Paper
10 February 1999 Analysis of field data from the Duke Forest and Project OPTEX studies
Frances Lew, Robert J. Paine, Judith O. Zwicker, Howard Feldman
Author Affiliations +
Proceedings Volume 3534, Environmental Monitoring and Remediation Technologies; (1999) https://doi.org/10.1117/12.339043
Event: Photonics East (ISAM, VVDC, IEMB), 1998, Boston, MA, United States
Abstract
The American Petroleum Institute (API) has developed data sets for the evaluation of dispersion modeling and optical remote sensing techniques. An initial field study (in Duke Forest, North Carolina) conducted in early 1995 at an open field site featured several tracer gas releases from simulated point, area, and volume sources with release heights up to 7 meters. A second study took place at an operational petrochemical facility in Texas and featured tracer releases at heights up to 41 meters from points located in an active process unit. Both field studies featured measurements of tracer gas concentrations using bag samplers and Open-Path Fourier Transform Infrared (OP-FTIR) instrumentation. One of the issues of interest to API that are currently being investigated from these field studies is the ability for OP- FTIR technology to be used to determine emission rates from point, area, and volume sources for known source locations. The ISCST3 and AERMOD air quality dispersion models have been employed to estimate the emission rate of a tracer gas by computing a ratio of the measured to the modeled path-averaged concentration. The results of tests using point, volume, and area source depictions of the emissions configurations are reported.
© (1999) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Frances Lew, Robert J. Paine, Judith O. Zwicker, and Howard Feldman "Analysis of field data from the Duke Forest and Project OPTEX studies", Proc. SPIE 3534, Environmental Monitoring and Remediation Technologies, (10 February 1999); https://doi.org/10.1117/12.339043
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Cited by 2 scholarly publications.
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KEYWORDS
Data modeling

Atmospheric modeling

Meteorology

Receptors

FT-IR spectroscopy

Gases

Systems modeling

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