Combination of UNMIX, PMF model and Pb-Zn-Cu isotopic compositions for quantitative source apportionment of heavy metals in suburban agricultural soils

Pollution characteristics and quantitative source apportionment of heavy metals within a zinc smelting site by GIS-based PMF and APCS-MLR models

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

Determination of contamination sources and geochemical reactions in groundwater of a mine area using Cu, Zn, and S-O isotopes

To determine contamination sources and pathways, the use of multiple isotopes, including metal isotopes, can increase the reliability of environmental forensic techniques. This study differentiated contamination sources in groundwater of a mine area and elucidated geochemical processes using Cu, Zn, S-O, and O-H isotopes. Sulfate reduction and sulfide precipitation were elucidated using concentrations of dissolved sulfides, δ34SSO4, δ18OSO4, and δ66Zn. The overlying contaminated soil was possibly responsible for the contamination of groundwater at <5 mbgl, which was suggested by low δ65Cu values (0.419-1.120‰) reflecting those of soil (0.279-1.115‰). The existence of dissolved Cu as Cu(I) may prevent the increase in δ65Cu during leaching of contaminated soil in the sulfate-reducing environment. In contrast, the groundwater at >5 mbgl seemed to be highly affected by the contamination plume from the adit water, which was suggested by high SO42- concentrations (407-447 mg L-1) and δ65Cu (0.252-2.275‰) and δ66Zn (-0.105‰-0.362‰) values at a multilevel sampler approaching those of the adit seepages. Additionally, the O-H isotopic ratios were distinguished between <5 mbgl and >5 mbgl. Using δ65Cu and δ66Zn to support the determination of groundwater contamination sources may be encouraged, particularly where the isotopic signatures are distinct for each source.

A comprehensive study of source apportionment, spatial distribution, and health risks assessment of heavy metal(loid)s in the surface soils of a semi-arid mining region in Matehuala, Mexico

BACKGROUND

This study investigates the contamination level, spatial distribution, pollution sources, potential ecological risks, and human health risks associated with heavy metal(loid)s (i.e., arsenic (As), copper (Cu), iron (Fe), manganese (Mn), lead (Pb), and zinc (Zn)) in surface soils within the mining region of Matehuala, located in central Mexico.

OBJECTIVES

The primary objectives are to estimate the contamination level of heavy metal(loid)s, identify pollution sources, assess potential ecological risks, and evaluate human health risks associated with heavy metal(loid) contamination.

METHODS

Soil samples from the study area were analysed using various indices including Igeo, Cf, PLI, mCd, EF, and PERI to evaluate contamination levels. Source apportionment of heavy metal(loid)s was conducted using the APCS-MLR and PMF receptor models. Spatial distribution patterns were determined using the most efficient interpolation technique among five different approaches. The total carcinogenic risk index (TCR) and total non-carcinogenic index (THI) were used in this study to assess the potential carcinogenic and non-carcinogenic hazards posed by heavy metal(loid)s in surface soil to human health.

RESULTS

The study reveals a high contamination level of heavy metal(loid)s in the surface soil, posing considerable ecological risks. As was identified as a priority metal for regulatory control measures. Mining and smelting activities were identified as the primary factors influencing heavy metal(loid) distributions. Based on spatial distribution mapping, concentrations were higher in the northern, western, and central regions of the study area. As and Fe were found to pose considerable and moderate ecological risks, respectively. Health risk evaluation indicated significant levels of carcinogenic risks for both adults and children, with higher risks for children.

CONCLUSION

This study highlights the urgent need for monitoring heavy metal(loid) contamination in Matehuala's soils, particularly in regions experiencing strong economic growth, to mitigate potential human health and ecological risks associated with heavy metal(loid) pollution.

Distribution, risk evaluation, and source allocation of cesium and strontium in surface soil in a mining city

Radioactive nuclides cesium (Cs) and strontium (Sr) possess long half-lives, with 135Cs at approximately 2.3 million years and 87Sr at about 49 billion years. Their persistent accumulation can result in long-lasting radioactive contamination of soil ecosystems. This study employed geo-accumulation index (Igeo), pollution load index (PLI), potential ecological risk index (PEPI), health risk assessment model (HRA), and Monte Carlo simulation to evaluate the pollution and health risks of Cs and Sr in the surface soil of different functional areas in a typical mining city in China. Positive matrix factorization (PMF) model was used to elucidate the potential sources of Cs and Sr and the respective contribution rates of natural and anthropogenic sources. The findings indicate that soils in the mining area exhibited significantly higher levels of Cs and Sr pollution compared to smelting factory area, agricultural area, and urban residential area. Strontium did not pose a potential ecological risk in any studied functional area. The non-carcinogenic health risk of Sr to the human body in the study area was relatively low. Because of the lack of parameters for Cs, the potential ecological and human health risks of Cs was not calculated. The primary source of Cs in the soil was identified as the parent material from which the soil developed, while Sr mainly originated from associated contamination caused by mining activities. This research provides data for the control of Cs and Sr pollution in the surface soil of mining city.

Isotopic insights and integrated analysis for heavy metal levels, ecological risks, and source apportionment in river sediments of the Qinghai-Tibet Plateau

The research was carried out to examine the pollution characteristics, ecological risk, and origins of seven heavy metals (Hg, As, Pb, Cu, Cd, Zn, and Ni) in 51 sediment samples gathered from 8 rivers located on the Qinghai-Tibet Plateau (QTP) in China. The contents of Hg and Cd were 5.0 and 1.1 times higher than their background values, respectively. The mean levels of other measured heavy metals were below those found naturally in the local soil. The enrichment factor showed that the study area exhibited significantly enriched Hg with 70.6% sampling sites. The Cd contents at 19.6% of sampling sites were moderately enriched. The other sampling sites were at a less enriched level. The sediments of all the rivers had a medium level of potential ecological risk. Hg was the major ecological risk factor in all sampling sites, followed by Cd. The findings from the positive matrix factorization (PMF) analysis shown agricultural activities, industrial activities, traffic emissions, and parent material were the major sources. The upper, middle, and low reaches of the Quanji river had different Hg isotope compositions, while sediments near the middle reaches were similar to the δ202Hg of the industrial source. At the upstream sampling sites, the Hg isotope content was very close to the background level. The results of this research can establish a strong scientific sound to improve the safety of the natural circumstances of rivers on the QTP.

