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The COVID-19 pandemic has significantly influenced various aspects of society, including environmental factors such as methane emissions. This study investigates the changes in methane concentrations in Seoul, South Korea, from 2019 to 2023, using TROPOMI satellite data and rigorous statistical analyses. The normality of the sample data is first assessed using the Shapiro-Wilk (S-W) and Kolmogorov-Smirnov (K-S) tests, indicating that the data can be considered to come from a normal distribution. The S-W test demonstrated superior discriminative power (highest statistical power: 0.8668) compared to the K-S test (highest statistical power: 0.4002), confirming the validity of parametric tests for our data. The S-W test shows better discriminative power than the K-S test in terms of sensitivity to departures from normality, particularly for small sample sizes. Based on this confirmation, parametric tests such as analysis of variance (ANOVA) and post-hoc tests (Bonferroni correction, Tukey's HSD, Scheffe's method) are employed to identify significant differences in methane levels across different years. The ANOVA results show a statistically significant difference in methane concentrations across years (p-value: 2.02 × 10 - 13 , F-value: 26.572). Post-hoc analyses reveal no significant difference in methane concentrations between 2019 and 2020 (p-values: Bonferroni - 0.1045, Tukey's HSD - 0.397, Scheffe's - 0.1045), and no significant difference between 2020 and 2021 (p-values: Bonferroni - 0.917, Tukey's HSD - 0.840, Scheffe's - 0.917). However, a significant increase in methane levels is observed from 2022 to 2023 (p-values: Bonferroni - 0.0001, Tukey's HSD - 0.0002, Scheffe's - 0.0001), correlating with the "new normal" policy implemented in South Korea starting in November 2021 and effectively from the beginning of 2022. This suggests that changes in industrial activities and transportation patterns due to the "new normal" have contributed to higher methane emissions. Student's t-test and Welch's t-test were used to validate the ANOVA results. Permutation tests showed no significant difference between 2019 and 2020 (test statistic: -0.0096, p-values: 0.1191 for Student's and 0.1156 for Welch's). However, a significant difference was found between 2022 and 2023 (test statistic: -0.0172, p-value: 0.0001), confirming ANOVA results that indicated increased methane levels post-pandemic. This study provides a robust quantitative assessment of the pandemic's impact on methane levels and sets a methodological statistical approach for future research in the environmental research community., (© 2024. The Author(s).)

In India, the spatial coverage of air pollution data is not homogeneous due to the regionally restricted number of monitoring stations. In a such situation, utilising satellite data might greatly influence choices aimed at enhancing the environment. It is essential to estimate significant air contaminants, comprehend their health impacts, and anticipate air quality to safeguard public health from dangerous pollutants. The current study intends to investigate the spatial and temporal heterogeneity of important air pollutants, such as sulphur dioxide, nitrogen dioxide, carbon monoxide, and ozone, utilising Sentinel-5P TROPOMI satellite images. A comprehensive spatiotemporal analysis of air quality was conducted for the entire country with a special focus on five metro cities from 2019 to 2022, encompassing the pre-COVID-19, during-COVID-19, and current scenarios. Seasonal research revealed that air pollutant concentrations are highest in the winter, followed by the summer and monsoon, with the exception of ozone. Ozone had the greatest concentrations throughout the summer season. The analysis has revealed that NO 2 hotspots are predominantly located in megacities, while SO 2 hotspots are associated with industrial clusters. Delhi exhibits high levels of NO 2 pollution, while Kolkata is highly affected by SO 2 pollution compared to other major cities. Notably, there was an 11% increase in SO 2 concentrations in Kolkata and a 20% increase in NO 2 concentrations in Delhi from 2019 to 2022. The COVID-19 lockdown saw significant drops in NO 2 concentrations in 2020; specifically, - 20% in Mumbai, - 18% in Delhi, - 14% in Kolkata, - 12% in Chennai, and - 15% in Hyderabad. This study provides valuable insights into the seasonal, monthly, and yearly behaviour of pollutants and offers a novel approach for hotspot analysis, aiding in the identification of major air pollution sources. The results offer valuable insights for developing effective strategies to tackle air pollution, safeguard public health, and improve the overall environmental quality in India. The study underscores the importance of satellite data analysis and presents a comprehensive assessment of the impact of the shutdown on air quality, laying the groundwork for evidence-based decision-making and long-term pollution mitigation efforts., (© 2024. The Author(s).)

