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Heavy metals (Cr, Co, Ni, As, Cd, and Pb) can be bound to PM adversely affecting human health. Quantifying the source impacts on heavy metals can provide source-specific estimates of the heavy metal health risk (HMHR) to guide effective development of strategies to reduce such risks from exposure to heavy metals in PM 2.5 (particulate matter (PM) with aerodynamic diameter less than or equal to 2.5 μm). In this study, a method combining Multilinear Engine 2 (ME2) and a risk assessment model is developed to more effectively quantify source contributions to HMHR, including heavy metal non-cancer risk (non-HMCR) and cancer risk (HMCR). The combined model (called ME2-HMHR) has two steps: step1, source contributions to heavy metals are estimated by employing the ME2 model; step2, the source contributions in step 1 are introduced into the risk assessment model to calculate the source contributions to HMHR. The approach was applied to Huzou, China and five significant sources were identified. Soil dust is the largest source of non-HMCR. For HMCR, the source contributions of soil dust, coal combustion, cement dust, vehicle, and secondary sources are 1.0 × 10 −4 , 3.7 × 10 −5 , 2.7 × 10 −6 , 1.6 × 10 −6 and 1.9 × 10 −9 , respectively. The soil dust is the largest contributor to HMCR, being driven by the high impact of soil dust on PM 2.5 and the abundance of heavy metals in soil dust. [ABSTRACT FROM AUTHOR]

PM 2.5 -bound heavy metals were measured in a Chinese megacity (Tianjin) in 2013, 2016 and 2019, and analyzed by a new RSDA method (source directional apportionment of risks). Through combining the receptor model, cluster analysis of back trajectories, and risk assessment, the RSDA was developed in this work to quantify source-specific risks from each direction. Concentrations of PM 2.5 and most species (especially for heavy metals) underwent various reductions, and the incremental lifetime cancer risk (ILCR) and non-cancer risk (HQ) declined by more than 80% from 2013 to 2019. Pb was the highest contributor to the reduction of HMs mass concentration (58.6%), while Cr (85.5% for cancer risk) and As (26.0% for non-cancer risk) were more prominent for the reduction of HM risks. The coal combustion and industrial emissions were vital contributors to the reduction of both PM 2.5 mass concentrations (contributed 34.0% and 7.8% to the reduction respectively) and health risks (contributed 36.1% and 25.7% to the cancer risk reduction respectively). Although the percentage mass contribution of traffic emissions increased (7.7% in 2013 and 21.9% in 2019), the associated risks decreased (contributed 26.8% to the cancer risk reduction). Furthermore, the results of RSDA consistently implied that coal combustion, industrial emissions and traffic emissions controls in the northeast/north-northeast, south and southwest of the studied area played important roles in the risk reductions, which mainly due to the risk reduction of air masses from NE/NNE, S and SW, and their strong influence to Tianjin. The RSDA method can quantify the health risks from different sources and directions, and the evaluation of contributors to the reductions of risks in this work would provide a meaningful reference for policy maker to control PM 2.5 emissions and protect population health. • An advanced method, source directional apportionment of health risks was developed. • Decrease of heavy metals risks was mainly due to the decrease of Cr and As. • Coal combustion from the south was main contributor to health risks reduction. [ABSTRACT FROM AUTHOR]

