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7.0 Emission Inventory

Section 51.308(d)(4)(v) of the EPA’s Regional Haze Rule, 40 CFR 51.308 

requires the establishment of a statewide emission inventory of pollutants that 

are reasonably anticipated to cause or contribute to visibility impairment in any 

mandatory Class I area. The pollutants inventoried by New York include volatile 

organic compounds, nitrogen oxides, fine particles (PM2.5), coarse particles 

(PM10), ammonia, carbon monoxide and sulfur dioxides. The information for New 

York was provided to MANE-VU, which conducted the modeling of visibility 

impacts for the MANE-VU region. This section provides information on the 

development of baseline and future emission inventories that were used in 

modeling visibility for the purposes of this SIP. 

7.1 Baseline and Future Year Emission Inventories for Modeling

Section 51.308(d)(3)(iii) of the EPA’s Regional Haze Rule requires the State of 

New York as well as other states to identify a baseline emission inventory upon 

which future emission projections will be based and from which the necessary 

emission reductions for meeting reasonable progress goals can be determined. 

Based on EPA guidance entitled, 2002 Base Year Emission Inventory SIP 

Planning: 8-hour Ozone, PM 2.5, and Regional Haze Programs, found at the 

following link: 

http://www.epa.gov/ttnchie1/eidocs/2002baseinven_102502new.pdf

 

which identifies the anticipated baseline emission inventory year for regional 

haze, MANE-VU and the State of New York are using 2002 as the baseline year. 

From this, future year inventories were developed for 2009, 2012 and 2018 

based on this base year. These future year emission inventories include 

emissions growth due to projected increases in population and economic activity 

as well as the emissions reductions due to the implementation of control 

measures. 

7.1.1 Baseline Inventory

The 2002 emissions inventory data were first generated by individual states in 

the MANE-VU area. MARAMA then coordinated and quality-assured the 2002 

inventory data, and projected it for the relevant control years. The 2002 

emissions from non-MANE-VU areas within the modeling domain were obtained 

from other Regional Planning Organizations for their corresponding areas. 

These Regional Planning Organizations included the Visibility Improvement State 

and Tribal Association of the Southeast (VISTAS), the Midwest Regional 

Planning Organization (MRPO) and the Central Regional Air Planning 
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Association (CENRAP). 

Version 3 of the 2002 base year emission inventory was used in the regional 

modeling exercise. A technical support document for the MANE-VU 2002 base 

inventory is presented in Appendix H, Technical Support Document (TSD) for 

2002 MANE-VU SIP Modeling Inventories, Version 3. This document explains 

the data sources, methods, and results for preparing this version of the 2002 

base year criteria air pollutant and ammonia emissions inventory. 

Documentation for the future year estimations is presented in Appendix E, 

Development of Emission Projections for 2009, 2012 and 2018 for NonEGU 

Point, Area, and Nonroad Sources in the MANE-VU Region of this document. 

The inventory and supporting data prepared includes the following: 

1. Comprehensive, county-level, mass emissions and modeling inventories 

for 2002 emissions for criteria air pollutants and ammonia for the State 

and Local agencies included in the MANE-VU region. 

2. The temporal, speciation, and spatial allocation profiles for the MANE-VU 

region inventories. 

3. Inventories for wildfires, prescribed burning and agricultural field burning 

for the southeastern provinces of Canada. 

4. Inventories for other Regional Planning Organizations, Canada, and 

Mexico. 

The mass emissions inventory files were converted to the National Emissions 

Inventory Input Format Version 3.0. The modeling inventory files were 

processed in Sparse Matrix Operator Kernel Emissions/Inventory Data Analyzer 

(SMOKE). The inventories include annual emissions for oxides of nitrogen (NOX), 

volatile organic compounds (VOC), carbon monoxide, ammonia, particles with an 

aerodynamic diameter less than or equal to a nominal 10 micrometers (PM10) 

and PM2.5. Temporal profiles prepared for MANE-VU were used to calculate 

daily emissions for all MANE-VU states. 

Work on Version 1 of the 2002 MANE-VU inventory began in April 2004. The 

consolidated inventory for point, area, onroad, and nonroad sources was 

prepared starting with the inventories that MANE-VU state and local agencies 

submitted to the EPA from May through July of 2004 as a requirement of the 

Consolidated Emissions Reporting rule. The EPA’s format and content quality 

assurance (QA) programs (and other QA checks not included in the EPA’s QA 

software) were run on each inventory to identify format and/or data content 

issues. A contractor, E.H. Pechan & Associates, Inc. (Pechan), worked with the 

MANE-VU state/local agencies and the MARAMA staff to resolve QA issues and 

augment the inventories to fill data gaps in accordance with the Quality 

Assurance Project Plan prepared for MANE-VU. The final inventory and SMOKE 

and input files were finalized during January 2005. 
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Work on Version 2 (covering the period from April through September 2005) 

involved incorporating revisions requested by some MANE-VU state/local 

agencies on the point, area, and onroad inventories. Work on Version 3 

(completed on November 20, 2006) included additional revisions to the point, 

area, and onroad inventories as requested by some states. Thus, the Version 3 

inventory for point, area, and onroad sources was built upon Versions 1 and 2. 

