A very important process of
air quality modeling is preparing emissions inventory data.
Emissions data are divided into four source categories:
Point Source Emissions Data
TCEQ processes point source emissions for use in
photochemical modeling in several steps. The first step is to
acquire a
point source emissions inventory for the year being modeled.
Point source emissions are retrieved from the agency's database
using the State of Texas Air Reporting System (STARS). STARS data
consist of daily average emission rates, location coordinates,
stack parameters, chemical species, standard industrial
classification (SIC), source classification code (SCC), and other
data needed to model each source. Location coordinates (for
example, longitude and latitude) allow the emissions to be placed
at the appropriate location in the modeling grid. Depending on
stack parameters (stack height, discharge velocity, etc.), the
emissions may also be placed directly into elevated layers of the
grid. Emissions from areas outside of Texas are obtained from a
variety of sources, including the National Emissions
Inventory (NEI) 
. TCEQ also exchanges
emissions information with adjoining states.
Because the composition of VOC emissions is critically important
to accurately simulating ozone formation, the TCEQ asks industries
to provide detailed breakdowns of the hydrocarbon species emitted
at each reported emission point. In cases where this information is
unavailable or incomplete, default speciation profiles are used to
complete the speciation of each point based on its reported
SCC.
To determine the time pollutants are emitted, TCEQ uses a
variety of information. Most point sources simply report operating
24 hours, seven days a week, but some report different operating
schedules. For some sources, hourly emissions data are available
and these are used whenever possible. Most large electricity
generating facilities nationwide report hourly emissions of
NOx to the Acid
Rain Program Data Base , and the TCEQ occasionally
conducts special inventory surveys to obtain hourly speciated
emissions from specific sources over a period of time. TCEQ
conducted such a survey during the
Second Texas Air Quality Study (TexAQS II) intensive period,
collecting hourly emissions from major point sources in East Texas
from August 15 through September 15, 2006.
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On-Road Mobile Source Emission Data
For ozone nonattainment areas within Texas, on-road mobile
source emission inventories are typically based on vehicle miles
traveled (VMT) estimates that are output from local travel demand
models (TDMs) for various roadway segments or “links.”
Hourly VMT estimates for each link are multiplied by emission rates
calculated with EPA's MOBILE6.2 model. Emission rates are developed
separately for freeway and arterial links and matched to the hourly
VMT based on average hourly operating speed. Hourly temperature and
humidity inputs based on locally observed data from specific time
periods are used as MOBILE6.2 inputs to more accurately
characterize the emissions on the ozone episode days chosen for
modeling.
For attainment and/or non-metropolitan areas within Texas that
do not have TDMs, Highway Performance Monitoring System (HPMS) data
are used to determine hourly VMT by roadway type for each county.
Similar to the approach described above, hourly VMT estimates by
roadway type are multiplied by emissions rates from MOBILE6.2 that vary as a function of
speed, temperature, humidity, and drive cycle (i.e., high-speed
freeway driving versus stop-and-go arterial driving).
Whether the VMT data are developed with TDMs or HPMS data sets,
Weekday, Friday, Saturday, and Sunday “day type”
on-road inventories are developed that differ in both the magnitude
and hourly distribution of both VMT and estimated emissions. TCEQ
uses Version 3 of the Emissions Preprocessor System (EPS3) to
convert the on-road inventory data into a gridded format
appropriate for
photochemical model input. For the TDM-based inventories, grid
cell allocation is based on the X-Y locations of the link
endpoints. For the HPMS-based inventories, grid cell allocation is
based on spatial surrogates specific to each county and roadway
type. For example, if a single grid cell contains 15% of the
interstate highway miles in a specific county, then 15% of the
interstate highway emissions are assigned to that grid cell.
In addition to gridding the hourly emissions, EPS3 assigns
speciation profiles to appropriately group the exhaust and
evaporative hydrocarbon emissions estimates based on reactivity for
ozone formation. EPS3 is also used to make necessary emission
adjustments by county and/or vehicle type. Sometimes these
adjustments are needed to test out various control strategy
scenarios, but this approach is also taken to apply both
temperature and humidity NOx emission rate
post-processing adjustments for diesel vehicles because MOBILE6.2
does not include such corrections.
For non-Texas areas contained within the modeling domain, EPA's
National Mobile
Inventory Model (NMIM) is used to develop daily
emission estimates by county for an average Summer Weekday. These
emissions are processed with EPS3 and adjustments are applied to
develop Friday, Saturday, and Sunday day type inventories based on
pollutant-specific ratios from the Texas on-road inventories for
Friday/Weekday, Saturday/Weekday, and Sunday/Weekday. In addition,
the hourly distributions of the Texas on-road inventories by both
pollutant and day type are applied to the non-Texas portions of the
modeling domain. The end result of this process is a gridded and
speciated inventory for
photochemical model input with relatively high spatial and
temporal resolution of on-road emissions.
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Area Source Emission Data
Area source emissions come from of a variety of anthropogenic
(man-made) sources which are too small, too abundant, or too
dispersed geographically to inventory individually. Examples of
these sources include dry cleaning, vehicle refueling, cooking, and
solvent usage. Area sources are modeled using a top-down approach,
meaning emission totals are estimated for large geographic regions,
usually states or counties. When possible, the TCEQ will conduct
special studies to develop bottom-up inventories for area source
emissions of concern. TCEQ obtains Texas county emission totals
from Texas Air
Emissions Repository (TexAER), and obtains data from other
areas from the NEI and other sources.
