Occurrence and potential risks of organophosphate esters in agricultural soils: A case study of Fuzhou City, Southeast China.

Fifty agricultural soil samples collected from Fuzhou, southeast China, were first investigated for the occurrence, distribution, and potential risks of twelve organophosphate esters (OPEs). The total concentration of OPEs (ΣOPEs) in soil ranged from 1.33 to 96.5 ng/g dry weight (dw), with an average value of 17.1 ng/g dw. Especially, halogenated-OPEs were the predominant group with a mean level of 9.75 ng/g dw, and tris(1-chloro-2-propyl) phosphate (TCIPP) was the most abundant OPEs, accounting for 51.1% of ΣOPEs. The concentrations of TCIPP and ∑OPEs were found to be significantly higher (P < 0.05) in soils of urban areas than those in suburban areas. In addition, the use of agricultural plastic films and total organic carbon had a positive effect on the occurrence of OPE in this study. The positive matrix factorization model suggested complex sources of OPEs in agricultural soils from Fuzhou. The ecological risk assessment demonstrated that tricresyl phosphate presented a medium risk to land-based organisms (0.1 ≤ risk quotient < 1.0). Nevertheless, the carcinogenic and non-carcinogenic risks for human exposure to OPEs through soil ingestion and dermal absorption were negligible. These findings would facilitate further investigations into the pollution management and risk control of OPEs.

Driving factor, source identification, and health risk of PFAS contamination in groundwater based on the self-organizing map.

The complex interactions between groundwater chemical environments and PFAS present challenges for data analysis and factor assessment of the spatial distribution and source attribution of PFAS in groundwater. This study employed spatial response analysis combining self-organizing maps (SOM), K-means clustering, Spearman correlation, positive matrix factorization (PMF) and risk quotient (RQ), to uncover the spatial characteristics, driving factors, sources, and human health risks of groundwater PFAS in the Pearl River Basin. The results indicated that the characteristics of PFAS in groundwater were classified into 16 neurons, which were further divided into 6 clusters (I-VI). This division was due to the contribution of industrial pollution (33.2 %) and domestic pollution (31.5 %) to the composition of PFAS in groundwater. In addition, the hydrochemical indicators such as pH, dissolved organic carbon (DOC), chloride (Cl-), and calcium ions (Ca2+) might also affect the distribution pattern of PFAS. The potential human health risk in the area was minimal, with cluster Ⅱ presenting the highest risk (RQ value 0.25) which is closely related to PFOA emissions from fluoropolymer industry. This study provides a theoretical basis and data support for applying of SOM to the visualization and control of PFAS contamination in groundwater.

Bioaccumulation of Atmospherically Deposited Cadmium in Soybean: Three-Year Field Experiment Combined with Cadmium Isotopes.

Atmospheric deposition plays a significant role in introducing cadmium (Cd) into agroecological systems; however, accurately determining its accumulation in crops through foliar and root uptake presents challenges. This study investigated the bioaccumulation of atmospherically deposited Cd in soybean using a three-year fully factorial atmospheric exposure experiment incorporating Cd isotope analysis. Results shown that atmospheric deposition accounted for 1-13% of soil Cd pools, yet contributed 11-72% of Cd to soybean tissues during the growing seasons. Over the course of soil exposure to atmospheric deposition ranging from 1 to 3 years, no notable variations were observed in Cd concentrations in soil solutions and soybean tissues, nor in isotope ratios. Newly deposited Cd was a major source in soybean plants, and the bioavailability of deposited Cd rapidly aged in soils. Atmospheric Cd enriched in lighter isotopes induced negative isotope shifts in soybean plants. By employing an optimized isotope mixing model in conjunction with a mass balance approach, foliar Cd uptake contributed 13-51%, 16-45%, and 21-56% to stem, leaf, and seed, respectively. This study highlights substantial contribution of foliar uptake of atmospheric deposition to Cd levels in soybean and controlling foliar uptake as a potential strategy in agroecological systems experiencing high atmospheric Cd deposition.

Toxicity assessment of heavy metals translocation in maize grown in the Ganges delta floodplain soils around the Payra power plant in Bangladesh.

