Air Quality In India Research Articles

A systematic scrutiny of artificial intelligence-based air pollution prediction techniques, challenges, and viable solutions

Air is an essential human necessity, and inhaling filthy air poses a significant health risk. One of the most severe hazards to people’s health is air pollution, and appropriate precautions should be taken to monitor and anticipate its quality in advance. Among all the countries, the air quality in India is decreasing daily, which is a matter of concern to the health department. Many studies use machine learning and Deep learning methods to predict atmospheric pollutant levels, prioritizing accuracy over interpretability. Many research studies confuse researchers and readers about how to proceed with further research. This paper aims to give every detail of the considered air pollutants and brief about the techniques used, their advantages, and challenges faced during pollutant prediction, which leads to a better understanding of the techniques before starting any research related to air pollutant prediction. This paper has given numerous prospective questions on air pollution that piqued the study’s interest. This study discussed various machine and deep learning methods and optimization techniques. Despite all the discussed machine learning and deep learning techniques, the paper concluded that more datasets, better learning techniques, and a variety of suggestions would enhance interpretability while maintaining high accuracy for air pollution prediction. The purpose of this review is also to reveal how a family of neural network algorithms has helped researchers across the globe to predict air pollutant(s).

Assessing the impact of forest fires on air quality in Northeast India

This study investigates the impact of forest fires on air quality in India's northeastern (NE) region, focusing on Guwahati, Tezpur, and Aizawl.

Changing PM2.5 and related meteorology over India from 1950–2014: a new perspective from a chemistry-climate model ensemble

Surface PM2.5 concentrations in India have increased dramatically as emissions have risen in recent years. The role of meteorological factors in this increase is unclear, mainly due to a lack of long-term observations over the region. A 12-member ensemble of historical (1950–2014) simulations from the Community Earth System Model version 2-Whole Atmosphere Community Climate Model version 6 (CESM2-WACCM6) offers an unprecedented opportunity to examine simulated PM2.5 and meteorology for 20th century climates that can arise due to ‘climate noise’ under the same historical greenhouse gas and air pollutant emission trajectories. CESM2-WACCM6 includes interactive aerosol and gas-phase chemistry in the atmosphere coupled to ocean-sea ice-land models, and each ensemble member differs only in its initial conditions of the climate state. We systematically examine, decade-by-decade, the changes in PM2.5 and associated meteorology, including wind speed, surface temperature inversions, boundary layer height, precipitation, and relative humidity in four cities in India: Chennai, Kolkata, Mumbai, and New Delhi. Forced changes clearly emerge in meteorological variables from 1950 to 2014, including increases in both relative humidity and temperature inversion strength, and decreases in boundary layer height and average surface wind speed. The timing of these changes varies by city: boundary layer heights decrease most over New Delhi in the premonsoon season (ensemble average decrease of 400 m), but over Mumbai in the postmonsoon season (ensemble average decrease of 100 m). PM2.5 concentrations increase across India regardless of climate variability, with an almost threefold increase from 1950 to 2014 over New Delhi. Analysis of dimensionless variables shows that PM2.5 exhibits larger ensemble mean trends and smaller variability than the trends in the meteorological variables, enabling us to infer that the increase in PM2.5 is predominantly controlled by increases in anthropogenic emissions rather than climate variability. Overall, our simulations corroborate the dominant role of air pollutant emissions on poor air quality in India.

Improved air quality leads to enhanced vegetation growth during the COVID–19 lockdown in India

