Impact of city lockdown on the air quality of COVID-19-hit of Wuhan city

The effects of COVID-19 pandemic on the air pollutants concentration during the lockdown in Tehran, Iran

In this study, 24-h average concentration of major pollutants, including PM2.5, PM10, NO₂, SO₂, O₃ and CO in the period 1 January to 30 July 2016 to 2020 were investigated to show how partial lockdown affects the behavior of pollutants' concentrations in an urban region. For this purpose, three sites of Aghdasieh, Setad-e Bohran and Shahr-e-Rey, which are located in various parts of Tehran considered. Results showed that PM10 had maximum reduction especially for Aghdasieh and Setad-e Bohran stations (20-30%) compared to the 5-year monthly average. Furthermore, the highest reduction in the Shahr-e-Rey station was related to NO₂ (-17.99%). The trend of AQI decreased considerably in 2020 compared to its pre-lockdown values. The relative reduction of AQI in March compared to February was about -12.8%, -27.6%, and -2.27% for Shahr-e-Rey, Aghdasieh, and Setad-e Bohran, respectively. The concentration of pollutants was expected to fall after the lockdown, but it was noted that compared to their average during the 5-year period, the concentrations of all pollutants especially O₃ increased to some extent. A major reason for this trend is the removal of the traffic control plan and the increasing use of private vehicles in an effort to implement social distancing.

How changes in human activities during the lockdown impacted air quality parameters: A review

The health emergency linked to the spread of COVID-19 has led to important reduction in industrial and logistics activities, as well as to a drastic changes in citizens' behaviors and habits. The restrictions on working activities, journeys and relationships imposed by the lockdown have had important consequences, including for environmental quality. This review aims to provide a structured and critical evaluation of the recent scientific bibliography that analyzed and described the impact of lockdown on human activities and on air quality. The results indicate an important effect of the lockdown during the first few months of 2020 on air pollution levels, compared to previous periods. The concentrations of particulate matter, nitrogen dioxide, sulfur dioxide and carbon monoxide have decreased. Tropospheric ozone, on the other hand, has significantly increased. These results are important indicators that can become decision drivers for future policies and strategies in industrial and logistics activities (including the mobility sector) aimed at their environmental sustainability. The scenario imposed by COVID-19 has supported the understanding of the link between the reduction of polluting emissions and the state of air quality and will be able to support strategic choices for the future sustainable growth of the industrial and logistics sector.

Human mobility behavior in COVID-19: A systematic literature review and bibliometric analysis

This article maps the scientific literature in human mobility behavior in the context of the current pandemic. Through bibliometrics, we analyze the content of published scientific studies indexed on the Web of Science and Scopus during 2020. This enables us the detection of current hotspots and future directions of research. After a co-occurrence of keywords and evidence map analysis, four themes are identified, namely, Land Transport - Operations, Land Transport - Traffic Demand, Air Transport and Environment. We show how air transportation- and environmental-related studies tend to be more mature research whereas the understanding of changes in travel behavior (e.g., telecommuting, preventive measures or health protection behavior) tends to be immature. By using a topic modeling approach, we identify multiple sub-themes within each theme. Our framework adopts a smart literature review approach that can be constantly updated, enabling an analysis of many articles, with little investment of the researcher's time, but also provides high degree of transparency and replicability. We also put forth a research agenda that can help inform and shape transport policy and practice responses to COVID-19.

How do pollutants change post-pandemic? Evidence from changes in five key pollutants in nine Chinese cities most affected by the COVID-19

Under the COVID-19 global pandemic, China has weakened the large-scale spread of the epidemic through lockdown and other measures. At the same time, with the recovery of social production activities, China has become the only country which achieves positive growth in 2020 in the major economies. It entered the post pandemic period. These measures improved the local environmental quality. However, whether this improvement can be sustained is also a problem that needs to be solved. So, this study investigated the changes of five air pollutants (PM2.5, PM10, NO2, SO2, and CO) in the nine cities most severely affected by the pandemic in China during the lockdown and post pandemic period. We emphasized that when analyzing the changes of environmental quality during the epidemic, we must consider not only the impact of the day and short-term changesbut also the cumulative lag effect and sustainable development. Through a combination of qualitative and quantitative methods, it is found that the concentration of pollutants decreased significantly during the lockdown compared to the situation before the epidemic. PM10 and NO2 are falling most, which downs 39% and 46% respectively. During the lockdown period, the pollutant concentrations response to the pandemic has a lag of 3-7 days. More specifically, in the cities related to single pollutants, the impact on the pollutant shows a significant correlation when the measures are delayed for seven days. In the cities that are related to multiple pollutants, the correlation is usually highest in 3-5 days. This means that the impact of policy measures on the environment lasted for 3-5 days. Besides, Wuhan, Jingmen and Jingzhou have seen the most obvious improvement. However, this improvement did not last. In the post pandemic period, the pollutants rebounded, the growth rates of PM10 and NO2 reached 44% and 87% in September. When compared with the changes of pollutants concentration in the same period from 2017 to 2019, the decline rate has also been significantly slower, even higher than the average concentration of previous years. The research not only contributes to China's economic "green recovery" plan during the post epidemic period, but also provides references for environmental governance during economic recovery in other countries.

Measuring the global economic impact of the coronavirus outbreak: Evidence from the main cluster countries

This study measures the global economic impact of the coronavirus outbreak. This pandemic is characterized by demand and supply shocks, leading to restrictions on trade, product and service transactions, and capital flow mobility. We investigate its impact on currency markets, stock market performance, and investor fear sentiment. We employ an empirical, time-scale approach based on the continuous wavelet transform-appropriate for time-series characteristics during times of turmoil. Based on daily data for four main cluster countries (China, France, Italy, and the USA), our results show that the impact of the pandemic's evolution on the main economic indicators in China exhibits a different pattern from France, Italy, and the USA. For China, our results show that the pandemic evolution co-moves with the main economic indicators only in the short term (one week). The effect is more persistent in other countries. We also show that the main economic indicators are more sensitive to pandemic evolution assessed by the number of deaths rather than number of cases, and that currency and financial markets are affected in different timescales. These findings might assist policymakers in addressing the feedback loop between currency markets and capital flows and help investors find alternative assets to hedge against heath shocks.

Effect of COVID-19 pandemic-induced lockdown (general holiday) on air quality of Dhaka City

A worldwide pandemic of COVID-19 has forced the Government of Bangladesh to implement a lockdown during April-May 2020 by restricting people's movement; shutdown of industries and motor vehicles; and closing markets, public places, and schools to contain the virus. This type of strict measures caused an outcome, the reduction of urban air pollution, around the world. The present study aims to investigate the reduction of the concentration of pollutants in the air of Dhaka City and the reduction of the Air Quality Index (AQI). Necessary time-series data of the concentration of PM_2.5, NO₂, SO₂, and CO have been collected from the archive of the Air Quality Monitoring Station of the US Embassy in Dhaka and Sentinel-5P. The time-series data have been analyzed by descriptive statistics, and AQI was calculated following an appropriate formula suggested by the Environmental Protection Agency (EPA) based on the criteria pollutants. The study found that the concentrations of PM_2.5, NO₂, SO₂, and CO during April-May 2020 have been reduced by 26, 30, 07, and 07%, respectively, compared with the preceding year's concentrations. Moreover, the AQI has also been reduced by about 35% on average during the lockdown period than the same times of the previous year. However, the magnitude of pollution reduction in Dhaka is lower than in other cities and countries globally, including Delhi, Sao Paulo, Wuhan, Spain, Italy, the USA. The main reasons may include, among others, the poor implementation of lockdown (especially in the first week of April and the second fortnight of May), pre-existing pollution, transboundary pollution, incineration of solid waste, etc. This study will help policymakers figure out how to regulate pollution sources and improve the air quality of Dhaka.

Machine Learning on the COVID-19 Pandemic, Human Mobility and Air Quality: A Review

The ongoing COVID-19 global pandemic is touching every facet of human lives (e.g., public health, education, economy, transportation, and the environment). This novel pandemic and non-pharmaceutical interventions of lockdown and confinement implemented citywide, regionally or nationally are affecting virus transmission, people's travel patterns, and air quality. Many studies have been conducted to predict the diffusion of the COVID-19 disease, assess the impacts of the pandemic on human mobility and on air quality, and assess the impacts of lockdown measures on viral spread with a range of Machine Learning (ML) techniques. This literature review aims to analyze the results from past research to understand the interactions among the COVID-19 pandemic, lockdown measures, human mobility, and air quality. The critical review of prior studies indicates that urban form, people's socioeconomic and physical conditions, social cohesion, and social distancing measures significantly affect human mobility and COVID-19 viral transmission. During the COVID-19 pandemic, many people are inclined to use private transportation for necessary travel to mitigate coronavirus-related health problems. This review study also noticed that COVID-19 related lockdown measures significantly improve air quality by reducing the concentration of air pollutants, which in turn improves the COVID-19 situation by reducing respiratory-related sickness and deaths. It is argued that ML is a powerful, effective, and robust analytic paradigm to handle complex and wicked problems such as a global pandemic. This study also explores the spatio-temporal aspects of lockdown and confinement measures on coronavirus diffusion, human mobility, and air quality. Additionally, we discuss policy implications, which will be helpful for policy makers to take prompt actions to moderate the severity of the pandemic and improve urban environments by adopting data-driven analytic methods.

