## Report on Air Quality in Nonattainment Areas For 2003-2005 Covering Ozone, Particulate Matter, Carbon Monoxide, Sulfur Dioxide, Nitrogen Dioxide, and Lead Technical Summary

November 2006 (Revised 2/14/07)

U.S. Environmental Protection Agency Office of Air Quality Planning and Standards Air Quality Assessment Division Air Quality Analysis Group Research Triangle Park, NC 27701TABLE OF CONTENTS Page INTRODUCTION

............................................................................................................... 1 SUMMARY

......................................................................................................................... 1 BACKGROUND INFORMATION

.................................................................................... 2 AIR QUALITY DESIGNATIONS AND CLASSIFICATIONS

........................................ 3 CRITERIA POLLUTANTS

................................................................................................ 4 Ozone

.............................................................................................................................. 4 8-Hour Ozone

.............................................................................................................. 5 Early Action Compacts

............................................................................................. 13 Particulate Matter

.......................................................................................................... 13 PM 2.5 ......................................................................................................................... 14 PM 10 .......................................................................................................................... 18 Carbon Monoxide

......................................................................................................... 22 Sulfur Dioxide

............................................................................................................... 23 Nitrogen Dioxide

.......................................................................................................... 24 Lead

............................................................................................................................... 24

LIST OF APPENDICES
Page

A Additional Information on Area Classifications for the 8-Hour Ozone Standard A1 B Interpretation of the 8-Hour Prim ary and Secondary National Ambient Air Quality Standards for Ozone.................................................................................B1 C Interpretation of the National Ambient Air Quality Standards for PM 2.5 .............C1 D Interpretation of the National Ambi ent Air Quality Standards for PM ................D1

LIST OF TABLES
Page 1 National Ambient Air Quality Standards for Criteria Pollutants

............................. 3 2 Areas Designated Nonattainment in June 2004 and Classifications for the 8-Hour Ozone NAAQS

........................................................................................................ 6 3 Trends in Design Values for the 8-Hour Ozone NAAQS 2001-2005 for Designated Nonattainment Areas

............................................................................ 7 4 20 Areas Measuring Highest 8-Hour Oz one Design Values Above the NAAQS: 2003-2005

.............................................................................................................. 12 5 Current Designated Nonattainment Areas (Jan 2005) and Design Values for the PM 2.5 NAAQS

........................................................................................................ 15 6 20 Areas Measuring Highest Annual PM 2.5 Design Values Above the NAAQS: 2003-2005

.............................................................................................................. 17 7 Areas Newly Violating the PM 2.5 NAAQS: 2003-2005

....................................... 18 8 Area Designations and Cl assifications for the PM 10NAAQS

............................... 18

i9 Current Designated Nonattainment Areas and Design Values for the PM 10 NAAQS: 2001-2003 through 2003-2005

.............................................................. 20 10 Areas Newly Violating the PM 10NAAQS: 2003-2005

........................................ 22 11 Current Designated Nonattainment Areas and Design Values for the 8-Hour CO NAAQS: 2002-2003 through 2004-2005

.............................................................. 23 12 Area Newly Violating the CO NAAQS: 2003-2005

............................................ 23 13 Areas Currently Designated Nonattainment for the Lead NAAQS or Designated Attainment But Not Meeting the Lead NAAQS

.................................................... 26

LIST OF FIGURES
Page

1 Original 8-Hour Ozone Nonattainment Areas with 2001-2003 Data and Areas Remaining Above the NAAQS with 2003-2005 Data

........................................... 10 2 20 Areas Measuring Highest 8-Hour Oz one Design Values Above the NAAQS: 2003-2005

.............................................................................................................. 12 3 PM 2.5 Nonattainment Areas with 2001- 2003 Data and Areas Above the NAAQS with 2003-2005 Data

.............................................................................................. 16

iiINTRODUCTION This report presents information on outdoor air quality based on monitoring data collected throughout the country during 2003-2005. It focuses on areas where air quality was previously determined by the U.S. Environmental Protection Agency (EPA or agency) to be unhealthy and designated as nonattainment for one or more of the six principal outdoor air pollutants referred to as criteria pollutants. The criteria pollutants are ozone, particulate matter (PM), car bon monoxide (CO), sulfur dioxide (SO 2 ), nitrogen dioxide (NO 2 ) and lead. Each year the EPA looks at the levels of thes e pollutants in the air measured at monitors located across th e country to evaluate how air quality has changed over time and summarizes the curren t status of air quality in designated nonattainment areas. Background information on the pollutants is in cluded to set the context for readers.

SUMMARY

• Ozone
o Ozone design values in designate d nonattainment areas are improving.
o An increasing number of designated nonattainment areas are attaining the ozone National Ambient Air Quality St andards (NAAQS or standards).
o There are no areas newly violating the ozone NAAQS.

• PM 2.5 o PM 2.5 design values in designated nonattainment areas are improving.
o One designated nonattainment area is measuring attainment with monitoring data collected during 2003-2005.
o There are five areas newly violating the PM 2.5 NAAQS.

• PM 10 o There are 46 designated nonattainment areas for the PM 10NAAQS. Air quality in 29 of these areas is measuring attainment.
o There are 21 areas newly violating the PM 10NAAQS.
o There are three maintenance areas violating the PM 10NAAQS.

• CO
o All of the designated nonattainment ar eas have air quality monitoring data measuring attainment of the CO NAAQS.
o There is one area newly violating the CO NAAQS.

• SO 2 o All of the designated nonattainment ar eas have air quality monitoring data measuring attainment of the SO 2NAAQS.
o There is one area newly violating both the 24-hour and 3-hour secondary SO 2NAAQS.

• NO 2 o There are no designated NO 2 nonattainment areas.
o All areas are meeting the NO 2NAAQS.

• Lead

1o There are two areas designated as nonattainment for the lead NAAQS. Air quality monitoring is no longer c onducted in one area and air quality in the second area is violating the NAAQS.
o There is one area that is designated as attainment with a monitor that is violating the lead NAAQS.

BACKGROUND INFORMATION The Clean Act (CAA) requires EPA to set NAAQS for ‘criteria pollutants.’ Currently, lead and five other major pollu tants are listed as criteria pollutants. (The others are ozone, nitrogen oxide s, carbon monoxide, sulfur dioxide, and particulate matter.) The law also requires EPA to periodically review the standards to ensure that they provide adequate health and environmental protection, and to update those standard s as necessary. The CAA requires two types of national air qualitystandards. Primary standards set limits to protect public health, including the health of "sensitive" populations such as asthmatics, children, and the elderly. Secondary standards set limits to prot ect public welfare, including protection against visibility impairment, damage to animals, crops, vegetation, and buildings. The NAAQS for criteria pollutants are shown in Table 1. It is followed by a discussion of term s or names that are applied to an area based on how air quality compares to the NAAQS.

2-------

-------

------- Table 1. National Ambient Air Quality Standards for Criteria Pollutants

Pollutant Primary Stds. Averaging Times Secondary Stds. Carbon Monoxide 9 ppm (10 mg/m 3 ) 8-hour 1 None 35 ppm (40 mg/m 3 ) 1-hour 1 None Lead 1.5 μg/m 3 Quarterly Average Same as Primary Nitrogen Dioxide 0.053 ppm (100 μg/m 3 ) Annual (Arithmetic Mean) Same as Primary Particulate Matter (PM 10 ) Revoked 2 Annual (Arith. Mean) Same as Primary 150 μg/m 3 24-hour 3 Particulate Matter (PM 2.5 ) 15.0 μg/m 3 Annual 4(Arith. Mean) Same as Primary 35 μg/m 3 24-hour 5 Ozone 0.12 ppm 1-hour 6 Applies only in limited areas Same as Primary
0.08 ppm 8-hour 7 Same as Primary Sulfur Oxides 0.03 ppm Annual (Arith. Mean) 0.14 ppm 24-hour 1 3-hour 1 0.5 ppm (1300 μg/m 3 ) Units of measure for the standards are parts per million (ppm) by volume, milligrams per cubic meter of air (mg/m 3 ), and micrograms per cubic meter of air (μg/m 3 ).

1 Not to be exceeded more than once per year. 2Due to a lack of evidence linking health problems to long-term exposure to coarse particle pollution, the agency revoked the annual PM 10standard in 2006. 3 Not to be exceeded more than once per year on average over 3 years. 4To attain this standard, the 3-year average of the weighted annual mean PM 2.5 concentrations from single or multiple community-oriented monitors must not exceed 15.0 μg/m3

. 5 To attain this standard, the 3-year average of the 98th percentile of 24-hour concentrations at each population-oriented monitor within an area must not exceed 35 μg/m3
6 (a) This standard is attained when the expected number of days per calendar year with maximum hourly average concentrations above 0.12 ppm (235 μg/m 3 ) is equal to or less than 1. (b) As of June 15, 2005, the agency revoked the 1-hour ozone standard in all areas except the fourteen 8-hour ozone nonattainment Early Action Compact Areas. 7 To attain this standard, the 3-year average of the fourth-highest daily maximum 8-hour average ozone concentrations measured at each monitor within an area over each year must not exceed 0.08 ppm.

AIR QUALITY DESIGNATIONS AND CLASSIFICATIONS A designation is the term EPA uses to de scribe how the air quality status in a given area compares to the NAAQS for any of th e six criteria pollutants. To determine the correct designation, air quality data is colle cted at each monitoring site and used to calculate a design value. The design value is the pollutant concentration that describes whether a site is at, above, or below the level of the NAAQS. Design values are especially helpful when the standard is exce edance-based because they are expressed as a concentration instead of an exceedance count, thereby allowing a direct comparison to the level of the standard. Information on howdesign values are determined for selected pollutants is included in the Appendix.

3EPA designates areas as nonattainment , unclassifiable/attainment, or unclassifiable. When air qua lity in an area exceeds the NAAQS for one of the criteria pollutants or contributes to a nearby area that exceeds the NAAQS, EPA designates that area as nonattainment. Under certain conditi ons, a designated nonattainment area may consist of a full or partial c ounty or counties within an urbanized area or a rural area. Where data show that air quality in an area meets the NAAQS, that is, the pollution concentration is at or below the level of the NAAQS, the area may be designated as unclassifiable/attainment. If an area cannot be determined on the basis of available information as meeting or not meetin g the NAAQS, EPA may designate the area unclassifiable. A nonattainment or unclassifiable area may be eligible for redesignation to attainment when air quality data show that the NAAQS and other requirements for redesignation are met. In addition to a nonattainment designation, EPA classifies O 3 , CO, and some PM nonattainment areas, based on the area’s design value, for the purpose of applying an attainment date or to specify the requirements to which it will be subject. For example, an area’s ozone classification may be marginal, moderate, serious, severe, or extreme. Subpart 1 is not a classification but is a term used in connection with certain areas to indicate the section of the CAA cont aining basic requirements that must be met to improve air quality. The technical details underlying classifications are contained in Title I of the CAA, Sections 172 and 181 and in the Title 40 of the Code of Federal Regulations (CFR) Part 51 Subpart X. General information on classifications is provided in the Appendix. The following discussion prov ides information on each of the criteria pollutants.

CRITERIA POLLUTANTS

Ozone Ozone is a photochemical oxidant that is the prime ingredient of smog in cities and other areas of the country. While ozone in the upper atmosphere is beneficial to life by shielding the earth from harmful ultr aviolet radiation from the sun, high concentrations of ozone at ground level are a major health and environmental concern. Ozone is not emitted directly into the ai r but is formed through complex chemical reactions between precursor emissions of volatile organic compounds (VOCs) and oxides of nitrogen (NOx) in the presence of sunlight . These reactions are stimulated by sunlight and temperature so that peak ozone levels occur typically duri ng the warmer times of the year. Both VOCs and NOx are emitted by hum an activity such as transportation and industrial processes. VOCs are emitted from sources as diverse as autos, chemical manufacturing, dry cleaners, paint shops and other sources using solvents. NOx is emitted as a byproduct of most combustion processes. Changing weather patterns contribute to yearly differences in ozone concentrations from city to city. Also, ozone and the pollutants that cause ozone can be carried to an area from pollution sources located hundreds of miles upwind. The reactivity of ozone causes health problems because it damages lung tissue, reduces lung function and sensitizes the lungs to other irrita nts. Ozone can irritate your respiratory system, causing coughing, irritation in your throat or a burning sensation in

4your airways. It can reduce lung function, so that you may have feelings of chest tightness, wheezing, or shortness of breath. Ozone can aggravate asthma and trigger asthma attacks. People at greater risk fr om ground-level ozone ar e people with lung diseases, such as asthma, and children and adults who are active outdoors. Damage to lung tissue may be caused by repeated exposures to ozone -- something like repeated sunburns of the lungs -- and this could result in a reduced quality of life as people age.

Ground-level ozone interferes with the ability of pl ants to produce and store food, so that growth, reproduction and overall pl ant health are compromised. By weakening sensitive vegetation, ozone makes plants more susceptible to disease, pests, and environmental stresses. Ground-level ozone has been shown to reduc e agricultural yields for many economically important crops (e.g., soybeans, kidney beans, wheat, cotton). The effects of ground-level ozone on long-lived species such as trees are believed to add up over many years so that whole forests orecosystems can be affected. For example,
ozone can adversely impact ecol ogical functions such as water movement, mineral nutrient cycling, and habitats for various an imal and plant species. Ground-level ozone can kill or damage leaves so that they fall off the plants too soon or become spotted or brown. These effects can significantly decrease th e natural beauty of an area, such as in national parks and recreation areas. One of the key components of ozone, nitrogen oxides, contributes to fish kills and algae blooms in sensitive waterways, such as the Chesapeake Bay.

