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A computationally inexpensive and data parsimonious direct model for identification of groundwater pollution sources that captures their location, spatial extent and flux intensities at a chosen reference time is presented in this study. The model is based upon instantaneous micro-level mass balance that is depicted by a pseudo steady state solute transport equation. Clusters of polluting locations were identified by finite differencing the solute transport equation and applying K-means clustering algorithm. The model is validated by the problem taken from Singh, Datta, and Jain (2004) and is also illustrated by applying it to an area lying between river Krishni and Hindon. Validation results showed that the model captured closely the pollution source locations; their corresponding spatial extents and flux intensities. Model captured the sources even when the concentration plumes are far away from the source locations due to advection dominated contaminant transport. Illustration results showed that the model identified the leachate flux intensity from irrigation in the form of a regional source. Further, it established a few local sources arising possibly out of localized industrial and/or municipal waste water disposal. [ABSTRACT FROM AUTHOR]

The small muddy areas developed in the southern Shandong Peninsula have attracted increasing attention from researchers because of complex changes in sediment sources driven by sea-level fluctuations and land-sea interactions since the late Pleistocene. This study investigates the evolution of sediment sources and their responses to environmental changes since the late Pleistocene, using core WHZK01 collected from the nearshore muddy area in southern Weihai for rare earth element (REE) analysis. In doing so, this work highlights the changing patterns of material sources and the primary control factors. The results reveal that the sedimentary deposits in core WHZK01 exhibit distinct terrestrial characteristics. Discriminant function analysis (FD) and source discrimination diagrams both suggest that the primary sources of these deposits are the Yellow River and adjacent small and medium-sized rivers, although the sources vary among different sedimentary units. Furthermore, the DU3 layer (17.82–25.10 m) displays typical riverine sedimentation, dominated by terrestrial detrital input, primarily from the local rivers, namely the Huanglei and Muzhu Rivers. The material in the DU2 layer (14.91–17.82 m) is mainly influenced by a mixture of the Qinglong and Yellow Rivers. The DU1 layer (0–14.91 m) is influenced by sea-level changes during the Holocene, with the Yellow River being the primary source, although there is also some input from local rivers. The changes in sea level during the Holocene and the input of Yellow River material carried by the coastal currents of the Yellow Sea are identified as the main controlling factors for the changes in material sources in the study area since the late Pleistocene, with small and medium-sized rivers also exerting some influence on the material sources. The above mentioned findings not only contribute to a better understanding of the source-sink systems of the Yellow River and adjacent small and medium-sized rivers but also deepen our understanding of the late Quaternary land-sea interactions in the Shandong Peninsula. [ABSTRACT FROM AUTHOR]

Per- and polyfluoroalkyl substances (PFASs) are emerging persistent organic pollutants (POPs). In this study, 47 surface sediment samples were collected from the Yellow River Delta wetland (YRDW) to investigate the occurrence, spatial distribution, potential sources, and ecological risks of PFASs. Twenty-three out of 26 targeted PFASs were detected in surface sediment samples from the YRDW, with total ∑23PFASs concentrations ranging from 0.23 to 16.30 ng g−1 dw and a median value of 2.27 ng g−1 dw. Perfluorooctanoic acid (PFOA), perfluorobutanoic acid (PFBA) and perfluorooctanesulfonic acid (PFOS) were the main contaminants. The detection frequency and concentration of perfluoroalkyl carboxylic acids (PFCAs) were higher than those of perfluoroalkanesulfonic acids (PFSAs), while those of long-chain PFASs were higher than those of short-chain PFASs. The emerging PFASs substitutes were dominated by 6:2 chlorinated polyfluoroalkyl ether sulfonic acid (6:2 Cl-PFESA). The distribution of PFASs is significantly influenced by the total organic carbon content in the sediments. The concentration of PFASs seems to be related to human activities, with high concentration levels of PFASs near locations such as beaches and villages. By using a positive matrix factorization model, the potential sources of PFASs in the region were identified as metal plating mist inhibitor and fluoropolymer manufacturing sources, metal plating industry and firefighting foam and textile treatment sources, and food packaging material sources. The risk assessment indicated that PFASs in YRDW sediments do not pose a significant ecological risk to benthic organisms in the region overall, but PFOA and PFOS exert a low to moderate risk at individual stations. [ABSTRACT FROM AUTHOR]

Tracing the origin of information spread in social networks is a crucial yet challenging issue. Different from prior studies largely centered on discrete-time transmission frameworks, this paper fulfills source identification for continuous-time diffusion networks. Specifically, a path-wise continuous-time transmission model is first proposed to unveil the probabilistic dynamic through potential paths, based on which the probability of the incomplete cascade under partial observations can be yielded. Finally, a path-wise continuous-time source identification method (PCSI) is proposed under partial-observation conditions and path-wise modelings. To test it, three synthetic networks and two real networks are selected, with series of experiments conducted to evaluate the influence of observation size and cascade number, as well as its robustness to noises. Experiment results verify that our method is able to achieve obviously better source identification accuracies than the previous studies. [ABSTRACT FROM AUTHOR]

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The identification of groundwater contamination sources (IGCSs) is an important requirement for the remediation and treatment of groundwater contamination. The data assimilation methods such as ensemble Kalman filter (EnKF) and ensemble smoother (ES) have been applied to IGCSs in recent years and obtained good identification results. The unscented kalman filter (UKF) is also a data assimilation method with the potential to simultaneously identify hydraulic conductivity and GCSs. However, when UKF is applied to identify hydraulic conductivity and GCSs, it is necessary to use the observed data at different times separately, which increases the complexity of the update process and this may result in low identification accuracy. ES is a variant of EnKF that updates the system parameters with all observed data in all time periods, which makes ES faster and easier to implement than EnKF. Therefore, inspired by the ES, an unscented kalman smoother (UKS) based on UKF was proposed for simultaneously identifying the hydraulic conductivity and GCSs in this study. The UKS can use the data observed in all time periods simultaneously, while it is also simpler to operate and the calculation speed is faster. Present studies have shown that ES can solve IGCS problems. Thus, ES was also applied to identify the hydraulic conductivity and GCSs in this study, and its identification performance was compared with UKS. In contrast to previous applications of ES to IGCSs, both UKS and ES were set up with stop iteration conditions instead of only performing one update process, and thus both methods applied multiple update processes. The results showed that compared with ES, the identification results obtained by UKS were characterized by greater stability, higher accuracy, and the iterative process required less iteration process and computational time. [ABSTRACT FROM AUTHOR]

Acoustic Emission (AE) testing is a non-destructive evaluation technique that has gained significant attention in pipeline monitoring. Pencil-lead breaks (PLBs) are commonly used in reproducing and characterising sensors used in AE applications and have emerged as a valuable tool for calibration processes. This technique involves breaking a pencil lead by pressing it on the surface of the test structure and applying a bending moment at a given angle on a surface. The applied force produces a local deformation on the test surface, which is released when the lead breaks. The fracture in these PLBs is assumed to be a step unload; however, this is not the case. In this work, a series of PLB source experiments complemented with parallel numerical simulations were carried out to investigate the actual unload rate by correlating the relationship between AE speed, frequency, and power from PLBs. This was achieved by varying the simulation unload rates recorded over a duration of 2 s on a steel pipe and comparing to the experiment. Analysis of the investigated results from the experimental and numerical models suggests that although the AE line structure of a PLB can be reproduced by simulation for short times only (1 µs), the actual unload rate for PLBs is in the region of 10–8 s. It is concluded that FEA has the potential to help in the recovery of the temporal structure from real AE structures. The establishment of this model will provide a theoretical basis for future studies on the monitoring of non-impulsive AE sources such as impact on pipelines using finite element analysis. [ABSTRACT FROM AUTHOR]