The impact of the COVID-19 outbreak on the air quality in China: Evidence from a quasi-natural experiment

The outbreak of coronavirus (COVID-19) in early 2020 posed a significant threat to people's health and economic sustainability in China and worldwide. This study investigated whether the lockdown measures precipitated by the COVID-19 pandemic affected air pollutants in the short term. Moreover, we investigated the impact of the heterogeneity of cities and regions. Using city-level daily panel data for the 2018-2020 lunar calendar, we employed a two-way fixed effects model and interrupted time-series analysis to inspect the effects of the lockdown measures. Interesting empirical findings emerged from our analysis. First, compared with the base period from 2018 to 2019, the COVID-19 lockdown measures significantly reduced air pollutants. In 2020, compared to 2018, PM₁₀ and SO₂ dropped by 15.28 μg/m³ and 6.55 μg/m³, and compared to 2019, PM_2.5, PM₁₀, and SO₂ declined by 7.4 μg/m³, 19.34 μg/m³, and 1.41 μg/m³, respectively. Second, our dynamic analysis showed that as more time elapsed since the start of the lockdown, the associated reduction in air pollution became more significant. Third, the proportion of secondary industries and the cumulative number of confirmed cases had a considerable heterogeneity impact on lockdown measures. Policymakers should encourage investment in new infrastructure and initiatives to boost efficiency and enhance environmental outcomes.

Air Quality During COVID-19 Lockdown in the Yangtze River Delta and the Pearl River Delta: Two Different Responsive Mechanisms to Emission Reductions in China

Despite the large reduction in anthropogenic activities due to the outbreak of COVID-19, air quality in China has witnessed little improvement and featured great regional disparities. Here, by combining observational data and simulations, this work aims to understand the diverse air quality response in two city clusters, Yangtze River Delta region (YRD) and Pearl River Delta region (PRD), China. Though there was a noticeable drop in primary pollutants in both the regions, differently, the maximum daily 8 h average ozone (O3) soared by 20.6-76.8% in YRD but decreased by 15.5-28.1% in PRD. In YRD, nitrogen oxide (NOx) reductions enhanced O3 accumulation and hence increased secondary aerosol formation. Such an increment in secondary organic and inorganic aerosols under stationary weather reached up to 36.4 and 10.2%, respectively, which was further intensified by regional transport. PRD was quite the opposite. The emission reductions benefited PRD air quality, while regional transport corresponded to an increase of 17.3 and 9.3% in secondary organic and inorganic aerosols, respectively. Apart from meteorology, the discrepancy in O3-VOCs-NOx relationships determined the different O3 responses, indicating that future emission control shall be regionally specific, instead of one-size-fits-all cut. Overall, the importance of regionally coordinated and balanced control strategy for multiple pollutants is highly emphasized.

Changes in the concentration of air pollutants before and after the COVID-19 blockade period and their correlation with vegetation coverage

In order to control the spread of COVID-19, China had implemented strict lockdown measures. The closure of cities had had a huge impact on human production and consumption activities, which had greatly reduced population mobility. This article used air pollutant data from 341 cities in mainland China and divided these cities into seven major regions based on geographic conditions and climatic environment. The impact of urban blockade on air quality during COVID-19 was studied from the perspectives of time, space, and season. In addition, this article used Normalized Difference Vegetation Index (NDVI) to systematically analyze the characteristics of air pollution in the country and used the Pearson correlation coefficient to explore the relationship between NDVI and the air pollutant concentrations during the COVID-19 period. Then, linear regression was used to find the quantitative relationship between NDVI and AQI, and the fitting effect of the model was found to be significant through t test. Finally, some countermeasures were proposed based on the analysis results, and suggestions were provided for improving air quality. This paper has drawn the following conclusions: (1) the concentration of pollutants varied greatly in different regions, and the causes of their pollution sources were also different. The region with the largest decline in AQI was the Northeast China (60.01%), while the AQI in the southwest China had the smallest change range, and its value had increased by 1.72%. In addition, after the implementation of the city blockade, the concentration of NO2 in different regions dropped the most, but the increase in O3 was more obvious. (2) Higher vegetation coverage would have a beneficial impact on the atmospheric environment. Areas with higher NDVI values have relatively low AQI. There is a negative correlation between NDVI and AQI, and an average increase of 0.1 in NDVI will reduce AQI by 3.75 (95% confidence interval). In the case of less human intervention, the higher the vegetation coverage, the lower the local pollutant concentration will be. Therefore, the degree of vegetation coverage would have a direct or indirect impact on air pollution.

Substantial Changes of Gaseous Pollutants and Health Effects During the COVID-19 Lockdown Period Across China

The human movement and economic activities have been drastically reduced due to the Coronavirus Disease 2019 (COVID-19) outbreak, leading to the sharp decreases of pollutant emissions and remarkable air quality improvement. Nevertheless, however, the changes of gaseous pollutant concentrations and health effects across China during the COVID-19 lockdown period remained poorly understood. Here, a random forest model was applied to assess the impact of COVID-19 lockdown on pollutant concentrations and potential health effects. The results suggested that estimated NO2, SO2, and CO concentrations in China during January 23-March 31, 2020 decreased by 13.68%, 25.71%, and 7.42%, respectively compared with the same periods in 2018-2019. Nonetheless, the predicted 8-h O3 concentrations across China suffered from 1.29% increases during this period. The avoided premature all-cause, cardiovascular disease (CVD), respiratory disease (RD), and chronic obstructive pulmonary disease (COPD) mortalities induced by NO2 decrease during COVID-19 lockdown period reached 3,954 (3,076-4,832), 635 (468-801), 612 (459-765), and 920 (653-1,186) cases. However, the increases of all-cause, CVD, RD, and COPD mortalities due to O3 increase during COVID-19 lockdown period achieved 462 (250-674), 79 (29-129), 40 (-25-105), and 52 (-34-138) cases. The natural experiment demonstrated the drastic emission reduction measures could significantly decrease the NO2, SO2, and CO concentrations, while they significantly elevated the O3 concentration. It is highly imperative to propose more coordinated air pollution control strategies to control O3 pollution.

The Climate Response to Emissions Reductions Due to COVID-19: Initial Results From CovidMIP

Many nations responded to the corona virus disease-2019 (COVID-19) pandemic by restricting travel and other activities during 2020, resulting in temporarily reduced emissions of CO2, other greenhouse gases and ozone and aerosol precursors. We present the initial results from a coordinated Intercomparison, CovidMIP, of Earth system model simulations which assess the impact on climate of these emissions reductions. 12 models performed multiple initial-condition ensembles to produce over 300 simulations spanning both initial condition and model structural uncertainty. We find model consensus on reduced aerosol amounts (particularly over southern and eastern Asia) and associated increases in surface shortwave radiation levels. However, any impact on near-surface temperature or rainfall during 2020-2024 is extremely small and is not detectable in this initial analysis. Regional analyses on a finer scale, and closer attention to extremes (especially linked to changes in atmospheric composition and air quality) are required to test the impact of COVID-19-related emission reductions on near-term climate.

Impact of SARS-CoV-2 on Ambient Air Quality in Northwest China (NWC)

SARS-CoV-2 was discovered in Wuhan (Hubei) in late 2019 and covered the globe by March 2020. To prevent the spread of the SARS-CoV-2 outbreak, China imposed a countrywide lockdown that significantly improved the air quality. To investigate the collective effect of SARS-CoV-2 on air quality, we analyzed the ambient air quality in five provinces of northwest China (NWC): Shaanxi (SN), Xinjiang (XJ), Gansu (GS), Ningxia (NX) and Qinghai (QH), from January 2019 to December 2020. For this purpose, fine particulate matter (PM2.5), coarse particulate matter (PM10), sulfur dioxide (SO2), nitrogen dioxide (NO2), carbon monoxide (CO), and ozone (O3) were obtained from the China National Environmental Monitoring Center (CNEMC). In 2020, PM2.5, PM10, SO2, NO2, CO, and O3 improved by 2.72%, 5.31%, 7.93%, 8.40%, 8.47%, and 2.15%, respectively, as compared with 2019. The PM2.5 failed to comply in SN and XJ; PM10 failed to comply in SN, XJ, and NX with CAAQS Grade II standards (35 µg/m3, 70 µg/m3, annual mean). In a seasonal variation, all the pollutants experienced significant spatial and temporal distribution, e.g., highest in winter and lowest in summer, except O3. Moreover, the average air quality index (AQI) improved by 4.70%, with the highest improvement in SN followed by QH, GS, XJ, and NX. AQI improved in all seasons; significant improvement occurred in winter (December to February) and spring (March to May) when lockdowns, industrial closure etc. were at their peak. The proportion of air quality Class I improved by 32.14%, and the number of days with PM2.5, SO2, and NO2 as primary pollutants decreased while they increased for PM10, CO, and O3 in 2020. This study indicates a significant association between air quality improvement and the prevalence of SARS-CoV-2 in 2020.