This study aims at exploring size distribution, meteorological influence and uncertainty for source-specific risks of atmospheric particulate matter (PM), which can improve risk-mitigation strategies for health protection. Heavy metals (HMs) and polycyclic aromatic hydrocarbons (PAHs) in PM 2.5 and PM 10 were detected in a Chinese megacity during 2011–2021. A new method named as PMFBMR, which combines the Positive Matrix Factorization, Bootstrapping, Mote Carlo and Risk assessment model, was developed to estimate uncertainty of source-specific risks. It was found that PAH risks concentrated in fine PM, while HMs showed high risks in both fine and coarse PMs. For PM 2.5 , HQ (non-cancer risk hazard quotient) of gasoline combustion (GC), diesel and heavy oil combustion (DC), coal combustion (CC), industrial source (IS), resuspended dust (RD) and secondary and transport PM (ST) were 0.6, 1.4, 0.9, 1.6, 0.3, and 0.3. ILCR (lifetime cancer risk) of sources were IS (9.2E-05) > DC (2.6E-05) = CC (2.6E-05) > RD (2.2E-05) > GC (1.7E-05) > ST (6.4E-06). PM 2.5 from GC, DC, CC and IS caused higher risks than coarse PM, while coarse PM from RD caused higher risks. Source-specific risks were influenced not only by emissions, but also by meteorological condition and dominant toxic components. Risks of GC and DC were usually high during stable weather. Some high risks of CC, IS and RD occurred at strong WS due to transport or wind-blown resuspension. GC and DC risks (influenced by both PAHs and HMs) showed strong relationship with T, while IS and RD risks (dominated by HMs) showed weak link with meteorological conditions. For uncertainty of source-specific risks, HQ and ILCR were sensitive for different variables, because they were dominated by components with different uncertainties. When using source-specific risks for risk-mitigation strategies, the focused toxic components, used toxic values, PM sizes and uncertainty are necessary to be considered. [Display omitted] • PM 2.5 - and PM 10 -bound heavy metals (HMs) and PAHs were detected in 2011–2021. • PAH risks were more sensitive to meteorological variations than HM risks. • A new method was developed to estimate uncertainty of source-specific risks. • Coarse PM from resuspended dust caused higher risk, contrary to other sources. • Meteorological impacts on source-specific risks varied with sources. [ABSTRACT FROM AUTHOR]

The health effects of potentially toxic elements (PTEs) in airborne particulate matter (PM) are strongly dependent on their size distribution and dissolution. This study examined PTEs within nine distinct sizes of PM in a Chinese megacity, with a focus on their deposited and dissolved bioaccessibility in the human pulmonary region. A Multiple Path Particle Dosimetry (MPPD) model was used to estimate the deposited bioaccessibility, and an in-vitro experiment with simulated lung fluid was conducted for dissolved bioaccessibility. During the non-heating season, the dissolved bioaccessible fraction (DBF) of As, Cd, Co, Cr, Mn, Pb and V were greater in fine PM (aerodynamics less than 2.1 μm) than in coarse PM (aerodynamics between 2.1 and 10 μm), and vice versa for Ni. With the increased demand of heating, the DBF of Pb and As decreased in fine particle sizes, probably due to the presence of oxide/silicate compounds from coal combustion. Inhalation health risks based on the bioaccessible concentrations of PTEs displayed the peaks in <0.43 μm and 2.1–3.3 μm particulate sizes. The non-cancer risk was at an acceptable level (95th percentiles of hazard index (HI) was 0.49), but the cancer risk exceeded the threshold value (95th percentiles of total incremental lifetime cancer risk (TCR) was 8.91 × 10−5). Based on the results of uncertainty analysis, except for the exposure frequency, the total concentrations and DBF of As and Cr in <0.43 μm particle size segment have a greater influence on the uncertainty of probabilistic risk. [Display omitted] • Size distribution of inhaled bioaccessibility is considered in risk assessment. • As and Pb related to coal-fired reduce their dissolved fractions in fine particles. • Total concentration of As and Cr in <0.43 μm strongly affect risk uncertainty. • The 95th percentiles of inhaled cancer and non-cancer risk were 8.91 × 10−5 and 0.49. • As in <0.43 μm (non-cancer) and Cr in <0.43 μm (cancer) contributed to high risk. [ABSTRACT FROM AUTHOR]