The oil industry in Khuzestan province (Southwest Iran) is one of the main reasons contributing to the pollution of the environment in this area. TPH, including both aromatic and aliphatic compounds, are important parameters in creating pollution. The present study aimed to investigate the source of soil contamination by TPH in the Ahvaz oil field in 2022. The soil samples were collected from four oil centers (an oil exploitation unit, an oil desalination unit, an oil rig, and a pump oil center). An area outside the oil field was determined as a control area. Ten samples with three replicates were taken from each area according to the standard methods. Aromatic and aliphatic compounds were measured by HPLC and GC methods. The positive matrix factorization (PMF) model and isomeric ratios were used to determine the source apportionment of aromatic compounds in soil samples. The effects range low and effects range median indices were also used to assess the level of ecological risk of petroleum compounds in the soil samples. The results showed that Benzo.b.fluoranthene had the highest concentration with an average of 5667.7 ug/kg in soil samples in the Ahvaz oil field. The highest average was found in samples from the pump oil center area at 7329.48 ug/kg, while the lowest was found in control samples at 1919.4 ug/kg−1. The highest level of aliphatic components was also found in the pump oil center, with a total of 3649 (mg. Kg−1). The results of source apportionment of petroleum compounds in soil samples showed that oil activities accounted for 51.5% of the measured PAHs in soil. 38.3% of other measured compounds had anthropogenic origins, and only 10.1% of these compounds were of biotic origin. The results of the isomeric ratios also indicated the local petroleum and pyrogenic origin of PAH compounds, which is consistent with the PMF results. The analysis of ecological risk indices resulting from the release of PAHs in the environment showed that, except for fluoranthene, other PAHs in the oil exploitation unit area were above the effects range median level (ERM) and at high risk. The results of the study showed that soil pollution by total petroleum hydrocarbons (TPH), both aromatic and aliphatic, is at a high level, and is mainly caused by human activities, particularly oil activities. [ABSTRACT FROM AUTHOR]

Numerous scholars worldwide have conducted extensive research on the identification of water sources for mine water inflows, among which the utilization of groundwater's chemical properties for water source discrimination is characterized by its rapidity, effectiveness, and economy. In the Gaohe Coal Mine of Shanxi Province, anomalous water discharge has been observed from boreholes in some coal-bearing aquifers. The water quality differs from both coal-bearing aquifer water and Ordovician limestone aquifer water. Analysis of K+, Na+, and SO42- suggests that the water does not belong to coal-bearing aquifer water, while the analysis of Ca2+ indicates it is not Ordovician limestone aquifer water. Particularly, in the 8# Coal-Bearing Aquifer Observation Borehole, the concentration of Ca2+ is extremely low, consistent with coal-bearing aquifer water, yet the concentration of SO42- is extremely high, resembling Ordovician limestone water. This is speculated to be due to Ordovician limestone water replenishing the aquifer where the observation borehole is located, triggering a series of chemical reactions. Using the PHREEQC (Version 2) hydrochemical simulation software, hydrochemical simulation experiments were conducted to model the process of different proportions of Ordovician limestone water entering the coal-bearing aquifer. This study explored the reaction mechanisms between Ordovician limestone water, coal-bearing aquifer water, and coal measure aquifer rock samples, validated the hydrochemical and water–rock interactions occurring during this process, and estimated the proportion of water sources in the anomalous borehole water discharge based on the ion concentration profiles of the simulated mixed water. These findings can be applied to the prevention and control of Ordovician limestone water hazards, especially those caused by water-conducting pathways. [ABSTRACT FROM AUTHOR]

Accurate estimation of pollution sources of industrial wastewater, which is detrimental to the environment and human health, facilitates river quality management. In this study wastewater-specific elements in downstream river water were used to trace back to pollution origin by upstream industry categories. In addition, a sensitivity test is performed on lanthanides to determine the importance of low-concentration elements in the analysis. Over a period of 45 days, water samples are obtained twice daily from a polluted river in southern Taiwan near industrial areas. During the monitoring period, wastewater samples from potential contamination sources are conducted to establish the source profiles. Positive matrix factorization is used to determine the pollution sources from the 31 elements measured in the stream. The results show that heavy metal pollution is primarily caused by wafers and semiconductors (47%), sewage treatment (27%), and electroplating products (12%). The sensitivity test results for lanthanides show that excluding some or all of them renders it impossible to classify pollution sources into the correct industry categories. Because lanthanides are key elements in certain industry categories, they are distinguishing factors in profiles among industries. Therefore, the source profiles of low-concentration lanthanides can aid in identifying pollution sources. [ABSTRACT FROM AUTHOR]

Fifty-one street dust samples were systematically collected from the urban core of Zhengzhou, China, and analyzed for potentially toxic metals. The concentrations of vanadium (V), manganese (Mn), copper (Cu), zinc (Zn), arsenic (As), lead (Pb), and nickel (Ni) in the samples surpassed the background values of the local soil, indicating a notable potential for contamination. Spatially, the traffic area was the most polluted with a total heavy metal concentration of Cu, Zn, As, Pb, and Ni, while the pollution levels were lower in the culture and education area and commercial area with total concentrations of V and Mn. Seasonal variations were discerned in the concentrations of heavy metals, with V, Cu, Zn, and As exhibiting heightened levels during the fall and winter, while Mn, Ni, and Pb reached peaks in the spring season. Zn exhibited the highest mean geo-accumulation index (Igeo) value at 2.247, followed by Cu at 2.019, Pb at 0.961, As at 0.590, Ni at 0.126, Mn at −0.178, and V at −0.359. The potential ecological risk index (RI) in the traffic-intensive area markedly exceeded other functional areas. Health risk assessments showed that children were more vulnerable to heavy metal exposure than adults, particularly through the ingestion pathway. Correlation analysis, principal component analysis (PCA), and cluster analysis (CA) were applied in conjunction with the spatial–temporal concentration patterns across various functional areas to ascertain the plausible sources of heavy metal pollutants. The results indicated that heavy metals in the urban street dust of Zhengzhou were multifaceted, stemming from natural processes and diverse anthropogenic activities such as coal burning, industrial emissions, traffic, and construction operations. [ABSTRACT FROM AUTHOR]

İzmir, Turkey’s third most populous city, is in an important position in terms of both agriculture and industry. The province, which contributes 9.3% to the country’s industrial production, also has an important potential in terms of olive cultivation. However, until now, no research has been undertaken to analyze the content of trace elements (TEs) in the soil of olive orchards in İzmir. This study was carried out to determine the pollution level and ecological risks of TEs in the olive orchards soils of İzmir province, to reveal their potential sources and to evaluate their health risks. Among the TEs, the average content of only Ni (37.9 mg/kg) exceeded the world soil average content (29 mg/kg), while the average content of only Cd (0.176 mg/kg) exceeded the upper continental crust content (0.09 mg/kg). Enrichment factor revealed that there was significant enrichment for Cd in 73.6%, Ni in 11.6% and Cr in 5.4% of olive orchards, respectively, due to polluted irrigation water and agrochemicals. Similarly, ecological risk factor indicated that there were moderate and considerable ecological risks for Cd in 48.8% and 23.3% of olive orchards, respectively. Absolute principal component scores-multiple linear regression (APCS-MLR) model showed that Ni and Cr in the study area are affected by agricultural sources, Al, Co, Cu, Fe, Mn, Pb and Zn originate from lithogenic sources, and Cd originates from mixed sources. Based on health risk evaluation methods, non-carcinogenic and carcinogenic effects would not be expected for residents. This study provides significant knowledge for evaluating soil TE pollution in olive orchards and serves a model for source apportionment and human health risk evaluation of TEs in other agricultural regions. [ABSTRACT FROM AUTHOR]