The direct effect of pandemic induced lockdown (LD) on environment is widely explored, but its secondary impacts remain largely unexplored. Therefore, we assess the response of surface greenness and photosynthetic activity to the LD-induced improvement of air quality in India. Our analysis reveals a significant improvement in air quality marked by reduced levels of aerosols (AOD, −19.27%) and Particulate Matter (PM 2.5, −23%) during LD (2020)from pre-LD (March–September months for the period 2017–2019). The vegetation exhibits a positive response, reflected by the increase in surface greenness [Enhanced Vegetation Index (EVI, +10.4%)] and photosynthetic activity [Solar Induced Fluorescence (SiF, +11%)], during LD from pre-LD that coincides with two major agricultural seasons of India; Zaid (March–May) and Kharif (June–September). In addition, the croplands show a higher response [two-fold in EVI (14.45%) and four-fold in SiF (17.7%)] than that of forests. The prolonged growing period (phenology) and high rate of photosynthesis (intensification) led to the enhanced greening during LD owing to the reduced atmospheric pollution. This study, therefore, provides new insights into the response of vegetation to the improved air quality, which would give ideas to counter the challenges of food security in the context of climate pollution, and combat global warming by more greening.

Health Impact Assessment of Air Pollution in India During COVID-19 Lockdown by Using Satellite Remote Sensing and Deep Learning

Air pollution produces major environmental health problems with a vast number of entropies that can affect healthy, sustainable environments across the globe. Millions of people are dying prematurely each year as a direct cause of poor air quality. According to recent studies, living within 50 meters of any significant road can increase the risk of lung cancer by up to 10%. World Health Organization declares that approximately 3.7 million people died worldwide in 2012 due to outdoor air pollution. In this analysis, we analyzed air pollutants that were released into the air from a wide range of sources, such as motor vehicles, industrial combustion processes, etc. We analyzed the Sentinel-5 precursor data, which provides time series data on a multitude of trace gaseous compounds such as CO, NO2, SO2, O3, PM10, PM2.5 aerosols, etc. with efficient statistics and special resolution. For better comparison, we have trained our statistical atmospheric data with deep learning methodology and analyzed them to obtain a reference for air quality in India. This study describes the scientific aspects and probable atmospheric composition entropy due to pollution. We also presented the overall operational product outcomes and emissions from the energy sectors, which involves the advancement of data analysis in a particular coordinate system.

Geospatial Technology-Based Analysis of Air Quality in India during the COVID-19 Pandemic

The study evaluates the impacts of India’s COVID-19 lockdown and unlocking periods on the country’s ambient air quality. India experienced three strictly enforced lockdowns followed by unlocking periods where economic and social restrictions were gradually lifted. We have examined the in situ and satellite data of NO2 emissions for several Indian cities to assess the impacts of the lockdowns in India. Additionally, we analyzed NO2 data acquired from the Sentinel-5P TROPOMI sensor over a few districts of the Punjab state, as well as the National Capital Region. The comparisons between the in situ and satellite NO2 emissions were performed for the years 2019, 2020 and up to July 2021. Further analysis was conducted on the satellite data to map the NO2 emissions over India during March to July for the years of 2019, 2020 and 2021. Based on the in situ and satellite observations, we observed that the NO2 emissions significantly decreased by 45–55% in the first wave and 30% in the second wave, especially over the Northern Indian cities during the lockdown periods. The improved air quality over India is indicative of reduced pollution in the atmosphere due to the lockdown process, which slowed down the industrial and commercial activities, including the migration of humans from one place to another. Overall, the present study contributes to the understanding of the trends of the ambient air quality over large geographical areas using the Sentinel-5P satellite data and provides valuable information for regulatory bodies to design a better decision support system to improve air quality.

Energy Anxiety in Decentralized Electricity Markets: A Critical Review on EV Models

