Yang, Hong, Wang, Zhu, Zuo, and Gao: Characteristics and risk assessment of atmospheric PM2.5 heavy metals pollution near coal gangue sites in Huaibei, China
Research
Environmental Engineering Research 2024; 29(5): 230720.
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
Abstract
To study the level of atmospheric PM2.5 and its heavy metal pollution near the coal gangue mountain, this study analyzed the content of seven heavy metals (Zn, Pb, Cu, Cd, Hg, Ni, Cr) and As through the PM2.5 samples from the vicinity of a large-scale coal gangue filed of Tongting coal mine in Huaibei, and evaluated the level of pollution, sources, and health effects. The results showed that during the sampling period, the average concentration of PM2.5 near the coal gangue field was 169.83 μg·m−3, which was 2.26 times that of the national air quality level II daily standard. The coal gangue field may be an important source of air pollution, with the degree of heavy metal and arsenic pollution in the order of Cd, Pb, Zn, Hg (extremely heavy pollution) > As, Cu (medium pollution) > Ni, Cr (light pollution) and coal gangue dust and mining dust contributed more. This study provides data for atmospheric particulate matter and heavy metal and arsenic pollution levels near coal gangue fields and provides a theoretical basis for air pollution prevention and control near coal gangue hills.
Keywords: Coal gangue, Heavy metals, Health risk assessment, PM2.5, Principal component analysis
Graphical Abstract
Keywords: Coal gangue, Heavy metals, Health risk assessment, PM2.5, Principal component analysis
1. Introduction
In recent years, due to growing demands for improved living environments and concerns about air quality, atmospheric particulate matter (PM) has attracted extensive attention from the public [1]. Efficiently regulating the emission of atmospheric pollutants proves to be more efficacious in mitigating the risk of respiratory tract infections in the human population compared to solely implementing socio-economic interventions during smog days [2]. PM2.5, PM10, nitrogen oxides, and hundreds of atmospheric particles contained in haze can not only reduce atmospheric visibility but also pose health risks, potentially leading to fatalities. Specifically, atmospheric PM2.5 contributed to 30.2% of the combined mortality from ischemic heart disease, stroke, chronic obstructive pulmonary disease, and lung cancer in China in 2015 [3,4]. Among them, PM2.5, with its small particle size and a large specific surface area, can easily transport polycyclic aromatic hydrocarbons (PAHs), metal elements, bacteria, viruses, and other harmful substances to the lungs, thereby causing cardiopulmonary dysfunction [5,6]. Metallic elements, including the metalloid element As in this manuscript, constitute important components of PM2.5. They exhibit clear cytotoxicity, persistence, and bioaccumulation potential, which pose significant harm to the human body. For example, nickel (Ni), cadmium (Cd), arsenic (As), and chromium (Cr), some of the compounds that have been listed by the International Agency for Research on Cancer, are carcinogens [7] can cause arteriosclerosis, hypertension, and heart disease [8]. Scholars currently have conducted extensive research on heavy metals in atmospheric particulates, mainly focusing on their pollution characteristics [9] sources [10], and ecological and health risk assessment [11,12]. The research sites have been primarily concentrated in large cities, such as Beijing, Tianjin, and Jinan, and now gradually transitioning to small and medium-sized cities [13–15]; however, fewer studies have been conducted at coal mining cities [16,17]. The numerous coal bases in China are widely distributed, and it is crucial to give sufficient attention to the resulting air pollution problems.
Numerous studies have shown that the main sources of air pollution in China include coal combustion, motor vehicle emissions, soil dust, industrial production, and biomass burning [18], and coal mining cities are no exception [19]. For example, some research reported on the pollution levels, risks, and sources of heavy metals in atmospheric PM2.5 and PM10 in the Fengfeng mining area, Hebei Province, and found that the main sources of heavy metals in particulate matter were vehicle exhaust emissions, coal combustion emissions, industrial activities, and agricultural activities [17]. However, there is still a type of solid waste that covers extensive areas of coal mining areas, such as coal gangue. Coal gangue is a solid waste discharged from coal mining and washing, and its production rate often reaches 10–15% of the total raw coal production [20]. Over the past three decades, the rapid development of the economy and coal industry has led to the massive accumulation of coal gangue. According to statistics, in 2017, there were nearly 1600 large-scale coal gangue mountains in China, with a coal gangue accumulation of 7 billion metric tons. Approximately 150–300 million tons of coal gangue that cannot be fully utilized will be newly generated every year [21]. It is difficult to fundamentally alleviate the situation of a large amount of coal gangue being piled up in the open air in the short-term owing to the low calorific value and low utilization rate of coal gangue [22]. As for the environmental impact of coal gangue stacking in the open air, pollution of local soil and water caused by the release of heavy metals and PAHs from coal gangue due to long-term weathering has been the main concern in the past [23,24]. However, the impact on the atmospheric environment has rarely been reported. Large coal gangue hills usually pile up for a long time, and there are different degrees of weathering on the surface. It is not clear whether the weathered particles that carry heavy metals and other harmful substances enter the atmosphere with the wind, and then are transported to the downwind residential areas or long distances through the airflow area. Although some studies have pointed out that the downwind air quality of coal gangue is favorable, the air quality in the downwind direction is good and slightly above standard limits [25]; however, no direct evidence has been found.