Health risk assessment of soil heavy metals in a typical mining town in north China based on Monte Carlo simulation coupled with Positive matrix factorization model

The accumulation of heavy metals (HMs) in soil caused by mineral resource exploitation and its ancillary industrial processes poses a threat to ecology and public health. Effective risk control measures require a quantification of the impacts and contributions to health risks from individual sources of soil HMs. Based on high-density sampling, soil contamination risk indexes, positive matrix factorization (PMF) model, Monte Carlo simulation and human health risk analysis model were applied to investigate the risk of HMs in a typical mining town in North China. The results showed that As was the most dominant soil pollutant factor, Cd and Hg were the most dominant soil ecological risk factors, and Cr and Ni were the most dominant health risk factors in the study area. Overall, both pollution and ecological risks were at low levels, while there were still some higher hazard areas located in the central and south-central part of the region. According to the probabilistic health risk assessment (HRA), children suffered greater health risks than adults, with 21.63% of non-carcinogenic risks and 53.24% of carcinogenic risks exceeding the prescribed thresholds (HI > 1 and TCR>1E-4). The PMF model identified five potential sources: fuel combustion (FC), processing of building materials with limestone as raw materials (PBML), industry source (IS), iron ore mining combined with garbage (IOG), and agriculture source (AS). PBML is the primary source of soil HM contamination, as well as the major anthropogenic source of carcinogenic risk for all populations. Agricultural inputs associated with As are the major source of non-carcinogenic risk. This study offers a good example of probabilistic HRA using specific sources, which can provide a valuable reference for strategy establishment of pollution remediation and risk prevention and control.

A Modified Model for Quantitative Heavy Metal Source Apportionment and Pollution Pathway Identification

Current source apportionment models have successfully identified emission sources and quantified their contributions. However, when being utilized for heavy metal source apportion in soil, their accuracy needs to be improved, regarding migration patterns. Therefore, this work intended to improve the pre-existing principal component analysis and multiple linear regression with distance (PCA-MLRD) model to effectively locate pollution pathways (traffic emissions, irrigation water, atmospheric depositions, etc.) and achieve a more precise quantification. The dataset of soil heavy metals was collected from a typical area in the Chang-Zhu-Tan region, Hunan, China in 2021. The identification of the contribution of soil parent material was accomplished through enrichment factors and crustal reference elements. Meanwhile, the anthropogenic emission was identified with principal component analysis and GeoDetector. GeoDetector was used to accurately point to the pollution source from a spatial differentiation perspective. Subsequently, the pollution pathways linked to the identified sources were determined. Non-metal manufacturing factories were found to be significant anthropogenic sources of local soil contamination, mainly through rivers and atmospheric deposition. Furthermore, the influence of irrigation water on heavy metals showed a more pronounced effect within a distance of 1000 m, became weaker after that, and then gradually disappeared. This model may offer improved technical guidance for practical production and the management of soil heavy metal contamination.

Anthropogenic processes drive spatiotemporal variability of sulfate in groundwater from a multi-aquifer system: Dilution caused by mine drainage

The water quality evolution of surface and groundwater caused by mining activities and mine drainage is a grave public concern worldwide. To explore the effect of mine drainage on sulfate evolution, a multi-aquifer system in a typical coal mine in Northwest China was investigated using multi-isotopes (δ34SSO4, δ18OSO4, δD, and δ18Owater) and Positive Matrix Factorization (PMF) model. Before mining, the Jurassic aquifer was dominated by gypsum dissolution, accompanied by cation exchange and bacterial sulfate reduction, and the phreatic aquifers and surface water were dominated by carbonate dissolution. Significant increase in sulfate in phreatic aquifers due to mine drainage during the early stages of coal mining. However, in contrast to common mining activities that result in sulfate contamination from pyrite oxidation, mine drainage in this mining area resulted in accelerated groundwater flow and enhanced hydraulic connections between the phreatic and confined aquifers. Dilution caused by the altered groundwater flow system controlled the evolution of sulphate, leading to different degrees of sulfate decrease in all aquifers and surface water. As the hydrogeochemical characteristic of Jurassic aquifer evolved toward phreatic aquifer, this factor should be considered to avoid misjudgment in determining the source of mine water intrusion. The study reveals the hydrogeochemical evolution induced by mine drainage, which could benefit to the management of groundwater resources in mining areas.

Integrated pollution analysis, pollution area identification and source apportionment of heavy metal contamination in agricultural soil

Given the global prevalence of soil heavy metal contamination, knowledge concerning of soil environmental quality assessment, pollution area identification and source apportionment is critical for implementation of soil pollution prevention and safe utilization strategies. In this study, soil static environmental capacity (QI) for heavy metals was selected to evaluate pollution risks in agricultural soils of Wenzhou, southeast China. Combined with geostatistical methods, the pollution area was identified along with uncertainty analysis. Potential sources were quantitatively apportioned using a positive matrix factorization model (PMF). Results showed that agricultural soils in this study were mainly contaminated by Cd and Pb based on both Nemerow and QI indices. The environmental capacity assessment found more than 90% areas were identified as polluted soils for Qi-Zn, Qi-Cd and Qi-Pb, with minor uncertain areas. Cu was identified as having a high proportion of uncertain pollution area status, which was similar to the results of the integrated environmental capacity for all metals. PMF results indicated that industrial discharge, agrochemicals and parent material accounted for 32.1%, 32.2% and 35.7% of heavy metal accumulation in soils, respectively. Implementation of strict policies to reduce anthropogenic source emissions and remediate soil pollution are crucial to minimize metal pollution inputs, improve agricultural soil quality and enhance food safety.

Using machine learning to trace the pollution sources of disinfection by-products precursors compared to receptor models

To increase the efficiency of managing backup water resources, it is critical to identify and allocate pollution sources. Source apportionment of dissolved organic matter (DOM) was investigated in our work. Parallel factor analysis (PARAFAC) and the Spearman correlation analysis were used for source identification. After that, a newly hybrid model applying the fuzzy c-means and support vector regression (FCM-SVR) was employed for source apportionment compared to receptor models. The results demonstrated that the FCM-SVR model exhibited excellent generalization, and only required standardization and normalization as pre-processing steps for dataset. According to the results, microbial sources played a key role (28.1 %) in the formation potential of disinfection byproducts (DBPFPs). Additionally, shipping marine sources exhibited a substantial contribution (21.2 %) to DBPFPs. The prediction accuracy of DBPFPs was matched or exceeded receptor models, and the R2 of DOC (0.884) was significantly high. Therefore, we recommend the FCM-SVR model combined with PARAFAC to trace the source of DBPFPs as its significant effectiveness in source identification, source apportionment, and prediction accuracy, possessing the potential for further applicability in tracking more organic compounds. ENVIRONMENTAL IMPLICATION: The disinfection byproducts precursors in water sources, which were thought to be hazardous materials in this study, are proved to be chlorinated into carcinogenic disinfection byproducts (DBPs) during drinking water treatment, However, the source apportionment methods of DBPs are not well developed compared to other inorganic matter, e.g., heavy metals and ammonia nitrogen. We proposed a new FCM-SVR model to trace the source of DBPs, which required easier pre-treatment and resulted a better source apportionment and prediction accuracy. As a result, it could provide a different prospect and useful management advices to trace the source of DBPs.

