# UNITED STATES ENVIRONMENTAL PROTECTION AGENCY REGION II AIR PROGRAMS BRANCH

Technical Support Document EPA’s Notice of Proposed Rulemaking

For Approval and Promulgation of Air Quality Plans; Determination of Attainment of the 1997 Fine P article Standard

July 2010

# 2

Technical Support Document I. INTRODUCTION..................................................................................... ...2 . II. CLEAN AIR ACT REQUIREMENTS FOR FINE PARTICLE (PM 2.5 

# ) ATTAINMENT. ..3 A. PM 2.5 

# Attainment Requirements .............................................................. ...3 B. Determining Attainment and EPA’s Clean Data Policy ........................................ .4 III. MONITORING NETWORK ............................................................ ............5 IV . PS 59 MONITORING SITE.................................................................. ........8 V. PS 19 MONITORING SITE ........................ ..................................................8 VI . EPA’S ANALYSI S .................................................................................. ..8 A. Analys is of Air Quality Data .....................................................................8 B. Addressing Missing Data ..........................................................................9 C. Additional Analysis ...............................................................................20 D. Trends .............................. .................................................................20 VII. CONCLUSION.................................................................................... ....22 APPENDIX A Annual Means for NY-NJ - CT PM2.5 

# FRM monitors ...................................23 APPENDIX B Network Review Letters .....................................................................26

I. INTRODUCTION In this technical support document, EPA provides information supporting our proposed determination that the New York-N. New Jersey- Long Island, NY-NJ - CT fine particle (PM2.5 

# ) nonattainment area has attained the 1997 annual fine particle (PM2.5 

# ) National Ambient Air Quality Standard (NAAQS). In this technical support document, EPA:

- summarizes the statutory and policy requirements for PM2.5 

# nonattainment area SIPs and EPA’s policy

concerning clean data;

- provides a description of the air quality monitoring network for the NY-NJ - CT fine particle

# 3 nonattainment area

- describes the PS 59 monitoring site, and provides an explanation for site shutdown;

- describes the PS 19 monitoring site, and provides an explanation for incomplete data;

- describe s our detailed analysis of our proposed clean data determination, including our analys is of the air quality data, and the methodology used for substituting for missing data;

- describes air quality

trends in the the NY-NJ - CT fine particle nonattainment area

- summarizes our conclusions on the clean data determination with respect to EPA requirements. II. CLEAN AIR ACT REQUIREMENTS FOR FINE PARTICLE (PM 2.5

# ) ATTAINMENT A. PM 2.5 

# Attainment Requirements In 1997, EPA revised the health-based NAAQS for PM2.5 

# , setting it at 15.0 micrograms per cubic meter (ug/m3 

# ) based on a 3 - year average of annual mean PM2.5 

# concentrations, and a 24 -hour standard of 65 ug/m3 

# based on a 3 - ye ar average of the 98th percentile of 24 -hour concentrations. EPA established the standards based on significant evidence and numerous health studies demonstrating that serious health effects are associated with exposures to p articulate matter. On January

5, 2005, (70 FR 944) EPA finalized its air quality designations and classifications across the country

with respect to the 1997 PM 2.5 

# standard . These designations became effective on April 5, 2005. The NY-NJ - CT PM2.5 

# nonattainment area was designated nonattainment for the 1997 annual PM2.5 

# NAAQS (see 40 CFR part 81.333). These designations triggered the Clean Air Act’s requirements under section 172(c), which requires the submission of an attainment plan for each designated nonattainment area. EPA’s PM2.5 

# implementation rule, published on April 25, 2007 (72 Fed. Reg. 20586) specifies that states must submit attainment plans for their nonattainment areas to the EPA by no later than three years from the effective date of designation, that is, by April 5, 2008. EPA’s PM2.5 

# implementation rule outlines the SIP requirements for the attainment plan, which includes among other things, the submission of an attainment demonstration showing the air- quality improvements expected to result from national and local control measures, an analys is of reasonably available control measures (RACM), including all reasonably available control technology (RACT), reasonable further progress plan, and contingency measures. The States of New Y

ork, New Jersey

, and Connecticut, are subject to these requirements since several counties in the State are located in a PM2.5 

# nonattainment area. The NY-NJ - CT PM2.5 

# nonattainment area (40 CFR 81.331) is comprised of the following portions of New York, New Jersey , and Connecticut: the New York portion contains the counties of the Bronx, Kings, Nassau, New York, Orange, Queens, Richmond, Rockland 1 

# , Suf folk, and We stchester. The New Jersey portion of the NY

- 1 

## On July 7, 2009, the United States Court of Appeals for the D.C. Circuit rendered its decisions in the PM 2.5 

## Designations Litigation, Catawba County, NC v. EPA , 571 F.3d 20 (D.C. Cir. 2009). The Court denied all of the petitions for review except Rockland County, New York and remanded the designation of Rockland County to EPA for further explanation of its designation.

# 4

NJ - CTPM2.5 

# nonattainment area contains the c ounties of Bergen, Essex, Hudson, Mercer, Middlesex, Monmouth, Morris, Passaic, Somerset, and Union. The Connecticut portion of the nonattainment area includes the counties of Fairfield and New Haven. New York, New Jersey

, and Connecticut submitted their attainment plans for this area on October 27, 2009, April 1, 2009, and November 18, 2008 respectively. EP A has not yet taken action on these submittals. B. Determining Attainment and EPA’s Clean Data Policy Under EPA regulations at 40 CFR 50.7: The annual primary and secondary PM2.5 

# standards are met when the annual arithmetic mean concentration, as determined in accordance with 40 CFR part 50, Appendix N, is less than or equal to 15.0 ug/m3



# . Data handling conventions and computations necessary for determining whether areas have met the PM2.5 

# NAAQS, including requirements for data completeness, are listed in Appendix N of 40 CFR Part 50. A year meets data completeness requirements when at least 75 percent of the scheduled sampling days for each quarter have valid data. 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 nearb y concentrations in determining whether to use such data. EP A issued a “Clean Data” policy in December 2004 describing possible reduced regulatory requirements for areas that attain the standards, but have not yet been designated as attainment. 2 

# In EPA’s PM2.5 

# implementation rule, published on April 25, 2007 (72 Fed. Reg. 20586), EPA finalized in section 51.1004(c) of the text the statutory interpretation that was embodied in the policy . As described in EPA’s clean data policy, upon a determination by EPA that an area designated nonattainment for the PM2.5 

# NAAQS has attained the standard, the requirements for such area to submit attainment demonstrations, reasonably available control measures, reasonable further progress plans, contingency

measures, and other planning SIPs related to attainment of the PM2.5 

# NAAQS shall be suspended until such time as: the area is redesignated to attainment, at which time the requirements no longer apply; or EPA determines that the area has violated the PM2.5 

# NAAQS , at which time the area is again required to submit such plans. Attainment determinations under EPA’s clean data policy do not shield an area from other required actions such as New Source Review (NSR), conformity and emission inventory

requirements, and provisions to address pollution transport, which would require emiss ion reductions at sources or other ty pes of emission activities contributing significantly to nonattainment in other areas or states, or interfering with maintenance in those areas. Determinations as to whether individual areas have attained the PM2.5 sta ndard and thus qualify

2 

## Memorandum of December 14, 2004, from Steve Page, Director, EPA Office of Air Quality Planning and Standards to EPA Air Divisi on Directors, “Clean Data Policy for the Fine Particle National Ambient Air Quality Standards.” This document is available at: http://www.epa.gov/pmdesignations/1997standards/guidance.htm

