both dail y average F RM data and continuous data), as well as major s peciat ion –SO 4 

## , NO 3 

## , N H 4 

## , EC, O M (defined here operationa ll y as 1.8×blank- corrected organic carbon), and cru stal mass (sum of oxides of Al, Ca, Fe, Si, and Ti) – across the OTR were

7

## comp ared in this anal ys is. The data cover the period May 15 – September 30, and again the July 6-9 period was excluded, when numerous sites in the eastern US were affected b y large forest fires in Quebec. The continuous and FR M PM 2 .5 

## data are sho wn ever y da y, since there are amp le daily FRM sites across the OTR. The speciation data included here are dail y averages every third da y, and con sist of the largel y urban EPA ST N and the largel y rural I MPRO VE network. The two s peciation networks collect P M 2. 5 

## , SO 4 

## , NO 3 

## , EC, OM , and crustal mass, while onl y the STN reports N H 4 

## at a sufficient number of locations. Table 3 lists the med ian and range in mean fractiona liz ed bias calcula ted at each site over the season u sed in this anal ys is. The values listed in Table 3 were compu ted at each site over the entire sea son. Figures 25-39 displa y ti me series of co mposite average observed and predicted

dail y concentrat ions; in these figures, for each day the statistics were co mputed u sing all monitors with valid data. The best qualitat ive agreemen t between observed and mod eled concentrations is exhibited for P M 2. 5 

## and S O 4 

## . N ote that in the case of crustal m ass, the data from July 4 are also not included since this da y

is greatl y affected by fireworks. O n Jul y 4, the composit e average observed and predicted crustal concentrat ions were 4.59 μg m -3 

## and 1.74 μg m -3 

## , respectivel y at the ST N moni tors, and 4.46 μg m -3 

## and 0.99 μg m -3 

## , respectivel y at the I MPRO VE monitors. As with the ga seous co- pollutant data, there is a sub stantia l spread in M FB across the sites. Ho wever, the median M FB for PM 2 .5 

## mass and S O 4 

## was generall y smal l (<12%) for both urban and rural sites. C MAQ tends to overpredict N O 3 

## , more so at the IMPR OVE sites. C MAQ also tends to underpredict O M at both urban and rural sites, although some of this discrepanc y ma y be attributed to the fact

that OM is operationa ll y defined and is highl y dependent on the blank correction and mult ipli er to account for other componen ts of O M not directl y measured. C MAQ tends to overpredict both EC and cru stal mass, especiall y at urban sites; sim ilar to O M, the crustal mass overprediction is related to the fact that

this parame ter

is operationa ll y defined. Wet deposition of sulfate, nitrate, and amm oniu m Observed and predicted wet deposition of S O 4 

## , NO 3 

## , and NH 4 

## were co mpared over the periodMay 14 – September 30. For this anal ys is, weekl y or event- based wet deposition amoun ts from the N AD P/NTN (43 sites), N AD P/AIRMoN (7 sites), and New York State DEC (19 sites) covering the entire OTR plus all of V A and WV were integrat ed over the four-and-a-half months. Because the ob served weekly wet deposition sampl es did include July 6-9, the corresponding CMA Q predictions also include this period. Table 4 lists the model evaluation statistics for integrated w et deposition of S O 4 

## , NO 3 

## , and NH 4 

## at each site over the season, while Figures 40-42 co mpare the observed and predicted

weekly values relative to the 1:1 line. Overall CM AQ tended to overpredict wet deposition of these ions. On a percentage basis, the overpredict ion was least for S O 4 

## and highest for N O 3 

## . The NME, MN GE, M NB, and NMB w ere less than 50% for the three ions. Given that precipitat ion is ver y difficult

to predict, especiall y during the summ er months when rainfall can var y

8

## tre mendousl y over a 12 km b y 12 km area represented

b y this model grid, CM AQ did a rather good jo b reproducing seasonal wet deposition over the OTR. Upper-air O 3 

## , CO, and SO 2 

## data The University of Mar yl and operated an instrum ented light aircraft during the summ er of 2002. On 26 day s from May

- A ugust me teorolog ica l, trace gas, and particl e scattering /absorption data were collected during ascent or descent spirals over 41 regional airports. In all, 144 s pirals were perform ed from nearthe surface to about 3 km above ground level. For this analy si s, composit e average profiles of O 3 

## , CO, and SO 2 

## were created over three time periods: “morning” (08-11 EST), “afternoon” (12-16 EST), and “evening” (17-19 EST). The minute average observed concentrat ions were aggregated into la ye r averages, which correspond to the lowest 15 model la ye rs. Model lay er s are increasingl y thick

away from the s urface; the surface la y er is about 20 m thick while the 15 th 

## la ye r is about 500 m thick (and centered about 2.8 km above the ground). Figures 43-51 displa y the observed and predicted composi te vertica l profiles of O 3 

## , CO, and S O 2 

## for the three ti me periods. In terms of profile shape, CMA Q was in good qualita tive agreem ent for all three species above the s urface during the afternoon hour s. For CO, the mode l tends to greatl y underpredict observed levels near

the surface, whereas the predicted

O 3 

## and S O 2 

## concentrations are closer to the respective ob served values. Su m m ar y Various mode l evaluation statistics are pre sented here for a variet y of gaseous and aerosol s pecies in addition to O 3 

## . In general, the CMA Q results were best for dail y max im um O 3 

## and dail y average P M 2. 5 

## and S O 4 

## mass. Many other species vary tre mendousl y over the course of a day , or from da y to day , and smal l mode l over- or underpredict ion at low concentrations can lead to large biases on a composi te basis. It is impor tant to demonstr ate that the mode l performs reasonabl y over the diurnal cy cl e, not ju st in terms of daily m axim um or average values. Al so, it is import ant to demonstrat e that the model can reproduce concentrations above the ground level.

