Air Pollutants and Their Impact on Chronic Diseases—A Retrospective Study in Bucharest, Romania

Air pollution is a serious problem in Romania, with the country ranking 13th among the most polluted countries in Europe in the 2021 World Air Quality Report. Despite the recognized impact of pollutants on health, there has been a lack of large-scale studies conducted in Romania. This study investigated the impact of air pollutants on patients with chronic respiratory, cardiovascular, cerebrovascular, or metabolic diseases in Bucharest and its metropolitan area from 20 August 2018 to 1 June 2022. The daily limit values for particulate matter PM10 and PM2.5 were exceeded every month, especially during the cold season, with a decrease during the COVID-19 pandemic restrictions. A significant statistical correlation was found between the monthly average values of PM2.5 and PM10 and hospitalizations for respiratory and cardiovascular diseases. A 10 µg/m3 increase in monthly average values resulted in a 40–60% increase in admissions for each type of pathology, translating to more than 2000 admissions for each pathology for the study period. This study highlights the urgent need for national and local measures to ensure a cleaner environment and enhance public health in Romania according to international regulations. © 2023 by the authors.

Influence of Temperature and Relative Humidity on PM2.5 Concentration over Delhi

The present study is an attempt to establish relationship between the concentrations of particulate matter especially (PM2.5) and background meteorological parameters over Delhi, India with the help of statistical and correlative analysis. This work presents the evaluation of air quality in three different locations of Delhi. These locations were selected to fulfil the characteristics as residential, industrial and background locations and performed the analysis for pre and post covid-19, i.e. for 2019 and 2021. The outcome of the study shows that the meteorological parameters have significant influence on the PM2.5 concentration. It was also found that it has a seasonality with low concentration in the monsoon season, moderate in the pre-monsoon season and high during the winters and post-monsoon seasons. However, the statistical and correlative study shows a negative relation with the temperature during the winter, pre-monsoon and post-monsoon and has a positive correlation during the monsoon season. Similarly, it also has been observed that the concentration of PM2.5 shows strong negative correlation with temperature during the high humid conditions, i.e. when the relative humidity is above 50%. However, a weak correlation with ambient temperature has been established during the low humidity condition, i.e. below 50%. The overall study showed that the highest PM2.5 pollution has been observed at residential location followed by industrial and background. The study also concluded that the seasonal meteorology has a complex role in the PM2.5 concentration of the selected areas.

Air pollution with pm10 for the municipality of Burgas and the monthly cases of disease with COVID 19, 2021

An important environmental problem for the Municipality of Burgas is the relatively high levels of PM10 pollution. Particulate matter PM10 is defined as the fraction of particles with an aerodynamic diameter smaller than 10 pm. The article provides statistical processing and evaluation of daily data on the concentration of PM10 in the air by quarters fix Burgas, 2021. A histogram of the frequency distribution of concentrations by quarters was prepared. A regression model for calculating the monthly concentrations in the atmospheric air is derived The tests and inspections performed show that the performed modelling is suitable for evaluation, analysis and forecast. Air pollution harms human health and the environment. Exposure ID air pollution is associated with a wide range of acute and chronic health effects, ranging from irritating effects to death From the end of 2019 until now in the world, Europe and in particular Bulgaria is raging a dangerous respiratory disease known as COVD19. The average monthly new cases of COVD19 for Burgas were assessed, as well as the respective maximum and minimum monthly values. A qualitative assessment of the relationship between the monthly concentrations of PM10 and the incidence of COVID19 was made.