This study conducts a spatio-temporal analysis of tropospheric nitrogen dioxide (NO 2 ) and total carbon monoxide (CO) concentrations in the Punjab and Haryana regions of India and Pakistan, using datasets from the Sentinel 5-Precursor (S5P) satellite. These regions, marked by diverse economic growth factors including population expansion, power generation, transportation, and agricultural practices, face similar challenges in atmospheric pollution, particularly evident in major urban centers like Delhi and Lahore, identified as pollution hotspots. The study also spotlights pollution associated with power plants. In urban areas, tropospheric NO 2 levels are predominantly elevated due to vehicular emissions, whereas residential activities mainly contribute to CO pollution. However, precisely attributing urban CO sources is complex due to its longer atmospheric residence time and intricate circulation patterns. Notably, the burning of rice crop residue in November significantly exacerbates winter pollution episodes and smog, showing a more pronounced correlation with total CO than with tropospheric NO 2 levels. The temporal analysis indicates that the months from October to December witness peak pollution, contrasted with the relatively cleaner period during the monsoon months of July to September. The severe pollution in the OND quarter is attributed to factors such as variations in boundary layer height and depletion of OH radicals. Furthermore, the study highlights the positive impact of the COVID-19 lockdown on air quality, with a significant decrease in NO 2 concentrations during April, 2020 (Delhi: 59%, Lahore: 58%). However, the reduction in total CO columns was less significant. The study also correlates lockdown stringency with tropospheric NO 2 columns (R2: 0.37 for Delhi, 0.25 for Lahore, 0.22 for Rawalpindi/Islamabad), acknowledging the influence of various meteorological and atmospheric variables. The research highlights the significant impact of crop residue burning on winter pollution levels, particularly on total CO concentrations. The study also shows the notable effect of the COVID-19 lockdown on air quality, significantly reducing NO 2 levels. Additionally, it explores the correlation between lockdown stringency and tropospheric NO 2 columns, considering various meteorological factors., (© 2024. The Author(s), under exclusive licence to Springer Nature Switzerland AG.)

The frequency of wildfires in the western United States has escalated in recent decades. Here we examine the impacts of wildfires on ground-level ozone (O 3 ) precursors and the O 3 -NO x -VOC chemistry from the source to downwind urban areas. We use satellite retrievals of nitrogen dioxide (NO 2 ) and formaldehyde (HCHO, an indicator of VOC) from the Tropospheric Monitoring Instrument (TROPOMI) to track the evolution of O 3 precursors from wildfires over California from 2018 to 2020. We improved these satellite retrievals by updating the a priori profiles and explicitly accounting for the effects of smoke aerosols. TROPOMI observations reveal that the extensive and intense fire smoke in 2020 led to an overall increase in statewide annual average HCHO and NO 2 columns by 16% and 9%. The increase in the level of NO 2 offsets the anthropogenic NO x emission reduction from the COVID-19 lockdown. The enhancement of NO 2 within fire plumes is concentrated near the regions actively burning, whereas the enhancement of HCHO is far-reaching, extending from the source regions to urban areas downwind due to the secondary production of HCHO from longer-lived VOCs such as ethene. Consequently, a larger increase in NO x occurs in NO x -limited source regions, while a greater increase in HCHO occurs in VOC-limited urban areas, both contributing to more efficient O 3 production.

