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The key problems with Positive Matrix Factorization (PMF) model for PM2.5 source apportionment were inconsistent results with different species selections and a lack of evaluation criteria for results accuracy. Moreover, high proportions of secondary inorganic aerosols sources (SNA) were identified by PMF without corresponding primary sources. This study develops a new method that combines multi‐isotopes (34S, 15N, 18O and 14C) and PMF model to optimize source apportionment. Data sets A–F, constructed from PM2.5 components, were input into PMF model to obtain optimal results (3–9 factors), which changed with the selection of species. Specifically, the contributions of coal combustion (CC, 3%–36%), biomass burning (BB, 11%–38%), and vehicle sources (VS, 4%–15%) showed significant differences in data sets, indicating that conventional methods cannot obtain accurate results. Then, 15N, 34S, 18O were introduced to restrict and reallocate identified SNA sources to primary sources, overcoming the influence of species on results. Additionally, 14C was used to evaluate data sets results, which showed that the combination of PMF model with more markers (data set F, 9‐factor) and multi‐isotopes techniques obtained optimized results that aligned with 14C results. Compared with the initial results, the contributions of CC, VS, and BB in the allocated 9‐factor increased by 26.4%, 5%, and 19.5%, respectively, becoming main sources of PM2.5. This study represents the first time that combination of PMF model and multi‐isotopes achieves SNA sources reapportionment and results evaluation, improving source apportionment methods. Plain Language Summary: Positive Matrix Factorization has been widely used for PM2.5 source apportionment. However, there are still key issues to be addressed in this method, such as the inconsistent results with different species selections and a lack of evaluation criteria for result accuracy. To solve these problems, we develop a new method using the combination of multi‐isotopes (15N, 34S, 18O, and 14C) and the PMF model to improve the source apportionment method. Initially, data sets A–F, constructed from PM2.5 components, were input into PMF model to obtain the optimal results of 3–9 factors, respectively. It was found that source contributions in different data sets changed with species selection. Subsequently, the incorporation of multi‐isotopes (15N, 34S, 18O) were used to restrict and reallocate secondary inorganic aerosol sources (SNA) to primary sources, eliminating the influence of species on source apportionment. Finally, the results evaluation of data sets by 14C found that data set F (9‐factor) results were reasonable and accurate. The combination of PMF models and multi‐isotopes accomplished result evaluation and method optimization for source apportionment, providing insight into a more accurate understanding of emission sources. Key Points: Different data sets were input into Positive Matrix Factorization (PMF) model, obtaining significant difference results due to changes of species selectionMulti‐isotopes (34S, 15N, 18O and 14C) and PMF model were used to optimize source apportionment and evaluate result accuracy from data setsEvidence from 14C showed that data set F (9‐factor) results were aligned with 14C results [ABSTRACT FROM AUTHOR]

Positive matrix factorisation (PMF) is a receptor model, which is frequently used in environmental geochemistry for metal(loid)s' source apportionment in various matrices. In this study, concentration data for As, Cu, Co, Cr, Fe, Mn, Ni, Pb, Sb, V and Zn in urban soils of two land uses (playground and roadside soils) from the city of Bratislava (Slovak Republic) were reinterpreted using the PMF model to quantify the contributions of individual sources of metal(loid)s in soils. Brake and tyre abrasion (27.0%), mixed traffic/industrial sources (14.3%), and natural origin (58.7%) were identified for roadside soils, while mixed traffic sources (28.4%), Cu-specific source (24.6%), and natural origin (47.0%) contributed to the metal(loid) concentrations in playground soils. Factor contributions revealed prevailing non-exhaust sources dominated by Cu, Sb and Zn over mixed traffic/industrial sources in roadside soils, following the world trend. Strong negative correlations of the 206Pb/207Pb isotopic ratio with Factor 1 in both groups of soils, representing traffic and industrial sources, are an evidence of the correct assignment of the obtained factor profiles to the actual sources of metal(loid)s in soils. There were significant differences in the proportion of mixed traffic sources in playground soils among the five urban districts, while the largest proportion of this source was identified in the city centre with the longest urbanisation and industrial history. Error estimation methods (displacement, bootstrap, displacement with bootstrap) proved that the data fit the model well and there was a minimal rotational ambiguity and random errors in the base model run. [ABSTRACT FROM AUTHOR]

The Bohai Sea is one of the most polluted sea areas in China. In this study, we used 2184 integrated concentrations of dissolved inorganic nitrogen (DIN) and dissolved inorganic phosphorus (DIP) in the Bohai Sea of China during spring (March, April, and May), summer (June, July, and August), and autumn (October and November) from 2015 to 2022 to explore the trends and sources of nutrients variations. From 2015 to 2022, DIN showed a downward trend until 2020 and then an upward trend, whereas DIP exhibited a stable trend with a slight decrease. The concentrations of DIN and DIP had similar seasonal pattern which was the highest in autumn (0.292 ± 0.247 mg/L for DIN and 0.013 ± 0.016 mg/L for DIP) but lower in spring (0.267 ± 0.238 mg/L for DIN and 0.006 ± 0.010 mg/L for DIP) and summer (0.263 ± 0.324 mg/L for DIN and 0.008 ± 0.010 mg/L for DIP). Sources of DIN and DIP apportioned by the positive matrix factorization (PMF) model were riverine input, sediment resuspension, sewage discharge, atmospheric deposition, and underground input. During 2015–2022, the largest contributor to DIN was sewage discharge (28.7%) and the largest contributor to DIP was sediment resuspension (44.6%). Seasonally, DIN in spring and autumn was dominated by sewage discharge (45.4% and 27.8%, respectively). Whereas in summer, it was dominated by riverine input (32.4%) and atmospheric deposition (29.7%). DIP was dominated by sediment resuspension during all three seasons (35.8%–52.5%). In addition, the increase in DIN concentrations in 2021 and 2022 were mainly due to the incremental input of river discharge and atmospheric deposition caused by increased precipitation during summer and autumn. [ABSTRACT FROM AUTHOR]

Scrap-iron smelting, a critical industry for metal recycling, is notorious for releasing potentially toxic elements (PTEs) into the environment. This study investigates pollution levels, sources, and health risks of ten PTEs (Fe, As, Cd, Zn, Cu, Mn, Pb, Cr, Co, and Ni) in indoor and outdoor areas surrounding a major scrap-iron recycling plant in northcentral Nigeria. The potential sources of studied PTEs pollution during the rainy and dry seasons were evaluated using Positive Matrix Factorization (PMF) model. Ecological risk assessments of studied PTEs were conducted using different pollution indices such as Enrichment Factor (EF), Geo-accumulation Index (Igeo), Contamination Factor (Cf), Potential Ecological Risks Index (PERI), Nemerov Integrated Pollution Index (NIPI), and Nemerov Integrated Risk Index (NIRI). Out of the 10 PTEs studied, Cd had the highest pollution level and exhibited a high potential to cause cancer in children during the two seasons considered. Sources of PTEs identified for rainy season included recycling process, electronic waste, coal combustion, steel production, and other smelting activities whereas steel production, electronic waste, coal combustion, recycling process, and traffic emission contributed to the PTE levels obtained in the dry season. This study contributes to the understanding of the environmental impact of scrap-iron smelting operations and advocate for the implementation of sustainable practices that protect both human health and the environment.Highlights: Seasonal variation of ten PTEs in indoor and outdoor areas near a scrap iron recycling were investigated. Electronic waste, and fossil fuel combustion were identified as most contributing factors. Cd was the major contaminant that posed higher ecological risks. Concerted effort is required to reduce human exposure. [ABSTRACT FROM AUTHOR]

This study aimed to assess the characteristics of particulate matter (PM) and polycyclic aromatic hydrocarbons (PAHs) from various stationary and mobile emission sources in Taiwan, with a focus on source apportionment and associated health risks. The northern power plant, equipped with bag filters operating at 150 °C, had significantly lower FPM and CPM levels (0.44 and 0.13 mg/m3, respectively) compared to the central and southern power plants, which used electrostatic precipitators operating at 250 °C (FPM, 1.45–8.35 mg/m3; CPM, 2.37–3.73 mg/m3). Additionally, emissions from diesel vehicles under both idle and high-speed conditions exhibited higher FPM levels (3.46–4.67 mg/m3) than gasoline vehicles (0.19–0.40 mg/m3). In terms of PAH toxicity, diesel vehicle emissions had significantly higher BaP-TEQ (87.3 ng/m3) and BaP-MEQ (25.9 ng/m3) levels compared to power plants (BaP-TEQ, 5.49 ng/m3; BaP-MEQ, 2.65 ng/m3). The highest ambient concentrations of PM2.5, BaP-TEQ, and BaP-MEQ were recorded at traffic sites, with values of 48 ± 36 µg/m3, 0.29 ng/m3, and 0.11 ng/m3, respectively. Differences in PAH distributions between stationary and mobile sources were influenced by factors such as pollution control technologies, combustion temperatures, and fuel types. Diesel vehicle emissions were dominated by benzo[g,h,i]perylene (BghiP), indeno[1,2,3-cd]pyrene (IND), benzo[a]pyrene (BaP), and benzo[b]fluoranthene (BbF) under idle conditions, while phenanthrene (PA), pyrene (Pyr), and BghiP were prevalent under high-speed conditions. Source apportionment conducted using principal component analysis (PCA) and positive matrix factorization (PMF) identified diesel and gasoline vehicles as the dominant contributors to atmospheric PAHs in Taiwan, accounting for 38% of the total, followed by coal-fired power plants at 35%. The highest lifetime excess cancer risk (ECR) of 2.5 × 10⁻5 was observed in traffic-dense areas, emphasizing the public health implications of vehicle emissions. The study adds credibility to the source apportionment findings, and the health risk analysis highlights variations across different regions, including traffic, urban, rural, and background zones. [ABSTRACT FROM AUTHOR]