8-Hour Ozone In June 2004, EPA designated and cla ssified 126 areas in the U.S. as nonattainment for the 8-hour ozone NAAQS based on air quality data exceeding the NAAQS collected primarily in 2001-2003. Thes e areas included 462 whole and part counties and the District of Columbia. Appr oximately 159 million people were living in areas designated as not meeting the sta ndard (2000 census). The area names and classifications are shown in Table 2. Table 3 shows the design values for 2001-2003 at designation, 2002-2004, and 2003-2005, and if the area’s design value meets the 8-hour ozone NAAQS based on the most recent data collected during 2003-2005. Fourteen of these areas had the effective date of their nonattainment designation date delayed. These areas have entered into an Early Action Compact (EAC or compact) with EPA as discussed below. The remaining areas were designated as unclassifiable/attainment or unclassifiable. At designation, design values of the nonattainment areas ranged from 0.085 to 0.131 ppm. The average value was 0.092 ppm.

5Table 2. Areas Designated Nonattainment in June 2004 and Classifications for the 8-Hour Ozone NAAQS

Table 2 State Area Classification State Area Classification NY MI MI Allegan County MD Kent and Queen Anne's Counties PA CA ) PA Altoona WI Kewaunee County CA Subpart 1 TN Knoxville Subpart 1 GA Atlanta IN MD Moderate PA Lancaster Marginal LA Baton Rouge MI NV MI OH Benzie County CA

WV CA ) AL Louisville MA ) GA

NH ) VA ( NY WI

OH CA ( MI Cass County MI

NC-SC Charlotte-Gastonia-Rock Hill WI Chattanooga

GA (

CA Chico TN Nashville Clarksville-Hopkinsville CA ) Subpart 1

PA CT

OH VA (HR) SC

OH PA-NJModerate TX AZ OH PA Pittsburgh-Beaver Valley Subpart 1 CO ME Portland NY WI RI ) PA Erie NC Subpart 1 NY PA Reading IN Evansville VA Marginal NC-SC Fayetteville CA ) Flint VA Roanoke IN Fort Wayne NY Rochester PA NC VA CA VA San Antonio MI CA San Diego CT CA PA CA San Joaquin Valley PA NC-SC WI Albany-Schenectady-Troy Subpart 1 Kalamazoo-Battle Creek Subpart 1 Subpart 1 Marginal Allentown-Bethlehem-East on Subpart 1 Kern County (Eastern Kern Subpart 1 Subpart 1 Subpart 1 Amador and Calaveras Counties (Central Mtn) Marginal La Porte Marginal Baltimore Marginal Lansing-East Lansing Subpart 1 TX Beaumont-Port Arthur Marginal Las Vegas Subpart 1 Benton Harbor Subpart 1 Lima Subpart 1 MI Subpart 1 Los Angeles South Coast Air Basin Severe 17 Berkeley and Jefferson Counties Subpart 1 Los Angeles-San Bernardino Counties (W Mojave Moderate Birmingham Subpart 1 KY- IN Subpart 1 Boston-Lawrence-Worcester (E. MA Moderate Macon Subpart 1
Boston-Manchester-Portsmouth (SE Moderate Madison and Page Counties Shenandoah NP) Subpart 1 Buffalo-Niagara Falls Subpart 1 Manitowoc County Subpart 1

Canton-Massillon Subpart 1 Mariposa and Tuolumne Counties Southern Mtn) Subpart 1 Marginal Mason Co Subpart 1 WV Charleston Subpart 1 TN-AR Memphis Marginal Moderate Milwaukee-Racine Moderate TN-GA Subpart 1 IN Muncie Subpart 1

IL-IN Chicago-Gary-Lake County Moderate Murray Co Chattahoochee National Forest) Subpart 1 Subpart 1 MI Muskegon Marginal OH-KY-IN Cincinnati-Hamilton Subpart 1 Subpart 1 TN-KY Subpart 1 Nevada County (Western Part

Clearfield and Indiana Counties Subpart 1 NY-NJNew York-N. New Jersey-Long Island Moderate

Cleveland-Akron-Lorain Moderate Norfolk-Virginia Beach-Newport News Marginal Columbia Subpart 1 WV-OH Parkersburg-Marietta Subpart 1

Columbus Subpart 1 MD-DE Philadelphia-Wilmington- Atlantic City Dallas-Fort Worth Moderate Phoenix-Mesa Subpart 1 Dayton-Springfield Subpart 1 Denver-Boulder-Greeley-Ft Collins-Loveland Subpart 1 Marginal MI Detroit-Ann Arbor Marginal Poughkeepsie Moderate Door County Subpart 1 Providence (All RI Moderate Subpart 1 Ralei gh-Durham-Chapel Hill Essex County (Whiteface Mtn) Subpart 1 Subpart 1 Subpart 1 Richmond-Petersburg Subpart 1 Riverside County (Coachella Valley Serious MI Subpart 1 Subpart 1 Subpart 1 Subpart 1 Franklin County Subpart 1 Rocky Mount Subpart 1 Frederick County Subpart 1 Sacramento Metro Serious Fredericksburg Moderate TX Subpart 1 Grand Rapids Subpart 1 Subpart 1 Greater Connecticut Moderate San Francisco Bay Area Marginal Greene County Subpart 1 Serious IN Greene County Subpart 1 Scranton-Wilkes-Barre Subpart 1 Greensboro-Winston Salem-High Point Marginal Sheboygan Moderate

6Table 2 State Area Classification State Area Classification SC IN Subpart 1 ME MA ) PA

NC NP) PA State College NC TX CA (

MI PA CA OH IN CA

VA NY MD NY TN PA York PA Greenville-Spartanburg-A nderson Subpart 1 South Bend-Elkhart Hancock, Knox, Lincoln & Waldo Counties Subpart 1 Springfield (Western MA Moderate Harrisburg-Lebanon-Carlisle Subpa rt 1 MO-IL St Louis Moderate Haywood and Swain Counties (Great Smoky Subpart 1 Subpart 1 Hickory-Morganton-Lenoir Subpart 1 OH-WV Steubenville-Weirton Subpart 1 Houston-Galveston-Brazoria Moderate Sutter County Sutter Buttes) Subpart 1 WV-KY Huntington-Ashland Subpart 1 IN Terre Haute Subpart 1 Huron County Subpart 1 Tioga County Subpart 1 Imperial County Marginal Toledo Subpart 1 Indianapolis Subpart 1 Ventura County Moderate IN Jackson County Subpart 1 DC-MDWashington Subpart 1 Jamestown Subpart 1 Washington County (Hagerstown) Moderate Jefferson County Moderate WV-OH Wheeling Subpart 1 Johnson City-Kingsport-Bristol Subpart 1 Subpart 1 Johnstown Subpart 1 OH-PA Y oungstown-Warren-Sharon Subpart 1

Table 3. Trends in Design Values for the 8-Hour Ozone NAAQS 2001-2005 for Designated Nonattainment Areas

Design Value Table 3 State Area 2001­ 2003 ) 2002­ 2004 ) 2003­ 2005 ) 2005

NY Yes MI Allegan County No PA No PA Altoona Yes CA No GA Atlanta No MD No LA Baton Rouge No TX No MI Yes MI Benzie County Yes WV Yes AL Yes MA ) No NH ) Yes NY No OH Yes MI Cass County ** WV Yes NC-SC Charlotte-Gastonia-Rock Hill No Yes No CA Chico Yes No Clarksville-Hopkinsville* Yes PA Yes OH No SC Yes OH No TX No OH ** CO Yes (ppm (ppm (ppm Meets NAAQS 2003­

Albany-Schenectady-Troy 0.087 0.086 0.082 0.097 0.093 0.089 Allentown-Bethlehem-Easton 0.091 0.088 0.087 0.085 0.081 0.077 Amador and Calaveras Counties (Central Mtn) 0.091 0.09 0.091 0.091 0.093 0.09 Baltimore 0.103 0.094 0.091 0.086 0.089 0.096 Beaumont-Port Arthur 0.091 0.092 0.088 Benton Harbor 0.091 0.086 0.084 0.088 0.083 0.083 Berkeley and Jefferson Counties (EAC area) 0.086 0.08 0.076 Birmingham* 0.087 0.085 0.084 Boston-Lawrence-Worcester (E. MA 0.095 0.091 0.086 Boston-Manchester-Portsmouth (SE 0.087 0.084 0.08 Buffalo-Niagara Falls 0.099 0.091 0.086 Canton-Massillon 0.09 0.086 0.082 0.093 0.089 Incomplete Data Charleston* 0.086 0.081 0.078 0.1 0.094 0.088 TN-GA Chattanooga (EAC area) 0.088 0.086 0.08 IL-IN Chicago-Gary-Lake County 0.101 0.094 0.086 0.089 0.088 0.083 OH-KY-IN Cincinnati-Hamilton 0.096 0.091 0.089 TN-KY 0.085 0.082 0.077 Clearfield and Indiana Counties 0.09 0.085 0.082 Cleveland-Akron-Lorain 0.103 0.095 0.091 Columbia (EAC area) 0.089 0.086 0.083 Columbus 0.095 0.091 0.088 Dallas-Fort Worth 0.1 0.098 0.095 Dayton-Springfield 0.09 0.087 Incomplete Data Denver-Boulder-Greeley-Ft Collins-Loveland (EAC 0.087 0.084 0.084

7Design Value Table 3 State Area 2001­ 2003 ) 2002­ 2004 ) 2003­ 2005 ) 2005
area) MI No WI No PA Erie Yes NY ** IN Evansville* Yes NC-SC Yes MI Flint Yes IN Fort Wayne Yes PA Yes VA Yes VA Yes MI Yes CT No IN Yes PA Yes NC-SC ) Yes SC ) Yes ME Yes PA Yes NC Yes NC Yes TX No Yes MI Yes CA Yes IN No IN Yes NY No NY Yes TN Yes PA Yes MI Yes MD Kent and Queen Anne's Counties Yes CA ) No WI Kewaunee County No TN Knoxville No IN ** PA Lancaster Yes MI Yes NV Las Vegas No OH Yes CA No CA No Louisville Yes GA Yes VA ** WI Manitowoc Co No CA No MI Yes TN-AR No WI No IN Yes GA ( Yes MI Yes TN Yes (ppm (ppm (ppm Meets NAAQS 2003­

Detroit-Ann Arbor 0.097 0.092 0.09 Door County 0.094 0.088 0.09 0.092 0.087 0.083 Essex County (Whiteface Mtn) 0.091 0.083 Incomplete Data 0.085 0.083 0.077 Fayetteville (EAC area) 0.087 0.084 0.083 0.09 0.085 0.082 0.088 0.085 0.083 Franklin County 0.093 0.085 0.075 Frederick County (EAC area) 0.085 0.078 0.073 Fredericksburg* 0.088 0.084 0.079 Grand Rapids 0.089 0.084 0.082 Greater Connecticut 0.095 0.089 0.087 Greene County* 0.088 0.084 0.08 Greene County 0.089 0.084 0.081 Greensboro-Winston Salem- High Point (EAC area 0.093 0.087 0.082 Greenville-Spartanburg- Anderson (EAC area 0.087 0.084 0.081 Hancock, Knox, Lincoln & Waldo Counties 0.094 0.088 0.082 Harrisburg-Lebanon-Carlisle 0.088 0.082 0.078 Haywood and Swain Counties (Great Smoky NP) 0.085 0.082 0.078 Hickory-Morganton-Lenoir (EAC area) 0.088 0.082 0.077 Houston-Galveston-Brazoria 0.102 0.101 0.103 WV-KY Huntington-Ashland 0.091 0.086 0.079 Huron County 0.087 0.08 0.077 Imperial County 0.087 0.085 0.084 Indianapolis 0.096 0.092 0.087 Jackson County* 0.085 0.08 0.075 Jamestown 0.094 0.093 0.089 Jefferson County 0.097 0.086 0.081 Johnson City-Kingsport-Bristol (EAC area) 0.086 0.084 0.079 Johnstown 0.087 0.08 0.077 Kalamazoo-Battle Creek 0.086 0.081 0.078 0.095 0.089 0.082 Kern County (Eastern Kern 0.098 0.092 0.09 0.093 0.087 0.086 0.092 0.091 0.086 La Porte 0.093 0.086 Incomplete Data 0.092 0.087 0.083 Lansing-East Lansing 0.086 0.08 0.078 0.086 0.085 0.085 Lima 0.089 0.087 0.081 Los Angeles South Coast Air Basin 0.131 0.127 0.127 Los Angeles-San Bernardino Counties (W. Mojave) 0.106 0.107 0.105 KY-IN 0.092 0.088 0.082 Macon 0.086 0.086 0.083 Madison and Page Coun ties (Shenandoah NP)* 0.087 0.082 Incomplete Data 0.09 0.083 0.087 Mariposa and Tuolumne Counties (Southern Mtn) 0.091 0.09 0.088 Mason Co 0.089 0.082 0.081 Memphis 0.092 0.087 0.086 Milwaukee-Racine 0.101 0.094 0.088 Muncie* 0.088 0.083 0.078 Murray Co Chattahoochee National Forest) 0.085 0.083 0.079 Muskegon 0.095 0.086 0.084 Nashville (EAC area) 0.086 0.083 0.082

8Design Value Table 3 State Area 2001­ 2003 ) 2002­ 2004 ) 2003­ 2005 ) 2005

CA ) No No VA ) Yes Yes

DE No

AZ Yes PA Pittsburgh-Beaver Valley Yes ME Portland Yes NY No RI ) No NC No PA Reading Yes VA Yes CA ) No VA Yes NY Rochester Yes NC Yes CA No TX No CA San Diego No CA Yes CA San Joaquin Valley No PA Yes WI No IN Yes MA ) Yes No PA State College Yes Yes CA ( Yes IC Yes PA Yes OH No CA No MD ( Yes No Yes PA York Yes OH-PA No (ppm (ppm (ppm Meets NAAQS 2003­

