Systematic assessment of source identification and ecological and probabilistic health risks of potentially toxic elements (PTEs) in soils of a typical coal mining area in Guanzhong region.

Mining activities may cause the accumulation of potentially toxic elements (PTEs) in surrounding soils, posing ecological threats and health dangers to the local population. Therefore, a comprehensive assessment using multiple indicators was used to quantify the level of risk in the region. The results showed that the mean values of the nine potentially toxic elements in the study area were lower than the background values only for Cr, and the lowest coefficient of variation was 17.1 % for As, and the spatial distribution characteristics of the elements indicate that they are enriched by different factors. The elements Hg and Cd, which have substantial cumulative features, are the key contributors to ecological risk in the study region, which is overall at moderate risk. APCS-MLR model parses out 4 possible sources: mixed industrial, mining and transportation sources (53.98 %), natural sources (24.56 %), atmospheric deposition sources (12.60 %), and agricultural production sources (8.76 %). The probabilistic health risks show that children are more susceptible to health risks than adults; among children, the safety criteria (HI < 1 and CR < 10-4) were surpassed by 29.29 % of THI and 8.58 % of TCR. According to source-orientated health hazards, the element Ni significantly increases the risk of cancer. Mixed sources from industry, mining, and transportation are important sources of health risks. The results of this research provide some scientific references for the management and decrease of regional ecological and health risks.

Assessment of health risks based on different populations and sources of heavy metals on agricultural lane in Tengzhou City by APCS-MLR models.

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

Soil pollution and elemental sources along Barapukuria coal mine, Bangladesh: Implications for eco-environmental and health risk assessment.

For the first time, different pollution indices and a receptor model have been used to quantify eco-environmental and health risk assessments as well as identify the sources of potentially toxic elements in soil along the Barapukuria Coal Mine (BCM). Individual indices include enrichment and contamination factors showing the soil samples are moderately to highly contaminated by arsenic, cobalt, chromium, copper, lead, and zinc and heavily contaminated by sulfur. According to the geo-accumulation index, there is significant pollution with arsenic (1.24 ± 0.38), lead (1.49 ± 0.58), cobalt (1.49 ± 0.58), and sulfur (1.63 ± 0.38). Modified hazard quotient and ecological risk factor values also suggest low to moderate environmental risk hazards from the same elements. The nemerow pollution index, pollution load index, nemerow risk index, ecological risk index, and toxic risk index of soil range from 1.65 to 3.03, 0.82-1.23, 11-26, 77-165, and 6.82-11.76 suggest low toxic risk and moderate pollution, among other synergistic indices. Health risk assessment indicates that iron poses lower cancer risk for children than adults, while both face unacceptable cancer risks from inhaling chromium, cobalt, or arsenic. Principal component and phylogenetic cluster analysis extracted by the multiple linear regression with the absolute principal component score (APCS-MLR) model refer to the fact that manganese, iron, titanium, and nickel have originated from geogenic sources, while coal mine effluents enrich elements like arsenic, chromium, zinc, lead, uranium, sulfur, thorium, and zinc and phosphorous sourced from agriculture. In addition, geogenic and anthropogenic sources, including mine and agriculture activities, could potentially pollute the soil and ecosystem. The findings are crucial for regional and national planners in devising strategies to mitigate potentially toxic element pollution in soil along coal mine areas.

A Monte Carlo simulation-based health risk assessment of heavy metals in soils of the tropical region in southern China.

