# UNITED STATES ENVIRONMENTAL PROTECTION AGENCY Office of Air Quality Planning and Standards Research Triangle Park, NC 27711

April 14, 2011



# MEMORANDUM

SUBJECT: PM 10 

# and PM 10-2.5 

# Air Quality Analyses

FROM: Mark Schmidt, OAR/OAQPS/AQAD /s/

TO: PM NAAQS Review Docket EPA-OAR-2007-0492

Overview

This memorandum documents updates (since the analys es described in Schmidt and Jenkins, 2010) to PM 10 

# and PM 10-2.5 

# air quality analyses conducted to support the review of th e Particulate Matter (PM) national ambient air quality standard s (NAAQS). The purpose of these analyses is to inform staff conclusions on the current 24-hour PM 10 

# standard as well as on potential alternative standards meant to protect against exposures to PM 10-2.5 

# . The following are presented in this memo:

 Relationships between PM 10 

# expected exceedance concentration-equivalent design values and 98 th 

# percentile PM 10 

# concentration design values

 Comparison of the coeffici ents of variation for PM 10 

# expected exceedance concentrationequivalent design values and 98 th 

# percentile PM 10 

# concentration design values

 U.S. counties with monitors, and the population si zes in those counties, not likely to meet the current PM 10 

# standard as well as different potential alternative standards

 Detailed distributions of PM 10 

# air quality concentrations

General data processing

As described in Schmidt and Jenkins (2010), the air qua lity data for this projec t originated from EPA’s Air Quality System (AQS) data base, the offi cial repository of NAAQ S-comparable ambient measurements. See Schmidt and Je nkins (2010) for more detail.

Inter-Metric Comparability

The approach to comparing PM 10 

# expected exceedance concentration- equivalent design values and 98 th 

# percentile PM 10 

# concentration design values is the same as that described in Schmidt and Jenkins (2010). When the national analysis descri bed by Schmidt and Jenkins (2010) wa s conducted using air quality data from 1988 to 2008, a 98 th 

# percentile PM 10 

# concentration design value of 87 μg/m 3 

# was generally equivalent to the current standard level (Schmidt and Jenkins, 2010). Regional relationships from this analysis are presented below.

# 2 Figure 1: Regional 98th percentile PM 10 

# concentration design value s (y-axis) versus the PM 10 

# expected exceedance concentration-equivalent design values (x-axis) using 1988-2008 data*

*Bold regression lines reflect region-specific relationships between 98 th 

# percentile PM 10 

# concentration design values and PM 10 

# expected exceedance concentration-equivalent design values. Non-bolded regression lines reflect the overall relationship across all regions, as illustrated by Schmid t and Jenkins (2010). In some areas (i.e ., southeast, upper Midwest, northwest, southwest, and southern California), the two regression lines are almost indistinguishable. Vertical lines mark the level of t he current standard and horizontal lines mark a 98 th 

# percentile concentration of 87 μg/m 3



# .

# 3 When the national analysis was repeated using only the most recent air quality data available (2007 to 2009), a 98 th 

# percentile PM 10 

# concentration design value of 78 μg/m 3 

# was generally equivalent to the current standard level, on average across the U.S. as shown in Figure 2.

Figure 2: National 98th percentile PM 10 

# concentration design value s (y-axis) versus the PM 10 

# expected exceedance concentration-equivalent design values (x-axis) using 2007-2009 data

Comparison of the coefficients of variation for PM 10 

# expected exceedance concentration-equivalent design values and 98 th 

# percentile PM 10 

# concentration design values

Figure 3 below shows box-plots of the distributions of monito r-level coefficients of variation (COV) for PM 10 

# expected exceedance concentration-equivalent de sign values (left plot) and 98th percentile PM 10 

# concentration design values (right pl ot). Monitor-level design values were computed for all complete 3- year periods from 1988 through 2009. The COV in each of the the two types of design values were computed for all monitors that had at least 3 vali d pairs of (3-year) design va lues; there were 952 such monitors. As seen in the figure, there is more variation in the expected exceedance concentrationequivalent design values than in the 98th percentile PM 10 

# concentration design values. The mean COV of the expected exceedance concentration-equivalent de sign values is 70 percent higher than the mean COV of the 98th percentile PM 10 

# concentration design values. 0 10 20 30 40 50 60 70 80 90 100 110 120 130 140 150 160 170 180 190 200 210

0 50 100 150 200 250 300 

# • Note that the only valid 2007-2009 data pairs (i.e., those composed of three complete years) were considered for this evaluation. Further, the model was constrained to data pairs where the expected exceedance equivalent design values did not exceed 300 μg/m 3



# . • N = 596 (out of 613 valid pairs) • R-square: 0.70 • Model equation: 3yr_P98 = 19.4 + (0.38 *

EE_DV) • PM 10 

# 3yr P98 concentration equivalent to

a 154 μg/m3 EE_DV is ~ 78 μg/m 3 

# •Lower bound of 95% confidence interval = 52 μg/m 3 

# •Upper bound of 95% confidence interval = 104 μg/m 3 

# Current PM10 NAAQS

regression line

PM 10 

# expected exceedance concentration-equivalent design valuePM103-year average 98thpercentile 24-hr avg. concentration

# 4 Figure 3: Distribution of monitor-level coefficients of variation for the PM 10 

# expected exceedance concentration-equivalent design values and the 98th percentile PM 10 

# concentration design values based on data from 1988 through 2009



# PM 10 

# one-expectedexceedance concentrationequivalent design value 3-year average 98th percentile PM 10 

# concentration design valuecoefficients of variation (percent)

# 5 Numbers of counties with monitors, and population si zes in those counties, no t likely to meet the current PM 10 

# standard as well as pote ntial alternative standards

These analyses were conducted as described by Schmid t and Jenkins (2010), except that more recent air quality data were used (i.e., from 2007 to 2009) in this iteration.

Table 1: Estimates of the numbers and percentage s of counties with monitors, and populations, which are not likely to meet various alternative PM 10 

# NAAQS levels (based on 2007-2009 data)

Region > All U.S. Northeast Southeast Industrial Midwest Upper Midwest Southwest Northwest Southern California Outlying

areas Total # of counties with monitors > 307 37 57 50 40 25 77 18 3

Total population (x 1000) > 120,090 15,397 27,181 21,352 5,917 11,112 15,270 22,695 1,167

Potential Alternative Standard (μg/m 3 

# ) Statistic Numbers of counties with monitors, p opulations (x 1000), and percentages of total

87 # counties 37 0 2 2 2 11 10 9 1 population 20,515 0 4,063 507 552 5,924 1,789 7,421 260 % # counties 12% 0% 4% 4% 5% 44% 13% 50% 33% % population 17% 0% 15% 2% 9% 53% 12% 33% 22%

85 # counties 39 0 2 3 2 12 10 9 1 population 21,887 0 4,063 1,789 552 6,014 1,789 7,421 260 % # counties 13% 0% 4% 6% 5% 48% 13% 50% 33% % population 18% 0% 15% 8% 9% 54% 12% 33% 22%

80 # counties 45 0 2 4 3 13 11 11 1 population 24,535 0 4,063 3,183 599 6,131 1,833 8,467 260 % # counties 15% 0% 4% 8% 8% 52% 14% 61% 33% % population 20% 0% 15% 15% 10% 55% 12% 37% 22%

75 # counties 55 0 3 6 5 13 15 12 1 population 35,703 0 4,626 3,491 637 6,131 2,570 17,986 260 % # counties 18% 0% 5% 12% 13% 52% 19% 67% 33% % population 30% 0% 17% 16% 11% 55% 17% 79% 22%

70 # counties 71 0 4 7 7 13 27 12 1 population 43,823 0 4,644 8,868 881 6,131 5,052 17,986 260 % # counties 23% 0% 7% 14% 18% 52% 35% 67% 33% % population 36% 0% 17% 42% 15% 55% 33% 79% 22%

65 # counties 87 2 4 9 10 14 33 13 2 population 49,394 775 4,644 10,421 1,029 7,507 5,989 18,739 290 % # counties 28% 5% 7% 18% 25% 56% 43% 72% 67% % population 41% 5% 17% 49% 17% 68% 39% 83% 25%

Current Standard # counties 41 0 3 0 1 11 13 12 1 population 32,835 0 4,626 0 14 5,485 1,878 20,571 260 % # counties 13% 0% 5% 0% 3% 44% 17% 67% 33% % population 27% 0% 17% 0% 0% 49% 12% 91% 22%


# Identification of specific counties with mo nitors not likely to meet the current PM 10 

# standard as well as potential alternative standards

The tables below present information on the counties with monitors that are not likely to meet the current PM 10 

# standard, as well as potential alternative PM 10 

# standards, based on the most recent air quality data that is available (i.e., 2007-2009) as we ll as historic air quality data. Th e purpose of these tables is to use available data to provide some perspective on the potential impacts of revising the current PM 10 

# standard. The tables below do not reflect the o fficial list of counties that have been designated as “non-attainment” for PM 10 

# . That list can be found at the following website: http://www.epa.gov/airquality/greenbk/

.