Long-term coal mining, utilization, and transportation exert a significant influence on the air quality in mining areas. Coal mining has produced large quantities of coal gangue for many years. In the past, coal gangue was often naturally and loosely deposited around mines in conical shapes. The coal gangue hills in the Huaibei urban area have essentially disappeared, and the large gangue hills are predominantly found in the Liuqiao, Wugou, and Suntuan Towns. This study considered a large coal gangue hill located in the Tongting coal mine, Wugou Town, Suixi County, Huaibei, Anhui Province as the research object, and analyzed the impact of coal gangue fields on the surrounding air quality and the health of nearby residents through research on the pollution level, pollution characteristics, ecological risks, and health hazards of PM2.5 heavy metals and arsenic in the atmosphere near coal gangue. The findings of our study provide a scientific basis for environmental management near coal gangue hills.
2. Materials and Methods
2.1. Study Area
Huaibei City is located in the north of Anhui Province (115°58′ to 117°12′E, 33°20′ to 34°28′N) at the intersection of the four provinces of Jiangsu, Shandong, Henan, and Anhui, with a coal-bearing area of ~4,100 km2. This is an important energy city in China. Tongting Coal Mine is located in Wugou Town, Suixi County, Huaibei City, Anhui Province. It is affiliated to Huaibei Mining (Group) Co., Ltd. The mine is 8.58 km long from east to west and 2.07 km wide from north to south, with a total area of 17.26 km2. It was completed and put into operation in 1989 and has been exploited for 30 years. The local environment has been seriously damaged by coal mining for many years and a large amount of waste coal gangue has been produced. At present, there are five gangue hills of different sizes in the mining area, among which the largest gangue hill (Fig. S1(a), Fig. S1(b) and Fig. S1(c)) is about 75 m high, 130 m long, and 105 m wide. Except for the newly discharged gangue area in the north, the other three sides of the coal gangue hill have been formed for a long time and exhibit obvious weathering (10–30 years). There are many man-made small particle gangue piles distributed in the coal gangue field, which are weathered to a certain extent and covered with open roofs. There are villages in the southwest of the coal gangue field, and the population density is relatively high. The village roads are made of coal gangue as the roadbed material, and the surface layer of coal gangue is exposed.
2.2. Sample Collection
From November 2019 to January 2020, atmospheric PM2.5 was monitored near the gangue field of the Tongting Coal Mine, and there was no industrial zone nearby. The locations of the sampling sites are shown in Table S1. Four sampling points (A, B, C, D) were set nearby according to the distance from the coal gangue quarry and the wind direction (Fig. 1), among which points A and B were located in the downwind residential area of the coal gangue field (500 m and 1500 m away from the gangue quarry, respectively), while points C and D were located in the upwind direction of the gangue field (500 m and 1500 m away from the gangue field, respectively). The coal gangue quarry was~ 500 m away from the nearest residential area and~ 600 m away from the main traffic roads in the county. The local background air particles were collected for calibration in the control area of Huaibei Xiangshan Park (far from the pollution source area). Atmospheric PM2.5 was collected using a Japanese MLY-60 atmospheric sampler (Fig. S1(d), Fig. S1(e)). The sampling flow was set to 90 L·min−1, the single sample collection time was 23h, and the sampling filter was a 90 mm diameter polytetrafluoroethylene filter (Whatman Company, UK). Atmospheric data such as temperature, humidity, wind speed, and direction were recorded synchronously during the sampling period. Before sampling, the quartz filter membrane should be calcined at a high temperature (450°C) to remove background organic matter. Before and after sampling, the filter membrane should be equilibrated for 48 h in a constant temperature and humidity environment (25°C ± 0.5°C, 50% ± 2%) and then weighed. The samples were stored in a refrigerator at 4°C. A total of 330 effective filter membrane samples were obtained except for those that failed to be sampled due to accidents such as rain and instrument failure.
2.3. Sample Test
One-fourth of the quartz filter membrane was cut into pieces and placed in a microwave digestion tank, digested with HF-HNO3-HClO4 triacid, transferred to a Teflon beaker, and the acid was removed using an electric heating plate. When the acid was about to evaporate to dryness, it was transferred to a centrifuge tube, cooled to volume using 2% HNO3, and then stored in a refrigerator at 4°C. The contents of seven heavy metals (zinc (Zn), plumbum (Pb), Cuprum (Cu), Cd, hydrargyrum (Hg), Ni, and Cr) and metalloid As in the liquid to be tested were determined using ICP-MS (NexIon300X, manufactured by PerkinElmer Instruments (Shanghai) Co., Ltd.). A blank membrane of identical area was taken and similar treatment as the sample was performed, and the blank value of the filter membrane was measured.
2.4. Data Processing
2.4.1. Geoaccumulation index
The geological accumulation index is often used to study the pollution of heavy metals in sediments and soil [26], which has been widely used in recent years to evaluate the environmental risk caused by metal elements in particles [27]. This was calculated by Eq. (1):
(1)
where:
Igeo= the geological accumulation index;
Ci= the content of metal element i in particulate matter, μg·g−1;
Bi = the background value of metal element i in soil, μg·g−1.
Pollution degree classification criteria: Igeo≤0, no pollution; 0<Igeo ≤1, mild pollution; 1<Igeo≤3, moderate pollution; 3<Igeo≤5, heavy pollution; and 5<Igeo, extremely heavy pollution.
2.4.2. Enrichment factor
The enrichment factor method is often used to express the enrichment degree of elements in atmospheric particles and to identify the pollution degree and sources of elements (natural sources and anthropogenic sources) [28,29]. This was calculated using the Eq. (2):
(2)
where:
Ci = the content of heavy metal element i (μg·g−1);
Cn = the content of reference element (μg·g−1);
(Ci/Cn)sample = the ratio of heavy metal i to reference element n in PM2.5;
(Ci/Cn)background = ratio of heavy metal i to reference element n in the background.