The automobile sector is a promising avenue for enhancing energy security, economic opportunity, and air quality in India. Before penetrating a large number of electric vehicles (EV) into the power grid, a thorough investigation and assessment of significant parameters are required, as additional nonlinear and EV loads are linked to the decentralized market. Many automobile companies have already invested in electric vehicle research; hence, a detailed analysis on range anxiety and grid connectivity concerns are the important factors affecting the future of the electric vehicle industry. In this paper, the initial review is about the decentralized market in India and sustainable aspects of electric mobility based on the Indian context, as it is a developing nation with an enormous resource and scope for EV markets. With recent literature from the last three years, the substantial constraints observed in benefits and challenges are reviewed. The financial stability aspects and the incentives to overcome the barriers to EV adoption are briefly discussed. From the review, it has come to the limelight that infrastructure availability, technology, load demand, and consumer behaviour are all major obstacles in the electric vehicle ecosystem. For the overall design and study of the vehicle to grid (V2G) infrastructure, this paper also provides insight into the representation of electric vehicles in different energy-efficient models and their categorization while connecting to the grid. The methodology adopted for energy-efficient models includes lifecycle emissions, economy, smart charging, real-time optimization, aggregated EV resource modelling, and a support vector machine (SVM)-based method. This paper gives a positive impact on EV fleet integration and electric mobility in general, as it critically reviews the influential parameters and challenges. This classification depends on crucial parameters that are at the frontline of EV grid integration research. This review is a solution to enhance grid stability in regard to new EV models. With the advanced electric motors development and renewed battery technology models, longer-distance automobiles are now available on the market. This paper investigates the constraints of EV grid integration and analyzes different EV models to ease the grid stability for a decentralized market.

Air quality in India has worsened again after improving during the 2020 lockdown

Air quality in India has worsened again after improving during the 2020 lockdown

Variation in Air Quality over Delhi Region: A Comparative Study for 2019 and 2020

Air quality of highly industrialized cities has shown enhanced potential for adverse impacts upon environment and human health. Spread of the COVID-19 in people suffering from some ailment is one of the examples. Meanwhile, complete and partial lockdown were imposed, nationwide, throughout the globe. This study portrays the spatio-temporal variations of atmospheric pollutants over eight regions in National Capital Territory (NCT) Delhi, India, during 2019–2020. It focusses on the entire year with special emphasis on four phases of lockdown and unlock with varying restrictions. As compared to 2019, the results show decrease in relative percent by for fine particulate matters (~ 11.6%), oxides of nitrogen (~ 7%), oxides of sulfur (~ 3.7%), ozone (~ 7.7%), carbon monoxide (~ 20.7%), benzene (~ 11%) and toluene (~ 14%). It was found that strict lockdown phase-I had major contribution to this change. Toluene:Benzene ratios for summer coinciding with strict lockdown confirmed non-operating stationary sources. Later phases were provided with relaxation in certain sectors (mainly vehicular mobility and industrial sector) accompanied with various meteorological impacts, hence did not show much variations. After unlock-IV, anthropogenic activities were found to be accelerated to meet the halted economic demands. Meanwhile, during winter season, biogenic emissions and meteorological factors together affect the air quality in India, aiding air dispersion inhibition due to which the pollutants level showed immediate rise. Restricted human activities prevailing during the lockdown and unlock phases proved to be beneficial in terms of stumping the emission of pollutants into the ambient environment proving that the imposed lockdown healed the environment temporarily.

Air quality change and public perception during the COVID-19 lockdown in India

This study aims at analyzing the change in air quality following the COVID-19 lockdown in India and its perception by the general public. Air quality data for 100 days recorded at 193 stations throughout India were analyzed between 25th March to 17th May 2020. A nationwide online survey was conducted to obtain public perceptions of air quality improvement (n = 1750). On average, approximately 40% improvement in the air quality index was observed, contributed by a reduction in 40% of PM10, 44% of PM2.5, 51% of NO2 and 21% of SO2. There was a significant difference between the levels of all the pollutants before and after the lockdown (p < 0.05), except ozone. The correlation between PM10 and PM2.5 with ozone was significant after the lockdown period, indicating that a significant portion of the particulates present in the atmosphere after the lockdown period is secondary. The values of PM2.5/PM10 were found to be >0.5 in North East states and this observation points to the long-distance transport of PM2.5 from other places. The survey for public perception showed that 60% of the respondents perceived improvement in air quality. Household emissions were perceived to be a significant source of pollution after the lockdown. An odds ratio (OR) of 17 (95%, CI: 6.42, 47.04) indicated a very high dependence of perception on actual air quality. OR between air quality and health improvement was 5.2 (95%, CI: 2.69, 10.01), indicating significant health improvement due to air quality improvement. Google Trends analysis showed that media did not influence shaping the perception. There was a significant improvement in the actual and perceived air quality in India after the COVID-19-induced lockdown. PM10 levels had the most decisive influence in shaping public perception.