Discrimination of metal contaminant sources in river sediments influenced by mining and smelting activities using stable Pb and Zn isotopes

To determine the sources and pathways of lead (Pb) and zinc (Zn) in river sediments contaminated with metals from mining and smelting activities, metal concentrations and Pb and Zn isotope ratios were measured in river water and sediment, and potential metal contaminant samples (imported Zn concentrates, smelting wastes, soils around the smelter, mine ores, and riverside tailings). Zn and cadmium (Cd) concentrations in river water and sediment samples were 30- and 11-25-fold higher, respectively, near the smelter than upstream, while a 6-fold increase in sediment Pb concentrations was detected over the same region. Sediment samples near the smelter (207Pb/206Pb = 0.8638 and 208Pb/206Pb = 2.0960) were observed to have a different Pb isotopic composition from upstream of the smelter (207Pb/206Pb = 0.8322 and 208Pb/206Pb = 2.0502), with δ66Zn values increasing from -0.01 to 0.82‰. Analysis of Pb and Zn isotopes and concentrations revealed that dust-contaminated soils were a major Pb source, and baseline sediments were found to be contaminated by regional mining tailings. For Zn in sediments, the main Zn sources were groundwater-derived Zn (δ66Zn = 1.02 ± 0.43‰, n = 4), dust-contaminated soils (δ66Zn = -0.18 ± 0.08‰, n = 3), and tailings-contaminated sediments (δ66Zn = 0.01 ± 0.07‰, n = 10). Endmember mixing model results showed that dust-contaminated soils contributed 78% and 64% of sediment Pb and Zn, respectively, within 2 km of the Zn smelter, decreasing to negligible levels after 47.1 km downstream. Downstream of the smelter, groundwater-derived Zn contributed 54% of sediment Zn, whereas tailings contaminated sediments contributed 70% and 25% of Pb and Zn, respectively.

Health risk assessment of heavy metals in wild fish and seasonal variation and source identification of heavy metals in sediments: a case study of typical urban river in Xi'an, China

In order to determine the status of heavy metal pollution in river sediments and wild fish in Xi'an, concentrations of heavy metals (Cr, Ni, Cu, Zn, As, and Pb) were collected and analyzed in sediments and wild fish during dry season (October-November 2020) and wet season (June-July 2021). This study aimed to investigate the spatial and temporal variations of heavy metals in urban rivers of Xi'an, China. Their distribution characteristics and sources as well their pollution levels and health risks were assessed. The findings revealed that influenced by human activities, the heavy metal content in sediments (mg·kg-1 dry weight) in wet season was ranked as follows: Cr (73.09) > Zn (63.73) > Pb (40.31) > Ni (31.52) > Cu (24.86) > As (6.83); in the dry season: Zn (94.07) > Cr (69.59) > Cu (34.24) > Ni (33.60) > Pb (32.87) > As (7.60). Moreover, 32 fish samples from six species indicated an average metal content trend (mg·kg-1 wet weight) of Zn (8.70) > Cr (0.57) > Pb (0.28) > Ni (0.27) > Cu (0.24) > As (0.05). The potential ecological risk indices for sediment heavy metal concentrations in both seasons were well below the thresholds, which indicates that the aquatic environment is in safe level. The analysis of the potential ecological risk of sediment heavy metal concentrations indicates that the aquatic environment is safe for the time being. Based on the estimated daily intake (EDI), target risk quotient (THQ), total target risk quotient (TTHQ), cancer risk (CR), total cancer risk (TCR), and the permissible safety limits set by the agencies, the consumption of the fish examined is safe for human health. However, the presence of Cr and As in wild fish should still be a concern for human health, especially for children. The cumulative effect of heavy metals and the bioconcentration factor (BCF) suggest that sediment and heavy metals in fish are closely related, with higher concentrations in fish living in the bottom layer of the water column than in other water layers, and increasing with increasing predator levels. Correlation analysis and PMF modeling identified and determined four comparable categories of potential sources, namely, (1) atmospheric deposition and traffic sources, (2) agricultural sources, (3) industrial sources, and (4) natural sources.

Field application of hydroxyapatite and humic acid for remediation of metal-contaminated alkaline soil

The quality of soil is essential for ensuring the safety and quality of agricultural products. However, soils contaminated with toxic metals pose a significant threat to agricultural production and human health. Therefore, remediation of contaminated soils is an urgent task, and humic acid (HA) with hydroxyapatite (HAP) materials was applied for this study in contaminated alkaline soils to remediate Cd, Pb, Cu, and Zn. Physiochemical properties, improved BCR sequential extraction, microbial community composition in soils with superoxide dismutase (SOD), peroxidase (POD), and chlorophyll content in plants were determined. Among the studied treatments, application of HAP-HA (2:1) (T7) had the most significant impact on reducing the active forms of toxic metals from soil such as Cd, Pb, Cu, and Zn decreased by 18.59%, 9.12%, 11.83%, and 3.33%, respectively, but HAP and HA had a minor impact on metal accumulation in Juncao. HAP (T2) had a beneficial impact on reducing the TCleaf/root of Cd, Cu, and Zn, whereas HAP-HA (T5) showed the best performance for reducing Cd and Cu in EFleaf/soil. HAP-HA (T5 and T7) showed higher biomass (57.3%) and chlorophyll (17.9%), whereas HAP (T4) showed better performance in POD (25.8%) than T0 in Juncao. The bacterial diversity in soil was increased after applying amendments of various treatments and enhancing metal remediation. The combined application of HAP and HA effectively reduced active toxic metals in alkaline soil. HAP-HA mixtures notably improved soil health, plant growth, and microbial diversity, advocating for their use in remediating contaminated soils.

Application of Cu isotopes to identify Cu sources in soils impacted by multiple anthropogenic activities

Copper (Cu) is an important micronutrient for animals and plants, but it is toxic at high concentrations in soil. Soils adjacent to industrial areas would be subjected to severe Cu pollution. Identifying Cu sources in the surface environment is crucial for understanding their pollution level and fate. This study investigated Cu content, isotope composition of topsoils, and two soil profiles with varying levels of Cu contamination and related potential Cu sources in southwest China. The difference in Cu isotope compositions of tailing (1.29 ± 0.08 ‰), smelting fly ash (0.04 ± 0.03 ‰), coal (2.44 ± 0.09 ‰), coal-burning fly ash (0.34 ± 0.03 ‰), and geogenic soil (0.10 ± 0.03 ‰) enabled us to distinguish anthropogenic Cu from geogenic Cu. The plot of δ65Cu and 1/Cu demonstrates that Cu of the polluted soils was from three end-members: the smelting fly ash, the vehicle exhaust, and the background soils. Based on the mass balance model, we calculated that the fly ash from smelting was the major anthropogenic source, contributing approximately 29 % of Cu contamination in soils, and the diesel exhaust was another important source, with a contribution rate of approximately 25 %. Additionally, soil profile results suggest that anthropogenic Cu could transport through soil profiles and influence Cu content and isotope signatures of subsurface soils, at least to a depth of ∼60 cm. Finally, our research indicates that Cu isotopes could be a promising tool for tracing industrial pollution, as significant Cu isotope fractionation would occur during the smelting process. Our research highlights the contribution of smelting and diesel exhaust to Cu contamination in the soils in a representative mining area. These findings serve as a scientific foundation for the development of policy for pollution control in industrial-affected regions.

