Characterization, Pollution Sources, and Health Risk of Ionic and Elemental Constituents in PM2.5 of Wuhan, Central China

Pollution levels and health risk assessment of potentially toxic metals of size-segregated particulate matter in rural residential areas of high lung cancer incidence in Fuyuan, China

The highest incidence and mortality rate of lung cancer in rural area of Fuyuan has been a research hotspot, and the pathogenesis is still unclear. Therefore, atmospheric particulate matters (APMs) samples were collected between 18 February and 01 March 2017, exploring water-soluble potentially toxic metals (WSPTMs) and water-soluble inorganic ionic species (WSIIs) levels, size distribution, sources, acidity and alkalinity, and potential carcinogenic and non-carcinogenic risks, hoping to provide scientific basic data to solve this problem. In our study, the average ratio of nitrate ion (NO₃^-)/sulfate ion (SO₄^2-) within PM_1.1, PM_1.1-2.0, PM_2.0-3.3, PM_3.3-7.0, and PM_>7.0 were 0.22, 0.18, 0.15, 0.34 and 0.36, respectively, that revealed that combustion sources contributed to PM were more significant. The anions in equilibrium (ANE) / cations in equilibrium (CAE) < 1 for all samples within PM_1.1, PM_2.0-3.3, PM_3.3-7.0 indicate that the APMs were alkaline, but PM_1.1-2.0 particulate matter shows weak acidity. SO₄^2- prefers to combine with NH₄⁺ to form (NH₄)₂SO₄, which hinders the formation of NH₄NO₃, the remaining SO₄^2- and NO₃^- to neutralize the K⁺, KNO₃ was formed at all particulate, however, K₂SO₄ can only be formed in PM_<3.3. Arsenic (As) and Selenium (Se) were identified as the most enriched WSPTMs in all PM sizes, predominantly from anthropogenic emissions, were suggested that coal combustion is a significant source of PM-bound WSPTMs. Total WSPTMs exhibited high total carcinogenic risks (TCR) values (9.98 × 10^-6, 1.06 × 10^-5, and 1.19 × 10^-5 for girls, boys and adults, respectively) in the smaller particles (< 1.1 μm). Se was considered as the major contributor (63.60%) to carcinogenic risk (CR) in PM_2.0 and had an inverse relationship with PM size that should be of prime concern.

Mass, composition, and sources of particulate matter in residential and traffic sites of an urban environment

Present study aims to assess the mass, composition, and sources of PM₁₀ and PM_2.5 (particulate matter having aerodynamic diameter less than or equal to 10 and 2.5 µm aerodynamic diameter, respectively) in Vellore city. Seasonal samples collected in traffic and residential sites were analyzed for ions, elements, organic carbon (OC), and elemental carbon (EC). Source apportionment of PM₁₀ and PM_2.5 is carried out using Chemical Mass Balance, Unmix, Positive Matrix Factorization and Principal Component Analysis receptor models. Results showed that traffic site had higher annual concentration (PM_2.5 = 62 ± 32 and PM₁₀ = 112 ± 23 µg m^-3) when compared to residential site (PM_2.5 = 54 ± 22 and PM₁₀ = 98 ± 20 µg m^-3). Al, Ca, Fe, K, and Mg known to have crustal origin dominated the element composition irrespective of PM size and sampling site. Among ions, SO₄^2- accounted highest in both sites with an average of 70 and 60% to PM_2.5 and PM₁₀ ionic mass. Elemental carbon contribution to PM mass was found highest in traffic site (PM_2.5 = 17 to 23% and PM₁₀ = 8 to 10%) than residential site (PM_2.5 = 9 to 17% and PM₁₀ = 4 to 8%). Elements, ions, OC, and EC accounted 12, 28, 34, and 16% of PM_2.5 mass and 12, 21, 20, and 8% of PM₁₀ mass, respectively. Different sources identified by the receptor models are resuspended road dust, crustal material, secondary aerosol, traffic, non-exhaust vehicular emissions, secondary nitrate, construction, cooking, and biomass burning. Since Vellore is aspiring to be a smart city, this study can help the policymakers in effectively curbing PM.

