Critical air pollutant assessments and health effects attributed to PM2.5 during and after COVID-19 lockdowns in Iran: application of AirQ+ models.

Objectives: The aim of this study was to evaluate changes in air quality index (AQI) values before, during, and after lockdown, as well as to evaluate the number of hospitalizations due to respiratory and cardiovascular diseases attributed to atmospheric PM2.5 pollution in Semnan, Iran in the period from 2019 to 2021 during the COVID-19 pandemic. Methods: Daily air quality records were obtained from the global air quality index project and the US Environmental Protection Administration (EPA). In this research, the AirQ+ model was used to quantify health consequences attributed to particulate matter with an aerodynamic diameter of <2.5 µm (PM2.5). Results: The results of this study showed positive correlations between air pollution levels and reductions in pollutant levels during and after the lockdown. PM2.5 was the critical pollutant for most days of the year, as its AQI was the highest among the four investigated pollutants on most days. Mortality rates from chronic obstructive pulmonary disease (COPD) attributed to PM2.5 in 2019-2021 were 25.18% in 2019, 22.55% in 2020, and 22.12% in 2021. Mortality rates and hospital admissions due to cardiovascular and respiratory diseases decreased during the lockdown. The results showed a significant decrease in the percentage of days with unhealthy air quality in short-term lockdowns in Semnan, Iran with moderate air pollution. Natural mortality (due to all-natural causes) and other mortalities related to COPD, ischemic heart disease (IHD), lung cancer (LC), and stroke attributed to PM2.5 in 2019-2021 decreased. Conclusion: Our results support the general finding that anthropogenic activities cause significant health threats, which were paradoxically revealed during a global health crisis/challenge.

Effects of Precipitation on the Air Quality Index, PM2.5 Levels and on the Dry Deposition of PCDD/Fs in the Ambient Air

The effects of 9 precipitation events in Suzhou City in Anhui Province, China, on the air quality index (AQI), PM2.5, and dry deposition flux of PCDD/Fs (polydibenzo-p-dioxins and polydibenzofurans) were investigated. A total of 7 precipitation events were positive contributes to the reduction of AQI;among them, the AQI were between 23 and 216, with an average of 75, the PM2.5 concentrations were between 5.0 and 169 mu g m-3, with an average of 25 mu g m-3, while the total-PCDD/F-TEQ dry deposition flux ranged from 149 to 1034 pg WHO2005-TEQ m-2 day-1 and averaged 315 pg WHO2005-TEQ m-2 day-1. By comparing the average AQI and PM2.5, respectively, during and after rainfall with that before rainfall, the results indicated that the average reduction fractions of AQI were 26% and 44%, respectively, while those of PM2.5 were 58% and 43%. In addition, the effect of precipitation on the average reduction fraction of total PCDD/F-TEQ dry deposition flux was 31%. However, in the other 2 AQI elevation events, the AQI were between 23 and 100, and averaged 51;when comparing the average AQI and PM2.5 concentrations, during and after the rain with that before the rain, the increases in AQI were 42% and 49%, respectively, while the increases in PM2.5 concentration were 26% and 29%, respectively. The above results show that, on the whole, rain and snow improved the air quality. This is because rainwater removes particles or dissolved gaseous pollutants from the atmosphere and brings aerosols to the ground. However, in some cases, the increase of source emissions and atmospheric vertical convection, the effect of precipitation or air humidity increased the AQI and elevated the concentration of PM2.5, and dry deposition flux of PCDD/Fs. The results of this study provide useful information for both scientific communities and air quality management.

Air pollution and its associated health risks before and after COVID-19 in Shaanxi Province, China.