9

## Table 1. Median and range in fractional error (FE, %) and me an fractional ized bias

(MFB, %) for dail y maxi mu m 8-hour O 3 

## u sing the 40 ppb and 60 ppb ob served thresholds. The values u sing only SLA MS/NA MS sites are boldfaced, the values using all sites are in regular

font. Metric, t hreshold R ange (% ) Median (% ) FE, 40 ppb + 10 to + 34% +10 to +32 % + 15% +15% MFB, 40 ppb -34 to + 23% -29 to +23 % -6% -6% FE, 60 ppb + 9 to + 40% +9 to +40 % + 15% +15% MFB, 60 ppb -40 to + 22% -40 to +22 % -12% -11%

Table 2. Median and range in mean fractionali zed bias (%) for dail y average C O, NO, NO 2 

## , S O 2 

## , C 2 

## H 4 

## , H CHO, and C 5 

## H8. Pollutant Range in MFB ( %) Median MFB (% ) C O (97 sites) -128 to + 144% -10% N O (75 sites) -182 to + 116% -46% N O 2 

## (97 sites) -125 to + 107% + 13% S O 2 

## (134 sites) -139 to 140% + 3% C 2 

## H 4 

## (19 sites) + 28 to + 168% + 86% HCH O (18 sites) -66 to + 96% -13% C 5 

## H 8 

## (19 sites) -54 to + 165% + 43%

10

## Table 3. Median and range in mean fractionali zed bias (%) for dail y average P M 2. 5 

## , SO 4 

## ,

NO 3 

## , N H 4 

## , EC, and O M.

Pollutant Range in MFB ( %) Median MFB (% ) P M 2. 5 

## (FRM; 257 sites) -59 to + 119% -4% PM 2 .5 

## (continuous; 57 sites) -39 to + 85% + 5% STN P M 2 .5 

## (49 sites) -45 to + 102% -9% I MPROVE P M 2. 5 

## (21 sites) -36 to + 19% -10% STN S O 4 

## (49 sites) -21 to + 60% + 12% I MPROVE S O 4 

## (21 sites) -26 to + 16% -7% STN N O 3 

## (49 sites) -73 to + 406% + 25% I MPROVE N O 3 

## (21 sites) -57 to + 358% + 64% STN N H 4 

## (49 sites) -36 to + 112% + 16% STN EC (49 sites) -42 to + 269% + 34% I MPROVE EC (21 sites) -60 to + 146% -27% STN OM (49 sites) -82 to -25% -58% I MPROVE O M (21 sites) -60 to + 7% -40% STN cru stal (49 sites) + 2 to + 546% + 182% IMPR OVE crustal (21 sites) -18 to + 163% + 38%

Table 4. Model evaluation statistics for integrated wet deposition of S O 4 

## , N O 3 

## , and N H 4



## . Para meter SO 4 

## NO 3 

## NH 4 

## Observed average, mg m -2 

## 1063 704 185 Predicted average, mg m -2 

## 946 367 117 Correlation coefficien t, R 2 

## 0.17 0.22 0.12 N ME, % 34 49 48 RMSE, mg m -2 

## 490 417 109 FE, % 36 62 57 M AGE, mg m -2 

## 365 344 89 MN GE, % 36 45 46 MB, mg m -2 

## -118 -337 -68 MNB, % -3 -44 -28 MFB, % -13 -61 -44 NMB, % -11 -48 -37

11

## Figure 1.
O b s e r v e d a n d P r

e d i c t e d a v e r

a g e s 2 0 8 S L A M S/ N A M S s i t e s ; 4 0 p p b t h r e s h o l d

0 1 0 2 0 3 0 4 0 5 0 6 0 7 0 8 0 9 0 1 0 0

2 0 0 2 0 5 1 5 2 0 0 2 0 5 2 3 2 0 0 2 0 5 3 1 2 0 0 2 0 6 0 8 2 0 0 2 0 6 1 6 2 0 0 2 0 6 2 4 2 0 0 2 0 7 0 2 2 0 0 2 0 7 1 0 2 0 0 2 0 7 1 8 2 0 0 2 0 7 2 6 2 0 0 2 0 8 0 3 2 0 0 2 0 8 1 1 2 0 0 2 0 8 1 9 2 0 0 2 0 8 2 7 2 0 0 2 0 9 0 4 2 0 0 2 0 9 1 2 2 0 0 2 0 9 2 0 2 0 0 2 0 9 2 8ppb 

### o b s a v

g , p p b C M AQ a v

g , p p b



## Figure 2. O b s e r v e d a n d P r

e d i c t e d a v e r

a g e s 2 0 8 S L A M S/ N A M S s i t e s ; 6 0 p p b t h r e s h o l d

0 1 0 2 0 3 0 4 0 5 0 6 0 7 0 8 0 9 0 1 0 0

2 0 0 2 0 5 1 5 2 0 0 2 0 5 2 3 2 0 0 2 0 5 3 1 2 0 0 2 0 6 0 8 2 0 0 2 0 6 1 6 2 0 0 2 0 6 2 4 2 0 0 2 0 7 0 2 2 0 0 2 0 7 1 0 2 0 0 2 0 7 1 8 2 0 0 2 0 7 2 6 2 0 0 2 0 8 0 3 2 0 0 2 0 8 1 1 2 0 0 2 0 8 1 9 2 0 0 2 0 8 2 7 2 0 0 2 0 9 0 4 2 0 0 2 0 9 1 2 2 0 0 2 0 9 2 0 2 0 0 2 0 9 2 8ppb 