The disturbance of ecological stability may take place in tropical regions due to the elevated biomass density resulting from heavy metal and other contaminant pollution. In this study, 62 valid soil samples were collected from Sanya. Source analysis of heavy metals in the area was carried out using absolute principal component-multiple linear regression receptor modelling (APCS-MLR); the comprehensive ecological risk of the study area was assessed based on pollution sources; the Monte-Carlo model was used to accurately predict the health risk of pollution sources in the study area. The results showed that: The average contents of soil heavy metals Cu, Ni and Cd in Sanya were 5.53, 6.56 and 11.66 times higher than the background values of heavy metals. The results of soil geo-accumulation index (Igeo) showed that Cr, Mo, Mn and Zn were unpolluted to moderately polluted, Cu and Ni were moderately polluted, and Cd was moderately polluted to strongly polluted. The main sources of heavy metal pollution were natural sources (57.99%), agricultural sources (38.44%) and traffic sources (3.57%). Natural and agricultural sources were jointly identified as priority control pollution sources and Cd was the priority control pollution element for soil ecological risk. Heavy metal content in Sanya did not pose a non-carcinogenic risk to the population, but there was a carcinogenic risk to children. The element Zn had a high carcinogenic risk to children, and was a priority controlling pollutant element for the risk of human health, with agricultural sources as the priority controlling pollutant source.

Toxic element characterization against a typical high geology background: Pollution enrichment, source tracking, spatial distribution, and ecological risk assessment.

The geological environment determines the initial content of various elements in soil, while the late input of toxic elements produced through weathering and leaching is a persistent threat to food security and human health. In this study, we selected the Lou Shao Basin, a black rock system background, and combined geostatistical analysis and multivariate statistics to quantify the specific contribution of weathering of the black rock system, and to analyze the source traces, spatial distributions, and ecological risks of the soil toxicity of elements. The results show that the soils in the study area are acidic, which is related to the weathering of sulfides in the black rock system. The concentrations of most elements in the soil were determined to exceed the soil background values, and the Cd, Se and N contents, exceeded more than five times, especially Se, Mo nearly as high as 13 times. Strong positive correlation between Se, Cu, V and P, low correlation between N and Se, Cu, V, P, Ni and Cd.72.52%, 43%, 77.79%, 82%, 77%, and 44.1% of Cd, Se, Ni, Cu, B, and Mo came from the black rock system, respectively, which were greatly affected by geogenic weathering; V, Zn, Pb, and As are mainly from biomass burning sources; N and P are mainly from agricultural surface sources. Comparison found that the Cd and Se elements in the rocks in the study area were 16.78 times and 1.36 times higher than the world shale average, respectively, and need to pay attention to the weathering process of the two, and the spatial distribution of the 12 elements in soils showed a striped and centralized block distribution pattern, specifically around the distribution of carbonate and metamorphic rocks and other high-geology blocks. The ecological risk results showed that Cd was the main element causing high ecological risk, followed by Se and N, which were at moderate to high ecological risk levels, and Se and N showed similar ecological risk patterns, which may be related to the fact that selenium can promote the uptake and transformation of nitrogen. The present results add to the endogenous sources of toxic elements, quantify the source contributions of toxic elements in soils with high geologic backgrounds, fill this knowledge gap, and provide new insights for pollution control and ecological protection in areas with high geochemical backgrounds.

[Spatiotemporal Distribution and Source Analysis of Heavy Metals in Surface Sediments in Lake Ulansuhai Based on PCA-APCS-MLR Model].

To explore the spatial and temporal distribution characteristics of heavy metals in the surface sediments of lakes in cold regions during ice-sealing and non-ice-sealing periods, we analyzed the potential ecological risk degree and the pollution sources. A total of 20 sampling sites in Lake Ulansuhai in cold regions were collected from 2020 to 2021, and 120 surface sediment samples were collected during different periods. The contents of As, Cd, Cr, Cu, Ni, Pb, Zn, and Hg were determined. Correlation analysis, principal component analysis, and the absolute factor score-multiple linear regression (APCS-MLR) receptor model were used to trace the source of heavy metal pollution. The results showed that:① the distribution of heavy metals in lake surface sediments was different between the ice-sealing period and the non-ice-sealing period. The distribution of heavy metals during the ice-sealing period was higher in the north and lower in the south. Cd and Hg were mainly distributed in the central and southern lakes during the non-glacial period. ② Hg, Cd, and As were moderately polluted, and Ni was mildly polluted in the surface sediments of the lake. The overall performance was at a high risk level, and the pollution level during the non-ice-sealing period was higher than that during the ice-sealing period. The main environmental risk factors were Hg and Cd, which showed high risk and moderate risk, respectively. ③ The sources of heavy metals in lake surface sediments were mainly industrial sources from mining and transportation, agricultural sources, and natural sources. As, Ni, Pb, and Hg were mainly affected by industrial sources, with contribution rates of 62.67%, 75.31%, 77.47%, and 80.11%, respectively. The main sources of Cu and Zn were natural sources, and Cd was greatly affected by agricultural sources. The contribution rate was 81.57%. The source of Cr was mainly affected by natural factors, and the influence of human activities and unknown sources require further attention.