As a cereal crop, maize ranked third place after wheat and rice in terms of land area coverage for its cultivation, and in Bangladesh, it ranked second place after rice in its production. As the substitution of wheat products, maize has been used widely in baking for human consumption and animal fodder. However, maize grown in this soil around the coal-burning power plant may cause heavy metals uptake that poses a risk to humans. The study was conducted at the maize fields in the Ganges delta floodplain soils of Bangladesh to know the concentration of eight heavy metals (Ni, Cr, Cd, Mn, As, Cu, Zn, and Pb) in soil and maize samples using an inductively coupled plasma mass spectrometer (ICP-MS) and to estimate the risk of heavy metals in maize grains. Mean concentrations of heavy metals (mg/kg) in soil were in decreasing order of Zn (10.12) > Cu (10.02) > Mn (5.48) > Ni (4.95) > Cr (3.72) > As (0.51) > Pb (0.27) > Cd (0.23). The plant tissues showed the descending order of heavy metal concentration as roots > grains > stems > leaves. BCF values for As, Cd, Pb, and Mn in roots were higher than 1.0, indicating considerable accumulation of these elements in maize via roots. Total hazard quotient (Æ©THQ) of heavy metals through maize grain consumption was 3.7E+00 and 3.9E+00 for adults and children, respectively, indicating non-cancer risk to the consumers. Anthropogenic influences contributed to the heavy metals enrichment in the Ganges delta floodplain soils around the thermal plant, and potential risks (non-carcinogenic and carcinogenic) were observed due to the consumption of maize grain cultivated in the study area.

Cadmium contamination in sediments from a mangrove wetland: Insights from lead isotopes.

Cadmium (Cd) pollution has gained significant attention in mangrove sediments due to its high toxicity and mobility. However, the sources of Cd and the factors influencing its accumulation in these sediments have remained elusive. In this study, we utilized lead (Pb) isotopic signatures for the first time to assess Cd contamination in mangrove sediments from the northern region of the Beibu Gulf. A strong correlation was observed between Cd and Pb concentrations in the mangrove sediments, suggesting a shared source that can be estimated using Pb isotopic signatures. By employing a Bayesian mixing model, we determined that 70.1 ± 8.2 % of Cd originated from natural sources, while 12.9 ± 4.9 %, 9.8 ± 3.7 %, and 7.1 ± 3.4 % were attributed to agricultural activities, non-ferrous metal smelting, and coal combustion, respectively. Our study clearly suggests that natural Cd could also dominate the high Cd content. Agricultural activities were the most important anthropogenic Cd sources, and the increased anthropogenic Cd accumulation in mangrove sediment was related to organic matter. This study introduces a novel approach for assessing Cd contamination in mangrove sediment, providing useful insights into Cd pollution in coastal wetlands.

Occurrence, sources and risk assessment of 12 dioxin-like polychlorinated biphenyls (DL-PCBs) in sediments from the Soummam River protected area, Algeria: A potential threat to the Mediterranean Sea.

The levels, the sources and the potential risks associated with twelve dioxin-like PCBs were investigated in the sediments of the Soummam River in northeastern Algeria. Total dl-PCBs concentrations ranged from 3.64 ng/g to 9.38 ng/g with PCB 118 and PCB 105 being the predominant congeners. Principal component analysis suggested that commercial mixtures and municipal waste incineration could be responsible for the presence of PCBs in the region. TEQ values ranged from 12.93 pg/g to 60.98 pg/g indicating adverse effects on aquatic organisms. Moreover, cancer risk assessed via Total Lifetime Cancer Risk (TLCR) suggested that for all the stations, the risk was low but not negligible. Additionally, the non-cancer risk was significant at half of the stations for children but negligible for adults at all the stations. Consequently, measures must be taken by local authorities to protect the environment and the human health.

[Characteristics of Water-soluble Ion Pollution in PM2.5 and the Causes of High Acidity of PM2.5 in Dalian].

