This section contains brief descriptions of the methods used to implement various sections of the 2002 NATA. More detailed information may be found in the many links referred to in each section. The methods discussed are:
- Preparation of Emission Estimates
- Development of Background Concentrations
- Approach for Modeling POM
- Emissions Modeling with ASPEN and HEM
- HAPEM5 Modeling
- Estimating Exposure Concentrations
- Risk and Hazard Characterization
- Assessment Uncertainty and Variability
The 2002 National Emissions Inventory version 3 (NEI) is the underlying basis for the 2002 emissions used in the national-scale assessment. The types of emissions sources in this inventory include major stationary sources, e.g., large waste incinerators and factories; area and other sources, e.g., dry cleaners, small manufacturers, wildfires; and both onroad and nonroad mobile sources, e.g., cars, trucks, boats. In preparing the inventory for modeling, EPA used default, or simplifying assumptions where data were missing or of poor quality. For example, when data on stack height or facility location were not available or were flawed, they were replaced by default assumptions, e.g., a stack height for a facility might be set equal to stack heights at comparable facilities; the location of the facility might be placed at the center of a census tract; etc. A few changes in the 2002 NEI include the addition of 'fires' with point source data such as location and emissions information, and the addition of 'airports' as point sources. Only the airports were modeled as point sources. Fires were modeled as area sources.
EPA compiled the 2002 National Emissions Inventory (NEI) using a variety of data from six possible sources. These sources include:
- State and local toxic air pollutant inventories (developed by State and local air pollution control agencies)
- Existing databases related to EPA's air toxics regulatory program
- EPA's Toxic Release Inventory (TRI) database
- Estimates developed using mobile source methodologies (developed by EPA's Office of Transportation and Air Quality)
- Emission estimates generated from emission factors and activity data, and
- Revisions to source inventories made in response to the various Risk and Technology Review requests, i.e., changes resulting from the reviews of the Advanced Notice of Proposed Rulemaking (AMPRM) for RTR group 1 and 2a. It is advised that users review the specific source category changes in the RTR assessments in order to obtain a better characterization for these source categories
In compiling stationary source emissions information for the NEI, preference was given to State- and locally-generated information where available. When such data were not available, existing data from EPA's regulatory development databases were utilized. If neither of these data sources contains information for a known stationary source, EPA used data from the TRI. EPA also gave preference in inventory development to emissions data resulting from direct measurements over those generated from emissions factors and activity data.
For more information on emission inventories, see the National Emission Inventory Data web page or the NEI documentation page at http://www.epa.gov/ttn/chief/net/2002inventory.html. For additional information about the 2002 emissions of air toxics, including sources of emissions, visit AIRData. For summary information on air pollution trends, including air toxics trends, visit EPA's Air Trends.
The models discussed below do not estimate outdoor concentrations of air pollutants attributable to long-range pollutant transport, unidentified emission sources, and natural emission sources. These "background" contributions can be significant for some air toxics and should be accounted for to accurately estimate ambient concentrations. For NATA, background concentration estimates are intended to reflect contributions from sources farther than 50 km away, unidentified emissions sources, and natural emissions sources.
Two methods were used to develop estimates of background air toxics concentrations for the NATA 2002. The first method relies on ambient air toxics measurements (ambient-based method) and the second method relies on HAPs emission inventory data (emissions-based method). The ambient-based method is preferred because the background estimates are based on measured air toxics concentrations throughout the United States. Background concentrations were estimated for 14 HAPS using this method. However, reliable ambient measurements are not always available for every pollutant of interest. Background estimates based on the available ambient data for these pollutants could either have too few sites to extrapolate from or poor quality measurements on which to base background estimates. Therefore, an emissions-based method was developed to handle those pollutants with inadequate ambient measurements. Background concentrations were estimated for 16 HAPs using this method. In addition, a few pollutants were assigned uniform spatial concentrations based on their long lifetimes and well-characterized concentrations. These pollutants are carbon tetrachloride, methyl chloride, methyl bromide, and methyl chloroform. All are routinely measured at remote sites and have well-mixed concentrations in the Northern Hemisphere. More complete discussions of this may be found in the documents, Estimation of background concentrations for NATA 2002 (PDF) (43pp, 641k) and 2002 NATA background concentrations by county (Excel) (2.1 MB).