How Does COVID-19 Lockdown Impact Air Quality in India?

Air pollution is a severe environmental problem in the Indian subcontinent. Largely caused by the rapid growth of the population, industrialization, and urbanization, air pollution can adversely affect human health and environment. To mitigate such adverse impacts, the Indian government launched the National Clean Air Programme (NCAP) in January 2019. Meanwhile, the unexpected city-lockdown due to the COVID-19 pandemic in March 2020 in India greatly reduced human activities and thus anthropogenic emissions of gaseous and aerosol pollutants. The NCAP and the lockdown could provide an ideal field experiment for quantifying the extent to which various levels of human activity reduction impact air quality in the Indian subcontinent. Here, we study the improvement in air quality due to COVID-19 and the NCAP in the India subcontinent by employing multiple satellite products and surface observations. Satellite data shows significant reductions in nitrogen dioxide (NO2) by 17% and aerosol optical depth (AOD) by 20% during the 2020 lockdown with reference to the mean levels between 2005–2019. No persistent reduction in NO2 nor AOD is detectable during the NCAP period (2019). Surface observations show consistent reductions in PM2.5 and NO2 during the 2020 lockdown in seven cities across the Indian subcontinent, except Mumbai in Central India. The increase in relative humidity and the decrease in the planetary boundary layer also play an important role in influencing air quality during the 2020 lockdown. With the decrease in aerosols during the lockdown, net radiation fluxes show positive anomalies at the surface and negative anomalies at the top of the atmosphere over most parts of the Indian subcontinent. The results of this study could provide valuable information for policymakers in South Asia to adjust the scientific measures proposed in the NCAP for efficient air pollution mitigation.

Nationwide CoViD-19 lockdown impact on air quality in India

This paper discusses the comparative results of surface and satellite measurements made during the Phase1 (25 March to 14 April), Phase2 (15 April to 3 May) and Phase3 (3 May to 17May) of Covid-19 imposed lockdown periods of 2020 and those of the same locations and periods during 2019 over India. These comparative analyses are performed for Indian states and Tier 1 megacities where economic activities have been severely affected with the nationwide lockdown. The focus is on changes in the surface concentration of sulfur dioxide (SO2), carbon monoxide (CO), PM2.5 and PM10, Ozone (O3), Nitrogen dioxide (NO2) and retrieved columnar NO2 from TROPOMI and Aerosol Optical Depth (AOD) from MODIS satellite. Surface concentrations of PM2.5 were reduced by 30.59%, 31.64% and 37.06%, PM10 by 40.64%, 44.95% and 46.58%, SO2 by 16.73%, 12.13% and 6.71%, columnar NO2 by 46.34%, 45.82% and 39.58% and CO by 45.08%, 41.51% and 60.45% during lockdown periods of Phase1, Phase2 and Phase3 respectively as compared to those of 2019 periods over India. During 1st phase of lockdown, model simulated PM2.5 shows overestimations to those of observed PM2.5 mass concentrations. The model underestimates the PM2.5 to those of without reduction before lockdown and 1st phase of lockdown periods. The reduction in emissions of PM2.5, PM10, CO and columnar NO2 are discussed with the surface transportation mobility maps during the study periods. Reduction in the emissions based on the observed reduction in the surface mobility data, the model showed excellent skills in capturing the observed PM2.5 concentrations. Nevertheless, during the 1st &amp; 3rd phases of lockdown periods AOD reduced by 5 to 40%. Surface O3 was increased by 1.52% and 5.91% during 1st and 3rd Phases of lockdown periods respectively, while decreased by -8.29% during 2nd Phase of lockdown period.

