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Wastewater-based epidemiology is an economical and effective tool for monitoring the COVID-19 pandemic. In this study we proposed sampling campaigns that addressed spatial-temporal trends within a metropolitan area. This is a local study of detection and quantification of SARS-CoV-2 in wastewater during the onset, rise, and decline of COVID-19 cases in Salta city (Argentina) over the course of a twenty-one-week period (13 Aug to 30 Dec) in 2020. Wastewater samples were gathered from 13 sewer manholes specific to each sewershed catchment, prior to convergence or mixing with other sewer lines, resulting in samples specific to individual catchments with defined areas. The 13 sewershed catchments selected comprise 118,832 connections to the network throughout the city, representing 84.7 % (534,747 individuals) of the total population. The number of COVID19-related exposure and symptoms cases in each area were registered using an application developed for smartphones by the provincial government. Geographical coordinates provided by the devices were recorded, and consequently, it was possible to geolocalise all app-cases and track them down to which of the 13 sampling catchments belonged. RNA fragments of SARS-CoV-2 were detected in every site since the beginning of the monitoring, anticipating viral circulation in the population. Over the course of the 21-week study, the concentrations of SARS-CoV-2 ranged between 1.77 × 104 and 4.35 × 107 genome copies/L. There was a correspondence with the highest viral load in wastewater and the peak number of cases reported by the app for each catchment. The associations were evaluated with correlation analysis. The viral loads of SARS-CoV-2 in wastewater were a feasible means to describe the trends of COVID-19 infections. Surveillance at sewershed scale, provided reliable and strategic information that could be used by local health stakeholders to manage the COVID-19 pandemic.

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The aim of this work was to evaluate if rivers could be used for SARS-CoV-2 surveillance. Five sampling points from three rivers (AR-1 and AR-2 in Arenales River, MR-1 and MR-2 in Mojotoro River, and CR in La Caldera River) from Salta (Argentina), two of them receiving discharges from wastewater plants (WWTP), were monitored from July to December 2020. Fifteen water samples from each point (75 in total) were collected and characterized physico-chemically and microbiologically and SARS-CoV-2 was quantified by RT-qPCR. Also, two targets linked to human contributions, human polyomavirus (HPyV) and RNase P, were quantified and used to normalize SARS-CoV-2 concentration, which was compared to reported COVID-19 cases. Statistical analyses allowed us to verify the correlation between SARS-CoV-2 and the concentration of fecal indicator bacteria (FIB), as well as to find similarities and differences between sampling points. La Caldera River showed the best water quality; FIBs were within acceptable limits for recreational activities. Mojotoro River's water quality was not affected by the northern WWTP of the city. Instead, Arenales River presented the poorest water quality; at AR-2 was negatively affected by the discharges of the southern WWTP, which contributed to significant increase of fecal contamination. SARS-CoV-2 was found in about half of samples in low concentrations in La Caldera and Mojotoro Rivers, while it was high and persistent in Arenales River. No human tracers were detected in CR, only HPyV was found in MR-1, MR-2 and AR-1, and both were quantified in AR-2. The experimental and normalized viral concentrations strongly correlated with reported COVID-19 cases; thus, Arenales River at AR-2 reflected the epidemiological situation of the city. This is the first study showing the dynamic of SARS-CoV-2 concentration in an urban river highly impacted by wastewater and proved that can be used for SARS-CoV-2 surveillance to support health authorities.

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A novel and versatile plasma reactor was used to modify Polyethersulphone commercial membranes. The equipment was applied to: i) functionalize the membranes with low-temperature plasmas, ii) deposit a film of poly(methyl methacrylate) (PMMA) by Plasma Enhanced Chemical Vapor Deposition (PECVD) and, iii) deposit silver nanoparticles (SNP) by Gas Flow Sputtering. Each modification process was performed in the same reactor consecutively, without exposure of the membranes to atmospheric air. Scanning electron microscopy and transmission electron microscopy were used to characterize the particles and modified membranes. SNP are evenly distributed on the membrane surface. Particle fixation and transport inside membranes were assessed before- and after-washing assays by X-ray photoelectron spectroscopy depth profiling analysis. PMMA addition improved SNP fixation. Plasma-treated membranes showed higher hydrophilicity. Anti-biofouling activity was successfully achieved against Gram-positive (Enterococcus faecalis) and -negative (Salmonella Typhimurium) bacteria. Therefore, disinfection by ultrafiltration showed substantial resistance to biofouling. The post-synthesis functionalization process developed provides a more efficient fabrication route for anti-biofouling and anti-bacterial membranes used in the water treatment field. To the best of our knowledge, this is the first report of a gas phase condensation process combined with a PECVD procedure in order to deposit SNP on commercial membranes to inhibit biofouling formation.

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Several recreational surface waters in Salta, Argentina, were selected to assess their quality. Seventy percent of the measurements exceeded at least one of the limits established by international legislation becoming unsuitable for their use. To interpret results of complex data, multivariate techniques were applied. Arenales River, due to the variability observed in the data, was divided in two: upstream and downstream representing low and high pollution sites, respectively, and cluster analysis supported that differentiation. Arenales River downstream and Campo Alegre Reservoir were the most different environments, and Vaqueros and La Caldera rivers were the most similar. Canonical correlation analysis allowed exploration of correlations between physicochemical and microbiological variables except in both parts of Arenales River, and principal component analysis allowed finding relationships among the nine measured variables in all aquatic environments. Variable's loadings showed that Arenales River downstream was impacted by industrial and domestic activities, Arenales River upstream was affected by agricultural activities, Campo Alegre Reservoir was disturbed by anthropogenic and ecological effects, and La Caldera and Vaqueros rivers were influenced by recreational activities. Discriminant analysis allowed identification of subgroup of variables responsible for seasonal and spatial variations. Enterococcus, dissolved oxygen, conductivity, E. coli, pH, and fecal coliforms are sufficient to spatially describe the quality of the aquatic environments. Regarding seasonal variations, dissolved oxygen, conductivity, fecal coliforms, and pH can be used to describe water quality during dry season, while dissolved oxygen, conductivity, total coliforms, E. coli, and Enterococcus during wet season. Thus, the use of multivariate techniques allowed optimizing monitoring tasks and minimizing costs involved.

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Many developing and threshold countries rely on shallow groundwater wells for their water supply whilst pit latrines are used for sanitation. We employed a unified strategy involving satellite images and environmental monitoring of 16 physico-chemical and microbiological water quality parameters to identify significant land uses that can lead to unacceptable deterioration of source water, in a region with a subtropical climate and seasonally restricted torrential rainfall in Northern Argentina. Agricultural and non-agricultural sources of nitrate were illustrated in satellite images and used to assess the organic load discharged. The estimated human organic load per year was 28.5 BOD(5) tons and the N load was 7.5 tons, while for poultry farms it was 9940-BOD(5) tons and 1037-N tons, respectively. Concentrations of nitrates and organics were significantly different between seasons in well water (p values of 0.026 and 0.039, respectively). The onset of the wet season had an extraordinarily negative impact on well water due in part to the high permeability of soils made up of fine gravels and coarse sand. Discriminant analysis showed that land uses had a pronounced seasonal influence on nitrates and introduced additional microbial contamination, causing nitrification and denitrification in shallow groundwater. P-well was highly impacted by a poultry farm while S-well was affected by anthropogenic pollution and background load, as revealed by Principal Component Analysis. The application of microbial source tracking techniques is recommended to corroborate local sources of human versus animal origin.

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