Impact of lockdown on particulate matter concentrations in Colombia during the COVID-19 pandemic

The first confirmed case of COVID-19 in Colombia was reported on March 6, 2020. For this reason, on March 25, preventive isolation was declared mandatory. These measures involved the suspension of economic activities and drastically reduced the number of vehicles on the road. The objective of this study is to evaluate the impact of the lockdown due to the COVID-19 pandemic on PM_2.5 concentrations at 5 monitoring stations and aerosol optical depth values of the Terra/MODIS satellite. We analyzed and compared the weekly and monthly concentrations of PM_2.5 before and during the lockdown between the week of January 6 to June 22, 2020, and compared the daily values obtained from the Terra/MODIS satellite for the months of January-June during the years 2018-2020 to elucidate the effects of the lockdown. Similar to other monitored sites in the world, we observed substantial reductions in weekly PM_2.5 concentrations, from 41 to 84% (Bogotá), from 13 to 66% (Funza), from 17 to 57% (Boyacá), from 35 to 86% (Valledupar) and 31 at 60% (Risaralda). Unlike other studies, the aerosol optical depth values increased up to 59% during the months of lockdown compared to previous years and up to 70% of the weekly mean when compared to before the lockdown. These spatiotemporal behaviors of PM_2.5 and the aerosol optical depth in Colombia are influenced by reductions in vehicular flow during quarantine, regional rainfall, and height of the planetary boundary layer. Emissions from economic activities affect pollutant levels in the area. The analysis of the levels of pollutants during the lockdown provides a baseline for regulatory agencies to establish mitigation plans.

Observed and estimated prevalence of Covid-19 in Italy: How to estimate the total cases from medical swabs data

During the Covid-19 pandemic in Italy, official data are collected with medical swabs following a pure convenience criterion which, at least in an early phase, has privileged the exam of patients showing evident symptoms. However, there are evidences of a very high proportion of asymptomatic patients. In this situation, in order to estimate the real number of infected (and to estimate the lethality rate), it should be necessary to run a properly designed sample survey through which it would be possible to calculate the probability of inclusion and hence draw sound probabilistic inference. Unfortunately, the survey run by the Italian Statistical Institute encountered many field difficulties. Some researchers proposed estimates of the total prevalence based on various approaches, including epidemiologic models, time series and the analysis of data collected in countries that faced the epidemic in earlier times. In this paper, we propose to estimate the prevalence of Covid-19 in Italy by reweighting the available official data published by the Istituto Superiore di Sanità so as to obtain a more representative sample of the Italian population. Reweighting is a procedure commonly used to artificially modify the sample composition so as to obtain a distribution which is more similar to the population. In this paper, we will use post-stratification of the official data, in order to derive the weights necessary for reweighting the sample results, using age and gender as post-stratification variables, thus obtaining more reliable estimation of prevalence and lethality. Specifically, for Italy, we obtain a prevalence of 9%. The proposed methodology represents a reasonable approximation while waiting for more reliable data obtained with a properly designed national sample survey and that it could be further improved if more data were made available.

COVID-19-Induced Lockdowns Indicate the Short-Term Control Effect of Air Pollutant Emission in 174 Cities in China

The contradiction between the regional imbalance and an one-size-fits-all policy is one of the biggest challenges in current air pollution control in China. With the recent implementation of first-level public health emergency response (FLPHER) in response to the COVID-19 pandemic in China (a total of 77 041 confirmed cases by February 22, 2020), human activities were extremely decreased nationwide and almost all economic activities were suspended. Here, we show that this scenario represents an unprecedented "base period" to probe the short-term emission control effect of air pollution at a city level. We quantify the FLPHER-induced changes of NO₂, SO₂, PM_2.5, and PM₁₀ levels in 174 cities in China. A machine learning prediction model for air pollution is established by coupling a generalized additive model, random effects meta-analysis, and weather research and forecasting model with chemistry analysis. The short-term control effect under the current energy structure in each city is estimated by comparing the predicted and observed results during the FLPHER period. We found that the short-term emission control effect ranges within 53.0%-98.3% for all cities, and southern cities show a significantly stronger effect than northern cities (P < 0.01). Compared with megacities, small-medium cities show a similar control effect on NO₂ and SO₂ but a larger effect on PM_2.5 and PM₁₀.

Air quality characteristics in Wuhan (China) during the 2020 COVID-19 pandemic

Understanding the relationship between air quality, pollution emission control measures, and meteorological conditions is important for developing effective air quality improvement policies. In this study, we used pollution monitoring and meteorological data from January to May 2020 to analyze the air quality characteristics during the COVID-19 lockdown in Wuhan, which lasted from January 23 to April 8, 2020. Compared with the same period in 2019, the air quality in 2020 was significantly better. The total excellent and good air quality rates increased by 17.58%-90.08% in 2020; concentrations of NO₂, particulate matter with a diameter <10 μm (PM₁₀) and <2.5 μm (PM_2.5), and total volatile organic compounds (TVOCs) also decreased by 38.23%, 30.25%, 32.92%, and 39.80%, respectively. Moreover, the number of days with NO₂, PM₁₀, and PM_2.5 as the primary pollutants decreased by approximately 10%, 9%, and 15%, respectively. We compared the wind direction, wind speed, temperature, and relative humidity in January-April 2020, 2019, 2018, and 2017 and found no obvious correlation between meteorological factors and improved air quality during the 2020 lockdown. The implementation of strict lockdown measures, such as home quarantining, traffic restrictions, and non-essential enterprise shutdowns, was the dominant cause for the substantial air quality improvement during the 2020 COVID-19 lockdown in Wuhan.

Estimating the Impact of COVID-19 on the PM2.5 Levels in China with a Satellite-Driven Machine Learning Model

China implemented an aggressive nationwide lockdown procedure immediately after the COVID-19 outbreak in January 2020. As China emerges from the impact of COVID-19 on national economic and industrial activities, it has become the site of a large-scale natural experiment to evaluate the impact of COVID-19 on regional air quality. However, ground measurements of fine particulate matters (PM2.5) concentrations do not offer comprehensive spatial coverage, especially in suburban and rural regions. In this study, we developed a machine learning method with satellite aerosol remote sensing data, meteorological fields and land use parameters as major predictor variables to estimate spatiotemporally resolved daily PM2.5 concentrations in China. Our study period consists of a reference semester (1 November 2018-30 April 2019) and a pandemic semester (1 November 2019-30 April 2020), with six modeling months in each semester. Each period was then divided into subperiod 1 (November and December), subperiod 2 (January and February) and subperiod 3 (March and April). The reference semester model obtained a 10-fold cross-validated R2 (RMSE) of 0.79 (17.55 μg/m3) and the pandemic semester model obtained a 10-fold cross-validated R2 (RMSE) of 0.83 (13.48 μg/m3) for daily PM2.5 predictions. Our prediction results showed high PM2.5 concentrations in the North China Plain, Yangtze River Delta, Sichuan Basin and Xinjiang Autonomous Region during the reference semester. PM2.5 levels were lowered by 4.8 μg/m3 during the pandemic semester compared to the reference semester and PM2.5 levels during subperiod 2 decreased most, by 18%. The southeast region was affected most by the COVID-19 outbreak with PM2.5 levels during subperiod 2 decreasing by 31%, followed by the Northern Yangtze River Delta (29%) and Pearl River Delta (24%).

Attitudes towards outdoor and neighbour noise during the COVID-19 lockdown: A case study in London

To stop the spread of COVID-19 transmission, the UK put a first lockdown on the entire country during the months of March and May 2020, which strictly curtailed personal mobility and economic activities. The present study is aimed to understand attitude of people towards noise inside their homes in London during the lockdown. Tweets from the social media platform were collected during the lockdown and the same periods in 2019. Additionally, subjective responses to outdoor and neighbour noises were collected through a questionnaire survey. Tweets about noise complaints during the lockdown were more than twice of those before introduction of lockdown. A substantial increase in talking/shouting, and TV/music activities were observed among the neighbour noise sources. Similar findings were obtained from the survey. The respondents answered that the perceived outdoor noise level decreased but perceived neighbour noise level increased during the lockdown. The outdoor noise annoyance ratings were revealed to be significantly lower than those before the lockdown. In contrast, neighbour noises were more frequently heard and annoyance ratings increased compared to the pre-lockdown period. In particular, talking/shouting and TV/music were most annoying. Furthermore, neighbour noise was more annoying than outdoor noise during the lockdown. This suggests that neighbour noise is more problematic than outdoor noise during lockdown. The findings of this study would be useful in designing the future strategy to enhance the acoustic comfort and city sustainability.

