Article ; Online: Location Optimisation in the Process of Designing Infrastructure of Point Pollutant Emitters to Meet Specific Environmental Protection Standards
Applied Sciences, Vol 12, Iss 3031, p
2022 Volume 3031
Abstract: This article addresses the challenge of searching for the optimal location for a newly designed pollutant emitter (new factory or other facility) in relation to the requirements imposed by environmental protection regulations on the concentrations of ... ...
| Abstract | This article addresses the challenge of searching for the optimal location for a newly designed pollutant emitter (new factory or other facility) in relation to the requirements imposed by environmental protection regulations on the concentrations of selected pollutants in a given area, taking into account the currently existing levels of analysed substances. The paper presents the key issues of the dispersion of pollutants in atmospheric air and pollutant dispersion models. The Gaussian model of a plume, based on the Pasquill diffusion equation, is chosen to simulate the dispersion of pollutants in atmospheric air. The key issue within the paper constitutes the research section responsible for using the Monte Carlo global optimisation method in order to find the optimal location. The proposed algorithm is intended to offer measurable and subjective arguments and options to preliminary discussions on choosing a location for new factories, while such discussions choices should be fact-based and ecologically acceptable instead of fulfilling only political or economical goals. The paper is intended to present the need for easily interpretable arguments for discussions and responsible decisions on choosing the lowest-impact location of pollutant emitters to the scientific community. |
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| Keywords | pasquill ; monte carlo ; emitter ; environmental protection ; Technology ; T ; Engineering (General). Civil engineering (General) ; TA1-2040 ; Biology (General) ; QH301-705.5 ; Physics ; QC1-999 ; Chemistry ; QD1-999 |
| Subject code | 333 |
| Language | English |
| Publishing date | 2022-03-01T00:00:00Z |
| Publisher | MDPI AG |
| Document type | Article ; Online |
| Database | BASE - Bielefeld Academic Search Engine (life sciences selection) |
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