NH Regional Haze 5

- Year Progress Report



### ATTACHMENT A

– Acronyms and Abbreviations

BART Best Availa ble Retrofit Technology bbl barrel (of oil) BLM Bureau of Land Management BOTW beyond

- on

- the

- way CAA Clean Air Act CAIR Clean Air Interstate Rule CAMD Clean Air Markets Division CEMS continuous emissions monitoring system CENRAP Central Regional Air Planning Association CFR Code of Federal Regulations CSAPR Cross

- State Air Pollution Rule EGU electricity generating unit EPA US Environmental Protection Agency ERTAC Eastern Regional Technical Advisory Committee FGD flue gas desulfurization FLM federal land manager FS US Forest Service FWS US Fish and Wildlife Service hr hour IMPROVE Interagency Monitoring of Protected Visual Environments LAC light

- absorbing carbon lb pound MANE

- VU Mid

- Atlantic/Northeast Visibility Union MAR marine air rail MARAMA Mid

- Atlantic Regional Air Management Association MATS Mercury and Air Toxics Standards MMBtu million British thermal units MOVES Motor Vehicle Emissions Simulator MRPO Midwest Regional Planning Organization MW megawatt NAAQS nation al ambient air quality standard ( s ) NESCAUM Northeast States for Coordinated Air Use Management NHDES New Hampshire Department of Environmental Services NMIM National Mobile Inventory Model N Ox nitrogen oxides NPS National Park Service NSPS new sou rce performance standard ( s ) OCM organic carbon mass ORISPL Office of Regulatory Information Systems Plant Location OTB/OTW on

- the

- books/on

- the

- way OTC Ozone Transport Commission PM particulate matter PM 2.5 particulate matter of diameter 2.5 microm eters or less
ppm parts per million PSD Prevention of Significant Deterioration PSNH Public Service of New Hampshire RPG reasonable progress goal RPO regional planning organization RACT reasonably available control technology RATA relative accurac y test audit SIP state implementation plan SO 2 sulfur dioxide TSD technical support document VISTAS Visibility Improvement State and Tribal Association of the Southeast VOC volatile organic compounds WRAP Western Regional Air PartnershipNH Regional Haze 5

- Year Progress Report



### This page is intentionally left blank.NH Regional Haze 5

- Year Progress Report



### ATTACHMENT B
Tracking Visibility Progress, 2004

- 2011

http://www.nescaum.org/documents/ manevu

- trends

- 2004

- 2011

- report

- final

- 20130430.pdfNH Regional Haze 5

- Year Progress Report



### This page is intentionally left blank.

# Tracking Visibility Progress

2004

- 2011

Prepared by NESCAUM for the Mid

- Atlantic/Northeast Visibility Union (MANE

- VU)



# April 30 , 2013

Revised May 24, 2013

## Members of Northeast States for Coordinated Air Use Management

Arthur Marin, Executive Director Northeast States for Coordinated Air Use Management

Anne Gobin, Bureau Chief Connecticut Department of Energy and Environmental Protection, Bureau of Air Management

Marc Cone, Bureau Director Maine Department of Environmental Protection, Bureau of Air Quality

Christine Kirby, Division Director Massachusetts Department of Environmental Protection, Bureau of Waste Prevention

Craig Wright, Acting Director New Hampshire Department of Environmental Services, Air Resources Division

William O’Sullivan, Director New Jersey Department of Environmental Protection, Office of Air Quality Management

David Shaw, Director New York Department of Environmental Conservation, Division of Air Resources

Douglas L. McVay, Chief Rhode Island Department of Environmental Management, Office of Air Resources

Richard A. Valentinetti, Director Vermont Department of Environmental Conservation, Air Pollution Control Division

### ii



# Tracking Visibility Progress 2004

- 2011

Prepared by NESCAUM for the Mid

- Atlantic/Northeast Visibility Union (MANE

- VU)



# April 30 , 2013

Revised May 24, 2013

### i ii



# TRACKING VISIBILITY PROGRESS

2004

- 2011

Project Manager

Paul Miller

Princip a l Contributor

Leiran Biton

### iv



## Acknowledgments

NESCAUM could not have completed this work without the IMPROVE Program and the long

- term commitment of the National Park Service and other federal partners to maintain visibility monitoring networks and the VIEWS data system. NESCAUM also acknowledges the funding for this work through USEPA agreement number XA

96309001 to the Ozone Transport Commission in support of MANE

- VU. Finally, special thanks to Tom Downs with the Maine Dep artment of Environmental Protection for his assistance in compiling observational data. NESCAUM is solely responsible for the content of this report and any errors it may contain.

Printed: May 2013

### v TABLE OF CONTENTS

Acknowledgments

................................ ................................ ................................ .............. iv Executive Summary

................................ ................................ ................................ ......... viii

1. Introduction

................................ ................................ ................................ ................ 1

- 1 1.1. Background

................................ ................................ ................................ ...... 1

- 1

2. Process for Tracking Progress

................................ ................................ ................... 2

- 1 2.1. Long Term Goals and Natural Visibility

................................ ......................... 2

- 1 2.2. Reasonable Progress Goals

................................ ................................ .............. 2

- 2 2.3. Measurement and Data Support

................................ ................................ ....... 2

- 3

3. Results

................................ ................................ ................................ ........................ 3

- 1 3.1. Haze Index Trends

................................ ................................ ........................... 3

- 1 3.2. Constituent Light Extinction Trends

................................ ................................ 3

- 9 3.3. Conclusions on Visibility Progress

................................ ................................ 3

- 23

4. Discussion

................................ ................................ ................................ .................. 4

- 1

5. References

................................ ................................ ................................ .................. 5

- 1 Appendix A: Tracking Progress Data for Class I Areas in and Adjacent to the MANE

- VU Region

### vi FIGURES Figure 1

- 1. Class I Areas of the MANE

- VU Region

................................ ...................... 1

- 2 Figure 3

- 1. Annual Haze Index Levels at Acadia National Park

................................ .... 3

- 2 Figure 3

- 2. Annual Haze Index Levels at Moosehorn Wilderness Area

........................ 3

- 3 Figure 3

- 3. Annual Haze Index Levels at Great Gulf Wilderness Area

......................... 3

- 4 Figure 3

- 4. Annual Haze Index Levels at Lye Brook Wilderness Area

......................... 3

- 5 Figure 3

- 5. Annual Haze Index Levels at Brigantine Wilderness Area

......................... 3

- 6 Figure 3

- 6. Annual Haze Index Levels at Dolly Sods Wilderness Area

........................ 3

- 7 Figure 3

- 7. Annual Haze Index Levels at Shenandoah National Park

........................... 3

- 8 Figure 3

- 8. Individual Constituent Contribution to Annual Haze Index Levels at Acadia National Park on 20 Percent Best and Worst Visibility Days

................ 3

- 11 Figure 3

- 9. Individual Constituent Contribution to Annual Haze Index Levels at Moosehorn Wilderness Area on 20 Percent Best and Worst V isibility Days

..... 3

- 12 Figure 3

- 10. Individual Constituent Contribution to Annual Haze Index Levels at Great Gulf Wilderness Area on 20 Percent Best and Worst Visibility Days

...... 3

- 13 Figure 3

- 11. Individual Constituent Contribution to Annual Haze Index Levels at L ye Brook Wilderness Area on 20 Percent Best and Worst Visibility Days

...... 3

- 14 Figure 3

- 12. Individual Constituent Contribution to A nnual Haze Index Levels at Brigantine Wilderness Area on 20 Percent Best and Worst Visibility Days

...... 3

- 15 Figure 3

- 13. Individual C onstituent Contribution to Annual Haze Index Levels at Dolly Sods Wilderness Area on 20 Percent Best and Worst Visibility Days

..... 3

- 16 Figure 3

- 14. Individual Constituent Contribution to Annual Haze Index Levels at Shenandoah National Park on 20 Percent Best and Worst Visibility Days

........ 3

- 17 Figure 3

- 15. Range of Observed and Estimated Natural Light Extinction for Select Individual Constituents at Acadia National Park on 20 Percent Best and Worst Visibility Days

................................ ................................ ................... 3

- 18 Figure 3

- 16. Range of Observed and Estimated Natural Light Extinction for Select Individual Constituents at Moosehorn Wilderness Area on 20 Percent Best and Worst Visibility Days

................................ .............................. 3

- 19 Figure 3

- 17. Range of Observed and Estimated Natura l Light Extinction for Select Individual Constituents at Great Gulf Wilderness Area on 20 Percent Best and Worst Visibility Days

................................ ................................ ........... 3

- 20 Figure 3

- 18. Range of Observed and Estimated Natural Light Extinction for Select Individual Constituents at Lye Brook Wilderness Area on 20 Percent Best and Worst Visibility Days

................................ ................................ ........... 3

- 21 Figure 3

- 19. Range of Observed and Estimated Natural Light Extinction for Select Individual Constituents at Brigantine Wilderness Area on 20 Percent Best and Worst Visibility Days

................................ ................................ ........... 3

- 22

### vii TABLES Table 1

- 1. Members of the Mid

- Atlantic/Northeast Visibility Union (MANE

- VU)

...... 1

- 1 Table 2

- 1. Natural Visibility Conditions for Class I Areas in and Adjacent to the MANE

- VU Region

................................ ................................ ............................... 2

- 1 Table 2

- 2. 2018 Goals for Class I Areas in or Adjacent to the MANE

- VU Region

...... 2

- 2 Table A

- 1. Tracking Progress Data for Class I Areas in and Adjacent to the MANE

- VU Region (dv)

................................ ................................ ....................... A

- 2

## Executive Summary In this report, we present visibility trends at federal “Class I areas” in the Mid

Atlantic/Northeast Visibility Union (MANE

- VU) region that are subject to the US Environmental Protection Agency’s ( USEPA’s ) Regional Haze Rule (RHR). This analysis was performed to determine the extent of progress in meeting short

- term and long

- term visibility goals under the RHR

. This technical docum ent provides an analysis of visibility data collected at the Class I areas , starting in the historic baseline period of 2000

- 2004 through 2007

- 2011, t h e most recent five

- year period with available data

. The results of this analysis show the following:

 T here are definite downward trends in overall haze levels at the Class I

a reas in and adjacent to the MANE

- VU region

.

 Based on rolling

- five year averages demonstrating progress since the 2000

- 2004 baseline period, the MANE

- VU Class I a reas appear to be on track to meet their 2018 R easonable P rogress G oals (RPGs) for both best and w orst visibility days.

 The trends are mainly driven by large reductions in sulfate light extinction, and to a les ser extent, nitrate light extinction.

 Levels of organic carbon ma ss (OCM) and light absorbing carbon (LAC ) appear to be approaching natural background levels at most of the MANE

VU Class I a reas

.

 In some cases, the levels set by 2018 RPG s have already been met, and progress beyond those goals appear s achievable.

 Though the Brigantine Wilderness Area is on track to meet its 2018 RPGs, challen ges remain. Sulfate light extinction levels are higher at this site than at others across the region . A dditional sulfate reduction s would be a significant driver in reduc ing overall haze levels at Brigantine

.Tracking Visibility Progress, 2004

- 2011 Page 1

- 1



## 1. I NTRODUCTION

1.1. Backgroun d Haze, or reduced visibility, occurs when ambient particulate matter and gases scatter or absorb light (“ light extinction ”) that would otherwise reach an observer . The particles responsible for regional haze are produced naturally, from windblown dust, forest fires, and aerosolized sea salt; and by human

- caused pollution from vehicles, power plants, and other combustion and dust

- generating activities. Haze

- forming particles can also cause serious health effects in the lungs and cardiopulmonary system, potentially leading to premature death. Some particle constituents contribute to acidic deposition and other environmental harm s. In 1999, the US Environmental Protec tion Agency (USEPA) issued a rule under Section 169 A of the Clean Air Act (Visibility Protection for the Federal Class I Areas) to address human

- caused regional haze: the Regional Haze Rule (RHR) [64 FR 35614 (July 1, 1999)]. The RHR is designed to improve visibility at certain national parks and wilderness areas (Class I areas ) on the haziest days while not exacerbating haze on the clearest days. The RHR requires states to submit state implementation plans (SIPs) to USEPA every ten year s , setting interim progress goals and strategies consistent with the lon g

- term national visibility goal of achieving natural conditions at Class I areas by 2064. States submitted their first haze SIPs to USEPA beginning in 2008. S tates are additionally req uired to track their progress against their historic baseline period 1 

### in achieving reductions in regional haze

, submitting reports every five years , and to adjust their emissions management strategies accordingly

.
The Mid

- Atlantic/Northeast Visibility Union (MANE

- VU) was formed to support visibility planning efforts in the mid

- Atlantic and northeastern portion of the country, and includes the members listed in Table 1

- 1

. The seven Class I areas in the MANE

- VU region are shown in Figure 1

- 1

. This document also includes in formation for two Class I

areas that are adjacent to the MANE

- VU region : the Dolly Sods Wilderness Area in West Virginia and Shenandoah National Park in Virginia. The purpose of this report is to

1 The title of this and earlier trends report s use 2004 as the base year because the trend is based on rolling averages of 5

- year periods , and 2004 was the end of the initial 5

- year period used a s the baseline. 

### Table 1

- 1 . Members of the Mid

- Atlantic/Northeast Visibility Union (MANE

- VU)

Connecticut Pennsylvania Delaware Penobscot Indian Nation District of Columbia Rhode Island Maine St. Regis Mohawk Tribe Maryland Vermont Massachusetts National Park Service New Hampshire U.S. EPA New Jersey U.S. Fish and Wildlife Service New York U.S. Forest Service

Source: MANE

- VU Board M embers, http://www.otcair.org/manevu/members.asp

.Tracking Visibility Progress, 2004

- 2011 Page 1

- 2



### support MANE

- VU stat es in meet ing the tracking progress requ irement of the RHR.

W hile this report provide s reade rs with a basic background on regiona l haze, it does not include in

- depth discussion of topics covered in previous reports. For a broader understanding of these topics, readers should visit the NESCAUM re gional haze documents archive , located at the following web address: http://www.nescaum.org/topics/regional

- haze

. In the documents archive, r eaders may find the following of particular interest in understanding regional haze in the MANE

- VU region :

 Regional Haze and Visibility in the Northeast and Mid

- Atlantic States (2001)

 2002: A Year in Review (2004)

 Contributions to Regional Haze in the Northeast and Mid

- Atlantic United States (2006)

 Public Health Benefits of Reducing Ground

- level Ozone and Fine Particulate Matter in the Northeast U.S. (2008)

 MANE

- VU Modeling for Reasonable Progress Goals (2008 )

 2018 Visibility Projections (2008)

 Tracking Visibility Progress, 2004

- 2008 (2010)

 Contribution of Non

- Sulfate Aerosols to MANE

- VU Regional Haze (2012)

Figure 1

- 1

. Class I Areas of the MANE

- VU RegionTracking Visibility Progress, 2004

- 2011 Page 1

- 3



###  The Nature of the Fine Particle and Regional Haze Air Quality Problems in the MANE

- VU Region: A Concept ual Description (Updated July 31, 2012)Tracking Visibility Progress, 2004

- 2011 Page 2

- 1



## 2. PROCESS FOR TRACKING PROGRESS

2.1. Long Term Goals and Natural Visibility
Even in the absence of emissions from human activities, some level of light extinction occurs from natural causes. This “natural haze” represents the best expectation for long

- term progress at Class I areas , and is the goal for these areas by 206 4.

The USEPA (2003a) has guidance for calculating natural haze levels based on measurements of particulate constituents at Class I areas during a baseline period. States combine measurements of several parameters to calculate a “ Haze Index ” in deciview (dv) units based on estimates of light extinction. A fuller explanation of tracking progress procedures is presented in a 2003 USEPA guidance document for tracking progress (USEPA 2003b; hereafter, “the Guidance”), though readers s hould note that the calculation for estimating total light extinction has since been updated. Details on the revised IMPROVE algorithm used to estimate light extinction are presented elsewhere (e.g., NESCAUM 2010).

Natural haze levels are calculated for b oth the least impaired (i.e., clearest or “best”) days and the most impaired (i.e., haziest or “worst”) days, because changing natural processes lead to variability in natural visibility. Natural visibility levels on least and most impaired (i.e., best and worst) days for the MANE

- VU and adjacent Class I

Table 2

- 1 . Natural Visibility Conditions for Class I Areas in and Adjacent to the MANE

- VU Region

Class I Area State Abbr. Best Days

(dv) Worst

Days (dv)

Acadia National Park ME 4.66 12.43

Moosehorn Wilderness Area ME 5.01 12.01
Roosevelt Campobello International Park * ME

- -
Great Gulf Wilderness Area NH 3.73 11.99
Presidential Range/Dry River Wilderness Area * NH

- -
Lye Brook Wilderness Area VT 2.79 11.73
Brigantine Wilderness Area NJ 5.51 12.24
Dolly Sods Wilderness Area † WV 3.63 10.39

Shenandoah National Park † VA 3.14 11.35

Note: The Class I areas are arranged with the areas located in the MANE

- VU region presented first, followed by those adjacent to MANE

- VU

. * Natural haze values are not calculated for areas without baseline monitoring data. V isibility for the Pr esidential Range/Dry River Wilderness Area and Roosevelt Campobello International Park are represented by the IMPROVE monitors for Great Gulf and Moosehorn, respectively. Source: IMPROVE 201 1 ( IMPROVE Natural Haze Levels II version 2 workbook )

. † Class I a rea adjacent to the MANE

- VU region

.Tracking Visibility Progress, 2004

- 2011 Page 2

- 2



### areas are presented in Table 2

- 1

. Achievement of these goals through constant annual incremental improvement in the Haze Index (in dv) such that natural conditions will be reached by 2064 is termed a “uniform rate of progress

. ” Natural background haze levels are not available for some Class I areas without monitoring data , i.e.

, Presidential Range/Dry River Wilderness A rea and Roosevelt Campobello International Park.



## 2.2. Reasonable Progress Goals The RHR requires states to evaluate current regional haze conditions at Class I

areas subject to the rule relative to conditions during a historic baseline period . The baseline period is the five

- year period from 2000 through 2004. The state haze SIPs established reasonable progress goals (RPGs) for reduction of regional haze through 2018. Comparison between the five

- year average Haze Index in 2018 (a back average of the previous five years ’ annual Haze Index values) and the baseline Haze Index will determine whether a state has met its 2018 RPG.

A state sets RPGs for the 20 percent most impaired (i.e., the haziest or “worst”) days and for the 20 percent least impaired (i.e., clearest or “best”) days. The RPGs are designed to at least ensure no degradation for best

- day visibility and achievement of uniform rate of progress for worst

- day visibility. In most cases, states in the MANE

- VU region have adopted RPGs that achieve lower H aze I ndex values by 2018 than would be achieved using either the “no degradation” and “uniform rate of progress” rates for best

an d worst days, respectively. Table 2

- 2 presents the best

- and worst

- day RPGs adopted

Table 2

- 2 . 2018 Goals for Class I Areas in or A djacent to the MANE

- VU Reg ion

Class I Area State Abbr. Best Days Worst Days

No Degradation (dv) Reasonable

Progress Goal (dv) Uniform

Rate of Progress (dv) Reasonable

Progress Goal (dv)

Acadia National Park ME 8.8 8.3 20.4 19.4

Moosehorn Wilderness Area ME 9.2 8.6 19.4 19.0
Roosevelt Campobello International Park ME 9.2 8.6 19.4 19.0

Great Gulf Wilderness Area NH 7.7 7.2 20.3 19.1
Presidential Range/Dry River Wilderness Area NH 7.7 7.2 20.3 19.1

Lye Brook Wilderness Area VT 6.4 5.5 21.5 20.9
Brigantine Wilderness Area NJ 14.3 14.3 25.1 25.1
Dolly Sods Wilderness Area † WV 12.3 11.1 24.7 21.7

Shenandoah National Park † VA 10.9 8.7 25.1 21.9

Note: The Class I areas are arranged with the areas located in the MANE

- VU region presented first, followed by those adjacent to MANE

- VU

. † Class I a rea adjacent to the MANE

- VU region

. Sources: Maine: 76 FR 73956

- 73982 ; New Hampshire: 77 FR 11809

- 11826 ; New Jersey: 76 FR 49711

- 49724 ; Vermont: 77 FR 11914

- 11928 ; Virginia: 77 FR 3691

- 3711 ; West Virginia: 76 FR 41158

- 41177

.Tracking Visibility Progress, 2004

- 2011 Page 2

- 3



### by states for each Class I a rea in or adjacent to the MANE

- VU region per state haze S IP s.



## 2.3. Measurement and D ata S upport
The Haze Index is calculated using light extinction estimates based on measured concentrations of particulate matter (PM) species . Measurements are taken at a network of sites in the Interagency Monitoring of Protected V isual Environments (IMPROVE) program at or near Class I areas . IMPROVE is the result of coordination between the National Park Service, the Fish and Wildlife Service, the Bureau of Land Management, the Forest Service, and USEPA. IMPROVE has operated 17 sit es within the MANE

- VU region since 2002.

The Visibility Information Exchange Web System (VIEWS) team develops and maintains the IMPROVE website in addition to its other activities related to maintenance of air quality monitoring databases. Using the data from IMPROVE, the VIEWS team calculates and regularly posts updated metrics for tracking visibil ity across the country at the national parks and wilderness areas subject to the RHR. VIEWS is hosted at the Colorado State University’s Cooperative Institute for Research in the Atmosphere (CIRA). Another resource, the Federal Land Manager Database (FED), is an extensive database of environmental data and an integrated suite of online tools and resources to help Federal Land Managers assess and analyze the air quality and visibility in f ederally protected lands such as National Parks, National Forests, and Wilderness Areas. For this analysis, we used data from IMPROVE (2011) downloaded through VIEWS for both the natural haze levels (calculated using the revised IMPROVE algorithm) and daily values

, including patched values

, 2 

### for 2000 through 2010. For 2011, we used unpatched data obtained from FED. We analyzed the individual missing constituent data for 2011 using the patching methodology described in the Guidance and determined that patching was unnecessary for all sites in and adjacent to the MANE

- VU region for this analysis

.

2 “Patching” is a procedure for replacing missing values for individual or multiple measured PM constituents with appropriate values, per the Guidance.Tracking Visibility Progress, 2004

- 2011 Page 3

- 1



## 3. RESULTS We analyzed total Haze Index and individual constituent light extinction annual results for each site in or adjacent to the MANE

- VU region for years between 2000 and 2011. The following sections describe the r esults of this analysis. Section 3.1 provides results for the total Haze Index for each site and discusses trends and progress toward short

- term goa ls. Section 3.2 provides individual constituent analysis and trends for each site over the time period in the context of regional emissions reducti on efforts and continued regional and federal policy directions. Finally, Section 3.3 summarizes conclusions based on these results. Results indicate consistent improvement in regional haze on the best and wors t vis ibility days across the region.



## 3.1. Haze Index T rends Figure 3

- 1 (page 3

- 2 ) through Figure 3

- 7 (page 3

- 8 ) present the annual Haze Index on the 20 percent most and least impaired days at MANE

- VU and adjacent Class I

areas between 2000 and 2011 in the context of short

- and long

- term visibility goals

. The figures are arranged with the areas located in the MANE

- VU region presented first, followed by tho se adjacent to MANE

- VU. Table A

- 1 in Appendix A presents these data numerically. Annual average best and worst visibility day Haze Index values are represented by blue and purple diamonds, respectively. Five

- year back annual averages are represented by solid red (worst) and blue (best) lines. Red (worst) and black (best) plus signs represent the 2018 RPGs described in the state haze SIP . The red (worst) and black (best) dotted lines represent the glidepaths to meet 2018 RPGs. Red (worst) and black (best) dashed lines represent the glidepaths to meet long

- term natural visibility goals; the
worst

- day glidepath is also called the “ uniform rate of progress ” line, and the bes t

- day glidepath is also called the “ no degradation ” line. 3 

### The grey region denotes the range of 20

- percent best to worst haze levels expected to occur under natural conditions. Thus, the uniform rate of progress line intersects with highest portion of the grey area in 2064. These figures indicate that haze levels on the best and worst days from 2000 through 2011 have dropped across the entire region. Trends evident in our last report (NESCAUM 2010) for annual average haze levels on best an d worst days through 2008 have largely continued through 2010. In 2011, most of the areas experienced around the same or slightly higher levels of haze on both best and worst days as compared to 2010. The steep drop in Haze Index values for the 20 percent worst days, therefore, appear s to have occurred primarily during the period between 2007 and 2010 for these areas.

3 For the Brigantine and Dolly Sods Wilderness Areas, whose haze levels on the 20 percen t best days during the 2000 to 2004 baseline period were higher than estimated natural conditions on the 20 percent worst days, the no degradation line (representing the long

- term best

- day goal) is higher than the uniform rate of progress line (representin g the long

- term worst

- day goal) at dates approaching 2064. This nonsensical situation by 2064 is an artifact of technical guidance and only represents stated haze level goals, not anticipated results.Tracking Visibility Progress, 2004

- 2011 Page 3

- 2



### Figure 3

- 1

. Annual Haze Index L evels at Acadia National ParkTracking Visibility Progress, 2004

- 2011 Page 3

- 3



### Figure 3

- 2

. Annual Haze Index Levels at Moosehorn Wilderness AreaTracking Visibility Progress, 2004

- 2011 Page 3

- 4



### Figure 3

- 3

. Annual Haze Index L evels at Great Gulf Wilderness AreaTracking Visibility Progress, 2004

- 2011 Page 3

- 5



### Figure 3

- 4

. Annual Haze Index L evels at Lye Brook Wilderness AreaTracking Visibility Progress, 2004

- 2011 Page 3

- 6



### Figure 3

- 5

. Annual Haze Index Levels at Brigantine Wilderness AreaTracking Visibility Progress, 2004

- 2011 Page 3

- 7



### Figure 3

- 6

. Annual Haze Index L evels at Dolly Sods Wilderness AreaTracking Visibility Progress, 2004

- 2011 Page 3

- 8



### Figure 3

- 7

. Annual Haze Index L evels at Shenandoah National ParkTracking Visibility Progress, 2004

- 201 1 Page 3

- 9



### Comparison of the five

- year annual average haze index to the glidepaths for the 2018 SIP commitments show that all areas in and adjacent to the MANE

- VU region are on pace to meet those commitments

. In fact, the 2018 RPGs will be met if 5

- year average level s for best and worst days are maintained at Acadia National Park and at the Great Gulf, Lye Brook, and Moosehorn Wilderness Areas. However, the small uptick in annual average haze levels in 2011 for most areas in the MANE

- VU region demonstrates that effort s are still needed to ensure that 2018 RPGs will be met and to prevent backsliding. The small relative increase for 2011 over the previous several years is almost certainly due, at least in part, to special and converging circumstances: the economic downtu rn followed by slow recovery, unusual meteorology, and the rapid shift toward natural gas

. At Brigantine Wilderness Area and both Class I areas adjacent to the MANE

- VU region , best

- day visibility levels are already below 2018 RPGs, but worst

- day visibility levels require additional progress to meet the short

- term goals.



## 3.2. Constituent Light Extinction Trends In addition to analyzing trends in overall visibility changes at the sites, we also examined the data for changes in individual PM constituent contributions to visibility impairment. Figure 3

- 8 through Figure 3

- 14 present the annual Haze Index by constituent on the 20 percent least and most imp aired days at MANE

- VU and adjacent Class I areas between 2000 and 2011 in the context of RPGs. The figures are arranged with the areas located in the MANE

- VU region presented first, followed by those adjacent to MANE

VU. These figures show individual const ituent values as stacked bar charts for sulfate, nitrate, organic carbon mass (OCM) , light absorbing carbon ( LAC ), soil, co a rse mass, sea salt, and Rayleigh extinction levels on best (left, “a”) and worst (right, “b”) days

. The total of the stacked bars re present annual Haze Index values, and are marked by circles connected by a thin black line. The thick black line represents five

- year back annual averages from 2004 to 2011. The 2018 RPG from the state haze SIP is marked with a black plus sign. Two red lin es descend from the 2004 five

- year back average (i.e., the baseline value): the red dotted line represents the glidepath to the 2018 RPG; and the red dashed line represents the glidepath to the 2064 natural visibility goal, or the “uniform rate of progress ” line. These figures confirm that large reductions in overall Haze Index values on the 20 percent worst days are primarily due to decreases in sulfate visibility impacts at MANE

- VU Class I areas

. Steady decreases in sulfate and nitrate contributions have also reduced overall haze levels on the least impaired days. These decreases occurred mainly from 2005 through 2011 at most of the studied areas, though in some locations (e.g., Dolly Sods Wilderness Area

, Shenandoah National Park ) , the contribution from s ulfate stopped its decline in 2009 and held steady or increased on the worst days through 2011

. Despite the reduced contribution from sulfate on the worst days at most of the MANE

- VU Class I areas , the overall level of haze has remained largely unchanged since about 2009 on the worst days due to increases in contributions from sea salt and organic carbon mass, depending on the site. At Brigantine, the contribution from co a rse mass in 2011 was unusually high, indicating a possible anomaly for that year (Pie tarinen 2013)

.Tracking Visibility Progress, 2004

- 201 1 Page 3

- 10



### This increase in co a rse mass contribution offset reductions in both nitrate and sulfate levels from the preceding years. Contribution from OCM appears to be highly variable from year to year at most sites. For instance, high OCM extinction l evels at Brigantine and Lye Brook Wilderness Areas in 2002, and at Great Gulf Wilderness Area in 2011 on the worst days, undercut declines in contributions from sulfate to raise overall haze levels for those years. Sulfate remains the most significant cont ributor to light extinction at all Class I

areas on the most impaired days in and adjacent to the MA N E

- VU region , followed by OCM and nitrate. For the most part, light extinction from soil and sea salt, which help indicate the extent to which natural haze processes contribute to overall haze levels, are insignificant when compared to extinction from sulfate and nitrate. Based on these figures, continued progress in sulfate and nitrate levels appears to be driving the trend in overall improvement in worst

- a nd best

- day haze level reductions.