Ambient PM2.5-bound ions, OC, EC, heavy metals (HMs), 18 polycyclic aromatic hydrocarbons (PAHs), 7 hopanes, and 29 n-alkanes were detected at Tuoji Island (TI), the only marine background atmospheric monitoring station in North China. The annual PM2.5 average concentration was 47 ± 31 μg m−3, and the average concentrations of the compositions in PM2.5 were higher in cold seasons than in warm seasons. The cancer and non-cancer risks of HMs and PAHs in cold seasons were also higher than in warm seasons. BaP, Ni, and As dominated the ∑HQ (hazard quotient) in cold seasons, while the non-carcinogenic risk in warm seasons was mainly dominated by Ni, Mn, and As. The ILCR (incremental lifetime cancer risk) values associated with Cr and As were higher in the cold season, while ILCR-Ni values were higher in the warm season. The backward trajectory was calculated to identify the potential directions of air mass at TI. Through the diagnostic ratios of organic and inorganic tracers, the sources of particulate matter in different directions were judged. It was found that ship emissions and sea salt were the main sources from marine directions, while coal combustion, vehicles emissions, industrial process, and secondary aerosols were the main source categories for inland directions. In addition, potential HM and PAH risks from inland and marine directions were explored. The non-cancerous effects of TI were mainly affected by inland transport, especially from the southeast, northwest, and west-northwest. The cancerous effects of TI were mainly simultaneously affected by the inland direction and marine direction of transport. [ABSTRACT FROM AUTHOR]

The health effects of PM 2.5 associated heavy metals have caused wide public concern. To more accurately assess source-specific health risks of PM 2.5 -bound heavy metals, and to formulate a cost-effective control strategy to health risk reduction, it is necessary to have a better understanding of the temporal variation of source-specific health risks. For this purpose, hourly PM 2.5 and associated heavy metals were measured during four seasons in 2018–2019 in a Chinese megacity. A method integrating positive matrix factorization (PMF) with the health risk assessment model was used to quantify the source-specific health risks. Results showed that the total hazard index (HI) of PM 2.5 -bound heavy metals was 1.35, higher than the safety level, the sum cancer risks (R) of carcinogenic elements (Cr, Co, Ni and As) were 2.8 × 10−5, implying nonnegligible risks. Industrial source 1 (61.3%), which was related with Mn posed the largest non-cancer risk, while coal combustion (36.1%) and industrial source 1 (34.9%) posed most of the cancer risk, and slightly fluctuated with seasons. Health risks of most resolved sources were higher in autumn and winter than in other seasons. In terms of the diurnal variation, they were the lowest in the afternoon. Besides, the health risks of vehicle source had a peak value in rush hours. Different scenarios were simulated to understand the influences of time resolutions and sampling periods on source-specific risk assessment. The results showed the cancer risks of coal combustion and industrial source 1 calculated from the dataset with reduced sampling periods were different from those calculated from the whole dataset. We conclude that source-specific health risks of heavy metals show seasonal and diurnal variations, which suggests that targeted strategies should be adopted on the basis of seasonal and diurnal cycles to protect public health. In addition, a sufficient sampling period is required to generate representative and reliable results for source-specific health risk assessment. [Display omitted] • Temporal variations of source-specific risks of heavy metals in PM 2.5 were estimated. • Mn-related industry source and coal combustion posed most of the cancer risk. • Health risks of most sources were higher in autumn and winter than in other seasons. • Health risks from vehicle source reached their peaks at the morning rush hour. [ABSTRACT FROM AUTHOR]

Heavy metals in size-segregated particulate matter (PM) were investigated in a Chinese megacity, and an advanced model was developed to quantify source-specific risks focusing on size-segregated respiratory exposure. Incremental lifetime cancer risk (ILCR) and non-cancer risk (hazard quotient: HQ) based on deposition concentrations of heavy metals displayed a peak at 4.7–5.8 µm. The percentage contributions to cancer risk were as follows: industrial emission (IE, 34%) > secondary and transport (ST, 29%) > resuspended dust (RD, 21%) > coal combustion (CC, 11%) > traffic emission (TE, 4%) during spring and summer (SS), and CC (31%) > ST (26%) > IE (21%) > RD (11%) ≈ TE (11%) during autumn and winter (AW). RD (41% of HQ during SS, 28% during AW) and IE (45% of HQ during SS, 35% during AW) dominated non-cancer risk. ILCR and HQ of CC were high at sizes 1.1–2.1 µm and 0.43–0.65 µm; those of RD were high at sizes > 3.3 µm; and those of IE were bimodal at fine (<2.1 µm) and coarse (>2.1 µm) sizes, respectively. Cancer risk was more susceptible to small particles than non-cancer risk, partly because higher ILCR was from CC, but higher HQ was attributed by RD. ga1 • Heavy metals in size-segregated particulate matter were measured in an industrial megacity. • A model was developed to quantify source-specific risk of size-segregated particulate matter. • Industrial emission is a key contributor of risks, and its size distribution was bimodal. • Coal combustion contributed higher risks in small PM and during autumn and winter. • Resuspended dust contributed higher risks in coarse PM and during spring and summer. [ABSTRACT FROM AUTHOR]

