Air Pollution Dispersion Modelling Using Spatial Analyses

Abstract

Air pollution dispersion modelling via spatial analyses (Land Use Regression—LUR) is an alternative approach to the standard air pollution dispersion modelling techniques in air quality assessment. Its advantages are mainly a much simpler mathematical apparatus, quicker and simpler calculations and a possibility to incorporate more factors affecting pollutant’s concentration than standard dispersion models. The goal of the study was to model the PM10 particles dispersion via spatial analyses in the Czech–Polish border area of the Upper Silesian industrial agglomeration and compare the results with the results of the standard Gaussian dispersion model SYMOS’97. The results show that standard Gaussian model with the same data as the LUR model gives better results (determination coefficient 71% for Gaussian model to 48% for LUR model). When factors of the land cover were included in the LUR model, the LUR model results improved significantly (65% determination coefficient) to a level comparable with the Gaussian model. A hybrid approach of combining the Gaussian model with the LUR gives superior quality of results (86% determination coefficient).

The Neural Network Assisted Land Use Regression

“…Observed PM 10 concentrations vs. Gaussian model results.Both linear regression-based LUR models provided a similar performance, the R 2 of the models was 0.639 for the emission factor linear model and 0.652 for the linear model based on the Gaussian model results. The results of these LUR models are similar to those of the other LUR models, which are 0.65 in Bitta et al[31], 0.58 in Liu et al[49] or 0.66-0.76 in Masiol et al[50]. A more detail comparison of these studies and the model of the study is not possible, since each model used a different set of variables, different time scales, etc.…”

“…Factors of land cover and factors representing emission were calculated in a similar manner. Based on the experience from Bitta et al [31], all factors representing land cover and emission were enumerated as weighted averages, where the weights were defined by the estimated probability of the wind direction.…”

Method of Selecting a Decontamination Site Deployment for Chemical Accident Consequences Elimination: Application of Multi-Criterial Analysis

“…The model situation describes a case when there was a chemical substance leakage into the environment in a given space with the dimensions of 40 × 40 km [21]. It is considered to be such a toxic substance that it requires individual protection before the process of decontamination begins.…”

Using a Unmanned Aerial Vehicle to Assess Air Pollution and Identify Dominant Emission Sources

“…Weather conditions, combined with a high industrialization of regions lying along the border of Czech Republic and Poland, influence the formation of long smog episodes with PM10 concentrations in the atmosphere at the value of several hundred micrograms in a cubic meter (Moravian-Silesian Region, 2019). However, it has been observed that the main source of dust pollution in the area of the Polish-Czech border between most populated areas of Ostrava and Katowice (Silesian Province) is the residential heating fired with solid fuels [Bitta et al, 2018], participating at the level of not less than 21% in overall air contamination with dusts. It particularly concerns PM10, which is one of the major air pollutants produced by the combustion of solid fuels, such as biomass and coal [Chafe et al, 2015].…”