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Exploring Input Parameter Effects on Air Pollution Dispersion Models: Uncertainty and Implications for Environmental Assessments in Urban Infrastructures
Koulidis, A.G.; Progiou, A.G.; Sebos, I.; Boudouvis, A.G. Exploring Input Parameter Effects on Air Pollution Dispersion Models: Uncertainty and Implications for Environmental Assessments in Urban Infrastructures. Preprints2024, 2024011230. https://doi.org/10.20944/preprints202401.1230.v1
APA Style
Koulidis, A.G., Progiou, A.G., Sebos, I., & Boudouvis, A.G. (2024). Exploring Input Parameter Effects on Air Pollution Dispersion Models: Uncertainty and Implications for Environmental Assessments in Urban Infrastructures. Preprints. https://doi.org/10.20944/preprints202401.1230.v1
Chicago/Turabian Style
Koulidis, A.G., Ioannis Sebos and Andreas G. Boudouvis. 2024 "Exploring Input Parameter Effects on Air Pollution Dispersion Models: Uncertainty and Implications for Environmental Assessments in Urban Infrastructures" Preprints. https://doi.org/10.20944/preprints202401.1230.v1
Abstract
Air pollution poses a significant risk to public health and ecosystems. The use of sophisticated models to simulate the transformation and dispersion of pollutants in the atmosphere is a recognized method to assess air pollution levels and its sources and inform policy decisions for effective mitigation strategies in urban and industrial environments. The reliability of models depends, in part, on the sensitivity to the variance of input parameters, which can introduce uncertainty into the model's predictions. This uncertainty is especially challenging when the input parameters exhibit inherent variability. In this study, we analyse the uncertainty of an integrated emission/dispersion model by evaluating the relationship between input parameters and model outcomes. We uncover new aspects of this relationship while clarifying some previously known dependencies. Wind speed was found to have the most significant effect on calculated concentrations, with small differences leading to substantial concentration variations. The time of day, which reflects prevailing vertical turbulence conditions, was also found to have a notable impact on concentrations, whereas ambient temperature can also significantly influence model’s results. Based on these findings, we offer specific recommendations for regulators and scientists involved in environmental impact assessment to improve the accuracy and reliability of air pollution modelling.
Keywords
Airports; Model tests; Pollution; Sensitivity analysis; Environmental impact assessment
Subject
Environmental and Earth Sciences, Environmental Science
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