# 5

for application of the clean data policy are being made in the context of rulemakings for individual areas. This Technical Support Document (TSD) provides EPA’s analys is used to determine whether the NY-NJ - CT PM 2.5 

# nonattainment are a has achieved clean data. III. MONITORING NETWORK

With the promulgation of the annual and daily PM 2.5 

# national ambient air quality standards (NAAQS) in 1997, and the establishment of the Federal Reference Method (FRM) for monitoring PM 2.5 

# , air monitoring for this pollutant was initiated in the NY-NJ - CT PM2.5 

# nonattainment area beginning in 1998/1999. Only FRM data is used for determining compliance with the health based standards. The states also complement their FRM network with real -time direct reading hourly PM2.5 

# measurements . Real time monitors are used primarily in support of the Air Quality Index (AQI), which provides immediate information to the public about air quality and its re lationship to public health3



# . The PM2.5 

# FRM is a filter based method whereb y a sample is collected for a specified period of time (e.g., 24 hours) on filters that are weighed before and after collection to determine mass by difference . The mass value is divided by the total volume of air drawn through the filter, yielding the average mass concentration for the specified time period. Most of the FRM samplers in the NY-NJ - CT PM2.5 

# nonattainment area operate on a 1 - in- 3 - day schedule, although a few monitors operate on a daily basis. Also, as per network design requirements, several FRM sites have collocated duplicate samplers. The NY-NJ - CT PM 2.5 

# nonattainment area currently has thirty-nine air monitoring locations . This far exceeds the minimum regulatory requirements: 40 CFR part 58, Appendix D requires three monitoring locations for the NY M etropolitan Statistical Area based on a population above 1,000,000 and the most recent 3 year design value >=85% of the PM2.5 NAAQS . Table 1 shows the county design values (i.e., the 3 -ye ar average of annual mean PM2.5 conc entrations) for the years 2001 - 2009. The county design value is the highest annual mean measured for an FRM monitor that had complete data in a county. A map showing the locations of all FRM monitoring locations in the nonattainment area is shown in Figure 1. The annual design values for all FRM monitors in the three States located within the NY-NJ - CT PM2.5 

# nonattainment area since 1999 can be found in Appendix A.

3 

## Section 319 of the CAA requires EPA to establish a uniform air quality index for reporting of air quality. This section specifically directs the Administrator to ‘‘promulgate regulations establishing an air quality monitoring system throughout the United States which utilizes uniform air quality monitoring criteria and methodology and measures such air quality according to a uniform air quality index’’ and ‘‘provides for daily analysis and reporting of air quality based upon such uniform air quality index”

# 6

Table 1. --Design Values by County for the 1997 Annual PM 2.5 

## NAAQS for the NY -NJ - CT monitors in Micrograms per Cubic Meter (ug/m3 

## ). The standard for the 1997 Annual PM 2.5 

## NAAQS is 15.0 μg/m3 

## .

01 - 03 02 - 04 03 - 05 04 - 06 05 - 07 06 - 08 07 - 09 County DV DV DV DV DV DV DV

____________________________________________________________________________ Bronx 15.7 15.2 15.7 15.1 15.5 14.3 13.9 Kings 14.7 14.2 14.6 14.0 14.0 12.9 12.2 Nassau 12.2 11.7 12.1 11.5 11.4 10.9 10.3 New York4 

### 17.5 16.7 17.0 15.7 15.9 14.9 14.0 Orange 11.5 11.1 11.4 10.8 10.8 10.0 9.3 Queens INC 12.8 12.7 12.1 11.8 11.3 10.6 Richmond 12.0 11.5 11.8 13.4 13.2 12.4 11.6 Rockland NM NM NM NM NM NM NM Suffolk 12.1 11.3 11.5 INC INC 10.5 9.7 Westchester 12.3 11.7 11.9 11.6 11.7 11.2 10.6 Bergen INC 12.8 13.3 12.8 13.2 12.2 11.3 Essex 5 

### INC 13.5 INC 13.2 13.3 INC INC Hudson 14.7 14.3 14.7 14.1 14.0 14.1 13.1 Mercer 13.8 13.0 13.0 12.7 12.5 11.9 10.8 Middlesex 12.4 11.8 12.5 11.8 12.1 11.3 10.4 Monmouth NM NM NM NM NM NM NM Morris INC 11.6 11.9 11.2 11.3 10.3 9.6 Passaic INC 12.9 13.1 12.6 12.9 12.3 11.3 Somerset NM NM NM NM NM NM NM Union 15.5 15.3 15.5 14.8 14.4 13.6 12.6 Fairfield 13.1 12.7 13.3 13.2 13.2 12.4 11.3 New Haven 13.9 13.4 13.5 13.0 12.8 12.2 11.4 

## NM - No monitor located in county INC - Incom

plete data for time period. All counties listed as INC for time peri od did not meet 75 percent data completeness requirement, and had not previously shown violations of the NAAQS from years 2001 -2003 to present.

4 

## The monitor in New York County located at Public School 59 (P S 59) was the highest reading monitor at the time EPA made designations for the 1997 PM2.5 NAAQS on January 5, 2005. Midway through 2008, the monitor at PS59 was shut dow n due to the demolition of the building site. Therefore, the data up until 2008 was from PS 59. Missing 2008 data had an effect on calculating the design value for the annual standard. EPA developed an alternative procedure to determine the design value for the annual standard. This procedure used data representative of PS 59 based on EPA’s statistical analysis. A description of the alternate procedure can be found in Section VI. 5 

## The air monitor at the Newark Willis Center station in Essex County was discontinued on July 24 , 2008 due to an unexpected loss of access , and replaced with a new monitor at the Newark Firehouse . PM2.5 monitoring was established at the firehouse on May 13, 2009. Since three years of data was not collected at either monitoring site for 2006 - 08, and 2007 - 09, Essex County is listed as INC for the most recent three year periods

# 7

Figure 1: The PM2.5 

# FRM monitor locations in the NY-NJ - CT PM2.5 

# nonattainment area

The States o f New York, New Jersey, and Connecticut have been very diligent in the number and placement of PM 2.5 

# monitors in the nonattainment area. EPA meets annually with each state to discuss any problems or issues concerning the State’s air monitoring data and/or network. In addition, EPA and the States communicate many times during the ye ar so that issues can be addressed as they show up. EPA regulations require states to submit annual network plans to their respective Regions. These plans outline the current networks and any proposed changes in the upcoming 18 months. Regions 1 and 2 have always been able to approve these plans due to the high quality of the New York, New Jersey, and Connecticut monitoring networks. Copies of the approved annual network revi ew letters can be found in the Appendix B.

