Dustfall source-apportionment and source-oriented health risk assessment using unsupervised machine learning, PMF, and HYSPLIT: Insights from a hotspot area in Xinjiang, China.

Excessive heavy metals (HMs) exposure in surface soils may cause non-negligible health risks to human beings; however, the potential health risk assessment of HMs in Yellow River Delta wetland (YRDW) soils has rarely been evaluated. In this study, we sampled surface wetland soils from ten typical functional areas in YRDW, assessed the HMs pollution status, evaluated their potential health risks, stimulated their probabilistic distributions of health risks and analyzed their potential source apportionment using Positive matrix factorization and Monte Carlo simulation. Enrichment factor (EF) and geo-accumulation index (Igeo) indicated significant anthropogenic impacts, particularly in oil-contaminated sites, while Sediment Quality Guidelines (SQGs) comparison results suggested potential ecological risks, especially for As and Ni, which were occasionally above threshold effect levels. The potential health risks based on Monte Carlo simulations revealed no non-carcinogenic health risks to all populations, but highlighted potential carcinogenic risks within the acceptable range (1E-06 to 1E-04), especially for children. Positive Matrix Factorization (PMF) identified primary HMs sources as industrial emissions, agricultural activities and local geochemical background. This study underscores the need for continuous monitoring and remediation to mitigate health and ecological risks in the YRDW soils.

Abstract. Given the increasing complexity of the chemical composition of PM2.5, identifying and quantitatively assessing the contributions of pollution sources has played an important role in formulating policies to control particle pollution. This study provides a comprehensive assessment between PM2.5 chemical characteristics, sources, and health risks based on sampling data conducted over 1 year (March 2018 to February 2019) in Nanjing. Results show that PM2.5 exhibits a distinct variation across different seasons, which is primarily driven by emissions, meteorological conditions, and the chemical conversion of gaseous pollutants. First, the chemical mass reconstruction shows that secondary inorganic aerosols (62.5 %) and carbonaceous aerosols (21.3 %) contributed most to the PM2.5 mass. The increasing oxidation rates of SO2 and NO2 from summer to winter indicate that the secondary transformation of gaseous pollutants is strongly positively correlated with relative humidity. Second, the positive matrix factorization (PMF) method shows that identified PM2.5 sources include secondary inorganic aerosol source (SIS, 42.5 %), coal combustion (CC, 22.4 %), industry source (IS, 17.3 %), vehicle emission (VE, 10.7 %), fugitive dust (FD, 5.8 %), and other sources (1.3 %). The Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model and the concentration-weighted trajectory (CWT) analysis are used to further explore different spatial distributions and regional transport of sources. The concentrations (10–11 µg m−3) of SIS and CC distribute in Nanjing and central China in winter. The concentrations (8–10 µg m−3) of IS and VE are potentially located north of Jiangsu, Anhui, and Jiangxi. Finally, the health risk assessment indicates that the carcinogenic and non-carcinogenic risks of toxic elements (Cr, As, Ni, Mn, V, and Pb) mainly come from IS, VE, and CC, which are within the tolerance or acceptable level. Although the main source of pollution in Nanjing is SIS at present, we should pay more attention to the health burden of vehicle emissions, coal combustion, and industrial processes.

<strong class="journal-contentHeaderColor">Abstract.</strong> Given the increasing complexity of the chemical composition of PM_2.5, identifying and quantitatively assessing the contributions of pollution sources has played an important role in formulating policies to control particle pollution. This study provides a comprehensive assessment between PM_2.5 chemical characteristics, sources, and health risks based on sampling data conducted over one year (March 2018 to February 2019) in Nanjing. Results show that PM_2.5 exhibits a distinct variation across different seasons, which is primarily driven by emissions, meteorological conditions, and chemical conversion of gaseous pollutants. First, the chemical mass reconstruction shows that secondary inorganic aerosols (SIA, 62.5 %) and carbonaceous aerosols (21.3 %) contributed most to the PM_2.5 mass. The increasing oxidation rates of SO2 and NO2 from summer to winter indicate that the secondary transformation of gaseous pollutants is strongly positively correlated with relative humidity. Second, the positive matrix factorization (PMF) method shows that identified PM_2.5 sources include SIA (42.5 %), coal combustion (CC, 22.4 %), industry source (IS, 17.3 %), vehicle emission (VE, 10.7 %), fugitive dust (FD, 5.8 %) and other sources (1.3 %). The Hybrid Single Particle Lagrangian Integrated Trajectory (HYSPLIT) model and the concentration-weighted trajectory (CWT) analysis are used to further explore different spatial distributions and regional transport of sources. High emissions (10-11 &mu;g&middot;m^&minus;3) of SIA and CC distribute in Nanjing and central China in winter. Moderate emissions (8-9 &mu;g&middot;m^&minus;3) of IS and VE are potentially located in the north of Jiangsu, Anhui, and Jiangxi. The PM_2.5 pollution from long-range transport is attenuated by meteorological conditions and ocean air masses. Finally, the health risk assessment indicates that the carcinogenic and non-carcinogenic risks of toxic elements (Cr, As, Ni, Mn, V, and Pb) mainly come from IS, VE, and CC, which are within the tolerance or acceptable level. Although the main source of pollution in Nanjing is SIA at present, we should pay more attention to the health burden of vehicle emissions, coal combustion, and industrial processes.

