%0 Journal Article %A Asif, Zunaira %A Chen, Zhi %A Han, Yi %D 2018 %T Air quality modeling for effective environmental management in the mining region %U https://tandf.figshare.com/articles/journal_contribution/Air_quality_modeling_for_effective_environmental_management_in_the_mining_region/6154454 %R 10.6084/m9.figshare.6154454.v1 %2 https://tandf.figshare.com/ndownloader/files/11122694 %K mining site %K field case study %K target air pollutants %K TSP %K air quality management %K MADA %K MADM %K PM 10 %K mining air dispersion model %K mining region Air quality %K PM 2.5 %K air quality modeling %K monitoring field values %K air pollutants %K air pollutants concentration %K air quality %K Physical removal effects %K CALPUFF modeling values %X

Air quality in the mining sector is a serious environmental concern and associated with many health issues. Air quality management in mining regions has been facing many challenges due to lack of understanding of atmospheric factors and physical removal mechanisms. A modeling approach called the mining air dispersion model (MADM) is developed to predict air pollutants concentration in the mining region while considering the deposition effect. The model takes into account the planet’s boundary conditions and assumes that the eddy diffusivity depends on the downwind distance. The developed MADM is applied to a mining site in Canada. The model provides values for the predicted concentrations of PM10, PM2.5, TSP, NO2, and six heavy metals (As, Pb, Hg, Cd, Zn, Cr) at various receptor locations. The model shows that neutral stability conditions are dominant for the study site. The maximum mixing height is achieved (1280 m) during the evening in summer, and the minimum mixing height (380 m) is attained during the evening in winter. The dust fall (PM coarse) deposition flux is maximum during February and March with a deposition velocity of 4.67 cm/sec. The results are evaluated with the monitoring field values, revealing a good agreement for the target air pollutants with R-squared ranging from 0.72 to 0.96 for PM2.5, from 0.71 to 0.82 for PM10, and from 0.71 to 0.89 for NO2. The analyses illustrate that the presented algorithm in this model can be used to assess air quality for the mining site in a systematic way. Comparisons of MADM and CALPUFF modeling values are made for four different pollutants (PM2.5, PM10, TSP, and NO2) under three different atmospheric stability classes (stable, neutral, and unstable). Further, MADM results are statistically tested against CALPUFF for the air pollutants and model performance is found satisfactory.

Implications: The mathematical model (MADM) is developed by extending the Gaussian equation particularly when examining the settling process of important pollutants for the industrial region. Physical removal effects of air pollutants with field data have been considerred for the MADM development and for an extensive field case study. The model is well validated in the field of an open pit mine to assess the regional air quality. The MADA model helps to facilitate the management of the mining industry in doing estimation of emission rate around mining activities and predicting the resulted concentration of air pollutants together in one integrated approach.

%I Taylor & Francis