Appendix C
Categories of Environmental Regulatory Models
As discussed in Chapter 2, models can be categorized according to their fit into a continuum of processes that translate human activities and natural systems interactions into human health and environmental impacts (see Figure 2-1). The categories of models that are integral to environmental regulation include human activity models, natural systems models, emissions models, fate and transport models, exposure models, human health and environmental response models, economic impact models, and noneconomic impact models. Examples of models in each of these categories are discussed below.
HUMAN ACTIVITY MODELS
Anthropogenic emissions to the environment are inherently linked to human activities. Activity models simulate the human activities and behaviors that result in pollutants. In the environmental regulatory modeling arena, examples of modeled activities are the following:
-
Demographic information, such as the magnitude, distribution, and dynamics of human populations, ranging from national growth projections to local travel activity patterns on the order of hours.
-
Economic activity, such as the macroeconomic estimates of national economic production and income, final demands for aggregate
-
industrial sectors, prices, international trade, interest rates, and financial flows.
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Human consumption of resources, such as gasoline or feed, may be translated into pollutant releases, such as nitrogen oxides or nutrients. Human food consumption is also used to estimate exposure to pollutants such as pesticides. Resource consumption in dollar terms may be used to assess economic impacts.
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Distribution and characteristics of land use are used to assess habitat, impacts on the hydro-geologic cycle and runoff, and biogenic pollutant releases.
Human Activity Models
Model |
Type |
Use |
Additional Information |
TRANSCAD, TRANPLAN, MinUTP |
Travel demand forecasting models |
Develops estimations of motor vehicle miles traveled for use in estimating vehicle emissions. Can be combined with geographic information systems (GIS) for providing spatial and temporal distribution of motor vehicle activity. |
Caliper Corporation 2007 |
DRI |
Forecasts national economic indicators |
Model can forecast over 1,200 economic concepts including aggregate supply, demand, prices, incomes, international trade, interest rates, etc. The eight sectors of the model are: domestic spending, domestic income, tax sector, prices, financial, international trade, expectations, and aggregate supply. |
EIA 1993 |
E-GAS |
National and regional economic activity model |
Emissions growth factors for various sector for estimating volatile organic compounds, nitrogen oxides, and carbon monoxide emissions. |
Young et al. 1994 |
YIELD |
Crop-growth yield model |
Predicts temporal and spatial crop yield. |
Hayes et al. 1982 |
NATURAL SYSTEMS PROCESS AND EMISSIONS MODELS
Natural systems process and emissions models simulate the dyna-
mics of ecosystems that directly or indirectly give rise to fluxes of nutrients and other environmental emissions.
Natural Systems Process and Emissions Models
Model |
Type |
Use |
Additional Information |
Marine Biological Laboratory General Ecosystem Model (MBL-GEM) |
Plot-scale nutrient cycling of carbon and nitrogen |
Simulates plot-level photosynthesis and nitrogen uptake by plants, allocation of carbon and nitrogen to foliage, stems, and fine roots, respiration in these tissues, turnover of biomass through litter fall, and decomposition of litter and soil organic matter. |
MBL 2005 |
BEIS |
Natural emissions of volatile organic compounds |
Simulates nitric oxide emissions from soils and volatile organic compound emissions from vegetation. Input to grid models for NAAQS attainment (CAA). |
EPA 2006a Vukovich and Pierce 2002 |
Natural Emissions Model |
Natural emissions of methane and nitrous oxide |
Models methane and nitrous oxide emissions from the terrestrial biosphere to atmosphere. |
MIT 2006, Sokolov et al. 2005 |
EMISSIONS MODELS
These models estimate the rate or the amount of pollutant emissions to water bodies and the atmosphere. The outputs of emission models are used to generate inventories of pollutant releases that can then serve as an input to fate and transport models.
Emissions Models
Model |
Type |
Use |
Additional Information |
PLOAD |
Releases to water bodies |
GIS bulk loading model providing annual pollutant loads to waterbodies. Conducts simplified analyses of sediment issues, including a bank erosion hazard index. |
EPA 2007a EPA 2001 |
Model |
Type |
Use |
Additional Information |
SPARROW |
Releases to water bodies |
Relates nutrient sources and watershed characteristics to total nitrogen. Predicts contaminant flux, concentration, and yield in streams. Provides empirical estimates (including uncertainties) of the fate of contaminants in streams. |
USGS 2007a Schwarz et al. 2006 |
MOBILE MOVES NONROAD |
Releases to air |
Factors and activities for anthropogenic emissions from mobile sources. Estimates current and future emissions (hydrocarbons, carbon monoxide, nitrogen oxides, particulate matter, hazardous air pollutants, and carbon dioxide) from highway motor vehicles. Model used to evaluate mobile source control strategies, control strategies for state implementation plans, and for developing environmental impact statements, in addition to other research. |
EPA 2007b EPA 2006b EPA 2004, EPA 2005a Glover and Cumberworth 2003 |
FATE AND TRANSPORT MODELS
Fate and transport models calculate the movement of pollutants in the environment. A large number of EPA models fall into this category. They are further categorized into the transport media they represent: subsurface, air, and surface water. In each medium, there are a range of models with respect to their complexity, where the level of complexity is a function of the following:
-
The number of physical and chemical processes considered.