Policy-driven variations in oxidation potential and source apportionment of PM2.5 in Wuhan, central China

China has implemented several control measures to mitigate PM_2.5 pollution and improve air quality, such as the Action Plan for the Prevention and Control of Air Pollution (APPCAP). To comprehensively assess the changes in ambient PM_2.5 concentrations and the corresponding health risk with the implementation of APPCAP, this study examined PM_2.5 samples collected in Wuhan in 2012/2013 and 2018 for water-soluble ions, carbonaceous fractions, and elements, respectively. Dithiothreitol (DTT) assay was used to determine the oxidation potential (OP) of PM_2.5. The positive matrix factorization (PMF) model and the multiple linear regression (MLR) model were used to analyze PM_2.5 sources and the contribution of each source to the OP of PM_2.5. The results showed that PM_2.5 concentrations in Wuhan decreased significantly, however, there was little change in the health risk and a significant increase in intrinsic toxicity. DTT_v (the volume-normalized dithiothreitol) showed high correlations (r > 0.5, p < 0.01) with water-soluble organic carbon (WSOC), organic carbon (OC), secondary ions (NO₃^-, SO₄^2-, and NH₄⁺), and elements. Compared to 2012/2013, the contribution of vehicle emissions and secondary aerosol sources to PM_2.5 increased significantly in 2018. Biomass burning sources significantly contribute to DTT_v in the summer and autumn, and secondary aerosol sources significantly contribute to DTT_v in winter. The human health impacts from coal combustion sources remained high, while vehicle emission sources increased. In the context of decreasing PM_2.5 concentrations, the role of vehicle emissions health impacts is increasingly significant due to the large increment in vehicle ownership and high inherent OP. Therefore, targeting vehicle emissions for control is of great importance for human health and needs to be given great attention in future policymaking.

Source Apportionment and Health Risk Assessment of Heavy Metals in PM2.5 in Handan: A Typical Heavily Polluted City in North China

In order to determine the pollution sources and human health risks of metal elements in PM2.5, samples were collected by a large flow particulate matter sampler in the four seasons in 2013, 2015, and 2017 (January, April, July, and October). The mass concentrations of 10 metals (Ti, V, Cr, Mn, Ni, Cu, Zn, As, Cd, and Pb) were analyzed. The sources of heavy metals were identified by Unmix, and the potential non-carcinogenic/carcinogenic risk was evaluated. The influences of local and regional sources were also explored during the high-carcinogenic risk period (HCRP). The wind field and 72 h backward trajectories were performed to identify the potential local and regional sources in HCRP. The results showed that the average annual concentrations of PM2.5 in the urban area of Handan city were 105.14, 91.18, and 65.85 μg/m3 in 2013, 2015, and 2017, respectively. The average daily concentrations of the metals in PM2.5 in January were higher than that of April, July, and October. The average mass concentrations of the 10 heavy metal elements in PM2.5 were 698.26, 486.92, and 456.94 ng·m−3 in 2013, 2015, and 2017, respectively. The main sources of the metals in PM2.5 were soil dust sources, vehicular emissions, coal burning, and industrial activities. The carcinogenic risks of Cr and As were above 1 × 10−6 over the three years. Wind direction analysis showed that the potential local sources were heavy industry enterprises and the economic development zone. The backward trajectory analysis indicated that PM2.5 long transported from Shandong, Henan, and the surrounding cities of Handan had quite an impact on the heavy metals contained in the atmosphere of the studied area. The health risk assessment results demonstrated that the trend for non-carcinogenic risk declined, and there was no non-carcinogenic risk in 2017. However, the carcinogenic risk levels were high over the three years, particularly in January.