# 6 Table 2: Counties with monitors that are not meeting the current PM 10 

# standard (based on 2007- 2009 data)

PM region name State County CBSA name

Northwest CO Archuleta Northwest CO Garfield Northwest CO Alamosa Northwest WY Albany Laramie, WY Northwest WY Sweetwater Rock Springs, WY Northwest UT Utah Provo-Orem, UT

Northwest CA Yolo Sacramento--Arden-Arcade--Roseville, CA Northwest CO La Pl ata Durango, CO Northwest CA Shasta Redding, CA Northwest UT Salt Lake Salt Lake City, UT Northwest WA Stevens Northwest CA Siskiyou Northwest CA Trinity Not in PMREG Region AK Anchorage Anchorage, AK Southeast AL Jefferson Birmingham-Hoover, AL Southeast OK Tulsa Tulsa, OK Southeast TX Harris Houston-Sugar Land-Baytown, TX Southern California CA Orange Los Angeles-Long Beach-Santa Ana, CA Southern California CA Ventura Oxnard-Thousand Oaks-Ventura, CA Southern California CA Los Angeles Los Angeles-Long Beach-Santa Ana, CA

Southern California CA Santa Barbara Santa Barbara-Santa Maria-Goleta, CA
Southern California CA Kern Bakersfield, CA Southern California CA Kings Hanford-Corcoran, CA Southern California CA San Diego San Diego-Carlsbad-San Marcos, CA

Southern California CA San Bernardino Riverside-San Bernardino-Ontario, CA Southern California NV Nye Pahrump, NV Southern California CA Imperial El Centro, CA Southern California CA Inyo Bishop, CA Southern California CA Riverside Riverside-San Bernardino-Ontario, CA Southwest AZ Cochise Sie rra Vista-Douglas, AZ Southwest AZ Pima Tucson, AZ Southwest AZ Gila Payson, AZ Southwest TX El Paso El Paso, TX Southwest AZ Maricopa Phoenix-Mesa-Scottsdale, AZ Southwest AZ Yuma Yuma, AZ Southwest CA Imperial El Centro, CA Southwest NM Luna Deming, NM Southwest AZ Santa Cruz Nogales, AZ Southwest NM Dona Ana Las Cruces, NM Southwest AZ Pinal Phoenix-Mesa-Scottsdale, AZ Upper Midwest CO Prowers

# 7 Table 3: Counties with monitors that are not meeting the current PM 10 

# standard (based on 2006- 2008 data)

PM region name State County CBSA name
Industrial Midwest MO St. Louis City St. Louis, MO-IL Northeast ME Aroostook Northwest UT Utah Provo-Orem, UT Northwest CO Garfield Northwest ID Power Pocatello, ID Northwest WY Sweetwater Rock Springs, WY

Northwest CA Yolo Sacramento--Arden-Arcade--Roseville, CA Northwest CA Shasta Redding, CA Northwest CA Mendocino Ukiah, CA Northwest CO Alamosa Northwest UT Salt Lake Salt Lake City, UT Northwest CA Siskiyou Northwest CA Trinity Not in PMREG Region AK Anchorage Anchorage, AK

Not in PMREG Region AK Matanuska Susitna Anchorage, AK Southeast AL Jefferson Birmingham-Hoover, AL Southeast TX Harris Houston-Sugar Land-Baytown, TX Southern California CA Orange Los Angeles-Long Beach-Santa Ana, CA Southern California CA Ventura Oxnard-Thousand Oaks-Ventura, CA Southern California CA Los Angeles Los Angeles-Long Beach-Santa Ana, CA Southern California CA Santa Barbara Santa Barbara-Santa Maria-Goleta, CA Southern California CA Kern Bakersfield, CA Southern California CA Riverside Riverside-San Bernardino-Ontario, CA Southern California CA Kings Hanford-Corcoran, CA Southern California NV Nye Pahrump, NV Southern California CA San Diego San Diego-Carlsbad-San Marcos, CA Southern California CA San Bernardino Riverside-San Bernardino-Ontario, CA Southern California CA Imperial El Centro, CA Southern California CA Inyo Bishop, CA Southwest NM Sandoval Albuquerque, NM Southwest AZ Cochise Sie rra Vista-Douglas, AZ Southwest AZ Pima Tucson, AZ Southwest AZ Gila Payson, AZ Southwest CA Imperial El Centro, CA Southwest AZ Yuma Yuma, AZ Southwest TX El Paso El Paso, TX Southwest AZ Maricopa Phoenix-Mesa-Scottsdale, AZ Southwest NM Dona Ana Las Cruces, NM Southwest AZ Santa Cruz Nogales, AZ Southwest AZ Pinal Phoenix-Mesa-Scottsdale, AZ Southwest NV Clark Las Vegas-Paradise, NV

# 8 Table 4: Counties with monitors that are not meeting the current PM 10 

# standard (based on 2005- 2007 data)

PM region name State County CBSA name
Industrial Midwest MO St. Louis City St. Louis, MO-IL Northeast ME Aroostook Northwest WY Campbell Gillette, WY Northwest CO Mesa Grand Junction, CO Northwest CO Alamosa Northwest UT Salt Lake Salt Lake City, UT Northwest WY Sweetwater Rock Springs, WY Northwest CA Siskiyou Not in PMREG Region AK Anchorage Anchorage, AK

Not in PMREG Region AK Matanuska Susitna Anchorage, AK Southeast AL Jefferson Birmingham-Hoover, AL Southeast TX Harris Houston-Sugar Land-Baytown, TX Southern California NV Nye Pahrump, NV Southern California CA Orange Los Angeles-Long Beach-Santa Ana, CA Southern California CA Ventura Oxnard-Thousand Oaks-Ventura, CA Southern California CA Los Angeles Los Angeles-Long Beach-Santa Ana, CA

Southern California CA Santa Barbara Santa Barbara-Santa Maria-Goleta, CA

Southern California CA Riverside Riverside-San Bernardino-Ontario, CA

Southern California CA San Bernardino Riverside-San Bernardino-Ontario, CA Southern California CA Imperial El Centro, CA Southern California CA Inyo Bishop, CA Southwest AZ Pima Tucson, AZ Southwest NM Sandoval Albuquerque, NM Southwest AZ Gila Payson, AZ Southwest NM Dona Ana Las Cruces, NM Southwest AZ Yuma Yuma, AZ Southwest CA Imperial El Centro, CA Southwest TX El Paso El Paso, TX Southwest AZ Maricopa Phoenix-Mesa-Scottsdale, AZ Southwest AZ Pinal Phoenix-Mesa-Scottsdale, AZ Southwest AZ Santa Cruz Nogales, AZ Upper Midwest MO Jasper Joplin, MO

# 9 Table 5: Counties with monitors that are not likely to meet potential alternative PM 10 

# standards with 98 th 

# percentile forms (based on ai r quality data from 2007 to 2009)

98 th 

# Percentile Standard Level PM region name State County CBSA name

85 μg/m 3 

# Industrial Midwest PA Allegheny Pittsburgh, PA

Industrial Midwest IA Scott Davenport-Moline-Rock Island, IA-IL Industrial Midwest MO St. Louis City St. Louis, MO-IL Upper Midwest NE Douglas Omaha-Council Bluffs, NE-IA Upper Midwest SD Pennington Rapid City, SD Southwest NM Bernalillo Albuquerque, NM Southwest NM Sandoval Albuquerque, NM Northwest WY Campbell Gillette, WY Northwest WY Converse Northwest CO Gunnison Northwest NV Washoe Reno-Sparks, NV Southern California CA Tulare Visalia-Porterville, CA Not in PMREG Region AK Anchorage Anchorage, AK

Southeast TX Harris Houston-Sugar LandBaytown, TX Southeast AL Jefferson Birmingham-Hoover, AL Southwest NM Dona Ana Las Cruces, NM Southwest TX El Paso El Paso, TX Southwest AZ Gila Payson, AZ Southwest CA Imperial El Centro, CA Southwest NM Luna Deming, NM Southwest AZ Maricopa Phoenix-Mesa-Scottsdale, AZ Southwest AZ Pima Tucson, AZ Southwest AZ Pinal Phoenix-Mesa-Scottsdale, AZ Southwest AZ Santa Cruz Nogales, AZ Southwest AZ Yuma Yuma, AZ Northwest WY Albany Laramie, WY Northwest UT Salt Lake Salt Lake City, UT Northwest WA Stevens Northwest WY Sweetwater Rock Springs, WY Northwest CA Trinity Northwest UT Utah Provo-Orem, UT Southern California CA Imperial El Centro, CA Southern California CA Inyo Bishop, CA Southern California CA Kern Bakersfield, CA Southern California CA Kings Hanford-Corcoran, CA Southern California NV Nye Pahrump, NV

Southern California CA Riverside Riverside-San BernardinoOntario, CA

Southern California CA San Bernardino Riverside-San BernardinoOntario, CA Southern California CA San Diego San Diego-Carlsbad-San Marcos, CA

80 μg/m 3 

# * 

# Industrial Midwest OH Cuyahoga Cleveland-Elyria-Mentor, OH Upper Midwest IA Cerro Gordo Mason City, IA Southern California CA Fresno Fresno, CA

Southern California CA San Luis Obispo San Luis Obispo-Paso Robles, CA Southwest AZ Cochise Sie rra Vista-Douglas, AZ Northwest CO Garfield

# 10 75 μg/m 3 

# * 

# Industrial Midwest KY Boyd Huntington-Ashland, WV-KYOH Industrial Midwest IL Madison St. Louis, MO-IL Upper Midwest NE Cass Omaha-Council Bluffs, NE-IA Northwest MT Flathead Kalispell, MT Northwest CO Routt Northwest CA Stanislaus Modesto, CA Northwest UT Weber Ogden-Clearfield, UT Southeast OK Tulsa Tulsa, OK Upper Midwest CO Prowers Southern California CA Los Angeles Los Angeles-Long BeachSanta Ana, CA

70 μg/m 3 

# * 

# Southeast TN Union Knoxville, TN

Industrial Midwest IL Cook Chicago-Naperville-Joliet, ILIN-WI Upper Midwest MO Buchanan St. Joseph, MO-KS Upper Midwest KS Wyandotte Kansas City, MO-KS Northwest CO Adams Denver-Aurora, CO Northwest CA Butte Chico, CA Northwest UT Davis Ogden-Clearfield, UT Northwest CA Glenn Northwest OR Klamat h Klamath Falls, OR Northwest WY Lincoln Northwest CO Mesa Grand Junction, CO Northwest CA Mono