Revisiting air quality during lockdown persuaded by second surge of COVID-19 of megacity Delhi, India

Is the impact of city-scale lockdown in response to 2nd surge of COVID-19, behavioural changes in people owing to yearlong cohabitation with COVID-19, and partial vaccination on air quality different from the impact of nationwide lockdown during COVID-19's 1st surge in March 2020? Targeting this objective, the present work has selected four phases pre-lockdown and lockdown of 1st and 2nd cycles of lockdown taking average air quality index (NAQI) from Central Pollution Control Board (CPCB). The results clearly show that both the nationwide lockdown and the city-scale restriction are responsible for improving air quality in India's megacity Delhi, but the rate of improvement was higher (39%) during the first cycle of lockdown (nationwide) than during the second cycle of lockdown (city-scale). During city-scale lockdown, the disparity in NAQI between the core and the periphery is obvious. Due to the effect of economic activities surrounding Delhi, around 10 km of the city's interior has experienced high NAQI. The reason for the lower NAQI improvement during the second lockdown cycle is likely due to relief from initial fear following a year of cohabitation with COVID-19, partial vaccination, and partial relaxation in industrial sectors to avoid the economic hardships experienced during the first lockdown cycle.

Effect of Atmospheric Aerosol Particles and Pollutants on Regional Air Quality: A Review in Reference to Chhattisgarh State of India

Poor air quality in India is considered as one of the critical issues resulting largely by industrial emissions, burning of agricultural wastes, automobile emissions etc. Also, particularly in north India, a practice of crop residue burning is followed particularly in autumn and winter months as a low cost alternative to mechanical tilling. This results in large amount of smoke, smog and particulate matter thereby impacting the air quality of nearby regions. So far as the emission of greenhouse gases is concerned, India ranks low however is the third largest emitter of particulate matter only behind China and United States. This article reviews the air quality of Chhattisgarh in India, an important industrial state, effect of poor air quality and presence of aerosols.

Short-term environmental impact of ambient air quality trends in during the COVID-19 pandemic in India

The lockdown, implemented in response to the COVID-19 epidemic, restricted the operation of various sectors in the country and its highlights a good environmental outcome. Thus, a comparison of air pollutants in India before and after the imposed lockdown indicated an overall improvement air quality across major Indian cities. This was established by utilizing the Central Pollution Control Board’s database of air quality monitoring station statistics, such as air quality patterns. During the COVID-19 epidemic, India’s pre-to-post nationwide lockdown was examined. The air quality data was collected from 30-12-2019 to 28-04-2020 and synthesized using 231 Automatic air quality monitoring stations in a major Indian metropolis. Specifically, air pollutant concentrations, temperature, and relative humidity variation during COVID-19 pandemic pre-to-post lockdown variation in India were monitored. As an outcome, several cities around the country have reported improved air quality. Generally, the air quality, on a categorical scale was found to be ‘Good’. However, a few cities from the North-eastern part of India were categorized as ‘Moderate/Satisfactory’. Overall, the particulate matters reduction was in around 60% and other gaseous pollutants was in 40% reduction was observed during the lockdown period. The results of this study include an analysis of air quality data derived from continuous air quality monitoring stations from the pre-lockdown to post-lockdown period. Air quality in India improved following the national lockdown, the interpretation of trends for PM 2.5, PM 10, SO2, NO2, and the Air Quality Index has been provided in studies for major cities across India, including Delhi, Gurugram, Noida, Mumbai, Kolkata, Bengaluru, Patna, and others.