• Source-specific risks of synchronous PAHs and heavy metals at different PM levels were studied. • Industrial source caused high health risks (81% of HQ and 49% of R) even during 'clean' days. • Relative impacts of industrial source to risks declined by about 25% during haze. • Relative impacts of diesel and gasoline vehicles to R, and crustal dust to HQ increased during haze. Synchronous heavy metals (HMs) and polycyclic aromatic hydrocarbons (PAHs) in inhalable particulate matter (PM 10) were measured during 2009–2012 and 2015–2016 in a Chinese megacity (Chengdu) to understand the variations in source-specific health risks during haze episodes. Samples were divided into four mass concentration levels: PM 10 ≤ 150 μg m−3 (L1), 150 μg m−3 < PM 10 ≤ 250 μg m−3 (L2), 250 μg m−3 < PM 10 ≤ 350 μg m−3 (L3), and PM 10 > 350 μg m−3 (L4). The percentages of some HMs and PAHs (accounting for PM 10) decreased from L1 to L4, indicating that they exhibited lower growth rates than other species during heavy pollution. The combined cancer risk (R) for HMs and PAHs was higher at L1 and L4, and the combined non-cancer risk (HQ) was significantly high at L4. The HMs and PAHs combined source-specific risk apportion (HP-SRA) model was employed to quantify the source-specific risks. The relative contributions of (i) diesel and gasoline vehicles to the R, and (ii) crustal dust to the HQ increased during heavy pollution (L3 and L4). The relative contribution of industrial source declined from 81% (L1) to 60% (L4) for the HQ, and from 49% (L1) to 36% (L4) for the R, implying that the control of industrial emissions during heavy pollution events could alleviate risk growth as a co-benefit of controlling PM mass concentration. However, the risks associated with industrial emissions should also be considered during 'clean' days. [ABSTRACT FROM AUTHOR]

To comparatively analyze source-specific risks of atmospheric particulate matter (PM), PM 10 -bound polycyclic aromatic hydrocarbons (PAHs) and heavy metals (HMs) were synchronously detected in a megacity (Chengdu, China) from 2009 to 2016. Non-cancer risk (assessed by hazard quotient, HQ) of PAHs and HMs was within the acceptable level, while cancer risk (assessed by incremental life cancer risk (ILCR), R) of PAHs and HMs were 1.01 × 10−4 and 9.40 × 10−5 in DP and WP, which showed low risk. HMs dominated cancer (92.12%) and non-cancer (99.99%) risks. An advanced method named as joint source-specific risk assessment of HMs and PAHs (HP-SRA model) was developed to assess comprehensive source-specific risks. Gasoline combustion (contributed 9.6% of PM 10 , 0.3% of HQ and 10.0% of R), diesel combustion (6.2% of PM 10 , 0.2% of HQ and 10.7% of R), coal combustion (17.5% of PM 10 , 1.8% of HQ and 13.4% of R), industrial source (9.1% of PM 10 , 80.7% of HQ and 35.0% of R), crustal dust (28.1% of PM 10 , 9.0% of HQ and 1.6% of R), nitrate (7.5% of PM 10 , 1.1% of HQ and 6.2% of R) and sulphate & secondary organic carbon & adsorption (SSA, 19.6% of PM 10 , 6.9% of HQ and 23.1% of R) were identified as main sources. For cancer risk, industrial sources and SSA posed the highest proportion. Higher levels of Co and Ni generated from industrial sources and Cr (Ⅵ), Cd and Ni absorbed in the SSA can result in high-risk contributions. Thus, controlling HMs levels in industrial emissions is essential to protecting human health. Image 1 • Long-term and synchronous risks assessment of PAHs and heavy metals was conducted. • Heavy metals (HMs) dominated the cancer and non-cancer risks. • Based on PAHs and other species, diesel and gasoline vehicles were distinguished. • Source-specific non-cancer and cancer risks of PAHs and HMs were quantified. [ABSTRACT FROM AUTHOR]

