NATA: Glossary of Terms
On this page:
- "N" in 1 million cancer risk
- Activity pattern data
- AMS/EPA Regulatory Model (AERMOD)
- Air toxics
- Area and other sources
- Assessment System for Population Exposure Nationwide (ASPEN)
- Atmospheric transformation (secondary formation)
- Background concentrations
- Biogenic emissions
- Cancer risk
- Chemical Abstracts Service (CAS) number
- Census tracts
- Community Multi-scale Air Quality (CMAQ) modeling system
- Consolidated Human Activity Database (CHAD)
- Diesel particulate matter
- Dispersion model
- Emission Inventory System (EIS)
- Exposure assessment
- Hazard index (HI)
- Hazard quotient (HQ)
- Hazardous Air Pollutant Exposure Model (HAPEM)
- Human Exposure Model (HEM)
- Integrated Risk Information System (IRIS)
- Lifetime cancer risk
- Major sources
- Maximum likelihood estimate (MLE)
- Motor Vehicle Emission Simulator (MOVES)
- National-Scale Air Toxics Assessments (NATA)
- National Emissions Inventory (NEI)
- National Mobile Inventory Model (NMIM)
- Non-cancer risk
- Nonroad mobile sources
- Onroad mobile sources
- Polycyclic organic matter (POM)
- Reference concentration (RfC)
- Science Advisory Board (SAB)
- Secondary transformation
- Secondary sources
- Sparse Matrix Operator Kernel Emissions (SMOKE)
- Stationary Sources
- Upper-bound lifetime cancer risk
- Unit risk estimate (URE)
- Weight-of-evidence for carcinogenicity
- Carcinogenic to humans
- Likely to be carcinogenic to humans
- Suggestive evidence of carcinogenic potential
- Inadequate information to assess carcinogenic potential
- Not likely to be carcinogenic to humans
- Weather Research and Forecasting (WRF) model
"N" in 1 million cancer risk:
A risk level of “N”-in-1 million implies a likelihood that up to “N” people, out of one million equally exposed people would contract cancer if exposed continuously (24 hours per day) to the specific concentration over 70 years (an assumed lifetime). This would be in addition to those cancer cases that would normally occur in an unexposed population of one million people. Note that this assessment looks at lifetime cancer risks, which should not be confused with or compared to annual cancer risk estimates. If you would like to compare an annual cancer risk estimate with the results in this assessment, you would need to multiply that annual estimate by a factor of 70 or alternatively divide the lifetime risk by a factor of 70.
In an inhalation exposure assessment, activity-pattern data depict both the actual physical activity (including an associated inhalation exertion level); the physical location; and, the time of day the activity takes place (e.g., at midnight, while sleeping at home, jogging in the park at 8 a.m., or driving in a car at 6 p.m.). The Hazardous Air Pollution Model (HAPEM) uses activity-pattern data from EPA's Comprehensive Human Activity Database (CHAD).
EPA’s preferred model for near-field (i.e., within 50 km) simulations of dispersion of emissions. In simulating boundary-layer turbulence, it has the capability to model complex terrain, elevated sources, numerous discrete receptors, and source types ranging from point to line to volume, at hourly resolution.
Also known as toxic air pollutants or hazardous air pollutants*; those pollutants known to cause or suspected of causing cancer or other serious health problems. Health concerns could be associated with both short- and long-term exposures to these pollutants. Many are known to have respiratory, neurological, immune, or reproductive effects, particularly for more susceptible or sensitive populations such as children. Five important air pollutants are not included in the list of air toxics because the Clean Air Act addresses them separately as “criteria pollutants.” These are particulate matter (PM), nitrogen oxides (NOx), sulfur oxides (SOx), ozone, and carbon monoxide. Lead is both a criteria pollutant and an air toxic. Criteria pollutants are not addressed in NATA.
*Diesel particulate matter is not a hazardous air pollutant but is included in the NATA air toxics.
Surrounding, as in the surrounding environment. In NATA assessments, ambient air refers to the outdoor air surrounding a person through which pollutants can be carried. Therefore, the ambient concentrations estimated by NATA are those concentrations estimated in the outdoor environment. NATA also estimates exposure concentrations that result from an individual's movement through various microenvironments, including the indoor environment.