Air pollution is a serious environmental problem that damages public health. In the present study, we used the segmentation function to improve the health risk-based air quality index (HAQI) and named it new HAQI (NHAQI). To investigate the spatiotemporal distribution characteristics of air pollutants and the associated health risks in Shaanxi Province before (Period I, 2015-2019) and after (Period II, 2020-2021) COVID-19. The six criteria pollutants were analyzed between January 1, 2015, and December 31, 2021, using the air quality index (AQI), aggregate AQI (AAQI), and NHAQI. The results showed that compared with AAQI and NHAQI, AQI underestimated the combined effects of multiple pollutants. The average concentrations of the six criteria pollutants were lower in Period II than in Period I due to reductions in anthropogenic emissions, with the concentrations of PM2.5 (particulate matter ≤2.5 µm diameter), PM10 (PM ≤ 10 µm diameter) SO2, NO2, O3, and CO decreased by 23.5%, 22.5%, 45.7%, 17.6%, 2.9%, and 41.6%, respectively. In Period II, the excess risk and the number of air pollution-related deaths decreased considerably by 46.5% and 49%, respectively. The cumulative population distribution estimated using the NHAQI revealed that 61% of the total number of individuals in Shaanxi Province were exposed to unhealthy air during Period I, whereas this proportion decreased to 16% during Period II. Although overall air quality exhibited substantial improvements, the associated health risks in winter remained high.

Statistical assessment of COVID-19 lockdowns on ambient air quality, Himachal Pradesh and learnings for implementing clean technologies: insight from industrial town, India

PurposeThe current study investigates the impact of the coronavirus disease 2019 (COVID-19) lockdown restrictions on air quality in an industrial town in Himachal Pradesh (HP) (India) and recommends policies and strategies for mitigating air pollution.Design/methodology/approachThe air quality parameters under study are particulate matter10 (PM10), PM2.5, SO2 and NO2. One-way ANOVA with post-hoc analysis and non-parametric Kruskal–Wallis test, and multiple linear regression analysis are used to validate the data analysis results.FindingsThe findings indicate that the lockdown and post-lockdown periods affected pollutant levels even after considering the meteorological conditions. Except for SO2, all other air quality parameters dropped significantly throughout the lockdown period. Further, the industrial and transportation sectors are the primary sources of air pollution in Paonta Sahib.Research limitations/implicationsFuture research should include other industrial locations in the state to understand the relationship between regional air pollution levels and climate change. The findings of this study may add to the discussion on the role of adopting clean technologies and also provide directions for future research on improving air quality in the emerging industrial towns in India.Originality/valueVery few studies have examined how the pandemic-induced lockdowns impacted air pollution levels in emerging industrial towns in India while also considering the confounding meteorological factors.Graphical abstract

Impact of ambient air pollution on physical activity and sedentary behavior in children.

BACKGROUND: Exposure to air pollution has become a serious environmental issue affecting children's health and health-related behavior in China. Previous studies have focused on the associations between air pollution and physical activity among adults; however, few have examined the relationship between air pollution and health-related behavior among children, which are particularly susceptible population subgroups. The present study aims to examine the impact of air pollution on daily physical activity (PA) and sedentary behavior (SB) among children in China. METHODS: PA and SB data were collected by actiGraph accelerometers for eight consecutive days. PA and SB data from 206 children were matched to daily air pollution obtained from the Ministry of Environmental Protection of the People's Republic of China, including the average daily air quality index (AQI), PM2.5 (µg/m³), and PM10 (µg/m³). Associations were estimated using linear individual fixed-effect regressions. RESULTS: A 10-unit increase in daily AQI was associated with a reduction in daily PA by 5.94 (95% confidence interval [CI] = -8.79, -3.08) minutes of moderate to vigorous physical activity (MVPA) and 229.82 (95% CI = -345.35, -114.28) walking steps and an increase in daily SB by 15.77 (95% CI = 9.01, 22.53) minutes. A 10 µg/m³ increase in air pollution concentration in daily PM2.5 was associated with a reduction in daily PA by 7.51 (95% CI = -11.04, -3.97) minutes of MVPA, 295.69 (95% CI = -438.46, -152.92) walking steps and an increase in daily SB by 21.12 (95% CI = 12.77, 29.47) minutes. A 10 µg/m³ increase in air pollution concentration in daily PM10 was associated with a reduction in daily PA by 13.18 (95% confidence interval [CI] = -15.98, -10.37) minutes of MVPA, 518.34 (95% CI = -631.77, -404.91) walking steps and an increase in daily SB by 19.87 (95% CI = 13.10, 26.64) minutes. CONCLUSION: Air pollution may discourage physical activity and increase sedentary behavior among children. Policy interventions are needed to reduce air pollution and develop strategies to decrease risks to children's health.