### o b s a v

g , p p b C M AQ a v

g , p p b



## 12

## Figure 3. O b s e r v e d a n d P r

e d i c t e d a v e r

a g e s 2 8 s p e c i a l m o n i t o r

s ; 4 0 p p b t h r

e s h o l d

0 1 0 2 0 3 0 4 0 5 0 6 0 7 0 8 0 9 0 1 0 0

2 0 0 2 0 5 1 5 2 0 0 2 0 5 2 3 2 0 0 2 0 5 3 1 2 0 0 2 0 6 0 8 2 0 0 2 0 6 1 6 2 0 0 2 0 6 2 4 2 0 0 2 0 7 0 2 2 0 0 2 0 7 1 0 2 0 0 2 0 7 1 8 2 0 0 2 0 7 2 6 2 0 0 2 0 8 0 3 2 0 0 2 0 8 1 1 2 0 0 2 0 8 1 9 2 0 0 2 0 8 2 7 2 0 0 2 0 9 0 4 2 0 0 2 0 9 1 2 2 0 0 2 0 9 2 0 2 0 0 2 0 9 2 8ppb 

### o b s a v

g , p p b C M AQ a v

g , p p b



## Figure 4. O b s e r v e d a n d P r

e d i c t e d a v e r

a g e s 2 8 s p e c i a l s i t e s ; 6 0 p p b t h r e s h o l d

0 1 0 2 0 3 0 4 0 5 0 6 0 7 0 8 0 9 0 1 0 0

2 0 0 2 0 5 1 5 2 0 0 2 0 5 2 3 2 0 0 2 0 5 3 1 2 0 0 2 0 6 0 8 2 0 0 2 0 6 1 6 2 0 0 2 0 6 2 4 2 0 0 2 0 7 0 2 2 0 0 2 0 7 1 0 2 0 0 2 0 7 1 8 2 0 0 2 0 7 2 6 2 0 0 2 0 8 0 3 2 0 0 2 0 8 1 1 2 0 0 2 0 8 1 9 2 0 0 2 0 8 2 7 2 0 0 2 0 9 0 4 2 0 0 2 0 9 1 2 2 0 0 2 0 9 2 0 2 0 0 2 0 9 2 8ppb 

### o b s a v

g , p p b C M AQ a v

g , p p b



## 13

## Figure 5.

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E W S 

### F E , 4 0 p p b c u t o f

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## Figure 6.

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### 7 - 1 4 % # 

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3 0 0 0 3 0 0 6 0 0 M i l e s N
E W S



## 14

## Figure 7.

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### - 3 5 - - 2 5 % # 

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### 5 - 1 5 % # 

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3 0 0 0 3 0 0 6 0 0 M i l e s N
E W S 

## Figure 8.

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E W S 

### M F B , 6 0 p p b c u t o f

f # 

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## 15

## Figure 9. O z o n e ( S L A M S / N A M S ) - 2 0 8 s i t e s

0

. 0 1 0

. 0 2 0

. 0 3 0

. 0 4 0

. 0 5 0

. 0 6 0

. 0

0 4 8 1 2 1 6 2 0 2 4O3(ppb) 

### O b s e r v e d Pr e d i c t e d



## Figure 10. O z o n e ( C A S T N e t & o t h e r

s ) - 2 8 s i t e s

0

. 0 1 0

. 0 2 0

. 0 3 0

. 0 4 0

. 0 5 0

. 0 6 0

. 0

0 4 8 1 2 1 6 2 0 2 4O3(ppb) 

### O b s e r v e d Pr e d i c t e d



## 16

## Figure 11. C o n t i n u o u s P M 2 . 5 

### m a s s - 5 7 s i t e s

0

. 0 0 5

. 0 0 1 0

. 0 0 1 5

. 0 0 2 0

. 0 0 2 5

. 0 0 3 0

. 0 0

0 4 8 1 2 1 6 2 0 2 4PM2.5(ug/m3) 

### O b s e r v e d Pr e d i c t e d



## Figure 12. C a r b o n m o n o x i d e - 9 7 s i t e s

0

. 0 1 0 0

. 0 2 0 0

. 0 3 0 0

. 0 4 0 0

. 0 5 0 0

. 0 6 0 0

. 0

0 4 8 1 2 1 6 2 0 2 4CO(ppb) 

### O b s e r v e d Pr e d i c t e d



## 17

## Figure 13. N i t r i c o x i d e - 7 5 s i t e s

0

. 0 0 2

. 0 0 4

. 0 0 6

. 0 0 8

. 0 0 1 0

. 0 0 1 2

. 0 0 1 4

. 0 0 1 6

. 0 0

0 4 8 1 2 1 6 2 0 2 4NO(ppb) 

### O b s e r v e d Pr e d i c t e d



## Figure 14. N i t r o g e n d i o x i d e - 9 7 s i t e s

0

. 0 0 5

. 0 0 1 0

. 0 0 1 5

. 0 0 2 0

. 0 0 2 5

. 0 0 3 0

. 0 0

0 4 8 1 2 1 6 2 0 2 4NO2(ppb) 

