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Impacts of irregular and strategic lockdown on air quality over Indo-Pak Subcontinent: Pre-to-post COVID-19 analysis
... Air pollution stems from a variety of human activities and natural occurrences, including industrial emissions, vehicle exhaust, burning of fossil fuels, agricultural practices, wildfires, and volcanic eruptions. [2] These sources release harmful pollutants like particulate matter, nitrogen oxides, sulfur dioxide, and volatile organic compounds into the atmosphere, leading to the deterioration of air quality. The repercussions of air pollution on human health are significant, with exposure to pollutants such as particulate matter (PM10, PM2.5), ozone(O3), Sulphur dioxide (SO2), and nitrogen oxides (NO2) resulting in respiratory issues, exacerbation of conditions like asthma, and heightened risks of lung diseases. ...
Air pollution has become a significant global issue, with India ranking 8th in the world for hazardous air quality based on the latest 2022 report. (World Air Quality Report 2023). The growing urban sprawl and human-induced environmental activities have led to a decline in air quality. The Air Quality Index assesses the level of pollution in the air at a particular region. It is a fundamental right for individuals to be informed about the quality of the air they breathe for their well-being. This study aims to examine air pollution levels and trends across various geographical locations in India using data provided by the Central Pollution Control Board under the Ministry of Environment, Forest, and Climate Change in India. The study focuses on analyzing the annual growth of pollutants such as SO2, NO2, PM10, and PM2.5 from 2016 to 2021, collected from monitoring stations in 28 states across 256 locations. The research evaluates the impact of different particulate matter concentrations and showcases the spatial variation of air pollutants between 2016 and 2021. Results indicate a significant decrease in air pollution levels during lockdown periods compared to pre-lockdown periods. On an average (over all cities), more than 24% decrease has been observed for all the AQI of the pollutants. Additionally, a comparative analysis reveals correlations between meteorological factors and air quality, showing that temperature, relative humidity, and wind speed are negatively correlated with AQI, while surface pressure is positively correlated. Temporal analysis was also conducted to examine the relationship between air pollutant concentrations and meteorological parameters.
The aim of this study was to evaluate the impact of pandemic‐related lockdown on Turkey's air quality throughout time and space. For this purpose, statistical techniques were used to assess daily particulate matter (PM 10 ), sulfur dioxide (SO 2 ), nitrogen oxides and nitrogen dioxide (NO x and NO 2 ), ozone (O 3 ), and carbon monoxide (CO). The study's findings showed that, while the lockdown improved air quality in terms of air pollutant emissions, the most notable reduction was in NO 2 and NO x emissions. When comparing the months prior to the pandemic (November 2019 to January 2020) with the months during the pandemic (November 2020 to January 2021), the declines in NO 2 were 20%, 3%, and 0.5%, respectively. NO x emissions decreased by an average of 19% and 5% in November and December, respectively, and increased by an average of 16% in January during the pandemic. When the data for the 33 days of lockdown were compared to the data for the same 33 days the previous year, significant differences were determined at several Clean Air Centers, which were two for PM 10 , two for SO 2 , seven for NO x , four for NO 2 , two for CO, and three for O 3 , respectively. In this study, pollutant concentrations were found in the following ranges from November 2019 to January 2021: PM 10 : 3–208 µg m –3 , SO 2 : 1–56 µg m –3 , NO x : 6–600 µg m –3 , NO 2 : 4–155 µg m –3 , CO: 1–3921 µg m –3 , and O 3 : 2–119 µg m –3 . There were days that exceeded the limit values for PM 10 .
With the current COVID-19 pandemic being spread all over the world, lockdown measures are being implemented, making air pollution levels go down in several countries. In this context, the air quality changes in the highly populated and trafficked Brazilian states of São Paulo (SP) and Rio de Janeiro (RJ) were addressed using a combination of satellite and ground-based daily data analysis. We explored nitrogen dioxide (NO2) and fine particulate matter (PM2.5) daily levels for the month of May from 2015–2020. Daily measurements of NO2 column concentrations from the Ozone Monitoring Instrument (OMI) aboard NASA’s Aura satellite were analyzed and decreases of 42% and 49.6% were found for SP and RJ, respectively, during the year 2020 compared to the 2015–2019 average. Besides NO2 column retrievals, ground-based data measured by the Brazilian States Environmental Institutions were analyzed and correlated with satellite retrievals. Correlation coefficients between year-to-year changes in satellite column and ground-based concentrations were 77% and 53% in SP and RJ, respectively. Ground-based data showed 13.3% and 18.8% decrease in NO2 levels for SP and RJ, respectively, in 2020 compared to 2019. In SP, no significant change in PM2.5 was observed in 2020 compared to 2019. To further isolate the effect of emissions reduction due to the lockdown, meteorological data and number of wildfire hotspots were analyzed. NO2 concentrations showed negative and positive correlations with wind speed and temperature, respectively. PM2.5 concentration distributions suggested an influence by the wildfires in the southeast region of the country. Synergistic analyses of satellite retrievals, surface level concentrations, and weather data provide a more complete picture of changes to pollutant levels.
One of the consequences of the COVID-19 lockdowns has been the modification of the air quality in many cities around the world. This study focuses on the variations in pollutant concentrations and how important meteorological conditions were for those variations in Barcelona and the surrounding area during the 2020 lockdown. Boundary-layer height, wind speed, and precipitation were compared between mid-March and April 2016–2019 (pre-lockdown) and the same period in 2020 (during lockdown). The results show the limited influence of meteorological factors on horizontal and vertical dispersion conditions. Compared with the pre-lockdown period, during lockdown the boundary-layer height slightly increased by between 5% and 9%, mean wind speed was very similar, and the fraction of days with rainfall increased only marginally, from 0.33 to 0.34, even though April 2020 was extremely wet in the study area. Variations in nitrogen dioxide ( $$\hbox {NO}_{{2}}$$ NO 2 ), particulate matter with a diameter less than 10 $${\mu }$$ μ m (PM10), and ozone ( $$\hbox {O}_{{3}}$$ O 3 ) concentrations over a 10-year period showed a 66% reduction in $$\hbox {NO}_{{2}}$$ NO 2 , 37% reduction in PM10, and 27% increase in $$\hbox {O}_{{3}}$$ O 3 at a traffic station in Barcelona. The differences in the daily concentration cycle between weekends and weekdays were heavily smoothed for all pollutants considered. The afternoon $$\hbox {NO}_{{2}}$$ NO 2 peak at the traffic station was suppressed compared with the average daily cycle. The analysis of ozone was extended to the regional scale, revealing lower concentrations at rural sites and higher ones in urban zones, especially in Barcelona and the surrounding area. The results presented not only complement previous air quality COVID-19 lockdown studies but also provide insights into the effects of road-traffic reduction.
Rapid industrialization and urbanization along with a growing population are contributing significantly to air pollution in China. Evaluation of long-term aerosol optical depth (AOD) data from models and reanalysis, can greatly promote understanding of spatiotemporal variations in air pollution in China. To do this, AOD (550 nm) values from 2000 to 2014 were obtained from the Coupled Model Inter-comparison Project (CIMP6), the second version of Modern-Era Retrospective analysis for Research, and Applications (MERRA-2), and the Moderate Resolution Imaging Spectroradiometer (MODIS; flying on the Terra satellite) combined Dark Target and Deep Blue (DTB) aerosol product. We used the Terra-MODIS DTB AOD (hereafter MODIS DTB AOD) as a standard to evaluate CMIP6 Ensemble AOD (hereafter CMIP6 AOD) and MERRA-2 reanalysis AOD (hereafter MERRA-2 AOD). Results show better correlations and smaller errors between MERRA-2 and MODIS DTB AOD, than between CMIP6 and MODIS DTB AOD, in most regions of China, at both annual and seasonal scales. However, significant under- and over-estimations in the MERRA-2 and CMIP6 AOD were also observed relative to MODIS DTB AOD. The long-term (2000–2014) MODIS DTB AOD distributions show the highest AOD over the North China Plain (0.71) followed by Central China (0.69), Yangtse River Delta (0.67), Sichuan Basin (0.64), and Pearl River Delta (0.54) regions. The lowest AOD values were recorded over the Tibetan Plateau (0.13 ± 0.01) followed by Qinghai (0.19 ± 0.03) and the Gobi Desert (0.21 ± 0.03). Large amounts of sand and dust particles emitted from natural sources (the Taklamakan and Gobi Deserts) may result in higher AOD in spring compared to summer, autumn, and winter. Trends were also calculated for 2000−2005, for 2006−2010 (when China introduced strict air pollution control policies during the 11th Five Year Plan or FYP), and for 2011−2014 (during the 12th FYP). An increasing trend in MODIS DTB AOD was observed throughout the country during 2000−2014. The uncontrolled industrialization, urbanization, and rapid economic development that mostly occurred from 2000 to 2005 probably contributed to the overall increase in AOD. Finally, China's air pollution control policies helped to reduce AOD in most regions of the country; this was more evident during the 12th FYP period (2011−2014) than during the 11th FYP period (2006−2010). Therefore this study strongly advises the authority to retain or extend these policies in the future for improving air quality.
