# UNITED STATES ENVIRONMEN TAL PROTECTION AGENCY

REGION II AIR PROGRAMS BRANCH

Technical Support Document

EPA’s Notice of Proposed Rulemaking

For

Approval and Promulgation of Air Quality Plan s; Determination of Attainment of the

2006 24-hour Fine Particle Standard

June 2012

# 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. MONITORING SITES WITH INCOMPLETE DATA ...........................................9

A. Newark-Willis Center: AQS ID 340130015.....................................................9

B. Elizabeth Lab: AQS ID 240390004...............................................................9

C. PS 59: AQS ID 360610056.........................................................................9

D. Canal Street: AQS ID 360610062...............................................................10

E. PS 19: AQS ID 360610128.......................................................................10

V. EPA’S ANALYSIS OF MONITORING SITES WITH INCOMPLETE DATA.............10

A. Analysis of Air Quality Data.....................................................................10

B. Addressing Missing Data..........................................................................11

C. Results of Regression Analysis....................................................................14

VI. ADDITIONAL INFORMATION SUMBITTED BY THE STATES...........................29

VII. CONCLUSION.........................................................................................29

APPENDIX A 24-Hour Means for NY-NJ-CT PM 2.5 

# FRM monitors ...................................30

APPENDIX B Design Value Trends..........................................................................34

APPENDIX C Network Review Letters......................................................................38

I. INTRODUCTION

In this technical support document, EPA provides information supporting our proposed

determination that the New York-N. New Jers ey-Long Island, NY-NJ-CT fine particle (PM 2.5 

# )

nonattainment area has attained th e 2006 24-hour fine particle (PM 2.5 

# ) National Ambient Air Quality

Standard (NAAQS).

In this technical support document, EPA:

2

# 3 - summarizes the statutory a nd policy requirements for PM 2.5 

# nonattainment area SIPs and

EPA’s policy concerning clean data;

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

nonattainment area

- describes the Newark-Willis Center monitoring site, and provides an explanation for

incomplete data;

- describes the Elizabeth Lab monitoring site, and provides an explanation for incomplete data;

- describes the PS 59 monitoring site, and provi des an explanation for incomplete data;

- describes the Canal Street monitoring site, a nd provides an explanation for incomplete data;

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

- describes our detailed analysis of our proposed clean data determination, including our

analysis of the air quality data, and the met hodology used for substituting for missing data;

- describes air quality trends in the NY-NJ -CT fine particle nonattainment area

- summary of our conclusions on the clean da ta determination with respect to EPA

requirements.

II. CLEAN AIR ACT REQUIREMENTS FOR FINE PARTICLE (PM 2.5 

# ) ATTAINMENT

A. PM 2.5 

# Attainment Requirements

On October 17, 2006, (71 FR 61144), EPA established a 24-hour PM 2.5 

# NAAQS at 35.0

micrograms per cubic meter (μg/m 3 

# ) and retained the annual PM 2.5 

# NAAQS at 15.0 μg/m 3 

# . EPA

established these standards based on significant evid ence and numerous health studies demonstrating

that serious health effects are associated with exposures to particulate matter.

On November 13, 2009, (74 FR 58688), EPA publishe d its air quality designations for the 2006

24-hour PM 2.5 

# NAAQS based upon air quality monitoring data for calendar years 2006-2008. These

designations became effective on December 14, 2009. The NY-NJ-CT PM 2.5 

# area was designated as

nonattainment for the 2006 24-hour PM 2.5 

# NAAQS.

These designations triggered the Clean Air Act’ s (CAA) requirements under section 172(c), which

requires the submission of an attainment plan for each designated nonattainment area. The CAA

specifies that for nonattainment areas states must s ubmit attainment plans that demonstrate that the area

will attain the NAAQS “as expeditiously as practicable” but no later than five years from effective date

of the designation, by no later than three years from the effective date of designation, that is, by

December 14, 2012. EPA’s Implementation Guidance for the 2006 24-Hour PM 2.5 

# NAAQS 1 

# , which

follows the framework established by the PM 2.5 

# implementation rule published on April 25, 2007 (72

Fed. Reg. 20586), outlines the SIP requirements for the attainment plan, which includes among other

things, the submission of an attainment demonstrati on showing the air quality improvements expected to

result from national and local control measures, an analysis of reasonably av ailable control measures

1 

## Memorandum of March 2, 2012, from Steve Page, Director, EPA Office of Air Quality Planning and Standards to EPA Air

Division Directors, with the subject line of: “Implement ation Guidance for the 2006 24-Hour Fine Particle (PM 2.5 

## ) National

Ambient Air Quality Standards (NAAQS)” This document is available at:

http://www.epa.gov/ttn/naaqs/pm/pm25_guide.html

# 4 (RACM), including all reasonably available contro l technology (RACT), reas onable further progress

plan, and contingency measures.

The States of New York, New Jersey, and Connec ticut, are subject to th ese requirements since

several counties in each State are located in a PM 2.5 

# nonattainment area. The NY-NJ-CT PM 2.5 

# nonattainment area is comprised of the following por tions of New York, New Je rsey, and Connecticut:

the New York portion (40 CFR 81.333) contains th e counties of the Bronx, Kings, Nassau, New York,

Orange, Queens, Richmond, Rockland, Suffolk, and Westchester. The New Jersey portion (40 CFR

81.331) of the NY-NJ-CT PM 2.5 

# nonattainment area contains the c ounties of Bergen, Essex, Hudson,

Mercer, Middlesex, Monmouth, Morr is, Passaic, Somerset, and Uni on. The Connecticut portion (40

CFR 81.307) of the nonattainment area includes the counties of Fair field and New Haven.

B. Determining Attainment and EPA’s Clean Data Policy

Compliance with the 24-hour primary and secondary PM 2.5 

# standards is determined for a

monitoring site by rank-ordering all the 24-hour monitor samples taken ov er the course of a year and

selecting the 98 th 

# percentile value. This would be the 3 rd 

# highest value if there are up to 120 samples

recorded during the year. The desi gn value for a monitori ng site is then calcul ated by averaging the 98 th



# percentile value for each of three consecutive year s. The standard is met when the design value

calculated in this manner is less than or equal to 35 μg/m 3



# .

Data handling conventions and computations ne cessary for determining whether areas have met

the PM 2.5 

# NAAQS, including requirements for data comp leteness, are listed in Appendix N of 40 CFR

Part 50. A year meets data completeness requirem ents 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/relocation, monitoring

diligence, and nearby concentrations in determining whether to use such data.

EPA issued a “Clean Data” policy in Decembe r 2004 describing possible reduced regulatory

requirements for areas that attain the standards, but have not yet been designated as attainment. 2 

# In

EPA’s PM 2.5 

# implementation rule, published on April 25, 2007 (72 Fed. Reg. 20586), EPA finalized in

section 51.1004(c) of the te xt the statutory interpretation that was embodied in the policy. The 2006 24-

hour PM 2.5 

# NAAQS implementation guidance reaffirms an d continues the use of this policy.

As described in EPA’s clean data policy, upon a determination by EPA that an area designated

nonattainment for the PM 2.5 

# NAAQS has attained the standard, the requirements for such area to submit

attainment demonstrations, reasonabl y available control measures, reas onable further progress plans,

contingency measures, and ot her planning SIPs related to attainment of the PM 2.5 

# NAAQS shall be

suspended until such time as: the area is redesignat ed to attainment, at which time the requirements no

longer apply; or EPA determines that the area has violated the PM 2.5 

# 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,

2 

## Memorandum of December 14, 2 004, from Steve Page, Director , EPA Office of Air Quality Pl anning and Standards to EPA

Air Division Directors, “Clean Data Policy for the Fine Par ticle National Ambient Air Quality Standards.” This document is

available at: http://www.epa.gov/pmdesignations/1997standards/guidance.htm

# 5 and provisions to address pollution transport, whic h would require emission re ductions at sources or

other types of emission activities co ntributing significantly to nonattainment in other areas or states, or

interfering with maintenance in those areas.