To gain a deeper understanding of the pollution status and influencing factors of fine particles （PM2.5） and their water-soluble ions （WSI） in Dalian and to implement precise control of pollution events such as haze and acid rain, PM2.5 samples were collected in Dalian from June 2021 to May 2022. Then, the mass concentrations of PM2.5 and WSI were determined using the weight method and ion chromatography, respectively, and the pollution characteristics and sources were analyzed. Furthermore, the causes of the high acidity of PM2.5 in spring were discussed. The results showed that the annual average mass concentrations of PM2.5 and WSI in Dalian during the sampling period were （33.24 ±28.87） µg·m-3 and （18.66 ±20.52） µg·m-3, respectively, and the secondary ions （SNA, including SO42-, NO3-, and NH4+） accounted for the highest proportion of WSI [（86.2 ±9.3）%]. The order of ion concentration levels from highest to lowest was： NO3->SO42->NH4+>Cl->K+>Ca2+>Na+>Mg2+>F-. Due to the influence of meteorological conditions and coal combustion emissions during the concentrated heating period from late autumn to early spring, the seasonal variation in PM2.5 and WSI was winter>spring>autumn>summer, whereas SNA was the highest in spring and the lowest in summer. The results of correlation and principal component analysis showed that WSI in PM2.5 was mainly from the secondary transformation of atmospheric SO2 and NO2 （contributing to the majority of SNA）, mixed sources of combustion and dust （characterized by K+, Mg2+, Cl-, and F-）, and sources of sand and sea salt （characterized by Na+, Ca2+, and Mg2+）. In summer, the main combustion source was biomass burning, whereas in autumn, winter, and spring, coal combustion emissions were predominant. The change in wind direction from autumn to winter brought by a shift from the source of sea salt to soil dust； additionally, the external pollution transported by northwest winds contributed to the complexity of the sources of WSI in PM2.5 during spring in Dalian. ISORROPIA-II model simulations suggested NH4NO3 as the most present solid aerosol form in PM2.5 in Dalian, followed by CaSO4 and （NH4）2SO4； compared to that in solid aerosols, more SNA existed in liquid aerosols. The annual average pH of PM2.5 in Dalian was 5.65 ±3.00, with pH values close to neutral in summer, autumn, and winter but significantly acidic in spring （2.03 ±3.18）. The high acidity observed in spring was attributed to the combination of low temperature, high humidity, and high SNA concentrations. These conditions resulted in higher aerosol water content and increased gas-to-particle conversion rates, ultimately leading to an ammonia-deficient environment. The backward trajectory and PSCF results indicated that the external transport of high acidity PM2.5 in spring mainly came from the northwest （45.0%） and southwest （40.8%） directions. Mobile source emissions made the most significant contribution to the transportation of pollutants in the former, forming high-pollution source areas in the Beijing-Tianjin-Hebei Region, which may have been mainly related to urban motor vehicle and port vessel emissions； the latter was influenced by relatively strong stationary sources and showed higher SO2 emissions in the southern part of Henan Province and the central part of Jiangsu Province.

Mechanisms of evolution and pollution source identification in groundwater quality of the Fen River Basin driven by precipitation.

Groundwater pollution has attracted widespread attention as a threat to human health and aquatic ecosystems. However, the mechanisms of pollutant enrichment and migration are unclear, and the spatiotemporal distributions of human health risks are poorly understood, indicating insufficient groundwater management and monitoring. This study assessed groundwater quality, human health risks, and pollutant sources in the Fen River Basin(FRB). Groundwater quality in the FRB is good, with approximately 87 % of groundwater samples rated as "excellent" or "good" in both the dry and rainy seasons. Significant precipitation elevates groundwater levels, making it more susceptible to human activities during the rainy season, slightly deteriorating water quality. Some sampling points in the southern of Taiyuan Basin are severely contaminated by mine drainage, with water quality index values up to 533.80, over twice the limit. Human health risks are mainly from As, F, NO3-, and Cr. Drinking water is the primary pathway of risk. From 2019 to 2020, the average non-carcinogenic risk of As, F, and NO3- increased by approximately 28 %, 170 % and 8.5 %, respectively. The average carcinogenic risk of As and Cr increased by 28 % and 786 %, the overall trend of human health risks is increasing. Source tracing indicates As and F mainly originate from geological factors, while NO3- and Cr are significantly influenced by human activities. Various natural factors, such as hydrogeochemical conditions and aquifer environments, and processes like evaporation, cation exchange, and nitrification/denitrification, affect pollutant concentrations. A multi-tracer approach, integrating hydrochemical and isotopic tracers, was employed to identify the groundwater pollution in the FRB, and the response of groundwater environment to pollutant enrichment. This study provides a scientific basis for the effective control of groundwater pollution at the watershed scale, which is very important in the Loess Plateau.

Evaluation of fluoride emissions and pollution from an electrolytic aluminum plant located in Yunnan province.

