The levels of HCH isomers, HCB and summation DDTs were determined in five species of Baltic fish collected during 1995-2006. Some downward time trends of HCH isomer, pp'-DDE and pp'-DDD concentrations in Baltic fish were observed; in contrast, HCB and DDT concentrations did not exhibit any obvious trend. Concentrations of summation HCHs expressed on a lipid weight basis were very similar in all species studied. In contrast, concentrations of summation DDTs varied in tested species. The most abundant HCH isomer was beta-HCH and among DDT-related compounds, pp'-DDE prevailed. In our investigations the sampling sites were not a crucial factor for organochlorine pesticide concentrations and patterns observed in fish, but the occurrence of several inter-species differences in the bioaccumulation features of OC pesticides were observed. For cod there was a positive correlation between fish size (length) and summation DDT concentration. In herring, sprat and salmon samples, summation DDT concentrations were negatively correlated with fat content.
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http://dx.doi.org/10.1016/j.marpolbul.2008.01.029 | DOI Listing |
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Sci Rep
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College of Jilin Emergency Management, Changchun Institute of Technology, Changchun, 130012, China.
Globally, heavy metal (HM) soil pollution is becoming an increasingly serious concern. Heavy metals in soils pose significant environmental and health risks due to their persistence, toxicity, and potential for bioaccumulation. These metals often originate from anthropogenic activities such as industrial emissions, agricultural practices, and improper waste disposal.
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Institute for Health and the Environment, 5 University Place, University at Albany, Rensselaer, New York, USA.
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Key Laboratory of Integrated Regulation and Resources Development of Shallow Lakes of Ministry of Education, Hohai University, Nanjing 210098, China; College of Environment, Hohai University, Nanjing 210098, China. Electronic address:
Accurate prediction of bioaccumulation parameters is essential for assessing exposure, hazards, and risks of chemicals. However, the majority of prediction models on bioaccumulation parameters are individual models based on a single algorithm and lack model interpretation, resulting in unsatisfactory prediction accuracy due to inherent constraints of the algorithm and weak interpretability. Ensemble learning (EL) that combine multiple algorithms, coupled with SHapley Additive exPlanation (SHAP) method, may overcome the limitations.
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