Assessment of air pollution around coal mining area: Emphasizing on spatial distributions, seasonal variations and heavy metals, using cluster and principal component analysis
“…This may be due to presence of coal fire, mining activities and road transportation (heavy vehicles). Similar findings have been reported earlier also 8,40,41 . Figure 5 shows particle mass concentration analysis on the basis of size (0.225-34.0 m) at all locations.…”
supporting
confidence: 81%
“…Health problems are also related to size and composition of trafficrelated PM with toxicological evidence 5 . Huge amounts of PM are generated in and around surface mining areas due to operational use of high-capacity machines [6][7][8] . The increasing use of motor vehicles in urban areas is also a major source of generation of PM emission 9,10 .…”
mentioning
confidence: 99%
“…Problems of air pollution and generation of dust are more critical in the cities like Dhanbad due to narrow width and poor surface quality of roads. Jharia coalfield (JCF) in Dhanbad has been classified as a non-attainment area 24 , because it exceeds NAAQS and air pollution levels in the roadside areas are increasing at an alarming rate 8,25,26 . Gautam et al 20 reported higher variation of PM in terms of size range 10-20 m (inhalable), 4-10 m (thoracic) and <4 m (alveolic) in various places of three Indian opencast mines.…”
“…This may be due to presence of coal fire, mining activities and road transportation (heavy vehicles). Similar findings have been reported earlier also 8,40,41 . Figure 5 shows particle mass concentration analysis on the basis of size (0.225-34.0 m) at all locations.…”
supporting
confidence: 81%
“…Health problems are also related to size and composition of trafficrelated PM with toxicological evidence 5 . Huge amounts of PM are generated in and around surface mining areas due to operational use of high-capacity machines [6][7][8] . The increasing use of motor vehicles in urban areas is also a major source of generation of PM emission 9,10 .…”
mentioning
confidence: 99%
“…Problems of air pollution and generation of dust are more critical in the cities like Dhanbad due to narrow width and poor surface quality of roads. Jharia coalfield (JCF) in Dhanbad has been classified as a non-attainment area 24 , because it exceeds NAAQS and air pollution levels in the roadside areas are increasing at an alarming rate 8,25,26 . Gautam et al 20 reported higher variation of PM in terms of size range 10-20 m (inhalable), 4-10 m (thoracic) and <4 m (alveolic) in various places of three Indian opencast mines.…”
“…Research carried out in Chinese coal fields [13][14][15][16][17] comes to similar conclusions. Coal miners in India are equally aware of these health problems [6][7][8]. Mostly, these papers [18][19][20][21][22][23][24] are well-researched scholarly works from prestigious universities and are published in peer-reviewed journals.…”
Section: Epidemiological Evidence For the Health Hazards In Open-cut mentioning
“…Generation of huge quantity of particulate matter (PM) during mining activities is a subject of immense concern with regard to human health (Pandey et al 2014;Dubey et al 2012). Earlier studies (Aneja et al 2012;Hendryx 2009;Tecer et al 2008;Pless-Mulloli et al 2001) show that PM from different mining operations contributes to significant adverse effect on human health in the form of black lung, asthma, cardiovascular diseases and lung cancer.…”
Springer Science+Business Media Dordrecht Particulate matter (PM) is a major pollutant in and around opencast mine areas. The problem of degradation of air quality due to opencast mine is more severe than those in underground mine. Prediction of dust concentration must be known to implement control strategies and techniques to control air quality degradation in the workplace environment. Limited studies have reported the dispersion profile and travel time of PM between the benches inside the mine. In this paper, PM concentration has been measured and modeled in Malanjkhand Copper Project (MCP), which is one of the deepest opencast copper mines in India. Meteorological parameters (wind speed, temperature, relative humidity) and PM concentration in seven size ranges (i.e., PM0.23–0.3, PM0.3–0.4, PM0.4–0.5, PM0.5–0.65, PM0.65–0.8, PM0.8–1, and PM1–1.6) have been measured for 8 days. The results of the field study provide an understanding of the dispersion of the PM generated due to mining activities. This research work presents an approach to assess the exposure of enhanced level of PM concentration on mine workers and its variation with depth. The correlations study shows that concentration of PM during its travel from source to surface is associated with depth. Empirical equations are developed to represent relationships between concentrations of PM and depth. Artificial neural network (ANN) model showing the relationship between PM concentration and meteorological parameters has been developed. The performance of the ANN model is evaluated in terms of the correlation coefficient between the real and the forecasted data. The results show strong agreement between the experimental data and the modeled output. The findings of this work are important in understanding fine PM variation inside the mine at the workplace and the associated exposure of mine workers
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