Learn About RSEI
Get the basics by watching this short video introduction to RSEI:
On this page:
- What is RSEI?
- How RSEI works
- Using RSEI to explore TRI data
- Some limitations of RSEI
- Types of simplifying assumptions RSEI uses
What is RSEI?
EPA’s Risk-Screening Environmental Indicators (RSEI) is a geographically based model that helps policy makers, researchers and communities explore data on releases of toxic substances from industrial facilities. RSEI can be used to help establish priorities for further investigation and to look at changes in potential chronic human healthchronic human healthThe RSEI model addresses both chronic effects and chronic exposures related to human health. Chronic effects are those that generally persist over a long period of time whether or not they occur immediately after exposure or are delayed. Chronic exposure refers to multiple exposures occurring over an extended period of time, or a significant fraction of an individual's lifetime. impacts over time.
RSEI incorporates information from EPA’s Toxics Release Inventory (TRI), which tracks certain toxic chemical releases and waste management activities at federal facilities and larger industrial facilities across the United States. Find out more about the TRI Program.
By analyzing TRI data on the amount of toxic chemicals released, together with risk factors such as the chemical’s fate and transport through the environment, each chemical’s relative toxicity, and the number of people potentially exposed, RSEI calculates a numeric score designed to be compared to other RSEI Scores.
RSEI is a screening-level model, and uses worst-case assumptions about toxicity and potential exposure where data are lacking, and simplifying assumptions to reduce the complexity of the calculations. A more refined assessment should be conducted before any conclusions about potential health impacts can be determined. RSEI does not produce a risk assessment, nor can RSEI results be used to determine whether a facility is in compliance with federal or state regulations.
How RSEI works
RSEI incorporates 28 years of TRI chemical release data, three U.S. censuses, toxicity and physical properties for more than 400 chemicals, and geographical information for more than 50,000 facilities and thousands of streams and other waterbodies. All of this information is used to model the route of each chemical release through the environment and the potential human exposure that may result.
RSEI first locates each facility geographically using EPA locational data. For water releases, chemical concentrations are calculated in each segment of the stream or river downstream from the facility. RSEI calculates potential human exposures that could result from eating contaminated fish caught in the stream or river, or if a drinking water intake is located downstream of the chemical release, from drinking contaminated water.
For air releases, RSEI calculates concentrations in air up to 49 kilometers from the releasing facility using an EPA dispersion model called AERMOD. RSEI then calculates potential exposure results from residents within the 49-kilometer radius.
RSEI estimates the exposed population using block-level census data for 1990, 2000, and 2010, and estimates the dose, or how much of the chemical a person might take into their body, based on the calculated concentration in air and water. For each chemical with available toxicity data, separate toxicity weights are calculated for oral ingestion and inhalation. RSEI Scores are calculated by multiplying the toxicity weight of the chemical by the estimated dose and the number of exposed people. More information on understanding RSEI results.
RSEI results are provided in a downloadable Microsoft Access-based application called EasyRSEI. Users do not need to have Microsoft Access installed to use the application. Expert users can also download the RSEI Queries database, which provides direct access to the data for more complex data applications, and instructions on accessing the RSEI Geographic Microdata.
RSEI updates all years of reported TRI data once a year, usually in December. You should always use the latest version of RSEI, regardless of what year’s emissions you are analyzing. Check the ways to get RSEI results page for the latest version.
Using RSEI to explore TRI data
RSEI helps users to:
- Look at trends in RSEI Score over time and across sectors, chemicals, facilities and locations;
- Rank and prioritize chemicals, industry sectors, and locations for strategic planning;
- Support community-based projects; and
- Highlight situations with higher relative RSEI Scores that may warrant further investigation to better assess potential chronic human health risks.
Some limitations of RSEI
As with any model, RSEI is subject to the limitations of the underlying data sources and models that it incorporates, in addition to its own limitations:
- RSEI relies exclusively on TRI-reported data (TRI-listed chemicals reported by TRI-regulated facilities) for release estimates; TRI does not include all toxic chemicals or all sources of risk from environmental pollution. (Read about factors to consider when using TRI data.)
- A low RSEI Score indicates low potential concern from reported TRI releases, but other kinds of environmental risk may also be present.
- RSEI does not provide RSEI Scores for all TRI chemicals because information required for modeling, such as toxicity data, is not available for every chemical.
- RSEI does not cover all exposure routes or all chronic health effects.
- RSEI toxicity weights are based only on chronic human toxicity and do not address acute human toxicity or environmental toxicity.
- Dermal and food ingestion pathways (other than fish consumption) and other indirect exposure pathways are not evaluated.
- RSEI does not produce risk estimates such as excess cancer cases. RSEI Scores are unitless and only for comparison to other RSEI Scores.
- RSEI uses a number of simplifying assumptions.
Types of simplifying assumptions RSEI uses
Screening-level calculations, like those in RSEI, frequently require simplifying assumptions. These assumptions are used to fill data gaps or reduce the complexity of the calculations. Some examples of simplifying assumptions used by RSEI include:
- When facility-specific information is available, the median parameter values for all stacks at that facility is used to model all of the facility's air releases.
- When facility-specific information is not available, RSEI uses median stack parameter values by industry sector.
- Data for representative chemical substances are assigned to some chemical categories, e.g., metals and metal compounds.
- Air concentrations are the same both indoors and out.
- People are home all day and are continuously exposed.
- Assumptions are made about fishing behavior and fish consumption, and that a fixed percentage of people with fishing licenses consume caught fish as a major part of their diet.
- Tap water ingestion rates and breathing rates are estimated by sex and age groups.