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Introduction

By Dawn Owens,2014-07-01 11:24
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Introduction

Introduction

Mobile sources include on-road and off-road vehicles and engines. On-road mobile

    sources include vehicles certified for highway use cars, trucks, and motorcycles. For

    reporting on-road mobile source emissions, vehicles are divided into two major classes

    light-duty and heavy-duty. Light-duty vehicles include passenger cars, light-duty trucks

    (up to 8500 lbs gross vehicle weight [GVW]), and motorcycles. Heavy-duty vehicles are

    trucks of more than 8500 lbs GVW.

Off-road mobile equipment encompasses a wide variety of equipment types that either

    move under their own power or are capable of being moved from site to site. Off-road

    mobile equipment sources are defined as those that move or are moved within a 12-

    month period and are covered under the EPA’s emissions regulations for nonroad mobile

    sources. Off-road mobile sources are vehicles and engines in the following categories:

    ? Agricultural equipment, such as tractors, combines, and balers;

    ? Aircraft, jet and piston engines;

    ? Airport ground support equipment, such as terminal tractors;

    ? Commercial marine vessels, such as ocean-going deep draft vessels;

    ? Commercial and industrial equipment, such as fork lifts and sweepers;

    ? Construction and mining equipment, such as graders and back hoes;

    ? Lawn and garden equipment, such as leaf and snow blowers;

    ? Locomotives, switching and line-haul trains;

    ? Logging equipment, such as shredders and large chain saws;

    ? Pleasure craft, such as power boats and personal watercraft;

    ? Railway maintenance equipment, such as rail straighteners;

    ? Recreational equipment, such as all-terrain vehicles and off-road motorcycles; and

    ? Underground mining and oil field equipment, such as mechanical drilling engines.

Road dust emissions estimates are also included in the mobile source emissions category,

    and are discussed separately with the fugitive dust emissions inventory summary.

Mobile Source Inventory Scope

The scope of the WRAP mobile sources emission inventories is as follows:

    Geographic domain: Emissions were estimated by county for all counties in 14

    states: Alaska, Arizona, California, Colorado, Idaho, Montana, Nevada, New

    Mexico, North Dakota, Oregon, South Dakota, Utah, Washington, and Wyoming.

    Temporal resolution: Emissions were estimated for an average day in each of the

    four seasons, and for an average annual weekday. Seasons are defined as three-

    month periods: spring is March through May; summer is June through August;

    fall is September through November; and winter is December through February.

    Emissions were estimated for the 2002 base year and for three future years 2008,

    2013, and 2018.

    Pollutants: Emissions were estimated for primary particulate matter (PM and 10

    PM), nitrogen oxides (NO), sulfur dioxide (SO), volatile organic compounds 2.5x2

    (VOCs), carbon monoxide (CO), ammonia (NH), elemental and organic carbon 3

    (EC/OC), and sulfate (SO4).

    Sources: For all pollutants, emissions were estimated separately by vehicle class

    for on-road sources and by equipment type/engine type for off-road sources.

    Emissions were summarized for gasoline and diesel-fueled engines.

    Approach For Estimating Mobile Source Emissions

    As with most emissions sources, on-road and off-road mobile source emissions are

    estimated as the products of emission factors and activity estimates. Except for

    California, the on-road mobile sources emission factors were derived from EPA’s

    MOBILE6 model, available at http://www.epa.gov/OMSWWW/m6.htm. Activity for

    on-road mobile sources is vehicle miles traveled (VMT). State and local agencies were

    provided default modeling inputs and VMT levels for base and future years for review

    and update; all states and several agencies provided updated. The California Air

    Resources Board (CARB) provided on-road emissions estimates by county and vehicle

    class directly; these were based on CARB’s in-house version of their EMFAC model.

    For all states except California, EPA’s draft NONROAD2004 model was used to

    estimate so-called traditional off-road sources

    1, all sources listed above except aircraft,

    commercial marine, and locomotives. The NONROAD model includes estimates of

    emission factors, activity levels, and growth factors for all traditional off-road sources.