The monitoring and evaluation of fluoride pollution are essentially important to make sure that concentrations do not exceed threshold limit, especially for surrounding atmosphere and soil, which are located close to the emission source. This study aimed to describe the atmospheric HF and edaphic fluoride distribution from an electrolytic aluminum plant located in Yunnan province, on which the effects of meteorological conditions, time, and topography were explored. Meanwhile, six types of solid waste genereted from different electrolytic aluminum process nodes were characterized to analyze the fluoride content and formation characteristics. The results showed that fluoride in solid waste mainly existed in the form of Na3AlF6, AlF3, CaF2, and SiF4. Spent electrolytes, carbon residue, and workshop dust are critical contributors to fluoride emissions in the primary aluminum production process, and the fluorine content is 17.14 %, 33.30 %, and 31.34 %, respectively. Unorganized emissions from electrolytic aluminum plants and solid waste generation are the primary sources of fluoride in the environment, among which the edaphic fluoride content increases most at the sampling sites S1 and S7. In addition, the atmospheric HF concentration showed significant correlations with wind speed, varying wildly from March to September, with daily average and hourly maximum HF concentrations of 4.32 µg/m3 and 9.0 µg/m3, respectively. The results of the study are crucial for mitigating fluorine pollution in the electrolytic aluminum industry.

Natural vs. anthropogenic sources of N-Nitrosodimethylamine precursors in surface water.

N-nitrosodimethylamine (NDMA) is a carcinogenic disinfection byproduct formed from reactions between dichloramine and organic nitrogen-containing precursors. It is unclear if NDMA precursors in surface water intakes originate in anthropogenic (i.e., wastewater) or natural sources. The Truckee River has a single point source release of treated wastewater effluent, making it an ideal system to study the relative importance of precursor sources. Three Lagrangian sampling events were conducted. NDMA formation potential (FP, a measurement of precursors) above the wastewater outfall indicated that the natural background of NDMA precursors was 2-28 ng/L. NDMA FP increased to 18-31 ng/L immediately downstream of the wastewater outfall, but decreased rapidly in a first order manner, and were not statistically different from the upstream samples in only ∼6 km. This suggests that the dominant source of NDMA precursors may be wastewater derived only near wastewater outfalls and deviates from the previous belief that wastewater-derived precursors are responsible for NDMA formation in drinking water sources located further downstream. Additionally, given the rapid loss of the wastewater precursors in this study, precursors which are slow to biodegrade/photolyze/adsorb to sediment are likely to be poor surrogates for the overall wastewater NDMA precursor pool. To understand temporal changes in the wastewater impact on environmental NDMA precursor loading, two 24-hour sampling events were conducted near (<3 km) the wastewater outfall and demonstrated that temporal changes in the NDMA precursors directly downstream of the wastewater outfall are directly linked to the wastewater flow contribution.

Levels, sources, and health risk assessment of phthalate acid esters in indoor dust of various microenvironments in university.

Phthalate acid esters (PAEs), as a common group of plasticizers, are widely present in indoor environments and pose a risk to human health. Indoor dust samples collected from dormitory, classroom, laboratory, and office in several universities in China, were analyzed for seven types of PAEs. The total concentrations of seven PAEs (Σ7PAEs) ranged from 4.87 to 360 µg/g, with a median concentration of 51 µg/g, which is lower than that reported by other studies. Using the median concentration of Σ7PAEs as a metric, we assessed the levels of contamination in different microenvironments, resulting in the following ranking: dormitory > classroom > laboratory > office. There are significant differences in the levels of individual PAEs in different microenvironments. Radiation from sunlight, ventilation rates, cleaning frequency, and sprays were influential factors for the concentrations of individual PAEs in indoor dust. The indoor environmental conditions and consumption patterns profoundly affect PAEs levels. The sources of PAEs in classroom and office were more complex than in dormitory and laboratory. Daily intakes of PAEs were used to calculate carcinogenic and non-carcinogenic human risk for males and females, indicating a low health risk to humans. This is the first study to assess the risk of PAEs in university microenvironments and provides a valuable reference for further research.

A study on source identification of contaminated soil with total petroleum hydrocarbons (aromatic and aliphatic) in the Ahvaz oil field.

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.

Identification of dense nonaqueous phase liquid sources in groundwater: a review of isotope technique.

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.

Investigation of groundwater quality in the Southern Coast of the Black Sea: application of computational health risk assessment in Giresun, Türkiye.

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.

Predictive analysis and risk assessment of potentially toxic elements in Beijing gas station soils using machine learning and two-dimensional Monte Carlo simulations.