An integrated overview of metals contamination, source-specific risks investigation in coal mining vicinity soils

Heavy metals in soil are harmful to natural biodiversity and human health, and it is difficult to estimate the effects accurately. To reduce pollution and manage risk in coal-mining regions, it is essential to evaluate risks for heavy metals in soil. The present study reviews the levels of 21 metals (Nb, Zr, Ag, Ni, Na, K, Mg, Rb, Zn, Ca, Sr, As, Cr, Fe, Pb, Cd, Co, Hg, Cu, Mn and Ti) in soils around Barapukuria coal-mining vicinity, Bangladesh which were reported in literature. An integrated approach for risk assessments with the positive matrix factorization (PMF) model, source-oriented ecological and health hazards were applied for the study. The contents of Rb, Ca, Zn, Pb, As, Ti, Mn, Co, Ag, Zr, and Nb were 1.63, 1.10, 1.97, 14.12, 1.20, 3.13, 1.22, 3.05, 3.85, 5.48, and 7.21 times greater than shale value. About 37%, 67%, 12%, and 85% of sampling sites posed higher risks according to the modified contamination factor, Nemerow pollution index, Nemerow integrated risk index, and mean effect range median quotient, respectively. Five probable metal sources were computed, including industrial activities to coal mining (17%), agricultural activities (33%), atmospheric deposition (19%), traffic emission (16%), and natural sources (15%). Modified Nemerow integrated risk index reported that agricultural activities, industrial coal mining activities, and atmospheric deposition showed moderate risk. Health hazards revealed that cancer risk values computed by the PMF-HHR model with identified sources were higher than the standard value (1.0E-04) for children, adult male, and female. Agricultural activities showed higher cancer risks to adult male (39%) and children (32%) whereas traffic emission contributed to female (25%). These findings highlight the ecological and health issues connected to potential sources of metal contamination and provide useful information to policymakers on how to reduce such risks.

Source apportionment of heavy metal(loid)s in sediments of a typical karst mountain drinking-water reservoir and the associated risk assessment based on chemical speciations

As important place for water storage and supply, drinking-water reservoirs in karst mountain areas play a key role in ensuring human well-being, and its water quality safety has attracted much attention. Source apportionment and ecological risks of heavy metal(loid)s in sediments of drinking-water reservoir are important for water security, public health, and regional water resources management, especially in karst mountain areas where water resources are scarce. To expound the accumulation, potential ecological risks, and sources of heavy metal(loid)s in a drinking-water reservoir in Northwest Guizhou, China, the surface sediments were collected and analyzed based on the combined use of the geo-accumulation index (Igeo), sequential extraction (BCR), ratios of secondary phase and primary phase (RSP), risk assessment code (RAC), modified potential ecological risk index (MRI), as well as the positive matrix factorization methods. The results indicated that the accumulation of Cd in sediments was obvious, with approximately 61.9% of the samples showing moderate to high accumulation levels, followed by Pb, Cu, Ni, and Zn, whereas the As and Cr were at low levels. A large proportion of BCR-extracted acid extractable and reducible fraction were found in Cd (72.5%) and Pb (40.3%), suggesting high bioavailability. The combined results of RSP, RAC, and MRI showed that Cd was the major pollutant in sediments with high potential ecological risk, while the risk of other elements was low. Source apportionment results of heavy metal(loid)s indicated that Cd (75.76%) and Zn (23.1%) mainly originated from agricultural activities; As (69.82%), Cr (50.05%), Cu (33.47%), and Ni (31.87%) were associated with domestic sources related to residents' lives; Cu (52.36%), Ni (44.57%), Cr (34.33%), As (26.51%), Pb (24.77%), and Zn (23.80%) primarily came from natural geological sources; and Pb (47.56%), Zn (22.46%) and Cr (13.92%) might be introduced by mixed sources of traffic and domestic. The contribution ratios of the four sources were 18.41%, 36.67%, 29.48%, and 15.44%, respectively. Overall, priority control factors for pollution in relation to agricultural sources included Cd, while domestic sources are primarily associated with As. It is crucial to place special emphasis on the impacts of human activities when formulating pollution prevention and control measures. The results of this study can provide valuable reference and insights for water resources management and pollution prevention and control strategies in karst mountainous areas.

Heavy metals contamination, receptor model-based sources identification, sources-specific ecological and health risks in road dust of a highly developed city

The present study quantified Ni, Cu, Cr, Pb, Cd, As, Zn, and Fe levels in road dust collected from a variety of sites in Tangail, Bangladesh. The goal of this study was to use a matrix factorization model to identify the specific origin of these components and to evaluate the ecological and health hazards associated with each potential origin. The inductively coupled plasma mass spectrometry was used to determine the concentrations of Cu, Ni, Cr, Pb, As, Zn, Cd, and Fe. The average concentrations of these elements were found to be 30.77 ± 8.80, 25.17 ± 6.78, 39.49 ± 12.53, 28.74 ± 7.84, 1.90 ± 0.79, 158.30 ± 28.25, 2.42 ± 0.69, and 18,185.53 ± 4215.61 mg/kg, respectively. Compared to the top continental crust, the mean values of Cu, Pb, Zn, and Cd were 1.09, 1.69, 2.36, and 26.88 times higher, respectively. According to the Nemerow integrated pollution index (NIPI), pollution load index (PLI), Nemerow integrated risk index (NIRI), and potential ecological risk (PER), 84%, 42%, 30%, and 16% of sampling areas, respectively, which possessed severe contamination. PMF model revealed that Cu (43%), Fe (69.3%), and Cd (69.2%) were mainly released from mixed sources, natural sources, and traffic emission, respectively. Traffic emission posed high and moderate risks for modified NIRI and potential ecological risks. The calculated PMF model-based health hazards indicated that the cancer risk value for traffic emission, natural, and mixed sources had been greater than (1.0E-04), indicating probable cancer risks and that traffic emission posed 38% risk to adult males where 37% for both adult females and children.

Heavy metals distribution characteristics, source analysis, and risk evaluation of soils around mines, quarries, and other special areas in a region of northwestern Yunnan, China

In this study, based on the assessment of soil heavy metals (HMs) pollution using relevant indices, a comprehensive approach combined network environ analysis (NEA), human health risk assessment (HHRA) method and positive definite matrix factor (PMF) model to quantify the risks among ecological communities in a special environment around mining area in northwest Yunnan, calculated the risk to human health caused by HMs in soil, and analyzed the pollution sources of HMs. The integrated risks for soil microorganisms, vegetations, herbivores, and carnivores were 2.336, 0.876, 0.114, and 0.082, respectively, indicating that soil microorganisms were the largest risk receptors. The total hazard indexes (HI_T) for males, females, and children were 0.542, 0.591, and 1.970, respectively, revealing a relatively high and non-negligible non-carcinogenic risks (NCR) for children. The total cancer risks (TCR) for both females and children exceeded 1.00E-04, indicating that soil HMs posed carcinogenic risks (CR) to them. Comparatively, Pb was the high-risk metal, accounting for 53.76%, 57.90%, and 68.09% of HI_T in males, females, and children, respectively. PMF analysis yielded five sources of pollution, F1 (industry), F2 (agriculture), F3 (domesticity), F4 (nature), and F5 (traffic).