This work also included development of the biogenics inventory. In Version 3, 

the nonroad inventory was completely redone because of changes that the EPA 

made to the NONROAD2005 model. Emissions inventory data files are available 

on the MARAMA website at: 

http://www.marama.org/visibility/EI_Projects/index.html 

7.1.2 Future Year Emission Control Inventories 

An inventory technical support document for these future inventories is included 

in Appendix E, Development of Emission Projections for 2009, 2012 and 2018 for 

NonEGU Point, Area, and Nonroad Sources in the MANE-VU Region of this 

document and explains the data sources, methods, and results for future year 

emission forecasts for three years; four emission sectors; two emission control 

scenarios; seven pollutants; and eleven states plus the District of Columbia. The 

following is a summary of the future year inventories that were developed: 

The three projection years are 2009, 2012, and 2018; 

1. The five source sectors are Electric Generating Units (EGUs), non-electrical 

generating units (non EGUs), point sources, area sources, and nonroad 

mobile sources. MANE-VU prepared EGU projections using the Integrated 

Planning Model (IPM) and onroad mobile source projections using the 

SMOKE emission modeling system.

2. The two emission control scenarios are: 

a. A combined “on-the-books/on-the-way” (OTB/OTW) control strategy 

accounting for emission control regulation already in place, as well as 

some emission control regulations that will be instituted as a result of this 

SIP. 

b. A beyond on the way (BOTW) scenario to account for controls from 

potential new regulations that may be necessary to meet visibility and 

other regional air quality goals. 

(Note that these measures are described in detail in Section 10, and that 
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emission reductions based on currently expected measures to which New 

York is committing are presented at the end of this section). 

3. The inventories were developed for seven pollutants, which are SO2, NOX, 

VOCs, carbon monoxide, PM10 – Primary (sum of the filterable and 

condensable components), PM2.5 – Primary (sum of the filterable and 

condensable components), and ammonia. 

4. The states are those that comprise the MANE-VU region. In addition to the 

District of Columbia, the other 11 MANE-VU states are Connecticut, 

Delaware, Maine, Maryland, Massachusetts, New Hampshire, New Jersey, 

New York, Pennsylvania, Rhode Island, and Vermont. 

7.2 Inventories for Specific Source Types

There are five emission source classifications in the emissions inventory as 

follows; Stationary point, Stationary area, Off-road mobile, On-road mobile, and 

Biogenic. 

Stationary point sources are large sources that emit greater than a specified 

tonnage per year. Stationary area sources are those sources whose emissions 

are relatively small but due to the large number of these sources, the collective 

emissions could be significant (i.e., dry cleaners, service stations, agricultural 

sources, fire emissions, etc.). Off-road mobile sources are equipment that can 

move but do not generally use roadways, (i.e., lawn mowers, construction 

equipment, railroad locomotives, aircraft, etc.). On-road mobile sources are 

automobiles, trucks, and motorcycles that use the roadway system. The 

emissions from these sources are estimated by vehicle type and road type. 

Biogenic sources are natural sources like trees, crops, grasses and natural 

decay of plants. Stationary point sources emission data is tracked at the facility, 

point and process level. For all other source types, emissions are summed on 

the county level. 

7.2.1 Stationary Point Sources

Point source emissions are emissions from large individual sources. Generally, 

point sources have permits to operate and their emissions are individually 

calculated based on source specific factors on a regular schedule. The largest 

point sources are inventoried annually. These are considered to be major 

sources having emissions of 100 tons per year (TPY) of a criteria pollutant, 25 

tpy of NOx and VOC in the New York City Metropolitan Area, 10 tpy of a single 

hazardous air pollutant (HAP), or 25 tpy total HAPs. Emissions from smaller 

sources are also calculated individually but less frequently. Point sources are 

grouped into EGU sources and other industrial point sources, termed as nonEGU point sources. 
7-5 

7.2.1.1 Electric Generating Units

The base year inventory for EGU sources used 2002 continuous emissions 

monitoring (CEM) data reported to the EPA in compliance with the Acid Rain 

program or 2002 hourly emission data provided by stakeholders. These data 

provide hourly emissions profiles that can be used in the modeling of emissions 

of SO2 and NOx from these large sources. Emission profiles are used to estimate 

emissions of other pollutants (volatile organic compounds, carbon monoxide, 

ammonia, fine particles) based on measured emissions of SO2 and NOx. 

Future year inventories of EGU emissions for 2009 and 2018 were developed 

using the IPM model to forecast growth in electric demand and replacement of 

older, less efficient and more polluting power plants with newer, more efficient 

and cleaner units. While the output of the IPM model predicts that a certain 

number of older plants will be replaced by newer units to meet future electric 

growth and state-by-state NOx and SO2 caps, the State of New York did not 

directly rely upon the closure of any particular plant in establishing the 2018 

inventory upon which the reasonable progress goals were set. This results in a 

conservative (higher) future year emission estimate. 

7.2.1.2 Non-EGU Point Sources

The non-EGU category used annual emissions as reported for the base year 

2002 in MANE-VU Version 3. These emissions were temporally allocated to 

month, day, and source category code (SCC) based allocation factors. The 

general approach for estimating future year emissions was to use growth and 

control data consistent with EPA’s CAIR analyses. This data was supplemented 

with site-specific growth factors as appropriate. 

7.2.2 Stationary Area Sources

Stationary area sources include sources whose individual emissions are 

relatively small but due to the large number of these sources, the collective 

emissions are significant. Some examples include the combustion of fuels for 

heating, dry cleaners, and service stations. Emissions are estimated by 

multiplying an emission factor by some known indicator of collective activity, such 

as fuel usage, or number of households or population. The general approach for 

estimating future year emissions was to use growth and control data consistent 

with EPA’s CAIR analyses. This data was supplemented with state-specific 

growth factors as appropriate. 

7.2.3 Off-Road Mobile Sources

Off-road mobile sources are equipment that can move but do not use the 
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roadways, such as construction equipment, aircraft, railroad locomotives, and 

lawn and garden equipment. For the majority of the off-road mobile sources, the 

emissions for base year 2002 were estimated using the EPA’s nonroad model. 