The lockdown policy deals a severe blow to the economy and greatly reduces the nitrogen oxides (NOx) emission in China when the coronavirus 2019 spreads widely in early 2020. Here we use satellite observations from Tropospheric Monitoring Instrument to study the year-round variation of the nitrogen dioxide (NO 2 ) tropospheric vertical column density (TVCD) in 2020. The NO 2 TVCD reveals a sharp drop, followed by small fluctuations and then a strong rebound when compared to 2019. By the end of 2020, the annual average NO 2 TVCD declines by only 3.4% in China mainland, much less than the reduction of 24.1% in the lockdown period. On the basis of quantitative analysis, we find the rebound of NO 2 TVCD is mainly caused by the rapid recovery of economy especially in the fourth quarter, when contribution of industry and power plant on NO 2 TVCD continues to rise. This revenge bounce of NO 2 indicates the emission reduction of NOx in lockdown period is basically offset by the recovery of economy, revealing the fact that China's economic development and NOx emissions are still not decoupled. More efforts are still required to stimulate low-pollution development., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022. Published by Elsevier B.V.)

Anthropogenic volatile organic compounds (VOCs) are serious pollutants in the atmosphere because of their toxicity and as precursors of secondary organic aerosols and ozone pollution. Although in-situ measurements provide accurate information on VOCs, their spatial coverage is limited and insufficient. In this study, we provide a global perspective for identifying anthropogenic VOC emission sources through the ratio of glyoxal to formaldehyde (RGF) based on satellite observations. We assessed typical cities and polluted areas in the mid latitudes and found that some Asian cities had higher anthropogenic VOC emissions than cities in Europe and America. For heavily polluted areas, such as the Yangtze River Delta (YRD), the areas dominated by anthropogenic VOCs accounted for 23 % of the total study areas. During the COVID-19 pandemic, a significant decline in RGF values was observed in the YRD and western United States, corresponding to a reduction in anthropogenic VOC emissions. Furthermore, developing countries appeared to have higher anthropogenic VOC emissions than developed countries. These observations could contribute to optimising industrial structures and setting stricter pollution standards to reduce anthropogenic VOCs in developing countries., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in the paper., (Copyright © 2022 Elsevier B.V. All rights reserved.)

The outbreak of coronavirus in 2019 (COVID-19) posed a serious global threat. However, the reduction in man-made pollutants during COVID-19 restrictions did improve the ecological environment of cities. Using multi-source remote sensing data, this study explored the spatiotemporal variations in air pollutant concentrations during the epidemic prevention and control period in Urumqi and quantitatively analyzed the impact of different air pollutants on the surface urban heat island intensity (SUHII) within the study area. Urumqi, located in the hinterland of the Eurasian continent, northwest of China, in the central and northern part of Xinjiang was selected as the study area. The results showed that during COVID-19 restrictions, concentrations of air pollutants decreased in the main urban area of Urumqi, and air quality improved. The most evident decrease in NO 2 concentration, by 77 ± 1.05% and 15 ± 0.98%, occurred in the middle of the first (January 25 to March 20, 2020) and second (July 21 to September 1, 2020) COVID-19 restriction periods, respectively, compared with the corresponding period in 2019. Air pollutant concentrations and the SUHIIs were significantly and positively correlated, and NO 2 exhibited the strongest correlation with the SUHIIs. We revealed that variations in the air quality characteristics and thermal environment were observed in the study area during the COVID-19 restrictions, and their quantitative relationship provides a theoretical basis and reference value for improving the air and ecological environment quality within the study area., (© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

