Statistical modeling approach for PM10 prediction before and during confinement by COVID-19 in South Lima, Perú.

A total of 188,859 meteorological-PM[Formula: see text] data validated before (2019) and during the COVID-19 pandemic (2020) were used. In order to predict PM[Formula: see text] in two districts of South Lima in Peru, hourly, daily, monthly and seasonal variations of the data were analyzed. Principal Component Analysis (PCA) and linear/nonlinear modeling were applied. The results showed the highest annual average PM[Formula: see text] for San Juan de Miraflores (SJM) (PM[Formula: see text]-SJM: 78.7 [Formula: see text]g/m[Formula: see text]) and the lowest in Santiago de Surco (SS) (PM[Formula: see text]-SS: 40.2 [Formula: see text]g/m[Formula: see text]). The PCA showed the influence of relative humidity (RH)-atmospheric pressure (AP)-temperature (T)/dew point (DP)-wind speed (WS)-wind direction (WD) combinations. Cool months with higher humidity and atmospheric instability decreased PM[Formula: see text] values in SJM and warm months increased it, favored by thermal inversion (TI). Dust resuspension, vehicular transport and stationary sources contributed more PM[Formula: see text] at peak times in the morning and evening. The Multiple linear regression (MLR) showed the best correlation (r = 0.6166), followed by the three-dimensional model LogAP-LogWD-LogPM[Formula: see text] (r = 0.5753); the RMSE-MLR (12.92) exceeded that found in the 3D models (RMSE [Formula: see text]) and the NSE-MLR criterion (0.3804) was acceptable. PM[Formula: see text] prediction was modeled using the algorithmic approach in any scenario to optimize urban management decisions in times of pandemic.

Considerations on water quality and the use of chlorine in times of SARS-CoV-2 (COVID-19) pandemic in the community

This review goal is to reflect on the challenges and prospects for water quality in the face of the pandemic caused by the new SARS-CoV-2 coronavirus (COVID-19). Based on the information available so far, the detection of SARS-CoV-2 RNA in wastewater has raised interest in using it as an early warning method, to detect the resurgence of infections and to report the risk associated with contracting SARS-CoV-2 in contact with untreated water or inadequately treated wastewater is discharged. The wastewater-based epidemiological approach can be used as an early indicator of infection within a specific population. On the other hand, it is necessary to collect information from the managers of drinking water supply companies and professionals who are related to water quality, to know SARS-CoV-2 data and information, and its influence on drinking water quality. The basic purpose of this review article is to try to provide a valuable and quick reference guide to COVID-19. Important topics were discussed, such as detection of SARS-CoV-2 in wastewater in various parts of the world;wastewater screening to monitor COVID-19;persistence of SARS-CoV-2 in aquatic systems;the presence of SARS-CoV-2 in drinking water;clean water as a mechanism to deal with the COVID-19 pandemic;chlorine as a disinfectant to eliminate SARS-CoV-2 and damage to ecosystems by the use of chlorine. Currently does not exist extensive literature on the effectiveness of water and wastewater treatment processes that ensure the correct elimination of SARS-CoV-2. Excessive use of disinfectants such as chlorine is causing effects on the environment. This document highlights the need for further research to establish the behavior of the SARS-CoV-2 virus in aquatic systems. This study presents an early overview of the observed and potential impacts of COVID-19 on the environment.