# 8

IV. PS 59 MONITORING SITE

The design value monitor for the NY-NJ - CT PM 2.5 

# nonattainment area was located on the roof of Public School 59 (AQS ID: 360610056) in New York County . The PS 59 monitor was the highest reading monitor at the time EPA made designations for the 1997 PM2.5 NAAQS on January 5, 2005. The unit was largely operational since monitoring was initiated in1999, with the exception of monitor shut down for most of the third quarter of 2003 due to roof repairs. Ambient monitoring was resumed at this site in October 2003. The site operated until mid 2008 , when monitoring was discontinued permanently at the site due to the building demolition of PS 59. This was a planned shutdown and although New York could have shut the monitor down at the beginning of the year, the state chose to continue operation as long as possible to collect data. Unfortunately, the monitor at this location c ould not be replaced, because the roof of the new building was too far above sidewalk level to serve as a valid monitoring site under 40 CFR part 86 , Appendix E. NY and EPA could not locate a suitable replacement monitoring site in the immediate vicinity

of PS 59 that would also meet siting criteria. The monitor at PS 59 was one of only two sites in the NY-NJ - CT PM2.5 

# nonattainment area without a valid attaining design value due to incomplete data. See section VI. for additional information. V. PS 19 MONITORING SITE

The monitor located on the roof of Public School 19 (AQS ID: 360610128) had the second highest PM2.5 ambient concentration in New York County based on data collected from 2002 - 2004 . The unit was largely operational since monitoring was initiated in October 2001, except for 2008 (i.e. quarters two thru f

our) and the first quarter of 2009 due to roof repair issues. Ambient monitoring was resumed at this site in March 2009. The monitor at PS 19 did not have a valid attaining design value due to incomplete data. See section VI. for additional informati on. VI. EPA’S ANALYSIS OF STATE SUBMITTAL A. Analysis of Air Quality Data EPA has reviewed the ambient air monitoring data for PM2.5 

# , consistent with the requirements contained in 40 CFR part 50 and recorded in the EPA Air Quality S ystem database for the NY-NJ - CT PM2.5 

# nonattainment area from 2001 through the present time. Currently al l monitors are well below the

# 9

annual standard of 15.0 ug/m3 

# . The highest design value for the most recent three ye ars, 2007 - 2009, for the NY -NJ - CT PM2.5 

# nonattainment area i s 14.0 ug/m3 

# , which is representative of monitoring data collected in New York County at Public School 59. All 3 -ye ar averages of the annual mean PM2.5 

# concentrations have been below the NAAQS since 2005 - 2007. Five sites in the NY-NJ - CT PM 2.5 

# nonattainment area had previously shown violations of the PM2.5 

# annual NAAQS when EPA finalized its air quality designations on January

5, 2005 . Two of those sites, PS 59 and PS 19, have not posted valid attaining design values due to incomplete data. The other three sites have all posted valid attaining values. In order to determine whether the NAAQS has been attained for PS 59 and PS 19, EPA has developed a procedure to address the missing data, and determine valid design value s for those sites for the annual standard for 2007 - 2009. EPA’s procedure is described in the following section. B. Addressing Missing Data An objective statistical method was developed to determine if previously violating monitors in the NY-NJ - CT PM2.5 nonattainment area that lack c omplete data would have met the NAAQS in subsequent time periods. Two previously violating monitors in the nonattainment area lacked complete data due to building demolition and roof repair. The general concept behind the statistical method to determine whether an incomplete monitor (target) would have met the NAAQS is to establish a linear regression relationship between the target monitor and another monitor in the nonattainment area (candidate). The linear regression would then be used to fill in the missing data for the target monitor. The results are checked with an additional statistical technique, known as bootstrapping, to verify if the conclusion of attainment is correct. The NY-NJ - CT PM2.5 nonattainment area has 39 monitoring locations which provide an ample number of monitors to compare to the target monitor. The two previously violating monitors in the NY-NJ - CT PM2.5 nonattainment area that had incomplete data were: PS 59 and PS 19 (AQS ID’s 360610056 and 360610128, respectively). PS 59 ce ased monitoring in June 2008 and had an incomplete design value of 15.5 μg/m3 

# for 2006 - 2008. PS 19 had poor data capture for 2008 due to roof repair. The goal of this methodology is to appropriately fill in the missing data from the last two quarters of 2008, and quarters 1 -4 of 2009 to determine if the NY-NJ - CT PM2.5 nonattainment area is attaining the NAAQS. Concept for determining design values The concept behind the method for determining design values (DVs) for the monitors with incomplete data is to establish a linear regression relationship between the target site with incomplete data and another site in the NY-NJ - CT PM2.5 nonattainment area which has more complete data in the period in which the target site is data deficient. The linear regress ion relationship would be based on time periods in which both the target and candidate monitors were operating. The linear regression

# 10

equation developed from the relationship between the target and candidate monitors were used to fill in missing data for the target site in any quarter in the most recent three - ye ar period that did not have 75 percent completeness based on actual observations, so that the normal data completeness requirement of 75 percent of data in each quarter of the three years is met. After the missing data for the sites was filled in, the results were verified through an additional statistical test. The additional statistical test used, referred to as bootstrapping, examines the differences between the predicted fill in concentrations and the actual observed concentrations to determine if the design values for the monitors with incomplete data meet the annual NAAQS for PM2.5. Eligibility Eligibility

criteria was established in order to assure that the method used to determine design values for the target monitors in the NY-NJ - CT PM2.5 nonattainment area was robust enough to allow consideration of the results in a weight of evidence decision. EPA has not established bright lines or specific requirements for determining design values for sites with less than complete data. Operating period Candidate monitors would have operated during the 3 - year period (2007 - 2009) in the NY-NJ - CT PM2.5 nonattainment area in which the target monitor has incomplete data in order to establish a signif icant relationship between the monitors. Candidate monitors do not necessarily have to have complete data in all 12 quarters of the 3 - ye ar period, but candidate monitors would have enough observations to allow it to be used to fill in enough missing days for target monitor so that the target monitor will end up with at least 75 percent completeness in all 12 quarters. Paired samples Pairs of sample data for target monitors and candidate monitors from the most recent 20 - quarter period of operation of the target monitors were used. The “period of operation” of the target monitors was based on the date of the last reported sample from the monitor. Candidate monitors had at least 100 historical sample pairs in common with target monitors during this perio d. When there were more than 100 pairs in the 20 - quarter period all available pairs were used. In addition to the 100 pairs over the 20 - quarters, candidate monitors had at least 20 paired days of data in common with the target monitors for each calendar quarter (adding together the number of days in a given calendar quarter [Q1, Q2, Q3, or Q4] across the 20 - quarter period). Several candidate sites met the eligibility criteria of 100 pairs over the 20 - quarters, and at least 20 paired days of data in common with the target monitors for each calendar quarter. Method for determining design values Step 1

– Organize data and perform linear regression(s) between target monitor and candidate monitors .

# 11

All the available paired data within the period limit described in the Eligibility section was used to develop a linear regression to predict target concentrations from candidate concentrations. A regression was performed for each possible pairing that met the criteria utilized for 100 data points and 20 data points per calendar quarter (across all ye ars) in the most recent 20 quarters for each candidate monitor in the NY-NJ - CT PM2.5 nonattainment area. Step 2

– Select Candidate site The NY-NJ - CT PM2.5 nonattainment area has a large number of monitors which could have been used as candidate sites. Only one candidate monitor was selected for each target monitor. The follow steps were used to select the candidate monitor. 1) Candidate monitors were placed into order of highest correlation (highest r- squared in the linear regression) with the Target. 2) Using the regression equation relating concentrations at the Target monitor and the Candidate monitor, estimates of the 24 -hour average concentrations were made at the Target monitor for all missing sche duled days in the initially incomplete quarters in the most recent three - ye ar period at the Target. Estimates were only made for days on which a concentration is available at the Candidate monitor. Estimates were not made for any days in quarters for which the Target had 75 percent or more complete data initially . The estimates were combined with any reported data at the Target in the recent 3 -ye ar period and the data capture rates were computed for each originally incomplete quarter. The computation of data capture rates required an assumption that the required sampling frequency for the Target was recorded. If the Candidate monitor had a lower sampling frequency than the Target, some missing scheduled days for the Target were not substituted for the regression-based estimates. When the Candidate monitor had a lower sampling frequency than the Target, the Target sampling schedule was assumed to be a combination of the Target and Candidate schedules, weighted by the number of originally present and originally missing scheduled days at the Target. 3) If after performing the process in #2 results in all 12 quarters at the Target having at least 75 percent of scheduled values, the Candidate monitor was selected as the Candidate for the remaining steps. I f 75 percent of the scheduled values for the Target were not obtained, the steps in #2 were repeated for the next best correlated other site. This process was repeated until the Target had 75 percent of its scheduled values. Step 3