To examine the individual constituent trends more closely, we plotted the range of individual light extinction on best and worst days from 2000 through 2011 at the Class I

areas against the estimated light extinction unde r natural conditions. Figure 3

- 15 through Figure 3

- 19 show the range of light extinction levels at the MANE

- VU Class I areas (areas adjacent to the MANE

- VU region are excluded from this analysis for simplicity) as compared to natural light extinction for selected constituents. Estimated n atural light extincti on is represented in each chart by the lighter grey band, and observed extinction by the other band. For the case of the carbonaceous species, OCM and LAC, the green band is observed OCM and the dark grey band is observed LAC. Note that the observations do not represent the range of the highest and lowest 20 percent light extinction levels for those constituents; rather, they represent the range of constituent light extinction levels on the 20 percent least and most impaired visibility days. For Great Gulf Wilderness Area , where observations were missing in 2009 and 2010, 2011 observations are presented as a broad range rather than a single data point for ease of visualization, but note that this is a visual distortion. It is clear from these charts that levels of extinction from sulfate have dropp ed significantly since 2002 at all the MANE

- VU Class I areas , although still remaining at levels much higher than the estimated natural range at all sites. E xtinction due to nitrate has also dropped steadily

, and at several sites is approaching natural levels on the best days. At Brigantine Wilderness Area , extinction due to nitrate remains considera bly higher than the natural baseline. At Acadia National Park, levels of extinction due to carbonaceous constituents and co a rse mass appear to be approximately at natural levels. At Great Gulf, Lye Brook, and Moosehorn Wilderness Areas , co a rse mass extinct ion is approximately at natural levels, and carbonaceous matter has dropped from levels slightly above natural into the natural range. Prior peaks in carbonaceous matter extinction at these sites were driven by OCM levels. At Brigantine Wilderness Area , ca rbonaceous matter has been holding steadily above natural levels with little observable trend downward, and co a rse mass light extinction levels also remain above natural levels, though the 2011 peak in co a rse mass light extinction may be a result of constr uction activity near the monitor location (Pietarinen 2013).Tracking Visibility Progress, 2004

- 2011 Page 3

- 11



### Figure 3

- 8

. Individual Constituent Contribution to Annual Haze Index L evels at Acadia National Park on 20 Percent Best and Worst Visibility Days

(b) 20% Worst Days (a) 20% Best DaysTracking Visibility Progress, 2004

- 2011 Page 3

- 12



### Figure 3

- 9

. Individual Constituent Contribution to Annual Haze Index Levels at Moosehorn Wilderness Area on 20 Percent Best and Worst Visibility Days

(b) 20% Worst Days (a) 20% Best DaysTracking Visibility Progress, 2004

- 2011 Page 3

- 13



### Figure 3

- 10

. Individual Constituent Contribution to Annual Haze Index Levels at Great Gulf Wilderness Area on 20 Percent Best and Worst Visibility Days

(b) 20% Worst Days (a) 20% Best DaysTracking Visibility Progress, 2004

- 2011 Page 3

- 14



### Figure 3

- 11

. Individual Constituent Contribution to Annual Haze Index Levels at Lye Brook Wilderness Area on 20 Percent Best and Worst Visibility Days

(b) 20% Worst Days (a) 20% Best DaysTracking Visibility Progress, 2004

- 2011 Page 3

- 15



### Figure 3

- 12

. Individual Constituent Contribution to Annual Haze Index Levels at Brigantine Wilderness Area on 20 Percent Best and Worst Visibility Days

(b) 20% Worst Days (a) 20% Best DaysTracking Visibility Progress, 2004

- 2011 Page 3

- 16



### Figure 3

- 13

. Individual Constituent Contribution to Annual Haze Index Levels at Dolly Sods Wilderness Area on 20 Percent Best and Worst Visibility Days

(b) 20% Worst Days (a) 20% Best DaysTracking Visibility Progress, 2004

- 2011 Page 3

- 17



### Figure 3

- 14

. Individual Constituent Contribution to Annual Haze Index Levels at Shenandoah National Park on 20 Percent Best and Worst Visibility Days

(b) 20% Worst Days (a) 20% Best DaysTracking Visibility Progress, 2004

- 2011 Page 3

- 18



### Figure 3

- 15

. Range of Observed and Estimated Natural Light Extinction for Select Individual Constituents at Acadia National Park on 20 Percent Best and Worst Visibility Day s

Notes: Light extinction from (a) sulfate, (b) nitrate, (c) carbonaceous matter (i.e., organic carbon mass or OCM and light absorbing carbon or LAC), and (d) co a rse mass, alongside estimated natural light extinction from those constituents.Tracking Visibility Progress, 2004

- 2011 Page 3

- 19



### Figure 3

- 16

. Range of Observed and Estimated Natural Light Extinction for Select Individual Constituents at Moosehorn Wilderness Area on 20 Percent Best and Worst Visibility Days

Notes: Light extinction from (a) sulfate, (b) nitrate, (c) carbonaceous matter (i.e., organic carbon mass or OCM and light absorbing carbon or LAC), and (d) co a rse mass, alongside estimated natural light extinction from those constituents.Tracking Visibility Progress, 2004

- 2011 Page 3

- 20



### Figure 3

- 17

. Range of Observed and Estimated Natural Light Extinction for Select Individual Constituents at Great Gulf Wilderness Area on 20 Percent Best and Worst Visibility Days

Notes: Light extinction from (a) sulfate, (b) nitrate, (c) carbonaceous matter (i. e., organic carbon mass or OCM and light absorbing carbon or LAC), and (d) co a rse mass, alongside estimated natural light extinction from those constituents.Tracking Visibility Progress, 2004

- 2011 Page 3

- 21



### Figure 3

- 18

. Range of Observed and Estimated Natural Light Extinction for Select Individual Constituents at Lye Brook Wilderness Area on 20 Percent Best and Worst Visibility Days

Notes: Light extinction from (a) sulfate, (b) nitrate, (c) carbonaceous matter (i.e ., organic carbon mass or OCM and light absorbing carbon or LAC), and (d) co a rse mass, alongside estimated natural light extinction from those constituents.Tracking Visibility Progress, 2004

- 2011 Page 3

- 22



### Figure 3

- 19

. Range of Observed and Estimated Natur al Light Extinction for Select Individual Constituents at Brigantine Wilderness Area on 20 Percent Best and Worst Visibility Days

Notes: Light extinction from (a) sulfate, (b) nitrate, (c) carbonaceous matter (i.e., organic carbon mass or OCM and light absorbing carbon or LAC), and (d) co a rse mass, alongside estimated natural light extinction from those constituents.Tracking Visibility Progress, 2004

- 2011 Page 3

- 23



## 3.3. Conclusions on Visibility Progress Despite variability in the year

- to

- year data, there are definite downward trends in overall haze levels at the Class I a reas in and adjacent to the MANE

- VU region . Based on rolling five

- year averages demonstrating progress since the 2000

- 2004 baseline period, the MANE

- VU Class I a reas appear to be on track to meet their 2018 RPGs for both best and worst visibility days. The trends are mainly driven by large reductions in sulfate light
ext inction, and to a les ser extent, nitrate light extinction. Levels of carbonaceous matter (OCM and LAC) appear to be approaching natural levels at most of the MANE

- VU Class I a reas . In some cases, the levels set by these goals have already been met, and
pro gress beyond the 2018 RPGs appears achievable. Though it is on track to meet its 2018 RPGs, challenges remain for the Brigantine Wilderness Area. Sulfate light extinction levels are higher at this site than at others across the region, and continued sulfat e reductio ns would be a significant driver in continuing to improve visibility at this site.Tracking Visibility Progress, 2004

- 2011 Page 4

- 1



## 4. DISCUSSION Reductions in air pollution continue to bring down levels of fine particulate matter in the eastern United States, which in turn are leading to improved visibility at federally protected Class I areas within and adjacent to the MANE

- VU region. Since our last report (NESCAUM 2010), significant improvements in visibility at the MANE

- VU Class I sites have been observed, and these changes have been largely dr iven by reductions in sulfate levels. Levels of nitrates and carbonaceous PM are also decreasing. Large emission reductions of nitrogen oxides (NOx) and sulfur dioxide (SO 2 

### ) across the region in response to regional emission reduction requirements for pow er plants is likely a principal driver for these visibility improvements. Further reductions over the next several years should occur if t he power sector continues to control or phase
out coal plants across the eastern United States in response to competit ive pressures from natural gas generation, overall reduced electricity demand, and more stringent requirements to reduce emissions of air toxics (e.g., acid gases, toxic me tals )

. In addition to addressing emissions from power plants , states across the Northeast have enacted or are in process of enacting low sulfur content requirements for fuel oil s, which cover home heating oil (distillate) and residual oil s (#4 and #6)

. At the federal level, US EPA has proposed the Tier 3 motor vehic le program that includes low ering sulfur content in gasoline. While gasoline combustion is a minor source of SO 2 

### emissions, the Tier 3 fuel requirements would significantly reduc e NOx emissions from the existing fleet of on

- road gasoline vehicles by reduci ng sulfur poisoning of the catalyst in catalytic converters, thus improving control technology performance . This w ould lead
to lower nitrate levels

, most notably during colder weather months when nitrates are more thermally stable

. In warmer weather months

, NOx promote s ground

- level ozone formation , which in turn can enhance formation of visibility

- limiting secondary organic aerosols (Carleton et al. 2010) . Therefore, lower levels of NOx as a result of Tier 3 can also improve visibility by reducing ozone formation that lead s to carbonaceous PM

. In summary, t he visibility data examined in this report demonstrate that broad, regional efforts to reduce emissions of visibility

- impairing pollutants are having a beneficial effect at the region’s Class I a reas

. The most recent IMPROVE data indicate that the states continue to be on track to meet their 2018 reasonable progress goals for improved visibility

. F urther progress may occur through additional pollution reductions achievable under recently adopted o r proposed regulatory programs.Tracking Visibility Progress, 2004

- 2011 Page 5

- 1



## 5. REFERENCES
Carleton, A.G., R.W. Pinder, P.V. Bhave, and G.A. Pouliot. 2010. To What Extent Can Biogenic SOA be Controlled? 44 Environ. Sci. Technol. 3376

- 3380, doi: 10.1021/es903506b

. IMPROVE. 2011. IMPROVE and RHR Summary Data. Available at: http://vista.cira.colostate.edu/improve/Data/IMPROVE/summary_data.htm

NESCAUM. 2010. Tracking Visibility Progress, 2004

- 2008 (2010). MANE

- VU Technical Memorandum, May 12, 2010 . Available at http://www.nescaum.org/documents/track ing

- progress

- final

- 05

- 12

- 10.pdf

Pietarinen, C. 2013. Conversation with Charles Pietarinen, Chief of the Bureau of Air Monitoring at the New Jersey Department of Environmental Protection on March 11, 2013. Mr. Pietarine n indicated that construction activity at the Brigantine Visitor’s Center

, which is very close to the monitor

, may have affected the monitoring site in recent years. P rescribed burns may also be having an influenc e at the site

.

US Environmental Protection Agency (USEPA). 2003a. Guidance for Estimating Natural Visibility Conditions Under the Regional Haze Rule. Research Triangle Park: Office of Air Quality Planning and Standards, September 2003. EPA

- 454/B

- 03

- 005.

US Environmental Protection Agency (USEPA). 2 003b. Guidance for Tracking Progress Under the Regional Haze Rule. Research Triangle Park: Office of Air Quality Planning and Standards, September 2003. EPA

- 454/B

- 03

- 004.Tracking Visibility Progress, 2004

- 2011 Page A

- 1



# Appendix A: Tracking Progress Data for Class I Areas in and Adjacent to the MANE

- VU RegionTracking Visibility Progress, 2004

- 2011 Page A

- 2



## Appendix A: Tracking Progress Data for Class I Areas in and Adjacent to the MANE

- VU Region Tracking progress data for sites in the MANE

- VU region are presented in Table A

- 1, and for sites adjacent to it in Table A

- 2.

Table A

- 1

. Tracking Progress Data for Class I Areas in and Adjacent to the MANE

VU Region (dv)

Class I Area Year Best Days Worst Days Haze Index, Annual Haze Index, 5

-

Year Rolling Haze Index,

Annual Haze Index, 5

-

Year Rolling Acadia National Park 2000 8.90

- 21.64

- 2001 8.87

- 23.28

- 2002 8.77

- 23.91

- 2003 8.77

- 23.65

- 2004 8.56 8.78 21.98 22.89 2005 7.58 8.51 23.01 23.17 2006 8.17 8.37 23.37 23.19 2007 8.21 8.26 21.74 22.75 2008 7.76 8.06 20.21 22.06 2009 6.92 7.73 18.93 21.45 2010 6.57 7.53 18.16 20.48 2011 7.35 7.36 18.80 19.57 Moosehorn Wilderness Area 2000 8.94

- 20.63

- 2001 9.31

- 22.14

- 2002 9.12

- 23.07

- 2003 9.48

- 22.50

- 2004 8.93 9.16 20.28 21.72 2005 7.99 8.97 22.36 22.07 2006 8.60 8.82 21.55 21.95 2007 7.79 8.56 19.24 21.19 2008 7.75 8.21 18.73 20.43 2009 6.83 7.79 17.71 19.92 2010 5.85 7.37 17.09 18.87 2011 6.84 7.01 17.07 17.97 Great Gulf Wilderness Area 2000

- - 2001 8.26

- 23.29

- 2002 7.77

- 24.84

- 2003 6.94

- 21.59

- 2004 7.68 7.66 21.56 22.82 2005 6.90 7.51 21.53 22.56 2006 6.43 7.14 21.12 22.13 2007 6.86 6.96 21.35 21.43 2008 6.20 6.81 16.78 20.47 2009 * 6.60 * 20.19 2010 * 6.50 * 19.75 2011 6.15 6.40 18.96 19.03 Symbols: “

- ” = not applicable; “ * ” = m issing data; “ † ” = Class I Area adjacent to the MANE

- VU region
Table continued on next page.Tracking Visibility Progress, 2004

- 2011 Page A

- 3



### Table A

- 1

. Tracking Progress Data for Class I Areas in and Adjacent to the MANE

VU Region (dv) , continued

Best Days Worst Days

Class I Area Year Haze Index, Annual Haze Index, 5

-

Year Rolling Haze Index,

Annual Haze Index, 5

-

Year Rolling Lye Brook Wilderness Area 2000 6.49

- 23.45

- 2001 6.47

- 26.33

- 2002 6.43

- 25.52

- 2003 5.83

- 24.02

- 2004 6.61 6.37 22.91 24.45 2005 5.74 6.22 26.04 24.96 2006 5.24 5.97 22.31 24.16 2007 5.68 5.82 25.25 24.11 2008 * 5.82 * 24.13 2009 4.11 5.19 18.44 23.01 2010 3.96 4.75 19.88 21.47 2011 5.28 4.76 19.47 20.76 Brigantine Wilderness Area 2000 14.26

- 28.95

- 2001 13.83

- 28.38

- 2002 14.83

- 29.31

- 2003 14.39

- 29.79

- 2004 14.36 14.33 28.59 29.01 2005 14.61 14.40 29.62 29.14 2006 15.35 14.71 28.50 29.16 2007 12.74 14.29 26.91 28.68 2008 * 14.26 * 28.41 2009 12.78 13.87 24.25 27.32 2010 11.70 13.14 25.22 26.22 2011 12.78 12.50 25.78 25.54 Dolly Sods Wilderness Area† 2000 12.96

- 29.03

- 2001 13.30

- 28.24

- 2002 11.91

- 28.47

- 2003 11.54

- 29.73

- 2004 11.67 12.28 29.76 29.05 2005 12.09 12.10 30.89 29.42 2006 10.57 11.56 29.80 29.73 2007 10.27 11.23 29.52 29.94 2008 9.44 10.81 25.39 29.07 2009 8.70 10.21 22.17 27.55 2010 9.62 9.72 23.94 26.16 2011 8.67 9.34 24.44 25.09 Shenandoah National 2000 11.08

- 28.53

- Park † 2001 13.21

- 29.21

- 2002 11.49

- 30.54

- 2003 9.48

- 28.94

- 2004 9.37 10.93 29.32 29.31 2005 10.48 10.81 30.75 29.75 2006 10.59 10.28 29.30 29.77 2007 11.13 10.21 28.79 29.42 2008 8.16 9.95 25.65 28.76 2009 8.23 9.72 21.81 27.26 2010 9.67 9.56 23.44 25.80 2011 7.80 9.00 23.42 24.62 Symbols: “

- ” = not applicable; “ * ” = missing data; “ † ” = Class I Area adjacent to the MANE

- VU regionNH Regional Haze 5

- Year Progress Report



### ATTACHMENT C

Overview of State and Federal Actions Relative to MANE

- VU AsksNH Regional Haze 5

- Year Progress Report



### This page is intentionally le ft blank.

### 1 

# Memorandum

Date: March 28, 2013

To: MANE-VU
From: Paul Miller, NESCAUM

Re: Overview of state and federal actions relative to MANE-VU Asks

This memorandum provides a summary of certain eleme nts in regional haze state implementation plans (SIPs) within and outside the Mid-Atlantic/Northeast Visibility (MANE-VU) regional planning area. 1 

### The SIPs covered are either from members of the MANE-VU regional planning organization (RPO), or fr om states outside the MANE-VU region that were identified as having emissions con tributing 2% or more to sulfate levels at MANE-VU Class 1 areas.

The elements reviewed in each regional haze SIP wer e in the context of requests from MANE-VU in 2007 that certain measures, or their equ ivalents, be adopted within each jurisdiction by 2018 (referred to as the “MANE-VU A sks”). MANE-VU deemed these measures as appropriate for making reasonable progr ess towards achieving the national goal of natural background visibility in Class 1 ar eas by 2064. The MANE-VU Asks differed in some respects between the MANE-VU membe rs and states outside of the MANE-VU region, but were intended to encompass comp arable sulfur dioxide (SO 2 

### ) measures across all states. The specific elements of the MANE-VU Asks for inside and outside the MANE-VU region are given below accordin g to two groupings of SIPs from inside and outside the MANE-VU region.

A common Ask element inside and outside the MANE-VU region was for a 90% or greater SO 2 

### emissions reduction by 2018 relative to 2002 from 167 electric generating unit (EGU) stacks. MANE-VU identified these specif ic stacks through modeling as having the largest impacts on visibility in its Cla ss 1 areas among all modeled EGUs. This Ask element included flexibility for achieving the 90% reduction through alternative measures if not feasible at the stack.

This summary provides a “snap shot” of SO 2 

### emissions in 2011 at the individual stacks on the 167 EGU list. To provide additional context of state-wide reductions from

1 NESCAUM thanks the following people for helpful as sistance in reviewing and commenting on the state summaries: Robert Betterton, WV Department of Envir onmental Protection; James Boylan, GA Department of Natural Resources; John Hornback, SES ARM; Wendy Jacobs, CT Department of Energy and Environmental Protection; Joseph Jakuta, OTC; R ob Kaleel, LADCO; Glenn Keith, MA Department of Environmental Protection; Martin Luther, KY Divisio n for Air Quality; Charles Martone, NH Department of Environmental Services; Julie McDill, MARAMA; Do ris McLeod, VA Department of Environmental Quality; Anne McWilliams, EPA Region 1; Albert Pear ce, GA Department of Natural Resources; John Sipple, DE Department of Natural Resources and Envi ronmental Control; Roger Thunell, MD Department of the Environment.

### 2

potential “alternative measures,” we also use EPA’s Acid Rain Program data to compare overall state-wide SO 2 

### reductions occurring in 2011 relative to 2002 agai nst the requested amount from a state’s stacks on the 167 EGU stack l ist. The comparison uses reported emissions from the Acid Rain Program rather than fr om the Clean Air Interstate Rule (CAIR) because not all states receiving a MANE-VU A sk are covered by CAIR. In addition, emissions reporting under CAIR started se veral years after the 2002 MANE-VU Ask baseline. A state-level comparison of 2011 SO 2 

### emissions reported in the Acid Rain Program and in the CAIR program found that reported SO 2 

### emissions in both programs were within about 5% for most states.

In addition to the MANE-VU Asks for states, MANE-VU also presented a federal ask to the U.S. Environmental Protection Agency (EPA) for additional national SO 2 

### reductions from power plants. The current status of federal e fforts is summarized in the third section of this memorandum.



## 1. INSIDE MANE-VU REGION

For the MANE-VU members, the “MANE-VU Ask” requeste d the following actions:

• Timely implementation of BART requirements; and

• A low sulfur fuel oil strategy in the inner zone St ates (New Jersey, New York, Delaware and Pennsylvania, or portions thereof) to reduce the sulfur content of: distillate oil to 0.05% sulfur by weight (500 ppm) by no later than 2012, of #4 residual oil to 0.25% sulfur by weight by no later than 2012, of #6 residual oil to 0.3 – 0.5% sulfur by weight by no later than 2012, and to further reduce the sulfur content of distillate oil to 15 ppm by 2016; and

• A low sulfur fuel oil strategy in the outer zone St ates (the remainder of the MANE-VU region) to reduce the sulfur content of dis tillate oil to 0.05% sulfur by weight (500 ppm) by no later than 2014, of #4 resid ual oil to 0.25 – 0.5% sulfur by weight by no later than 2018, and of #6 residual oil to no greater than 0.5% sulfur by weight by no later than 2018, and to furt her reduce the sulfur content of distillate oil to 15 ppm by 2018, depending on supp ly availability; and

• A 90% or greater reduction in sulfur dioxide (SO 2 

### ) emissions from each of the top 100 electric generating units (EGUs) identified by MANE-VU (comprising a total of 167 stacks) as reasonably anticipated to c ause or contribute to impairment of visibility in each mandatory Class 1 Federal are a in the MANE-VU region. If it is infeasible to achieve that level of reduction from a unit, alternative measures will be pursued in such State; and

• Continued evaluation of other control measures incl uding energy efficiency, alternative clean fuels, and other measures to redu ce SO 2 

### and nitrogen oxide (NOx) emissions from all coal-burning facilities by 2018 and new source performance standards for wood combustion. These m easures and other measures

### 3 identified will be evaluated during the consultatio n process to determine if they are reasonable and cost-effective.



## Connecticut Submittal Date of Regional Haze SIP November 18, 2009; February 24, 2012; March 12, 201 2; November 23, 2012

Haze SIP Status as of January 24, 2013 EPA proposed approval, 77 FR 17367 (March 26, 2012) ; EPA supplemental proposed approval, 78 FR 5158 (January 24, 2013); final by A pril 26, 2013 (under extended consent decree). 2



### BART Requirements Connecticut identified an initial list of ten BART- eligible sources. Three BART-eligible sources were subsequently capped by consent order a t below BART-eligible levels, removing them from the list. Connecticut determine d that its existing rules achieved greater reductions from its remaining BART-eligible sources than from application of BART alone.

Low Sulfur Oil Strategy Inner Zone Does not apply.

Low Sulfur Oil Strategy Outer Zone Connecticut adopted low sulfur fuel oil rules and s tatute but implementation of the statute is contingent upon adoption of rules by Massachuset ts (enacted), New York (enacted), and Rhode Island (not yet proposed).

90% SO 2 

### reduction of 167 EGU stacks Does not have listed stack.

Evaluation of other control measures Connecticut agreed to continue evaluating other pos sible control measures consistent with the MANE-VU Ask, including investigating succe ss of other state programs regulating outdoor wood burning furnaces, and adopt ion of the California Low Emission Vehicle (CA LEV) program revisions for mobile sourc es.



## Delaware Submittal Date of Regional Haze SIP September 25, 2008

Haze SIP Status as of December 18, 2012 EPA final approval, 76 FR 42557 (July 19, 2011)

BART Requirements

2 Communication from David Conroy, EPA Region 1 (Dec ember 18, 2012).

### 4

Delaware identified four EGUs and one steel mill as BART-eligible sources. Delaware established enforceable caps for the steel mill to limit emissions below BART-eligible levels. Delaware also considers that in the aggreg ate, DE Regulation 1146 achieves greater reductions from its EGUs than would be achi eved by applying presumptive BART on the BART-eligible EGUs.

Low Sulfur Oil Strategy Inner Zone Delaware has not yet adopted low sulfur fuel strate gy, but considers equivalent reductions met by including SO 2 

### reductions from all Delaware EGUs (in excess of 90 % reductions).

Low Sulfur Oil Strategy Outer Zone Does not apply.

90% SO 2 

### reduction of 167 EGU stacks Delaware has five stacks at two power plants among the MANE-VU 167 EGU stacks list. Delaware indicated that the 90% reduction in SO 2 

### from the Edge Moor Unit 5 and Indian River Units 1-4 was relative to a baseline of calen dar year 2002 actual SO 2 

### mass emissions levels from those units. Based on the ac tual 2002 SO 2 

### mass emissions from the subject Delaware EGUs, and applying the 90% red uction factor, Delaware determined that the actual SO 2 

### reduction obligation for those units was 19,909 to ns/year. However, Delaware’s analysis indicated that it was not feasible to achieve an SO 2 

### mass emissions reduction of 19,909 tons/year from Edge M oor Unit 5 and Indian River Units 1-4 alone. Alternatively, in the 2008 Visibility S IP document Delaware indicated that SO 2 

### emissions reductions from all of the EGU units aff ected by Delaware’s 7 DE Admin Code 1146, Electric Generating Unit (EGU) Multi-Pol lutant Regulation, would exceed 19,909 tons of annual SO 2 

### reductions. Delaware indicated that the SO 2 

### emissions reductions achieved by 7 DE Admin Code 1146 demonst rated that Delaware had met its obligation. Subsequent to the promulgation of 7 DE Admin Code 1146 (and Delaware’s 2008 SIP submittal), units subject to the regulatio n have come into compliance with the regulation in 2009 and 2012 (phase-in), or have com e into compliance with consent decrees and permanent, federally enforceable permit conditions related to the regulation. Beginning in 2011, the annual SO 2 

### emission reductions of 21,906 tpy have exceeded th e 2018 target level of 19,909 tpy (7 years early). T his is consistent with reported emissions in the Acid Rain Program.

Evaluation of other control measures Delaware is evaluating diversity of fuels for energ y needs, electricity conservation programs, and efficient energy infrastructure, alon g with encouraging new energy efficient product makers and promoting renewables, among other measures.



## District of Columbia 3 

### Submittal Date of Regional Haze SIP

3 The District of Columbia contributes less than 0.1 μg/m 3 or 2% sulfate at nearby Class 1 areas, so its long-term strategy consists of adopting the control measures in the MANE-VU “on-the-books/on-the-way” scenario and meeting the BART requirements.

### 5

October 27, 2011

Haze SIP Status as of December 18, 2012 EPA final approval, 77 FR 5191 (February 2, 2012)

BART Requirements The District of Columbia has two BART-eligible sour ces that were to shut down by December 17, 2012.

Low Sulfur Oil Strategy Inner Zone Does not apply.

Low Sulfur Oil Strategy Outer Zone No rule proposed.

90% SO 2 

### reduction of 167 EGU stacks Does not have listed stack.

Evaluation of other control measures The District of Columbia plans to continue to pursu e adoption of MANE-VU measures in “beyond-on-the-way” (BOTW) and “best and final” sce narios by 2018, as appropriate and necessary.



## Maine Submittal Date of Regional Haze SIP December 9, 2010; supplemented September 14, 2011, November 9, 2011

Haze SIP Status as of December 18, 2012 EPA final approval, 77 FR 24385 (April 24, 2012)

BART Requirements Maine identified 10 BART-eligible sources, and dete rmined all 10 were subject to BART. In 2007, ME legislature adopted BART require ments and deadlines. BART controls must be installed and operating by January 1, 2013 and either (1) require low sulfur oil (1% or less) or (2) be equivalent to a u nit-specific 50% reduction in sulfur emissions from baseline. Three BART sources capped out under permit limits. Maine determined that existing controls and lower sulfur oil (where applicable) satisfied BART for the remaining sources.

Low Sulfur Oil Strategy Inner Zone Does not apply.

Low Sulfur Oil Strategy Outer Zone Legislation passed. Distillate = 50 ppm in 2016; 1 5 ppm in 2018. #6 Fuel - 0.5% in 2018.

### 6

90% SO 2 

### reduction of 167 EGU stacks Maine has one stack on MANE-VU 167 stacks list. Ma ine determined it was not costeffective to add controls to the unit, and will use lower sulfur fuel to comply by 2013. Low sulfur fuel will get an 84% reduction. In 2011 , the unit had SO 2 

### emissions 76% lower than its 2002 levels, and greater than 90% lo wer when including additional SO 2 

### reductions from other units at the same power plant . EPA Acid Rain Program data indicate that state-wide SO 2 

### reductions in 2011 exceeded the MANE-VU Ask amount by 48%.

Evaluation of other control measures Maine has adopted rules on outdoor wood and pellet boilers, an outdoor wood boiler replacement and buy-back program, and a wood stove replacement buy-back program.



## Maryland Submittal Date of Regional Haze SIP February 13, 2012

Haze SIP Status as of December 18, 2012 EPA final approval, 77 FR 39938 (July 6, 2012).

BART Requirements Maryland identified four EGUs and three non-EGUs as BART-eligible. Of the three nonEGUs, one was determined to not be a BART source ba sed on start up date, one had existing and future selective non-catalytic reducti on (SNCR) controls considered to satisfy BART, and one had additional requirements p ut in place to satisfy BART. For EGU BART-eligible sources, Maryland accepted existi ng controls and measures as satisfying BART on all units.

Low Sulfur Oil Strategy Inner Zone Does not apply.

Low Sulfur Oil Strategy Outer Zone No rule proposed. Maryland committed to pursuing a low sulfur fuel oil strategy as apporpriate and necessary.

90% SO 2 

### reduction of 167 EGU stacks Maryland has nine stacks (12 units) at six power pl ants listed among the MANE-VU 167 stacks. Maryland’s approach to the 90% MANE-VU Ask from its listed stacks is to use the state’s Healthy Air Act (HAA) as approved in it s SIP. Maryland operated from a total emissions baseline for the state’s EGU units identified by the MANE-VU Ask. Maryland arrived at the total emissions needed to s atisfy the Ask by totaling the 2002 base year emissions for the state’s units on the 16 7 list and multiplying by 90%. This number is 211,892 tpy of SO 2 

### . In 2011, Maryland achieved 208,941 tpy of reduct ions from the units in question and an additional 6,671 tpy from units regulated by the HAA but not included in the MANE-VU Ask. Maryland stat es that the Maryland HAA is

### 7

obtaining SO 2 

### reductions in excess of the 90% MANE-VU Ask before 2018. This is consistent with reported emissions in the Acid Rain Program.

Evaluation of other control measures Maryland committed to evaluating other measures per MANE-VU Ask. Maryland also cited the Maryland Strategic Energy Investment Fund as a funding source for renewables and energy efficiency.



## Massachusetts Submittal Date of Regional Haze SIP December 30, 2011; supplemented August 9, 2012; Aug ust 28, 2012

Haze SIP Status as of December 18, 2012 EPA final approval signed in September 2012; FR not ice pending. 4



### BART Requirements Massachusetts identifed nine power plants and eight non-EGUs as BART-eligible, and subsequently subject to BART. Seven BART sources w ere determined to have de minimis impacts and did not justify controls. Massachuset ts adopted an Alternative to BART program achieving greater emissions reductions than source-by-source BART for EGUs (permit restriction, cap, retirement, low sulf ur fuel). Massachusetts determined additional SO 2 

### control for one non-EGU BART source was not cost-e ffective and would have minimal impact on visibility. Volatile organi c compounds (VOCs) from three petroleum storage facilities were addressed under M assachusetts’ ozone SIPs rather than BART.

Low Sulfur Oil Strategy Inner Zone Does not apply.

Low Sulfur Oil Strategy Outer Zone Massachusetts adopted rules for 15 ppm sulfur #2 oi l, and 0.5% sulfur by weight for #4 and #6 residual oils by 2018.

90% SO 2 

### reduction of 167 EGU stacks Massachusetts has 10 stacks at five power plants on the MANE-VU 167 stacks list. Massachusetts estimates that based on its Alternati ve to BART, EPA’s Mercury and Air Toxics Standards (MATS), and EGU closures, 2018 EGU SO 2 

### emissions will be 87% lower than 2002 emissions. In 2011, seven stacks h ad SO 2 

### emissions more than 90% lower than 2002 levels when including plant-wide em ission reductions at the stacks. The remaining three stacks were 50-80% lower in 2011. EPA Acid Rain Program data indicate that state-wide SO 2 

### reductions in 2011 were 94% of the MANE-VU Ask amo unt.

Evaluation of other control measures

4 Communication from David Conroy, EPA Region 1 (Dec ember 18, 2012).

### 8

Massachusetts is implementing controls on outdoor w ood-fired boilers. Massachusetts will pursue other reasonable and cost-effective mea sures as needed.



