Main Title |
Dispersion modeling of sulfur dioxide in the vicinity of two Hawaiian power plants / |
Other Authors |
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Publisher |
Environmental Monitoring and Support Laboratory, Office of Research and Development, U.S. Environmental Protection Agency, |
Year Published |
1978 |
Report Number |
EPA 331-R-78-002 |
OCLC Number |
900612771 |
Subjects |
Sulfur dioxide--Dispersion--Mathematical models ;
Sulfur dioxide--Environmental aspects ;
Sulfur dioxide mitigation--Law and legislation
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Internet Access |
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Holdings |
Library |
Call Number |
Additional Info |
Location |
Last Modified |
Checkout Status |
EJBD |
EPA 331-R-78-002 |
|
Headquarters Library/Washington,DC |
01/27/2015 |
ELBD ARCHIVE |
EPA 331-R-78-002 |
Received from HQ |
AWBERC Library/Cincinnati,OH |
10/04/2023 |
|
Collation |
76 pages : illustrations, charts ; 28 cm |
Notes |
"Project Officer, Jeffrey van Ee, Monitoring Operations Devision Environmental Monitoring and Support Laboratory, Las Vegas, Nevada." Includes bibliographical references (page 75). Prepared under subcontract ... for Northrop Services, Incorporated Contract Number: No. 9460-1100Y EPA Contract Contract Number: No. 68-03-2591 |
Contents Notes |
1. Introduction -- 2. Conclusions and recommendations -- 3. Model input data -- Kahului meteorological data -- Kahului emission data -- Kahe point meteorological data -- Kahe point emission data -- 4. Air quality data -- 5. Model selection and modification -- Kahului modifications -- Verification of model performance at Kahului -- Kahe point modifications -- Verification of model performance at Kahe Point -- 6. Modeling results and evaluation of strategies -- 7. Feasibility of a supplementary control system. Regulations for air quality in the State of Hawaii do not cite emission standards but rely on air quality monitoring data to determine that air quality standards are met. In order to develop an air quality control strategy for sulfur dioxide (SOb2s) that is based on emission limitations, it is desirable to test how effectively alternative strategies will control present sources. A first step in making this assessment is to measure the present air quality around significant sources. The expense of maintaining an array of monitoring sites for a sufficiently long period of time to assure that air quality standards are being met can be significantly reduced by combining monitoring with mathematical modeling. Application of mathematical dispersion modeling was selected as a practical alternative to determine where and at what levels ambient concentrations of sulfur dioxide may be expected. More specifically, two electricity-generating stations were selected to be studied by both a short-term monitoring-data collection period and dispersion modeling. The two stations were Maui Electric Company power plant in Kahului, Maui, and the Hawaiian Electric Company power plant at Kahe Point, Oahu. |