Impact of Lockdown on Air Quality in India

The Covid-19 crisis has forced activity freezes, Lockdowns and calls to shelter-in-place have closed schools and non -essential businesses. Minimal activities from industrial sites, factories and construction sectors have minimized the risks for toxins to escape, in turn improving air quality. People are forced to stay at home practicing social distancing and working remotely. It is all aimed at controlling the spread of Covid-19 and hopefully reducing the death toll. But all this change has also led to some unexpected consequences. One among them is pollution levels and the natural environment. Before the start of the Covid-19 pandemic, the air around us had been deemed very toxic to breathe in due to the number of greenhouse gases that had been emitted over the centuries. But after the coronavirus lockdown commenced, there were slight changes in the environment. In the above context, a study should be undertaken to analyze the air quality indicators during non-lockdown period and the lockdown period is inevitable and essential. In this regard, the researcher wants to analyze the air quality of Chennai City by comparing the air quality indicators values like P.M.2.5, NO2, SO2, CO for the year 2019 with 2020 (same period). Accordingly, the researcher has collected data information and analysed it with the help of regression analysis and trend lines. The results revealed that during the lockdown period, everything was shut down and it would decrease the values of the above said air quality indicators, especially the concentration of P.M.2.5 because it is the major factor contributing to air pollution. It was proved by many earlier studies and this study also proved the same. The data set revealed that nearly 80 percent of the air pollution was due to the concentration of P.M.2.5 and its concentration was lowered during the lockdown period. Hence, to avoid air pollution, authorities should be taken steps to reduce P.M.2.5 concentration. It is good for the environment, the health of the living organism and the sustainable development of the economy.

COVID-19 slowdown induced improvement in air quality in India: rapid assessment using Sentinel-5P TROPOMI data

The COVID-19 lock/slow down affected humanity and livelihood, while it showed some positive effects on the environment with improvement in air quality indicators. Though many studies published after COVID-19 first phase lockdown observed reduction in pollutants over India, no studies yet compared the air quality indicators over the two lock/slow down windows during 2020–2021. This study reports results of rapid assessment of seven air quality indicators such as Nitrogen dioxide (NO2), Sulphur dioxide (SO2), Formaldehyde (HCHO), Methane (CH4), Carbon monoxide (CO), Aerosol (Ultraviolet Aerosol Index, UVAI), and Ozone (O3) for the past three years on monthly time scale using TROPOMI (Tropospheric Monitoring Instrument) data on GEE (Google Earth Engine) platform over India, with focus on the Gangetic plain, an air pollution hotspot. Significant reduction in NO2, SO2, HCHO and Absorbing Aerosol Index (AAI) was observed during March–May 2020 as compared to the same period in 2019, while the levels of NO2, SO2, HCHO and CO increased significantly in 2021 compared to March–May 2020. This suggests that COVID-19 lock/slow down in 2020 played a significant role in improving air quality indicators, while the relaxation in 2021 has led to detoriation, compared to 2020. The pyrogenic (forest fire and slash and burn agriculture) and agricultural (wet crop) sources were identified to contaminate the expression of slow/lock down effects on air quality indicators such as HCHO, CO and CH4 over India.

PM&amp;lt;sub&amp;gt;1&amp;lt;/sub&amp;gt; composition and source apportionment at two sites in Delhi, India, across multiple seasons

