Have any effect of COVID-19 lockdown on environmental sustainability? A study from most polluted metropolitan area of India

Spatiotemporal changes in fine particulate matter and ozone in the oasis city of Korla, northeastern Tarim Basin of China

Air pollution is a serious environmental health concern for humans and other living organisms. This study analyzes the spatial and temporal characteristics of air pollutant concentrations, changes in the degree of pollution, and the wavelet coherence of the air quality index (AQI) with pollutants in various monitoring stations. The analysis is based on long-term time series data (January 2016 to December 2023) of air pollutants (PM2.5, PM10, and O3) from Korla, an oasis city in the northeastern part of the Tarim Basin, China. The concentrations of PM2.5, PM10, and O3 in Korla showed a cyclical trend from 2016 to 2023; PM10 concentrations exhibited all-season exceedance and PM2.5 exhibited exceedance only in spring. PM2.5 and PM10 showed a seasonal distribution of spring > winter > fall > summer; O3 concentrations showed a seasonal distribution of summer > spring > fall > winter. Strong positive wavelet coherence between PM and Air Quality Index (AQI) data series suggests that the AQI data series can effectively characterize fluctuating trends in PM concentrations. Moreover, PM10 levels IV and VI were maintained at approximately 10%, indicating that sand and dust have a substantial influence on air quality and pose potential threats to the health of urban inhabitants. Based on the results of this study, future efforts must strengthen relative countermeasures for sand prevention and control, select urban greening species with anti-pollution capabilities, rationally expand urban green spaces, and restrict regulations for reducing particulate matter emissions within city areas.

The Effect of the COVID-19 Pandemic on Environmental Health (Two Sides of the Same Coin): A Systematic Review

BACKGROUND

The outbreak of the COVID-19 pandemic in late 2019 has led to many changes such as reduced human activities and effects on the environment. There is no big picture of the effects of pandemics on the environment using related evidence.

OBJECTIVES

This study was conducted to investigate the effect of the COVID-19 pandemic on environmental health.

METHODS

A systematic search of English language studies was performed in major electronic databases; Web of Science, PubMed, Scopus, and Google scholar web search engine from December 2019 to February 2022. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) standard guidelines were used to follow up the review process. finally 58 articles entered the review procedure.

RESULTS

The results of indicate a significant reduction of air pollutants and improved air quality. It improved the water quality of some rivers, canals, and seas during the lockdown of the COVID-19 pandemic. The effects of this disease on the environment cannot be fully described yet.

CONCLUSION

In the short term, the amount of air, water, and coastal pollution has been reduced. few studies have examined the effects of pandemics on the environment in the long run, which paves the way for more researches.

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, PM_2.5, 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 Information

The online version contains supplementary material available at 10.1007/s00500-021-06012-9.

Assessment of air quality before and during the COVID-19 and its potential health impacts in an arid oasis city: Urumqi, China

As a key node city of the "Silk Road Economic Belt" Urumqi has been listed as one of the ten most polluted cities in the world, posing a serious threat to the urban environment and residents' health. This study analyzed the air quality before and during the COVID-19 (Coronavirus disease 2019) pandemic and its potential health effects based on the data of PM_2.5, PM₁₀, SO₂, NO₂, CO, and O₃_8h levels from 10 air quality monitoring stations in Urumqi from January 1, 2017, to December 31, 2021. As per the results, the concentrations of the air pollutants PM_2.5, PM₁₀, SO₂, NO₂, CO, and O₃_8h in Urumqi from 2017 to 2021 showed a cyclical trend, and the implementation of COVID-19 prevention and control measures could effectively reduce the concentration(ρ) of air pollutants. The mean value of ρ(PM_2.5) decreased from 2017 to 2021, whereas ρ(O₃_8h) showed a waveform change trend (increased in 2017-2018, decreased in 2018-2020, and increased after 2020). Meanwhile, the maximum annual average values of ρ(PM_2.5) and ρ(O₃_8h) for the six monitoring stations during 2017-2021 occurred at sites S2 (74.37 µg m^-3) and S6 (91.80 µg m^-3), respectively; rapid industrialization had a greater impact on PM_2.5 and O₃_8h concentrations compared to commercial and residential areas. In addition, the air quality index data series can characterize the fluctuation trend of PM_2.5. The high pollution levels (Class IV and V) of the air pollutants PM_2.5 and O₃_8h in Urumqi have been decreasing annually, and good days can account for 80-95% of the total number of days in the year, indicating that the number of days with a potential threat to residents' health is gradually decreasing. Therefore, more attention should be paid in controlling and managing air pollution in Urumqi.