Intensive measurements were conducted in Xi’an, China before and during a COVID-19 lockdown period to investigate how changes in anthropogenic emissions affected the optical properties and radiative effects of brown carbon (BrC) aerosol. The contribution of BrC to total aerosol light absorption during the lockdown (13%–49%) was higher compared with the normal period (4%–29%). Mass absorption cross-sections (MAC) of specific organic aerosol (OA) factors were calculated from a ridge regression model. Of the primary OA (POA), coal combustion OA (CCOA) had the largest MACs at all tested wavelengths during both periods due to high molecular-weight BrC chromophores; that was followed by biomass burning OA (BBOA) and hydrocarbon-like OA (HOA). For secondary OA (SOA), the MACs of the less-oxidized oxygenated OA (OOA) species (LO-OOA) at λ = 370–590 nm were higher than those of more-oxidized OOA (MO-OOA) during both periods, presumably due to chromophore bleaching. The largest contributor to BrC absorption at the short wavelengths was CCOA during both periods, but BrC absorption by LO-OOA and MO-OOA became dominant at longer wavelengths during the lockdown. The estimated radiation forcing efficiency of BrC over 370–600 nm increased from 37.5 W· g⁻¹ during the normal period to 50.2 W·g⁻¹ during the lockdown, and that enhancement was mainly caused by higher MACs for both LO-OOA and MO-OOA. This study provides insights into the optical properties and radiative effects of source-specific BrC aerosol when pollution emissions are reduced.
The coronavirus has a high basic reproduction number (R0) and has caused the global COVID-19 pandemic. Governments are implementing lockdowns that are leading to economic fallout in many countries. Policy makers can take better decisions if provided with the indicators connected with the disease spread. This study is aimed to cluster the countries using social, economic, health and environmental related metrics affecting the disease spread so as to implement the policies to control the widespread of disease. Thus, countries with similar factors can take proactive steps to fight against the pandemic. The data is acquired for 79 countries and 18 different feature variables (the factors that are associated with COVID-19 spread) are selected. Pearson Product Moment Correlation Analysis is performed between all the feature variables with cumulative death cases and cumulative confirmed cases individually to get an insight of relation of these factors with the spread of COVID-19. Unsupervised k-means algorithm is used and the feature set includes economic, environmental indicators and disease prevalence along with COVID-19 variables. The learning model is able to group the countries into 4 clusters on the basis of relation with all 18 feature variables. We also present an analysis of correlation between the selected feature variables, and COVID-19 confirmed cases and deaths. Prevalence of underlying diseases shows strong correlation with COVID-19 whereas environmental health indicators are weakly correlated with COVID-19.
The lockdown period (March–May 2020) during the COVID‐19 pandemic in Europe led to a reduction in the anthropogenic emissions of primary pollutants. For three‐quarters of over 1,100 available monitoring stations, the average nitrogen dioxide (NO2) concentrations decreased by at least 2.7 μg·m−3 (or 25%) compared with the average concentrations recorded during the same period of the previous seven years. This reduction was not specific to urban or rural areas because the relative reduction was of similar magnitude in both areas. The ozone (O3) response differed spatially, with positive anomalies in Northern Europe and negative anomalies in Southwestern Europe. Reduced cloudiness and related enhanced radiation in Northern Europe played a significant role in the increase of surface O3 concentrations by shifting the photochemical partitioning between NO2 and O3 toward more O3. The level of total oxidant (Ox = O3 + NO2) remained unchanged, except in Southwestern Europe where it decreased. Several episodes lasting a few days of a high level of total oxidants were observed in Northern Europe. The results illustrate the complexity of the atmospheric response to the unprecedented reduction in the emission of primary pollutants. Anomalies of (a) nitrogen dioxide (NO2) mean concentration and (b) ozone (O3) mean concentration at European Air Quality e‐Reporting database (AirBase) stations in 2020 compared with the previous seven years (2013–2019) for the period March 18–May 18, 2020. Dots are coloured according to the anomalies in concentration (μg·m−3) and sized proportionally to the relative change (%). Black dots correspond to stations with < 30% of available data.
The preventive and cautionary measures taken by the UAE and Abu Dhabi governments to reduce the spread of the coronavirus disease (COVID-19) and promote social distancing have led to a reduction of mobility and a modification of economic and social activities. This paper provides statistical analysis of the air quality data monitored by the Environment Agency - Abu Dhabi (EAD) during the first 10 months of 2020, comparing the different stages of the preventive measures. Ground monitoring data is compared with satellite images and mobility indicators. The study shows a drastic decrease during lockdown in the concentration of the gaseous pollutants analysed (NO2, SO2, CO, and C6H6) that aligns with the results reported in other international cities and metropolitan areas. However, particulate matter (PM10 and PM2.5) averaged concentrations followed a markedly different trend from the gaseous pollutants, indicating a larger influence from natural events (sand and dust storms) and other anthropogenic sources. The ozone (O3) levels increased during the lockdown, showing the complexity of O3 formation. The end of lockdown led to an increase of the mobility and the air pollution; however, air pollutant concentrations remained in lower levels than during the same period of 2019. The results in this study show the large impact of human activities on the quality of air and present an opportunity for policymakers and decision-makers to design stimulus packages to overcome the economic slow-down, with strategies to accelerate the transition to resilient, low-emission economies and societies more connected to the nature that protect human health and the environment.
Supplementary information:
The online version contains supplementary material available at 10.1007/s11869-021-01000-2.
We offer and overview of the COVID-19 -driven air quality changes across 11 metropolises in Spain with the focus on lessons learned on how continuing abating pollution. Traffic flow decreased by up to 80% during the lockdown and remained relatively low during the full relaxation (June and July). After the lockdown a significant shift from public transport to private vehicles (+21% in Barcelona) persisted due to fair to infection, which need to be reverted as soon as possible. NO2 levels fell below 50% of the WHO annual air quality guidelines (WHOAQGs), but PM2.5 were reduced less than expected due to its lower contributions from traffic, increased contributions from agricultural and domestic biomass burning, or large secondary aerosol contributions. Even during the lockdown, the annual PM2.5 WHOAQG was exceeded in cities within the NE and E regions with high NH3 emissions from farming and agriculture. Decreases in PM10 levels were greater than in PM2.5 due to reduced emissions from road dust, vehicle wear, and construction/demolition activities. Averaged O3 daily maximum 8-hours (8hDM) experienced a generalized decrease in the rural receptor sites in the relaxation (June-July) with -20% reduced mobility. For urban areas O3 8hDM responses were heterogeneous, with increases or decreases depending on the period and location. Thus, after cancelling out the effect of meteorology, 5 out of 11 cities experienced O3 decreases during the lockdown, while the remaining 6 either did not experience relevant reductions or increased. During the relaxation period and coinciding with the growing O3 season (June-July), most cities experienced decreases. However, the O3 WHOAQG was still exceeded during the lockdown and full relaxation periods in several cities For secondary pollutants such as O3, further chemical and dispersion modeling along with source apportionment techniques to identify major precursor reduction targets are required to evaluate the O3 abatement potential.