Gas stations not only serve as sites for oil storage and refueling but also as locations where vehicles frequently brake, significantly enriching the surrounding soil with potentially toxic elements (PTEs). Herein, 117 topsoil samples from gas stations were collected in Beijing to explore the impact of gas stations on PTE accumulation. The analysis revealed that the average Pollution Index (PI) values for Cd, Hg, Pb, Cu, and Zn in the soil samples all exceeded 1. The random forest (RF) model, achieving an AUC score of 0.95, was employed to predict PTE pollution at 372 unsampled gas stations. Additionally, a Positive Matrix Factorization (PMF) model indicated that gas station operations and vehicle emissions were responsible for 70 % of the lead (Pb) enrichment. Probabilistic health risk assessments showed that the carcinogenic risk (CR) and noncarcinogenic risk (NCR) for PTE pollution to adult females were the highest, at 0.451 and 1.61E-05 respectively, but still within acceptable levels. For adult males at contaminated sites, the Pb-associated CR and NCR were approximately twice as high as those at uncontaminated sites, with increases of 107 % and 81 %, respectively. This study provides new insights for managing pollution caused by gas stations.

Rapid identification model of mine water inrush source using random forest optimized by multi-strategy improved sparrow search algorithm.

Mine water inrush accident is one of the most threatening disasters in coal mine production process. In order to improve the identification accuracy of mine water inrush source, a fast identification method of mine water inrush source based on improved sparrow search (SSA) algorithm coupled with Random Forest algorithm was proposed. Firstly, taking Zhaogezhuang Mine as the research object, six factors were selected as the discriminant index and three principal components were extracted by kernel principal component analysis. Secondly, four strategies are employed to enhance the SSA for achieving the ISSA, while multiple benchmark functions are utilized to validate its performance. The extracted principal components serve as input, and the categories of water inrush sources act as output. Subsequently, the prediction results of Random Forest (RF) algorithm after optimizing hyperparameters through Improve SSA are compared with those obtained from other models. The research findings demonstrate that optimizing the RF model using Improve SSA yields superior predictive performance compared to alternative models. Finally, this model is applied to identify water inrush sources in a mine located in Shandong province. The discrimination results exhibit higher accuracy, precision, recall, and F1 index than other models, thereby confirming the reliability and stability of this approach. The results demonstrate that the kernel principal component analysis-based rapid identification model for mine water outburst source, combined with an improved sparrow search algorithm to optimize Random Forest, exhibits excellent robustness and accuracy. This model effectively fulfills the requirements of identifying mine water outbursts and provides a reliable guarantee for ensuring mining safety production.

Identification of illicit discharges in sewer networks by an SWMM-Bayesian coupled approach.

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.

Morphological Enrichment and Environmental Factors Correlation of Heavy Metals in Dominant Plants in Typical Manganese Ore Areas in Guizhou, China.

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.

Crucial time of emergency monitoring for reliable numerical pollution source identification.

The Pollution source identification (PSI) is an important issue on river water quality management especially for urban receiving water. Numerical inversion method is theoretically an effective PSI technique, which employs monitored downstream pollutant breakthrough curves to identify the pollution source. In practice, it is important to know how much monitoring data should be accumulated to provide PSI results with acceptable accuracy and uncertainty. However, no literature reports on this key point and it seriously handers the numerical PSI technology to mature practical applications. To seek a monitoring guideline for PSI, we conducted extensively numerical experiments for single-point source instantaneous release taking Bayesian-MCMC method as the baseline inversion technique. The crucial time (Tc) phenomenon was found during the data accumulation process for Bayesian source inversion. After Tc, estimated source parameters subsequent sustained low error levels and uncertainty convergence. Results shown the presence of Tc impacted by the number and location of monitoring sections, while monitoring frequency and data error do not. Under different river hydrodynamic conditions, relative crucial time (Λ) is determined by the river's Peclet number, and minimum effective Λ was controlled by dispersion coefficient (Dx). Analytic spatial structure of Λ(U, Dx) was uncovered and this relationship successfully explained by the information entropy theory. Based on these findings, a novel design method of PSI emergency monitoring network for preparedness plan and a practical framework of PSI for emergency response were established. These findings fill the important knowledge gap in PSI applications and the guidelines provide valuable references for river water quality management.

Evaluation of ecological and health risks of trace elements in soils of olive orchards and apportionment of their sources using the APCS-MLR receptor model.

Izmir, 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 Izmir. This study was carried out to determine the pollution level and ecological risks of TEs in the olive orchards soils of Izmir 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.