Approval Research for Carcinogen Humic-Like Substances (HULIS) Emitted from Residential Coal Combustion in High Lung Cancer Incidence Areas of China

The incidence and mortality rate of lung cancer is the highest in Xuanwei County, Yunnan Province, China. The mechanisms of the high lung incidence remain unclear, necessitating further study. However, the particle size distribution characteristics of HULIS emitted from residential coal combustion (RCC) have not been studied in Xuanwei. In this study, six kinds of residential coal were collected. Size-resolved particles emitted from the coal were sampled by using a burning system, which was simulated according to RCC made in our laboratory. Organic carbon (OC), elemental carbon (EC), water-soluble inorganic ion, water-soluble potentially toxic metals (WSPTMs), water-soluble organic carbon (WSOC), and HULIS-C (referred to as HULIS containing carbon contents) in the different size-segregated particulate matter (PM) samples were determined for health risk assessments by inhalation of PM. In our study, the ratio of HULIS-Cx to WSOCx values in RCC particles were 32.73–63.76% (average 53.85 ± 12.12%) for PM2.0 and 33.91–82.67% (average 57.06 ± 17.32%) for PM2.0~7.0, respectively. The carcinogenic risks of WSPTMs for both children and adults exceeded the acceptable level (1 × 10−6, indicating that we should pay more attention to these WSPTMs). Exploring the HULIS content and particle size distribution of the particulate matter produced by household coal combustion provides a new perspective and evidence for revealing the high incidence of lung cancer in Xuanwei, China.

Toxic metals in outdoor/indoor airborne PM2.5 in port city of Northern, China: Characteristics, sources, and personal exposure risk assessment

Outdoor and indoor PM_2.5 samples were simultaneously collected over four seasons (2017-2018) in Caofeidian, China, and analyzed for 15 elements to investigate the characteristics, sources, and health risks of PM_2.5-bound metals. Source-specific PM_2.5-bound metals were analyzed using positive matrix factorization, combined with the conditional probability function and potential source contribution function model. The health risks were evaluated using the health risk assessment model, which included the exposure parameters of indoor and outdoor activities of Chinese residents. The annual median of PM_2.5 concentrations (89.68 μg/m³) and total metals (2.67 μg/m³) from the outdoor samples significantly surpassed that of the indoor samples (51.56 μg/m³) and total metals (1.51 μg/m³) (P < 0.05). In addition, the indoor/outdoor concentration ratios indicated that most indoor metals mainly originated from outdoor emission sources. In the annual analysis of PM_2.5-bound metal sources, this study identified five metal sources: coal combustion, resuspended dust, traffic emissions, fuel combustion sources, and industrial sources, among which industry sources (36.6%) contributed the most. The non-carcinogenic risks of metals for adults (2.81) and children (2.80) all exceed the acceptable non-carcinogenic risk level (1). The non-carcinogenic risk of Mn (1.46 for children, 1.48 for adults) was a key factor in the total non-carcinogenic risk. The total carcinogenic risk of metals for children (3.75 × 10^-5) was above the acceptable level (1.0 × 10^-6) but within the tolerant limit (1.0 × 10^-4), and that for adults (1.48 × 10^-4) was above the tolerant limit. The lifetime carcinogenic risk of Cr⁶⁺ had the highest proportion of the total carcinogenic risk for children (87.5%) and adults (87.8%). Our results revealed that both adults and children suffered carcinogenic and non-carcinogenic risks from the PM_2.5-bound metals in Caofeidian. The corresponding emission control measures of metals in atmosphere should be considered.

Impact of Municipal, Road Traffic, and Natural Sources on PM10: The Hourly Variability at a Rural Site in Poland

The paper presents data from a monthly campaign studying the elemental composition of PM10, as measured by a specific receptor in Kotórz Mały (Opole Voivodeship)—located in the vicinity of a moderately inhabited rural area—measured in one-hour samples using a Horiba PX-375 analyzer. The hourly variability of SO2, NO, NO2, CO, and O3 concentrations, as well as the variability of meteorological parameters, was also determined. On average, during the entire measurement period, the elements related to PM10 can be arranged in the following order: As < V < Ni < Pb < Cr < Mn < Cu < Ti < Zn < K < Fe < Ca < Al < Si < S. Trace elements, including toxic elements—such as As, V, Ni, Pb, Cr, and Mn—were present in low concentrations, not exceeding 10 ng/m3 (average daily value). These elements had fairly even concentrations, both daily and hourly. The concentrations of the main elements in the PM10, as measured by the receptor, are subject to strong hourly changes related not only to changes in the structures of the sources identified in the statistical analysis, but also to wind speed and direction changes (soil and sand particle pick-up and inflow of pollutants from coal combustion). It has been shown that the transport emissions measured by the receptor can have an intense effect on PM10 in the afternoon.