Clean air is a fundamental necessity for human health and well-being. Anthropogenic emissions that are harmful to human health have been reduced substantially under COVID-19 lockdown. Satellite remote sensing for air pollution assessments can be highly effective in public health research because of the possibility of estimating air pollution levels over large scales. In this study, we utilized both satellite and surface measurements to estimate air pollution levels in 20 cities across the world. Google Earth Engine (GEE) and Sentinel-5 Precursor TROPOspheric Monitoring Instrument (TROPOMI) application were used for both spatial and time-series assessment of tropospheric Nitrogen Dioxide (NO2) and Carbon Monoxide (CO) statuses during the study period (1 February to 11 May 2019 and the corresponding period in 2020). We also measured Population-Weighted Average Concentration (PWAC) of particulate matter (PM2.5 and PM10) and NO2 using gridded population data and in-situ air pollution estimates. We estimated the economic benefit of reduced anthropogenic emissions using two valuation approaches: (1) the median externality value coefficient approach, applied for satellite data, and (2) the public health burden approach, applied for in-situ data. Satellite data have shown that ∼ 28 tons (sum of 20 cities) of NO2 and ∼ 184 tons (sum of 20 cities) of CO have been reduced during the study period. PM2.5, PM10, and NO2 are reduced by ∼37 (μg/m3), 62 (μg/m3), and 145 (μg/m3), respectively. A total of ∼1310, ∼401, and ∼430 premature cause-specific deaths were estimated to be avoided with the reduction of NO2, PM2.5, and PM10. The total economic benefits (Billion US$) (sum of 20 cities) of the avoided mortality are measured as ∼10, ∼3.1, and ∼3.3 for NO2, PM2.5, and PM10, respectively. In many cases, ground monitored data was found inadequate for detail spatial assessment. This problem can be better addressed by incorporating satellite data into the evaluation if proper quality assurance is achieved, and the data processing burden can be alleviated or even removed. Both satellite and ground-based estimates suggest the positive effect of the limited human interference on natural environments. Further research in this direction is needed to explore this synergistic association more explicitly.
Meteorology and long-term trends in air pollutant concentrations may obscure the results from short-term policies implemented to improve air quality. This study presents changes in CO, NO2, O3, SO2, PM10, and PM2.5 based on their anomalies during the COVID-19 partial (Phase 2) and total (Phase 3) lockdowns in Mexico City (MCMA). To minimise the impact of the air pollutant long-term trends, pollutant anomalies were calculated using as baseline truncated Fourier series, fitted with data from 2016 to 2019, and then compared with those from the lockdown. Additionally, days with stagnant conditions and heavy rain were excluded to reduce the impact of extreme weather changes. Satellite observations for NO2 and CO were used to contrast the ground-based derived results. During the lockdown Phase 2, only NO2 exhibited significant decreases (p < 0.05) of between 10 and 23% due to reductions in motor vehicle emissions. By contrast, O3 increased (p < 0.05) between 16 and 40% at the same sites where NO2 decreased. During Phase 3, significant decreases (p < 0.05) were observed for NO2 (43%), PM10 (20%), and PM2.5 (32%) in response to the total lockdown. Although O3 concentrations were lower in Phase 3 than during Phase 2, those did not decrease (p < 0.05) from the baseline at any site despite the total lockdown. SO2 decreased only during Phase 3 in a near-road environment. Satellite observations confirmed that NO2 decreased and CO stabilised during the total lockdown. Air pollutant changes during the lockdown could be overestimated between 2 and 10-fold without accounting for the influences of meteorology and long-term trends in pollutant concentrations. Air quality improved significantly during the lockdown driven by reduced NO2 and PM2.5 emissions despite increases in O3, resulting in health benefits for the MCMA population. A health assessment conducted suggested that around 588 deaths related to air pollution exposure were averted during the lockdown. Our results show that to reduce O3 within the MCMA, policies must focus on reducing VOCs emissions from non-mobile sources. The measures implemented during the COVID-19 lockdowns provide valuable information to reduce air pollution through a range of abatement strategies for emissions other than from motor vehicles.
Daily Google mobility data covering 130 countries over the period between February 15, 2020 and May 2, 2020 suggest that less mobility is associated with lower COVID-19 cases and deaths. This observation is formally tested by using a difference-in-difference design, where country-fixed effects, day-fixed effects, as well as the country-specific timing of the 100th COVID-19 case are controlled for. The results suggest that 1% of a weekly increase in being at residential places leads to about 70 less weekly COVID-19 cases and about 7 less weekly COVID-19 deaths, whereas 1% of a weekly decrease in visits to transit stations leads to about 33 less weekly COVID-19 cases and about 4 less weekly COVID-19 deaths, on average across countries. Similarly, 1% of a weekly reduction in visits to retail & recreation results in about 25 less weekly COVID-19 cases and about 3 less weekly COVID-19 deaths, or 1% of a weekly reduction in visits to workplaces results in about 18 less weekly COVID-19 cases and about 2 less weekly COVID-19 deaths.
The 2019 pandemic of Severe Acute Respiratory Syndrome-Corona Virus Diseases (COVID-19) has posed a substantial threat to public health and major global economic losses. The Northern Emirates of the United Arab Emirates (NEUAE) had imposed intense preventive lockdown measures. On the first of April 2020, a lockdown was implemented. It was assumed, due to lower emissions, that the air quality and Surface Urban Heat Island Intensity (SUHII) had been strengthened significantly. In this research, three parameters for Nitrogen Dioxide (NO2), Aerosol Optical Depth (AOD), and SUHII variables were examined through the NEUAE. we evaluated the percentage of the change in these parameters as revealed by satellite data for two cycles in 2019 (March 1st to June 30th) and 2020 (March 1st to June 30th). The core results showed that during lockdown periods, the average of NO2, AOD, and SUHII levels declined by 23.7%, 3.7%, and 19.2%, respectively, compared to the same period in 2019. Validation for results demonstrates a high agreement between the predicted and measured values. The agreement was as high as R2=0.7, R2=0.6, and R2=0.68 for NO2, AOD, and night LST, respectively, indicating significant positive linear correlations. The current study concludes that due to declining automobile and industrial emissions in the NEUAE, the lockdown initiatives substantially lowered NO2, AOD, and SUHII. In addition, the aerosols did not alter significantly since they are often linked to the natural occurrence of dust storms throughout this time of the year. The pandemic is likely to influence several policy decisions to introduce strategies to control air pollution and SUHII. Lockdown experiences may theoretically play a key role in the future as a possible solution for air pollution and SUHII abatement.
This study leverages satellite remote sensing to investigate the impact of the coronavirus outbreak and the resulting lockdown of public venues on air pollution levels in East Asia. We analyze data from the Sentinel-5P and the Himawari-8 satellites to examine concentrations of NO2, HCHO, SO2, and CO, and the aerosol optical depth (AOD) over the BTH, Wuhan, Seoul, and Tokyo regions in February 2019 and February 2020. Results show that most of the concentrations of pollutants are lower than those of February 2019. Compared to other pollutants, NO2 experienced the most significant reductions by almost 54%, 83%, 33%, and 19% decrease in BTH, Wuhan, Seoul, and Tokyo, respectively. The greatest reductions in pollutants occurred in Wuhan, with a decrease of almost 83%, 11%, 71%, and 4% in the column densities of NO2, HCHO, SO2, and CO, respectively, and a decrease of about 62% in the AOD. Although NO2, CO, and formaldehyde concentrations decreased in the Seoul and Tokyo metropolitan areas compared to the previous year, concentrations of SO2 showed an increase in these two regions due to the effect of transport from polluted upwind regions. We also show that meteorological factors were not the main reason for the dramatic reductions of pollutants in the atmosphere. Moreover, an investigation of the HCHO/NO2 ratio shows that in many regions of East China, particularly in Wuhan, ozone production in February 2020 is less NOX saturated during the daytime than it was in February 2019. With large reductions in the concentrations of NO2 during lockdown situations, we find that significant increases in surface ozone in East China from February 2019 to February 2020 are likely the result of less reaction of NO and O3 caused by significantly reduced NOX concentrations and less NOX saturation in East China during the daytime.