Impact of Anthropogenic Emission Reduction during COVID-19 on Air Quality in Nanjing, China

To avoid the spread of COVID-19, China has implemented strict lockdown policies and control measures, resulting in a dramatic decrease in air pollution and improved air quality. In this study, the air quality model WRF-Chem and the latest MEIC2019 and MEIC2020 anthropogenic emission inventories were used to simulate the air quality during the COVID-19 lockdown in 2020 and the same period in 2019. By designing different emission scenarios, this study explored the impact of the COVID-19 lockdown on the concentration of air pollutants emitted by different sectors (industrial sector and transportation sector) in Nanjing for the first time. The results indicate that influenced by the COVID-19 lockdown policies, compared with the same period in 2019, the concentrations of PM2.5, PM10, and NO2 in Nanjing decreased by 15%, 17.1%, and 20.3%, respectively, while the concentration of O3 increased by 45.1% in comparison;the concentrations of PM2.5, PM10 and NO2 emitted by industrial sector decreased by 30.7%, 30.8% and 14.0% respectively;the concentrations of PM2.5, PM10 and NO2 emitted by transportation sector decreased by 15.6%, 15.7% and 26.2% respectively. The COVID-19 lockdown has a greater impact on the concentrations of PM2.5 and PM10 emitted by the industrial sector, while the impact on air pollutants emitted by the transportation sector is more reflected in the concentration of NO2. This study provides some theoretical basis for the treatment of air pollutants in different departments in Nanjing.

Impact of COVID-19 Lockdown on Ambient Air Quality in the Southwest Coastal Urban Regions of India

The rapid growth of urban areas and population as well as associated development over recent decades have been a major factor controlling ambient air quality of the urban environment in Kerala (India). Being located at the southwestern fringe of the Indian peninsula, Kerala is one of the regions that has been significantly influenced by the activities in the Indian Ocean. The present study focuses on the effect of the COVID-19 lockdown (in 2021) on ambient air quality in the selected coastal metropolitan areas of Kerala. Although previous research studies reported improvement in ambient air quality in Kerala during the lockdown period, this study demonstrates the potential of onshore transport of air pollutants in controlling the air quality of coastal urban regions during the lockdown period. Data from the ambient air quality monitoring stations of the Kerala State Pollution Control Board in the urban areas of Thiruvananthapuram (TM), Kollam (KL), Kozhikode (KZ), and Kannur (KN) are used for the analysis. Temporal variation in the concentration of air pollutants during the pre-lockdown (PRLD), lockdown (LD), and post-lockdown (PTLD) periods (i.e., 1 March to 31 July) of 2021 is examined to assess the effect of lockdown measures on the National Air Quality Index (AQI). Results indicate a significant decline in the levels of air pollutants and subsequent improvement in air quality in the coastal urban areas. All the effect of lockdown measures has been evident in the AQI, an increase in the concentration of different pollutants including CO, SO2, and NH3 during the LD period suggests contributions from multiple sources including onshore transport due to marine traffic and transboundary transport. © 2023, The Author(s) under exclusive licence to Institute of Earth Environment, Chinese Academy Sciences.

Peculiar weather patterns effects on air pollution and COVID-19 spread in Tokyo metropolis.

As a pandemic hotspot in Japan, between March 1, 2020-October 1, 2022, Tokyo metropolis experienced seven COVID-19 waves. Motivated by the high rate of COVID-19 incidence and mortality during the seventh wave, and environmental/health challenges we conducted a time-series analysis to investigate the long-term interaction of air quality and climate variability with viral pandemic in Tokyo. Through daily time series geospatial and observational air pollution/climate data, and COVID-19 incidence and death cases, this study compared the environmental conditions during COVID-19 multiwaves. In spite of five State of Emergency (SOEs) restrictions associated with COVID-19 pandemic, during (2020-2022) period air quality recorded low improvements relative to (2015-2019) average annual values, namely: Aerosol Optical Depth increased by 9.13% in 2020 year, and declined by 6.64% in 2021, and 12.03% in 2022; particulate matter PM2.5 and PM10 decreased during 2020, 2021, and 2022 years by 10.22%, 62.26%, 0.39%, and respectively by 4.42%, 3.95%, 5.76%. For (2021-2022) period the average ratio of PM2.5/PM10 was (0.319 ± 0.1640), showing a higher contribution to aerosol loading of traffic-related coarse particles in comparison with fine particles. The highest rates of the daily recorded COVID-19 incidence and death cases in Tokyo during the seventh COVID-19 wave (1 July 2022-1 October 2022) may be attributed to accumulation near the ground of high levels of air pollutants and viral pathogens due to: 1) peculiar persistent atmospheric anticyclonic circulation with strong positive anomalies of geopotential height at 500 hPa; 2) lower levels of Planetary Boundary Layer (PBL) heights; 3) high daily maximum air temperature and land surface temperature due to the prolonged heat waves (HWs) in summer 2022; 4) no imposed restrictions. Such findings can guide public decision-makers to design proper strategies to curb pandemics under persistent stable anticyclonic weather conditions and summer HWs in large metropolitan areas.