In this study, the background value of soil elements in layer A of Huaibei was selected as the background concentration, and Al with a high abundance in the crust and less anthropogenic pollution was selected as the reference element.
2.4.3. Principal components
Principal component analysis (PCA) is a method used for extracting multiple component data and identifying specific pollutant sources through data dimensionality reduction. In this study, SPSS 20.0 was used to perform factor analysis on heavy metal elements and arsenic data in atmospheric PM2.5, and principal component extraction was used. The maximum variance orthogonal rotation (varimax) method was used.
2.4.4. Health risk assessment
Considering that the major exposure pathway for heavy metals and arsenic in residents near the coal gangue mountain may be air pollution, this study only evaluated the health risk of heavy metals and arsenic through air quality. The health risk assessment was performed using the model of the United States Environmental Protection Agency. The evaluation results for heavy metals and arsenic can be divided into carcinogenic and noncarcinogenic risks. In this study, Cd, Ni, As, and Cr were identified as carcinogens, and the carcinogenic risk assessment model was adopted; while Cu, Zn, Pb, and Hg are non-carcinogens, and a non-carcinogenic risk assessment model was adopted. The average daily exposure of each population to Hazardous Materials was calculated by Eq. (3):
(3)
The formulas for calculating the non-carcinogenic and carcinogenic risks of heavy metals and arsenic in atmospheric particulates to humans are as Eq. (4) and Eq. (5):
(4)
(5)
where:
ADD = the average daily exposure of non-carcinogens, mg·(kg·d)−1;
C = the concentration of heavy metal elements in particulate matter, mg·m−3;
IR = respiratory rate, m3·d−1;
ED = continuous exposure time, a;
EF = exposure frequency, d·a−1;
BW = body weight, kg;
AT = average exposure time, d;
RfD = the reference dose, mg·(kg·d)−1;
SF is the carcinogenic factor, (mg·(kg·d)−1)−1.
For noncarcinogens, an HQ >1 indicates non-carcinogenic risk, and an HQ≤1 indicates no harm to the human body. For carcinogens, ILCR, which is the lifetime carcinogenic risk, greater than 1×10−6 indicates a risk of cancer. Refer to the relevant literature for the values of each parameter [30,31] (Table S2 and Table S3).
3. Results and Discussion
3.1. PM2.5 Mass Concentration Near Coal Gangue Farm
During the sampling period, the average mass concentration of atmospheric PM2.5 near the coal gangue field was 73.80–300.13 μg·m−3, and the total average was 169.83 μg·m−3. The average mass concentration of PM2.5 at different sampling points is shown in Fig. S2. The PM2.5 mass concentration range of point A in the downwind residential area (~500 m away from the gangue site) was 110.25–300.13 μg·m−3, with an average value of 208.10 μg·m−3.
The PM2.5 concentration at point B in the downwind residential area (~1500 m away from the gangue farm) was 84.13–237.48 μg·m−3, with an average of 165.16 μg·m−3. The PM2.5 concentration at point C in the upwind direction (500m away from the gangue field) was 98.12–248.74 μg·m−3, with an average value of 178.23 μg·m−3. The concentration of PM2.5 at point D in the upwind direction of coal gangue (~ 1500 m away from the gangue field) was 73.80–200.40 μg·m−3, with an average value of 117.25 μg·m−3. The concentration of PM2.5 at the control point was 31.28–175.24 μg·m−3, with an average of 94.31 μg·m−3. The data shows that the PM2.5 concentration near the coal gangue was in the order of point A > point C > point B > point D, and the concentration in the downwind direction was generally greater than that in the upwind direction, indicating that the wind direction will lead to the migratory distribution of PM2.5 in the gangue dumps, which will have an impact on the environment. During the sampling period, the mean PM2.5 concentration at each point was considerably higher than the secondary standard of China’s ambient air quality standard (GB 3095-2012) (75.00 μg·m−3), higher than the Huaibei urban area (105.50 μg·m−3), Hebei PM2.5 mass concentration in the Fengfeng mining area (106.00 μg·m−3), Baiyin City (44.89 μg·m−3), and Huainan winter (107.80 μg·m−3) [32,33]. Coal gangue is piled in the open air, weathered into fine particles, flown by the wind, thus polluting the air environment, resulting in a significant decline in air quality near the coal gangue farm, and the downwind air quality of coal gangue was significantly worse than that of upwind air.
3.2. Concentration of Heavy Metals and Arsenic PM2.5 Near Coal Gangue Field
3.2.1. Concentration of heavy metals and arsenic in PM2.5 in downwind direction of coal gangue field
The concentrations of PM2.5 heavy metals and arsenic in the atmosphere near the coal gangue farms are listed in Table S4. Fig. 2 showed that the concentration of heavy metals and arsenic at point A was generally higher than that at point B, indicating that the location closer to the coal gangue field, the higher the concentration of heavy metals and arsenic in the ambient air. Point B is located near the village, with no other heavy metal and arsenic pollution sources. Although the concentration of heavy metals and arsenic was lower than that of point A, it was considerably higher than that of the control point, indicating that point B may also be affected by the coal gangue field. The concentration of Pb at point B was slightly higher than that at point A, which may be related to different environmental conditions near the sampling site, such as road traffic, dust, and residential activities.