Association of the corona virus (Covid-19) epidemic with environmental risk factors.

The current outbreak of the novel coronavirus SARS-CoV-2 (coronavirus disease 2019; previously 2019-nCoV), epicenter in Hubei Province (Wuhan), People's Republic of China, has spread too many other countries. The transmission of the corona virus occurs when people are in the incubation stage and do not have any symptoms. Therefore, the role of environmental factors such as temperature and wind speed becomes very important. The study of Acute Respiratory Syndrome (SARS) indicates that there is a significant relationship between temperature and virus transmission and three important factors, namely temperature, humidity and wind speed, cause SARS transmission. Daily data on the incidence and mortality of Covid-19 disease were collected from World Health Organization (WHO) website and World Meter website (WMW) for several major cities in Iran and the world. Data were collected from February 2020 to September 2021. Meteorological data including temperature, air pressure, wind speed, dew point and air quality index (AQI) index are extracted from the website of the World Meteorological Organization (WMO), The National Aeronautics and Space Administration (NASA) and the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor. Statistical analysis carried out for significance relationships. The correlation coefficient between the number of infected people in one day and the environmental variables in the countries was different from each other. The relationship between AQI and number of infected was significant in all cities. In Canberra, Madrid and Paris, a significant inverse relationship was observed between the number of infected people in one day and wind speed. There is a significant positive relationship between the number of infected people in a day and the dew point in the cities of Canberra, Wellington and Washington. The relationship between the number of infected people in one day and Pressure was significantly reversed in Madrid and Washington, but positive in Canberra, Brasilia, Paris and Wuhan. There was significant relationship between Dew point and prevalence. Wind speed showed a significant relationship in USA, Madrid and Paris. AQI was strongly associated with the prevalence of covid19. The purpose of this study is to investigate some environmental factors in the transmission of the corona virus.

On the transition of major pollutant and O3 production regime during Covid-19 lockdowns.

Lockdowns enforced amid the pandemic facilitated the evaluation of the impact of emission reductions on air quality and the production regime of O3 under NOx reduction. Analysis of space-time variation of various pollutants (PM10, PM2.5, NOx, CO, O3 and VOC or TNMHC) through the lockdown phases at eight typical stations (Urban/Metro, Rural/high vegetation and coastal) is carried out. It reveals how the major pollutant (PM10 or PM2.5 or O3, or CO) differs from station to station as lockdowns progress depending on geography, land-use pattern and efficacy of lockdown implementation. Among the stations analyzed, Delhi (Chandnichowk), the most polluted (PM10 = 203 µgm-3; O3 = 17.4 ppbv) in pre-lockdown, experienced maximum reduction during the first phase of lockdown in PM2.5 (-47%), NO2 (-40%), CO (-37%) while O3 remained almost the same (2% reduction) to pre-lockdown levels. The least polluted Mahabaleshwar (PM10 = 45 µgm-3; O3 = 54 ppbv) witnessed relatively less reduction in PM2.5 (-2.9%), NO2 (-4.7%), CO (-49%) while O3 increased by 36% to pre-lockdown levels. In rural stations with lots of greenery, O3 is the major pollutant attributed to biogenic VOC emissions from vegetation besides lower NO levels. In other stations, PM2.5 or PM10 is the primary pollutant. At Chennai, Jabalpur, Mahabaleshwar and Goa, the deciding factor of Air Quality Index (AQI) remained unchanged, with reduced values. Particulate matter, PM10 decided AQI for three stations (dust as control component), and PM2.5 decided the same for two but within acceptable limits for stations. Improvement of AQI through control of dust would prove beneficial for Chennai and Patiala; anthropogenic emission control would work for Chandani chowk, Goa and Patiala; emission control of CO is required for Mahabaleshwar and Thiruvanathapuram. Under low VOC/NOx ratio conditions, O3 varies with the ratio, NO/NO2, with a negative (positive) slope indicating VOC-sensitive (NOx-sensitive) regime. Peak O3 isopleths as a function of NOx and VOC depicting distinct patterns suggest that O3 variation is entirely non-linear for a given NOx or VOC.