-
The mathematical representation of those processes and their numerical solution.
-
The spatial and temporal scales over which the processes are modeled.
Even though some fate and transport models can be statistical models, the majority is mechanistic (also referred to as process-based models). Such models simulate individual components in the system and the
mathematical relationships among the components. Fate and transport model output has traditionally been deterministic, although recent focus on uncertainty and variability has led to some probabilistic models.
Subsurface Models
Subsurface transport is governed by the heterogeneous nature of the ground, the degree of saturation of the subsurface, as well as the chemical and physical properties of the pollutants of interest. Such models are used to assess the extent of toxic substance spills. They can also assess the fate of contaminants in sediments. The array of subsurface models is tailored to particular application objectives, for example, assessing the fate of contaminants leaking from underground gasoline storage tanks or leaching from landfills. Models are used extensively for site-specific risk assessments; for example, to determine pollutant concentrations in drinking-water sources. The majority of models simulate liquid pollutants; however, some simulate gas transport in the subsurface.
Subsurface Models
Model |
Type |
Use |
Additional Information |
MODFLOW |
3D finite difference for ground water transport |
Risk Assessments (RBCA) Superfund Remediation (CERCLA). Modular three-dimensional model that simulates ground water flow. Model can be used to support groundwater management activities. |
USGS 2007b Prudic et al. 2004, Wilson and Naff 2004 |
PRZM |
Hydrogeological |
Pesticide leaching into the soil and root zone of plants (FIFRA). Estimates pesticide and nitrogen fate in the crop zone root and can simulate soil temperature, volatilization and vapor phase transport in soil, irrigation, and microbial transformation. |
EPA 2007c EPA 2005b |
BIOPLUME |
Two-dimensional finite difference |
Simulates organic contaminants in groundwater due to natural processes of |
EPA 2006c EPA 1998 |
Model |
Type |
Use |
Additional Information |
|
and Method of Characteristics (MOC) model |
dispersion, advection, sorption, and biodegradation. Simulates aerobic and anaerobic biodegradation reactions. |
|
Surface Water Quality Models
Surface water quality models are often related to, or are variations of, hydrological models. The latter are designed to predict flows in water bodies and runoff from precipitation, both of which govern the transport of aqueous contaminants. Of particular interest in some water quality models is the mixing of contaminants as a function of time and space, for example, following a point-source discharge into a river. Other features of these models are the biological, chemical, and physical removal mechanisms of contaminants, such as degradation, oxidation, and deposition, as well as the distribution of the contaminants between the aqueous phase and organisms.
Surface Water Quality Models
Model |
Type |
Use |
Additional Information |
HSPF |
Combined watershed hydrology and water quality |
Total maximum daily load determinations TMDL (CWA). Watershed model simulating nonpoint pollutant load and runoff, fate and transport processes in streams. |
EPA 2006d Donigian 2002 |
WASP |
Compartment modeling for aquatic systems |
Supports management decisions by predicting water quality responses to pollutants in aquatic systems. Multicompartment model that examines both the water column and underlying benthos. |
EPA 2006e Brown 1986 Brown and Barnwell 1987 |
QUAL2E |
Steady-state and quasi-dynamic water quality model |
Stream water quality model used as a planning tool for developing TMDLs. The model can simulate nutrient cycles, benthic and carbonaceous demand, algal production, among other parameters. |
Birgand 2004 Brown 1986, Brown and Barnwell 1987 |
Air Quality Models
The fate of gaseous and solid particle pollutants in the atmosphere is a function of meteorology, temperature, relative humidity, other pollutants, and sunlight intensity, among other things. Models that simulate concentrations in air have one of three general designs: plume models, grid models, and receptor models. Plume models are used widely for permitting under requirements to assess the impacts of large new or modified emissions sources on air quality or to assess air toxics (HAPs) concentrations close to sources. Plume models focus on atmosphere dynamics. Grid models are used primarily to assess concentrations of secondary criteria pollutants (e.g., ozone) in regional airsheds to develop plans (SIPs) and rules with the objective of attaining ambient air quality standards (NAAQS). Both atmospheric dynamics and chemistry are important components of 3-D grid models. In contrast to mechanistic plume and grid models, receptor models are statistical; they determine the statistical contribution of various sources to pollutant concentrations at a given location based on the relative amounts of pollutants at source and receptor. Most air quality models are deterministic.