Northwest CA Sacramento Sacramento--Arden-Arcade-- Roseville, CA Northwest MT Silver Bow Butte-Silver Bow, MT Northwest CO Alamosa

Northwest CA Yolo Sacramento--Arden-Arcade-- Roseville, CA

65 μg/m 3 

# * 

# Not in PMREG Region PR Catano San Juan-Caguas-Guaynabo, PR

Northeast NJ Camden Philadelphia-CamdenWilmington, PA-NJ-DE-MD

Northeast ME Cumberland Portland-South PortlandBiddeford, ME Industrial Midwest OH Franklin Columbus, OH

Industrial Midwest IN Lake Chicago-Naperville-Joliet, ILIN-WI Upper Midwest SD Codington Watertown, SD Upper Midwest MO Jasper Joplin, MO Upper Midwest KS Neosho Southwest NV Clark Las Vegas-Paradise, NV Northwest ID Canyon Boise City-Nampa, ID Northwest CA Mariposa Northwest CA Merced Merced, CA Northwest ID Power Pocatello, ID Northwest CA San Joaquin Stockton, CA Northwest CO San Miguel

Southern California CA Ventura Oxnard-Thousand OaksVentura, CA *Listed counties are those additional counties (i.e., in addition to the counties listed for higher 98 th 

# percentile standard levels) that are not likely to meet a potential alternative standard with a 98 th 

# percentile form. For example, all of the counties listed in this table are not likely to meet a 98 th 

# percentile standard with a level of 65 μg/m 3



# .

# 11 Table 6: Counties with monitors that are not likely to meet potential alternative PM 10 

# standards with 98 th 

# percentile forms (based on ai r quality data from 2006 to 2008)

Standard Level PM region name State County CBSA name

85 μg/m 3 

# Industrial Midwest PA Allegheny Pittsburgh, PA Industrial Midwest IA Scott Davenport-Moline-Rock Island, IA-IL Industrial Midwest MO St. Louis City St. Louis, MO-IL Northwest WY Campbell Gillette, WY Northwest WY Converse Northwest MT Flathead Kalispell, MT Northwest CO Gunnison Northwest NV Washoe Reno-Sparks, NV Northwest UT Salt Lake Salt Lake City, UT Northwest WY Sweetwater Rock Springs, WY Northwest CA Trinity Not in PMREG Region AK Anchorage Anchorage, AK Southeast TX Harris Houston-Sugar Land-Baytown, TX Southeast AL Jefferson Birmingham-Hoover, AL Southern California CA Fresno Fresno, CA Southern California CA San Luis Obispo San Luis Obispo-Paso Robles, CA Southern California CA Tulare Visalia-Porterville, CA Southern California CA Imperial El Centro, CA Southern California CA Inyo Bishop, CA Southern California CA Kern Bakersfield, CA Southern California CA Kings Hanford-Corcoran, CA Southern California NV Nye Pahrump, NV Southern California CA Riverside Riverside-San Bernardino-Ontario, CA Southern California CA San Bernardino Riverside-San Bernardino-Ontario, CA Southern California CA San Diego San Diego-Carlsbad-San Marcos, CA Southwest NM Bernalillo Albuquerque, NM Southwest NM Dona Ana Las Cruces, NM Southwest TX El Paso El Paso, TX Southwest AZ Gila Payson, AZ Southwest CA Imperial El Centro, CA Southwest AZ Maricopa Phoenix-Mesa-Scottsdale, AZ Southwest AZ Pima Tucson, AZ Southwest AZ Pinal Phoenix-Mesa-Scottsdale, AZ Southwest NM Sandoval Albuquerque, NM Southwest AZ Santa Cruz Nogales, AZ Southwest AZ Yuma Yuma, AZ Upper Midwest NE Cass Omaha-Council Bluffs, NE-IA Upper Midwest IA Cerro Gordo Mason City, IA Upper Midwest NE Douglas Omaha-Council Bluffs, NE-IA Upper Midwest SD Pennington Rapid City, SD Upper Midwest KS Wyandotte Kansas City, MO-KS

80 μg/m 3 * 

# Industrial Midwest KY Boyd Huntington-Ashland, WV-KY-OH Northwest CO Alamosa Northwest CO Garfield Southeast TN Union Knoxville, TN Southern California CA Orange Los Angeles-Long Beach, CA Upper Midwest MO Jasper Joplin, MO

# 12 75 μg/m 3 * 

# Northeast ME Aroostook Northwest CO Adams Denver-Aurora, CO Northwest MT Big Horn Northwest CA Butte Chico, CA Northwest CO Routt Northwest CA San Joaquin Stockton, CA Northwest CA Stanislaus Modesto, CA Northwest ID Power Pocatello, ID Northwest UT Utah Provo-Orem, UT Northwest CA Yolo Sacramento--Arden-Arcade--Roseville, CA Southeast OK Kay Ponca City, OK Southeast SC Lexington Columbia, SC Southern California CA Los Angeles Los Angeles-Long Beach-Santa Ana, CA Southwest NV Clark Las Vegas-Paradise, NV Southwest AZ Cochise Sie rra Vista-Douglas, AZ

70 μg/m 3 * 

# Industrial Midwest IL Cook Chi cago-Naperville-Joliet, IL-IN-WI Industrial Midwest OH Cuyahoga Cleveland-Elyria-Mentor, OH Industrial Midwest IN Lake Chicago-Naperville-Joliet, IL-IN-WI Northwest CA Merced Merced, CA Northwest CO Mesa Grand Junction, CO Northwest CA Mono Northwest MT Silver Bow Butte-Silver Bow, MT Not in PMREG Region PR Catano San Juan-Caguas-Guaynabo, PR Not in PMREG Region PR Guaynabo San Juan-Caguas-Guaynabo, PR Not in PMREG Region AK Matanuska Susitna Anchorage, AK Southeast LA West Baton Rouge Baton Rouge, LA Southwest AZ Apache Upper Midwest MO Buchanan St. Joseph, MO-KS Upper Midwest CO Prowers

65 μg/m 3 * 

# Industrial Midwest WV Brooke Weirton-Steubenville, WV-OH Industrial Midwest OH Franklin Columbus, OH Industrial Midwest PA Lawrence New Castle, PA Industrial Midwest IL Madison St. Louis, MO-IL Industrial Midwest IN Perry Industrial Midwest MI Wayne Detroit-Warren-Livonia, MI Northeast ME Cumberland Portland-South Portland-Biddeford, ME Northeast VA Frederick Winchester, VA-WV Northeast PA Northampton Alle ntown-Bethlehem-Easton, PA-NJ Northwest ID Canyon Boise City-Nampa, ID Northwest UT Davis Ogden-Clearfield, UT Northwest OR Klamat h Klamath Falls, OR Northwest CA Mariposa Northwest MT Missoula Missoula, MT Northwest WY Sheridan Sheridan, WY Northwest WA Spokane Spokane, WA Northwest CA Tehama Red Bluff, CA Northwest WA Walla Walla Walla Walla, WA Northwest UT Weber Ogden-Clearfield, UT Northwest CA Shasta Redding, CA Southeast TX Nueces Co rpus Christi, TX Southern California CA Ventura Oxnard-Thousand Oaks-Ventura, CA Southwest TX Hidalgo McAllen-Edinburg-Mission, TX Southwest TX Webb Laredo, TX Upper Midwest KS Neosho *Listed counties are those additional counties (i.e., in addition to the counties listed for higher 98 th 

# percentile standard levels) that are not likely to meet a potential alternative standard with a 98 th 

# percentile form. For example, all of the counties listed in this table are not likely to meet a 98 th 

# percentile standard with a level of 65 μg/m 3



# .

# 13 Table 7: Counties with monitors that are not likely to meet potential alternative PM 10 

# standards with 98 th 

# percentile forms (based on ai r quality data from 2005 to 2007)

Standard Level PM region name State County CBSA name

85 μg/m 3 

# Industrial Midwest PA Allegheny Pittsburgh, PA Industrial Midwest IA Scott Davenport-Moline-Rock Island, IA-IL Industrial Midwest MO St. Louis City St. Louis, MO-IL Northwest WY Converse Northwest NV Washoe Reno-Sparks, NV Northwest WY Campbell Gillette, WY Northwest UT Salt Lake Salt Lake City, UT Northwest WY Sweetwater Rock Springs, WY Not in PMREG AK Anchorage Anchorage, AK Southeast OK Kay Ponca City, OK Southeast SC Lexington Columbia, SC Southeast TX Harris Houston-Sugar Land-Baytown, TX Southeast AL Jefferson Birmingham-Hoover, AL Southern California CA Fresno Fresno, CA Southern California CA Kern Bakersfield, CA Southern California CA Kings Hanford-Corcoran, CA Southern California CA Tulare Visalia-Porterville, CA Southern California CA Imperial El Centro, CA Southern California CA Inyo Bishop, CA Southern California CA Riverside Riverside-San Bernardino-Ontario, CA Southern California CA San Bernardino Riverside-San Bernardino-Ontario, CA Southwest NM Bernalillo Albuquerque, NM Southwest NM Dona Ana Las Cruces, NM Southwest TX El Paso El Paso, TX Southwest AZ Gila Payson, AZ Southwest CA Imperial El Centro, CA Southwest AZ Maricopa Phoenix-Mesa-Scottsdale, AZ Southwest AZ Pima Tucson, AZ Southwest AZ Pinal Phoenix-Mesa-Scottsdale, AZ Southwest NM Sandoval Albuquerque, NM Southwest AZ Santa Cruz Nogales, AZ Southwest AZ Yuma Yuma, AZ Upper Midwest NE Cass Omaha-Council Bluffs, NE-IA Upper Midwest IA Cerro Gordo Mason City, IA Upper Midwest NE Douglas Omaha-Council Bluffs, NE-IA Upper Midwest SD Pennington Rapid City, SD Upper Midwest MO Jasper Joplin, MO