Improving Urban Air Quality Monitoring in Delhi, India: Reflections on Low-Cost Air Quality Sensors (LCAQS) and Participatory Engagement

In Delhi, the capital city of India, air pollution has been a perpetual menace to urban sustainability and public health. The present study uses a mixed-method approach to enumerate to the urban authorities: (a) the state of air pollution in the city;(b) systemic flaws in the current monitoring network;(c) potential means to bolster it;and (d) need of a participatory framework for monitoring. Information about Air Quality Index (AQI), obtained from 36 monitoring stations across Delhi is compared between 2021 (20 April–25 May;2nd year/phase of SARS-CoV-2 lockdown), and the corresponding time periods in 2020 (1st year/phase of lockdown), and 2019 (business-as-usual) using the Mann–Whitney U Test. AQI during the 2021 lockdown (a) appeared statistically more similar (p <.01) to that of 2019 and (b) exceeded the environmental health safety benchmark for 85% days during the study period (20 April–25 May). However, this only presented a partial glimpse into the air pollution status. It owes to numerous ‘holes’ in the AQI data record (no data and/or insufficient data). Moreover, certain areas in Delhi yet have no monitoring station, or only too few, to yield a ‘representative’ estimate (inadequate spatial coverage). Such shortcomings in the existing monitoring network may deter future research and targeted/informed decision-making for pollution control. To that end, the present research offers a summary view of Low-Cost Air Quality Sensors (LCAQS), to offer the urban sustainability authorities, ‘complementary’ technique to bolster and diversify the existing network. The main advantages and disadvantages of various LCAQS sensor technologies are highlighted while emphasizing on the challenges around various calibration techniques (linear and non-linear). The final section reflects on the integration of science and technology with social dimensions of air quality monitoring and highlights key requirements for (a) community mobilization and (b) stakeholder engagement to forge a participatory systems’ design for LCAQS deployment. © 2022 National Institute of Urban Affairs.

Spatio-temporal analysis of air quality and its relationship with COVID-19 lockdown over Dublin.

Air pollution has become one of the biggest challenges for human and environmental health. Major pollutants such as Nitrogen Dioxide (NO 2 ), Sulphur Dioxide (SO 2 ), Ozone (O 3 ), Carbon Monoxide (CO), and Particulate matter (PM10 and PM2.5) are being ejected in a large quantity every day. Initially, authorities did not implement the strictest mitigation policies due to pressures of balancing the economic needs of people and public safety. Still, after realizing the effect of the COVID-19 pandemic, countries around the world imposed a complete lockdown to contain the outbreak, which had the unexpected benefit of causing a drastic improvement in air quality. The present study investigates the air pollution scenarios over the Dublin city through satellites (Sentinel-5P and Moderate Resolution Imaging Spectroradiometer) and ground-based observations. An average of 28% reduction in average NO 2 level and a 27.7% improvement in AQI (Air Quality Index) was experienced in 2020 compared to 2019 during the lockdown period (27 March-05 June). We found that PM10 and PM2.5 are the most dominating factor in the AQI over Dublin.

Environmental Factors Affecting Covid-19 Dynamics: A Study in Bengaluru City of Karnataka State of India.