The nonroad model assumes that a certain number of off-road sources will be 

replaced every year by newer, less polluting vehicles that meet the new EPA 

standards for off-road sources. These lower emissions have been built into the 

2018 inventory as well as the benefits received from lower sulfur gasoline in offroad vehicles. Aircraft engines, railroad locomotives and commercial marine 

vessels are not included in the nonroad model. 

7.2.4 Highway Mobile Sources

For on-road vehicles, EPA’s MOBILE6.2 was used to estimate emissions. For 

future year emissions the MOBILE6.2 model considers that a certain number of 

the vehicle fleet in each State will be replaced every year by newer, less polluting 

vehicles that meet the California Low Emission Vehicle standards promulgated 

by New York State as 6NYCRR Part 218. These lower emissions have been 

built into the 2018 inventory as well as the benefits received from lower sulfur 

gasoline in on-road diesel and gasoline vehicles and the 2007 heavy-duty diesel 

standards. All new mobile source measures and standards, as well as any 

benefits from implementation of individual State Inspection and Maintenance 

programs, were used in developing the 2018 inventory. 

7.2.5 Biogenic Emission Sources

Biogenic emissions were estimated using SMOKE-BEIS3 (Biogenic Emission 

Inventory System 3 version 0.9) preprocessor. Further information on Biogenic 

emissions estimation is contained in the modeling section of this document. 

7.3 Emission Processor Selection and Configuration (SMOKE) 

The mass emissions inventory files were converted to the National Emissions 

Inventory Input Format Version 3.0. The modeling inventory files were 

processed in Sparse Matrix Operator Kernel Emissions/Inventory Data Analyzer 

(SMOKE). The SMOKE Processing System was selected for the modeling 

analysis. SMOKE is principally an emissions processing system, as opposed to 

a true emissions inventory preparation system, in which emissions estimates are 

simulated from “first principles.” This means that, with the exception of mobile 

and biogenic sources, its purpose is to provide an efficient, modern tool for 

converting emissions inventory data into the formatted emissions files required 

for a photochemical air quality model. Inside the MANE-VU region, the modeling 

inventories were processed by the Department using the SMOKE (Version 2.1) 

processor to provide inputs for the CMAQ model. A detailed description of all 

SMOKE input files such as area, mobile, fire, point and biogenic emissions files 

and the SMOKE model configuration are provided in the Technical Support 
7-7 

Document on Agricultural and Forestry Smoke Management in the MANE-VU 

Region, Appendix I. The MANE-VU member states selected several control 

strategies for inclusion in the modeling. Emission reduction requirements 

mandated by the Clean Air Act were also included in projecting future year 

emissions. In addition, Section 51.308(d)(3)(v)(D) requires the State of New 

York to consider source retirement and replacement schedules in developing the 

future inventories and long-term strategy. 

7.4 Sources of Visibility Impairing Pollutants in MANE-VU

This section explores the origin and quantity of haze-forming pollutants emitted in 

the eastern and the mid-Atlantic United States. Section 51.308(d)(4)(v) of EPA’s 

Regional Haze Rule requires a statewide emission inventory of pollutants that 

are reasonably anticipated to cause or contribute to visibility impairment in any 

mandatory Class I area. The pollutants that affect fine particle formation, and 

thus contribute to regional haze, are sulfur oxides (SOX), nitrogen oxides (NOX), 

volatile organic compounds (VOC), and ammonia (NH3). Particles with an 

aerodynamic diameter less than or equal to 10 and 2.5 μm (i.e., primary PM10

and PM2.5) can be directly emitted from various sources. 

The emissions dataset illustrated below is the 2002 MANE-VU Version 2 regional 

haze emissions inventory. The emission inventories include carbon monoxide 

(CO), but it is not considered here as it does not contribute to regional haze. The 

MANE-VU regional haze emissions inventory version 3.0, released in April 2006, 

has superseded version 2.0 for modeling purposes. This inventory update was 

developed through the Mid-Atlantic Regional Air Management Association 

(MARAMA) for the MANE-VU RPO. The trends among recent emission 

inventories presented here use the 1996 EPA NET and 1999 NEI and Version 2 

of the MANE-VU inventory. This section describes emission characteristics by 

pollutant and source type (e.g., point, area, and mobile). 

7.5 Emission Inventory Characteristics

This section reviews trends in emissions of SO2, VOC, NOx, PM and ammonia. 

The trends among recent emission inventories presented here use the 1996 EPA 

NET and 1999 NEI and Version 3.0 of the 2002 MANE-VU inventory.1

1 This 

 1 EPA's Emission Factor and Inventory Group (EFIG) (EPA/OAR (Office of Air and 

Radiation)/OAQPS (Office of Air Quality Planning and Standards)/EMAD (Emissions, Monitoring and 

Analysis Division) prepares a national database of air emissions information with input from numerous 

state and local air agencies, from tribes, and from industry. This database contains information on 

stationary and mobile sources that emit criteria air pollutants and their precursors, as well as hazardous 

air pollutants (HAPs). The database includes estimates of annual emissions, by source, of air pollutants in 

each area of the country on an annual basis. The NEI includes emission estimates for all 50 states, the 

District of Columbia, Puerto Rico, and the Virgin Islands. Emission estimates for individual point or major 
7-8 

section describes emission characteristics by pollutant and source type (e.g., 

point, area, and mobile). As described later, this data was superseded by more 

up-to-date data for modeling purposes, but this data shows trends in emissions. 