Determinations as to whether indi vidual areas have attained the PM 2.5 

# standard and thus qualify

for application of the clean data policy are being made in the context of rulemakings for individual

areas. This Technical Support Docu ment (TSD) provides EPA’s analysis used in determining whether

the NY-NJ-CT 24-Hour PM 2.5 

# nonattainment area has achieved clean data.

III. MONITORING NETWORK

With the promulgation of the annual and daily PM 2.5 

# 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 PM 2.5 

# nonattainment area beginning in 1998/1999.

Only FRM data is used for determining complian ce with the health based standards. The states

also complement their FRM network w ith real-time direct reading hourly PM 2.5 

# measurements. Realtime monitors are used primarily in support of the Air Quality Index ( AQI), which provides immediate

information to the public about air qual ity and its relationship to public health 3



# .

The PM 2.5 

# FRM is a filter based method whereby a samp le is collected for a specified period of

time (e.g., 24 hours) on filters that are weighed be fore 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

PM 2.5 

# nonattainment area operate on a 1-in-3-day sc hedule, although a few monitors operate on a daily

basis. Also, as per network design requirements, several FRM sites ha ve collocated duplicate samplers.

The NY-NJ-CT PM 2.5 

# nonattainment area had 42 air quality monitors in 2009. This far exceeds

the minimum regulatory requirements: 40 CFR part 58, Appendix D requires three monitoring locations

for the NY Metropolitan Statisti cal 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 design values for the years 20 01-2010 (i.e., design value for a monitoring site is

calculated by averaging the 98 th 

# percentile value of 24-hour values for each of three consecutive years) for the

counties in the NY-NJ-CT PM 2.5 

# nonattainment area. The 24-hour design values for all FRM monitors in the

three States located within the NY-NJ-CT PM 2.5 

# nonattainment area since 2001 can be found in Appendix A.

3 

## Section 319 of the CAA requires EPA to establish a unifor m 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 da ily analysis and reporting of air quality based upon such

uniform air quality index”

# 6 As shown in Table 1, none of the design values for the periods of 2007-2009 and 2008-2010 in the NY-NJ-CT

PM 2.5 

# nonattainment area exceed the 2006 24-hour PM 2.5 

# NAAQS of 35.0 μg/m 3



# .

A map showing the locations of all FRM monitoring lo cations in the nonattainment area is shown in

Figure 1.

# 7 Table 1 .--Design Values 4 

## by County for the 2006 24-hour PM 2.5 

## NAAQS for the NY-NJ-CT monitors in micrograms per

cubic meter (ug/m 3 

## ). The standard for the 2006 24-hour PM 2.5 

## NAAQS is 35.0 μg/m 3



## .

County 01-03 DV 02-04 DV 03-05 DV 04-06 DV 05-07 DV 06-08 DV 07-09 DV 08-10 DV 2011 5

N Y

Bronx 40 40 40 39 38 36 33 29 27

Kings 37 38 38 37 36 34 30 27 24

Nassau 6 34 34 35 33 INC INC INC 25 23

New York 7 42 42 42 41 39 37 33 8 31 8 27

Orange 30 30 29 28 29 28 26 24 21

Queens 38 37 36 INC INC 32 30 28 25

Richmond 39 39 37 34 34 30 29 26 24

Rockland NM NM NM NM NM NM NM NM NM

Suffolk 36 35 35 INC INC 29 26 25 22

Westchester 34 34 34 34 33 32 29 28 23

N J

Bergen 36 35 37 37 38 35 31 28 24

Essex 9 37 38 38 38 38 INC 30 8

26 8 24

Hudson 40 40 41 39 41 38 32 29 26

Mercer 37 37 36 34 34 33 29 27 28

Middlesex 36 36 38 34 32 31 27 23 21

4 

## PM 2.5 

## Design Values can be found at: http ://www.epa.gov/airtrends/values.html

5 

## 2011 data reported is the 98 th 

## percentile concentration from complete and quality assured data for the highest reading

monitor in the county for 2011.

6 

## The monitor located in Nassau County had incomplete data for 2007 which lead to the inability to calculate design values

for the periods of 2005-2007, 2006-2008, and 2007-2008. The monitor did not show previous violations and therefore it was

deemed that determining the design values though alternative procedures was not necessary. The 2008-2010 design value

was 25 μg/m3.

7 

## The monitor in New York County located at Public School 59 was the highest reading monitor at the time EPA made

designations for the 2006 24-hour PM 2.5 

## NAAQ. Midway through 2008, the monitor at PS 59 was shut down due to the

demolition of the building site. Missing 2008 data had an effect on calculating the design value for the 24-hour standard.

EPA used an alternative procedure to determine the design va lue for the 24-hour standard. A description of the alternate

procedure can be found in Section V.

8 

## Design Value was calculated using the alternative procedure described in Section V of the Technical Support Document.

9 

## 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. PM 2.5 

## monitoring was established at

the firehouse on May 13, 2009. EPA used an alternative proce dure to determine the design value for the 24-hour standard. A

description of the alternate proce dure can be found in Section V.Monmouth NM NM NM NM NM NM NM NM NM

Morris 38 35 34 31 32 29 26 23 24

Passaic 37 36 37 35 37 33 30 INC 25

Somerset NM NM NM NM NM NM NM NM NM

Union 41 41 41 41 39 36 32 8 30 33

C T

Fairfield 38 36 37 36 35 33 31 28 29

New Haven 40 39 40 38 36 34 31 29 28

NM- No monitor located in county

INC- Incomplete data for time period. All counties listed as INC for time period did not meet 75 percent data completeness req uirement



## Figure 1: PM 2.5 

## FRM monitor locations in the NY-NJ-CT PM 2.5 

## nonattainment area



# 8

# 9 The States of New York, New Jersey, and Connecticut have been very dili gent 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 year so that issues can be addressed as they show up. EPA regulations

require states to submit annual network plans to thei r respective Regions. These plans outline the current

networks and any proposed changes in the upcoming 18 mo nths. Regions 1 and 2 have always been able to

approve these plans due to the high quality of th e New York, New Jersey, and Connecticut monitoring

networks. Copies of the approve d annual network review letters can be found in the Appendix C.

IV. MONITORING SITES WI TH INCOMPLETE DATA

The following monitoring sites had incomplete monitoring data during 2006-2008, 2007-2009, and/or

2008-2010, had previously violated the 2006 annual PM 2.5 

# NAAQS, and did not have clean data

subsequent to their latest viola tion. EPA determined that the reas ons behind incomplete quarters were

valid and eligible for the data subst itution method presented in Section V.

A. NEWARK-WILLIS CENTER: AQS ID 340130015

The air monitor at the Newark Willis Center station is located in Newark, Essex County, NJ.

The monitor was discontinued on July 24, 2008 due to an unexpected loss of access. Since there was no

monitoring at this site for approxima tely half of 2008 to the present, de sign values were incomplete that

involve 2008 or later years (2006-2008, 2007-2009, and 2008-2010).

A new monitor at the Newark Firehouse was esta blished to replace the monitor at the NewarkWillis Center on May 13, 2009. The discontinuation and replacement of the monitor at the Newark

Willis Center was approved by EPA.

B. ELIZABETH LAB: AQS ID 340390004

The air monitor located in Elizabeth, Union C ounty, NJ is a long standing monitor that was

established in 1970. This monitor had incomplete data capture for 2 nd 

# quarter 2008 and very low data

capture for 3 rd 

# quarter 2008. The less than adequate data capture for 2008 and violating design value for

2007-2009 were the reasons behind EPA performing additi onal analysis to determine if the monitor met

the 2006 24-hour PM 2.5 

# NAAQS. EPA has not found any anomalies with the missing data and

approves of using data substitution for calculating a 2007-2009 design value.

C. PS 59 MONITORING SITE: AQS ID: 360610056

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

# nonattainment area was located on the roof of public

School 59 in New York County. The PS 59 monitor wa s the highest reading monitor at the time EPA

made designations for the 2006 PM 2.5 

# NAAQS on November 13, 2009.

The monitor began operating in 1999 and operated reliab ly with the exception of the third quarter of

2003. The monitor shut down due to roof repairs at PS 59. Ambient monitoring was resumed at this site

in October 2003.