### O b s e r v e d Pr e d i c t e d



## 18

## Figure 15. S u l f u r d i o x i d e - 1 3 4 s i t e s

0

. 0 0 1

. 0 0 2

. 0 0 3

. 0 0 4

. 0 0 5

. 0 0 6

. 0 0 7

. 0 0

0 5 1 0 1 5 2 0 2 5SO2(ppb) 

### O b s e r v e d Pr e d i c t e d



## Figure 16. E t h e n e - 1 9 s i t e s

0

. 0 0 0

. 5 0 1

. 0 0 1

. 5 0 2

. 0 0 2

. 5 0 3

. 0 0

0 4 8 1 2 1 6 2 0 2 4ethene(ppb) 

### O b s e r v e d Pr e d i c t e d



## 19

## Figure 17. I s o p r e n e - 1 9 s i t e s

0

. 0 0 0

. 5 0 1

. 0 0 1

. 5 0 2

. 0 0 2

. 5 0 3

. 0 0 3

. 5 0 4

. 0 0

0 4 8 1 2 1 6 2 0 2 4isoprene(ppb) 

### O b s e r v e d Pr e d i c t e d



## Figure 18. O b s e r v e d a n d P r

e d i c t e d a v e r

a g e C O ( 9 7 s i t e s )

0 1 0 0 2 0 0 3 0 0 4 0 0 5 0 0 6 0 0 7 0 0 8 0 0

2 0 0 2 0 5 1 5 2 0 0 2 0 5 2 3 2 0 0 2 0 5 3 1 2 0 0 2 0 6 0 8 2 0 0 2 0 6 1 6 2 0 0 2 0 6 2 4 2 0 0 2 0 7 0 2 2 0 0 2 0 7 1 0 2 0 0 2 0 7 1 8 2 0 0 2 0 7 2 6 2 0 0 2 0 8 0 3 2 0 0 2 0 8 1 1 2 0 0 2 0 8 1 9 2 0 0 2 0 8 2 7 2 0 0 2 0 9 0 4 2 0 0 2 0 9 1 2 2 0 0 2 0 9 2 0 2 0 0 2 0 9 2 8ppb 

### o b s a v

g , p p b C M AQ a v

g , p p b



## 20

## Figure 19. O b s e r v e d a n d P r

e d i c t e d a v e r

a g e N O ( 7 5 s i t e s )

0 2 4 6 8 1 0 1 2 1 4 1 6 1 8

2 0 0 2 0 5 1 5 2 0 0 2 0 5 2 3 2 0 0 2 0 5 3 1 2 0 0 2 0 6 0 8 2 0 0 2 0 6 1 6 2 0 0 2 0 6 2 4 2 0 0 2 0 7 0 2 2 0 0 2 0 7 1 0 2 0 0 2 0 7 1 8 2 0 0 2 0 7 2 6 2 0 0 2 0 8 0 3 2 0 0 2 0 8 1 1 2 0 0 2 0 8 1 9 2 0 0 2 0 8 2 7 2 0 0 2 0 9 0 4 2 0 0 2 0 9 1 2 2 0 0 2 0 9 2 0 2 0 0 2 0 9 2 8ppb 

### o b s a v

g , p p b C M AQ a v

g , p p b



## Figure 20. O b s e r v e d a n d P r

e d i c t e d a v e r

a g e NO 2 

### ( 9 7 s i t e s )

0 5 1 0 1 5 2 0 2 5 3 0 3 5

2 0 0 2 0 5 1 5 2 0 0 2 0 5 2 3 2 0 0 2 0 5 3 1 2 0 0 2 0 6 0 8 2 0 0 2 0 6 1 6 2 0 0 2 0 6 2 4 2 0 0 2 0 7 0 2 2 0 0 2 0 7 1 0 2 0 0 2 0 7 1 8 2 0 0 2 0 7 2 6 2 0 0 2 0 8 0 3 2 0 0 2 0 8 1 1 2 0 0 2 0 8 1 9 2 0 0 2 0 8 2 7 2 0 0 2 0 9 0 4 2 0 0 2 0 9 1 2 2 0 0 2 0 9 2 0 2 0 0 2 0 9 2 8ppb 

### o b s a v

g , p p b C M AQ a v

g , p p b



## 21

## Figure 21. O b s e r v e d a n d P r

e d i c t e d a v e r

a g e S O 2 

### ( 1 3 4 s i t e s )

0 1 2 3 4 5 6 7 8

2 0 0 2 0 5 1 5 2 0 0 2 0 5 2 3 2 0 0 2 0 5 3 1 2 0 0 2 0 6 0 8 2 0 0 2 0 6 1 6 2 0 0 2 0 6 2 4 2 0 0 2 0 7 0 2 2 0 0 2 0 7 1 0 2 0 0 2 0 7 1 8 2 0 0 2 0 7 2 6 2 0 0 2 0 8 0 3 2 0 0 2 0 8 1 1 2 0 0 2 0 8 1 9 2 0 0 2 0 8 2 7 2 0 0 2 0 9 0 4 2 0 0 2 0 9 1 2 2 0 0 2 0 9 2 0 2 0 0 2 0 9 2 8ppb 