Temporal and spatial analysis of COVID-19 transmission in China and its influencing factors

OBJECTIVES

The purpose of this study was to explore the temporal and spatial characteristics of COVID-19 transmission and its influencing factors in China, from January to October 2020.

METHODS

About 81,000 COVID-19 confirmed case data, Baidu migration index data, air pollutants, meteorological data, and government response strictness index data were collected from 31 provincial-level regions (excluding Hong Kong, Macao, and Taiwan) and 337 prefecture-level cities. The spatio-temporal characteristics of COVID-19 were explored using spatial autocorrelation, hot spot, and spatio-temporal scanning statistics. At the same time, Spearman rank correlation analysis and multiple linear regression were used to explore the relationship between influencing factors and confirmed COVID-19 cases.

RESULTS

The distribution of COVID-19 in China tends to be stable over time, with spatial correlation and prominent clustering regions. Spatio-temporal scanning analysis showed that most COVID-19 high-incidence months were from January to March at the beginning of the epidemic, and the area with the highest aggregation risk was Hubei Province (RR=491.57) which was 491.57 times the aggregation risk of other regions. Among the meteorological variables, the daily average temperature, wind speed, precipitation, and new COVID-19 cases were negatively correlated. The air pollution concentration and migration index were positively correlated with new confirmed cases, and the government response strict index was strongly negatively correlated with confirmed COVID-19 cases.

CONCLUSIONS

Environmental temperature has a certain inhibitory effect on the transmission of COVID-19; the air pollution concentration and migration index have a certain promoting effect on the transmission of COVID-19. The strict government response index indicates that the greater the intensity of government intervention, the fewer COVID-19 cases will occur.

Global Changes in Secondary Atmospheric Pollutants During the 2020 COVID-19 Pandemic

We use the global Community Earth System Model to investigate the response of secondary pollutants (ozone O3, secondary organic aerosols SOA) in different parts of the world in response to modified emissions of primary pollutants during the COVID-19 pandemic. We quantify the respective effects of the reductions in NOx and in volatile organic carbon (VOC) emissions, which, in most cases, affect oxidants in opposite ways. Using model simulations, we show that the level of NOx has been reduced by typically 40% in China during February 2020 and by similar amounts in many areas of Europe and North America in mid-March to mid-April 2020, in good agreement with space and surface observations. We show that, relative to a situation in which the emission reductions are ignored and despite the calculated increase in hydroxyl and peroxy radicals, the ozone concentration increased only in a few NOx-saturated regions (northern China, northern Europe, and the US) during the winter months of the pandemic when the titration of this molecule by NOx was reduced. In other regions, where ozone is NOx-controlled, the concentration of ozone decreased. SOA concentrations decrease in response to the concurrent reduction in the NOx and VOC emissions. The model also shows that atmospheric meteorological anomalies produced substantial variations in the concentrations of chemical species during the pandemic. In Europe, for example, a large fraction of the ozone increase in February 2020 was associated with meteorological anomalies, while in the North China Plain, enhanced ozone concentrations resulted primarily from reduced emissions of primary pollutants.

The role of seasonality in the spread of COVID-19 pandemic

It has been reported that the transmission of COVID-19 can be influenced by the variation of environmental factors due to the seasonal cycle. However, its underlying mechanism in the current and onward transmission pattern remains unclear owing to the limited data and difficulties in separating the impacts of social distancing. Understanding the role of seasonality in the spread of the COVID-19 pandemic is imperative in formulating public health interventions. Here, the seasonal signals of the COVID-19 time series are extracted using the EEMD method, and a modified Susceptible, Exposed, Infectious, Recovered (SEIR) model incorporated with seasonal factors is introduced to quantify its impact on the current COVID-19 pandemic. Seasonal signals decomposed via the EEMD method indicate that infectivity and mortality of SARS-CoV-2 are both higher in colder climates. The quantitative simulation shows that the cold season in the Southern Hemisphere countries caused a 59.71 ± 8.72% increase of the total infections, while the warm season in the Northern Hemisphere countries contributed to a 46.38 ± 29.10% reduction. COVID-19 seasonality is more pronounced at higher latitudes, where larger seasonal amplitudes of environmental indicators are observed. Seasonality alone is not sufficient to curb the virus transmission to an extent that intervention measures are no longer needed, but health care capacity should be scaled up in preparation for new surges in COVID-19 cases in the upcoming cold season. Our study highlights the necessity of considering seasonal factors when formulating intervention strategies.

The Role of Primary Emission and Transboundary Transport in the Air Quality Changes During and After the COVID-19 Lockdown in China

In late January 2020, China's rapid and strict control measures to curb the COVID-19 spread led to a sharp halt in socio-economic activity and a significant reduction in emissions. Using the ground-based observational data, the authors synergistically quantify the nation-wide variations of major air pollutant as well as meteorology during and after the lockdown. Their concentrations (except O3) exhibited significant reduction during February and March 2020, by more than 24% during the lockdown compared with the earlier time period and by more than 17% compared with that in the same period in 2019. In contrast, ozone increased rapidly by about 60% across the country during the lockdown. Abnormal increases in carbon monoxide and particulate matter concentrations in southwest China are attributed to the severe wildfires in Southeast Asia. The concentration of air pollutants bounced back rapidly after the full-scale reopen in March 2020, indicating the decisive role of emissions in the pollution formation.

Twelve things we have learned from medical students during the Pandemic

This article was migrated. The article was marked as recommended. While the COVID-19 pandemic has disrupted every aspect of modern life, including medical education, the response has been remarkable. Ingenuity and innovation have flourished in the face of adversity. An international community of practice has blossomed in response to the challenges posed by COVID-19. Communication and sharing of information have been a hallmark of this community. In Australasia, the Medical Education Collaborative Committee hosted a series of meetings and webinars which enabled educators from all Australian and New Zealand medical schools to share experiences, solutions and resources. This group is auspiced by the Medical Deans Australia and New Zealand, which is the peak body representing professional entry-level medical education, training and research. One of these webinars focused on the student experience, featuring a panel of Australasian medical students drawn from a range of medical schools. The discussion during this session was wide reaching, including topics such as communication, co-designing curriculum changes, the importance of compassion, innovative practice, and meaningful student participation in placements. The ideas drawn from the panel discussion augmented by rich audience participation form the basis of the twelve tips presented in this paper. While derived from the experience in Australia and New Zealand, the authors believe these lessons are likely to be relevant in other jurisdictions.

Air Pollution Status in 10 Mega-Cities in China during the Initial Phase of the COVID-19 Outbreak

Over the past decades, urbanization and industrialization have led to a change in air quality, bringing researchers to a full realization of the damaging effects of human activities on the environment. This study focused on describing air quality during the initial phase of the Novel Coronavirus disease (COVID-19) pandemic (since there were fewer anthropogenic activities) in 10 Chinese mega-cities. Using the independent t-test, the means of air quality index (AQI) scores and individual air pollutants concentration during the outbreak were compared with the means before the outbreak. Cohen’s d was estimated to quantify how much difference was observed. Based on the AQI score, the air quality in these 10 cities ranged from excellent (Shenzhen) to light pollution (Xi’an) with 44.8 μg m⁻³ and 119.7 μg m⁻³, respectively. In comparison to the 2019 air quality, Guangzhou and Wuhan noted major differences in air quality during the outbreak. Indicators of traffic pollution, particularly NO₂, were significantly lower during the outbreak in all cities. Particulate matter pollution varied, with some cities observing lower concentrations and other higher concentrations during the outbreak. There was a significant decrease in air pollution levels during the outbreak. More researchers should observe changes in air quality during peculiar or major events. Implementation of stringent regulation on vehicle use should be considered in mega-cities. Relevant findings should be employed in emphasizing the detrimental effects of anthropogenic activities and support the need for stringent emission control regulations.