The secondary limits of As and Cr in PM2.5 stipulated in China’s Ambient Air Quality Standard GB 3095-2012 are 6 and 0.025 ng·m−3, respectively, while the mean concentrations of As and Cr in PM2.5 downwind of coal gangue were 17.58 and 38.86 ng·m−3, respectively, which exceed the standard by 2.93 and 1554.40 times, respectively. The concentrations of Cd, Ni, Pb, Zn, Cu, and Hg did not exceed the standard but were far higher than the control point. Compared with other cities within the country and worldwide, the Ni, Pb, Zn, Cr, Cu, Cd, and As in atmospheric PM2.5 near coal and gangue sites were higher than those in the Huainan mining area [15], Hebei Fengfeng Mining area [17], Nanning [27] and Zhengzhou [30]. Ni, Cu, Zn, Pb, and Cr concentrations were notably lower than those in Shihe City, Changchun underground parking lot, and Lanzhou Electronic Waste Disposal Plant [34–36]; while Zn, Pd, and As were notably higher than those in Beijing and Shanghai [37]. Compared with foreign cities, the concentrations of Ni, Cu, and Pb were lower than those in Tehran and India [38], but significantly higher than those in South Korea [39]. The atmospheric PM2.5 heavy metal and arsenic concentration in the vicinity of the Tongting coal gangue field was at a medium-to-upper level, and its content was significantly higher than that in the control area, indicating air pollution in the vicinity of the coal gangue field.
3.2.2. Concentration of heavy metals and arsenic in PM2.5 in the upwind direction of coal gangue field
The mean concentration of heavy metals and arsenic in the wind direction was consistent with the downwind direction. The average concentration of heavy metal elements and arsenic in the upwind direction of the coal gangue field was consistent with that in the downwind direction. The total average concentration at points C and D was significantly lower than the upwind direction (Fig. 3) and higher than the control area. Compared to the national secondary standard of ambient air quality, As and Cr in the upwind direction exceeded the standard, and the concentrations of other elements were all within the standard limit. The concentrations of heavy metals and arsenic at different sampling points differed significantly. In the upwind direction, the concentration of heavy metals and arsenic tends to decrease farther away from the gangue field, indicating that the concentration at point C was significantly lower than that at point D. Compared with the concentration of heavy metals and arsenic in the downwind direction, the concentration at point C was lower than that at point A, but higher than that at point B, indicating that the closer the location to the coal gangue field, the lower the concentration of heavy metal elements and arsenic in the air; the downwind direction was significantly higher than the upwind direction, indicating that the coal gangue farms can be a significant source of air pollution. The concentration of As at point D in the upwind direction was slightly higher than that at point C, possibly because point D was close to the farmland. Herbicides were important sources of As and speculated that this might be the reason for the higher concentration of As in the upwind than in the downwind direction.
3.3. Assessment of Heavy Metal and Arsenic Pollution in PM2.5
Generally speaking, the enrichment coefficient (EF) of an element can not only reflect the enrichment degree of elements in PM2.5 but also qualitatively evaluate the main sources of elements and their contribution to pollution. Fig. 4 shows the enrichment of each element in PM2.5 in the upwind and downwind directions of the coal gangue field (Table S5). EF values less than 10 indicate that these elements have significant crustal sources, while EF values greater than 10 are attributed to elements of anthropogenic origin. As can be seen from Fig. 4, EF values of Cd, As, Cu, Zn, Pb, and Hg in PM2.5 are higher than 10. This suggests that they are major anthropogenic emissions, such as from industry, coal mining, agricultural activity, and fossil fuel combustion. EF values of Ni and Cr in PM2.5 in the upwind and downwind directions of the coal gangue field are less than 10, which indicates their contents were mainly affected by natural sources. The average EF of Cd, As, Cu, Zn, Pb, Ni, Cr, and Hg in PM2.5 of the downwind directions is higher than that in upwind directions and background area, which indicates these elements are more enriched in PM2.5 from downwind directions compared to that in downwind.
The geological accumulation index method (Igeo) was used to evaluate PM2.5 heavy metal and arsenic pollution at different sampling points near coal gangue farms (Table S6). The results of the geological index method show that the Igeo values of PM2.5 heavy metals and arsenic in the wind and downwind directions were Hg > Cd > Zn > Pb > Cu > As > Cr > Ni, and Ni and Cr were between 1 and 2 overall, indicating mild pollution (Fig. 5). The Igeo of As and Cu was between 2 and 3, indicating moderate pollution; the Igeo of Cd, Pb, Zn, and Hg was greater than 5, indicating extremely heavy pollution. From different sampling points, Igeo of heavy metals and arsenic in downwind direction of coal gangue was slightly higher than that in upwind direction, indicating that the degree of heavy metal and arsenic pollution in downwind direction was higher than that in upwind direction; in the case of excluding other anthropogenic pollution, the weathered fine particles of coal gangue may have a significant relationship with the enrichment of heavy metals and arsenic in atmospheric particulate matter.