    The default activity levels were provided to state agencies for input and update; however,

    no state provided updated off-road activity data. Emissions estimation methods for

    aircraft, commercial marine, and locomotives were similar to approaches EPA has

    recently used in developing national emission inventories. For California, CARB

    provided off-road emissions estimates by source category and county directly.

Emissions Models Used and Additional Calculations for Air Quality Modeling

On-road and off-road mobile source emissions are estimated as the products of emission

    factors and activity estimates. Except for California, the on-road mobile sources

    emission factors were derived from the EPA MOBILE6 model. Activity for on-road

    mobile sources is vehicle miles traveled (VMT). EPA’s NONROAD2004 model was

    used to estimate emissions from off-road mobile sources except for aircraft, commercial

    marine, and locomotives.

     1 The final version of NONROAD (NONROAD2005, available at http://www.epa.gov/otaq/nonrdmdl.htm)

    was released after the work in this project was completed.

EPA MOBILE6 Model

The MOBILE model is EPA’s regulatory model for estimating on-road mobile source

    gram per mile emission factors for VOC (exhaust and evaporative), NO, CO, PM, NH, X3

    and SO. The current regulatory version of the model is MOBILE6, released in 2002. 2

    The model and supporting documentation may be found on EPA’s web site at

    http://www.epa.gov/OMSWWW/m6.htm.

The MOBILE6 model includes the effects of all of the following ―on the books‖ Federal

    regulations for on-road motor vehicles:

    ? Tier 1 light-duty vehicle standards, beginning with, beginning MY 1996;

    ? National Low Emission Vehicle (NLEV) standards, beginning MY 2001;

    ? Tier 2 light-duty vehicle standards beginning MY 2005, with low sulfur gasoline

    beginning summer 2004;

    ? Heavy-duty vehicle standards beginning MY 2004; and

    ? Heavy-duty vehicle standards beginning MY 2007, with low sulfur diesel

    beginning summer 2006.

MOBILE6 estimates emissions by vehicle class, for 28 vehicle classes. For the WRAP

    modeling, the emissions were estimated for eight vehicle classes, which are combined

    from these 28. The eight vehicle classes are those that were modeled in the prior

    generation of the mode, MOBILE5, as shown in Table 1.

Table 1. MOBILE5 vehicle classes for which emissions were estimated.

    Vehicle Class MOBILE Weight Description

    Code

    Light-duty gasoline vehicles LDGV Up to 6000 lb gross vehicle weight (GVW)

    (passenger cars) 1 Light-duty gasoline trucksLDGT1 Up to 6000 lb GVW (pick-ups, minivans, passenger

    vans, and sport-utility vehicles) LDGT2 6001-8500 lb GVW Heavy-duty gasoline vehicles HDGV 8501 lb and higher GVW equipped with

    heavy-duty gasoline engines Light-duty diesel vehicles LDDV Up to 6000 lb GVW (passenger cars)

    Light-duty diesel trucks LDDT Up to 8500 lb GVW

    Heavy-duty diesel vehicles HDDV 8501 lb and higher GVW

     2 MotorcyclesMC 1 Emissions for light-duty trucks are modeled separately for two weight classes with different emissions standards in the Clean Air Act 2 Highway-certified motorcycles only are included in the model. Off-road motorcycles, such as dirt bikes, are modeled as a no-road mobile source in EPA’s NONROAD model.

The particulate matter emission factors in MOBILE6 are from an earlier EPA particulates

    emission factor model called PART5. The tire and brake wear estimates from PART5

    used in MOBILE6 are dated, and newer brake wear estimates were available (Garg et al,)

    and were used to develop revised brake wear emission factors, the same as used in the

    previous WRAP mobile sources emission inventory (Pollack et al., 2004).

EPA NONROAD Model

Off-road mobile equipment encompasses a wide variety of equipment types that either

    move under their own power or are capable of being moved from site to site. Off-road

    mobile equipment sources are defined as those that move or are moved within a 12-

    month period and are covered under the EPA’s emissions regulations for nonroad mobile

    sources. Emissions for so-called traditional nonroad sources are estimated by EPA in

    their NONROAD emissions model, available on the NONROAD web page at

    http://www.epa.gov/otaq/nonrdmdl.htm.