Change of CO Concentration Due to the COVID-19 Lockdown in China Observed by Surface and Satellite Observations

The nationwide lockdown due to the COVID-19 pandemic in 2020 reduced industrial and human activities in China. In this study, we investigate atmospheric carbon monoxide (CO) concentration changes during the lockdown from observations at the surface and from two satellites (TROPOspheric Monitoring Instrument (TROPOMI) and Infrared Atmospheric Sounding Interferometer (IASI)). It is found that the average CO surface concentration in 2020 was close to that in 2019 before the lockdown, and became 18.7% lower as compared to 2019 during the lockdown. The spatial variation of the change in the CO surface concentration is high, with an 8–27% reduction observed for Beijing, Shanghai, Chengdu, Zhengzhou, and Guangzhou, and almost no change in Wuhan. The TROPOMI and IASI satellite observations show that the CO columns decreased by 2–13% during the lockdown in most regions in China. However in South China, there was an 8.8% increase in the CO columns observed by TROPOMI and a 36.7% increase observed by IASI, which is contrary to the 23% decrease in the surface CO concentration. The enhancement of the CO column in South China is strongly affected by the fire emissions transported from Southeast Asia. This study provides an insight into the impact of COVID-19 on CO concentrations both at the surface and in the columns in China, and it can be extended to evaluate other areas using the same approach.

Polycyclic Aromatic Hydrocarbons in Indoor Dust Collected during the COVID-19 Pandemic Lockdown in Saudi Arabia: Status, Sources and Human Health Risks

To control the spread of coronavirus disease (COVID-19), Saudi Arabia's government imposed a strict lockdown during March-July 2020. As a result, the public was confined to indoors, and most of their daily activities were happening in their indoor places, which might have resulted in lower indoor environment quality. Polycyclic aromatic hydrocarbons (PAHs) were analyzed in household dust (n = 40) collected from different residential districts of Jeddah, Saudi Arabia, during the lockdown period. PAHs' levels were two folds higher than the previously reported PAHs in indoor dust from this region. We detected low molecular weight (LMW) with two to four aromatic ring PAHs in all the samples with a significant contribution from Phenanthrene (Phe), present at an average concentration of 1590 ng/g of dust. Although high molecular weight (HMW) (5-6 aromatic ring) PAHs were detected at lower concentrations than LMW PAHs, however, they contributed >90% in the carcinogenic index of PAHs. The estimated daily intake (EDI) of specific PAHs was above the reference dose (RfD) for young children in high-end exposure and the calculated Incremental Lifetime Cancer Risk (ILCR) was >1.00 × 10-4 for both Saudi adults and young children. The study highlighted that indoor pollution has increased significantly during lockdown due to the increased indoor activities and inversely affect human health. This study also warrants to conduct more studies involving different chemicals to understand the indoor environment quality during strict lockdown conditions.

Weather variability and transmissibility of COVID-19: a time series analysis based on effective reproductive number

COVID-19 is causing a significant burden on medical and healthcare resources globally due to high numbers of hospitalisations and deaths recorded as the pandemic continues. This research aims to assess the effects of climate factors (i.e., daily average temperature and average relative humidity) on effective reproductive number of COVID-19 outbreak in Wuhan, China during the early stage of the outbreak. Our research showed that effective reproductive number of COVID-19 will increase by 7.6% (95% Confidence Interval: 5.4% ~ 9.8%) per 1°C drop in mean temperature at prior moving average of 0-8 days lag in Wuhan, China. Our results indicate temperature was negatively associated with COVID-19 transmissibility during early stages of the outbreak in Wuhan, suggesting temperature is likely to effect COVID-19 transmission. These results suggest increased precautions should be taken in the colder seasons to reduce COVID-19 transmission in the future, based on past success in controlling the pandemic in Wuhan, China.

COVID-19 pandemic in Wuhan: Ambient air quality and the relationships between criteria air pollutants and meteorological variables before, during, and after lockdown

As a result of the lockdown (LD) control measures enacted to curtail the COVID-19 pandemic in Wuhan, almost all non-essential human activities were halted beginning on January 23, 2020 when the total lockdown was implemented. In this study, changes in the concentrations of the six criteria air pollutants (PM_2.5, PM₁₀, SO₂, NO₂, CO, and O₃) in Wuhan were investigated before (January 1 to 23, 2020), during (January 24 to April 5, 2020), and after the COVID-19 lockdown (April 6 to June 20, 2020) periods. Also, the relationships between the air pollutants and meteorological variables during the three periods were investigated. The results showed that there was significant improvement in air quality during the lockdown. Compared to the pre-lockdown period, the concentrations of NO₂, PM_2.5, PM₁₀, and CO decreased by 50.6, 41.2, 33.1, and 16.6%, respectively, while O₃ increased by 149% during the lockdown. After the lockdown, the concentrations of PM_2.5, CO and SO₂ declined by an additional 19.6, 15.6, and 2.1%, respectively. However, NO₂, O₃, and PM₁₀ increased by 55.5, 25.3, and 5.9%, respectively, compared to the lockdown period. Except for CO and SO₂, WS had negative correlations with the other pollutants during the three periods. RH was inversely related with all pollutants. Positive correlations were observed between temperature and the pollutants during the lockdown. Easterly winds were associated with peak PM_2.5 concentrations prior to the lockdown. The highest PM_2.5 concentrations were associated with southwesterly wind during the lockdown, and northwesterly winds coincided with the peak PM_2.5 concentrations after the lockdown. Although, COVID-19 pandemic had numerous negative effects on human health and the global economy, the reductions in air pollution and significant improvement in ambient air quality likely had substantial short-term health benefits. This study improves the understanding of the mechanisms that lead to air pollution under diverse meteorological conditions and suggest effective ways of reducing air pollution in Wuhan.

The concentration of major air pollutants during the movement control order due to the COVID-19 pandemic in the Klang Valley, Malaysia

The COVID-19 pandemic forced many governments across the world to implement some form of lockdown to minimalize the spread of the virus. On 18th March 2020, the Malaysian government put into action an enforced movement control order (MCO) to reduce the numbers of infections. This study aims to investigate the concentrations of air pollutants during the MCO in the Klang Valley. The concentrations of air pollutants were recorded by the continuous air quality monitoring system (CAQMS) operated by the Department of Environment. The results showed that there were significant reductions (p < 0.05) of PM₁₀, PM_2.5, NO₂ and CO during the MCO compared with the same periods in 2019 and 2018. The highest percentage of reduction during the MCO was recorded by NO₂ with a percentage reduction of between -55 % and -72 %. O₃ concentrations at several stations showed an increase due to the reductions of its precursors such as NO. Further investigation using diurnal patterns of air pollutant concentrations both before and during the MCO showed that NO₂ and CO were both reduced significantly during the rush hours, indicating the reduction in motor vehicles on the roads as a consequence of the MCO influenced the levels of these pollutants.

Effect of the COVID-19 Lockdown on Ambient Air Quality in Major Cities of Nepal

BACKGROUND

The Nepalese government announced a nationwide lockdown beginning on March 24, 2020 as an attempt to restrain the spread of COVID-19. The prohibition in flight operations and movement of vehicles, factory shutdowns and restriction in people's movement due to the lockdown led to a significant reduction in the amounts of pollutants degrading air quality in many countries.

OBJECTIVES

The present study aimed to analyze changes in particulate matter (PM) emissions and the air quality index (AQI) of six cities in Nepal i.e., Damak, Simara, Kathmandu, Pokhara, Nepalgunj and Surkhet due to the nationwide lockdown in response to the COVID-19 outbreak.

METHODS

Daily PM concentrations of each of the six study cities from January 24 to September 21, 2020 were obtained from the World Air Quality Index project (https://aqicn.org) and analyzed using R Studio software. The drop percentage was calculated to determine the change in PM_2.5 and PM₁₀ concentration during different time periods. Independent sample Mann-Whitney U tests were performed to test the significance of differences in mean concentration for each site during the lockdown period (24 March-24 July 2020) and its corresponding period in 2019. Similarly, the significance of differences in mean concentrations between the lockdown period and the period immediately before lockdown (23 January-23 March) was also examined using the same test.

RESULTS

During the lockdown period, in overall Nepal, AQI_PM2.5 and AQI_PM10 were within the moderate zone for the maximum number of days. As a result of the lockdown, the highest immediate and final drop of PM_2.5 was observed in Damak (26.37%) and Nepalgunj (80.86%), respectively. Similarly, the highest immediate drop of PM₁₀ was observed in Surkhet (37.22%) and finally in Nepalgunj (81.14%). Analysis with the Mann-Whitney U test indicated that for both PM types, all sites showed a statistically significant (p < 0.05) difference in mean concentrations during lockdown and the corresponding period in 2019.

CONCLUSIONS

The present study explored the positive association between vehicular movement and PM emissions, highlighting the need for alternative fuel sources to improve air quality and human health.

COMPETING INTERESTS

The authors declare no competing financial interests.

