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Soil pollution is becoming increasingly serious due to resource exploitation in mining areas, which directly affects the stability of the surrounding soil and water environment, and the accurate prediction of heavy metal pollution source analysis has an important guiding role in scientific mine remediation and treatment. On the basis of the previous study, in order to improve the interpretation of the soil media model, positive matrix factorization (PMF) and absolute factor analysis-multiple linear regression (APCS-MLR) models, which have a high degree of maturity and accuracy in the evaluation of heavy metal source analysis in soils, were further selected to enrich the UNMIX model in the previous study. The results of the multiple receptor models analyzing the sources of heavy metal contamination and the contribution of the sources were combined with the ecological risk assessment method to determine the most suitable model in study area under quantitative conditions. The results showed that: 1) the ecological high-risk areas were mainly concentrated in the south and east part of the study area, and Cd was the main risk element of the mine; the mean value of igeoaccumulation index was 3.75, which was highly consistant with the mean value of 731.22 for the potential ecological risk index though latter provided a more comprehensive evaluation of ecological hazards. 2) Comparing the results of the three models, the PMF model resolved four pollution sources: coal combustion source, natural-traffic integrated source, natural source and atmospheric deposition source, and the source contribution rates are 38.15%, 20.62%, 24.28% and 16.95%, respectively. 3) The fitted variables R2 in the PMF model reached to 0.96, which showed the best fitting effect. The PMF model refines source apportionment by accounting for sampling point errors and accurately ascertaining pollution sources and their contributions, making it highly suitable for complex mine-contaminated soils in realistic research settings. The findings of this study can provide a reference for tracing the origins of contaminants, which is essential for the remediation efforts of polluted soils following mining activities in the area. [ABSTRACT FROM AUTHOR]

In the study, presence, distribution of 18 polychlorinated biphenyls (PCBs), including 7 indicator PCBs, 12 dioxin-like PCBs (DL-PCBs), and 4 heavy metals (Pb, As, Cd, Hg) have been investigated in Ictalurus punctatus, sediment and water from Jiangsu fish farms; thereafter, risk assessment have been conducted for the ecological risk and human health. The results showed that PCB28, PCB52, PCB114 were the most frequently found pollutants in all collected fish, sediment and water samples. Upon to the different geographical location of fishery farms across Jiangsu Province, components of PCBs presented differently, which implied different pollution sources. The concentration of PCBs found in sediment (178.4-457.2 pg/g) was higher than that detected in water (0.2-11.9 ng/L). Higher concentrations of PCBs was also found in fish meat (1.28-267.96 pg/g), compared to that in fish liver (0.64-95.46 pg/g), and guts and stomach (1.20-45.94 pg/g). Higher content of fat in fish meat could be the possibility of higher enrichment of PCBs compared to the other tissues. Meanwhile, higher concentration of heavy metal was found in sediment than that in water. The total enrichment of heavy metal in fish was found to be Pb﹥As﹥Cd﹥Hg in descend order. Total amount of heavy metals enriched in different tissues were found to be liver ﹥gastrointestinal system﹥meat. All the DL-PCBs TEQ (1.9 pg/g) is less than the maximum residue limit (MRL) of EU (6.5 pg/g). THQ (US, EPA) and R model were employed for the risk assessment by comprising the estimated daily intake and the daily allowed intake. The results revealed that the carcinogenic risk of 18 kinds PCBs and 4 kinds heavy metals remained acceptable level in this study. [ABSTRACT FROM AUTHOR]