In this study, the estimated amounts of discarded face masks due to COVID 19 were investigated. In this context, the amount of waste face masks was determined separately according to the mask types used (nonwoven, meltblown, and 3-ply, pleated) and the importance of waste face masks was revealed. According to obtained data, the estimated total daily face mask use in Turkey is 72,351,638. The highest amounts of nonwoven, meltblown, and 3-ply face mask waste were determined as 26.88, 36.29, and 43.68 tonnes/day for İstanbul city, respectively. Total amounts of nonwoven, meltblown and 3-ply face mask waste in Turkey were calculated as 144.7, 195.35, and 235.14 tonnes/day, respectively. The top 5 provinces with the highest amount of waste masks are listed as follows; İstanbul (nonwoven=26.88, meltblown=36.29, 3ply=43.68 tonnes/day), Ankara (nonwoven=9.91, meltblown=13.38, 3ply=16.11 tonnes/day), İzmir (nonwoven=7.76, meltblown=10.47, 3ply=12.61 tonnes/day), Bursa (nonwoven=5.40, meltblown=7.29, 3ply=8.78 tonnes/day), and Antalya (nonwoven=4.45, meltblown=6.01, 3ply=7.23 tonnes/day), respectively. In Turkey, 91.3% of medical waste collected in health institutions in 2019 (90,920 tonnes) was sterilized and disposed of in storage areas (83,010 tonnes). 8.7% of medical waste was sent to incineration facilities and disposed (7,910 tonnes). Considering these values, 132, 178.35, and 214.7 tonnes/day of nonwoven, meltblown, and 3-ply face mask wastes can be disposed by sterilization and the remaining 12.7, 17, and 20.44 tonnes/day by incineration, respectively.

Studies have reported significant reductions in air pollutant levels due to the COVID-19 outbreak worldwide global lockdowns. Nevertheless, all of the reports are limited compared to data from the same period over the past few years, providing mainly an overview of past events, with no future predictions. Lockdown level can be directly related to the number of new COVID-19 cases, air pollution, and economic restriction. As lockdown status varies considerably across the globe, there is a window for mega-cities to determine the optimum lockdown flexibility. To that end, firstly, we employed four different Artificial Neural Networks (ANN) to examine the compatibility to the original levels of CO, O₃, NO₂, NO, PM₂.₅, and PM₁₀, for São Paulo City, the current Pandemic epicenter in South America. After checking compatibility, we simulated four hypothetical scenarios: 10%, 30%, 70%, and 90% lockdown to predict air pollution levels. To our knowledge, ANN have not been applied to air pollution prediction by lockdown level. Using a limited database, the Multilayer Perceptron neural network has proven to be robust (with Mean Absolute Percentage Error ∼ 30%), with acceptable predictive power to estimate air pollution changes. We illustrate that air pollutant levels can effectively be controlled and predicted when flexible lockdown measures are implemented. The models will be a useful tool for governments to manage the delicate balance among lockdown, number of COVID-19 cases, and air pollution.

Knowledge about how the COVID-19 pandemic can affect aquatic wildlife is still extremely limited, and no effect of SARS-CoV-2 or its structural constituents on invertebrate models has been reported so far. Thus, we investigated the presence of the 2019-new coronavirus in different urban wastewater samples and, later, evaluated the behavioral and biochemical effects of the exposure of Culex quinquefasciatus larvae to two SARS-CoV-2 spike protein peptides (PSPD-2002 and PSPD-2003) synthesized in our laboratory. Initially, our results show the contamination of wastewater by the new coronavirus, via RT-qPCR on the viral N1 gene. On the other hand, our study shows that short-term exposure (48 h) to a low concentration (40 μg/L) of the synthesized peptides induced changes in the locomotor and the olfactory-driven behavior of the C. quinquefascitus larvae, which were associated with increased production of ROS and AChE activity (cholinesterase effect). To our knowledge, this is the first study that reports the indirect effects of the COVID-19 pandemic on the larval phase of a freshwater invertebrate species. The results raise concerns at the ecological level where the observed biological effects may lead to drastic consequences.