# 10 The site operated until mid 2008, when monitoring was discontinued permanently 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 l ong as possible to collect

data. Unfortunately, the monitor at this location c ould not be replaced becau se the roof of the new

building did not meet the criteria of a valid mon itoring 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.

D. CANAL STREET: AQS ID 360610062

The Canal Street monitoring site started up in August of 1999. It was shut down in March 2007

due to a hotel next door purchasing the rights to the roof of the bu ilding. The state had notified EPA

well in advance of this happening, th us making this a planned shutdown.

E. PS 19 MONITORING SITE: AQS ID 360610128

The monitor located at Public School 19 ha d incomplete design values for 2006-2008, 2007-

2009, and 2008-2010. The monitor began operation in October 2001. The monitor had two periods of

time where complete data was not recorded: 2 nd 

# thru 4 th 

# quarters of 2008, and the 1 st 

# quarter of 2009 due

to roof repair issues. Ambient monitoring was re sumed at this site in March 2009. EPA has not found

any anomalies with the missing data and approves of using data substitution for calculating 2007-2009

and 2008-2010 design values.

V. EPA’S ANALYSIS OF MONITORING SITES WITH INCOMPLETE DATA

A. Analysis of Air Quality Data

EPA has reviewed the ambient air monitoring data for PM 2.5 

# , consistent with the requirements

contained in 40 CFR part 50 and recorded in the EPA Air Quality System database for the NY-NJ-CT

PM 2.5 

# nonattainment area from 2001 through the present time. Currently all ope rating monitors are

meeting the 24-hour standard of 35.0 μg/m 3 

# . All complete 24-hour PM 2.5 

# 3-year average concentrations

have been below the NAAQS since 2007-2009. Appendix A shows the 24-hour design values for

monitors in the NY-NJ-CT PM 2.5 

# nonattainment area. There has been a declining trend in 3-year

averages for monitors with complete data since 2001. Appendix B contains graphs which show the

downward trend of 24-hour PM 2.5 

# averages in the NY-NJ-CT PM 2.5 

# nonattainment area. Certified,

complete, and quality assured data for 2011 continues to show th e declining trend.

Five sites (discussed in Section IV) in the NY-NJ-CT PM 2.5 

# nonattainment area had previously

shown violations of the 24-hour PM 2.5 

# NAAQS and have not posted valid attaining design values due to

incomplete data since EPA finalized its air qual ity designations on November 13, 2009. In order to

determine whether the NAAQS has been attained for sites with incomplete data, EPA has developed a

procedure to address the missing da ta, and determine valid design values for those sites for the 24-hour

PM 2.5 

# standard for 2007-2009 and 2008-2010. EPA had previ ously used this procedure to determine

attainment for the annual PM 2.5 

# NAAQS for the NY-NJ-CT PM 2.5 

# nonattainment area. See 75 FR

45076, 75 FR 45079 and 75 FR 69589 for informa tion regarding the annual NY-NJ-CT PM 2.5

# 11 nonattainment area.

EPA examined the two most recen t 3-year time periods for the five monitors that had previously

violated the 24-hour PM 2.5 

# NAAQS and had not posted attaining de sign values. The two most recent

periods helped demonstrate th e declining trend of 24-hour PM 2.5 

# in the NY-NJ-CT PM 2.5 

# nonattainment

area. Certified, complete, and quality assured data for 2011 continues to show the declining trend.

B. Addressing Missing Data

An objective statistical method was used to determine if previously violating monitors in the NY-NJCT PM 2.5 

# nonattainment area that lack complete data w ould have met the NAAQS in subsequent time

periods.

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 relations hip between the target

monitor and another monitor in the n onattainment area (candidate). Th e linear regression would then be

used to fill in the missing data for the target mo nitor. The results are checked with an additional

statistical technique, known as bootst rapping, to verify if the conclusi on of attainment is correct. The

NY-NJ-CT PM 2.5 

# nonattainment area has 42 monitoring locati ons which provide an ample number of

monitors to compare to the target monitor.

The five previously violating monitors in the NY-NJ-CT PM 2.5 

# nonattainment area that the statistical

method was used on were in New Jersey: Newark-Willis Center and Elizabeth Lab; and in New York:

PS 59, Canal Street and PS 19. EPA found that all of these monitors had valid reasons for having

incomplete data during the time periods used in this analysis. Descriptions of these monitors can be

found in Section IV.

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 PM 2.5 

# nonattainment area which has more complete data in the

period in which the target site is data deficient. The linear regression rela tionship would be based on

time periods in which both the ta rget and candidate monitors were operating. The linear regression

equation developed from the relationship between the target and candidate monitors was used to fill in

missing data for the target site in any quarter in the most recent thre e-year period that did not have 75

percent completeness based on actual observations, so that the normal da ta 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. Th e additional statis tical 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 24-hour NAAQS for PM 2.5



# .

# 12 Eligibility

Eligibility criteria was es tablished in order to assure that the method used to determine design

values for the target monitors in the NY-NJ-CT PM 2.5 

# nonattainment area were robust enough to allow

consideration of the results in a weight of evid ence decision. EPA has not es tablished bri ght lines or

specific requirements for determining design values fo r sites with less than complete data using this

method. EPA has determined that this method is a pplicable to this specif ic situation due to the

robustness of the monitoring network, historical dilig ence in operation of monitors, and valid reasons for

incomplete data.

Operating period

Candidate monitors would have operated dur ing the 3-year period (2007-2009 and/or 2008-

2010) in the NY-NJ-CT PM 2.5 

# nonattainment area in which the target monitor has incomplete data in

order to establish a significant relationship between the monitors. Candidate monitors do not necessarily

have to have complete data in all 12 quarters of the 3-year 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 of the respective 3-

year period.

Paired samples

Pairs of sample data for target monitors and candidate monitors from the 2007-2009 and/or

2008-2010 periods of operation of the ta rget monitors were used. The “p eriod of operation” of the target

monitors was based on the date of th e last reported sample from the monitor. Candidate monitors had at

least 100 historical sample pairs in common with target monitors duri ng this period. When there were

more than 100 pairs in the 5-year period all available pairs were used. In addition to the 100 pairs over

the 5-year period, 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 5-year period).

Several candidate sites met the e ligibility 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

The following are the steps used in determining desi gn values for incomplete periods for the NewarkWillis Center, Elizabeth Lab, PS 59, Canal Stre et and PS 19 monitors in the NY-NJ-CT PM 2.5 

# nonattainment area. The analysis was performed for each monitor twice, once for the 2007-2009 period

and once for the 2008-2010 period (except for Elizabet h Lab which had a complete DV for that time

period).

Step 1 – Organize data and perform linea r regression(s) between target monitor and candidate monitors.

All the available paired data with in the period limit described in th e Eligibility section was used to

develop a linear regression to predic t target concentrations from candi date concentrations. A regression

was performed for each possible pairing that met the criteria utilized for 100 data points and 20 data

# 13 points per calendar quarter (across al l years) in the last 20 quarters of the 3-year time period for each

candidate monitor in the NY-NJ-CT PM 2.5 

# nonattainment area.

Step 2 – Select Candidate site

The NY-NJ-CT PM 2.5 

# nonattainment area has a larg e number of monitors which could have been used as

candidate sites. Only one candidate monitor was se lected 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 rela ting concentrations at the target monitor and the candidate monitor,

estimates of the 24-hour average co ncentrations were made at th e target monitor for all missing

scheduled days in the initially incomplete quarters in the most recent three-year period at the target.

Estimates were only made for days on which a concen tration is available at the candidate monitor.

Estimates were not made for any days in quarters fo r which the target had 75 percent or more complete

data initially. The estimates were combined with any reported data at the ta rget in the recent 3-year

period and the data capture rates were computed for each originally incomplete quarter. The

computation of data capture rates required an assu mption that the required sampling frequency for the

Target was recorded. If the candidate monitor ha d 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 th an the target, the targ et sampling schedule was

assumed to be a combination of the target and candidate schedules, weig hted by the number of

originally present and originally missi ng scheduled days at the Target.