Nevada County (Western Part 0.098 0.097 0.098 NY-NJ-CT New York-N. New Jersey-Long Island 0.102 0.095 0.091 Norfolk-Virginia Beach-Newport News (HR 0.09 0.086 0.078 WV-OH Parkersburg-Marietta 0.087 0.084 0.081 PA-NJ-MD- Philadelphia-Wilmington-Atlantic City 0.106 0.099 0.094

Phoenix-Mesa 0.087 0.085 0.084 0.094 0.09 0.084 0.091 0.084 0.077 Poughkeepsie 0.094 0.089 0.086 Providence (All RI 0.095 0.09 0.089 Raleigh-Durham-Chapel Hill 0.094 0.089 0.085 0.091 0.083 0.08 Richmond-Petersburg 0.094 0.09 0.082 Riverside County (Coachella Valley 0.108 0.104 0.104 Roanoke (EAC area) 0.085 0.079 0.074 0.088 0.081 0.073 Rocky Mount 0.089 0.085 0.079 Sacramento Metro 0.107 0.102 0.097 San Antonio (EAC area) 0.089 0.091 0.086 0.093 0.089 0.086 San Francisco Bay Area 0.086 0.084 0.078 0.115 0.116 0.113 Scranton-Wilkes-Barre 0.086 0.081 0.077 Sheboygan 0.1 0.092 0.089 South Bend-Elkhart 0.093 0.088 0.083 Springfield (Western MA 0.094 0.09 0.084 MO-IL St Louis 0.092 0.089 0.086 0.088 0.084 0.079 OH-WV Steubenville-Weirton 0.086 0.083 0.077 Sutter County Sutter Buttes) 0.088 0.09 0.083 Terre Haute* 0.087 0.083 0.076 Tioga County 0.086 0.085 0.081 Toledo 0.093 0.089 0.086 Ventura County 0.095 0.094 0.091 Washington County (Hagerstown) EAC area) 0.086 0.083 0.078 DC-MD-VA Washington 0.099 0.096 0.091 WV-OH Wheeling 0.087 0.078 0.076 0.089 0.086 0.082 Youngstown-Warren-Sharon 0.095 0.091 0.086 *This area was originally designated as nonattainment for the ozone NAAQS; however, based on later air quality data, it has bee n redesignated to attainment. **A determination of whether this area meets the NAAQS cannot be made due to incomplete data. Source: AQS July 10, 2006
Table 3 demonstrates that ozone ai r quality is improving in designated nonattainment areas. Ozone air qual ity in 73 of the original 126 O 3 areas is meeting the NAAQS based on data collect during 2003-2005; thus, satisfying one of several criteria that must be met prior to re designation to attainment. Table 3 further shows that 10 of the original areas have effective redesignations to attainment. These redesignations were based on earlier data collect ed during 2002-2004 or 2003-2005 s howing attainment of the NAAQS and other criteria needed to assure that the area will remain in attainment. Based on the redesignations, there are now 116 areas with 157 million people living in areas designated as nonattainment fo r the 8-hour ozone NAAQS (2000 census).

9Figure 1 displays designated ozone nonattainment areas. The map on the left shows areas designated as nonattainment for the 8-hour ozone NAAQS in 2004 based on air quality data collected during 2001-2003. The map on the right shows 48 remaining areas with air quality above the NAAQS based on data collected during 2003-2005. Included on the map are four additional areas with incomplete data for 2003-2005 (Cass County, Michigan; Dayton-Springfield, Ohio ; Essex County (Whiteface Mountain), New York; and, La Porte, Indiana). Not included on the map is one area with incomplete data 2003-2005 that is redesignated to attainmentbased on earlier data (Madison and Page Counties (Shenandoah National Park), Virginia. These areas do not have complete data as of this writing; therefore, a determination of whether the areas are attaining or not attaining cannot be made at this time. Only one area, Mariposa and Tuolumne Counties in California with air quality monitoring data measuring attainment of the standard during the 2002-2004 time period, went back into nonattainment based on their monitoring data collected during 2003-2005. Twenty-two ar eas not attaining in 2002-2004 are now attaining based on 2003-2005 data. In 2005, th ere were no new areas monitoring air quality in violation of the ozone NAAQS.

Figure 1. Ozone Nonattainment Areas with 2001-2003 Data and Areas Above the NAAQS with 2003-2005 Data During 2002-2004, design values of the origin al nonattainment areas ranged from 0.078 ppm to 0.127 ppm. The average was 0.088 pp m. Air quality improved in all but four areas. In the four areas, air quality inAmador and Calaveras Counties and Nevada County, California remained the same while ozone design values in Baton Rouge, Louisiana and Houston, Texas increase d from 0.086 to 0.096 ppm and 0.102 to 0.103 ppm, respectively. During 2003-2005, design values of the origin al nonattainment areas ranged from 0.073 ppm to 0.127 ppm. The average was 0.084 ppm. Reflecting the lower ozone pollution, all but eight areas show lower desi gn values than those measured during the 2002 through 2004 time period. The improvement s range from about 1 percent to 12 percent. There are 44 areas with five per cent or more improvement. The areas are:

10- California: Chico, San Francisco Bay Area, and Sutter County (Sutter Buttes );

- District of Columbia-Maryland-Virginia: Washington;

- Illinois-Indiana: Chicago-Gary-Lake County;

- Indiana: Evansville, Indianapol is, Jackson County, Muncie, South BendElkhart, and Terre Haute;

- Kentucky-Indiana; Louisville;

- Maine: Hancock, Knox, Lincoln & Waldo Counties; and Portland;

- Maryland: Kent and Queen Anne ’s Counties, and Washington County (Hagerstown);

- Massachusetts: Boston-L awrence-Worcester (Eastern. MA), and Springfield (Western MA);

- Michigan: Grand Rapids;

- New York: Buffalo-Niagara Falls , Jefferson County, and Rochester;

- North Carolina: Greensboro-Winston Salem-High Point, Hickory-MorgantonLenoir, and Rocky Mount;

- North Carolina-South Carolina: Charlotte-Gastonia-Rock Hill;

- Ohio: Lima;

- Ohio-Pennsylvania: Youngstown-Warren-Sharon;

- Ohio-West Virginia: Steubenville-Weirton;

- Pennsylvania: Franklin County, Pitts burgh-Beaver Valley, and State College;

- Pennsylvania-New Jersey-Maryland-Dela ware: Philadelphia-WilmingtonAtlantic City;

- Tennessee: Johnson City-Kingsport-Bristol, and Knoxville;

- Tennessee-Georgia: Chattanooga;

- Tennessee-Kentucky: Clarksville-Hopkinsville;

- Texas: San Antonio;

- Virginia: Frederick County, Norfol k-Virginia Beach-Newport News (HR), Richmond-Petersburg, and Roanoke;

- West Virginia: Berkeley and Jefferson Counties;

- West Virginia-Kentucky: Huntington-Ashland; and,

- Wisconsin: Milwaukee-Racine. In the same time period, air quality in six areas worsened from about 1 percent to 8 percent. The areas are:

- Louisiana: Baton Rouge, from 0.089 ppm to 0.096 ppm ; - Texas: Houston-Galveston-Br azoria, from 0.101 ppm to 0.103 ppm ;

- Wisconsin: Manitowoc County, from 0.083 ppm to 0.087 ppm;

- Wisconsin: Door County, from 0.088 ppm to 0.090 ppm;

- California: Amador and Calaveras Counties (Central Mtn), from 0.090 ppm to 0.091 ppm; and,

- California: Nevada County (Weste rn Part), from 97 ppm to 98 ppm. Table 4 and Figure 2 show the top 20 areas with ozone air quality problems in the U.S. along with their design values for data collected in 2003-2005. Although these areas have the highest ozone design values, air quality has improved since 2001-2003 in all

11areas except Baton Rouge, Louisiana, and H ouston-Galveston-Brazoria, Texas, where it has worsened as noted above and several areas where it has remained stable.
Table 4. 20 Areas Measuring Highest 8-Ho ur Ozone Design Values Above the NAAQS: 2003-2005

Table 4 State ) CA CA San Joaquin Valley CA CA )

CA ) CA LA Baton Rouge

CA MD OH

CA

GA Atlanta MI

CA ) Area Design Value (ppm Los Angeles South Coast Air Basin 0.127 0.113 Los Angeles-San Bernardi no Counties (W Mojave) 0.105 Riverside County (Coachella Valley 0.104 TX Houston-Galveston-Brazoria 0.103 Nevada County (Western Part 0.098 Sacramento Metro 0.097 0.096 TX Dallas-Fort Worth 0.095 PA-NJ-MD-DE Philadelphia-Wilmington-Atlantic City 0.094 Amador and Calaveras Counties (Central Mtn) 0.091 Baltimore 0.091 Cleveland-Akron-Lorain 0.091 NY-NJ-CT New York-N. New Jersey-Long Island 0.091 Ventura County 0.091 DC-MD-VA Washington 0.091 0.090 Detroit-Ann Arbor 0.090 WI Door County 0.090 Kern County (Eastern Kern 0.090 Source: AQS July 10, 2006

Figure 2. 20 Areas Measuring Highe st 8-Hour Ozone Design Values Above the NAAQS: 2003-2005

12Early Action Compacts Several communities around the country are working with EPA to achieve clean air as soon as possible. The communities are:

- Berkeley and Jefferson Counties, West Virginia;

- Chattanooga, Tennessee-Georgia;

- Columbia, South Carolina;

- Denver-Boulder-Greeley-Fort CollinsLoveland, Colorado;

- Fayetteville, North Carolina-South Carolina;

- Frederick County, Virginia;

- Greensboro-Winston-Salem-Highpoint, North Carolina-South Carolina; - Greenville-Spart anburg-Anderson, South Carolina;

- Hickory-Morganton-Lenoir, North Carolina;

- Johnson City-Kingsport-Bristol, Tennessee;

- Nashville, Tennessee;

- Roanoke, Virginia;

- San Antonio, Texas; and

- Washington County (Hagerstown), Maryland.

Together with EPA, these communities entered into Early Action Compacts (EACs). The goal of EACs is to reduce ground-level ozone as quickly as possible. Communities with EACs started reducing air pollution about tw o years sooner than required by the CAA. For example, states with communities participating in the EACs submitted plans for meeting the national 8-hour ozone standard in December 2004, rather than waiting until 2007 -- the deadline for other areas not meeti ng the 8-hour ozone standard. By reducing pollution ahead of schedule, these communities will bring substantial, sustainable health and environmental improvements to their residents sooner than would have been achieved without these agreements.

These areas are listed in Table 2 as nonattainment areas for the 8-hour standard. However, EPA has deferred the effective date of the nonattainment designation for as long as areas meet agreed upon milestones. Th is means that the impact of nonattainment designation for the 8-hour ozone standard will be deferred, i.e., certain CAA requirements, such as controls on new sources, will not apply

. Air quality in all of the EAC areas is meeting the 8-hour ozone NAAQS during the 2003-2005 time period except San Antonio where the design value of 0.086 pp m is slightly above the NAAQS. The 1­ hour NAAQS applies to these areas until one year after the eff ective date of the designation of that area for the 8-hour ozone NAAQS. All of the areas are in attainment for the 1-hour O 3 NAAQS.

Particulate Matter Particulate matter, also known as partic le pollution, is a complex mixture of extremely small particles and liquid droplets. Particle pollution is made up of a number of components, including acids and their neutra lized precipitates suchas nitrates and sulfates, organic chemicals, metals, and soil or dust particles. They are directly emitted into the air by sources such as factories, power plants, cars an d trucks, construction

13activity, fires and natural windblown dust. Particles formed in the atmosphere by condensation or the transformati on of emitted gases such as SO 2, NO x , and VOCs are also considered particulate matter. Based on studies of human populations exposed to high concentrations of particles and laboratory studies of animals a nd humans, there are major effects of concern for human health. These in clude effects on breathing and respiratory symptoms, aggravation of existing respir atory and cardiovascular diseas e, alterations in the body's defense systems against foreign materials, damage to lung tissue, carcinogenesis and premature death. Even if you are healthy, you may experience temporary symptoms from exposure to elevated levels of particles. Symptoms may include irritation of the eyes, nose and throat; coughing; phlegm, chest tightness; and shortness of breath. The major subgroups of the population that appear to be most sensitive to the effects of PM include individuals with chronic obstructive pulmonary or cardiovascular di sease or influenza, asthmatics, the elderly and children. Particulat e matter also soils and damages materials, and is a major cause of visibility impairment in the United States.

EPA established a set of standards to PM in1997 covering particle size up to 2.5 microns in diameter and also particle size up to 10 microns in diameter . To be in attainment, the 3-year average of the weighted annual mean PM 2.5 concentrations from single or multiple community-oriented monitors must not exceed 15.0 μg/m 3 and the 3-year average of the 98th percentile of 24-hour concentrations ateach population-oriented monitor within an area must not exceed 65 μg/m 3 . For PM 10 , an area may not exceed the daily standard of 150 μg/m 3 more than once per year on average over 3 years and the 3-year average weighted annual arithmetic mean of 50 μg/m3 at each monitor. On September 21, 2006, EPA completed a review of the particle pollution NAAQS. In the final rule, EPA retained the annual PM 2.5 standard and lowered the 24-hour PM 2.5 standard. The revision is effective December 18, 2006.