Strict lockdown measures reduced PM2.5 concentrations during the COVID-19 pandemic in Kolkata, India

The COVID-19 situation is a critical state throughout the world that most countries have been forced to implement partial to total lockdown to control the COVID-19 disease outbreak. And displays the natural power to rejuvenate herself without the interference of human beings. So, the top-level emergency response including full quarantine actions are significant measures against the COVID-19 and resulted in a notable reduction in PM_2.5 in the atmosphere. India was severely attacked by COVID-19, and as a result, the Government of India has imposed a nationwide lockdown from 24th March (2020) to 30th May (2020) in different phases. The COVID-19 outbreak and lockdown had a significant negative impact on India's socioeconomic structure but had a positive impact on environmental sustainability in terms of improved air quality due to the 68 days of the shutdown of India's industrial, commercial, construction, and transportation systems. The current study looked at the spatio-temporal changes in PM_2.5 concentrations at different air quality monitoring stations (AQMS) in Kolkata during the COVID-19 period. The study revealed that the average concentration of PM_2.5 (µg/m³) was slightly high (139.82) in the pre-lockdown period which was rapidly reduced to 37.77 (72.99% reduction) during the lockdown period and it was further increased (137.11) in post-lockdown period. The study also shows that the average concentration of PM_2.5 was 66.83 in 2018, which slightly increased to 70.43 (5.39%) in 2019 and dramatically decreased to 37.77 (46.37%) in the year 2020 due to the COVID-19 outbreak and lockdown. The study clearly shows that air quality improves during lockdown periods in Kolkata, but it is not a permanent solution rather than temporary. Therefore, it is necessary to make the proper policies and strategies by policymakers and government authorities, and environmental scientists to maintain such good air quality by controlling several measures of air pollutants.

Potential hotspot modeling and monitoring of PM2.5 concentration for sustainable environmental health in Maharashtra, India

Modern human civilization has suffered from the disastrous impact of COVID-19, but it teaches us the lesson that the environment can restore its stability without human activity. The Government of India (GOI) has launched many strategies to prevent the situation of COVID-19, including a lockdown that has a great impact on the environment. The present study focuses on the analysis of Particulate Matter 2.5 (PM2.5) concentration levels in pre-locking, lockdown, and unlocking phases across ten major cities of Maharashtra (MH) that were the COVID hotspot of India during the COVID-19 outbreak; phase-wise and year-wise (2018-2020) hotspot analysis, box diagram and line graph methods were used to assess spatial variation in PM2.5 across MH cities. Our study showed that the PM2.5 concentration level was severe at pre-lockdown stage (January-March) and it decreased dramatically at the lockdown stage, later it also increased in its previous position at the unlocking stages, i.e., PM2.5 decreased dramatically (59%) during the lockdown period compared to the pre-lockdown period due to the shutdown of outdoor activities. It returns to its previous position due to the unlocking situation and increases (70%) compared to the lockdown period which illustrated the ups and downs of PM2.5 and ensures the position of different cities in the Air Quality Index (AQI) categories at different times. In the pre-lockdown phase, maximum PM2.5 concentration was in Navi Mumbai (NAV) (358) and Mumbai (MUM) (338), and Pune (PUN) (335) and Nashik NAS (325) subsequently, whereas at the last of the lockdown phase, it becomes Chandrapur (CHN) (82), Nagpur (NAG) (76), and Solapur (SOL) (45) subsequently. Hence, the restoration of the environment during the lockdown phase was temporary rather than permanent. Therefore, our findings propose that several effective policies of government such as relocation of polluting industries, short-term lockdown, odd-even vehicle number, installation of air purifier, and government strict initiatives are needed in making a sustainable environment.