3) If after performing the pr ocess 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. If 75

percent of the scheduled values fo r 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 Computed

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 the five target monitors in the

NY-NJ-CT PM 2.5 

# nonattainment area were both below the NAAQS

Step 4 –Statistical confidence of a design value below the NAAQS checked

The results of Step 3 showed design values for the five target monitors in NY-NJ-CT PM 2.5 

# nonattainment area to be below the NAAQS. In orde r to show that there is at most a 10 percent

probability that the actual design va lue (had the target monitors operated more days) was above the

NAAQS further analysis wa s performed as follows:

# (a) Residuals were calculated from the regression.

(b) A bootstrap analysis was perf ormed, repeating the re gression-based substitution in Step 2 but

adding to each estimated 24-hour value that substitu tes 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 a pplies real residuals from the linea r regression to the imputed currentperiod target values.

(c) Repeat (b) for a total of 1000 runs.

(d) For each of the 1000 bootstrap tr ials, the 3-year design value was calculated. This will provide a

pseudo confidence interval for the partially impu ted current-period design value for the target.

(e) Since none of the 1000 runs resulted in a design values a bove the NAAQS, the targets were

considered to have met the NAAQS.

C. Results of Regression Analysis

Determining the design value for Newark-Willis Center (AQS ID 340130015)

Steps 1 and 2 were performed with Newark Willis Cent er as the target monitor. On Figures 2, 3, 6 and

7, the Newark-Willis Center monitor (target) is listed as Site A. All the candidate sites that were used

are listed as Site B. The highe st correlating monitor for 2007-2009 wa s located at the Mitchell Building

in Elizabeth, Union County (AQS ID 340390006). The Mitchell Building monitor had sufficient

correlation and data capture to deve lop a regression equation between the target and candidate monitor.

The results of the regression can be found in Figure 4. The regression was used to fill in missing values

for the Newark-Willis Center monitor to yield a design value for 2007-2009. For 2008-2010, Newark

Firehouse (AQS ID 340171003) had suffi cient correlation and data captu re to develop a regression

equation between the target and candidate monitor. The Mitchell Building monitor did not have

sufficient paired data to establis h a good relationship due to incomple te data for quarter 1 of 2010. The

results of the 2008-2010 regressions can be found in Figure 8. The results of the analysis produced

design values of 30 μg/m 3 

# and 26 μg/m 3 

# for 2007-2009 and 2008-2010, respectively. The design values

for both time periods passed the boostrapping test descri bed in Step 4 (Figures 5 and 9) which provides

statistical confidence that the monitor at Newark -Willis Center would have attained the 24-hour PM 2.5 

# NAAQS.

Figure 2: Monitor correlations with Newark-Willis Center and candidate mo nitors for 2007-2009 npairsQ1 npairsQ2 npairsQ3 npairsQ4 corr

New York, 340130015 340130015 32 inc-a 32 inc-a 166 157 144 138 1

New York, 340130015 340390006 32 inc-a 31 A 149 142 129 121 0.971616

New York, 340130015 340171003 32 inc-a 32 A 161 151 136 132 0.965167

New York, 340130015 340390004 32 inc-a 32 inc-a 160 144 134 134 0.961005

New York, 340130015 340030003 32 inc-a 31 A 150 141 139 127 0.957764

New York, 340130015 360610079 32 inc-a 32 A 163 149 142 134 0.955341

New York, 340130015 360610134 32 inc-a 33 inc-a 20 46 39 29 0.954282 Area Site A Site B DV Site

A DV

status

Site A DV Site

B DV

status

Site B 20-quarter look



# 14

# 15 Figure 3: Data capture for Newark Willis Center and candidate monitors for 2007-2009

Figure 4: Newark Willis Center and Mitchell Building regressi on results for 2007-2009. The computed Newark Willis

Center: Mitchell Building linear relationship is:

Newark Willis Center concentration = -0.031539 + 0.984558 * Mitchell Building concentration 2007 Q1 2007 Q2 2007 Q3 2007 Q4 2008 Q1 2008 Q2 2008 Q3 2008 Q4 2009 Q1 2009 Q2 2009 Q3 2009 Q4



### 340130015 90% 80% 100% 97% 94% 87% 26%

340390006 90% 90% 74% 87% 97% 93% 90% 100% 87% 100% 100% 90%

340171003 98% 97% 76% 89% 95% 88% 83% 95% 91% 89% 100% 89%

340390004 99% 88% 97% 93% 89% 60% 76% 99% 98% 86% 99% 97%

340030003 97% 90% 100% 100% 94% 83% 81% 90% 97% 97% 100% 84%

360610079 100% 100% 100% 100% 97% 100% 100% 93% 100% 100% 100% 100%

360610134 10% 100% 100% 100% 61% 93% 97% 93% 100% 97% 93% 100% Quarterly Data Capture, 2007-2009



### Site B

v_a

0 10 20 30 40 50

v_b 0 1 0 20 30 40 50

## Figure 5: Bootstrapping results from the 1000 simulations for the Newark Willis Center fo r 2007-2009. “dv” is the

resulting design value after application of residuals from linear regression. “ct” is the number of simulations that

yielded that specific design value. None of the simulations produced a violating design value.

Figure 6: Monitor correlations with Newark-Willis Center and candidate moni tors for 2008-2010.

Figure 7: Data capture for Newark Willis Center and candidate monitors for 2008-2010. npairsQ1 npairsQ2 npairsQ3 npairsQ4 corr

New York 340130015 340130015 29 inc-a 29 inc-a 137 131 144 138 1

New York 340130015 340390006 29 inc-a 27 A 121 119 129 121 0.972045

New York 340130015 340171003 29 inc-a 29 A 132 127 136 132 0.965867

New York 340130015 340390004 29 inc-a 30 A 132 120 134 134 0.962916

New York 340130015 340030003 29 inc-a 28 A 124 117 139 127 0.958111

New York 340130015 360610079 29 inc-a 29 A 134 123 142 134 0.956101

New York 340130015 360610134 29 inc-a 29 A 20 46 39 29 0.954282

New York 340130015 340392003 29 inc-a 26 A 124 112 131 129 0.953898

New York 340130015 360470122 29 inc-a 27 A 121 120 130 126 0.953835

New York 340130015 340172002 29 inc-a 29 A 79 69 80 82 0.952322

Area Site A Site B DV Site

A DV

status

Site A DV Site

B DV

status

Site B 20-quarter look (2003-Q3 - 2008-Q2)

2008 Q1 2008 Q2 2008 Q3 2008 Q4 2009 Q1 2009 Q2 2009 Q3 2009 Q4 2010 Q1 2010 Q2 2010 Q3 2010 Q4

340130015 94% 87% 26% 0% 0% 0% 0% 0% 0% 0% 0% 0%

340390006 97% 93% 90% 100% 87% 100% 100% 90% 67% 100% 97% 87%

340171003 95% 88% 83% 95% 91% 89% 100% 89% 96% 99% 100% 90%

340390004 89% 60% 76% 99% 98% 86% 99% 97% 90% 97% 93% 98%

340030003 94% 83% 81% 90% 97% 97% 100% 84% 100% 97% 100% 97%

360610079 97% 100% 100% 93% 100% 100% 100% 100% 100% 100% 97% 90%

360610134 61% 93% 97% 93% 100% 97% 93% 100% 83% 97% 97% 100%

340392003 94% 73% 97% 100% 100% 90% 100% 100% 83% 100% 100% 100%

360470122 81% 90% 94% 93% 93% 100% 77% 97% 93% 100% 84% 94%

340172002 100% 67% 94% 100% 97% 97% 97% 94% 80% 100% 97% 90% Quarterly Data Capture, 2008-2010

Site B



# 16

# 17 Figure 8: Newark Willis Center and Newark Firehouse reg ression results for 2008-2010. The computed Newark

Willis Center: Newark Fireho use linear relationship is:

Newark Willis Center concentration = -0.34544 + 0.95545 * Newark Firehouse concentration

Figure 9: Bootstrapping results from the 1000 simulations for the Newark Willis Center fo r 2008-2010. “dv” is the

resulting design value after application of residuals from linear regression. “ct” is the number of simulations that

yielded that specific design value. None of the simulations produced a violating design value.