On-road traffic is the primary source of air pollutants in Cuenca (2500 m. a.s.l.), an Andean city in Ecuador. Most of the buses in the country run on diesel, emitting high amounts of NO x (NO + NO 2) and PM 2.5 , among other air pollutants. Currently, an electric tram system is beginning to operate in this city, accompanied by new routes for urban buses, changing the spatial distribution of the city's emissions, and alleviating the impact in the historic center. The Ecuadorian energy efficiency law requires that all vehicles incorporated into the public transportation system must be electric by 2025. As an early and preliminary assessment of the impact of this shift, we simulated the air quality during two scenarios: (1) A reference scenario corresponding to buses running on diesel (DB) and (2) the future scenario with electric buses (EB). We used the Eulerian Weather Research and Forecasting with Chemistry (WRF-Chem) model for simulating the air quality during September, based on the last available emission inventory (year 2014). The difference in the results of the two scenarios (DB-EB) showed decreases in the daily maximum hourly NO 2 (between 0.8 to 16.4 µg m −3 , median 7.1 µg m −3), and in the 24-h mean PM 2.5 (0.2 to 1.8 µg m −3 , median 0.9 µg m −3) concentrations. However, the daily maximum 8-h mean ozone (O 3) increased (1.1 to 8.0 µg m −3 , median 3.5 µg m −3). Apart from the primary air quality benefits acquired due to decreases in NO 2 and PM 2.5 levels, and owing to the volatile organic compounds (VOC)-limited regime for O 3 production in this city, modeling suggests that VOC controls should accompany future NO x reduction for avoiding increases in O 3. Modeled tendencies of these pollutants when moving from the DB to EB scenario were consistent with the tendencies observed during the COVID-19 lockdown in this city, which is a unique reference for appreciating the potentiality and identifying insights for air quality improvements. This consistency supports the approach and results of this contribution, which provides early insights into the effects on air quality due to the recent operability of the electric tram and the future shift from diesel to electric buses in Cuenca.
The global response to the COVID-19 pandemic has led to a sudden reduction of both GHG emissions and air pollutants. Here, using national mobility data, we estimate global emission reductions for ten species during the period February to June 2020. We estimate that global NOx emissions declined by as much as 30% in April, contributing a short-term cooling since the start of the year. This cooling trend is offset by ~20% reduction in global SO2 emissions that weakens the aerosol cooling effect, causing short-term warming. As a result, we estimate that the direct effect of the pandemic-driven response will be negligible, with a cooling of around 0.01 ± 0.005 °C by 2030 compared to a baseline scenario that follows current national policies. In contrast, with an economic recovery tilted towards green stimulus and reductions in fossil fuel investments, it is possible to avoid future warming of 0.3 °C by 2050. Reduced GHG and air pollutant emissions during the COVID-19 lockdowns resulted in declines in NOx emissions of up to 30%, causing short-term cooling, while ~20% SO2 emissions decline countered this for overall minimal temperature effect.
Shortly after the outbreak of the novel infectious disease (COVID-19) started at the end of 2019, it turned into a global pandemic, which caused the lockdown of many countries across the world. Various strict measures were adopted to reduce anthropogenic activities in order to prevent further spread and infection of the disease. In this study, we utilized continental scale remotely sensed data along with city scale in situ air quality observations for 2020 as well as data from the baseline period (2015-2019) to provide an early insight on air pollution changes in response to the COVID-19 pandemic lockdown, by combining both continental and city scales. For the continental scale analysis, data of NO2, SO2, and O3 were acquired from the ozone monitoring instrument (OMI) and data of aerosol optical depth (AOD) were collected from the moderate resolution imaging spectroradiometer (MODIS). For city scale analysis, data of NO2, CO, PM2.5, O3, and SO2 were derived from ground-based air quality observations. Results from satellite observations at the continental scale showed that concentrations of NO2, SO2, and AOD substantially dropped in 2020 during the lockdown period compared to their averages for the baseline period over all continents, with a maximum reduction of ~33% for NO2 in East Asia, ~41% for SO2 in East Asia, and ~37% for AOD in South Asia. In the case of O3, the maximum overall reduction was observed as ~11% in Europe, followed by ~10% in North America, while a slight increase was found in other study regions. These findings align with ground-based air quality observations, which showed that pollutants such as NO2, CO, PM2.5, and SO2 during the 2020 lockdown period decreased significantly except that O3 had varying patterns in different cities. Specifically, a maximum reduction of ~49% in NO2 was found in London, ~43% in CO in Wuhan, ~38% in PM2.5 in Chennai, and ~48% in SO2 in Beijing. In the case of urban O3, a maximum reduction of ~43% was found in Wuhan, but a significant increase of ~47% was observed in Chennai. It is obvious that restricted human activities during the lockdown have reduced the anthropogenic emissions and subsequently improved air quality, especially across the metropolitan cities.
Many governments around the world have enforced quarantine policies to control the spread of the new coronavirus (SARS-CoV-2). These policies have had positive and negative effects on the environment. For example, the concentrations of certain harmful pollutants have decreased in some countries. In contrast, the concentrations of other pollutants have increased. This research analyzes the effect of quarantine policies on air quality in Quito, Ecuador. Using a parametric approach, it was found that NO2 and PM2.5 concentrations have decreased significantly since the establishment of lockdown measures. However, O3 concentrations have increased considerably in 2020.
Lockdown seems the most effective way to prevent the spread of Coronavirus disease (COVID-13 19) as no vaccine is currently available in the market to cure it. Thus, India has enforced nation-14 wide lockdown from 25 th March to lower the spread of this contagious virus and associated 15 illness. This study aims to quantify the changes in pollution levels as well as meteorology 16 during the 6-weeks COVID-19 lockdown over 17 cities of India for 5 major criteria pollutants 17 using publicly available air quality data. Hourly averaged data is accessed from the air quality 18 monitoring stations during the lockdown and immediate pre-lockdown periods and also 19 corresponding data from the previous year (2019). During the lockdown, PM2.5, PM10, NO2, 20 and CO reduced significantly with relatively small changes in meteorological conditions 21 compared to the pre-lockdown period. The highest decline is observed over Ahmedabad (68%), 22 Delhi (71%), Bangalore (87%), and Nagpur (63%) for PM2.5, PM10, NO2, and CO, respectively. 23 The Northern region shows the highest decline for all the pollutants with most days below 24 NAAQS during lockdown-86%, 68%, and 100% compared to 18%, 0%, and 38% in 2019 for 25 PM2.5, PM10, and NO2, respectively. The smaller cities Dewas and Jorapokhar show lesser 26 improvement with only 3% and 16% improvement in days under NAAQS for PM2.5. SO2 is the 27 least affected pollutant with little improvement. The major decline is observed during 7-10am 28 and 7-10pm hours of the day for PM2.5, PM10, NO2, and CO with more than 40% reduction. 29 The meteorological changes are very small and heterogeneous over India showing a similar 30 extent of changes compared to the previous year but the pollution levels have reduced 31 significantly. Thus, the sharp decline in pollutant concentration during the ~6 weeks period 32 national lockdown can be attributed to the reduced economic and transport activities. 33
A novel infectious coronavirus disease (COVID-19) identified in late 2019 has now been labelled as a global pandemic by World Health Organization (WHO). The COVID-19 outbreak has shown some positive impacts on the natural environment. In present work, India is taken as a case study to evaluate the effect of lockdown on air quality of three Indian cities. The variation in concentration of key air pollutants including PM10, PM2.5, NO2, SO2 and O3 during two phases, pre-lockdown and post-lockdown phases, was analysed. The concentration of PM10, PM2.5, NO2 and SO2 reduced by 55%, 49%, 60% and 19%, and 44%, 37%, 78% and 39% for Delhi and Mumbai, respectively, during post-lockdown phase. Overall, the findings in present study may provide confidence to the stakeholders involved in air quality policy development that a significant improvement in air quality can be achieved in future if better pollution control plans are strictly executed.
In December 2019, the outbreak of viral disease labeled as Novel Coronavirus started in Wuhan, China, which later came to be known as Covid-19. The disease has spread in almost every part of the world and has been declared a global pandemic in March 2020 by World Health Organization (WHO). The corona virus outbreak has emerged as one of the deadliest pandemics of all time in human history. The ongoing pandemic of COVID-19 has forced several countries of the world to observe complete lockdown forcing people to live in their homes. India also faced the phase of total lockdown for 21 days (in first phase) to avoid the spread of coronavirus to the maximum possible extent. This lockdown impacted the pollution levels of environment and improved air and water quality in the short span owing to very less human activities. The present work scientifically analyzed the available data for primary air pollutants (PM2.5, NO2, SO2 and CO) from two major Indian cities, Lucknow and New Delhi. The analysis was based on air quality data for before lockdown and after lockdown (first phase of 21 days) periods of 21 days each. The results showed significant decline in the studied air pollution indices and demonstrated improvement of air quality in both the cities. The major impact was seen in the levels of PM2.5, NO2 and CO. The levels of SO2 showed less significant decline during the lockdown period. The results are presented with future perspectives to mitigate air pollution in near future by adopting the short and periodical lockdown as a tool.