Adsorption-desorption characteristics of typical heavy metal pollutants in submerged zone sediments: a case study of the Jialu section in Zhengzhou, China

In recent years, the accumulation ability of heavy metals in sediment has become a key indicator for sediment pollution prevention and control. The adsorption-desorption processes of typical heavy metal pollutants in sediments under different conditions were explored and relied in this article. In addition, different binary competitive adsorption systems were designed to study the competitive adsorption properties of heavy metal contaminants, The quasi-secondary kinetic model simulated the adsorption kinetic process. The sediment adsorption rates for heavy metals were (in descending order) Cu, Pb, Cd, Zn. The Elovich equation simulated the desorption kinetics process better, and the sediment desorption rates for heavy metals were (in descending order) Cd, Cu, Zn, Pb. The average free adsorption energy E of heavy metals was within the range of 8-16 kJ∙mol-1. After the removal of organic matter, the ability of the sediment to sequester heavy metals decreases, The binary competitive adsorption results showed that the presence of interfering ions had the greatest effect on Cd and the least effect on Pb. The adsorption and desorption of the four heavy metals by the sediments in the submerged zone increased with the increase of temperature, and the ratio of desorption to adsorption also increased therewith: the adsorptions of heavy metals by the sediments were all spontaneous processes (under heat absorption reactions). The presence of organic matter can increase the ability of the sediment to sequester Cd, Pb, Cu, and Zn. Additionally, heavy metals exhibited significant selective adsorption properties.

Characteristics and pollution risks of potentially toxic elements and nematode community structure on farm soil near coal mines

As one of the most important coal-producing provinces of China, Shanxi Province has been concerned about soil potentially toxic elements (PTEs) contamination in recent years. The study aimed to determine the status and sources of PTEs contamination and evaluate the quality of the soil ecology. This study investigated the degree of 13 PTEs contamination. The sources and contributions of PTEs were traced by the absolute principal component score followed by a multiple linear regression model (APCS-MLR). And the status of the soil ecosystem was verified by evaluating the soil nematode community around the coal mining areas in Jinzhong. The results showed that the mean PTEs concentration of 5 trace elements were higher than the background values of Shanxi, and safe to considerable was indicated by the pollution and ecological risk values. Soil Hg was the most contaminated element, followed by Cd. The distribution of PTEs was determined by coal mining activities (44.72%) followed by agricultural practice (32.37%) and coal transportation (21.37%). The nematode genera Acrobeloides (4.01%), Aphelenchus (20.30%), Meloidogyne (11.95%) and Aporcelaimus (2.74%) could be regarded as bioindicators of soil PTEs contamination by their tolerance. Concentrations of soil Cr, Mn, Ti and Cd showed remarkable influences on the total nematode abundance, maturity index, enrichment index, structural index, Shannon-Wiener diversity index and Pielou index of soil nematode. It is an appropriate method to evaluate the status of soil PTEs contamination combining the response of a single nematode genus and the nematode community evaluation index.

Attribution of sources to heavy metal accumulation in the anthropogenically impacted Bach Dang River Estuary, Vietnam

In the present study, concentrations of 10 heavy metals (Ti, Cr, Mn, Fe, Ni, Cu, Zn, As, Cd and Pb) were determined in superficial sediments from 20 sites within the Bach Dang Estuary, Vietnam. An integrated approach including correlation analysis, principal components analysis and positive matrix factorization was successfully applied to identify possible sources of these heavy metals. The results of this study identified four sources of the heavy metals, namely: natural geogenic, mixed anthropogenic, marine transportation and antifouling paint related sources, contributing 34.33 %, 14.80 %, 23.02 % and 27.86 % to the total metal concentrations, respectively. From an environmental impact perspective, these findings could provide a scientific basis for prevention and control of sediment metal pollution. Accordingly, the use of more environmental friendly antifouling paints should be encouraged to minimize metal accumulation in sediments.

Source apportionment and transfer characteristics of Pb in a soil-rice-human system, Jiulong River Basin, southeast China

The source apportionment and transfer of Pb in a paddy soil-rice-human system within the Jiulong River Basin in southeast China was investigated by analyzing (1) the chemical fractionation of Pb in paddy soils using a modified BCR four-step sequential extraction procedure, and (2) the bioaccessibility of Pb in both paddy soils and rice grains using a Simple Bioaccessibility Extraction Test method. In addition, a qualitative Pb isotopic model was used in combination with IsoSource software to quantify the contribution of potential Pb sources. The results show the enrichment of Pb in agro-ecosystems in the Jiulong River Basin. Contaminant Pb in paddy soils was mainly present in the reducible (42.9%) and the residual fractions (27.1%). The average bioaccessibility of Pb in rice grains was significantly higher than that in paddy soil, with values of 77.85% and 37.44%, respectively. Lead in paddy soils was primarily derived from agricultural (35.3%), natural (25.5%), industrial (24.5%) and coal combustion sources (14.7%), while Pb in rice grains was primarily derived from coal combustion (54.1%), agricultural (35.1%), industrial (6.0%) and natural sources (4.8%). The bioaccessible Pb was mainly derived from anthropogenic sources [agricultural (42.3% for soil and 25.3% for grain) and coal combustion sources (25.3% for soil and 59.3% for grain)]. Lead isotopic ratios are an effective tracer of Pb transfer from potential sources to rice plants and within the rice plants. Rice plants absorb Pb from the soil and the atmosphere through the roots and leaves, respectively. Most of the Pb was accumulated in roots. The integrated use of chemical fractionation, bioaccessibility and Pb isotopic data provides an effective method to study the source apportionment and transfer characteristics of Pb in paddy soil-rice-human systems.

Human health-risk assessment of heavy metal-contaminated soil based on Monte Carlo simulation

Soil contamination soils of by heavy metals (HMs) poses serious threats to the soil environment and enters the human body through exposure pathways such as ingestion and skin contact, posing a threat to human health. The purpose of this study was to analyze the sources and contributions of soil HMs, and to quantitatively assess the human health risks of soil HMs to different populations (i.e. children, adult females and adult males), and to analyze the human health risks caused by various sources of sensitive populations. 170 topsoil (0-20 cm) were collected from Fukang, Jimsar and Qitai on the northern slope of Tianshan Mountains in Xinjiang, China, and the contents of Zn, Cu, Cr, Pb and Hg were determined. This study used the Unmix model and a health-risk assessment (HRA) model to assess the human health risks of five HMs. The results showed that: (1) The mean values of Zn and Cr were lower than the background values of Xinjiang, the mean values of Cu and Pb were slightly higher than the background values of Xinjiang but lower than the national standard, and the mean value of Hg and Pb was higher than the background value of Xinjiang and the national standard. (2) The sources of soil HMs in the region were mainly traffic, natural, coal, and industrial sources. Moreover, the HRA model combined with Monte Carlo simulation showed similar trends in the health-risk status of all population groups in the region. Probabilistic HRA revealed that noncarcinogenic risks were acceptable for all populations (HI < 1) while carcinogenic risks were high (children: 77.52%; female: 69.09%; male: 65.63%). For children, carcinogenic risk from industrial and coal sources exceeded the acceptable threshold by 2.35 and 1.20 times, respectively, and Cr was the main element contributing to human carcinogenic risk. These findings suggest that carcinogenic risks from coal-based Cr emissions cannot be ignored, and the study area should aim to control Cr emissions from industrial sources. The results of this study provide support for the prevention of human health risks and the control of soil HMs pollution across different age groups.