Changes of Air Pollutants in Urban Cities during the COVID-19 Lockdown-Sri Lanka

In response to the COVID-19 pandemic in early 2020, Sri Lanka underwent a nationwide lockdown that limited motor vehicle movement, industrial operations, and human activities. This study analyzes the impact of COVID-19 lockdown on carbon monoxide (CO), ozone (O3), nitrogen dioxide (NO2), sulfur dioxide (SO2), and particulate matter (PM10, PM2.5) concentrations in two urban cities (Colombo and Kandy) in Sri Lanka, by comparison of data from the lockdown period (March to May 2020) with its analogous period of 2019 and 2021. The results showed that the percentage change of daytime PM10, PM2.5, CO, and NO2 concentration during the lockdown in Colombo (Kandy) is –42.3% (–39.5%), –46% (–54.2%), –14.7% (–8.8%) and –82.2% (–80.9%), respectively. In both cities, the response of NO2 to the lockdown was the most sensitive. In contrast, daytime O3 concentration in Colombo (Kandy) has increased by 6.7% (27.2%), suggesting that the increase in O3 concentration was mainly due to a reduction in NOx emissions leading to lower O3 titration by NO. In addition, daytime SO2 concentration in Colombo has increased by 22.9%, while daytime SO2 concentration in Kandy has decreased by –40%. During the lockdown period, human activities were significantly reduced, causing significant reductions in industrial operations and transportation activities, further reducing emissions and improving air quality in two cities. The results of this study offer potential for local authorities to better understand the emission sources, assess the effectiveness of current air pollution control strategies, and form a basis for formulating better environmental policies to improve air quality and human health. © The Author(s).

Impact of COVID-19 lockdown on particulate matter (PM2.5) concentration in Kathmandu, Nepal

This paper reports a study on the statistics for particulate matter pollution (PM2.5) and the COVID-19 lockdown in the Kathmandu valley. The PM2.5 decreased during the COVID-19 pandemic lockdown periods 2020 compared to the average value of the previous three years (2017, 2018, and 2019). Further, analysis of active fire and air mass trajectory for April and May in 2019 and 2020 shows that the particulate matter trend associated with Kathmandu is not directly influenced by the long-range transport of wind carrying aerosols from the active fire regions. Statistical tests indicate a reduction of particulate matter pollution during the period.