Include sources that generally have lower emissions on an individual basis than “major sources” and are often too small or ubiquitous to be inventoried as individual sources. “Area sources” include facilities that have air toxics emissions below the major source threshold as defined in the air toxics sections of the Clean Air Act and thus emit less than 10 tons of a single toxic air pollutant or less than 25 tons of multiple toxic air pollutants in any one year. Area sources include smaller facilities, such as dry cleaners.
As a separate definition, area sources in air-quality modeling refer to those modeled in two dimensions (with length and width), as compared to point sources modeled at a single location.
A computer simulation model used to estimate toxic air pollutant concentrations. The ASPEN model takes into account important determinants of pollutant concentrations, such as: rate of release, location of release, the height from which the pollutants are released, wind speeds and directions from the meteorological stations nearest to release, breakdown of the pollutants in the atmosphere after being released (i.e., reactive decay), settling of pollutants out of the atmosphere (i.e., deposition), and transformation of one pollutant into another (i.e., secondary formation or decay). The model estimates toxic air pollutant concentrations for every census tract in the United States, Puerto Rico, and the Virgin Islands.
The process by which chemicals are transformed in the air into other chemicals. When a chemical is transformed, the original HAP no longer exists; it is replaced by one or more chemicals. Compared to the original chemical, the newer reaction products can have more, less, or the same toxicity. Transformations and removal processes affect both the fate of the chemical and its atmospheric persistence. Persistence is important because human exposure to chemical is influenced by the length of time the chemical remains in the atmosphere. Note that in NATA the terms atmospheric transformation and secondary formation are used interchangeably.
For NATA, the contributions to outdoor air toxics concentrations resulting from natural sources, persistence in the environment of past years' emissions, and long-range transport from distant sources. Background concentrations could be levels of pollutants that would be found in a particular year, even if there had been no recent manmade emissions. Background concentrations are added to the AERMOD concentrations but not to the CMAQ modeled concentrations which account for long range transport and emissions from outside the domain through boundary conditions. The vast majority of risk from the NATA background concentrations is from carbon tetrachloride, a ubiquitous pollutant that has few sources of emissions but is persistent due to its long half-life.
Biogenic emissions are emissions from natural sources, such as plants and trees. These sources emit formaldehyde, acetaldehyde and methanol as well as large quantities of other non-HAP VOCs. Formaldehyde and acetaldehyde are key risk drivers in NATA. Biogenic emissions are typically computed using a model which utilizes spatial information on vegetation and land use and environmental conditions of temperature and solar radiation. In addition to being a primary source of HAP, other VOCs emitted by Biogenic sources react with anthropogenic VOCs and NOX to produce secondary formed HAPs. The NATA biogenics source group includes only the primary emissions.
The probability of contracting cancer over the course of a lifetime, assuming continuous exposure (assumed to be 70 years for the purposes of NATA risk characterization).
A chemical or physical agent that can cause cancer.
A unique number assigned to a chemical by the Chemical Abstracts Service, a service of the American Chemical Society that indexes and compiles abstracts of worldwide chemical literature called “Chemical Abstracts.” The purpose is to make database searches more convenient, as chemicals often have many names.
Land areas defined by the U.S. Census Bureau. Tracts can vary in size but each typically contains about 4,000 residents. Census tracts are usually smaller than 2 square miles in cities, but are much larger in rural areas.
Generally defined as a group of people within a population who are assumed to have identical exposures during a specified exposure period. The use of cohorts is a necessary simplifying assumption for modeling exposures of a large population. For the exposure assessment, the population is divided into a set of cohorts such that (1) each person is assigned to one and only one cohort, and (2) all the cohorts combined encompass the entire population.
A multi-pollutant air quality modeling system using a three-dimensional gridded simulation environment with atmospheric chemistry to model transport of emissions across local to long-range scales.
The Consolidated Human Activity Database (CHAD) is an EPA comprehensive human-activity database consisting of data from numerous activity studies since 1982 and supporting assessments of human exposure, intake dose, and risk.