Before the
photochemical model can be run, the geographic location of air
pollution emissions must be identified. It must also be determined
what time of day pollutants were emitted and what particular VOCs
were present. Timing is important in
photochemical modeling, as the sun plays a large role in the
chemical reactions that create ozone. So emissions occurring midday
will react differently from emissions at midnight. Identifying the
correct VOCs present (or chemical speciation) is important because
some VOCs are far more reactive than others.
TCEQ uses spatial surrogates, diurnal profiles, and chemical
profiles to accomplish these goals. A surrogate is a readily
available geographic substitute that can be used to help locate
area source emissions spatially. A good example is emissions from
personal care products, which should be highly correlated spatially
with population. Using census tract population data from the U.S.
Census Bureau, county-level emissions from these sources can be
reasonably distributed geographically within the counties.
Determining the time of day that emissions are released is
accomplished by using diurnal profiles. For example, vehicle
refueling activity is related to driving activity, so refueling
emissions are distributed through the day in proportion to the
amount of traffic. Modeled emissions also vary by day-of-week and
by month through the application of activity profiles.
Chemical speciation is simply assigning the correct proportion
of different chemicals to different activities. For example,
emissions from a dry cleaner will differ chemically from those of a
print shop, so each category is assigned its own speciation
profile.
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Non-road Mobile Source Emission Data
Like area sources, emissions from non-road mobile come from of a
variety of anthropogenic (man-made) sources which are too small,
too abundant, or too dispersed geographically to inventory
individually. Examples of non-road mobile sources include
construction, recreational boating, lawn care, and logging. For
Texas sources, county total emissions are obtained from TexAER, and for
areas outside Texas emissions are calculated using EPA's NMIM or are obtained from other
sources. The TexAER data for
categories covered by the NONROAD model are developed using a
Texas-specific version of the latest NONROAD model. For modeling,
the TCEQ also adjusts emissions of NOx from diesel
equipment to account for humidity.
Emissions from ships, locomotives, and aircraft are not
available through NMIM or the NONROAD model. These
sources are sometimes referred to as off-road mobile sources to
distinguish them from other non-road sources. Texas emissions for
off-road sources are obtained from TexAER, except
emissions from ships in the HGB and BPA areas. For these areas,
where shipping contributes a considerable fraction of daily
emissions, ship emissions are estimated based on a special study
conducted in 2000. Outside Texas, emissions for off-road sources
are obtained from the NEI and from other sources.
Spatial allocation of non- and off-road emissions is analogous
to that described for area sources above, except that off-road
sources use special surrogates tied to their specific
characteristics (rail lines, airports, and shipping lanes). In
addition, because large ships emit their exhaust from stacks, TCEQ
has developed a methodology which allows ship emissions to be more
accurately modeled in the same way as elevated point sources.
Similar to area source emissions, modeled non-road emissions
vary by hour, day-of-week, and month through application of
activity profiles. Chemical speciation is also accomplished by
using profiles.
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Biogenic Source Emissions Data
In the 1980s, air pollution researchers discovered that in order
to properly simulate ozone formation in their computer models, they
needed to take into account the natural emissions of various
chemicals. These natural emissions are referred to as biogenic
emissions, and they can play an important role in the atmospheric
chemistry of a city. The most important sources of biogenic
emissions are trees, which can emit a number of compounds. Pine
trees, for example, produce compounds called pinenes, which have
the familiar resinous aroma of pine needles. There are many factors
affecting the biogenic emissions. In order to keep track of the
effects of the many different factors, TCEQ uses computer models
such as GLOBEIS to estimate the biogenic
emissions. These models incorporate the latest surveys of local
land cover and vegetation type, and up-to-date scientific knowledge
of biogenic emissions. Since 1997, the TCEQ has commissioned
several special studies on the biogenic emissions of Texas
vegetation, in order to ensure that the biogenic emissions models
will work well for Texas cities.
The following types of data are needed to estimate biogenic
emissions:
- Land use/land cover (LULC) map - Based upon satellite
data, field surveys, and aerial photography of the area of
interest, researchers determine whether the land is covered by
forest, pasture, swamp, pavement, housing, or other natural and
man-made materials. Each parcel of land in the area of interest is
classified, and this map forms the basis of the biogenic emissions
model. The researchers then determine the type and density of
vegetation that each land category supports.
- Species composition - The relative abundance of
different types of trees in the area to be modeled is particularly
important because different types of trees emit different types and
vastly different quantities of VOC. Species composition is
ascertained primarily from field surveys.
- Leaf biomass density - Emissions are directly related to
the leaf biomass - all other factors being equal, more leaf biomass
means more emissions. Leaf biomass density is determined by field
study and by remote sensing. Surveyors first identify the tree and
then measure the height of the tree and diameter of the trunk. From
those data, they calculate the crown area and total leaf biomass of
a typical tree of that type, based on equations published in the
scientific literature. If there are areas that cannot be surveyed
on foot, the researchers rely upon aerial photographs and satellite
imagery.
- Meteorological variables - Emissions depend strongly
upon the temperature and solar radiation to which the leaves are
exposed. TCEQ uses the extensive network of temperature
measurements made by the National Weather Service (NWS)
, the TCEQ, and other
academic and governmental entities to create maps of temperature to
drive the model. To create hourly maps of solar radiation
intensity, TCEQ staff acquire solar radiation data from scientists
in academia, who have determined effective methods of estimating
solar radiation from satellite imagery of cloud cover.
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