Risk assessment on air environment control in ship negative pressure ward

OBJECTIVE: To explore the air environment control in ship negative pressure ward and conduct the risk assessment. METHODS: STARCCM+ simulation software was employed to simulate the air environment in the negative pressure ward of ships, and the impact of ventilation volume, non-equilibrium pressure difference and open/close door disturbance on the flow of polluted gas in the ward and the pressure control between compartments was observed. RESULTS: It was found that the pressure gradient and airflow direction of adjacent cabins were basically the same under different ventilation conditions;the pressure fluctuation of the medical corridor had the greatest impact on the buffer room, and when the negative pressure fluctuated higher than the design value, the pressure difference between the buffer room and the negative pressure ward was lower than the design requirement of 5 Pa;when the cabin door was opened from the buffer room to the corridor, that was, when the cabin door was opened to an area with low negative pressure, a low pressure area appears in the buffer room, and the polluted air flowed from the corridor to the buffer room. Finally, the risk of airborne infection was assessed by using the Wells-Riley model, doubling the amount of ventilation reduced the probability of transmission of SARS-CoV-2 infection by about 100%. The results showed that the ventilation volume had little effect on the pressure control, but it wound affect the probability of transmission of viral infection;the pressure fluctuation in a certain compartment would affect the pressure in other areas, so that the pressure control between the compartments did not meet the design requirements, opening the hatch door to the area with low negative pressure could reduce the risk of virus transmission. CONCLUSION: The research provides guidance for the air environment control in the ship's negative pressure isolation ward so as to prevent the spread of infectious diseases in the ship.

Air pollution assessment in Seoul, South Korea, using an updated daily air quality index

The variability of daily air quality index DAQx* was analyzed for types of air quality monitoring stations (AQMSs) in Seoul, South Korea, from 2018 to 2021. Daily maximum 1-h means of O3 and NO2 and daily 24-h means of PM10 and PM2.5 from 42 AQMSs were used to calculate the DAQx*. The frequencies of DAQx* values in DAQx* classes 3 (satisfactory) and 4 (sufficient) dominated for all station types, followed by DAQx* class 5 (poor). The variability of DAQx* values within station types mostly corresponded approximately to one DAQx* class, with mean frequencies of 82% for roadside, 81% for urban, and 72% for background stations. Lower air pollution levels on weekends than weekdays were shown for roadside stations by frequencies of DAQx* values in classes 3 (11% higher) and 4 (12% lower) during summer. NO2 was the air pollutant that annually most frequently formed DAQx* at roadside (48%) and urban (32%) stations, while O3 was the dominant pollutant (38%) at background stations. In winter, PM10 was the most common contributor to the DAQx* (at least 47%) at all station types. The dominant air pollutants in summer were NO2 at roadside stations (72%) and O3 at urban (63%) and background (68%) stations. Air quality improvement during a stronger social distancing period in 2020 due to the COVID-19 pandemic was evidenced by higher frequencies in DAQx* class 3 (up to 26%) but lower frequencies in DAQx* class 4 (up to 24%) than that during the reference period, especially for the roadside stations. © 2023 Turkish National Committee for Air Pollution Research and Control

An empirical analysis of Delhi's air quality throughout different COVID-19 pandemic waves

Delhi was one of India's COVID-19 hotspots, with significant death rates during the year 2021. This study looked at the link between COVID-19 cases in Delhi, and key meteorological variables. The study found that COVID-19 cases during the second wave (P2-March- May 2021) were much higher than during the first wave (P1-Jan-Feb 2021) in Delhi. During P1 (Jan-Feb 2021) the mean PM2.5, PM10, NO2 and CO concentrations were greater than that of P2 (March-May 2021) while the reverse happened for SO2 and O3. Spearman correlation test indicated that COVID-19 cases maintained a significant positive correlation with the high temperature of P2 (March-May 2021) and high humidity of P1 (Jan-Feb 2021) in line with the accepted notion that COVID-19 transmitted favourably in hot and humid climates. The Multilayer perceptron (MLP) model indicated that COVID-19 spread was supported by air pollutants and climate variables like PM2.5, NO2, RH, and WS in P1(Jan-Feb 2021) and PM2.5 and O3 in P2 (March-May 2021). Owing to chemical coupling, across all six monitoring stations, O3 maintained an inverse relationship with NO2 throughout the COVID-19 phases in Delhi. The city dwellers had health risks also due to PM pollution at varying degrees, indicated by high hazard quotients (HQs), requiring lowering of air pollution concentrations on an urgent basis. [ FROM AUTHOR] Copyright of Journal of Applied & Natural Science is the property of Applied & Natural Science Foundation and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)