– Design Value Compute d The three - year design value was calculated using the actual observations of the Target and the regression-based estimates of daily concentrations. The design values for both Target monitors in the NY-NJ - CT PM2.5 nonattainment area were both below the NAAQS

# 12

Step 4

– Statistical confidence of a design value below the NAAQS checked The results of Step 3 showed design values for both Target monitors in NY -NJ - CT PM2.5 nonattainment area to be below the NAAQS. In order to show that there is at most a 10 percent probability

that the actual design value (had the Target monitors operated more days) was above the NAAQS further analys is was performed as follows: (a) Residuals were calculated from the regression. (b) A bootstrap analys is was performed, repeating the regression-based substitution in Step 2 but adding to each estimated 24 -hour value that substitutes for a missing scheduled monitored value a plus or minus residual that has been randomly drawn (with replacement) from the pool of regression residuals . This step randomly applies real residuals from the linear regression to the imputed currentperiod Target values. (c) Repeat (b) for a total of 1000 runs. (d) For each of the 1000 bootstrap trials, the 3 - year design value was calculated. This will provide a pseudo confidence interval for the partially imputed current-period design value for the Target. (e) Since none of the 1000 runs resulted in a design values above the NAAQS, the Target were considered to have met the NAAQS. Determining the design value for PS 59 (AQS ID: 360610056) Steps 1 and 2 were performed with PS 59 as the Target monitor. The results of the regressions can be found in Figure 2. On Figure 2, the Target monitor is listed as Site A. All the Candidate sites that were used are listed as Site B. The monitor (AQS ID: 360610134) had the highest correlation with the Target monitor and met the operating period and paired data eligibility criteria for being a Candidate site. The results of the regression between the Target and Candidate monitor are shown in Figure 3. Estimates for the missing data for quarters 3 and 4 of 2008, and quarters 1 thru 4 of 2009 for the Target were made. These quarters were the quarters with less than 75 percent data capture. As a result of fi lling in the missing data, the Target monitor now had 30 and 28 days of data for quarters 3 and 4, respectively, for 2008, and 30, 30, 28, 31 for quarters 1 thru 4 of 2009 . A design value of 14.0 g/m 3 

# was calculated for the Target monitor when the missing data was filled in Figure 4. The statistical confidence of the design value was checked using the method outlined in Step 4. The results of the 1000 bootstrap trials provided the following results : 108 DVs of 13.9 μg/m3 

# , 578 DVs of 14.0 μg/m3 

# , 301 DVs of 14.1 μg/m3 

# , and 13 DVs of 14.2 μg/m3



# . None of the 1000 bootstrapping trials resulted in a violating DV, which provides statistical confidence that the monitor at PS 59 (AQS ID: 360610056) is attaining the annual PM2.5 NAAQS. Determining the design value for PS 19 (AQS ID: 360610128) Steps 1 and 2 were performed with PS 19 as the Target monitor. The results of the regressions can be found in Figure 5. On Figure 5, the Target monitor is listed as Site A. All the Candidate sites that were used are li sted as Site B. The highest correlating monitor was PS 59, but that did not meet the eligibility criteria because it was also missing data for the 3 rd 

# and 4 th 

# quarters of 2008. The 2 nd 

# and 4 th 

# highest

# 13

correlating monitors did not meet the stipulated minimum number of pairs needed to construct a “good” regression model. The 3 rd 

# highest correlating monitor did not meet the minimum number of pairs needed and also did not have data for the 3 rd 

# and 4 th 

# quarters of 2008. The fifth highest correlated monitor (AQS ID: 360470122) did meet all the eligibility criteria and was used to determine a design value for PS 59. The results of the regression between the Target and Candidate monitor are shown in Figure 6 Estimates were made for the missing data in 2 nd 

# , 3 rd 

# and 4 th 

# quarters of 2008, and quarter 1 of 2009 . As a result of filling in missing data, PS 19 had 28, 30 and 28 days of data for the 2 nd 

# , 3 rd 

# and 4 th 

# quarters of 2008, and 30 for quarter 1 of 2009, respectively . A design value of 12.0 μg/m3 

# was calculated for the Target monitor when the missing data was filled in Figure 7. The statistical confidence of the design value was checked using the method outlined in Step 4. The results of the 1000 bootstrap trials provided the following results : 1 DV of 11. 6 μg/m3 

# , 1 DV of 11.7, 11 DVs of 11.8 μg/m3 

# , 89 DVs of 11.9 μg/m3 

# , 365 DVs of 12.0 μg/m3 

# , 439 DVs of 12.1 μg/m3 

# , 93 DVs of 12.2 μg/m3 

# , and 1 DV of 12.3 μg/m3



# . None of the 1000 bootstrapping trials resulted in a violating DV, which provides statistical confidence that the monitor at PS 19 (AQS ID: 360610128) is attaining the annual PM2.5 NAAQS.