PM 2.5 In January 2005, EPA designated 39 areas in the U.S. as nonattainment for the PM 2.5 NAAQS based on air quality data ex ceeding the NAAQS collected during 2001­ 2003. These areas include a combination of 208 whole and part c ounties incl uding the District of Columbia. This means that approximately 89,000 peopl e are living in areas designated as not meeting the standard (2000 census). Greenville, South Carolina was designated as unclassifiable. The remaining areas were designated as unclassifiable/attainment. Table 5 shows the areas designated as nonattainment, the design value for 2001-2003 at designati on, the design value for 2002-2004 and 2003­ 2005, and if the area’s de sign value meets the PM 2.5 NAAQS based on the most recent data collected during 2003-2005. At desi gnation, annual design values of the nonattainment areas ranged from 15.2 μg/m 3 to 27.8 μg/m 3

.

14PM Table 5. Current Designated Nonattainment Areas (Jan 2005) and Design Values for the

2.5NAAQS

(μg/m 3 )

State Area Annual 2001­ 2003 2001­ 2003 Annual 2002­ 2004 2002­ 2004 Annual 2003­ 2005 2003­ 2005 Meets

2003­ 2005 GA Atlanta 18 39 39 38 No MD 42 41 41 No AL 1 40 40 44 No OH 40 37 * No 40 36 36 No Chattanooga 37 35 36 No County 40 39 46 No 42 41 40 No OH 46 45 46 No OH 40 38 16 40 No OH 39 37 40 No MI 44 43 45 No IN Evansville 16.2 40 15.5 37 15.7 37 No

NC 35 33 32 No

PA Carlisle 43 41 40 No

NC 34 34 36 No

OH 41 37 35 No IN 39 16 38 38 No PA 41 40 39 No TN Knoxville 35 34 33 No PA 17 45 42 44 No MT 45 42 * No PA 63 65 68 No

CA Air Basin 72 67 65 No KY-IN Louisville 42 15.9 38 16.5 37 No GA 33 34 34 No

MD 40 39 36 No

48 50 17 46 No 16 37 35 34 No 43 39 37 No PA 16.9 45 16.5 45 16.6 43 No PA Reading 46 42 39 No GA 36 35 36 No CA San Joaquin Valley 76 62 19 60 No 40 40 17 40 No 46 17 47 45 No 44 42 37 Yes 37 36 33 No PA 17 45 43 41 No 1

Note: Table 5 Design Value

24-Hour 24-Hour 24-Hour NAAQS

17.5 17.4 Baltimore 16.6 16.3 16.6 Birmingham 17.3 16.8 17.4 Canton-Masillon 17.3 16.5 16.7 WV Charleston 17.1 16.4 16.6 TN-GA-AL 16.1 15.7 16.1

IL-IN Chicago-Gary-Lake 17.7 17.2 16.1 OH-KY-IN Cincinnati-Hamilton 17.8 16.9 17.9 Cleveland-Akron-Lorain 18.3 17.6 18.1 Columbus 16.7 15.7 Dayton-Springfield 15.2 15.5 15.9 Detroit-Ann Arbor 19.5 18.6 18.2

Greensboro-Winston Salem-High Point 15.8 15.4 15.2Harrisburg-Lebanon15.7 15.4 15.8Hickory-MorgantonLenoir 15.5 15.1 15.3WV-KYHuntington-Ashland 17.2 15.8 16.3 Indianapolis 16.7 16.4 Johnstown 15.8 15.3 15.6 16.4 15.7 15.6 Lancaster 16.8 17.5 Libby 16.2 15.2 15.1 Liberty-Clairton 21.2 20.4 20.8 Los Angeles-South Coast 27.8 24.8 22.6 16. 9 Macon 15.2 15.5 16.1Martinsburg, WVHagerstown 16.3 16.1 16.2

NY-NJ-CT New York-N. New Jersey-Long Island 17.7 16.8 WV-OH Parkersburg-Marietta 15.2 15.4 PA-NJ-DE Philadelphia-Wilmington 16.2 15.4 15.7 Pittsburgh-Beaver Valley 16.4 16.1 16.2 Rome 15.6 15.5 16.2 21.8 20.6 MO-IL St. Louis 17.5 16.9 OH-WV Steubenville-Weirton 17.8 17.2 DC-MD-VA Washington 15.8 15.1 14.8 WV-OH Wheeling 15.7 15.1 15.3 York 16.9 17.3 Two sites in Jefferson County, AL are encompassed in a Community Monitoring Zone (i.e. utilize spatial averaging); the spatiall y averaged design value for the CMZ is 17. 4, which is the maximum for the county. *The 24-hour PM 2.5 design value cannot be determined due to incomplete data. Data that have been flagged for natural and excepti onal events, for which documentation has been submitted and approvedby the EPA (AQS concurrence field set to ‘Y’), we re excluded from the design value calculations. Source: AQS July 10, 2006

15Table 5 shows that PM 2.5 air quality in designat ed nonattainment areas is improving. The range of annual design valu es of the nonattainment areas during 2002­ 2004 dropped to 15.1 μg/m 3 to 24.8 μg/m 3 and during 2003-2005 the range dropped to 14.8 μg.m 3 to 22.6 μg/m 3 . Reflecting the lower PM 2.5 pollution, all but ten areas show an air quality improvement over that monito red during 2001-2003. Most improved although still in violation of the PM 2.5 NAAQS are the Los Angeles-S outh Coast Air Basin and San Joaquin Valley areas in California whose design values went from 27.8 to 22.6 μg/m 3 and 21.8 to 19.0 μg/m 3 , respectively. One of the area s, Washington, DC-MD-VA, is now meeting the NAAQS, thus satisfying one of seve ral criteria that must be met prior to redesignation to attainment. Of the remaining areas, eight show a degrad ation in air quality over the 2001-2003 time period and tw o have no change. The degradation concentrations range from 0.1 to 0.9 μg/m 3 or 0.6 percent to 5 .9 percent. The areas showing poorer air quality are: Birmi ngham, Alabama; Cincinnati-Hamilton, OhioKentucky-Indiana; Dayton-Springfield, Ohio; Harrisburg-Lebanon-Carlisle, Pennsylvania; Lancaster, Pennsylvania; M acon, Georgia; Reading, Pennsylvania; and, York, Pennsylvania. No areas have been redesignated to attainment. In the 2001-2003 time period, two areas, the Los Angeles-South Coast Air Basin and the San Joaquin Valley in California, were violating the 24-hour PM 2.5 NAAQS whereas only the Liberty-Clairton area in Pennsylvania is violating the 24-hour PM 2.5 NAAQS during 2003-2005. Most improved is th e San Joaquin Valley with a 21 percent decrease in 24-hour design values from 76 μg/m 3 during 2001-2003 to 60 μg/m 3 during 2003-2005. Figure 3 displays designated PM 2.5 nonattainment areas. The map on the left shows areas designated as nonattainment in2005 based on air quality data collected during 2001-2003. The map on the right shows the remaining areas with air quality above the NAAQS based on data collected during 2003-2005.

Figure 3. PM 2.5 Nonattainment Areas with 2001-2003 Data and Areas Above the NAAQS with 2003­

2005 Data

16Table 6 shows the top 20 areas with PM 2.5 quality problems in the U.S. along with their design values during 2003-2005. Although these areas have the highest PM 2.5 design values, since 2001-2003 air quality has improved with decreases in design values ranging from 0.3 μg/m 3 in Pittsburg-Beaver Valley, Pennsylvania, and Indianapolis, Indiana, to 5.2 μg/m 3 in the Los Angeles-South Coast Air Basin area in California. Most improved is the Los Angeles-South Coast Va lley area with a 19 percent decrease in annual design values from 27.8 μg/m 3 during 2001-2003 to 22.6 μg/m 3 during 2003­ 2005. Lastly, there are five areas newly violating the annual PM 2.5 NAAQS. They are shown in Table 7.
Table 6. 20 Areas Measuring Highest Annual PM 2.5 Design Values Above the NAAQS: 2003-2005

Table 6 Area Design Value 3 ) CA PA CA San Joaquin Valley MI OH

PA GA Atlanta AL PA York OH-WV 17.2

OH

WV PA 16.6 Louisville (μg/m Los Angeles-South Coast Air Basin 22.6 Liberty-Clairton 20.8 19.0 Detroit-Ann Arbor 18.2 Cleveland-Akron-Lorain 18.1 OH-KY-IN Cincinnati-Hamilton 17.9 Lancaster 17.5 17.4 Birmingham 17.4 17.3 Steubenville-Weirton NY-NJ-CT New York-N.New Jersey-Long Island 17.0 MO-IL St. Louis 17.0 Canton-Masillon 16.7 MD Baltimore 16.6 Charleston 16.6 Pittsburgh-Beaver Valley KY-IN 16.5 IN Indianapolis 16.4 WV-KY-OH Huntington-Ashland 16.3 Source: AQS July 10, 2006

17Table 7. Areas Newly Violating the PM 2.5NAAQS: 2003-2005

Table 7 Design Value (μg/m 3 ) State Area Annual 24-hr
1 37 GA ( 33 KY 31 NC ( 32 AL-GA Columbus-Phenix City 15.2 Richmond County Augusta) 15.5 Fayette County (Lexington) 15.1 Mecklenburg County Charlotte) 15.3 OH Mahoning County (Youngstown) 15.5 38

1 Two sites in the Columbus-Phenix City, Al-GA metropolitan area have opted to use spatial averaging. The spatially averaged design value is 15.2 μg/m3 which is the maximum for the area (Community Monitoring Zone.) Note: Data that have been flagged for natural and ex ceptional events, for which documentation has been submitted and approved by the EPA (AQS concurrence field set to ‘Y’), were excluded from the design value calculations. Source: AQS July 10, 2006

PM 10 Following the amendments to the Clean Air Act in 1990, 73 areas were designated as nonattainment by law and 13 a dditional areas through other redesignation actions were designated as nonattainment for the PM 10NAAQS. The names and classifications are shown in Table 8. Since th at time, air quality in 40 areas attained the PM 10 NAAQS and the areas have an effective redesignation to attainment leaving 46 areas currently designated as nonattainment. As a result of this progress, approximately seven million additional people are now liv ing in areas that are meeting the PM 10 NAAQS (2000 census). Table 9 shows the ar eas that are currently designated as nonattainment, the design value fo r 2001-2003, 2002-2004, and 2003-2005, and if the area meets the NAAQS based on the most r ecent data collected during 2003-2005. On September 21, 2006, EPA completed a review of the particle pollution NAAQS. In the final rule, EPA retained the 24-hour PM 10standard but revoked the annual PM 10 standard. Design values for the annual PM 10NAAQS in 2003-2005 are shown because the revocation did not become effective until December 18, 2006.
Table 8. Area Designations and Classifications for the PM 10NAAQS

Table 8 State Area

AZ Ajo NM Anthony CO Aspen* ID Boise* AZ Bullhead City* MT Butte CO PA IN Clinton Township* CA MT CA OH CO MI Detroit* Classification

Moderate Moderate Moderate Moderate Moderate Moderate Canon City* Moderate Clairton & 4 Boroughs* Moderate Moderate Coachella Valley Serious Columbia Falls and vicinity Moderate Coso Junction Moderate Cuyahoga County* Moderate Denver Metro* Moderate Moderate

18Table 8 State Area

AZ Douglas/Paul Spur AK IN )* TX El Paso OR WV Follansbee* ID Fort Hall IL

OR Grants Pass* PR AZ CA CA AK Juneau MT Kalispell WA Kent* OR OR OR CO MT NV Las Vegas MT IL CA OR OH MT CA CT New Haven* NY AZ Nogales OR UT Ogden IL Oglesby* WA CA CO AZ AZ Phoenix ID MT Polson ID ME NV Reno AZ Rillito MN Rochester* MT Ronan CA MN Saint Paul* UT CA CA San Joaquin Valley ID ) WA Seattle* WY Sheridan ID Classification

Moderate Eagle River Moderate East Chicago (Lake County Moderate Moderate Eugene-Springfield Moderate Moderate Moderate Granite City, Nameoki Township* Moderate

Moderate Guaynabo County Moderate Hayden/Miami Moderate Imperial Valley Serious Indian Wells* Moderate Moderate Moderate Moderate Klamath Falls* Moderate LaGrande* Moderate Lakeview* Moderate Lamar* Moderate Lame Deer Moderate Serious Libby Moderate Lyons Township* Moderate Mammoth Lakes Moderate Medford-Ashland* Moderate Mingo Junction* Moderate Missoula Moderate Mono Basin Moderate Moderate New York County Moderate Moderate Oakridge Moderate Moderate Moderate Olympia, Tumwater, Lacey* Moderate Owens Valley Serious Pagosa Springs* Moderate Payson* Moderate Serious Pinehurst Moderate Moderate Portneuf Valley* Moderate Presque Isle* Moderate Moderate Moderate Moderate Moderate Sacramento County Moderate Moderate Salt Lake County Moderate San Bernardino Moderate Serious Sandpoint (Bonner County Moderate Moderate Moderate Shoshone County Moderate

19Table 8 State Area

CA IL Southeast Chicago* WA Spokane* CO WA CO MT CA UT Utah County WA Wallula* WV MT County) WA AZ

10 Classification

South Coast Air Basin Serious Moderate Moderate Steamboat Springs* Moderate Tacoma* Moderate Telluride* Moderate Thompson Falls and vicinity Moderate Trona Moderate Moderate Serious Weirton* Moderate Whitefish and vicinity (Flathead Moderate

Yakima* Moderate Yuma Moderate *Since designation as a nonattainment area for the PM NAAQS, this area has been redesignated to attainment.
Table 9. Current Designat ed Nonattainment Areas and Design Values for the PM 10NAAQS: 2001-2003 through 2003-2005

Table 9 3 )

Annual 2001­ 2003 2001­ 2003 Annual 2002­ 2004 2002­ 2004 Annual 2003­ 2005 Expected Exceedances 2003­ 2005 Meets

