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The presence of antibiotic resistant bacteria (ARB) in wastewater was investigated and the role of wastewater treatment plants (WWTPs) in promoting or limiting antibiotic resistance was assessed. Escherichia coli (E. coli) and total heterotrophic bacteria (THB) resistance to ampicillin, chloramphenicol and tetracycline was monitored in three WWTPs located in Milan urban area (Italy), differing among them for the operating parameters of biological process, for the disinfection processes (based on sodium hypochlorite, UV radiation, peracetic acid) and for the discharge limits to be met. Wastewater was collected from three sampling points along the treatment sequence (WWTP influent, effluent from sand filtration, WWTP effluent). Antibiotic resistance to ampicillin was observed both for E. coli and for THB. Ampicillin resistant bacteria in the WWTP influents were 20–47% of E. coli and 16–25% of THB counts. A limited resistance to chloramphenicol was observed only for E. coli, while neither for E. coli nor for THB tetracycline resistance was observed. The biological treatment and sand filtration led to a decrease in the maximum percentage of ampicillin-resistant bacteria (20–29% for E. coli, 11–21% for THB). However, the conventionally adopted parameters did not seem adequate to support an interpretation of WWTP role in ARB spread. Peracetic acid was effective in selectively acting on antibiotic resistant THB, unlike UV radiation and sodium hypochlorite. The low counts of E. coli in WWTP final effluents in case of agricultural reuse did not allow to compare the effect of the different disinfection processes on antibiotic resistance.

In recent years, the presence of micropollutants in drinking water has become an issue of growing global concern. Due to their low concentrations, monitoring databases are usually rich in censored data (e.g. samples with concentrations reported below the limit of quantification, LOQ) which are typically eliminated or replaced with a value arbitrarily chosen between 0 and LOQ. These conventional methods have some limitations and can lead to erroneous conclusions on: presence of micropollutants in the source water, treatment efficiencies, produced water quality and associated human health risk. In this work, an advanced approach, based on Maximum Likelihood Estimation method for left-censored data (MLELC), was applied on monitoring data of 19 contaminants (metals, volatile organic compounds, pesticides and perfluorinated compounds) in 5362 groundwater (GW) and 12,344 drinking water (DW) samples, collected from 2012 to 2017 in 28 drinking water treatment plants in an urbanized area. This study demonstrates the benefits of MLELC method, especially for high percentages of censored data. Data are used to build statistical distributions which can be effectively used for several applications, such as the time trend evaluation of GW micropollutant concentrations and the estimation of treatment removal efficiency, highlighting the adequacy or the need for an upgrade. Moreover, the MLELC method has been applied to assess the human health risk associated with micropollutants, indicating the high discrepancy in the estimations obtained with conventional methods, whose results do not follow precautionary or sustainability criteria.