Black carbon aerosols and PM2.5 have been identified as one of the major factors responsible for the ambient air quality index in Jamshedpur. The real-time measurement of BC concentration is determined with the help of an Aethalometer (AE-33), which was analyzed from November 2022 to April 2023. In the present study, we have compared the aerosol parameters during haze (Nov-Jan) and normal days (Oct, Feb-May) periods. We estimated the average mass concentration of BC, PM2.5 and AQI during haze days (HD) and normal days (ND), respectively. BC concentrations showed significant temporal variations with around 6.25 ± 3.05 and 2.52 ± 2.75 μg m − 3 during HD and ND, respectively. While PM2.5 and AQI concentrations in HD were found to be 264.64 ± 58.8 and 267.84 ± 56.72 μg m − 3, which were double of 130.19 ± 60.1 and 141.98 ± 52.44 μg m − 3, respectively, during ND. The highest monthly concentration of BC, PM2.5 and AQI was noticed in December at 8.35, 291.9 and 298 μg m − 3, respectively. Large-scale energy production in industries can consume coal and petroleum as primary fuels, which may be a major reason for the high concentrations. Due to low mixing height during winter, these emissions are not spread properly. Hence, higher concentration was found in December. The values for BC/PM2.5 were observed as 2.37% with a range from 0.54 to 4.4% and 2.48% (0.5 to 21.78%) during HD and ND, respectively. The study determined the source apportionment of BC with biomass dominance found in HD. The % BB was obtained around 53.1% throughout haze session, which was approximately 1.57 times higher than normal day (33.77%). In winter, burning wood and other solid fuels to warm the atmosphere may increase the contribution of BB to BC emissions. Furthermore, the backward trajectories calculated that air masses were concentrated within the IGP regions at lower altitudes during the HD while there was a diverse circulation of air parcels throughout the ND. Air masses were majorly coming to the receptor site from west India in ND. GIOVANNI NASA satellite model proved that surface mass concentrations of BC and PM2.5 were observed higher over IGP areas as well as other parts of India during HD with respect to ND. [ABSTRACT FROM AUTHOR]

In recent years, industrial waste and agrochemicals have reduced soil fertility and productivity, significantly impacting food security and ecosystems. In China, areas near red mud deposits from the aluminum industry show severe heavy metal contamination. This study examines agricultural soil near a red mud site in Shanxi Province, analyzing Cd, Cr, Hg, Ni, Pb, As, Cu, and Zn levels and distribution. Geostatistical methods and GIS are utilized to assess heavy metal pollution using the single factor index, the Nemerow integrated index, and the Hakanson potential ecological risk index. Absolute Principal Component Scores-Multiple Linear Regression (APCS-MLR) and Positive Matrix Factorization (PMF) models are used for quantitative analysis of pollution sources. Research indicates that the average concentrations of eight heavy metals exceed the natural background values of Shanxi, placing them at a severe pollution level with moderate ecological risk. Specifically, indices for As, Pb, and Cr are 3.79, 3.38, and 3.26, indicating severe pollution; Cd, Cu, and Hg at 2.36, 2.62, and 3.00 suggest moderate pollution; Ni at 1.87 shows mild pollution, while Zn at 0.97 is not polluted. Hg presents the highest ecological risk with a coefficient of 120.00, followed by Cd (70.69) and As (37.92). Spatial analysis shows significant correlations among Pb, Zn, Cu, and Ni, while Cr, Cd, Hg, and As show greater variability and weaker correlations. Both models identify five main sources: industrial activities, agricultural fertilizers, red mud leachate, energy combustion, and natural geological backgrounds, with respective contribution rates in the APCS-MLR model at 27.7%, 24.6%, 18.1%, 15.2%, and 14.4%, and in the PMF model at 29.2%, 21.5%, 16.9%, 16.7%, and 15.7%. This study offers a scientific basis for controlling soil pollution in the region, filling a literature gap. [ABSTRACT FROM AUTHOR]

The present study focuses on the elemental characterization and contribution of prominent sources of particulate matter (PM) in Darjeeling, the high-altitudinal eastern Himalayan station. The concentration of PM10 and PM2.5 was exceeded the National Ambient Air Quality Standards (NAAQS) for 72% and 83% of the sampling days, respectively. Since the World Health Organization or other government organizations has not set any standards for PM1, the standards of PM10 and PM2.5 were considered as benchmarks. The concentration of PM1 exceeded the NAAQS for PM10 and PM2.5 on 57% and 85% of the days, respectively. The elemental characterization using wavelength dispersive X-ray fluorescence (WD-XRF) technique identified 21 elements with the dominance of Si, Na, B, Ba, Al, and K in PM10; while, Al, N, and B in PM2.5 and PM1. Principal component analysis depicted that biomass burning, fossil fuel combustion, crustal/soil dust, and industrial emissions were identified as primary contributors to PM10; PM2.5 was substantially attributed to industrial emissions, agricultural activities, biomass burning, vehicular activities and natural sources. Additionally, natural sources and anthropogenic activities like vehicular, agricultural, and industrial emissions, and combustion were identified as the major sources of PM1 in Darjeeling. The findings of this study could potentially raise awareness among researchers and policymakers, prompting them to develop sustainable strategies in hill regions across the globe. [ABSTRACT FROM AUTHOR]

The current study is based on the measurement and monitoring of selected trace metals in coarse particles (PM10) from Islamabad, Pakistan. The particulate samples were analysed by atomic absorption spectroscopy to assess the concentration of trace metals: K, Ca, Fe, Zn, Mg, Cu, Cr, Mn, Pb, Sr, Li, Ni, Co, Ag, and Cd. The mean concentration of PM10 was 88.31 µg/m3. Among the trace metals, dominant mean contribution was shown by K (3477 ng/m3), followed by Ca (1812 ng/m3), Fe (797.9 ng/m3), Zn (619.5 ng/m3), and Mg (562.6 ng/m3) with following ascending order; Cd < Li < Ag < Co < Mn < Sr < Pb < Ni < Cr < Cu < Mg < Zn < Fe < Ca < K. Multivariate analyses showed that transportation/industrial emissions, and combustion processes were the major anthropogenic emission sources of the particulates. The pollution status was evaluated in terms of enrichment factor and geoaccumulation index; the study revealed that Ag exhibited the highest contamination, followed by Cu, Zn, and Cd. Moreover, assessment of health risks for toxic metals showed that the prevailing metal concentrations were safe for non-carcinogenic risk, however, Co was the only metal that exceeded the safe limit. Toxic metals including Cr, Co, and Ni showed significant cancer risk through inhalation of the atmospheric particulates. The current elemental concentrations in PM10 were compared to the previously reported levels from other regions around the globe. It was revealed that PM10 levels in Islamabad exhibited relatively lower concentration than those found in Asian cities, but higher than those observed in European and American cities. Similarly, the metal levels were found to be relatively higher in the neighbouring countries. [ABSTRACT FROM AUTHOR]

ABSTRACT Studying initial geothermal fluids and tectonic active zones is crucial for exploiting intermediate high‐temperature geothermal resources. This study aims to investigate the genesis, circulation and environmental implications of geothermal water in the Riduo–Cuona Rift (RCR) of the eastern Tibetan Plateau. By integrating hydrochemical analysis, stable isotope geochemistry (δ2H, δ18O and 87Sr/86Sr), and noble gas isotope characteristics, the research seeks to develop comprehensive geothermal circulation models in the RCR. (M1) The spatial distribution of geothermal waters near the molten magmatic domes indicated 87Sr/86Sr ranges consistent with those of the rock, respectively. The high Ca, Mg ‘hardness’ spring waters were attributed to strata surrounding the dome resulting from the last leaching, as confirmed by the estimated higher hydraulic head, mainly located in ‘immature water.’ (M2) The spatial distribution of geothermal waters corresponding to an orogenic belt revealed HCO3·SO4–Na as the dominant hydrochemical facies in the northern RCR. Research suggests that springs exhibit greater circulation depths and that spring solute SO4 is related to the Gangdise magmatic arc leaching. (M3) However, the active tectonic zone's springs 87Sr/86Sr (0.705763–0.709754) indicated evaporite characteristics. The thermal reservoir temperature in this structural junction zone is the highest (256.75°C–287.03°C). The high trace alkali element concentrations, particularly of B, F and As, exceeded the WHO guideline; the drainage system analysis indicates regional nonnegligible environmental risks in the Gudui. Establishing these models can clarify the relationships between geothermal fluids, tectonic structures and regional faults, providing insights into geothermal resource potential, environmental risks and possible strategies for sustainable resource exploitation in the region. [ABSTRACT FROM AUTHOR]