State Area AZ Ajo 18 139 20 139 22 0 139 Yes NM Anthony 34 394 31 333 30 148 Yes MT Butte 16 66 17 60 19 0 69 Yes CA 53 309 50 276 47 4 227 No MT 19 125 22 123 22 0 125 Yes CA 17 175 18 483 18 118 No AZ Douglas/Paul Spur 30 137 30 127 30 207 No AK 23 590 20 92 18 0 90 Yes TX 47 589 54 533 49 504 No OR 19 65 18 63 18 0 50 Yes ID Fort Hall 29 214 24 214 24 134 Yes PR 35 117 34 95 35 0 115 Yes AZ 34 141 33 128 31 0 128 Yes CA 81 647 74 373 63 211 No
AK Juneau 7 29 7 34 10 0 42 data MT Kalispell 21 117 22 117 24 0 105 Yes
MT 29 169 26 169 24 117 data NV 46 274 46 358 42 274 No MT 24 110 25 110 27 0 103 Yes
CA 13 134 22 129 22 0 86 data MT 13 116 20 110 22 0 110 Yes CA 54 5283 78 5745 70 5283 No NY 4 77 No data No data No data No data No data No data AZ Nogales 49 213 44 188 46 280 No OR 18 89 19 80 18 0 76 Yes UT Ogden 27 163 31 136 27 111 Yes CA 189 120 7071 89 4125 No AZ Phoenix 63 280 61 248 62 240 No Design Value (μg/m

24-Hour 24-Hour Number of 24-Hour NAAQS 2003-2005

0.7
Coachella Valley Columbia Falls and vicinity Coso Junction 1.2 2.1 Eagle River El Paso County 10.3 Eugene-Springfield 0.8 Guaynabo County Hayden/Miami Imperial Valley 11.1 Incomplete

Lame Deer 0.7 Incomplete
Las Vegas 3.8 Libby
Mammoth Lakes Incomplete

Missoula Mono Basin 22.2 New York County 10.2 Oakridge 0.7 Owens Valley 12160 23.5 4.6

20ID 2 39 19 78 20 0 85 Yes Polson 20 108 20 105 20 0 105 Yes NV Reno 41 113 41 126 42 153 Yes AZ Rillito 37 118 36 118 37 0 118 Yes MT Ronan 17 58 19 58 17 0 61 Yes CA 25 144 27 144 26 0 110 Yes UT 42 421 41 169 40 421 No CA 31 172 31 198 29 162 No CA San Joaquin Valley 52 212 51 217 46 150 Yes ID ) 12 96 17 67 17 0 71 Yes WY Sheridan 30 137 30 137 31 0 137 Yes ID 19 68 19 78 20 0 85 Yes CA 59 166 57 159 54 149 No MT 16 69 16 69 13 0 48 Yes CA 20 186 24 186 19 136 Yes UT Utah County 31 111 29 118 27 111 Yes
MT ( ) 17 109 26 100 25 0 104 Yes
AZ 39 154 42 127 38 0 127 Yes

(
(

. Pinehurst MT 0.3

Sacramento County Salt Lake County 2.1 San Bernardino 1.3 0.3 Sandpoint (Bonner County

Shoshone County South Coast Air Basin 1.1 Thompson Falls and vicinity Trona 0.5 0.3 Whitefish and vicinity Flathead County Yuma Table 9 Notes: 1. Underlined values are based on incomplete data and are generally not valid for regulatory usage. Either the re are no other sites in the area with complete data for this 3-year period or a complete site or sites are located in the area buthave an expected estimated ex ceedance value of zero and an incomplete site in the area registered the non-zero value shown. 2. Data that have been flagged for natu ral and exceptional events, for which documentation has been submitted and approved by t he EPA AQS concurrence field set to “Y”), were excluded from the design value calculations. 3. Some valid values are based on sites that did not meet the minimum 75 percent data capture requirements per quarter for all12 quarters). These values are considered valid for regulatory usage per 40 CFR Part 50 Appendix K or the Guideline on Exceptions to Data Requirements for Determining Attainment of Particulate Matter Standards An incomplete, potentially violating annual standard design value is valid if by substituting one half the minimum detectable concentration values for missing values in deficient quarters, i.e., those with less than 75 percent data capture, the recalcul ated 3-year metric still exceeds 50. Incomplete, potentially ‘meeting’ values for expected numbers of exceedances and annual standard design value are valid if same -site maximum quarterly values for the 3-years period are substituted for missing data and both recalculated 3-year metrics still meet the NAAQS. See substitution requirements and computation detail in stated references. Source: AQS October 6, 2006

In 29 of the remaining 46 nonattainment areas, air quality is now attaining the PM 10 NAAQS based on monitoring data collectedduring 2003-2005. About 28 million people live in these 46 areas (2000 cen sus). Of the 17 remaining nonattainment areas, four areas have incomplete or no data on which to make a determination of attainment or nonattainment. Also, three maintenance ar eas have air quality data during 2003-2005 that does not meet the PM 10 NAAQS. Maintenance areas are previously designated nonattainment areas that have been redesignate d to attainment with a plan to maintain clean air quality. The areas are Detroit, Michigan; East Chicago (Lake County), Indiana; and, Indian Wells Valley, California. A total of 16 of the 86 areas previously designated as nonattainment for the PM 10NAAQS failed to meet the standards based on 2003-2005 air quality data. Lastl y, there are 21areas (countie s) newly violating the PM 10 standard. These areas are listed in Table 10.

21Table 10. Areas Newly Violating the PM 10NAAQS: 2003-2005

(μg/m 3 ) 1 (μg/m 3 ) 1

State County 30 159 WY 24 167 NM 2 42 205 SC 26 157 MT Glacier 18 195 MO Jasper 32 152 AL 53 179 MN 37 209 23 221 AZ 2 54 158 CO Mesa 31 198 WY 19 194 NV Nye 37 252 AZ Pinal 2 44 289 CA 30 155 NM Sandoval 27 165 OH Scioto 20 210 MO ) 50 191 Sweetwater 24 306 TN Union 39 148 CA Yolo 26 169

1 ( 2 10 Table 10 Design Value Design Value

Annual 2003-2005 Expected Number of Exceedances 24-Hour 2003-2005

WY Campbell 1.1 Carbon 7.4 Dona Ana 6.1 Georgetown 1.2 2.0 1.1 Jefferson 3.1 Kandiyohi 6.1 WY Lincoln 4.4 Maricopa 3.2 4.0 Natrona 2.1 4.9 8.1 San Diego 3.1 2.9 2.8 St. Louis (city 7.7 WY 2.9 1.1 2.0 Underlined annual design values are based on incomplete data. The corresponding e xpected number of ex ceedances are valid per data substitution protocol. See endnote for Table 9. Data that have been flagged for natural and exceptional events, for which documentati on has been submitted and approved by the EPA AQS concurrence field set to “Y”), were excluded from the design value calculations. These counties are near or, in some cases, overl ap or totally contain previously designated PM nonattainment areas. However, the monitoring sites from which these design values are derived are located outside the boundaries of the nonattainment area. Therefore, these counties are listed here as new areas. Source: AQS October 6, 2006

Carbon Monoxide
CO is a colorless, odorle ss and poisonous gas produced by incomplete burning of carbon in fuels. When CO enters the bloodstream, it reduces the delivery of oxygen to the body's organs and tissues. Hea lth threats are most serious for those who suffer from cardiovascular disease, particularly those withangina or peripheral vascular disease. Exposure to elevated CO levels can cause impairment of visual perception, manual dexterity, learning abil ity and performance of complex tasks. Seventy-seven percent of the nationwid e CO emissions are from transportation sources. The largest emissions contribution comes from highway motor vehicles. Thus, the focus of CO monitoring has been on traffi c oriented sites in urban areas where the main source of CO is motor vehicle exhaus t. Other major CO sources are wood-burning stoves, incinerators and industrial sources. There are six areas designated as nonattainment for the 8-hour CO NAAQS consisting of all or parts of 10 counties. About 15 million people live in these areas (2000 census). All designated nonattainmen t areas meet the CO NAAQS based on 2004­ 2005 data. Table 11 shows the areas designate d as nonattainment, the design value for

222002-2003, 2003-2004, and 2004-2005. There is one area newly violating the 8-hour CO standard. The area and design values are shown in Table 12. All areas met the 1-hour NAAQS based on 2004-2005 data.
Table 11. Current Designated Nonattainment Areas and Design Values for the 8-Hour CO NAAQS: 2002-2003 through 2004-2005

Table 11 )

State Area 2002­ 2003 2003­ 2004 2004­ 2005 Meets

TX El Paso Yes NV Las Vegas Yes

CA Coast Air Basin Yes MT Yes NV Reno Yes OR Not Classified Yes 8-Hour (ppm

Classification NAAQS 2004-2005 Moderate 6.8 6.4 6.4 Serious 5.8 5.3 5.2 Los Angeles South Serious 8.5 7.2 6.1 Missoula Moderate 3.6 3.6 3.6 Moderate 4.4 3.9 3.9 Salem 5.2 4.9 3.8 Source: AQS October 28, 2006

Table 12. Area Newly Violating the CO NAAQS: 2004-2005

Table 12 )

State Area 2002­ 2003 2003­ 2004 2004­ 2005 Meets

WV Hancock County No 8-Hour (ppm

NAAQS 2004-2005 12.1 12.0 12.0 Source: AQS October 28, 2006
Sulfur Dioxide High concentrations of SO 2affect breathing and may aggravate existing respiratory and cardiovascular disease. Sensitive populations include asthmatics, individuals with bronchitis or emphysema, children and the elderly. SO 2is also a primary contributor to acid deposition, or acid rain, which causes acidification of lakes and streams and can damage trees, crops, historic buildings and statues. In addition, sulfur compounds in the air contribute to visibility impairment in large parts of the country. This is especially noticeable in national parks. SO 2also contributes to the formation of PM 2.5.
Ambient SO 2results largely from stationary sources such as coal and oil combustion, steel mills, refineries, pulp and paper mills and from nonferrous smelters. There are 11 areas designated as nonattainment for the SO 2NAAQS consisting of all or parts of ten counties. The areas are Pennsylvania: Armstrong County; Montana: East Helena and Laurel Areas; Arizona: Hayden, Miami, and San Manual; Guam: Piti and Tanguisson; Utah: Salt Lake and Tooele Counties; and,

23New Jersey: Warren County. About 1 million people are li ving in these areas (2000 cens us). All of the areas meet the SO 2 NAAQS based on air monitoring data collected during 2004-2005. However, there is one newly violating area, Volcanoes National Park in Hawaii, with air quality monitoring data that is not meeti ng both the 3-hour standard and the 24-hour standard in 2004-2005. The area’s design va lue is 0.19 ppm and 0.6 ppm for the 24-hour and 3-hour NAAQS, respectively.

Nitrogen Dioxide

NO 2is a brownish, highly reactive gas that is present in all urban atmospheres. Nitrogen dioxide can irritate the lungs, cau se bronchitis and pneumonia, and lower resistance to respiratory infections. Nitrogenoxides are an importantprecursor both to O 3 and acid rain, and may affect both terrestrial and aquatic ecosystems. The major mechanism for the formation of NO 2in the atmosphere is the oxidation of the primary air pollutant nitric oxide (NO). NOx plays a major role, together with VOCs, in the atmospheric reactions that produce O 3 . NOx forms when fuel is burned at high temperatures. The two major emissions source s are transportation and stationary fuel combustion sources such as elec tric utility and industrial boilers. There are no designated nonattainment areas for NO 2 . There are no newly violating areas based on 2004-2005 data.

Lead Exposure to lead can occur through multiplepathways, including inhalation of air and ingestion of lead in food, water, soil or dust. Excessive lead exposure can cause seizures, mental retardation and/or behavior al disorders. A recent National Health and Nutrition Examination Survey reported a 78 percent decrease in blood lead levels from 12.8 to 2.8 μg/dL between 1976 and 1980 and from 1988 to 1991. This dramatic decline can be attributed to the reduc tion of leaded gasoline and to the removal of lead from soldered cans. Although this study shows great progress, in fants and young children are especially susceptible to low doses of lea d, and this age group still shows the highest levels. Low doses of lead can lead to central nervous system damage. Recent studies have also shown that lead may be a factor in high blood pressure and in subsequent heart disease in middle-aged males. Lead gasoline additives, non-ferrous sme lters, and battery plants are the most significant contributors to atmospheric lead emissions. In 1993 transportation sources contributed 33 percent of the annual emissions, down substan tially from 81 percent in 1985. Total lead emissions from all sources dropped from 20,100 tons in 1985 to 4,900 tons in 1993. The decrease in lead emi ssions from highway vehicles accounts for essentially all of this decline. The reas ons for the decrease are noted below. Two air pollution control programs implemented by EPA before promulgation of the lead standard in October 1978 have result ed in lower ambient lead levels. First, regulations issued in the early 1970's required gradual reduction of the lead content of all

24gasoline over a period of many y ears. The lead content of th e leaded gasoline pool was reduced from an average of 12.0 gram/gallon, to 0.5 gram/gallon on July 1, 1985, and still further to 0.1 gram/gallon on January 1, 1986. Second, as part of the EPA's overall automotive emission control program, unlead ed gasoline was in troduced in 1975 for automobiles equipped with catalytic control devices. These devices reduce emissions of CO, VOCs and NOx. In 1993, unleaded gasolinesales accounted for 99 percent of the total gasoline market. In contrast, the unlead ed share of the gasoline market in 1984 was approximately 60 percent. These programs have essentially eliminated violations of the lead standard in urban areas except those areas with lead point sources. Programs are also in place to control lead emissions from stationary point sources. Lead emissions from stationary sources ha ve been substantially reduced by control programs oriented toward attainment of the PM 10and lead ambient standards. However, significant and ambient problems still remainaround some lead point sources, which are now the focus of new monito ring initiatives. Lead emissions in 1993 from industrial sources, e.g., primary and secondary lead smelters, dropped by about 91 percent from levels reported in 1970. Emissions of lead fr om solid waste disposal are down about 76 percent since 1970. In 1993, emissions from so lid waste disposal, industrial processes and transportation were: 500, 2,300 and 1,600 short tons, respectively. The overall effect of the control programs for these three cat egories has been a major reduction in the amount of lead in the ambient air. There are two areas currently designate d as nonattainment for the lead NAAQS. They are East Helena Area portion of Lewis and Clark Counties, M ontana; and the area within the city limits of Herculaneum in Jefferson County, Missouri. That means that about 4600 people are living in areas designate d as nonattainment for the standard (2000 census). Air quality monitoring in the Ea st Helena Nonattainment Area has been discontinued and the lead source has closed. Air quality in Herculaneum is violating the NAAQS as shown in Table 13. There is one area, Delaware County, Indiana, with newly violating air quality monitoring data for th e lead NAAQS. Table 13 shows lead design values for these areas for 2003-2004 and 2004-2005 and if the areas’ design values meet the NAAQS based on the most recen t data collected during 2004-2005.

