Weather indicators and improving air quality in association with COVID-19 pandemic in India.
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ABSTRACT: Supplementary information
The online version contains supplementary material available at 10.1007/s00500-021-06012-9.
SUBMITTER: Chakrabortty R
PROVIDER: S-EPMC8276232 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Spatial hot spots of COVID-19 infections and fatalities are observed at places exposed to high levels of air pollution across many countries. This study empirically investigates the relationship between exposure to air pollutants that is, sulfur dioxide, nitrogen dioxide, and particulate matter (SO2, NO2, and PM10) and COVID-19 infection at the smallest administrative level (ward) of Mumbai City in India. The paper explores two hypotheses: COVID-19 infection is associated with air pollution; the pollutants act as determinants of COVID-19 deaths. Kriging is used to assess the spatial variations of air quality using pollution data, while information on COVID-19 are retrieved from the database of Mumbai municipality. Annual average of PM10 in Mumbai over the past 3 years is much higher than the WHO specified standard across all wards; further, suburbs are more exposed to SO2, and NO2 pollution. Bivariate local indicator of spatial autocorrelation finds significant positive relation between pollution and COVID-19 infected cases in certain suburban wards. Spatial Auto Regressive models suggest that COVID-19 death in Mumbai is distinctly associated with higher exposure to NO2, population density and number of waste water drains. If specific pollutants along with other factors play considerable role in COVID-19 infection, it has strong implications for any mitigation strategy development with an objective to curtail the spreading of the respiratory disease. These findings, first of its kind in India, could prove to be significant pointers toward disease alleviation and better urban living.
| S-EPMC8287720 | biostudies-literature
Project description:COVID-19 pandemic compelled many countries in the world to go for a nationwide lockdown to prevent the spread of the coronavirus. India started the lockdown on 24 March 2020. We analyzed the air quality of three megacities of India, namely Mumbai, Delhi, and Kolkata, during the lockdown phase and compared it with the pre-lockdown and post-lockdown scenarios. We considered seven major air pollutants: PM2.5, PM10, NO2, NH3, SO2, CO, and O3. We analyzed the data acquired from 56 automatic air-monitoring stations (AAMS) under the Central Pollution Control Board (CPCB) spread across the megacities. The air pollution level in the eastern part of Mumbai and the western part of Delhi and Kolkata usually remains high. Delhi was the worst polluted megacity, followed by Kolkata and Mumbai. The stop of vehicular movements and industrial lockdown across the nation has substantial effects on the environment, especially in the atmosphere near the Earth's surface. Our analysis showed significant improvements in air quality during the period of lockdown (25 March to 14 April 2020) compared to the pre-lockdown phase (3 March to 23 March 2020) and the same time window of the previous year (25 March to 14 April 2019). The post-lockdown (15 April to 5 May) phase exhibited mixed results. We mapped the spatial pattern of these pollutants and the air quality index (AQI). According to CPCB, PM2.5, PM10, and CO are the major air pollutants in India that reduced by 47%, 41%, and 27% in Mumbai; 52%, 39%, and 13% in Delhi; and 49%, 37%, and 21% in Kolkata, respectively, in the lockdown phase. PM2.5, PM10, and NO2 exhibited significant correlations across the three megacities. This study shows that occasional short-term lockdowns can effectively refresh the air in these megacities.
| S-EPMC9757857 | biostudies-literature
Project description:Background:COVID-19 is a global pandemic. The purpose of this study is to explore correlations between the novel coronavirus (COVID-19) and meteorological indicators from cities across China. Methods:We collected daily data of the cumulative number of infected, recovered and death cases, and the meteorological indicators including average temperature, wind speed, relative humidity, precipitation and air quality index (AQI) from 12 cities in China during the period of Jan 23 to Feb 22, 2020. Correlation tests were chosen for data analysis. Results:The average temperature and AQI showed significant association with the mortality rate of COVID-19. The mortality rate was not correlated with wind speed, relative humidity or precipitation. Meanwhile, higher average temperatures and more precipitation were beneficial for the recovery rate of COVID-19, but the recovery rate was not correlated with wind speed, relative humidity or AQI. Conclusions:Our study provides a new basis for correlations between COVID-19, meteorological indicators and air quality index, which can help authorities to combat COVID-19.