To understand the pollution characteristics and potential sources of heavy metal(loid)s in the nearshore sediments of Qionghai, 93 surface sediment samples were collected from the region. The concentrations of 20 elements, including Fe, Mg, Ca, Ti, Mn, Ba, Cr, Sr, Ni, Cu, Zr, As, Hg, Se, Be, Co, Mo, Cd, Ga, and Pb, were measured. The extent of contamination and ecological risk posed by these heavy metals/metalloids were evaluated using the geo-accumulation index, potential ecological risk index, and Nemerow comprehensive risk index. Additionally, correlation analysis, principal component analysis (PCA), and positive matrix factorization (PMF) were employed to identify the potential sources of these elements in the sediments. The findings reveal the following: (1) The mean concentrations of Fe, Ca, Mg, Ti, Cu, Sr, Zr, Mo, Cd, Pb, Hg, As, and Se exceed the background values for shallow sea sediments in China. Notably, Ca, Ti, Sr, Zr, Mo, Hg, and As exhibit coefficients of variation greater than 51%, indicating significant spatial variability primarily driven by anthropogenic activities. (2) The ecological risk assessment identifies Sr, Hg, and As as the principal pollutants and key potential ecological risk factors in the study area, necessitating prioritization in subsequent monitoring efforts. (3) Correlation and source analysis suggest that As and Mn primarily originate from agricultural activities, Sr, Ca, and Mg from aquaculture, Zr, Ti, Mo, Se, Pb, Be, Co, Cu, Ga, Ni, Fe, and Cd from natural sources, and Hg, Ba, and Cr from transportation sources. Additionally, this study identified Sr, Hg, and As as the primary pollutants in the Qionghai nearshore area, with sources predominantly linked to agriculture, aquaculture, and traffic. Regular monitoring will help track the effectiveness of implemented control measures and provide data for ongoing risk assessments, ensuring the protection and sustainability of the marine environment. [ABSTRACT FROM AUTHOR]

The identification and quantification of soil heavy metal (HM) pollution sources and the identification of driving factors is a prerequisite of soil pollution control. In this paper, the Sabaochaqu Basin of the Tuotuo River, located in the Tibetan Plateau and the headwater of the Yangtze River, was selected as the study area. The soil pollution was evaluated using geochemical baseline, and the source apportionment of soil HMs was performed using absolute principal component score-multiple linear regression (APCS-MLR), edge analysis (UNMIX) and positive matrix decomposition (PMF). The driver of the source factor was identified with the geodetector method (GDM). The results of pollution evaluation showed that the HM pollution of soil in the study area was relatively light. By comparison, UNMIX model was considered to be the preferred model for soil HMs quantitative distribution in this study area, followed by PMF model. The UNMIX model results show that source 1 (U-S1) was dominated by As, with a contribution rate of 53.31%; source 2 (U-S2) was dominated by Cd and Zn, whose contribution rates are 50.35% and 46.60% respectively; source 3 (U-S3) was dominated by Pb, with a contribution rate of 45.58%; source 4 (U-S4) was dominated by Cr, Cu, Hg and Ni, with contribution rates of 60.58%, 60.07%, 51.58% and 56.45%, respectively. The GDM results showed that the main driving factors of U-S1 were distance from lake (explanatory power q = 0.328) and distance from wind channel (q = 0.168), which were defined as long-distance migration sources. The main driving factors of U-S2 were parent material type (q = 0.269) and distance from Tuotuo river (q = 0.213), which were defined as freeze-thaw sources. The main driving factors of U-S3 were distance from town (q = 0.255) and distance from county road (Yanya Line) (q = 0.221), which were defined as human activity sources. The main drivers of U-S4 were V (q = 0.346) and Sc (q = 0.323), which were defined as natural sources. The GDM results of the 3 models were generally consistent with the analytical results of similar types of sources, especially the results of PMF model and Unmix model can basically verify each other. The research results can provide important theoretical reference for the analysis of HM sources in the soil of high-cold and high-altitude regions. [ABSTRACT FROM AUTHOR]

We introduce a new model for non-linear endmember extraction and spectral unmixing of hyperspectral imagery called Generative Simplex Mapping (GSM). The model represents endmember mixing using a latent space of points sampled within a (n − 1) -simplex corresponding to n unique sources. Barycentric coordinates within this simplex are naturally interpreted as relative endmember abundances satisfying both the abundance sum-to-one and abundance non-negativity constraints. Points in this latent space are mapped to reflectance spectra via a flexible function combining linear and non-linear mixing. Due to the probabilistic formulation of the GSM, spectral variability is also estimated by a precision parameter describing the distribution of observed spectra. Model parameters are determined using a generalized expectation-maximization algorithm, which guarantees non-negativity for extracted endmembers. We first compare the GSM against three varieties of non-negative matrix factorization (NMF) on a synthetic data set of linearly mixed spectra from the USGS spectral database. Here, the GSM performed favorably for both endmember accuracy and abundance estimation with all non-linear contributions driven to zero by the fitting procedure. In a second experiment, we apply the GTM to model non-linear mixing in real hyperspectral imagery captured over a pond in North Texas. The model accurately identified spectral signatures corresponding to near-shore algae, water, and rhodamine tracer dye introduced into the pond to simulate water contamination by a localized source. Abundance maps generated using the GSM accurately track the evolution of the dye plume as it mixes into the surrounding water. [ABSTRACT FROM AUTHOR]

Excessive levels of heavy metals in soil can significantly impact human health and ecological safety. Evaluating heavy metal pollution and identifying its sources are crucial for environmental management. This study investigates the status of heavy metal pollution in a southeastern region of China and aims to identify its sources using data from the first national soil pollution survey, which includes 282 sampling points. Indicators such as the geoaccumulation index (Igeo), the potential ecological risk index (RI), the hazard index (HI), and the total lifetime cancer risk (TLCR) were utilized to assess contamination levels. Geographic information systems (GIS), positive matrix factorization (PMF) receptor modeling, cluster analysis (ClusA) and human health risk assessments were integrated to analyze the sources of heavy metals. The results indicate that agricultural pollution sources have a minor impact on overall heavy metal contamination, with low ecological risk levels in the eastern and western regions. In contrast, the central region exhibited moderate risk, with areas of extremely high risk distributed across the central-west and central-south regions. PMF analysis identified pollution sources including natural origins, coal combustion, industrial emissions, and traffic, with contributions of 17.62%, 18.50%, 28.35%, and 35.56%, respectively. Overall, the carcinogenic risk in the study area is not high. Targeted recommendations were made in response to the pollution situation in the study area. This research enhances our understanding of heavy metal pollution in the soil of the study area and provides a reference for pollution source delineation in other regions. [ABSTRACT FROM AUTHOR]

The spatial distribution and seasonal variation in heavy metal pollution in road dust in Liuzhou, China, were investigated. Road dust samples were collected during both drought and wet periods, and the concentrations of nine heavy metals—Cr, Ni, Cu, Pb, Zn, Cd, As, Sb, and Hg—were analyzed. The analysis showed that all nine heavy metals were higher than the background values of Chinese urban soils in both the drought and wet periods, and the mean heavy metal contents of road dust in the dry period were higher than those in the wet period, except for Cd. In the assessment of the pollution of heavy metals in road dust, the results of Igeo showed that Cd and Hg were significant; the results of NI showed that Cr and Ni were more significant. The spatial analysis shows that the industrial concentration areas in the north and west of Liuzhou City are concentration areas of heavy metal pollution. A Pearson correlation analysis showed high correlation between Cd in road dust heavy metals and Cd in the surrounding soil. Source identification via PCA revealed four main contributors: metallurgical and coal-fired industries, mechanical manufacturing, green belt maintenance, and waste treatment facilities. A quantitative analysis via APCS-MLR modeling confirmed that metallurgical and coal-fired industrial sources are the most widespread and important pollution sources in Liuzhou. There is a significant increase in the contribution of waste treatment sources to Hg contamination during wet periods. [ABSTRACT FROM AUTHOR]

Seosan is a concentrated industrial complex in the midwestern region of Korea. A study was conducted from December 2020 to January 2021, measuring PM2.5 and chemical components in Seosan using online instruments every hour. The concentration of PM2.5 during the winter season was 31.4±17.8 μg/m3, exceeding the national ambient air quality standard of Korea. The mass fraction of organic matter, elemental carbon, three major ions, five minor ions, crustal elements, and trace elements in PM2.5 accounted for 24.5%, 4.36%, 32.0%, 2.82%, 4.11%, and 5.17% of the total PM2.5 mass concentration, respectively. Source identification was conducted using positive matrix factorization modeling, revealing eight sources of PM2.5: Secondary inorganic aerosol (SIA), vehicle exhaust, industry, coal combustion, biomass burning/incinerator, oil combustion, soil, and aged sea salt. Source contributions varied during high pollution episodes (HPE), with SIA dominating in HPE1 and soil and aged sea salt in HPE2. The potential source contribution function and conditional probability function were utilized to estimate the potential local and regional emission areas for the identified sources. In Seosan, vehicle exhaust and biomass burning/incinerator were primarily influenced by local sources. SIA, industry, and oil combustion sources were significantly affected by short-range transport from eastern China. Soil and aged sea salt, which exhibited high contributions during HPE2, were associated with long-range transport from Inner Mongolia. Coal combustion was attributed to both local sources, particularly large industrial complexes near Seosan, and long-range transport from Northeast China and Inner Mongolia. [ABSTRACT FROM AUTHOR]

Current regulations mandate the monitoring of respirable coal mine dust (RCMD) mass and crystalline silica in underground coal mines to safeguard miner health. However, other RCMD characteristics, such as particle size and chemical composition, may also influence health outcomes. This study collected RCMD samples from two underground coal mines and performed detailed chemical speciation. Source apportionment was used to estimate RCMD and silica contributions from various sources, including intake air, fire suppression limestone dust, coal dust, diesel engine exhaust, and rock strata. The mine dust mass-based size distributions were comparable to those recorded over a decade ago, with a peak around 10 μm and the majority of the mass in the supermicron size range. The current mine conditions and mining practices do not appear to have significantly increased the generation of smaller particles. Limestone rock dust was prevalent in many locations and, along with coal dust, was the main contributor to RCMD at high-concentration locations. Silica accounted for over 10% of RCMD mass at several active mining locations, primarily from limestone and rock strata dust. Reducing the concentration of limestone dust and its silica content could reduce RCMD and silica levels. Further cleaning of the intake air could also improve the overall mine air quality. [ABSTRACT FROM AUTHOR]

