期刊
ENVIRONMENTAL POLLUTION
卷 255, 期 -, 页码 -出版社
ELSEVIER SCI LTD
DOI: 10.1016/j.envpol.2019.113222
关键词
Refuse; Leachates; Antibiotic; Heavy metals; ARGs
资金
- National Key R&D Program of China [2018YFC1901000]
- National Science Foundation of China [21577038]
- Fundamental Research Funds for the Central Universities
- East China Normal University Academic Innovation Promotion Program for Excellent Doctoral Students [YBNLTS2019-018]
Antibiotics, heavy metals and related antibiotic resistance genes (ARGs) in municipal solid waste (MSW) landfills have aroused more attentions due to their potential risk toward the ecosystems and public healthcare, but the contents and relationships of them have yet to be systematically understood during landfilling process. In this study, we selected refuse samples with different ages from two representative landfills and leachate samples from three major landfills. The total contents of measured antibiotics and metals respectively ranged from 157.22 to 1752.01 mu g/kg and 19624.62-30624.01 mg/kg in refuse, while 3961.59-4497.12 ng/L and 9.16-10.82 mg/L in detected leachates. Among them, Ten of fourteen antibiotics were relatively higher in aged refuse, and contrary results were presented in most detected metals. Three ARGs (sul1, ermB and sul2) and intl1 were found with a higher abundance across all detected samples. Network analysis indicated that the abundance of tetM and tetQ in refuse were positively correlated with corresponding antibiotics doxycycline (DC) and oxytetracycline (OTC), respectively (P<0.05). Similarly, ermB and bla(CTX-M) in leachates were respectively related with corresponding roxi-thromycin (RTM) and cefalexin (CEF), (P<0.01). Moreover, Cu exhibited positive and significant correlations with sul1, mexF and intl1 in all refuse and leachates (P<0.05). Mantel test indicated that the quantified intl1 was closely correlated with detected contents of ARGs (Mantel test, R=0.48, P<0.05), and the highly abundant intl1 were correlated with sull (P<0.001) and bla(CTX-M) (P<0.05) across all samples. (C) 2019 Elsevier Ltd. All rights reserved.
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