UNITED STATES ENVIRONMENTAL PROTECTION AGENCY

RESEARCH TRIANGLE PARK, NC 27711



### DEC 

## r,ö'¿014,

MEMORANDUM 

## TO: EPA Docket EPA-HQ-OAR-2012-0918

Air Quality Designations for 

### the 2OI2PMz.sStandards

FROM: Liz P. Naess, Air Quality Assessment Division

US EPA Office of Air Quality Planning and Standards OFFICE OF AIR OUALITY PLANNING AND STANDARDS



## SUBJECT: Data Quality lssues in Florida Affecting Air Quality Designations for 

### the 2012

PMz.s National Ambient Air Quality Standards

The purpose of 

### this memorandum 

### isto discuss PMz.s data quality issues 

### identified in Florida as

a result of a technical systems audit (TSA) of 

### the Florida Department 

### of Environmental Protection (FLDEP) ambient air monitoring 

### program. TSAs are systematic and objective examinations of a monitoring program 

### to determine 

### whether environmental data collection activities and related results comply 

### with regulatory requirements, 

### the project's Quality
Assurance Project Plan and 

### other planning documents, are implemented effectively, and are suitable 

### to achieve its data quality goals.

EPA RegioÅ 4 conducted a TSA in Septemb 

### er 2OL4on 

### the FLDEP including 

### the FLDEP PMz.s gravimetric laboratory and identified 

### that laboratory humidity conditions were not being correctly monitored and did 

### not meet 

### the requirements of the federal reference method 

### for

PMz.s found in 40 CFR Part 50, Appendix L. As a result, PMz.s 

### filters were sometimes being weighed outside of 

### the allowable 

### humidity ranges, and could be deemed invalid. Humidity 

### control ranges are among parameters identified as "critical 

### criteria" in the federal reference method 

### for PMz.s 

### found in 40 CFR Part 50, Appendix L. Accordingly, when 

### filters are weighed outside of ihese allowable ranges, 

### the associated data should be considered invalid 

### for regulatory purposes unless 

### there is a compelling reason and 

### justification for not doing 

### so. A large 

### portion of 

### the PMz.s samples 

### for some quarters in 

### the 

### 2OIL- 2013 

### time frame were weighed under humidity conditions outside 

### the required range. Since all of 

### the PMz.s sites in 

### the state send samples 

### to the same state laboratory, this problem has 

### the potential 

### to affect 

### the validity of 

### the data collected in any of 

### the Florida areas.

lntemet Address (URL)



### . http://www.epa.gov Recycled/Hecyclable

. Pñnted with Vegetable Oil Based lnks on Recycled Peper (Minimum 257o Postconsumer)

### Region 4 has not completed their final assessment of the Florida data. Once the TSA findings and data evaluations are completed and provided to FLDEP it is expected that additional technical discussion will ensue before making a final data validity determination.

Attachments:
1. Correspondence related to the Florida Department of Environmental Protection’s monitoring program:

 November 17, 2014 memorandum to Paula Cobb and Justin B. Green, FLDEP

 November 24, 2014 letter to Jeaneanne Gettle, Region 4 EPA

## Florida Department of

Memorandum 

# Environmental Protection

___________________________________________________________________

To: Paula Cobb, Director Air Resource Management

Justin B. Green, Deputy Director Air Resource Management

From: Timothy W. Fitzpatrick, Administrator Bureau of Laboratories

Date: November 17 , 2014

Subject: Evaluation of Concerns Raised by EPA Regarding the Validity of the PM2.5 Laboratory Data for Attainment Cycle 2011

- 2013

During EPA’s September 2014 on

- site assessment of the PM2.5 data generated for attainment years 20 1 1

- 2013, the assessor noted , particularly in September 2012, spikes in humidity above the range specified at 40 CFR Part 50 ( Appendix L Section 8.2 ) for filter conditioning. EPA noted that those data were not qualified for exceeding the humidity limits est ablished for the operation of PM2.5 laboratories per the Code of Federal Regulations (CFR) citation above and the DEP Quality Assurance Project Plan (QAPP)

.
The FL DEP laboratory staff asserts that the preponderance of those reported values are valid and t hat the temperature and humidity control meets the requirements for filter conditioning cited in the CFR

. Chapter 40 CFR Part 50, Appendix L Section 8.0 references EPA’s Quality Assurance Guidance Document 2.12 for detailed guidance on filter weighing ope rations. Section 7.6 of that guidance document help s the laboratory interpret filter conditioning requirements and, specifically

, spikes in temperature or humidity. The laboratory is instructed to evaluate relevant data, and in particular filter blanks, before deciding “if spikes are significant enough to compromise the conditioning period”. Furthermore, the document states that experience evaluating the performance of filter blanks should allow the laboratory to estimate whi ch spikes are too big and might affect filter weight based on the timing of the spikes relative to the time of weighing.