# Determining the design value for Elizabeth Lab (AQS ID 340390004)

Elizabeth Lab only had an incomplete design valu e for 2007-2009. Steps 1 and 2 were performed with

Elizabeth Lab as the target monitor. On Figures 10 and 11, the Elizabet h Lab monitor (target) is listed

as Site A. All the candidate sites that were used are listed as Site B. The hi ghest correlating monitor for

2007-2009 was located at the Mitche ll Building in Elizabeth, Uni on County (AQS ID 340390006). The

Mitchell Building monitor had sufficient correlation a nd data capture to deve lop a regression equation

between the target and candidate monitor. The resu lts of the regression can be found in Figure 12. The

regression was used to fill in missing values for the Elizabeth Lab monitor to yield a design value for

2007-2009. The results of the analysis produced 2007-2009 design value of 32 μg/m 3 

# . The design value

v_a

0 10 20 30 40 50

v_b 0 1 0 20 30 40 50

# passed the boostrapping test described in Step 4 (Fi gure 13) which provides sta tistical confidence that

the monitor at Elizabeth Lab is attaining the 24-hour PM 2.5 

# NAAQS.

Figure 10: Monitor correlations with Elizabeth Lab and candidate monitors for 2007-2009.

Figure 11: Data capture for Elizabeth La b and candidate monitors for 2007-2009.

Figure 12: Elizabeth Lab and Mitchell Building regression results for 2007-2009. Th e computed Elizabeth Lab:

Mitchell Building linear relationship is: npairsQ1 npairsQ2 npairsQ3 npairsQ4 corr

New York, 340390004 340390004 32 inc-a 32 inc-a 506 474 504 523 1

New York, 340390004 340390006 32 inc-a 31 A 151 151 163 190 0.966399

New York, 340390004 340130015 32 inc-a 32 inc-a 107 96 88 84 0.964194

New York, 340390004 340392003 32 inc-a 30 inc-a 163 152 163 172 0.962078

New York, 340390004 340171003 32 inc-a 32 A 380 336 363 383 0.95619

New York, 340390004 340130003 32 inc-a 25 inc-a 28 27 59 58 0.954873 Area Site A Site B DV Site

A DV

status

Site A DV Site

B DV

status

Site B 20-quarter look

v_a

0 10 20 30 40 50 60

v_b 0 1 0 20 30 40 50



# 18 Elizabeth Lab concentration = 1.261699 + 1.02085 * Mitchell Building concentration

# 19 Figure 13: Bootstrapping results from the 1000 simulations fo r the Elizabeth Lab for 2007-200 9. “dv” is the resulting



# etermining the design value for PS 59 (AQS ID: 360610056) design value after application of residua ls from linear regression. “ct” is the number of simulations that yielded that

specific design value. None of the simulations produced a violating design value.



# D

On Figures 14, 15, 18, and 19, the PS

for

n

Figure 14: Monitor correlations with PS 59 and candidate moni tors for 2007-2009. 

# Steps 1 and 2 were performed with PS 59 as the ta rget monitor.

59 monitor (target) is listed as Site A. All the candid ate sites that were used are listed as Site B. The

highest correlating monitor for 2007-2009 was located at Queens College, Queens County (AQS ID

360810124). The Queens College monitor had sufficient correlation and data capture to develop a

regression equation between the target and candidate monitor. The results of the regression can be

found in Figure 16. Other monitors that had good correla tion but did not have su fficient paired data

2007-2009 were PS 124 (AQS ID 360610134), PS 19 (AQS ID 360610128), and Pfizer Lab (AQS ID

360050133). The regression using Queens College as the candidate monitor was used to fill in missing

values for the PS 59 monitor to yield a de sign value for 2007-2009. For 2008-2010, Queens College

(AQS ID 360810124) again had sufficien t correlation and data capture to develop a regression equatio

between the target and candidate monitor. The resu lts of the regression can be found in Figure 20. The

PS 124 monitor did not have sufficien t paired data and incomplete da ta for quarter 1 of 2008. Other

monitors, the same as for 2007-2009, that had good correlation but did not have sufficient paired data

for 2008-2010 were PS 124, PS 19, and Pfizer Lab. The resu lts of the analysis produced design values

of 33 μg/m 3 

# and 31 μg/m 3 

# for 2007-2009 and 2008-2010, respectively. The design values for both time

periods passed the boostrapping test described in Step 4 (Figures 17 a nd 21) which provides statistical

confidence that the monitor at PS 59 would have attained the 24-hour PM 2.5 

# NAAQS.

npairsQ1 npairsQ2 npairsQ3 npairsQ4 corr

New York, 360610056 360610056 35 inc-a 35 inc-a 152 146 121 146 1

New York, 360610056 360610134 35 inc-a 33 inc-a 22 54 31 30 0.980713

New York, 360610056 360610128 35 inc-a 31 inc-a 132 131 117 134 0.976113

New York, 360610056 360050133 35 inc-a 29 inc-a 27 28 0.966112

New York, 360610056 360810124 35 inc-a 30 A 136 138 99 130 0.958301

New York, 360610056 360610079 35 inc-a 32 A 150 144 120 144 0.957539

New York, 360610056 360470122 35 inc-a 30 A 138 140 111 135 0.95364

New York, 360610056 360050110 35 inc-a 32 A 152 146 121 145 0.949793 Area Site A Site B DV Site

A DV

status

Site A DV Site

B DV

status

Site B 20-quarter look

## Figure 15: Data capture for PS 59 a nd candidate monitors for 2007-2009.

Figure 16: PS 59 and Queens College regression results fo r 2007-2009. The computed PS 59: Queens College linear

relationship is: PS 59 concentration = 3.193116 + 1.027248 * Queens College concentration

Figure 17: Bootstrapping results from the 1000 simulations fo r the PS 59 for 2007-2009. “dv” is the resulting design

value after application of residuals from linear regression. “ct” is the number of simulations that yielded that specific

design value. None of the simulations produced a violating design value. 2007 Q1 2007 Q2 2007 Q3 2007 Q4 2008 Q1 2008 Q2 2008 Q3 2008 Q4 2009 Q1 2009 Q2 2009 Q3 2009 Q4



### 360610056 100% 90% 100% 100% 100% 93%

360610134 10% 100% 100% 100% 61% 93% 97% 93% 100% 97% 93% 100%

360610128 100% 100% 94% 70% 77% 50% 30% 97% 93% 87%

360050133 87% 100% 100% 97% 100% 100% 100% 100%

360810124 82% 95% 87% 100% 99% 98% 99% 96% 100% 99% 93% 88%

360610079 100% 100% 100% 100% 97% 100% 100% 93% 100% 100% 100% 100%

360470122 97% 100% 90% 100% 81% 90% 94% 93% 93% 100% 77% 97%

360050110 99% 92% 92% 99% 87% 92% 96% 100% 100% 89% 89% 98% Quarterly Data Capture, 2007-2009



### Site B

v_a

0 10 20 30 40 50

v_b 0 1 0 20 30 40 50



# 20

# 21 Figure 18: Monitor correlations with PS 59 and candidate moni tors for 2008-2010.

Figure 19: Data capture for PS 59 a nd candidate monitors for 2008-2010. npairsQ1 npairsQ2 npairsQ3 npairsQ4 corr

New York 360610056 360610056 33 inc-a 33 inc-a 152 146 121 146 1

New York 360610056 360610134 33 inc-a 29 A 22 54 31 30 0.980713

New York 360610056 360610128 33 inc-a 27 inc-a 132 131 117 134 0.976113

New York 360610056 360050133 33 inc-a 27 A 27 28 0.966112

New York 360610056 360810124 33 inc-a 28 A 136 138 99 130 0.958301

New York 360610056 360610079 33 inc-a 29 A 150 144 120 144 0.957539

New York 360610056 360470122 33 inc-a 27 A 138 140 111 135 0.95364

New York 360610056 360050110 33 inc-a 29 inc-a 152 146 121 145 0.949793

New York 360610056 360050080 33 inc-a 29 A 141 142 114 138 0.948624

New York 360610056 340171003 33 inc-a 29 A 148 137 112 140 0.942114

Area Site A Site B DV Site

A DV

status

Site A DV Site

B DV

status

Site B 20-quarter look (2003-Q3 - 2008-Q2)