The present study investigates the reduction in nitrogen dioxide (NO 2 ) levels using satellite-based (Sentinel-5P TROPOMI) and ground-based (Central Pollution Control Board) observations of 2020. The lockdown duration, monthly, seasonal and annual changes in NO 2 were assessed comparing the similar time period in 2019. The study also examines the role of atmospheric parameters like wind speed, air temperature, relative humidity, solar radiation and atmospheric pressure in altering the monthly and annual values of the pollutant. It was ascertained that there was a mean reduction of ~ 61% (~ 66.5%), ~ 58% (~ 51%) in daily mean NO 2 pollution during lockdown phase 1 when compared with similar period of 2019 and pre-lockdown phase in 2020 from ground-based (satellite-based) measurements. April month with ~ 57% (~ 57%), summer season with ~ 48% (~ 32%) decline and an annual reduction of ~ 20% (~ 18%) in tropospheric NO 2 values were observed (p < 0.001) compared to similar time periods of 2019. It was assessed that the meteorological parameters remained almost similar during various parts of the year in 2019 and 2020, indicating a negligent role in reducing the values of atmospheric pollution, particularly NO 2 in the study area. It was concluded that the halt in anthropogenic activities and associated factors was mainly responsible for the reduced values in the Delhi conglomerate. Similar work can be proposed for other pollutants to holistically describe the pollution scenario as an aftermath of COVID-19-induced lockdown., (© 2022. The Author(s), under exclusive licence to Springer Nature Switzerland AG.)

Nitrogen dioxide (NO 2 ) is one of the main air pollutants, formed due to both natural and anthropogenic processes, which has a significant negative impact on human health. The COVID-19 pandemic has prompted countries to take various measures, including social distancing or stay-at-home orders. This study analyzes the impact of COVID-19 lockdown measures on nitrogen dioxide (NO 2 ) changes in Central Asian countries. Data from TROPOspheric Monitoring Instrument (TROPOMI) on the Sentinel-5 Precursor satellite, as well as meteorological data, make it possible to assess changes in NO 2 concentration in countries and major cities in the region. In particular, the obtained satellite data show a decreased tropospheric column of NO 2 . Its decrease during the lockdown (March 19-April 14) ranged from - 5.1% (Tajikistan) to - 11.6% (Turkmenistan). Based on the obtained results, it can be concluded that limitations in anthropogenic activities have led to improvements in air quality. The possible influence of meteorology is not assessed in this study, and the implied uncertainties cannot be quantified. In this way, the level of air pollution is expected to decrease as long as partial or complete lockdown continues., (© 2021. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

The unequal spatial distribution of ambient nitrogen dioxide ([Formula: see text]), an air pollutant related to traffic, leads to higher exposure for minority and low socioeconomic status communities. We exploit the unprecedented drop in urban activity during the COVID-19 pandemic and use high-resolution, remotely sensed [Formula: see text] observations to investigate disparities in [Formula: see text] levels across different demographic subgroups in the United States. We show that, prior to the pandemic, satellite-observed [Formula: see text] levels in the least White census tracts of the United States were nearly triple the [Formula: see text] levels in the most White tracts. During the pandemic, the largest lockdown-related [Formula: see text] reductions occurred in urban neighborhoods that have 2.0 times more non-White residents and 2.1 times more Hispanic residents than neighborhoods with the smallest reductions. [Formula: see text] reductions were likely driven by the greater density of highways and interstates in these racially and ethnically diverse areas. Although the largest reductions occurred in marginalized areas, the effect of lockdowns on racial, ethnic, and socioeconomic [Formula: see text] disparities was mixed and, for many cities, nonsignificant. For example, the least White tracts still experienced ∼1.5 times higher [Formula: see text] levels during the lockdowns than the most White tracts experienced prior to the pandemic. Future policies aimed at eliminating pollution disparities will need to look beyond reducing emissions from only passenger traffic and also consider other collocated sources of emissions such as heavy-duty vehicles., Competing Interests: The authors declare no competing interest., (Copyright © 2021 the Author(s). Published by PNAS.)