| S-EPMC7561282 | biostudies-literature
Project description:Weather forecasts play essential parts in economic activity. Assimilation of meteorological observations from aircraft improves forecasts greatly. However, global lockdown during the COVID-19 pandemic (March to May 2020) has eliminated 50-75% aircraft observations and imperiled weather forecasting. Here, we verify global forecasts against reanalysis to quantify the impact of the pandemic. We find a large deterioration in forecasts of surface meteorology over regions with busy air flights, such as North America, southeast China, and Australia. Forecasts over remote regions are also substantially worse during March to May 2020 than 2017-2019, and the deterioration increases for longer-term forecasts. This could handicap early warning of extreme weather and cause additional economic damage on the top of that from the pandemic. The impact over Western Europe is buffered by the high density of conventional observations, suggesting that introduction of new observations in data-sparse regions would be needed to minimize the impact of global emergencies on weather forecasts.
| S-EPMC7404364 | biostudies-literature
Project description:The coronavirus disease 2019 (COVID-19) pandemic has caused an unprecedented global health crisis, with several countries imposing lockdowns to control the coronavirus spread. Important research efforts are focused on evaluating the association of environmental factors with the survival and spread of the virus and different works have been published, with contradictory results in some cases. Data with spatial and temporal information is a key factor to get reliable results and, although there are some data repositories for monitoring the disease both globally and locally, an application that integrates and aggregates data from meteorological and air quality variables with COVID-19 information has not been described so far to the best of our knowledge. Here, we present DatAC (Data Against COVID-19), a data fusion project with an interactive web frontend that integrates COVID-19 and environmental data in Spain. DatAC is provided with powerful data analysis and statistical capabilities that allow users to explore and analyze individual trends and associations among the provided data. Using the application, we have evaluated the impact of the Spanish lockdown on the air quality, observing that NO2, CO, PM2.5, PM10 and SO2 levels decreased drastically in the entire territory, while O3 levels increased. We observed similar trends in urban and rural areas, although the impact has been more important in the former. Moreover, the application allowed us to analyze correlations among climate factors, such as ambient temperature, and the incidence of COVID-19 in Spain. Our results indicate that temperature is not the driving factor and without effective control actions, outbreaks will appear and warm weather will not substantially limit the growth of the pandemic. DatAC is available at https://covid19.genyo.es.
| S-EPMC7399783 | biostudies-literature
Project description:India enforced stringent lockdown measures on March 24, 2020 to mitigate the spread of the Severe Acute Respiratory Syndrome Coronovirus-2 (SARS-CoV-2). Here, we examined the impact of lockdown on the air quality index (AQI) [including ambient particulate matter (PM10 and PM2.5), nitrogen dioxide (NO2), sulfur dioxide (SO2), carbon monoxide (CO), ozone (O3), and ammonia (NH3)] and tropospheric NO2 and O3 densities through Sentinel-5 satellite data approximately 1 d post-lockdown and one month pre-lockdown and post-lockdown. Our findings revealed a marked reduction in the ambient AQI (estimated mean reduction of 17.75% and 20.70%, respectively), tropospheric NO2 density, and land surface temperature (LST) during post-lockdown compared with the pre-lockdown period or corresponding months in 2019, except for a few sites with substantial coal mining and active power plants. We observed a modest increase in the O3 density post-lockdown, thereby indicating improved tropospheric air quality. As a favorable outcome of the COVID-19 lockdown, road accident-related mortalities declined by 72-folds. Cities with poor air quality correlate with higher COVID-19 cases and deaths (r = 0.504 and r = 0.590 for NO2; r = 0.744 and r = 0.435 for AQI). Conversely, low mortality was reported in cities with better air quality. These results show a correlation between the COVID-19 vulnerable regions and AQI hotspots, thereby suggesting that air pollution may exacerbate clinical manifestations of the disease. However, a prolonged lockdown may nullify the beneficial environmental outcomes by adversely affecting socioeconomic and health aspects.
| S-EPMC7590817 | biostudies-literature
Project description:With the emergence of the COVID-19 pandemic, several governments imposed severe restrictions on socio-economic activities, putting most of the world population into a general lockdown in March 2020. Although scattered, studies on this topic worldwide have rapidly emerged in the literature. Hence, this systematic review aimed to identify and discuss the scientifically validated literature that evaluated the impact of the COVID-19 pandemic and associated restrictions on air quality. Thus, a total of 114 studies that quantified the impact of the COVID-19 pandemic on air quality through monitoring were selected from three databases. The most evaluated countries were India and China; all the studies intended to evaluate the impact of the pandemic on air quality, mainly concerning PM10, PM2.5, NO2, O3, CO, and SO2. Most of them focused on the 1st lockdown, comparing with the pre- and post-lockdown periods and usually in urban areas. Many studies conducted a descriptive analysis, while others complemented it with more advanced statistical analysis. Although using different methodologies, some studies reported a temporary air quality improvement during the lockdown. More studies are still needed, comparing different lockdown and lifting periods and, in other areas, for a definition of better-targeted policies to reduce air pollution.