2008 Q1 2008 Q2 2008 Q3 2008 Q4 2009 Q1 2009 Q2 2009 Q3 2009 Q4 2010 Q1 2010 Q2 2010 Q3 2010 Q4

360610056 100% 93% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0%

360610134 61% 93% 97% 93% 100% 97% 93% 100% 83% 97% 97% 100%

360610128 77% 50% 0% 0% 30% 97% 93% 87% 100% 93% 94% 100%

360050133 87% 100% 100% 97% 100% 100% 100% 100% 100% 100% 97% 100%

360810124 99% 98% 99% 96% 100% 99% 93% 88% 100% 100% 91% 93%

360610079 97% 100% 100% 93% 100% 100% 100% 100% 100% 100% 97% 90%

360470122 81% 90% 94% 93% 93% 100% 77% 97% 93% 100% 84% 94%

360050110 87% 92% 96% 100% 100% 89% 89% 98% 96% 79% 0% 0%

360050080 94% 97% 97% 93% 100% 81% 93% 87% 100% 87% 91% 95%

340171003 95% 88% 83% 95% 91% 89% 100% 89% 96% 99% 100% 90% Quarterly Data Capture, 2008-2010

Site B

# 22 Figure 20: PS 59 and Queens College regression results fo r 2008-2010. The computed PS 59: Queens College linear

relationship is: PS 59 concentration = 3.19312 + 1.02725 * Queens College concentration

Figure 21: Bootstrapping results from the 1000 simulations fo r the PS 59 for 2008-2010. “dv” is the resulting design

value after application of residuals from linear regression. “ct” is the number of simulations that yielded that specific

design value. None of the simulations produced a violating design value.



# Determining the design value fo r Canal Street (AQS ID 360610062)

Steps 1 and 2 were performed with Canal Street as the target monito r. On Figures 22, 23, 26 and 27, the

Canal Street monitor (target) is listed as Site A. All the candidate sites that were used are listed as Site

B. The highest correlating monitor for 2007-2009 and 2008-2010 was located at JHS 126, Kings

County (AQS ID 360470122). The JHS 126 monitor had su fficient correlation and data capture to

develop a regression equation betw een the target and candidate monitor for 2007-2009 and 2008-2010.

The results of the regressions can be found in Figures 24 and 28. The results of the analysis produced

design values of 30 μg/m 3 

# and 28 μg/m 3 

# for 2007-2009 and 2008-2010, respectively. The design values

for both time periods passed the boo tstrapping test described in St ep 4 (Figures 25 and 29) which

provides statistical confidence that the monitor at Canal Street w ould have attained the 24-hour PM 2.5 

# NAAQS.

v_a

0 10 20 30 40 50

v_b 0 1 0 20 30 40 50

# 23 Figure 22: Monitor correlations with Canal St reet and candidate monitors for 2007-2009.

Figure 23: Data capture for Canal Street and candidate monitors for 2007-2009.

Figure 24: Canal Street and JHS 126 regression result s for 2007-2009. The comp uted Canal Street: JHS 126

relationship is: Canal Street concentration = 0.677334 + 0.997611 * JHS 126 concentration npairsQ1 npairsQ2 npairsQ3 npairsQ4 corr

360610062 360610062 35 inc-a 35 inc-a 175 139 148 149 1

360610062 360470122 35 inc-a 30 A 160 132 136 137 0.982028

360610062 360610079 35 inc-a 32 A 171 137 146 146 0.980414

360610062 340171003 35 inc-a 32 A 170 131 141 143 0.976562

360610062 360050110 35 inc-a 32 A 174 137 148 148 0.970477

360610062 360610128 35 inc-a 31 inc-a 135 137 144 142 0.969341

360610062 340172002 35 inc-a 33 inc-a 74 28 46 56 0.968423

Site A Site B DV Site

A DV

status

Site A DV Site

B DV

status

Site B 20-quarter look

2007 Q1 2007 Q2 2007 Q3 2007 Q4 2008 Q1 2008 Q2 2008 Q3 2008 Q4 2009 Q1 2009 Q2 2009 Q3 2009 Q4



### 360610062 90%

360470122 97% 100% 90% 100% 81% 90% 94% 93% 93% 100% 77% 97%

360610079 100% 100% 100% 100% 97% 100% 100% 93% 100% 100% 100% 100%

340171003 98% 97% 76% 89% 95% 88% 83% 95% 91% 89% 100% 89%

360050110 99% 92% 92% 99% 87% 92% 96% 100% 100% 89% 89% 98%

360610128 100% 100% 94% 70% 77% 50% 30% 97% 93% 87%

340172002 100% 90% 90% 90% 100% 67% 94% 100% 97% 97% 97% 94% Quarterly Data Capture, 2007-2009



### Site B

v_a

0 10 20 30 40 50 60 70 80 90

v_b 0 10 20 30 40 50 60 70 80 90

## Figure 25: Bootstrapping results from the 1000 simulations fo r the Canal Street for 2007-200 9. “dv” is the resulting

design value after application of residua ls from linear regression. “ct” is the number of simulations that yielded that

specific design value. None of the simulations produced a violating design value.

Figure 26: Monitor correlations with Canal St reet and candidate monitors for 2008-2010.

Figure 27: Data capture for Canal Street and candidate monitors for 2008-2010. npairsQ1 npairsQ2 npairsQ3 npairsQ4 corr

New York 360610062 360610062 ? ? ? ? 175 139 148 149 1

New York 360610062 360470122 ? ? 27 A 160 132 136 137 0.982028

New York 360610062 360610079 ? ? 29 A 171 137 146 146 0.980414

New York 360610062 340171003 ? ? 29 A 170 131 141 143 0.976562

New York 360610062 360050110 ? ? 29 inc-a 174 137 148 148 0.970477

New York 360610062 360610128 ? ? 27 inc-a 135 137 144 142 0.969341

New York 360610062 340172002 ? ? 29 A 74 28 46 56 0.968423

New York 360610062 360610056 ? ? 33 inc-a 173 139 118 143 0.966599

New York 360610062 360050080 ? ? 29 A 162 136 142 139 0.965321

New York 360610062 360810124 ? ? 28 A 153 128 123 128 0.964161

Area Site A Site B DV Site

A DV

status

Site A DV Site

B DV

status

Site B 20-quarter look (2002-Q1 - 2007-Q1)

2008 Q1 2008 Q2 2008 Q3 2008 Q4 2009 Q1 2009 Q2 2009 Q3 2009 Q4 2010 Q1 2010 Q2 2010 Q3 2010 Q4

360610062 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0%

360470122 81% 90% 94% 93% 93% 100% 77% 97% 93% 100% 84% 94%

360610079 97% 100% 100% 93% 100% 100% 100% 100% 100% 100% 97% 90%

340171003 95% 88% 83% 95% 91% 89% 100% 89% 96% 99% 100% 90%

360050110 87% 92% 96% 100% 100% 89% 89% 98% 96% 79% 0% 0%

360610128 77% 50% 0% 0% 30% 97% 93% 87% 100% 93% 94% 100%

340172002 100% 67% 94% 100% 97% 97% 97% 94% 80% 100% 97% 90%

360610056 100% 93% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0%

360050080 94% 97% 97% 93% 100% 81% 93% 87% 100% 87% 91% 95%

360810124 99% 98% 99% 96% 100% 99% 93% 88% 100% 100% 91% 93% Quarterly Data Capture, 2008-2010

Site B



# 24

# 25 Figure 28: Canal Street and JHS 126 regression result s for 2008-2010. The comp uted Canal Street: JHS 126

relationship is: Canal Street concentration = 0.67733 + 0.99761 * JHS 126 concentration

Figure 29: Bootstrapping results from the 1000 simulations fo r the Canal Street for 2008-201 0. “dv” is the resulting

design value after application of residua ls from linear regression. “ct” is the number of simulations that yielded that

specific design value. None of the simulations produced a violating design value.