<strong class="journal-contentHeaderColor">Abstract.</strong> Given the increasing complexity of the chemical composition of PM_2.5, identifying and quantitatively assessing the contributions of pollution sources has played an important role in formulating policies to control particle pollution. This study provides a comprehensive assessment between PM_2.5 chemical characteristics, sources, and health risks based on sampling data conducted over one year (March 2018 to February 2019) in Nanjing. Results show that PM_2.5 exhibits a distinct variation across different seasons, which is primarily driven by emissions, meteorological conditions, and chemical conversion of gaseous pollutants. First, the chemical mass reconstruction shows that secondary inorganic aerosols (SIA, 62.5 %) and carbonaceous aerosols (21.3 %) contributed most to the PM_2.5 mass. The increasing oxidation rates of SO2 and NO2 from summer to winter indicate that the secondary transformation of gaseous pollutants is strongly positively correlated with relative humidity. Second, the positive matrix factorization (PMF) method shows that identified PM_2.5 sources include SIA (42.5 %), coal combustion (CC, 22.4 %), industry source (IS, 17.3 %), vehicle emission (VE, 10.7 %), fugitive dust (FD, 5.8 %) and other sources (1.3 %). The Hybrid Single Particle Lagrangian Integrated Trajectory (HYSPLIT) model and the concentration-weighted trajectory (CWT) analysis are used to further explore different spatial distributions and regional transport of sources. High emissions (10-11 &mu;g&middot;m^&minus;3) of SIA and CC distribute in Nanjing and central China in winter. Moderate emissions (8-9 &mu;g&middot;m^&minus;3) of IS and VE are potentially located in the north of Jiangsu, Anhui, and Jiangxi. The PM_2.5 pollution from long-range transport is attenuated by meteorological conditions and ocean air masses. Finally, the health risk assessment indicates that the carcinogenic and non-carcinogenic risks of toxic elements (Cr, As, Ni, Mn, V, and Pb) mainly come from IS, VE, and CC, which are within the tolerance or acceptable level. Although the main source of pollution in Nanjing is SIA at present, we should pay more attention to the health burden of vehicle emissions, coal combustion, and industrial processes.

Source apportionment and source specific health risk assessment of HMs and PAHs in soils with an integrated framework in a typical cold agricultural region in China

In this study, 130 surface soil samples were collected at an industrial pollution site in Beijing and the contents of As, Be, Cd, Cu, Cr, Hg, Ni, Pb, Sb, Ti, Zn, and 16 PAHs were determined. The positive matrix factorization (PMF) model was used to analyze the sources of heavy metals and PAHs, and the contributions of these sources to carcinogenic risk and hazard index in the study area were calculated. The results showed that the contents of Cd, Cu, Pb, Hg, As, Zn, and Cr in the soil exceeded the background values in different degrees; Cd, Hg, Pb, Zn, and Cu exceeded the background values by>50%. Low molecular weight PAHs (two and three rings) and high molecular weight PAHs (four to six rings) accounted for 39.6% and 60.4% of the total content of 16 PAHs. The PAH content at 77% of the sampling points at the target site was more than 1000 μg ·kg-1, which suggests severe PAH pollution at the site. Heavy metals Be, Ti, As, and Ni mainly originated from natural sources. There are three major sources of 7 heavy metals and 16 PAHs at the site: coal combustion (Hg and ∑16PAHs), smelting (Cu, Cr, Pb, and Zn), and traffic (Sb and Cd). The contribution rates of these sources to the total average contents of seven heavy metals and sixteen PAHs at 130 sampling sites were 8.46% (coal combustion), 90.61% (smelting), and 0.94% (traffic). Human health risk assessment results showed that the carcinogenic risk of seven heavy metals and ∑16PAHs ranged from 4.17×10-6 to 39.38×10-4, and the hazard index ranged from 0 to 32.23. The maximum carcinogenic risk and hazard index values were calculated near the coking plant. Benzo[α]pyrene was the PAH that posed the highest carcinogenic risk and Zn was the heavy metal that had the highest hazard index value. The average carcinogenic risk of coal combustion was 2.16×10-4, accounting for 50.26% of the total average carcinogenic risk. The average hazard index of smelting was 0.834, accounting for 56.43% of the total average non-carcinogenic risk. These two pollution sources are responsible for the high levels of heavy metals and PAHs in the soil of the steel smelting sites that pose the most severe health risks. The results of this study can provide reference for soil remediation and process optimization at other heavily polluted industrial sites.