7.5.1 Sulfur Dioxide (SO2)

SO2 is the primary precursor pollutant for sulfate particles. Sulfate particles 

commonly account for more than 50 percent of particle-related light extinction at 

northeastern Class I areas on the clearest days and for as much as or more than 

80 percent on the haziest days. Hence, SO2 emissions are an obvious target of 

opportunity for reducing regional haze in the eastern United States. Combustion 

of coal and, to a lesser extent, of certain petroleum products accounts for most 

anthropogenic SO2 emissions. In fact, in 1998 a single source category, coalburning power plants, was responsible for two-thirds of total SO2 emissions 

nationwide (NESCAUM, 2001a). Figure 7-1 shows SO2 emissions trends in the 

MANE-VU states extracted from the NEI for the years 1996, 1999, and the 2002 

MANE-VU inventory (EPA 2005 and MARAMA, 2004). 

Most of the states (with the exception of Maryland) show declines in year 2002 

annual SO2 emissions as compared to 1996 emissions. Some of the states 

show an increase in 1999 followed by a decline in 2002 and others show 

consistent declines throughout the entire period. The upward trend in emissions 

after 1996 probably reflects electricity demand growth during the late 1990s 

combined with the availability of banked emissions allowances from initial overcompliance with control requirements in Phase 1 of the EPA Acid Rain Program. 

This led to relatively low market prices for allowances later in the decade, which 

encouraged utilities to purchase allowances rather than implement new controls 

as electricity output expanded. 

The observed decline in the 2002 SO2 emissions inventory reflects 

implementation of the second phase of the EPA Acid Rain Program, which in 

2000 further reduced allowable emissions and extended emissions limits to more 

power plants. Figure 7-2 shows the percent contribution from different source 

categories to overall, annual 2002 SO2 emissions in the MANE-VU states. The 

chart shows that point sources dominate SO2 emissions, which primarily consist 

of stationary combustion sources for generating electricity, industrial energy, and 

 sources (facilities), as well as county level estimates for area, mobile and other sources, are available 

currently for years 1985 through 1999 for criteria pollutants, and for years 1996 and 1999 for HAPs. Data 

from the NEI help support air dispersion modeling, regional strategy development, setting regulation, air 

toxics risk assessment, and tracking trends in emissions over time. For emission inventories prior to 

1999, the National Emission Trends (NET) database maintained criteria pollutant emission estimates and 

the National Toxics Inventory (NTI) database maintained HAP emission estimates. Beginning with 1999, 

the NEI began preparing criteria and HAP emissions data in a more integrated fashion to take the place 

of the NET and the NTI. 
7-9 

heat. Smaller stationary combustion sources called “area sources” (primarily 

commercial and residential heating, and smaller industrial facilities) are another 

important source category in the MANE-VU states. By contrast, on-road and 

non-road mobile sources make only a relatively small contribution to overall SO2

emissions in the region (NESCAUM, 2001). 

Figure 7-1 - State Level Sulfur Dioxide Emissions 

0.0

0.2

0.4

0.6

0.8

1.0

1.2

1.4

Connecticut

Delaware

District of Columbia

Maine

Maryland

Massachusetts

New Hampshire

New Jersey

New York

Pennsylvania

Rhode Island

Vermont

million t/y

NEI 1996

NEI 1999

MV 2002 v.2
7-10 

Figure 7-2 - 2002 SO2 Emissions (Bar graph: Percentage fraction of four source 

 categories, Circle: Annual emissions amount in million (106) tons per year)

0%

25%

50%

75%

100%

Connecticut

Delaware

District of Columbia

Maine

Maryland

Massachusetts

New Hampshire

New Jersey

New York

Pennsylvania

Rhode Island

Vermont

0.0

0.2

0.4

0.6

0.8

1.0

1.2

million t/y

AREA NONROAD ONROAD POINT Emission
7-11 

7.5.2 Volatile Organic Compounds (VOCs)

Existing emission inventories generally refer to “volatile organic compounds” 

(VOCs) as hydrocarbons whose volatility in the atmosphere makes them 

particularly important from the standpoint of ozone formation. From a regional 

haze perspective, there is less concern with the volatile organic gases emitted 

directly to the atmosphere and more with the secondary organic aerosol (SOA) 

that the VOCs form after condensation and oxidation processes. Thus, the VOC 

inventory category is of interest primarily from the organic carbon perspective of 

PM2.5. After sulfate, organic carbon generally accounts for the next largest share 

of fine particle mass and particle-related light extinction at northeastern Class I 

sites. The term organic carbon encompasses a large number and variety of 

chemical compounds that may come directly from emission sources as a part of 

primary PM or may form in the atmosphere as secondary pollutants. The organic 

carbon present at Class I sites includes a mix of species, including pollutants 

originating from anthropogenic (i.e., manmade) sources as well as biogenic 

hydrocarbons emitted by vegetation. Recent efforts to reduce manmade organic 

carbon emissions have been undertaken primarily to address summertime ozone 

formation in urban centers. Future efforts to further reduce organic carbon 

emissions may be driven by programs that address fine particles and visibility. 

These efforts are discussed in Section 10 of this document. 

Understanding the transport dynamics and source regions for organic carbon in 

northeastern Class I areas is likely to be more complex than for sulfate. This is 

partly because of the large number and variety of organic carbon (OC) species, 

the fact that their transport characteristics vary widely, and the fact that a given 

species may undergo numerous complex chemical reactions in the atmosphere. 

Thus, the organic carbon contribution to visibility impairment at most Class I sites 

in the East is likely to include manmade pollution transported from a distance, 

manmade pollution from nearby sources, and biogenic emissions, especially 

terpenes from coniferous forests. 

As shown in Figure 7-3, the VOC inventory is dominated by mobile and area 

sources. On-road mobile sources of VOCs include exhaust emissions from 

gasoline passenger vehicles and diesel-powered heavy-duty vehicles as well as 

evaporative emissions from transportation fuels. VOC emissions may also 

originate from a variety of area sources (including solvents, architectural 

coatings, and dry cleaners) as well as from some point sources (e.g., industrial 

facilities and petroleum refineries). 

