Dynamic adaptation of the Gaussian dispersion equation

TY - CONF

T1 - Dynamic adaptation of the Gaussian dispersion equation

AU - Serjak, E. Tamsin

AU - Ruth, Matthias

PY - 1996

Y1 - 1996

N2 - Until recently, there was no need for a facility to estimate pollutant impacts down to time frames less than one hour. Today, concerns of industry and the regulators include short-term impacts from compounds which are toxic or have nuisance causing qualities. To date, the EPA has not approved a short-term impact predicting model which is not based on screening level approaches. While screening level approaches simplify the modeling process, the results may either over or under estimate impacts by several orders of magnitude. The need is clear for a more realistic model capable of estimating short-term impacts. The model must be acceptable to the regulators as well as accessible to industry. The model must work well with currently accessible data while addressing the flaws of the less than dynamic nature of hourly averaged meteorological parameters. These requirements are fulfilled by modifying the existing ISC model to allow the model's dynamic variables to fluctuate during a model run as they do in reality. Running the dynamic ISC model for various time steps under an hour produces more realistic estimates of short-term impacts. By tracking the peak prediction as well as the mean over the hour, a peak to mean ratio can be determined for an hourly averaged set of meteorological parameters. This paper discusses the results of modeling the ISC Gaussian equation with dynamically fluctuating variables. The analysis investigates the results of using a new modeling platform for the ISC model such that the meteorological parameters become dynamic. The Gaussian equation is programmed into STELLA_software which is designed to allow each variable to fluctuate according to predetermined boundaries. The model is used to calculate peak and mean concentrations over averaging times less than an hour.

AB - Until recently, there was no need for a facility to estimate pollutant impacts down to time frames less than one hour. Today, concerns of industry and the regulators include short-term impacts from compounds which are toxic or have nuisance causing qualities. To date, the EPA has not approved a short-term impact predicting model which is not based on screening level approaches. While screening level approaches simplify the modeling process, the results may either over or under estimate impacts by several orders of magnitude. The need is clear for a more realistic model capable of estimating short-term impacts. The model must be acceptable to the regulators as well as accessible to industry. The model must work well with currently accessible data while addressing the flaws of the less than dynamic nature of hourly averaged meteorological parameters. These requirements are fulfilled by modifying the existing ISC model to allow the model's dynamic variables to fluctuate during a model run as they do in reality. Running the dynamic ISC model for various time steps under an hour produces more realistic estimates of short-term impacts. By tracking the peak prediction as well as the mean over the hour, a peak to mean ratio can be determined for an hourly averaged set of meteorological parameters. This paper discusses the results of modeling the ISC Gaussian equation with dynamically fluctuating variables. The analysis investigates the results of using a new modeling platform for the ISC model such that the meteorological parameters become dynamic. The Gaussian equation is programmed into STELLA_software which is designed to allow each variable to fluctuate according to predetermined boundaries. The model is used to calculate peak and mean concentrations over averaging times less than an hour.

UR - http://www.scopus.com/inward/record.url?scp=19244377711&partnerID=8YFLogxK

M3 - Paper

AN - SCOPUS:19244377711

SP - 16

T2 - Proceedings of the 1996 Air & Waste Management Association's 89th Annual Meeting & Exhibition

Y2 - 23 June 1996 through 28 June 1996

ER -