80 μg/m 3 

# * 

# Industrial Midwest IN Lake Chicago-Naperville-Joliet, IL-IN-WI Northwest CO Adams Denver-Aurora, CO Northwest MT Flathead Kalispell, MT Northwest CO Gunnison Not in PMREG region PR Catano San Juan-Caguas-Guaynabo, PR

Not in PMREG region PR Ponce Ponce, PR
Southeast TN Union Knoxville, TN

75 μg/m 3 

# * 

# Industrial Midwest KY Boyd Huntington-Ashland, WV-KY-OH Industrial Midwest IL Cook Chi cago-Naperville-Joliet, IL-IN-WI Industrial Midwest OH Cuyahoga Cleveland-Elyria-Mentor, OH Industrial Midwest MI Wayne Detroit-Warren-Livonia, MI Northeast PA Northampton Alle ntown-Bethlehem-Easton, PA-NJ Northwest CA Santa Clara San Jose-Sunnyvale-Santa Clara, CA

# 14 Northwest WY Sheridan Sheridan, WY Northwest CA Stanislaus Modesto, CA Northwest CO Alamosa Not in PMREG region AK Matanuska Susitna Anchorage, AK Southeast SC Georgetown Georgetown, SC Southeast FL Manatee Sarasota-Bradenton-Venice, FL Southern California NV Nye Pahrump, NV Southwest NV Clark Las Vegas-Paradise, NV Southwest AZ Cochise Sie rra Vista-Douglas, AZ Upper Midwest KS Wyandotte Kansas City, MO-KS

70 μg/m 3 

# * 

# Industrial Midwest WV Brooke Weirton-Steubenville, WV-OH Industrial Midwest OH Franklin Columbus, OH Northwest UT Davis Ogden-Clearfield, UT Northwest CA Merced Merced, CA Northwest CO Routt Northwest MT Silver Bow Butte-Silver Bow, MT Northwest WA Spokane Spokane, WA Northwest UT Utah Provo-Orem, UT Northwest CO Mesa Grand Junction, CO Not in PMREG region PR Guaynabo San Juan-Caguas-Guaynabo, PR Southeast TX Cameron Brownsville-Harlingen, TX Southeast TN McMinn Athens, TN Southeast LA West Baton Rouge Baton Rouge, LA Southern California CA Los Angeles Los Angeles-Long Beach, CA Southern California CA Orange Los Angeles-Long Beach, CA Southwest TX Webb Laredo, TX

65 μg/m 3 

# * 

# Industrial Midwest PA Beaver Pittsburgh, PA Industrial Midwest OH Columbiana East Liverpool-Salem, OH Industrial Midwest WV Hancock Weirton-Steubenville, WV-OH Industrial Midwest PA Lawrence New Castle, PA Industrial Midwest IL Madison St. Louis, MO-IL Industrial Midwest IN Perry Industrial Midwest IL Saint Clair St. Louis, MO-IL Industrial Midwest OH Scioto Portsmouth, OH Northeast ME Aroostook Northwest OR Klamat h Klamath Falls, OR Northwest MT Lincoln Northwest CA Mono Northwest ID Power Pocatello, ID Northwest CA San Joaquin Stockton, CA Northwest CO Summit Silverthorne, CO Northwest WA Walla Walla Walla Walla, WA Northwest UT Weber Ogden-Clearfield, UT Not in PMREG region PR San Juan San Juan-Caguas-Guaynabo, PR Southeast FL Hillsborough Tampa- St. Petersburg-Clearwater, FL Southeast OK Mus kogee Muskogee, OK Southern California CA Ventura Oxnard-Thousand Oaks-Ventura, CA Southwest TX Hidalgo McAllen-Edinburg-Mission, TX Upper Midwest MN Ramsey Minneapolis-St. Paul, MN-WI *Listed counties are those additional counties (i.e., in addition to the counties listed for higher 98 th 

# percentile standard levels) that are not likely to meet a potential alternative standard with a 98 th 

# percentile form. For example, all of the counties listed in this table are not likely to meet a 98 th 

# percentile standard with a level of 65 μg/m 3



# .

# 15 Table 8: Counties with monitors that meet the current standard but are not likely to meet a potential alternative standard with a 98 th 

# percentile form (based on air quality from 2007 to 2009) #



# Potential Alternative Standard PM region name State County CBSA name

85 μg/m 3 

# Industrial Midwest IA Scott Davenport-Moline-Rock Island, IA-IL MO St. Louis City St. Louis, MO-IL PA Allegheny Pittsburgh, PA

Northwest CO Gunnison NV Washoe Reno-Sparks, NV WY Campbell Gillette, WY
WY Converse Southern California CA Tulare Visalia-Porterville, CA

Southwest NM Bernalillo Albuquerque, NM NM Sandoval Albuquerque, NM

Upper Midwest NE Douglas Omaha-Council Bluffs, NE-IA SD Pennington Rapid City, SD

80 μg/m 3 

# * Industrial Midwest OH Cuyahoga Cleveland-Elyria-Mentor, OH

Southern California CA Fresno Fresno, CA CA San Luis Obispo San Luis Obispo-Paso Robles, CA Upper Midwest IA Cerro Gordo Mason City, IA

75 μg/m 3 

# * Industrial Midwest IL Madison St. Louis, MO-IL KY Boyd Huntington-Ashland, WV-KY-OH

Northwest CA Stanislaus Modesto, CA
CO Routt MT Flathead Kalispell, MT UT Weber Ogden-Clearfield, UT Upper Midwest NE Cass Omaha-Council Bluffs, NE-IA

70 μg/m 3 

# * Industrial Midwest IL Cook Chi cago-Naperville-Joliet, IL-IN-WI

Northwest CA Butte Chico, CA
CA Glenn
CA Mono

CA Sacramento Sacramento--Arden-Arcade--Roseville, CA CO Adams Denver-Aurora, CO CO Mesa Grand Junction, CO MT Silver Bow Butte-Silver Bow, MT OR Klamath Klamath Falls, OR UT Davis Ogden-Clearfield, UT
WY Lincoln
Southeast TN Union Knoxville, TN

Upper Midwest KS Wyandotte Kansas City, MO-KS MO Buchanan St. Joseph, MO-KS

# 16 65 μg/m 3 

# * Industrial Midwest IN Lake Chicago-Naperville-Joliet, IL-IN-WI OH Franklin Columbus, OH

Northeast ME Cumberland Portland-South Portland-Biddeford, ME

NJ Camden Philadelphia-Camden-Wilmington, PA-NJ-DE-MD

Northwest CA Mariposa CA Merced Merced, CA CA San Joaquin Stockton, CA CO San Miguel ID Canyon Boise City-Nampa, ID ID Power Pocatello, ID Southwest NV Clark Las Vegas-Paradise, NV

Upper Midwest KS Neosho MO Jasper Joplin, MO SD Codington Watertown, SD Not in PMREG Region PR Catano San Juan-Caguas-Guaynabo, PR

# 

# PM 10 

# air quality in these counties is characterized in more detail in the appendix to this memo (see below). *Listed counties are those additional counties (i.e., in addition to the counties listed for higher 98 th 

# percentile standard levels) that meet the current standard bu t are not likely to meet a potential alternative standard with a 98 th 

# percentile form. For example, all of the counties listed in this table are not likely to meet a 98 th 

# percentile standard with a level of 65 μg/m 3



# .



# Table 9: Counties with monitors that do not meet the current standard but are likely to meet a potential alternative standard with a 98 th 

# percentile form (based on air quality from 2007 to 2009) #

# 

# PM 10 

# air quality in these counties is characterized in more detail in the appendix to this memo (see below). *Listed counties are those additional counties (i.e., in addition to the counties listed for lower 98 th 

# percentile standard levels) that are not likely to meet the cu rrent standard but meet a potential alternative standard with a 98 th 

# percentile form. For example, all counties listed in this table are likely to meet a 98 th 

# percentile standard with a level of 85 μg/m 3



# .



# References Schmidt, M., Jenkins S.M. (2010). Analyses of PM 10 

# and PM 10-2.5 

# Data for the PM NAAQS Review. Memorandum to PM NAAQS re view docket EPA-HQ-OAR-2007-0492. 98 th 

# Percentile Standard Level PM region name State County CBSA name

65 μg/m 3 

# Northwest CA Shasta Redding, CA CA Siskiyou CO Archuleta CO La Plata Durango, CO

Southern California CA Orange Los Angeles-Long Beach-Santa Ana, CA CA Santa Barbara Santa Barbara-Santa Maria-Goleta, CA 70 μg/m 3 

# * Southern California CA Ventura Oxnard-Thousand Oaks-Ventura, CA
75 μg/m 3 

# * Northwest CA Yolo Sacramento--Arden-Arcade--Roseville, CA CO Alamosa

80 μg/m 3 

# * Southeast OK Tulsa Tulsa, OK Southern California CA Los Angeles Los Angeles-Long Beach-Santa Ana, CA Upper Midwest CO Prowers
85 μg/m 3 

