Co-exposure levels of volatile organic compounds and metals/metalloids in children: Implications for E-waste recycling activity prediction.

Sci Total Environ

State Environmental Protection Key Laboratory of Environmental Pollution Health Risk Assessment, South China Institute of Environmental Sciences, Ministry of Ecology and Environment, Guangzhou 510655, PR China. Electronic address:

Published: March 2023

Identifying informal e-waste recycling activity is crucial for preventing health hazards caused by e-waste pollution. This study attempted to build a prediction model for e-waste recycling activity based on the differential exposure biomarkers of the populations between the e-waste recycling area (ER) and non-ER. This study recruited children in ER and non-ER and conducted a quasi-experiment among the adult investigators to screen differential exposure or effect biomarkers by measuring urinary 25 volatile organic compound (VOC) metabolites, 18 metals/metalloids, and 8-hydroxy-2'-deoxyguanosine (8-OHdG). Compared with children of the non-ER, the ER children had higher metal/metalloid (e.g., manganese [Mn], lead [Pb], antimony [Sb], tin [Sn], and copper [Cu]) and VOC exposure (e.g., carbon-disulfide, acrolein, and 1-bromopropane) levels, oxidative DNA damage, and non-carcinogenic risks. Individually added 8-OHdG, VOC metabolites, and metals/metalloids to the support vector machine (SVM) classifier could obtain similar classification effects, with the area under curve (AUC) ranging from 0.741 to 0.819. The combined inclusion of 8-OHdG and differential VOC metabolites, metals/metalloids, and mixed indexes (e.g., product items or ratios of different metals/metalloids) in the SVM classifier showed the highest performance in predicting e-waste recycling activity, with an AUC of 0.914 and prediction accuracy of 83.3 %. "Sb × Mn", followed by "Sn × Pb/Cu", "Sb × Mn/Cu", and "Sn × Pb", were the top four important features in the models. Compared with non-ER children, the levels of urinary Mn, Pb, Sb, Sn, and Cu in ER children were 1.2 to 2.4 times higher, while the levels of "Sb × Mn", "Sn × Pb/Cu", "Sb × Mn/Cu", and "Sn × Pb" were 3.5 to 4.7 times higher, suggesting that these mixed indexes could amplify the differences between e-waste exposed and non-e-waste exposed populations. With the continued inclusion of new biomarkers of e-waste pollution in the future, our prediction model is promising for screening informal e-waste recycling sites.

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Source
http://dx.doi.org/10.1016/j.scitotenv.2022.160911DOI Listing

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