Lockdown restrictions were implemented in Italy from 10 March 2020 to contain the COVID-19 pandemic. Our study aims to evaluate air pollution changes, with focus on nitrogen dioxide (NO 2 ), before and during the lockdown in Rome and in the surroundings. Significant NO 2 declines were observed during the COVID-19 pandemic with reductions of - 50%, - 34%, and - 20% at urban traffic, urban background, and rural background stations, respectively. Tropospheric NO 2 vertical column density (VCD) from the TROPOspheric Monitoring Instrument (TROPOMI) was used to evaluate the spatial-temporal variations of the NO 2 before and during the lockdown for the entire area where the surface stations are located. The evaluation is concerned with the pixels including one or more air quality stations to explore the capability of the unprecedented high spatial resolution to monitor urban and rural sites from space with relation to the surface measurements. Good agreement between surface concentration and TROPOMI VCD was obtained in Rome (R = 0.64 in 2019, R = 0.77 in 2020) and in rural sites (R = 0.71 in 2019). Inversely, a slight correlation (R = 0.20) was observed in rural areas during the lockdown due to very low levels of NO 2 . Finally, the TROPOMI VCD showed a sharp decline in NO 2 , larger in urban (- 43%) than in rural sites (- 17%) as retrieved with the concurrent surface measurements averaging all the traffic and urban background (- 44%) and all the rural background stations (- 20%). These results suggest air pollution improvement in Rome gained from implementing lockdown restrictions.

Clean air is a fundamental necessity for human health and well-being. Anthropogenic emissions that are harmful to human health have been reduced substantially under COVID-19 lockdown. Satellite remote sensing for air pollution assessments can be highly effective in public health research because of the possibility of estimating air pollution levels over large scales. In this study, we utilized both satellite and surface measurements to estimate air pollution levels in 20 cities across the world. Google Earth Engine (GEE) and Sentinel-5 Precursor TROPOspheric Monitoring Instrument (TROPOMI) application were used for both spatial and time-series assessment of tropospheric Nitrogen Dioxide (NO 2 ) and Carbon Monoxide (CO) statuses during the study period (1 February to May 11, 2019 and the corresponding period in 2020). We also measured Population-Weighted Average Concentration (PWAC) of particulate matter (PM 2.5 and PM 10 ) and NO 2 using gridded population data and in-situ air pollution estimates. We estimated the economic benefit of reduced anthropogenic emissions using two valuation approaches: (1) the median externality value coefficient approach, applied for satellite data, and (2) the public health burden approach, applied for in-situ data. Satellite data have shown that ~28 tons (sum of 20 cities) of NO 2 and ~184 tons (sum of 20 cities) of CO have been reduced during the study period. PM 2.5 , PM 10 , and NO 2 are reduced by ~37 (μg/m 3 ), 62 (μg/m 3 ), and 145 (μg/m 3 ), respectively. A total of ~1310, ~401, and ~430 premature cause-specific deaths were estimated to be avoided with the reduction of NO 2 , PM 2.5 , and PM 10 . The total economic benefits (Billion US$) (sum of 20 cities) of the avoided mortality are measured as ~10, ~3.1, and ~3.3 for NO 2 , PM 2.5 , and PM 10 , respectively. In many cases, ground monitored data was found inadequate for detailed spatial assessment. This problem can be better addressed by incorporating satellite data into the evaluation if proper quality assurance is achieved, and the data processing burden can be alleviated or even removed. Both satellite and ground-based estimates suggest the positive effect of the limited human interference on the natural environments. Further research in this direction is needed to explore this synergistic association more explicitly., (Copyright © 2021 The Author(s). Published by Elsevier Inc. All rights reserved.)