TIME-SERIES ANALYSIS OF AIR QUALITY IN MAJOR CITIES IN THE PHILIPPINES DURING THE COVID-19 PANDEMIC THROUGH SENTINEL-5

Air pollution causes respiratory ailments and drives climate change. Air quality is driven by emissions from various sources, weather patterns, and transport of pollutants. Satellite analysis of pollutants in the atmosphere can provide temporally consistent and spatially wide measurements. In this study, the monthly concentrations of Nitrogen Dioxide (NO2), Sulfur Dioxide (SO2), Carbon Monoxide (CO), and Ozone (O3) from the Sentinel-5 Tropospheric Monitoring Instrument (TROPOMI) were analyzed in four major cities in the Philippines, representing different climate types. Satellite-based measurements of land surface temperature and rainfall were used to investigate meteorological effects to air pollutants. Seasonal patterns were observed in the time series of NO2, O3 and CO alongside rainfall and LST. During the dry season, high LST and low precipitation is observed to be associated with increase in NO2, O3, and CO concentrations. On the other hand, wet seasons show decreases in concentrations of air pollutants, consistent with the washout effect. The NO2 average concentration in NCR is 1.9, 2.1, 2.3 times higher than in Metro Cebu, Davao City, and Legazpi City, respectively. In contrast, SO2 average concentration is highest in Legazpi City due to the nearby active volcano by a maximum factor of 1.8 compared to other cities. In addition, air quality changes brought about by community quarantines were examined since the onset of the COVID-19 crisis. Transition from the pre-quarantine period to the first lockdown shows sudden decrease by 28% in satellite-based retrievals of NO2 in NCR, mainly due to reduced anthropogenic emissions. As tiers of community quarantines were introduced, an increase in pollutant concentrations was observed, returning to pre-pandemic air quality as the guidelines ease physical and economic restrictions. Monitoring and analyzing the patterns in concentration of air pollutants in relation to meteorological and anthropogenic drivers can help in the air quality management in the country. © 43rd Asian Conference on Remote Sensing, ACRS 2022.

Spatio-temporal air quality assessment in Tehran, Iran, during the COVID-19 lockdown periods

Based on ground-based and satellite-based data, spatio-temporal analyses of air quality in Tehran were carried out during the lockdown periods (February-April) in 2020 and 2021. We evaluated the differences in temporal emissions of six air pollutants (NO2, CO, SO2, O3, PM2.5, and PM10) at various time scales, including diurnal, monthly, and relative changes. The results of ground-based measurements indicated that for all pollutants except O3, the magnitude decreased in 2020 (11-42%) compared to the baseline period (2015-2021). As a result of eased restrictions and unfavorable meteorological conditions, the reduction in air pollutants was lower in 2021 (5-32%), and PM2.5 and PM10 levels increased (3.75 and 11.22%). Satellite-based concentrations (NO2, CO, SO2, and AOD) varied from −8 to 54% in 2020 and from −41 to 60% in 2021 compared to 2019 as the pre-lockdown year. Concerning AOD, the trend is consistent with dust events during March and April in our region. © 2023 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.

Sequential spatiotemporal distribution of PM2.5, SO2 and Ozone in China from 2015 to 2020