At the time that the off-road emissions were estimated for this project, the latest version

    of the model was draft NONROAD2004. In December of 2005 final NONROAD2005

    was released. The web page above provides now only the NONROAD2005 final model.

The NONROAD model includes both emission factors and default county-level

    population and activity data. The model therefore estimates not just emission factors but

    also emissions. Technical documentation of all aspects of the model can be found on the

    EPA NONROAD web page.

The NONROAD model includes more than 80 basic and 260 specific types of nonroad

    equipment, and further stratifies equipment types by horsepower rating and fuel type, in

    the following categories:

    ? airport ground support, such as terminal tractors;

    ? agricultural equipment, such as tractors, combines, and balers;

    ? construction equipment, such as graders and back hoes;

    ? industrial and commercial equipment, such as fork lifts and sweepers;

    ? recreational vehicles, such as all-terrain vehicles and off-road motorcycles;

    ? residential and commercial lawn and garden equipment, such as leaf and

    snowblowers;

    ? logging equipment, such as shredders and large chain saws;

    ? recreational marine vessels, such as power boats;

    ? underground mining equipment; and

    ? oil field equipment.

The NONROAD model does not include commercial marine, locomotive, and aircraft

    emissions. Emissions for these three source categories are estimated using other EPA

    methods and guidance documents (described in Sections 5-7). However, support

    equipment for aircraft, locomotive, and commercial marine operations and facilities are

    included in the NONROAD model.

The NONROAD model estimates emissions for six exhaust pollutants: hydrocarbons

    (HC), NO, carbon monoxide (CO), carbon dioxide (CO), sulfur oxides (SO), and PM. X2X

    The model also estimates emissions of non-exhaust HC for six modes hot soak,

    diurnal, refueling, resting loss, running loss, and crankcase emissions.

    The NONROAD model used in this study incorporates the effects of all of the following

    ―on the books‖ Federal nonroad equipment regulations:

    $ Emission standards for new nonroad spark-ignition engines below 25 hp;

    $ Phase 2 emission standards for new spark-ignition hand-held engines below 25 hp;

    $ Phase 2 emission standards for new spark-ignition nonhandheld engines below 25

    hp;

    $ Emission standards for new gasoline spark-ignition marine engines;

    $ Tier 1 emission standards for new nonroad compression-ignition engines above

    50 hp;

    $ Tier 1 and Tier 2 emission standards for new nonroad compression-ignition

    engines below 50 hp including recreational marine engines;

    $ Tier 2 and Tier 3 standards for new nonroad compression-ignition engines of 50

    hp and greater not including recreational marine engines greater than 50 hp; and

    $ Tier 4 emissions standards for new nonroad compression-ignition engines above

    50 hp, and reduced nonroad diesel fuel sulfur levels.

    The NONROAD model provides emission estimates at the national, state, and county

    level. The basic equation for estimating emissions in the NONROAD model is as

    follows:

     Emissions = (Pop)(Power)(LF)(A)(EF)

    where

    Pop = Engine Population

    Power = Average Power (hp)

    LF = Load Factor (fraction of available power)

    A = Activity (hrs/yr)

     EF = Emission Factor (g/hp-hr)

    The national or state engine population is estimated and multiplied by the average power,

    activity, and emission factors. Equipment population by county is estimated in the model

    by geographically allocating national engine population through the use of econometric

    indicators, such as construction valuation. The manner in which the geographic

    allocation is performed is as follows:

(County Population) /(National Population) = (County Indicator) /(National Indicator) iIii

    where

     i is an equipment application like construction or agriculture.

Activity is temporally allocated through the use of monthly, and day of week fractions of

    yearly activity.

The NONROAD model has default estimates for all variables and factors used in the

    calculations. All of these estimates are in model input files, and can be changed by the

    user if data more appropriate to the local area are available.

California Models

The California Air Resources Board (CARB) provided on-road and off-road emissions

    data for base and future years for use in this project. CARB has developed their own

    models for on-road and off-road emissions estimation. CARB’s on-road model is

    referred to as EMFAC. The version of the model that was used to generate the CARB

    on-road emissions was EMFAC2002 (available at http://www.arb.ca.gov/msei/on-

    road/latest_version.htm), with internal updates for some of the activity data that were not

    publicly available.