Previous studies have investigated the major sources and health risks associated with atmospheric volatile organic compounds (VOCs). However, the spatial variability of the impact of their emission sources on health risks has rarely been studied. In this study, passive air sampling of VOCs was conducted at 24 sites in Ulsan, the largest industrial city in South Korea. Toluene exhibited the highest time-averaged concentration (6.37 µg/m3), followed by m,p,o-xylenes (4.69 µg/m3), ethyl acetate (3.26 µg/m3), and ethylbenzene (2.70 µg/m3). Higher concentrations of total (Σ59) VOCs and BTEX (benzene, toluene, ethylbenzene, and m,p,o-xylenes) were observed near industrial complexes. The mean cumulative (Σ11) cancer risk was 9.1E-6, with the highest contribution from benzene (4.7E-6), while the mean cumulative (Σ17) non-cancer risk was 2.6E-1, primarily driven by naphthalene (1.7E-1), suggesting the importance of carcinogenic VOCs. Five major sources were identified using the positive matrix factorization model, revealing the dominance of industrial activities. Both cancer and non-cancer risks were elevated in the petrochemical industrial complex, which is located close to densely populated areas. Consequently, prioritized management of VOC exposure to workers and residents is necessary for the petrochemical industrial complex and nearby residential areas. [ABSTRACT FROM AUTHOR]

Variation in emitted particle sizes between sources offers potential for source identification. Seven thousand two hundred particle size distributions collected in a single-family home were categorized into four classes: (1) smoking, (2) cooking, (3) household cleaning, and (4) background (no source). We created a multi-class classifier (neural network) to predict the presence of these three source types and background air. Number, surface, and volume concentration profiles (each with 16 particle size bins from 0.3 to 10 µm) were used as input features. Surface or volume concentration profiles were better predictors than number concentration profiles; accuracy was highest when concatenating the number, surface, and volume profiles (48 features). The model achieved ~ 98% accuracy in predicting the four classes when using a 10-unit hidden layer for the 48 input features (compared to ~ 66% for multinomial logistic regression). Smoking has the highest F-score among the four classes (0.999). We applied the model to time series of size-resolved concentrations for three successive indoor particle emissions (pan frying food, sweeping the floor, and smoldering marijuana). Time-varying probabilities of the four classes were visualized. We examined the effects of source, space, ventilation, and temperature/relative humidity on source identification. Using training examples from the single-family home, the model reasonably predicted smoking in another residence under different indoor settings (accuracies > 96%). This study applied, for the first time, the neural network method to identify patterns across different particle size distribution types (number, surface, and volume). It demonstrates the potential of using machine learning for source recognition of transient indoor aerosol emissions (e.g., identifying smoking in a rental property). [ABSTRACT FROM AUTHOR]

Excessive dense nonaqueous phase liquids (DNAPLs) in subsurface aquifers posed a threat to human health and sustainable development of groundwater resources. Accurately identifying the sources of DNAPLs is crucial for groundwater remediation and prevention efforts. In the previous studies, significant advances were made in using isotope techniques for identifying DNAPLs in groundwater. In this paper, we provide a comprehensive overview of the commonly used isotopic tools applied to source identification. This overview will outline the advantages and limitations of the isotope technique and describe the needs for future research. Isotope tracing techniques are based on the unique isotopic characteristics of DNAPLs from different sources, enabling the identification and differentiation of DNAPL sources. The δ13C and δ37Cl values are most commonly used for identifying DNAPLs in groundwater. In field applications, however, the differences in isotopic characteristics from diverse sources can be weakened after undergoing a series of human and natural factors, which can affect the accuracy of source identification. To improve the accuracy of DNAPL source identification, a dual-isotope tracing approach seems the best available solution. Nonetheless, in the face of complex polluted environments, the dual-isotope method seems stretched. Therefore, further researches remain to be carried out to accurately and efficiently assess the sources of DNAPLs in groundwater and their individual contributions. This is a prerequisite for groundwater resource conservation and remediation efforts. [ABSTRACT FROM AUTHOR]

Potentially toxic elements (PTEs), especially arsenic in drinking water, pose significant global health risks, including cancer. This study evaluates the groundwater quality in Giresun province on the Black Sea coast of Türkiye by analyzing twelve groundwater resources. The mean concentrations of macronutrients (mg/L) were: Ca (10.53 ± 6.63), Na (6.81 ± 3.47), Mg (3.39 ± 2.27), and K (2.05 ± 1.10). The mean levels of PTEs (µg/L) were: Al (40.02 ± 15.45), Fe (17.65 ± 14.35), Zn (5.63 ± 2.59), V (4.74 ± 5.85), Cu (1.57 ± 0.81), Mn (1.02 ± 0.76), As (0.93 ± 0.73), Cr (0.75 ± 0.57), Ni (0.41 ± 0.18), Pb (0.36 ± 0.23), and Cd (0.10 ± 0.05). All PTE levels complied with WHO drinking water safety guidelines, and overall water quality was excellent. The heavy metal evaluation index (HEI < 10) and heavy metal pollution index (HPI < 45) indicate low pollution levels across all stations. Irrigation water quality was largely adequate, as shown by the magnesium hazard (MH), sodium adsorption ratio (SAR), Na%, and Kelly's ratio (KR). The total hazard index (THI) values consistently remained below 1, indicating no non-carcinogenic health risks. However, at station 10 (city center), the cancer risk (CR) for adults due to arsenic was slightly above the threshold (1.44E-04). Using principal component analysis (PCA), positive matrix factorization (PMF), and geographic information system (GIS) mapping, the study determined that most PTEs originated from natural geological formations or a combination of natural and human sources, with minimal impact from human activities. These findings highlight the safety and reliability of the groundwater sources studied, emphasizing their potential as a long-term, safe water supply for nearby populations. [ABSTRACT FROM AUTHOR]

Identifying the source of an oil spill is an essential step in environmental forensics. The Bayesian approach allows to estimate the source parameters of an oil spill from available observations. Sampling the posterior distribution, however, can be computationally prohibitive unless the forward model is replaced by an inexpensive surrogate. Yet the construction of globally accurate surrogates can be challenging when the forward model exhibits strong nonlinear variations. We present an iterative data-driven algorithm for the construction of polynomial chaos surrogates whose accuracy is localized in regions of high posterior probability. Two synthetic oil spill experiments, in which the construction of prior-based surrogates is not feasible, are conducted to assess the performance of the proposed algorithm in estimating five source parameters. The algorithm successfully provided a good approximation of the posterior distribution and accelerated the estimation of the oil spill source parameters and their uncertainties by an order of 100 folds. [ABSTRACT FROM AUTHOR]