## Figure 2 Correlation and data capture for monitors used to determine a design value for PS 59. npairs Q1 npairs Q2 npairs Q3 npairs Q4 corr 2006 Q1 2006 Q2 2006 Q3 2006 Q4 2007 Q1 2007 Q2 2007 Q3 2007 Q4 2008 Q1 2008 Q2 2008 Q3 2008 Q4 360610056 360610056 0.0 15.5 inc-na 152 146 121 146 1.0000 100% 100% 87% 97% 100% 90% 100% 100% 100% 93% 360610056 360610134 3.4 13.2 inc-a 22 54 31 30 0.9807 10% 100% 100% 100% 61% 93% 97% 93% 360610056 360610128 2.2 14.2 inc-a 132 131 117 134 0.9761 87% 100% 94% 94% 100% 100% 94% 70% 77% 50% 360610056 360050133 8.8 11.7 inc-a 27 28 0.9661 87% 100% 100% 97% 360610056 360810124 7.8 11.3 A 136 138 99 130 0.9583 77% 95% 91% 83% 82% 95% 87% 100% 99% 98% 99% 96% 360610056 360610079 3.3 12.8 A 150 144 120 144 0.9575 100% 100% 100% 94% 100% 100% 100% 100% 97% 100% 100% 93% 360610056 360610062 3.3 14.3 inc-a 114 88 87 112 0.9569 100% 93% 90% 87% 90% 360610056 360470122 2.9 12.9 A 138 140 111 135 0.9536 93% 100% 94% 81% 97% 100% 90% 100% 81% 90% 94% 93% 360610056 360050110 5.2 12.4 A 152 146 121 145 0.9498 96% 100% 91% 93% 99% 92% 92% 99% 87% 92% 96% 100% 360610056 360050080 5.8 14.3 A 141 142 114 138 0.9486 97% 100% 87% 94% 100% 100% 97% 97% 94% 97% 97% 93% 360610056 340171003 5.1 12.9 A 148 137 112 140 0.9421 100% 100% 97% 94% 98% 97% 76% 89% 93% 88% 83% 95% 360610056 360050083 8.6 12.6 inc-a 120 118 118 144 0.9397 100% 100% 94% 94% 100% 100% 97% 97% 360610056 340130015 13.0 13.1 inc-a 135 122 114 134 0.9230 90% 97% 94% 97% 90% 80% 100% 97% 94% 87% 26% 360610056 360850055 12.5 12.4 A 141 119 113 129 0.9213 83% 90% 94% 94% 100% 93% 100% 100% 100% 70% 100% 97% 360610056 340172002 3.5 14.1 A 87 71 74 86 0.9162 87% 97% 94% 100% 100% 90% 90% 90% 100% 67% 94% 100% 360610056 340390004 15.1 13.6 A 146 131 116 141 0.9161 96% 95% 93% 92% 99% 88% 97% 93% 89% 60% 76% 99% 360610056 361191002 15.9 11.2 A 149 143 117 142 0.9150 100% 97% 100% 97% 97% 100% 90% 97% 94% 97% 100% 100% 360610056 340030003 6.4 12.2 A 141 133 118 136 0.9109 97% 100% 97% 97% 97% 90% 100% 100% 94% 83% 81% 90% 360610056 340390006 14.2 12.6 A 136 131 106 128 0.9102 87% 100% 100% 87% 90% 90% 74% 87% 97% 93% 90% 100% 360610056 340392003 19.5 12.3 A 141 122 109 138 0.9036 100% 100% 100% 97% 97% 77% 84% 93% 94% 73% 97% 100% 360610056 340270004 27.2 10.3 A 141 135 112 125 0.8972 93% 90% 84% 90% 93% 87% 100% 93% 97% 93% 74% 83% 360610056 360850067 14.0 10.9 A 142 129 108 135 0.8948 100% 87% 100% 94% 90% 100% 84% 87% 97% 90% 97% 100% 360610056 090010010 49.3 12.4 A 141 145 103 130 0.8900 93% 100% 97% 97% 97% 97% 97% 90% 87% 100% 81% 90% 360610056 340230006 31.0 11.3 A 142 129 111 139 0.8857 97% 93% 94% 97% 100% 90% 90% 90% 81% 93% 94% 97% 360610056 340310005 15.2 12.3 A 135 126 112 132 0.8784 90% 93% 97% 97% 93% 90% 94% 90% 100% 93% 90% 93% 360610056 090013005 38.1 11.8 A 133 119 115 135 0.8781 93% 83% 90% 94% 90% 93% 90% 100% 90% 97% 90% 87% 360610056 360590008 15.1 10.9 A 149 136 110 135 0.8733 100% 90% 100% 84% 97% 87% 74% 97% 100% 93% 100% 93% 360610056 090091123 66.7 12.2 A 141 133 113 141 0.8690 90% 90% 94% 100% 97% 93% 100% 100% 100% 100% 87% 100% 360610056 090092008 67.4 10.7 A 141 143 116 133 0.8681 93% 100% 100% 100% 100% 100% 100% 100% 100% 100% 87% 83% 360610056 090019003 41.2 10.6 A 140 134 104 144 0.8667 100% 70% 77% 97% 84% 100% 91% 99% 84% 100% 99% 99% 360610056 340210008 55.9 11.9 A 136 120 114 130 0.8657 70% 57% 87% 100% 99% 90% 100% 88% 97% 86% 91% 99% 360610056 090090027 66.9 11.7 A 126 136 113 114 0.8647 89% 96% 99% 98% 90% 100% 99% 97% 96% 97% 95% 100% 360610056 090090026 66.9 11.6 A 146 140 117 130 0.8645 93% 97% 97% 100% 97% 90% 97% 90% 100% 100% 97% 97% 360610056 361030002 28.7 10.5 A 88 83 56 54 0.8504 100% 100% 100% 81% 93% 97% 94% 97% 97% 97% 84% 90% 360610056 360710002 51.2 10 A 143 143 114 136 0.8414 100% 97% 81% 90% 100% 100% 90% 97% 90% 100% 97% 97% 360610056 340218001 55.8 10.1 A 142 107 106 118 0.8324 97% 100% 97% 94% 90% 57% 68% 90% 90% 50% 81% 93% 360610056 090092123 72.8 11.9 A 145 140 116 143 0.8264 93% 100% 97% 100% 100% 100% 100% 100% 97% 100% 100% 100% 360610056 090011123 52.0 12 A 140 136 109 139 0.8252 97% 97% 77% 100% 97% 100% 100% 100% 94% 97% 94% 97% 360610056 340273001 37.2 9.4 A 126 131 116 128 0.8213 100% 97% 90% 81% 74% 92% 100% 87% 81% 83% 97% 93% Site A Quarterly Data Capture, 2006-2008 20-quarter look (2003-Q3 - 2008-Q2) Site B dist

(miles) DV Site B DV status Site B

# 15 Figure 3 Regression results computed from360610056 (Target/Site A/PS 59) – 360610134 (Candidate/Site B). The linear relationship between the two monitors is: Target concentration= 0.44277 + 0.98545 * Candidate concentration. Th e correlation coefficient was 0.9807.

v_a

0 10 20 30 40

v_b 0 10 20 30 40

# 16 Figure 4. Results for PS 59 after filling in missing data for quarters 3 and 4 of 2008, and all quarters of 2009

# 17 npairs Q1 npairs Q2 npairs Q3 np airs Q4 corr 2006 Q1 2006 Q2 2006 Q3 2006 Q4 2007 Q1 2007 Q2 2007 Q3 2007 Q4 2008 Q1 2008 Q2 2008 Q3 2008 Q4 