Abstract. Air pollution in urban environments has been shown to have a negative impact on air quality and human health, particularly in megacities. Over recent decades, Delhi, India, has suffered high atmospheric pollution, with significant particulate matter (PM) concentrations as a result of anthropogenic activities. Organic aerosols (OAs) are composed of thousands of different chemical species and are one of the main constituents of submicron particles. However, quantitative knowledge of OA composition, their sources and their processes in urban environments is still limited. This is important particularly in India, as Delhi is a massive, inhomogeneous conurbation, where we would expect the apportionment and concentrations to vary depending on where in Delhi the measurements/source apportionment is performed, indicating the need for multisite measurements. This study presents the first multisite analysis carried out in India over different seasons, with a focus on identifying OA sources. The measurements were taken during 2018 at two sites in Delhi, India. One site was located at the India Meteorological Department, New Delhi (ND). The other site was located at the Indira Gandhi Delhi Technical University for Women, Old Delhi (OD). Non-refractory submicron aerosol (NR-PM1) concentrations (ammonium, nitrate, sulfate, chloride and organic aerosols) of four aerosol mass spectrometers were analysed. Collocated measurements of volatile organic compounds, black carbon, NOx and CO were performed. Positive matrix factorisation (PMF) analysis was performed to separate the organic fraction, identifying a number of conventional factors: hydrocarbon-like OAs (HOAs) related to traffic emissions, biomass burning OAs (BBOAs), cooking OAs (COAs) and secondary OAs (SOAs). A composition-based estimate of PM1 is defined by combining black carbon (BC) and NR-PM1 (C-PM1= BC + NR-PM1). No significant difference was observed in C-PM1 concentrations between sites, OD (142 ± 117 µg m−3) compared to ND (123 ± 71 µg m3), from post-monsoon measurements. A wider variability was observed between seasons, where pre-monsoon and monsoon showed C-PM1 concentrations lower than 60 µg m−3. A seasonal variation in C-PM1 composition was observed; SO42- showed a high contribution over pre-monsoon and monsoon seasons, while NO3- and Cl− had a higher contribution in winter and post-monsoon. The main primary aerosol source was from traffic, which is consistent with the PMF analysis and Aethalometer model analysis. Thus, in order to reduce PM1 concentrations in Delhi through local emission controls, traffic emission control offers the greatest opportunity. PMF–aerosol mass spectrometer (AMS) mass spectra will help to improve future aerosol source apportionment studies. The information generated in this study increases our understanding of PM1 composition and OA sources in Delhi, India. Furthermore, the scientific findings provide significant information to strengthen legislation that aims to improve air quality in India.

Weather indicators and improving air quality in association with COVID-19 pandemic in India.

The COVID-19 pandemic enforced nationwide lockdown, which has restricted human activities from March 24 to May 3, 2020, resulted in an improved air quality across India. The present research investigates the connection between COVID-19 pandemic-imposed lockdown and its relation to the present air quality in India; besides, relationship between climate variables and daily new affected cases of Coronavirus and mortality in India during the this period has also been examined. The selected seven air quality pollutant parameters (PM10, PM2.5, CO, NO2, SO2, NH3, and O3) at 223 monitoring stations and temperature recorded in New Delhi were used to investigate the spatial pattern of air quality throughout the lockdown. The results showed that the air quality has improved across the country and average temperature and maximum temperature were connected to the outbreak of the COVID-19 pandemic. This outcomes indicates that there is no such relation between climatic parameters and outbreak and its associated mortality. This study will assist the policy maker, researcher, urban planner, and health expert to make suitable strategies against the spreading of COVID-19 in India and abroad.Supplementary InformationThe online version contains supplementary material available at 10.1007/s00500-021-06012-9.

Impact of reduced anthropogenic emissions during COVID-19 on air quality in India

Abstract. To mitigate the impacts of the pandemic of coronavirus disease 2019 (COVID-19), the Indian government implemented lockdown measures on 24 March 2020, which prohibited unnecessary anthropogenic activities, thus leading to a significant reduction in emissions. To investigate the impacts of this lockdown measure on air quality in India, we used the Community Multi-Scale Air Quality (CMAQ) model to estimate the changes of key air pollutants. From pre-lockdown to lockdown periods, improved air quality is observed in India, indicated by the lower key pollutant levels such as PM2.5 (−26 %), maximum daily 8 h average ozone (MDA8 O3) (−11 %), NO2 (−50 %), and SO2 (−14 %). In addition, changes in these pollutants show distinct spatial variations with the more important decrease in northern and western India. During the lockdown, our results illustrate that such emission reductions play a positive role in the improvement of air quality. Significant reductions of PM2.5 concentration and its major components are predicted, especially for secondary inorganic aerosols that are up to 92 %, 57 %, and 79 % for nitrate (NO3-), sulfate (SO42-), and ammonium (NH4+), respectively. On average, the MDA8 O3 also decreases 15 % during the lockdown period although it increases slightly in some VOC-limited urban locations, which is mainly due to the more significant reduction of NOx than VOCs. More aggressive and localized emission control strategies should be implemented in India to mitigate air pollution in the future.