# * Northwest CO Garfield Southwest AZ Cochise Sie rra Vista-Douglas, AZ

# 17 Appendix: PM 10 

# Air Quality Distributions

# 18 Table A-1: Average 24-Hour PM 10 

# concentrations in counties with monitors that meet the current PM 10 

# standard but are not likely to meet a potential alternative standard with a 98 th 

# percentile form and a level of 75 μg/m 3 

# (2007-2009)

County 3-year average PM 10 

# concentration (μg/m 3 

# ) 

# * 3-year average of the annual 98 th 

# percentile PM 10 

# concentration (μg/m 3 

# ) 

# *

Fresno 37.3 80.7 San Luis Obispo 24.5 78.7 Stanislaus 28.2 75.7 Tulare 43.2 88.7 Gunnison 28.4 90.0 Routt 24.7 77.7 Madison 33.0 76.0 Cerro Gordo 32.0 82.3 Scott 40.7 93.7 Boyd 31.2 76.7 St. Louis 36.9 97.3 Cass 27.5 79.7 Douglas 36.5 92.3 Washoe 40.0 96.7 Bernalillo 36.5 104.3 Sandoval 42.7 86.0 Cuyahoga 34.8 80.7 Allegheny 31.0 85.7 Pennington 33.5 95.3 Weber 26.5 75.7 Campbell 33.0 90.7 Converse 34.4 93.0 Flathead 28.8 78.0 Average 33.3 85.9 *Distributions of PM 10 

# concentrations for the counties included in Tables A-1 and A-2 are presented below. For the 3-year average of 98 th 

# percentile PM 10 

# concentrations, we averaged together 98 th 

# percentile concentrations for 2007, 2008, and 2009 (labeled “EPA_P98” in the tables below).


# Table A-2: Average PM 10 

# concentrations in counties with moni tors that do not meet the current PM 10 

# standard but are likely to meet a po tential alternative standard with a 98 th 

# percentile form and a level of 75 μg/m 3 

# (2007-2009)

County 3-year average PM 10 

# concentration (μg/m 3 

# ) 

# * 3-year average of the annual 98 th 

# percentile PM 10 

# concentration (μg/m 3 

# ) 

# * Orange 32.8 61.0 Santa Barbara 20.6 54.0 Shasta 17.0 59.0 Siskiyou 16.8 63.3 Ventura 26.1 69.3 Yolo 25.7 74.3 Alamosa 26.9 71.3 Archuleta 23.7 57.3 La Plata 20.7 48.3 Average 23.4 62.0 *Distributions of PM 10 

# concentrations for the counties included in Tables A-1 and A-2 are presented below. For the 3-year average of 98 th 

# percentile PM 10 

# concentrations, we averaged together 98 th 

# percentile concentrations for 2007, 2008, and 2009 (labeled “EPA_P98” in the tables below).

# 19 PM 10 

# air quality distributions at monitors in count ies that meet the current standard but are not likely to meet a potential al ternative standard with a 98 th 

# percentile form and a level of 75 μg/m 3

0 25 50 75 100 125 150 175 200 225 250 275 300 325 350 375 400 425 450 475 500

2007 2008 2009 3 years 

### SITE=060190007 POC=1

71 87 84 EPA_P98 1 060190007 98 84 98 92 max 1 060190007 92 84 98 92 Pct99 1 060190007 84 71 87 84 Pct98 1 060190007 80 71 87 84 Pct97 1 060190007 77 69 80 78 Pct96 1 060190007 72 69 77 78 Pct95 1 060190007 67 63 69 70 Pct90 1 060190007 56 51 61 57 Pct85 1 060190007 52 50 55 48 Pct80 1 060190007 48 45 53 47 Pct75 1 060190007 0 0 0 0 n > 154 1 060190007 9 1 4 4 n 76 - 154 1 060190007 173 61 57 55 n < 76 1 060190007 182 62 61 59 n 1 060190007 33 30 35 35 median 1 060190007 37.26 34.55 39.64 37.66 mean 1 060190007 3 yrs 2009 2008 2007 Statistic P O C Site 

# Meets EE-154, violates P98-75

# 20 0 25 50 75 100 125 150 175 200 225 250 275 300 325 350 375 400 425 450 475 500

2007 2008 2009 3 years 

### SITE=060792004 POC=1

78 75 83 EPA_P98 1 060792004 130 101 88 130 max 1 060792004 101 101 88 130 Pct99 1 060792004 83 78 75 83 Pct98 1 060792004 75 78 75 83 Pct97 1 060792004 73 73 63 69 Pct96 1 060792004 63 73 63 69 Pct95 1 060792004 54 56 50 57 Pct90 1 060792004 43 51 41 38 Pct85 1 060792004 35 45 35 29 Pct80 1 060792004 29 29 33 26 Pct75 1 060792004 0 0 0 0 n > 154 1 060792004 5 2 1 2 n 76 - 154 1 060792004 169 57 55 57 n < 76 1 060792004 174 59 56 59 n 1 060792004 17 17 17 19 median 1 060792004 24.52 24.86 24.09 24.59 mean 1 060792004 3 yrs 2009 2008 2007 Statistic P O C Site 

# Meets EE-154, violates P98-75

0 25 50 75 100 125 150 175 200 225 250 275 300 325 350 375 400 425 450 475 500

2007 2008 2009 3 years SITE=060990005 POC=3

64 88 75 EPA_P98 3 060990005 111 65 111 83 max 3 060990005 88 65 111 83 Pct99 3 060990005 75 64 88 75 Pct98 3 060990005 73 64 88 75 Pct97 3 060990005 70 60 73 73 Pct96 3 060990005 69 59 73 73 Pct95 3 060990005 53 51 69 50 Pct90 3 060990005 45 39.5 49 43 Pct85 3 060990005 40 36.5 48 39 Pct80 3 060990005 37.5 30 42 34 Pct75 3 060990005 0 0 0 0 n > 154 3 060990005 3 0 2 1 n 76 - 154 3 060990005 173 60 55 58 n < 76 3 060990005 176 60 57 59 n 3 060990005 21 20 25 21 median 3 060990005 28.16 25.57 32.28 26.81 mean 3 060990005 3 yrs 2009 2008 2007 Statistic P O C Site 

# Meets EE-154, violates P98-75

# 21 0 25 50 75 100 125 150 175 200 225 250 275 300 325 350 375 400 425 450 475 500

2007 2008 2009 3 years SITE=061072002 POC=2

87 91 88 EPA_P98 2 061072002 103 92 103 98 max 2 061072002 98 92 103 98 Pct99 2 061072002 91 87 91 88 Pct98 2 061072002 87 87 91 88 Pct97 2 061072002 85 78 85 85 Pct96 2 061072002 80 75 82.5 82.5 Pct95 2 061072002 68 66 72 65.5 Pct90 2 061072002 61 61 66.5 58 Pct85 2 061072002 58 53 63.5 54.5 Pct80 2 061072002 54 52 59 51 Pct75 2 061072002 0 0 0 0 n > 154 2 061072002 13 3 5 5 n 76 - 154 2 061072002 168 58 55 55 n < 76 2 061072002 181 61 60 60 n 2 061072002 41 38 43 40 median 2 061072002 43.22 41.23 46.35 42.12 mean 2 061072002 3 yrs 2009 2008 2007 Statistic P O C Site 

# Meets EE-154, violates P98-75

0 25 50 75 100 125 150 175 200 225 250 275 300 325 350 375 400 425 450 475 500

2007 2008 2009 3 years SITE=080510004 POC=2

83 97 90 EPA_P98 2 080510004 109 99 108 109 max 2 080510004 99 83 99 94 Pct99 2 080510004 91 83 97 90 Pct98 2 080510004 83 76 91 66 Pct97 2 080510004 67 67 91 65 Pct96 2 080510004 65 57 76 60 Pct95 2 080510004 51 42 58 49 Pct90 2 080510004 44 38 48 46 Pct85 2 080510004 38 33 43 39 Pct80 2 080510004 34 30 36 36.5 Pct75 2 080510004 0 0 0 0 n > 154 2 080510004 14 4 7 3 n 76 - 154 2 080510004 342 114 115 113 n < 76 2 080510004 356 118 122 116 n 2 080510004 24 21 25 26 median 2 080510004 28.36 25.1 30.34 29.59 mean 2 080510004 3 yrs 200 9 2008 2007 Statistic P O C Site 

# Meets EE-154, violates P98-75

# 22 0 25 50 75 100 125 150 175 200 225 250 275 300 325 350 375 400 425 450 475 500

2007 2008 2009 3 years SITE=081070003 POC=2

74 80 79 EPA_P98 2 081070003 124 83 124 99 max 2 081070003 83 78 98 84 Pct99 2 081070003 77 73.5 80 79 Pct98 2 081070003 69 63 75 65 Pct97 2 081070003 62 60.5 70 57 Pct96 2 081070003 57 57 67 54 Pct95 2 081070003 47 49.5 49 39 Pct90 2 081070003 37 42 40 32 Pct85 2 081070003 32 32 36 30 Pct80 2 081070003 29 27 32 28 Pct75 2 081070003 0 0 0 0 n > 154 2 081070003 21 5 8 8 n 76 - 154 2 081070003 984 345 290 349 n < 76 2 081070003 1005 350 298 357 n 2 081070003 20 18 23 21 median 2 081070003 24.67 23.51 26.91 23.93 mean 2 081070003 3 yrs 2009 2008 2007 Statistic P O C Site 