Assessment of household water consumption during COVID-19 pandemic: a cross-sectional web-based study in India

The fatal novel COVID-19 creates precarious threats to humans through speedy diffusion. This virus not only disrupts human health but also makes multidirectional loss and slowdown of modern earth. Almost all countries strictly imposed lockdown and social distancing norms to prevent the infection of COVID-19 virus. In almost all parts of the world, people are using more water for washing, cleaning, bathing and hand washing practices. As a result, per capita water demand along with expenditure have been significantly increased. The principal objective of this study is to evaluate the household level water consumption status and to improve the water security with management for future. The current study has been conducted among the general population of India to assess household level water consumption through internet E-Surveys Google form from August 18 to September 8, 2020. Around 1850 respondents have sent their comments from different sites (rural and urban areas in various climatic regions) of Indian subcontinent. The results show the tremendous increase of water usage along with electrical consumption and expenditure during COVID-19 pandemic situation. Our results revels that 10%, 15% and 17% of higher water consumption per day in rural, urban and peri-urban residential respectively. We hypothesize that the reasons for the increasing water demand and household consumption per day may be found in changed behavioral routines through bathing, washing clothes, and hand washing practices. This web-based study also suggests that few alternative and dependable management techniques i.e. rain water harvesting can be installed to fight the crisis and for the sustainable future. Subsequently, research and development are highly required for long-term management of water resources or reuse of water.

An application of artificial intelligence for investigating the effect of COVID-19 lockdown on three-dimensional temperature variation in equatorial Africa

We present interesting application of artificial intelligence for investigating effect of the COVID-19 lockdown on 3-dimensional temperature variation across Nigeria (2°-15° E, 4°-14° N), in equatorial Africa. Artificial neural networks were trained to learn time-series temperature variation patterns using radio occultation measurements of atmospheric temperature from the Constellation Observing System for Meteorology, Ionosphere, and Climate (COSMIC). Data used for training, validation and testing of the neural networks covered period prior to the lockdown. There was also an investigation into the viability of solar activity indicator (represented by the sunspot number) as an input for the process. The results indicated that including the sunspot number as an input for the training did not improve the network prediction accuracy. The trained network was then used to predict values for the lockdown period. Since the network was trained using pre-lockdown dataset, predictions from the network are regarded as expected temperatures, should there have been no lockdown. By comparing with the actual COSMIC measurements during the lockdown period, effects of the lockdown on atmospheric temperatures were deduced. In overall, the mean altitudinal temperatures rose by about 1.1 °C above expected values during the lockdown. An altitudinal breakdown, at 1 km resolution, reveals that the values were typically below 0.5 °C at most of the altitudes, but exceeded 1 °C at 28 and 29 km altitudes. The temperatures were also observed to drop below expected values at altitudes of 0-2 km, and 17-20 km.