Currently, in the modeling of various atmospheric pollutants, the simulation of independent trace gases (SO2 and O3) is constrained by the insufficient resolution of key remote sensing products, resulting in insufficient simulation reliability. In this study, spatial sampling and parameter convolution are combined to optimize LightGBM by utilizing ground observations, remote sensing products, meteorological data, assistance data, and random ID. Through the above techniques and an sequentialsimulation of air pollutants, we produce seamless daily 1-km-resolution products of PM2.5, SO2 and O3 for most parts of China from 2015 to 2020. Through random sampling, random site sampling, area-specific validation, comparisons of different models, and a cross26 sectional comparison of different studies, we verified that our simulations of the spatial distribution of multiple atmospheric pollutants are reliable and effective. The CV of the random sample yielded an R² of 0.88 and an RMSE of 9.91 ㎍/m³ for PM2.5, an R² of 0.89 and an RMSE of 4.62 ㎍/m³ for SO2, and an R² of 0.91 and an RMSE of 6.88 ㎍/m3 for O3. Combined with the SHapley Additive exPlanations (SHAP) approach, the roles of different parameters in the simulation process were clarified, and the positive role of parameter convolution was confirmed. Our dataset was used to assess the changes in the Air Pollution Index (API) in China before and after the outbreak of COVID-19, and the results indicate that these 34 changes were relatively small huge, suggesting that the epidemic control measures in 2020 were effective. The study demonstrates that the multipollutant datasets produced with the proposed models are of great value for long-term, large-scale, and regional-scale air pollution monitoring and prediction, as well as population health evaluation. [ABSTRACT FROM AUTHOR] Copyright of Earth System Science Data Discussions is the property of Copernicus Gesellschaft mbH and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Footprints of COVID-19 on Pollution in Southern Spain

Background: Many annual deaths in Spain could be avoided if pollution levels were reduced. Every year, several municipalities in the Community of Andalusia, located in southern Spain, exceed the acceptable levels of atmospheric pollution. In this sense, the evolution of primary air pollutants during the March–June 2020 lockdown can be taken as reliable evidence to analyze the effectiveness of potential air quality regulations. Data and Method: Using a multivariate linear regression model, this paper assesses the levels of NO2, O3, and PM10 in Andalusia within the 2017–2020 period, relating these representative indices of air quality with lockdown stages during the pandemic and considering control variables such as climatology, weekends, or the intrusion of Saharan dust. To reveal patterns at a local level between geographic zones, a spatial analysis was performed. Results: The results show that the COVID-19 lockdown had a heterogeneous effect on the analyzed pollutants within Andalusia's geographical regions. In general terms, NO2 and PM10 concentrations decreased in the main metropolitan areas and the industrial districts of Huelva and the Strait of Gibraltar. At the same time, O3 levels rose in high-temperature regions of Cordoba and Malaga. © 2022 by the authors.

The impacts of COVID-19 pandemic on air pollution from energy consumption: diverse evidence from China

Based on panel data of 31 provincial capital cities in the country from January 21 to November 20, 2020, this research empirically analyzes the impacts of daily newly confirmed cases and daily new deaths from COVID-19 on PM10, PM2.5, SO2, CO, and NO2 emissions form green energy consumption by using the method of System Generalized Moments (SYS-GMM). We conclude that the COVID-19 pandemic has an inhibitory effect on all types of emissions, in that a greater number of confirmed cases and deaths brings about more stringent anti-epidemic policies, fewer emissions, and better air quality in China. Moreover, we use the methods of sample segmentation, cross-sectional regression, and pollutant emissions of the top three cities in terms of GDP to test their robustness. Overall, our evidence advances the debate over air quality after COVID-19, and that evidence from China provides beneficial experiences that correlate to its provincial data.

Racial disparities in air pollution burden and COVID-19 deaths in Louisiana, USA, in the context of long-term changes in fine particulate pollution. (Special Issue: Disparities during times of a pandemic and epidemic.)