During the days where transient humidity spikes were observed, the laboratory explicitly followed the guidance offered in Section 7.6 of EPA QA Document 2.12 as directed by 40 CFR Part 50 (Appendix L Section 8.2)

. The transient spikes were less than 30

– 40 minutes in duration and typically occurred 4 or more hours before filter weighing commenced. During all of those periods where filter weights were reported, the filter blanks were in good control and satisfied method requirements. Transient humidity spikes, if significant, would have led to a high bias in the weights of field filters and the filter blanks. No such bias was observed in the blanks. Each week, conditioning controls for pre

- sampling and post

- sampling gravimetric operations were evaluated for bias and none was observed. Therefore, the laboratory determined, based on guidance cited in the CFR , that the transient spikes had no effect on the condit ioning of the filters.

It should also be stressed that the filter blanks, in addition to providing controls for detecting particulate contamination, also serve to assess bias induced by humidity differences encountered during the conditioning periods for the pre

- sampling and the post

- sampling gravimetric operations. All of the sample filters conditioned and weighed pre

- sampling are identical to the filter blanks. Subsequent conditioning andweighing of the filter blanks during the post

- sampling operation s would rev eal bias induced by differences in relative humidity between the pre

- and post

- sampling cond itioning periods. No effect of humidity differences during conditioning periods have been noted in any of the reported filter blank data.

More recentl y, laboratory staff performed a study to evaluate the effect of a much longer humidity spike on the weights of actual field samples. A series of pre

- conditioned field filters were deliberately exposed to >70% RH for a duration of 2.5 hours , nearly 4 times the duration of the typical spike . After the 2.5 hour exposure, weighing commenced at a rate of one filter per minute. The study demonstrated three results: all the filters exhibited modest weight gains immediately after exposure ; none of the gains exc eeded the variability requirements of the method ( ± 15 μ g or ± 0.015 mg ) ; and, within 6 minutes after exposure, the filters were within ± 5 μ g of their pre

- exposure weights

.
In addition to th e study described above

, we implemented a plan to re

- weigh field samples originally analyzed on days when humidity excursions occurred during conditioning

. The lab archives field filters in individual petri dishes that are double

- bagged and held in a dedicated refrigerator at 4 0 C . The inte grity of the archived filters i s considered to be excellent. Therefore, a total of 6 0 field samples plus associated duplicates and filter blanks were selected from batches or iginally weighed on 10/08/2012 and 10/29/2012. These dates represen t some of the largest excursions of humidity recorded by the laboratory’s continuous monitoring system

. The original recorded weights and the weights obtained recently are shown in tables below. During the re

weighing, temperature and humidity control was maintained well within the controls cited by the CFR and the DEP QAPP (see table below)

. As the data demonstrate, within the bounds of precision defined for laboratory duplicates ( ± 15 μ g or ± 0.015 mg ), there is no difference between the original filter weights and the weights for both field samples and blanks obtained up to two years later, when th e conditioning room was held in rigorous control. All records supporting this study are available f or inspection. Th e findings of this study are consistent with the conclu sions of recent publications 1,2 and support the lab’s assertion that the data reported originally are valid and of high quality despite some transient humidity excursions

.

In su mmary, while humidity spikes could conceivably cause a high bias in subsequent weight measurements, data from filter blanks, conditioning controls, and a controlled study demonstrated that the transient spikes that occurred h ad no significant effect on filter weights obtained following the conditioning period

. Therefo re, per guidance cited in the CFR for filter weighing, those data were not qualified by the laboratory and we believe the preponderance of the data reported should be considered valid for their intended use. This

conten tion is fully supported by data obta ined through re

- weighing archived filters.

W e have add ed improvements in the temperature and humidity controls within the lab oratory and in the documentation trail for gravimetric operations. In order to increase transparency , the laboratory commit s to qualifying data that do not meet the requirements of the DARM QAPP.