Rapid industrialization and urbanization have resulted in widespread pollution of airborne particulate matter (PM) containing various heavy metals with adverse human-health effects. Health risk assessment of PM calls for accurate evaluation of the bioaccessibility, instead of the total content, of heavy metals in PM. Here, we demonstrated that the leachable fraction of particle-bound As, Pb, Cr, Mn, Cd, Cu, Ni and Zn in lung fluid within the typical retention duration of particles in human lungs varied drastically among particles originated from different air pollution sources, including coal combustion, biomass combustion, fugitive dust, road dust, construction dust, cement and soil. Moreover, bioaccessibility of heavy metals, particularly in biomass combustion, cement and soil particles, was strongly dependent on pollution sources, and the particulate Cu, Ni, Pb and Cd appeared to be the primary indicators of the source dependence of heavy metal bioaccessibility. Using total rather than bioaccessible concentrations of particle-bound heavy metals not only led to overestimation of the health risk of source particles, but more importantly, inaccurate identification of the high-risk pollution sources and the priority metal pollutants in the source particles. When considering bioaccessibility of particle-bound heavy metals examined in this study, coal combustion products exhibited the highest carcinogenic and noncarcinogenic risks among all source particles, whereas cement particles would be the source with highest risk based on total metal content. As and Mn appeared to be the main drivers for the noncarcinogenic risks of source particles, while As, Ni and Cr were the major contributors to the carcinogenic risks of source particles, significantly different from those based on total contents. This research underlines the importance of incorporating bioaccessibility into health risk indexes of frequently occurring particle-bound heavy metals from specific air pollution sources, which will facilitate risk-based assessment of source contribution and hence effective source regulation of airborne PM. Image 1 • Bioaccessibility of heavy metals in particulate matter depends on pollution sources. • Cu, Ni, Pb and Cd determine the source dependence of heavy metal bioaccessibility. • High-risk pollution sources are misidentified using total particulate metal content. • Priority metal pollutants are misidentified if not consider metal bioaccessibility. Capsule: Understanding bioaccessibility of heavy metals in source particles enables accurate identification of high-risk atmospheric pollution sources and priority metal pollutants. [ABSTRACT FROM AUTHOR]

[Display omitted] • Online Mn, Pb, Cu, and Zn concentrations showed good agreement with offline results. • Online and offline health risks of PM 2.5 were generally comparable. • Different analytical methods of As may pose different uncertainty for risk analysis. • Advantages and limitations of two methods on source analysis were gauged. • Online and offline source-specific risks showed insignificant difference. Accurate measurements of PM 2.5 related heavy metals (HMs) and some components are critical to better understanding the sources and health risks of PM 2.5. HMs and other components in PM 2.5 were simultaneously measured using online and offline filter-based methods in a Chinese megacity. Online Mn, Pb, Cu, and Zn concentrations exhibited good correspondence with offline results (R2 ≥ 0.7, relative biases = −3%–22%). Some differences were observed for Cr, As, Co, and V. The assessment of online and offline probabilistic health risks indicated that non-cancer and total cancer risks were higher than the acceptable limits. Different analytical methods of As may result in different uncertainties in risk analysis. The positive matrix factorization model (PMF) was used to perform online and offline source apportionment. Five sources (coal combustion, vehicle source, industrial source, secondary source, and resuspended dust) were identified. Lower online percentage contribution of resuspended dust (8%) might relate to the lack of Si and Al measurements. The different rate contributions of vehicle source were potentially linked to the different time resolutions of the online and offline data. The assessment of online and offline source-specific health risks revealed that industrial source and coal combustion were the most important sources. Online and offline source-specific risks were not significantly different (P > 0.05). This contrastive study not only helps decision makers to manage health risk more effectively, but also provides insights into the applicability of online and offline measurements for quantifying source-specific risks. [ABSTRACT FROM AUTHOR]