### 360610128 360610128 14.2 inc-a 132 136 146 139 1 87% 100% 94% 94% 100% 100% 94% 70% 77% 50% 

### 360610128 360610056 15.5 inc-n a 132 131 117 134 0.976113 100% 100% 87% 97% 100% 90% 100% 100% 100% 93% 

### 360610128 360050133 11.7 inc-a 21 15 0.963585 87% 100% 100% 97% 

### 360610128 360610062 14.3 inc-a 102 88 114 114 0.959232 100% 93% 90% 87% 90% 

### 360610128 360610134 13.2 inc-a 19 44 29 21 0.958674 10% 100% 100% 100% 61% 93% 97% 93% 

### 360610128 360470122 12.9 A 119 130 133 127 0.951831 93% 100% 94% 81% 97% 100% 90% 100% 81% 90% 94% 93% 

### 360610128 360810124 11.3 A 117 128 116 124 0.950918 77% 95% 91% 83% 82% 95% 87% 100% 99% 98% 99% 96% 

### 360610128 360610079 12.8 A 131 134 145 138 0.950684 100% 100% 100% 94% 100% 100% 100% 100% 97% 100% 100% 93% 

### 360610128 360050080 14.3 A 122 133 138 131 0.947271 97% 100% 87% 94% 100% 100% 97% 97% 94% 97% 97% 93% 

### 360610128 340171003 12.9 A 128 129 135 135 0.945114 100% 100% 97% 94% 98% 97% 76% 89% 93% 88% 83% 95% 

### 360610128 360050110 12.4 A 132 136 146 138 0.942447 96% 100% 91% 93% 99% 92% 92% 99% 87% 92% 96% 100% 

### 360610128 360050083 12.6 inc-a 107 121 143 138 0.938215 100% 100% 94% 94% 100% 100% 97% 97% 

### 360610128 360850055 12.4 A 123 112 131 124 0.928428 83% 90% 94% 94% 100% 93% 100% 100% 100% 70% 100% 97% 

### 360610128 340130015 13.1 inc-a 120 111 129 125 0.918609 90% 97% 94% 97% 90% 80% 100% 97% 94% 87% 26% 

### 360610128 340390006 12.6 A 119 121 127 122 0.918115 87% 100% 100% 87% 90% 90% 74% 87% 97% 93% 90% 100% 

### 360610128 340390004 13.6 A 127 123 139 135 0.912213 96% 95% 93% 92% 99% 88% 97% 93% 89% 60% 76% 99% 

### 360610128 361191002 11.2 A 129 134 142 135 0.911511 100% 97% 100% 97% 97% 100% 90% 97% 94% 97% 100% 100% 

### 360610128 360850067 10.9 A 124 119 124 130 0.904567 100% 87% 100% 94% 90% 100% 84% 87% 97% 90% 97% 100% 

### 360610128 340392003 12.3 A 121 113 128 131 0.901542 100% 100% 100% 97% 97% 77% 84% 93% 94% 73% 97% 100% 

### 360610128 340030003 12.2 A 122 122 139 129 0.898353 97% 100% 97% 97% 97% 90% 100% 100% 94% 83% 81% 90% 

### 360610128 340172002 14.1 A 76 63 73 77 0.896528 87% 97% 94% 100% 100% 90% 90% 90% 100% 67% 94% 100% 

### 360610128 340230006 11.3 A 123 120 133 134 0.892395 97% 93% 94% 97% 100% 90% 90% 90% 81% 93% 94% 97% 

### 360610128 360590008 10.9 A 129 126 134 130 0.890902 100% 90% 100% 84% 97% 87% 74% 97% 100% 93% 100% 93% 

### 360610128 090010010 12.4 A 122 135 127 120 0. 88534 93% 100% 97% 97% 97% 97% 97% 90% 87% 100% 81% 90% 

### 360610128 090013005 11.8 A 115 109 131 128 0.882825 93% 83% 90% 94% 90% 93% 90% 100% 90% 97% 90% 87% 

### 360610128 090092008 10.7 A 123 133 139 123 0.874719 93% 100% 100% 100% 100% 100% 100% 100% 100% 100% 87% 83% 

### 360610128 090091123 12.2 A 121 123 136 134 0.874092 90% 90% 94% 100% 97% 93% 100% 100% 100% 100% 87% 100% 

### 360610128 090090026 11.6 A 126 130 135 123 0.873219 93% 97% 97% 100% 97% 90% 97% 90% 100% 100% 97% 97% 

### 360610128 340270004 10.3 A 121 125 131 117 0.872935 93% 90% 84% 90% 93% 87% 100% 93% 97% 93% 74% 83% 

### 360610128 090019003 10.6 A 120 124 127 137 0.871809 100% 70% 77% 97% 84% 100% 91% 99% 84% 100% 99% 99% 

### 360610128 340210008 11.9 A 118 110 134 124 0.868544 70% 57% 87% 100% 99% 90% 100% 88% 97% 86% 91% 99% 

### 360610128 340310005 12.3 A 117 116 133 125 0. 86366 90% 93% 97% 97% 93% 90% 94% 90% 100% 93% 90% 93% 

### 360610128 090090027 11.7 A 109 126 115 105 0.862537 89% 96% 99% 98% 90% 100% 99% 97% 96% 97% 95% 100% 

### 360610128 361030002 10.5 A 77 74 56 44 0.845237 100% 100% 100% 81% 93% 97% 94% 97% 97% 97% 84% 90% 

### 360610128 360710002 10.0 A 125 133 132 128 0.836385 100% 97% 81% 90% 100% 100% 90% 97% 90% 100% 97% 97% 

### 360610128 340218001 10.1 A 123 99 127 112 0.832777 97% 100% 97% 94% 90% 57% 68% 90% 90% 50% 81% 93% 

### 360610128 090011123 12.0 A 121 127 131 131 0.832678 97% 97% 77% 100% 97% 100% 100% 100% 94% 97% 94% 97% 

### 360610128 090092123 11.9 A 125 130 139 135 0.829176 93% 100% 97% 100% 100% 100% 100% 100% 97% 100% 100% 100% 

### 360610128 340273001 9.4 A 112 122 135 122 0.808837 100% 97% 90% 81% 74% 92% 100% 87% 81% 83% 97% 93% 

### Site A Quarterly Data Capture, 2006-2008 20-quarter look (2003-Q3 - 2008-Q2) 

### Site B DV

Site B DV status Site B



## Figure 5 Correlation and data capture for monitors used to determine a design value for PS 19.

# 18 v_a

0 10 20 30 40 50

v_b 0 10 20 30 40 50 60 

## Figure 6 Regression results computed from360610128 (Target/Site A/PS 19) – 360470122 (Candidate/Site B). The linear relationship between the two monitors is: Target concentration= 1.98081 + 0.95622 * Site B concentration. The correlation coefficient was 0.9518.

# 19

VII. Figure 7. Results for PS 19 after filling in missing data for quarters 2, 3 and 4 of 2009, and quarter 1 of 2009.

# C. Additional Analysis Additional statistical analysis was performed for PS 59 using a different candidate site. EPA re -ran the analysis using the highest correlated monitor (corr 0.9583) with PS59 (AQS ID360810124) that had complete data from 2006 - 2009. The monitoring site previously selected as site B (AQS ID 360610134) had the highest overall correlation with PS59 (corr 0.9807), but quarterly data capture was below 75 percent completeness in the first quarter of 2008. Although requiring 75 percent data completeness in all 12 quarters would go beyond the previously described eligib ility

criteria for data capture, EPA believes that it ’ s worth noting whether the area would attain the NAAQS when the correlation is made with another site with more complete, but not as well correlated data . The results of the analys is using AQS ID 360 810124 as the Candidate monitor produced a 2007 - 2009 DV of 14.6 μg/m3 

# , which is below the NAAQS of 15.0 ug/m3



# . D. Trends

Figure 8 displays the county design value trends for the years 2001 - 2009. The annual NAAQS of 15.0 ug/m3 

# is shown for reference. Appendix A displays the annual design values for each individual FRM monitors in the NY-NJ - CT PM2.5 

# nonattainment area from 1999 thru 2009.

Figure 8 illustrates the overall declining county design values across the nonattainment area. Beginning in 2006 - 2008 all county design values including New York County, which includes substituted data due to monitor shut down of the NAA design value site at PS 59, have been below the NAAQS of 15.0 ug/m 3 

# . Monitored data collected from FRM monitors (see Appendix A) have not exceeded the NAAQS of 15.0 ug/m3 

# since 05 - 07.

It should be noted that Richmond County in New York shows an increase in the county design value from 2003 - 05 to 2004 - 06. However, this is not due to an increase of PM2.5 

# concentrations at a specific monitor; but reflects that the county design monitor was changed during this time period: Site number 360850055 was the new design value site for 2004 - 06 which had a higher monitored concentration than the previous county design site for 2003 - 05 (i.e., s ite 360855067). Previously

site 360850055 had incomplete data. A review of data from both sites in Appendix A shows a mostly declining trend at both sites.