Water-soluble inorganic ions (WSIIs) can increase the hygroscopicity of aerosols, which will transform aerosols into larger sizes and reduce visibility by enhancing light scattering. To explore the characteristics of WSII concentrations and their impacts on visibility in a coastal airport, in this study, PM1.0 samples at two monitoring sites (including airport site and background site) were collect in spring and summer, and 12 species of ions were detected. In general, secondary water-soluble inorganic ions (SNA, including SO 4 2 − , NO 3 − and NH 4 + ) and Ca 2 + were the dominant WSIIs in PM1.0, contributing about 89% to 95% of the total measured ions. The continental contributions of SO 4 2 − , K + , and Ca 2 + accounted for more than 60% during the whole period, while Na+ and Cl − were mainly from marine sources. The source identification showed that airport emissions were a major source at the sampling site and significantly contributed to the levels of sulfate, nitrate, and ammonium. Agricultural activities were the dominant sources impacting visibility in spring, while airport emissions and secondary inorganic aerosols were the main components affecting visibility in summer. Therefore, improving atmospheric visibility in coastal airport areas should focus on reducing the precursors of secondary particulates and reducing biomass-burning activities. [ABSTRACT FROM AUTHOR]

This study utilized the Community Multiscale Air Quality (CMAQ) model to assess the impact of open biomass burning (OBB) in Thailand and neighboring countries—Myanmar, Laos, Cambodia, and Vietnam—on the PM2.5 concentrations in the Bangkok Metropolitan Region (BMR) and Upper Northern Region of Thailand. The Upper Northern Region was further divided into the west, central, and east sub-regions (WUN, CUN, and EUN) based on geographical borders. The CMAQ model was used to simulate the spatiotemporal variations in PM2.5 over a wide domain in Asia in 2019. The Integrated Source Apportionment Method (ISAM) was utilized to quantify the contributions from OBB from each country. The results showed that OBB had a minor impact on PM2.5 in the BMR, but transboundary transport from Myanmar contributed to an increase in PM2.5 levels during the peak burning period from March to April. In contrast, OBB substantially impacted PM2.5 in the Upper Northern Region, with Myanmar being the major contributor in WUN and CUN and domestic burning being the major contributor to EUN during the peak months. Despite Laos having the highest OBB emissions, meteorological conditions caused the spread of PM2.5 eastward rather than into Thailand. These findings highlight the critical impact of regional transboundary transport and emphasize the necessity for collaborative strategies for mitigating PM2.5 pollution across Southeast Asia. [ABSTRACT FROM AUTHOR]

The increasing Ozone (O3) concentration in various regions of China has garnered significant attention, highlighting the need to understand the mechanisms of O3 formation. This study focuses on the source apportionment of O3 in Jilin City during and after the COVID-19 lockdown countermeasure, and also the influence of anthropogenic emissions on O3 concentration. The contributions of different O3 emission sources were quantified using the Weather Research and Forecasting Community Multi-Scale Air Quality (WRF-CMAQ) model in conjunction with the Integrated Source Apportionment Method (ISAM). The results indicate a significant increase in O3 concentrations during the lockdown in Jilin City, which were particularly characterized by long-distance transportation. Transportation is identified as the primary direct source of O3 in Jilin City, with Yongji County contributing the most among the six designated regions. This study highlights variations in the causes and sources of O3 pollution among the different regions of Jilin City. Simply controlling anthropogenic emissions is inadequate for effectively managing O3 pollution and may even worsen the situation. It is more effective to focus on controlling O3's precursors. These findings improve the understanding of O3 pollution in Jilin City and provide valuable insights for developing O3 control policies. Similarly, this research is applicable to other countries and regions. [ABSTRACT FROM AUTHOR]

Heavy metal accumulation in soil can seriously harm human health, and it is necessary to identify the accumulation status and access the potential risks for local pollution control and sustainable economic development. This study evaluated the pollution level, spatial distribution, potential risk and sources of soil heavy metals along the Zhengzhou-Kaifeng intercity railway and compared pollution characteristics in north side soils with south side soils of the railway. A total of 260 soil samples were collected from a section along the railway. In practice, only the average Zn and Pb contents in soils were slightly higher than their corresponding risk screening values. The heavy metal enrichment in the north side soils was marginally lower than that in the south side soils. The spatial distribution of soil heavy metals except Pb could be mainly influenced by the different land use types. The geoaccumulation index and potential ecological risk of a single heavy metal indicated that Cd was the major contaminant with moderate pollution and high ecological risks in the south side soils and none to moderate pollution and moderate ecological risks in the north side soils. However, the mean multimetal potential ecological risk values suggested that the north side soils were at low ecological risks and the south side soils were at moderate ecological risks. The comprehensive non-carcinogenic risks and total carcinogenic risks for adults were low and acceptable, respectively. Pearson correlation analysis, PCA, and APCS-MLR analyses identified that the contributions of natural sources, mixed sources of industrial and traffic activities, agricultural activities, and other sources were 57.49%, 21.44%, 12.67% and 8.40%, respectively, and the major soil pollution Cd was mainly related to mixed sources of industrial and traffic activities. Therefore, continuous soil heavy metal monitoring is essential to elucidate the long-term railway operation effect on soil heavy metal accumulation. [ABSTRACT FROM AUTHOR]

Herbicides (HBCs) are extensively used in modern agriculture. However, their potential negative impacts on environmental media have emerged as a significant environmental concern. In this study, we employed positive matrix factorization (PMF) to identify the potential sources of HBCs. Furthermore, we utilized a multi-matrix ecological risk model to assess the risks associated with HBCs in both surface water and groundwater in the black soil region of Northeast China. The findings revealed that the levels of ∑ 15 HBCs in surface water and groundwater ranged from 585.84 to 6466.96 ng/L and 4.80 to 11,774.64 ng/L, respectively. The PMF results indicated that surface runoff and erosion accounted for 50% of the total HBCs in water, serving as the primary sources. All tested HBCs exhibited acute risk values within acceptable levels. The risk index for the ∑ 15 HBCs was categorized as "moderate risk" in 31% of the surface waters and 13% of the groundwaters. However, 4% of the groundwater sampling sites reached the "high risk" level. The chronic risk quotient of ∑ 15 HBCs in surface water and groundwater was 92% and 62% at the "high risk" level, respectively. Interestingly, non-carcinogenic HBCs contributed more significantly to the ecotoxicology of the aquatic system than carcinogenic HBCs. This study provides comprehensive information on the legacy of HBCs in water bodies and emphasizes the potential risks posed by HBCs to aquatic systems. The results obtained from this study could help relevant management authorities in developing and implementing effective regulations to mitigate the ecological and environmental risks associated with HBCs. [Display omitted] [ABSTRACT FROM AUTHOR]

PM2.5 pollution is problematic in megacities on the western coast in South Korea (Seoul, Incheon, and Gwangju). As these megacities are located downwind of China, their air quality is easily affected by local and long-range transport sources. PM2.5 samples collected in Seoul (n = 222), Incheon (n = 221), and Gwangju (n = 224) from September 2020 to March 2022, were chemically characterized. Dispersion normalized positive matrix factorization was applied to these PM2.5 speciated data to provide source apportionments. Nine common sources (including secondary nitrate, secondary sulfate, biomass burning, mobile, and waste incinerator) were identified at all sites. The conditional bivariate probability function helped to identify each site's local sources. Joint potential source contribution function analysis identified northeast China and Inner Mongolia as potential source areas of long-range transport pollutants affecting all sites. Forced lifestyle changes due to the pandemic such as limited gatherings while increased recreational activities may have caused different patterns on the biomass burning source. The constraints on old vehicles during the policy implementation periods likely reduced the mobile source contributions in cities that adopted the policy. Secondary nitrate accounted for 40% of the PM2.5 mass at all sites, implying a significant impact from NOX sources. While the current policy focuses primarily on controlling primary emission sources, it should include secondary sources as well which may include precursor emissions control. Healthier air quality would be achieved if the policy effects are not limited to local, but also to foreign sources in regions upwind of Korea by intergovernmental collaboration. [ABSTRACT FROM AUTHOR]

Volatile organic compounds (VOCs) are ubiquitous in the atmosphere, posing significant adverse impacts on air quality and human health. However, current research on atmospheric VOCs mainly focuses on specific regions or industries, without comprehensive national-level analysis. In this study, a total of 99 articles on atmospheric VOCs in China published from 2015 to 2024 were screened, and data on their concentrations, source apportionment, and health risks were extracted and summarized. The results revealed that the annual average concentrations of TVOCs and their groups in China generally increased and then decreased between 2011 and 2022, peaking in 2018–2019. A distinct seasonal pattern was observed, with the highest concentrations occurring in winter, followed by autumn, spring, and summer. TVOC emissions were highly concentrated in northern and eastern China, mainly contributed by alkanes and alkenes. Source apportionment of VOCs indicated that vehicle sources (32.9% ± 14.3%), industrial emissions (18.0% ± 12.8%), and other combustion sources (13.0% ± 13.0%) were the primary sources of VOCs in China. There was a significant positive correlation (p < 0.05) between the annual mean VOC concentration and population size, and a notable negative correlation (p < 0.05) with GDP per capita. Atmospheric VOCs had no non-carcinogenic risk (HI = 0.5) but exhibited a probable carcinogenic risk (7.5 × 10−5), with relatively high values for 1,2-dibromoethane, 1,2-dichloroethane, and naphthalene. The health risk was predominantly driven by halocarbons. These findings are essential for a better understanding of atmospheric VOCs and for developing more targeted VOC control measures. [ABSTRACT FROM AUTHOR]