# Meets EE-154, violates P98-75

0 25 50 75 100 125 150 175 200 225 250 275 300 325 350 375 400 425 450 475 500

2007 2008 2009 3 years SITE=171191007 POC=4

54 79 95 EPA_P98 4 171191007 128 68 100 128 max 4 171191007 95 59 86 107 Pct99 4 171191007 85 54 79 95 Pct98 4 171191007 75 49 73 90 Pct97 4 171191007 72 48 72 87 Pct96 4 171191007 68 44 67 78 Pct95 4 171191007 56 38 57 67 Pct90 4 171191007 51 35 50 58 Pct85 4 171191007 48 33 47 53 Pct80 4 171191007 43 30 45 50.5 Pct75 4 171191007 0 0 0 0 n > 154 4 171191007 27 0 8 19 n 76 - 154 4 171191007 876 243 328 305 n < 76 4 171191007 903 243 336 324 n 4 171191007 28 22 30 36 median 4 171191007 32.99 24.23 33.26 39.27 mean 4 171191007 3 yrs 2009 2008 2007 Statistic P O C Site 

# Meets EE-154, violates P98-75

# 23 0 25 50 75 100 125 150 175 200 225 250 275 300 325 350 375 400 425 450 475 500

2007 2008 2009 3 years SITE=190330018 POC=1

68 84 95 EPA_P98 1 190330018 162 97 104 162 max 1 190330018 97 74 99 103 Pct99 1 190330018 84 68 84 95 Pct98 1 190330018 74 67 77 87 Pct97 1 190330018 71 63 74 77 Pct96 1 190330018 69 61 71 72 Pct95 1 190330018 56 50 59 61 Pct90 1 190330018 49 44 50 53 Pct85 1 190330018 45 38.5 46 47 Pct80 1 190330018 40.5 35 42 44 Pct75 1 190330018 1 0 0 1 n > 154 1 190330018 29 2 12 15 n 76 - 154 1 190330018 1066 363 354 349 n < 76 1 190330018 1096 365 366 365 n 1 190330018 28 25 28 32 median 1 190330018 31.96 27.43 32.52 35.92 mean 1 190330018 3 yrs 2009 2008 2007 Statistic P O C Site 

# Meets EE-154, violates P98-75

0 25 50 75 100 125 150 175 200 225 250 275 300 325 350 375 400 425 450 475 500

2007 2008 2009 3 years SITE=191630017 POC=2

96 85 100 EPA_P98 2 191630017 119 119 116 113 max 2 191630017 103 105 98 104 Pct99 2 191630017 96 96 85 100 Pct98 2 191630017 91 94 81 95 Pct97 2 191630017 86 88 77 93 Pct96 2 191630017 83 83 76 87 Pct95 2 191630017 72 65 67 78 Pct90 2 191630017 63 60 60 71 Pct85 2 191630017 58 55.5 55 64 Pct80 2 191630017 53 50 52 57 Pct75 2 191630017 0 0 0 0 n > 154 2 191630017 94 28 20 46 n 76 - 154 2 191630017 998 337 344 317 n < 76 2 191630017 1092 365 364 363 n 2 191630017 36.5 34 36.5 38 median 2 191630017 40.65 38.61 39.33 44.02 mean 2 191630017 3 yrs 2009 2008 2007 Statistic P O C Site 

# Meets EE-154, violates P98-75

# 24 0 25 50 75 100 125 150 175 200 225 250 275 300 325 350 375 400 425 450 475 500

2007 2008 2009 3 years SITE=210190002 POC=1

49 87 94 EPA_P98 1 210190002 117 100 117 98 max 1 210190002 100 100 117 98 Pct99 1 210190002 94 49 87 94 Pct98 1 210190002 87 49 87 94 Pct97 1 210190002 77 47 79 92 Pct96 1 210190002 76 47 76 92 Pct95 1 210190002 54 43 54 69 Pct90 1 210190002 47 37 46 61 Pct85 1 210190002 45 32 39 50 Pct80 1 210190002 41 29 37 47 Pct75 1 210190002 0 0 0 0 n > 154 1 210190002 9 1 4 4 n 76 - 154 1 210190002 167 56 57 54 n < 76 1 210190002 176 57 61 58 n 1 210190002 25 20 23 38.5 median 1 210190002 31.2 24.02 30.56 38.95 mean 1 210190002 3 yrs 2009 2008 2007 Statistic P O C Site 

# Meets EE-154, violates P98-75

0 25 50 75 100 125 150 175 200 225 250 275 300 325 350 375 400 425 450 475 500

2007 2008 2009 3 years SITE=295100093 POC=1

82 113 97 EPA_P98 1 295100093 191 107 191 121 max 1 295100093 107 88 126 107 Pct99 1 295100093 96 82 113 97 Pct98 1 295100093 88 74 97 90 Pct97 1 295100093 82 72 92 82 Pct96 1 295100093 75 70 82 81 Pct95 1 295100093 65 61 67 67 Pct90 1 295100093 58 51 59 61 Pct85 1 295100093 52 46 54 55 Pct80 1 295100093 48 42.5 48 51 Pct75 1 295100093 2 0 2 0 n > 154 1 295100093 48 10 19 19 n 76 - 154 1 295100093 1013 354 324 335 n < 76 1 295100093 1063 364 345 354 n 1 295100093 33 28 33 36 median 1 295100093 36.85 32.6 38.49 39.62 mean 1 295100093 3 yrs 2009 2008 2007 Statistic PO C Site 

# Meets EE-154, violates P98-75

# 25 0 25 50 75 100 125 150 175 200 225 250 275 300 325 350 375 400 425 450 475 500

2007 2008 2009 3 years SITE=310250009 POC=1

73 79 87 EPA_P98 1 310250009 167 134 102 167 max 1 310250009 88 78 82 114 Pct99 1 310250009 78 73 79 87 Pct98 1 310250009 69 62 72 74 Pct97 1 310250009 64 55 65 67 Pct96 1 310250009 61.5 52 61 66 Pct95 1 310250009 49 43 49 53 Pct90 1 310250009 42 38 42 47 Pct85 1 310250009 37 34 37 42 Pct80 1 310250009 34 31 34 37 Pct75 1 310250009 1 0 0 1 n > 154 1 310250009 22 6 8 8 n 76 - 154 1 310250009 957 319 308 330 n < 76 1 310250009 980 325 316 339 n 1 310250009 24 22 24 27 median 1 310250009 27.52 24.93 27.22 30.27 mean 1 310250009 3 yrs 2009 2008 2007 Statistic P O C Site 

# Meets EE-154, violates P98-75

0 25 50 75 100 125 150 175 200 225 250 275 300 325 350 375 400 425 450 475 500

2007 2008 2009 3 years SITE=310550045 POC=1

75 106 96 EPA_P98 1 310550045 143 140 143 98 max 1 310550045 106 85 121 98 Pct99 1 310550045 98 75 106 96 Pct98 1 310550045 95 71 104 96 Pct97 1 310550045 91 67 98 88 Pct96 1 310550045 87 65 95 88 Pct95 1 310550045 73 51 86 75 Pct90 1 310550045 66 44 76 72 Pct85 1 310550045 58 40 71 67 Pct80 1 310550045 49 37 66 56 Pct75 1 310550045 0 0 0 0 n > 154 1 310550045 68 7 56 5 n 76 - 154 1 310550045 710 358 299 53 n < 76 1 310550045 778 365 355 58 n 1 310550045 29 24 37 38 median 1 310550045 36.52 28.18 44.43 40.62 mean 1 310550045 3 yrs 2009 2008 2007 Statistic P O C Site 

# Meets EE-154, violates P98-75

# 26 0 25 50 75 100 125 150 175 200 225 250 275 300 325 350 375 400 425 450 475 500

2007 2008 2009 3 years SITE=320310022 POC=1

88 87 115 EPA_P98 1 320310022 130 91 87 130 max 1 320310022 115 91 87 130 Pct99 1 320310022 88 88 87 115 Pct98 1 320310022 87 88 87 115 Pct97 1 320310022 86 77 86 88 Pct96 1 320310022 85 77 85 88 Pct95 1 320310022 71 67 73 76 Pct90 1 320310022 64 57 65 67 Pct85 1 320310022 58 50 61 64 Pct80 1 320310022 50 45 54 58 Pct75 1 320310022 0 0 0 0 n > 154 1 320310022 15 3 6 6 n 76 - 154 1 320310022 163 55 55 53 n < 76 1 320310022 178 58 61 59 n 1 320310022 34 30 34 40 median 1 320310022 40.03 34.9 41.11 43.97 mean 1 320310022 3 yrs 2009 2008 2007 Statistic PO C Site 

# Meets EE-154, violates P98-75

0 25 50 75 100 125 150 175 200 225 250 275 300 325 350 375 400 425 450 475 500

2007 2008 2009 3 years SITE=350010026 POC=2

75 98 140 EPA_P98 2 350010026 140 105 99 140 max 2 350010026 105 105 99 140 Pct99 2 350010026 98 75 98 118.5 Pct98 2 350010026 98 75 98 97 Pct97 2 350010026 91 72 98 91.5 Pct96 2 350010026 86 72 98 86 Pct95 2 350010026 67 64 60 77 Pct90 2 350010026 58 58 54 67 Pct85 2 350010026 52 52 53 57 Pct80 2 350010026 48 37 47 50 Pct75 2 350010026 0 0 0 0 n > 154 2 350010026 10 1 4 5 n 76 - 154 2 350010026 147 52 50 45 n < 76 2 350010026 157 53 54 50 n 2 350010026 31 30 26 39.5 median 2 350010026 36.48 33.45 33.37 43.06 mean 2 350010026 3 yrs 2009 2008 2007 Statistic P O C Site 