## New Hampshire Submittal Date of Regional Haze SIP January 29, 2010; supplemented January 14, 2011; Au gust 26, 2011

Haze SIP Status as of December 18, 2012 EPA final approval, 77 FR 50602 (August 22, 2012)

BART Requirements New Hampshire has two BART-eligible sources: Merrim ack Unit 2 and Newington Unit 1, and both are included in the MANE-VU 167 stacks list. Control measures for these sources are described below in the 167 EGU stacks s ection. New Hampshire adopted BART in New Hampshire rule Env-A 2300: Mitigation o f Regional Haze; effective date January 8, 2011.

Low Sulfur Oil Strategy Inner Zone Does not apply.

Low Sulfur Oil Strategy Outer Zone New Hampshire made commitment to continue evaluatin g strategy. No rule proposed.

90% SO 2 

### reduction of 167 EGU stacks New Hampshire has three stacks at two power plants listed among the MANE-VU 167 stacks.

Merrimack Unit 1: No specific SO 2 

### limit given in haze SIP. Page 118 of the New Hampshire regional haze SIP indicates Merrimack Uni t 1 required by rule to reduce mercury by 80% with flue gas desulfurization (FGD) that has an expected 90% minimum co-benefit in SO 2 

### reduction. 2011 SO 2 

### emissions were 17% below 2002 levels.

Merrimack Unit 2: Requires FGD operated at maximum sustainable reduction rate, but not less than 90% calendar month average, to be acc omplished by July 1, 2013. 2011 SO 2 

### emissions were 32% below 2002 levels.

New Hampshire expects that controls at the Merrimac k units will exceed the 90% MANE-VU Ask request.

Newington Unit 1: Requires an SO 2 

### limit of 0.50 lb/MMBtu by July 1, 2013; 2002 rate was 1.08 lb/MMBtu. 2011 SO 2 

### emissions were 94% below 2002 levels, in part due to lower utilization. New Hampshire determined that a n enforceable 90% MANE-VU Ask reduction at this unit was not reasonable at this t ime.

EPA Acid Rain Program data indicate that state-wide SO 2 

### reductions in 2011 were 60% of the MANE-VU Ask amount.

### 9

Evaluation of other control measures New Hampshire is seeking alternative measures for N ewington Unit 1, including >90% SO 2 

### reduction at Merrimack Station, possible additiona l controls on other coal-burning units, and use of low sulfur fuel oil (p. 27 and Lo ng Term Strategy, NH haze SIP).



## New Jersey Submittal Date of Regional Haze SIP July 28, 2009; supplemented December 9, 2010; March 2, 2011; December 7, 2011

Haze SIP Status as of December 18, 2012 EPA final approval, 77 FR 19 (January 3, 2012)

BART Requirements New Jersey identified four refineries and one EGU ( Hudson) as BART-eligible and subject to BART. New Jersey believes that the stat e’s adopted rules in its 8-hour ozone and PM 2.5 

### SIPs along with consent decrees to address NOx, SO 2 

### , and particulate matter (PM) at these sources will likely address BART. 5 

### New Jersey did not rely on CAIR for the Hudson EGU (also a 167 EGU stack).

Low Sulfur Oil Strategy Inner Zone The New Jersey regional haze SIP stated an intent t o propose and adopt low sulfur rules in accordance with the MANE-VU Ask. Current rule N .J.A.C. 7:27-9 already meets #6 fuel oil sulfur levels in parts of state. New Jers ey proposed a low sulfur fuel oil rule on April 4, 2011. The rule now is in effect and will meet MANE-VU Ask sulfur levels by July 1, 2016.

Low Sulfur Oil Strategy Outer Zone Does not apply.

90% SO 2 

### reduction of 167 EGU stacks New Jersey has four stacks among the MANE-VU 167 st acks list. New Jersey indicates that existing orders on all four will result in mor e than a 90% SO 2 

### reduction by December 15, 2012. All four New Jersey stacks had 2011 SO 2 

### emissions more than 90% below 2002 levels. This is consistent with reported emis sions in the Acid Rain Program.

Evaluation of other control measures New Jersey cites draft Energy Master Planning as in cluding ways to increase energy efficiency. It also cites the state’s Global Warmi ng Response Act signed in 2007 that will decrease greenhouse gases, which will help red uce haze pollutants. New Jersey lists a number of other measures under consideration that would address fugitive dust, open burning, residential wood burning, VOCs, and diesel exhaust.



## New York

5 One refinery (Hess Port Reading) has since announ ced plans to shut down by the end of February 2013.

### 10

Submittal Date of Regional Haze SIP March 15, 2010; supplemented August 2, 2010; April 16, 2012; July 2, 2012

Haze SIP Status as of December 18, 2012 EPA partial approval 17 BART sources/partial disapp roval 2 BART sources, 77 FR 51915 (August 28, 2012)

BART Requirements New York required source-specific analysis of all B ART-eligible sources. BARTeligible EGUs under CAIR were not exempted from BAR T analysis. EPA approved 17 source-specific SIP revisions for New York’s BART s ources, and issued FIPs for 2 additional BART sources.

Low Sulfur Oil Strategy Inner Zone New York committed to adopting low sulfur fuel oil rules under 6 NYCRR Part 225, and adopted the rules subsequent to the state’s regiona l haze SIP submittal. A 15 ppm heating oil requirement became effective in 2012. The remaining distillates’ effective date is in 2014.

Low Sulfur Oil Strategy Outer Zone Does not apply.

90% SO 2 

### reduction of 167 EGU stacks New York has 11 stacks listed among the MANE-VU 167 stacks list. With the exception of the Oswego unit, all listed New York stacks were expected to either shut down or be controlled in range of 80-95% for SO 2 

### . In the aggregate, accounting for shutdowns, controls, and new EGUs, New York expects to achieve the 90% MANE-VU Ask. 2011 SO 2 

### emissions at most of the state’s listed stacks wer e at or approaching levels more than 90% below 2002 emissions at the individual stack, o r were greater than 90% below when including SO 2 

### reductions/shutdowns at other units at the same fa cility. EPA Acid Rain Program data indicate that state-wide SO 2 

### reductions in 2011 exceeded the MANE-VU Ask amount by 27%.

Evaluation of other control measures New York was to continue evaluating energy efficien cy, alternative clean fuels, and other measures to reduce NOx and SO 2 

### at all coal-burning facilities, and new source performance standards for wood combustion. New Yor k was also pursuing VOC measures under its ozone SIPs.



## Pennsylvania Submittal Date of Regional Haze SIP December 20, 2010

Haze SIP Status as of December 18, 2012 EPA limited approval, 77 FR 41279 (July 13, 2012); EPA limited disapproval with FIP to replace CAIR with CSAPR, 77 FR 33642 (June 7, 2012)

### 11

BART Requirements Pennsylvania accepted CAIR as BART for EGU NOx and SO 2 

### . Pennsylvania made BART determinations for EGU particulate matter (PM) and all non-EGU BART-eligible sources that did not elect to be not BART-eligible through permit limitations. Pennsylvania determined that existing controls at a ll BART-eligible sources met BART requirements.

Low Sulfur Oil Strategy Inner Zone Pennsylvania committed to a low sulfur fuel strateg y not less stringent than the outer zone MANE-VU Ask, based on supply concerns. It pro posed a rule in September 2010, with a full effective date by 2016.

Low Sulfur Oil Strategy Outer Zone Does not apply.

90% SO 2 

### reduction of 167 EGU stacks Pennsylvania has 15 stacks among the MANE-VU 167 st acks. In 2011, SO 2 

### emissions at 2 of the 15 stacks were more than 90% below 2002 l evels. The remaining 13 stacks all had lower 2011 SO 2 

### emissions than in 2002 at levels less than a 90% r eduction. EPA Acid Rain Program data indicate that state-wide SO 2 

### reductions in 2011 equaled the MANE-VU Ask amount.

Evaluation of other control measures Pennsylvania lists a number of measures being under taken in on-going programs that can address haze, including refinery consent decrees, r ulemakings on cement kilns and glass furnaces, and state energy initiatives to address p eak demand days, and promote renewables, energy efficiency, and energy conservat ion.



## Rhode Island Submittal Date of Regional Haze SIP August 7, 2009

Haze SIP Status as of December 18, 2012 EPA final approval, 77 FR 30214 (May 22, 2012)

BART Requirements Does not have BART-eligible sources.

Low Sulfur Oil Strategy Inner Zone Does not apply.

Low Sulfur Oil Strategy Outer Zone Rhode Island made a SIP commitment to adopt a low s ulfur rule consistent with the MANE-VU Ask for the outer zone. A rule has not yet been proposed as of December 18, 2012.

### 12

90% SO 2 

### reduction of 167 EGU stacks Does not have listed stack.

Evaluation of other control measures Rhode Island stated an intent to adopt all reasonab le control measures as expeditiously as practicable consistent with state law within 10 yea r planning period. It cited a possible state law to address outdoor wood boilers.



## Vermont Submittal Date of Regional Haze SIP August 26, 2009; supplemented January 3, 2012

Haze SIP Status as of December 18, 2012 EPA final approval, 77 FR 30212 (May 22, 2012)

BART Requirements Does not have BART-eligible sources.

Low Sulfur Oil Strategy Inner Zone Does not apply.

Low Sulfur Oil Strategy Outer Zone Vermont adopted low sulfur fuel oil requirements in the “Vermont Energy Act of 2011.” Full implementation wil be by July 1, 2018.

90% SO 2 

### reduction of 167 EGU stacks Does not have listed stack.

Evaluation of other control measures Vermont stated an intent to continue investigating cleaner sources of energy.

### 13



## 2. 

## OUTSIDE MANE-VU REGION

For states outside the MANE-VU region, the “MANE-VU Ask” requested:

• Timely implementation of BART requirements;

• A 90% or greater reduction in sulfur dioxide (SO 2 

### ) emissions from each of the top 100 electric generating units (comprising a total o f 167 stacks) impacting any mandatory Class 1 Federal area in the MANE-VU regio n, or an equivalent SO 2 

### reduction from alternative measures within each Sta te;

• The application of reasonable controls on non-EGU s ources resulting in a 28% reduction in non-EGU SO 2 

### emissions, relative to on-the-books, on-the-way 20 18 projections used in regional haze planning, by 2018 , which is equivalent to the projected reductions MANE-VU will achieve through i ts low sulfur fuel oil strategy;

• Continued evaluation of other measures including me asures to reduce SO 2 

### and nitrogen oxide (NOx) emissions from all coal-burnin g facilities by 2018 and promulgation of new source performance standards fo r wood combustion. These measures and other measures identified will be eval uated through consultation processes to determine if they are reasonable.



## Georgia 6 

### Submittal Date of Regional Haze SIP February 11, 2010; supplemented September 19, 2010

Haze SIP Status as of December 18, 2012 EPA limited approval, 77 FR 38501 (June 28, 2012); EPA limited disapproval with FIP to replace CAIR with CSAPR, 77 FR 33642 (June 7, 20 12)

BART Requirements Georgia accepted CAIR as BART for EGU NOx and SO 2 

### . Georgia identified 24 BARTeligible sources, which included EGUs for PM only, and accepted exemption

6 When contacted by MANE-VU states before the releas e of the “MANE-VU Ask” letters, The Georgia Environmental Protection Division (Georgia EPD) had the following response to those states:

Georgia EPD is a member of the VISTAS Regional Plan ning Organization. Based on VISTAS SO 2 emissions sensitivity modeling for 2009 and VISTAS SO 2 Area of Influence (AOI) work for 2018, we have concluded that Georgia does not reaso nably contribute to visibility impairment at [MANE-VU] Class I Area[s]. Furthermore, it should be noted that Georgia EPD is currently in the process of requiring 95% SO 2 controls to be installed on the seven largest coal fired power plants in Georgia. Not all of these controls were accounted for in the SO 2 emissions sensitivity modeling or the SO 2 AOI work; therefore, Georgia’s contributions to [M ANE-VU] Class I areas in these analyses will be a conservative upper boun d leading to our conclusion that Georgia EGU and non-EGU SO 2 sources do not reasonably contribute to visibility impairment at [MANE-VU Class I Areas].

### 14

demonstrations from 22 of the 24 BART-eligible sour ces based on a 0.5 dv contribution threshold. A paper facility was required to use na tural gas in one boiler. All other available BART control options were deemed not cost effective. The second BART facility was an EGU (Bowen), and no available BART control options for PM were deemed cost effective.

90% SO 2 

### reduction of 167 EGU stacks Georgia has five stacks at two power plants listed in the MANE-VU Ask. Four of the stacks carry emissions from Bowen Units 1 through 4 . The fifth stack carries the combined emissions from Harllee Branch Units 3 and 4. Georgia Rule 391-3-1- .02(2)(uuu) requires 95% removal of SO 2 

### from Bowen Units 1- 4 no later than January 1, 2012, and from Harllee Branch Units 1 – 4 no later than January 1, 2016. 7 

### Since the filing of the Georgia haze SIP, Georgia Power Compa ny has filed requests to decommission Harllee Branch Units 1 and 2 in 2013 a nd Units 3 and 4 in 2015. In 2011, SO 2 

### emissions from the four units at Bowen were greate r than 90% below 2002 emissions, with 2011 emissions at the Harllee Branc h units about 25% below 2002 levels. EPA Acid Rain Program data indicate that state-wide SO 2 

### reductions in 2011 exceeded the MANE-VU Ask amount by 73%.

28% SO 2 

### reduction in non-EGU emissions Georgia required lower SO 2 

### permit limits for eight emissions units at five no n-EGU facilities based on four-factor analysis. Georgia also required lower SO 2 

### permit emissions rates for two emissions units at one non- EGU facility for the purpose of BART exemption. Overall, 8,223 tons of SO 2 

### reductions are required between 2012 and 2018, which is approximately 15% of 2002 non-EGU facility SO 2 

### emissions. 7



### Evaluation of other control measures No additional measures listed for further evaluatio n.



## Illinois Submittal Date of Regional Haze SIP June 24, 2011

Haze SIP Status as of December 18, 2012 EPA final approval, 77 FR 39943 (July 6, 2012)

BART Requirements Ilinois identified nine EGUs and two refineries as subject to BART. Illinois did not rely on CAIR for BART, and applied standards more string ent than CAIR to affected EGUs. Illinois considers federal consent decrees for the two refineries as BART for NOx and SO 2


### .

90% SO 2 

### reduction of 167 EGU stacks

7 Communication from Georgia EPD – Air Protection Br anch (March 5, 2013).

### 15

Illinois has one stack listed among the MANE-VU 167 stacks. The identified stack at Ameren-Coffeen has selective catalytic reduction (S CR) that will operate year-round, and a wet scrubber to comply with Illinois’ multi-pollu tant standards. Illinois states that the level of control required on the power plant will s atisfy the MANE-VU Ask. In 2011, SO 2 

### emissions at the Ameren-Coffeen stack were more th an 90% less than 2002 levels. EPA Acid Rain Program data indicate that state-wide SO 2 

### reductions in 2011 exceeded the MANE-VU Ask amount by 267%.

28% SO 2 

### reduction in non-EGU emissions Illinois expects on-the-books federal and state con trol measures will achieve sufficient reductions to satisfy MANE-VU Ask. Reductions not quantified.

Evaluation of other control measures No additional measures listed for further evaluatio n.



## Indiana Submittal Date of Regional Haze SIP January 14, 2011; March 10, 2011

Haze SIP Status as of December 18, 2012 EPA limited approval, 77 FR 34218 (June 11, 2012); EPA limited disapproval with FIP to replace CAIR with CSAPR, 77 FR 33642 (June 7, 20 12)

BART Requirements Indiana identified 32 BART-eligible sources, which included EGUs. Initial analysis determined four non-EGU facilities and nine power p lants were subject to BART. Of the four non-EGU BART sources, Indiana determined three were exempt based on additional modeling, and required BART measures on the fourth. For the power plants, Indiana accepted CAIR as BART for NOx and SO 2 

### , and determined one EGU remained subject to BART for PM only (Alcoa Boiler 4). Indiana adop ted a BART rule in 2010 for the EGU with a PM emission rate of 0.1 lb/MMBtu using a n ESP.

90% SO 2 

### reduction of 167 EGU stacks Indiana has 15 stacks at 9 power plants listed in t he MANE-VU Ask; most of these stacks have or will have post-combustion emission controls (i.e., scrubbers). In 2011, 9 of the 15 listed stacks had SO 2 

### emissions more than 90% below 2002 levels. Anothe r three stacks had decreases less than 90% relative to 2002 . 2011 emissions at Clifty Creek (two stacks) increased, with about a doubling over 2002 emissions. The Rockport stack was about 7% higher in 2011 over 2002. EPA Acid Rain P rogram data indicate that statewide SO 2 

### reductions in 2011 were 86% of the MANE-VU Ask amo unt.

28% SO 2 

### reduction in non-EGU emissions No additional measures identified. Indiana noted o ther existing federal requirements (e.g., low sulfur diesel) would result in additiona l reductions.

Evaluation of other control measures

### 16

No additional measures listed for further evaluatio n.


## Kentucky Submittal Date of Regional Haze SIP June 25, 2008; revised May 28, 2010

Haze SIP Status as of December 18, 2012 EPA limited approval, 77 FR 19098 (March 30, 2012); EPA limited disapproval with FIP to replace CAIR with CSAPR, 77 FR 33642 (June 7, 20 12)

BART Requirements Kentucky accepted CAIR as BART for EGU NOx and SO 2 

### . Kentucky identified 26 BART-eligible sources of which 21 were exempted bas ed on further analysis of impacts. BART analysis of five EGUs as subject to BART for P M provided for installing controls for visibility improvements.

90% SO 2 

### reduction of 167 EGU stacks Kentucky has 10 stacks at 8 power plants on the MAN E-VU 167 stacks list, comprising 14 units. Kentucky indicates that 13 of the 14 uni ts (93%) have or will have SO 2 

### controls in 2015, including a unit which may instead opt to retire. The one remaining unit has plans to retire or to convert to natural gas by the federal Utility Mercury and Air Toxics Standards (MATS) deadline. 8 

### Kentucky believes that these controls more than adequately address MANE-VU’s request. Of the ten s tacks on the MANE-VU list, five had 2011 emissions more than 90% below 2002 levels at the plant level. Two other stacks had 2011 emissions more than 80% below 2002 levels, and one stack was 5% below 2002 levels. The remaining two stacks had 20 11 emissions 1% and 49% higher than in 2002, of which respectively, one announced plans to retire, convert to natural gas, or install scrubbers, and the other has announced p lans to replace the existing scrubber by the federal MATS deadline. This source also has pl ans to upgrade (replace or modify) two other existing scrubbers for the source’s three non-167 Ask units. 8 

### EPA Acid Rain Program data indicate that state-wide SO 2 

### reductions in 2011 exceeded the MANE-VU Ask amount by 2%.

28% SO 2 

### reduction in non-EGU emissions Kentucky believes that the significant existing and expected EGU emission controls more than adequately address MANE-VU’s non-EGU emission control requests.

Evaluation of other control measures Open burning regulation referenced, but not include d in modeling.



## Michigan Submittal Date of Regional Haze SIP November 5, 2010

8 Communication from the Kentucky Division for Air Q uality (March 8, 2013).

### 17

Haze SIP Status as of December 18, 2012 EPA partial approval with FIP for two BART sources, 77 FR 71533 (December 3, 2012); EPA limited disapproval with FIP to replace CAIR wi th CSAPR, 77 FR 33642 (June 7, 2012)

BART Requirements Michigan stated that CAIR addresses BART for EGUs. Michigan identified 35 nonEGUs as BART-eligible, and reduced the number of BA RT-eligible sources to six based on emissions and distance from Class 1 areas. Of t he remaining six, one shut down and Michigan accepted mostly existing measures along wi th a few additional requirements as BART for the remaining sources. EPA determined Mic higan failed to address two BART sources and issued a FIP.

90% SO 2 

### reduction of 167 EGU stacks Michigan has five stacks at four facilities among t he MANE-VU 167 list. Of the five listed stacks in Michigan, two had 2011 SO 2 

### emissions more than 90% below 2002 levels, and the remaining three had SO 2 

### emissions 2%-20% below 2002 levels. EPA Acid Rain Program data indicate that state-wide SO 2 

### reductions in 2011 exceeded the MANE-VU Ask amount by 3%.

28% SO 2 

### reduction in non-EGU emissions Michigan did not include additional measures beyond “on the books” requirements. Michigan listed potential reductions from its Renew able Energy Portfolio requirements, Mercury/multi-pollutants rules, PM 2.5 

### and ozone SIPs, and greenhouse gas programs. Reductions were not quantified.

Evaluation of other control measures No additional measures listed for further evaluatio n.



## North Carolina Submittal Date of Regional Haze SIP December 17, 2007

Haze SIP Status as of December 18, 2012 EPA limited approval, 77 FR 38185 (June 27, 2012); EPA limited disapproval with additional time given to revise SIP for CAIR defici ency, 77 FR 33642 (June 7, 2012)

BART Requirements North Carolina accepted CAIR as BART for EGU NOx an d SO 2 

### in addition to EGU requirements under the North Carolina Clean Smokest acks Act. North Carolina identified 17 BART-eligible sources. Of those, 15 w ere exempted based on further analysis. North Carolina determined that no additio nal controls were required at the BART-subject facilities.

90% SO 2 

### reduction of 167 EGU stacks

### 18

North Carolina has 12 stacks at 7 power plants in t he MANE-VU 167 stacks list. Under the North Carolina Clean Smokestacks Act, 11 of tho se EGUs were controlled. Additionally, scrubbers are expected on 3 EGUs not identified by MANE-VU. North Carolina believes that these reductions satisfy the MANE-VU Ask. In 2011, 9 of the 12 EGUs had SO 2 

### emissions more than 90% lower than in 2002, and a 10 th 

### EGU retired in 2012. The remaining 2 EGUs had 2011 emissions 54% and 74% lower in 2011 than 2002 on a facility-wide basis. EPA Acid Rain Progr am data indicate that state-wide SO 2 

### reductions in 2011 exceeded the MANE-VU Ask amount by 34%.

28% SO 2 

### reduction in non-EGU emissions North Carolina indicated it believed that under the North Carolina Clean Smokestacks Act, additional reductions from EGUs not on the 167 list would satisfy the MANE-VU Ask. No additional non-EGU measures beyond existin g and previously planned requirements were noted.

Evaluation of other control measures Dust, methane, and ammonia controls from some non-E GU sector sources.



## Ohio Submittal Date of Regional Haze SIP March 11, 2011

Haze SIP Status as of December 18, 2012 EPA limited approval, 77 FR 39177 (July 2, 2012); E PA limited disapproval with FIP to replace CAIR with CSAPR, 77 FR 33642 (June 7, 2012)

BART Requirements Ohio identified 18 generating stations with 37 unit s as BART-eligible, and accepted CAIR as BART for NOx and SO 2 

### . Ohio also determined that PM emissions from all BART-eligible EGUs did not contribute to visibility impairment above the 0.5 dv level at any Class 1 area, thus would not be subject to BART . Ohio identified 12 non-EGUs as BART-eligible. Ohio determined with additional mod eling that it had one non-EGU source subject to BART. The source will implement an energy efficiency program as an alternative to BART that includes additional SO 2 

### controls or shut-downs.

90% SO 2 

### reduction of 167 EGU stacks Ohio has 28 stacks at 15 power plants among the MAN E-VU 167 EGU stacks list. Ohio listed a number of planned controls since 2002 in t he context of the MANE-VU Ask. In 2011, 16 of the 28 EGU stacks had SO 2 

### emissions more than 90% below 2002 levels on a facility-wide basis. An additional seven EGU stack s indicated plans to install controls, convert to natural gas, or shut down prior to 2018. Another three EGU stacks had 2011 SO 2 

### emissions between approximately10-60% below 2002 l evels. The remaining two EGU stacks increased emissions in 2011 relative to 2002, with one stack (Kyger Creek) doubling emissions, while planning to install scrub bers by mid-2012. EPA Acid Rain Program data indicate that state-wide SO 2 

### reductions in 2011 were 61% of the MANEVU Ask amount.

### 19

28% SO 2 

### reduction in non-EGU emissions No additional non-EGU measures listed. Ohio believ es on-the-books measures are currently sufficient to meet reasonable progress in MANE-VU.

Evaluation of other control measures In response to MANE-VU Ask, Ohio believes on-the-bo oks measures are currently sufficient to meet reasonable progress goals, and i ts emission sources have relatively insignificant impacts on MANE-VU Class 1 areas. No additional measures listed for further evaluation.



## South Carolina 9 

### Submittal Date of Regional Haze SIP December 17, 2007

Haze SIP Status as of December 18, 2012 EPA limited approval, 77 FR 38509 (June 28, 2012); EPA limited disapproval with FIP to replace CAIR with CSAPR, 77 FR 33642 (June 7, 20 12)

BART Requirements South Carolina accepted CAIR as BART for EGU NOx an d SO 2 

### . South Carolina identified 21 BART-eligible sources, including six EGUs for PM only. Of these 21 sources, 19 demonstrated exemptions to BART, includ ing 4 of the 6 EGUs (for PM only). South Carolina determined no additional con trols were needed on the remaining subject-to-BART sources.

90% SO 2 

### reduction of 167 EGU stacks South Carolina has six stacks at four power plants listed in the MANE-VU 167 stacks list. In 2011, four stacks had SO 2 

### emissions that were approximately 90% below 2002 levels. The remaining two stacks were more than 70% below 2002 levels, with announced plans to retire at a date yet to be dete rmined. EPA Acid Rain Program data indicate that state-wide SO 2 

### reductions in 2011 exceeded the MANE-VU Ask amount by 43%.

28% SO 2 

### reduction in non-EGU emissions None listed.

Evaluation of other control measures No additional measures listed for further evaluatio n.



## Tennessee Submittal Date of Regional Haze SIP

9 In its response to consultation requests from New Jersey and New Hampshire, South Carolina indicated it did not believe the state’s emissions reasonably co ntributed to visibility impairment at Class 1 areas in the MANE-VU region.

### 20

April 4, 2008; revised May 14, 2012

Haze SIP Status as of December 18, 2012 EPA limited approval with no action on Eastman BART , 77 FR (April 24, 2012); EPA approval Eastman BART, 77 FR 70689 (November 27, 20 12); EPA limited disapproval with FIP to replace CAIR with CSAPR, 77 FR 33642 (J une 7, 2012)

BART Requirements Tennessee accepted CAIR as BART for EGU NOx and SO 2 

### . Tennessee identified twelve operating BART-eligible sources, including two EGUs (for PM only), with eight subsequently exempted based on demonstrations that they did not cause or contribute to visibility impairment at any Class 1 area, includin g one of the two EGUs (Bull Run). The four subject-to-BART sources had additional BART li mitations put into permits, with no additional controls required at the remaining EGU ( Cumberland).

90% SO 2 

### reduction of 167 EGU stacks Tennessee has five stacks at four power plants on t he MANE-VU 167 list. The Tennessee Valley Authority (TVA) controlled or expe cts to control Kingston 1 & 2 and John Sevier. TVA plans to control Gallatin if need ed to meet its CAIR obligations or to achieve possible more stringent proposed national a mbient air quality standards, and repower or shut down Johnsonville by the next revie w period in 2018. In 2011, SO 2 

### emissions at one stack (Sevier) were more than 90% lower than in 2002 when including plant-wide reductions. The other four stacks had S O 2 

### emissions lower than in 2002 in the range of 40-70%. EPA Acid Rain Program data indica te that state-wide SO 2 

### reductions in 2011 exceeded the MANE-VU Ask amount by 6%.

28% SO 2 

### reduction in non-EGU emissions Tennessee does not believe MANE-VU’s request is jus tified for the state’s emissions. Tennessee believes that MANE-VU’s 2018 modeling in its technical support document for the August 2007 meeting did not prove that the state’s non-EGU emissions were adversely impacting any of the Class 1 areas in the MANE-VU region.

Evaluation of other control measures MANE-VU did not identify TVA Bull Run as part of 16 7 stacks, which is getting scrubbers and is located closer to Great Smoky Moun tains than Johnsonville and Gallatin.



## Virginia Submittal Date of Regional Haze SIP Main plan and narrative: October 4, 2010. Permits: June 17, 2008; March 6, 2009; January 14, 2010. Revisions: November 19, 2010; Ma y 6, 2011; December 21, 2012

Haze SIP Status as of December 18, 2012 EPA limited approval, 77 FR 35287 (June 13, 2012); EPA limited disapproval with FIP to replace CAIR with CSAPR, 77 FR 33642 (June 7, 20 12)

### 21

BART Requirements Virginia accepted CAIR as BART for EGU NOx and SO 2 

### . Virginia has four EGU units that are BART eligible for PM: Units 5 and 6 at Che sterfield Power Station (ORIS 3797), Unit 5 at Possum Point Power Station (ORIS 3804), a nd Unit 3 at Yorktown Power Station (ORIS 3809). Units 5 and 6 at Chesterfield are coal-fired boilers. Both are controlled by SCR, wet FGD, and ESPs. Unit 6 is al so controlled by a polishing baghouse. Unit 3 at Yorktown and Unit 5 at Possum Point are residual oil-fired units. Economic models such as IPM predicted the retiremen t of residual oil fired units; however, the most recent Integrated Resource Plan f iled by Dominion did not suggest that these units will be retired. These residual o il-fired units are infrequently utilized. 10



### Virginia identified 13 facilities having a total of 72 BART-eligible units. Ten facilities with BART-eligible units were exempted from BART ba sed on modeling. The three remaining subject-to-BART sources were O-N Minerals (Chemstone)-Strasburg, Georgia Pacific-Big Island, and Meadwestvaco-Covington.

The units at O-N Minerals (Chemstone)-Strasburg tha t are subject to BART are the rotary kiln (U5) and the calcimatic kiln (U12). The calci matic kiln was permanently retired. The rotary kiln was retrofitted with an SO 2 

### CEMs for continuous monitoring of exhaust gases as part of the BART requirements. Beginning in 2010, the kiln was required to meet an SO 2 

### limitation of 0.29 lbs/ton stone feed.

The units subject to BART at Georgia Pacific-Big Is land are two coal-fired boilers, #4 and #5. Boiler #4 was permanently retired. For BA RT, Boiler #5 was required to retrofit with FGD.

Units at Meadwestvaco-Covington that are subject to BART are Boiler #9, a coal-fired unit; Boiler #10, a predominantly natural gas-fired unit; Recovery Furnace #1; and Smelt Dissolving Tank #1. Emissions are predominantly fr om Boiler #9. This unit’s BART determination required the upgrade of the existing FGD system for increased removal efficiency.

90% SO 2 

### reduction of 167 EGU stacks Virginia has eight stacks at four power plants list ed among the MANE-VU 167 stacks. Virginia estimates that based on federal consent de crees, knowledge of owner control program estimates, and IPM projections, these units will reduce SO 2 

### emissions approximately 82% by 2018 from 2002 levels. In 201 1, five listed stacks had SO 2 

### emissions approximately 90% below 2002 levels. The other three stacks had 40%-60% lower emissions, and two of these three had announc ed plans to retire or convert to natural gas prior to 2018. EPA Acid Rain Program d ata indicate that state-wide SO 2 

### reductions in 2011 exceeded the MANE-VU Ask amount by 28%.

28% SO 2 

### reduction in non-EGU emissions

10 Communication from VA DEQ, February 4, 2013.

### 22

Virginia notes that enforceable SO 2 

### reductions at two EGUs not on the MANE-VU Ask 167 list and additional reductions at one non-EGU i ndustrial source would meet the MANE-VU Ask request by 2018.