Citations

1. NPL Report DQL

- AS 015; Ambient Air Particulate Matter: Quantifying Errors in Gravimetric
Measurements (January 2005); http://publications.npl.co.uk/npl_web/pdf/dql_as15.pdf )

2. Aerosol and Air Quality Research, 13: 137

– 147, 2013; Comparing the Performance of Teflon and Quartz Membrane Filters Collecting A tmospheric PM: Influence of Atmospheric Water Cinzia Perrino, Silvia Canepari, Maria Catrambone

## Comparison of Filter Weights Originally Reported and Weights Obtained Recently From the Archived Filters

Filter ID Sample Type Original Weighing Date Original Weight (mg) Re-Weiging Date Re-Weighing Value (mg) Difference (mg)

300mg MR 10/08/2012 09:00 300.001 11/05/2014 15:30 300 500 mg MR 10/08/2012 09:01 500.001 11/05/2014 15:31 500.003
T1555802 SF 10/08/2012 09:02 389.376 11/05/2014 15:32 389.376 0
T1555804 SF 10/08/2012 09:03 385.222 11/05/2014 15:33 385.218 0.004
T1555805 SF 10/08/2012 09:04 385.753 11/05/2014 15:34 385.76 -0.007
T1555806 SF 10/08/2012 09:05 384.921 11/05/2014 15:35 384.919 0.002
T1555807 SF 10/08/2012 09:06 382.993 11/05/2014 15:36 382.995 -0.002
T1555808 SF 10/08/2012 09:07 385.203 11/05/2014 15:37 385.199 0.004
T1555809 SF 10/08/2012 09:08 386.958 11/05/2014 15:38 386.958 0
T1555810 SF 10/08/2012 09:09 391.073 11/05/2014 15:39 391.068 0.005
T1555811 SF 10/08/2012 09:10 384.251 11/05/2014 15:40 384.245 0.006
T1555813 SF 10/08/2012 09:11 386.291 11/05/2014 15:41 386.289 0.002 300mg MR 10/08/2012 09:12 300 11/05/2014 15:42 299.999 500 mg MR 10/08/2012 09:13 500 11/05/2014 15:43 500.002
T1555814 SF 10/08/2012 09:14 387.489 11/05/2014 15:44 387.487 0.002
T1555815 SF 10/08/2012 09:15 388.481 11/05/2014 15:45 388.477 0.004
T1555816 SF 10/08/2012 09:16 382.465 11/05/2014 15:46 382.459 0.006
T1555817 SF 10/08/2012 09:17 386.803 11/05/2014 15:47 386.796 0.007
T1555818 SF 10/08/2012 09:18 383.59 11/05/2014 15:48 383.588 0.002
T1555819 SF 10/08/2012 09:19 386.956 11/05/2014 15:49 386.948 0.008
T1555821 SF 10/08/2012 09:20 383.917 11/05/2014 15:50 383.913 0.004
T1555822 SF 10/08/2012 09:21 384.455 11/05/2014 15:51 384.45 0.005
T1555823 SF 10/08/2012 09:22 384.317 11/05/2014 15:52 384.312 0.005
T1555824 SF 10/08/2012 09:23 386.175 11/05/2014 15:53 386.171 0.004 300mg MR 10/08/2012 09:24 300 11/05/2014 15:54 300 500 mg MR 10/08/2012 09:25 500.001 11/05/2014 15:55 500.002
T1555825 SF 10/08/2012 09:26 389.935 11/05/2014 15:56 389.929 0.006
T1555826 SF 10/08/2012 09:27 403.244 11/05/2014 15:57 403.238 0.006
T1555827 SF 10/08/2012 09:28 399.577 11/05/2014 15:58 399.586 -0.009
T1555829 SF 10/08/2012 09:29 395.252 11/05/2014 15:59 395.249 0.003
T1555830 SF 10/08/2012 09:30 399.734 11/05/2014 15:60 399.735 -0.001
T1555831 SF 10/08/2012 09:31 399.431 11/05/2014 15:61 399.44 -0.009
T1555832 SF 10/08/2012 09:32 400.703 11/05/2014 15:62 400.699 0.004
T1555833 SF 10/08/2012 09:33 395.531 11/05/2014 15:63 395.526 0.005
T1555834 SF 10/08/2012 09:34 401.534 11/05/2014 15:64 401.525 0.009
T1555835 SF 10/08/2012 09:35 393.162 11/05/2014 15:65 393.161 0.001
T1555801 LB 10/08/2012 09:36 382.61 11/05/2014 15:66 382.612 -0.002
T1555802 BD 10/08/2012 09:37 389.38 11/05/2014 15:67 389.378 0.002 300mg MR 10/08/2012 09:38 300.001 11/05/2014 15:68 300.002 500 mg MR 10/08/2012 09:39 500 11/05/2014 15:69 500.005