Biogenic VOCs may play an important role within the rural settings typical of 

Class I sites. The oxidation of hydrocarbon molecules containing seven or more 

carbon atoms is generally the most significant pathway for the formation of lightscattering organic aerosol particles (Odum et al., 1997). Smaller reactive 

hydrocarbons that may contribute significantly to urban smog (ozone) are less 
7-12 

likely to play a role in organic aerosol formation, though it was noted that high 

ozone levels can have an indirect effect on visibility by promoting the oxidation of 

other available hydrocarbons, including biogenic emissions (NESCAUM, January 

2001). In short, further work is needed to characterize the organic carbon 

contribution to regional haze in the Northeast and Mid-Atlantic states and to 

develop emissions inventories that will be of greater value for visibility planning 

purposes. 

Figure 7-3 - 2002 VOC Emissions (Bar graph: Percentage fraction of four source 

categories, Circle: Annual emissions in 106

 tons per year)

7.5.3 Oxides of Nitrogen (NOX)

NOX emissions contribute to visibility impairment in the eastern U.S. by forming 

light-scattering nitrate particles. Nitrates generally account for a substantially 

smaller fraction of fine particle mass and related light extinction than sulfates and 

organic carbon at northeastern Class I sites. Notably, nitrates may play a more 

important role at urban sites and in the wintertime. In addition, NOX may have an 

indirect effect on summertime visibility by virtue of its role in the formation of 

ozone, which in turn promotes the formation of secondary organic aerosols 

(NESCAUM 2001a). Figure 7-4 shows NOX emissions in the MANE-VU region at 

the state level. Since 1980, nationwide emissions of NOX from all sources have 

0%

25%

50%

75%

100%

Connecticut

Delaware

District of Columbia

Maine

Maryland

Massachusetts

New Hampshire

New Jersey

New York

Pennsylvania

Rhode Island

Vermont

million t/y

0.0

0.2

0.4

0.6

0.8

1.0

1.2

1.4

1.6

AREA NONROAD ONROAD POINT Emission
7-13 

shown little change. In fact, emissions increased by 2 percent between 1989 and 

1998 (EPA, 2000a). This increase is most likely due to industrial sources and the 

transportation sector, as power plant combustion sources have implemented 

modest emissions reductions during the same time period. Most states in the 

MANE-VU region experienced declining NOX emissions from 1996 through 2002, 

except Massachusetts, Maryland, New York, and Rhode Island, which show an 

increase in NOX emissions in 1999 before declining to levels below 1996 

emissions in 2002. Power plants and mobile sources generally dominate state 

and national NOX emissions inventories. Nationally, power plants account for 

more than one-quarter of all NOX emissions, amounting to more than six million 

tons. The electric sector plays an even larger role, however, in parts of the 

industrial Midwest where high NOX emissions have a particularly significant power 

plant contribution. By contrast, mobile sources dominate the NOX inventories for 

more urbanized Mid-Atlantic and New England states to a far greater extent, as 

shown in Figure 7-5. In these states, on-road mobile sources - a category that 

mainly includes highway vehicles - represent the most significant NOX source 

category. Emissions from non-road (i.e., off-highway) mobile sources, primarily 

diesel-fired engines, also represent a substantial fraction of the inventory. While 

there are fewer uncertainties associated with available NOX estimates than in the 

case of other key haze-related pollutants - including primary fine particle and 

ammonia emissions - further efforts could improve current inventories in a number 

of areas (NESCAUM, 2001a). 

In particular, better information on the contribution of area and non-highway 

mobile sources may be of most interest in the context of regional haze planning. 

First, available emission estimation methodologies are weaker for these types of 

sources than for the large stationary combustion sources. Moreover, because 

SO2 and NOX emissions must mix with ammonia to participate in secondary 

particle formation, emissions that occur over large areas at the surface may be 

more efficient in secondary fine particulate formation than concentrated emissions 

from isolated tall stacks (Duyzer, 1994). 
7-14 

Figure 7-4 - State Level Nitrogen Oxides Emissions 

Figure 7-5 - 2002 NOX Emissions (Bar graph: Percentage fraction of four source 

categories, Circle: Annual emissions amount in 106

 tons per year) 

0.0

0.2

0.4

0.6

0.8

1.0

1.2

Connecticut

Delaware

strict of Columbia

Maine

Maryland

Massachusetts

New Hampshire

New Jersey

New York

Pennsylvania

Rhode Island

Vermont

million t/y

NEI 1996

NEI 1999

MV 2002 v.2

0%

25%

50%

75%

100%

Connecticut

Delaware

District of Columbia

Maine

Maryland

Massachusetts

New Hampshire

New Jersey

New York

Pennsylvania

Rhode Island

Vermont

million t/y

0.0

0.3

0.6

0.9

AREA NONROAD ONROAD POINT Emission
7-15 

7.5.4 Primary Particulate Matter (PM10 and PM2.5)

Directly-emitted or “primary” particles (as distinct from secondary particles that 

form in the atmosphere through chemical reactions involving precursor pollutants 

like SO2 and NOX) can also contribute to regional haze. For regulatory purposes, 

a distinction is made between particles with an aerodynamic diameter less than or 

equal to 10 micrometers and smaller particles with an aerodynamic diameter less 

than or equal to 2.5 micrometers (i.e., primary PM10 and PM2.5, respectively). 

Figure 7-6 and Figure 7-7 show PM10 and PM2.5 emissions for the MANE-VU 

states for the years 1996, 1999, and 2002. Note that for PM10 the inventory 

values are drawn from the 2002 NEI. Most states show a steady decline in 

annual PM10 emissions over this time period. 