A mixture of particles that is a component of diesel exhaust. EPA lists diesel exhaust as a mobile-source air toxic due to the cancer and non-cancer health effects associated with exposure to whole diesel exhaust. Diesel PM (expressed as grams diesel PM/m3) has historically been used as a surrogate measure of exposure for whole diesel exhaust. Although uncertainty exists as to whether diesel PM is the most appropriate parameter to correlate with human health effects, it is considered a reasonable choice until more definitive information about the mechanisms of toxicity or mode(s) of action of diesel exhaust becomes available.
A computerized set of mathematical equations that uses emissions and meteorological information to simulate the behavior and movement of air pollutants in the atmosphere. The results of a dispersion model are estimated outdoor concentrations of individual air pollutants at specified locations.
Emission Inventory System (EIS):
An EPA information system for storing all current and historical emission inventory data. It is used to receive and store emissions data and generate emission inventories beginning with the 2008 National Emissions Inventory (NEI). Partners used the EIS Exchange to submit Facility Inventory, Point, Nonpoint, Onroad and Nonroad data categories to the EIS Production or Quality Assurance (QA) environments.
Identifying the ways in which chemicals might reach individuals (e.g., by breathing); estimating how much of a chemical an individual is likely to be exposed to; and, estimating the number of individuals likely to be exposed.
The sum of hazard quotients for substances that affect the same target organ or organ system. Because different pollutants (air toxics) can cause similar adverse health effects, combining hazard quotients associated with different substances is often appropriate. EPA has drafted revisions to the national guidelines on mixtures that support combining the effects of different substances in specific and limited ways. Ideally, hazard quotients should be combined for pollutants that cause adverse effects by the same toxic mechanism. Because detailed information on toxic mechanisms is not available for most of the substances in NATA, however, EPA aggregates the effects when they affect the same target organ regardless of the mechanism. The hazard index (HI) is only an approximation of the aggregate effect on the target organ (e.g., the lungs) because some of the substances might cause irritation by different (i.e., non-additive) mechanisms. As with the hazard quotient, aggregate exposures below an HI of 1.0 derived using target organ specific hazard quotients likely will not result in adverse non-cancer health effects over a lifetime of exposure and would ordinarily be considered acceptable. An HI equal to or greater than 1.0, however, does not necessarily suggest a likelihood of adverse effects. Because of the inherent conservatism of the reference concentration (RfC) methodology, the acceptability of exceedances must be evaluated on a case-by-case basis, considering such factors as the confidence level of the assessment, the size of the uncertainty factors used, the slope of the dose-response curve, the magnitude of the exceedance, and the number or types of people exposed at various levels above the RfC. Furthermore, the HI cannot be translated to a probability that adverse effects will occur, and it is not likely to be proportional to risk.
The ratio of the potential exposure to the substance and the level at which no adverse effects are expected. A hazard quotient less than or equal to one indicates that adverse noncancer effects are not likely to occur, and thus can be considered to have negligible hazard. HQs greater than one are not statistical probabilities of harm occurring. Instead, they are a simple statement of whether (and by how much) an exposure concentration exceeds the reference concentration (RfC). Moreover, the level of concern does not increase linearly or to the same extent as HQs increase above one for different chemicals because RfCs do not generally have equal accuracy or precision and are generally not based on the same severity of effect. Thus, we can only say that with exposures increasingly greater than the RfC, (i.e., HQs increasingly greater than 1), the potential for adverse effects increases, but we do not know by how much. An HQ of 100 does not mean that the hazard is 10 times greater than an HQ of 10. Also an HQ of 10 for one substance may not have the same meaning (in terms of hazard) as another substance resulting in the same HQ.
A computer model that has been designed to estimate inhalation exposure for specified population groups and air toxics. Through a series of calculation routines, the model makes use of census data, human-activity patterns, ambient air quality levels, and indoor/outdoor concentration relationships to estimate an expected range of inhalation exposure concentrations for groups of individuals.
The Human Exposure Model (HEM) is a computer model used primarily for conducting inhalation risk assessments for sources emitting air toxics to ambient air. HEM-3 contains the AERMOD dispersion model for air-transport simulations and U.S. Census data for identifying population receptors.