Asymmetric impact of pandemics-related uncertainty on CO2 emissions: evidence from top-10 polluted countries

The recent COVD-19 pandemic has been a major shock, affecting various macroeconomic indicators, including the environmental quality. The question of how the pandemics-related uncertainty will affect the environment is of paramount importance. The study analyzes the asymmetric impact of pandemic uncertainty on CO₂ emissions in top-10 polluted economies (China, USA, India, Russia, Germany, Japan, Iran, South Korea, Indonesia, and Saudi Arabia). Taking panel data from 1996 to 2018, a unique technique, 'Quantile-on-Quantile (QQ)', is employed. CO₂ emissions are used as an indicator of environmental quality. The outcomes define how the quantiles of pandemic uncertainty impact the quantiles of carbon emissions asymmetrically by providing an effective paradigm for comprehending the overall dependence framework. The outcomes reveal that pandemic uncertainty promotes environmental quality by lowering CO₂ emissions in our sample countries at various quantiles. However, Japan shows mixed findings. The effect of PUN on CO₂ is substantially larger in India, Germany, and South Korea and lower in Russia and Saudi Arabia. Furthermore, the magnitude of asymmetry in the pandemic uncertainty-CO₂ emissions association differs by economy, emphasizing that government must pay particular caution and prudence when adopting pandemics-related uncertainty and environmental quality policies.

Changes in tropospheric ozone concentration over Indo-Gangetic Plains: the role of meteorological parameters

This study seeks to understand and quantify the changes in tropospheric ozone (O3) in lower troposphere (LT), middle troposphere (MT) and upper middle troposphere (UMT) over the Indo-Gangetic Plains (IGPs), India during the COVID-19 lockdown 2020 with that of pre-lockdown 2019. The gridded datasets of ozone from the European Centre for Medium-range Weather Forecasts (ECMWF) reanalysis product, ERA5 in combination with statistical interpolated (IDWs) surface NO2 observations, present a consistent picture and indicate a significant tropospheric ozone enhancement over IGP during COVID-19 lockdown restrictions in May 2020. The Paper also examines the influencing role of meteorological parameters on increasing ozone concentration. Over LT, an increase in O3 concentration (23%) is observed and in MT to UMT an enhancement of about 9–18% in O3 concentration have been seen during May 2020 with respect to May 2019. An investigation on causes of increasing  ozone concentration (35–85 ppbv) from MT to UMT during May 2020 reveals that there was significant rise (by 1–6%) in low cloud cover (LCC). Notably, higher LCC increases the backscattering of upward solar radiation from the top of the atmosphere. A positive difference of 5–25 W/m2 in upward solar radiation (USR) is observed across the entire study region. The result suggests that higher LCC significantly contributed to the enhanced USR. Thereby, resulting in higher photolysis rate that lead to an increase in mid tropospheric ozone concentration during May 2020. The results highlight the importance of LCC as an important pathway in ozone formation and aid in scientific understanding of it.

Association of pre-monsoon CG lightning activity and some surface pollutants in different Indian cities around the COVID-19 lockdown year 2020

In this paper, pre-monsoon (March – May) Cloud to Ground (CG) lightning activity over 6 mega cities (New Delhi, Kolkata, Mumbai, Chennai, Bengaluru and Hyderabad) in India is analysed with concentrations of four surface pollutants namely particulate matters (PM_2.5, PM₁₀), Sulphur dioxide (SO₂) and Ozone for a period of 2018 to 2021 that includes the lockdown year 2020. Pollution greatly reduced with an enhancement of air quality in this year. Lightning data for the analysis is derived from the ground based lightning Network -Earth Networks Global Lightning Network (ENGLN). Among the mega cities, Kolkata faces most lightning whereas Mumbai receives the least. CG lightning flash counts significantly decrease in 2020 for Kolkata, Bengaluru, New Delhi and increase for Chennai, Hyderabad and Mumbai though the increase for the last two cities are very insignificant. This increase may be due to greater impact of meteorological factors on lightning than the pollutant concentrations. The lightning activity averaged over all the mega cities follows the trend of pollutant concentrations and average CG lightning flash counts go to minimum in the COVID-19 lockdown year 2020. Analysis also reveals that average seasonal CG lightning flash counts, average positive CG lightning flash counts and maximum peak CG currents show positive correlations with the concentration of all the four pollutants. The overall study shows that control of pollution may reduce the lightning activity in some lightning prone urban areas.