Average Difference 0.002 Maximum Difference 0.009 Minumum Difference -0.009Notes: MR

– Mass Reference
SF

– Sample Filter
LB

– Lab Blank
BD

– Batch Duplicate Filter ID Sample Type Original Weighing Date Original Weight (mg) Re-Weighing
Date Re-Weighing Value (mg) Difference (mg)

300mg MR 10/29/2012 11:00 300.003 11/10/2014 08:00 300.002 500 mg MR 10/29/2012 11:01 500.004 11/10/2014 08:01 500.002
T1556202 SF 10/29/2012 11:02 388.22 11/10/2014 08:02 388.223 -0.003
T1556203 SF 10/29/2012 11:03 395.094 11/10/2014 08:03 395.099 -0.005
T1556204 SF 10/29/2012 11:04 398.816 11/10/2014 08:04 398.811 0.005
T1556217 SF 10/29/2012 11:05 397.575 11/10/2014 08:05 397.569 0.006
T1556231 SF 10/29/2012 11:06 391.223 11/10/2014 08:06 391.223 0
T1556232 SF 10/29/2012 11:07 396.458 11/10/2014 08:07 396.452 0.006
T1556233 SF 10/29/2012 11:08 389.53 11/10/2014 08:08 389.535 -0.005
T1556234 SF 10/29/2012 11:09 390.143 11/10/2014 08:09 390.143 0
T1556235 SF 10/29/2012 11:10 391.053 11/10/2014 08:10 391.06 -0.007
T1556236 SF 10/29/2012 11:11 388.715 11/10/2014 08:11 388.712 0.003 300mg MR 10/29/2012 11:12 300.002 11/10/2014 08:12 300.001 500 mg MR 10/29/2012 11:13 500.005 11/10/2014 08:13 500.003
T1556237 SF 10/29/2012 11:14 390.665 11/10/2014 08:14 390.673 -0.008
T1556239 SF 10/29/2012 11:15 388.51 11/10/2014 08:15 388.517 -0.007
T1556240 SF 10/29/2012 11:16 393.83 11/10/2014 08:16 393.835 -0.005
T1556241 SF 10/29/2012 11:17 392.836 11/10/2014 08:17 392.835 0.001
T1556242 SF 10/29/2012 11:18 394.289 11/10/2014 08:18 394.29 -0.001
T1556243 SF 10/29/2012 11:19 393.426 11/10/2014 08:19 393.423 0.003
T1556244 SF 10/29/2012 11:20 391.818 11/10/2014 08:20 391.813 0.005
T1556245 SF 10/29/2012 11:21 390.512 11/10/2014 08:21 390.507 0.005
T1556247 SF 10/29/2012 11:22 389.434 11/10/2014 08:22 389.434 0
T1556248 SF 10/29/2012 11:23 382.407 11/10/2014 08:23 382.41 -0.003 300mg MR 10/29/2012 11:24 300.001 11/10/2014 08:24 300 500 mg MR 10/29/2012 11:25 500 11/10/2014 08:25 500.002
T1556249 SF 10/29/2012 11:26 386.773 11/10/2014 08:26 386.768 0.005
T1556250 SF 10/29/2012 11:27 386.055 11/10/2014 08:27 386.049 0.006
T1556464 SF 10/29/2012 11:28 387.264 11/10/2014 08:28 387.259 0.005
T1556465 SF 10/29/2012 11:29 392.253 11/10/2014 08:29 392.247 0.006
T1556467 SF 10/29/2012 11:30 381.168 11/10/2014 08:30 381.161 0.007
T1556468 SF 10/29/2012 11:31 398.214 11/10/2014 08:31 398.215 -0.001
T1556469 SF 10/29/2012 11:32 394.793 11/10/2014 08:32 394.793 0
T1556201 LB 10/29/2012 11:33 390.385 11/10/2014 08:33 390.384 0.001
T1556451 LB 10/29/2012 11:34 390.699 11/10/2014 08:34 390.7 -0.001
T1556202 BD 10/29/2012 11:35 388.215 11/10/2014 08:35 388.222 -0.007 300mg MR 10/29/2012 11:36 300 11/10/2014 08:36 300.002 500 mg MR 10/29/2012 11:37 500.001 11/10/2014 08:37 500.002