Breathing. Once inhaled, contaminants can be deposited in the lungs, taken into the blood, or both.
The Integrated Risk Information System (IRIS) is an EPA program that identifies and characterizes the health hazards of chemicals found in the environment. IRIS is EPA’s preferred source of toxicity information.
The probability of contracting cancer over the course of a lifetime (assumed to be 70 years for the purposes of NATA risk characterization).
Defined by the Clean Air Act as those stationary facilities that emit or have the potential to emit 10 tons of any one toxic air pollutant or 25 tons of more than one toxic air pollutant per year.
The most accurate maximum likelihood estimate is, by definition, the mode of a data set (i.e., the most frequent observation). When data are too limited to identify a clear mode, the average or the median of the data is usually substituted. For some air toxics for which adequate human data exist, EPA has based the unit risk estimate on the maximum-likelihood estimate for response data or for fitted curves.
The middle value of a set of ordered values (i.e., half the numbers are less than or equal to the median value). A median is the 50th percentile of the data.
A state-of-the-science emissions modeling system that estimates emissions for mobile sources at the national, county, and project level for criteria air pollutants, air toxics, and greenhouse gases.
A small space in which human contact with a pollutant takes place. A microenvironment can be treated as a well-characterized, relatively homogenous location with respect to pollutant concentrations for a specified period. For NATA, the Hazardous Air Pollutant Exposure Model considers cohort activities in 18 microenvironment locations that include (1) indoor locations (e.g., residence, office, store, school, restaurant, church, manufacturing facility, auditorium, healthcare facility, service station, other public building, garage); (2) outdoor locations (e.g., parking lot/garage, near road, motorcycle, service station, construction site, residential grounds, school, sports arena, park/golf course); and (3) in-vehicle locations (e.g., car, bus, truck, other, train/subway, airplane).
One-millionth of a gram. One gram is about one twenty-eighth of an ounce.
EPA's ongoing comprehensive evaluation of air toxics in the United States. These activities include the expansion of air toxics monitoring, improvement and periodic updating of emission inventories, improvement of national- and local-scale modeling, continued research on health effects and exposures to both ambient and indoor air, and improvement of assessment tools.
EPA 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. The database includes estimates of annual emissions, by source, of air pollutants in each area of the country, on an annual basis. The National Emissions Inventory includes emission estimates for all 50 states, the District of Columbia, Puerto Rico, and the U.S. Virgin Islands.
National Mobile Inventory Model (NMIM):
Computer application containing EPA’s NONROAD model for estimating county level inventories of nonroad mobile emissions.
The risk associated with effects other than cancer, based on the reference concentration, which is an estimate, with uncertainty spanning perhaps an order of magnitude, of an inhalation exposure to the human population (including sensitive subgroups) that is likely to be without appreciable risks of deleterious effects during a lifetime.
Mobile sources not found on roads and highways (e.g., airplanes, trains, lawn mowers, construction vehicles, farm machinery).
Vehicles found on roads and highways (e.g., cars, trucks, buses).
Any one of the points dividing a distribution of values into parts that each contain 1/100 of the values. For example, the 75th percentile is a value such that 75 percent of the values are less than or equal to it. In this assessment, the distribution of values represented (national, state, or county percentiles) depends on the presentation format of the results (map, bar chart, or data table).
Defines a broad class of compounds that includes polycyclic aromatic hydrocarbons. Polycyclic organic matter (POM) compounds are formed primarily from combustion and are present in the atmosphere in particulate form. Sources of air emissions are diverse and include vehicle exhausts, forest fires and wildfires, asphalt roads, coal, coal tar, coke ovens, agricultural burning, residential wood burning, and hazardous waste sites. Not all POM reported to EPA's National Emission Inventory is speciated. As a result, EPA applies some simplifying assumptions to model and assess the risk from the individual pollutants that comprise polycyclic organic matter.
Reference concentration (RfC):
The reference concentration is an estimate (with uncertainty spanning perhaps an order of magnitude) of a continuous inhalation exposure to the human population (including sensitive subgroups that include children, asthmatics, and the elderly) that is likely to be without an appreciable risk of deleterious effects during a lifetime. It can be derived from various types of human or animal data, with uncertainty factors generally applied to reflect limitations of the data used.