3.4. Source Analysis of Heavy Metal Elements and Arsenic
The above research shows that Cd, Hg, Zn, and Pb were significantly enriched, indicating that they were significantly affected by anthropogenic sources. To further determine the source of heavy metals and arsenic, SPSS software was used to conduct a principal component analysis of heavy metal elements and arsenic in the atmospheric PM2.5 near the coal gangue field during the sampling period, and four main components were obtained, which accounted for 82.948% of the total variance (Table S7). The Hg, As, Cr and Ni loadings in Factor 1 were relatively high at 0.852, 0.813, 0.727, and 0.691, respectively. Hg and As are often derived from mining dust or coal combustion, and the enrichment factors for Cr and Ni were less than 10, indicating that they are affected by natural factors. Cr and Ni mostly originate from metallurgy processes. Except for underground coal mining, there were no other large metal smelters near the sampling point. Cr is also commonly detected in road dust [40]. The road dust pollution at the sampling point was serious. The Tongting coal gangue field has long-term coal gangue crushing and transportation operations, and the fine particles naturally weathered on the surface enter the surface under the action of wind and even participate in atmospheric circulation. In this study, the measured mass concentrations of Hg, As, Cr, and Ni in the weathered coal gangue particles in the Tongting coal gangue field were 102 ng·g−1 (n = 11), 35 μg·g−1 (n = 11), 52.91 μg·g−1 (n = 11), and 62 μg·g−1 (n = 11), respectively. Black-brown coal gangue debris could be seen on roads in residential areas and coal gangue fields. Broken coal gangue is often used to build roads or to fill depressions. The dust on the surface of the cement roads was dark in color, mostly black. No road-clearing measures were observed during the sampling period of ~ 60 d. Therefore, Factor 1 mainly reflected the influence of natural soil dust, mining dust, and fine particles weathered from the coal gangue field, with a contribution rate of 49.816%. The contribution rate of Factor 2 was 15.63%, among which, the loads of As, Pb, Cd, and Hg were relatively high. It was determined that this was mainly due to coal combustion. As and Pb are characteristic elements of coal combustion [41], and Cd and Hg are often closely related to coal combustion [42]. Coal-fired heating is often used in northern rural areas during winter. Therefore, it was inferred that Factor 2 was mainly derived from coal burning. In Factor 3, the loads of Zn and Cu were relatively high, with a contribution rate of 11.15%. Among these, Cu and Zn are characteristic elements of automobile tire wear and other components [43]. Based on this, Factor 3 reflects the impact of automobile emissions. The sampling point in this study was close to the main traffic road and there were several rural roads outside the coal gangue quarry, with frequent traffic by vehicles such as large diesel trucks. Factor 4 explains 6.35% of the total variance, the load was high, and the source of Cd was complex, which was not only related to industry and coal burning but also to agricultural planting and fertilization [44]. Therefore, Factor 4 was judged to be the influence of agricultural activities.
Through the analysis of the sources of heavy metal elements and arsenic at the monitoring points, it was found that the main sources in the study area were coal combustion, coal gangue dust, and surface composite pollution dust, which may also be affected by vehicle emissions and agriculture. The monitoring point was located near a large coal gangue field. Some gangue hills had been stacked for at least 20 years. Coal gangue roadbeds could be observed on village roads, with obvious weathering. Under the action of vehicle flow and wind, weathered coal gangue particles are likely to enter the air. Some atmospheric PM2.5, collected from residential areas near the coal gangue field, was characterized, and common particles such as aluminosilicate, sulfur-containing, and fly ash particles were observed (Fig. 6(b), Fig. 6(c)); special particles such as coal dust particles and suspected particles of weathered coal gangue were also observed (Fig. 6(a), Fig. (d)). The energy spectrum of weathered coal gangue particles mainly contained elements such as C, O, Si, Al, and Fe (Fig. 6(d)). Some studies have identified the composition of Huainan and Pingdingshan coal gangue and found its main chemical composition to be Fe2O3, SiO2, and Al2O3, which are characterized by sharp edges and natural fractures [45,46]. Measures such as rebuilding rural roads, use of stones instead of coal gangue as the roadbed, and frequent cleaning of the road should be adopted by the government to deal with heavy metal and arsenic pollution. To reduce the weathered particles emission from coal gangue mountains to the atmosphere, the surface layer should be covered with dust cloth or soil, to plant vegetation.
3.5. Health Risk Assessment of Heavy Metals and Arsenic in PM2.5
The health risk assessment statistics of heavy metals and arsenic in atmospheric PM2.5 near coal gangue quarries to different groups of people are shown in Table S8 and Table S9. Cr, Cd, As, and Ni were evaluated for carcinogenicity (Fig. 7), while Zn, Pb, Cu, and Hg were evaluated for non-carcinogenicity (Fig. 8). During the observation period, in terms of carcinogenic risk, the order of carcinogenic risk of heavy metals and arsenic in PM2.5, near coal gangue farm was Cr > As > Cd > Ni, and the carcinogenic risk of the same metal to the human body was elderly male > elderly female > adult male > adult female > underage male > underage female. From different sampling points, the carcinogenic risk value of each heavy metal and arsenic in the downwind direction of coal gangue was significantly greater than that in the upwind direction. As and Cr pose carcinogenic risks to nearby populations. The average carcinogenic risk of Cr for adult males (2.05×10−4), adult females (1.92×10−4), elderly males (2.80×10−4), and elderly females (2.67×10−4) was one order of magnitude higher than that for underage males (8.84×10−5) and females (8.82×10−5). The average carcinogenic risk of As for different populations was between 10−6 and 10−4, and the carcinogenic risk of As to the human body was significantly lower than that of Cr, which also deserves attention. The risk values of Cd and Ni did not fall within the range of 10−6–10−4, indicating that they are not harmful to the human body. Through a comparison of different populations, it was found that the cancer risk of heavy metals and arsenic to men was greater than that to women, which may be related to the long outdoor activities of men. In addition, the risk of cancer is closely related to age, with age and cancer increasing in parallel.