For many years, CARB has been developing its own off-road emissions model, called

    OFFROAD. Although CARB has developed most of the model inputs as part of their

    analyses in support of their off-road equipment regulations, the model has never been

    publicly released.

Pollutants Added for Air Quality Modeling For all California emissions, CARB provided their emissions estimates for the base and

     future years. Emissions data only were provided, not activity data and emission factors.

    For CMAQ modeling, additional model species are required beyond what is estimated in

    MOBILE, NONROAD, EMFAC, and OFFROAD. Specifically, particulate matter

    needed to be split into elemental carbon (EC), organic carbon (OC), and sulfate (SO); 4

    and NO needed to be split into NO and NO. X2

    EC and OC were estimated by applying EC/OC fractions to the PM and PM 102.5

    emissions estimates. The EC/OC splits used for these calculations are summarized in

    Table 2. These are the same EC/OC fractions used in the previous WRAP mobile

    sources emissions estimates; their derivation is described in Pollack et al., 2004. Sulfate

    was then estimated as PM EC OC, for both PM10 and PM2.5. Coarse PM is

    calculated as PM10 PM2.5

Table 2. Elemental carbon/organic carbon fractions.

    Process/Pollutant EC OC Source Gasoline Exhaust 23.9% 51.8% Gillies and Gertler, 2000 Light-Duty Diesel Exhaust 61.3% 30.3% Gillies and Gertler, 2000 Heavy-Duty Diesel Exhaust 75.0% 18.9% Gillies and Gertler, 2000 Tire Wear 60.9% 21.75% Radian, 1988 Brake Wear 2.8% 97.2% Garg et al, 2000

While there have been several studies and reviews of particulate composition (e.g. EPA,

    2001 and Turpin and Lim, 2000) since the time of the work referenced in Table 2, there

    has not been a comparable comprehensive evaluation of particulate composition. Many

    particulate source/receptor statistical modeling efforts have been attempted, but all used

    source profiles that predate those listed in Table 2. A comprehensive evaluation of

    source profiles needs to include the effect of the proper age distribution and maintenance

    history of in-use vehicles. No recent studies have investigated the source profiles using

    such an evaluation, and so could not be used for this work. In addition, the default EPA

    resource for compositional estimates of emissions, SPECIATE, has not provided any

    revised profiles since October 1999.

The ratio of NO to NO2 for NOx emissions from mobile sources is a result of the

    chemical equilibrium formed during internal combustion with NO the primary constituent

    of NOx. Aftertreatment devices may begin to perturb the ratio of NO and NO2 as NOx

    and particulate control are applied to diesel engines (Tonkyn, 2001, Herndon, 2002, and

    Chatterjee, 2004). However, these systems have not yet been widely employed, so it is

    not possible to judge what the proportion of NOx that NO and NO2 will be in the future.

    For this work the EPA default proportions of NO and NO2 (90/10) were used to

    apportion the NOx emission estimates.

Temporal Profiles

The on-road and off-road emissions are estimated as average day, per season. For use in

    air quality modeling, these average day emissions must be temporally allocated to the 24

    hours of the day for each day of the week. This temporal allocation is done in the

    SMOKE emissions processing system. The EPA temporal profiles for on-road and off-

    road emissions were reviewed and found to be deficient for on-road sources. The EPA

    defaults for on-road temporal profiles vary only by weekday vs. weekend; for both

    weekdays and weekends the 24-hour profiles do not vary by vehicle class. And there are

    only two day of week profiles one for light-duty gasoline vehicles and one for all

    vehicle classes.

