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Risk-Screening Environmental Indicators (RSEI) Model

How RSEI Should Be Used

EPA's Risk-Screening Environmental Indicators (RSEI) is a screening-level model that helps you use  Toxics Release Inventory (TRI ) data. RSEI results allow you to focus on chemicals, industry sectors, and facilities with the greatest potential for chronic human health risk. 

Common uses for RSEI include:

  • Identifying high-scoring facilities and industry sectors for further investigation and pollution prevention opportunities.
  • Examining trends over time for facilities, industry sectors or geographic areas. In some cases, potential for chronic human health risk can increase even though fewer total pounds are released.
  • Helping to prioritize issues for communities relating to toxics management. RSEI can identify chemicals, facilities, and kinds of releases and transfers that may be of most concern and require further investigation.
  • Looking at environmental justice issues. Combining RSEI data with demographic and income data can help communities and policymakers identify areas of potential concern.

Understanding RSEI results provides more details on what the results mean. All RSEI results should be followed up with additional analysis before drawing conclusions or making decisions about the potential risk posed to any particular population.

RSEI uses simplified data for modeling, and this can affect the results. RSEI is designed to represent a worst-case scenario, so in many cases, additional investigation will indicate less potential for concern, such as in the following cases:

  • Actual stack heights are much higher than RSEI assumes, leading to lower potential air concentrations around the facility.
  • The metal compound actually released is less toxic than what RSEI models (facilities do not report which kind of metal compound they release, just the elemental component, such as “lead compounds”).
  • The facility location is actually further away from residential populations than modeled.
  • The water discharge is to a larger stream or river than modeled.

What to do after an analysis using RSEI

Because RSEI uses simplifying assumptions, high RSEI Scores can only indicate the need for further investigation. There are a number of ways to investigate how RSEI assumptions may affect risk-related results. For each facility and release, users are able to review the specific parameters used to generate the estimates. Users may want to research those parameters to determine if they represent the best estimate for a specific facility. Examples of steps one might take include:

  • Verify reported releases (e.g., check EPA's Envirofacts database for corrected TRI reporting forms). Companies occasionally submit corrections to reported releases that may not be reflected in RSEI before the next update.
  • Determine what specific chemical substance is being released when chemicals are reported as categories (metals and metal compounds, diisocyanates, polycyclic aromatic compounds, etc.). For screening-level purposes, RSEI assumes all releases in the category are for the chemical with the greatest chronic toxicity, with some exceptions.
  • Verify other RSEI simplifying assumptions, for example:
    • Parameters related to air releases such as stack heights – If actual stack heights are greater than the modeled stack heights, ambient concentration will be below the RSEI estimated concentration and therefore potential concerns are lessened.
    • Water releases – Is the outfall location correct- on the correct stream or river and on the correct segment?
  • Compare TRI sources of substances of concern with other sources (mobile sources, area sources, non-TRI point sources, indirect exposure to TRI sources) and assess the relative contribution of TRI releases. If the direct exposure to the TRI source is a minimal contributor, further efforts should focus on other sources of those substances. Other sources of environmental information provides links and information to help assess situations of potential concern.
  • Consider more detailed modeling using appropriate air and water dispersion models, or, if resources permit, monitor ambient concentrations (air, water, fish tissue) to see if pollutant levels rise above the level of concern (reference dose or reference concentration, or acceptable cancer risk levels).