Average Difference 0.00 Maximum Difference 0.007 Minimum Difference -0.008Filter Conditioning Parameters on 11/05/2014 for filter batches originally weighed on 10/08/2012 Humidity (RH) Temperature (C)
24

- hour Average 32% (± 0.67) 21 (± 0.08)
Minimum 30 20 Maximum 35 21

Filter Conditioning Parameters on 11/10/2014 for filter batches originally weighed on 10/29/2012

Humidity (RH) Temperature (C)
24

- hour Average 32% (± 0.69) 21 (± 0.27)
Minimum 30 20 Maximum 39 21

Filter Conditioning Parameters for the 10/30/2014 Humidity Study (Prior to 70% RH Excursion)

Humidity (RH) Temperature (C)
24

- hour Average 36% (± 1.7) 21 (± 0.23)
Minimum 32 20 Maximum 40 21

Filter Conditioning Parameters for the 10/30/2014 Humidity Study (After the 70% RH Excursion)

Humidity (RH) Temperature (C)
24

- hour Average 35% (± 2.0) 21 (± 0.22)
Minimum 31 20 Maximum 39 21

# F LORIDA 

# D EPARTMENT OF 

# E NVIRONMENTAL 

# P ROTECTION

BOB MARTINEZ CENTER 2600 BLAIRSTONE ROAD TALLAHASSEE, FLORIDA 32399

- 2400 RICK SCOTT GOVERNOR

CARLOS LOPEZ

- CANTERA LT. GOVERNOR

HERSCHEL T. VINYARD J R. SECRETARY



### BY ELECTRONIC MAIL

November 2 4 , 2014

Jeaneanne Gettle , Deputy Director Air, Pesticides and Toxics Management Division Gettle.Jeaneanne@epa.gov

Re: PM 2.5 

### Monitoring Data

This letter is provided in response to recent conversations between the U.S. Environmental Protection Agency

– Region 4 and the Florida Department of Environmental Protection, Division of Air Resource Management, regarding PM 2.5 

### air monitoring data collected during calendar years 20 11

- 2013. EPA has expressed concerns that identified excursions in the Department’s contracted weighing lab might negatively affect EPA’s proposed designation of the entire State of Florida as unclassifiable/attainment for the 2012 Revised Primary Annual PM 2.5 

### NAAQS. However, the Department is confident that the data are valid, both from a scientific and regulatory perspective. This letter and the attached memorandum from the Lab provide proof of data quality and validity and should provide EPA additional co mfort to move forward with its designation as proposed.

During its September 2014 Technical Systems Audit, EPA identified transient relative humidity excursions in the Lab during September and October of 2012. Department records from specific days during that time period show excursions in relative humidity for periods of fewer than 30 to 40 minutes during the night, and at least four hours prior to weighing. As we are all aware, the technical field and laboratory requirements for PM 2.5 

### monitoring are ver y stringent, especially for a humid environment like Florida. The Department is committed to meeting these requirements and understands that doing so allows for quick and efficient approval of its submitted data. However, EPA guidance recognizes that excur sions do occur and that they do not necessarily affect data quality or validity. Under Section 7.6 of EPA QA Document 2.12 (referenced in 40 CFR Part 50), local operators are afforded discretion in assessing excursions to determine the extent to which the underlying data, analyses, or conclusions drawn from specific monitoring or measurement activities might, or might not, have been compromised.

The attached memorandum from the Lab details how it used this discretion and concluded that the data were not c ompromised by the identified excursions. Specifically, the lab states:

• It correctly used the discretion provided by Section EPA QA Document 2.12 to exclude excursions that were not “significant enough to compromise the (filter) conditioning period”;

• Filt ers were weighed while the laboratory was in proper control and after filters were properly conditioned;

www.dep.state.fl.us

### Jeaneanne Gettle November 24, 2014 Page 2 of 7

• A study conducted by the laboratory using filters of known weights exposed to excursions three to four times the length of the excursions in September

- October 2012 indicated no bias; and

• Recent reweighing of the filters at issue showed no significant differences in weight from when originally weighed.

In addition, other information fully supports the quality and validity of the data. The graph below shows recorded PM 2.5 

### concentrations as collected by the Department’s continuous concentration monitors, plotted alongside the FRM PM 2.5 

### data. The Department recognizes that continuous monitors generally are not used for regulatory purposes, but it is telli ng that the graph shows a strong correlation between concentrations recorded by the continuous monitors and concentrations indicated by the filters weighed by the Lab.

www.dep.state.fl.us

### Jeaneanne Gettle November 24, 2014 Page 3 of 7

The next chart shows the 2012 average PM 2.5 

### FRM data plotted with the PM 2.5 

### speciation concentration data analyzed by EPA’s contract laboratory, Research Triangle Institute. Here, too, the data are strongly correlated.