The outbreak of coronavirus disease (COVID-19) was first reported from Wuhan, China, on December 31st, 2019. As the number of coronavirus infections has exceeded 100,000 with toll deaths of about 5000 worldwide as of early March, 2020, scientists and researchers are racing to investigate the nature of this virus and evaluate the short and long term effects of this disease. Despite its negative impacts that obliged the World Health Organization to declare COVID-19 epidemic as a Public Health Emergency of International Concern, the rate of mortality of this infection has not exceeded 3.4% globally. On the other hand, the mortality rate caused by ambient air pollution has contributed to 7.6% of all deaths in 2016 worldwide. The outbreak of COVID-19 has forced China to lockdown its industrial activities and hence dropped its NO2 and carbon emissions by 30 and 25%, respectively. This work reports on the first case study that compares the air quality status before and after the crisis. It sheds light on the facts related to the demographics of deaths by gender, age and health status before infection. The historical data on air quality, estimates of annual deaths and its economic burden have been presented and analyzed. The actual daily deaths due to COVID-19 have been obtained from the official records of the daily Situation Reports published by World Health Organization as of March 11th. The rate of mortality due to COVID-19 was impacted by two factors: age and health status. Results show that 75% of deaths were related to cases that had underlying present diseases with the majority aged of 80+ years. The reported figures were compared with the average daily mortality due to poor air quality which reached up to 3287 deaths due to high levels of NO2, O3 and PM. The air quality status before the crisis was compared with the current situation showing that COVID-19 forced-industrial and anthropogenic activities lockdown may have saved more lives by preventing ambient air pollution than by preventing infection.
The novel corona outbreak that started in Wuhan China in Autumn 2019, has infected and killed hundreds of thousands of people all over the world. People around the world are scared because a vaccine has not yet been developed to cure this disease. Scientists and health experts around the world are working hard to develop medical countermeasures to control the spread of the COVID 19 outbreak. COVID-19 pandemic created an unprecedented world crisis to our health and changed the way we perceived our world and our everyday lives. To be able to contain the pattern of transmission of this deadly virus, health experts suggests to each one of us to observe the required safety measures such as social distancing and washing our hands with soap and water in a regular basis and observe a proper hygiene. The role of different mass media channels skyrocketing in our lives on different levels. During this time of the pandemic, mass media have been highly recognized as strongest forces in promoting solidarity to people around the world. It has been followed by an increasing volume of research closed to the footsteps of technological transformations intended to map mass media strongest impacts on how we perceived ourselves during this time of the pandemic. Why lockdown and social distancing amid corona virus? When will this outbreak end? What does flattening the curve mean in relation to Corona Virus? This paper discusses the significance of social distancing, lockdown and flattening the curve as countermeasures in order to win the fight against COVID 19. Meanwhile, other interventions and prevention measures such as, lockdown, community quarantine and social distancing are all the necessary interventions and prevention measures that governments all over the world are urging their citizens to do in order to delay and prevent the spread as well as to flatten the curve against COVID-19.
The Severe Acute Respiratory Syndrome-Coronavirus Disease 2019 (COVID-19) pandemic caused by a novel coronavirus known as SARS-CoV-2 has caused tremendous suffering and huge economic losses. We hypothesized that extreme measures of partial-to-total shutdown might have influenced the quality of the global environment because of decreased emissions of atmospheric pollutants. We tested this hypothesis using satellite imagery, climatic datasets (temperature, and absolute humidity), and COVID-19 cases available in the public domain. While the majority of the cases were recorded from Western countries, where mortality rates were strongly positively correlated with age, the number of cases in tropical regions was relatively lower than European and North American regions, possibly attributed to faster human-to-human transmission. There was a substantial reduction in the level of nitrogen dioxide (NO2: 0.00002 mol m⁻²), a low reduction in CO (<0.03 mol m⁻²), and a low-to-moderate reduction in Aerosol Optical Depth (AOD: ~0.1–0.2) in the major hotspots of COVID-19 outbreak during February–March 2020, which may be attributed to the mass lockdowns. Our study projects an increasing coverage of high COVID-19 hazard at absolute humidity levels ranging from 4 to 9 g m⁻³ across a large part of the globe during April–July 2020 due to a high prospective meteorological suitability for COVID-19 spread. Our findings suggest that there is ample scope for restoring the global environment from the ill-effects of anthropogenic activities through temporary shutdown measures.
The rapid pace of economic growth and urbanization in China affects both large and small cities of the country, causing an increase of pollutant concentrations in the air. The South Gobi is one of the main deserts and semidesert regions of the country; therefore, the study of air pollution near the potential source of natural aerosols is of great importance. Data obtained in the period from 1 January 2016 to 31 December 2019 was used to analyze spatial-temporal characteristics of atmospheric pollutants (PM2.5, PM10, SO2, NO2, and CO) in eight cities. Total mean concentrations of PM2.5 and PM10 were 36.1 ± 21.1 μg/m3 and 98.6 ± 108.7 μg/m3. The occurrence rates of concentrations exceeding the Chinese National Ambient Air Quality Standard (CNAAQS) grade 1 and grade 2 were 40.1% and 5.4% for PM2.5 and 82.9% and 11.64% for PM10 in the region. Total concentrations of SO2, NO2, and CO did not exceed the CNAAQS standard and were 20.8 ± 23.6 μg/m3, 22.6 ± 11.9 μg/m3, and 0.72 ± 0.39 mg/m3, respectively. The PM2.5 to PM10 ratio increased from 0.35 in spring to 0.46 in winter suggesting the predominance of coarse aerosol fractions in the atmosphere. Based on data on aerosol optical depth (AOD) and Ångström exponent (AE) ratio obtained from Moderate Resolution Imaging Spectroradiometer (MODIS), the predominant aerosol types in the region are Clean Сontinental and Mixed. Maximum concentrations of pollutants and the highest AOD values in the region air are observed in spring and winter. Results set forth in this article will be an important basis for further regional studies on air quality and distribution of sources.
In December 2019, the world was disrupted by the news of a new strain of virus known as Novel Corona virus, taking lives of many in China. Wuhan, the capital of Central China's Hubei province is said to be the place where the outbreak started. The city went on a lockdown as the disease spread rapidly. After the lockdown, most countries like India and Bangladesh airlifted their citizens who were studying in Wuhan. Similarly, Nepal also has many youth studying medicine in Wuhan. Pleas for help from the students reached the government. This was a first encounter of such experience for Nepal government. With the help of Health Emergency Organizing committee, Epidemiology and Disease Control Division, Nepal Army Hospital, Nepal Police Hospital, Waste Management team, Nepal Ambulance service, Tribhuwan Airport and Royal Airlines the government of Nepal planned, organized and successfully brought back all the 175 students on 15 the February, 2019 from Wuhan, China. The aim of the present article is to share the experience, the challenges faced and recommendations for future similar cases. Keywords: evacuation; Nepal; Novel Corona virus; Wuhan.
In late 2019, a novel infectious disease with human to human transmission (COVID-19) was identified in Wuhan China, which now has turned into a global pandemic. Countries all over the world have implemented some sort of lockdown to slow down its infection and mitigate it. Lockdown due to COVID-19 has drastic effects on social and economic fronts. However, this lockdown also have some positive effect on natural environment. Recent data released by NASA (National Aeronautics and Space Administration) and ESA (European Space Agency) indicates that pollution in some of the epicenters of COVID-19 such as Wuhan, Italy, Spain and USA etc. has reduced up to 30%. This study compiled the environmental data released by NASA and ESA before and after the coronavirus pandemic and discusses its impact on environmental quality.