For non-carcinogenic risks, the HQ values of Zn, Pb, Cu, and Hg in PM2.5 in the study area were all less than one, indicating their low non-carcinogenic risks. The non-carcinogenic risk of different populations was as follows: underage male > underage female > adult male > adult female > elderly female > elderly male (Fig. 8). The non-carcinogenic risk to people in the downwind direction of the coal gangue field was also significantly higher than that in the upwind direction. The non-carcinogenic risk of Pb was higher than that of other metals; as Pb can cause multiple organ lesions in the brain, liver, nerves, and stomach, it warrants more attention [39].
4. Conclusions
In this study, the PM2.5 heavy metals and arsenic pollution status at different sampling points were analyzed using the geoaccumulation index (Igeo) and potential ecological hazard index (RI) methods. The corresponding human health risks were predicted by combining the carcinogenic risk evaluation model (ILCR) with the physical and chemical characterization of potential pollution sources, taking the typical coal gangue hills in Huaibei City as the target. The main conclusions were as follows:
The atmospheric PM2.5 concentration near the coal gangue field was 73.8–300.13 μg·m−3, with a total mean value of 169.83 μg·m−3, which was significantly higher than the national secondary air quality standard. The mass concentration of PM2.5 in the upwind direction of the coal gangue field was significantly higher than that in the downwind direction.
The results of the risk assessment indicate a high health risk in the vicinity of the gangue site. According to the Igeo, the Ni and Cr were slightly polluted, As and Cu were moderately polluted, and Cd, Pb, Zn, and Hg were extremely polluted, all of them on the downwind direction of coal gangue were slightly larger than the upwind direction. The carcinogenic risk near coal gangue quarries to different groups reveals that elderly male > elderly female > adult male > adult female > underage male > underage female. The carcinogenic risk value of heavy metals and arsenic in the downwind direction of coal gangue was higher than that in the upwind direction, and Cr and As had certain carcinogenic risks.
The serious air pollution in the vicinity of the gangue quarry depends less on natural factors than on anthropogenic activity. Factor analysis shows that the contribution rate of composite pollution sources such as coal gangue dust and mining dust accounted for 49.816%. The PM2.5 particle characterization results also found coal dust particles and suspected weathered coal gangue particles.
There are some limitations in this study, a larger range of PM2.5 monitoring around the coal gangue should be carried out to confirm the study of the damage to human health by the interaction of atmospheric pollution. The causal coupling of air pollution is explored in depth to propose more scientific environmental management.
This work was supported by the Natural Science Research Project of Colleges and Universities in Anhui Province (grant number 2022AH050375), the National Natural Science Foundation of China (grant number 41902172), Anhui Natural Science Foundation Project (grant number 2008085QD169).
Notes
Conflict of Interest
The authors have no relevant financial or non-financial interests to disclose.
Author Contribution
K.Y. (PhD student) experimented and wrote the draft. X.P.H. (Associate Professor) directed the research and revised the manuscript. X.W. (Associate Professor) helped in developing the methodology. Y.J.Z (Undergraduate student), P.T.Z (Undergraduate student), and G.G. (Undergraduate student) help complete field sampling. All the co-authors commented on the first drafted manuscript and approved the final manuscript.
References
1. Laura DP, Stephen A, Ashfold MJ, Mohankumar SK, Ahimsa CA, Prasad VK. The link between knowledge, attitudes and practices in relation to atmospheric haze pollution in Peninsular Malaysia. Plos One. 2015;10:1–18.
http://doi:10.1371/journal.pone.0143655
2. Tang S, Yan Q, Shi W, et al. Measuring the impact of air pollution on respiratory infection risk in China. Environ. Pollut. 2018;232:477–486.
https://doi.org/10.1016/j.envpol.2017.09.071
3. Lelieveld J, Evans JS, Fnais M, Giannadaki D, Pozzer A. The contribution of outdoor air pollution sources to premature mortality on a global scale. Nature. 2015;525:367–371.
https://doi.org/10.1038/nature15371
5. Liu B, Li T, Yang J, et al. Source apportionment and a novel approach of estimating regional contributions to ambient PM2.5 in Haikou, China. Environ. Pollut. 2017;223:334–345.
https://doi.org/10.1016/j.envpol.2017.01.030
6. Chen P, Bi X, Zhang J, Wu J, Feng Y. Assessment of heavy metal pollution characteristics and human health risk of exposure to ambient PM2.5 in Tianjin, China. Particuology. 2015;20:104–109.
https://doi.org/10.1016/j.partic.2014.04.020
7. Yang PY, Palida Y. Pollution characteristics and risk assessment of heavy metals in atmospheric particulates in Urumqi City. Res. Environ. Sci. 2019;32(12)2084–2090.
https://doi.org/10.13198/j.issn.1001-6929.2019.06.08
8. Choi JS, Fuentes M, Reich BJ. Spatial-temporal association between fine particulate matter and daily mortality. Comput. Stat. Data. An. 2009;53(8)2989–3000.
https://doi.org/10.1016/j.csda.2008.05.018
9. Zhang J, Hua P, Krebs P. Influences of land use and antecedentdry-weather period on pollution level and ecological risk of heavy metals in road-deposited sediment. Environ. Pollut. 2017;228:158–168.
https://doi.org/10.1016/j.envpol.2017.05.029
10. Tao J, Zhang L, Cao J, et al. Source apportionment of PM2.5 at urban and suburban areas of the Pearl River Delta region, south China-With emphasis on ship emissions. Sci. Total Environ. 2017;574:1559–1570.
https://doi.org/10.1016/j.scitotenv.2016.08.175
11. Agarwal A, Mangal A, Satsangi A, Lakhani A, Kumari KM. Characterization, sources and health risk analysis of PM2.5 bound metals during foggy and non-foggy days in sub-urban atmosphere of Agra. Atmos Res. 2017;197:121–131.