Study on the Characteristics of Size-Segregated Particulate Water-Soluble Inorganic Ions and Potentially Toxic Metals during Wintertime in a High Population Residential Area in Beijing, China

Airborne particulate matter (PM) pollution often occurs in the wintertime in northern China, posing a potential threat to human health. To date, there are limited studies about the metals and inorganic ions to link source apportionments and health risk assessments in the different size-segregated PM samples. In this study, our samples were collected by a high-volume air sampler from 26 December 2018 to 11 January 2019 in a high population residential area (Beijing). Water-soluble inorganic ions, metal elements in the different size-segregated PM samples were determined for health risk assessments by inhalation of PM. During the sampling period in Beijing, the average concentrations of PM1.1 and PM1.1–2.0 were 39.67 ± 10.66 μg m−3 and 32.25 ± 6.78 μg m−3. Distinct distribution profiles characterized the different elements. The markers of coal combustion Pb, As, and Se had >52% of their mass concentration in PM1.1. The average mass ratios of (NO3− + NO2−)/SO42−, Cl−/Na+, Cl−/K+, and Cl−/(NO3− + NO2−) were 1.68, 6.58, 6.18, and 0.57, which showed that coal combustion and vehicle emissions were the main anthropogenic sources of PM in Beijing in winter. PM1.1 was the major contributor of Pb, Cd, and As for carcinogenic risks (CR) and hazard quotient (HQ). It was indicated that PM1.1 is more harmful than coarse PM. The toxic elements of Cr (VI) (1.12 × 10−6), V (0.69 × 10−6), and As (0.41 × 10−6) caused higher CR for children than Ni, Cd, Co, and Pb. Meanwhile, Pb (35.30 × 10−6) and Ni (21.07 × 10−6) caused higher CR for adults than As, Cr (VI), V, Co, and Cd, especially PM1.1. This study provides detailed composition data and the first report on human health in a high population residential area in Beijing.

Estimate hourly PM2.5 concentrations from Himawari-8 TOA reflectance directly using geo-intelligent long short-term memory network

Fine particulate matter (PM_2.5) has attracted extensive attention because of its baneful influence on human health and the environment. However, the sparse distribution of PM_2.5 measuring stations limits its application to public utility and scientific research, which can be remedied by satellite observations. Therefore, we developed a Geo-intelligent long short-term network (Geoi-LSTM) to estimate hourly ground-level PM_2.5 concentrations in 2017 in Wuhan Urban Agglomeration (WUA). We conducted contrast experiments to verify the effectiveness of our model and explored the optimal modeling strategy. It turned out that Geoi-LSTM with TOA reflectance, meteorological conditions, and NDVI as inputs performs best. The station-based cross-validation R², root mean squared error and mean absolute error are 0.82, 15.44 μg/m³, 10.63 μg/m³, respectively. Based on model results, we revealed spatiotemporal characteristics of PM_2.5 in WUA. Generally speaking, during the day, PM_2.5 concentration remained stable at a relatively high level in the morning and decreased continuously in the afternoon. While during the year, PM_2.5 concentrations were highest in winter, lowest in summer, and in-between in spring and autumn. Combined with meteorological conditions, we further analyzed the whole process of a PM_2.5 pollution event. Finally, we discussed the loss in removing clouds-covered pixels and compared our model with several popular models. Overall, our results can reflect hourly PM_2.5 concentrations seamlessly and accurately with a spatial resolution of 5 km, which benefits PM_2.5 exposure evaluations and policy regulations.