Air Quality Models
Model |
Type |
Use |
Additional Information |
CMAQ |
3-D Grid |
SIP development, NAAQS setting (CAA). The model provides estimates of ozone, particulates, toxics, and acid deposition and simulates chemical and physical properties related to atmospheric trace gas transformations and distributions. Model has three components including, meteorological system, an emissions model for estimating anthropogenic and natural emissions, and a chemistry-transport modeling system. |
EPA 2007d Byun and Ching 1999 |
UAM |
3-D Grid |
Model calculates concentrations of inert and chemically reactive pollutants and is used to evaluate air quality, particularly related to ambient ozone concentrations. |
Systems Applications International, Inc., 1999 |
Model |
Type |
Use |
Additional Information |
REMSAD |
3-D Grid |
Using simulation of physical andchemical processes in the atmosphere that impact pollutant concentrations, model calculates concentration of inert and chemically reactive pollutants. |
ICF International/ Systems Applications International 2006, ICF Consulting 2005 |
ICSC |
Plume |
PSD permitting; toxics exposure (CAA, TSCA). |
|
CALPUFF |
|
Non-steady-state air quality dispersion model that simulates long range transport of pollutants. |
|
CMB |
Receptor |
Relative contributions of sources. Receptor model used for air resource management purposes. |
EPA 2006f Coulter 2004 |
EXPOSURE MODELS
The primary objective of exposure models is to estimate the dose of pollutant which humans or animals are exposed to via inhalation, ingestion and/or dermal uptake. These models bridge the gap between concentrations of pollutants in the environment and the doses humans receive based on their activity. Pharmacokinetic models take this one step further and estimate dose to tissues in the body. Since exposure is inherently tied to behavior, exposure models may also simulate activity, for example a model that estimates dietary consumption of pollutants. In addition to the Lifeline model described below, other examples of models that estimate dietary exposure to pesticides include Calendex and CARES. These models can be either deterministic or probabilistic, but are well-suited for probabilistic methods due to the variability of activity within a population.
Exposure Models
Model |
Type |
Use |
Additional Information |
Lifeline |
Diet, water and dermal of single chemical |
Aggregate dose of pesticide via multiple pathways. |
Lifeline Group, Inc. 2007 Lifeline Group, Inc. 2006 |
IEUBK |
Multipathway, single chemical |
Dose of lead to children’s blood via multiple pathways. Estimates exposure from lead in media (air, water, soil, dust, diet, and paint and other sources) using pharmacokinetic models to predict blood lead levels in children 6 months to 7 years old. The model can be used as a tool for the determination of site-specific cleanup levels. |
EPA 2005c EPA 1994 |
Air Pollutants Exposure Model (APEX) |
Inhalation exposure model |
Simulates an individual’s exposure to an air pollutant and their movement through space and time in indoor or outdoor environments. Provides dose estimates and summary exposure information for each individual. |
EPA 2007e Richmond et al. 2001 |
HUMAN HEALTH AND ENVIRONMENT RESPONSE MODELS
Human Health Effects Models
Health effects models provide a statistical relationship between a dose of a chemical and an adverse human health effect. Health effects models are statistical methods, hence models in this category are almost exclusively empirical. They can be further classified as toxicological and epidemiological. The former refer to models derived from observations in controlled experiments, usually with nonhuman subjects. The latter refer to models derived from observations over large populations. Health models use statistical methods and assumptions that ultimately assume cause and effect. Included in this category are models that extrapolate information from non-human subject experiments. Also, physiologically based pharmacokinetic models can help predict human toxicity to contaminants through mathematical modeling of absorption, distribution, storage, metabolism, and excretion of toxicants.
The output from health models is almost always a dose, such as a safe level (for example, reference dose [RfD]), a cancer potency index (CPI), or an expected health end point (for example, lethal dose for 50% of the population (LD50) or number of asthma cases). There also exist model applications that facilitate the use of the statistical methods.