Previous nationwide studies have reported links between long-term concentrations of fine particulate matter (PM2.5) and COVID-19 infection and mortality rates. In order to translate these results to the state level, we use Bayesian hierarchical models to explore potential links between long-term PM2.5 concentrations and census tract-level rates of COVID-19 outcomes (infections, hospitalizations, and deaths) in Colorado. We explicitly consider how the uncertainty in PM2.5 estimates affects our results by comparing four different PM2.5 surfaces from academic and governmental organizations. After controlling for 20 census tract-level covariates, we find that our results depend heavily on the choice of PM2.5 surface. Using PM2.5 estimates from the United States EPA, we find that a 1 μg/m³ increase in long-term PM2.5 concentrations is associated with a statistically significant 26% increase in the relative risk of hospitalizations and a 34% increase in mortality. Results for all other surfaces and outcomes were not statistically significant. At the same time, we find a clear association between communities of color and COVID-19 outcomes at the Colorado census tract level that is minimally affected by the choice of PM2.5 surface. A per-interquartile range (IQR) increase in the percent of non-African American people of color was associated with a 31%, 43%, and 56% increase in the relative risk of infection, hospitalization, and mortality respectively, while a per-IQR increase in the proportion of non-Hispanic African Americans was associated with a 4% and 7% increase in the relative risk of infections and hospitalizations. The current disagreement among the different PM2.5 estimates is a key factor limiting our ability to link environmental exposures and health outcomes at the census tract level. These results have strong implications for the implementation of an equitable public health response during the crisis and suggest targeted areas for additional air monitoring in Colorado.

The COVID-19 pandemic has resulted in an unprecedented surge of production, consumption, and disposal of personal protective equipment (PPE) including face masks, disposable gloves, and disinfectant wipes, which are often made of single use plastic. Widespread public use of these items has imposed pressure on municipalities to properly collect and dispose of potentially infectious PPE. There has been a lack of structured monitoring efforts to quantify the emerging trend of improperly disposed of PPE debris. In this study, we present a baseline monitoring survey to describe the spatial distribution of PPE debris during the COVID-19 pandemic from the metropolitan city of Toronto, Canada. Our objectives were to: (1) quantify PPE debris types among surveyed areas and; (2) identify PPE debris densities and accumulation of surveyed areas. A total of 1306 PPE debris items were documented, with the majority being disposable gloves (44%), followed by face masks (31%), and disinfecting wipes (25%). Of the face masks, 97% were designed for single use while only 3% were reusable. Of the surveyed locations, the highest daily average densities of PPE debris were recorded in the large and medium-sized grocery store parking lots and the hospital district (0.00475 items/m², 0.00160 items/m², and 0.00133 items/m² respectively). The two surveyed residential areas had the following highest PPE densities (0.00029 items/m² and 0.00027 items/m²), while the recreational trail had the lowest densities (0.00020 items/m²). Assuming a business-as-usual accumulation, an estimated 14,298 PPE items will be leaked as debris in just the surveyed areas annually. To facilitate proper disposal of PPE debris by the public we recommend development of municipal efforts to improve PPE collection methods that are informed by the described PPE waste pathways.

COVID-19 pandemic has led to concerns on the circulation of SARS-CoV-2 in the environment, its infectivity from the environment and, the relevance of transmission via environmental compartments. During 31 weeks, water samples were collected from a heavily contaminated stream going through an urban, underprivileged community without sewage collection. Our results showed a statistically significant correlation between cases of COVID-19 and SARS in the community, and SARS-CoV-2 concentrations in the water. Based on the model, if the concentrations of SARS-CoV-RNA (N1 and N2 target regions) increase 10 times, there is an expected increase of 104% [95%CI: (62–157%)] and 92% [95%CI: (51–143%)], respectively, in the number of cases of COVID-19 and SARS. We believe that differences in concentration of the virus in the environment reflect the epidemiological status in the community, which may be important information for surveillance and controlling dissemination in areas with vulnerable populations and poor sanitation. None of the samples were found infectious based cultures. Our results may be applicable globally as similar communities exist worldwide.

While local anthropogenic emission sources contribute largely to deteriorate metro air quality, long range transport can also play a significant role in influencing levels of pollutants, particularly carbon monoxide (CO) that has a relatively long life span. A nationwide lockdown of two months imposed across India amid COVID-19 led to a dramatic decline in major sources of emissions except for household, mainly from cooking. This initially led to declined levels of CO in two of the largest megacities of India, Delhi and Mumbai under stable weather conditions, followed by a distinctly different variability under the influence of prevailing mesoscale circulation. We hereby trace the sources of CO from local emissions to transport pathways and interpret the observed variability in CO using the interactive WRF-Chem model and back trajectory analysis. For this purpose, COVID-19 emission inventory of CO has been estimated. Model results indicate a significant contribution from externally generated CO in Delhi from surrounding regions and an unusual peak on 17th May amid lockdown due to long range transport from the source region of biofuel emissions in central India. However, the oceanic winds played a larger role in keeping CO levels in check in a coastal megacity Mumbai which otherwise has high CO emissions from household sources due to a larger share of urban slums. Keeping track of evolving carbon-intensive pathways can help inform government responses to the COVID-19 pandemic to prioritize controls of emissions sources.