Evaluation of other control measures Included in the Virginia Regional Haze SIP was a co mmitment to finalize a reasonable progress review focusing on SO 2 

### emissions for Meadwestvaco Covington’s Stack 25, t he main power house boiler stack. This stack had calc ulated visibility impacts, as described in the Virginia Regional Haze SIP, on multiple Clas s 1 areas. The reasonable progress determination was submitted to EPA as a SIP revisio n on May 6, 2011. The units exhausting to Stack #25 are Boilers 6, 7, 8, and 9. Boilers 6 and 9 are predominantly coal fired units. Boilers 7 and 8 may burn coal as well as biomass and are generally fired on biomass. The reasonable progress determination res ulted in the permitted limit of the stack being reduced from just over 8,000 tpy of SO 2 

### to approximately 6,800 tpy of SO 2 

### , representing a decrease of more than 1,200 tons of SO 2 

### annually.



## West Virginia Submittal Date of Regional Haze SIP June 18, 2008

Haze SIP Status as of December 18, 2012 EPA limited approval, 77 FR 16937 (March 23, 2012); EPA limited disapproval with FIP to replace CAIR with CSAPR, 77 FR 33642 (June 7, 20 12)

BART Requirements West Virginia identified 22 BART-eligible sources, including 7 EGUs, with 19 able to demonstrate exemptions. West Virginia accepted CAI R as BART for EGU NOx and SO 2 

### , with all BART-eligible EGUs installing scrubbers and NOx controls. For PM, only one of the seven EGUs demonstrated it significantly contributed to visibility impairment at a Class 1 area. The subject to BART sources hav e or will shut down, or had an emission rate lowered using existing controls.

90% SO 2 

### reduction of 167 EGU stacks West Virginia has 14 stacks at 10 power plants in t he MANE-VU 167 stack list, and expects all stacks to have at least 90% control eff iciency by 2018. In 2011, nine stacks had SO 2 

### emissions more than 90% below 2002 levels. The re maining five stacks had 2011 SO 2 

### emissions 35%-70% below 2002 levels, with three of the five stacks announcing plans to retire prior to 2018. 11 

### EPA Acid Rain Program data indicate that state-wide SO 2 

### reductions in 2011 were 99% of the MANE-VU Ask amo unt.

28% SO 2 

### reduction in non-EGU emissions

11 The two stacks at Pleasants are equipped with wet scrubbers with an SO 2 removal efficiency of greater than 90%. In 2007, Pleasants replaced its stacks, eliminating the 15% bypass that had been used for s tack gas reheat, and is now scrubbing 100% of the flue g as. The elimination of the bypass allowed for the 70% reduction in emissions from 2002 levels (communicat ion from WV DEP, January 10, 2013)

### 23

West Virginia believes that additional SO 2 

### controls and unit shutdowns at EGUs not among the MANE-VU 167 stacks list satisfy the MANE- VU Ask. No additional nonEGU measures were noted.

Evaluation of other control measures No additional measures listed for further evaluatio n.



## Wisconsin 12 

### Submittal Date of Regional Haze SIP January 18, 2012; supplemented June 7, 2012

Haze SIP Status as of 12/18/12 EPA final approval, 77 FR 46952 (August 7, 2012)

BART Requirements Wisconsin identified four non-EGUs as BART-eligible , and one of the four subsequently determined as subject to BART. Wisconsin drafted a n admistrative order for the BART source to cap NOx and SO 2 

### emissions from several boilers. Wisconsin accepte d CAIR/CSAPR as BART for EGU NOx and SO 2 

### , and determined existing controls and permit limits satisfied BART for EGU PM.

90% SO 2 

### reduction of 167 EGU stacks Does not have listed stack.

28% SO 2 

### reduction in non-EGU emissions None listed.

Evaluation of other control measures Wisconsin plans to evaluate potential measures on a gricultural ammonia sources post2018. Wisconsin will also continue to evaluate pot ential additional reductions from ICI boilers, reciprocating internal combustion engines and turbines, and mobile sources, as needed to meet reasonable progress goals.

12 Wisconsin does not have a listed 167 EGU stack, bu t Vermont listed it among the states identified as having at least a 2% modeled sulfate impact at a MA NE-VU Class 1 area, and as a state to be invited to the MANE-VU consultation process (letter from Justin Jo hnson, VT DEC, July 17, 2007; in MANE-VU InterRPO Consultation Briefing Book, 2007, at pp. 16-18) . The Wisconsin haze SIP does not indicate it received a MANE-VU Ask.

### 24



## 3. U.S. EPA

For additional national measures, the federal “MANE -VU Ask” requested “that EPA work with the eastern Regional Planning Organizatio ns to develop a proposal for tightening the CAIR program to achieve an additiona l 18% reduction in SO 2 

### [from power plants 13 

### ] by no later than 2018.”

While EPA has not developed a new proposal with the RPOs in response to the MANEVU Ask, it has sought to implement two new rules si nce CAIR requiring greater SO 2 

### reductions from power plants by 2018. The projecte d reductions from these rules can be placed in the context of the reduction request in t he MANE-VU Ask to EPA.

The first rule was the Cross-State Air Pollution Ru le (CSAPR), also known as the Transport Rule, which was finalized in August 2011, then subsequently vacated by the D.C. Circuit in August 2012. Although no longer in effect, it was an effort by EPA that would have resulted in additional SO 2 

### reductions from EGUs beyond CAIR. The second rule is EPA’s Utility Mercury and Air Toxics Standa rds (Utility MATS) finalized in February 2012. While this rule’s focus is on air t oxics, EPA projected additional significant SO 2 

### reductions from EGUs beyond CSAPR (and by inferenc e CAIR as well) as a co-benefit from additional controls needed to meet the new air toxics standards. The potential additional reductions of each rule are su mmarized in the following sections.

Cross-State Air Pollution Rule A straightforward accounting of additional EGU SO 2 

### reductions from CSAPR compared to CAIR is not possible due to differences in the s tates covered under the two rules, and differences in the reduced scope of emissions tradi ng allowed under CSAPR relative to CAIR. At a basic level, the overall emission caps under each program can be compared and are shown in the table below, with accompanying caveats as noted. Also note that the full implementation of CAIR is in 2015, while C SAPR would have imposed its final cap by 2014.

Program SO 2 

### cap (million tons annually)

CAIR 2.6 (2015)*

CSAPR 2.4 (2014)**

CSAPR % reduction beyond CAIR -7.6%

* Due to EGUs’ ability to use banked allowances und er CAIR, EPA estimated actual SO 2 emissions in 2015 would be 4.1 million tons. **EPA provided a “variability limit” that is a fixe d percentage above each state’s emissions budget to allow for year-to-year fluctuations in electricity generation. Therefore, the state “budget” may be

13 Bracketed text is not in original. The MANE-VU As k to EPA does not explicitly mention power plants in the quoted text, but the preceding paragraphs in its request to EPA indicate that the focus of the additional 18% SO 2 reductions is on power plants.

### 25

exceeded in any given year within the variability l imit, resulting in emissions above the overall prog ram cap to a limited extent.



### Utility Mercury and Air Toxics Standards The Utility MATS address air toxics emitted by foss il fuel power plants, but EPA estimated that the projected controls needed to be installed on affected EGUs would result in an additional 41% reduction in SO 2 

### emissions beyond CSAPR nationally. 14 

### A listing of states and DC covered by the MANE-VU A sk is given in the following table, which shows EPA’s projected EGU SO 2 

### emissions in a 2017 future baseline case that assumes CSAPR is in place and a 2017 MATS future co ntrol case. 15 

### The table indicates that while the overall regional SO 2 

### reduction beyond CSAPR resulting from Utility MATS among the MANE-VU Ask states is less than the relative national reduction, the regional reduction of 24% still exceeds the MANE-VU Ask to EPA of 18%. The 24% additional reduction in EGU SO 2 

### emissions would also be a conservative minimum relative to CAIR, as it allows more emissions than CSAPR.

State 2017 future baseline EGU SO 2 

### (tons) 15 

### 2017 MATS future

control case EGU SO 2 

### (tons) 15


### CT 3,581 1,400
DE 2,835 4,160 DC 5 0 GA 96,712 78,197
IL 118,217 103,867
IN 200,969 156,781
KY 116,927 125,430
ME 2,564 1,372
MD 29,786 18,091
MA 15,133 5,033
MI 163,168 82,834
NH 6,719 2,102
NJ 9,042 6,404
NY 14,653 28,174 NC 71,113 59,551 OH 180,935 139,208
PA 126,316 93,606
RI 0 0 SC 103,694 40,901

14 EPA Fact Sheet: Mercury and Air Toxics Standards, Benefits and Costs of Cleaning Up Toxic Air Pollution from Power Plants, December 21, 2011. Available at http://www.epa.gov/airquality/powerplanttoxics/pdfs /20111221MATSimpactsfs.pdf (accessed January 2, 2013).
15 U.S. EPA, Regulatory Impact Analysis for the Final Mercury an d Air Toxics Standards, EPA-452/R-11- 011, December 2011 (Table 5A-12).

### 26

TN 33,080 42,666
VT 264 264
VA 51,004 33,704
WV 84,344 66,857
WI 50,777 28,322 Subtotal MANE-VU Ask States only 1,478,257 1,117,52 4 MATS % reduction beyond CSAPR --- -24%NH Regional Haze 5

- Year Progress Report



### ATTACHMENT D
Regional Emissions Trends Analysis for MANE

- VU StatesNH Regional Haze 5

- Year Progress Report



### This page is intentionally left blank.

# Regional Emissions Trends Analysis for MANEVU States
Technical Support Document

Revision 3

Prepared by:

Mid-Atlantic Regional Air Management Association (M ARAMA)

8600 LaSalle Road, Suite 636 Towson, MD 21286 (443) 901-1882

March 22, 2013

### Acknowledgements

Funds for this project were provided by MARAMA’s Me morandum of Agreement with the Ozone Transport Commission (OTC), which is funded b y USEPA grant agreement XA96309001. The purpose of that Memorandum of Agre ement is to support the Mid-Atlantic / Northeast Visibility Union (MANE-VU) in developing programs to control regional haze or visibility impairment in the Northeast and Mid-Atla ntic states.

About MARAMA

The Mid-Atlantic Regional Air Management Associatio n, Inc. is a voluntary, non-profit association of ten state and local air pollution co ntrol agencies. MARAMA's mission is to strengthen the skills and capabilities of member ag encies and to help them work together to prevent and reduce air pollution in the Mid-Atlanti c Region. MARAMA provides cost-effective approaches to regional collaboration by pooling res ources to develop and analyze data, share ideas, and train staff to implement common requirem ents.Emissions Trends Analysis for MANE-VU March 22, 2013 Page i



## Table of Contents

1.0 INTRODUCTION ..................................

................................................... ................................................... ......... 1

1.1 THE PURPOSE OF THIS EMISSION TREND ANAYSIS

.................................................. ........................................... 1
1.2 R EPORT O RGANIZATION

.................................................. ................................................... ............................. 1

2.0 METHODOLOGY AND DATA SOURCES ..................

................................................... .................................. 2

2.1 G EOGRAPHIC AND T EMPORAL R ESOLUTION

.................................................. .................................................. 2
2.2 P OLLUTANTS

.................................................. ................................................... ............................................... 2
2.3 S OURCE C ATEGORIES

.................................................. ................................................... .................................. 2
2.4 D ATA F ORMATS

.................................................. ................................................... .......................................... 3
2.5 D ATA S OURCES

.................................................. ................................................... ........................................... 3
2.5.1 The 2002 Base Inventory with Projections to 2018 Ve rsion 3.3 ......................................... ................... 4
2.5.2 The 2007 Base Inventory with Projections to 2017 an d 2020 ............................................ ................... 5
2.5.3 The 2010 Clean Air Markets Division (CAMD) Reported Emissions ........................................ ............ 6
2.6 A NTHROPOGENIC V ERSUS B IOGENIC E MISSIONS

.................................................. ........................................... 7
2.7 C ONSIST E NCY OF D ATA S OURCES

.................................................. ................................................... .............. 8
2.7.1 Consistency across Inventories ....................

................................................... ....................................... 8
2.7.2 Changes in Energy Information Agency (EIA) Growth F actors ............................................ ................ 8
2.8 R EGIONAL N ATURE OF THE A NALYSIS

.................................................. ................................................... ...... 11
2.9 Q UALITY A SSURANCE

.................................................. ................................................... ............................... 11

3.0 AREA SOURCES ..................................

................................................... ................................................... ........ 12

3.1 B ACKGROUND

.................................................. ................................................... ........................................... 12
3.2 I SSUES WITH A REA S ECTOR D ATA S ETS

.................................................. ................................................... ... 12
3.2.1 Transport Fraction ................................

................................................... ........................................... 12
3.2.2 Inconsistencies between area data sources .........

................................................... ............................. 12
3.2.3 State Specific Issues .............................

................................................... ............................................. 14

3.2.3.1 District of Columbia ..............................

................................................... ................................................... .... 14
3.2.3.2 New Jersey ........................................

................................................... ................................................... ........ 14
3.3 O BSERVED R EGIONAL A REA S OURCE T RENDS

.................................................. ............................................ 15
3.3.1 Nitrogen Oxides (NO X ) .................................................

................................................... .................... 15
3.3.2 Sulfur Dioxide (SO 2 ) .................................................

................................................... ........................ 15
3.3.3 Fine Particulate (PM 2.5 – Direct) ........................................

................................................... ............. 16
3.3.4 Volatile Organic Compounds (VOC) ..................

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

4.0 POINT SOURCES .................................

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

4.1 BACKGROUND

.................................................. ................................................... ........................................... 18
4.2 I SSUES E NCOUNTERED WITH THE P OINT S ECTOR D ATA S ETS

.................................................. ...................... 18
4.2.1 Splitting the EGU and nonEGU files ................

................................................... ................................ 18
4.2.2 EGU point source growth ...........................

................................................... ...................................... 19
4.2.3 Missing Data from EGU Units .......................

................................................... .................................. 19
4.2.1 Missing Data from NonEGU Units ....................

................................................... ............................... 20
4.2.2 Condensable Particulate Matter Emissions Factor ...

................................................... ....................... 20
4.2.3 Transport Fraction ................................

................................................... ........................................... 21Emissions Trends Analysis for MANE-VU March 22, 2013 Page ii

4.2.1 New Jersey 2002 PM2.5 .............................

................................................... ...................................... 21
4.3 O BSERVED R EGIONAL P OINT S OURCE T RENDS

.................................................. ............................................ 21
4.3.1 Nitrogen Oxides (NO X ) .................................................

................................................... .................... 21
4.3.2 Sulfur Dioxide (SO 2 ) .................................................

................................................... ........................ 22
4.3.3 Fine Particulate (PM 2.5 -Direct) ..........................................

................................................... .............. 22
4.3.4 Volatile Organic Compounds (VOC) ..................

................................................... .............................. 23

5.0 NONROAD MOBILE SOURCES INCLUDED IN NMIM .......

................................................... ................... 23

5.1 B ACKGROUND

.................................................. ................................................... ........................................... 23
5.2 I SSUES E NCOUNTERED WITH N ONROAD S ECTOR D ATA S ETS

................................................... ...................... 24
5.2.1 2002 inventory NonRoad Modeling ...................

................................................... ............................... 24
5.2.2 2007 inventory NonRoad modeling ...................

................................................... ............................... 24
5.2.3 SCCs Included in Non-Road Sector ..................

................................................... ................................ 25
5.2.4 Future Year Emissions Projection ..................

................................................... .................................. 25
5.3 O BSERVED R EGIONAL N ONROAD S ECTOR T RENDS

................................................... ..................................... 29
5.3.1 Nitrogen Oxides (NO X ) .................................................

................................................... .................... 29
5.3.2 Sulfur Dioxide (SO 2 ) .................................................

................................................... ........................ 29
5.3.3 Fine Particulate (PM 2.5 – Direct) ........................................

................................................... ............. 29
5.3.4 Volatile Organic Compounds (VOC) ..................

................................................... .............................. 30

6.0 MARINE VESSELS, AIRPORTS, AND RAILROADS .......

................................................... ........................ 31

6.1 B ACKGROUND

.................................................. ................................................... ........................................... 31
6.2 I SSUES E NCOUNTERED WITH MAR S ECTOR D ATA S ETS

.................................................. .............................. 31
6.3 O BSERVED R EGIONAL MAR S ECTOR T REND

.................................................. ............................................... 32
6.3.1 Nitrogen Oxides (NO X ) .................................................

................................................... .................... 32
6.3.2 Sulfur Dioxide (SO 2 ) .................................................

................................................... ........................ 32
6.3.3 Fine Particulate (PM 2.5 – Direct) ........................................

................................................... ............. 33
6.3.4 Volatile Organic Compounds (VOC) ..................

................................................... .............................. 33

7.0 ONROAD MOBILE SOURCES .........................

................................................... ............................................ 34

7.1 BACKGROUND

.................................................. ................................................... ........................................... 34
7.2 I SSUES WITH M OBILE S ECTOR D ATA S ETS

.................................................. ................................................... 35
7.2.1 2002 and 2018 inventory ...........................

................................................... ....................................... 35
7.2.2 2007 and 2020 inventory ...........................

................................................... ....................................... 35
7.3 O BSERVED R EGIONAL O NROAD M OBILE S ECTOR T REND

.................................................. ............................ 36
7.3.1 Nitrogen Oxides (NO X ) .................................................

................................................... .................... 36
7.3.2 Sulfur Dioxide (SO 2 ) .................................................

................................................... ........................ 37
7.3.3 Fine Particulate (PM 2.5 – Direct) ........................................

................................................... ............. 37
7.3.4 Volatile organic compounds (VOC) ..................

................................................... ................................ 37

8.0 EMISSION SUMMARIES ............................

................................................... .................................................. 38

9.0 ELECTRONIC FILES ..............................

................................................... ................................................... .... 53

10.0 REFERENCES ...................................

................................................... ................................................... ......... 54Emissions Trends Analysis for MANE-VU March 22, 2013 Page iii



## List of Appendices

Appendix A List of Participants on the State Review CommitteeEmissions Trends Analysis for MANE-VU March 22, 2013 Page iv



## List of Exhibits

E XHIBIT 2.1

– D ATA S OURCES BY S ECTOR
E XHIBIT 2.2

– B IOGENIC VERSUS A NTHROPOGENIC VOC E MISSIONS
E XHIBIT 2.3

– C HANGE BETWEEN 2008 AND 2020 OF THE E NERGY I NFORMATION A GENCY P ROJECTION OF C OAL
C ONSUMPTION FOR E NERGY G ENERATION

. E XHIBIT 2.4

– C HANGE BETWEEN 2008 AND 2020 OF THE E NERGY I NFORMATION A GENCY P ROJECTION OF
P ETROLEUM C ONSUMPTION FOR E NERGY G ENERATION

. E XHIBIT 2.5

– C HANGE BETWEEN 2008 AND 2020 OF THE E NERGY I NFORMATION A GENCY P ROJECTION OF
N ATURAL G AS C ONSUMPTION FOR E NERGY G ENERATION

. E XHIBIT 3.1

– R ESIDENTIAL W OOD E MISSIONS OF PM 2.5 FROM THE 2002 VERSUS THE 2007 I NVENTORY S UITE

. E XHIBIT 3.2 –A REA S OURCE

- A IR P OLLUTION E MISSIONS BETWEEN 2002 AND 2020

E XHIBIT 3.3 –N UMBER 2 F UEL O IL SO 2 E MISSIONS T REND FOR MANE VU S TATE 2002 TO 2020

E XHIBIT 3.4 –R ESIDENTIAL W OOD C OMBUSTION

– D IFFERENCE BETWEEN 2002 AND 2007 I NVENTORY S UITES
E XHIBIT 4.1

– EGU P OINT S OURCE

- A IR P OLLUTION E MISSIONS BETWEEN 2002 AND 2020

E XHIBIT 4.2 –N ON -EGU P OINT

- A IR P OLLUTION E MISSIONS BETWEEN 2002 AND 2020

E XHIBIT 5.1 N ONROAD C ONTROL P ROGRAMS I NCLUDED IN 2007 I NVENTORY S UITE
E XHIBIT 5.2

– R EGIONAL N ONROAD S OURCE

- E MISSIONS BETWEEN 2002 AND 2020
E XHIBIT 6.1

– R EGIONAL MAR S OURCES

- A IR P OLLUTION E MISSIONS BETWEEN 2002 AND 2020

E XHIBIT 7.1

– R EGIONAL M OBILE O NROAD S OURCES

- A IR P OLLUTION E MISSIONS BETWEEN 2002 AND 2020

E XHIBIT 8.1 A NNUAL A IR P OLLUTANT E MISSION T RENDS BY S ECTOR BETWEEN 2002 AND 2020 R EGIONAL
S UMMARY
E XHIBIT 8.2 A NNUAL A IR P OLLUTANT E MISSION T RENDS BY S ECTOR BETWEEN 2002 AND 2020 C ONNECTICUT
E XHIBIT 8.3 A NNUAL A IR P OLLUTANT E MISSION T RENDS BY S ECTOR BETWEEN 2002 AND 2020 D ELAWARE
E XHIBIT 8.4 A NNUAL A IR P OLLUTANT E MISSION T RENDS BY S ECTOR BETWEEN 2002 AND 2020 D ISTRICT OF
C OLUMBIA
E XHIBIT 8.5 A NNUAL A IR P OLLUTANT E MISSION T RENDS BY S ECTOR BETWEEN 2002 AND 2020 M AINE
E XHIBIT 8.6 A NNUAL A IR P OLLUTANT E MISSION T RENDS BY S ECTOR BETWEEN 2002 AND 2020 M ARYLAND
E XHIBIT 8.7 A NNUAL A IR P OLLUTANT E MISSION T RENDS BY S ECTOR BETWEEN 2002 AND 2020 M ASSACHUSETTS
E XHIBIT 8.8 A NNUAL A IR P OLLUTANT E MISSION T RENDS BY S ECTOR BETWEEN 2002 AND 2020 N EW H AMPSHIRE
E XHIBIT 8.9 A NNUAL A IR P OLLUTANT E MISSION T RENDS BY S ECTOR BETWEEN 2002 AND 2020 N EW J ERSEY
E XHIBIT 8.10 A NNUAL A IR P OLLUTANT E MISSION T RENDS BY S ECTOR BETWEEN 2002 AND 2020 N EW Y ORK
E XHIBIT 8.11 A NNUAL A IR P OLLUTANT E MISSION T RENDS BY S ECTOR BETWEEN 2002 AND 2020 P ENNSYLVANIA
E XHIBIT 8.12 A NNUAL A IR P OLLUTANT E MISSION T RENDS BY S ECTOR BETWEEN 2002 AND 2020 R HODE I SLAND
E XHIBIT 8.13 A NNUAL A IR P OLLUTANT E MISSION T RENDS BY S ECTOR BETWEEN 2002 AND 2020 V ERMONT
E XHIBIT 9.1 E MISSION I NVENTORY D ATA F ILESEmissions Trends Analysis for MANE-VU March 22, 2013 Page v


## Acronyms and Abbreviations

Acronym Description
AEO Annual Energy Outlook APU Auxiliary Power Unit BEIS Biogenic Emissions Inventory System BOTW Beyond on the way

CAA Clean Air Act CMAQ Community Multi-scale Air Quality Modeling Sys tem CAMD Clean Air Markets Division (USEPA) CEM Continuous emission monitoring

CAIR Clean Air Interstate Rule

CMV Commercial marine vessel

CO Carbon monoxide

CSAPR Cross-State Air Pollution Rule EGU Electric generating unit EIA Energy Information Agency ERTAC Eastern Regional Technical Advisory Committee FIPS Federal Information Processing Standard GSE Ground support equipment IPM Integrated Planning Model MANE-VU Mid-Atlantic/Northeast Visibility Union MAR Marine, airport, rail MARAMA Mid-Atlantic Regional Air Management Associa tion

MEGAN Model of Emissions of Gases and Aerosols from Nature

MOBILE6 USEPA model used to estimate onroad mobile emissions, now outdated

MOVES Motor Vehicle Emissions Simulator model NAAQS National Ambient Air Quality Standards NCD National County Database NEI National Emission Inventory

NESCAUM Northeast States for Coordinated Air Use Ma nagement NIF3.0 NEI Input Format Version 3.0 NMIM National Mobile Input Model

NONROAD USEPA model used to estimate off-road mobil e emissions

NO x Oxides of nitrogen OTB/OTW On the books/On the way ORL One-record-per-line (SMOKE format) OTAQ Office of Transportation and Air Quality (USEP A) OTC Ozone Transport Commission

PFC Portable fuel container PM-CON Primary PM, condensable portion only ( < 1 m icron) PM-FIL Primary PM, Filterable portion only

PM-PRI Primary PM, includes filterable and condensable PM-PRI= PM-FIL + PM-CON PM25-FIL Primary PM 2.5 , filterable portion only

PM25-PRI Primary PM 2.5 , includes filterable and condensable PM25-PRI= PM25-FIL + PM-CONEmissions Trends Analysis for MANE-VU March 22, 2013 Page vi

Acronym Description
QAPP Quality Assurance Project Plan RPO Regional Planning Organization

RWC Residential wood combustion SIP State Implementation Plan

SCC Source classification code SMOKE Sparse Matrix Operator Kernel Emissions

SO 2 Sulfur dioxide TSD Technical Support Document USEPA U.S. Environmental Protection Agency

VMT Vehicle miles traveled VOC Volatile organic compoundsEmissions Trends Analysis for MANE-VU March 22, 2013 Page 1



## 1.0 INTRODUCTION

This technical support document (TSD) explains the data sources and methods for analyzing the anthropogenic pollutant emissions tre nds since 2002 in the Mid-Atlantic / Northeast Visibility Union (MANE-VU) region. Result s of the analysis are presented. The MANE-VU region includes Connecticut, Delaware, the District of Columbia, Maine, Maryland, Massachusetts, New Hampshire, New Jersey, New York, Pennsylvania, Rhode
Island and Vermont.

1.1 THE PURPOSE OF THIS EMISSION TREND ANAYSIS

States are required to submit a periodic report eve ry five years beginning five years after submittal of the initial regional haze SIP. The En vironmental Protection Agency’s (EPA) regional haze rule requires states to prepare
“An analysis tracking the change over the past 5 ye ars in emissions of pollutants contributing to visibility impairment from all sour ces and activities within the State. Emissions changes should be identified by ty pe of source or activity. The analysis must be based on the most recent updated e missions inventory, with estimates projected forward, to account for emissio ns changes during the applicable 5-year period.” To support MANE-VU states’ preparation of their pro gress reports, the change in emissions in the region is evaluated. Reductions a re evaluated by sector and state. It is anticipated that MANE-VU member states will use thi s report in conjunction with other information developed by Northeast States for Coord inated Air Use Management (`), the Ozone Transport Commission (OTC) and the MANE-VU me mber states to develop their first five-year progress report.

1.2 REPORT ORGANIZATION

Section 2 describes the methodology and data source s used to analyze emission trends. Sections 3 to 7 provide a detailed approach for eac h inventory sector: area sources; point sources; nonroad mobile sources included in the NMI M model; other nonroad mobile sources (marine vessels, aircraft, and railroad loc omotives); and onroad mobile sources. Section 8 provides emission trend summaries. Secti on 9 provides the file name and a description of the electronic files developed as pa rt of this project. References are provided in Section 10.Emissions Trends Analysis for MANE-VU March 22, 2013 Page 2



## 2.0 METHODOLOGY AND DATA SOURCES

2.1 GEOGRAPHIC AND TEMPORAL RESOLUTION

The geographic area for the inventory trend analysi s is the MANE VU states including: Connecticut, Delaware, District of Columbia, Maine, Maryland, Massachusetts, New Hampshire, New Jersey, New York, Pennsylvania, Rhod e Island, and Vermont.

The temporal resolution is annual.

2.2 POLLUTANTS

In other work, the OTC has established that SO 2 

### is the most important pollutant driving fine particle ambient concentrations and visibility impairment in the northeastern United States. (NESCAUM 2006a) However, other pollutants also play a role. Therefore, this study includes an analysis of emission changes for the following pollutants: oxides of nitrogen (NO x 

### ), sulfur dioxide (SO 2 

### ), volatile organic compounds (VOC) and particulate matter less than 2.5 microns in size (PM 2.5 

### ).

Where Clean Air Market’s Division (CAMD) data is us ed, only NO x 

### , and SO 2 

### emission data is available so only those two pollutants are compared. The fine particulate species in the inventory are categorized as particles with an aerodynamic diameter less than or equal to a nominal 2.5 micrometers (PM 2.5 

### -PRI), which includes both condensable (PM-CON) and filterable particles (PM 2.5 

### -FIL).

2.3 SOURCE CATEGORIES

The trend in emission is analyzed for the following inventory sector:

• EGU Point Sources are units that generate electric power and sell mos t of that power to the electrical grid.

• NonEGU Point Sources are individual industrial, commercial, and institut ional
facilities.

• Stationary Area Sources are facilities that in and of themselves are quite small, but in aggregate may contribute significant emissio ns. Examples include small industrial/commercial facilities, residential heati ng furnaces, VOCs volatizing from house painting or consumer products, gasoline servi ce stations, and agricultural fertilizer/pesticide application sites.Emissions Trends Analysis for MANE-VU March 22, 2013 Page 3



### • Non-road Mobile Sources are vehicles and equipment that are operated off pu blic roadways. This includes equipment such as forklift s, lawn and garden equipment, and portable generators. Marine, air, and rail sou rces are not included in this

sector.

• Marine Air Rail (MAR) Sources include marine vessels, airplanes, and railroad locomotives (MAR).

• On-road Mobile Sources include cars, trucks, buses, and other vehicles th at operate on public roadways.

Biogenic/geogenic emissions are included in modelin g, but are not considered to change over time. For the purposes of the Clean Air Act, biogenic emissions do not need to be considered in determining progress to meeting the S tate’s visibility goals as only anthropogenic air pollution affecting visibility is addressed. In general, this trend analysis does not include any consideration of biogenic emis sions. One exception is a discussion of biogenic emissions of VOC, which predominate in man y rural environments.

2.4 DATA FORMATS

Besides this report, easy-to-review spreadsheets we re prepared for each inventory sector that provides a more detailed look at the emissions for each year analyzed. State-level tabular and graphical summaries are also available. These are stored on the MARAMA FTP server, as described in Section 9, Electronic F iles.

2.5 DATA SOURCES

A variety of data sources were integrated to produc e the emissions trends reported in this document. These include two inventory suites prepa red by MARAMA as inputs to the OTC multi-pollutant regional air quality modeling. Each inventory suite includes a base year and estimates of future year emissions. Withi n a given suite, the base year emissions are “actual” emissions from a year that was in the recent past at the time that the inventory suite was prepared. They are either measured value s or estimates based on measured activity data. Examples of activity data include c ounty population or numbers of cars registered in a county. Future year emissions key off the base year with growth and control factors applied to the base year emissions. Logically, the future year estimates include all of the assumptions and emissions estima tion methodologies used for the associated base year. As a result, future years es timated in one suite may not align well with future years from a different suite because di fferent growth and control assumptions, models, and methodologies were used from one suite to another. The two inventory suites included in this study are:Emissions Trends Analysis for MANE-VU March 22, 2013 Page 4



### • 2002 base with projections to 2018 (MANE-VU 2006; M ANE-VU 2007)

• 2007 base with projections to 2017 and 2020 (MANE-V U 2011a & b)

As will be discussed further below, the two suites underwent multiple renditions to incorporate comments and improvements.