By contrast, emission trends for primary PM2.5 are more variable. Crustal sources 

are significant contributors of primary PM emissions. This category includes 

fugitive dust emissions from construction activities, paved and unpaved roads, 

and agricultural tilling. Typically, monitors estimate PM10 emissions from these 

types of sources by measuring the horizontal flux of particulate mass at a fixed 

downwind sampling location within perhaps 10 meters of a road or field. 

Comparisons between estimated emission rates for fine particles using these 

types of measurement techniques and observed concentrations of crustal matter 

in the ambient air at downwind receptor sites suggest that physical or chemical 

processes remove a significant fraction of crustal material relatively quickly. As a 

result, it rarely entrains into layers of the atmosphere where it can transport to 

downwind receptor locations. Because of this discrepancy between estimated 

emissions and observed ambient concentrations, modelers typically reduce 

estimates of total PM2.5 emissions from all crustal sources by applying a factor of 

0.15 to 0.25 to the total PM2.5 emissions before including it in modeling analyses. 

From a regional haze perspective, crustal material generally does not play a major 

role. On the 20 percent best-visibility days during the baseline period (2000-2004), 

it accounted for six to eleven percent of particle-related light extinction at MANEVU Class 1 sites. On the 20 percent worst-visibility days, however, crustal 

material generally plays a much smaller role relative to other haze-forming 

pollutants, ranging from two to three percent. Moreover, the crustal fraction 

includes material of natural origin (such as soil or sea salt) that is not targeted 

under the Regional Haze Rule. 

Of course, the crustal fraction can be influenced by certain human activities, such 

as construction, agricultural practices, and road maintenance (including wintertime 

salting) — thus, to the extent that these types of activities are found to affect 

visibility at northeastern Class I sites, control measures targeted at crustal 

material may prove beneficial. Experience from the western United States, where 

the crustal component has generally played a more significant role in driving 

overall particulate levels, may be helpful to the extent that it is relevant in the 

eastern context. In addition, a few areas in the Northeast, such as New Haven, 
7-16 

Connecticut and Presque Isle, Maine, have some experience with the control of 

dust and road-salt as a result of regulatory obligations stemming from their past 

non-attainment status with respect to the NAAQS for PM10. 

Current emissions inventories for the entire MANE-VU area indicate residential 

wood combustion represents 25 percent of primary fine particulate emissions in 

the region. This implies that rural sources can play an important role in addition to 

the contribution from the region’s many highly populated urban areas. An 

important consideration in this regard is that residential wood combustion occurs 

primarily in the winter months, while managed or prescribed burning activities 

occur largely in other seasons. The latter category includes agricultural fieldburning activities, prescribed burning of forested areas and other burning activities 

such as construction waste burning. Limiting burning to times when favorable 

meteorological conditions can efficiently disperse resulting emissions can manage 

many of these types of sources. 

Figure 7-8 and Figure 7-9 show that area and mobile sources dominate primary 

PM emissions. (The NEI inventory categorizes residential wood combustion and 

some other combustion sources as area sources.) The relative contribution of 

point sources is larger in the primary PM2.5 inventory than in the primary PM10

inventory since the crustal component (which consists mainly of larger or “coarsemode” particles) contributes mostly to overall PM10 levels. At the same time, 

pollution control equipment commonly installed at large point sources is usually 

more efficient at capturing coarse-mode particles. 

Figure 7-6 - State Level Primary PM10 Emissions 

0.0

0.2

0.4

0.6

0.8

Connecticut

Delaware

District of Columbia

Maine

Maryland

Massachusetts

New Hampshire

New Jersey

New York

Pennsylvania

Rhode Island

Vermont

million t/y

NEI 1996

NEI 1999

NEI 2002
7-17 

Figure 7-7 - State Level Primary PM2.5 Emissions

Figure 7-8 - 2002 Primary PM10 Emissions (Bar graph: Percentage fraction of four 

source categories, Circle: Annual emissions amount in 106 tons per year)

0.0

0.1

0.2

0.3

Connecticut

Delaware

District of Columbia

Maine

Maryland

Massachusetts

New Hampshire

New Jersey

New York

Pennsylvania

Rhode Island

Vermont

million t/y

NEI 1996

NEI 1999

MV 2002 v.2

0%

20%

40%

60%

80%

100%

Connecticut

Delaware

District of Columbia

Maine

Maryland

Massachusetts

New Hampshire

New Jersey

New York

Pennsylvania

Rhode Island

Vermont

mill oi n t/y

0.0

0.1

0.2

0.3

0.4

0.5

AREA NONROAD ONROAD POINT Emission
7-18 

Figure 7-9 - 2002 Primary PM2.5 Emissions (Bar graph: Percentage fraction of four 

source categories, Circle: Annual emissions amount in 106 tons per year) 

7.5.5 Ammonia Emissions (NH3)

Knowledge of ammonia emission sources will be necessary in developing 

effective regional haze reduction strategies because of the importance of 

ammonium sulfate and ammonium nitrate in determining overall fine particle mass 

and light scattering. Identifying emissions from ammonia sources is necessary to 

help develop regional haze reduction strategies. According to 1998 estimates, 

livestock agriculture and fertilizer use accounted for approximately 86 percent of 

all ammonia emissions to the atmosphere (EPA, 2000b). However, better 

ammonia inventory data is needed for the photochemical models used to simulate 

fine particle formation and transport in the eastern United States. States were not 

required to include ammonia in their air emissions data collection efforts until fairly 

recently (see consolidated emissions reporting rule, 67 FR 39602; June 10, 2002), 

and so it will take time for the quality of ammonia inventory data to match the 

quality of the data for the other criteria pollutants. 