Geospatial analysis of COVID-19 lockdown effects on air quality in the South and Southeast Asian region

The COVID-19 pandemic, induced by the novel Coronavirus worldwide outbreak, is causing countries to introduce different types of lockdown measures to curb the contagion. The implementation of strict lockdown policies has had unprecedented impacts on air quality globally. This study is an attempt to assess the effects of COVID-19 induced lockdown measures on air quality in both regional, country, and city scales in the South and Southeast Asian region using open-source satellite-based data and software frameworks. We performed a systematic review of the national lockdown measures of 19 countries of the study area based on publicly available materials. We considered two temporal settings over a period of 66 days to assess and compare the effects of lockdown measures on air quality levels between standard business as usual and current situation COVID-19 lockdown. Results showed that compared to the same period of 2019, atmospheric NO2, SO2, PM2.5, and CO levels decreased by an average of 24.16%, 19.51%, 20.25%, and 6.88%, respectively during the lockdown, while O3 increased by a maximum of 4.52%. Among the 19 studied cities, Dhaka, Kathmandu, Jakarta, and Hanoi experienced the highest reduction of NO2 (40%-47%) during the lockdown period compared to the corresponding period of 2019. The methodological framework applied in this study can be used and extended to future research in the similar domain such as understanding long-term effects of COVID-19 mitigation measures on the atmospheric pollution at continental-scale or assessing the effects of the domestic emissions during the stay-at-home; a standard and effective COVID-19 lockdown measure applied in most of the countries.

Positive environmental effects of the coronavirus 2020 episode: a review

The outbreak of COVID-19 has made a global catastrophic situation that caused 1,039,406 deaths out of 35,347,404 infections, and it will also cause significant socio-economic losses with poverty increasing from 17.1 to 25.9%. Although the spreading rate of COVID-19 is very high on October 6, 2020, the death rate is still less than 2.94%. Nonetheless, this review article shows that the lockdown has induced numerous positive impacts on the environment and on energy consumption. For instance, the lockdown has decreased the electricity demand by 30% in Italy, India, Germany, and the USA, and by 12-20% in France, Germany, Spain, India, and the UK. Additionally, the expenditure of the fuel supply has been decreased by 4% in 2020 as compared to the previous years (2012-2019). In particular, The global demand for coal fuel has been reduced by 8% in March and April 2020 as compared to the same time in 2019. In terms of harmful emissions, the lockdowns reduced the emissions of nitrous oxides by 20-30% in China, Italy, France, Spain, and by 77.3% in São Paulo, Brazil. Similarly, the particulate matter level has been reduced from 5-15% in Western Europe, to 200% in New Delhi, India, which in turn has enhanced the air quality in a never-seen manner in recent times. In some places, such as New York, USA, CO2 emission was also reduced by 5-10%. The water quality, in several polluted areas, has also been remarkably enhanced, for example, the dissolved oxygen content in the Ganga River, India, has increased by about 80%. Traffic congestion has also been reduced worldwide, and in some areas, it has been reduced by 50%, such as New York and Los Angeles, USA. Overall, while the COVID-19 pandemic has shrinked the global economy by 13-32%, the pandemic has also clearly benefited to other sectors, which must be considered as the spotlight for the permanent revival of the global ecosystem.

Environmental Indicator for COVID-19 Non-Pharmaceutical Interventions

A novel coronavirus (COVID-19) has caused viral pneumonia worldwide, posing a major threat to international health. Our study reports that city lockdown is an effective way to reduce the number of new cases and the nitrogen dioxide (NO2) concentration can be used as an environmental lockdown indicator to evaluate the effectiveness of lockdown measures. The airborne NO2 concentration steeply decreased over the vast majority of COVID-19-hit areas since the lockdown. The total number of newly confirmed cases reached an inflection point about two weeks since the lockdown and could be reduced by about 50% within 30 days of the lockdown. The stricter lockdown will help newly confirmed cases to decline earlier and more rapidly, and at the same time, the reduction rate of NO2 concentration will increase. Our research results show that NO2 satellite observations can help decision makers effectively monitor and manage non-pharmaceutical interventions in the epidemic.

Identifying Transcriptomic Signatures and Rules for SARS-CoV-2 Infection

The world-wide Coronavirus Disease 2019 (COVID-19) pandemic was triggered by the widespread of a new strain of coronavirus named as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Multiple studies on the pathogenesis of SARS-CoV-2 have been conducted immediately after the spread of the disease. However, the molecular pathogenesis of the virus and related diseases has still not been fully revealed. In this study, we attempted to identify new transcriptomic signatures as candidate diagnostic models for clinical testing or as therapeutic targets for vaccine design. Using the recently reported transcriptomics data of upper airway tissue with acute respiratory illnesses, we integrated multiple machine learning methods to identify effective qualitative biomarkers and quantitative rules for the distinction of SARS-CoV-2 infection from other infectious diseases. The transcriptomics data was first analyzed by Boruta so that important features were selected, which were further evaluated by the minimum redundancy maximum relevance method. A feature list was produced. This list was fed into the incremental feature selection, incorporating some classification algorithms, to extract qualitative biomarker genes and construct quantitative rules. Also, an efficient classifier was built to identify patients infected with SARS-COV-2. The findings reported in this study may help in revealing the potential pathogenic mechanisms of COVID-19 and finding new targets for vaccine design.

Meteorological parameters and COVID-19 spread-Russia a case study

An attempt was made in this chaper to understand the meteorological controls on SARS-CoV-2 (COVID-19) spread in Russia. Russia is one of the most affected country for COVID-19 and significant death cases were recorded. A continuous seven-month data from 31 January to 23 August 2020 from different locations in the country was collected through the commonly available websites. COVID data (total cases (966189), daily new cases (11656), daily deaths (232), and total recovered (777960)) and meteorological parameters (temperature, dew, precipitation, humidity, and wind speed) were used for this analysis. The results show an increasing trend of daily new cases and daily deaths during lock down period, and it gradually decreased or stabilized in the post lock down period. It infers the effectiveness of movement control during the lock down period, that stops further spreading. The positive correlation between COVID cases and temperature indicate that the increase of temperature increases the spreading and vice versa. The negative relationship of humidity with death cases also facilitates the pandemic spread. Thus, the outcome of this study may help to address concerns about the COVID-19 pandemic among the public and policymakers.

Reduction in concentration of PM2.5 in India's top most polluted cities: with special reference to post-lockdown period

Lockdown in India begins from 25 March and continues until 31 May 2020 due to the COVID-19 pandemic situation. Due to such an extended period of lockdown for about more than 2 months resulted in 1.38 billion populations restricted themselves from mass activities that contribute to air pollution. Thus, through our quantitative approach and trend analysis, the study aims to evaluate the changes in the level of PM_2.5 as a major pollutant for the top ten polluted cities in India, with a special emphasis on finding what happened to its concentration after the lockdown ended. Thus, to better understand the nature of variation in PM_2.5, we divide the entire 7 months into three periods for our analysis, i.e., before lockdown (1 January to 24 March), during lockdown (25 March to 31 May), and post-lockdown or unlock 1 and 2 (1 June to 31 July). Our investigation reveals that before lockdown, all the top polluted cities of India violating the national standard of PM_2.5, as the lockdown begins interestingly, all cities show a momentous reduction in PM_2.5 concentration. Further, surprisingly we found that after the post-lockdown period, the concentration of PM_2.5 was reduced to minimal, as the average concentration of PM_2.5 for all the cities is below the National Ambient Air Quality Standard (NAAQS). The study reveals that the lockdown has a consequence in improving overall air quality for the top polluted cities in India and further lockdown in the future with proper planning should be considered an alternative approach to restrain excessive emissions.

High resolution mapping of nighttime light and air pollutants during the COVID-19 lockdown in Wuhan

The novel coronavirus (COVID-19) has induced unprecedented improvements of air quality due to drastic shrinking of human activities during the pandemic lockdown in 2020. While declines of most air pollutants have been globally evidenced in most cities worldwide, there is few detailed spatial knowledge at local scale. Therefore, we present here a high resolution mapping of the 2018-2020 evolution of human activities and air pollutants in Wuhan. Human activities were assessed by nighttime light radiance. We measured the air quality index (AQI) as the maximum value among air quality sub-indices of SO₂, NO₂, CO, O₃ and particulate matter. We also compared mean monthly pollutant concentration during January-April in 2018, 2019 and 2020. Mapping results show that variations of nighttime light radiance were heterogenous at local scale, showing both rises and declines in the same district. The radiance decreased in eight districts located mostly in the city center, as a result of lower human activity, but the radiance increased in the five surrounding districts, as a consequence of people staying at home. AQI was low during lockdown, averaging at 57, but showed strong daily variations with a slight pollution around February 5 with AQI rising to 126. During this pollution event, particulate matter, SO₂, NO₂ and CO levels were positively correlated, suggesting common sources, but were not correlated with ozone; and particulate matter, SO₂, NO₂ and CO decreased with relative humidity, suggesting removal by precipitation. Comparison of 2020 data with previous years shows that particulate matter and NO₂ were highly reduced, CO was less reduced due to ongoing power industries, SO₂ first declined then increased to exceed 2018-19 values due to coal combustion, and ozone levels was more abundant due both to less NO_x pollution and the weekend effect.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s10311-021-01222-x.