https://doi.org/10.1016/j.atmosres.2017.06.027
12. Kamani H, Mahvi AH, Seyedsalehi M, et al. Contamination and ecological risk assessment of heavy metals in street dust of Tehran, Iran. Int. J. Environ. Sci. Technol. 2017;14(12)2675–2682.
https://doi.org/10.1007/s13762-017-1327-x
13. Yang YY, Liu LY, Guo LL, et al. Seasonal concentrations, contamination levels, and health risk assessment of arsenic and heavy metals in the suspended particulate matter from an urban household environment in a metropolitan city, Beijing, China. Environ. Monit. Assess. 2015;187(7)1–15.
https://doi.org/10.1007/s10661-015-4611-6
14. Xia ZY, Hou LJ, Gao SL, Li HB, Fu HX, Chen YJ. Pollution characteristics, ecological risk and source analysis of metal elements in PM2.5 in Jinan. Ecol. Environ. Sci. 2020;29(5)971–976.
https://doi.org/10.16258/j.cnki.1674-5906.2020.05.013
15. Zhang F, Peng M, Wang H, et al. Ecological risk assessment of heavy metals at township scale in the high background of heavy metals, Southwestern, China. China Environ. Sci. 2020;41(9)4197–4209.
https://doi.org/10.13227/j.hjkx.201912241
16. Wei Z, Li TW, Ming ZC, Zheng Y. The 2013 severe haze over the Southern Hebei, China: PM2.5, composition and source apportionment. Atmos. Pollut. Res. 2014;5(4)759–768.
https://doi.org/10.5094/APR.2014.085
17. Lan JL, Zhu XN, Liu YB, Jin XY, Niu HY, Fan JS. Pollution level and comprehensive risk assessment of heavy metals of PM2.5, PM10 in coal mines area. Ecol. Environ. Sci. 2020;29(8)1592–1601.
https://doi.org/10.16258/j.cnki.1674-5906.2020.08.010
18. Zhang Y, Lang J, Cheng S, et al. Chemical composition and sources of PM1 and PM2.5 in Beijing in autumn. Sci. Total Environ. 2018;630:72–82.
https://doi.org/10.1016/j.scitotenv.2018.02.151
19. He Q, Yan Y, Guo L, Zhang Y, Zhang G, Wang X. Characterization and source analysis of water-soluble inorganic ionic species in PM2.5 in Taiyuan city, China. Atmos. Res. 2017;184:48–55.
https://doi.org/10.1016/j.atmosres.2016.10.008
20. Wu YG, Yu XY, Hu SY, Shao H, Liao Qi, Fan YR. Experimental study of the effects of stacking modes on the spontaneous combustion of coal gangue. Process Saf. Environ. 2019;123:39–47.
https://doi.org/10.1016/j.psep.2018.12.025
21. Xie MZ, Liu FQ, Zhao HL, Ke CY, Xu ZQ. Mineral phase transformation in coal gangue by high temperature calcination and high-efficiency separation of alumina and silica minerals. J. Mater. Res. Technol. 2021;14:2281–2288.
https://doi.org/10.1016/j.jmrt.2021.07.129
22. Liang YC, Liang HD, Zhu SQ. Mercury emission from spontaneously ignited coal gangue hill in Wuda coalfield, Inner Mongolia, China. Fuel. 2016;182:525–530.
https://doi.org/10.1016/j.fuel.2016.05.092
23. Zhou C, Liu G, Xu Z, Sun H, Lam PKS. The retention mechanism, transformation behavior and environmental implication of trace element during co-combustion coal gangue with soybean stalk. Fuel. 2017;189:32–38.
https://doi.org/10.1016/j.fuel.2016.10.093
24. Ouyang ZZ, Gao LM, Yang C. Distribution, sources and influence factors of polycyclic aromatic hydrocarbon at different depths of the soil and sediments of two typical coal mining subsidence areas in Huainan, China. Ecotox. Environ. Safe. 2018;163:255–265.
https://doi.org/10.1016/j.ecoenv.2018.07.024
26. Liu JW, Chao SH, Chen YJ, Cao HB, Zhang AC. Health risk of PM2.5-bound heavy metals for different age population in Beijing, China. China Environ. Sci. 2018;38(4)1540–1549.
https://doi.org/10.19674/j.cnki.issn1000-6923.2018.0187
27. Qin JR, Zhang XY, Huang JL, et al. Pollution characteristics and health risk assessment of heavy metal in atmospheric PM2.5 in Nanning City. Environ. Sci. Technol. 2020;43(7)35–44.
https://doi.org/10.19672/j.cnki.1003-6504.2020.07.006
28. Wu YF, Lu XW. Physicochemical properties and toxic elements in bus stop dusts from Qingyang, NW China. Sci. Rep-UK. 2018;8:12568–12576.
https://doi.org/10.1038/s41598-018-30452-3
29. Wu Y, Zhang N, Wang Y, Ren Y, Yuan Z, Li N. Concentrations of polycyclic aromatic hydrocarbons in street dust from bus stops in Qingyang city: Estimates of lifetime cancer risk and sources of exposure for daily commuters in Northwest China. Environ Pollut. 2020;266:115222–115230.
https://doi.org/10.1016/j.envpol.2020.115222
30. He RD, Zhang YS, Chen YY, et al. Heavy metal pollution characteristics and ecological and health risk assessment of atmospheric PM2.5 in a living area of Zhengzhou city [J]. China Environ. Sci. 2019;40(11)4774–4782.
