Air Pollution Emissions 2008–2018 from Australian Coal Mining: Implications for Public and Occupational Health

Abstract

Occupational exposure limits for respirable coal dust are based on exposure during working hours, but coal miners may experience additional community-based exposures during nonworking hours. We analyzed Australia National Pollutant Inventory (NPI) data for the years 2008-2018 to estimate air pollutants (metals, nitrogen oxides, particulate matter ≤ 10 micrometers (PM10) and ≤2.5 micrometers (PM2.5)) originating from coal mines. PM10 levels from community-based air monitors in Queensland and New South Wales were also compared between mining and nonmining communities. Results indicated that tons of coal mined increased over the study period, and that levels of particulate matter, metals, and nitrogen oxides increased significantly over time as well. Coal mines accounted for 42.1% of national PM10 air emissions from NPI sites. PM2.5 from coal mines accounted for 19.5% of the national total, metals for 12.1%, and nitrogen oxides for 10.1%. Coal mining occurred in 57 different post codes; the 20 coal-mining post codes with the highest PM10 emissions were home to 160,037 people. Emissions of all studied pollutants were significantly higher from coal mining sites than from other types of NPI sites. Results from community-based air monitoring stations indicated significantly higher population PM10 exposure in coal mining communities than in nonmining communities. The health of the public at large is impacted by coal mining, but to the extent that miners also live near coal mining operations, their total exposure is underestimated by consideration of exposure only during working hours.

3D Spatial Interpolation Methods for Open-Pit Mining Air Quality with Data Acquired by Small UAV Based Monitoring System

“…Meanwhile, CO 2 and PM2.5 distributed entirely in the open-pit area, which not only impacts on the working environment but increases environmental risks in surrounding areas. These findings provide additional evidence explaining regional pollution caused by mining activities in many countries worldwide (Gautam et al, 2018;Hendryx et al, 2020). It also raises the necessity of reducing air pollution in mining sites to prevent health-related issues in both local and regional scales.…”

Meteorological normalisation of PM10 using machine learning reveals distinct increases of nearby source emissions in the Australian mining town of Moranbah

“…Negative correlations were observed for most individual mine sites, with the exception of the Broadlea North Coal Project (R = 0.75), the Isaac Plains Coal Mine (R = 0.16), Coppabella Coal Mine (R = 0.17), Moranbah North (R = 0.28), the South Walker Creek Mine Operations (R = 0.10) and Grosvenor (R = 0.43). It should be noted that the magnitude of mining emissions reported may be a conservative estimate ( Hendryx et al, 2020 ). Although the reported emissions from each mine are only estimates and are only on an annual basis, this might suggest that the mining activity from one individual mine is not responsible for the entirety of increase in the normalised PM 10 observed in the town of Moranbah, or that the reported annual emissions are not accurate.…”

“…The Australian National Pollutant Inventory (NPI) has identified open-cut coal mines as the most significant source of PM emissions, with approximately 25% of industrial emissions arising from coal mining activities ( Richardson et al, 2018 ). Furthermore a recent study, has shown the PM 10 concentrations in Australia are higher in coal mining towns than non-mining urban and rural regions ( Hendryx et al, 2020 ). Previous studies have shown clear links between coal mining and respiratory diseases ( Perret et al, 2017 ; Laney and Weissman, 2014 ).…”

Polydisperse Aerosol Transport and Deposition in Upper Airways of Age-Specific Lung

“…In general, respiratory disorders are preferably treated by transferring drugs to patients through inhalation [ 13 , 14 , 15 ]. To administer a dose and assess the risk from inhaled aerosols, the prediction of particle deposition is important for the treatment of respiratory ailments [ 16 , 17 ]. Particle deposition is usually based on various factors such as age, flow rate, particle size, the physical and chemical properties of particles, and the respiratory tract geometry.…”