Risk assessment and source apportionment of available atmospheric heavy metal in a typical sandy area reservoir in Inner Mongolia, China.

This study evaluated dry and wet deposition of atmospheric heavy metals (HMs) in a sandy area of Inner Mongolia, China, with the Dahekou Reservoir, Xilin Gol League, adopted as the study area. Monthly monitoring of atmospheric HM dry and wet deposition was conducted over one year (2021 to 2022) at 12 monitoring points, producing 144 dry and wet deposition samples, respectively. The sample contents of eight HMs (Cr, Ni, Pb, Cu, Zn, Mn, As, and Cd) were determined to estimate the fluxes of available forms of heavy metal (AHM) in dry and wet deposition. The potential ecological index (Eri), risk assessment coding (RAC), and ratio of secondary phase to primary phase (RSP) were used to evaluate the impact of atmospheric HM dry deposition on ecological security. Correlation analysis, principal component analysis, and the absolute principal component scores-multiple linear regression (APCS-MLR) receptor model were used to quantitatively analyze the sources of AHMs in atmospheric dry and wet deposition. The results showed that the study area experienced annual dry and wet deposition fluxes of AHMs of 1712.59 kg and 534.97 kg, respectively. Atmospheric heavy metal dry deposition over the entire year presented a strong ecological risk, with Cd contributing most to this risk. Risk assessment of HM speciation showed that the greatest risks of migration and transformation were for Cd and Pb. The APCS-MLR receptor model identified five and three sources of dry and wet deposition, respectively, in order of proportion of total contribution of: natural wind and sand > road traffic and coal combustion > mineral mining > other human activities > industrial soot.

Source identification and risk assessment of trace metals in surface sediment of China Sea by combining APCA-MLR receptor model and lead isotope analysis.

This study aimed to investigate the distribution, pollution, risk and sources of trace metals in sediments along China Sea. Clear spatial variations were found for Cr, Mn, Co, Ni, Cu, Zn, Se, Mo, Ag, Cd, and Pb, whereas As did not show spatial variation. East China Sea (ECS) contained the highest concentrations of Mn, Co, Ni, Cu, Zn, South China Sea (SCS) shallow sea contained the highest concentrations of Zn, Se, Mo, Ag, Cd, and Pb, whereas coral reefs contained the lowest concentrations of trace metals. Spatial variations could be explained by economic development characteristics along China Sea. As, Se and Cd exhibited low to moderate pollution in China Sea sediment, yet pollution for Cu, Zn, Ni, and Ag appeared in some regions. Sediment in ECS had moderate ecological risks and other regions at low ecological risks. The absolute principle component score-multiple linear regression (APCS-MLR) and Pb stable isotope indicated that 43-74% of trace metals (Ni, Cu, Zn, As, Se, Cd, and Pb) were derived from anthropogenic sources like traffic emission, agricultural activities, industrial source. No pollution and ecological risk were observed in coral reefs, yet 39-71% (Pb) was derived from anthropogenic activities such as motor vessels.

[Hydrochemical Characteristics and Control Factors of Surface Water in Kuaize River Basin at the Upper Pearl River].

