An effective tool for tracking steroids and their metabolites at the watershed level: Combining fugacity modeling and a chemical indicator. (1st June 2023)

• Record Type: Journal Article
• Authors: Xu, Ru; Liu, Shan; Chen, Hui; Hao, Qin-Wei; Hu, Yong-Xia; Li, Heng-Xiang; Lin, Lang; Hou, Rui; Hong, Bing; Yu, Shen; Xu, Xiang-Rong
• Is Part Of: Environmental pollution. Volume 326(2023)
• Publication Date: 2023-06-01
• Subjects: Androgens -- Progestagens -- Glucocorticoids -- Spatiotemporal patterns -- Ecological risk -- Modeling evaluation; Pollution -- Periodicals; Pollution -- Environmental aspects -- Periodicals; Environmental Pollution -- Periodicals; Pollution -- Périodiques; Pollution -- Aspect de l'environnement -- Périodiques; Pollution -- Effets physiologiques -- Périodiques; Pollution; Pollution -- Environmental aspects; Periodicals; Electronic journals; 363.73
• DOI: 10.1016/j.envpol.2023.121499
• Languages: English
• ISSNs: 0269-7491

Abstract

Abstract: Steroids have attracted concern worldwide because of their potential carcinogenicity and severe adverse effects on aquatic organisms. However, the contamination status of various steroids, particularly their metabolites, at the watershed level remains unknown. This was the first study to employ field investigations to elucidate the spatiotemporal patterns, riverine fluxes, and mass inventories, and conduct a risk assessment of 22 steroids and their metabolites. This study also developed an effective tool for predicting the target steroids and their metabolites in a typical watershed based on the fugacity model combined with a chemical indicator. Thirteen steroids in the river water and seven steroids in sediments were identified with total concentrations of 1.0–76 ng/L and <LOQ–121 ng/g, respectively. In water, the levels of steroids were higher in the dry season, but the opposite trend was observed in sediments. Approximately 89 kg/a flux of steroids were transported from the river to the estuary. Mass inventories indicated that sediments acted as crucial sinks for steroids. Steroids in rivers might pose low to medium risks to aquatic organisms. Importantly, the fugacity model combined with a chemical indicator effectively simulated the steroid monitoring results within an order of magnitude at the watershed level, and various key sensitivity parameter settings provided reliable steroid concentration predictions under different circumstances. Our results should benefit environmental management and pollution control of steroids and their metabolites at the watershed level. Graphical abstract: Image 1 Highlights: Steroids and metabolites exhibited spatiotemporal distribution in Jiulong River. Compared to river water, sediment was a crucial sink for steroids. Steroids in the Jiulong River were at low or medium ecological risk. Natural androgen 4-androstene-3, 17-dione was a reliable indicator of steroids. Fugacity model and chemical indicator effectively simulated the fate of steroids.