A regional fully coupled meteorology–chemistry model, Weather Research and Forecasting model with Chemistry (WRF-Chem), was employed to study the seasonality of ozone (O3) pollution and its sources in both China and India. Observations and model results suggest that O3 in the North China Plain (NCP), Yangtze River Delta (YRD), Pearl River Delta (PRD), and India exhibit distinctive seasonal features, which are linked to the influence of summer monsoons. Through a factor separation approach, we examined the sensitivity of O3 to individual anthropogenic, biogenic, and biomass burning emissions. We found that summer O3 formation in China is more sensitive to industrial and biogenic sources than to other source sectors, while the transportation and biogenic sources are more important in all seasons for India. Tagged simulations suggest that local sources play an important role in the formation of the summer O3 peak in the NCP, but sources from Northwest China should not be neglected to control summer O3 in the NCP. For the YRD region, prevailing winds and cleaner air from the ocean in summer lead to reduced transport from polluted regions, and the major source region in addition to local sources is Southeast China. For the PRD region, the upwind region is replaced by contributions from polluted PRD as autumn approaches, leading to an autumn peak. The major upwind regions in autumn for the PRD are YRD (11 %) and Southeast China (10 %). For India, sources in North India are more important than sources in the south. These analyses emphasize the relative importance of source sectors and regions as they change with seasons, providing important implications for O3 control strategies.
The pandemic COVID-19 brings with it the need for studies and tools to help those in charge make decisions. Working with classical time series methods such as ARIMA and SARIMA has shown promising results in the first studies of COVID-19. We advance in this branch by proposing a risk factor map induced by the well-known Pearson diagram based on multivariate kurtosis and skewness measures to analyze the dynamics of deaths from COVID-19. In particular, we combine bootstrap for time series with SARIMA modeling in a new paradigm to construct a map on which one can analyze the dynamics of a set of time series. The proposed map allows a risk analysis of multiple countries in the four different periods of the pandemic COVID-19 in 55 countries. Our empirical evidence suggests a direct relationship between the multivariate skewness and kurtosis. We observe that the multivariate kurtosis increase leads to the rise of the multivariate skewness. Our findings reveal that the countries with high risk from the behavior of the number of deaths tend to have pronounced skewness and kurtosis values.
Understanding the dynamics of cryptocurrency markets during financial crises such as the recent one caused by the COVID-19 pandemic is crucial for policy makers and investors. In this study, the effect of COVID-19 pandemic on the return-volatility and return-volume relationships for the ten most traded cryptocurrencies, namely Tether, Bitcoin, Ethereum, Ripple, Litecoin, Bitcoin Cash, EOS, Chainlink, Cardano, and Monero is examined. Further, the behavior of cryptocurrencies during COVID-19 pandemic is compared with less volatile markets such as Gold, WTI, and BRENT crude oil markets. To study the effect of volatility on cryptocurrency return, an EGARCH-M model is employed while for the return-volume relationships the VAR model and Granger causality tests are utilized. Results show that the return-volatility relationships for Tether, Ethereum, Ripple, Bitcoin Cash, EOS, and Monero are significant during COVID-19 pandemic, while the same relationship is not significant prior to the pandemic for any of the studied cryptocurrencies. Our findings of the return-volume relationship support the availability of causal relations from return to trading volume changes for Chainlink and Monero in the pre-COVID-19 period and for Ethereum, Ripple, Litecoin, EOS, and Cardano during the COVID-19 period. However, considering the absolute values of returns, we found a significant relationship from cryptocurrencies' absolute returns to trading volume changes for both the prior and during COVID-19 periods. From a managerial perspective, gold can be considered a suitable asset for portfolio hedging during the pandemic period and trading volume can help traders and investors identify the effect of momentum and potential trend in cryptocurrencies on their investments.
In this article, we are studying a Covid-19 mathematical model in the fractal-fractional sense of operators for the existence of solution, Hyers-Ulam (HU) stability and computational results. For the qualitative analysis, we convert the model to an equivalent integral form and investigate its qualitative analysis with the help of iterative convergent sequence and fixed point approach. For the computational aspect, we take help from the Lagrange’s interpolation and produce a numerical scheme for the fractal-fractional waterborne model. The scheme is then tested for a case study and we obtain interesting results.
Coronavirus disease 2019 (CoViD-19) is an infectious disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Among many symptoms, cough, fever and tiredness are the most common. People over 60 years old and with associated comorbidities are most likely to develop a worsening health condition. This paper proposes a non-integer order model to describe the dynamics of CoViD-19 in a standard population. The model incorporates the reinfection rate in the individuals recovered from the disease. Numerical simulations are performed for different values of the order of the fractional derivative and of reinfection rate. The results are discussed from a biological point of view.
The world is facing an unexpected, like never before, situation due to COVID-19. The measures to contain the COVID-19 pandemic are to incorporate lockdown, social distancing, disconnection, and home isolation. Lockdown was enforced by the various governments of the South Asian countries, which include non-working of all the businesses and assembling units, with limited access to the outer world pertaining to essential commodities. However, During the COVID-19 pandemic, an uncommon positive impact is noteworthy for worldwide abatement in air-contamination levels. Principally, specialists have estimated significant improvement in air quality and a remarkable decrease in concentration levels of various harmful gases like sulfur dioxide (SO2), nitrogen dioxide (NO2), carbon monoxide (CO), and ozone (O3). In this article, there is an analysis made on the impact of Covid-19 lockdown on the air quality of the South Asian region i.e. (that is) the various environmental parameters along with others namely aerosol, temperature, and particulate matter (PM2.5, PM10). The work includes the refining and analysis of crude information of this present (2020) and the past year of different toxic gases and parameters of air pollutants. These have been obtained from pollution control boards of respective South Asian nations alongside information and satellite pictures from the UN Environment Program and Space Administration for correlation of various parameters. It has been observed that there is a sharp dip in the pollutant concentration in South Asia. This examination altogether will be valuable data to environmentalists and experts to make the future policies for improving air quality and the environment.
Corona virus is highly uncertain and complex in space and time. Atmospheric parameters such as type of pollutants and local weather play an important role in COVID-19 cases and mortality. Many studies were carried out to understand the impact of weather on spread and severity of COVID-19 and vice-versa. A review study is conducted to understand the impact of weather and atmospheric pollution on morbidity and mortality.
Studies show that aerosols containing corona virus generated by sneezes and coughs are major route for spread of virus. Viability and virulence of SARS-CoV-2 stuck on the surface of particulate matter is not yet confirmed. Studies found that an increase in particulate matter concentration causes more COVID-19 cases and mortality. Gaseous pollutant and COVID-19 cases are positively correlated.
Local meteorology plays crucial role in the spread of corona virus and thus mortality. Decline in number of cases with rising temperature observed. Few studies also find that lowest and highest temperatures were related to lesser number of cases. Similarly humidity shows negative or no relationship with COVID-19 cases. Rainfall was not related whilst wind-speed plays positive role in spread of COVID-19. Solar radiation threats survival of virus, areas with lower solar radiation showed high exposure rate.
Air quality tremendously improved during lockdown. A significant reduction in PM10, PM2.5, BC, NOx, SO2, CO and VOCs concentration were observed. Lockdown had a healing effect on ozone; significant increase in its concentration was observed. Aerosols Optical Depths were found to decrease up to 50%.
Covid-19 was first reported in Iraq on February 24, 2020. Since then, to prevent its propagation, the Iraqi government declared a state of health emergency. A set of rapid and strict countermeasures have taken, including locking down cities and limiting population's mobility. In this study, concentrations of four criteria pollutants, NO2, O3, PM2.5 and PM10 before the lockdown from January 16 to February 29, 2020, and during four periods of partial and total lockdown from March 1 to July 24, 2020, in Baghdad were analysed. Overall, 6, 8 and 15% decreases in NO2, PM2.5, and PM10 concentrations, respectively in Baghdad during the 1st partial and total lockdown from March 1 to April 21, compared to the period before the lockdown. While, there were 13% increase in O3 for same period. During the 2nd partial lockdown from June 14 to July 24, NO2 and PM2.5 decreases 20 and 2.5%, respectively. While, there were 525 and 56% increase in O3 and PM10, respectively for same period. The air quality index (AQI) improved by 13% in Baghdad during the 1st partial lockdown from March 1 to April 21, compared to its pre-lockdown. The results of NO2 tropospheric column extracted from the Sentinel-5P satellite shown the NO2 emissions reduced up to 35 to 40% across Iraq, due to lockdown measures, between January and July 2020, especially across the major cities such as Baghdad, Basra and Erbil. The lockdown due to COVID-19 has drastic effects on social and economic aspects. However, the lockdown also has some positive effect on natural environment and air quality improvement.