Not all POM reported to EPA's national emission inventory (NEI) are speciated into individual compounds. As a result, we must apply some simplifying assumptions in order to model and assess the risk from the individual pollutants that comprise POM. This involves establishing different POM "groups" and modeling them as separate pollutants. In establishing these groups, we considered the need to provide the most detailed information about risks from the individual pollutants within POM while taking into account the inconsistencies in how much speciation is reported in the inventory. We used a more refined method to establish POM groups for the 1999 and 2002 NATA than we did for the 1996 NATA to reflect improvements in the speciation of POM within the inventory. Specifically, for the 1996 NATA we had two overlapping POM groups and for the 1999 and 2002 NATA we have eight distinct groups. See the document Approach for Modeling POMs (PDF) (4pp, 35k) and Appendix H in the Science Advisory Board's peer review report on the 1996 NATA for more detailed discussion.Emissions Modeling System for Hazardous Pollutants (EMS-HAP) was used to process the emission inputs into the Assessment System for Population Exposure Nationwide, or ASPEN, the computer simulation model used to estimate toxic air pollutant concentrations. This model is based on the EPA's Industrial Source Complex Long Term model (ISCLT) which simulates the behavior of the pollutants after they are emitted into the atmosphere. ASPEN uses estimates of toxic air pollutant emissions and meteorological data from National Weather Service Stations to estimate air toxics concentrations nationwide. The ASPEN model takes into account important determinants of pollutant concentrations, such as:
- The rates of emission releases
- The location of these releases
- The height from which the pollutants are released
- The wind speeds and directions from the meteorological stations nearest to the release
- The breakdown of the pollutants in the atmosphere after being released, i.e., reactive decay
- The deposition or settling of pollutants out of the atmosphere, and
- The atmospheric transformation of one pollutant into another, i.e., secondary formation
Aspen was used to model the area and mobile source emissions. These estimates of toxic air pollutant concentrations were generated for every census tract in the continental United States, Puerto Rico and the Virgin Islands. Census tracts are land areas defined by the U.S. Bureau of the Census and typically contain about 4,000 residents each. They are usually smaller than 2 square miles in size in cities, but much larger in rural areas. More information including the ASPEN users guide is available at the SCRAM website.
Stationary source emissions were modeled using the EPA's Human Exposure Model (HEM). The HEM is used primarily for performing risk assessments for major point sources (usually producers or large users of specified chemicals) of air toxics. Like ASPEN, HEM only addresses the inhalation pathway of exposure, and is designed to predict risks associated with emitted chemicals in the ambient air, i.e., in the vicinity of an emitting facility but beyond the facility's property boundary. The HEM used for NATA 2002 contains:
- The AERMOD an atmospheric dispersion model, with included meteorological data, and
- U.S. Bureau of Census population data at the Census block level. Census blocks are the smallest spatial area modeled in NATA. Census blocks contain approximately 40 people, but the number of people may vary in size depending on whether they are located in urban or rural environments.
Both models utilizes the 2000 Census data. Each source must be specifically located by latitude and longitude, and its release parameters must be described. These include stack height, exit velocity, emission rate, etc. Based on the inputs for source parameters and the meteorological data, the model estimates the magnitude and distribution of ambient air concentrations in the vicinity of each source (at the census block or tract levels depending on which model was used). These models generally are used to estimate ambient concentrations within a radial distance of 50 kilometers (30.8 miles) from the source.
The concentrations estimated by these models are ambient air concentrations in micrograms per cubic meter. Ambient concentration estimates are actually surrogates for exposure, as important exposure variables, e.g., duration, human activity patterns, residential occupancy period, etc., are not explicitly addressed by these models. The ambient air concentrations were then used as inputs to the exposure model, HAPEM5 which is described below. More technical information about the HEM may be found at http://www.epa.gov/ttn/fera/human_hem.html.
The outputs from dispersion modeling (ASPEN or HEM) were used as input to the screening-level inhalation exposure model, HAPEM5. Estimating exposure is a key step in determining potential health risk. People move around from one location to another, e.g., outside to inside, commute to work, etc. Exposure isn't the same as concentration at a static site. People also breathe at different rates depending on their activity levels. For these reasons, the average concentration of a pollutant that people breathe, i.e., exposure concentration, may be significantly higher or lower than the concentration at a fixed location.
An updated HAPEM model, HAPEM5, was employed in the 1999 NATA to estimate exposure concentrations based on the dispersion model outputs. The HAPEM5 model is designed to predict the "apparent" inhalation exposure for specified population groups and air toxics. Through a series of calculation routines, the model makes use of census data, human activity pattern data, ambient air quality levels, climate data, and indoor/outdoor concentration relationships to estimate an expected range of "apparent" inhalation exposure concentrations for groups of individuals. Using four primary sources of information: population data from the US Census, population activity data, air quality data, and microenvironmental data, HAPEM5 uses the general approach of tracking representatives of specified demographic groups as they move among indoor and outdoor microenvironments (37 microenvironments have been identified and used in this assessment) and among geographic locations. The estimated pollutant concentrations in each microenvironment visited are combined into a timeweighted average concentration which is assigned to members of each demographic group. HAPEM5 divides the population into 10 demographic groups, based on combinations of age and gender, i.e., (males or females; within the age groups: 0-4, 5-11, 12-17, 18-64, 65+). Activity pattern data are also separated into 3 day types: summer weekdays, other weekdays, and weekends. From this set of model data, a single "population-weighted, median exposure concentration" which represents the best estimate of exposure for a "typical" person for a given census tract, is estimated. This concentration is then used to estimate risk and hazard for each HAP. This census tract level exposure concentration cannot be used to predict local-scale "hot spot" exposures or to capture a range of exposures experienced by individuals, including maximally exposed individuals. For more information, see the HAPEM5 Users Guide or go to 1996 NATA section on HAPEM.