### o b s a v

g , p p b C M AQ a v

g , p p b



## Figure 22. O b s e r v e d a n d Pr

e d i c t e d C 2 

### H 4 

### ( 1 9 s i t e s )

0 0

. 5 1 1

. 5 2 2

. 5

2 0 0 2 0 6 0 1 2 0 0 2 0 6 0 6 2 0 0 2 0 6 1 1 2 0 0 2 0 6 1 6 2 0 0 2 0 6 2 1 2 0 0 2 0 6 2 6 2 0 0 2 0 7 0 1 2 0 0 2 0 7 0 6 2 0 0 2 0 7 1 1 2 0 0 2 0 7 1 6 2 0 0 2 0 7 2 1 2 0 0 2 0 7 2 6 2 0 0 2 0 7 3 1 2 0 0 2 0 8 0 5 2 0 0 2 0 8 1 0 2 0 0 2 0 8 1 5 2 0 0 2 0 8 2 0 2 0 0 2 0 8 2 5 2 0 0 2 0 8 3 0ppb o b s a v

g , p p b C M A Q a v

g , p p b



## 22

## Figure 23. O b s e r v e d a n d P r

e d i c t e d H C H O ( 1 8 s i t e s )

0 1 2 3 4 5 6 7 8 9

2 0 0 2 0 6 0 1 2 0 0 2 0 6 0 7 2 0 0 2 0 6 1 3 2 0 0 2 0 6 1 9 2 0 0 2 0 6 2 5 2 0 0 2 0 7 0 1 2 0 0 2 0 7 0 7 2 0 0 2 0 7 1 3 2 0 0 2 0 7 1 9 2 0 0 2 0 7 2 5 2 0 0 2 0 7 3 1 2 0 0 2 0 8 0 6 2 0 0 2 0 8 1 2 2 0 0 2 0 8 1 8 2 0 0 2 0 8 2 4 2 0 0 2 0 8 3 0ppb o b s a v

g , p p b C M A Q a v

g , p p b



## Figure 24. O b s e r v e d a n d Pr

e d i c t e d C 5 

### H 8 

### ( 1 9 s i t e s )

0 0

. 5 1 1

. 5 2 2

. 5 3

2 0 0 2 0 6 0 1 2 0 0 2 0 6 0 6 2 0 0 2 0 6 1 1 2 0 0 2 0 6 1 6 2 0 0 2 0 6 2 1 2 0 0 2 0 6 2 6 2 0 0 2 0 7 0 1 2 0 0 2 0 7 0 6 2 0 0 2 0 7 1 1 2 0 0 2 0 7 1 6 2 0 0 2 0 7 2 1 2 0 0 2 0 7 2 6 2 0 0 2 0 7 3 1 2 0 0 2 0 8 0 5 2 0 0 2 0 8 1 0 2 0 0 2 0 8 1 5 2 0 0 2 0 8 2 0 2 0 0 2 0 8 2 5 2 0 0 2 0 8 3 0ppb o b s a v

g , p p b C M A Q a v

g , p p b



## 23

## Figure 25. O b s e r v e d a n d Pr

e d i c t e d PM 2 .5 

### ( F R M ; 2 5 7 s i t e s )

0 5 1 0 1 5 2 0 2 5 3 0 3 5 4 0 4 5

2 0 0 2 0 5 1 5 2 0 0 2 0 5 2 3 2 0 0 2 0 5 3 1 2 0 0 2 0 6 0 8 2 0 0 2 0 6 1 6 2 0 0 2 0 6 2 4 2 0 0 2 0 7 0 2 2 0 0 2 0 7 1 0 2 0 0 2 0 7 1 8 2 0 0 2 0 7 2 6 2 0 0 2 0 8 0 3 2 0 0 2 0 8 1 1 2 0 0 2 0 8 1 9 2 0 0 2 0 8 2 7 2 0 0 2 0 9 0 4 2 0 0 2 0 9 1 2 2 0 0 2 0 9 2 0 2 0 0 2 0 9 2 8μgm-3 o b s a v

g , u g / m 3 C M AQ a v

g , u g / m 3



## Figure 26. O b s e r

v e d a n d P r

e d i c t e d P M 2. 5 

### ( c o n t i n u o u s ; 5 7 s i t e s )

0 5 1 0 1 5 2 0 2 5 3 0 3 5 4 0 4 5

2 0 0 2 0 5 1 5 2 0 0 2 0 5 2 3 2 0 0 2 0 5 3 1 2 0 0 2 0 6 0 8 2 0 0 2 0 6 1 6 2 0 0 2 0 6 2 4 2 0 0 2 0 7 0 2 2 0 0 2 0 7 1 0 2 0 0 2 0 7 1 8 2 0 0 2 0 7 2 6 2 0 0 2 0 8 0 3 2 0 0 2 0 8 1 1 2 0 0 2 0 8 1 9 2 0 0 2 0 8 2 7 2 0 0 2 0 9 0 4 2 0 0 2 0 9 1 2 2 0 0 2 0 9 2 0 2 0 0 2 0 9 2 8μgm-3 o b s a v

g , u g / m 3 C M AQ a v

g , u g / m 3



## 24

## Figure 27. O b s e r v e d a n d P r

e d i c t e d P M 2 .5 

### ( ST N; 4 9 s i t e s )

0 5 1 0 1 5 2 0 2 5 3 0 3 5 4 0

2 0 0 2 0 5 1 7 2 0 0 2 0 5 2 6 2 0 0 2 0 6 0 4 2 0 0 2 0 6 1 3 2 0 0 2 0 6 2 2 2 0 0 2 0 7 0 1 2 0 0 2 0 7 1 0 2 0 0 2 0 7 1 9 2 0 0 2 0 7 2 8 2 0 0 2 0 8 0 6 2 0 0 2 0 8 1 5 2 0 0 2 0 8 2 4 2 0 0 2 0 9 0 2 2 0 0 2 0 9 1 1 2 0 0 2 0 9 2 0 2 0 0 2 0 9 2 9μgm-3 o b s a v

g , u g / m 3 C M AQ a v

g , u g / m 3



## Figure 28. O b s e r

v e d a n d P r

e d i c t e d P M 2 .5 

### ( I M PR O

VE ; 2 1 s i t e s )