Lockdown measures to contain COVID-19 pandemic has resulted in a considerable change in air pollution worldwide. We estimate the temporal and diurnal changes of the six criteria air pollutants, including particulate matter (PM2.5 and PM10) and gaseous pollutants (NO2, O3, CO, and SO2) during lockdown (25th March – 3rd MHA, 2020) across regions of India using the observations from 134 real-time monitoring sites of Central Pollution Control Board (CPCB). Significant reduction in PM2.5, PM10, NO2, and CO has been found in all the regions during the lockdown. SO2 showed mixed behavior, with a slight increase at some sites but a comparatively significant decrease at other locations. O3 also showed a mixed variation with a mild increase in IGP and a decrease in the South. The absolute decrease in PM2.5, PM10, and NO2 was observed during peak morning traffic hours (08-10 Hrs) and late evening (20-24 Hrs), but the percentage reduction is almost constant throughout the day. A significant decrease in day-time O3 has been found over Indo Gangetic plain (IGP) and central India, whereas night-time O3 has increased over IGP due to less O3 loss. The most significant reduction (∼40-60%) was found in PM2.5 and PM10. The highest decrease in PM was found for the north-west and IGP followed by South and central regions. A considerable reduction (∼30-70%) in NO2 was found except for a few sites in the central region. A similar pattern was observed for CO having a ∼20-40% reduction. The reduction observed for PM2.5, PM10, NO2, and enhancement in O3 was proportional to the population density. Delhi’s air quality has improved with a significant reduction in primary pollutants, however, an increase in O3 was observed. The changes reported during the lockdown are combined effect of changes in the emissions, meteorology, and atmospheric chemistry that requires detailed investigations.
The lockdown response to coronavirus disease 2019 (COVID-19) has caused an unprecedented reduction in global economic and transport activity. We test the hypothesis that this has reduced tropospheric and ground-level air pollution concentrations, using satellite data and a network of >10,000 air quality stations. After accounting for the effects of meteorological variability, we find declines in the population-weighted concentration of ground-level nitrogen dioxide (NO 2 : 60% with 95% CI 48 to 72%), and fine particulate matter (PM 2.5 : 31%; 95% CI: 17 to 45%), with marginal increases in ozone (O 3 : 4%; 95% CI: −2 to 10%) in 34 countries during lockdown dates up until 15 May. Except for ozone, satellite measurements of the troposphere indicate much smaller reductions, highlighting the spatial variability of pollutant anomalies attributable to complex NO x chemistry and long-distance transport of fine particulate matter with a diameter less than 2.5 µm (PM 2.5 ). By leveraging Google and Apple mobility data, we find empirical evidence for a link between global vehicle transportation declines and the reduction of ambient NO 2 exposure. While the state of global lockdown is not sustainable, these findings allude to the potential for mitigating public health risk by reducing “business as usual” air pollutant emissions from economic activities. Explore trends here: https://nina.earthengine.app/view/lockdown-pollution .
The Severe Acute Respiratory Syndrome-COronaVirus Diseases 2019 (SARS-COVID-19) pandemic has posed a serious threat to human health (death) and substantial economic losses across the globe. It was however presumed that extreme preventive measures of entire lockdown in India might have reduced the air pollution level and therefore decreased the aerosol optical depth (AOD). The Moderate Resolution Imaging Spectroradiometer (MODIS)-based Multi-angle Implementation of Atmospheric Correction (MAIAC) daily AOD product was deployed to investigate the change in AOD level during lockdown phases across the Indian Territory as compared to the long-term mean AOD level (2000–2019) of the same periods. The key findings of the study revealed that AOD level over the Indian Territory is greatly reduced (~45%) during the lockdown periods as compared to the long-term mean AOD level (2000–2019). Furthermore, a noteworthy negative AOD anomaly (~6 to 37%) was observed across the four metropolitan cities in India during the entire lockdown period (25th March to 15th May 2020). However, coal mining regions of the various coalfields in India showed a positive anomaly (~+11 to 40%) during the lockdown periods due to ongoing mining operations. In a nutshell, the study results indicated a huge drop in the AOD level over Indian Territory during lockdown periods. It is expected that the pandemic can influence some policy decisions to propose air pollution control methods. Lockdown events possibly may play a crucial role as a potential solution for air pollution abatement in the future. It may not be uncommon in future when the governments may implement deliberately selective lockdowns at pollution hotspots to control the pollution level.
The outbreak of COVID-19 disrupts the life of many people in the world. The state of Arizona in the U.S. emerges as one of the country's newest COVID-19 hot spots. Accurate forecasting for COVID-19 cases will help governments to implement necessary measures and convince more people to take personal precautions to combat the virus. It is difficult to accurately predict the COVID- 19 cases due to many human factors involved. This paper aims to provide a forecasting model for COVID-19 cases with the help of human activity data from the Google Community Mobility Reports. To achieve this goal, a specific partial differential equation (PDE) is developed and validated with the COVID-19 data from the New York Times at the county level in the state of Arizona in the U.S. The proposed model describes the combined effects of transboundary spread among county clusters in Arizona and human activities on the transmission of COVID-19. The results show that the prediction accuracy of this model is well acceptable (above 94%). Furthermore, we study the effectiveness of personal precautions such as wearing face masks and practicing social distancing on COVID-19 cases at the local level. The localized analytical results can be used to help to slow the spread of COVID- 19 in Arizona. To the best of our knowledge, this work is the first attempt to apply PDE models on COVID-19 prediction with the Google Community Mobility Reports.
The effect of lockdown due to coronavirus disease (COVID-19) pandemic on air pollution in four Southern European cities (Nice, Rome, Valencia and Turin) and Wuhan (China) was quantified, with a focus on ozone (O3). Compared to the same period in 2017–2019, the daily O3 mean concentrations increased at urban stations by 24% in Nice, 14% in Rome, 27% in Turin, 2.4% in Valencia and 36% in Wuhan during the lockdown in 2020. This increase in O3 concentrations is mainly explained by an unprecedented reduction in NOx emissions leading to a lower O3 titration by NO. Strong reductions in NO2 mean concentrations were observed in all European cities, ~53% at urban stations, comparable to Wuhan (57%), and ~65% at traffic stations. NO declined even further, ~63% at urban stations and ~78% at traffic stations in Europe. Reductions in PM2.5 and PM10 at urban stations were overall much smaller both in magnitude and relative change in Europe (~8%) than in Wuhan (~42%). The PM reductions due to limiting transportation and fuel combustion in institutional and commercial buildings were partly offset by increases of PM emissions from the activities at home in some of the cities. The NOx concentrations during the lockdown were on average 49% lower than those at weekends of the previous years in all cities. The lockdown effect on O3 production was ~10% higher than the weekend effect in Southern Europe and 38% higher in Wuhan, while for PM the lockdown had the same effect as weekends in Southern Europe (~6% of difference). This study highlights the challenge of reducing the formation of secondary pollutants such as O3 even with strict measures to control primary pollutant emissions. These results are relevant for designing abatement policies of urban pollution.
The link is: https://doi.org/10.1016/j.scitotenv.2020.139542
Covid-19 was first reported in Morocco on March 2, 2020. Since then, to prevent its propagation, the Moroccan government declared a state of health emergency. A set of rapid and strict countermeasures have taken, including locking down cities, limiting population's mobility and prohibiting almost all avoidable activities. In the present study, we attempted to evaluate the changes in levels of some air pollutants (mainly PM10, NO2 and SO2) in Salé city (North-Western Morocco) during the lockdown measures. In this context, a continuous measurement of PM10, SO2 and NO2 was carried before and during the Covid-19 lockdown period. As a consequence of the security measures and control actions undertaken, the emissions from vehicle exhaust and industrial production were significantly reduced, which contribute to the decrease in the concentrations of the studied pollutants. The obtained results showed that the difference between the concentrations recorded before and during the lockdown period were respectively 75%, 49% and 96% for PM10, SO2 and NO2. PM10 levels were much less reduced than NO2. The three-dimensional air mass backward trajectories, using the HYSPLIT model, demonstrated the benefits of PM10 local emission reductions related to the lockdown were overwhelmed by the contribution of long-range transported aerosols outside areas. In addition, noteworthy differences in the air mass back trajectories and the meteorology between these two periods were evidenced.