Human Health Effects Models
Model |
Type |
Use |
Additional Information |
Benchmark dose model |
Software tool for applying a variety of statistical models to analyze dose-response data |
To estimate risk of pollutant exposure. Models fit to dose-response data to determine a benchmark dose that is associated with a particular benchmark response. |
EPA 2007f EPA 2000 |
Linear Cancer model |
Statistical analysis method |
To estimate the risk posed by carcinogenic pollutants. |
|
Ecological Effects Models
Ecological effects models, like human health effects models, define relationships between a level of pollutant exposure and a particular ecological indicator. Many ecological effects models simulate aquatic environments, and ecological indicators are related directly to environmental concentrations. Examples of ecological effects indicators that have been modeled are: algae blooms, BOD, fish populations, crop yields, coast line erosion, lake acidity, and soil salinity.
Ecological Effects Models
Model |
Type |
Use |
Additional Information |
AQUATOX |
Integrated fate and effects of pollutants in aquatic environment |
Ecosystem model that predicts the environmental fate of chemicals in aquatic ecosystems, as well as direct and indirect effects on the resident organisms. Potential applications to management decisions include water quality criteria and standards, TMDLs, and ecological risk assessments of aquatic systems. |
EPA 2006g Hawkins 2005, Rashleigh 2007 |
BASS |
Simulates fish populations exposed to pollutants (mechanistic) |
Models dynamic chemical bioconcentration of organic pollutants and metals in fish. Estimates are being used for ecological risks to fish in addition to realistic dietary exposures to humans and wildlife. |
EPA 2006h |
SERAFM |
Steady-state modeling system used to predict mercury concentration in wildlife |
Predicts total mercury concentrations in fish and speciated mercury concentrations in water and sediments. |
EPA 2007g Knightes 2005 |
PATCH |
Movement of invertebrates in their habitat |
Provides population estimates of territorial terrestrial vertebrate species over time, in addition to survival and fecundity rates, and orientation of breeding sites. Determine ecological effects of regulation. |
EPA 2007h Lawler et al. 2006 |
ECONOMIC IMPACT MODELS
This category includes a broad group of models that are used in many different aspects of EPA’s activities including: rulemaking (regulatory impact assessments), priority setting, enforcement, and retrospective analyses. Models that produce a dollar value as output belong in this category. Models can be divided into cost models, which may include or exclude behavior responses, and benefit models. The former incorporate economic theory on how markets (supply, demand, and pricing) will respond as a result of an action.
Economic models are traditionally deterministic, though there is a trend toward greater use of uncertainty methods in cost-benefit analysis.
Economic Impact Models
Model |
Type |
Use |
Additional Information |
ABEL |
Micro Economic |
Assess a single firm’s ability to pay compliance costs or fees. Estimates claims from defendants that they cannot afford to pay for compliance, clean-up or civil penalties using information from tax return data and cash-flow analysis. Used for settlement negotiations. |
EPA 1999 |
Nonroad Diesel Economic |
Macro economic for impact |
Multimarket model to analyze how producers and consumers are expected to respond to compliance costs associated with the rule. |
EPA 2005d |
Model |
Type |
Use |
Additional Information |
Impact Model (NDEIM) |
of the nonroad diesel emissions standards rule |
Estimates and stratifies emissions for nonroad equipment. Model can be used to inform State Implementation Plans and regulatory analyses. |
|
BenMAP |
Noneconomic and economic benefits from air quality |
Model that estimates the health benefits associated with air quality changes by estimating changes in incidences of a wide range of health outcomes and then placing an economic value on these reduced incidences. |
EPA 2007i |
NONECONOMIC IMPACT MODELS
Noneconomic impact models evaluate the effects of contaminants on a variety of noneconomic parameters, such as on crop yields and buildings. Note that other noneconomic impacts, such as impacts on human health or ecosystems, are derived from the human health and ecological effects models discussed previously.
Noneconomic Impact Models
Model |
Type |
Use |
Additional Information |
TDM (Travel Demand Management) |
Model used to evaluate travel demand management strategies |
Evaluates travel demand management strategies to determine vehicle-trip reduction effects. Model used to support transit policies including HOV lanes, carpooling, telecommuting, and pricing and travel subsidies. |
Shiftan and Suhrbier 2002 |
CERES-Wheat |
Crop-growth yield model |
Simulates effects of planting density, weather, water, soil, and nitrogen on crop growth, development, and yield. Predicts management strategies that impact crop yield. |
Ritchie and Godwin 2007 |
PHREEQE-A |
Models effects of acidification on stone |
Simulates the effects of acidic solutions on carbonate stone. |
Parkhurst et al. 1980 |
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