Besides these inventory suites, an additional sourc e of data integrated into the analysis is the 2010 Clean Air Markets Division (CAMD) actual e missions (CAMD 2010). Exhibit 2.1 shows the data sources, including specific inve ntory versions that were accessed for this project and how each data sources is used in t he emissions trends analysis.

Exhibit 2.1 – Data Sources by Sector

2002 Actual 2007 Actual 2010 Actual 2017 Projected 201 8 Projected 2020 Projected
EGU Point MANE-VU V3.3 MARAMA V3 CAMD ** MARAMA V3 * MANE-VU V3.3 MARAMA V3 *

NonEGU Point MANE-VU V3.3 MARAMA V3

--- MARAMA V3 MANE-VU V3.3 MARAMA V3

Mobile MANE-VU V3.3 MARAMA V2

--- --- MANE-VU V3.3 MARAMA V3 *

Area MANE-VU V3.3 MARAMA V3

--- MARAMA V3 MANE-VU V3.3 MARAMA V3

Nonroad (NMIM) MANE-VU V3.3 MARAMA V3

--- MARAMA V3 MANE-VU V3.3 MARAMA V3

MAR MANE-VU V3.3 MARAMA V3 --- MARAMA V3 MANE-VU V3.3 MARAMA V3



### * Not currently complete. Will be included if comp lete in time for use in this project ** To the extent crosswalk matching of units allows

. The following sections provide more details on each of the data sources included in this study.

2.5.1 The 2002 Base Inventory with Projections to 2018 Ve rsion 3.3
The 2002 modeling inventory suite was prepared by M ARAMA and finalized in 2006. Future year projections based on the base year 2002 inventory were prepared for 2009 and 2018. Two scenarios for the future year were prepa red as follows:

On the Books /On the Way (OTB/OTW) – These projecti ons reflect a scenario accounting for all in-place controls that were full y adopted into federal or individual state regulations or SIPs. This include s the anticipated effect of the Clean Air Interstate Rule (CAIR). Modelers often refer to this scenario as the
"future base case".
Beyond On the Way (BOTW) - These projections reflec t a scenario accounting for
all measures in the OTB/OTW scenario and also addit ional controls that statesEmissions Trends Analysis for MANE-VU March 22, 2013 Page 5



### commit to adopt as part of the SIP process. Modele rs often refer to this scenario as the "future control case". The BOTW projection to 2018 was used by MANE VU states air quality modeling to support certain PM, ozone and visibility SIPs.
The Beyond on the Way (BOTW) projection for 2018 wa s used for this emissions trend analysis because this scenario was used in OTC regi onal photochemical air quality modeling to develop reasonable progress goals for v isibility State Implementation Plans (SIP).

Several versions of the 2002 inventory suite were p repared. With each subsequent version improvements were made to the emissions estimation. The last and best version is called
Version 3.3. This is the version that was used in air quality modeling and is also used in this emission trend analysis.

Details of the approach taken to prepare the 2002 m odeling suite are found in the documentation for the base year (MANE-VU 2006) and future projections (MANE-VU 2007).

2.5.2 The 2007 Base Inventory with Projections to 2017 an d 2020
The 2007 modeling inventory suite used in this anal ysis was prepared by MARAMA and finalized in 2012. (MANE-VU 2011a). Future year p rojections from base year 2007 were prepared for 2017 and 2020 (MANE-VU 2011b) for all sectors except the electric generation. In addition only a 2020 onroad future projection was prepared. The 2007 inventory suite was used by MANE VU states in photo chemical air quality screening modeling in 2011 and 2012.

Electric Generating Units (EGU) emissions are only available for the base year, 2007. For preliminary modeling purposes, provisional EGU esti mates were developed for future year 2020 based on the CSAPR caps (now abolished). High quality future year modeling inventories for EGUs are currently being developed under a separate effort lead by the Eastern Regional Technical Advisory Committee (ERTA C). These are not yet available for this study.

Onroad emissions are only available for base year 2 007 and future year 2020. Use of the MOVES model proved so resource intensive that no fu nds were available to develop a 2017 onroad inventory. Under a separate effort, NE SCAUM developed a 2007 onroad inventory using the MOVES model to support air qual ity modeling (NESCAUM 2011). Those runs were further revised by the Virginia Dep artment of Environmental Quality to adjust for the height at which temperature was meas ured. This adjusted run (Version 2) was used in OTC Level 3 screening modeling and also in this analysis.Emissions Trends Analysis for MANE-VU March 22, 2013 Page 6



### Two scenarios for the future year were prepared as follows:

On the Books /On the Way (OTB/OTW) – This projection reflects a scenario accounting for controls that are fully adopted into federal or individual state regulations or SIPs. Also included in this scenari o were some proposed (but not final) control programs that are reasonably anticip ated by states to result in post2007 emission reductions. Finally, low sulfur fuel rules were included in this inventory for New Jersey, Maryland and New York.

OTC Control Measures – This suite of projections reflect a scenario acc ounting for all measures in the OTB/OTW scenario and, in ad dition, the application of nine control measures for which the OTC has developed mo del rules. This scenario is
not addressed in this document.
For this emission trend analysis, the OTB/OTW proje ction for 2017 and 2020 was used. As noted above, EGU emissions were not prepared for either of these projection scenarios.

Several versions of the 2007 inventory suite were p repared. With each subsequent version, improvements were made to the emissions estimation. The last and best version is called Version 3.3 which was used in OTC Level 3 screening photochemical air quality modeling and also in this emission trend analysis.

Details of the approach taken to prepare the 2007 m odeling suite are found in the documentation for the base year (MANE-VU 2011a) and future projections (MANE-VU 2011b)

2.5.3 The 2010 Clean Air Markets Division (CAMD) Reported Emissions

CAMD collects emissions of NO x 

### , SO 2 

### and heat input (HI) from large point sources in order to implement the emissions cap and trade prog ram under the Acid Rain Control Program, the NO x 

### Budget Trading Program, or the Clean Air Interstat e Rule found in Volume 40 Part 75 of the Code of Federal Regulation s (CFR). These rules require hourly reporting of SO 2 

### and NO X 

### emissions from each participating unit. Most of t he CAMD units are traditional power plants that sell electr icity to the electrical grid (EGUs). There are, however, other types of units that report to C AMD that are not considered to be EGUs, such as petroleum refineries and cement kilns. For this report, only the EGU data was
used. The annual unit level CAMD NO X 

### and SO 2 

### emissions files for 2010 were downloaded for use in this project. (CAMD2010)Emissions Trends Analysis for MANE-VU March 22, 2013 Page 7



### 2.6 ANTHROPOGENIC VERSUS BIOGENIC EMISSIONS

In general, this report deals only with anthropogen ic emissions. However, biogenic VOC emissions are significant, particularly in rural ar eas where they can be many times the anthropogenic contribution. This can be seen compa ring biogenic and anthropogenic VOC emissions for a rural state like Vermont where biog enic emissions are four times anthropogenic emissions, with an urban jurisdiction like the District of Columbia where, conversely, anthropogenic emissions are five times biogenic. Thus, when we examine VOC emission trends, it should be noted that we are only examining the change in anthropogenic emissions, which in some cases is a v ery small portion of the whole. In the OTC photochemical air quality modeling studies, bio genic emissions are assumed to be unchanged between base and future years.

Exhibit 2.2 – Biogenic versus Anthropogenic VOC Emi ssions

200 2 Biogenic 20 07

Biogenic 2007

Anthropogenic

Data Source 2002 V3 2007 V3 Total 2007 V3 without EGU
CT 64,017 150,695 114,826 DE 46,343 46,598 31,147 DC 1,726 2,200 10,450 ME 600,205 484,376 82,517 MD 210,104 313,773 161,807 MA 113,958 211,136 177,998 NH 141,894 171,863 54,049 NJ 181,617 229,424 231,320 NY 492,487 878,461 485,262 PA 585,272 995,491 459,576 RI 19,233 34,177 42,304 VT 118,377 145,008 34,694 Total 2,575,233 3,663,203 1,885,950



### Additionally, it should be noted that the differenc e between estimates of biogenic
emissions for 2002 and 2007. The estimate for 2007 is much higher because of a change
in the model used to estimate these emissions. For the 2002 inventory suite, BEIS was used
while in the 2007 suite MEGAN was used. In states where biogenic emissions predominate, like Connecticut and Vermont, this dif ference may be significantly greater than anticipated anthropogenic reduction of VOC.Emissions Trends Analysis for MANE-VU March 22, 2013 Page 8



### It is also important to note that Clean Air Act onl y requires reductions in manmade air pollution to achieve the national visibility goals. The visibility goal was established to prevent visibility impairment from manmade and not biogenic emissions.

2.7 CONSISTENCY OF DATA SOURCES

2.7.1 Consistency across Inventories
The data sources used in this analysis were develop ed at different times and for different purposes. The 2002 and 2007 inventory suites are c alculated estimations prepared as input files for regional modeling. CAMD data are emissio ns measurements collected to demonstrate compliance with regulations. Different methodologies, suitable to the purpose of the inventory, were used for development.

Both between and within inventory suites, there are significant differences in methodology and in the sources inventoried. This may be a resu lt of local custom or may result from regional differences in source importance. For exa mple, the New Hampshire inventory
includes emissions from industrial wood combustion but this Source Classification Code (SCC) is not included in the New Jersey inventory a s it is unlikely that wood is used as an energy source in any New Jersey industry. Finally, the resources available to collect the data vary between states. For inventories suites, when resources are limited, states may consolidate minor SCCs. For this study, these disc repancies are handled differently depending on the source sector, as is further descr ibed in each section describing that

sector.

2.7.2 Changes in Energy Information Agency (EIA) Growth F actors
Both the 2002 and 2007 inventory suites use the Ene rgy Information Administration (EIA) Annual Energy Outlook

(AEO) to develop growth factors for many SCCs, par ticularly those which involve fuel usage. Energy projections evolve over time with near-year projections being more certain than years farther i n the future. In recent AEOs, there has been a significant shift in projected energy consum ption toward natural gas. In addition, the economic downturn of 2009 and the emphasis on i ncreased energy efficiency have resulted in lower future expectations for total ene rgy usage.
Exhibits 2.3, 2.4 and 2.5 show the change from AEO2 005 to AEO2012 of the expected use of coal, natural gas, and petroleum for power gener ation. The blue dashed line in each chart is AEO2005, which was used in the 2002 invent ory suite to grow the base year to future projections. The blue solid line in each ch art is AEO2010 which was used by most states in the 2007 inventory suite to grow the base year to future projections. Note that New Jersey used AEO 2011, and certain other SCC cod es for other MARAMA states wereEmissions Trends Analysis for MANE-VU March 22, 2013 Page 9



### updated to include AEO 2011. In Exhibit 2.3, it can be seen that the expected future coal use dropped significantly between AEO2005 and AEO 2 010. It should be noted that the projected use of coal further declines in future ye ars for the most recent AEO growth estimation. A similar pattern can be seen in Exhib it 2.4 for petroleum. The trend is less clear for natural gas as can be seen in Exhibit 2.5 . AEO2005 predicted that stronger growth for natural gas was expected than in AEO2010 ; however more recent growth factors are closer to the strong growth predicted i n AEO2005 as a result of the recent surge in natural gas exploration and production. Lower g rowth of coal electricity generation translates into lower expected future emissions. I t is important to note that this difference in growth rate systemically reduces the future emis sions from fuel burning in the 2007 inventory suite compared to the 2002 inventory suit e.
Exhibit 2.3 – Change between 2008 and 2020 of the E nergy Information Agency

Projection of Coal Consumption for Energy Generatio n.

1200 1500 1800 2100 2400 2700

2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 M i l l i o n M e g a w a t t - H o u r s AEO2005

AEO2008
AEO2009
AEO2010
AEO2011
AEO2012
AEO2013Emissions Trends Analysis for MANE-VU March 22, 2013 Page 10



### Exhibit 2.4 – Change between 2008 and 2020 of the E nergy Information Agency Projection of Petroleum Consumption for Energy Gene ration.

10 30 50 70 90 110 130 150 170

2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020Million Megawatt-Hours AEO2005

AEO2008
AEO2009
AEO2010
AEO2011
AEO2012
AEO2013Emissions Trends Analysis for MANE-VU March 22, 2013 Page 11



### Exhibit 2.5 – Change between 2008 and 2020 of the E nergy Information Agency Projection of Natural Gas Consumption for Energy Ge neration.

500 600 700 800 900 1000 1100 1200 1300

2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 M i l l i o n M e g a w a t t - H o u r s 

### EIA's AEO Projection of Gas

- based Electricity Generation

AEO2005

AEO2008

AEO2009

AEO2010

AEO2011

AEO2012

AEO2013



### 2.8 REGIONAL NATURE OF THE ANALYSIS
The emission trend analysis presented in this repor t is done at a regional level. As a result, larger states dominate the results. Trends for ind ividual states, especially smaller states, may vary. State level data is provided in Section 8 in addition to the regional data that has been analyzed to present a regional emissions trend

.

2.9 QUALITY ASSURANCE

The approach outlined in the Quality Assurance Proj ect Plan (QAPP) was used to guide the project. (MARAMA 2012) An important element o f quality control is review of work products by the state workgroup formed to guide the emissions trend analysis process. Participants of this group are listed in Appendix A . The workgroup met via teleconference on multiple occasions to discuss plans for the emis sions trend analysis. In addition, members reviewed and commented on project work prod ucts.Emissions Trends Analysis for MANE-VU March 22, 2013 Page 12



## 3.0 AREA SOURCES

3.1 BACKGROUND

The area sector includes sources which individually are too small or too numerous to inventory as individual point sources. Area source s are estimated as an aggregate by county. Examples are emissions from home heating s ystems, house painting, consumer products usage, and small industrial/commercial ope rations not included in the inventory as point sources.

Two data sources were combined in this study to est ablish an emission trend for area
sources. These are:

• 2002 MANE VU V3.3 modeling inventory with a project ion to 2018

• 2007 MARAMA V3 modeling inventory with projections to 2017, and 2020

3.2 ISSUES WITH AREA SECTOR DATA SETS

3.2.1 Transport Fraction
USEPA proscribed emission estimation methodologies overestimate fugitive dust in the ambient air. They are intended to estimate the emi ssions at the exact source of emission (dust from roadways or construction). However, fug itive dust does not transport far and is not measured in ambient air sampling monitors. To adjust the inventories, fugitive dust
emissions of PM25-PRI for certain SCCs are reduced using a USEPA-developed methodology that accounts for the removal of fugiti ve particles near their emission point by vegetation and surface features. This is termed application of a “Transport Fraction.” The largest categories adjusted are paved and unpav ed roads, construction activity, and agricultural crop land tilling. In this inventory trend analysis, there have been no reductions to the inventory to account for this tra nsport reduction for fugitive dust.

3.2.2 Inconsistencies between area data sources
Between development of the 2002 and the 2007 modeli ng inventories, significant improvements were made to estimation methodologies, and emission and growth factors
used to estimate area source emissions. These are noted in this documentation, however, no attempt has been made to adjust the inventories to account for these changes. Changes affecting the area source sector include:Emissions Trends Analysis for MANE-VU March 22, 2013 Page 13



### Residential Wood Combustion : Residential wood combustion is the largest contributor to regional fine particulate emissions. A new calculation tool was developed in advance of the 2007 inventory to estim ate emissions from residential
wood combustion. For the tool a new suite of SCC s ource categories was developed. In addition new emission factors and ne w calculation methodology were developed. Thus, the resulting emissions for this sub-category of area emissions are not comparable between the two invent ory suites. Fine particulate emissions are particularly affected by this change as can be seen in Exhibit 3.1.
While the effect of the new tool varies from state to state, the 2007 inventory suite
residential wood combustion PM2.5 emission estimate is, on average, 40 percent lower than the 2002 inventory suite for the MANE VU region.

Exhibit 3.1 – Residential Wood Emissions of PM 2.5 

### from the 2002 versus the 2007 Inventory Suite.

Inconsistency in the included source categories bet ween inventory suites: In addition to residential wood, the estimation method ology for many other smaller sources was improved. In some cases several SCC co des were consolidated into a single combined SCC. In other cases new SCC codes were established. These shifts make a direct comparison of the inventories at the SCC level difficult. An analysis of the consistency between inventories was prepared by MARAMA to assist states in their review of this sector (MARAM A 2013).Emissions Trends Analysis for MANE-VU March 22, 2013 Page 14



### Road dust PM25 Direct emissions : USEPA revised the recommended calculation methodology for road dust prior to completion of th e 2007 inventory suite. As a result of this revision, the emissions from paved r oads generally increased.

Energy use growth factor: The Energy Information Agency (EIA) Annual Energy Outlook (AEO) is used to project future area source fuel combustion emissions. As was described earlier, there has bee n an overall damping down of fuel use growth projected looking into the future a nd a significant fuel shift away from coal and toward natural gas. Both of these ch anges result in lower emissions in future projections. Thus, if 2018 had been proj ected from base year 2002 using current growth factors, estimated emissions from fu el combustion would have been
lower.

Shift of sources between area and point source sect or: For a variety of reasons, in some states emissions may be characterized as po int sources in one inventory
and area sources in another.

Natural variation in the base year: Emissions such as forest wildfires are dependent upon the year inventoried. These emissi ons are held constant in the future year for a particular inventory suite, but v ary from suite to suite.

3.2.3 State Specific Issues

3.2.3.1 

### D

istrict of Columbia

The District of Columbia revised emissions for a va riety of area source SCCs for all pollutants for both 2002 and 2007. No adjustments were made to future year projections (2017, 2018, 2020). Details of adjustments are ava ilable on the MARAMA ftp.

3.2.3.2 

### N

ew Jersey
New Jersey revised 2007, 2017 and 2020 wildfire emi ssions from those presented in the 2007 2017 and 2020 Technical Support Documents. Em issions were averaged over a period of years, which provides for a more appropri ate trend analysis evaluation. USEPA also uses this methodology in projection inventorie s and modeling.Emissions Trends Analysis for MANE-VU March 22, 2013 Page 15



### 3.3 OBSERVED REGIONAL AREA SOURCE TRENDS

This section describes regional trends. The region al data drawn on is presented in Section 8. In addition, Section 8 provides state level dat a, where the trends may be different than what holds true at the regional level. The regional data for area sources extracted from the larger Section 8 tables is summarized in Exhibit 3. 2. Note that the three data sources are delineated by color differences:

• Blue - 2002V3 inventory suite

• Tan - 2007V3 inventory suite

• White – CAMD 2010 actual data (where available)

Exhibit 3.2 –Area Source - Air Pollution Emissions between 2002 and 2020

2002 2007 

### 2010 2017 2018 2020
2002 V3 2007 V3 

### CAMD 2007 V3 2002 V3 2007 V3



### NOX 266,747 207,054



### --- 194,832 263,954 194,868



### PM2.5 332,676 259,938



### --- 262,887 339,518 264,959



### SO2 316,287 212,471



### --- 119,215 190,437 116,511



### VOC 1,366,735 784,233



### --- 702,289 1,334,175 696,125



### 3.3.1 Nitrogen Oxides (NO X 

### )
In 2007 area sources accounted for approximately 10 percent of regional NO X 

### emissions and were already below the 2018 target set by regio nal air quality modeling. Furthermore, they are projected to decline further by 2017. Red uctions are largely due to turn over to cleaner emission units in the future. However, wit hout additional control programs or conservation measures, area sector NO X 

### emissions are projected to rise slightly again between 2017 and 2020. Projected 2020 emissions st ill remain below the 2018 regional target for this sector.

3.3.2 Sulfur Dioxide (SO 2 

### )
Area sources account for approximately 10 percent o f regional SO 2 

### emissions in 2007. These emissions are primarily from residential heat ing with distillate oil. Regional area
source SO 2 

### emissions trend downward through 2020 and are proj ected to fall below the 2018 regional target by 2017. Expected future redu ctions are due to reduced fuel sulfur content and fuel use shifts to natural gas. Signif icant state differences exist with projected reductions more significant in New Jersey, Maryland and New York where the implementation of low sulfur rules are included in future year inventories, as can be seen in
Exhibit 3.3.Emissions Trends Analysis for MANE-VU March 22, 2013 Page 16



### Exhibit 3.3 –Number 2 Fuel Oil SO 2 

### Emissions Trend for MANE VU State 2002 to 2020

3.3.3 Fine Particulate (PM 2.5 

### – Direct)
Area sources account for approximately 65 percent o f directly emitted regional fine particulate in 2007. Regionally, estimated area so urce emissions for fine particulate are generally lower in the 2007 inventory suite than th e 2002 inventory suite. This is primarily because of a change in the emission factor used for residential wood combustion emissions as was shown in Exhibit 3.1. In addition, the road dust calculation method was revised, further confounding any possible conclusions. We t herefore conclude that no trends can be drawn from the combined data set. However, by look ing at the two individual inventory suites it can be seen that regionally PM 2.5 

### from area sources are expected to increase slightly in the future.

3.3.4 Volatile Organic Compounds (VOC)
Area sources account for approximately 41 percent o f regional anthropogenic VOC
emissions in 2007. Estimated emissions for VOC are generally lower in the 2007 inventory than the 2002 inventory because of a chan ge in emission factor and calculation methodology used for residential wood combustion em issions. The difference in the two inventory suites for VOC from RWC is shown in Exhib it 3.4. We, therefore, conclude thatEmissions Trends Analysis for MANE-VU March 22, 2013 Page 17



### no trends can be drawn from the combined data set. However, both inventory suites separately show anthropogenic VOC from area sources decreasing in the future.

Exhibit 3.4 –Residential Wood Combustion – Differen ce between 2002 and 2007 Inventory SuitesEmissions Trends Analysis for MANE-VU March 22, 2013 Page 18



## 4.0 POINT SOURCES

4.1 BACKGROUND

Point sources are those that are individually chara cterized within the inventory. In most cases, states track these sources through a permitt ing and emissions reporting process.

The point source sector has two subcategories: Ele ctric Generating Units (EGU) and NonElectric Generating units (Non-EGU). This distinct ion is drawn because the approach
taken to estimate base and future emissions in the two subcategories is quite different. Non-EGUs emissions are reported by sources, but are generally estimated using emission factors rather than measured. They are projected b ased on expected business growth
patterns.

EGU emissions of NO X 

### and SO 2 

### are generally measured using continuous emission monitors (CEMs). Emissions of VOC and PM 2.5 

### are estimated using emission factors. The approach taken for EGUs future projection varie d between the two suites of modeling inventories, and will be discussed in detail later.

Three sources were combined in this study to establ ish an emission trend for point sources
as follows:

• 2002 MANE VU V3.3 modeling inventory with a project ion to 2018

• 2007 MARAMA V3 modeling inventory with projections to 2017, and 2020

• 2010 actual emissions as reported to CAMD (for EGU sources only)

4.2 ISSUES ENCOUNTERED W ITH THE POINT SECTOR DATA SETS

4.2.1 Splitting the EGU and nonEGU files
Most, but not all, units that report hourly emissio ns to CAMD are classified as EGUs. The following criteria were used to classify units:

• An EGU sells most of the power generated to the ele ctrical grid;

• An EGU burns mostly commercial fuel which is define d in this case as natural gas, oil, and coal. Wood is not considered a commercial fuel as some states identify wood as renewable. To avoid double counting, units that burn wood and other renewable sources (depending on each state's own de finition) are not included in the EGU dataset as they are included in the nonEGU point source sector.

• In addition, the following units were not considere d EGUs: (1) a unit that generates power for a facility but occasionally sells to the grid; (2) emergency generators; or (3) distributed generation units.Emissions Trends Analysis for MANE-VU March 22, 2013 Page 19



### In the 2002 inventory, EGU and Non-EGU point source s were combined in a single file. Separate EGU and NonEGU files were developed for pr ojection year 2018. For this project, the 2002 data was split into EGU and NonEG U using a crosswalk, developed with the 2002 inventory suite that identifies each unit as either EGU or nonEGU. After review by the states, additional units were removed from t he 2002 EGU file and reclassified as
nonEGU.

For the 2007 inventory suite, states classified poi nt source units as either EGU or nonEGU and this classification was incorporated into the 2 007 point source file. This classification was used to split the 2007 combined file into EGU a nd nonEGU point files.

The 2002 and 2007 inventory suites along with the 2 010 CAMD data were combined to form a single file using ACCESS queries matching OR IS and/or state unit identifiers. For EGU emissions, a trend was established using 2002, 2007, 2010, and 2018 data. For NonEGU sources, a trend was established using 2002, 20 07, 2017, 2018 and 2020 data.

4.2.2 EGU point source growth
For the 2002 inventory suite, EGU emissions were projected to 2018 using t he Integrated Planning Model (IPM) by ICF. ICF is both the owner /developer of the IPM model and the contractor that completed the work. Because IPM us es a different unit naming scheme and
also includes a number of smaller units that are no t in the base year most units cannot be matched with the 2002 base year. The additional un its added by IPM are generally small and atypical such as generators located at landfill s and firing landfill gas. Finally, the IPM model dramatically shifts unit utilization to minim ize emissions for the least cost. In most states IPM predicted that many units, particularly oil burning units, would shut down and new replacement units would be built. In some case s, the projection was considered unrealistic and was adjusted (MARAMA 2009).

For the 2007 inventory, there are plans in place to project emissions using a new model being developed by an inter-Regional Planning Organ ization (RPO) cooperative team called ERTAC EGU. No EGU emissions results are yet available for use in this report. As a result, projection years 2017 and 2020 are not in cluded for EGUs in this emissions trend analysis.

4.2.3 Missing Data from EGU Units

MARAMA noted that in the EGU combined datasets some units were missing emissions data from one or more of the trend years. States w ere asked to review the combined files and complete data for as many units as possible. I f a unit was off-line or shut down they
were asked to confirm the shutdown. In these cases a zero was entered for the years that
the source was shutdown. Where states were unable to complete the data, the emissionEmissions Trends Analysis for MANE-VU March 22, 2013 Page 20



### unit was removed from the analysis to maintain cont inuity between the analysis years. Because removal of data reduces the impact of the s ector, a target of 90 percent complete
records was set. All states were able to achieve 9 0 percent complete for NO X 

### , SO 2 

### , and VOC emission data. In the summary tables in Sectio n 8, values that represent 90 percent complete are indicated with a tag of “2”. An analy sis of the consistency between inventories was prepared by MARAMA to assist states in their review of this sector (MARAMA 2013)

The inventory year 2018 is an exception to this app roach. Because of the above described difficulties in matching IPM generated files, no at tempt was made to match the EGU
emissions estimated for 2018. The 2018 emissions a s projected by IPM were assumed to be complete without matching or adjustment.

4.2.1 Missing Data from NonEGU Units

MARAMA noted that in the Non-EGU combined datasets some units were missing emissions data from one or more of the trend years. States were asked to review the combined files and complete data for as many units as possible. If a unit was off-line or shut down they were asked to confirm that zero was the correct entry.

States that provided adjusted non-EGU data include Pennsylvania, Maine, District of Columbia, New Hampshire and Connecticut. Only Penn sylvania was able to achieve the target of 90 percent for non-EGU data. Connecticut declined to complete all non-EGU point source information because it would result in double counting of emissions that were accounted for in the area source inventory. Maryla nd was unable to align any of their Non-EGU point sources between the 2002 and 2007 inv entory suites because the source identification system was changed in the intervenin g years.
While most states were unable to achieve the target of 90% complete for non-EGU point sources, no emission units was removed from the ana lysis. Instead, the non-EGU point inventory is presented regardless of completeness a s the best available data.

4.2.2 Condensable Particulate Matter Emissions Factor
The PM species in the inventory are categorized as particles with an aerodynamic diameter less than or equal to a nominal 2.5 micrometers (PM 25-PRI), which includes both condensable particles (PM-CON) and filterable parti cles (PM25-FIL). In many cases states provide an estimate for PM25-FIL but not PM- CON. For the 2002 inventory suite, in this situation an AP-42 emission factor (USEPA 1 997) was used to estimate PM-CON. Prior to development of the 2007 inventory suite, M ARAMA commissioned a study of condensable emissions from a variety of unit types. (MARAMA 2009) These newEmissions Trends Analysis for MANE-VU March 22, 2013 Page 21



### emission factors were used to augment the 2007 inve ntory suite. As a result, PM25-PRI emissions in the 2007 inventory suite cannot be com pared to the 2002 suite.

4.2.3 Transport Fraction
The use of transport fractions to account for the d ifference in fugitive dust emissions and
ambient concentrations was discussed in the area so urce sector part of this report (see Section 3.2.1). Similarly to area sources, no tran sport fractions were applied to point
source emissions.

4.2.1 New Jersey 2002 PM2.5
New Jersey’s 2002 PM2.5 inventory was calculated us ing PM10 as a base and using the USEPA PM calculator. Actual PM2.5 emission reports began in 2003 and were more than double what was estimated. Therefore, the actual de creasing trend in PM2.5 from 2003 into the future is not reflected in a comparison us ing 2002.

4.3 OBSERVED REGIONAL POINT SOURCE TRENDS

This section describes regional trends. The region al data drawn on is presented in Section 8. In addition, Section 8 provides state level dat a, where the trends may be different than what holds true at the regional level. The regional data for point sources extracted from the larger Section 8 tables is summarized in Exhibit 4. 1 and 4.2. Note that the three data sources are delineated by color differences:

• Blue - 2002V3 inventory suite

• Tan - 2007V3 inventory suite

• White – CAMD 2010 actual data (where available)

Exhibit 4.1 – EGU Point Source - Air Pollution Emis sions between 2002 and 2020

2002 2007 

### 2010 2017 2018 2020
2002 V3 2007 V3 

### CAMD 2007 V3 2002 V3 2007 V3



### NOX 453,395 338,488 

### 214,623 --- 168,268 ---



### PM2.5 20,670 44,921



### --- --- 51,109 ---



### SO2 1,670,176 1,546,335 

### 620,183 --- 365,024 ---



### VOC 11,943 4,975



### --- --- 4,344 ---



### 4.3.1 Nitrogen Oxides (NO X 

### )
EGU point sources account for approximately 15 perc ent of total regional NO X 

### emissions in 2007. Regionally, EGU point source NO X 

### emissions declined over 50 percent from 2002 through 2010. Reductions are largely due to t he installation of controls. To achieve the regional target for 2018, emissions will need t o decline an additional 10 percent beyondEmissions Trends Analysis for MANE-VU March 22, 2013 Page 22



### what was achieved in 2010. Many EGU units are proj ected to shutdown or convert to more efficient natural gas units before 2018 which will result in substantial additional NO X 

### reductions.

Exhibit 4.2 –Non-EGU Point - Air Pollution Emission s between 2002 and 2020

2002 2007 

### 2010 2017 2018 2020
2002 V3 2007 V3 

### CAMD 2007 V3 2002 V3 2007 V3



### NOX 213,414 174,043



### --- 169,188 174,218 169,668



### PM2.5 33,948 29,880



### --- 29,659 38,393 29,868



### SO2 239,400 129,615



### --- 112,784 201,478 112,828



### VOC 92,562 68,003



### --- 68,099 103,727 68,005



### Non-EGU point sources account for approximately 8 p ercent of regional NO X 

### emissions in 2007. Regional non-EGU source NO X 

### emissions are projected to fall below the 2018 regional target by 2017. Trends vary by state, how ever. Reductions are largely due to unit
shut-downs and the installation of controls. Witho ut additional initiatives, emissions are projected to rise slightly between 2017 and 2020 bu t will still remain below the 2018 visibility target in 2020.