The Kuaize River is a small typical karst watershed in the source area of the Pearl River as well as an important coal mining area in Eastern Yunnan with a fragile ecological environment. Strengthening the research on the water environment in the region plays an important role in supporting the comprehensive management of the ecological environment and water resources in the source region of the Pearl River. Through the systematic collection of surface water, karst groundwater, and mine water samples, mathematical statistics analysis, correlation analysis, ion ratio analysis, absolute principal component scores multiple linear regression(APCS-MLR), and other methods were used to study the characteristics of hydrochemical evolution and control factors in Kuaize River Basin. The results showed that the average pH value of surface water in Kuaize River Basin was 7.8, which was weakly alkaline. The main cations were Ca2+ and Na+, showing the characteristics of Ca2+>Na+>Mg2+>K+. The main anions were HCO3- and SO42-, showing the characteristics of HCO3->SO42->NO3->Cl-. The variation coefficients of Na+, SO42-, and NO3- in surface water were high, showing strong spatial variability. The water chemical type of the trunk stream was mainly HCO3-Ca, whereas the water chemical type of the tributary was relatively complex, mainly HCO3-Ca, HCO3-Ca·Na, and HCO3·SO4-Ca·Na. The chemical composition of surface water was mainly affected by rock weathering, cation exchange, and human activities. Ca2+, Mg2+, Na+, and HCO3- in surface water mainly came from the weathering of carbonate rock and silicate rock; SO42- mainly came from the oxidation of sulfide, such as pyrite in coal seams; K+, Cl-, and NO3- mainly came from domestic sewage and agricultural activities. The APCS-MLR receptor model analysis results showed that the surface water in the Kuaize River Basin was mainly affected by sulfide oxidation, carbonate weathering, weathering of silicate rock in mine water, domestic sewage, agricultural activities, and unknown sources. In general, the contribution rate of human activities such as mining, domestic sewage, and agricultural activities to the surface water reached 47.17%, indicating that human activities were the key driving factor of surface water chemistry in the Kuaize River Basin.

Receptor model-based source apportionment and ecological risk assessment of metals in sediment of river Ganga, India.

Ganga river surface sediment was sampled from 11 locations, which revealed average concentrations (mg/kg) of metals in the order Mn (296.93) > Zn (61.94) > Cr (54.82) > Cu (30.19) > Pb (24.42) > Cd (0.36). Sediment quality guidelines showed metals rarely to occasionally exhibit adverse biological effects. Indices like potential ecological risk, contamination security index, hazard quotients, multiple probable effect concentrations quality, mean probable effects level quotients, mean effects range median quotient suggest nil to a very low level of pollution with low ecological risk. Contamination factor, geo accumulation index, enrichment factor, quantification of contamination revealed that Pb and Cd originated from anthropogenic activities. APCS-MLR model revealed that metals contributed from natural sources (Zn, Mn, Cr; 20.18 %), industrial-agricultural (Cd; 21.35 %); and discharge of paints, Pb batteries, fossil fuel (Pb; 8.49 %). Present findings will serve as an effective guideline for managing and ameliorating pollution in the river system.

Pollution source identification of nitrogen and phosphorus in the lower West Main Canal, the Ganfu Plain irrigation district (South China).

The degradation of surface water quality has been a widespread concern around the world. However, irrigation canal water does not attract much attention although it is important to agriculture and population. In this study, a 5-year water quality monitoring of surface water was conducted in the lower West Main Canal of the Ganfu Plain irrigation district to identify the levels and pollution sources of nitrogen and phosphorus.Over 75% of samples had total phosphorus (TP) concentrations of > 0.02 mg/L, and all samples had total nitrogen (TN) concentrations of > 0.2 mg/L, indicating a risk of eutrophication. The concentrations of NO3--N and NH4+-N averagely occupied 57% and 18% of TN, respectively. PCA analysis showed that phosphorus and nitrogen in canal water were associated with meteorological factors, urban life and surface runoff, agricultural cultivation, livestock-poultry breeding, and water-sediment interaction in the wet season, whereas they were affected by meteorological factors, industrial effluent, urban domestic sewage, and livestock-poultry breeding in the dry season. Absolute principal component score-multiple linear regression (APCS-MLR) model results revealed that (1) agricultural cultivation plus livestock-poultry breeding contributed 43.2% of TP in canal water in the wet season, while livestock-poultry breeding contributed 52.9% in the dry season, and (2) domestic sewage plus surface runoff contributed 29.4% of TN in the wet season, while livestock-poultry breeding contributed 45.9% in the dry season. The unidentified sources had significant contributions of > 20% for almost all variables. So further investigations are required for determining unidentified sources, and anthropogenic pollution control is imperative for canal water quality protection.