The probability that damage to life, health, or the environment will occur as a result of a given hazard (such as exposure to a toxic chemical). Some risks can be measured or estimated in numerical terms (e.g., one chance in a hundred).
Consistent with the definition EPA used in the analyses to support the Integrated Urban Air Toxics Strategy, a county is considered “rural” if it does not contain a metropolitan statistical area with a population greater than 250,000 and the U.S. Census Bureau does not designate more than 50 percent of the population as “urban.” Note that this definition does not necessarily apply for any regulatory or implementation purpose.
A panel of scientists, engineers, and economists who provide EPA with independent scientific and technical advice.
A modeling system that processes emissions data for use in gridded air quality models. It uses the Biogenic Emission Inventory System (BEIS) to model biogenic emissions. It also has a feature to use MOVES emission factors, activity data and meteorological data to compute hourly gridded onroad mobile emissions.
Emission sources other than mobile sources such as large industrial sources such as power plants and refineries, smaller industrial and commercial sources such as dry cleaners and commercial cooking, and residential sources such as residential wood combustion and consumer products usage. Stationary sources may be characterized as being emitted from “major“ sources or “area“ sources based on the 10-ton or 25-ton definitions contained in the Clean Air Act. For presentation purposes, the NATA results are identified as “point“ and “nonpoint“ sources rather than “major“ and “area“ sources. The point and nonpoint designations reflect the way each source of emissions is modeled. Some smaller sources that are area sources in the inventory (based on the amount of their emissions) are modeled as point sources because the location of their emissions was identified with latitude and longitude coordinates.
An increased likelihood of an adverse effect, often discussed in terms of relationship to a factor (e.g., life stage, demographic feature, or genetic characteristic) that can be used to describe a human subpopulation.
A relative risk evaluation tool that normalizes the emissions rates of each pollutant to a hypothetical substance with an inhalation unit risk value of 1/μg/m3 (for carcinogenic effects) or a reference concentration of 1 mg/m3 (for non-cancer effects). It is entirely emissions-based and toxicity-based, and does not consider dispersion, fate, receptor locations, and other exposure parameters. It may be calculated based on the emissions data for all pollutants released from a facility or source being assessed. It is particularly useful if the number of pollutants is large and the desire is to focus the risk analysis on a smaller subset of pollutants that contribute the most to risk.
Describes a hypothetical person living at the census-tract centroid (defined as a reference point that is usually but not always located at the geographic center of a census tract) and engaging in a range of activities (indoors and outdoors) that are representative of those in which individuals residing in that tract might engage. To characterize the risk that this person might experience, NATA divides the population as a whole into cohorts (groups who are assumed to have identical exposures during a specified exposure period) based on where they live, how old they are, and what their daily-activity patterns might be. For each combination of residential census tract, age, various age-appropriate daily-activity patterns are selected to represent the range of exposure conditions for residents of the tract. A population-weighted typical exposure estimate is calculated for each cohort, and this value is used to estimate representative risks for a “typical” individual residing in that tract.
A plausible upper limit to the true value of a quantity; usually not a true statistical confidence limit.
A plausible upper limit to the true probability that an individual will contract cancer over a 70-year lifetime as a result of a given hazard (such as exposure to a toxic chemical). This risk can be measured or estimated in numerical terms (e.g., one chance in a hundred).
The upper-bound excess lifetime cancer risk estimated to result from continuous exposure to an agent at a concentration of 1 µg/m3 in air. The interpretation of the unit risk estimate (URE) would be as follows: If the URE = 1.5 x 10-6 per µg/m3, 1.5 excess tumors are expected to develop per 1,000,000 people if they were exposed daily for a lifetime to 1 µg of the chemical in 1 m3 of air. UREs are considered upper-bound estimates, meaning they represent a plausible upper limit to the true value. (Note that this is usually not a true statistical confidence limit.) The true risk is likely to be less, but could be greater.