| S-EPMC8871899 | biostudies-literature
Project description:Rising temperature levels during spring and summer are often argued to enable lifting of strict containment measures even in the absence of herd immunity. Despite broad scholarly interest in the relationship between weather and coronavirus spread, previous studies come to very mixed results. To contribute to this puzzle, the paper examines the impact of weather on the COVID-19 pandemic using a unique granular dataset of over 1.2 million daily observations covering over 3700 counties in nine countries for all seasons of 2020. Our results show that temperature and wind speed have a robust negative effect on virus spread after controlling for a range of potential confounding factors. These effects, however, are substantially larger during mealtimes, as well as in periods of high mobility and low containment, suggesting an important role for social behaviour.
| S-EPMC8585954 | biostudies-literature
Project description:This study aims at analyzing the change in air quality following the COVID-19 lockdown in India and its perception by the general public. Air quality data for 100 days recorded at 193 stations throughout India were analyzed between 25th March to 17th May 2020. A nationwide online survey was conducted to obtain public perceptions of air quality improvement (n=1750). On average, approximately 40% improvement in the air quality index was observed, contributed by a reduction in 40% of PM10, 44% of PM2.5, 51% of NO2 and 21% of SO2. There was a significant difference between the levels of all the pollutants before and after the lockdown (p<0.05), except ozone. The correlation between PM10 and PM2.5 with ozone was significant after the lockdown period, indicating that a significant portion of the particulates present in the atmosphere after the lockdown period is secondary. The values of PM2.5/PM10 were found to be greater than 0.5 in North East states and this observation points to the long-distance transport of PM2.5 from other places. The survey for public perception showed that 60% of the respondents perceived improvement in air quality. Household emissions were perceived to be a significant source of pollution after the lockdown. An odds ratio (OR) of 17 (95%, CI: 6.42, 47.04) indicated a very high dependence of perception on actual air quality. OR between air quality and health improvement was 5.2 (95%, CI: 2.69, 10.01), indicating significant health improvement due to air quality improvement. Google Trends analysis showed that media did not influence shaping the perception. There was a significant improvement in the actual and perceived air quality in India after the COVID-19-induced lockdown. PM10 levels had the most decisive influence in shaping public perception.
| S-EPMC9065608 | biostudies-literature
Project description:BackgroundThe COVID-19 pandemic has had a deep global impact, not only from a social and economic perspective, but also with regard to human health and the environment. To restrict transmission of the virus, the Indian government enforced a complete nationwide lockdown except for essential services and supplies in phases from 25 March to 31 May 2020. Ambient air quality in and around New Delhi, one of the most polluted cities of world, was also impacted during this period.ObjectiveThe aim of the present study was to assess and understand the impact of four different lockdown phases (LD1, LD2, LD3 and LD4) on five air pollutants (particulate matter (PM) PM2.5, PM10, nitrogen oxide (NOx), sulfur dioxide (SO2) and ozone (O3)) compared to before lockdown (BLD) at 13 air monitoring stations in and around New Delhi.MethodsSecondary data on five criteria pollutants for 13 monitoring stations in and around New Delhi for the period 1 March to 31 May 2020 was accessed from the Central Pollution Control Bard, New Delhi. Data were statistically analyzed across lockdown phases, meteorological variables, and prevailing air sources around the monitoring stations.ResultsPollutant concentrations decreased during LD1 compared to BLD except for O3 at all stations. PM2.5 and PM10 remained either close to or higher than the National Ambient Air Quality Standards (NAAQS) due to prevailing high-speed winds. During lockdown phases, NO2 decreased, whereas O3 consistently increased at all stations. This was a paradoxical situation as O3 is formed via photochemical reactions among NOx and volatile organic compounds. Principal component analysis (PCA) extracted two principal components (PC1 and PC2) which explained up to 80% of cumulative variance in data. PM2.5, PM10 and NO2 were associated with PC1, whereas PC2 had loadings of either O3 only or O3 and SO2 depending upon monitoring station.ConclusionsThe present study found that air pollutants decreased during lockdown phases, but these decreases were specific to the site(s) and pollutant(s). The decrease in pollutant concentrations during lockdown could not be attributed completely to lockdown conditions as the planetary boundary layer increased two-fold during lockdown compared to the BLD phase. Such restrictions could be applied in the future to control air pollution but should be approached with caution.Competing interestsThe authors declare no competing financial interests.
| S-EPMC8276728 | biostudies-literature