25Table 13. Areas Currently Designated Nonatt ainment for the Lead NAAQS or Designated Attainment But Not Meeting the Lead NAAQS: 2003-2004 through 2004-2005

Table 13 Design Value (μg/m 3 ) State Area 2003-2004 2004-2005 Meets NAAQS 2004-2005 MT E. Helena Source closed, site remediated, monitoring discontinued MO No Herculaneum 1.49 1.93 IN Delaware County 4.09 4.09 No Source: AQS November 2, 2006 Additional air quality information for all ozone and particulate matter monitors can be found at http://www.epa.gov/air/airtrends/ . Sstatistics and capability for the user to create maps, graphs, and data tables is located at http://www.epa.gov/airexplorer/

. Daily and forecast air quality information is available at http://airnow.gov/

. EPA’s tracking system for all criteria pollutant designated nonattainment and maintenance areas is located at http://www.epa.gov/oar/ oaqps/greenbk/index.html

.

26List of Appendices Appendix A Page A1 Additional Information on Area Classifications for the 8-Hour Ozone Standard Appendix B Page B1 Interpretation of the 8-Hour Primary and Secondary National Ambient Air Quality Standards for Ozone Appendix C Page C1 Interpretation of the National Ambient Air Quality Standards for Particulate Matter 2.5 Appendix D Page D1 Interpretation of National Ambient Air Quality Standards for Particulate Matter 10

27Appendix A

Additional Information on Area Classifications for the 8-Hour Ozone Standard

40 CFR Part 51.902

Sec. 51.902 Which classification and nonattain ment area planning provisions of the CAA shall apply to areas designated nonattainment for the 8-hour NAAQS? (a) Classification under subpart 2. An area designated nonattainment for the 8-hour NAAQS with a 1-hour ozone design value equa l to or greater than 0.121 ppm at the time the Administrator signs a final rule designating or redesignating the area as nonattainment for the 8-hour NAAQS will be classified in accordance with secti on 181 of the CAA, as interpreted in §51.903(a), for purposes of the 8-hour NAAQS, and will be subject to the requirements of subpart 2 that apply for that classification. (b) Covered under subpart 1. An area designated nonattainment for the 8-hour ozone NAAQS with a 1-hour design value less than 0.121 ppm at the time the Administrator signs a final rule designati ng or redesignating the area as nonattainment for the 8-hour NAAQS will be covered under section 172(a)(1) of the CAA and will be subject to the requirements of subpart 1. Sec. 51.903 How do the classification and attainment date provi sions in section 181 of subpart 2 of the CAA apply to areas subject to section 51.902(a)? (a) In accordance with section 181(a)(1) of the CAA, each area subject to §51.902(a) shall be classified by operation of law at the time of designation. However, the classification shall be based on the 8-hour desi gn value for the area, in accordance with Table 1 below, or such higher or lower classi fication as the State may request as provided in paragraphs (b) and (c) of this section. The 8-hour design value for the area shall be calculated using the three most recent years of air quality data. For each area classified under this section, the primary NAAQS attainment date for the 8-hour NAAQS shall be as expeditious as practicable but not later than the date pr ovided in the following Table.

A 1CLASSIFICATION FOR 8-HOUR OZONE NAAQS FOR AREAS SUBJECT TO SECTION 51.902(a) Area class 8-hour design value (ppm ozone) Maximum Period for Attainment Dates in State Plans (years after effective date of nonattainment designation for 8­ hour NAAQS) Marginal from 0.085 3 up to* 0.092 Moderate from 0.092 6 up to* 0.107 Serious from 0.107 9 up to* 0.120 Severe-15 from 0.120 15 up to* 0.127 Severe-17 from 0.127 17 up to* 0.187 Extreme equal to or above 0.187 20
* but not including
(b) A State may request a higher classification for any reason in accordance with section 181(b)(3) of the CAA.
(c) A State may request a lower classificati on in accordance with se ction 181(a)(4) of the CAA.

A 2Appendix B Interpretation of the 8-Hour Primary and Secondary National Ambient Air Quality Standards for O 3 40 CFR Part 50 Appendix I

1. General. This appendix explains the data handli ng conventions and computations necessary for determining whether the national 8-hour primary and secondary ambient air quality standards for ozone specified in Sec. 50.10 are met at an ambient ozone air quality monitoring site. Ozone is m easured in the ambient air by a reference method based on appendix D of this part. Data reporting, datahandling, and computati on procedures to be used in making comparisons between reported ozone concentrations and the level of the ozone standard are specified in the following sections. Whether to exclude, retain, or make adjustments to the data affected by stratospheric ozone intrus ion or other natural events is subject to the approval of the appropriate Regional Administrator.

2. Primary and Secondary Ambient Air Quality Standards for Ozone.

2.1 Data Reporting and Handling Conventions.

2.1.1 Computing 8-hour averages. Hourly average concentrations shall be reported in parts per million (ppm) to the third decimal place, with additional digits to the right being truncated. Running 8-hour averages sha ll be computed from the hourly ozone concentration data for each hour of the year and the result shall be stor ed in the first, or start, hour of the 8-hour period. An 8-hour average shall be cons idered valid if at least 75 percent of the hourly averages for the 8-hour pe riod are available. In the event that only 6 (or 7) hourly averages are available, the 8-houraverage shall be computed on the basis of the hours available using 6 (or 7) as the divi sor. (8-hour periods with three or more missing hours shall not be ignored if, after s ubstituting one-half the minimum detectable limit for the missing hourly concentrations, th e 8-hour average concentration is greater than the level of the standar d.) The computed 8-hour averag e ozone concentrations shall be reported to three decimal places (the insi gnificant digits to th e right of the third decimal place are truncated, cons istent with the data handling procedures for the reported data.)

2.1.2 Daily maximum 8-hour average concen trations. (a) There ar e 24 possible running 8-hour average ozone concentrations for each calendar day during the ozone monitoring season. (Ozone monitoring seasons vary by geog raphic location as designated in part 58, appendix D to this chapter.) The daily maximum 8-hour concentration for a given calendar day is the highest of the 24 possible 8-hour average concentrations computed for that day. This process is repeated, yielding a daily maximum 8-hour average ozone concentration for each calendar day with am bient ozone monitoring data. Because the 8­ hour averages are reco rded in the start hour, the daily maximum 8-hour concentrations

B 1from two consecutive days may have some hourly concentrations in common. Generally, overlapping daily maximum 8-hour averages are not likely, except in those non-urban monitoring locations with less pronounced di urnal variation in hourly concentrations.
(b) An ozone monitoring day shall be c ounted as a valid day if valid 8-hour averages are available for at least 75percent of possible hours in the day (i.e., at least 18 of the 24 averages). In the event that less than 75 per cent of the 8-hour averag es are available, a day shall also be counted as a valid day if the daily maximum 8-hour average concentration for that day is greater th an the level of the ambient standard.

2.2 Primary and Secondary Standard-rel ated Summary Statistic . The standard-related summary statistic is the annual fourth -highest daily maximum 8-hour ozone concentration, expressed in parts per milli on, averaged over three years. The 3-year average shall be computed using the three most recent, consecutive calendar years of monitoring data meeting the data completene ss requirements described in this appendix. The computed 3-year average of the annual fourth-highest daily maximum 8-hour average ozone concentrations shall be expres sed to three decimal places (the remaining digits to the right are truncated.)

2.3 Comparisons with the Primary and Secondary Ozone Standards. (a) The primary and secondary ozone ambient air quality standards are met at an ambient air quality monitoring site when the 3-year average of the annual fourth-highest daily maximum 8­ hour average ozone concentrati on is less than or equal to 0.08 ppm. The number of significant Figures in the level of the sta ndard dictates the rounding convention for comparing the computed 3-year average a nnual fourth-highest daily maximum 8-hour average ozone concentration with the level of the standard. The third decimal place of the computed value is rounded, with values e qual to or greater th an 5 rounding up. Thus, a computed 3-year average ozone concentration of 0.085 ppm is the sma llest value that is greater than 0.08 ppm.

(b) This comparison shall be based on three consecutive, complete calendar years of air quality monitoring data. This requirement is met for the three year period at a monitoring site if daily maximum 8-hour average concentrations are available for at least 90 percent, on average, of the days during the designate d ozone monitoring season, with a minimum data completeness in any one year of at l east 75 percent of the de signated sampling days. When computing whether the minimum data completeness requirements have been met, meteorological or ambient data may be suffi cient to demonstrate that meteorological conditions on missing days were not conducive to concentrations above the level of the standard. Missing days assumed less than the level of the standard are counted for the purpose of meeting the data completeness re quirement, subject to the approval of the appropriate Regional Administrator.
(c) Years with c oncentrations greater than the level of the standard shall not be ignored on the ground that they have less than comp lete data. Thus, in computing the 3-year average fourth maximum concentration, cale ndar years with less than 75 percent data

B 2------------------------------------------------------------------------------------------------------------

------------------------------------------------------------------------------------------------------------

------------------------------------------------------------------------------------------------------------ completeness shall be included in the comput ation if the average annual fourth maximum 8-hour concentration is greater th an the level of the standard.
(d) Comparisons with the primary and secondary ozone standards are demonstrated by examples 1 and 2 in paragraphs (d)(1) and (d) (2) respectively as follows:
(1) As shown in example 1, the primary and secondary standards are met at this monitoring site because the 3- year average of the annual fourth-highest daily maximum 8-hour average ozone concentrations (i.e., 0.084 ppm) is less than or equal to 0.08 ppm. The data completeness requirement is also me t because the average percent of days with valid ambient monitoring data is greater than90 percent, and no single year has less than 75 percent data completeness. Example 1. Ambient monitori ng site attaining the primary and secondary ozone standards

1st Hi ghest 2nd Highest 3rd Highest 4th Highest 5th Highest Percent Daily Max 8- Da ily Max 8- Daily Max 8- Da ily Max 8- Daily Max 8- Year Valid Days hour Conc. hour Conc. hour Conc. hour Conc. hour Conc. (ppm) (ppm) (ppm) (ppm) (ppm)

1993 100% 0.092 0.091 0.090 0.088 0.085

1994 96% 0.090 0.089 0.086 0.084 0.080

1995 98% 0.087 0.085 0.083 0.080 0.075

=================================== Average 98 %

(2) As shown in example 2, the primary and secondary standards are not met at this monitoring site because the 3- year average of the fourth-h ighest daily maximum 8-hour average ozone concentrations (i.e., 0.093 ppm) is greater than 0.08 ppm. Note that the ozone concentration data for 1994 is used inthese computations, even though the data capture is less than 75 percent, because the average fourth-highest daily maximum 8-hour average concentration is greater than 0.08 ppm. Example 2. Ambient monitoring site failing to meet the primary and secondary ozone standards

1s t Highest 2nd Highest 3rd Highe st 4th Highest 5th Highest Percent Daily Max 8- Daily Max 8- Daily Max 8- Daily Max 8- Daily Max 8- Year Valid Days hour Conc. hour Conc . hour Conc. hour Conc. hour Conc. (ppm) (ppm) (ppm) (ppm) (ppm)

B 3------------------------------------------------------------------------------------------------------------

------------------------------------------------------------------------------------------------------------ 1993 96% 0.105 0.103 0.103 0.102 0.102

1994 74% 0.090 0.085 0.082 0.080 0.078

1995 98% 0.103 0.101 0.101 0.097 0.095

=================================== Average 89 %

3. Design Values for Primary and Secondary Ambient Air Quality Standards for Ozone. The air quality design value at a monito ring site is defined as that concentration that when reduced to the level of the standardensures that the site meets the standard. For a concentration-based standard, the air quality design value is simply the standard-related test statistic. Thus, for the primary and sec ondary ozone standards, the 3-year average annual fourth-highest daily maximum 8-hour av erage ozone concentration is also the air quality design value for the site. [62 FR 38895, July 18, 1997]

B 4Appendix C Interpretation of the National Ambient Air Quality Standards for PM 2.5 40 CFR Part 50 Appendix N

