The UK implemented a lockdown in Spring (2020) to curtail the person-to-person transmission of the SARS-CoV-2 virus. Measures restricted movements to one outing per day for exercise and shopping, otherwise most people were restricted to their dwelling except for key workers (e.g. medical, supermarkets, and transport). In this study, we quantified changes to air quality across the United Kingdom from 30/03/2020 to 03/05/2020 (weeks 14–18), the period of most stringent travel restrictions. Daily pollutant measurements of NO₂, O₃ and PM₂.₅ from the national network of monitoring sites during this period were compared with measurements over the same period during 2017–19. Comparisons were also made with predicted concentrations for the 2020 period from business-as-usual (BAU) modelling, where the contributions of normal anthropogenic activities were estimated under the observed meteorological conditions. During the lockdown study period there was a 69% reduction in traffic overall (74% reduction in light and 35% in heavy vehicles). Measurements from 129 monitoring stations, identified mean reductions in NO₂ of 38.3% (−8.8 μg/m³) and PM₂.₅ of 16.5% (−2.2 μg/m³). Improvements in NO₂ and PM₂.₅ were largest at urban traffic sites and more modest at background locations where a large proportion of the population live. In contrast, O₃ concentrations on average increased by 7.6% (+4.8 μg/m³) with the largest increases at roadside sites due to reductions in local emissions of NO. A lack of VOC monitoring limited our capacity to interpret changes in O₃ at urban background locations. BAU models predicted comparable NO₂ reductions and O₃ gains, although PM₂.₅ episodes would have been more prominent without lockdown. Results demonstrate the relatively modest contribution of traffic to air quality, suggesting that sustained improvements in air quality require actions across various sectors, including working with international and European initiatives on long-range transport air pollutants, especially PM₂.₅ and O₃.

Identifying the individuals and geographical regions witnessing early infections or outbreaks of SARS-CoV-2 and its variants is helpful for studying the early epidemiology or even the origin of the novel coronavirus. Here, we put forward a strategy that can potentially contribute to this goal. Human body fluids and biological materials collected before the COVID-19 pandemic may serve as archives for retrospective testing of early human infections before the recent outbreaks. These have been routinely donated, collected, and archived, creating biorepositories or “biobanks” for clinical or research purposes. SARS-CoV-2 genetic materials and its antibodies have been confirmed in various types of biological samples from COVID-19 patients, including blood, sperm, umbilical cord blood, lung, heart, kidney and so on, making these biological archives as candidates for detecting early COVID-19 infections. Unlike sewage-based epidemiology which only provides information on the geographical aspect, viruses identified in archived human biological samples provide direct links to individuals, from whom a wealth of personal information including their profession, hobbies and activities, travel history, and previous exposure to wildlife can all be retrieved. By analyzing the patterns and links in the behavior of those early infected individuals, it is possible to trace the origin of the virus, for instance, in certain wild animals or local environments.

On December 31, 2019, the Chinese authorities reported to the World Health Organization (WHO) the outbreak of a new strain of coronavirus that causes a serious disease in the city of Wuhan, China. This outbreak was classified as SARS-CoV2 and is the cause of the COVID-19 disease. On March 11, 2020, the WHO declares it a Pandemic and today it is considered the greatest challenge in global health that humanity has faced since World War II and it is estimated that between 40 and 60% of the population worldwide will catch the virus. This has caused enormous challenges in countries around the world in social, economic, environmental and obviously health issues. These challenges are mainly due to the effects of the established quarantines in almost all capitals and major cities around the world, from Asia, Europe to America. However, these lockdown which began worldwide from January 23, have had a significant impact on the environment and on the air quality of cities as recently reported by NASA (National Aeronautics and Space Administration) and ESA (European Space Agency), with reductions according to them of up to 30% in some of the epicenters such as the case of Wuhan. Knowing that air pollution causes approximately 29% of lung cancer deaths, 43% of COPD deaths, and 25% of ischemic heart disease deaths, it is important to know the effects of quarantines in cities regarding air quality to take measures that favor populations and urban ecosystems when the emergency ends. Therefore, this paper describes the behavior of PM₂.₅ emissions particulate matter from the 50 most polluted capital cities in the world according to the WHO, measured before-after the start of the quarantine. Likewise, the impact at the local and global level of this emissions behavior, which averaged 12% of PM₂.₅ decrease in these cities.