The heavy metals in the atmospheric particulate matters are now considered a risk for humans and the environment. The purpose of this study was to assess the concentration, source apportionment, and health risk of heavy metals in atmospheric dustfall in Dezful City of Khuzestan Province, Iran. The dustfall samples were collected from five locations every month for one year (2018-2019). The heavy metals ( lead (Pb), cadmium (Cd), chromium (Cr), iron (Fe), and nickel (Ni)) contents of dustfall samples were determined by ICP-OES. The monthly mean of dustfall for five sampling locations was 22.81 ± 21.9 ton.km- 2.month- 1. The mean concentrations of the examined heavy metals were assessed as Fe > Cr > Ni > Pb > Cd. The highest enrichment level belonged to Cd (59.35 ± 128.18) and all heavy metals had enrichment levels beyond 10. The HI (Hazard Index) values were less than one and there was no significant non-carcinogenic risk due to these heavy metals. For children, Ni showed the most HI with a value of 0.205. The calculations demonstrate that the obtained values of cancer risk in both groups are less than the acceptable range (10- 6 to 10- 4). The PMF (Positive Matrix Factorization) results indicated four main sources of pollutants, namely, vehicular exhaust, industrial, road dust, and nonferrous smelting. The results of the study revealed that industrial activities and traffic play crucial roles in increasing the heavy metals contamination of dustfall in Dezful City.

Pollutant source, ecological and human health risks assessment of heavy metals in soils from coal mining areas in Xinjiang, China

Geochemical characteristics and health risks of heavy metals in agricultural soils and crops from a coal mining area in Anhui province, China

Identifying the quantitative source and hazardous areas of heavy metals in soils plays a pivotal role in soil pollution research, and can provide a basis for regional soil risk monitoring and environmental management. For this purpose, a total of 175 samples were collected in topsoils from Linzi, a typical petrochemical industrial city in Shandong Province. Positive matrix factorization (PMF) and factor analysis with non-negative constraints (FA-NNC) receptor models were applied to analyze the sources of the heavy metals. Based on the multivariate statistical simulation methods of min/max autocorrelation factors (MAF) and sequential Gaussian simulation (SGS), the distribution of heavy metal and potential pollution areas were determined. As, Co, Cr, and Mn were mainly affected by natural sources, their concentrations were dominated by the parent materials, and the high-value areas were distributed in the south of the study area. Hg was the most serious pollution element among the 10 heavy metals analyzed in Linzi and originated from atmosphere deposition from industrial emissions and coal combustion, and the highest values were distributed in the northeast of the study area. Cd, Cu, Ni, Pb, and Zn were dominated by natural sources and human activities. The hot-spot areas were mainly concentrated in the middle of the study area. The potentially contaminated areas of Cd and Hg were 580.80 km2 and 666.60 km2, about 85.04% and 97.59% of the total area, and should require more attention. The potential pollution area of most elements was small and scattered across the study area, accounting for less than 1%.

Seasonal variations, gas-PM2.5 partitioning and long-distance input of PM2.5-bound and gas-phase polycyclic aromatic hydrocarbons in Shanghai, China

To explore the pollution sources and health risks of heavy metals in the soil of the southern margin of the Tarim Basin, 1231 soil samples were collected and analyzed for pH and eight heavy metals (Cr, Cd, Pb, Zn, Cu, Ni, As, and Hg). The self-organizing map (SOM) and positive matrix factorization (PMF) models were used to analyze the sources of heavy metals in the soil of the southern Tarim Basin, and a Monte Carlo method-based health risk assessment model was used to quantify the human health risks of different sources of pollution. The results showed that the average contents of all elements did not exceed the local soil background values, except Cd and Hg. The content of As in 0.24% samples was higher than the national risk screening value of China, and the content of the other heavy metals was lower than the Chinese national risk screening value. The main sources of heavy metal pollution were natural–traffic–agricultural mixed sources (60.9%), atmospheric dust fall sources (18.4%), and agricultural sources (20.7%). Soil As, Cr, Pb, Zn, Cu, and Ni were mainly influenced by natural–traffic–agricultural mixed sources. Hg was influenced by atmospheric dust fall (55%) and agricultural sources (45%). Cd was mainly influenced by natural–traffic–agricultural mixed sources (61.6%) and agricultural sources (37.8%). The levels of heavy metals in the soil in Yutian County did not pose a non-carcinogenic risk to humans, but they pose an alert carcinogenic risk to children and adults. Cr is identified as the priority pollutant for human health risk control, while the mixed sources from natural, traffic, and agricultural activities are recognized as the primary targets for pollution control. This study provides a reference for the precise prevention and control of soil heavy metal pollution in the southern margin of the Tarim Basin.