Rockfall poses a formidable threat to the ongoing fast-paced construction of large-scale projects in uninhabited areas in high mountain valleys. In this study, an optimization method for arranging passive nets on high and steep slopes was presented to mitigate the threat from rockfalls. This method diverges from the conventional method of subjectively arranging passive nets along the perimeter of protected regions (due to its emphasis on cost considerations), in which the quantitative appraisal of rockfall movement characteristics and interception rates is frequently omitted, consequently failing to comprehensively ensure transportation routes and temporary construction sites. The methodology encompasses the acquisition of terrain data by unmanned aerial vehicles (UAVs), identification of rockfall sources based on UAV point clouds, quantitative assessment of rockfall hazards using a 3D probabilistic model, and optimization of the layout of passive nets based on the assessment results. The aim of the optimization of passive nets is to quantitatively assess the cost–effect relationship of passive nets, accounting for construction feasibility, interception potential, and likelihood of successful rockfall interception. We applied this method to the Feishuiyan slope in southwest China as an example, and the results demonstrated an enhanced interception rate of 99% and cost reduction by a factor of three relative to the original scheme. This innovative approach could enhance rockfall mitigation in high and steep areas, providing a viable strategy for future prevention efforts in these areas. [ABSTRACT FROM AUTHOR]

Ambient particulate matter (PM10) and its chemical composition in polycyclic aromatic hydrocarbons (PAHs) were studied in areas of specific interest, between September 2015 and July 2016. The principal aim of this study was to assess the different PAH source profiles in each area, as well as their potential health risk. In particular, the studied areas were (a) the semiurban industrialized zone of the Municipality of Peloponnese (Meligalas, Messini) of Messinia prefecture, due to the intensive olive-productive activity in the extensive area, (b) the industrialized zone of Oinofyta in Voiotia prefecture, and (c) the urban/traffic center of Athens (Aristotelous). Intense spatial and seasonal variations in PAH levels were observed among the study areas collectively, but also for each one individually. During the winter period, the total PAHs average concentration was 11.45 and 9.84 ng/m3 at Meligalas–Skala (S1, S2 stations), 8.84 ng/m3 at Messini (S3 station), and 6.30 ng/m3 at the center of Athens (Aristotelous). During the summer campaign, the corresponding levels were 0.99, 1.20, and 0.70 ng/m3 (S1, S2, and S3 stations), and 5.84 ng/m3 (Aristotelous), respectively. The highest potential cancer risk of the PAHs mixture was estimated based on winter season measurements taken at the Municipality of Peloponnese. In order to determine PAH sources, two different source apportionment techniques were applied, i.e., diagnostic ratios (DRs) and the positive matrix factorization (PMF) model. [ABSTRACT FROM AUTHOR]

Illicit discharges into sewer systems are a widespread concern within China's urban drainage management. They can result in unforeseen environmental contamination and deterioration in the performance of wastewater treatment plants. Consequently, pinpointing the origin of unauthorized discharges in the sewer network is crucial. This study aims to evaluate an integrative method that employs numerical modeling and statistical analysis to determine the locations and characteristics of illicit discharges. The Storm Water Management Model (SWMM) was employed to track water quality variations within the sewer network and examine the concentration profiles of exogenous pollutants under a range of scenarios. The identification technique employed Bayesian inference fused with the Markov chain Monte Carlo sampling method, enabling the estimation of probability distributions for the position of the suspected source, the discharge magnitude, and the commencement of the event. Specifically, the cases involving continuous release and multiple sources were examined. For single-point source identification, where all three parameters are unknown, concentration profiles from two monitoring sites in the path of pollutant transport and dispersion are necessary and sufficient to characterize the pollution source. For the identification of multiple sources, the proposed SWMM-Bayesian strategy with improved sampling is applied, which significantly improves the accuracy. HIGHLIGHTS Identifying pollution sources can be applied for both instantaneous and continuous discharge scenarios.; To characterize a single pollution source, data from two monitoring sites along the pollutant's path are necessary and sufficient.; The strategic placement of monitoring sites and improved sampling enhance the effectiveness and precision of the Bayesian-SWMM approach for identifying multiple unauthorized discharge sources.;

Efficient control of heavy metal pollution necessitates a comprehensive understanding of pollutant sources. In this study, we conducted a thorough investigation of 11 metals in the soil of an electronic waste (e-waste) recycling facility in South China. The sources of these metals were determined through a combination of statistical analysis and the UNMIX model. Despite government intervention, our findings reveal significant pollution of nickel, copper, zinc, cadmium, and lead in the study area. Primary contributors to heavy metal contamination in the soil were identified as demolition activities, transport emissions, and atmospheric deposition. Utilizing a source risk assessment model, we observed that children face higher noncarcinogenic and carcinogenic risks compared to adults. Remarkably, the total hazard index of the study area was found to be considerably lower than that of other e-waste dismantling cities. Moreover, the total carcinogenic risk was noted to be one order of magnitude lower than both other e-waste dismantling cities and industrial and mining cities. While acknowledging the government's commendable achievements in the standardized management of e-waste dismantling activities, our study underscores the need for targeted measures to further reduce pollution and safeguard the health of residents. These results emphasize the importance of ongoing efforts to enhance environmental protection strategies and underscore the significance of tailored interventions for sustainable pollution control in e-waste recycling facilities. [ABSTRACT FROM AUTHOR]

Bioavailable heavy metal and their efficient phytoremediation in mining areas have major implications for environmental and human health. In this study, we investigated 12 dominant plants in a typical Mn ore area of Zunyi, Guizhou Province, China, to determine the heavy metal contents, morphologies, and environmental factors affecting Mn, Cd, Pb, Cu, Zn, and Cr in the plant parts and rhizosphere soil. The bioavailabilities and degrees of metals were evaluated using the ratios of the secondary to primary phase distributions and potential ecological risk indices. Principal component analysis, cluster analysis, positive matrix factorisation modelling, and redundancy analysis were used to trace the origins and correlations among the metals. The results indicate that the bioavailabilities were the highest for Mn and Cd in the study area, and all of the target heavy metals had bioavailabilities above the moderate ecological harm level. Statistical modelling indicates that there are four main pollution sources: mining, smelting, processing operations, and atmospheric deposition. The dominant plants had high heavy metal enrichments, bioconcentration factors, and translocation factors for Mn, Cu, Cr, Cd, and Zn. The redundancy analysis indicates that soil total N, total P, and pH affect metal absorption and distributions in Compositae and non-Compositae plants in low-N, low-P, and slightly alkaline mining environments. This study provides a feasible basis for the screening of heavy metal enrichment plants and the improvement of remediation technology in manganese ore area under the extreme environment of poor nutrition. [ABSTRACT FROM AUTHOR]

Acoustic Emission (AE) testing is a non-destructive evaluation technique that has gained significant attention in pipeline monitoring. Pencil-lead breaks (PLBs) are commonly used in reproducing and characterising sensors used in AE applications and have emerged as a valuable tool for calibration processes. This technique involves breaking a pencil lead by pressing it on the surface of the test structure and applying a bending moment at a given angle on a surface. The applied force produces a local deformation on the test surface, which is released when the lead breaks. The fracture in these PLBs is assumed to be a step unload; however, this is not the case. In this work, a series of PLB source experiments complemented with parallel numerical simulations were carried out to investigate the actual unload rate by correlating the relationship between AE speed, frequency, and power from PLBs. This was achieved by varying the simulation unload rates recorded over a duration of 2 s on a steel pipe and comparing to the experiment. Analysis of the investigated results from the experimental and numerical models suggests that although the AE line structure of a PLB can be reproduced by simulation for short times only (1 µs), the actual unload rate for PLBs is in the region of 10–8 s. It is concluded that FEA has the potential to help in the recovery of the temporal structure from real AE structures. The establishment of this model will provide a theoretical basis for future studies on the monitoring of non-impulsive AE sources such as impact on pipelines using finite element analysis.