0%

25%

50%

75%

100%

Connecticut

Delaware

District of Columbia

Maine

Maryland

Massachusetts

New Hampshire

New Jersey

New York

Pennsylvania

Rhode Island

Vermont

million t/y

0.00

0.05

0.10

0.15

0.20

AREA NONROAD ONROAD POINT Emission
7-19 

Ammonium ions (formed from ammonia emissions to the atmosphere) are an 

important constituent of airborne particulate matter, typically accounting for 10–20 

percent of total fine particle mass. Reductions in ammonium ion concentrations 

can be extremely beneficial because a more-than-proportional reduction in fine 

particle mass can result. Ansari and Pandis (1998) showed that a one mg/m3

reduction in ammonium ion could result in up to a four mg/m3 reduction in fine 

particulate matter. Decision makers, however, must weigh the benefits of 

ammonia reduction against the significant role it plays in neutralizing acidic 

aerosols.2 

To address the need for improved ammonia inventories, MARAMA, NESCAUM 

and EPA funded researchers at Carnegie Mellon University (CMU) in Pittsburgh to 

develop a regional ammonia inventory (Davidson et al., 1999). This study 

focused on three issues with respect to current emissions estimates: (1) a wide 

range of ammonia emission factor values, (2) inadequate temporal and spatial 

resolution of ammonia emissions estimates, and (3) a lack of standardized 

ammonia source categories. 

The CMU project established an inventory framework with source categories, 

emissions factors, and activity data that are readily accessible to the user. With 

this framework, users can obtain data in a variety of formats3

 and can make 

updates easily, allowing additional ammonia sources to be added or emissions 

factors to be replaced as better information becomes available (Strader et al., 

2000; NESCAUM, 2001b). Figure 7-10 shows that estimated ammonia emissions 

were fairly stable in the 1996, 1999, and 2002 NEI for MANE-VU states, with 

some increases observed for Massachusetts, New Jersey and New York. Area 

and on-road mobile sources dominate according to Figure 7-11. Specifically, 

emissions from agricultural sources and livestock production account for the 

largest share of estimated ammonia emissions in the MANE-VU region, except in 

the District of Columbia. The two remaining sources with a significant emissions 

contribution are wastewater treatment systems and gasoline exhaust from 

highway vehicles. 

 2 SO2 reacts in the atmosphere to form sulfuric acid (H2SO4). Ammonia can partially or fully 

neutralize this strong acid to form ammonium bisulfate or ammonium sulfate. If planners focus future 

control strategies on ammonia and do not achieve corresponding SO2 reductions, fine particles formed in 

the atmosphere will be substantially more acidic than those presently observed.

3 For example, the user will have the flexibility to choose the temporal resolution of the output 

emissions data or to spatially attribute emissions based on land-use data.
7-20 

Figure 7-10 - State Level Ammonia Emissions 

Figure 7-11 - 2002 NH3 Emissions (Bar graph: Percentage fraction of 

four source categories, Circle: Annual emissions amount in 106 tons per year)

0.000

0.025

0.050

0.075

0.100

Connecticut

Delaware

District of Columbia

Maine

Maryland

Massachusetts

New Hampshire

New Jersey

New York

Pennsylvania

Rhode Island

Vermont

million t/y

NEI 1996

NEI 1999

MV 2002 v.2

0%

25%

50%

75%

100%

Connecticut

Delaware

District of Columbia

Maine

Maryland

Massachusetts

New Hampshire

New Jersey

New York

Pennsylvania

Rhode Island

Vermont

million t/y

0.00

0.06

0.12

AREA NONROAD ONROAD POINT Emission
7-21 

7.5.6 Further Discussion

Figures 7-1, 7-4, 7-6, 7-7, and 7-10 show SO2, NOx, PM10, PM2.5 and ammonia 

emissions trends in the MANE-VU states extracted from the NEI for the years 

1996, 1999, and the 2002 MANE-VU inventory. Comparing emissions from each 

year, these figures provide an indication of whether there is an identifiable trend in 

emissions prior to the base year, as well as the ability to show the relative 

emissions on a state-specific basis for these three years. It is thus possible to 

compare the relative emissions from each state as well as to assess whether a 

trend in emissions is evident over this period. This information is useful in 

determining what air program-related changes might have been effective in 

influencing the levels of these pollutants in recent years, and is suggestive of what 

trends might be seen in the first planning period. For example, the figures related 

to SO2 suggests that most states show declines in year 2002 as compared tn 

1996 emissions. Where it occurred. the upward trend in emissions after 1996 

likely reflects electricity demand growth during the late 1990s combined with the 

availability of banked emissions allowances from initial overcompliance with 

control requirements in Phase 1 of the EPA Acid Rain Program. Understanding 

the material presented in these graphs if useful in determining how to project 

emissions and judging whether projections are reasonable. The specific 

interpretation of each graph is discussed in detail in the adjacent portions of 

section 7. 

7.6 Summary of Emission Inventories

The tables below summarize the 2002 and 2018 emissions as developed by the 

methods described above, and used in the modeling for haze impacts through the 

period of this SIP. Tables 7-1 and 7-2 present the MANE-VU-wide figures, with 

the percent changes over the period for the entire MANE-VU region shown in 

Table 7-3. Likewise, Tables 7-4 and 7-5 summarize the emissions for New York 

State, with Table 7-6 showing the percent changes over time. 

For MANE-VU, while both PM2.5 and PM10 emissions are shown to increase 

slightly, the emission of the precursors for particulate matter VOC, NOx and SO2 

decrease significantly. With sulfate being the predominate contributor to regional 

haze, the reductions are dramatic, contribuing to the expected meeting of the 

reasonable progress goals for the Class I areas within MANE-VU. 

