4.5 Article

Fate of phthalates in a river receiving wastewater treatment plant effluent based on a multimedia model

期刊

WATER SCIENCE AND TECHNOLOGY
卷 86, 期 9, 页码 2124-2137

出版社

IWA PUBLISHING
DOI: 10.2166/wst.2022.347

关键词

fate and transfer; level III fugacity model; phthalic acid esters; receiving river; secondary effluent; sensitivity analysis

资金

  1. National Natural Science Foundation of China, (China) [51908398]
  2. Research Project of Tianjin Education Commission [2017KJ055, 2018KJ166]
  3. Tianjin Research Innovation Project for Postgraduate Students [2021YJSS346]

向作者/读者索取更多资源

The study found that PAEs are mainly distributed in soil and sediment, and upstream advection contributes significantly to the total source of PAEs in river water. Emission and inflow parameters have a greater influence on the multimedia distributions of PAEs.
Phthalic acid esters (PAEs) can enter environment media by secondary effluent discharge from wastewater treatment plants (WWTP) into receiving rivers, thus posing a threat to ecosystem health. A level III fugacity model was established to simulate the fate and transfer of four PAEs in a study area in Tianjin, China, and to evaluate the influence of WWTP discharge on PAEs levels in the receiving river. The results show that the logarithmic residuals of most simulated and measured values of PAEs are within one order of magnitude with a good agreement. PAEs in the study area were mainly distributed in soil and sediment phases, which accounted for 84.66%, 50.26%, 71.96% and 99.09%for dimethyl phthalate (DMP), diethyl phthalate (DEP), dibutyl phthalate (DBP) and di-(2-ethylhexyl) phthalate (DEHP), respectively. The upstream advection accounted for 77.90%, 93.20%, 90.21% and 90.93% of the total source of DMP, DEP, DBP and DEHP in the river water, respectively, while the contribution of secondary effluent discharge was much lower. Sensitivity analysis shows that emission and inflow parameters have greater influences on the multimedia distributions of PAEs than physicochemical and environmental parameters. Monte Carlo analysis quantifies the uncertainties and verifies the reliability of the simulation results.

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