20

## An nual PM2.5 Design Values for the NY-NJ-CT PM2.5 nonattainment area

8.0 10.0 12.0 14.0 16.0 18.0

01-03 02-04 03-05 04-06 05-07 06-08 07-09 3-Yr Design ValuesConcentration (ug/m3)



### Bronx Kings Nassau New York Orange Queens Richmond Suffolk We stchester Bergen Essex Hudson Mercer Middlesex Morris Passaic Union Fairfield New Haven NAAQS = 15.0



## Figure 8 Design value trends for counties in the NY-NJ- C T PM2.5 nonattainment area for the years 2001 -2009.

# VIII. CONCLUSION EPA is proposing to determine that the NY-NJ - CT PM 2.5 

# nonattainment area for the 1997 annual PM2.5 

# NAAQS has attained the 1997 PM2.5 

# NAAQS and continues to attain the standard based on data through 2009.

EPA has reviewed the ambient air monitoring data for PM2.5 

# , consistent with the requirements contained in 40 CFR part 50 and recorded in the EPA Air Quality System database for the NY -NJ - CT PM2.5 

# nonattainment area. The 3 -ye ar average s of the annual mean PM2.5 

# concentrations continue to be below the NAAQS of 15.0 ug/m3



# .

EPA has concluded that less than complete data from the PS 59 monitoring site is warranted for determining attainment of the NAAQS. The States of New York, New Jers ey, and Connecticut have been very diligent in the number and placement of PM2.5 

# monitors in the nonattainment area . The monitor at PS 59 was shutdown due to a planned building demolition, and could not be replaced. An EPA procedure using a statistical method to estimate concentrations at the design value site at PS 59, if the monitor continued to operate, demonstrated attainment of the NAAQS.

As provided in 40 CFR 51.1004(c), if EPA finalizes this determination, it would suspend the requirements for this area to submit attainment demonstrations , reasonably available control measures, reasonable further progress plans, and contingency measures related to attainment of the 1997 annual PM2.5 