ENVIRON has analyzed an extremely large database of detailed traffic counter data by

    vehicle class, roadway type, and state under contract to EPA (Lindhjem, 2004). From

    this work using national databases of vehicle activity maintained by the Federal Highway

    Administration (FHWA), revised temporal profiles for on-road sources were

    developed. The databases used were the FHWA Traffic Volume Trends

    (http://www.fhwa.dot.gov/policy/ohpi/travel/index.htm) for temporal activity of vehicles,

    and the FHWA Vehicle Travel Information System (VTRIS)

    (http://www.fhwa.dot.gov/ohim/ohimvtis.htm) that identifies individual vehicle classes to

    estimate temporal variation in the vehicle mix. Three sets of profiles were developed:

    day of week profiles by vehicle class (Figure 1); hour of day profiles for weekdays, by

    vehicle class (Figure 2); and hour of day profiles for weekends, by vehicle class (Figure

    3). These temporal profiles show important differences in vehicle activity by vehicle

    class across the days of the week and the hours of the day.

     Day of Week Profiles

    0.200

    0.180

    0.160

    0.140LDGV0.120LDGT1

    LDGT20.100HDGV0.080LDDV

    LDDT0.060HDDV0.040MC0.020

    0.000SMTWThFSat

    Figure 1. Day of week profiles by vehicle class.

    Weekday Diurnal Profiles

    LDGV0.09LDGT1

    LDGT20.08HDGV

    LDDV0.07LDDT0.06HDDV

    MC0.05

    0.04

    0.03

    0.02

    0.01

    0123456789101112131415161718192021222324

    Figure 2. Weekday hour of day profiles by vehicle class.

     Weekend Diurnal Profiles

    0.08

    0.07

    0.06

    0.05

    LDGV

    LDGT10.04

    LDGT20.03HDGV

    LDDV0.02LDDT

    HDDV0.01MC

    0123456789101112131415161718192021222324

Figure 3. Day of week profiles by vehicle class.

Locomotive Emissions Estimation Methodology

County level locomotive emissions estimates were estimated as the product of

    locomotive fuel consumption and average locomotive emission factors. Previous WRAP

    locomotive emissions estimates (Pollack et al., 2004) allocated national fuel consumption

    estimates to counties using emissions data offered by the National Emissions Inventory.

    A detailed revision to that allocation method was developed for allocating 2002 national

    fuel consumption estimates. Emission factors were also revised to combine line-haul and

     switching engines because only national total fuel consumption was available. Additional emission factors for ammonia and fuel sulfur provided by EPA were also 2002 Locomotive Emissions incorporated and form the basis from which sulfur dioxide was estimated.

    Development of the 2002 locomotive emissions involved spatially allocated 2002 national locomotive activity, in the form of fuel consumption, using historic data of freight movements. The 2002 Class I railroad activity data were derived from national fuel consumption data reported by the Association of American Railroads (AAR, 2003), and the activity data for Class II/III railroads from data reported by the American Short Line & Regional Railroad Association (ASLRRA, 1999 and Benson, 2004). To allocate this national fuel consumption to the county level, ENVIRON used the most recent county level rail activity estimates available. These activity estimates were ton-miles of freight movement estimated by the Bureau of Transportation Statistics (2002), using data from 1995. The 2002 national activity data were allocated to each county in the WRAP states using the fraction of the 1995 national rail activity that occurred in each county and then multiplying that fraction by the 2002 national rail activity, as demonstrated in equation (1).

    CA02 = NA02 * (CA95/NA95) (1)

    where

    CA02 = 2002 county locomotive fuel consumption

    NA02 = 2002 national locomotive fuel consumption

    CA95 = 1995 county million gross ton miles (MGTM)

    NA95 = 1995 national total MGTM

    The spatial allocation of the national emissions in this work followed the methods of the EPA National Emission Inventory (NEI, 1999 and unchanged for 2002) of allocating locomotive activity. The 1995 activity data were obtained as GIS shapefiles containing track segments and an associated database of rail density per mile (MGTM/mi) corresponding to those segments. The segment-specific rail density estimates were provided as ranges. For each segment, the midpoint of the density range was assumed to represent the average track loading on that segment. Table 3 shows a list of the ranges and the midpoint values used in this study. The top end density was reported as an open-ended range, greater than 100 MGTM/mi, which was estimated as 120 MGTM/mi. This differs from the allocation method used in the NEI 2002, which represented the top end traffic density as 100 MGTM/mi. The use of 120 MGTM/mi is expected to more accurately reflect the relative importance of those main line track segments than using the minimum value of 100 MGTM/mi.

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