Assessment of Elemental Components in Atmospheric Particulate Matter from a Typical Mining City, Central China: Size Distribution, Source Characterization and Health Risk

Microscopic characteristics and sources of atmospheric dustfall in open-pit mining coal resource-based city in the arid desert area of Northwest China

Atmospheric dustfall is solid air pollutant, has a major impact on the environment and human health. The objective of this study was to investigate the microscopic characteristics and sources of atmospheric dustfall in open-pit mining coal resource-based city in the arid desert area of Northwest China. The characteristics of size and shape factors, variation of shape factors with size distribution, types of individual particles, and sources of atmospheric dustfall, which were collected in the open-pit mining area and surrounding areas, were analyzed by X-ray diffraction (XRD) and scanning electron microscopy coupled with an energy dispersive spectrometer (SEM-EDS) combined with graphical method and shape factors. The results showed that the atmospheric dustfall in all functional areas was dominated by coarse-grained particles. The shape of the atmospheric dustfall deviated from spherical shape, and with decreasing particle size, the difference in shape factors increased in each functional area. The EDS and XRD analyses indicated the presence of 13 types of particles. The sources were mainly local and included soil dust from each functional area; industrial dust, construction dust, biogenic impurities, fossil fuel combustion, wear products of motor vehicle parts, motor vehicle exhaust emissions, and emission and excreta from biological activities in each functional area except the desert area; emissions from a steel plant in the industrial area; coal-associated ore, coal dust, coal gangue emissions, and emissions from the spontaneous combustion of coal gangue in the open-pit mining area; secondary chemical crystallization products in the industrial area and the open-pit mining area; dust generated by vehicles abrading the surface of the off-mine coal road and in the open-pit mining area.

The Predominant Sources of Heavy Metals in Different Types of Fugitive Dust Determined by Principal Component Analysis (PCA) and Positive Matrix Factorization (PMF) Modeling in Southeast Hubei: A Typical Mining and Metallurgy Area in Central China

To develop accurate air pollution control policies, it is necessary to determine the sources of different types of fugitive dust in mining and metallurgy areas. A method integrating principal component analysis and a positive matrix factorization model was used to identify the potential sources of heavy metals (HMs) in five different types of fugitive dust. The results showed accumulation of Mn, Fe, and Cu can be caused by natural geological processes, which contributed 38.55% of HMs. The Ni and Co can be released from multiple transport pathways and accumulated through local deposition, which contributed 29.27%. Mining-related activities contributed 20.11% of the HMs and showed a relatively high accumulation of As, Sn, Zn, and Cr, while traffic-related emissions contributed the rest of the HMs and were responsible for the enrichment in Pb and Cd. The co-applied source-identification models improved the precision of the identification of sources, which revealed that the local geological background and mining-related activities were mainly responsible for the accumulation of HMs in the area. The findings can help the government develop targeted control strategies for HM dispersion efficiency.

Analysis of the influencing factors of atmospheric particulate matter accumulation on coniferous species: measurement methods, pollution level, and leaf traits

Urban trees, especially their leaves, have the potential to capture atmospheric particulate matter (PM) and improve air quality. However, the amount of PM deposited on leaf surfaces detected by different methods varies greatly, and quantitative understanding of the relationship between PM retention capacity and various microstructures of leaf surfaces is still limited. In this study, three measurement methods, including the leaf washing (LW) method, aerosol regeneration (AR) method, and scanning electron microscopy and energy-dispersive X-ray spectroscopy (SEM-EDX) method, were used to determine the PM retention capacity of leaf surfaces of three coniferous species. Additionally, we analyzed the leaf traits and elemental composition of PM on leaves collected from different sites. The results showed that Pinus tabulaeformis and Abies holophylla were more efficient species in capturing PM than Juniperus chinensis, but different measurement methods could affect the detected results of PM accumulation on leaf surfaces. The concentrations of trace elements accumulated on leaf surfaces differed considerably between different sites. The greatest accumulation of elements that occurred on the leaf surface was at the Shenfu Highway site exposed to high PM pollution levels and the smallest accumulation at the Dongling park site. The stomatal density and contact angle were highly correlated with the PM retention capacity of leaf surfaces of the tested species (Pearson coefficient: r = 0.87, p < 0.01 and r =  - 0.70, p < 0.05), while the roughness and groove width were not significantly correlated (Pearson coefficient: r = 0.16 and r =  - 0.03). This study suggests that a methodological standardization for measuring PM is urgently required and this could contribute to selecting greening tree species with high air purification capacity.

Elemental Composition of PM2.5 and PM10 and Health Risks Assessment in the Industrial Districts of Chelyabinsk, South Ural Region, Russia

Air pollution impacts all populations globally, indiscriminately and has site-specific variation and characteristics. Airborne particulate matter (PM) levels were monitored in a typical industrial Russian city, Chelyabinsk in three destinations, one characterized by high traffic volumes and two by industrial zone emissions. The mass concentration and trace metal content of PM2.5 and PM10 were obtained from samples collected during four distinct seasons of 2020. The mean 24-h PM10 ranged between 6 and 64 μg/m3. 24-h PM2.5 levels were reported from 5 to 56 μg/m3. About half of the 24-h PM10 and most of the PM2.5 values in Chelyabinsk were higher than the WHO recommendations. The mean PM2.5/PM10 ratio was measured at 0.85, indicative of anthropogenic input. To evaluate the Al, Fe, As, Cd, Co, Cr, Cu, Mn, Ni, Pb, and Zn concentration in PM2.5 and PM10, inductively coupled plasma mass spectrometry (ICP-MS) was used. Fe (337-732 ng/m3) was the most abundant component in PM2.5 and PM10 samples while Zn (77-206 ng/m3), Mn (10-96 ng/m3), and Pb (11-41 ng/m3) had the highest concentrations among trace elements. Total non-carcinogenic risks for children were found higher than 1, indicating possible health hazards. This study also presents that the carcinogenic risk for As, Cr, Co, Cd, Ni, and Pb were observed higher than the acceptable limit (1 × 10-6).