This study aimed to assess the levels of inorganic substances, including trace metals and ionic species in PM2.5 in a semi-urban region located in the lower northern region of Thailand. It also aims to investigate the potential impacts of trace metals on human health. Samples of PM2.5 were collected using a low volume air sampler (LVS) with a flow rate of 5 L min−1 over a period of 24 h. Trace metal concentrations were measured using inductively coupled plasma-mass spectroscopy (ICP-MS) and ionic compositions were determined using ion chromatography (IC). Human health risk evaluations were carried out in accordance with the health risk assessment regulations of the United States Environmental Protection Agency (USEPA). The results of this study showed that the average concentration of PM2.5 was 69.0 ± 33.4 µg m−3 above the standards set by USEPA for a 24 h average. Source identification using principal component analysis (PCA) based on trace metal and ion compositions suggested that the main sources of PM2.5 were crustal elements (28%) and a combination of biomass burning and motor vehicles (19%). High enrichment factor (EF) values (> 100) for As, Cd, and Pb indicated that these metals were significantly enriched and greatly influenced by anthropogenic sources. The trace metal hazard quotients (HQ) and excess lifetime cancer risks (ELCR) were within acceptable limits. This study suggests the need for an awareness of PM2.5 emissions and their trace metal compositions, especially from motor vehicles and biomass burning. [ABSTRACT FROM AUTHOR]

With the increasing demand for clean energy and water resources, hydropower engineering is gradually expanding worldwide. Revealing the status and toxic risks of riverine pollutants is of considerable theoretical importance for water safety management. However, damming complicates the geochemical behavior of pollutants in river water, especially in large reservoirs with intensive anthropogenic activities. Whether damming amplifies the environmental risks of pollutants needs to be clarified. This study selected heavy metals (HMs) as major pollutants, combining positive matrix factorization (PMF) and Monte Carlo simulation (MCS), identifying the damming impacts on riverine HMs in the Three Gorges Reservoir (TGR). The average concentrations of most HMs increased manyfold than the background, and the HMs loading rates of outflow was increased, suggesting the obvious disturbance by human activities. Through PMF, about 70% of Cu came from industrial wastewater discharges, and more than half of As, V, Mo and Ni were contributed by agricultural activities. The risk assessment results indicated that the concentration of most riverine HMs during the study period did not pose human health damage, children exposed to As have an 9.8 ± 0.9% occurrence probability of non-carcinogenic risk. The results coupled with PMF and MSC showed agricultural activities contributed most (51.3 ± 0.3%) to inducing HMs health hazard. In addition, the contribution rate of each potential source of HMs along the river remained relatively stable, suggesting that damming has limited impact on the risk occurrence. Overall, agricultural activities and the drinking water quality from TGR source should to be constraint preferentially for HMs risks prevention. [ABSTRACT FROM AUTHOR]

In this study, a total of 180 surface soil samples were collected from a control area and residential, commercial, and industrial regions of Hamedan, Iran during the fall season in 2023. Contents of analyzed elements were then determined using ICP-OES. The results illustrated that the average contents of As, Cd, Cu, Mn, Ni, and Pb were 1.17–2.26 times greater than those reported as local background values, while the mean contents of As, Cd, and Cu were respectively 3.41, 1.25, and 1.00 times greater than the background contents for Iran by implying the possible human sources of these PTEs. The cumulative average ecological risk value with 81.9, demonstrated moderate ecological risk across the study area. The results of source apportionment showed that the PTEs contamination in the soil of the study area mainly originates from the anthropogenic activities (65.6%) and traffic emissions as the primary pollution source (47.3%) had the highest contribution to the PTE pollution in the study area. In conclusion, by providing a useful approach to identifying the sources and contributions of toxic elements across different functional areas, this study has the potential to guide future efforts aimed at managing and mitigating the pollution caused by metal elements. [ABSTRACT FROM AUTHOR]

Suspended atmospheric microplastics (SAMPs) display varying occurrence characteristics on different underlying surfaces in urban areas. This study investigated the occurrence characteristics, source apportionment, and transportation patterns of SAMPs in two typical underlying surfaces: the downtown area (Site T) and the industrial area (Site C) of a coastal city in China. In the spring of 2023, a total of 32 types comprising 1325 SAMPs were detected. The average MP abundances were found to be 3.74 ± 2.86 n/m3 in Site T and 2.67 ± 1.68 n/m3 in Site C. In Site T, SAMPs attributed to living source constituted 78.05%, while industry was the main source in Site C with a proportion reaching 42.89%, consistent with the functional zoning of the underlying surface. Furthermore, HYSPLIT analysis revealed that there was no significant difference between these two sites in long-distance horizontal transport affected by external airflow regardless of altitude; conversely, PCA indicated a notable correlation between vertical velocity and both abundance and species diversity. According to the hourly average wind speeds, the maximum transmission distance was computed as 350 km for updraft and the minimum transmission distances was as low as 32 m for downdraft. Subsequently, the coincidence between the source proportion of SAMPs on random day and meteorological parameters confirmed the synergistic impact on SAMPs transport influenced by functional zoning, geographic environment, and vertical velocity. [ABSTRACT FROM AUTHOR]

Soil contamination of heavy metals in urban greenspaces can exert detrimental impacts on ecological biodiversity and the health of inhabitants through cross-media migration-induced risks. Here, a total of 72 topsoil samples were collected from greenspaces in the popular tourist city of Tianshui, ranging from areas with parks, residential, road, industrial and educational soils. The study aimed to evaluate an integrated source-specific ecological and human health risk assessment of heavy metals. Among the analyzed heavy metals, except Cr (mean), all exceeded the local background values by 1.30–5.67-fold, and Hg, Cd, Pb and As were the metals with large CV values. The Igeo and CF results showed Hg, Cd, As and Pb exhibited significantly high pollution levels and were the primary pollution factors. The mean PLI values indicated moderate pollution in educational (2.21), industrial (2.07), and road (2.02) soils but slight pollution in park (1.84) and residential (1.39) greenspaces. The Igeo, CF, and PLI results also revealing that these heavy metals are more likely to be affected by human activity. Four primary source factors were identified based on PMF model: coal combustion (25.57%), agricultural sources (14.49%), atmospheric deposition (20.44%) and mixed sources (39.50%). In terms of ecological risk, the mean IRI values showed considerable risks in educational soils (287.52) and moderate risks in road (215.09), park (151.27) and residential (136.71) soils. And the contribution ratio of atmospheric deposition for park, residential, road, industrial and educational greenspaces were 57.72%, 65.41%, 67.69%, 59.60% and 75.76%, respectively. In terms of human health risk, the HI (below 1) and CR (below 1.00E−04) for adults from soils of all land use types was negligible. However, children have more significant non-carcinogenic and carcinogenic hazards especially in residential soils, the HI (above 1) and CR (above 1.00E−04) revealed the significance of regarding legacy As contamination from coal combustion when formulating risk mitigation strategies in this area. The proposed method for source and risk identification makes the multifaceted concerns of pollution and the different relevant risks into a concrete decision-making process, providing robust support for soil contamination control. [ABSTRACT FROM AUTHOR]

To identify the sources of heavy metals in local soils and their risks to human health. This study quantified the concentrations of eight heavy metals in 504 soil samples collected in Tengzhou, China. The ecological risks of a single heavy metal (EI), a comprehensive ecological risk index (RI), and a health risk assessment model were used to evaluate the level of contamination in the city. The results of the research study indicate that there are different levels of heavy metal pollution in rural and urban agricultural areas in Tengzhou. Moreover, the spatial variability of mercury (Hg) is considerable, reaching 0.96, indicating a significant impact of anthropogenic activities. For the ecological risk, the heavy metal element with the highest EI value was mercury with a mean value of 67.22 and a peak value of 776.00. The heavy metal with the lowest mean EI value was Zn with only 1.03. Meanwhile, the average RI is only 128.59, but some areas have an RI as high as 842.2. The sources of heavy metals were identified using principal component analysis, correlation analysis, and an absolute principal component score multiple linear regression model (APCS-MLR). The non-carcinogenic risk for children, the carcinogenic risk for children, and the carcinogenic risk for adults were 1.23, 2.42×10–4 and 1.00×10–4, respectively, and these values exceeded their respective recommended values, and As and Cr had some carcinogenic hazards. Heavy metals in the soil come from natural, industrial, traffic and agricultural sources and represent 39.59%, 29.48%, 25.17% and 5.77%, respectively. The main source of heavy metals in local agricultural soils is the geological background, and the government needs to strengthen the monitoring of As and Cr in drinking water resources, as well as reduce traffic pollution and factory waste emissions to reduce Hg in soils. [ABSTRACT FROM AUTHOR]

Groundwater serves as a crucial resource, with its quality significantly impacted by both natural and human-induced factors. In the highly industrialized and urbanized Yangtze River Delta region, the sources of pollutants in shallow groundwater are more complex, making the identification of groundwater pollution sources a challenging task. In this study, 117 wells in Wujiang District of Suzhou City were sampled, and 16 groundwater quality parameters were analyzed. The fuzzy synthetic evaluation method was used to assess the current status of groundwater pollution in the study area; the principal component analysis (PCA) was employed to discern the anthropogenic and natural variables that influence the quality of shallow groundwater; and the absolute principal component scores–multiple linear regression (APCS-MLR) model was applied to quantify the contributions of various origins toward the selected groundwater quality parameters. The results indicate that the main exceeding indicators of groundwater in Wujiang District are I ( 28 % ), N H 4 - N ( 18 % ), and Mn ( 14 % ); overall, the groundwater quality is relatively good in the region, with localized heavy pollution: class IV and class V water are mainly concentrated in the southwest of Lili Town, the north of Songling Town, and the south of Qidu Town. Through PCA, five factors contributing to the hydrochemical characteristics of groundwater in Wujiang District were identified: water–rock interaction, surface water–groundwater interaction, sewage discharge from the textile industry, urban domestic sewage discharge, and agricultural non-point source pollution. Additionally, the APCS-MLR model determined that the contributions of the three main pollution sources to groundwater contamination are in the following order: sewage discharge from the textile industry ( 10.63 % ) > urban domestic sewage discharge ( 8.69 % ) > agricultural non-point source pollution ( 6.26 % ). [ABSTRACT FROM AUTHOR]