Anthropogenic and natural contribution of potentially toxic elements in southwestern Ganges-Brahmaputra-Meghna delta, Bangladesh.

Elemental composition, multivariate statistical analyses with the absolute principal component score-multiple linear regression (APCS-MLR) model, and different pollution indices in Upper and Lower Southwestern Ganges-Brahmaputra-Meghna (GBM) delta sediments were studied to characterize pollution, ecological risk and quantify potential toxic element sources of the area. Toxic metals concentrations were higher in Lower Delta and individual pollution indices showed Upper Delta was moderately polluted by arsenic, chromium, cobalt, copper and lead, and Lower Delta was moderately-strongly polluted by the same metals. Synergistic indices include Potential Ecological, Toxic, Nemerow, and Pollution Risk indices in Upper and Lower Delta sediment ranged from 47.17-128.07, 2.03-12.19, 29.92-65.42, 0.28-1.62, and 69.17-246.90, 8.00-13.47, 20.53-152.92, 1.18-1.58, indicated low and moderate risk pollution, respectively. Statistical models represent the metals dominantly originated from nature for Upper Delta, and both natural and anthropogenic activities contributed to Lower Delta sediment. The study found that the modern deposit in Lower Delta became more contaminated and thus enhanced ecological risk.

[Source Analysis and Ecological Risk Assessment of Heavy Metals in the Arable Soil at the Geological High Background, Based on the Township Scale].

Due to the extensive development of carbonate rocks in southwest China, heavy metals are naturally occurring elements that have high natural background levels in the environment. Therefore, it is important to conduct ecological risk assessments and identify potential sources of heavy metals in the geological high background area. Based on the township scale, a total of 307 surface soil samples were collected in Qinglong Town, Fengjie County, Chongqing. The concentrations of As, Cd, Cr, Cu, Hg, Ni, Pb, and Zn and pH were analyzed and determined. The spatial distribution and source of soil heavy metals were discussed using the geostatistical analysis and an absolute principal component score-multiple linear regression (APCS-MLR) model in the studied area. The results showed that the average values of seven heavy metals (As, Cd, Cr, Cu, Hg, Ni, and Zn) in the arable soil exceeded the background values of Chongqing, and the cumulative effect of Cd and As was obvious. The concentrations of Cd significantly exceededthe screening values in The Risk Control Standard for Soil Environmental Quality and Soil Pollution in Agricultural Land (GB 15618-2018), with the over-standard rates of 52.12%. The spatial characteristics of soil heavy metal contents exhibited a pattern of high in the south and low in the north. PCA and APCS-MLR modeling revealed that the contributions of natural sources to Cr, Cu, Ni, and Zn were 86.62%, 64.34%, 76.44%, and 85.46%, respectively. As, Pb, and Hg mainly derived from industrial activities, which accounted for 74.63%, 61.90%, and 73.49%, respectively, and Cd was affected by both natural sources and industrial activities (accounting for 47.74% and 39.56% of the total Cd content, respectively). The evaluation of the soil by the Nemerow comprehensive index (P) showed that Cd pollution was relatively serious, accounting for 27.04% of soil pollution. The potential ecological hazard index showed that Cd and Hg were the main ecological hazard elements, and the distribution range of RI was 51.77 to 2228, indicating mainly mild and moderate risks, and the moderate and above risk areas in the study area were mainly located around the southern industrial source area. Altogether, our results revealed that in the study area, the heavy metal pollution was mainly caused by industrial activities, and the heavy metal pollution caused by geological background was mainly light to moderate. In conclusion, the medium and above risk areas in the study area were mainly caused by mineral and industrial activities, whereas the heavy metal pollution caused by geological background was mainly light to moderate pollution.