And, as indicated in the table below, the 2011

- 2013 design values calculated using the monitoring data analyzed by the Research Triangle Institute show attainment with the PM 2.5 

### standard.

AQS Site Number Site N ame City Speciation Design Value (mg/m 3 ) FRM Design Value (mg/m 3 )

12

- 011

- 1002 U of F Agricultural Research Center Fort Lauderdale 8.1* 7.1*

12

- 057

- 3002 Sydney Tampa 9.2 7.1

12

- 073

- 0012 Tallahassee Community College Tallahassee 10.4 8.9



### * Substitution procedures were used to calculate the design value due to loss of data during construction.

Furthermore, declining emissions trends also support the air monitoring data collected by the Department. The three graphs below, based on Annual Oper ating Report data from CY 2000

– CY2013, show that emissions of SO 2 

### , NO X 

### , and PM 10 

### have decreased an aggregated 69%. Emissions reported during the time period at issue show that emissions remained at these reduced levels during 2011

- 2013.

www.dep.state.fl.us

### Jeaneanne Gettle November 24, 2014 Page 4 of 7

www.dep.state.fl.us

### Jeaneanne Gettle November 24, 2014 Page 5 of 7

Region al data further support the Department’s air monitoring data . In the Southeast region, PM 2.5 

### concentrations have declined 27% over the last ten years. Based on geography and historic monitoring data, Florida would be expected to have some of the lowest concentrations in the region. This is reflected in the chart below (Florida data is displayed in orange).

0 2 4 6 8 10 12 1401-003-001001-033-100201-155-001001-073-002301-073-100901-073-200301-073-500201-073-300401-097-000301-101-100201-113-000101-121-000201-127-000212-011-100212-011-500512-013-003212-031-009912-057-300212-073-001212-086-101612-095-100412-099-000812-099-200512-103-100912-115-001312-127-500213-021-001213-051-009113-063-009113-067-000413-089-200113-115-000313-121-003913-135-000213-153-000113-215-000113-215-001113-245-000513-295-000213-319-0001 

## 2011

- 2013 PM2.5 Design Values for Alabama, Florida and Georgia

www.dep.state.fl.us

### Jeaneanne Gettle November 24, 2014 Page 6 of 7

Finally, mobile source NO X 

### and VOC emission reductions support the concentrations measured by the Department.

If EPA ultimately finds that the data in question cannot be used to support its proposed attainment designation, the Department would advocate using EPA’s data substitution procedures. If the PM 2.5 

### Design Values were determined using these procedures for the five areas in the state with required monitoring (with estimates of design values for the other three areas), all areas in the state would still show levels significantly below the 12 μg/m 3 

### standard.

MSA Design Value Site Substitution Design Value Original Design Value

Miami 12

- 086

- 1016 8.35 7.2 Tampa 12

- 057

- 3002 7.36 7.1
Orlando 12

- 095

- 2002 6.85 6.5
Jacksonville 12

- 031

- 0099 (2011 2Q missing 52%) 11.02 7.3
Sarasota 12

- 115

- 0013 (TEOM) 8 6.6
Lakeland 12

- 105

- 6006 7.33 6.8
Melbourne 12

- 009

- 0007 (2Q 2012 missing 54%) 6.89 6.1 Fort Myers 12

- 071

- 0005 6.90 6.6



### Given the extensive information provided above, and in the Lab’s memorandum, the Department is confident that its data are more than sufficient to support EPA’s proposed designation. The Department prides itself on its robust air monitoring network and technical expertise and has already implemen ted a ctions to further strengthen laboratory procedures. 0 100,000 200,000 300,000 400,000 500,000 600,000 700,000 800,000

2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012tons 

## Florida Mobile Source Emissions (Highway and Off

- road)

Volatile Organic Compounds Oxides of Nitrogen (NOx)

www.dep.state.fl.us

### Jeaneanne Gettle November 24, 2014 Page 7 of 7

If you have any questions, please contact me at any time at (850) 717

- 9000 or Paula.Cobb@dep.state.fl.us

.

Paula Cobb, Director Division of Air Resource Management Florida Department of Environmental Protection

c: Gregg Worley, EPA Sandra Veazey, DARM Thomas Frick, DEAR

www.dep.state.fl.us