Determination of contamination sources and geochemical behaviors of metals in soil of a mine area using Cu, Pb, Zn, and S isotopes and positive matrix factorization

The use of multiple isotopic ratios and statistical methods can substantially increase the reliability and precision of determining contamination sources and pathways. In this study, contamination sources were differentiated in three subareas in one mine area and geochemical processes were investigated using Cu, Pb, Zn, and S isotopes and positive matrix factorization (PMF). Soil samples downstream of the adit seepages exhibited distinctly higher δ⁶⁵Cu values than those from other areas. δ⁶⁵Cu in adit seepages increased substantially from ore sulfides owing to large isotopic fractionation during oxidative dissolution. Although δ⁶⁵Cu decreased during sulfide precipitation in seepage-contaminated soil, the discrimination of δ⁶⁵Cu was still valid. Therefore, δ⁶⁵Cu is particularly useful for differentiating between contamination by sulfides (tailings) and water (adit seepages). Moreover, sulfide precipitation following sulfate reduction was verified by the decreased δ⁶⁶Zn and δ³⁴S in the soil. In addition, the plot of ²⁰⁸Pb/²⁰⁶Pb versus Pb^-1 distinguished contamination sources. Furthermore, PMF analysis confirmed the determination of sources and differentiated between contamination by As- and Cu-enriched tailings. The effect of Cu-enriched tailings further downstream suggested that the lower specific gravity of chalcopyrite compared to that of arsenopyrite affected the distribution of soil contamination.

Isotopic (Cu, Zn, and Pb) and elemental fingerprints of antifouling paints and their potential use for environmental forensic investigations

Antifouling paints (APs) are one of the important sources of Cu and Zn contamination in coastal environments. This study applied for the first-time a multi-isotope (Cu, Zn, and Pb) and multi-elemental characterization of different AP brands to improve their tracking in marine environments. The Cu and Zn contents of APs were shown to be remarkably high ∼35% and ∼8%, respectively. The δ⁶⁵Cu_AE647, δ⁶⁶Zn_IRMM3702, and ²⁰⁶Pb/²⁰⁷Pb of the APs differed depending on the manufacturers and color (-0.16 to +0.36‰, -0.34 to +0.03‰, and 1.1158 to 1.2140, respectively). A PCA analysis indicates that APs, tires, and brake pads have also distinct elemental fingerprints. Combining isotopic and elemental ratios (e.g., Zn/Cu) allows to distinguish the environmental samples. Nevertheless, a first attempt to apply this approach in highly urbanized harbor areas demonstrates difficulties in source apportionments, because the sediment was chemically and isotopically homogeneous. The similarity of isotope ranges between the harbor and non-exhaust traffic emission sources suggests that most metals are highly affected by urban runoff, and that APs are not the main contributors of these metals. It is suspected that AP-borne contamination should be punctual rather than dispersed, because of APs low solubility properties. Nevertheless, this study shows that the common coastal anthropogenic sources display different elemental and isotopic fingerprints, hence the potential for isotope source tracking applications in marine environments. Further study cases, combined with laboratory experiments to investigate isotope fractionation during releasing the metal sources are necessary to improve non-traditional isotope applications in environmental forensics.

Identification of factors controlling heavy metals/metalloid distribution in agricultural soils using multi-source data

Understanding the factors that controlling the agricultural soil heavy metals/metalloids distribution is vital for cropland soil remediation and management. For this objective, 227 agricultural soils were sampled in the Guanzhong Plain, China, to measure the concentration of five heavy metals (Pb, Cd, Ni, Zn, and Cu) and one metalloid (As) by X-ray fluorescence spectrometer, meanwhile, 24 possible influencing factors to agricultural soil heavy metals/metalloid distribution were collected and grouped into three categories. A sequential multivariate statistical analysis was carried out to provide insight into the controlling factors of soil heavy metals/metalloid distribution, then stepwise multiple linear regression (SMLR) and partial least squares regression (PLS) were used to predict heavy metals/metalloid concentrations in agricultural soil based on the result of soil heavy metals/metalloid controlling factors identification. The results demonstrated the types of soil and land use did not have a substantial effect on soil heavy metals/metalloid distribution, except Zn and Cu. The soil properties category played a major role in influencing the soil heavy metals/metalloid concentration. The concentrations of Mn and Fe, which are the main constitute elements of soil inorganic colloid, were the most significant factors, followed by the concentrations of P, K and Ca. Soil pH and soil organic matter (SOM) content, which are often considered as important factors for soil heavy metals/metalloid distribution, were not important in the present study. The SMLR was more effective than the PLS for predicting soil heavy metals/metalloid content. The results of this study enlighten that future soil heavy metals/metalloid contamination treatment in regions with high pH and low SOM content should concentrate on inorganic colloid particles, which have strong adsorption capacity for soil heavy metals/metalloid and are environmentally friendly. Moreover, the combination of successive multivariate statistical analysis and SMLR provide an effective tool to predict and monitor agricultural soil heavy metals/metalloid distribution, and facilitate the improvement of environmental and territorial management.

Quantitative Source Apportionment of Potentially Toxic Elements in Baoshan Soils Employing Combined Receptor Models

Arable soils are crucial for national development and food security; therefore, contamination of agricultural soils from potentially toxic elements (PTEs) is a global concern. In this study, we collected 152 soil samples for evaluation. Considering the contamination factors and using the cumulative index and geostatistical methods, we investigated the contamination levels of PTEs in Baoshan City, China. Using principal component analysis, absolute principal component score-multivariate linear regression, positive matrix factorization, and UNMIX, we analyzed the sources and quantitatively estimated their contributions. The average Cd, As, Pb, Cu, and Zn concentrations were 0.28, 31.42, 47.59, 100.46, and 12.36 mg/kg, respectively. The Cd, Cu, and Zn concentrations exceeded the corresponding background values for Yunnan Province. The combined receptor models showed that natural and agricultural sources contributed primarily to Cd and Cu and As and Pb inputs, accounting for 35.23 and 7.67% pollution, respectively. Industrial and traffic sources contributed primarily to Pb and Zn inputs (47.12%). Anthropogenic activities and natural causes accounted for 64.76 and 35.23% of soil pollution, respectively. Industrial and traffic sources contributed 47.12% to pollution from anthropogenic activities. Accordingly, the control of industrial PTE pollution emissions should be strengthened, and awareness should be raised to protect arable land around roads.