During the outbreak of the coronavirus disease 2019 (COVID-19) in China in January and February 2020, production and living activities were drastically reduced to impede the spread of the virus, which also caused a strong reduction of the emission of primary pollutants. However, as a major species of secondary air pollutant, tropospheric ozone did not reduce synchronously, but instead rose in some region. Furthermore, higher concentrations of ozone may potentially promote the rates of COVID-19 infections, causing extra risk to human health. Thus, the variation of ozone should be evaluated widely. This paper presents ozone profiles and tropospheric ozone columns from ultraviolet radiances detected by TROPOospheric Monitoring Instrument (TROPOMI) onboard Sentinel 5 Precursor (S5P) satellite based on the principle of optimal estimation method. We compare our TROPOMI retrievals with global ozonesonde observations, Fourier Transform Spectrometry (FTS) observation at Hefei (117.17°E, 31.7°N) and Global Positioning System (GPS) ozonesonde sensor (GPSO 3 ) ozonesonde profiles at Beijing (116.46°E, 39.80°N). The integrated Tropospheric Ozone Column (TOC) and Stratospheric Ozone Column (SOC) show excellent agreement with validation data. We use the retrieved TOC combining with tropospheric vertical column density (TVCD) of NO 2 and HCHO from TROPOMI to assess the changes of tropospheric ozone during the outbreak of COVID-19 in China. Although NO 2 TVCD decreased by 63%, the retrieved TOC over east China increase by 10% from the 20-day averaged before the lockdown on January 23, 2020 to 20-day averaged after it. Because the production of ozone in winter is controlled by volatile organic compounds (VOCs) indicated by monitored HCHO, which did not present evident change during the lockdown, the production of ozone did not decrease significantly. Besides, the decrease of NO x emission weakened the titration of ozone, causing an increase of ozone., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2020 Elsevier B.V. All rights reserved.)

This study leverages satellite remote sensing to investigate the impact of the coronavirus outbreak and the resulting lockdown of public venues on air pollution levels in East Asia. We analyze data from the Sentinel-5P and the Himawari-8 satellites to examine concentrations of NO 2 , HCHO, SO 2 , and CO, and the aerosol optical depth (AOD) over the BTH, Wuhan, Seoul, and Tokyo regions in February 2019 and February 2020. Results show that most of the concentrations of pollutants are lower than those of February 2019. Compared to other pollutants, NO 2 experienced the most significant reductions by almost 54%, 83%, 33%, and 19% decrease in BTH, Wuhan, Seoul, and Tokyo, respectively. The greatest reductions in pollutants occurred in Wuhan, with a decrease of almost 83%, 11%, 71%, and 4% in the column densities of NO 2 , HCHO, SO 2 , and CO, respectively, and a decrease of about 62% in the AOD. Although NO 2 , CO, and formaldehyde concentrations decreased in the Seoul and Tokyo metropolitan areas compared to the previous year, concentrations of SO 2 showed an increase in these two regions due to the effect of transport from polluted upwind regions. We also show that meteorological factors were not the main reason for the dramatic reductions of pollutants in the atmosphere. Moreover, an investigation of the HCHO/NO 2 ratio shows that in many regions of East China, particularly in Wuhan, ozone production in February 2020 is less NO X saturated during the daytime than it was in February 2019. With large reductions in the concentrations of NO 2 during lockdown situations, we find that significant increases in surface ozone in East China from February 2019 to February 2020 are likely the result of less reaction of NO and O 3 caused by significantly reduced NO X concentrations and less NO X saturation in East China during the daytime., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2020 Elsevier B.V. All rights reserved.)