0 5 1 0 1 5 2 0 2 5 3 0

2 0 0 2 0 5 1 7 2 0 0 2 0 5 2 6 2 0 0 2 0 6 0 4 2 0 0 2 0 6 1 3 2 0 0 2 0 6 2 2 2 0 0 2 0 7 0 1 2 0 0 2 0 7 1 0 2 0 0 2 0 7 1 9 2 0 0 2 0 7 2 8 2 0 0 2 0 8 0 6 2 0 0 2 0 8 1 5 2 0 0 2 0 8 2 4 2 0 0 2 0 9 0 2 2 0 0 2 0 9 1 1 2 0 0 2 0 9 2 0 2 0 0 2 0 9 2 9μgm-3 o b s a v

g , u g / m 3 C M A Q a v

g , u g / m 3



## 25

## Figure 29. O b s e r v e d a n d P r

e d i c t e d SO 4 

### ( ST N; 4 9 s i t e s )

0 5 1 0 1 5 2 0 2 5

2 0 0 2 0 5 1 7 2 0 0 2 0 5 2 6 2 0 0 2 0 6 0 4 2 0 0 2 0 6 1 3 2 0 0 2 0 6 2 2 2 0 0 2 0 7 0 1 2 0 0 2 0 7 1 0 2 0 0 2 0 7 1 9 2 0 0 2 0 7 2 8 2 0 0 2 0 8 0 6 2 0 0 2 0 8 1 5 2 0 0 2 0 8 2 4 2 0 0 2 0 9 0 2 2 0 0 2 0 9 1 1 2 0 0 2 0 9 2 0 2 0 0 2 0 9 2 9μgm-3 o b s a v

g , u g / m 3 C M AQ a v

g , u g / m 3



## Figure 30. O b s e r v e d a n d P r

e d i c t e d S O 4 

### ( I M P R O

V E ; 2 1 s i t e s )

0 2 4 6 8 1 0 1 2 1 4 1 6 1 8

2 0 0 2 0 5 1 7 2 0 0 2 0 5 2 6 2 0 0 2 0 6 0 4 2 0 0 2 0 6 1 3 2 0 0 2 0 6 2 2 2 0 0 2 0 7 0 1 2 0 0 2 0 7 1 0 2 0 0 2 0 7 1 9 2 0 0 2 0 7 2 8 2 0 0 2 0 8 0 6 2 0 0 2 0 8 1 5 2 0 0 2 0 8 2 4 2 0 0 2 0 9 0 2 2 0 0 2 0 9 1 1 2 0 0 2 0 9 2 0 2 0 0 2 0 9 2 9mgm-3 o b s a v

g , u g / m 3 C M A Q a v

g , u g / m 3



## 26

## Figure 31. O b s e r v e d a n d P r

e d i c t e d NO 3 

### ( ST N; 4 9 s i t e s )

0 0

. 5 1 1

. 5 2 2

. 5 3 3

. 5

2 0 0 2 0 5 1 7 2 0 0 2 0 5 2 6 2 0 0 2 0 6 0 4 2 0 0 2 0 6 1 3 2 0 0 2 0 6 2 2 2 0 0 2 0 7 0 1 2 0 0 2 0 7 1 0 2 0 0 2 0 7 1 9 2 0 0 2 0 7 2 8 2 0 0 2 0 8 0 6 2 0 0 2 0 8 1 5 2 0 0 2 0 8 2 4 2 0 0 2 0 9 0 2 2 0 0 2 0 9 1 1 2 0 0 2 0 9 2 0 2 0 0 2 0 9 2 9μgm-3 o b s a v

g , u g / m 3 C M AQ a v

g , u g / m 3



## Figure 32. O b s e r v e d a n d P r

e d i c t e d N O 3 

### ( I M P R O

V E ; 2 1 s i t e s )

0 0

. 2 0

. 4 0

. 6 0

. 8 1 1

. 2 1

. 4 1

. 6 1

. 8 2

2 0 0 2 0 5 1 7 2 0 0 2 0 5 2 6 2 0 0 2 0 6 0 4 2 0 0 2 0 6 1 3 2 0 0 2 0 6 2 2 2 0 0 2 0 7 0 1 2 0 0 2 0 7 1 0 2 0 0 2 0 7 1 9 2 0 0 2 0 7 2 8 2 0 0 2 0 8 0 6 2 0 0 2 0 8 1 5 2 0 0 2 0 8 2 4 2 0 0 2 0 9 0 2 2 0 0 2 0 9 1 1 2 0 0 2 0 9 2 0 2 0 0 2 0 9 2 9μgm-3 o b s a v