This comprehensive review synthesizes the current knowledge regarding the characteristics of particulate matter (PM) at locations directly impacted by industrial emissions. A particular emphasis was given to the morphology and size of these particles and their chemical characteristics per type of industrial activity. The relationship between the exposure to PM from industrial activities and health issues such as cancer, cardiovascular, and respiratory diseases was also discussed, highlighting significant epidemiological findings. Furthermore, this work highlights the source apportionment of PM in these areas as well as available databases for source profiles. The majority of the studies accentuate the ambiguity found in the identification of industrial sources mainly due to the lack of specific tracers and the overlapping between these sources and other natural and anthropogenic ones. The contribution of industrial sources to PM concentrations is generally less than 10%. Moreover, this review gathers studies conducted in the 18 countries of the East Mediterranean-Middle East (EMME) region, focusing on sites under industrial influence. In these studies, PM10 concentrations range from 22 to 423 μg/m3 while PM2.5 levels vary between 12 and 250 μg/m3. While extensive studies have been conducted in Egypt, Iran, and Lebanon, a lack of research in the UAE, Bahrain, Greece, Israel, Palestine, and Yemen highlights regional disparities in environmental health research. The major industrial sources found in the region were oil and gas industries, metallurgical industries, cement plants, petrochemical complexes, and power plants running on gas or heavy fuel oil. Future research in the region should focus on longitudinal studies and a more detailed chemical analysis of PM in the vicinity of industrial areas to enhance the accuracy of current findings and support effective policy making for air pollution control. [ABSTRACT FROM AUTHOR]

The South China Sea (SCS) is a crucial region for studying atmospheric aerosols, given its unique geographical location and the interaction of various natural and anthropogenic sources. In this study, we measured the isotopic characteristics of sulfate and nitrate in PM2.5 and utilized a Bayesian isotope mixing model (SIAR) to analyze their sources and formation pathways. Sulfur isotopic values in sulfate (δ34S-SO42−) were 8.7 ± 1.8‰, while nitrogen and oxygen isotopic values in nitrate (δ15N-NO3− and δ18O-NO3−) were −0.9 ± 2.4‰ and 52.3 ± 7.3‰, respectively. The results revealed that sulfate was primarily influenced by marine biogenic sulfur emissions (mostly dimethyl sulfide, DMS), fossil fuel combustion, and biomass burning. Nitrate formation was dominated by the NO2 + •OH pathway (accounting for 69.8–85.7%), with significant contributions from vehicle emissions, biomass burning, and lightning. These findings offer key insights into the complex interactions between natural and anthropogenic aerosol sources in the SCS, contributing to a broader understanding of marine aerosol chemistry. [ABSTRACT FROM AUTHOR]

Carbonyl compounds are important oxygenated volatile organic compounds (VOCs) that play significant roles in the formation of ozone (O3) and atmospheric chemistry. This study presents comprehensive field observations of carbonyl compounds during an unusual wintertime ozone pollution event at a suburban site in Guangzhou, South China, from 19 to 28 December 2020. The aim was to investigate the characteristics and sources of carbonyls, as well as their contributions to O3 formation. Formaldehyde, acetone, and acetaldehyde were the most abundant carbonyls detected, with average concentrations of 7.11 ± 1.80, 5.21 ± 1.13, and 3.00 ± 0.94 ppbv, respectively, on pollution days, significantly higher than those of 2.57 ± 1.12, 2.73 ± 0.88, and 1.10 ± 0.48 ppbv, respectively, on nonpollution days. The Frame for 0-D Atmospheric Modeling (F0AM) box model simulations revealed that local production accounted for 62–88% of observed O3 concentrations during the pollution days. The calculated ozone formation potentials (OFPs) for various precursors (carbonyls and VOCs) indicated that carbonyl compounds contributed 32.87% of the total OFPs on nonpollution days and 36.71% on pollution days, respectively. Formaldehyde, acetaldehyde, and methylglyoxal were identified as the most reactive carbonyls, and formaldehyde ranked top in OFPs, and it alone contributed 15.92% of total OFPs on nonpollution days and 18.10% of total OFPs on pollution days, respectively. The calculation of relative incremental reactivity (RIR) indicates that ozone sensitivity was a VOC-limited regime, and carbonyls showed greater RIRs than other groups of VOCs. The model simulation showed that secondary formation has a significant impact on formaldehyde production, which is primarily controlled by alkenes and biogenic VOCs. The characteristic ratios and backward trajectory analysis also indicated the indispensable impacts of local primary sources (like industrial emissions and vehicle emissions) and regional sources (like biomass burning) through transportation. This study highlights the important roles of carbonyls, particularly formaldehyde, in forming ozone pollution in megacities like the Pearl River Delta region. [ABSTRACT FROM AUTHOR]

The significant increase in ambient ozone (O3) levels across China highlights the urgent need to investigate the sources and mechanisms driving regional O3 events, particularly in densely populated urban areas. This study focuses on Xi'an, located in northwestern China on the Guanzhong Plain near the Qinling Mountains, where the unique topography contributes to pollutant accumulation. Urbanization and industrial activities have significantly increased pollutant emissions. Utilizing the Weather Research and Forecasting–Community Multiscale Air Quality Model (WRF-CMAQ), we analyzed the contributions of specific regional and industrial sources to rising O3 levels, particularly during an atypical winter event characterized by unusually high concentrations. Our findings indicated that boundary conditions were the primary contributor to elevated O3 levels during this event. Notably, Xianyang and Baoji accounted for 30% and 22% of the increased O3 levels in Xi'an, respectively. Additionally, residential sources and transportation accounted for 31% and 28% of the O3 increase. Within the Xi'an metropolitan area, Baqiao District (18–27%) and Weiyang District (23–30%) emerged as leading contributors. The primary industries contributing to this rise included residential sources (28–37%) and transportation (35–43%). These insights underscore the need for targeted regulatory measures to mitigate O3 pollution in urban settings. [ABSTRACT FROM AUTHOR]

To investigate the characteristics and sources of volatile organic compounds (VOCs) as well as their impacts on secondary organic aerosols (SOAs) formation during high-incidence periods of PM2.5 pollution, a field measurement was conducted in December 2019 in Hefei, a typical city of the Yangtze River Delta (YRD). During the whole process, the mixing ratios of VOCs were averaged as 21.1 ± 15.9 ppb, with alkanes, alkenes, alkyne, and aromatics accounting for 59.9%, 15.3%, 15.0%, and 9.8% of the total VOCs, respectively. It is worth noting that the contributions of alkenes and alkyne increased significantly during PM2.5 pollution periods. Based on source apportionment via the positive matrix factorization (PMF) model, vehicle emissions, liquefied petroleum gas/natural gas (LPG/NG), and biomass/coal burning were the main sources of VOCs during the research in Hefei. During pollution periods, however, the contribution of biomass/coal burning to VOCs increased significantly, reaching as much as 47.6%. The calculated SOA formation potential (SOAFP) of VOCs was 0.38 ± 1.04 µg m−3 (range: 0.04–7.30 µg m−3), and aromatics were the dominant contributors, with a percentage of 96.8%. The source contributions showed that industrial emissions (49.1%) and vehicle emissions (28.3%) contributed the most to SOAFP during non-pollution periods, whereas the contribution of biomass/coal burning to SOA formation increased significantly (32.8%) during PM2.5 pollution periods. These findings suggest that reducing VOCs emissions from biomass/coal burning, vehicle, and industrial sources is a crucial approach for the effective control of SOA formation in Hefei, which provides a scientific basis for controlling PM2.5 pollution and improving air quality in the YRD region. [ABSTRACT FROM AUTHOR]

To establish and implement effective policies for controlling fine particle matters (PM2.5), which is associated with high-risk diseases, continuous research on identifying PM2.5 sources was conducted. This study utilized the positive matrix factorization (PMF) receptor model to estimate the sources and characteristics of PM2.5 between Baengnyeong Island (BNI) and the Seoul Metropolitan Area (SMA). We conducted PMF modeling and backward trajectory analysis using the data on PM2.5 and its components collected from 2020 to 2021 at the Air quality Research Centers (ARC). The PMF modeling identified nine pollution sources in both BNI and the SMA, including secondary sulfate, secondary nitrate, vehicles, biomass burning, dust, industry, sea salt particles, coal combustion, and oil combustion. Secondary particulate matter, vehicles, and biomass burning were found to be major contributors to PM2.5 concentrations in both regions. A backward trajectory analysis indicated that air masses, passing through BNI to the SMA, showed higher concentrations and contributions of ammonium nitrate, vehicles, and biomass burning in the SMA site compared to BNI site. These findings suggest that controlling nitrogen oxides (NOx) and ammonia emissions in the SMA, as well as monitoring the intermediate products that form aerosols, such as HNO3, are needed. [ABSTRACT FROM AUTHOR]