# Meets EE-154, violates P98-75

# 27 0 25 50 75 100 125 150 175 200 225 250 275 300 325 350 375 400 425 450 475 500

2007 2008 2009 3 years SITE=350439004 POC=1

70 105 83 EPA_P98 1 350439004 251 82 145 251 max 1 350439004 102 72 135 98 Pct99 1 350439004 92 70 105 83 Pct98 1 350439004 89 68 100 73 Pct97 1 350439004 81 67 98 71 Pct96 1 350439004 78 66 94 69 Pct95 1 350439004 69 62 84 62 Pct90 1 350439004 64 58 78 56 Pct85 1 350439004 60 53 72 53 Pct80 1 350439004 55 51 69 50 Pct75 1 350439004 1 0 0 1 n > 154 1 350439004 51 1 43 7 n 76 - 154 1 350439004 876 314 223 339 n < 76 1 350439004 928 315 266 347 n 1 350439004 41 41 52 35 median 1 350439004 42.67 40.46 51.09 38.22 mean 1 350439004 3 yrs 2009 2008 2007 Statistic P O C Site 

# Meets EE-154, violates P98-75

0 25 50 75 100 125 150 175 200 225 250 275 300 325 350 375 400 425 450 475 500

2007 2008 2009 3 years SITE=390350065 POC=1

74 95 73 EPA_P98 1 390350065 118 118 110 91 max 1 390350065 110 118 110 91 Pct99 1 390350065 91 74 95 73 Pct98 1 390350065 83 74 95 73 Pct97 1 390350065 80 73 85 67 Pct96 1 390350065 73 73 85 67 Pct95 1 390350065 61 59 71 61 Pct90 1 390350065 56 51 62 51 Pct85 1 390350065 48 48 57 46 Pct80 1 390350065 45 45.5 44 43 Pct75 1 390350065 0 0 0 0 n > 154 1 390350065 7 1 5 1 n 76 - 154 1 390350065 164 55 52 57 n < 76 1 390350065 171 56 57 58 n 1 390350065 29 29.5 28 29.5 median 1 390350065 34.76 34.21 35.96 34.1 mean 1 390350065 3 yrs 2009 2008 2007 Statistic PO C Site 

# Meets EE-154, violates P98-75

# 28 0 25 50 75 100 125 150 175 200 225 250 275 300 325 350 375 400 425 450 475 500

2007 2008 2009 3 years SITE=420037004 POC=5

68 82 107 EPA_P98 5 420037004 129 90 129 125 max 5 420037004 102 81 102 109 Pct99 5 420037004 90 68 82 107 Pct98 5 420037004 83 62 80 99 Pct97 5 420037004 78 59 75 91 Pct96 5 420037004 74 55 73 89 Pct95 5 420037004 62 47 66 73 Pct90 5 420037004 52 42 53 62 Pct85 5 420037004 45 38 46 54 Pct80 5 420037004 40 34 41 47 Pct75 5 420037004 0 0 0 0 n > 154 5 420037004 49 4 13 32 n 76 - 154 5 420037004 1026 354 346 326 n < 76 5 420037004 1075 358 359 358 n 5 420037004 25 22 26 28 median 5 420037004 31 25.49 31.99 35.51 mean 5 420037004 3 yrs 2009 2008 2007 Statistic P O C Site 

# Meets EE-154, violates P98-75

0 25 50 75 100 125 150 175 200 225 250 275 300 325 350 375 400 425 450 475 500

2007 2008 2009 3 years SITE=461030020 POC=3

101 97 88 EPA_P98 3 461030020 138 138 131 109 max 3 461030020 106 110 108 101 Pct99 3 461030020 98 101 97 88 Pct98 3 461030020 90 94 97 87 Pct97 3 461030020 85 82 90 77 Pct96 3 461030020 77 73 88 76 Pct95 3 461030020 63 59 66 64 Pct90 3 461030020 54 49 54 57 Pct85 3 461030020 47 46 47 53 Pct80 3 461030020 43 40 43 47 Pct75 3 461030020 0 0 0 0 n > 154 3 461030020 59 16 24 19 n 76 - 154 3 461030020 1027 347 339 341 n < 76 3 461030020 1086 363 363 360 n 3 461030020 28 26 28 29 median 3 461030020 33.5 31.42 34.09 35.03 mean 3 461030020 3 yrs 2009 2008 2007 Statistic P O C Site 

# Meets EE-154, violates P98-75

# 29 0 25 50 75 100 125 150 175 200 225 250 275 300 325 350 375 400 425 450 475 500

2007 2008 2009 3 years SITE=490570002 POC=1

78 65 84 EPA_P98 1 490570002 181 181 129 134 max 1 490570002 94 100 92 98 Pct99 1 490570002 74 78 65 84 Pct98 1 490570002 65 66 62 68 Pct97 1 490570002 60 56 57 64 Pct96 1 490570002 55 53 55 60 Pct95 1 490570002 46 44 40 50 Pct90 1 490570002 39 38 38 44 Pct85 1 490570002 35 34 35 39 Pct80 1 490570002 32 31 32 34 Pct75 1 490570002 1 1 0 0 n > 154 1 490570002 19 7 5 7 n 76 - 154 1 490570002 1039 351 347 341 n < 76 1 490570002 1059 359 352 348 n 1 490570002 23 22 23 24 median 1 490570002 26.47 25.7 25.66 28.08 mean 1 490570002 3 yrs 2009 2008 2007 Statistic PO C Site 

# Meets EE-154, violates P98-75

0 25 50 75 100 125 150 175 200 225 250 275 300 325 350 375 400 425 450 475 500

2007 2008 2009 3 years SITE=560050869 POC=2

81 91 100 EPA_P98 2 560050869 138 131 138 132 max 2 560050869 107 103 115 114 Pct99 2 560050869 94 81 91 100 Pct98 2 560050869 83 75 84 93 Pct97 2 560050869 80 68 82 83 Pct96 2 560050869 75 67 78 80 Pct95 2 560050869 61 56 63 64 Pct90 2 560050869 53 50 53 56 Pct85 2 560050869 47 45 50 50 Pct80 2 560050869 43 40 43.5 45 Pct75 2 560050869 0 0 0 0 n > 154 2 560050869 52 10 18 24 n 76 - 154 2 560050869 989 341 330 318 n < 76 2 560050869 1041 351 348 342 n 2 560050869 28 25 30 29 median 2 560050869 32.99 30.08 33.9 35.05 mean 2 560050869 3 yrs 2009 2008 2007 Statistic PO C Site 

# Meets EE-154, violates P98-75

# 30 0 25 50 75 100 125 150 175 200 225 250 275 300 325 350 375 400 425 450 475 500

2007 2008 2009 3 years SITE=560090851 POC=1

105 80 94 EPA_P98 1 560090851 154 154 112 109 max 1 560090851 106 106 87 105 Pct99 1 560090851 94 105 80 94 Pct98 1 560090851 85 88 72 88 Pct97 1 560090851 77 75 70 85 Pct96 1 560090851 72 72 67 78 Pct95 1 560090851 64 68 57 67 Pct90 1 560090851 54 47 47.5 63 Pct85 1 560090851 46 43 44 56 Pct80 1 560090851 43 41 42 50.5 Pct75 1 560090851 0 0 0 0 n > 154 1 560090851 14 4 3 7 n 76 - 154 1 560090851 328 114 117 97 n < 76 1 560090851 342 118 120 104 n 1 560090851 30 29.5 30 32.5 median 1 560090851 34.44 33.35 32.75 37.62 mean 1 560090851 3 yrs 2009 2008 2007 Statistic P O C Site 

# Meets EE-154, violates P98-75

Meets EE-154, violates P98-75

0 25 50 75 100 125 150 175 200 225 250 275 300 325 350 375 4 00 4 25 4 50 4 75 500

2007 2008 2009 3 y ears SITE=300290009



## Site Statistic 2007 2008 2009 3 yrs
300290009 mean 30.3894 27.8593 22.0500 28.7597 300290009 median 25 22 19.5 23
300290009 n 357 199 60 616
300290009 n < 76 342 193 60 595
300290009 n 76 - 154 15 6 0 21
300290009 n > 154 0 0 0 0
300290009 Pct75 38 35 25.5 36
300290009 Pct80 42 39 29 40
300290009 Pct85 49 41 33 44
300290009 Pct90 55 48 36.5 52
300290009 Pct95 71 59 42.5 66
300290009 Pct96 76 61 44 71
300290009 Pct97 80 76 52 76
300290009 Pct98 87 95 52 87
300290009 Pct99 104 97 69 97
300290009 max 132 106 69 132 300290009 EPA_P98 87 95 52 78

# 31 PM 10 

# air quality distributions at monitors in countie s that do not meet the current standard but are likely to meet a potential al ternative standard with a 98 th 

# percentile form and a level of 75 μg/m 3

0 25 50 75 100 125 150 175 200 225 250 275 300 325 350 375 400 425 450 475 500

2007 2008 2009 3 years SITE=060590007 POC=1

49 59 75 EPA_P98 1 060590007 489 63 61 489 max 1 060590007 75 63 61 489 Pct99 1 060590007 63 49 59 75 Pct98 1 060590007 61 49 59 75 Pct97 1 060590007 59 48 51 69 Pct96 1 060590007 53 48 51 69 Pct95 1 060590007 46 43 45 53 Pct90 1 060590007 42 40 42 48 Pct85 1 060590007 39 39 36 39 Pct80 1 060590007 35 37 35 35 Pct75 1 060590007 1 0 0 1 n > 154 1 060590007 0 0 0 0 n 76 - 154 1 060590007 172 56 58 58 n < 76 1 060590007 173 56 58 59 n 1 060590007 28 31 27 29 median 1 060590007 32.76 30.79 28.64 38.69 mean 1 060590007 3 yrs 2009 2008 2007 Statistic P O C Site 