g , u g / m 3 C M A Q a v

g , u g / m 3



## 27

## Figure 33. O b s e r v e d a n d P r

e d i c t e d NH 4 

### ( ST N; 4 9 s i t e s )

0 1 2 3 4 5 6 7

2 0 0 2 0 5 1 7 2 0 0 2 0 5 2 6 2 0 0 2 0 6 0 4 2 0 0 2 0 6 1 3 2 0 0 2 0 6 2 2 2 0 0 2 0 7 0 1 2 0 0 2 0 7 1 0 2 0 0 2 0 7 1 9 2 0 0 2 0 7 2 8 2 0 0 2 0 8 0 6 2 0 0 2 0 8 1 5 2 0 0 2 0 8 2 4 2 0 0 2 0 9 0 2 2 0 0 2 0 9 1 1 2 0 0 2 0 9 2 0 2 0 0 2 0 9 2 9μgm-3 o b s a v

g , u g / m 3 C M AQ a v

g , u g / m 3



## Figure 34. O b s e r v e d a n d Pr

e d i c t e d E C ( ST N; 4 9 s i t e s )

0 0

. 2 0

. 4 0

. 6 0

. 8 1 1

. 2 1

. 4 1

. 6 1

. 8

2 0 0 2 0 5 1 7 2 0 0 2 0 5 2 6 2 0 0 2 0 6 0 4 2 0 0 2 0 6 1 3 2 0 0 2 0 6 2 2 2 0 0 2 0 7 0 1 2 0 0 2 0 7 1 0 2 0 0 2 0 7 1 9 2 0 0 2 0 7 2 8 2 0 0 2 0 8 0 6 2 0 0 2 0 8 1 5 2 0 0 2 0 8 2 4 2 0 0 2 0 9 0 2 2 0 0 2 0 9 1 1 2 0 0 2 0 9 2 0 2 0 0 2 0 9 2 9μgm-3 o b s a v

g , u g / m 3 C M AQ a v

g , u g / m 3



## 28

## Figure 35. O b s e r v e d a n d P r

e d i c t e d E C ( I M P RO

V E; 2 1 s i t e s )

0 0

. 1 0

. 2 0

. 3 0

. 4 0

. 5 0

. 6 0

. 7 0

. 8

2 0 0 2 0 5 1 7 2 0 0 2 0 5 2 6 2 0 0 2 0 6 0 4 2 0 0 2 0 6 1 3 2 0 0 2 0 6 2 2 2 0 0 2 0 7 0 1 2 0 0 2 0 7 1 0 2 0 0 2 0 7 1 9 2 0 0 2 0 7 2 8 2 0 0 2 0 8 0 6 2 0 0 2 0 8 1 5 2 0 0 2 0 8 2 4 2 0 0 2 0 9 0 2 2 0 0 2 0 9 1 1 2 0 0 2 0 9 2 0 2 0 0 2 0 9 2 9μgm-3 o b s a v

g , u g / m 3 C M A Q a v

g , u g / m 3



## Figure 36. O b s e r v e d a n d P r

e d i c t e d O M ( S T N; 4 9 s i t e s )

0 2 4 6 8 1 0 1 2 1 4

2 0 0 2 0 5 1 7 2 0 0 2 0 5 2 6 2 0 0 2 0 6 0 4 2 0 0 2 0 6 1 3 2 0 0 2 0 6 2 2 2 0 0 2 0 7 0 1 2 0 0 2 0 7 1 0 2 0 0 2 0 7 1 9 2 0 0 2 0 7 2 8 2 0 0 2 0 8 0 6 2 0 0 2 0 8 1 5 2 0 0 2 0 8 2 4 2 0 0 2 0 9 0 2 2 0 0 2 0 9 1 1 2 0 0 2 0 9 2 0 2 0 0 2 0 9 2 9μgm-3 o b s a v

g , u g / m 3 C M AQ a v

g , u g / m 3



## 29

## Figure 37. O b s e r v e d a n d P r

e d i c t e d O M ( I M P RO

V E; 2 1 s i t e s )

0 1 2 3 4 5 6 7 8 9 1 0

2 0 0 2 0 5 1 7 2 0 0 2 0 5 2 6 2 0 0 2 0 6 0 4 2 0 0 2 0 6 1 3 2 0 0 2 0 6 2 2 2 0 0 2 0 7 0 1 2 0 0 2 0 7 1 0 2 0 0 2 0 7 1 9 2 0 0 2 0 7 2 8 2 0 0 2 0 8 0 6 2 0 0 2 0 8 1 5 2 0 0 2 0 8 2 4 2 0 0 2 0 9 0 2 2 0 0 2 0 9 1 1 2 0 0 2 0 9 2 0 2 0 0 2 0 9 2 9μgm-3 o b s a v

g , u g / m 3 C M A Q a v

g , u g / m 3



## Figure 38. O b s e r v e d a n d Pr

e d i c t e d c r u s t a l ( ST N; 4 9 s i t e s )

0 0

. 5 1 1

. 5 2 2

. 5 3

2 0 0 2 0 5 1 7 2 0 0 2 0 5 2 6 2 0 0 2 0 6 0 4 2 0 0 2 0 6 1 3 2 0 0 2 0 6 2 2 2 0 0 2 0 7 0 1 2 0 0 2 0 7 1 0 2 0 0 2 0 7 1 9 2 0 0 2 0 7 2 8 2 0 0 2 0 8 0 6 2 0 0 2 0 8 1 5 2 0 0 2 0 8 2 4 2 0 0 2 0 9 0 2 2 0 0 2 0 9 1 1 2 0 0 2 0 9 2 0 2 0 0 2 0 9 2 9μgm-3 o b s a v

g , u g / m 3 C M AQ a v

g , u g / m 3



## 30

## Figure 39. O b s e r v e d a n d P r

e d i c t e d c r u s t a l ( I M PR O VE ; 2 1 s i t e s )