4.3.2 Sulfur Dioxide (SO 2 

### )
EGU point sources account for approximately 80 percent of total regi onal SO 2 

### emissions in 2007. Regionally, EGU point source SO 2 

### emissions declined 60 percent between 2002 and 2010. Reductions are largely due to the instal lation of controls. To achieve the target for 2018, emissions must decline an additional 15 p ercent beyond what was already achieved in 2010. Many EGU units are projected to shutdown or convert to natural gas
before 2018 which will result in substantial additi onal SO 2 

### reductions.

Non-EGU point sources account for approximately 7 percent of regional SO 2 

### emissions in 2007. Regional non-EGU source SO 2 

### emissions are projected to be below the 2018 target by 2017. Reductions are largely due to unit shut-downs and the installation of controls. Without additional initiatives, regional emissions are projected to rise slightly
between 2017 and 2020 but will still remain below t he regional 2018 visibility target in 2020. With the transition to natural gas and ultra -low sulfur distillate fuels and lower sulfur content residual fuel, in the MANE-VU states , this sector can be expected to
decrease emissions from 2002 and 2007 levels.

4.3.3 Fine Particulate (PM 2.5 

### -Direct)
EGU point sources account for approximately 10 percent of the total regional PM 2.5 

### inventory in 2007. In general 2002 and 2018 estima tes are lower than was estimated for the 2007 inventory suite as a result of a change of estimation methodology. In 2002 mostEmissions Trends Analysis for MANE-VU March 22, 2013 Page 23



### states did not collect total direct PM2.5 emissions from EGUs. Rather they used the EPA PM-Calculator to estimate PM2.5 emissions as a prop ortion of PM10. In the 2007 inventory suite states used a combination of source reported data and a new set of emission factors generated by MARAMA in a study of stack tes ts of similar units. (MARAMA 2009) There is inadequate data to indicate a PM 2.5 

### trend for this pollutant.

Non-EGU point sources account for approximately 10 percent of total regi onal PM 2.5 

### - direct emissions in 2007. Regionally, non-EGU poin t source PM 2.5 

### -Direct emissions have declined 11 percent from 2002 to 2007. Reductions are largely due to unit shut-downs and the installation of controls. Regional emissions a re already well below the target for 2018 emission and are projected to drop further by 2017.

4.3.4 Volatile Organic Compounds (VOC)
EGU point sources account for less than one percent of total regiona l VOC emissions in 2007. There is inadequate data to indicate a VOC t rend for this pollutant.

Non-EGU point sources account for less than five percent of total region al VOC emissions in all inventoried years and this proport ion is expected to remain approximately the same in future years. Regionally, non-EGU poin t source VOC emissions have declined 28 percent from 2002 through 2007. Reductions are largely due to unit shut-downs and installation of controls. Regional emissions are a lready well below the target for 2018
emissions.



## 5.0 NONROAD MOBILE SOURCES INCLUDED IN NMIM

5.1 BACKGROUND

Non-road sources are mobile engine powered equipmen t operated off of public highways. Units include recreational marine vessels, recreati onal land-based vehicles, farm and construction machinery, lawn and garden equipment, aircraft ground support equipment, and rail maintenance equipment. This equipment is powered by diesel, gasoline, compressed natural gas, or liquefied petroleum gas engines.Emissions Trends Analysis for MANE-VU March 22, 2013 Page 24



### Two data sources were combined in this study to est ablish an emission trend for the nonroad sector as follows:

• 2002 MANE VU V3.3 modeling inventory with a project ion to 2018

• 2007 MARAMA V3 modeling inventory with projections to 2017, and 2020

5.2 ISSUES ENCOUNTERED W ITH NONROAD SECTOR DATA SETS

For most states, the EPA-developed NMIM/NONROAD mod el was used in both 2002 and 2007 inventory suites to estimate NONROAD sector em issions. While different versions of the model were used, with slightly different mod el adjustments, for the most part these differences did not change the resulting emission e stimation substantially. The following sections describe the model adjustments used in the 2002 and 2007 modeling suites.

5.2.1 2002 inventory NonRoad Modeling
The NONROAD2005 model was used as a starting point for the 2002 inventory. Changes were made to the National County Database (NCD) dat abase based on state review and comment. Complete documentation of the changes is available in the inventory documentation (MANE-VU 2006). A summary of the adj ustments to the default NCD for the 2002 National Mobile Input Model (NMIM) model r uns includes:

• Adjustments to fuel characteristics (Reid Vapor Pre ssure, sulfur and oxygenate fractions) to better represent county-specific fuel characteristics in 2002;

• Default diesel sulfur content values of 2457 parts per million (ppm) for land-based equipment, and 2767 ppm for recreational marine for all MANE VU counties.

5.2.2 2007 inventory NonRoad modeling
The NONROAD2008a (July 2009 NMIM20090504) and the N MIM County Database (version NCD20090531), were used as starting points for the 2007 inventory. Changes
were made to the NCD20090531 based on state review and comment. Complete documentation of the changes is available in the in ventory documentation (MANE-VU 2011a). A summary of the adjustments to the defaul t NMIM County Database for the
2007 NMIM model runs includes:

• Adjustments to fuel characteristics (Reid Vapor Pre ssure, sulfur and oxygenate fractions) to better represent county-specific fuel characteristics in 2007;

• The housing and population data contained in the NO NROAD model were updated using 2007 housing information and population estim ates.

• Recreational marine vessel populations were revised using population data provided by the National Marine Manufacturers Assoc iation (NMMA). Total state populations for each of the three major categories contained in the NONROADEmissions Trends Analysis for MANE-VU March 22, 2013 Page 25



### model (outboard, inboard/stern drive and personal w atercraft) were provided. Because the population files used by the NONROAD mo del (and thus NMIM) were configured with population values for various horsepower categories, the fraction of the total for each marine vessel type i n each horsepower category was determined from the NONROAD default population file s. These fractions were then used to allocate the total state population ob tained from NMMA to the various horsepower categories.

• Airport ground Support: The Federal Aviation Admin istration’s Emissions and Dispersion Modeling System (EDMS) model was used to estimate airport ground support emissions. They were included in the area source sector.

5.2.3 SCCs Included in Non-Road Sector

MARAMA determined that a different set of SCCs were included in the 2002 versus the 2007 non-road sector. Emissions for airport ground support equipment for 2002 and 2018
were moved from non-road to the area source sector. In addition, in 2007 the Marine, Air and Rail (MAR) sector was separated from the non ro ad sector, but this was not done in 2002. Therefore, for this study, MARAMA separated out the 2002 and 2018 MAR data into a separate MAR sector.

5.2.4 Future Year Emissions Projection
For future year projections, the NMIM/NONROAD model applies controls to account for all USEPA non-road emission control programs. (USEP A 2011) Exhibit 5.1 is a summary of the emission control programs accounted for in t he NMIM/NONROAD 2008a model that was used in the 2007 inventory suite. With on e exception, all of these rules were also
accounted for in the NMIM/NONROAD 2005 model. The only rule that is not accounted
for in the 2005 version of NMIM/NONROAD is the fina l one listed in the table: 2008 Control of Emissions from non-road Spark-Ignition E ngines and Equipment.Emissions Trends Analysis for MANE-VU March 22, 2013 Page 26



### Exhibit 5.1 Nonroad Control Programs Included in 2 007 Inventory Suite
Regulation Description
Control of Air Pollution; Determination of Significance for Nonroad Sources and Emission Standards for New Nonroad Compression Ignition Engines At or Above 37 Kilowatts 59 FR 31036 June 17, 1994 This rule establishes Tier 1 exhaust emission stand ards for HC, NO x , CO, and PM for nonroad compression-ignition (CI) engines ≥ 37kW ( ≥ 50hp). Marine engines are not included in this rule. The start dates and polluta nts affected vary by hp category as follows: 50-100 hp: Tier 1,1998; NO x only 100-175 hp: Tier 1, 1997; NO x only 175-750 hp: Tier 1, 1996; HC, CO, NO x , PM >750 hp: Tier 1, 2000; HC, CO, NO x , PMEmissions for New Nonroad SparkIgnition Engines at or Below 19 Kilowatts; Final Rule 60 FR 34581 July 3, 1995 This rule establishes Phase 1 exhaust emission stan dards for HC, N NO x Ox, and CO for nonroad spark-ignition engines ≤ 19kW ( ≤ 25hp). This rule includes both handheld (HH) and non-hand-held (NHH) engines. The Phase 1 standards become effective in 1997 for: Class I NHH engines (<225cc), Class II NHH engines ( ≥ 225cc), Class III HH engines (<20cc), and Class IV HH engines ( ≥ 20cc and <50cc).
The Phase 1 standards become effective in 1998 for: Class V HH engines ( ≥ 50cc)Final Rule for New Gasoline SparkIgnition Marine Engines; Exemptionsfor New Nonroad CompressionIgnition Engines at or Above 37Kilowatts and New Nonroad SparkIgnition Engines at or Below 19 Kilowatts 61 FR 52088 October 4, 1996 This rule establishes exhaust emission standards fo r HC+ NO x for personal watercraft and outboard (PWC/OB) marine SI engines. The standards are phased in fro m 1998-2006.

Control of Emissions of Air Pollution From Nonroad Diesel Engines 63 FR 56967 October 23, 1998 This final rule sets Tier 1 standards for engines u nder 50 hp, phasing in from 1999 to 2000. It also phases in more stringent Tier 2 standards for all engine sizes fro m 2001 to 2006, and yet more stringent Tier 3 standards for e ngines rated over 50 hp from 2006 to 2008. The Tier 2 sta ndards apply to NMHC+ NO x , CO, and PM, whereas the Tier 3 standards apply to NMHC+ NO x and CO. The start dates by hp category and tier are as follows:

hp<25: Tier 1,2000; Tier 2, 2005; no Tier 3 25-50 hp: Tier 1, 1999; Tier 2, 2004; no Tier 3 50-100 hp: Tier 2, 2004; Tier 3, 2008 100-175 hp: Tier 2, 2003; Tier 3, 2007 175-300 hp: Tier 2, 2003; Tier 3, 2006 300-600 hp: Tier 2, 2001, Tier 3, 2006 600-750 hp: Tier 2, 2002; Tier 3, 2006 >750 hp: Tier 2, 2006, no Tier 3 This rule does not apply to marine diesel engines a bove 50 hp.

Phase 2: Emission Standards for New Nonroad Non-handheld Spark This rule establishes Phase 2 exhaust emission stan dards for HC+ NO x for nonroad non-handheld (NHH) spark-Emissions Trends Analysis for MANE-VU March 22, 2013 Page 27

Regulation Description Ignition Engines At or Below 19 Kilowatts 64 FR 15207 March 30, 1999 ignition engines ≤ 19kW ( ≤ 25hp). The Phase 2 standards for Class I NHH engines (<225cc) become effective o n August 1, 2007 (or August 1, 2003 for any engine in itially produced on or after that date). The Phase 2 stand ards for Class II NHH engines ( ≥ 225cc) are phased in from 2001- 2005.

Phase 2: Emission Standards for New Nonroad Spark-Ignition Handheld Engines At or Below 19 Kilowatts and Minor Amendments to Emission Requirements Applicable to Small Spark-Ignition Engines and Marine Spark-Ignition Engines; Final Rule 65 FR 24268 April 25, 2000 This rule establishes Phase 2 exhaust emission stan dards for HC+ NO x for nonroad handheld (HH) spark-ignition engines ≤ 19kW ( ≤ 25hp). The Phase 2 standards are phased in from 2002-2005 for Class III and Class IV engines and are phased in from 2004-2007 for Class V engines.

Control of Emissions From Nonroad Large Spark-Ignition Engines and Recreational Engines (Marine and Land-Based); Final Rule 67 FR 68241 November 8, 2002 This rule establishes exhaust and evaporative stand ards for several nonroad categories: 1) Two tiers of emission standards are established for large spark-ignition engines over 19 kW. Tier 1 includes exhaust standards for HC+ NO x and CO and is phased in from 2004-2006. Tier 2 becomes effective in 2007 and in cludes exhaust standards for HC+ NO x and CO, as along with evaporative controls affecting fuel line permeation , diurnal emissions and running loss emissions. 2) Exhaust and evaporative emission standards are established for recreational vehicles, which includ e snowmobiles, off-highway motorcycles, and all-terra in vehicles (ATVs). For snowmobiles, HC and CO exhaus t standards are phased-in from 2006-2012. For off-hi ghway motorcycles, HC+ NO x and CO exhaust emission standards are phased in from 2006-2007. For ATVs, HC+NO x and CO exhaust emission standards are phased in from 2006-2007. Evaporative emission standards for fuel tank and hose permeation apply to all recreati onal vehicles beginning in 2008. 3) Exhaust emission standards for HC+ NO x , CO, and PM for recreational marine diesel engines over 50 hp b egin in 2006-2009, depending on the engine displacement. T hese are “Tier 2” equivalent standards.

Control of Emissions of Air Pollution From Nonroad Diesel Engines and Fuel; Final Rule (Clean Air Nonroad Diesel Rule – Tier 4) 69 FR 38958 June 29, 2004 This final rule sets Tier 4 exhaust standards for C I engines covering all hp categories (except marine and locomotives), and also regulates nonroad diesel fue l sulfur content. 1) The Tier 4 start dates and pollutants affected v ary by hp and tier as follows: hp<25: 2008, PM only 25-50 hp: Tier 4 transitional, 2008, PM only; Tier 4 final, 2013, NMHC+ NO x and PM

50-75 hp: Tier 4 transitional, 2008; PM only; Tier 4 final, 2013, NMHC+ NO x and PM 75-175 hp: Tier 4 transitional, 2012, HC, NO x , and PM;Emissions Trends Analysis for MANE-VU March 22, 2013 Page 28

Regulation Description Tier 4 final, 2014, HC, NO x , PM 175-750 hp: Tier 4 transitional, 2011, HC, NO x , and PM; Tier 4 final, 2014, HC, NO x , PM >750 hp: Tier 4 transitional, 2011, HC, NO x , and PM; Tier 4 final, 2015, HC, NO x , PM

2) This rule reduces nonroad diesel fuel sulfur lev els in two steps. First, starting in 2007, fuel sulfur levels in nonroad diesel fuel will be limited to a maximum of 500 ppm , the same as for current highway diesel fuel. Second, s tarting in 2010, fuel sulfur levels in most nonroad diesel fuel will be reduced to 15 ppm.

Control of Emissions From Nonroad Spark-Ignition Engines and Equipment; Final Rule (Bond Rule) 73 FR 59034 October 8, 2008 This rule establishes exhaust and evaporative stand ards for small SI engines and marine SI engines:

1) Phase 3 HC+ NO x exhaust emission standards are established for Class I NHH engines starting in 201 2 and for Class II NHH engines starting in 2011. There a re no new exhaust emission standards for handheld engines

. New evaporative standards are adopted for both hand held and non handheld equipment. The new evaporative standards control fuel tank permeation, fuel hose permeation, and diffusion losses. The evaporative standards begin in 2012 for Class I NHH engines and 2011 for Class II NHH engines. For handheld engines, th e evaporative standards are phased-in from 2012-2016.

2) More stringent HC+ NO x and CO standards are established for marine SI PWC/OB engines beginning in 2010. In addition, new exhaust HC+ NO x and CO standards are established for stern drive and inboa rd (SD/I) marine SI engines also beginning in 2010. H igh performance SD/I engines are subject to separate HC + NO x and CO exhaust standards that are phased-in from 2010-2011. New evaporative standards were also ado pted for all marine SI engines that control fuel hose pe rmeation, diurnal emissions, and fuel tank permeation emissio ns. The hose permeation, diurnal, and tank permeation standards take effect in 2009, 2010, and 2011, respectively.
Source: (USEPA 2010)Emissions Trends Analysis for MANE-VU March 22, 2013 Page 29



### 5.3 OBSERVED REGIONAL NONROAD SECTOR TRENDS

This section describes regional trends. The region al data drawn on is presented in Section 8. In addition, Section 8 provides state level dat a, where the trends may be different than what holds true at the regional level. The regiona l data for nonroad sources extracted from the larger Section 8 tables is summarized in Exhibi t 5.2. Note that the three data sources are delineated by color differences:

• Blue - 2002V3 inventory suite

• Tan - 2007V3 inventory suite

• White – CAMD 2010 actual data (where available)

Exhibit 5.2 – Regional Nonroad Source - Emissions b etween 2002 and 2020

2,002 2,007 

### 2010 2,017 2,018 2,020
2002 V3 2007 V3 

### CAMD 2007 V3 2002 V3 2007 V3



### NOX 289,392 263,931



### --- 153,553 158,843 135,962



### PM2.5 27,922 24,701



### --- 16,536 15,952 14,421



### SO2 24,774 14,167



### --- 420 466 443



### VOC 557,536 412,890



### --- 244,126 364,980 222,226



### 5.3.1 Nitrogen Oxides (NO X 

### )
The non-road sector accounts for approximately 10 p ercent of regional NO X 

### emissions in 2007. Regional non-road sources NO X 

### emissions are projected to trend downward through 2020 and are projected to fall below the 2018 targe t by 2017. Reductions are due to the turnover of old engines and bringing newer, cleaner engines online that meet recent federal
emissions standards.

5.3.2 Sulfur Dioxide (SO 2 

### )
The non-road sector accounts for less than one perc ent of regional SO 2 

### emissions in 2007. While insignificant, non-road source SO 2 

### emissions are projected to trend downward through 2020 and are projected to fall below the 20 18 target by 2017. Reductions are due
to reduced sulfur content in fuels.

5.3.3 Fine Particulate (PM 2.5 

### – Direct)
The non-road sector accounts for approximately six percent of directly emitted regional fine particulate emissions in 2007. Regional non-r oad source PM 2.5 

### emissions are projected to trend downward through 2020 and are pr ojected to fall below the 2018 target by 2020. Reductions are due the reduced sulfur con tent in fuels and the turnover of oldEmissions Trends Analysis for MANE-VU March 22, 2013 Page 30



### engines bringing newer, cleaner engines online that meet recent federal emissions
standards.

5.3.4 Volatile Organic Compounds (VOC)
The non-road sector accounts for approximately 20 p ercent of regional VOC emissions in 2007. Regional non-road source VOC emissions are p rojected to trend downward through 2020 and are projected to fall below the 2018 targe t by 2017. Reductions are due to the turnover of old engines bringing newer, cleaner eng ines online that meet recent federal
emissions standards.Emissions Trends Analysis for MANE-VU March 22, 2013 Page 31



## 6.0 MARINE VESSELS, AIRPORTS, AND RAILROADS

6.1 BACKGROUND

This category of sources is collectively referred t o as the MAR (marine, airports, and railroads) sector. Although MAR sources are genera lly nonroad engines, estimation of
these emissions are not included in the NONROAD mod el, therefore emission estimates and projections are developed as a separate effort. The MAR sector includes non-road engines associated with the following activities:

• Marine Vessels - The Commercial Marine Vehicle (CMV) sector includ es boats and ships used either directly or indirectly in the conduct of commerce or military activity. The majority of these vessels are powere d by diesel engines that are either
fueled with distillate or residual fuel oil blends.

• Airports - The aircraft sector includes all aircraft types used for public, private, and military purposes. This includes four types of aircraft 1) Commercial; 2) Air Taxis; 3) General Aviation; and 4) Military. Groun d support equipment (GSE) and auxiliary power units (APU) are not included in thi s sector. Rather, they have been
included in the area sector.

• Railroads - The railroad sector includes railroad locomotive s powered by dieselelectric engines. Locomotives are divided into Cla ss I line haul, Class II/III line haul, commuter/passenger, and Class I yard. Rail m aintenance equipment is
included in this sector.

Two data sources were combined in this study to est ablish an emission trend for the MAR
sector as follows:

• 2002 MANE VU V3.3 modeling inventory with a project ion to 2018

• 2007 MARAMA V3 modeling inventory with projections to 2017 and 2020

6.2 ISSUES ENCOUNTERED WITH MAR SECTOR DATA SETS

The methodology used to estimate MAR sources was si gnificantly revised between development of the 2002 and the 2007 inventory suit es. ERTAC prepared a study of rail emissions based on industry supplied activity data and new emission factors that was adopted by many states, and the USEPA contracted fo r a major new study to improve the airport inventory (USEPA 2009a). In the 2002 inven tory suite, the methodologies used to estimate this category were as described in EPA’s “ Documentation for Aircraft, Commercial Marine Vessel, Locomotive, and other Non -road Components of the National Emissions Inventory”. (USEPA, 2005) New studies by ERTAC (ERTAC 2009) and EPAEmissions Trends Analysis for MANE-VU March 22, 2013 Page 32



### (USEPA 2009) resulted in a reset to a generally hig her emissions basis for NO X 

### and VOC emissions in the 2007 inventory suite from the sect or. At the same time, the trend for
PM 2.5 

### Direct and SO 2 

### for the MAR sector remains largely unchanged. Det ails of the approach to each inventory are contained in the bas e and future documentation for each modeling suite. (Base: MANE-VU 2012a; MANE VU 2006 ) (Future MANE-VU 2012b, MANE-VU 2007).

6.3 OBSERVED REGIONAL MAR SECTOR TREND

This section describes regional trends. The region al data drawn on is presented in Section 8. The regional data for MAR sources extracted fro m the larger Section 8 tables is
summarized in Exhibit 6.1. Note that the three dat a sources are delineated by color
differences:

• Blue - 2002V3 inventory suite

• Tan - 2007V3 inventory suite

• White – CAMD 2010 actual data (where available)

Exhibit 6.1 – Regional MAR Sources - Air Pollution Emissions between 2002 and 2020

2002 2007 

### 2010 2017 2018 2020
2002 V3 2007 V3 

### CAMD 2007 V3 2002 V3 2007 V3



### NOX 137,733 173,855



### --- 127,391 111,425 118,025



### PM2.5 7,929 7,430



### --- 3,906 7,927 3,503



### SO2 32,123 30,318



### --- 4,870 8,172 4,183



### VOC 14,026 19,066



### --- 17,057 14,962 16,962



### 6.3.1 Nitrogen Oxides (NO X 

### )
The MAR sector accounts for approximately 7 percent of regional NO X 

### emissions in 2007.
Estimated emissions for NO X 

### are generally higher in the 2007 than the 2002 inv entory suite because of a change in estimation methodology rather than any real change in emissions. Therefore, no conclusions can be drawn from the combined data set. However, both inventory suites project NO X 

### from MAR sources to decrease in future years. Reductions are due to the turnover of old engines b ringing newer, cleaner engines online
that meet recent federal emissions standards.

6.3.2 Sulfur Dioxide (SO 2 

### )
The MAR sector accounts for only 1 to 2 percent of regional SO 2 

### emissions in 2007. While insignificant, regional MAR sector SO 2 

### emissions are projected to trend downward through 2020 and are projected to fall below the 20 18 target by 2017. Reductions are primarily due to reduced sulfur content in fuels.Emissions Trends Analysis for MANE-VU March 22, 2013 Page 33



### 6.3.3 Fine Particulate (PM 2.5 

### – Direct)
The MAR sector accounts for only 1 to 2 percent of directly emitted fine particulate emissions in 2007. While insignificant, MAR source PM 2.5 

### -Direct emissions trend downward through 2020 and are projected to fall bel ow the 2018 target by 2017. Reductions are primarily due to reduced sulfur cont ent in fuels.

6.3.4 Volatile Organic Compounds (VOC)
The MAR sector accounts for only 1 percent of regio nal VOC emissions in 2007, and can be considered to be an insignificant portion of the inventory. Estimated regional emissions for VOC are generally higher in the 2007 than the 2 002 inventory suite because of a change in estimation methodology rather than any re al change in emissions. Therefore, no
firm conclusions can be drawn from the combined dat a set. However, both inventory suites project VOC from MAR sources to decrease in future years.Emissions Trends Analysis for MANE-VU March 22, 2013 Page 34



## 7.0 ONROAD MOBILE SOURCES

7.1 BACKGROUND

Onroad mobile sector sources are mobile engine driv en equipment operated on public highways. Sources include cars, buses, trucks, and motorcycles. This equipment is powered by diesel, gasoline, and a variety of alter native fuels including compressed natural gas or liquefied petroleum gas.

Two sources were combined in this study to establis h an emission trend for the onroad
mobile sector as follows:

• 2002 MANE VU V3.3 modeling inventory with a project ion to 2018

• 2007 MARAMA V3 modeling inventory with projections to 2020. Unlike other sectors, no projection to 2017 was completed for mo bile emissions.
The calculation of mobile emissions is complex beca use emissions vary with ambient temperature, vehicle type, age, travel speeds, oper ating modes, and fuel volatility. For this reason, inventory models have been developed by USE PA to perform the numerous
calculations to estimate emissions from vehicle exh aust, evaporative and brake and tire wear. For many years, the MOBILE model was used to estimate onroad emissions. The MOBILE model was updated many times with the last v ersion being MOBILE6.2. The term “MOBILE6" is generally used to refer to any of the suite of released MOBILE versions. For regional air quality modeling purpos es to account for temporal and spatial meteorological differences, the MOBILE6.2 model was implemented as part of the Sparse Matrix Operator Kernel Emissions (SMOKE) gridded em issions model.

In recent years, USEPA has been developing a new mo del to estimate onroad mobile
emissions called MOVES ( MO tor V ehicle E mission S imulator) 

### . On March 2, 2010 EPA
announced the release of MOVES2010 in the Federal R egister (75 FR 9411). Starting in 2010 MOVES became the required model for SIP modeli ng, replacing MOBILE6.2. 

### EPA subsequently released two minor revisions -- MOVES2 010a in September 2010 and MOVES2010b in April 2012. Both revisions enhance m odel performance but do not significantly affect the criteria pollutant emissio ns calculated using MOVES2010. To smooth the transition to the new model, USEPA devel oped software tools to convert MOBILE6.2 inputs for MOVES. In addition, MOVES incl udes a preprocessing tool called the County Data Manager (CDM) to convert spreadshee t based information to MySQL database files required by the MOVES model

.Emissions Trends Analysis for MANE-VU March 22, 2013 Page 35



### There are two ways of running the MOVES model and t hey are known as:

• “Inventory” mode that provides emission estimates a s mass, and

• “Emissions rate” or “Lookup table” mode that produc es lookup tables of emission rates as mass per unit activity. a version of MOVE S is available that can be run within SMOKE to account for temporal and spatial me teorological differences for regional air quality modeling purposes. For SMOKE implementation, emission rate tables must first be developed for a wide rang e of meteorological conditions.
For the 2007 and 2020 modeling inventories, MOVES w as run in the emissions rate mode, which was necessary to be compatible with the regio nal air quality modeling.

7.2 ISSUES WITH MOBILE SECTOR DATA SETS

The shift from using MOBILE6.2 for the 2002 invento ry suite, to using the MOVES model for the 2007 inventory suite to estimate onroad emi ssions represents a significant change in the estimation methodology. A large body of new re search on emission factors; in addition to new source groupings were incorporated into the MOVES model. The effect on emissions, estimated by USEPA (USEPA 2009b), was ex pected to result in:

• Increased NO X 

### emission estimate by 5 percent

• Minor but lower estimates of VOC emissions

• Increased wintertime PM 2.5 

### emissions estimates

• Unchanged SO 2 

### emissions estimates.

7.2.1 2002 and 2018 inventory
For the 2002 MANE-VU inventory and future projectio n year 2018, onroad mobile emissions were estimated using MOBILE6.2 as it was implemented in SMOKE. Details of the assumptions used are provided in the inventory documentation. (NESCAUM 2006b)

7.2.2 2007 and 2020 inventory
For the 2007 MARAMA V3 inventory and the future pro jection year 2020, onroad mobile emissions were estimated using the MOVES 2010a mode l run in the emission rate mode. To reduce run time, states grouped counties and ide ntified a representative county to represent each group. County groupings and their r epresentative counties remained within state lines. In addition, months were grouped by s eason and a single month was selected to represent each group. NESCAUM, Pennsylvania, New Y ork and Virginia partnered to perform the runs for the region which resulted in a Version 1 of the mobile inventory. Version 1 was documented by Huiyan Yang of NESCAUM, who led the modeling effort. (NESCAUM 2011)Emissions Trends Analysis for MANE-VU March 22, 2013 Page 36



### A number of revisions were made to Version 1. Inpu t files were revised and SMOKEMOVES was rerun for the MANE VU region by Virginia DEQ for Delaware, Maryland and New Jersey. In addition, a systematic adjustme nt of all pollutants in all states and counties was made to revise the temperature used in Version 1. The temperature at 2
meters was used for the revised estimates. No new MOVES runs were made to address this revision; rather emission rates were interpola ted using Version 1 tables. After all of the adjustments were completed, a Version 2 of the mobile emissions inventory was prepared. Version 2 of the northeast MOVES mobile inventory is used in this analysis. Additional improvements may be made in the future i f resources permit.

7.3 OBSERVED REGIONAL ONROAD MOBILE SECTOR TREND

This section describes regional trends. The region al data drawn on is presented in Section 8. The regional data for onroad sources extracted from the larger Section 8 tables is
summarized in Exhibit 6.1. Note that the three dat a sources are delineated by color
differences:

• Blue - 2002V3 inventory suite

• Tan - 2007V3 inventory suite

• White – CAMD 2010 actual data (where available)

Exhibit 7.1 – Regional Mobile Onroad Sources - Air Pollution Emissions between 2002
and 2020

2002 2007 

### 2010 2017 2018 2020
2002 V3 2007 V3 

### CAMD 2007 V3 2002 V3 2007 V3



### NOX 1,308,235 1,175,916



### --- --- 303,956 471,558



### PM2.5 22,108 45,616



### --- --- 9,189 28,365



### SO2 40,092 8,974



### --- --- 8,756 7,202



### VOC 789,560 600,638



### --- --- 269,979 269,647



### 7.3.1 Nitrogen Oxides (NO X 

### )
The onroad mobile sector accounts for approximately 50 percent of 2007 regional NO X 

### emissions. Emissions in 2020 are estimated to be h igher than 2018, however this is due to a change in estimation methodology rather than any real change in emissions. Because of the significant change in calculation methodology n o conclusions can be drawn from the combined data set. However, both inventory suites show regional NO X 

### from onroad mobile sources decreasing over time. Reductions are due to the turnover of old engines bringing newer, cleaner engines online that meet re cent federal emissions standards.Emissions Trends Analysis for MANE-VU March 22, 2013 Page 37



### 7.3.2 Sulfur Dioxide (SO 2 

### )
The onroad mobile sector accounts for an insignific ant portion of SO 2 

### emissions accounting for less than one percent of regional SO 2 

### emissions in 2007. Regional onroad
mobile sector SO 2 

### emissions trend downward through 2020 and are proj ected to fall below the 2018 target by 2020. Reductions are primarily due to reduced sulfur content in fuels.