The airport and its surrounding areas are home to a variety of pollution sources, and air pollution is a recognized health concern for local populated regions. Submicron particulate matter (PM1 with an aerodynamic diameter of <1 mm) is a typical pollutant at airports, and the enrichment of heavy metals (HMs) in PM1 poses a great threat to human health. To comprehensively assess the source-specific health effects of PM1-bound HMs in an airport community, PM1 filter samples were collected around the Tianjin Binhai International Airport for 12 h during the daytime and nighttime, both in the spring and summer, and 10 selected HMs (V, Cr, Mn, Co, Ni, Cu, Zn, As, Cd, and Pb) were analyzed. The indicatory elements of aircraft emissions were certified as Zn and Pb, which accounted for more than 60% of the sum concentration of detected HMs. The health risks assessment showed that the total non-cancer risks (TNCRs) of PM1-bound HMs were 0.28 in the spring and 0.23 in the summer, which are lower than the safety level determined by the USEPA, and the total cancer risk (TCR) was 2.37 × 10-5 in the spring and 2.42 × 10-5 in the summer, implying that there were non-negligible cancer risks in the Tianjin Airport Community. After source apportionment with EF values and PMF model, four factors have been determined in both seasons. Consequently, the source-specific health risks were also evaluated by combining the PMF model with the health risk assessment model. For non-cancer risk, industrial sources containing high concentrations of Mn were the top contributors in both spring (50.4%) and summer (44.2%), while coal combustion with high loads of As and Cd posed the highest cancer risk in both seasons. From the perspective of health risk management, targeted management and control strategies should be adopted for industrial emissions and coal combustion in the Tianjin Airport Community.

Enrichment of heavy metals in urban soils has become a major regional environmental risk. At present, research on the soil heavy metals in cities lacks risk spatial correlation analyses between different heavy metals, and there is a relative lack of assessments of the ecological and health risks. We selected Wuxi, a typical developed city of eastern China, collected and tested the contents of heavy metals in the urban soils of Wuxi in May 2020. Combined with Pb isotope analysis, ecological and health risk assessment, we found that the high heavy metal concentrations in Wuxi are mainly located in the central and western regions, and that the changes in spatial fluctuation are relatively small. The Pb isotopes in the urban soils of Wuxi are distributed in areas, such as those are related to coal combustion, automobile exhaust and urban garbage, indicating that the heavy metals in the urban soils of Wuxi are affected by human activities such as coal combustion and automobile exhaust. The average value of the potential ecological risk index of soil heavy metal Cd is 80.3 (the threshold: 40), which represents a high-risk state. Whether adults or children, the risk of soil heavy metals via ingestion is much higher than that through skin exposure. High health risk values are present in the central area of Wuxi and decrease in a ring-shaped pattern, which is similar to the population distribution of Wuxi and greatly increases the potential risk from soil heavy metals, which should be given close attention. We should develop and use clean energy to replace petroleum fossil fuels, especially in densely populated areas. This study provides technical support for the prevention and control of urban heavy metal pollution.

Recently, a new method combining positive matrix factorization (PMF) and heavy metal health risk (HMHR) assessment was proposed to apportion sources of heavy metals in ambient particulate matter and the associated heavy metal cancer health risk (HMCR), which has been applied to data collected in Yangzhou, China. The annual average concentrations of six measured heavy metals were Pb (64.4 ng·m-3), followed by Cr (25.24 ng·m-3), As (6.36 ng·m-3), Ni (5.36 ng·m-3), Cd (3.34 ng·m-3), and Co (1.21 ng·m-3). The results showed that the major sources of PM2.5 were secondary sources (37.7%), followed by coal combustion (19.4%), resuspended dust (17.5%), vehicle emissions (16.9%), construction dust (5.2%), and industrial emissions (3.4%). As was primarily emitted from coal combustion, vehicle emissions, and resuspended dust. Co originated from industry emissions. Pb was mainly emitted from coal combustion. Ni and Cd were from industrial emissions. The major sources that contributed to HMCR were resuspended dust, coal combustion, vehicle emissions, industry emissions, and construction dust. The high contributions of resuspended dust and coal to HMCR were likely due to the high heavy metals concentrations in coal and the resuspended dust profile as well as high emissions of these sources.