0 0

. 2 0

. 4 0

. 6 0

. 8 1 1

. 2 1

. 4 1

. 6 1

. 8

2 0 0 2 0 5 1 7 2 0 0 2 0 5 2 6 2 0 0 2 0 6 0 4 2 0 0 2 0 6 1 3 2 0 0 2 0 6 2 2 2 0 0 2 0 7 0 1 2 0 0 2 0 7 1 0 2 0 0 2 0 7 1 9 2 0 0 2 0 7 2 8 2 0 0 2 0 8 0 6 2 0 0 2 0 8 1 5 2 0 0 2 0 8 2 4 2 0 0 2 0 9 0 2 2 0 0 2 0 9 1 1 2 0 0 2 0 9 2 0 2 0 0 2 0 9 2 9μgm-3 o b s a v

g , u g / m 3 C M A Q a v

g , u g / m 3



## Figure 40. W e t S O 4 

### D e p o s i t i o n

0 5 0 0 1 0 0 0 1 5 0 0 2 0 0 0 2 5 0 0

0 5 0 0 1 0 0 0 1 5 0 0 2 0 0 0 2 5 0 0 O b s e r ve d ( m g / m 2 )Predicted(mg/m2)



## 31

## Figure 41. W e t N O 3 

### D e p o s i t i o n

0 2 0 0 4 0 0 6 0 0 8 0 0 1 0 0 0 1 2 0 0 1 4 0 0 1 6 0 0

0 2 0 0 4 0 0 6 0 0 8 0 0 1 0 0 0 1 2 0 0 1 4 0 0 1 6 0 0 O b s e r ve d ( m g / m 2 )Predicted(mg/m2)



## Figure 42. W e t N H 4 

### D e p o s i t i o n

0 5 0 1 0 0 1 5 0 2 0 0 2 5 0 3 0 0 3 5 0 4 0 0 4 5 0 5 0 0

0 5 0 1 0 0 1 5 0 2 0 0 2 5 0 3 0 0 3 5 0 4 0 0 4 5 0 5 0 0 O b s e r ve d ( m g / m 2 )Predicted(mg/m2)



## 32

## Figure 43.

Figure 44.

33 M o r n i n g ( 0 8 - 1 1 E ST )

0 5 0 0 1 0 0 0 1 5 0 0 2 0 0 0 2 5 0 0 3 0 0 0

4 0 4 5 5 0 5 5 6 0 6 5 7 0 O 3 ( p p b )Z(m)

o b s e r v e d C

M A Q

A f t e r n o o n ( 1 2- 16 E ST )

0 5 0 0 1 0 0 0 1 5 0 0 2 0 0 0 2 5 0 0 3 0 0 0

5 0 6 0 7 0 8 0 9 0 O 3 ( p p b )Z(m)

o b s e r v e d C

M A Q

## Figure 45.

Figure 46.

34 E v e n i n g ( 1 7 - 1 9 E S T )

0 5 0 0 1 0 0 0 1 5 0 0 2 0 0 0 2 5 0 0 3 0 0 0

4 0 5 0 6 0 7 0 8 0 9 0 O 3 ( p p b )Z(m)

o b s e r v e d C

M A Q

M o r n i n g ( 0 8 - 1 1 E ST )

0 5 0 0 1 0 0 0 1 5 0 0 2 0 0 0 2 5 0 0 3 0 0 0

0 1 0 0 2 0 0 3 0 0 4 0 0 5 0 0 C O ( p p b )Z(m)

o b s e r v e d C

M A Q

## Figure 47.

Figure 48.

35 A f t e r n o o n ( 1 2- 16 E ST )

0 5 0 0 1 0 0 0 1 5 0 0 2 0 0 0 2 5 0 0 3 0 0 0

0 1 0 0 2 0 0 3 0 0 4 0 0 5 0 0 C O ( p p b )Z(m)

o b s e r v e d C

M A Q

E v e n i n g ( 1 7 - 1 9 E S T )

0 5 0 0 1 0 0 0 1 5 0 0 2 0 0 0 2 5 0 0 3 0 0 0

0 1 0 0 2 0 0 3 0 0 4 0 0 5 0 0 6 0 0 C O ( p p b )Z(m)

o b s e r v e d C

M A Q

## Figure 49.

Figure 50.

36 M o r n i n g ( 0 8 - 1 1 E ST )

0 5 0 0 1 0 0 0 1 5 0 0 2 0 0 0 2 5 0 0 3 0 0 0

0 1 2 3 4 5 6 SO 2 ( p p b )Z(m)

o b s e r v e d C

M A Q

A f t e r n o o o n ( 12 - 1 6 E

S T )

0 5 0 0 1 0 0 0 1 5 0 0 2 0 0 0 2 5 0 0 3 0 0 0

0 1 2 3 4 5 6 SO 2 ( p p b )Z(m)

o b s e r v e d C

M A Q

## Figure 51.

37 E v e n i n g ( 1 7 - 1 9 E S T )

0 5 0 0 1 0 0 0 1 5 0 0 2 0 0 0 2 5 0 0 3 0 0 0

0 1 2 3 4 5 SO 2 ( p p b )Z(m)

o b s e r v e d C

M A Q