Abstract Background Floods, especially flash floods, are the major transporting agent for fluvial sediments, whose pollution is a global concern. As floods result in the dispersion of and exposure to these sediments, a profound understanding of sedimentary dynamics during flood events and the related pollutant dispersion is of relevance. However, the characteristics of extreme flood events concerning pollutant dynamics are insufficiently known so far. Results In a Central European catchment impacted by intense industrial activities and former mining, over the course of five years, we surveyed six high-discharge events, five of them approx. bankfull discharge and one major flash flood event, supplemented by sampling of bank sediments. Fluvial sediments were analyzed for elemental composition by X-Ray fluorescence and for grain size distribution of the fine faction by laser diffraction. By applying a local enrichment factor, trace metal(loid) signatures in these sample sets were compared. Furthermore, Positive Matrix Factorization was used to investigate the trace metal(loid)s’ sources. The sediments deposited by minor flooding had continual trace metal(loid) signatures. However, for the extreme event, significant divergencies arose and persisted for the following years: The enrichment of anthropogenically influenced elements increased, with a slowly decreasing trend in the subsequent two years. Naturally dominated metal(oid)s decrease in enrichment without indicating a return to original levels. In contrast, other elements were insensitive to the extreme event. Positive Matrix Factorization identified anthropogenic influences in elements originating from copper and lead processing and mining activities. Furthermore, bed sediments and a natural background factor were found to dominate the non-anthropogenically influenced metal(loid)s. Conclusions In between extreme events, winnowing processes slowly alter the elemental composition of bed sediments. The depletion of such sediments due to the flash flood proves catchment-wide flushing, which induces a natural resetting of the geochemical signals. This ability to renew is an integral part of resilience in fluvial systems. This mechanism is disturbed by industrial activities in floodplains. The exceptional flooding reaches infrastructure that is assumed to be safe and, therefore, unprotected. These additional sources can shift flood sediments’ trace metal(loid) signature, which has a long-lasting impact on the catchment sediments. However, the modifications depend on the flooding extent, possible emitters, and protection measures.

Abstract The contamination and quantification of soil potentially toxic elements (PTEs) contamination sources and the determination of driving factors are the premise of soil contamination control. In our study, 788 soil samples from the National Agricultural Park in Chengdu, Sichuan Province were used to evaluate the contamination degree of soil PTEs by pollution factors and pollution load index. The source identification of soil PTEs was performed using positive matrix decomposition (PMF), edge analysis (UNMIX) and absolute principal component score-multiple line regression (APCS-MLR). The geo-detector method (GDM) was used to analysis drivers of soil PTEs pollution sources to help interpret pollution sources derived from receptor models. Result shows that soil Cu, Pb, Zn, Cr, Ni, Cd, As and Hg average content were 35.2, 32.3, 108.9, 91.9, 37.1, 0.22, 9.76 and 0.15 mg/kg in this study area. Except for As, all are higher than the corresponding soil background values in Sichuan Province. The best performance of APCS-MLR was determined by comparison, and APCS-MLR was considered as the preferred receptor model for soil PTEs source distribution in the study area. ACPS-MLR results showed that 82.70% of Cu, 61.6% of Pb, 75.3% of Zn, 91.9% of Cr and 89.4% of Ni came from traffic-industrial emission sources, 60.9% of Hg came from domestic-transportation emission sources, 57.7% of Cd came from agricultural sources, and 89.5% of As came from natural sources. The GDM results showed that distance from first grade highway, population, land utilization and total potassium (TK) content were the main driving factors affecting these four sources, with q values of 0.064, 0.048, 0.069 and 0.058, respectively. The results can provide reference for reducing PTEs contamination in farmland soil.

Soil in urban and industrial areas is one of the main sinks of pollutants. It is well known that there is a strong link between metal(loid)s bioaccessibility by inhalation pathway and human health. The critical size fraction is < 10 μm (inhalable fraction) since these particles can approach to the tracheobronchial region. Here, soil samples (< 10 μm) from a highly urbanized area and an industrialized city were characterized by combining magnetic measurements, bioaccessibility of metal(loids) and Pb isotope analyses. Thermomagnetic analysis indicated that the main magnetic mineral is impure magnetite. In vitro inhalation analysis showed that Cd, Mn, Pb and Zn were the elements with the highest bioaccessibility rates (%) for both settings. Anthropogenic sources that are responsible for Pb accumulation in < 10 μm fraction are traffic emissions for the highly urbanized environment, and Pb related to steel emissions and coal combustion in cement plant for the industrial setting. We did not establish differences in the Pb isotope composition between pseudo-total and bioaccessible Pb. The health risk assessment via the inhalation pathway showed limited non-carcinogenic risks for adults and children. The calculated risks based on pseudo-total and lung bioaccessible concentrations were identical for the two areas of contrasting anthropogenic pressures. Carcinogenic risks were under the threshold levels (CR < 10–4), with Ni being the dominant contributor to risk. This research contributes valuable insights into the lung bioaccessibility of metal(loids) in urban and industrial soils, incorporating advanced analytical techniques and health risk assessments for a comprehensive understanding. [ABSTRACT FROM AUTHOR]

Polycyclic aromatic hydrocarbons （PAHs） mainly from the incomplete combustion of organic materials, and are bioaccumulative and toxic（carcinogenic, teratogenic and mutagenic）, are a kind of persistent toxic substance. This paper reviews the classification, emission characteristics, temporal and spatial distribution characteristics, source analysis and health risk assessment of atmospheric PAHs, and lists the ways of classifying PAHs according to different molecular weight, existence form and chemical structure. It is pointed out that PAHs concentration presents seasonal variation, and the variation trend is from high to low: winter, spring, autumn and summer. The advantages and disadvantages of molecular diagnostic ratio （DRs） and receptor models, including principal component analysis（PCA）, chemical mass balance（CMB）, positive matrix factorization （PMF）and Unmix were compared. Source analysis shows that DRs and PCA are the most widely used methods, but the accuracy of source analysis results is affected by many factors. The combination of PMF and Unmix to resolve PAHs sources can assign sources based solely on measured concentrations at the receptor site, providing a time series of PAHs source contributions and making up for the limitations that require human interpretation. This paper shows how the incremental lifetime cancer risk （ILCR）model can be used to assign sources of PAHs to assess health risk, and identify key factors that affect the accuracy of ILCR. We hope this review can provide reference for further research on atmospheric PAHs pollution. [ABSTRACT FROM AUTHOR]