In the case of New York’s emissions, PM2.5 emissions are predicted to decrease 

slightly but, as is the case with MANE-VU emissions as a whole, VOC, NOx and 

SO2 emissions are expected to decrease significantly as well. 
7-22 

7.6.1 Summary of MANE-VU Emissions Inventories

Table 7-1 - MANE-VU 2002 Emissions Inventory Summary (TPY) 

Sector VOC NOx PM2.5 PM10 NH3 SO2 

Point 97,300 673,660 55,447 89,150 6,194 1,907,634 

Area 1,528,141 262,477 332,729 1,455,311 249,795 316,357 

On-Road 

Mobile 789,560 1,308,233 22,107 31,561 52,984 40,091 

Non-Road 

Mobile 572,751 431,631 36,084 40,114 287 57,257 

Biogenics 2,575,232 28,396 - - - - 

TOTAL 5,562,984 2,704,397 446,367 1,616,136 309,260 2,321,339 

Source: Pechan, 2006. "Technical Support Document for 2002 MANE-VU SIP Modeling Inventories, Version 3." 

November 2006. 

Available online: http://www.marama.org/visibility/Inventory%20Summary/2002EmissionsInventory.htm 

 

Table 7-2 - MANE-VU 2018 Emissions Inventory Summary (TPY)

 Sector VOC NOx PM2.5 PM10 NH3 SO2

Point 115,052 413,021 93,580 129,315 11,134 657,018 

Area 1,387,882 284,535 345,419 1,614,476 341,746 305,437 

On-Road 

Mobile 269,981 303,955 

 

9,189 9,852 66,476 8,757 

Non-Road 

Mobile 380,080 271,185 23,938 27,059 369 8,643 

Biogenics 2,575,232 28,396 - - - - 

TOTAL 4,728,227 1,301,092 472,126 1,780,702 419,725 979,855 

Source: MACTEC, 2007. "Development of Emission Projections for 2009, 2012, and 2018 for non-EGU 

Point, Area, and Nonroad Sources in the MANE-VU Region." February 28, 2007. 

Available online: 

http://www.marama.org/visibility/Inventory%20Summary/FutureEmissionsInventory.htm

EGU Point Emissions: VISTAS_PC_If IPM Run (Alpine Geophysics, 2008) 
7-23 

Table 7-3 - Change in MANE-VU Emissions 2002 to 2018 (*Percent) 

 Sector VOC NOx PM2.5 PM10 NH3 SO2

Point 18.2 -38.7 68.8 45.1 79.8 -65.6 

Area -9.2 8.4 3.8 10.9 36.8 -3.4 

On-Road 

Mobile -65.8 -76.8 -58.4 -68.8 25.5 -78.2 

Non-Road 

Mobile -33.6 -37.2 -33.7 -32.5 28.6 -84.9 

Biogenics 0.0 0.0 -- -- -- -- 

TOTAL -15.0 -51.9 5.8 10.2 35.7 -57.8 

*Negative percent indicates a decrease in emissions 

7.6.2 Summary of New York 2002 Emissions Inventories

Table 7-4 - New York 2002 Emissions Inventory Summary (TPY)

Sector CO NOx VOC NH3 SO2 PM10 PM25

Area 356,287 98,804 514,425 67,422 113,978 369,595 85,841

Point 53,563 584,450 134,363 1,861 686,426 10,326 25,075

Nonroad 1,205,509 119,808 158,121 79 13,288 9,605 9,000

Onroad 2,942,730 313,888 179,731 14,439 10,229 7,599 5,402

Biogenic 63,436 8,313 492,483 - - - - 

Totals 4,621,525 1,125,263 1,479,123 83,801 823,921 397,125 125,318

Source: NOx, SO2 and PM2.5: NYSDEC’s Proposed PM2.5 Attainment Demonstration (May 2008) 

 CO and VOC :NYSDEC’s Proposed 8-Hour Ozone Attainment Demonstration (Feb 2008) 

Others: MACTEC, 2007. "Development of Emission Projections for 2009, 2012, and 2018 for 

non-EGU Point, Area, and Nonroad Sources in the MANE-VU Region." February 28, 2007. 

Available online: http://www.marama.org/visibility/Inventory%20Summary/FutureEmissionsInventory.htm
7-24 

7.6.3 Summary of New York 2018 Emissions Inventories 

Table 7-5 - New York 2018 Emissions Inventory Summary (TPY)

 Sector CO NOx VOC NH3 SO2 PM10 PM25

Area 307,659 108,444 457,421 96,078 141,408 392,027 86,422

Point 101,118 55,681 13,091 2,767 118,936 17,062 13,460

Nonroad 1,474,727 72,400 104,562 103 1,686 5,830 5,349

Onroad 1,694,820 78,365 68,104 19,167 1,794 2,775 2,542

Biogenic 63,436 8,313 492,483 -- -- -- --

Totals 3,641,760 323,203 1,135,571 118,115 263,824 417,694 107,773

Source: MACTEC, 2007. "Development of Emission Projections for 2009, 2012, and 2018 for non-EGU 

Point, Area, and Nonroad Sources in the MANE-VU Region." February 28, 2007. 

Available online: http://www.marama.org/visibility/Inventory%20Summary/FutureEmissionsInventory.htm

Table 7-6 - Change in New York Emissions 

2002 to 2018 (*Percent)

 Sector CO NOx VOC NH3 SO2 PM10 PM25

Area -13.6 9.8 -11.1 42.5 24.1 6.1 0.7 

Point 88.8 -90.5 -90.3 48.7 -82.7 65.2 -46.3 

Nonroad 22.3 -39.6 -33.9 30.4 -87.3 -39.3 -40.6 

Onroad -42.4 -75.0 -62.2 32.7 -82.5 -63.5 -52.9 

Biogenic 0.0 0.0 0.0 -- -- -- -- 

Totals -21.2 -71.3 -23.2 40.9 -68.0 5.2 -14.0 

*Negative percent indicates a decrease in emissions