From a health prospective, it is critical to provide a comprehensive model which integrates all the parameters involved in virus transmission and its consequences on human body. In order to estimate the health risks, for workers and residents, associated with an exposure airborne viruses emitted from a wastewater treatment (WWTP), the concentration levels of viruses in emitted bioaerosols over a twelve-month period were measured by real-time polymerase chain reaction (RT-PCR). A combined Gaussian plum dispersion model and quantitative microbial risk assessment (QMRA) with Monte-Carlo simulation served as suitable explanatory tools to estimate the risk of acquiring gastrointestinal illness (GI) due to exposure to air containing Rotavirus (RoV) and Norovirus (NoV) bioaerosols. Additionally, DALY metric was applied to quantify the disability and mortality for workers and residents. RoV and NoV were detected above aeration tank with annual mean concentration 27 and 3099 (Viruses/m³.h), respectively. The medium calculated DALY indicator based on viral loads in contaminant source (RoV:5.76 × 10⁻² and NoV:1.23 × 10⁻¹) and estimated in different distances away (300–1000 m) (RoV:2.87 × 10⁻²- 2.75 × 10⁻² and NoV:1.14 × 10⁻¹-1.13 × 10⁻¹) were markedly higher than the threshold values recommended by US EPA (10⁻⁴ DALY pppy) and WHO (10⁻⁶ DALY pppy). The sensitivity analysis highlighted dose exposure and disease burden per case (DBPC) as two most influential factors for both workers and residents following exposure to two pathogens of concern. Due to high resistance and high concentration in the environment, the presence of RoV and NoV can intensify the consequences of diarrhea especially for children under five years of age; A comprehensible and transparent presentation of DALYs and QMRA can help decision makers and responsibilities to justify the priorities of exposure to wastewater in comparison with other risks of daily life.

The consequence of the lockdowns implemented to address the COVID-19 pandemic on human health damage due to air pollution and other environmental issues must be better understood. This paper analyses the effect of reducing energy demand on the evolution of environmental impacts during the occurrence of 2020-lockdown periods in Italy, with a specific focus on life expectancy. An energy metabolism analysis is conducted based on the life cycle assessment (LCA) of all monthly energy consumptions, by sector, category and province area in Italy between January 2015 to December 2020. Results show a general decrease (by ∼5% on average) of the LCA midpoint impact categories (global warming, stratospheric ozone depletion, fine particulate matter formation, etc.) over the entire year 2020 when compared to past years. These avoided impacts, mainly due to reductions in fossil energy consumptions, are meaningful during the first lockdown phase between March and May 2020 (by ∼21% on average). Regarding the LCA endpoint damage on human health, ∼66 Disability Adjusted Life Years (DALYs) per 100,000 inhabitants are estimated to be saved. The analysis shows that the magnitude of the officially recorded casualties is substantially larger than the estimated gains in human lives due to the environmental impact reductions. Future research could therefore investigate the complex cause-effect relationships between the deaths occurred in 2020 imputed to COVID-19 disease and co-factors other than the SARS-CoV-2 virus.

