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Model Report

Regional Air Impact Modeling Initiative Air Modeling Preprocessor

Last Revision Date: 07/11/2011 View as PDF
General Information Back to Top
Model Abbreviated Name:

RAIMI AMP
Model Extended Name:

Regional Air Impact Modeling Initiative Air Modeling Preprocessor
Model Overview/Abstract:
U.S. Environmental Protection Agency (U.S. EPA) Region 6 developed AMP under the Regional Air Impact Modeling Initiative (RAIMI) to meet the functional need of preparing data and input files for use in the ISCST3 air dispersion model. Other related air modeling processing tools include:

  • ISCBatch - executes multiple ISCST3 air modeling runs in a single batch run.
  • AIR2GIS - consolidates the large plot files generated by each ISCST3 run into a single file for each source to generate the Risk-MAP Node Array Index Table (NAIT).

AMP performs three key functions for air modeling within the RAIMI environment:

  • Implements site parameter quantification (surface roughness, urban/rural land use) for each emission source in accordance with RAIMI methods.
  • Prepares source-specific meteorological files using U.S. EPA Meteorological Processor for Regulatory Models (MPRM).
  • Auto-generates air model input files for multiple sources for all four potential contaminant phases to include source-centered universal grid node array with extracted terrain elevations.

RAIMI Background
The U.S. Environmental Protection Agency (EPA), Region 6, established the Regional Air Impact Modeling Initiative (RAIMI) Program as a risk-based prioritization tool and project platform designed to develop, implement, and track multi-media solutions to environmental problems. RAIMI allows for region-wide prioritization of the potential for health risks, on a community level of resolution, associated with exposure from multiple contaminants from multiple sources and through multiple exposure pathways. The RAIMI platform is a combination of flexible exposure/risk methodologies which depend on the integrated use of a number of components supported by advanced modeling/software tools. Specifically these include the following components and supporting software tools:

  • Emission Characterization - Data Miner
  • Air Dispersion Modeling - Air Modeling Preprocessor (AMP)
  • Risk Modeling - Risk Management and Analysis Platform (Risk-MAP)

Keywords: Air Modeling, RAIMI, ISCST3
Model Technical Contact Information:
Jeffrey Yurk
U.S. EPA, Region 6 (Mail Code: 6PD-O)
(214) 665-8309
yurk.jeffrey@epa.gov
Model Homepage: http://www.epa.gov/earth1r6/6pd/rcra_c/raimi/index.htm
Substantive Changes from Prior Version: Updated as an extension of Arc View 9.2

User Information Back to Top
Technical Requirements
Computer Hardware
Computer Hardware
Minimum:
  • PC - Intel
  • 128 MB RAM
  • 200 MB Disk Space

      Recommended:

      • 256 MB RAM
      • 3+ GB Disk Space
Compatible Operating Systems
Operating Systems
Windows 98, 2000, XP, ME
Other Software Required to Run the Model
Arc View 9.2
Download Information
This model can be downloaded at http://www.epa.gov/earth1r6/6pd/rcra_c/raimi/index.htm
Using the Model
Basic Model Inputs
AMP input files include:
  • MPRM Stage 2 processing inputs
  • Land Use Land Cover (LULC) shapefiles
  • DEM terrain elevation data
  • Surface and upper air met data
Basic Model Outputs
AMP output files include:
  • Source-specific meteorological files
  • ISCST3 input files
User Support
User's Guide Available?
User Guide available at http://www.epa.gov/earth1r6/6pd/rcra_c/raimi/index.htm

User Qualifications
Air Modeling Experience

Model Science Back to Top
Problem Identification
Air modeling for risk assessment must consider the local variability in land use and terrain to address site-specific fate and transport of airborne contaminants. Airflow surrounding a release is modified from the regionally measured meteorological data by local land features. Processing large data files of meteorological, land use and terrain information is time- and computer-intensive, particularly when assessing releases from hundreds or thousands of sources.

Additionally, automation of precise implementation methods ensures consistency among air modeling analyses. AMP implements automated data pre-processing to prepare source-specific meteorological and air model source input files accounting for localized variations in site characteristics.

The RAIMI AMP was developed to automate this process so that it would be practical to air model hundreds to thousands of sources which could be impacting air quality of a single community.

Summary of Model Structure and Methods
The three core capabilities of AMP provide the air modeler with a tool to prepare source-specific meteorological and ISCST3 air model input files to allow for completing the air modeling on numerous sources (greater than 1000) within a regional or county-wide study area. As each source has unique surrounding land use, available land use data analyzed using geographic information system (GIS) tools provides for accurate, repeatable determination of appropriate site parameters that influence the air dispersion and subsequent disposition of emitted contaminants downwind from a release source. These parameters may then be integrated with AMP into the MPRM input files for execution of source-specific meteorological data for a five-year period to satisfy RAIMI requirements. Finally, the location of each source is combined with surrounding terrain data from U.S. Geological Survey (USGS) digital elevation model (DEM) digital files to build a universal grid node array aligned with the USGS longitude/latitude specifications for DEM files to complete the creation of the required ISCST3 air model input files for volatile vapor, particle, particle-bound and mercury vapor phase air modeling.
Model Evaluation
See Validation Report at:
http://www.epa.gov/earth1r6/6pd/rcra_c/raimi/index.htm See Peer Review at:
http://www.epa.gov/earth1r6/6pd/rcra_c/raimi/index.htm

Key Limitations to Model Scope
  • Modeling domain form 10 meters to 10 kilometers from each emission source
  • Unit air parameters from 1-hour to multi-year average
  • Not compatible with AERMOD
Case Studies
See Case Study at: http://www.epa.gov/earth1r6/6pd/rcra_c/raimi/index.htm


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