7.3.3 Fine Particulate (PM 2.5 

### – Direct)
The onroad mobile sector accounts for approximately 10 percent of directly emitted fine particulate emissions in the region in 2007. Estim ated emissions for fine particles are generally higher in the 2007 than the 2002 inventor y suite because of a change in estimation methodology rather than any real change in emissions. Therefore, no
conclusions can be drawn from the combined data set . However, both inventory suites show regional fine particles from onroad mobile sou rces decreasing in future years. Reductions are due to the turnover of old engines b ringing newer, cleaner engines online
that meet recent federal emissions standards.

7.3.4 Volatile organic compounds (VOC)
The onroad mobile sector accounts for approximately 30 percent of regional VOC
emissions in 2007. Estimated emissions for VOC are generally lower in the 2007 than the 2002 inventory suite. However, the actual inventor y percentage of VOC from the onroad sector is higher in 2007. Because of a change in es timation methodology no conclusions can be drawn from the combined data set. However, both inventory suites show regional VOC from onroad mobile sources decreasing in future years. These reductions are due to fleet turnover bringing cleaner cars into service t hat comply with significant federal rules.Emissions Trends Analysis for MANE-VU March 22, 2013 Page 38



## 8.0 EMISSION SUMMARIES

Exhibit 8.1 summarizes the MANE VU regional emissio n trend for NO X 

### , SO 2 

### , PM 2.5 

### and VOC by sector. Exhibits 8.2 to 8.12 provide the sa me information on a state basis. Color coding and footnotes have been added to distinguish between the three data sources used in the analysis. Blue columns are from the 2002 inven tory suite, tan columns are from the 2007 inventory suite and the white column is from C AMD 2010. PM25 and VOC emissions from EGUs are still under review by state s and, therefore not provided in the table. Some general regional observations by pollu tant include:

NO X 

### - Regional NO x 

### emissions are dominated by two sectors: onroad mo bile and EGU in all inventoried years.

Recently measured EGU emissions tabulated for 2007 and 2010 indicate annual emissions from this sector are declining rapidly. In addition, EGU NO X 

### is projected to decline further in future years for th e 2002 inventory suites. The 2007 inventory suite is incomplete for this category.

The shift from MOBILE6 to MOVES represents a signif icant shift in methodology, which occurring between completion of the 2002 and 2007 inventory suite for
mobile NO X 

### emissions. Therefore, combining these data sets d oes not add understanding to the mobile NO X 

### trend analysis. However, each individual suite shows a declining trend.

Therefore, overall NO X 

### emissions appear to be trending lower with some uncertainty due to changing mobile calculation meth odologies and an incomplete EGU inventory.

• PM 2.5 

### - Directly emitted fine particle emissions are reg ionally dominated by the area sector and in particular residential wood comb ustion in all years inventoried. For this critical source, changes in both estimatio n methodology and emission
factors for direct PM 2.5 

### occurred between the 2002 and 2007 inventory suites

. These changes result in generally lower emissions e stimates for the 2007 inventory suite. Likewise, the methodology used to estimate smaller contributing sectors, namely EGU and mobile has also changed between 2002 and 2007. Therefore, combining these data sets does not add understandin g to the PM 2.5 

### trend analysis.

Overall, the trend for directly emitted fine PM is highly uncertain, with some sectors remaining largely unchanged, while others, particularly engine-based sectors, are projected to decrease.Emissions Trends Analysis for MANE-VU March 22, 2013 Page 39



### • SO 2 

### - Regional SO 2 

### emissions are dominated by EGU emissions. As with NO X 

### , regional EGU SO2 emissions in 2010 are significantl y lower than were estimated for 2007. Further reductions are projected in the future for the 2002 inventory suite. SO2 emissions in 2007 were already below th e estimate for 2018, well ahead of expectations. There is no significant impact of changing methodologies for any
sector calculations.

The combined evidence points towards a significant declining trend for SO 2


### .

• VOC - Regional VOC emissions are dominated by biogenic emissions which are estimated to remain unchanged in future years. The largest percentage of anthropogenic VOC emissions is from the area source sector in 2007 and in particular residential wood combustion in all years inventoried. For this critical source, changes in both estimation methodology and emission factors for VOC occurred between the 2002 and 2007 inventory suites . These changes result in generally lower emissions estimates for the 2007 in ventory suite. In addition, the calculation methodology changed for mobile emission s, also a significant contributor of VOC emissions in the region. Theref ore, combining these data sets does not add understanding to the VOC emission tren d analysis. However, the individual inventories when evaluated separately, b oth indicate a declining trend for the most important sectors.

• Overall, the trend for anthropogenic VOC emissions are projected to decrease in the future, primarily due to mobile and area source controls in being implemented
between 2007 and 2020.Emissions Trends Analysis for MANE-VU March 22, 2013 Page 40



### Exhibit 8.1 Annual Air Pollutant Emission Trends by Sector between 2002 and 2020 Regional Summary

2002 2007 2010 2017 2018 2020 Data Source(1) 2002 V3 2007 V3 CAMD 2007 V3 2002 V3 2007 V3 Oxides of Nitrogen (TPY) Area(4) 266,747 207,054 --- 194,832 263,954 194,868 Nonroad MAR(4) 137,733 173,855

--- 127,391 111,425 118,025 Nonroad NMIM(4) 289,392 263,931 --- 153,553 158,843 135,962 Onroad Mobile(4) 1,308,235 1,175,916 --- --- 303,956 471,558 Point EGU(2) 453,395 338,488 214,623 --- 168,268 --- Point nonEGU(3) 213,414 174,043

--- 169,188 174,218 169,668 Total 2,668,916 2,333,286 --- --- 1,180,664 --- Direct PM2.5 (TPY) Area(4) 332,676 259,938 --- 262,887 339,518 264,959 Nonroad MAR(4) 7,929 7,430 --- 3,906 7,927 3,503 Nonroad NMIM(4) 27,922 24,701 --- 16,536 15,952 14,421 Onroad Mobile(4) 22,108 45,616 --- --- 9,189 28,365 Point EGU(2) 20,670 44,921

--- --- 51,109

--- Point nonEGU(3) 33,948 29,881 --- 29,659 38,393 29,868 Total 445,253 412,486 --- --- 462,087 --- Sulfur Dioxide (TPY) Area(4) 316,287 212,471 --- 119,215 190,437 116,511 Nonroad MAR(4) 32,123 30,318

--- 4,870 8,172 4,183 Nonroad NMIM(4) 24,774 14,167 --- 420 466 443 Onroad Mobile(4) 40,092 8,974 --- --- 8,756 7,202 Point EGU(2) 1,670,176 1,546,335 620,183 --- 365,024 --- Point nonEGU(3) 239,400 129,615

--- 112,784 201,478 112,828 Total 2,322,851 1,941,879 --- --- 774,333 --- Volatile Organic Compounds (TPY) Area(4) 1,366,735 784,233 --- 702,289 1,334,175 696,125 Nonroad MAR(4) 14,026 19,066 --- 17,057 14,962 16,962 Nonroad NMIM(4) 557,536 412,890 --- 244,126 364,980 222,226 Onroad Mobile(4) 789,560 600,638 --- --- 269,979 269,647 Point EGU(2) 11,943 4,975

--- --- 4,344

--- Point nonEGU(3) 92,562 68,003 --- 68,099 103,727 68,005 Total 2,832,364 1,889,805 --- --- 2,092,168 --- 1) This trend is built from three sources: 2002 V3 with future projection to 2018 (Blue Column s) 2007 V3 with a projection to 2017 and 2020 (Tan Col umns) CAMD actual 2010 emissions as reported to the US EP A CAMD (White Columns) (2) Data meets or exceeds target of 90% complete ac ross all years for most states. Units with incomple te data for one or more years have been completed by states or have been removed so that a consistent set of data is presented across years. Therefore total s are not identical to modeled inventory or TSD. (3) Data does not meet target of 90% complete acros s all years. Total represents all units completed by state. Totals are not identical to modeled inventory or TS D. (4) Data identical to modeled inventory and TSD for most states. No revision to correct inconsistent methodology.

Nonroad MAR – includes commercial marine vessels, a irports, and railroad locomotives Nonroad NMIM – includes equipment included in USEPA ’s NMIM/NONROAD modelEmissions Trends Analysis for MANE-VU March 22, 2013 Page 41



### Exhibit 8.2 Annual Air Pollutant Emission Trends by Sector between 2002 and 2020
Connecticut

2002 2007 2010 2017 2018 2020 Data Source(1) 2002 V3 2007 V3 CAMD 2007 V3 2002 V3 2007 V3 Oxides of Nitrogen (TPY) Area(4) 12,745 12,421 --- 11,101 11,821 11,048 Nonroad MAR(4) 7,601 9,001 --- 5,934 6,475 5,344 Nonroad NMIM(4) 17,802 16,019 --- 8,721 9,732 7,762 Onroad Mobile(4) 68,816 53,860 --- --- 14,787 19,200 Point EGU(2) 6,106 4,706 2,901 --- 2,809 --- Point nonEGU(3) 6,994 5,489 --- 7,951 7,448 8,307 Total 120,065 101,496 --- --- 53,072 --- Direct PM2.5 (TPY) Area(4) 14,251 10,606 --- 10,290 12,368 10,217 Nonroad MAR(4) 221 391 --- 190 227 166 Nonroad NMIM(4) 1,569 1,338 --- 919 906 815 Onroad Mobile(4) 1,042 1,969 --- --- 500 978 Point EGU(2) 468 815

--- --- 746

--- Point nonEGU(3) 832 433 --- 483 902 493 Total 18,383 15,552 --- --- 15,649 --- Sulfur Dioxide (TPY) Area(4) 12,424 16,083 --- 12,943 3,398 12,401 Nonroad MAR(4) 715 1,541 --- 239 787 156 Nonroad NMIM(4) 1,366 799 --- 30 28 32 Onroad Mobile(4) 1,667 401 --- --- 366 340 Point EGU(2) 13,122 6,901 4,039 --- 6,443 --- Point nonEGU(3) 2,466 1,170 --- 1,212 2,371 1,228 Total 31,760 26,895 --- --- 13,393 --- Volatile Organic Compounds (TPY) Area(4) 87,308 57,253 --- 46,364 68,398 45,849 Nonroad MAR(4) 371 752 --- 633 392 633 Nonroad NMIM(4) 33,503 20,713 --- 11,797 20,299 10,980 Onroad Mobile(4) 31,755 34,764 --- --- 10,768 11,494 Point EGU(2) 396 251

--- --- 122

--- Point nonEGU(3) 4,635 1,366 --- 1,469 3,796 1,491 Total 157,968 115,099 --- --- 103,775 --- 1) This trend is built from three sources: 2002 V3 with future projection to 2018 (Blue Column s) 2007 V3 with a projection to 2017 and 2020 (Tan Col umns) CAMD actual 2010 emissions as reported to the US EP A CAMD (White Columns) (2) Data meets or exceeds target of 90% complete ac ross all years. Units with incomplete data for one or more years have been completed by states or have be en removed so that a consistent set of data is presented across years. Therefore totals are not i dentical to modeled inventory or TSD. (3) Data does not meet target of 90% complete acros s all years. Total represents all units completed by state. Totals are not identical to modeled inventory or TS D. (4) Data identical to modeled inventory and TSD. N o revision to correct inconsistent methodology.

Nonroad MAR – includes commercial marine vessels, a irports, and railroad locomotives Nonroad NMIM – includes equipment included in USEPA ’s NMIM/NONROAD modelEmissions Trends Analysis for MANE-VU March 22, 2013 Page 42



### Exhibit 8.3 Annual Air Pollutant Emission Trends by Sector between 2002 and 2020
Delaware

2002 2007 2010 2017 2018 2020 Data Source(1) 2002 V3 2007 V3 CAMD 2007 V3 2002 V3 2007 V3 Oxides of Nitrogen (TPY) Area(4) 2,617 2,238 --- 2,209 3,018 2,218 Nonroad MAR(4) 10,437 6,284 --- 4,298 11,671 3,915 Nonroad NMIM(4) 5,781 4,997 --- 3,095 2,956 2,723 Onroad Mobile(4) 21,341 22,026 --- --- 5,917 21,258 Point EGU(2) 8,610 10,004 4,346 --- 7,415 --- Point nonEGU(3) 8,084 5,692 --- 3,328 4,246 3,271 Total 56,870 51,241 --- --- 35,223 --- Direct PM2.5 (TPY) Area(4) 3,205 3,031 --- 3,131 3,426 3,212 Nonroad MAR(4) 402 339 --- 118 532 95 Nonroad NMIM(4) 523 453 --- 284 276 243 Onroad Mobile(4) 415 670 --- --- 191 1,938 Point EGU(2) 1,617 1,895

--- --- 2,313

--- Point nonEGU(3) 2,059 1,219 --- 876 1,254 848 Total 8,221 7,607 --- --- 7,992 --- Sulfur Dioxide (TPY) Area(4) 1,589 1,144 --- 946 1,545 911 Nonroad MAR(4) 3,471 2,139 --- 280 3,288 139 Nonroad NMIM(4) 511 266 --- 7 8 7 Onroad Mobile(4) 584 192 --- --- 128 380 Point EGU(2) 30,626 32,699 14,499 --- 8,077 --- Point nonEGU(3) 43,131 10,391 --- 6,541 7,610 6,357 Total 79,912 46,831 --- --- 20,656 --- Volatile Organic Compounds (TPY) Area(4) 15,520 9,482 --- 8,631 13,066 8,673 Nonroad MAR(4) 482 806 --- 748 539 742 Nonroad NMIM(4) 7,527 7,157 --- 3,888 5,113 3,498 Onroad Mobile(4) 10,564 10,289 --- --- 5,037 11,965 Point EGU(2) 1,100 80

--- --- 112

--- Point nonEGU(3) 4,674 3,413 --- 2,588 1,987 2,572 Total 39,867 31,227 --- --- 25,854 --- 1) This trend is built from three sources: 2002 V3 with future projection to 2018 (Blue Column s) 2007 V3 with a projection to 2017 and 2020 (Tan Col umns) CAMD actual 2010 emissions as reported to the US EP A CAMD (White Columns) (2) Data meets or exceeds target of 90% complete ac ross all years. Units with incomplete data for one or more years have been completed by states or have be en removed so that a consistent set of data is presented across years. Therefore totals are not i dentical to modeled inventory or TSD. (3) Data does not meet target of 90% complete acros s all years. Total represents all units completed by state. Totals are not identical to modeled inventory or TS D. (4) Data identical to modeled inventory and TSD. N o revision to correct inconsistent methodology.

Nonroad MAR – includes commercial marine vessels, a irports, and railroad locomotives Nonroad NMIM – includes equipment included in USEPA ’s NMIM/NONROAD modelEmissions Trends Analysis for MANE-VU March 22, 2013 Page 43



### Exhibit 8.4 Annual Air Pollutant Emission Trends by Sector between 2002 and 2020 District of Columbia

2002 2007 2010 2017 2018 2020 Data Source(1) 2002 V3 2007 V3 CAMD 2007 V3 2002 V3 2007 V3 Oxides of Nitrogen (TPY) Area(2) 1,390 1,547 --- 1,560 2,229 1,592 Nonroad MAR(4) 506 512 --- 358 372 326 Nonroad NMIM(4) 3,065 2,787 --- 1,560 1,443 1,249 Onroad Mobile(4) 8,902 8,724 --- --- 1,717 6,209 Point EGU(2) 539 177 510 --- 103 --- Point nonEGU(3) 748 611 --- 636 368 650 Total 15,150 14,358 --- --- 6,232 --- Direct PM2.5 (TPY) Area(2) 1,140 1,542 --- 1,560 860 1,566 Nonroad MAR(4) 11 11 --- 6 7 6 Nonroad NMIM(4) 288 234 --- 132 117 102 Onroad Mobile(4) 153 374 --- --- 58 590 Point EGU(2) 46 17

--- --- 99

--- Point nonEGU(3) 60 36 --- 21 98 21 Total 1,699 2,214 --- --- 1,239 --- Sulfur Dioxide (TPY) Area(2) 908 1,241 --- 995 522 953 Nonroad MAR(4) 34 38

--- 0 2 0 Nonroad NMIM(4) 341 196 --- 3 3 3 Onroad Mobile(4) 271 88 --- --- 41 124 Point EGU(2) 1,094 142 874 --- 83 --- Point nonEGU(3) 1,026 470

--- 379 553 380 Total 3,674 2,175 --- --- 1,204 --- Volatile Organic Compounds (TPY) Area(2) 5,705 5,568 --- 5,324 4,991 5,369 Nonroad MAR(4) 20 35 --- 24 18 21 Nonroad NMIM(4) 2,053 1,324 --- 749 1,351 710 Onroad Mobile(4) 4,895 3,470 --- --- 1,797 3,326 Point EGU(2) 9 6

--- --- 5

--- Point nonEGU(3) 67 53 --- 54 71 54 Total 12,750 10,456 --- --- 8,233 --- 1) This trend is built from three sources: 2002 V3 with future projection to 2018 (Blue Column s) 2007 V3 with a projection to 2017 and 2020 (Tan Col umns) CAMD actual 2010 emissions as reported to the US EP A CAMD (White Columns) (2) Data meets or exceeds target of 90% complete ac ross all years. Units with incomplete data for one or more years have been completed by states or have be en removed so that a consistent set of data is presented across years. Therefore totals are not i dentical to modeled inventory or TSD. (3) Data does not meet target of 90% complete acros s all years. Total represents all units completed by state. Totals are not identical to modeled inventory or TS D. (4) Data identical to modeled inventory and TSD. N o revision to correct inconsistent methodology. Nonroad MAR – includes commercial marine vessels, a irports, and railroad locomotives Nonroad NMIM – includes equipment included in USEPA ’s NMIM/NONROAD modelEmissions Trends Analysis for MANE-VU March 22, 2013 Page 44



### Exhibit 8.5 Annual Air Pollutant Emission Trends by Sector between 2002 and 2020
Maine

2002 2007 2010 2017 2018 2020 Data Source(1) 2002 V3 2007 V3 CAMD 2007 V3 2002 V3 2007 V3 Oxides of Nitrogen (TPY) Area(4) 7,391 6,655 --- 5,960 7,050 5,851 Nonroad MAR(4) 1,606 3,176

--- 2,500 1,583 2,341 Nonroad NMIM(4) 8,184 7,425 --- 5,206 4,946 4,774 Onroad Mobile(4) 54,687 36,922 --- --- 12,828 18,203 Point EGU(2) 1,005 696 719 --- 1,827 --- Point nonEGU(3) 19,055 17,050

--- 20,373 13,688 20,422 Total 91,928 71,924 --- --- 41,922 --- Direct PM2.5 (TPY) Area(4) 32,776 12,526 --- 12,061 33,202 12,000 Nonroad MAR(4) 196 452 --- 214 245 186 Nonroad NMIM(4) 1,131 1,078 --- 755 732 656 Onroad Mobile(4) 934 1,454 --- --- 266 2,564 Point EGU(2) 398 125

--- --- 279

--- Point nonEGU(3) 5,422 3,727 --- 3,628 5,622 3,623 Total 40,857 19,362 --- --- 40,346 --- Sulfur Dioxide (TPY) Area(4) 13,153 9,812 --- 7,870 4,940 7,609 Nonroad MAR(4) 146 296

--- 33 63 28 Nonroad NMIM(4) 767 415 --- 16 19 17 Onroad Mobile(4) 1,804 377 --- --- 894 566 Point EGU(2) 2,013 1,677 820 --- 7,422 --- Point nonEGU(3) 21,706 15,554

--- 12,655 18,492 12,535 Total 39,589 28,131 --- --- 31,830 --- Volatile Organic Compounds (TPY) Area(4) 100,624 31,966 --- 26,113 90,868 25,631 Nonroad MAR(4) 407 448 --- 378 443 356 Nonroad NMIM(4) 30,734 29,877 --- 19,301 21,543 16,727 Onroad Mobile(4) 23,037 15,239 --- --- 10,414 18,052 Point EGU(2) 843 32

--- --- 53

--- Point nonEGU(3) 5,250 4,987 --- 4,733 5,598 4,561 Total 160,895 82,549 --- --- 128,919 --- 1) This trend is built from three sources: 2002 V3 with future projection to 2018 (Blue Column s) 2007 V3 with a projection to 2017 and 2020 (Tan Col umns) CAMD actual 2010 emissions as reported to the US EP A CAMD (White Columns) (2) Data meets or exceeds target of 90% complete ac ross all years. Units with incomplete data for one or more years have been completed by states or have be en removed so that a consistent set of data is presented across years. Therefore totals are not i dentical to modeled inventory or TSD. (3) Data does not meet target of 90% complete acros s all years. Total represents all units completed by state. Totals are not identical to modeled inventory or TS D. (4) Data identical to modeled inventory and TSD. N o revision to correct inconsistent methodology.

Nonroad MAR – includes commercial marine vessels, a irports, and railroad locomotives Nonroad NMIM – includes equipment included in USEPA ’s NMIM/NONROAD modelEmissions Trends Analysis for MANE-VU March 22, 2013 Page 45



### Exhibit 8.6 Annual Air Pollutant Emission Trends by Sector between 2002 and 2020 Maryland

2002 2007 2010 2017 2018 2020 Data Source(1) 2002 V3 2007 V3 CAMD 2007 V3 2002 V3 2007 V3 Oxides of Nitrogen (TPY) Area(4) 15,842 10,312 --- 10,948 17,822 11,184 Nonroad MAR(4) 9,706 22,727

--- 15,421 8,528 13,870 Nonroad NMIM(4) 27,602 25,703 --- 15,340 15,653 13,466 Onroad Mobile(4) 122,210 115,128 --- --- 28,097 45,474 Point EGU(2) 77,062 54,686 22,610 --- 14,567 --- Point nonEGU(3) 19,317 20,204

--- 23,054 18,888 23,228 Total 271,739 248,760 --- --- 103,555 --- Direct PM2.5 (TPY) Area(4) 27,330 19,789 --- 20,884 30,158 21,201 Nonroad MAR(4) 1,490 786 --- 382 1,662 324 Nonroad NMIM(4) 2,856 2,470 --- 1,679 1,634 1,475 Onroad Mobile(4) 2,200 3,955 --- --- 1,033 1,837 Point EGU(2) 2,365 12,064

--- --- 6,431

--- Point nonEGU(3) 2,649 3,245 --- 3,682 3,501 3,689 Total 38,889 42,309 --- --- 44,419 --- Sulfur Dioxide (TPY) Area(4) 12,412 5,960 --- 1,674 9,118 1,704 Nonroad MAR(4) 5,375 2,482

--- 472 535 375 Nonroad NMIM(4) 2,548 1,434 --- 36 42 38 Onroad Mobile(4) 4,058 932 --- --- 656 977 Point EGU(2) 277,263 294,426 51,635 --- 36,962 --- Point nonEGU(3) 16,544 10,957

--- 14,058 38,886 14,069 Total 318,200 316,191 --- --- 86,199 --- Volatile Organic Compounds (TPY) Area(4) 120,272 64,429 --- 57,045 104,624 57,042 Nonroad MAR(4) 3,301 2,012 --- 1,659 3,867 1,642 Nonroad NMIM(4) 53,011 35,155 --- 21,223 34,093 19,887 Onroad Mobile(4) 61,847 55,628 --- --- 29,913 24,458 Point EGU(2) 5,193 428

--- --- 575

--- Point nonEGU(3) 5,714 4,583 --- 5,700 6,279 5,662 Total 249,338 162,235 --- --- 179,351 --- 1) This trend is built from three sources: 2002 V3 with future projection to 2018 (Blue Column s) 2007 V3 with a projection to 2017 and 2020 (Tan Col umns) CAMD actual 2010 emissions as reported to the US EP A CAMD (White Columns) (2) Data meets or exceeds target of 90% complete ac ross all years. Units with incomplete data for one or more years have been completed by states or have be en removed so that a consistent set of data is presented across years. Therefore totals are not i dentical to modeled inventory or TSD. (3) Data does not meet target of 90% complete acros s all years. Total represents all units completed by state. Totals are not identical to modeled inventory or TS D. (4) Data identical to modeled inventory and TSD. N o revision to correct inconsistent methodology.

Nonroad MAR – includes commercial marine vessels, a irports, and railroad locomotives Nonroad NMIM – includes equipment included in USEPA ’s NMIM/NONROAD modelEmissions Trends Analysis for MANE-VU March 22, 2013 Page 46



### Exhibit 8.7 Annual Air Pollutant Emission Trends by Sector between 2002 and 2020
Massachusetts

2002 2007 2010 2017 20 18 2020 Data Source(1) 2002 V3 2007 V3 CAMD 2007 V3 2002 V3 2007 V3 Oxides of Nitrogen (TPY) Area(4) 31,567 20,252 --- 18,984 36,296 19,151 Nonroad MAR(4) 12,729 12,576

--- 9,101 10,949 8,540 Nonroad NMIM(4) 29,830 26,464 --- 14,815 15,993 13,159 Onroad Mobile(4) 143,368 73,441 --- --- 22,813 19,171 Point EGU(2) 31,701 11,274 8,563 --- 18,157 --- Point nonEGU(3) 16,906 12,353

--- 14,308 20,090 14,788 Total 266,101 156,360 --- --- 124,298 --- Direct PM2.5 (TPY) Area(4) 42,082 30,438 --- 29,945 43,086 29,883 Nonroad MAR(4) 569 651

--- 435 541 404 Nonroad NMIM(4) 2,643 2,267 --- 1,539 1,505 1,354 Onroad Mobile(4) 2,410 2,798 --- --- 840 1,475 Point EGU(2) 1,491 2,433

--- --- 3,233

--- Point nonEGU(3) 2,789 2,257 --- 2,250 3,332 2,277 Total 51,984 40,844 --- --- 52,537 --- Sulfur Dioxide (TPY) Area(4) 54,947 19,859 --- 15,996 8,357 15,357 Nonroad MAR(4) 1,364 982

--- 290 395 278 Nonroad NMIM(4) 2,403 1,376 --- 41 47 44 Onroad Mobile(4) 4,399 767 --- --- 1,937 341 Point EGU(2) 92,996 54,628 36,969 --- 47,927 --- Point nonEGU(3) 13,965 8,603

--- 7,713 16,544 7,719 Total 170,074 86,215 --- --- 75,207 --- Volatile Organic Compounds (TPY) Area(4) 162,039 85,870 --- 66,211 134,974 65,306 Nonroad MAR(4) 1,915 1,926 --- 1,624 2,122 1,569 Nonroad NMIM(4) 54,811 35,675 --- 20,509 34,172 18,989 Onroad Mobile(4) 57,186 50,443 --- --- 17,056 16,414 Point EGU(2) 584 486

--- --- 484

--- Point nonEGU(3) 7,765 4,071 --- 4,081 10,356 3,999 Total 284,301 178,471 --- --- 199,164 --- (1) This trend is built from three sources: 2002 V3 with future projection to 2018 2007 V3 with a projection to 2017 and 2020 CAMD actual 2010 emissions as reported to the US EP A CAMD (2) Data meets or exceeds target of 90% complete ac ross all years. Units with incomplete data for one or more years have been completed by states or have be en removed so that a consistent set of data is presented across years. Therefore totals are not i dentical to modeled inventory or TSD. (3) Data does not meet target of 90% complete acros s all years. Total represents all units completed by state. Totals are not identical to modeled inventory or TS D. (4) Data identical to modeled inventory. No revisi on to correct inconsistent methodology.

Nonroad MAR – includes commercial marine vessels, a irports, and railroad locomotives Nonroad NMIM – includes equipment included in USEPA ’s NMIM/NONROAD modelEmissions Trends Analysis for MANE-VU March 22, 2013 Page 47

The SO 2 emissions reported from area sources in Massachuse tts match the value in the future year inventory documentation. This is because an error was corrected after final publication of the 2002 Version 3 documentation. However, the error was no t corrected in the modeling files. 

### Exhibit 8.8 Annual Air Pollutant Emission Trends by Sector between 2002 and 2020 New Hampshire

2002 2007 2010 2017 2018 2020 Data Source(1) 2002 V3 2007 V3 CAMD 2007 V3 2002 V3 2007 V3 Oxides of Nitrogen (TPY) Area(4) 10,992 4,737 --- 4,152 12,243 4,111 Nonroad MAR(4) 1,776 1,454

--- 1,306 1,723 1,286 Nonroad NMIM(4) 8,104 8,548 --- 5,521 4,558 5,268 Onroad Mobile(4) 33,283 33,923 --- --- 7,671 30,342 Point EGU(2) 6,894 4,754 4,788 --- 3,089 --- Point nonEGU(3) 3,576 2,694

--- 3,388 1,086 3,467 Total 64,625 56,110 --- --- 30,369 --- Direct PM2.5 (TPY) Area(4) 17,534 8,623 --- 8,598 18,089 8,633 Nonroad MAR(4) 95 62 --- 46 98 45 Nonroad NMIM(4) 868 798 --- 558 534 493 Onroad Mobile(4) 562 1,424 --- --- 263 3,010 Point EGU(2) 1,973 602

--- --- 2,156

--- Point nonEGU(3) 426 499 --- 1,169 940 1,179 Total 21,459 12,008 --- --- 22,080 --- Sulfur Dioxide (TPY) Area(4) 7,076 5,283 --- 4,176 3,123 3,991 Nonroad MAR(4) 220 545

--- 81 226 46 Nonroad NMIM(4) 668 440 --- 16 16 18 Onroad Mobile(4) 777 275 --- --- 537 542 Point EGU(2) 43,962 42,524 36,835 --- 10,766 --- Point nonEGU(3) 5,607 2,743

--- 2,655 3,086 2,658 Total 58,310 51,810 --- --- 17,753 --- Volatile Organic Compounds (TPY) Area(4) 65,374 22,343 --- 20,894 62,687 20,807 Nonroad MAR(4) 142 195 --- 175 158 178 Nonroad NMIM(4) 22,231 17,105 --- 11,028 14,807 9,783 Onroad Mobile(4) 16,762 13,599 --- --- 6,564 14,629 Point EGU(2) 101 110

--- --- 73

--- Point nonEGU(3) 1,815 768 --- 1,445 998 1,431 Total 106,425 54,120 --- --- 85,288 --- 1) This trend is built from three sources: 2002 V3 with future projection to 2018 (Blue Column s) 2007 V3 with a projection to 2017 and 2020 (Tan Col umns) CAMD actual 2010 emissions as reported to the US EP A CAMD (White Columns) (2) Data meets or exceeds target of 90% complete ac ross all years. Units with incomplete data for one or more years have been completed by states or have be en removed so that a consistent set of data is presented across years. Therefore totals are not i dentical to modeled inventory or TSD. (3) Data does not meet target of 90% complete acros s all years. Total represents all units completed by state. Totals are not identical to modeled inventory or TS D. (4) Data identical to modeled inventory and TSD. N o revision to correct inconsistent methodology.