The high-dimensional geographic dataset revealed significant differences in the migration ability of cadmium from various sources in paddy fields

Cadmium (Cd) contamination in paddy fields and its subsequent transfer in soil-rice systems are of particular concern. Significant discrepancies exist in the transfer process of Cd pollution sources from soil to rice. Here, we proposed a novel hybrid framework to reveal the priority of controlling Cd pollution sources in soil-rice systems, based on a high-dimensional geographical database. We further defined transfer potential (TP) to describe the ability of Cd from soil to rice (TP^r = Cd_r/Cd_s) and activated status (TP^a = Cd_a/Cd_s), respectively, to reveal the priority sources of Cd pollution at the regional scale. The mining source has both high levels of TP^r and TP^a, which should be a controlled priority. Followed by traffic sources with a higher value of TP^r, showing the risk to rice rather than the soil. The activated and enriched capacities of soil Cd are unequal in different sources that we attribute to the disparities of Cd transport in soil-rice systems. Cd contamination shows a significant spatial heterogeneity due to the difference in its transport performance. Our findings provide support for designing site-specific and pollution-targeted control priorities for suitable Cd pollution mitigation strategies at the regional scale.

Whole-Process Risk Management of Soil Amendments for Remediation of Heavy Metals in Agricultural Soil-A Review

Reducing the mobility and bioavailability of heavy metals in soils by adding exogenous materials is a technology for remediating soils contaminated with heavy metals. Unlike industrial sites, the use of such techniques in agricultural soils requires consideration of not only reducing the mobility of heavy metals but also avoiding adverse effects on soil fertility and the growth of plants. Due to the uncertainty of the stability of amendments applied to agricultural soil, the application of amendments in farmland soil is controversial. This article reviewed the field studies in which amendments were used to immobilize heavy metals, and identified the potential environmental impacts of all aspects of soil amendment usage, including production and processing, transportation, storage, application to soil, long-term stability, and plant absorption. Results of the study indicated that after identifying the environmental risks of the whole process of the application of improvers in agricultural fields, it is necessary to classify the risks according to their characteristics, and design differentiated risk control measures for the safe application of this type of technology.

An approach to quantify heavy metals and their source apportionment in coal mine soil: a study through PMF model

Mining activities in the opencast coal mines contaminate the surrounding soil by releasing coal dust containing heavy metals (HMs). The objective of the present study was to quantify the concentration of HMs like Fe, Cu, Mn, Ni, Cr, Zn, and Co in soil on profile and distance basis in the vicinity of the coal mines. This research also proposed the synthesis application of positive matrix factorization (PMF) model for the quantitative assessment of pollution sources. The results showed that the soil was more affected due to the presence of Cr in mining areas., and the contamination factor (C_f) of Cr was high at the edge of coal mine. It was observed from the study that C_f of the HMs was decreased with the increase in distance from the mine edge. The application of PMF model demonstrated that the contributions of Zn (4.2%), Ni (16.8%), and Mn (100%) were maximum in the pollution. The study concluded that soil contamination is inexorable due to opencast coal mining activities, and it can be mitigated by developing a green belt or through the process of ecological restoration and phytoremediation.

Source Apportionment of Heavy Metals Based on Multiple Approaches for a Proposed Subway Line in the Southeast Industrial District of Beijing, China

Apportioning the sources of heavy metals (HMs) in soil is of great importance for pollution control. A total of 64 soil samples from 13 sample points at depths of 0-21 m were collected along a proposed subway line in the southeast industrial district of Beijing. The concentrations, distribution characteristics, and sources of eight HMs were investigated. The results showed that the concentrations of Hg, Cd, Cu, Pb, As, and Zn in the topsoil (0-2 m) exceeded the Beijing soil background values. Three sources were identified and their respective contribution rates calculated for each of the HMs using multiple approaches, including correlation analysis (CA), top enrichment factor (TEF), principal component analysis (PCA), and positive matrix factor (PMF) methods. As (63.11%), Cr (61.67%), and Ni (70.80%) mainly originated from natural sources; Hg (97.0%) was dominated by fossil fuel combustion and atmospheric deposition sources; and Zn (72.80%), Pb (69.75%), Cu (65.36%) and Cd (53.08%) were related to traffic sources. Multiple approaches were demonstrated to be effective for HM source apportionment in soil, whilst the results using PMF were clearer and more complete. This work could provide evidence for the selection of reasonable methods to deal with soils excavated during subway construction, avoiding the over-remediation of the soils with heavy metals coming from natural sources.

Systematic Evaluation of Two Classical Receptor Models in Source Apportionment of Soil Heavy Metal(loid) Pollution Using Synthetic and Real-World Datasets

Due to the lack of a priori knowledge on true source makeup and contributions, whether the source apportionment results of Unmix and positive matrix factorization (PMF) are accurate cannot be easily assessed, despite the availability of built-in indicators for their goodness of fit and robustness. This study systematically evaluated, for the first time, the applicability and reliability of these models in source apportionment of soil heavy metal(loid)s with synthetic datasets generated using known source profiles and contributions and a real-world dataset as well. For eight synthetic datasets with different pollution source characteristics, feasible Unmix solutions were close to the true source component compositions (R² > 0.936; total mean squared errors (MSEs) < 0.04), while those of PMF had significant deviations (R² of 0.484-0.998; total MSEs of 0.04-0.16). Nonetheless, both models failed to accurately apportion the sources with collinearity or non-normal distribution. Unmix generally outperformed PMF, and its solutions showed much less dependence on sample size than those of PMF. While the built-in indicators provided little hint on the reliability of both models for the real-world dataset, their sample-size dependence indicated that Unmix probably yielded more accurate solutions. These insights could help avoid the potential misuse of Unmix and PMF in source apportionment of soil heavy metal(loid) pollution.

Source apportionment of soil heavy metals with PMF model and Pb isotopes in an intermountain basin of Tianshan Mountains, China

A boom in tourism may lead to the enrichment in heavy metals (HMs) in soils. Contamination with HMs poses a significant threat to the security of the soil environment. In this study, topsoil samples were collected from a tourist area of Sayram Lake, and the concentrations of HMs (Cr, Cu, Ni, Pb, Zn and Cd) were determined. With contamination and eco-risk assessment models, correlation analysis, Pb isotope ratios, redundancy analysis and positive matrix factorization (PMF) model, the risks and sources of HMs in the soil were studied. The I_geo results suggested that Cd was the primary pollutant in the tourist area of Sayram Lake. The potential ecological risk index (PERI) showed that the study area was at low risk, and the pollution load index (PLI) indicated that the study area had a moderate contamination level. Qualitative and quantitative analyses apportioned three sources of HMs, namely, natural sources (38.5%), traffic sources (27.2%) and mixed sources (tourist waste and atmospheric deposition) (34.3%). Redundancy analysis results showed that the HMs content was related to SiO₂, Al₂O₃, TiO₂, P₂O₅, MnO, K₂O, Fe₂O₃ and SOC, and heavy metals tended to be stored in soil particles of grain sizes < 32 µm. These findings are expected to provide useful insights into the source identification of HMs in the soils of mountain tourism areas and provide a scientific decision-making basis for sustainable tourism development and for the assessment of ecological service values in the Tianshan Mountains.