Abstract The COVID-19 pandemic has significantly influenced various aspects of society, including environmental factors such as methane emissions. This study investigates the changes in methane concentrations in Seoul, South Korea, from 2019 to 2023, using TROPOMI satellite data and rigorous statistical analyses. The normality of the sample data is first assessed using the Shapiro-Wilk (S-W) and Kolmogorov-Smirnov (K-S) tests, indicating that the data can be considered to come from a normal distribution. The S-W test demonstrated superior discriminative power (highest statistical power: 0.8668) compared to the K-S test (highest statistical power: 0.4002), confirming the validity of parametric tests for our data. The S-W test shows better discriminative power than the K-S test in terms of sensitivity to departures from normality, particularly for small sample sizes. Based on this confirmation, parametric tests such as analysis of variance (ANOVA) and post-hoc tests (Bonferroni correction, Tukey’s HSD, Scheffe’s method) are employed to identify significant differences in methane levels across different years. The ANOVA results show a statistically significant difference in methane concentrations across years (p-value: $$2.02\times 10^{-13}$$ 2.02 × 10 - 13 , F-value: 26.572). Post-hoc analyses reveal no significant difference in methane concentrations between 2019 and 2020 (p-values: Bonferroni - 0.1045, Tukey’s HSD - 0.397, Scheffe’s - 0.1045), and no significant difference between 2020 and 2021 (p-values: Bonferroni - 0.917, Tukey’s HSD - 0.840, Scheffe’s - 0.917). However, a significant increase in methane levels is observed from 2022 to 2023 (p-values: Bonferroni - 0.0001, Tukey’s HSD - 0.0002, Scheffe’s - 0.0001), correlating with the “new normal” policy implemented in South Korea starting in November 2021 and effectively from the beginning of 2022. This suggests that changes in industrial activities and transportation patterns due to the “new normal” have contributed to higher methane emissions. Student’s t-test and Welch’s t-test were used to validate the ANOVA results. Permutation tests showed no significant difference between 2019 and 2020 (test statistic: -0.0096, p-values: 0.1191 for Student’s and 0.1156 for Welch’s). However, a significant difference was found between 2022 and 2023 (test statistic: -0.0172, p-value: 0.0001), confirming ANOVA results that indicated increased methane levels post-pandemic. This study provides a robust quantitative assessment of the pandemic’s impact on methane levels and sets a methodological statistical approach for future research in the environmental research community.

The urban environment is at substantial risk due to the pace of urbanization. There are two major components of the urban environment viz. urban heating and urban pollution. The outbreak of the COVID-19 pandemic and the associated lockdown provided a stability to the deteriorating environment and all associated parameters. The study focuses on understanding the changes in the surface urban heat island (SUHI) and atmospheric/near-surface urban pollution island phenomenon (AUPI/NSUPI) as a result of lockdown in 2020 and 2021 w.r.t. averaged values of 2017–19, through parameters like LST, AOD, NO2 and PM2.5 for the Delhi region (Delhi urban area or DUA and non-urban area surrounding DUA) using in situ and remote sensing satellite measurements. A remarkable reduction in mean daytime/nighttime LST (1.99 °C/1.80 °C) using MODIS datasets and 5.46 °C using Landsat datasets was observed in LD-1 of 2020. SUHII values were 0.35 °C higher in 2020 as compared to 2017–19 due to thriving vegetation. Similarly, annual NO2/PM2.5 reduced by 61.39%/11.78% and satellite-based NO2/AOD reduced by 28.87%/9% in 2020 compared to 2017–19. A yearly reduction of ~ 41%, ~ 6%, ~ 10% and ~ 39% was observed in NSUPII (NO2), NSUPII (PM2.5), AUPII (AOD) and AUPII (NO2), respectively. The environmental regime of the urban purlieu was revitalized, and the ecological sensitiveness was restored by vegetation growth and reduced anthropogenic activities; however, the scenario was quickly restored in 2021 showing increased pollution levels. [ABSTRACT FROM AUTHOR]

In this study, the changes in nitrogen dioxide (NO2), carbon monoxide (CO) and sulfur dioxide (SO2) pollutant gases were examined between June 2019 and June 2021 during the COVID-19 pandemic period. For this purpose, monthly and annual averages of Sentinel-5P TROPOspheric Monitoring Instrument (TROPOMI) values were calculated on the Google Earth Engine (GEE) platform. According to the results obtained using the GEE platform, the average column density values of NO2, CO, and SO2 in the Marmara Region between the selected dates were calculated as 8.40E-05 mol/m2, 3.23E-02 mol/m2, and 3.75E-04 mol/m2, respectively. During the lockdown, these values decreased to 7.84E-05 mol/m2, 3.05E-02 mol/m2 and 2.75E-04 mol/m2 respectively. According to TROPOMI data, these three gas column density values showed a decreasing trend during the COVID-19 pandemic lockdown period. However, in a 25-month examination in general, these three gas values showed an increasing trend due to population growth, industrialization, and increasing traffic density.