# NAAQS so long as the area continues to attain the 1997 annual PM2 .5 

# NAAQS.

22

# 23 Appendix A Annual Means for NY-NJ- CT PM2.5 

# FRM monitorsConnecticut Fairfield New York-N. New Jersey-Long Island, NY- 1 090010010 13.6 A 13.5 A 13.1 A 12.7 A 13.3 A 13.2 A 13.2 A 12.4 A 11.3 A yes Connecticut Fairfield New York-N. New Jersey-Long Island, NY- 1 090010113 12.3 inc-a 12.5 inc-a 12.7 A 12.6 inc-a 12.3 inc-a yes Connecticut Fairfield New York-N. New Jersey-Long Island, NY- 1 090011123 12.8 inc-a 12.8 A 13.0 A 12.3 A 12.6 A 12.3 A 12.6 A 12.0 A 11.0 A yes Connecticut Fairfield New York-N. New Jersey-Long Island, NY- 1 090012124 12.4 inc-a 12.9 A 13.1 A 12.7 A 12.6 inc-a 11.8 inc-a yes Connecticut Fairfield New York-N. New Jersey-Long Island, NY- 1 090013005 13.0 inc-a 12.9 inc-a 13.0 A 12.5 A 12.7 A 12.3 A 12.3 A 11.8 A 11.1 A yes Connecticut Fairfield New York-N. New Jersey-Long Island, NY- 1 090019003 12.9 inc-a 12.2 inc-a 11.8 inc-a 11.4 A 11.7 A 11.4 A 11.3 A 10.6 A 10.0 A yes Connecticut New Haven New York-N. New Jersey-Long Island, NY- 1 090090026 11.9 inc-a 11.7 inc-a 12.2 inc-a 12.1 A 12.1 A 11.6 A 10.8 A yes Connecticut New Haven New York-N. New Jersey-Long Island, NY- 1 090090027 12.2 inc-a 12.8 inc-a 12.6 A 12.3 A 11.7 A 10.8 A Connecticut New Haven New York-N. New Jersey-Long Island, NY- 1 090091123 14.1 A 13.9 A 13.9 A 13.4 A 13.5 A 13.0 A 12.8 A 12.2 A 11.4 A yes Connecticut New Haven New York-N. New Jersey-Long Island, NY- 1 090092008 11.9 inc-a 11.5 inc-a 11.6 inc-a 11.2 A 11.1 A 10.7 A 9.9 A yes Connecticut New Haven New York-N. New Jersey-Long Island, NY- 1 090092123 13.6 A 13.6 A 13.2 A 12.6 A 12.9 A 12.7 A 12.6 A 11.9 A 11.0 A yes Connecticut New Haven New York-N. New Jersey-Long Island, NY- 1 090098003 12.9 inc-a 12.8 inc-a 12.8 inc-a 12.8 inc-a yes Connecticut New Haven New York-N. New Jersey-Long Island, NY- 1 090099005 11.6 inc-a 11.5 A 11.8 A 11.7 inc-a 12.3 inc-a yes New Jersey Bergen New York-N. New Jersey-Long Island, NY- 2 340030003 14.3 inc-a 14.0 inc-a 13.6 inc-a 12.8 A 13.3 A 12.8 A 13.2 A 12.2 A 11.3 A yes New Jersey Bergen New York-N. New Jersey-Long Island, NY- 2 340030007 19.1 inc-na 15.8 inc-na 15.8 inc-na yes New Jersey Bergen New York-N. New Jersey-Long Island, NY- 2 340030008 18.5 inc-na 15.3 inc-na 15.3 inc-na yes New Jersey Bergen New York-N. New Jersey-Long Island, NY- 2 340030009 18.8 inc-na 15.5 inc-na 15.5 inc-na yes New Jersey Essex New York-N. New Jersey-Long Island, NY- 2 340130003 8.3 inc-a yes New Jersey Essex New York-N. New Jersey-Long Island, NY- 2 340130011 16.1 inc-na yes New Jersey Essex New York-N. New Jersey-Long Island, NY- 2 340130015 15.0 inc-a 14.1 inc-a 13.6 inc-a 13.5 A 13.9 inc-a 13.2 A 13.3 A 13.1 inc-a 13.5 inc-a yes New Jersey Essex New York-N. New Jersey-Long Island, NY- 2 340130016 15.2 inc-na 14.7 inc-a 14.3 inc-a 13.9 inc-a 13.5 inc-a New Jersey Hudson New York-N. New Jersey-Long Island, NY- 2 340171003 15.9 NA 15.3 NA 14.7 A 14.3 A 14.7 A 14.1 A 14.0 A 12.9 A 11.9 A New Jersey Hudson New York-N. New Jersey-Long Island, NY- 2 340172002 17.5 NA 16.6 inc-na 16.3 inc-na 16.8 inc-na 17.4 inc-na 15.7 inc-na 15.4 inc-na 14.1 A 13.1 A New Jersey Mercer New York-N. New Jersey-Long Island, NY- 2 340210008 14.3 A 14.2 A 13.8 A 13.0 A 13.0 A 12.7 A 12.5 A 11.9 A 10.8 A yes New Jersey Mercer New York-N. New Jersey-Long Island, NY- 2 340218001 11.8 inc-a 11.9 inc-a 11.9 inc-a 11.5 A 11.7 A 11.0 A 10.8 A 10.1 A 9.4 A yes New Jersey Middlesex New York-N. New Jersey-Long Island, NY- 2 340230006 12.6 inc-a 12.5 A 12.4 A 11.8 A 12.5 A 11.8 A 12.1 A 11.3 A 10.4 A yes New Jersey Morris New York-N. New Jersey-Long Island, NY- 2 340270004 13.7 inc-a 12.6 inc-a 12.4 inc-a 11.6 A 11.9 A 11.2 A 11.3 A 10.3 A 9.6 A yes New Jersey Morris New York-N. New Jersey-Long Island, NY- 2 340273001 11.2 inc-a 11.1 inc-a 11.0 inc-a 10.5 A 10.6 A 10.0 A 10.1 A 9.4 A 8.8 A yes New Jersey Passaic New York-N. New Jersey-Long Island, NY- 2 340310005 13.0 inc-a 13.2 inc-a 13.1 inc-a 12.9 A 13.1 A 12.6 A 12.9 A 12.3 A 11.3 A yes New Jersey Union New York-N. New Jersey-Long Island, NY- 2 340390004 16.3 NA 15.8 NA 15.5 NA 15.3 NA 15.5 NA 14.8 A 14.4 A 13.6 A 12.6 A New Jersey Union New York-N. New Jersey-Long Island, NY- 2 340390006 14.5 inc-a 13.9 inc-a 13.5 inc-a 13.2 A 13.6 A 13.1 A 13.3 A 12.6 A 11.6 A yes New Jersey Union New York-N. New Jersey-Long Island, NY- 2 340392003 14.1 inc-a 13.1 A 12.8 A 12.8 A 13.3 A 12.9 A 13.0 A 12.3 A 11.5 A yes New York Bronx New York-N. New Jersey-Long Island, NY- 2 360050073 21.7 inc-na New York Bronx New York-N. New Jersey-Long Island, NY- 2 360050080 16.4 inc-na 16.0 NA 15.7 NA 15.2 NA 15.7 NA 15.1 NA 15.5 NA 14.3 A 13.9 A yes New York Bronx New York-N. New Jersey-Long Island, NY- 2 360050083 14.3 inc-a 14.1 A 13.7 A 13.2 A 13.4 A 12.9 A 13.0 A 12.6 inc-a 13.2 inc-a yes New York Bronx New York-N. New Jersey-Long Island, NY- 2 360050110 14.5 inc-a 14.8 inc-a 14.7 inc-a 14.3 A 14.1 A 13.3 A 13.0 A 12.4 A 11.8 A yes New York Bronx New York-N. New Jersey-Long Island, NY- 2 360050133 11.7 inc-a 10.8 inc-a yes New York Kings New York-N. New Jersey-Long Island, NY- 2 360470011 16.0 inc-na 16.2 inc-na New York Kings New York-N. New Jersey-Long Island, NY- 2 360470052 16.3 inc-na 15.5 inc-na 14.3 inc-a 13.4 inc-a 12.9 inc-a yes New York Kings New York-N. New Jersey-Long Island, NY- 2 360470076 14.4 inc-a 14.4 A 14.2 inc-a 13.7 inc-a 14.2 inc-a yes New York Kings New York-N. New Jersey-Long Island, NY- 2 360470122 15.3 inc-na 14.7 inc-a 14.7 A 14.2 A 14.6 A 14.0 A 14.0 A 12.9 A 12.2 A yes New York Nassau New York-N. New Jersey-Long Island, NY- 2 360590005 13.5 inc-a New York Nassau New York-N. New Jersey-Long Island, NY- 2 360590008 12.2 inc-a 12.1 A 12.2 A 11.7 A 12.1 A 11.5 A 11.4 A 10.9 A 10.3 A yes New York Nassau New York-N. New Jersey-Long Island, NY- 2 360590011 14.7 inc-a 15.3 inc-na New York Nassau New York-N. New Jersey-Long Island, NY- 2 360590012 12.5 inc-a 12.1 inc-a 11.4 inc-a 11.0 inc-a 10.7 inc-a yes New York Nassau New York-N. New Jersey-Long Island, NY- 2 360590013 12.4 inc-a 12.0 inc-a 11.5 inc-a 11.1 inc-a 10.9 inc-a yes New York New York New York-N. New Jersey-Long Island, NY- 2 360610010 16.7 inc-na 17.0 inc-na 17.1 inc-na yes New York New York New York-N. New Jersey-Long Island, NY- 2 360610056 17.8 NA 17.5 NA 17.5 NA 16.7 NA 17.0 NA 15.7 NA 15.9 NA 15.5 inc-na 16.0 inc-na yes New York New York New York-N. New Jersey-Long Island, NY- 2 360610062 17.1 NA 16.8 NA 16.2 NA 15.2 NA 15.3 NA 14.3 A 14.8 inc-a 14.3 inc-a 15.8 inc-na yes New York New York New York-N. New Jersey-Long Island, NY- 2 360610079 15.4 inc-na 15.0 A 14.6 A 13.9 A 14.0 A 13.3 A 13.5 A 12.8 A 12.1 A yes New York New York New York-N. New Jersey-Long Island, NY- 2 360610128 14.8 inc-a 15.2 inc-na 15.5 inc-na 15.6 NA 15.8 NA 15.1 NA 15.3 NA 14.2 inc-a 13.5 inc-a yes New York New York New York-N. New Jersey-Long Island, NY- 2 360610134 13.3 inc-a 13.2 inc-a 12.7 inc-a yes New York Orange New York-N. New Jersey-Long Island, NY- 2 360710002 11.7 inc-a 11.5 A 11.5 A 11.1 A 11.4 A 10.8 A 10.8 A 10.0 A 9.3 A yes New York Queens New York-N. New Jersey-Long Island, NY- 2 360810094 13.2 inc-a 13.7 inc-a 13.5 inc-a 13.3 inc-a yes New York Queens New York-N. New Jersey-Long Island, NY- 2 360810096 13.9 inc-a 13.7 inc-a 13.2 inc-a 12.7 inc-a 12.4 inc-a yes New York Queens New York-N. New Jersey-Long Island, NY- 2 360810097 13.3 inc-a 13.1 inc-a New York Queens New York-N. New Jersey-Long Island, NY- 2 360810124 14.2 inc-a 13.5 inc-a 13.5 inc-a 12.8 A 12.7 A 12.1 A 11.8 A 11.3 A 10.6 A yes New York Richmond New York-N. New Jersey-Long Island, NY- 2 360850055 13.6 inc-a 14.2 A 13.8 inc-a 13.4 inc-a 13.7 inc-a 13.4 A 13.2 A 12.4 A 11.6 A yes New York Richmond New York-N. New Jersey-Long Island, NY- 2 360850067 12.6 inc-a 12.3 A 12.0 A 11.5 A 11.8 A 11.5 A 11.5 A 10.9 A 10.2 A yes New York Suffolk New York-N. New Jersey-Long Island, NY- 2 361030001 12.9 inc-a 12.4 A 12.1 A 11.3 A 11.5 A 11.3 inc-a 12.0 inc-a yes New York Suffolk New York-N. New Jersey-Long Island, NY- 2 361030002 10.4 inc-a 10.6 inc-a 10.5 A 9.7 A yes New York Westchester New York-N. New Jersey-Long Island, NY- 2 361191002 12.8 inc-a 12.5 inc-a 12.3 A 11.7 A 11.9 A 11.6 A 11.7 A 11.2 A 10.6 A yes 2007-2009 2006-2008 2005-2007 2004-2006 2003-2005 2002-2004 2001-2003 2000-2002 pop_orient ed site annual_std_naa_name epa_re gion 1999-2001 Annual Design Values state_name county_name

# 26 Appendix B Network Review Letters

# 27

# 28

# 29

# 30

# 31

# 32

# 33

# 34

# 35

# 36

# 37

# 38

# 39

# 40

# 41