# Violates EE-154, meets P98-75

0 25 50 75 100 125 150 175 200 225 250 275 300 325 350 375 400 425 450 475 500

2007 2008 2009 3 years SITE=060830008 POC=1

41 49 72 EPA_P98 1 060830008 227 42 55 227 max 1 060830008 72 42 55 227 Pct99 1 060830008 49 41 49 72 Pct98 1 060830008 48 41 49 72 Pct97 1 060830008 42 34 49 48 Pct96 1 060830008 40 33 46 44 Pct95 1 060830008 31 30 33 32 Pct90 1 060830008 26 26 27 25.5 Pct85 1 060830008 25 22 25 24.5 Pct80 1 060830008 23 22 25 22.5 Pct75 1 060830008 1 0 0 1 n > 154 1 060830008 0 0 0 0 n 76 - 154 1 060830008 182 62 61 59 n < 76 1 060830008 183 62 61 60 n 1 060830008 18 17.5 20 18 median 1 060830008 20.6 18.16 21.21 22.48 mean 1 060830008 3 yrs 2009 2008 2007 Statistic P O C Site 

# Violates EE-154, meets P98-75

# 32 0 25 50 75 100 125 150 175 200 225 250 275 300 325 350 375 400 425 450 475 500

2007 2008 2009 3 years SITE=060831025 POC=1

33 48 51 EPA_P98 1 060831025 320 33 66 320 max 1 060831025 66 33 66 320 Pct99 1 060831025 48 33 48 51 Pct98 1 060831025 33 33 48 51 Pct97 1 060831025 32 29 35 32 Pct96 1 060831025 31 28 33 32 Pct95 1 060831025 26.5 26 26.5 27 Pct90 1 060831025 22 20 24 21 Pct85 1 060831025 20 19 22 19 Pct80 1 060831025 19 17 20 18 Pct75 1 060831025 1 0 0 1 n > 154 1 060831025 0 0 0 0 n 76 - 154 1 060831025 179 61 60 58 n < 76 1 060831025 180 61 60 59 n 1 060831025 15 13 15 15 median 1 060831025 16.56 13.36 16.78 19.64 mean 1 060831025 3 yrs 2009 2008 2007 Statistic P O C Site 

# Violates EE-154, meets P98-75

0 25 50 75 100 125 150 175 200 225 250 275 300 325 350 375 400 425 450 475 500

2007 2008 2009 3 years SITE=060890004 POC=2

31 113 33 EPA_P98 2 060890004 236 33 236 35 max 2 060890004 113 33 236 35 Pct99 2 060890004 74 31 113 33 Pct98 2 060890004 49 31 113 33 Pct97 2 060890004 38 30 112 32 Pct96 2 060890004 35 30 112 32 Pct95 2 060890004 29 23 49 27 Pct90 2 060890004 23 23 35 23 Pct85 2 060890004 21 20 23 22 Pct80 2 060890004 20 18 20 21 Pct75 2 060890004 1 0 1 0 n > 154 2 060890004 2 0 2 0 n 76 - 154 2 060890004 173 59 55 59 n < 76 2 060890004 176 59 58 59 n 2 060890004 13 12 11 14 median 2 060890004 17.03 13.37 22.67 15.14 mean 2 060890004 3 yrs 2009 2008 2007 Statistic P O C Site 

# Violates EE-154, meets P98-75

# 33 0 25 50 75 100 125 150 175 200 225 250 275 300 325 350 375 400 425 450 475 500

2007 2008 2009 3 years SITE=060932001 POC=2

29 97 64 EPA_P98 2 060932001 205 33 176 205 max 2 060932001 176 33 176 205 Pct99 2 060932001 87 29 97 64 Pct98 2 060932001 61 29 97 64 Pct97 2 060932001 52 19 87 36 Pct96 2 060932001 38 19 61 36 Pct95 2 060932001 26 17.5 38 22 Pct90 2 060932001 21 17 28 21 Pct85 2 060932001 18 16 25 18 Pct80 2 060932001 17 15 22 17 Pct75 2 060932001 2 0 1 1 n > 154 2 060932001 2 0 2 0 n 76 - 154 2 060932001 175 60 58 57 n < 76 2 060932001 179 60 61 58 n 2 060932001 12 12 13 12.5 median 2 060932001 16.83 12.05 21.57 16.79 mean 2 060932001 3 yrs 2009 2008 2007 Statistic P O C Site 

# Violates EE-154, meets P98-75

0 25 50 75 100 125 150 175 200 225 250 275 300 325 350 375 400 425 450 475 500

2007 2008 2009 3 years SITE=061113001 POC=1

85 61 62 EPA_P98 1 061113001 245 97 79 245 max 1 061113001 97 97 79 245 Pct99 1 061113001 79 85 61 62 Pct98 1 061113001 61 85 61 62 Pct97 1 061113001 47 41 52 45 Pct96 1 061113001 45 41 52 45 Pct95 1 061113001 39 33 41 40 Pct90 1 061113001 33 32 36 36 Pct85 1 061113001 31 31 32 30 Pct80 1 061113001 30 28 30 29 Pct75 1 061113001 1 0 0 1 n > 154 1 061113001 3 2 1 0 n 76 - 154 1 061113001 174 59 58 57 n < 76 1 061113001 178 61 59 58 n 1 061113001 23 24 22 24 median 1 061113001 26.1 24.61 25.19 28.6 mean 1 061113001 3 yrs 2009 2008 2007 Statistic PO C Site 

# Violates EE-154, meets P98-75

# 34 0 25 50 75 100 125 150 175 200 225 250 275 300 325 350 375 400 425 450 475 500

2007 2008 2009 3 years SITE=061131003 POC=1

54 109 60 EPA_P98 1 061131003 181 64 181 119 max 1 061131003 119 64 181 119 Pct99 1 061131003 90 54 109 60 Pct98 1 061131003 76 54 109 60 Pct97 1 061131003 64 47 90 54 Pct96 1 061131003 63 47 88.5 54 Pct95 1 061131003 42 36 63.5 40 Pct90 1 061131003 38 31 45.5 38 Pct85 1 061131003 36 30 40 36 Pct80 1 061131003 31 27 38 31 Pct75 1 061131003 1 0 1 0 n > 154 1 061131003 5 0 4 1 n 76 - 154 1 061131003 172 59 55 58 n < 76 1 061131003 178 59 60 59 n 1 061131003 20 17 25.5 22 median 1 061131003 25.74 20.2 32.35 24.56 mean 1 061131003 3 yrs 2009 2008 2007 Statistic P O C Site 

# Violates EE-154, meets P98-75

0 25 50 75 100 125 150 175 200 225 250 275 300 325 350 375 400 425 450 475 500

2007 2008 2009 3 years SITE=080030003 POC=1

58 85 71 EPA_P98 1 080030003 494 157 157 494 max 1 080030003 89 74 133 84 Pct99 1 080030003 73 58 85 71 Pct98 1 080030003 58 54 77 58 Pct97 1 080030003 55 49 66 56 Pct96 1 080030003 53 46 55 53 Pct95 1 080030003 43 40 42 45 Pct90 1 080030003 38 36 37 41 Pct85 1 080030003 35 32 35 38 Pct80 1 080030003 32 30 31 35 Pct75 1 080030003 4 1 2 1 n > 154 1 080030003 13 2 7 4 n 76 - 154 1 080030003 921 311 285 325 n < 76 1 080030003 938 314 294 330 n 1 080030003 23 21 23 26 median 1 080030003 26.91 24.49 27.19 28.95 mean 1 080030003 3 yrs 2009 2008 2007 Statistic P O C Site 

# Violates EE-154, meets P98-75

# 35 0 25 50 75 100 125 150 175 200 225 250 275 300 325 350 375 400 425 450 475 500

2007 2008 2009 3 years SITE=080070001 POC=3

73 52 47 EPA_P98 3 080070001 255 255 149 102 max 3 080070001 73 182 64 53 Pct99 3 080070001 55 73 52 47 Pct98 3 080070001 51 67 51 45 Pct97 3 080070001 47 54 47 42 Pct96 3 080070001 43 51 44 41 Pct95 3 080070001 37 37 37 35 Pct90 3 080070001 33 30 34 33 Pct85 3 080070001 30 27 32 31 Pct80 3 080070001 27 26 29 28 Pct75 3 080070001 4 4 0 0 n > 154 3 080070001 4 2 1 1 n 76 - 154 3 080070001 1059 348 353 358 n < 76 3 080070001 1067 354 354 359 n 3 080070001 21 20 21 21 median 3 080070001 23.69 24.93 23.61 22.56 mean 3 080070001 3 yrs 2009 2008 2007 Statistic P O C Site 

# Violates EE-154, meets P98-75

0 25 50 75 100 125 150 175 200 225 250 275 300 325 350 375 400 425 450 475 500

2007 2008 2009 3 years SITE=080670004 POC=1

50 57 38 EPA_P98 1 080670004 203 203 125 40 max 1 080670004 59 198 59 38 Pct99 1 080670004 51 50 57 38 Pct98 1 080670004 40 40 51 33 Pct97 1 080670004 38 38 51 31 Pct96 1 080670004 35 36 43 30 Pct95 1 080670004 29 31 31 27 Pct90 1 080670004 27 29 28 25 Pct85 1 080670004 25 26 25 24 Pct80 1 080670004 24 24 24 23 Pct75 1 080670004 2 2 0 0 n > 154 1 080670004 1 0 1 0 n 76 - 154 1 080670004 344 111 118 115 n < 76 1 080670004 347 113 119 115 n 1 080670004 18 19 17 18 median 1 080670004 20.66 23.2 20.22 18.61 mean 1 080670004 3 yrs 2009 2008 2007 Statistic PO C Site 

# Violates EE-154, meets P98-75