Nonroad MAR – includes commercial marine vessels, a irports, and railroad locomotives Nonroad NMIM – includes equipment included in USEPA ’s NMIM/NONROAD modelEmissions Trends Analysis for MANE-VU March 22, 2013 Page 48



### Exhibit 8.9 Annual Air Pollutant Emission Trends by Sector between 2002 and 2020 New Jersey

2002 2007 2010 2017 2018 2020 Data Source(1) 2002 V3 2007 V3 CAMD 2007 V3 2002 V3 2007 V3 Oxides of Nitrogen (TPY) Area(3) 29,637 21,829 --- 23,340 21,829 23,339 Nonroad MAR(4) 19,969 22,264

--- 20,390 17,575 19,335 Nonroad NMIM(4) 40,583 36,340 --- 20,710 23,457 18,358 Onroad Mobile(4) 152,076 135,339 --- --- 30,150 42,168 Point EGU(2) 33,171 16,530 9,317 --- 12,984 --- Point nonEGU(3) 18,599 13,517

--- 11,879 17,091 12,092 Total 294,035 245,819 --- --- 123,086 --- Direct PM2.5 (TPY) Area(2) 19,071 18,961 --- 18,441 17,322 18,568 Nonroad MAR(4) 1,047 866 --- 453 920 442 Nonroad NMIM(4) 3,831 3,212 --- 2,216 2,214 1,964 Onroad Mobile(4) 2,469 4,830 --- --- 1,140 2,167 Point EGU(2) 1,504 4,410

--- --- 2,825

--- Point nonEGU(3) 3,125 2,405 --- 2,527 4,203 2,568 Total 31,047 34,685 --- --- 28,624 --- Sulfur Dioxide (TPY) Area(2) 10,923 8,812 --- 706 4,374 704 Nonroad MAR(4) 12,162 7,274

--- 937 765 1,009 Nonroad NMIM(4) 3,345 1,905 --- 55 67 58 Onroad Mobile(4) 3,649 917 --- --- 785 715 Point EGU(2) 50,898 37,299 15,076 --- 15,918 --- Point nonEGU(3) 10,389 3,401

--- 2,591 7,800 2,645 Total 91,366 59,608 --- --- 29,709 --- Volatile Organic Compounds (TPY) Area(3) 168,931 96,243 --- 89,972 134,104 89,699 Nonroad MAR(4) 2,020 3,355 --- 3,396 2,175 3,453 Nonroad NMIM(4) 80,884 47,520 --- 27,429 51,435 25,801 Onroad Mobile(4) 89,753 72,224 --- --- 31,415 24,123 Point EGU(2) 1,091 383

--- --- 228

--- Point nonEGU(3) 13,431 10,100 --- 10,080 19,902 10,035 Total 356,110 229,826 --- --- 239,259 --- 1) This trend is built from three sources: 2002 V3 with future projection to 2018 (Blue Column s) 2007 V3 with a projection to 2017 and 2020 (Tan Col umns) CAMD actual 2010 emissions as reported to the US EP A CAMD (White Columns) (2) Data meets or exceeds target of 90% complete ac ross all years. Units with incomplete data for one or more years have been completed by states or have be en removed so that a consistent set of data is presented across years. Therefore totals are not i dentical to modeled inventory or TSD. (3) Data does not meet target of 90% complete acros s all years. Total represents all units completed by state. Totals are not identical to modeled inventory or TS D. (4) Data identical to modeled inventory and TSD. N o revision to correct inconsistent methodology.

Nonroad MAR – includes commercial marine vessels, a irports, and railroad locomotives Nonroad NMIM – includes equipment included in USEPA ’s NMIM/NONROAD modelEmissions Trends Analysis for MANE-VU March 22, 2013 Page 49



### Exhibit 8.10 Annual Air Pollutant Emission Trends b y Sector between 2002 and 2020
New York

2002 2007 2010 2017 2018 2020 Data Source(1) 2002 V3 2007 V3 CAMD 2007 V3 2002 V3 2007 V3 Oxides of Nitrogen (TPY) Area(4) 99,463 72,053 --- 63,711 93,946 63,082 Nonroad MAR(4) 31,278 55,900

--- 39,249 27,033 36,309 Nonroad NMIM(4) 77,940 72,224 --- 43,456 45,059 38,842 Onroad Mobile(4) 319,733 305,589 --- --- 78,365 129,829 Point EGU(2) 84,206 46,826 27,018 --- 24,175 --- Point nonEGU(3) 26,058 23,080

--- 20,452 19,308 20,898 Total 638,678 575,672 --- --- 287,886 --- Direct PM2.5 (TPY) Area(4) 87,202 63,906 --- 68,408 84,231 70,000 Nonroad MAR(4) 1,150 2,258 --- 1,134 1,090 986 Nonroad NMIM(4) 7,623 6,710 --- 4,426 4,239 3,840 Onroad Mobile(4) 5,898 14,225 --- --- 2,542 7,079 Point EGU(2) 3,826 3,553

--- --- 9,258

--- Point nonEGU(3) 3,115 2,212 --- 2,244 3,568 2,265 Total 108,814 92,863 --- --- 104,928 --- Sulfur Dioxide (TPY) Area(4) 130,484 70,044 --- 11,651 100,453 11,670 Nonroad MAR(4) 5,959 10,639

--- 1,631 1,556 1,480 Nonroad NMIM(4) 6,886 3,955 --- 118 129 126 Onroad Mobile(4) 10,640 2,177 --- --- 1,794 1,866 Point EGU(2) 265,268 106,081 47,968 --- 98,150 --- Point nonEGU(3) 15,815 14,696

--- 13,110 18,374 13,187 Total 435,052 207,592 --- --- 220,456 --- Volatile Organic Compounds (TPY) Area(4) 507,365 195,976 --- 184,269 440,927 183,721 Nonroad MAR(4) 2,149 4,599 --- 4,045 2,345 4,001 Nonroad NMIM(4) 155,390 114,923 --- 67,231 102,182 60,939 Onroad Mobile(4) 287,845 161,385 --- --- 68,014 70,838 Point EGU(2) 1,433 2,339

--- --- 731

--- Point nonEGU(3) 9,870 8,379 --- 8,421 12,124 8,455 Total 964,052 487,601 --- --- 626,323 --- 1) This trend is built from three sources: 2002 V3 with future projection to 2018 (Blue Column s) 2007 V3 with a projection to 2017 and 2020 (Tan Col umns) CAMD actual 2010 emissions as reported to the US EP A CAMD (White Columns) (2) Data meets or exceeds target of 90% complete ac ross all years. Units with incomplete data for one or more years have been completed by states or have be en removed so that a consistent set of data is presented across years. Therefore totals are not i dentical to modeled inventory or TSD. (3) Data does not meet target of 90% complete acros s all years. Total represents all units completed by state. Totals are not identical to modeled inventory or TS D. (4) Data identical to modeled inventory and TSD. N o revision to correct inconsistent methodology.

Nonroad MAR – includes commercial marine vessels, a irports, and railroad locomotives Nonroad NMIM – includes equipment included in USEPA ’s NMIM/NONROAD modelEmissions Trends Analysis for MANE-VU March 22, 2013 Page 50



### Exhibit 8.11 Annual Air Pollutant Emission Trends b y Sector between 2002 and 2020 Pennsylvania

2002 2007 2010 2017 2018 2020 Data Source(1) 2002 V3 2007 V3 CAMD 2007 V3 2002 V3 2007 V3 Oxides of Nitrogen (TPY) Area(4) 47,991 47,545 --- 45,925 50,015 46,318 Nonroad MAR(4) 41,622 35,853

--- 25,801 25,017 23,969 Nonroad NMIM(4) 61,803 55,300 --- 30,422 30,567 26,143 Onroad Mobile(4) 346,472 354,117 --- --- 91,516 119,917 Point EGU(2) 203,175 187,981 133,095 --- 82,461 --- Point nonEGU(2) 91,129 71,961

--- 62,174 69,382 60,875 Total 792,192 752,757 --- --- 348,958 --- Direct PM2.5 (TPY) Area(4) 74,954 73,514 --- 73,054 82,649 73,226 Nonroad MAR(4) 2,664 1,436 --- 806 2,516 736 Nonroad NMIM(4) 5,747 5,338 --- 3,506 3,280 3,025 Onroad Mobile(4) 5,331 12,461 --- --- 2,064 4,614 Point EGU(2) 6,979 18,951

--- --- 23,588

--- Point nonEGU(2) 13,036 13,609 --- 12,557 14,548 12,677 Total 108,711 125,309 --- --- 128,645 --- Sulfur Dioxide (TPY) Area(4) 63,725 66,584 --- 55,878 48,475 55,018 Nonroad MAR(4) 2,629 3,698

--- 799 515 600 Nonroad NMIM(4) 5,240 2,968 --- 84 92 86 Onroad Mobile(4) 10,924 2,509 --- --- 1,436 896 Point EGU(2) 892,918 969,936 411,451 --- 133,186 --- Point nonEGU(2) 105,189 59,813

--- 50,208 83,637 50,371 Total 1,080,625 1,105,508 --- --- 267,341 --- Volatile Organic Compounds (TPY) Area(4) 240,829 176,781 --- 164,863 230,033 162,374 Nonroad MAR(4) 3,106 4,519 --- 3,949 2,780 3,941 Nonroad NMIM(4) 99,180 86,383 --- 51,373 67,154 46,392 Onroad Mobile(4) 176,090 163,693 --- --- 78,624 58,026 Point EGU(2) 1,033 765

--- --- 1,916

--- Point nonEGU(2) 36,358 28,987 --- 28,267 39,127 28,480 Total 556,596 461,128 --- --- 419,634 --- 1) This trend is built from three sources: 2002 V3 with future projection to 2018 (Blue Column s) 2007 V3 with a projection to 2017 and 2020 (Tan Col umns) CAMD actual 2010 emissions as reported to the US EP A CAMD (White Columns) (2) Data meets or exceeds target of 90% complete ac ross all years. Units with incomplete data for one or more years have been completed by states or have be en removed so that a consistent set of data is presented across years. Therefore totals are not i dentical to modeled inventory or TSD. (3) Data does not meet target of 90% complete acros s all years. Total represents all units completed by state. Totals are not identical to modeled inventory or TS D. (4) Data identical to modeled inventory and TSD. N o revision to correct inconsistent methodology.

Nonroad MAR – includes commercial marine vessels, a irports, and railroad locomotives Nonroad NMIM – includes equipment included in USEPA ’s NMIM/NONROAD modelEmissions Trends Analysis for MANE-VU March 22, 2013 Page 51



### Exhibit 8.12 Annual Air Pollutant Emission Trends b y Sector between 2002 and 2020
Rhode Island

2002 2007 2010 2017 2018 2020 Data Source(1) 2002 V3 2007 V3 CAMD 2007 V3 2002 V3 2007 V3 Oxides of Nitrogen (TPY) Area(4) 3,897 3,469 --- 3,301 4,252 3,329 Nonroad MAR(4) 449 3,262

--- 2,196 437 1,956 Nonroad NMIM(4) 4,541 4,388 --- 2,348 2,281 2,114 Onroad Mobile(4) 16,677 18,775 --- --- 5,351 14,380 Point EGU(2) 659 426 574 --- 576 --- Point nonEGU(3) 2,388 950

--- 854 2,158 862 Total 28,611 31,270 --- --- 15,055 --- Direct PM2.5 (TPY) Area(4) 2,065 3,896 --- 3,922 2,068 3,936 Nonroad MAR(4) 74 128 --- 80 78 71 Nonroad NMIM(4) 369 349 --- 216 224 191 Onroad Mobile(4) 211 733 --- --- 148 1,781 Point EGU(2) 28 56

--- --- 156

--- Point nonEGU(3) 175 124 --- 124 178 128 Total 2,922 5,286 --- --- 2,852 --- Sulfur Dioxide (TPY) Area(4) 4,558 3,897 --- 3,222 1,368 3,108 Nonroad MAR(4) 43 667

--- 95 35 59 Nonroad NMIM(4) 333 211 --- 7 7 7 Onroad Mobile(4) 425 161 --- --- 100 393 Point EGU(2) 13 15 15 --- 55 --- Point nonEGU(3) 2,659 1,501

--- 1,415 2,998 1,437 Total 8,031 6,452 --- --- 4,563 --- Volatile Organic Compounds (TPY) Area(4) 31,403 24,214 --- 20,292 23,306 19,750 Nonroad MAR(4) 84 184 --- 217 89 214 Nonroad NMIM(4) 7,695 6,721 --- 2,885 5,299 2,657 Onroad Mobile(4) 12,538 10,263 --- --- 6,305 12,806 Point EGU(2) 37 73

--- --- 42

--- Point nonEGU(3) 1,903 922 --- 945 1,781 963 Total 53,659 42,377 --- --- 36,822 --- 1) This trend is built from three sources: 2002 V3 with future projection to 2018 (Blue Column s) 2007 V3 with a projection to 2017 and 2020 (Tan Col umns) CAMD actual 2010 emissions as reported to the US EP A CAMD (White Columns) (2) Data meets or exceeds target of 90% complete ac ross all years. Units with incomplete data for one or more years have been completed by states or have be en removed so that a consistent set of data is presented across years. Therefore totals are not i dentical to modeled inventory or TSD. (3) Data does not meet target of 90% complete acros s all years. Total represents all units completed by state. Totals are not identical to modeled inventory or TS D. (4) Data identical to modeled inventory and TSD. N o revision to correct inconsistent methodology.

Nonroad MAR – includes commercial marine vessels, a irports, and railroad locomotives Nonroad NMIM – includes equipment included in USEPA ’s NMIM/NONROAD modelEmissions Trends Analysis for MANE-VU March 22, 2013 Page 52



### Exhibit 8.13 Annual Air Pollutant Emission Trends b y Sector between 2002 and 2020
Vermont

2002 2007 2010 2017 2018 2020 Data Source(1) 2002 V3 2007 V3 CAMD 2007 V3 2002 V3 2007 V3 Oxides of Nitrogen (TPY) Area(4) 3,215 3,996 --- 3,641 3,433 3,645 Nonroad MAR(4) 54 846

--- 837 62 834 Nonroad NMIM(4) 4,156 3,736 --- 2,359 2,198 2,104 Onroad Mobile(4) 20,670 18,072 --- --- 4,744 5,407 Point EGU(2) 267 428 173 --- 105 --- Point nonEGU(3) 560 441

--- 791 466 808 Total 28,922 27,519 --- --- 11,008 --- Direct PM2.5 (TPY) Area(4) 11,065 13,106 --- 12,593 12,059 12,517 Nonroad MAR(4) 10 50 --- 42 11 42 Nonroad NMIM(4) 475 454 --- 306 291 263 Onroad Mobile(4) 483 723 --- --- 144 332 Point EGU(2) 8 0.1

--- --- 25

--- Point nonEGU(3) 259 114 --- 98 246 97 Total 12,300 14,447 --- --- 12,776 --- Sulfur Dioxide (TPY) Area(4) 4,088 3,752 --- 3,158 4,764 3,085 Nonroad MAR(4) 5 17

--- 13 5 13 Nonroad NMIM(4) 366 202 --- 7 8 7 Onroad Mobile(4) 894 178 --- --- 82 62 Point EGU(2) 3 7 2 --- 35 --- Point nonEGU(3) 903 316

--- 248 1,127 243 Total 6,259 4,472 --- --- 6,021 --- Volatile Organic Compounds (TPY) Area(4) 23,266 14,108 --- 12,311 26,197 11,904 Nonroad MAR(4) 29 235 --- 209 34 212 Nonroad NMIM(4) 10,518 10,337 --- 6,713 7,532 5,863 Onroad Mobile(4) 17,288 9,641 --- --- 4,072 3,516 Point EGU(2) 122 22

--- --- 3

--- Point nonEGU(3) 1,079 373 --- 316 1,707 302 Total 52,302 34,716 --- --- 39,545 --- 1) This trend is built from three sources: 2002 V3 with future projection to 2018 (Blue Column s) 2007 V3 with a projection to 2017 and 2020 (Tan Col umns) CAMD actual 2010 emissions as reported to the US EP A CAMD (White Columns) (2) Data meets or exceeds target of 90% complete ac ross all years. Units with incomplete data for one or more years have been completed by states or have be en removed so that a consistent set of data is presented across years. Therefore totals are not i dentical to modeled inventory or TSD. (3) Data does not meet target of 90% complete acros s all years. Total represents all units completed by state. Totals are not identical to modeled inventory or TS D. (4) Data identical to modeled inventory and TSD. N o revision to correct inconsistent methodology.

Nonroad MAR – includes commercial marine vessels, a irports, and railroad locomotives Nonroad NMIM – includes equipment included in USEPA ’s NMIM/NONROAD modelEmissions Trends Analysis for MANE-VU March 22, 2013 Page 53



## 9.0 ELECTRONIC FILES

Exhibit 9.1 lists the file names for all final deli verables. These files are stored on MARAMA ftp site available for access by states agen cy personnel.

Exhibit 9.1 Emission Inventory Data Files

File Name Description
TSD_10_23_ETrend.docx Regional Emissions Trends Ana lysis for MANEVU
All MAR Data All states All Pollutants.xlsx Complet e set of data for MAR. This includes all MANE VU States and all pollutants.
[State] EGU - Reviewed.xlsx An analysis of MANE VU NOX, SO2, PM25, and VOC emissions for electric generating units
where the data has been reviewed and accepted by the state. Replace [State] with the
abbreviation for the MANE VU state of interest.Example, for Delaware: DE_EGUReviewed.xlsx
[State] EGU.xlsx An analysis of MANE VU NOX, SO2, P M25, and VOC emissions for electric generating units where the data has not yet been reviewed and accepted by the state. Replace [State] with the
abbreviation for the MANE VU state of interest.Example, for New Jersey: NJ_EGUReviewed.xlsx

[Pollutant] Area Tier 3 Analysis.xlsx An analysis o f NO X emissions from area sources by MANE VU state, pollutant and year. This dataset breaks the data into Tiers up to Tier 3. Replace [Pollutant] with NOX, SO2, PM25 or SO2. Example NOX Area Tier3 Analysis.xlsx.
[State] NonEGU.xlsx An analysis for Non-EGUs by MAN E VU state, this includes all pollutants for each MANE VU state. Replace [State] with the abbreviation for the MANE VU state of interest. Example for New York: NY NOnEGU.xlsx.
Nonroad _Complete_Analysis.xlsx An analysis of Nonr oad emission trend by pollutant, MANE VU state and year.
Onroad Analysis.xlsx Summarized set of data for Onr oad at the state level. This includes all pollutants for all MANE VU states and all years.Emissions Trends Analysis for MANE-VU March 22, 2013 Page 54



## 10.0 REFERENCES

CAMD 2010. Data downloaded on July 14 th 

### 2011. http://camddataandmaps.epa.gov/gdm/index.cfm?fuseac tion=emissions.wizard

EIA 2005 . Annual Energy Outlook 2005 with Projections to 2 025 ftp://tonto.eia.doe.gov/forecasting/0383 (2005).pdf

EIA 2008 . Annual Energy Outlook 2008 with Projections to 2 030. http://www.eia.gov/oiaf/aeo/pdf/0383(2008).pdf

EIA 2009 . Annual Energy Outlook 2009 with Projections to 2 030 http://www.eia.gov/oiaf/aeo/pdf/0383(2009).pdf.

EIA 2010 . Annual Energy Outlook 2010 with Projections to 2 035 http://www.eia.gov/oiaf/aeo/pdf/0383(2010).pdf

ERTAC 2009. ERTAC Rail Emissions Inventory Part 3: Class II a nd III Locomotives. Michelle Bergin, GA Environmental Protection Divisi on Matthew Harrell, IL Environmental Protection Agency Mark Janssen, Lake Michigan Air Directors Consortium http://www.gaepd.org/air/airpermit/downloads/planni ngsupport/regdev/locomotives/class2 _3_doc2012.pdf

MANE-VU 2006. Prepared by E.H. Pechan & Associates, Inc. Technic al Support Document for 2002 MANE-VU SIP Modeling Inventories, Version 3. November 2006. http://www.marama.org/technical-center/emissions-in ventory/2002-inventory-andprojections/mane-vu-2002-emissions-inventory

MANE-VU 2007. Prepared by MACTEC Federal Programs, Inc. Develo pment of Emission Projections for 2009, 2012, and 2018 for N onEGU Point, Area, and Nonroad Sources in the MANE-VU Region. February 2007. http://www.marama.org/technicalcenter/emissions-inventory/2002-inventory-and-proje ctions/mane-vu-future-yearemissions-inventory

MANE-VU 2011a. Submitted by AMEC Environment & Infrastructure an d SRA International, Inc. Technical Support Document for the Development of the 2007 Emissions Inventory for Regional Air Quality Modeli ng in the Northeast/Mid-Atlantic Region Version 3.3. January 2011. http://www.marama.org/technical-center/emissionsinventory/2007-emissions-and-projections/version-3- 2007-emissions-inventory

MANE-VU 2011b. Submitted by AMEC Environment & Infrastructure an d SRA International, Inc. Technical Support Document for the Development of the 2017/2020 Emission Inventories for Regional Air Quality Model ing in the Northeast/Mid-AtlanticEmissions Trends Analysis for MANE-VU March 22, 2013 Page 55



### Region Version 3.3. January 2012. http://www.marama.org/technical-center/emissionsinventory/2007-emissions-and-projections/future-yea r-inventory-version-3

MARAMA 2009a. Documentation of 2018 Emissions from Electric Gener ating Units in the Eastern United States for MANE-VU’s Regional Ha ze Modeling. http://marama.org/publications_folder/EGU_Projectio ns_Summary_Final_Aug_2009.pdf

MARAMA 2009b . Emissions Factors for Condensable Particulate Ma tter Emissions From Electric Generating Units. http://marama.org/publications_folder/TechnicalMemo _EFs_for_CPM_from_EGUsRevise d_with_PAcomments_20090129.pdf

MARAMA 2012 . Combined Quality Assurance Project Plan (QAPP) a nd Work Plan.

MARAMA 2013 . MANE-VU States Emissions Inventory Completeness by State, Sector
and Pollutant.

NESCAUM 2006. Contributions to Regional Haze in the Northeast and Mid-Atlantic
United States. http://des.nh.gov/organization/divisions/air/do/asa b/rhp/documents/b.pdf

NESCAUM 2006b . Development of MANE-VU Mobile Source Projection Inventories for SMOKE/MOBILE6 Application. http://www.nescaum.o rg/documents/nescaummanevu-2002-and-future-onroad-inventory-20060620.pd f

NESCAUM 2011 . Development of MANE-VU Onroad Mobile Source Emis sions for 2007 and 2020 using MOVES. Prepared by Huiyan Yang of NESCAUM. http://www.nescaum.org/documents/nescaum-2007-2020- moves-modeling-tsd20120118.pdf

USEPA 2005. Documentation For Aircraft, Commercial Marine Vesse l, Locomotive, and other Nonroad Components of the National Emissions Inventory, Volume I – Methodology; EPA Contract No.: 68-D-02-063. Eastern Research Group (ERG) for E.H. Pechan & Associates, Inc. Prepared for the US EPA Emissions, Monitoring and Analysis Division, Sept. 30, 2005. ftp://ftp.epa.gov/EmisInventory/2002finalnei/docume ntation/mobile/2002nei_mobile_nonr oad_methods.pdf

USEPA 2009a . Documentation for Aircraft Component of the Nati onal Emissions Inventory Methodology. ERG No.: 0245.02.302.001. Fo r Laurel Driver of OAQPS. http://www.epa.gov/ttnchie1/net/aircraft_component. pdf

USEPA 2009b . Air Pollution Emissions from Highway Vehicles: Wh at MOVES Tells Us. M. Beardsley, D. Brzezinski, J. Koupal and J. Wari la, US EPA OTAQ. Presented at theEmissions Trends Analysis for MANE-VU March 22, 2013 Page 56



### 2009 USEPA Emissions Inventory Conference in Baltim ore MD. http://www.epa.gov/ttn/chief/conference/ei18/sessio n6/beardsley.pdf

USEPA 2010. U.S. Environmental Protection Agency. Transport Rul e Emission Inventories Notice of Data Availability (NODA). Docket ID No. E PA-HQ-OAR-2009-0491. October 27, 2010. TR_EI_NODA_relevant_CoSTpackets_and_inventori es.xls ftp://ftp.epa.gov/EmisInventory/2005v4/tr_ei_noda

USEPA 2011. U.S. Environmental Protection Agency. Emission Stan dards Reference Guide. http://www.epa.gov/oms/regs/nonroad/aviation/420f10 013.pdf

USEPA 1997. AP-42. Compilation of Air Pollutant Emission Fact ors. 

### Fifth Edition. http://www.epa.gov/ttnchie1/ap42/Emissions Trends Analysis for MANE-VU March 22, 2013 Appendix C



### Appendix A

State Review Workgroup

State Emission Inventory Contact SIP Writer Contact Delaware David Fees Jack Sipple 

### New Jersey Judy Rand Sharon Davis Danny Wong Stella Oluwaseun-Apo Ray Papalski 

### Rhode Island Karen Slattery Karen Slattery


### Vermont Jeff Merrell Rich Periot


### Connecticut Steven Potter Wendy Jacobs 

### New Hampshire David Healy Jeff Underhill 

### New York Ona Papageorgiou Diana Rivenburgh


### Maine Kristen Colby Jeff Crawford 

### Pennsylvania Randy Bordner (stationary) Randy Bordner Chris Trostle (mobile) 

### Maryland Roger Thunell Brian Hug Mary Jane Rutkowski 

### District of Columbia Jessica Daniels Jessica Daniels 

### Massachusetts Ken Santlal William LamkinNH Regional Haze 5

- Year Progress Report



### ATTACHMENT E

N ew H ampshire Administrative Rule Env

- A 2302.02 Emission Standar ds Applicable to Tangential

- Firing, Dry

- Bottom Boilers (Amended)NH Regional Haze 5

- Year Progress ReportNH Regional Haze 5

- Year Progress Report



### ATTACHMENT F
Evidence of Plan’s Adoption

[ 40 CFR Part 51, Appendix V, 2.1(b) ]NH Regional Haze 5

- Year Progress Report



### EVIDENCE OF PLAN’S ADOPTION

The cover letter, signed by the Governor’s designee, is evidence that the State of New Hampshire has adopted this revision to the State Implementation Plan (SIP). The only state requirement for SIP submittals is that

, at least 30 days before the date of any public hearing related to SIP revisions, public n otice shall be published in a newspaper of general daily statewide circulation (see Env

- A 204.01)

. Then

, if a hearing is held, it must be conducte d in accordance with Env

- C 205 (s ee Env

- A 204.02)

. F or evidence of the plan’s adopti on in accordance with En v

- A 204, s ee the Evidence of Public Notice and the Certification of Public Hearing (Attachments I and J ).NH Regional Haze 5

- Year Progress Report



### ATTACHMENT G
Evidence of Legal Authority

[ 40 CFR Part 51, Appendix V, 2.1(c) ]
Laws of New Hampshire, RSA 125

- C:6 Powers and D uties of the CommissionerNH Regional Haze 5

- Year Progress Report



### This page is intentionally left blank.NH Regional Haze 5

- Year Progress ReportNH Regional Haze 5

- Year Progress ReportNH Regional Haze 5

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### ATTACHMENT H
Evidence That New Hampshire Followed All Procedural Requirements

[ 40 CFR Part 51, Appendix V, 2.1(e) ]NH Regional Haze 5

- Year Progress Report



### EVIDENCE THAT NEW HAMPSHIRE FOLLOWED ALL PROCEDURAL REQUIREMENTS

The only state requirement for SIP submittals is that, at least 30 days before the date of any public hearing related to SIP revisions, public notice shall be published in a ne wspaper of general daily
st atewide circulation (see Env

- A 204.01)

. Then

, if a hearing is held, it must be conducte d in accordance with Env

- C 205 (s ee Env

- A 204.02)

. Fo r evidence of the plan’s adopti on in accordance with Env

- A 204, s ee the Evidence of Pu blic Notice and the Certification of Public Hearing (Attachments I and J).NH Regional Haze 5

- Year Progress Report



### ATTACHMENT I

Evidence of Public Notice
[40 CFR Part 51, Appendix V, 2.1(f)]NH Regional Haze 5

- Year Progress Report



### This page is intentionally left blank.NH Regional Haze 5

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- Year Progress ReportNH Regional Haze 5

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### ATTACHMENT J
Certification of Public Hearing

[ 40 CFR Part 51, Appendix V, 2.1(g)]NH Regional Haze 5

- Year Progress ReportNH Regional Haze 5

- Year Progress Report



### ATTACHMENT K
Compilation of Public Comments and NHDES’s Response Thereto

[ 40 CFR Part 51, Appendix V, 2.1(h) ]NH Regional Haze 5

- Year Progress ReportNH Regional Haze 5

- Year Progress ReportNH Regional Haze 5

- Year Progress ReportNH Regional Haze 5

- Year Progress ReportNH Regional Haze 5

- Year Progress ReportNH Regional Haze 5

- Year Progress ReportNH Regional Haze 5

- Year Progress Report



## NHDES’s Response to Comments on New Hampshire’s Regional Haze 5

- Year Progress Report

The New Hampshire Department of Environmental Services (NHDES) held a public hearing on September 23, 2014, and provided a public comment period, ex tending from that date to October 3, 2014, to accept testimony on New Hampshire’s draft Regional Haze Progress report and related amendments to administrative rule Env

- A 2302.02. No members of the public attended the hearing, but letters containing writte n comments were received from three entities: the U.S. Environmental Protection Agency (EPA), the U.S. Department of the Interior, National Park Service (NPS); and the U.S. Department of Agriculture, Forest Service (FS). Copies of the letters are attache d. The following is a summary of comments received and NHDES’s responses thereto.

Comment: EPA requested a technical clarification in the SIP Submittal (page v) and the correction of a typographical error in Section 12. EPA also encouraged New Hampshir e to move forward with adoption of a low

- sulfur fuel oil strategy as outlined in the MANE

- VU Ask.

Response: NHDES has included the requested minor revisions in the final document. New Hampshire continues to be interested in pursuing a low

- sulfur fuel oi l strategy. Recently, the Oil Heat Council of New Hampshire requested that the New Hampshire legislature consider a bill in the 2015 legislative session to require the use of low

- sulfur fuel oil throughout the state, effective in 2018. NHDES is actively engaged in the legislative process that would allow such a change to happen.

Comment: FS concurred that New Hampshire’s regional haze plan is sufficient in its current form to achieve the 2018 reasonable progress goals for visibility. FS also noted that the observed 2009

- 2013 visibility data for New Hampshire’s Class I areas are already better than the 2018 reasonable progress goals.

(No response is needed.)

Comment: NPS commented that New Hampshire has met the regulatory requirements for regional h aze progress reports and that New Hampshire’s regional haze SIP is sufficient to meet the 2018 reasonable progress goals at Class I areas in New Hampshire and neighboring states. NPS requested a few minor adjustments to the text. NPS also asked for an es timate of the magnitude of SO 2 

### emission reductions that could result from adoption of a low

- sulfur fuel oil strategy.

Response: NHDES has made the requested revisions to the text. With respect to the low

- sulfur fuel oil strategy, any estimate will dep end on the assumptions applied. As a starting point, it may be assumed that 2012 was a typical year, in which state totals for distillate and residual fuel oil consumption for all sectors were 3,589,000 and 262,000 bbl, respectively. 33 

### Further, it may be assumed that the reductions in fuel sulfur content from a low

- S strategy would average 0.3% for distillate oil and 1.0% for residual oil. Under this specific scenario, SO 2 

### emissions resulting from the combustion of both grades of fuel oil would be reduced by about 4,000 tons annually. The actual emission reductions could be smaller than this amount because current fuel oil in bulk storage already includes some lower

- sulfur material whose exact specifications are unknown.

33 Source: U.S. Energy Information Administration (EIA). At the time of this estimate, 2012 is the most recent year for which EIA annual data ar e available. See http://www.eia.gov/state/data.cfm?sid=NH#ConsumptionExpenditures

.