Source appointment of potentially toxic elements (PTEs) at an abandoned realgar mine: Combination of multivariate statistical analysis and three common receptor models

Identifying pollution sources and quantifying their contributions are of great importance for proposing management and control strategies of potentially toxic elements (PTEs) in soil. In this study, multivariate statistical analysis and receptor models were combined to identify potential pollution sources and apportion their contributions at an abandoned realgar mine. Principal component analysis (PCA) result shows that three factors are responsible for PTEs, which is also supported by cluster analysis (CA). Correlation analysis and spatial analysis also show that the heavy metals from the same pollution source are of higher correlation coefficients and similar spatial distribution. Three receptor models were combined to apportion contributions of pollution sources. Three pollution sources were detected by absolute principal component analysis-multiple linear regression (APCA-MLR). In contrast, four sources were identified by positive matrix factorization (PMF) and UNMIX. Soil parent material was heavily loaded on Cr, Cu, Ni and Zn, occupying the largest average contribution (30%-43%). Cadmium was mainly derived from agricultural activities with contribution higher than 60%. Arsenic accumulation was mainly associated with mining and smelting activity with contribution higher than 80%. PMF and UNMIX models showed that more than half of Pb concentrations were influenced by industrial activities. Comparatively speaking, APCA-MLR was a well-performing model for all PTEs even though it only detected three pollution sources. The study showed that it was a good choice to apply multiple receptor models in order to achieve more reliable and objective conclusions of source appointment.

Health Risk Assessment of Heavy Metals in Shallow Groundwater of Coal-Poultry Farming Districts

This study aimed to assess the heavy metal (Mn, Ni, Cu, Zn, Sr, Cd, Pb, and Cr) pollution characteristics, sources, and human health risks in shallow groundwater in the impact zones of urban and rural semi-intensive poultry farms in Suzhou City. Ordinary kriging interpolation showed that poultry farming contributed substantially to the pollution of shallow groundwater by Mn, Zn, and Cu. Positive matrix factorization was applied to identify the sources of heavy metals, and the health risks were assessed based on the hazard index and carcinogenic risks of the various sources. Heavy metal enrichment was closely related to anthropogenic activities. In addition, four sources were identified: poultry manure (29.33%), natural source (27.94%), industrial activities (22.29%), and poultry wastewater (20.48%). The main exposure route of carcinogenic and non-carcinogenic risks to adults and children was oral ingestion. The non-carcinogenic risk of oral ingestion in children was higher than that in adults; the carcinogenic risk was higher in adults than in children. Poultry manure (42.0%) was considered the largest contributor to non-carcinogenic risk, followed by poultry wastewater (21%), industrial activities (20%), and natural sources (17%). Industrial activity (44%) was the primary contributor to carcinogenic risk, followed by poultry wastewater (25%), poultry manure (19%), and natural sources (12%).

Effects of composite environmental materials on the passivation and biochemical effectiveness of Pb and Cd in soil: Analyses at the ex-planta of the Pak-choi root and leave

Passivation of soil heavy metals using environmental materials is an important method or important in situ remediation measure. There are more studies on inorganic environmental materials for heavy metal passivation, but not enough studies on organic and their composite environmental materials with inorganic ones. In order to reveal the passivation effect of coal-based ammoniated humic acid (CAHA), biochemical humic acid (BHA), biochar (BC) and other organic types and inorganic environmental materials such as zeolites (ZL) on soil heavy metals and their biological effectiveness. The microstructures of these materials were analyzed by Scanning electron microscope (SEM). The main components of the environmental materials were analyzed by Energy dispersive spectrometer (EDS), Fourier transforms infrared spectroscopy (FT-IR) and X-ray diffraction spectrum (XRD) to elucidate the mechanism of passivation of heavy metals in soil by these environmental materials. The study was conducted to investigate the effects of different types of environmental materials and their combinations on the passivation effect and biological effectiveness of Pb and Cd complex contamination in soil by means of soil incubation and pot experiments using single-factor and multifactor multilevel orthogonal experimental designs. Soil incubation experiments proved that the effective state of soil Pb and Cd in T₇ was reduced by 13.40% and 11.07%, respectively. The extreme difference analysis determined the optimized formulation of soil lead and cadmium passivation as BHA: CAHA: BC: ZL = 3.5:5:20:10. The pot experiment proved that the application of composite environmental materials led to the reduction of lead and cadmium content and increase of biomass of Pak-choi, and the optimal dosage of optimized composite environmental materials was 23.1 g/kg.

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.

Fluxes, characteristics and influence on the aquatic environment of inorganic nitrogen deposition in the Danjiangkou reservoir

Atmospheric reactive nitrogen (Nr) deposition has caused serious damage to the terrestrial and freshwater ecosystems and also affected human health. Measuring temporal and spatial characteristics of Nr deposition is critical for proposing control strategy to decrease negative effects. We investigated the fluxes of ammonia nitrogen (NH₄-N) and nitrate nitrogen (NO₃-N) in both dry and wet deposition from October 2017 to September 2020 at six sites around the Danjiangkou reservoir. The results showed that the fluxes of dissolved inorganic nitrogen (DIN) decreased from 24.39 kg ha^-1 yr^-1 (2017-2018) to 16.11 kg ha^-1 yr^-1 (2019-2020) for dry deposition, and from 19.71 kg ha^-1 yr^-1 (2017-2018) to 12.29 kg ha^-1 yr^-1 (2019-2020) for wet deposition. Both NH₄-N and NO₃-N in wet deposition exhibited significant (P < 0.01) differences among four seasons, and were markedly influenced by the precipitation. The fluxes of NO₃-N deposition showed significant (P < 0.05) difference among six samples. Dry component contributed more to total DIN deposition, and NH₄-N was the dominant species in DIN deposition. The ratios of NH₄-N to NO₃-N in four seasons were higher than 2. A positive matrix factorization (PMF) model estimated that the factors of agriculture and fossil fuel combustion accounted for 77.1 % and 17.0 %, respectively, to the dry NH₄-N deposition; and that the factors of agricultural source and biomass burning accounted for 56.2 % and 21.1 %, respectively, to the wet NH₄-N deposition. The DIN deposition contributed to 7.7 % of the total Nr input into the reservoir, and the contribution of DIN deposition to the increase in the nitrogen concentration (ΔN) of the Danjiangkou reservoir was 0.13 mg L^-1 yr^-1. The dry DIN deposition was significantly correlated with the concentration of nitrogen in Danjiangkou reservoir (P < 0.01). This study suggested that the control measures of agricultural activity were essential to reduce Nr deposition, and to decrease the potential risks of water pollution in the reservoir. Furthermore, more long-term study is necessary to understand the relation between control measures, Nr deposition and water quality.