The horrifying and fast spreading COVID-19 pandemic has shocked India and in fact the entire world to its core. Indian Government has taken all the possible preventive steps to contain the wider spread of this highly contagious disease but the second wave in the month of April, 2021 has turned this strong country in a helpless position. In this paper, the effect of environmental factors like temperature and air quality index on the new confirmed cases along with recovered cases has been seen in Bengaluru Urban district of Karnataka State of India. Regression analysis has been carried out with the help of SPSS software. The outcomes from the paper will definitely give some valuable insights for the researchers around the world in their future combat measures.

Statistical assessment of COVID-19 lockdowns on ambient air quality, Himachal Pradesh and learnings for implementing clean technologies: insight from industrial town, India

Purpose - The current study investigates the impact of the coronavirus disease 2019 (COVID-19) lockdown restrictions on air quality in an industrial town in Himachal Pradesh (HP) (India) and recommends policies and strategies for mitigating air pollution. Design/methodology/approach - The air quality parameters under study are particulate matter(10) (PM10), PM2.5, SO2 and NO2. One-way ANOVA with post-hoc analysis and non-parametric Kruskal-Wallis test, and multiple linear regression analysis are used to validate the data analysis results. Findings - The findings indicate that the lockdown and post-lockdown periods affected pollutant levels even after considering the meteorological conditions. Except for SO2, all other air quality parameters dropped significantly throughout the lockdown period. Further, the industrial and transportation sectors are the primary sources of air pollution in Paonta Sahib. Research limitations/implications - Future research should include other industrial locations in the state to understand the relationship between regional air pollution levels and climate change. The findings of this study may add to the discussion on the role of adopting clean technologies and also provide directions for future research on improving air quality in the emerging industrial towns in India. Originality/value - Very few studies have examined how the pandemic-induced lockdowns impacted air pollution levels in emerging industrial towns in India while also considering the confounding meteorological factors. [GRAPHICS] .

Air Quality Decrement after Lockdown in Major Cities of Rajasthan, India

The lockdown restrictions during the COVID-19 pandemic provided a 'path' of reinstatement of the air quality globally. Despite several financial challenges, air quality improvement positively impacted the environment due to lockdown in the worst pandemic situations. The present study assessed the air pollution scenario in the post lockdown phase in the seven major metropolises of Rajasthan, namely, Jodhpur, Alwar, Jaipur, Kota, Pali, Ajmer, and Udaipur) in the recent pandemic year 2020. The air pollution scenario is determined with the help of the Air Quality Index (AQI) and the concentration level of PM2.5 PM10, NO2, and SO2. This study reveals that Most Cities of Rajasthan are violating India's national ambient air quality standards (NAAQS). It is found that Jodhpur is on rank first in terms of pollution levels, followed by Alwar, Jaipur, Pali, and Udaipur. The pollution level was higher before the lockdown period then reduced to a certain level due to restricted activities in lockdown. The pollution level is not rapidly increased after lockdown due to rainfall occurred in Rainy season from Southwest monsoon. Winter Season consists of higher concentration levels of pollutant and higher than Before Lockdown Period. The study shows the Significant impact of lockdown in reducing air pollution levels in cities. But imposing lockdown in a city or country is not a permanent solution to curb air pollution. So, regulating agencies and stakeholders should implement better control and reduction technologies for Indian cities. © The Electrochemical Society

Methodical Approach to Inactivate Any Microbial Element like SARS-CoV2.

The proposed paper discusses Far UVC could assassinate microbes without harming healthy tissues. The plasma ion generation will increase the ion (O2 -) generation in abundance along with hydrogen ion (H+), and at the same time, the negative hydroxyl radical (OH-) formed will merge with the positive (H+) ion of the virus to break the structure of it. The silver nanoparticle which is present in the diffuser with thermostat support is very effective for destroying the microbial elements by heating the gel present within the diffuser. The gel will mix in the environment, and it will also increase the activity of T cell generation and act as an immunoglobulin booster in the human body while inhaling it. In the proposed device, we are using warm humidified CO2 strategic therapy in low dose which is able to suppress any microbial element like SARS-CoV2.