Among wild birds, lead (Pb) exposure caused by ingestion of ammunition is a worldwide problem. We aimed to reveal the behavior and toxic effect of Pb caused by ingesting Pb shots in waterfowl. Four male, eight-week old Muscovy ducks (Cairina moschata) were given three Pb shots (approximately 240 mg in total) orally and then fed for 29 days after exposure, simulating a low-dose Pb exposure in wild waterfowl. During the breeding period, blood samples were collected 10 times, and fecal samples every day. Additionally, 22 fresh tissue and 6 bone samples were obtained from each duck through the dissection. Although there were no gross abnormalities, the maximum blood Pb concentration of each duck ranged from 0.6 to 3.7 mg/L, reaching a threshold concentration indicative of clinical symptoms (>0.5 mg/L). δ-aminolevulinic acid dehydratase declined one day after exposure and remained low throughout the feeding period. Hematocrit also tended to decrease, indicating signs of anemia. The highest Pb accumulation was observed in the bones, followed by the kidneys, intestinal tracts, and liver. High Pb accumulation in the bones, which are known to have a long Pb half-life, suggested that Pb would remain in the body and possibly affect bird health beyond 28 days after exposure. Gene expression analysis showed a significant increase in the expression of the toll-like receptor-3 gene, which is involved in virus discrimination in the liver, suggesting a disruption of the immune system. Microbiota analyses showed a correlation between the blood Pb concentration and the abundances of Lachnospiraceae and Ruminococcaceae, suggesting that Pb affects lipid metabolism. These results provide fundamental data on Pb exposure in wild birds and a new perspective on the damage such exposure causes.

The widespread use of disposable face masks as a preventative strategy to address transmission of the SARS-CoV-2 virus has been a key environmental concern since the pandemic began. This has led to an unprecedented new form of contamination from improperly disposed masks, which liberates significant amounts of heavy metals and toxic chemicals in addition to volatile organic compounds (VOCs). Therefore, this study monitored the liberation of heavy metals, VOCs, and microfibers from submerged disposable face masks at different pH (4, 7 and 12), to simulate distinct environmental conditions. Lead (3.238% ppb), cadmium (0.672 ppb) and chromium (0.786 ppb) were found in the analyzed leachates. By pyrolysis, 2,4-dimethylhept-1-ene and 4-methylheptane were identified as the VOCs produced by the samples. The chemically degraded morphology in the FESEM images provided further evidence that toxic heavy metals and volatile organic compounds had been leached from the submerged face masks, with greater degradation observed in samples submerged at pH 7 and higher. The results are seen to communicate the comparable danger of passively degrading disposable face masks and the release of micro- or nanofibers into the marine environment. The toxicity of certain heavy metals and chemicals released from discarded face masks warrants better, more robust manufacturing protocols and increased public awareness for responsible disposal to reduce the adverse impact on ecology and human health.

During March 2020, most European countries implemented lockdowns to restrict the transmission of SARS-CoV-2, the virus which causes COVID-19 through their populations. These restrictions had positive impacts for air quality due to a dramatic reduction of economic activity and atmospheric emissions. In this work, a machine learning approach was designed and implemented to analyze local air quality improvements during the COVID-19 lockdown in Graz, Austria. The machine learning approach was used as a robust alternative to simple, historical measurement comparisons for various individual pollutants. Concentrations of NO₂ (nitrogen dioxide), PM₁₀ (particulate matter), O₃ (ozone) and Oₓ (total oxidant) were selected from five measurement sites in Graz and were set as target variables for random forest regression models to predict their expected values during the city’s lockdown period. The true vs. expected difference is presented here as an indicator of true pollution during the lockdown. The machine learning models showed a high level of generalization for predicting the concentrations. Therefore, the approach was suitable for analyzing reductions in pollution concentrations. The analysis indicated that the city’s average concentration reductions for the lockdown period were: -36.9 to −41.6%, and −6.6 to −14.2% for NO₂ and PM₁₀, respectively. However, an increase of 11.6–33.8% for O₃ was estimated. The reduction in pollutant concentration, especially NO₂ can be explained by significant drops in traffic-flows during the lockdown period (−51.6 to −43.9%). The results presented give a real-world example of what pollutant concentration reductions can be achieved by reducing traffic-flows and other economic activities.

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.

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.