# Determining the design value for PS 19 (AQS ID: 360610128)

Steps 1 and 2 were performed with PS 19 as the ta rget monitor. On Figures 30, 31, 34, and 35, the PS

19 monitor (target) is listed as Site A. All the candi date sites that were used are listed as Site B. The

highest correlating monitor with sufficient pair ed data with PS 19 for 2007-2009 was PS 124, New York

County (AQS ID 360610134). The results of the regres sion can be found in Figure 32. PS 59 and Pfizer

Lab had higher correlations but lacked sufficien t pairs due to incomplete quarters. PS 59 had

incomplete data, due to shutdown, from 3 rd 

# quarter of 2008 through the present and Pfizer Lab had

incomplete data for 2007. The highest correlating m onitor with sufficient paired data with PS 19 for

2008-2010 was located at Pfizer Lab. The results of the 2008-2010 regression can be found in Figure 36.

The results of the analysis pr oduced design values of 32 μg/m 3 

# and 28 μg/m 3 

# for 2007-2009 and 2008-

v_a

0 10 20 30 40 50 60 70 80 90

v_b 0 10 20 30 40 50 60 70 80 90

# 2010, respectively. The design values for both time pe riods passed the boostrapping test described in

Step 4 (Figures 33 and 37) which provides statistical confidence that the monitor at PS 19 is attaining

the 24-hour PM 2.5 

# NAAQS.

Figure 30: Monitor correlations with PS 19 and candidate moni tors for 2007-2009.

Figure 31: Data capture for PS 19 a nd candidate monitors for 2007-2009. npairsQ1 npairsQ2 npairsQ3 npairsQ4 corr

New York, 360610128 360610128 31 inc-a 31 inc-a 144 164 145 139 1

New York, 360610128 360610056 31 inc-a 35 inc-a 105 101 84 81 0.974468

New York, 360610128 360050133 31 inc-a 29 inc-a 60 73 56 57 0.965357

New York, 360610128 360610134 31 inc-a 33 inc-a 53 100 83 78 0.960733

New York, 360610128 360470122 31 inc-a 30 A 132 160 129 126 0.945033

New York, 360610128 360810124 31 inc-a 30 A 130 157 120 127 0.944688

New York, 360610128 360610079 31 inc-a 32 A 143 164 144 136 0.943699 Area Site A Site B DV Site

A DV

status

Site A DV Site

B DV

status

Site B 20-quarter look

2007 Q1 2007 Q2 2007 Q3 2007 Q4 2008 Q1 2008 Q2 2008 Q3 2008 Q4 2009 Q1 2009 Q2 2009 Q3 2009 Q4



### 360610128 100% 100% 94% 70% 77% 50% 30% 97% 93% 87%

360610056 100% 90% 100% 100% 100% 93%

360050133 87% 100% 100% 97% 100% 100% 100% 100%

360610134 10% 100% 100% 100% 61% 93% 97% 93% 100% 97% 93% 100%

360470122 97% 100% 90% 100% 81% 90% 94% 93% 93% 100% 77% 97%

360810124 82% 95% 87% 100% 99% 98% 99% 96% 100% 99% 93% 88%

360610079 100% 100% 100% 100% 97% 100% 100% 93% 100% 100% 100% 100% Quarterly Data Capture, 2007-2009



### Site B



# 26

# 27 Figure 32: PS 19 and PS 124 regression results for 2007-2009 . The computed PS 19: PS 124 relationship is: PS 19

concentration = 0.574804 + 0.93408 * PS 124 concentration

Figure 33: Bootstrapping results from the 1000 simulations fo r the PS 19 for 2007-2009. “dv” is the resulting design

value after application of residuals from linear regression. “ct” is the number of simulations that yielded that specific

design value.

Figure 34: Monitor correlations with PS 19 and candidate moni tors for 2008-2010. npairsQ1 npairsQ2 npairsQ3 npairsQ4 corr

New York 360610128 360610128 27 inc-a 27 inc-a 119 133 115 108 1

New York 360610128 360610056 27 inc-a 33 inc-a 80 70 54 50 0.970136

New York 360610128 360050133 27 inc-a 27 A 60 73 56 57 0.965357

New York 360610128 360610134 27 inc-a 29 A 53 100 83 78 0.960733

New York 360610128 360810124 27 inc-a 28 A 105 132 102 103 0.946096

New York 360610128 360610079 27 inc-a 29 A 118 133 114 105 0.935764

New York 360610128 360470122 27 inc-a 27 A 109 130 101 99 0.93342

New York 360610128 360050080 27 inc-a 29 A 116 124 106 101 0.927679

New York 360610128 360850055 27 inc-a 26 A 115 122 109 106 0.92271

New York 360610128 340171003 27 inc-a 29 A 118 129 110 101 0.919879

Area Site A Site B DV Site

A DV

status

Site A DV Site

B DV

status

Site B 20-quarter look (2006-Q1 - 2010-Q4) v_a

0 10 20 30 40 50

v_b 0 1 0 20 30 40 50

# 28 Figure 35: Data capture for PS 19 a nd candidate monitors for 2008-2010.

Figure 36: PS 19 and Pfizer Lab regressi on results for 2008-2010. The computed PS 19: Pfizer Lab relationship is: PS

19 concentration = 2.38803 + 0.93051 * Pfizer Lab

Figure 37: Bootstrapping results from the 1000 simulations fo r the PS 19 for 2008-2010. “dv” is the resulting design

value after application of residuals from linear regression. “ct” is the number of simulations that yielded that specific

design value. 2008 Q1 2008 Q2 2008 Q3 2008 Q4 2009 Q1 2009 Q2 2009 Q3 2009 Q4 2010 Q1 2010 Q2 2010 Q3 2010 Q4

360610128 77% 50% 30% 97% 93% 87% 100% 93% 94% 100%

360610056 100% 93%

360050133 87% 100% 100% 97% 100% 100% 100% 100% 100% 100% 97% 100%

360610134 61% 93% 97% 93% 100% 97% 93% 100% 83% 97% 97% 100%

360810124 99% 98% 99% 96% 100% 99% 93% 88% 100% 100% 91% 93%

360610079 97% 100% 100% 93% 100% 100% 100% 100% 100% 100% 97% 90%

360470122 81% 90% 94% 93% 93% 100% 77% 97% 93% 100% 84% 94%

360050080 94% 97% 97% 93% 100% 81% 93% 87% 100% 87% 91% 95%

360850055 100% 70% 100% 97% 100% 100% 93% 97% 100% 100% 94% 97%

340171003 95% 88% 83% 95% 91% 89% 100% 89% 96% 99% 100% 90% Quarterly Data Capture, 2008-2010

Site B

v_a

0 10 20 30 40 50

v_b 0 1 0 20 30 40 50

# 29 VI. ADDITIONAL INFORMATION SU MBITTED BY THE STATE

The States of Connecticut, New Jersey, and New York submitted letters and packages to their respective

EPA Regional Administrator regarding the de termination of attainment of the 24-hour PM 2.5 

# NY-NJ-CT

PM 2.5 

# nonattainment area. Each of the packages contained 24-hour PM 2.5 

# design values, analysis on the

decline of PM 2.5 

# concentrations, and details regarding PM 2.5 

# control measures. All the information

provided by the States support EPA’s determin ation of attainment of the 2006 24-hour PM 2.5 

# NAAQS

for the NY-NJ-CT PM 2.5 

# nonattainment area. The letters and pa ckages submitted by the States can be

found in the docket for this rulemaking.

VII. CONCLUSION

EPA is proposing to determine that the NY-NJ-CT PM 2.5 

# nonattainment area for the 2006 24-

hour PM 2.5 

# NAAQS has attained the 2006 24-hour PM 2.5 

# NAAQS and continues to attain the standard

based on data through 2011.