• Cd and Hg were the most polluted HMs in the study area. • ZZ3 and ZZ7 were the most polluted workshops and required priority control. • GIS, PMF, and APCS-MLR models were used to analyze the precise sources of HMs. • Cd and Hg were respectively derived from smelting process and atmospheric deposition. The abandoned smelters present a substantial pollution threat to the nearby soil and groundwater. In this study, 63 surface soil samples were collected from a zinc smelter to quantitatively describe the pollution characteristics, ecological risks, and source apportionment of heavy metal(loid)s (HMs). The results revealed that the average contents of Zn, Cd, Pb, As, and Hg were 0.4, 12.2, 3.3, 5.3, and 12.7 times higher than the risk screening values of the construction sites, respectively. Notably, the smelter was accumulated heavily with Cd and Hg, and the contribution of Cd (0.38) and Hg (0.53) to ecological risk was 91.58%. ZZ3 and ZZ7 were the most polluted workshops, accounting for 25.7% and 35.0% of the pollution load and ecological risk, respectively. The influence of soil parent materials on pollution was minor compared to various workshops within the smelter. Combined with PMF, APCS-MLR and GIS analysis, four sources of HMs were identified: P1(25.5%) and A3(18.4%) were atmospheric deposition from the electric defogging workshop and surface runoff from the smelter; P2(32.7%) and A2(20.9%) were surface runoff of As-Pb foul acid; P3(14.5%) and A4(49.8%) were atmospheric deposition from the leach slag drying workshop; P4(27.3%) and A1(10.8%) were the smelting process of zinc products. This paper described the distribution characteristics and specific sources of HMs in different process workshops, providing a new perspective for the precise remediation of the smelter by determining the priority control factors. [Display omitted] [ABSTRACT FROM AUTHOR]

There is a large surface-groundwater exchange downstream of wastewater treatment plants (WWTPs), and antibiotics upstream may influence sites downstream of rivers. Thus, samples from 9 effluent-receiving urban rivers (ERURs) and 12 groundwater sites were collected in Shijiazhuang City in December 2020 and April 2021. For ERURs, 8 out of 13 target quinolone antibiotics (QNs) were detected, and the total concentration of QNs in December and April were 100.6-4,398 ng/L and 8.02–2,476 ng/L, respectively. For groundwater, all target QNs were detected, and the total QNs concentration was 1.09–23.03 ng/L for December and 4.54–170.3 ng/L for April. The distribution of QNs was dissimilar between ERURs and groundwater. Most QN concentrations were weakly correlated with land use types in the system. The results of a positive matrix factorization model (PMF) indicated four potential sources of QNs in both ERURs and groundwater, and WWTP effluents were the main source of QNs. From December to April, the contribution of WWTP effluents and agricultural emissions increased, while livestock activities decreased. Singular value decomposition (SVD) results showed that the spatial variation of most QNs was mainly contributed by sites downstream (7.09%-88.86%) of ERURs. Then, a new method that combined the results of SVD and PMF was developed for a specific-source-site risk quotient (SRQ), and the SRQ for QNs was at high level, especially for the sites downstream of WWTPs. Regarding temporal variation, the SRQ for WWTP effluents, aquaculture, and agricultural emissions increased. Therefore, in order to control the antibiotic pollution, more attention should be paid to WWTP effluents, aquaculture, and agricultural emission sources for the benefit of sites downstream of WWTPs. [ABSTRACT FROM AUTHOR]

In order to study the characteristics of volatile organic compounds (VOCs) in Yantai city, VOCs chemical composition, concentration characteristics, ozone generation potential (OFP) and pollutant sources were analyzed based on VOCs monitoring data in Yantai in 2020 and 2022. Results indicated that the volume concentration of VOCs decreased by 12.4% from 2020 to 2022, which was attributed to the significant decline in the concentration of oxygen-containing volatile organic compounds (OVOCs) (decreased by --33.1%) with a stable concentration of ozone precursors (PAMS). Species concentration analysis showed that alkanes and aldehydes ranked first in the volume concentration of PAMS and OVOCs. The three components with the highest volume concentration were formaldehyde, ethane and propane, respectively, and the three components with the highest mass concentration were w-hexane, formaldehyde and propane, respectively. Time distribution characteristics displayed that the volume concentration of PAMS and OVOCs fluctuated greatly, and high concentrations were prone to appear in July and August. Total OFP value of Yantai city also showed a downward trend, decreasing by 14.0% compared with 2020, among which the OFP value of various types of VOCs was as follows % aldehydes > alkenes> alkanes > aromatics > ketones > alkynes, and the top three contribution values accounted for 88.2%. According to the calculated value of OFP, formaldehyde and acetaldehyde were always the top two contributors to the generation of O3 in the ambient are in Yantai city, and the ozone prevention and control in Yantai city should focus on the following five components % formaldehyde, acetaldehyde, 2-methyl-1, 3- butadiene, ethylene and propylene. Source analysis results showed that the VOCs in Yantai city came from aging are mass transport, in which formaldehyde and acetaldehyde were mainly from motor vehicle exhaust and man-made source. Aromatic hydrocarbons were mainly derived from vehicle exhaust and coal/biomass interaction in which motor vehicles had a more significant impact. In conclusion, this study provides a scientific basis for the formulation of VOCs emission and O3 pollution prevention and control measure. It is suggested that Yantai city should conduct accurate control of anthropogenic emissions (especially motor vehicles) and coal/biomass by combusting VOCs concentration characteristics, species characteristics, time distribution characteristics and chemical reactivity analytics, so as to improve the ambient are quality of Yantai city. [ABSTRACT FROM AUTHOR]

Understanding the pollution situation of potentially toxic metals (PTMs) in fine road dust (FRD) in emerging industrialized cities and identifying priority control factors is crucial for urban environmental management, resident health protection, and pollution control. This study conducted a comprehensive investigation on PTMs pollution in FRD in Zunyi, a representative emerging industrialized city in the karst region of southwestern China. The average contents of Ni, Cr, Mn, Cu, Zn, Ba, Pb, V, and Co in the FRD were 43.2, 127.0, 1232.1, 134.4, 506.6, 597.8, 76.1, 86.8, and 16.2 mg kg−1, respectively, which were obviously higher than the corresponding background levels of the local soil except for V and Co. The comprehensive pollution level of the determined PTMs in the FRD was very high, primarily caused by Zn and Cu. The sources of PTMs in Zunyi FRD were traffic, industrial, construction, and natural sources, accounting for 38.0, 23.7, 21.9, and 16.4% of the total PTMs content, respectively. The PTMs in Zunyi FRD exhibited a low to moderate overall ecological risk level, mainly contributed by Cu and traffic source. The cancer risks of PTMs in Zunyi FRD were high for all populations. The non-carcinogenic risk of PTMs in Zunyi FRD was acceptable for adults, but cannot be ignored for children. According to the source-specific probabilistic health risk estimation results, the priority control source is industrial source and the priority control PTM is Cr. Local governments need to give more attention to the carcinogenic risks and health hazards posed by PTMs in the FRD. [ABSTRACT FROM AUTHOR]

Due to very high mobility in the environment and penetration ability into living organisms, nanoparticles (NPs) of urban dust pose a potential threat to human health and urban ecosystems. Currently, data on the chemical composition of NPs of urban dust, their fate in the environment, and corresponding risks are rather limited. In the present work, NPs of deposited urban dust have been comprehensively studied for the first time; NPs isolated from 78 samples of dust collected in Moscow, the largest megacity in Europe, being taken as example. The elemental composition, potential sources as well as environmental, ecological, and health risks of NPs of urban dust are assessed. It is found that dust NPs are extremely enriched by Cu, Hg, Zn, Mo, Sb, and Pb, and can serve as their carrier in urban environments. No regularities in the spatial distribution of elements have been found, probably, due to high mobility of dust NPs. High ecological and health risks caused by dust NPs are demonstrated. Source apportionment study has evaluated one natural and two anthropogenic sources of elements in NPs of urban dust; the contribution of natural and anthropogenic sources being comparable. It is also shown that dust NPs may be considered as an important carrier of trace elements in urban aquatic systems. Additionally, the risks associated with NPs and bulk samples of dust have been compared. The observed risks associated with NPs are significantly higher. [ABSTRACT FROM AUTHOR]

Polycyclic aromatic hydrocarbons (PAHs) are a group of organic compounds that are both toxic and hazardous to human health and ecological systems. In recent work, a novel analytical strategy based on the chemometric-assisted HPLC-DAD method was proposed for the quantification and source apportionment of eight PAHs in PM10 samples. Compared to traditional chromatographic methods, this approach does not require the purification of complex PM10 samples. Instead, it utilizes a mathematical separation method to extract analytes' profiles from overlapping chromatographic peaks, enabling precise quantification of PAHs in PM10. Firstly, 40 PM10 samples collected in Loudi city during two sampling periods were used for analysis. Subsequently, the second-order calibration method based on alternating trilinear decomposition (ATLD) was employed to handle the three-way HPLC-DAD data. Finally, the pollution sources of PAHs were analyzed by the feature component analysis method according to the obtained relative concentration matrix. For the validation model, the average recoveries of eight PAHs were between (88.8 ± 7.6)% and (105.6 ± 7.5)%, and the root-mean-square errors of prediction ranged from 0.03 μg mL−1 to 0.47 μg mL−1. The obtained limits of quantification for eight PAHs were in the range of 0.0050 μg mL−1 to 0.079 μg mL−1. For actual PM10 samples, results of the feature component analysis indicated that the main source of PAHs in PM10 may be traffic emissions and coal combustion. In summary, the proposed method provided a new and rapid analysis method for the accurate determination and source apportionment of PAHs in atmospheric aerosols. [ABSTRACT FROM AUTHOR]