[Characteristics and Driving Factors of Hydrochemical Evolution in Tuochangjiang River Basin, Western Guizhou Province].

Tuochangjiang River is a typical mining-type watershed in the karst mountainous area of western Guizhou province. The study of its hydrochemical evolution characteristics and driving factors is of great significance to the local economic development and the scientific management of water resources. The samples of river water, spring water, and mine water in the Tuochangjiang River Basin were collected, and the sources of solutes and their contribution to the chemical components of river water were discussed by means of hydrochemical diagrams, mathematical statistics, and the absolute principal component scores-multivariate linear regression model (APCS-MLR). The results showed that the pH of the river water ranged between 7.30 to 8.31, and the TDS value ranged between 40 to 520 mg·L-1, which was mainly contributed by Ca2+, Na+, HCO3-, and SO42-. The dominant cations in river water were Ca2+ and Na+, the dominant anions were HCO3- and SO42-, and the main water chemistry transitioned from HCO3-Ca to HCO3-Ca·Na and HCO3·SO4-Ca·Na type, whereas that of the mine water was mainly the HCO3-Na and HCO3·SO4-Na types. The chemical composition of river water was affected by rock weathering, exchange adsorption of anions, mineral dissolution and precipitation, and human activities, in which Ca2+, Mg2+, and HCO3- were mainly derived from the weathering and dissolution of carbonate and silicate rocks, Na+and SO42- were mainly from the discharge of mining wastewater, and Cl- and NO3- were affected by domestic sewage and agricultural activities, respectively. APCS-MLR analysis further showed that the river water solutes mainly included five sources:discharge of mining wastewater, dissolution of soil minerals, geological background, agricultural activities, and unknown sources, and their contribution rates to river water were 23.49%, 35.04%, 13.87%, 7.96%, and 20.63%, respectively. Mining factors and soil factors were the most important sources of solutes in the river water, and they were the main driving factors for the hydrochemical evolution of the Tuochangjiang River Basin.

Contamination, Source Apportionment, and Health Risk Assessment of Heavy Metals in Farmland Soils Surrounding a Typical Copper Tailings Pond.

Tailings resulting from mining and smelting activities may cause soil heavy-metal pollution and harm human health. To evaluate the environmental impact of heavy metals from tailings on farmland soils in the surrounding area, heavy metals (As, Cd, Cr, Cu, Ni, Pb, and Zn) in tailings and farmland soils in the vicinity of a typical copper tailings pond were analyzed. Contamination status, potential sources, and health risks for farmland soils were investigated. The results showed that the tailings contained a high concentration of Cu (1136.23 mg/kg). The concentrations of Cd and Cu in the farmland soils exceeded the soil quality standard. The geoaccumulation index (Igeo) indicated that the soils were moderately polluted by Cu and Cd, and slightly polluted by Ni, Cr, and Zn. The absolute principal component scores-multiple linear regression (APCS-MLR) model was applied for source apportionment. The results showed that tailings release is the main source of soil heavy-metals contamination, accounting for 35.81%, followed by agricultural activities (19.41%) and traffic emission (16.31%). The health risk assessment suggested that the children in the study region were exposed to non-carcinogenic risks caused by As, while the non-carcinogenic risk to adults and the carcinogenic risk to both adults and children were at acceptable levels. It is necessary to take effective measures to control heavy-metal contamination from tailings releases to protect humans, especially children, from adverse health risks.

Health Risk Assessment of Heavy Metals in Groundwater of Hainan Island Using the Monte Carlo Simulation Coupled with the APCS/MLR Model.