https://doi.org/10.13227/j.hjkx.201905066
31. Zheng CL, Fan XL, Dong X, Qiu GL, Chen Z. Characteristics, Sources and Health Risk Assessment of Heavy Metals in PM2.5 Collected between Autumn and Winter in Guiyang City. Res. Environ. Sci. 2020;33(06)1376–1383.
https://doi.org/10.13198/j.issn.1001-6929.2020.01.03
32. Yang YP, Chen Q, Wang LN, Yang LL. Winter Pollution Characteristics and Physicochemical Properties of PM2.5 in a Northwest Industrial City. China Environ. Sci. 2020;41(12)5267–5276.
https://doi.org/10.13227/j.hjkx.202002136
33. Cheng Y, Huang W, Shen F, Luo Y, Chen MY, Ren YR. Temporal and Spatial Distribution Characteristics and Influencing Factors Analysis of PM2.5 Pollution in Anhui Province. Anhui Agric. Sci. Bull. 2021;27(2)144–147.
https://doi.org/10.16377/j.cnki.issn1007-7731.2021.02.053
35. Wei XD, Wang YJ, He ZJ. On health risk of heavy metals in PM2.5 of an underground parking lot in Changchun City. J. Saf. Environ. 2020;20(3)1154–1161.
https://doi.org/10.13637/j.issn.1009-6094.2019.0793
36. Cao HM, Zhao LY, Mu X, et al. Pollution Characteristics and Occupational Exposure Risk of Heavy Metals in Indoor and Outdoor Ambient Particles at a Scaled Electronic Waste Dismantling Plant, Northwest China. China Environ. Sci. 2019;40(3)1101–1110.
https://doi.org/10.13227/j.hjkx.201807176
37. Wang J, Hu Z, Chen Y, Chen Z, Xu S. Contamination characteristic sand possible sources of PM10 and PM2.5 in different functional areas of Shanghai, China. Atmos. Environ. 2013;68:221–229.
https://doi.org/10.1016/j.atmosenv.2012.10.070
38. Mohsenibandpi A, Eslami A, Ghaderpoori M, Shahsavani A, Alinejad A. Health risk assessment of heavy metals on PM2.5 in Tehran air, Iran. Data Brief. 2018;17:347–355.
https://doi.org/10.1016/j.dib.2018.01.018
39. Han YJ, Kim HW, Cho SH, Kim PR, Kim WJ. Metallic elements in PM2.5 in different functional areas of Korea: Concentrations and source identification. Atmos. Res. 2015;153:416–428.
https://doi.org/10.1016/j.atmosres.2014.10.002
40. Zhang XD, Yu X, Song QY, Sun LM, Du B, Chen WJ. Characteristics and health risk assessment of heavy metals in PM2.5 and PM10 at the south coast of Xiamen Bay. Environ. Sci. Technol. 2019;42(1)201–210.
https://doi.org/10.19672/j.cnki.1003-6504.2019.01.029
41. Wang MS, Cao JL, Li H, Gui CL, Song DY. Ecological risk assessment and source analysis of heavy metals in dust-fall during heating period in Jiaozuo city. J. Ecol. Environ. 2017;26(5)824–830.
https://doi.org/10.16258/j.cnki.1674-5906.2017.05.013
42. Li S, Li Y, Liang H, Wang ZY, Xue YL. Atmospheric mercury emissions from domestic coal and impacts on local environment of suburban Beijing. Res. Environ. Sci. 2014;27(12)1420–1425.
https://doi.org/10.13198/j.issn.1001-6929.2014.12.05
44. Zhu J, Hou YZ, Zhou SC, Cao MH, Tu SX. Spatio-temporal Distribution Characteristic and Risk Assessment of Heavy Metals in Soils around Wuhan Centralized Drinking Water Source. China. Environ Sci. 2021;42(7)3215–3222.
https://doi.org/10.13227/j.hjkx.202010196
45. Chen YC, Li SQ, Zhou CC. Material Composition Features and Reclaim Evaluation of Coal Gangue in Huainan Mining Area. Coal Geolo. China. 2011;23(11)20–23.
https://doi.org/10.3969/j.issn.1674-1803.2011.11.06
46. Xu HL, Guo H, Jiang SY, et al. Analysis of the characteristics and utilization of coal gangue in the NO.1 coal mine of Pingdingshan mine area. China Min. Magazine. 2012;21(7)49–52.
https://doi.org/10.1038/sj.cr.7290132
Fig. 1
Geographical location and sampling sites of coal gangue hills.
Fig. 2
Concentrations of heavy metals and arsenic in PM2.5 near the coal gangue field (ng·m−3).
Fig. 3
Distribution of heavy metals and arsenic and arsenic in PM2.5 in different sites near the coal gangue field.
Fig. 4
Enrichment factor values of metal elements and arsenic near coal gangue field.
Fig. 5
Pollution level of heavy metals and arsenic in PM2.5 near coal gangue field (I: no pollution; II: mild pollution; III: moderate pollution; IV: heavy pollution; V: extremely heavy pollution).
Fig. 6
SEM image of atmospheric PM2.5 with EDX spectra:(a) Raw coal dust particles, (b) Fly ash particles from coal burning, (c) Silicon aluminate particles; (d) Particles of weathered coal gangue.
Fig. 7
Carcinogenic risk of heavy metals and arsenic to different groups of people (Cd, Ni, As, and Cr).
Fig. 8
Non-carcinogenic risk of heavy metals to different populations (Pb, Zn, Cu, and Hg).