Abstract The identification and quantification of soil heavy metal (HM) pollution sources and the identification of driving factors is a prerequisite of soil pollution control. In this paper, the Sabaochaqu Basin of the Tuotuo River, located in the Tibetan Plateau and the headwater of the Yangtze River, was selected as the study area. The soil pollution was evaluated using geochemical baseline, and the source apportionment of soil HMs was performed using absolute principal component score-multiple linear regression (APCS-MLR), edge analysis (UNMIX) and positive matrix decomposition (PMF). The driver of the source factor was identified with the geodetector method (GDM). The results of pollution evaluation showed that the HM pollution of soil in the study area was relatively light. By comparison, UNMIX model was considered to be the preferred model for soil HMs quantitative distribution in this study area, followed by PMF model. The UNMIX model results show that source 1 (U-S1) was dominated by As, with a contribution rate of 53.31%; source 2 (U-S2) was dominated by Cd and Zn, whose contribution rates are 50.35% and 46.60% respectively; source 3 (U-S3) was dominated by Pb, with a contribution rate of 45.58%; source 4 (U-S4) was dominated by Cr, Cu, Hg and Ni, with contribution rates of 60.58%, 60.07%, 51.58% and 56.45%, respectively. The GDM results showed that the main driving factors of U-S1 were distance from lake (explanatory power q = 0.328) and distance from wind channel (q = 0.168), which were defined as long-distance migration sources. The main driving factors of U-S2 were parent material type (q = 0.269) and distance from Tuotuo river (q = 0.213), which were defined as freeze-thaw sources. The main driving factors of U-S3 were distance from town (q = 0.255) and distance from county road (Yanya Line) (q = 0.221), which were defined as human activity sources. The main drivers of U-S4 were V (q = 0.346) and Sc (q = 0.323), which were defined as natural sources. The GDM results of the 3 models were generally consistent with the analytical results of similar types of sources, especially the results of PMF model and Unmix model can basically verify each other. The research results can provide important theoretical reference for the analysis of HM sources in the soil of high-cold and high-altitude regions.

Abstract Seosan is a concentrated industrial complex in the midwestern region of Korea. A study was conducted from December 2020 to January 2021, measuring PM2.5 and chemical components in Seosan using online instruments every hour. The concentration of PM2.5 during the winter season was 31.4±17.8 μg/m3, exceeding the national ambient air quality standard of Korea. The mass fraction of organic matter, elemental carbon, three major ions, five minor ions, crustal elements, and trace elements in PM2.5 accounted for 24.5%, 4.36%, 32.0%, 2.82%, 4.11%, and 5.17% of the total PM2.5 mass concentration, respectively. Source identification was conducted using positive matrix factorization modeling, revealing eight sources of PM2.5: Secondary inorganic aerosol (SIA), vehicle exhaust, industry, coal combustion, biomass burning/incinerator, oil combustion, soil, and aged sea salt. Source contributions varied during high pollution episodes (HPE), with SIA dominating in HPE1 and soil and aged sea salt in HPE2. The potential source contribution function and conditional probability function were utilized to estimate the potential local and regional emission areas for the identified sources. In Seosan, vehicle exhaust and biomass burning/incinerator were primarily influenced by local sources. SIA, industry, and oil combustion sources were significantly affected by short-range transport from eastern China. Soil and aged sea salt, which exhibited high contributions during HPE2, were associated with long-range transport from Inner Mongolia. Coal combustion was attributed to both local sources, particularly large industrial complexes near Seosan, and long-range transport from Northeast China and Inner Mongolia. Graphical Abstract

Building conditions, outdoor climate, and human behavior influence residential concentrations of fine particulate matter (PM2.5). To study PM2.5 spatiotemporal variability in residences, we acquired paired indoor and outdoor PM2.5 measurements at 3,977 residences across the United States totaling >10,000 monitor-years of time-resolved data (10-min resolution) from the PurpleAir network. Time-series analysis and statistical modeling apportioned residential PM2.5 concentrations to outdoor sources (median residential contribution = 52% of total, coefficient of variation = 69%), episodic indoor emission events such as cooking (28%, CV = 210%) and persistent indoor sources (20%, CV = 112%). Residences in the temperate marine climate zone experienced higher infiltration factors, consistent with expectations for more time with open windows in milder climates. Likewise, for all climate zones, infiltration factors were highest in summer and lowest in winter, decreasing by approximately half in most climate zones. Large outdoor-indoor temperature differences were associated with lower infiltration factors, suggesting particle losses from active filtration occurred during heating and cooling. Absolute contributions from both outdoor and indoor sources increased during wildfire events. Infiltration factors decreased during periods of high outdoor PM2.5, such as during wildfires, reducing potential exposures from outdoor-origin particles but increasing potential exposures to indoor-origin particles. Time-of-day analysis reveals that episodic emission events are most frequent during mealtimes as well as on holidays (Thanksgiving and Christmas), indicating that cooking-related activities are a strong episodic emission source of indoor PM2.5 in monitored residences.

• Water-soluble metal ions were the dominant contributors to the DTT activity in PM 2.5. • Organics contributed more to DTT activity in 2022 than in 2017/2018. • PM 2.5 showed a lower exposure risk and higher intrinsic oxidative toxicity in 2022. • The relative contributions of vehicle emissions, coal/biomass burning, and ship emissions to DTT activity decreased dramatically in 2022. The toxicity of PM 2.5 does not necessarily change synchronously with its mass concentration. In this study, the chemical composition (carbonaceous species, water-soluble ions, and metals) and oxidative potential (dithiothreitol assay, DTT) of PM 2.5 were investigated in 2017/2018 and 2022 in Xiamen, China. The decrease rate of volume-normalized DTT (DTT v) (38%) was lower than that of PM 2.5 (55%) between the two sampling periods. However, the mass-normalized DTT (DTT m) increased by 44%. Clear seasonal patterns with higher levels in winter were found for PM 2.5 , most chemical constituents and DTT v but not for DTT m. The large decrease in DTT activity (84%−92%) after the addition of EDTA suggested that water-soluble metals were the main contributors to DTT in Xiamen. The increased gap between the reconstructed and measured DTT v and the stronger correlations between the reconstructed/measured DTT ratio and carbonaceous species in 2022 were observed. The decrease rates of the hazard index (32.5%) and lifetime cancer risk (9.1%) differed from those of PM 2.5 and DTT v due to their different main contributors. The PMF-MLR model showed that the contributions (nmol/(min·m3)) of vehicle emission, coal + biomass burning, ship emission and secondary aerosol to DTT v in 2022 decreased by 63.0%, 65.2%, 66.5%, and 22.2%, respectively, compared to those in 2017/2018, which was consistent with the emission reduction of vehicle exhaust and coal consumption, the adoption of low-sulfur fuel oil used on board ships and the reduced production of WSOC. However, the contributions of dust + sea salt and industrial emission increased. The change trends of PM 2.5 , DTT activity, non-cancer and cancer risks due to the selected elements (V, Cr(VI), Mn, Ni, As, Se, Cd, Ba, Pb, Mo, Sb, and Co) [Display omitted] [ABSTRACT FROM AUTHOR]

• Average HMs concentration near coking plant was 2.74 times as high as that of remote area. • HPI, NI and CD indices in nearby areas were 0.69 - 40.11 times higher than those in remote areas. • Coal washing and coking emission were the major sources of HMs pollution in this area. • Potential carcinogenic health risks were mainly from pb and ni with CR > 10−6. • Monte Carlo simulation results were in agreement with the calculated results. Coking industry is a potential source of heavy metals (HMs) pollution. However, its impacts to the groundwater of surrounding residential areas have not been well understood. This study investigated the pollution characteristics and health risks of HMs in groundwater nearby a typical coking plant. Nine HMs including Fe, Zn, Mo, As, Cu, Ni, Cr, Pb and Cd were analyzed. The average concentration of total HMs was higher in the nearby area (244.27 µg/L) than that of remote area away the coking plant (89.15 µg/L). The spatial distribution of pollution indices including heavy metal pollution index (HPI), Nemerow index (NI) and contamination degree (CD), all demonstrated higher values at the nearby residential areas, suggesting coking activity could significantly impact the HMs distribution characteristics. Four sources of HMs were identified by Positive Matrix Factorization (PMF) model, which indicated coal washing and coking emission were the dominant sources, accounted for 40.4%, and 31.0%, respectively. Oral ingestion was found to be the dominant exposure pathway with higher exposure dose to children than adults. Hazard quotient (HQ) values were below 1.0, suggesting negligible non-carcinogenic health risks, while potential carcinogenic risks were from Pb and Ni with cancer risk (CR) values > 10−6. Monte Carlo simulation matched well with the calculated results with HMs concentrations to be the most sensitive parameters. This study provides insights into understanding how the industrial coking activities can impact the HMs pollution characteristics in groundwater, thus facilitating the implement of HMs regulation in coking industries. [Display omitted] [ABSTRACT FROM AUTHOR]

VOCs (Volatile organic compounds) exert a vital role in ozone and secondary organic aerosol production, necessitating investigations into their concentration, chemical characteristics, and source apportionment for the effective implementation of measures aimed at preventing and controlling atmospheric pollution. From July to October 2020, online monitoring was conducted in the main urban area of Shijiazhuang to collect data on VOCs and analyze their concentrations and reactivity. Additionally, the PMF (positive matrix factorization) method was utilized to identify the VOCs sources. Results indicated that the TVOCs (total VOCs) concentration was (96.7 ± 63.4 µg/m3), with alkanes exhibiting the highest concentration of (36.1 ± 26.4 µg/m3), followed by OVOCs (16.4 ± 14.4 µg/m3). The key active components were alkenes and aromatics, among which xylene, propylene, toluene, propionaldehyde, acetaldehyde, ethylene, and styrene played crucial roles as reactive species. The sources derived from PMF analysis encompassed vehicle emissions, solvent and coating sources, combustion sources, industrial emissions sources, as well as plant sources, the contribution of which were 37.80%, 27.93%, 16.57%, 15.24%, and 2.46%, respectively. Hence, reducing vehicular exhaust emissions and encouraging neighboring industries to adopt low-volatile organic solvents and coatings should be prioritized to mitigate VOCs levels. [ABSTRACT FROM AUTHOR]