Noise pollution is the most serious environmental pollution, which seriously affects people's normal life and physical and mental health, as well as normal production work. Therefore, noise control is necessary, but before noise control, the first thing to do is to identify the location of the noise source, and the noise control work is meaningless when the noise cannot be identified. Flat plate structures are a fundamental part of complex ship structures, and their vibration, noise, and their interrelationships when excited by the outside world are receiving increasing attention. The core of the research in this paper is the identification of the sound source of the vibrating plate. A method combining phase conjugation with interior boundary element method is developed for the identification of the pressure and normal velocity distribution of a vibrating plate. An interior problem is formed by enclosing the phase conjugation array plane and the plate surface. The pressures at the array elements are phase-conjugated as the specified pressure boundary condition. The impedance relationship between the surface pressure and the surface normal velocity of the plate is utilized as a specified impedance boundary condition. The interior boundary element method is applied to solve the interior problem. The identification of the surface pressure and normal velocity distribution is studied numerically. The numerical results show that with the array located in the near field the proposed method achieves subwavelength focusing to identify the surface pressure and normal velocity distribution and clearly shows the response shapes. [ABSTRACT FROM AUTHOR]

[Objective) Based on the main input source of soil heavy metals pollution idenfitication and screening the most efficient immobilizing agent and low accumulation varieties of vegetable and rice for Cd contaminated soil, the study aimed to provide a reference for farmland soil heavy mtal pollution preventing and control. (Method) The expreriment was conducted to monitor heavy metals concentrations in atmospheric deposition, fertilizer, irrigation water and sediment and further calculated soil heavy metals input flux by these different pathways to find out the pollution source of soil heavy metals in some towns in Junlian county of Yibin, which was in the south of Sichuan province. Further field experiments were conducted to screen vegetables and rice varieties with lowest accumulation of Cd and the most efficient immobilizing agents in JL town. [Result] Hg, As, Pb and Zn in soil mainly came from atmospheric deposition, accounting for 99.99%, 75.88%, 90.57% and 84.82%, respectively. While Cd, Cr and Ni mainly came from fertilizer use, all accounting for 100%. Cu was mainly from irrigation water in the study area during 2019 to 2020, accounting for 93.66%. The application of iron manganese fertilizer (FeSO4 750 kg/ hm² + MnSO4 75 kg/hm²) had the best effect on reducing the Cd content in rice grains, mainly attributed to the improvement of soil microelement supplement on fertility, while the passivation material compounding (3000 kg/hm²) had the highest Cd content in rice grains. The screening results of low Cd accumulation of vegetables and rice varieties showed that Jiujing radish and Chuankangyou 6276 were the most suitable vegetable and rice varieties for planting in the Cd polluted soil in JL. town with the Cd content in edible parts after harvest met the national food safety standard. Conclusion] To ensure the quality and safety of crops, selecting fertilizers that meet national standards and con- trolling atmospheric decomposition are primary step. Besides the iron manganese fertilizer, humic acid and phosphorus fertilizer passivation agents are suggested to be used, and Jiujing radish and Chuankangyou 6276 varieties are recommended to be planted in the study area. [ABSTRACT FROM AUTHOR]

This research investigated the contamination characteristics, sources, and health risks of five metals in soils from two villages named DK and SXC, downstream from a battery industry hub in Xinxiang city, Henan Province, China. The average concentrations of Cd, Pb, Ni, Cu, and Zn in DK were 5.93, 41.31, 71.40, 62.20, and 115.83 mg/kg, respectively, and in SXC were 2.04, 30.41, 41.22, 36.18, and 96.04 mg/kg, respectively. The single factor pollution index (Pi) revealed a consistent descending order of Cd > Cu > Zn > Ni > Pb in DK and SXC. The geo-accumulation index (Igeo) indicated that the Cd pollution in DK was extreme, and in SXC was at a heavy to extreme level. The potential ecological risk index (PERI) indicated that Cd presented a significantly high ecological risk while it was low for other metals. Principal component analysis classified them into the anthropogenic origin of Cd and common mixed origin of others. The elevated levels and pollution load of heavy metals with closer proximity to the battery factory imply that the factory is a probable source of contamination. Overall, the health risks posed by heavy metals were more pronounced for local children compared to adults, with Cd being the primary contributor to both pollution and health risks. This investigation provides a crucial basis for the heavy metal pollution management and related risk prevention in areas affected by electronic waste irrigation. [ABSTRACT FROM AUTHOR]

Background: Floods, especially flash floods, are the major transporting agent for fluvial sediments, whose pollution is a global concern. As floods result in the dispersion of and exposure to these sediments, a profound understanding of sedimentary dynamics during flood events and the related pollutant dispersion is of relevance. However, the characteristics of extreme flood events concerning pollutant dynamics are insufficiently known so far. Results: In a Central European catchment impacted by intense industrial activities and former mining, over the course of five years, we surveyed six high-discharge events, five of them approx. bankfull discharge and one major flash flood event, supplemented by sampling of bank sediments. Fluvial sediments were analyzed for elemental composition by X-Ray fluorescence and for grain size distribution of the fine faction by laser diffraction. By applying a local enrichment factor, trace metal(loid) signatures in these sample sets were compared. Furthermore, Positive Matrix Factorization was used to investigate the trace metal(loid)s' sources. The sediments deposited by minor flooding had continual trace metal(loid) signatures. However, for the extreme event, significant divergencies arose and persisted for the following years: The enrichment of anthropogenically influenced elements increased, with a slowly decreasing trend in the subsequent two years. Naturally dominated metal(oid)s decrease in enrichment without indicating a return to original levels. In contrast, other elements were insensitive to the extreme event. Positive Matrix Factorization identified anthropogenic influences in elements originating from copper and lead processing and mining activities. Furthermore, bed sediments and a natural background factor were found to dominate the non-anthropogenically influenced metal(loid)s. Conclusions: In between extreme events, winnowing processes slowly alter the elemental composition of bed sediments. The depletion of such sediments due to the flash flood proves catchment-wide flushing, which induces a natural resetting of the geochemical signals. This ability to renew is an integral part of resilience in fluvial systems. This mechanism is disturbed by industrial activities in floodplains. The exceptional flooding reaches infrastructure that is assumed to be safe and, therefore, unprotected. These additional sources can shift flood sediments' trace metal(loid) signature, which has a long-lasting impact on the catchment sediments. However, the modifications depend on the flooding extent, possible emitters, and protection measures. [ABSTRACT FROM AUTHOR]

