Global and local sensitivity analysis of the Emission Dispersion Model input parameters, Samia Chettouh
Samia Chettouh
Laboratory of Research in Industrial Prevention, Institute of Health and Industrial Safety
University of Batna 2, Batna
Algeria
Email: samia.chettouh@yahoo.com
DOI: 10.1108/WJSTSD-12-2020-0102
Purpose: The objectives of this paper are the application of sensitivity analysis (SA) methods in atmospheric dispersion modeling to the emission dispersion model (EDM) to study the prediction of atmospheric dispersion of NO2 generated by an industrial fire, whose results are useful for fire safety applications. The EDM is used to predict the level concentration of nitrogen dioxide (NO2) emitted by an industrial fire in a plant located in an industrial region site in Algeria.
Design/methodology/approach: The SA was defined for the following input parameters: wind speed, NO2 emission rate and viscosity and diffusivity coefficients by simulating the air quality impacts of fire on an industrial area. Two SA methods are used: a local SA by using a one at a time technique and a global SA, for which correlation analysis was conducted on the EDM using the standardized regression coefficient.
Findings: The study demonstrates that, under ordinary weather conditions and for the fields near to the fire, the NO2 initial concentration has the most influence on the predicted NO2 levels than any other model input. Whereas, for the far field, the initial concentration and the wind speed have the most impact on the NO2 concentration estimation.
Originality/value: The study shows that an effective decision-making process should not be only based on the mean values, but it should, in particular, consider the upper bound plume concentration.
Keywords: Sensitivity analysis; Emission dispersion model; Correlation analysis; Standardized regression coefficient; Monte Carlo simulation.
Citation: Chettouh, S. (2021), "Global and local sensitivity analysis of the Emission Dispersion Model input parameters", World Journal of Science, Technology and Sustainable Development, Vol. 18 No. 4, pp. 513-532. https://doi.org/10.1108/WJSTSD-12-2020-0102