Consistent with the definition EPA used in the analyses to support the Integrated Urban Air Toxics Strategy, a county is considered “urban” if it either includes a metropolitan statistical area with a population greater than 250,000 or the U.S. Census Bureau designates more than 50 percent of the population as “urban.“ Note that this definition does not necessarily apply for any regulatory or implementation purpose.
The weight-of-evidence (WOE) narrative for carcinogenicity is a summary that explains what is known about an agent's human carcinogenic potential and the conditions that characterize its expression. The narrative should be sufficiently complete to stand alone, highlighting the key issues and decisions that were the basis for the evaluation of the agent's potential hazard. The WOE characterizes the extent to which the available data support the hypothesis that an agent causes cancer in humans. Under EPA's 1986 risk assessment guidelines, the weight of evidence is described by categories “A through E,” with Group A for known human carcinogens through Group E for agents with evidence of non-carcinogenicity. The approach outlined in EPA's guidelines for carcinogen risk assessment (2005) considers all scientific information in determining if and under what conditions an agent can cause cancer in humans, and provides a narrative approach to characterize carcinogenicity rather than categories. To provide clarity and consistency in an otherwise free-form, narrative characterization, standard descriptors are used as part of the hazard narrative to express the conclusion regarding the WOE for carcinogenic hazard potential. Five standard hazard descriptors are recommended: (1) carcinogenic to humans, (2) likely to be carcinogenic to humans, (3) suggestive evidence of carcinogenic potential, (4) inadequate information to assess carcinogenic potential, and (5) not likely to be carcinogenic to humans.
This descriptor indicates strong evidence of human carcinogenicity. It covers different combinations of evidence. This descriptor is appropriate when the epidemiologic evidence of a causal association between human exposure and cancer is convincing. An exception is that this descriptor might also be equally appropriate with a lesser weight of epidemiologic evidence that is strengthened by other lines of evidence. This descriptor can be used when all of the following conditions are met: (a) there is strong evidence of an association between human exposure and either cancer or the key precursor events of the agent's mode of action but not enough for a causal association; (b) there is extensive evidence of carcinogenicity in animals; (c) the mode(s) of carcinogenic action and associated key precursor events have been identified in animals, (d) there is strong evidence that the key precursor events that precede the cancer response in animals are anticipated to occur in humans and progress to tumors, based on available biological information.
This descriptor is appropriate when the weight of the evidence is adequate to demonstrate carcinogenic potential to humans but does not reach the WOE for the descriptor “carcinogenic to humans.” Adequate evidence consistent with this descriptor covers a broad spectrum. At one end of the spectrum is evidence for an association between human exposure to the agent and cancer and strong experimental evidence of carcinogenicity in animals; at the other, with no human data, the weight of experimental evidence shows animal carcinogenicity by a mode or modes of action that are relevant or assumed to be relevant to humans. The use of the term “likely” as a WOE descriptor does not correspond to a quantifiable probability. Moreover, additional information, for example, on mode of action, might change the choice of descriptor for the illustrated examples.
This descriptor is appropriate when the WOE suggests carcinogenicity; a concern for potential carcinogenic effects in humans is raised, but the data are judged insufficient for a stronger conclusion. This descriptor covers a spectrum of evidence associated with varying levels of concern for carcinogenicity, ranging from a positive cancer result in the only study on an agent to a single positive cancer result in an extensive data base that includes negative studies in other species. Depending on the extent of the data base, additional studies might or might not provide further insights.
This descriptor is appropriate when available data are judged inadequate for applying one of the other descriptors. Additional studies generally would be expected to provide further insights.
This descriptor is appropriate when the available data are considered robust for deciding that there is no basis for human hazard concern. In some instances, there can be positive results in experimental animals when the evidence is strong and consistent that each mode of action in experimental animals does not operate in humans. In other cases, the evidence in both humans and animals that the agent is not carcinogenic can be convincing. “Not likely” applies only to the circumstances supported by the data. For example, an agent might be “not likely to be carcinogenic” by one route but not necessarily by another. In cases having positive animal experiment(s) but the results are judged not to be relevant to humans, the narrative discusses why the results are not relevant.
A mesoscale numerical weather-prediction system for atmospheric research and weather forecasting. It can generate atmospheric conditions using real input data or idealized conditions.