The stable nitrogen isotopic composition (δ15N) has been widely used to quantify sources of ammonium (NH4+) in PM2.5. However, the overlap and uncertainty in δ15N values from different NH3 sources, coupled with their seasonal variability, hinder accurate identification of NH4+ source. Here, the δ15N values of various NH3 source samples collected by the active sampler were determined. Subsequently, we measured the δ15N values of NH4+ in PM2.5, which were collected seasonally in Tianjin. We found that the combustion‐related NH3 (c‐NH3) exhibiting higher δ15N values compared to volatile NH3 (v‐NH3), but all δ15N values was fell within the range reported by previous studies. Furthermore, inconsistent seasonal variations were observed in the δ15N‐NH3 values originating from emissions of agricultural soil and human excreta. The application of the Bayesian isotope mixing model (MixSIAR model) revealed a significant increase in the contribution of v‐NH3 to NH4+ when incorporating current source data, as opposed to previous data, for δ15N of NH3 source. Notably, the contribution of v‐NH3 (53.1%) to NH4+ was almost equivalent to that of c‐NH3 (46.9%) when considering the seasonal δ15N signatures of NH3 source. Additionally, the estimated contribution of v‐NH3 to NH4+ exhibited significant seasonal variability, which is more reasonable than in the non‐seasonal scenario. This study demonstrated that v‐NH3 and c‐NH3 contributed to NH4+ in PM2.5 in Tianjin almost equally, and it is highlighted that the seasonal δ15N values of NH3 sources should be considered when estimating the contributions of different NH3 sources to NH4+ in PM2.5 by the MixSIAR model. Plain Language Summary: Quantifying the source of NH4+ in PM2.5 through δ15N remains disputed, one possible reason was the uncertainty in δ15N values of NH3 sources. This study investigated the δ15N values from different NH3 sources collected by the active sampler, of which the δ15N‐NH3 from agricultural soils and human excreta emissions were characterized by season. Furthermore, we measured the δ15N values of NH4+ in PM2.5 collected seasonally in Tianjin to estimate the source contribution of NH4+ based on the MixSIAR model. Results found that a reasonable source‐resolved structure of NH4+ and their seasonal variations was obtained by the MixSIAR model using the seasonal δ15N data of NH3 source in this study. Specially, the contribution of c‐NH3 was significant overestimated when used the δ15N data of NH3 source from previous studies. Moreover, the estimated contribution of v‐NH3 to NH4+ exhibited significant seasonal variability, which is more reasonable than in the non‐seasonal scenario. These findings showed that the seasonal δ15N values of NH3 sources should be considered when estimating the contributions of different NH3 sources to NH4+ in PM2.5 using the MixSIAR model. Key Points: The δ15N values of six typical NH3 sources was systematically established using the active sampling methodThe δ15N‐NH3 values originating from agricultural soil and human excreta exhibit inconsistent seasonal variationsConsidering the seasonal δ15N variation in NH3 sources may obtained a reasonable seasonal source‐resolved structure of NH4+ [ABSTRACT FROM AUTHOR]

The contamination and quantification of soil potentially toxic elements (PTEs) contamination sources and the determination of driving factors are the premise of soil contamination control. In our study, 788 soil samples from the National Agricultural Park in Chengdu, Sichuan Province were used to evaluate the contamination degree of soil PTEs by pollution factors and pollution load index. The source identification of soil PTEs was performed using positive matrix decomposition (PMF), edge analysis (UNMIX) and absolute principal component score-multiple line regression (APCS-MLR). The geo-detector method (GDM) was used to analysis drivers of soil PTEs pollution sources to help interpret pollution sources derived from receptor models. Result shows that soil Cu, Pb, Zn, Cr, Ni, Cd, As and Hg average content were 35.2, 32.3, 108.9, 91.9, 37.1, 0.22, 9.76 and 0.15 mg/kg in this study area. Except for As, all are higher than the corresponding soil background values in Sichuan Province. The best performance of APCS-MLR was determined by comparison, and APCS-MLR was considered as the preferred receptor model for soil PTEs source distribution in the study area. ACPS-MLR results showed that 82.70% of Cu, 61.6% of Pb, 75.3% of Zn, 91.9% of Cr and 89.4% of Ni came from traffic-industrial emission sources, 60.9% of Hg came from domestic-transportation emission sources, 57.7% of Cd came from agricultural sources, and 89.5% of As came from natural sources. The GDM results showed that distance from first grade highway, population, land utilization and total potassium (TK) content were the main driving factors affecting these four sources, with q values of 0.064, 0.048, 0.069 and 0.058, respectively. The results can provide reference for reducing PTEs contamination in farmland soil. [ABSTRACT FROM AUTHOR]

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To explore the contamination status and identify the source of the heavy metals in the sediments in the major inflow rivers of Dianchi Lake in China, sediment samples were collected and analyzed. Specifically, the distribution, source, water quality, and health risk assessment of the heavy metals were analyzed using correlation analysis (CA), principal component analysis (PCA), the heavy metal contamination factor (Cf), the pollution load index (PLI), and the potential ecological risk index (PERI). Additionally, the chemical fractions were analyzed for mobility characteristics. The results indicate that the average concentration of the heavy metals in the sediment ranked in the descending order of Zn > Cr > Cu > Pb > As > Ni > Cd > Hg, and most of the elements existed in less-mobile forms. The Cfwas in the order of Hg > Zn > Cd > As > Pb > Cr > Ni; the accumulation of Hg, Zn, Cd, and As was obvious. Although the spatial variability of the heavy metal contents was pronounced, the synthetical evaluation index of the PLI and PERI both reached a high pollution level. The PCA and CA results indicate that industrial, transportation, and agricultural emissions were the dominant factors causing heavy metal pollution. These results provide important data for improving water resource management efficiency and heavy metal pollution prevention in Dianchi Lake. [ABSTRACT FROM AUTHOR]

Study region: The Seohwa watershed, South Korea. Study focus: Agricultural practices and urbanization in watersheds increase nutrient loads (total nitrogen (TN), total phosphorus (TP), and nitrate-nitrogen (NO3--N)) in streams and deteriorate water quality. Between October 2017 and October 2018, water samples were collected from a small stream (MS), main tributary (TS), and sub-tributaries (ST) characterized by different land-use patterns. The objective of this study was to identify the sources that determine water quality in the respective streams and to estimate whether water quality was dependent on land-use patterns. New hydrological insights for the region: TN in MS progressively decreased downstream, whereas such spatial variation was not observed in TS and ST. For TP, TS and ST samples showed elevated concentrations during storm events, but not in MS. These observations resulted from TN and TP derived from natural and anthropogenic sources associated with land-use patterns. Interestingly, TN/TP ratios were strongly negatively correlated with the proportion of residential area (R2 = 0.92) rather than other land-use patterns such as agricultural area and forest. In addition, statistical analysis and dual isotopes of nitrate (NO3-) showed that the water quality in MS and the one in TS and ST were predominantly affected by natural sources and anthropogenic sources, respectively. Considering the effects of land-use patterns and rainfall on water quality, anthropogenic sources should be precisely identified to manage stream water in small watersheds more effectively.

We study a source identification boundary value problem for a parabolic partial differential equation with multi-point Neumann type boundary condition. Stability estimates for the solution of the overdetermined mixed BVP for multi-dimensional parabolic equation were established. The first and second order of accuracy difference schemes for the approximate solution of this problem were proposed. Stability estimates for both difference schemes were obtained. The result of numerical illustration in test example was given.

The accumulation of toxic elements from sediments poses imminent threats to both the environment and humans. The variation of elements in different sedimentary systems within the same watershed is of significant importance for distinguishing the human activities and adopting relevant management strategies. Based on the surface sediment samples from the Lake Keluke and its wetland, the content and grain size of elements were analyzed. The human health risk indicated in the area the potentially toxic elements (PTEs: Cr, Cu, Zn, Cd and Pb) were at no non-carcinogenic risk to adults or children. Except for Cd, the pollution levels of other PTEs were clean, and potential ecological risk with a low level. However, the pollution of Cd implicated a moderate to heavy pollution intensity and a high ecological risk. According to principal component analysis (PCA), and self-organizing maps (SOM), the main sources of PTEs were of the weathering and leaching of bedrocks; transportation and human agriculture activities. The watershed should reduce pollution caused by human activities and implement efficient agricultural practices.