Groundwater is a significant component of water resources, but drinking groundwater with excessive heavy metals (HMs) is harmful to human health. Currently, quantitative source apportionment and probabilistic health risk assessment of HMs in groundwater are relatively limited. In this study, 60 groundwater samples containing seven HMs were collected from Hainan Island and analyzed by the coupled absolute principal component scores/multiple linear regression (APCS/MLR), the health risk assessment (HRA) and the Monte Carlo simulation (MCS) to quantify the pollution sources of HMs and the health risks. The results show that the high-pollution-value areas of HMs are mainly located in the industry-oriented western region, but the pollution level by HMs in the groundwater in the study area is generally low. The main sources of HMs in the groundwater are found to be the mixed sources of agricultural activities and traffic emissions (39.16%), industrial activities (25.57%) and natural sources (35.27%). Although the non-carcinogenic risks for adults and children are negligible, the carcinogenic risks are at a high level. Through analyzing the relationship between HMs, pollution sources, and health risks, natural sources contribute the most to the health risks, and Cr is determined as the priority control HM. This study emphasizes the importance of quantitative evaluation of the HM pollution sources and probabilistic health risk assessment, which provides an essential basis for water pollution prevention and control in Hainan Island.

Receptor model-oriented sources and risks evaluation of metals in sediments of an industrial affected riverine system in Bangladesh.

Toxic metals in river sediments may represent significant ecological concerns, although there has been limited research on the source-oriented ecological hazards of metals in sediments. Surface sediments from an industrial affected Rupsa River were utilized in this study to conduct a complete investigation of toxic metals with source-specific ecological risk assessment. The findings indicated that the average concentration of Ni, Cr, Cd, Zn, As, Cu, Mn and Pb were 50.60 ± 10.97, 53.41 ± 7.76, 3.25 ± 1.73, 147.76 ± 36.78, 6.41 ± 1.85, 59.78 ± 17.77, 832.43 ± 71.56 and 25.64 ± 7.98 mg/kg, respectively and Cd, Ni, Cu, Pb and Zn concentration were higher than average shale value. Based on sediment quality guidelines, the mean effective range median (ERM) quotient (1.29) and Mean probable effect level (PEL) quotient (2.18) showed medium-high contamination in sediment. Ecological indexes like toxic risk index (20.73), Nemerow integrated risk index (427.59) and potential ecological risk index (610.66) posed very high sediment pollution. The absolute principle component score-multiple linear regression (APCS-MLR) and positive matrix factorization (PMF) model indicated that Zn (64.21%), Cd (51.58%), Cu (67.32%) and Ni (58.49%) in APCS-MLR model whereas Zn (49.5%), Cd (52.7%), Cu (57.4%) and Ni (44.6%) in PMF model were derived from traffic emission, agricultural activities, industrial source and mixed sources. PMF model-based Nemerow integrated risk index (NIRI) reported that industrial emission posed considerable and high risks for 87.27% and 12.72% of sediment samples. This work will provide a model-based guidelines for identifying and assessing metal sources which would be suitable for mitigating future pollution hazards in Riverine sediments in Bangladesh.

Source apportionment and risk assessment for available occurrence forms of heavy metals in Dongdahe Wetland sediments, southwest of China.