The Contribution of Meteorological Parameters and the COVID-19 Partial Lockdown on Air Quality in Rio de Janeiro, Brazil

This study evaluated the pollutant levels (NO2, SO2, CO, and O-3), air quality index (AQI) and the influence of meteorological variables and coronavirus disease (COVID-19) pandemic on the air quality in Rio de Janeiro. The data set used comprises periods before (March-April, 2019) and during pandemic (March-April, 2020). According to the AQI results, on most days, the air quality was ranked as "good". Brazilian air quality standards for SO2, O-3, and NO2 were not exceeded in any of the monitoring stations during partial lockdown, while CO exceeded in all periods in one site due to industrial emission. Comparing both periods, descriptive statistics for the meteorological parameters presented no differences, which suggests similar conditions. However, when evaluated week by week in 2020, weather conditions presented some differences that probably affected pollutant concentrations. The correlations between O-3 and NO2 and some meteorological parameters indicate that variations in both favored ozone formation, since it is a photochemical process favored by temperature and solar radiation and that, in Rio de Janeiro, low NO2 concentrations lead to increased O-3. The improvements on air quality during the partial lockdown may be attributed mainly to a reduction on emission sources rather than weather conditions.

A concise air quality study on impact of COVID-19 lockdown for two industrial cities of Chhattisgarh

‘Good Outcomes from evil situation’ this phrase perfectly fits into the COVID-19 circumstances as several restrictions on anthropogenic activities provided an improvement in the ambient air quality status globally. The study deals with the consequences of COVID-19 lockdown on ambient air quality for 2 major industrial cities ( Raipur and Bilaspur) in Central Indian state Chhattisgarh moreover a comparison of air quality data was made with non-lockdown year (2019). The AQI and critical parameters (such as PM10, PM2.5, SO2 and NOx) were acquired form online available source and then analysed for the study period (2019 and 2020). Noteworthy reduction in AQI and concentration of pollutants in Raipur was detected whereas there was reduction in Bilaspur but it was less than Raipur. Evident changes in the level of pollutants (NOx and PM) were observed during the study. Meteorological parameters such as temperature and relative humidity were also examined for Raipur. Statistical analysis between data of meteorological parameters and AQI for capital city Raipur was also carried out.

Assessment of air quality index (AQI) in Riyadh, Saudi Arabia

Air pollution is increasingly becoming a main environmental matter in the world. It can impact public health, weather, and climate. Riyadh's air pollution poses significant environmental and health risks. The study aimed to analyze Riyadh's current and future air quality by using AQI. Main six air pollutants are considered, nitrogen dioxide (NO2), sulfur dioxide (SO2), particulate matter (PM), ground level ozone (O3), and carbon dioxide (CO2), carbon monoxide (CO). Eleven air quality stations located throughout Riyadh assess the concentration of six standard pollutants daily. A comparison of air quality in Riyadh was done at the local, regional, and international levels. Furthermore, diverse factors such as meteorological seasons, working periods, and the COVID-19 period are taken into account. Industrial emissions, as well as contributions from mobile sources and wind-blown dust, appear to be the principal pollutant sources affecting Riyadh. The measured air quality components for all contaminants were found to be below standard. PM poses the greatest damage to the city's human health of all the pollutants studied. It can be found in practically all locations of air quality stations, even though CO and O3 levels in the city are not at alarming levels.

In the Seeking of Association between Air Pollutant and COVID-19 Confirmed Cases Using Deep Learning.