Soil health is important, with soil chemical composition data, including potentially toxic elements (PTEs) being one of its conceptual components. This study aims to reveal the spatial distribution patterns of soil PTEs contents, identify their potential sources, and unveil their geochemical associations in Aragatsotn region, Armenia. For that purpose, the contents of Cr, V, Ti, As, Zn, Cu, Co, Fe, Mn, Ba, and Pb were determined using an X-ray fluorescence spectrometer. The mean contents of Cr and As exceeded their upper continental crust by 1.5 and 3.1 times and their maximum acceptable values by 1.5 and 1.5 times. The analysis demonstrated the presence of sites where all these elements displayed comparatively higher values. The combined application of compositional data analysis and geospatial mapping revealed multivariate outliers, which were located in structural-metallogenic zones with active ore exploitation . The application of unsupervised machine learning algorithm unveiled three groups within the main dataset and the clr-biplot identified the source-specific elements. Particularly, Group I included Cu and displayed the highest mean value among the identified groups. The soil samples included in Group I were in areas where Calcisols were developed and comparatively high Cu contents were attributed to agricultural activities and vehicle emissions. Group II is represented by the geochemical association of Fe, Co, Cr, Mn, Zn, and As. The formation of this group is conditioned by volcanic rocks of the local geological origin. However, no spatial pattern was identified in Group II distribution aligned with soil types. Group III included Ti, V, Pb, and Ba, which may have a mixed origin as it is spatially distributed in areas where regional highways pass through and where Group II elements also exhibit their higher values.

Abstract Gaseous and particulate 21 PAHs were monitored at a residential site in Ulsan, South Korea, over three seasons (December 2013–August 2014). The mean concentrations of Σ21 PAHs were highest in winter (16.2 ± 8.2 ng/m3), followed by spring (8.37 ± 4.53 ng/m3) and summer (6.23 ± 2.53 ng/m3). The mean gaseous concentration of Σ21 PAHs (7.39 ± 4.39 ng/m3) was 2.7 times higher than that of particulate PAHs (2.70 ± 3.38 ng/m3). To identify the sources of PAHs (both types of sources and their areas), diagnostic ratios, principal component analysis, and concentration-weighted trajectory (CWT) were used. The results showed that pyrogenic sources (e.g., coal combustion) were the primary emission sources of PAHs in winter and spring. In summer, the influence of both coal and heavy oil combustion was dominant, suggesting that PAHs could be transported from industrial areas of Ulsan (e.g., petrochemical and nonferrous industrial complexes) by seasonal winds. Regarding emission source areas, the CWT analysis revealed that in winter and spring, PAHs in Ulsan could be attributed to emissions from regional areas, e.g., China and North Korea. The PAH concentrations were also used to assess the health risks associated with the inhalation of these compounds for adults aged 18–70. The results showed that the cancer risks from Σ19 PAHs and Σ13 PAHs did not exceed the guideline set by the US EPA (10−6), indicating no cancer risks for this target group. However, it is worth noting that certain PAHs, which are not listed as priority PAHs by the US EPA, make significant contributions to the benzo[a]pyrene equivalent and the associated cancer risks. Therefore, it is necessary to investigate not only the priority PAHs but also other PAH species to fully evaluate their effect on human health.

Basin water pollution is a global problem, especially in the densely populated areas. The Huai River Basin (abbreviated as HRB), including the Huai River system and the Yishu River system, is the sixth-largest and most densely populated watershed in China. However, there is a lack of comprehensive studies of river and well water throughout the Huai River basin, including hydrochemistry characterization and assessment of health risks. This study investigated water quality and pollution sources of river and well water in the HRB based on the hydrochemistry analysis and different water quality indices. The water body in the HRB showed weak alkalinity (pH = 8.4 ± 0.7) and had high TDS values (TDS = 339 ± 186 mg/L) with water types of HCO3-Ca-Mg and SO4-Cl-Ca-Mg in the Huai River system, and SO4-Cl-Ca-Mg in the Yishu River system. Atmospheric input and evaporation had less impact on hydrochemistry. Evaporite dissolution and carbonate weathering had a greater impact on hydrochemistry. Carbonate precipitation and cation exchange also influenced the dissolved solutes, especially Ca2+ and Na+. Samples had low to medium salinity hazards and sodium absorption ratios and were suitable for irrigation. For drinking purposes, samples were fresh water and have good or excellent according to the Water Quality Index (WQI). Land use types influenced water quality with the worst river water quality from cropland. Combining different assessment indices, the water quality of the Yishu River system performed better than the Huai River system. Absolute principal component analysis-multiple linear regression and the positive matrix factorization models identified the main pollutants as As, Ba, Cr, Ni, and Mn, with natural sources of As, Ba, and Ni and anthropogenic inputs of Cr, and Mn. Although the water quality of the HRB has improved in recent years, high potential risk from As, Cr, Mn, Ba, and Ni should be noted. This study provided vital information for basin hydrochemistry analysis and water quality assessment. [ABSTRACT FROM AUTHOR]

This research was presented to obtain the first insight into the pollution profile, potential sources, and human health risks of polycyclic aromatic hydrocarbons (PAHs), polychlorinated biphenyls (PCBs) and organochlorine pesticides (OCPs) in indoor dusts taken from Istanbul and Kocaeli, Türkiye. ΣPAH concentrations in dusts from Istanbul varied between 73.64 ng/g d.w. (IST-3) and 434.3 ng/g d.w. (IST-2), whereas PAH concentrations changed between 4573 ng/g d.w. (KOC-2) and 12,311 ng/g d.w. (KOC-1) in Kocaeli which is at least 10.5 times higher than the measured PAH value in IST-2 which has the highest value in Istanbul. IST-1, IST-2, and IST-4 indoor dusts are weakly polluted in terms of PAH contamination, while the other two dusts (IST-3 and IST-5) in Istanbul are not polluted. In Kocaeli, however, they are heavily polluted because the ΣPAH concentrations in the dusts are much higher than 1000 ng/g. Pyrene, Fluoranthene, Phenanthrene, and Naphthalene were the dominant PAHs in all indoor dusts. The predominant OCPs found in all indoor dusts were DDE p,p, HCH alpha, and HCH beta, respectively. The source identification through diagnostic ratios demonstrated that PAHs arise from more than one source and they originated almost equally from petrogenic and pyrogenic sources due to the high traffic density from highways near the sampling points and the existence of many industrial activity areas. All HQ, HI, and TLCR values demonstrated that there is no risk of non-carcinogenic and carcinogenic hazards for children and adults in case of ingestion, inhalation, or skin contact with indoor dusts containing related POPs. [ABSTRACT FROM AUTHOR]

The variation in heavy metal concentration in different environment is dependent on the emission source. Source identification of heavy metal plays an important role in providing solution to its contamination in the atmosphere. Hence, the objective of this paper is to engage enrichment factor (EF) approach to evaluate the source identification of potentially toxic heavy metals along the Benin-Ore-Sagamu Expressway in Nigeria in four sampling locations (A, B, C and D) that are denoted with high traffic congestion. The source identification of Cu, Zn, Mn, Ni, Pd, Cd, Cr and Pb contamination in the study area were determined using appropriate standard methods. The EF values indicated for Cu ranged from (2.3-5.9), Zn (0.48-0.86), Mn (0.29-0.49), Ni (1.27-4.03), Pd (37012.18- 59922.57), Cd (1909.11-2844.81), Cr (4.56-7.76) and Pb (0.77-4.64). The results suggest crustal source enrichment for Zn and Mn while Cu, Ni, Cr and Pb were enriched moderately. However, the EF values for Pd and Cd were found to be greater than 50, indicating extremely severe enrichment. The findings of this study provide evidence of anthropogenic impact on heavy metals pollution in the study area that is attributed to the intense vehicular traffic. [ABSTRACT FROM AUTHOR]