Environmental effects of stratospheric ozone depletion, UV radiation, and interactions with climate change: UNEP Environmental Effects Assessment Panel, Update 2020

This assessment by the Environmental Effects Assessment Panel (EEAP) of the United Nations Environment Programme (UNEP) provides the latest scientific update since our most recent comprehensive assessment (Photochemical and Photobiological Sciences, 2019, 18, 595-828). The interactive effects between the stratospheric ozone layer, solar ultraviolet (UV) radiation, and climate change are presented within the framework of the Montreal Protocol and the United Nations Sustainable Development Goals. We address how these global environmental changes affect the atmosphere and air quality; human health; terrestrial and aquatic ecosystems; biogeochemical cycles; and materials used in outdoor construction, solar energy technologies, and fabrics. In many cases, there is a growing influence from changes in seasonality and extreme events due to climate change. Additionally, we assess the transmission and environmental effects of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which is responsible for the COVID-19 pandemic, in the context of linkages with solar UV radiation and the Montreal Protocol.

Relationship Between COVID-19-Infected Number and PM2.5 Level in Ambient Air of Bangkok, Thailand

Several empirical studies of reductions in air pollutants as social distancing and working from home (WFH) policies have sparked recommendations that the COVID-19 pandemic might have been responsible for better air quality particularly in urban area. These findings offer a compelling provocation for the scientific community to detect and investigate variations to air quality as a consequence of government enforced quarantine. In spite of countless research studies focusing on the connection between WFH policy and air pollutant levels, the majority of discussion has unfortunately ignored the central role of other potential sources (e.g. agricultural waste burnings, cooking emissions, and industrial releases) in governing air quality, or has neglected the psychological and social impacts of COVID-19. In this study, a t test was used to compare the average concentrations of PM_2.5 and COVID-19-infected numbers (n) in three different periods which were n < 300 vs. n ≧ 300, n < 500 vs. n ≧ 500, and n < 700 vs. n ≧ 700. Some significant differences were observed in the groups of n < 500 vs. n ≧ 500, and n < 700 vs. n ≧ 700 indicating that the psychological and social impacts play a crucial role in restricting daily activities and thus reducing the atmospheric contents of PM_2.5 in some areas. Further assessments were conducted by separating PM_2.5 contents into three different periods (i.e. Period-I: day-1 ~ day-10; Period-II: day-11 ~ day-20; Period-III: day-21 ~ day-31). Some significant reductions of PM_2.5 during the Period-I were detected in the eastern area of Bangkok. In addition, Pearson correlation analysis showed that hot-spot numbers appear to be a minor of importance in controlling PM_2.5 levels in the ambient air of Bangkok, Thailand.

The impact of COVID-19 lockdown on the air quality of Eastern Province, Saudi Arabia

Since the identification of the COVID-19 outbreak in Wuhan, China, in December 2019, the death toll from the direct infection by COVID-19 has exceeded 775,000, and more than 21 million cases have been reported to the World Health Organization (WHO) around the world. It is strongly believed that its impact might be worsened by poor outdoor and indoor air qualities, particularly on older adults. The nationwide lockdown measures were imposed between March 23 and June 20, 2020, to stop the spread of COVID-19 pandemic in the Kingdom of Saudi Arabia (KSA). In this work, the possible effects of the lockdown on the air quality were investigated using meteorological and air quality datasets obtained from eight monitoring stations covering the Eastern Province of the KSA. The studied air pollutants include carbon monoxide (CO), sulfur dioxide (SO₂), nitrogen dioxide (NO₂), ozone (O₃), and inhalable particulate matter (PM₁₀). The NO₂ was found to be the marker pollutant responding best to the lockdown measures since its concentrations decreased at all sites during- and post-lockdown periods and ranged between 12-86% and 14-81%, respectively. Compared with pre-lockdown period, the Eastern Province also experienced significant concentration reductions at varying rates for PM₁₀ (21-70%), CO (5.8-55%), and SO₂ (8.7-30%), while O₃ concentrations showed increasing rates ranging between 6.3 and 45%. The consequences of these reductions were reflected in easing the outdoor air quality, which might reduce the impact of COVID-19 pandemic, especially on elderly and sensitive groups.

Air quality index and criteria pollutants in ambient atmosphere over selected sites:Impact and lessons to learn from COVID-19

World Health Organization (WHO) declared the disease COVID-19, caused by novel virus SARS-CoV-2, as pandemic in March 2020 following which different countries adopted immediate stringent measures to save human lives. In order to restrict the spread of disease, intra- and interstate movements of public by road/rail and air were completely halted except for those involved in essential services. India followed the option of complete lockdown (LD) in phase 1 (25th March to 14th April 2020) followed by phase 2 (15th April to 3rd May), phase 3 (4th May to 17th May), and phase 4 (18th May to 31st May 2020). Restrictions on agriculture and industrial sector were eased out in each successive phase after LD 1 and eventually country started unlock phase from 1st June to 30th June and so on. In this chapter, a discussion is made based on the data on criteria pollutants and air quality index (AQI) for selected sites in New Delhi and for selected cities across the country, respectively to spell out impacts of COVID-19 (which are initially positive) and the lessons for long-term planning for improvement of air quality. During LD 1, emissions from vehicles, industries, and construction activities were substantially down and therefore, levels of criteria pollutants CO, NOx, SO₂, Pb, O₃, PM_2.5 in ambient atmosphere came down and AQI showed improvement which was considered as silver line of the COVID-19 pandemic. Interestingly, not all criteria pollutants showed decrease to same extent and rather some still stayed above the National Ambient Air Quality Standard (NAAQS) values over New Delhi, the national capital of India. As the restrictions eased out in LD 3 and LD 4, pollution levels started increasing but again not uniformly for all pollutants and for all locations in New Delhi. During Unlock 1.0, emissions did not increase suddenly rather in a systematic linear fashion. In addition, air quality and AQI did not deteriorate much during Unlock 1.0 due to onset of monsoon rains in the country. It is suggested that all emission sources and people’s movement cannot be restricted during normal days in any country, as it has hit the socioeconomic health of nation very hard. A close examination of pollution levels and emission sources during lockdown to unlock could help us in devising a long-term strategy to bring down air pollution particularly in worst hit regions such as New Delhi. Systematic restrictions on major pollution sources with intermittent relaxations could be a possible approach to constrain air pollution.

The COVID-19 pandemic: Impacts on cities and major lessons for urban planning, design, and management

Since the early days of the COVID-19 crisis the scientific community has constantly been striving to shed light on various issues such as the mechanisms driving the spread of the virus, its environmental and socio-economic impacts, and necessary recovery and adaptation plans and policies. Given the high concentration of population and economic activities in cities, they are often hotspots of COVID-19 infections. Accordingly, many researchers are struggling to explore the dynamics of the pandemic in urban areas to understand impacts of COVID-19 on cities. In this study we seek to provide an overview of COVID-19 research related to cities by reviewing literature published during the first eight months after the first confirmed cases were reported in Wuhan, China. The main aims are to understand impacts of the pandemic on cities and to highlight major lessons that can be learned for post-COVID urban planning and design. Results show that, in terms of thematic focus, early research on the impacts of COVID-19 on cities is mainly related to four major themes, namely, (1) environmental quality, (2) socio-economic impacts, (3) management and governance, and (4) transportation and urban design. While this indicates a diverse research agenda, the first theme that covers issues related to air quality, meteorological parameters, and water quality is dominant, and the others are still relatively underexplored. Improvements in air and water quality in cities during lockdown periods highlight the significant environmental impacts of anthropogenic activities and provide a wake-up call to adopt environmentally friendly development pathways. The paper also provides other recommendations related to the socio-economic factors, urban management and governance, and transportation and urban design that can be used for post-COVID urban planning and design. Overall, existing knowledge shows that the COVID-19 crisis entails an excellent opportunity for planners and policy makers to take transformative actions towards creating cities that are more just, resilient, and sustainable.