Foliar surfaces as dust and aerosol pollution monitors: An assessment by a mining site

Recent studies in the southwestern United States have shown that smelting processes and mine tailings emit heavy metal(loid)s that are distributed via wind dispersion to nearby communities. With increased attention regarding the effect of air pollution on environmental health, communities have begun to use citizen/community-based monitoring techniques to measure the concentration of metal(loid)s and evaluate their air quality. This study was conducted in a mining community to assess the efficacy of foliar surfaces as compared to an inverted disc (frisbee) to sample aerosol pollutants in ambient air. The assessment was conducted by evaluating As, Pb, Cd, Cu, Al, Ni, and Zn concentrations versus distance from a former smelter, statistical and regression analyses, and enrichment factor calculations compared to similar sites worldwide. Both the foliar and frisbee collection methods had a decrease in metal(loid)s concentration as a function of distance from the retired smelter. Statistical calculations show that the collection methods had similar mean concentrations for all of the metal(loid)s of interest; however, the tests also indicate that the frisbee collection method generally collected more dust than the foliar method. The enrichment factors from both collection methods were comparable to similar studies by other mining areas referenced, except for aluminum. Since there is evidence of enrichment, correlation between methods, and citizen/community science potential, these efforts show promise for the field. Further studies should consider alternating the types of plant used for foliar collection as well as collecting samples on a more frequent basis in order to sufficiently categorize results based on meteorological conditions.

Environmental Risk Assessment for PM2.5 Pollution from Non-Point Sources in the Mining Area Based on Multi-Source Superposition and Diffusion

To identify high-concentration contributing sources and highly dispersive pollution sources of fine particulate matter, analyze the relationship between the location and distribution shape of emission sources and the concentration contribution and dispersion of particulate matter, and realize the atmospheric environment risk simulation and the differential control of non-point sources in the mining area, taking a large mining area in Inner Mongolia as an example, we classified the emission sources of PM2.5 (particulate matter less than 2.5 μm) and complied with the emission inventory. A CALPUFF model was used to simulate the contribution for the PM2.5 concentration of six types of emission sources and a multi-source superposition. Through scenario simulation, we analyzed the relationship between the spatial distribution of emission sources and the emission concentration and diffusion in a large mining area. We analyzed the relative risks of six types of sources under the influence of other superimposed sources and the change of emission concentration during transmission. We established a three-dimensional evaluation model to assess the atmospheric environmental risk of PM2.5 non-point sources in the mining area, considering the change rate of PM2.5 concentration with migration, the relative contribution ratio of superimposed sources, and the equal contribution index of the standard concentration. The results show that the maximum equal contribution index of standard concentration of multi-source superposition was 4.40. Among them, non-paved roads, exposed surface sources of coal piles, and exposed surface sources of mine pits and dumps were the top three pollution contributors, and their maximum equal contribution indexes of standard concentration were 2.40, 2.21, and 2.10, respectively. The effect of superimposed pollution sources was affected by the wind field and the spatial distribution density of emission sources, while the dispersion was affected by the wind direction and the distribution direction of pollution sources. In the case of the same source intensity and emission area, the denser the source distribution was, the higher the emission concentration was, the smaller the contribution ratio of superimposed sources was, and the greater the relative pollution risk was. When the angle between the direction of dispersed linear pollution sources and the dominant wind direction was smaller, the emission concentration was higher, but the diffusion surface was smaller. When the angle with the direction of wind direction was larger, the emission concentration was lower, but the diffusion surface was larger. Concentrated pollution sources had the highest concentration and the diffusion surface was in the middle. Non-paved roads had the highest environmental risk, with an average risk of 5.61 × 10−2, followed by coal piles with an average value of 2.06 × 10−2, followed by pits and dumps with an average value of 1.89 × 10−2; the environmental risk of loading and unloading sources was the lowest. Unpaved roads were pollution sources with high relative pollution risk and diffusion risk, and their average relative pollution risk and diffusion risk were 2.34 × 10−2 and 3.28 × 10−2, respectively. In the case of multi-source superposition, the high-risk areas were mainly heavily polluted areas with intensive emission sources, while the medium-risk areas were moderately polluted areas with scattered pollution sources, and the diffusion risk was high. This research concludes that the dispersed distribution of pollution sources can reduce pollution risk, and the smaller the angle is between the linear distribution direction of pollution sources and the dominant wind direction, the smaller the diffusion risk is. Therefore, differentiated control can be carried out according to the characteristics of pollution sources. The conclusions can provide methods and theoretical support for the control of atmospheric environment risk, pollution prevention, and control planning in mining areas.