EPA has reviewed the ambient air monitoring data for PM 2.5 

# , consistent with the

requirements contained in 40 CFR part 50 and recorded in the EPA Air Quality System database for the

NY-NJ-CT PM 2.5 

# nonattainment area. The 3-year averages of the 24-hour PM 2.5 

# concentrations

continue to be belo w the NAAQS of 35.0 ug/m 3



# .

EPA has concluded that 5 mon itoring sites in the NY-NJ-CT PM 2.5 

# nonattainment area that

did not have complete and attaining design values would have attained the 2006 24-hour PM 2.5 

# NAAQS

if they had complete data. The statistical proced ure and bootstrapping test used by EPA demonstrated

that incomplete monitors would have had attaining design values if they had operating completely for

the 3 year period(s) of 2007-2009 and/or 2008-2010.

As provided in 40 CFR 51.1004(c), if EPA finalizes this determ ination, it would suspend the

requirements for the NY-NJ-CT PM 2.5 

# nonattainment area to submit attainment demonstrations,

reasonably available control measures, reasonable fu rther progress plans, and contingency measures

related to attainment of the 2006 24-hour PM 2.5 

# NAAQS so long as the area continues to attain the 2006

24-hour PM 2.5 

# NAAQS.

# Appendix A

24-hour design values for NY-NJ-CT PM 2.5 

# FRM monitorsCountyAQS SiteNumber24-hour Design Values2001-20032002-20042003-20052004-20062005-20072006-20082007-20092008-2010Bronx36005008040NA40NA40NA39NA38NA36NA33A29ABronx36005008336NA35A35A34A35A34inc-a33inc-aBronx36005011040NA38NA37NA36NA36NA34A32A29inc-aBronx36005013330inc-a29inc-a27AKings36047005232inc-a29inc-a26inc-aKings36047007633inc-a33inc-a33inc-aKings36047012237NA38NA38NA37NA36NA34A30A27ANassau36059000834A34A35A33A32inc-a30inc-a28inc-a25ANassau36059001230inc-a29inc-a26inc-aNassau36059001331inc-a30inc-a26inc-aNew York36061001044inc-naNew York36061005639NA39NA39NA41NA39NA37NA35inc-a33inc-aNew York36061006242NA41NA42NA38NA37NA35inc-a35inc-aNew York36061007939NA40NA40NA37NA36NA35A32A29ANew York36061012842NA42NA42NA38NA38NA34inc-a31inc-a27inc-aNew York36061013437inc-na34inc-a33inc-a29AOrange36071000230A30A29A28A29A28A26A24AQueens36081009435inc-a34inc-aQueens36081009635inc-a34inc-a33inc-aQueens36081012438NA37NA36NA34inc-a33inc-a32A30A28ARichmond36085005539NA39NA37NA34A34A33inc-a29A26ARichmond36085006731A31A33A33A31A30A27A24ASuffolk36103000136NA35A35A33inc-a34inc-aSuffolk36103000232inc-a30inc-a29A26A25AWestchester36119100234A34A34A34A33A32A29A28AFigure A-1: 24-hour PM2.5design values for New Yorkmonitors in the NY-NJ-CT PM2.5nonattainment area. “A” indicates attainment, “NA” indicatesnonattainment, “inc-a” indicates incomplete and attaining, and“inc-na” indicates incomplete and nonattainment. Rockland County does not have anair monitor.32CountyAQS SiteNumber24-hour Design Values2001-20032002-20042003-20052004-20062005-20072006-20082007-20092008-2010Bergen34003000336NA35A37NA37NA38NA35A31A28ABergen34003000731inc-a32inc-a32inc-a33inc-aBergen34003000832inc-a33inc-a33inc-a33inc-aBergen34003000931inc-a33inc-a33inc-a35inc-aEssex34013000325inc-a25inc-aEssex34013001537NA38NA38NA38NA38NA35inc-a32inc-a29inc-aEssex34013001636NA37inc-na35inc-aHudson34017100340NA40NA41NA39NA38NA36NA32A29AHudson34017200239inc-na38inc-na44inc-na43incna41NA38NA33inc-a29AMercer34021000837NA37NA36NA34A34A33A29A27AMercer34021800133inc-a32A32inc-a30inc-a30inc-a28inc-a26inc-a23AMiddlesex34023000636NA36NA38NA34A32A31A27A23AMorris34027000438NA35A34A31A32A29A26A23inc-aMorris34027300134inc-a33A33A31A31A28A26A23APassaic34031000537NA36NA37NA35A37NA33A30A26inc-aUnion34039000441NA41NA41NA41NA39NA36NA32inc-a30AUnion34039000635inc-a35A38NA37NA38NA35A31A27AUnion34039200335inc-a36NA37NA37NA36NA34inc-a30inc-a26AFigure A-2: 24-hour PM2.5design values for New Jerseymonitors in the NY-NJ-CT PM2.5nonattainment area. “A” indicates attainment, “NA”indicates nonattainment, “inc-a” indicates incomplete and attaining, and “inc-na” indicates incomplete and nonattainment. Monmouth and Passaiccounties do not have air monitors.33CountyAQS SiteNumber24-hour Design Values2001-20032002-20042003-20052004-20062005-20072006-20082007-20092008-2010Fairfield09001001038NA36NA37NA36NA35A33A31A28AFairfield09001011336NA37inc-na40inc-naFairfield09001112335A33A33A32A33A31A29A27AFairfield09001212438NA36NA37inc-na32inc-aFairfield09001300538NA36NA36NA33inc-a34A31A29A26inc-aFairfield09001900337NA36NA37NA32A32A30A29A27ANew Haven09009001841X39X40X39X44XNew Haven09009002646inc-na39inc-na38NA35A34A32A30A27inc-aNew Haven09009002733inc-a36inc-na36NA35A33A31A29ANew Haven09009112340NA39NA40NA38NA36NA34A31A29ANew Haven09009200844inc-na38inc-na36NA33A32A29A27A24inc-aNew Haven09009212335A34A35A34A35A32A30A27ANew Haven09009800347inc-na39inc-na39inc-na31inc-aNew Haven09009900536NA37inc-na44inc-naFigure A-3: 24-hour PM2.5design values for New Jerseymonitors in the NY-NJ-CT PM2.5nonattainment area. “A” indicates attainment, “NA”indicates nonattainment, “inc-a” indicates incomplete and attaining, “inc-na” indicates incomplete and nonattainment, and “X” indicates that thedesign value has not been compared to the NAAQS because the site is microscale and represents a unique area.

# Appendix B

Design value trends20253035404501‐03DV02‐04DV03‐05DV04‐06DV05‐07DV06‐08DV07‐09DV08‐10DVμg/m33yeardesignvalue24‐hourPM2.5DesignValuesfortheNewYorkcountiesintheNY‐NJ‐CTPM2.5nonattainmentareawithmonitors24‐hourstandardBronxKingsNassauNewYorkOrangeQueensRichmondSuffolkWestchesterFigure B-1: 24-hour PM2.5design values for New York monitorsin the 2006 24-hour NY-NJ-CT PM2.5nonattainment area.20253035404501‐03DV 02‐04DV 03‐05DV 04‐06DV 05‐07DV 06‐08DV 07‐09DV 08‐10DVμg/m33yeardesignvalue24‐hourPM2.5DesignValuesfortheNewJerseycountiesintheNY‐NJ‐CTPM2.5nonattainmentareawithmonitors24‐hourstandardBergenEssexHudsonMercerMiddlesexMorrisPassaicUnionFigure B-2: 24-hour PM2.5design values for New Jersey monitors in the 2006 24-hour NY-NJ-CT PM2.5nonattainment area363720253035404501‐03DV 02‐04DV 03‐05DV 04‐06DV 05‐07DV 06‐08DV 07‐09DV 08‐10DVμg/m33yeardesignvalue24‐hourPM2.5DesignValuesfortheConnecticutcountiesintheNY‐NJ‐CTPM2.5nonattainmentareawithmonitors24‐hourstandardFairfieldNewHavenFigure B-3: 24-hour PM2.5design values for Connecticut monitors in the 2006 24-hour NY-NJ-CT PM2.5nonattainment area

# Appendix C

Network Review Letters

# 39

# 40

# 41

# 42

# 43

# 44

# 45

# 46

# 47

# 48

# 49

# 50

# 51

# 52

# 53

# 54

# 55

# 56

# 57

# 58

# 59

# 60

# 61

# 62

# 63

# 64

# 65

# 66

# 67

# 68

# 69