Assessing the Impact of Lockdown on Atmospheric Ozone Pollution Amid the First Half of 2020 in Shenyang, China

During the eruption of COVID-19, a citywide lockdown was executed from 26 January to 23 March 2020, in Shenyang, in which the ozone pollution has recorded significant variations. This paper mainly anatomized the comprehensive characteristics and evolution trends of ozone pollution based on the lockdown period in the first half of 2020. Using the Hybrid Single Particle Lagrangian Integrated Trajectory (HYSPLIT) model and cluster analysis method to establish backward trajectories and channels, the spatial transport process of ozone in the preset period and the causation of typical ozone pollution events were investigated in depth. The results demonstrated that: The ozone concentration pollution in the first half of 2020 was increased than last year. During the lockdown period, the basic pollutants levels were lower than that in pre-lockdown under different proportions, except O₃ maximum 8-h moving average (MDA8) was increased by 69.7%, accompanied by the delay of daily peak value, increased pollution days and longer pollution cycle. The typical pollution events were highly consistent with the evolution path of fine aerosol compelled by extreme weather. The ozone concentration and the atmospheric oxidation capacity can be stably maintained at a low level when NO₂ concentration remained at 50–70 μg/m³, no matter how much the AQI was. Meanwhile, ozone concentration in the downwind suburban was as low as the central city and soared in few stations amid post-lockdown, simultaneous the correlation between ozone and other pollutants converted from negative to positive. The trajectory indicated that the pollution sources during the lockdown and pre-lockdown were basically Southern Russia, Inner Mongolia, and the three provinces of Northeast China, the pollution from the Bohai Sea provoked ozone pollutants in Shenyang to rebound briskly amid post-lockdown, the pollution of neighboring countries and areas would have a stronger impact on air quality under the effect of lockdown.

Impact of lockdown on air quality over major cities across the globe during COVID-19 pandemic

In present study, the variation in concentration of key air pollutants such as PM 2.5, PM 10, NO 2, SO 2 and O 3 during the pre-lockdown and post-lockdown phase has been investigated. In addition, the monthly concentration of air pollutants in March, April and May of 2020 is also compared with that of 2019 to unfold the effect of restricted emissions under similar meteorological conditions. To evaluate the global impact of COVID-19 on the air quality, ground-based data from 162 monitoring stations from 12 cities across the globe are analysed for the first time. The concentration of PM 2.5, PM 10 and NO 2 were reduced by 20-34%, 24-47% and 32-64%, respectively, due to restriction on anthropogenic emission sources during lockdown. However, a lower reduction in SO 2 was observed due to functional power plants. O 3 concentration was found to be increased due to the declined emission of NO. Nevertheless, the achieved improvements were temporary as the pollution level has gone up again in cities where lockdown was lifted. The study might assist the environmentalist, government and policymakers to curb down the air pollution in future by implementing the strategic lockdowns at the pollution hotspots with minimal economic loss.

Impact of lockdown on air quality over major cities across the globe during COVID-19 pandemic

In present study, the variation in concentration of key air pollutants such as PM _2.5, PM ₁₀, NO ₂, SO ₂ and O ₃ during the pre-lockdown and post-lockdown phase has been investigated. In addition, the monthly concentration of air pollutants in March, April and May of 2020 is also compared with that of 2019 to unfold the effect of restricted emissions under similar meteorological conditions. To evaluate the global impact of COVID-19 on the air quality, ground-based data from 162 monitoring stations from 12 cities across the globe are analysed for the first time. The concentration of PM _2.5, PM ₁₀ and NO ₂ were reduced by 20-34%, 24-47% and 32-64%, respectively, due to restriction on anthropogenic emission sources during lockdown. However, a lower reduction in SO ₂ was observed due to functional power plants. O ₃ concentration was found to be increased due to the declined emission of NO. Nevertheless, the achieved improvements were temporary as the pollution level has gone up again in cities where lockdown was lifted. The study might assist the environmentalist, government and policymakers to curb down the air pollution in future by implementing the strategic lockdowns at the pollution hotspots with minimal economic loss.

Non-negligible impacts of clean air regulations on the reduction of tropospheric NO2 over East China during the COVID-19 pandemic observed by OMI and TROPOMI

We study the variation of tropospheric NO₂ vertical column densities (TropNO₂VCDs) over East China during the 2005-2020 lunar new year (LNY) holiday seasons to understand factors on the reduction of tropospheric NO₂ during the outbreak of COVID-19 in East China using Ozone Monitoring Instrument (OMI) and TROPOspheric Monitoring Instrument (TROPOMI) observations. TropNO₂VCDs from OMI and TROPOMI reveal sharp reductions of 33%-72% during 2020 LNY holiday season and the co-occurring outbreak of COVID-19 relative to the climatological mean of 2005-2019 LNY holiday seasons, and 22%-67% reduction relative to the 2019 LNY holiday season. These reductions of TropNO₂VCD occur majorly over highly polluted metropolitan areas with condensed industrial and transportation emission sources. COVID-19 control measures including lockdowns and shelter-in-place regulations are the primary reason for these tropospheric NO₂ reductions over most areas of East China in 2020 LNY holiday season relative to the 2019 LNY holiday season, as COVID-19 control measures may explain ~87%-90% of tropospheric NO₂ reduction in Wuhan as well as ~62%-89% in Beijing, Yangtze River Delta (YRD) and Sichuan Basin areas. The clean air regulation of China also contributes significantly to reductions of tropospheric NO₂ simultaneously and is the primary factor in the Pearl River Delta (PRD) area, by explaining ~56%-63% of the tropospheric NO₂ reduction there.

Four-Month Changes in Air Quality during and after the COVID-19 Lockdown in Six Megacities in China

The pandemic of coronavirus disease 2019 (COVID-19) resulted in a stringent lockdown in China to reduce the infection rate. We adopted a machine learning technique to analyze the air quality impacts of the COVID-19 lockdown from January to April 2020 for six megacities with different lockdown durations. Compared with the scenario without lockdowns, we estimated that the lockdown reduced ambient NO2 concentrations by 36-53% during the most restrictive periods, which involved Level-1 public health emergency response control actions. Several cities lifted the Level-1 control actions during February and March, and the avoided NO2 concentrations subsequently dropped below 10% in late April. Traffic analysis during the same periods in Beijing and Chengdu confirmed that traffic emission changes were a major factor in the substantial NO2 reduction, but they were also associated with increased O3 concentrations. The lockdown also reduced PM2.5 concentrations, although heavy pollution episodes occurred on certain days due to the enhanced formation of secondary aerosols in association with the increased atmospheric oxidizing capacity. We also observed that the changes in air pollution levels decreased as the lockdown was gradually eased in various cities.

Effect of Road Traffic on Air Pollution. Experimental Evidence from COVID-19 Lockdown

The increasing concentration of human activities in cities has been leading to a worsening in air quality, thus negatively affecting the lives and health of humans living in urban contexts. Transport is one of the main sources of pollution in such environments. Several local authorities have therefore implemented strict traffic-restriction measures. The aim of this paper is to evaluate the effectiveness and limitations of these interventions, by analyzing the relationship between traffic flows and air quality. The used dataset contains concentrations of NO, NO2, NOx and PM10, vehicle counts and meteorology, all collected during the COVID-19 lockdown in the city of Padova (Italy), in which severe limitations to contain the spread of the virus simulated long and large-scale traffic restrictions in normal conditions. In particular, statistical tests, correlation analyses and multivariate linear regression models were applied to non-rainy days in 2020, 2018 and 2017, in order to isolate the effect of traffic. Analysis indicated that vehicle flows significantly affect NO, NO2, and NOx concentrations, although no evidence of a relationship between traffic and PM10 was highlighted. According to this perspective, measures to limit traffic flows seem to be effective in improving air quality only in terms of reducing nitrogen oxide.

Atmospheric Emission Changes and Their Economic Impacts during the COVID-19 Pandemic Lockdown in Argentina

This work studied the emission changes and their economic effects during the Argentina’s COVID-19 pandemic lockdown. We have analyzed the atmospheric emissions of the main greenhouse gases (GHG: CO2, CH4, and N2O) and other pollutants (NOx, CO, NMVOC, SO2, PM10, PM2.5, and BC) from various sectors such as private road transport, freight, public transport, agriculture machines, thermal power plants, residential, commercial, and governmental from January 2005 to April 2020. We focused on the months with the greatest restrictions of COVID-19 pandemic in Argentina (March and April 2020). The results show emissions reduction up to 37% for PM10, PM2.5, and BC, consistent with observed from satellite images and up to 160% for NOx, CO, NMVOC, and SOx. However, the residential sector has increased their emissions by 8% for the same period. As a consequence, 3337 Gg of CO2eq of GHG emissions were reduced, corresponding to a 20% reduction compared to the same period in 2019. Besides, a 26% reduction in gross domestic product (GDP) was observed due to the COVID-19 pandemic. Our results show that each Tg of GHG reduction was associated to a 0.16% reduction of the GDP from the analyzed sectors. Thus, without a voluntary reduction in consumption associated to significant cultural and technological changes, reduction in GHG would still be associated with deepening inequalities and asymmetries between high and low consumption sectors (i.e., with better (lesser) education, health, and job opportunities), even within countries and cities.