In December 2019, a novel disease, coronavirus disease 19 (COVID-19), emerged in Wuhan, People’s Republic of China. COVID-19 is caused by a novel coronavirus (SARS-CoV-2) presumed to have jumped species from another mammal to humans. This virus has caused a rapidly spreading global pandemic. To date, over 300,000 cases of COVID-19 have been reported in England and over 40,000 patients have died. While progress has been achieved in managing this disease, the factors in addition to age that affect the severity and mortality of COVID-19 have not been clearly identified. Recent studies of COVID-19 in several countries identified links between air pollution and death rates. Here, we explored potential links between major fossil fuel-related air pollutants and SARS-CoV-2 mortality in England. We compared current SARS-CoV-2 cases and deaths from public databases to both regional and subregional air pollution data monitored at multiple sites across England. After controlling for population density, age and median income, we show positive relationships between air pollutant concentrations, particularly nitrogen oxides, and COVID-19 mortality and infectivity. Using detailed UK Biobank data, we further show that PM₂.₅ was a major contributor to COVID-19 cases in England, as an increase of 1 m³ in the long-term average of PM₂.₅ was associated with a 12% increase in COVID-19 cases. The relationship between air pollution and COVID-19 withstands variations in the temporal scale of assessments (single-year vs 5-year average) and remains significant after adjusting for socioeconomic, demographic and health-related variables. We conclude that a small increase in air pollution leads to a large increase in the COVID-19 infectivity and mortality rate in England. This study provides a framework to guide both health and emissions policies in countries affected by this pandemic.

During the current pandemic, chemical disinfectants are ubiquitously and routinely used in community environments, especially on common touch surfaces in public settings, as a means of controlling the virus spread. An underappreciated risk in current regulatory guidelines and scholarly discussions, however, is that the persisting input of chemical disinfectants can exacerbate the growth of biocide-tolerant and antibiotic-resistant bacteria on those surfaces and allow their direct transfers to humans. For COVID-19, the most commonly used disinfecting agents are quaternary ammonium compounds, hydrogen peroxide, sodium hypochlorite, and ethanol, which account for two-thirds of the active ingredients in current EPA-approved disinfectant products for the novel coronavirus. Tolerance to each of these compounds, which can be either intrinsic or acquired, has been observed on various bacterial pathogens. Of those, mutations and horizontal gene transfer, upregulation of efflux pumps, membrane alteration, and biofilm formation are the common mechanisms conferring biocide tolerance in bacteria. Further, the linkage between disinfectant use and antibiotic resistance was suggested in laboratory and real-life settings. Evidence showed that substantial bacterial transfers to hands could effectuate from short contacts with surrounding surfaces and further from fingers to lips. While current literature on disinfectant-induced antimicrobial resistance predominantly focuses on municipal wastes and the natural environments, in reality the community and public settings are most severely impacted by intensive and regular chemical disinfecting during COVID-19 and, due to their proximity to humans, biocide-tolerant and antibiotic-resistant bacteria emerged in these environments may pose risks of direct transfers to humans, particularly in densely populated urban communities. Here we highlight these risk factors by reviewing the most pertinent and up-to-date evidence, and provide several feasible strategies to mitigate these risks in the scenario of a prolonging pandemic.

The occurrence of human pathogenic viruses in aquatic ecosystems and, in particular, in internal water bodies (i.e., river, lakes, groundwater, drinking water reservoirs, recreational water utilities, and wastewater), raises concerns regarding the related impacts on environment and human health, especially in relation to the possibility of human exposure and waterborne infections. This paper reviews the current state of knowledge regarding severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) presence and persistence in human excreta, wastewaters, sewage sludge as well as in natural water bodies, and the possible implications for water services in terms of fecal transmission, public health, and workers’ risk. Furthermore, the impacts related to the adopted containment and emergency management measures on household water consumptions are also discussed, together with the potential use of wastewater-based epidemiology (WBE) assessment as a monitoring and early warning tool, to be applied in case of infectious disease outbreaks. The knowledge and tools summarized in this paper provide a basic information reference, supporting decisions makers in the definition of suitable measures able to pursue an efficient water and wastewater management and a reduction of health risks. Furthermore, research questions are provided, in order to direct technical and public health communities towards a sustainable water service management in the event of a SARS-CoV-2 re-emergence, as well as a future deadly outbreak or pandemic.