Based on the rapid spread of the CoViD-2019, a lockdown was declared in the whole Northern Italy by the Government. The application of increasingly rigorous containment measures allowed to reduce the impact of the CoViD-2019 pandemic on the Italian National Health System but at the same time these restriction measures gave also the opportunity to assess the effect of anthropogenic activities on air pollutants in an unprecedented way. This paper aims to study the impact of the partial and total lockdown (PL and TL, respectively) on air quality in the Metropolitan City of Milan. As results, the severe limitation of people movements following the PL and the subsequent TL determined a significant reduction of pollutants concentration mainly due to vehicular traffic (PM10, PM2.5, BC, benzene, CO, and NOx). The lockdown led to an appreciable drop in SO2 only in the city of Milan while it remained unchanged in the adjacent areas. Despite the significant decrease in NO2 in the TL, the O3 exhibited a significant increase, probably, due to the minor NO concentration. In Milan and SaA the increase was more accentuated, probably, due to the higher average concentrations of benzene in Milan than the adjacent areas that might have promoted the formation of O3 in a more significant way.
Responding to the ongoing novel coronavirus (agent of COVID-19) outbreak, China implemented “the largest quarantine in human history” in an attempt to prevent the spread of the virus on 23 January 2020. Human mobility and relevant production and consumption activities have since decreased significantly. As a likely side effect of this decrease, many regions have recorded significant reductions in air pollution. We employed daily air pollution data and Intracity Migration Index (IMI) data form Baidu between 1 January and 21 March 2020 for 44 cities in northern China to examine whether, how, and to what extent travel restrictions affected air quality. On the basis of this quantitative analysis, we reached the following conclusions: (1) The reduction of air pollution was strongly associated with travel restrictions during this pandemic—on average, the air quality index (AQI) decreased by 7.80%, and five air pollutants (i.e., SO2, PM2.5, PM10, NO2, and CO) decreased by 6.76%, 5.93%, 13.66%, 24.67%, and 4.58%, respectively. (2) Mechanism analysis illustrated that the lockdowns of 44 cities reduced human movements by 69.85%, and a reduction in the AQI, PM2.5, and CO was partially mediated by human mobility, and SO2, PM10, and NO2 were completely mediated. (3) Our findings highlight the importance of understanding the role of green production and consumption.
Amid the COVID-19 pandemic, a nationwide lockdown is imposed in India initially for three weeks from 24th March to 14th April 2020 and extended up to 3rd May 2020. Due to the forced restrictions, pollution level in cities across the country drastically slowed down just within few days which magnetize discussions regarding lockdown to be the effectual alternative measures to be implemented for controlling air pollution. The present article eventually worked on this direction to look upon the air quality scenario amidst the lockdown period scientifically with special reference to the megacity Delhi. With the aid of air quality data of seven pollutant parameters (PM10, PM2.5, SO2, NO2, CO, O3 and NH3) for 34 monitoring stations spread over the megacity we have employed National Air Quality Index (NAQI) to show the spatial pattern of air quality in pre and during-lockdown phases. The results demonstrated that during lockdown air quality is significantly improved. Among the selected pollutants, concentrations of PM10 and PM2.5 have witnessed maximum reduction (>50%) in compare to the pre-lockdown phase. In compare to the last year (i.e. 2019) during the said time period the reduction of PM10 and PM2.5 is as high as about 60% and 39% respectively. Among other pollutants, NO2 (−52.68%) and CO (−30.35%) level have also reduced during-lockdown phase. About 40% to 50% improvement in air quality is identified just after four days of commencing lockdown. About 54%, 49%, 43%, 37% and 31% reduction in NAQI have been observed in Central, Eastern, Southern, Western and Northern parts of the megacity. Overall, the study is thought to be a useful supplement to the regulatory bodies since it showed the pollution source control can attenuate the air quality. Temporary such source control in a suitable time interval may heal the environment.
In early March 2020, the World Health Organization declared the COVID-19 as a pandemic, and in late March 2020 partial lockdown was ordered by the São Paulo State government. The aim of this study was to assess impacts on air quality in São Paulo – Brazil, during the partial lockdown implemented to provide social distancing required due to the COVID-19 pandemic. We have analyzed data from four air quality stations in São Paulo, Brazil to assess air pollutant concentration variations during the partial lockdown. Data were compared to the five-year monthly mean and to the four-week before the partial lockdown. Overall, drastic reductions on NO (up to −77.3%), NO2 (up to −54.3%), and CO (up to −64.8%) concentrations were observed in the urban area during partial lockdown compared to the five-year monthly mean. By contrast, an increase of approximately 30% in ozone concentrations was observed in urban areas highly influenced by vehicle traffic, probably related to nitrogen monoxide decreases. Although the partial lockdown has contributed to a positive impact on air quality, it is important to take into account the negative impacts on social aspects, considering the deaths caused by COVID-19 and also the dramatic economic effects.
Infection by coronavirus (CoV-19) has led to emergence of a pandemic called as Coronavirus Disease (COVID-19) that has so far affected about 210 countries. The dynamic data indicate that the pandemic by CoV-19 so far has infected 2,403,963 individuals, and among these 624,698 have recovered while, it has been fatal for 165,229. Without much experience, currently, the medicines that are clinically being evaluated for COVID-19 include chloroquine, hydroxychloroquine, azithromycin, tocilizumab, lopinavir, ritonavir, tocilizumab and corticosteroids. Therefore, countries such as Italy, USA, Spain and France with the most advanced health care system are partially successful to control CoV-19 infection. India being the 2nd largest populous country, where, the healthcare system is underdeveloped, major portion of population follow unhygienic lifestyle, is able to restrict the rate of both infection and death of its citizens from COVID-19. India has followed an early and a very strict social distancing by lockdown and has issued advisory to clean hands regularly by soap and/or by alcohol based sterilizers. Rolling data on the global index of the CoV infection is 13,306, and the index of some countries such as USA (66,148), Italy (175,055), Spain (210,126), France (83,363) and Switzerland (262,122) is high. The index of India has remained very low (161) so far, mainly due to early implementation of social lockdown, social distancing, and sanitizing hands. However, articles on social lockdown as a preventive measure against COVID-19 in PubMed are scanty. It has been observed that social lockdown has also drastic impacts on the environment especially on reduction of NO2 and CO2 emission. Slow infection rate under strict social distancing will offer time to researchers to come up with exact medicines/vaccines against CoV-19. Therefore, it is concluded that stringent social distancing via lockdown is highly important to control COVID-19 and also to contribute for self-regeneration of nature.
The effectiveness and cost are always top factors for policy-makers to decide control measures and most measures had no pre-test before implementation. Due to the COVID-19 pandemic, human activities are largely restricted in many regions in India since mid-March of 2020, and it is a progressing experiment to testify effectiveness of restricted emissions. In this study, concentrations of six criteria pollutants, PM10, PM2.5, CO, NO2, ozone and SO2 during March 16th to April 14th from 2017 to 2020 in 22 cities covering different regions of India were analysed. Overall, around 43, 31, 10, and 18% decreases in PM2.5, PM10, CO, and NO2 in India were observed during lockdown period compared to previous years. While, there were 17% increase in O3 and negligible changes in SO2. The air quality index (AQI) reduced by 44, 33, 29, 15 and 32% in north, south, east, central and western India, respectively. Correlation between cities especially in northern and eastern regions improved in 2020 compared to previous years, indicating more significant regional transport than previous years. The mean excessive risks of PM reduced by ~52% nationwide due to restricted activities in lockdown period. To eliminate the effects of possible favourable meteorology, the WRF-AERMOD model system was also applied in Delhi-NCR with actual meteorology during the lockdown period and an un-favourable event in early November of 2019 and results show that predicted PM2.5 could increase by only 33% in unfavourable meteorology. This study gives confidence to the regulatory bodies that even during unfavourable meteorology, a significant improvement in air quality could be expected if strict execution of air quality control plans is implemented.
This research aims to show the positive and negative indirect effects of COVID-19 on the environment, particularly in the most affected countries such as China, USA, Italy, and Spain. Our research shows that there is a significant association between contingency measures and improvement in air quality, clean beaches and environmental noise reduction. On the other hand, there are also negative secondary aspects such as the reduction in recycling and the increase in waste, further endangering the contamination of physical spaces (water and land), in addition to air. Global economic activity is expected to return in the coming months in most countries (even if slowly), so decreasing GHG concentrations during a short period is not a sustainable way to clean up our environment.