The COVID-19 pandemic raises awareness of how the fatal spreading of infectious disease impacts economic, political, and cultural sectors, which causes social implications. Across the world, strategies aimed at quickly recognizing risk factors have also helped shape public health guidelines and direct resources; however, they are challenging to analyze and predict since those events still happen. This paper intends to invesitgate the association between air pollutants and COVID-19 confirmed cases using Deep Learning. We used Delhi, India, for daily confirmed cases and air pollutant data for the dataset. We used LSTM deep learning for training the combination of COVID-19 Confirmed Case and AQI parameters over the four different lag times of 1, 3, 7, and 14 days. The finding indicates that CO is the most excellent model compared with the others, having on average, 13 RMSE values. This was followed by pressure at 15, PM2.5 at 20, NO2 at 20, and O3 at 22 error rates.

POSITIVE IMPACT ON ENVIRONMENT DUE TO COVID-19 LOCKDOWNS IN PARTS OF INDIA: A REVIEW

Due to the pandemic caused by SARS-CoV-2 (severe acute respiratory syndrome corona virus 2) commonly known as COVID-19, a nationwide lockdown came into effect in India from 24th March midnight, 2020, which slowed down the movement of vehicles, operation of industries etc. Due to this reason a drastic change in the environment occurred and it caused the reduction of pollution level in the environment. The study mainly focuses on the positive impacts of lockdown in India. Studies have shown that after the implementation of lockdown, the level of the various major air pollution constituents of such as particulate matter (PM2.5, PM10, etc.), NO2, CO and ozone etc. in the air has reduced substantially. The air quality index data have clearly shown the difference in the level of air pollution between the year 2019 and 2020. The study was mainly focused on the comparison of air quality parameters such as particulate matter, NO2, CO and ozone etc. as well as the water pollution parameters such as Biochemical oxygen demand (BOD), chemical oxygen demand (COD) and dissolved oxygen (DO) for the River Yamuna and it was observed that there was substantial amount of positive change in pollutants after lockdown compared to what was before lockdown. The observations are carried out in atime frame manner such as before lockdown and after lockdown and results have been found with a huge difference in reduction of air pollution as well as water pollution.

Analyzing the Sources of Air Pollution and Comparing Its Impact During the Phases of COVID-19 Pandemic and the Scope of IoT in Monitoring Air Quality

Air Pollution is a serious threat in the enlightened globe that impacts atmospheric change and human health. Air pollutants like Particulate Matter PM2.5, Particulate Matter PM10, ground-level ozone (O3), nitrogen dioxide (NO2), sulfur dioxide (SO2) and carbon monoxide (CO) lead to air pollution either in the form of gases or particles suspended in the air. The contemporary study aimed to analyze the source of air pollution and change in air quality during lockdown periods due to 1st and 2nd wave of COVID-19 pandemic within six different states namely, Uttar Pradesh, Madhya Pradesh, Delhi, Haryana, Rajasthan and Punjab. The selected states were analyzed in four different phases (i) Before First Covid Wave Lockdown (January 1, 2020 to March 24, 2020), (ii) During First Covid Wave Lockdown (March 25, 2020 to May 31, 2020), (iii) After First Covid Wave Lockdown (June 1, 2020 to April 19, 2021), (iv) During Second Covid Wave Lockdown (April 20, 2021 to May 26, 2021) from 45 air quality monitoring stations. This study also explains the limitations in stationary Ambient Air Monitoring Stations and the scope of IoT technology to improve the standards of monitoring air quality. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

Effect of COVID-19 on air pollution related illnesses in India.

Ambient air pollution level not only causes respiratory diseases but also cardiovascular diseases, besides, increased visits to the emergency department for asthma, chronic obstructive pulmonary disease (COPD), bronchitis, allergic rhinitis, attention deficit hyperactivity disorder (ADHD) in children and premature deaths in infants. The occurrence of Coronavirus-19 (COVID-19) pandemic is both, a boon and bane. Despite the deplorable situation aroused by the pandemic, strict lockdown measures implemented to curb the drastic spread of the disease, also culminated into astonishing outcomes that were not prioritized. This article illustrates the effects of the ongoing pandemic on air pollution and provides recommendations aimed at limiting it.