For the 2002 NATA, the exposure level concentrations for each source, (i.e., stationary, area, mobile, and background) were not estimated by direct modeling. Instead the ambient level concentrations for each source were multiplied by a ratio (or tract-level exposure factor) of the estimated HAP-specific exposure concentrations to HAP-specific ambient concentrations (HAPEM output / ASPEN output for the same HAP, source, and census tract) that were developed from the 1999 HAPEM5 modeling. When census block level ambient concentrations (stationary sources were initially modeled at the census block level) were being converted to tract-level exposure concentrations using the tract-level exposure factors, the exposure factors were applied to each census block equally. As described below, census block-level concentrations were aggregated up to the census tract-level which is the level presented for all HAPs in the results section of the 2002 NATA. See the following section for a brief description of the aggregation method. These exposure factors from the 1999 NATA assessment were used to save modeling time and because the demographic distributions within the census data were the same, i.e., both assessments used the 2000 Census data as the source of census tract demographic data.
The risk and hazard quotients for each toxic air pollutant modeled is estimated from the exposure concentrations (not ambient concentrations) by combining the exposure concentration estimates with available unit risk estimates and inhalation reference concentrations, respectively. More details about the dose-responses used are found in the document Health Effects Information Final (PDF) (12pp, 82k) and in the section on "Risk Characterization" on the NATA website.
As described above, ASPEN or HEM modeling produced census tract-level or census block-level ambient concentration estimates, respectively, for each HAP. To get all concentrations at the same spatial level, tract-level concentrations were divided evenly across all census blocks in the tract, thereby creating a data set of census block-level ambient concentrations for all census blocks in the country. These sets of data while not presented in the results section of the NATA 2002 website (these block-level files are very large), were used as the starting point for estimating cancer and noncancer effects, and for aggregating up to larger spatial scales, i.e., tract, county, state, and US levels.
- Block level ambient concentrations were aggregated up to the tract level by taking the average of the block level concentrations and applying it to the tract.
- Block level ambient concentrations were aggregated up to county, state, or US level by using the population-weighted method described below.
The ambient block-level concentrations were also used to estimate exposure concentrations using the exposure factors (HAPEM/ASPEN ratios) described above. Since the exposure factors from the 1999 NATA were at the tract-level, each census block was assigned the tract-level factor and census block-level exposure concentrations were estimated. As was done with the ambient-level concentrations above, the block-level exposure concentrations were used to estimate cancer and noncancer effects and to aggregate these concentrations up to larger spacial scales. To aggregate tract-level concentrations up to county, State, or US level concentrations, the tract-level concentrations were population-weighted. For example, census tract exposure concentration estimates were multiplied by the population of each tract, summed, and divided by their county populations to get a final population-weighted county level concentration. The formula for this is:
concentrationc = county-level population weighted concentration
concentrationt = tract concentration
populationt = tract population
populationcty = county population
The same method would be applied when aggregating up to a state level (or higher), except that the populations used would be for the state (or higher) level.
The 2002 NATA results section presents ambient and exposure concentrations, cancer and noncancer risk and HQ estimates, respectively, at the tract, county, and state levels. The noncancer results from previous NATA assessments have shown that the respiratory and neurologic endpoints were the drivers of noncancer hazards. Therefore, in the NATA 2002, the noncancer results are presented only for the neurologic and respiratory endpoints. Other noncancer endpoint results may be calculated using the additional dose-response information found in the document Health Effects Information Final (PDF) (12pp, 82k). A more complete discussion may be found in the section, "Background on Risk Characterization".
A discussion of the components of variability and uncertainty will help understand why it's important to use the NATA results to answer only those questions for which the assessment is suitable. Only a brief overview is provided here, but a more complete discussion of variability and uncertainty is found in the document, Variability and Uncertainty in NATA (PDF) (9pp, 34k).
Variability: Emissions, air concentrations, exposures and risks are not the same throughout the U.S., and are not the same for everyone. Some geographic areas have higher concentrations than others, and there are some periods of time when the concentration is higher at a given location than at other times. Some individuals have an exposure and/or risk below the national average, while others have an exposure and/or risk above the national average. For these reasons, it is necessary to have some idea of how the ambient air concentration, exposure, and risk from HAPs varies throughout the U.S.
Uncertainty: The EPA seeks to protect health with reasonable confidence. But scientific estimates of air concentrations, exposures and risks always involve assumptions that simplify the real situation but make the assessment possible given available information and resources. These assumptions introduce uncertainties into the results, since there is never complete confidence that the assumptions are entirely correct. It is necessary to understand the size of these uncertainties, the level of confidence that can be placed on any statement made about the assessment, and how this confidence affects the ability to make reasoned decisions.