雌酮
壬基酚
废水
污染
三氯生
污水处理
流出物
双酚A
化学
杀生物剂
炔雌醇
环境科学
环境化学
环境工程
有机化学
激素
生物
社会学
病理
人口学
环氧树脂
医学
生物化学
生态学
人口
研究方法
作者
Kristin H. Cochran,Danielle C. Westerman,Cassiana Carolina Montagner,Scott Coffin,L. Majano Díaz,Benjamin Fryer,Gary T. Harraka,Elvis Genbo Xu,Ying Huang,Daniel Schlenk,Dionysios D. Dionysiou,Susan D. Richardson
标识
DOI:10.1021/acs.est.3c05978
摘要
With increasing water scarcity, many utilities are considering the potable reuse of wastewater as a source of drinking water. However, not all chemicals are removed in conventional wastewater treatment, and disinfection byproducts (DBPs) can form from these contaminants when disinfectants are applied during or after reuse treatment, especially if applied upstream of advanced treatment processes to control biofouling. We investigated the chlorination of seven priority emerging contaminants (17β-estradiol, estrone, 17α-ethinylestradiol, bisphenol A (BPA), diclofenac, p-nonylphenol, and triclosan) in ultrapure water, and we also investigated the impact of chlorination on real samples from different treatment stages of an advanced reuse plant to evaluate the role of chlorination on the associated cytotoxicity and estrogenicity. Many DBPs were tentatively identified via liquid chromatography (LC)- and gas chromatography (GC)-high resolution mass spectrometry, including 28 not previously reported. These encompassed chlorinated, brominated, and oxidized analogs of the parent compounds as well as smaller halogenated molecules. Chlorinated BPA was the least cytotoxic of the DBPs formed but was highly estrogenic, whereas chlorinated hormones were highly cytotoxic. Estrogenicity decreased by ∼4–6 orders of magnitude for 17β-estradiol and estrone following chlorination but increased 2 orders of magnitude for diclofenac. Estrogenicity of chlorinated BPA and p-nonylphenol were ∼50% of the natural/synthetic hormones. Potential seasonal differences in estrogen activity of unreacted vs reacted advanced wastewater treatment field samples were observed.
科研通智能强力驱动
Strongly Powered by AbleSci AI