Browsing by Author "Huang, Jun"
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Item A machine-learning approach clarifies interactions between contaminants of emerging concern(CellPress, 2022-11-08) Chen, Jian; Wang, Bin; Huang, Jun; Deng, Shubo; Wang, Yujue; Blaney, Lee; Brennan, Georgina L.; Cagnetta, Giovanni; Jia, Qimeng; Yu, GangHumans and biotas are exposed to a cocktail of contaminants of emerging concern (CECs), but mixture regulation is lagging behind. This is largely attributed to inadequate experimental data of mixture risk; revealing intricate interactions among CECs in mixtures with random combinations remains a formidable challenge. Here, we propose a new framework comprised of 5,720 lab tests of mixture risk for 100 CECs with random combinations, extended prediction of mixture risk in any CEC combination via a new machine learning model, and validation in field sites. We identify a general concave-down relationship between CEC number and ecological risk of algae, invertebrates, and fish under different lab conditions and in more than 900 field sites worldwide. We propose a new “redundancy mechanism” to clarify interactions among CECs, suggesting implications in grouping CECs by action mode for developing mixture regulatory frameworks. Our framework provides a blueprint for addressing cocktail effects of multi-factors with random combinations in different disciplines.Item Emerging Organic Contaminants in Chinese Surface Water: Identification of Priority Pollutants(Elsevier, 2021-04-02) Zhong, Mengmeng; Wang, Tielong; Zhao, Wenxing; Huang, Jun; Wang, Bin; Blaney, Lee; Bu, Qingwei; Yu, GangThe occurrence and impacts of emerging organic contaminants (EOCs) in the aquatic environment have gained widespread attention over the past two decades. Due to large number of potential contaminants, monitoring campaigns, treatment plants, and proposed regulations should preferentially focus on specific pollutants with the highest potential for ecological and human health effects. In the present study, a multi-criteria screening approach based on hazard and exposure potentials was developed for prioritization of 405 unregulated EOCs already present in Chinese surface water. Hazard potential, exposure potential, and risk quotients for ecological and human health effects were quantitatively analyzed and used to screen contaminants. The hazard potential was defined by contaminant persistence, bioaccumulation, ecotoxicity, and human health effects; similarly, the exposure potential was a function of contaminant concentration and detection frequency. In total, 123 compounds passed the preselection process, which involved a priority index equal to the normalized hazard potential multiplied by the normalized exposure potential. Based on the prioritization scheme, 11 compounds were identified as top-priority, and 37 chemicals were defined as high-priority. The results obtained by the priority index were compared with four other prioritization schemes based on exposure potential, hazard potential, or risk quotients for ecological effects or human health. The priority index effectively captured and integrated the results from the more simplistic prioritization schemes. Based on identified data gaps, four uncertainty categories were classified to recommend: ① regular monitoring, derivation of environmental quality standards, and development of control strategies, ② increased monitoring, ③ fortified hazard assessment, and ④ increased efforts to collect occurrence and toxicity data. Overall, 20 pollutants were recommended as priority EOCs. The prioritized list of contaminants provides the necessary information for authoritative regulations to monitor, control, evaluate, and manage the risks of environmentally-relevant EOCs in Chinese surface water.Item Wastewater-based epidemiology in Beijing, China: Prevalence of antibiotic use in flu season and association of pharmaceuticals and personal care products with socioeconomic characteristics(Elsevier Ltd, 2019-04) Zhang, Yizhe; Duan, Lei; Wang, Bin; Du, Yulin; Cagnetta, Giovanni; Huang, Jun; Blaney, Lee; Yu, GangWastewater-based epidemiology is an emerging field that has mostly been applied to investigate consumption of illicit drugs. In this study, the wastewater-based epidemiology approach was employed to study consumption of pharmaceuticals and personal care products (PPCPs) and measure their prevalence of use in eight densely populated, urban areas of Beijing, China. Ammonium loads were used to estimate the population equivalents of each sewershed. These estimates were applied to calculate population-normalized antibiotic consumption and prevalence of use during flu season, when antibiotics are frequently misused as a medical treatment. Results indicated that 21.9 g d−1 (10⁴ people)⁻¹ of ten popular antibiotics were consumed across the eight sewersheds, indicating that 1.98‰ of the 12.5 million population equivalents used these antibiotics during the sampling period. A comparison of these results to calculations made using previously reported data from 2013 suggest that recent Chinese antibiotic control policies have been effective. Uncertainty analyses were conducted to identify the 95% confidence range for antibiotic prevalence of use as 1.44–3.61‰. Human excretion factors were identified as the most sensitive variable. The wastewater-based epidemiology methods were also applied to a wider range of PPCPs, and the results indicated positive relationships between consumption and socioeconomic factors, such as housing price and population density. Overall, this work provides important public health information on antibiotic use and elucidates relationships between PPCP consumption and socioeconomic characteristics.