1. General

. (a) This appendix explains the datahandling conventions and computations necessary for determining when the annual and 24-hour primary and secondary national ambient air quality standards (NAAQS) for PM 2.5 specified in §50.7 and §50.13 of this part are met. PM 2.5 , defined as particles with an aerodynamic diameter less than or equal to a nominal 2.5 micrometers, is measured in the ambient air by a Federal reference method (FRM) based on appendix L of this part, as applicable, and designated in accordance with part 53 of this chapter, or by a Federal equivalent method (FEM) designated in accordance with part 53 of this chapter, or by an Approved Regional Method (ARM) designated in accordance with part 58 of this chapter. Data handling and computation procedures to be used inmaking comparisons between reported PM 2.5 concentrations and th e levels of the PM 2.5 NAAQS are specified in the following sections.
(b) Data resulting from exceptional even ts, for example structural fires or high winds, may be given special consideration. In some cases, it may be appropriate to exclude these data in whole or part because they could result in inappropriate values to compare with the levels of the PM 2.5 NAAQS. In other cases, it may be more appropriate to retain the data for comparison with the levels of the PM 2.5 NAAQS and then for EPA to formulate the appropriate regulatory response.
(c) The terms used in this appendix are defined as follows:

Annual meanrefers to a weighted arithmetic mean, based on quarterly means, as defined in section 4.4 of this appendix.
Creditable samples are samples that are given cred it for data completeness. They include valid samples collected on required sampling days and valid “make-up” samples taken for missed or invalidated samples on required sampling days.
Daily values for PM 2.5 refers to the 24-hour average concentrations of PM 2.5 calculated (averaged from hourly measurements ) or measured from midnight to midnight (local standard time) that ar e used in NAAQS computations.
Designated monitors are those monitoring sites de signated in a State or local agency PM Monitoring Network Description inaccordance with part 58 of this chapter.
Design values are the metrics (i.e., statistics) that are compared to the NAAQS levels to determine compliance, calculated as shown in section 4 of this appendix:

C 1(1) The 3-year average of annual means for a single monitoring site or a group of monitoring sites (referred to as the “annual standard design value ”). If spatial averaging has been approved by EPA for a group of sites which meet the criteria specified in section 2(b) of this appendix and section 4.7.5 of appendix D of 40 CFR part 58, then 3 years of spatially averaged annual means will be averaged to derive the annual standard design valuefor that group of sites (further referre d to as the “spatially averaged annual standard design value ”). Otherwise, the annual standard design value will represent the 3­ year average of annual means for a single site(further referred to as the “single site annual standard design value ”).
(2) The 3-year average of annual 98 thpercentile 24-hour average values recorded at each monitoring site (referred to as the “24-hour standard design value ”).
Extra samples are non-creditable sample s. They are daily values that do not occur on scheduled sampling days and that can notbe used as make-ups for missed or invalidated scheduled samples. Extra sample s are used in mean calculations and are subject to selection as a 98 thpercentile.
Make-up samples are samples taken to supplant missed or invalidated required scheduled samples. Make-ups can be madeby either the primary or the collocated instruments. Make-up samples are either take n before the next required sampling day or exactly one week after the missed (or voided) sampling day. Also, to be considered a valid make-up, the sampling must be ad ministered according to EPA guidance.

98 thpercentileis the daily value out of a year of PM 2.5 monitoring data below which 98 percent of all daily values fall.

Year refers to a calendar year.

2.0 Monitoring Considerations

. (a) Section 58.30 of this ch apter specifies which monito ring locations are eligible for making comparisons with the PM 2.5 standards.
(b) To qualify for spatial averaging, m onitoring sites must meet the criterion specified in section 4.7.5 of appendix D of 40 CFR part 58 as well as the following requirements:
(1) The annual mean concentration at eachsite shall be within 10 percent of the spatially averaged annual mean.
(2) The daily values for each site pair among the 3-year period shall yield a correlation coefficient of at le ast 0.9 for each calendar quarter.

C 2(3) All of the monitoring sites should principally be affected by the same major emission sources of PM 2.5 . For example, this could be demonstrated by site-specific chemical speciation profiles confirming all ma jor component concentration averages to be within 10 percent for each calendar quarter.
(4) The requirements in paragraphs (b)(1 ) through (3) of this section shall be met for 3 consecutive years in order to produce a valid spatially averaged annual standard design value. Otherwise, the in dividual (single) site annual standard design values shall be compared directly to the level of the annual NAAQS.
(c) Section 58.12 of this chapter spec ifies the required minimum frequency of sampling for PM 2.5 . Exceptions to the specified sampli ng frequencies, such as a reduced frequency during a season of expected low conc entrations (i.e., “seasonal sampling”), are subject to the approval of EPA. Annual 98 thpercentile values are to be calculated according to equation 6 in section 4.5 of this appendix when a site operates on a “seasonal sampling” schedule.

3.0 Requirements for Data Used for Comparisons with the PM 2.5 NAAQS and Data Reporting Considerations

. (a) Except as otherwis e provided in this append ix, only valid FRM/FEM/ARM PM 2.5 data required to be submitted to EPA’s Ai r Quality System (AQS) shall be used in the design value calculations.
(b) PM 2.5 measurement data (typically hourly for continuous instruments and daily for filter-based instruments) shall bereported to AQS in micrograms per cubic meter ( μ g/m 3 ) to one decimal place, with additional digits to the right being truncated.
(c) Block 24-hour averages shall be computed from available hourly PM 2.5 concentration data for each co rresponding day of the year and the result shall be stored in the first, or start, hour (i.e., midnight, hour ‘0’) of the 24-hour period. A 24-hour average shall be considered valid if at least 75 percent (i.e., 18) of the hourly averages for the 24­ hour period are available. In th e event that less than all 24 hourly averages are available (i.e., less than 24, but at least 18), the 24-hour average shall becomputed on the basis of the hours available using the number of available hours as the divi sor (e.g., 19). 24-hour periods with seven or more missing hours shall be considered valid if, after substituting zero for all missing hourly concentrations, the 24-hour average concentration is greater than the level of the standard. The computed 24-hour average PM 2.5 concentrations shall be reported to one decimal place (the additional digits to the right of the first decimal place are truncated, consistent with the data handling procedures for the reported data).
(d) Except for calculatio n of spatially averaged annual means and spatially averaged annual standard design values, all other calculations show n in this appendix shall be implemented on a site-level basis. Si te level data shall be processed as follows:

C 3(1) The default dataset for a site shal l consist of the measured concentrations recorded from the designated primary FRM/FEM/ARM monitor. The primary monitor shall be designated in the appropriate State or local agency PM Monitoring Network Description. All daily values produced by the primary sampler are considered part of the site record (i.e., that site’s daily value); th is includes all creditable samples and all extra samples.
(2) Data for the primary monitor shall be augmented as much as possible with data from collocated FRM/FEM/ARM monitors . If a valid 24-hour measurement is not produced from the primary monitor for a partic ular day (scheduled or otherwise), but a valid sample is generated by a collocated FRM/FEM/ARM instrument (and recorded in AQS), then that collocated value shall be consid ered part of the site data record (i.e., that site’s daily value). If more than one valid collocated FRM/FEM/ARM value is available, the average of those valid collocated valu es shall be used as the daily value.
(e) All daily values in the composite s ite record are used in annual mean and 98 th percentile calculations, howeve r, not all daily values are give credit towards data completeness requirements. Only “creditable” samples are given credit for data completeness. Creditable samples include va lid samples on scheduled sampling days and valid make-up samples. All other types of daily values are referred to as “extra” samples.

4.0 Comparisons with the PM 2.5 NAAQS

.
4.1 Annual PM 2.5 NAAQS

. (a) The annual PM 2.5 NAAQS is met when the annual standard design value is less than or equal to 15.0 micrograms per cubic meter ( μ g/m 3 ).
(b) For single site comparisons, 3 ye ars of valid annual means are required to produce a valid annual standard design value. In the case of spatial averaging, 3 years of valid spatially averaged annual means are re quired to produce a valid annual standard design value. Designated sites with less than 3 years of data shall be included in annual spatial averages for those years that data completeness requirements are met. A year meets data completeness requirements when at least 75 percent of the scheduled sampling days for each quarter have valid data. [Quarterly data capture rates (expressed as a percentage) are specifically calculated as the number of creditable samples for the quarter divided by the number of scheduled samples fo r the quarter, the result then multiplied by 100 and rounded to the nearest integer.] Howeve r, years with at least 11 samples in each quarter shall be considered valid, notwithstan ding quarters with less than complete data, if the resulting annual mean, spatially averag ed annual mean concen tration, or resulting annual standard design value concentration (rounded according to the conventions of section 4.3 of this appendix) is greater than the level of the standard. Furthermore, where the explicit 11 sample per quart er requirement is not met, th e site annual mean shall still be considered valid if, by substituting a low value (described below) for the missing data in the deficient quarters (substituting e nough to meet the 11 sample minimum), the computation still yields a recalculated annual mean, spatially averaged annual mean

C 4concentration, or annual standard design value concentration ove r the level of the standard. The low value used for this substitu tion test shall be the lowest reported daily value in the site data record for that calenda r quarter over the most recent 3-year period. If an annual mean is deemed complete using this test, the original annual mean (without substituted low values) shall be considered th e official mean value for this site, not the result of the recalculated test using the low values.
(c) The use of less than complete data is subject to the approval of EPA, which may consider factors such as monitoring site closures/moves, monitoring diligence, and nearby concentrations in determin ing whether to use such data.
(d) The equations for calculating the annual standard design values are given in section 4.4 of this appendix.

4.2 24-Hour PM 2.5 NAAQS

. (a) The 24-hour PM 2.5 NAAQS is met when the 24-hourstandard design value at each monitoring site is less than or equal to 35 μ g/m 3 . This comparison shall be based on 3 consecutive, complete years of air quality data. A year meets data completeness requirements when at least 75 percent of th e scheduled sampling days for each quarter have valid data. However, years shall be c onsidered valid, notwithstanding quarters with less than complete data (even quarters with less than 11 samp les), if the resulting annual 98 thpercentile value or resulting 24-hour standard design value (rounde d according to the conventions of section 4.3 of this appendix) is greater than the level of the standard.
(b) The use of less than complete data is subject to the approval of EPA which may consider factors such as monitoring site closures/moves, monitoring diligence, and nearby concentrations in determining whether to use such data for comparisons to the NAAQS.
(c) The equations for calculating the 24-hour standard design values are given in section 4.5 of this appendix.

4.3 Rounding Conventions . For the purposes of comparing calculated values to the applicable level of the st andard, it is necessary to round the final results of the calculations described in s ections 4.4 and 4.5 of this appendix. Results for all intermediate calculations shall not be rounded.
(a) Annual PM 2.5 standard design values shall be rounded to the nearest 0.1 μ g/m 3 (decimals 0.05 and greater are rounded up to the next 0.1, and any decimal lower than 0.05 is rounded down to the nearest 0.1).
(b) 24-hour PM 2.5 standard design values sha ll be rounded to the nearest 1 μ g/m 3 (decimals 0.5 and greater ar e rounded up to the nearest w hole number, and any decimal lower than 0.5 is rounded down to the nearest whole number).

C 54.4 Equations for the Annual PM 2.5 NAAQS

. (a) An annual mean value for PM 2.5 is determined by first averaging the daily values of a calendar quarter usi ng equation 1 of this appendix:
Equation 1

n q 

## 1

n X s,y,q 

## = 

# ∑ X s,y,q,i
q i = 1 Where:

–

x n X

q,y,s = the mean for quarter q of the year y for site s;

q = the number of daily va lues in the quarter; and
i q,y,s = the i thvalue in quarter q for year y for site s.
(b) Equation 2 of this appendix is then us ed to calculate the site annual mean:
Equation 2
4 

## 1 4 X

s,y 

## = 

# ∑ X s,y,q
q = 1

Where:

– X y,s = the annual mean concentration for year y (y = 1, 2, or 3) and for site s; and

– X

q,y,s = the mean for quarter q of year y for site s.

(c) If spatial averaging is utilized, the si te-based annual means will then be averaged together to derive the spatially av eraged annual mean using equation 3 of this appendix. Otherwise (i.e., for si ngle site comparisons), skip to equation 4.B of this appendix.
Equation 3

n s 

## 1

n x y 

## = 

# ∑ x s,y

s s = 1 Where:

– = the spatially averaged mean for year y, x y

C 6– the annual mean for year y and site s fo r sites designated to be averaged that =

n x y,s meet completeness criteria , and

s = the number of sites designated to be averaged that meet completeness criteria
(d) The annual standard design value is ca lculated using equation 4A of this appendix when spatial averaging and equati on 4B of this appendix when not spatial averaging:
Equation 4A Equation 4B When spatial averaging When not spatial averaging

3 3 

### 1 3 x = 

# ∑ x y 

### x = 1 

# ∑ x s,y
y = 1 

### 3 y = 1

Where:

– = the annual standard design value (thespatially averaged annual standard x design value for equation 4A of this appendix and the single site annual standard design value for equati on 4B of this appendix); and

– = the spatially averaged an nual mean for year y (result of equation 3 of this x

y appendix) when spatial averaging is used, or

– = the annual mean for year y and site s (result of equation 2 of this appendix) x

y,s when spatial averaging is not used.
(e) The annual standard design value is rounded according to the conventions in section 4.3 of this appendix before a comparison with the standard is made.