Black Americans in Louisiana are disproportionately dying from COVID-19, and environmental disparities may be contributing to this injustice. While Black communities in Louisiana's industrialized regions (e.g., Cancer Alley, Calcasieu Parish) have been overburdened with pollution for decades, this disparity has not been evaluated by using recent data. Here, we explore statewide relationships among air pollution burden, race, COVID-19 death rates, and other health/socioeconomic factors. Measures of pollution burden included satellite-derived particulate matter (PM2.5) concentrations and health risks from toxic air pollution (i.e., respiratory hazard [RH] and immunological hazard [IH], estimated by the Environmental Protection Agency). In addition, we evaluate changes in emissions and ambient concentrations of fine PM2.5 in Louisiana over the past few decades. Our overall goal was to better understand Louisiana's burden of air pollution in the context of COVID-19. By all measures, a higher burden of air pollution was associated with larger percentages of Black residents and increased unemployment across Louisiana census tracts. Across parishes, higher COVID-19 death rates were associated with increased RH and IH and larger percentages of Black residents. These associations were not driven by diabetes, obesity, smoking, age, or poverty. Industrial sources comprised more of Louisiana's PM2.5 in 2017 versus 1990, as vehicle contributions declined 75% whereas industrial emissions remained about the same overall (despite variation in the interim). Ambient concentrations of PM2.5 decreased statewide from 2000 to 2015, but subsequently increased in south Louisiana, concurrent with an upward trend in industrial emissions. Our findings highlight the critical need to address Louisiana's pollution disparities and to recognize air pollution exposure as a risk factor for COVID-19.

Does air quality influence the spread of the SARS - Cov2 in metropolitan cities? - a case study from urban India

COVID 19 pandemic has gradually established itself as the worst pandemic in the last hundred years around the world after initial outbreak in China, including India. To prevent the spread of the infection the Government implemented lockdown measure initially from 24th March to 14th April, 2020 which was later extended to 3rd May, 2020. This lockdown imposed restrictions in human activities, vehicular movements and industrial functioning;resulting in reduced pollution level in the cities. This study was initiated with the objective to identify the change in the air quality of seven megacities in India and to determine any correlation between the active COVID cases with the air quality parameters. Air quality dataset of the most common parameters (PM2.5, PM10, SO2, NO2, NH3, CO and Ozone) along with air quality index for 70 stations of seven megacities (Delhi, Mumbai, Kolkata, Bengaluru, Hyderabad, Chennai and Chandigarh) were analysed. Comparison was made between AQI of pre lockdown and during lockdown periods. The results obtained indicate sufficient improvement in air quality during the period of the lockdown. For the next part of the study active COVID cases during the lockdown were compared to the air quality change of that period. A significant correlation between active COVID case and change in the air quality was observed for Delhi and Kolkata with 0.51 and 0.64 R2 values respectively. A positive correlation was also observed between air pollutant parameters and incidents of COVID cases in this study. Thus from the analysis it was identified that air quality index improved considerably as a result of the nationwide lockdown however, there was no significant impact of this improvement on the infection rate of the prevailing pandemic.

Significant effect of COVID-19 induced lockdown on air quality of the Indian metropolitan city Kolkata using air quality index and health air quality index

The lockdown, commencing in India from March 23, 2020 to control the escalation of Covid-19 cases, exhibited a positive impact on the air quality. The study attempts to assess the outcome of lockdown on the air quality of Kolkata, India followed by the comparison of six priority pollutants during pre-lockdown, lockdown, and unlock phases. Averaged concentrations of PM10 (72%), PM2.5 (73%), NOx (84%), SO2 (48%), and CO (61%) showed reduction throughout lockdown in comparison with pre-lockdown phase, although no significant reduction was observed in ground-level Ozone. Unlock Phases I and II showed similar concentrations of the pollutants as that in the lockdown period whereas, in unlock Phase-III, the air quality became comparable to that before lockdown. Statistical analysis confirmed that the reduction in air pollution is attributed to atmospheric factors. PCA analysis established significant positive correlation between particulate matters, CO, SO2, and NOx;however, no significant correlation was observed between NOx and O3. January and December showed the highest load of most of the pollutants. Health risk was evaluated by calculating the Relative risk and Health Air Quality Index, which showed maximum health risk during the pre-lockdown and minimum during lockdown and unlock Phase-II with the highest contributor being PM10. The study outcome manifests a reduction in environmental pollution as a result of controlled anthropogenic activities.