Urban wetland ecosystems are easily influenced by heavy metals (HMs) because of their functional properties. In this study, absolute principal component scores-multivariate linear regression (APCS-MLR) and positive matrix factorization (PMF) receptor models were applied for the source apportionment of available occurrence forms of heavy metals (AHMs) of surface sediments in a typical urban wetland of Dianchi Lake, southwest of China. The risk assessment was conducted to evaluate the potential ecological/human health risks of HMs. Results indicated that Zn, Pb, and Cr were the major pollutants affected by anthropogenic activities in sediments and their concentrations were significantly exceeding the background value. Most of the highly AHMs-polluted area was close to the river in wetland, and the concentration distribution of all AHMs were generally low in the southwest and high in the northeast. Both APCS-MLR and PMF models identified three comparable classes of potential sources, namely (1) agricultural fertilizer/insecticide, atmospheric deposition, and traffic emissions; (2) natural transitions; and (3) industrial and sewage wastes. Moreover, the comparison results implied that the PMF model was more feasible for quantifying AHMs sources in wetland sediments since it is capable to analyze one more source, namely plant maintenance and waterfowl feeding, and has higher accuracy in predicting the concentrations of AHMs. In addition, the risk assessment model revealed that all these HMs were within the acceptable ranges of ecological and carcinogenic/non-carcinogenic human health risks. Among these, ingestion was the major exposure pathway of HMs from local areas, followed by dermal exposure and oral or nasal inhalation. However, children were more easily exposed to HMs than adults by ingestion due to their hand-to-mouth behaviors. This study aims to assess the HM pollution status in a plateau urban wetland, and provides a practical case for modeling source apportionment and risk assessment of HMs in wetland sediments.

Receptor model-based source apportionment and ecological risk of metals in sediments of an urban river in Bangladesh.

Metal accumulation (As, Cd, Cr, Cu, Fe, Hg, Mn, Ni, Pb, and Zn) in Korotoa River sediment was studied in order to determine the metal content, distribution, sources, and their possible ecological impacts on the riverine ecosystem. Our study found significant spatial patterns of toxic metal concentration and principal coordinate analysis (PCoA) accounted for 45.2% of spatial variation from upstream to downstream. Metal contents were compared to sediment quality standards and found all studied metal concentrations exceeded the Threshold Effect Level (TEL) whereas Cr and Ni surpassed probable effect levels. All metal concentrations were higher than Average Shale Value (ASV) except Mn and Hg. The positive matrix factorization (PMF) and absolute principal component score-multiple linear regression models (APCS-MLR) were applied to identify promising sources of metals in sediment samples. Both models identified three potential sources i.e. natural source, traffic emission, and industrial pollution, which accounted for 50.32%, 20.16%, and 29.51% in PMF model whereas 43.56%, 29.42%, and 27.02% in APCS-MLR model, respectively. Based on ecological risk assessment, pollution load index (7.74), potential ecological risk (1078.45), Nemerow pollution index (5.50), and multiple probable effect concentrations quality (7.73) showed very high contamination of toxic metal in sediment samples.

[Source Apportionment of Soil PAHs in Lanzhou Based on GIS and APCS-MLR Model].

To evaluate the pollution by polycyclic aromatic hydrocarbons (PAHs) in the surface soil of the core urban area of Lanzhou, 62 topsoil samples were collected from the area. The soil samples were analyzed for the content of 16 priority PAHs, using gas chromatography-mass spectrometry. Descriptive statistical methods were used to characterize contamination by PAHs. An absolute principal component analysis-multiple linear regression (APCS-MLR) model was applied to determine the sources of PAHs in the soil samples, and the accuracy of the model results was verified. Finally, the main influence regions of each source were determined with a geo-statistical method. The results showed that the contents of Σ16 PAHs in the surface soils of Lanzhou ranged from 1069 to 7377 µg ·kg-1, with an average of 2423 µg ·kg-1. High molecular weight PAHs (4-6 rings) were dominant, accounting for 72.81% of the Σ16 PAHs. Verification results of the APCS-MLR model showed that the measured values were in good correspondence with the predicted values, which indicated that the model had good applicability for source apportionment of soil PAHs in the study area. The main sources of PAHs in Lanzhou were traffic emissions (35.42%), petroleum emissions (29.88%), and a mixture of coal and biomass combustion (33.91%). The sources were greatly affected by human activities, and high values were mainly distributed in traffic-intensive and industrial areas. The results indicated that the sources of soil PAHs were complex and influenced by anthropogenic activities in the study area. Stringent control measures should be placed on the sources and areas of influence that contribute to soil PAHs to reduce the emissions and the level of soil pollution resulting from PAHs.