4.5 Equations for the 24-Hour PM 2.5 NAAQS

. (a) When the data for a particular site and year meet the data completeness requirements in section 4.2 of this appendix, calculation of the 98 thpercentile is accomplished by the steps provided in this s ubsection. Equation 5 of this appendix shall be used to compute annual 98 th percentile values, except that where a site operates on an approved seasonal sampling schedule, equation 6 of this appendix shall be used instead.
(1) Regular formula for computing annual 98 thpercentile values . Calculation of annual 98th percentile values using the regular formula (equ ation 5) will be based on the creditable number of samples (as describe d below), rather than on the actual number of samples. Credit will not be granted for extra (non-creditable) samples. Extra samples, however, are candidates for selection as the annual 98th percentile. [The creditable number of samples will determine how deep to go into the data distribution, but all samples (creditable and extra) will be considered when making the percentile assignment.] The annual creditable number of samples is the sum of the four quarterly creditable number of samples. Sort all the daily values from a partic ular site and year by

C 7i ascending value. (For example: (x[1 ], x[2], x[3], ..., x[n]). In th is case, x[1] is the smallest number and x[n] is th e largest value.) The 98 th percentile is determined from this sorted series of daily values which is ordered from the lowest to the highest number. Compute

98 (0.98) x (cn) as the number “i.d,” where ‘cn’ is the annual creditable number of samples, “i” is the integer part of th e result, and “d” is the deci mal part of the result. The th percentile value for year y, P 0.98, y , is calculated using equation 5 of this appendix:
Equation 5



## P

y,98.0 

## = X [ 1 i 

### ] +

x Where: P 0.98, y= 98 thpercentile for year y;

[i+1] = the (i+1) thnumber in the ordered series of numbers; = the integer part of the product of 0.98 and cn.

(2) Formula for computing annual 98 thpercentile values when sampling frequencies are seasonal. Calculate the annual 98 thpercentiles by determining the smallest measured concentration, x, that makes W(x) greater than 0.98 using equation 6 of this appendix:

Equation 6



## W 

# ( ) = d High 

## x + x d d x High 

## + d Low 

## F High 

# ( ) d Low 

## F Low 

# ( )

High 

## + d Low Where:

d High = number of calendar days in the "High" season ; d Low = number of calendar days in the "Low" season; d High + days in a year; and = d Low are that a season in values daily of number ≤ x F a (x) = a season in values daily of number
Such that “a” can be either “High” or “Low ”; “x” is the measured concentration; and “d High/(d High+ d Low ) and d Low /(d High+ d Low )” are constant and are called seasonal “weights.”
(b) The 24-hour standard design value is then calculated by averaging the annual 98 thpercentiles using equatio n 7 of this appendix:
Equation 7

C 83 

# ∑ P .0 98 y,



## = y = 1 

## P

.0 98 

## 3
(c) The 24-hour standard design value (3-year average 98 th percentile) is rounded according to the conventions in section 4.3 of this appendix before a comparison with the standard is made.

C 9Appendix D Interpretation of the National Ambi ent Air Quality Standards for PM 40 CFR Part 50 Appendix K

1.0 General.
(a) This appendix explains the computations necessary for analyzing particulate matter data to determine attainment of the 24-hour standards specified in 40 CFR 50.6. For the primary and secondary standards, particulate matter is measured in the ambient air as PM 10(particles with an aerodynamic diameter less than or equal to a nominal 10 micrometers) by a reference method based on ap pendix J of this part and designated in accordance with part 53 of this chapter, or by an equivalent method designated in accordance with part 53 of this chapter. Th e required frequency of measurements is specified in part 58 of this chapter.
(b) The terms used in this appendix are defined as follows:
Average refers to the arithmetic mean of the estimated number of exceedances per year, as per Section 3.1.
Daily value for PM 10refers to the 24-hour av erage concentration of PM 10calculated or measured from midnight to midnight (local time).

Exceedance means a daily value that is above th e level of the 24-hour standard after rounding to the nearest 10 μ g/m 3 (i.e., values ending in 5 or greater are to be rounded up).
Expected annual value is the number approached whenthe annual values from an increasing number of years are averaged, in th e absence of long-term trends in emissions or meteorological conditions.

Year refers to a calendar year.
(c) Although the discussion in this appe ndix focuses on monitored data, the same principles apply to modeling data, s ubject to EPA modeling guidelines.

2.0 Attainment Determinations.

2.1 24-Hour Primary and Secondary Standards.
(a) Under 40 CFR 50.6(a) the 24-hour primary an d secondary standards are attained when the expected number of exceedances per year at each monitoring site is less than or equal to one. In the simplest case, the number of e xpected exceedances at a site is determined by recording the number of exceedances in eachcalendar year and then averaging them over the past 3 calendar years. Situations in which 3 years of data are not available and

D 1possible adjustments for unusual events or tre nds are discussed in sections 2.3 and 2.4 of this appendix. Further, when data for a year are incomplete, it is necessary to compute an estimated number of exceedances for that year by adjusting the observed number of exceedances. This procedure, performed by cal endar quarter, is described in section 3.0 of this appendix. The expected number of excee dances is then estimated by averaging the individual annual estimates for the past 3 years.
(b) The comparison with the allowable expectedexceedance rate of one per year is made in terms of a number rounded to the nearest tenth (fractional values equal to or greater than 0.05 are to be rounded up; e.g., an exceedance rate of 1.05 would be rounded to 1.1, which is the lowest rate for nonattainment).

2.2 Reserved

2.3 Data Requirements.
(a) 40 CFR 58.12 specifies the required minimum frequency of sampling for PM 10 . For the purposes of making comparisons with the particulate matter standards, all data produced by State and Local Air Monitoring Stations (SLAMS) and other sites submitted to EPA in accordance with the part 58 requirements must be used, and a minimum of 75 percent of the scheduled PM 10samples per quarter are required.
(b) To demonstrate attainment of the 24-hour standards at a monito ring site, the monitor must provide sufficient data to perform the required calculations of sections 3.0 and 4.0 of this appendix. The amount of data require d varies with the sampling frequency, data capture rate and the number of years of record. In all case s, 3 years of representative monitoring data that meet the 75 percent criterion of the previous paragraph should be utilized, if available, and would suffice. Mo re than 3 years may be considered, if all additional representative years of data meeti ng the 75 percent criteri on are utilized. Data not meeting these criteria may also suffice to show attainment; how ever, such exceptions will have to be approved by the appropriate Regional Administrator in accordance with EPA guidance.
(c) There are less stringent data requirements for showing that a monitor has failed an attainment test and thus has recorded a violati on of the particulat e matter standards. Although it is generally necessary to meet the minimum 75 percent data capture requirement per quarter to use the computational equations descri bed in section 3.0 of this appendix, this criterion does not apply wh en less data is sufficient to unambiguously establish nonattainment. The following examples illustrate how nonattainment can be demonstrated when a site fails to meet th e completeness criteria. Nonattainment of the 24-hour primary standards can be establis hed by the observed annual number of exceedances (e.g., four observed exceedances in a single year), or by the estimated number of exceedances derived from th e observed number of exceedances and the required number of scheduled samples (e.g., two observed exceedances with every other day sampling). In both cases, expected annual values must exceed the levels allowed by the standards.

D 22.4 Adjustment for Exceptional Events and Trends.
(a) An exceptional event is an uncontroll able event caused by natural sources of particulate matter or an event th at is not expected to recur ata given location. Inclusion of such a value in the computation of exceedance s or averages could result in inappropriate estimates of their respective expected annual values. To reduce the effect of unusual events, more than 3 years of representativ e data may be used. Alternatively, other techniques, such as the use of statistical models or the use of historical data could be considered so that the event may be discount ed or weighted accord ing to the likelihood that it will recur. The use of such techniques is subject to the approval of the appropriate Regional Administrator in accordance with EPA guidance.
(b) In cases where long-term trends in emissions and air quality are evident, mathematical techniques should be applied to account for the trends to ensure that the expected annual values are not inappropriately biased by unrepre sentative data. In the simplest case, if 3 years of data are available under stable emi ssion conditions, this data should be used. In the event of a trend or shift in emission patterns, either the most recent representative year(s) could be used or statistical techniques or models could be used in conjunction with previous years of data to adjust for trends. The use of less than 3 years of data, and any adjustments are subject to the approval of the appropriate Regi onal Administrator in accordance with EPA guidance.

3.0 Computational Equations for the 24-hour Standards.

3.1 Estimating Exceedances for a Year.
(a) If PM 10sampling is scheduled less frequently than every day, or if some scheduled samples are missed, a PM 10value will not be available for each day of the year. To account for the possible effect of incomplete data, an adjustment must be made to the data collected at each monitoring location to estimate the number of exceedances in a calendar year. In this adjustment, the assu mption is made that the fraction of missing values that would have exceeded the standard level is identica l to the fraction of measured values above this level. This comput ation is to be made for all sites that are scheduled to monitor throughout the entire year and meet th e minimum data requirements of section 2.3 of this appendix. Because of po ssible seasonal imbalance, this adjustment shall be applied on a quarterly basis. The es timate of the expected number of exceedances for the quarter is equal to the observed number of exceedances plus an increment associated with the missing data. The following equation must be used for these computations:
Equation 1 

## ⎛ ⎜ ⎜ N q 

## ⎞ ⎟ ⎟ e = v ×

q q 

## ⎝ n q 

## ⎠

D 3where:

e q= the estimated number of exceedances for calendar quarter q;

v q= the observed number of exceedances for calendar quarter q;

N q= the number of days in calendar quarter q;

n q= the number of days in calendar quarter q with PM 10data; and
q = the index for calendar quarter, q=1, 2, 3 or 4.
(b) The estimated number of exceedances for a calendar quarter must be rounded to the nearest hundredth (fractional valu es equal to or greater than0.005 must be rounded up).
(c) The estimated number of exceedances for th e year, e, is the sum of the estimates for each calendar quarter.
Equation 2

4 

## e = 

# ∑ e q

= 1 q (d) The estimated number of exceedances for a single year must be rounded to one decimal place (fractional values equal to or greater than 0.05 are to be rounded up). The expected number of exceedances is then estimated by averaging the individual annual estimates for the most recent 3 or more representative years of data. The expected number of exceedances must be rounded to one decimal place (fracti onal values equal to or greater than 0.05 ar e to be rounded up).
(e) The adjustment for incomplete data will not be necessary for monitoring or modeling data which constitutes a complete record, i.e., 365 days per year.
(f) To reduce the potential fo r overestimating the number of expected exceedances, the correction for missing data will not be require d for a calendar quarter in which the first observed exceedance has occurred if:
(1) There was only one exceedance in the calendar quarter;
(2) Everyday sampling is subsequently initiated and maintained for 4 calendar quarters in accordance with 40 CFR 58.12; and
(3) Data capture of 75 per cent is achieved during the re quired period of everyday sampling. In addition, if the first exceedance is observed in a calendar quarter in which

D 4the monitor is already sampling every day, no adjustment for missing data will be made to the first exceedance if a 75 percent data cap ture rate was achieved in the quarter in which it was observed.
Example 1

a. During a particular calendar quarter, 39 out of a possible 92 samples were recorded, with one observed exceedance of the 24-hour standard. Using Equation 1, the estimated number of exceedances for the quarter is:
eq=1×92/39=2.359 or 2.36.

b. If the estimated exceedances for the other 3 calendar quarters in the year were 2.30, 0.0 and 0.0, then, using Equation 2, the estimated number of exceedances for the year is 2.36+2.30+0.0+0.0 which equals 4.66 or 4.7. If no exceedances were observed for the 2 previous years, then the expected nu mber of exceedances is estimated by: (1/3)×(4.7+0+0)=1.57 or 1.6. Since 1.6 exceed s the allowable number of expected exceedances, this monitoring site would fail the attainment test.
Example 2
In this example, everyday sampling was initiated following the first observed exceedance as required by 40 CFR 58.12. Accordingly, the first observed exceedance would not be adjusted for incomplete sampling. During the next three quarters, 1.2 exceedances were estimated. In this case, the estimated exceedances for the year would be 1.0+1.2+0.0+0.0 which equals 2.2. If, as before, no exceedances were observed for the two previous years, then the estimated exceedances for the 3-year period would then be (1/3)×(2.2+0.0+0.0)=0.7, and the monitoring site would not fail the attainment test.

3.2 Adjustments for Non-Scheduled Sampling Days.
(a) If a systematic sampling schedule is us ed and sampling is performed on days in addition to the days specified by the system atic sampling schedule, e.g., during episodes of high pollution, then an adjustment must be made in the equation for the estimation of exceedances. Such an adjustment is needed to eliminate the bias in the estimate of the quarterly and annual number of exceedances that would occur if the chance of an exceedance is different for scheduled than fo r non-scheduled days, as would be the case with episode sampling.
(b) The required adjustment treats the syst ematic sampling schedule as a stratified sampling plan. If the period from one scheduledsample until the day preceding the next scheduled sample is defined as a sampling stratum, then there is one stratum for each scheduled sampling day. An aver age number of observed ex ceedances is computed for each of these sampling strata. With nonschedul ed sampling days, the estimated number of exceedances is defined as:

D 5Equation 3



## e = ⎜ ⎛ N ⎞ m q 

## ⎛ v j 

## ⎞ q 

## ⎟ ⎜ ⎟
q 

## ⎜ ⎟ × 

# ∑ ⎜ ⎝ m q 

## ⎠ j = 1 

## ⎝ k j 

## ⎠ ⎟

where:

e q= the estimated number of exceedances for the quarter;

N q= the number of days in the quarter;

mq= the number of strata withsamples during the quarter;

v

j = the number of observed exceedances in stratum j; and

k

j = the number of actual samples in stratum j.
(c) Note that if only one sample value is recorded in each stratum, then Equation 3 reduces to Equation 1.
Example 3
A monitoring site samples according to a systematic sampling schedule of one sample every 6 days, for a total of 15 scheduled sample s in a quarter out of a total of 92 possible samples. During one 6-day period, potential episode levels of PM 10were suspected, so 5 additional samples were taken. One of the regular scheduled samples was missed, so a total of 19 samples in 14 sampling strata we re measured. The one 6-day sampling stratum with 6 samples recorded 2 exceedances. The remainder of the quarter with one sample per stratum recorded zero exceedances. Using Equation 3, the estimated number of exceedances for the quarter is:
Eq = (92/14)×(2/6+0+. . .+0)=2.19.

D 6