The variation of tropospheric nitrogen dioxide (NO2) vertical column densities (VCDs) indirectly reflects the difference in pollution emissions from industrial production and transportation. Accurately analyzing its pollution sources and driving factors plays an important role in energy conservation, emission reduction, and air pollution reduction. NO2 concentration products of Sentinel-5P (Sentinel-5 Precursor) TROPOMI (TROPOspheric Monitoring Instrument) from 2019 to 2021 and Aura OMI (Ozone Monitoring Instrument) from 2009 to 2021, combined with China’s main energy consumption, the growth value of the industry, Gross Domestic Product (GDP), and other data were used to analyze the influencing factors of NO2 variations. Firstly, NO2 tropospheric vertical column densities (NO2 TVCDs) of China increased by 14.72% and 3.26% in 2021 and 2020 compared with the 2019. The secondary and tertiary industry and the national energy consumption increased synchronously, which was highly related to the increase in NO2 TVCDs. Secondly, the impact of COVID-19 (coronavirus disease 2019) on China’s industrial production and residents was mainly concentrated in the first quarter of 2020, which leading to a decline in the annual average NO2 concentration in densely populated areas in 2020 compared to the same period in 2019. The industrial production scale and production capacity has gradually recovered since April 2020, and the NO2 concentration has gradually reached or exceeded the level of the same period of 2019. Finally, atmospheric pollution prevention and control measures played a positive role in the decline of NO2 of China.

Satellite instruments have the most potential of capturing trace gas variability as they continually observe the atmosphere and its composition over wide regions. Yet the increasingly large data size of satellite products poses a challenge for their use as traditional data processing methods (e.g., averaging) may not be effective to extract the spatiotemporal variability without prior knowledge of an emission source's spatial and temporal behavior, such as location, time, and plume shape. Here, an agile clustering algorithm entitled CLustering of Atmospheric Satellite Products (CLASP) is presented to identify the spatiotemporal variability of trace gases captured in satellite observations. We find the knowledge discovery method for large data sets, clustering, is suited for identifying the variability of trace gases in satellite observations, as such CLASP is rooted in density‐based clustering methods. CLASP detects features from satellite observations and identifies their spatial, magnitude, and temporal axis leading to a better understanding of the spatiotemporal variability of atmospheric trace gases. To test the applicability of CLASP, the algorithm is applied to TROPOspheric Monitoring Instrument NO2 observations illustrating some of its different capabilities. Implementing CLASP for event identification, capturing plume variability, and source detection, CLASP identified wildfires, observed disruptions from COVID‐19 lockdown restrictions, and detected irregular emissions from oil and gas operations. Plain Language Summary: Satellite instruments capture the location and timing of trace gases as they have daily observations of the atmosphere over a wide spatial coverage. With increasing spatial and temporal resolutions of satellite products, traditional data‐reducing methods such as averaging could be insufficient in analyzing increasingly large satellite observations. The user must have prior knowledge of the location and temporal behavior of emission sources in order to choose the suitable averaging intervals and such information is often lacking or unreliable for non‐urban and point sources. To alleviate this limitation, a clustering algorithm titled CLustering of Atmospheric Satellite Products (CLASP) is presented in this work. CLASP identifies features in satellite observations by their location, amount, and time. CLASP was applied to the satellite observational data set, TROPOspheric Monitoring Instrument NO2, to identify wildfires, observe COVID‐19 lockdown changes, and spot irregular emissions from oil and gas operations. Key Points: Density‐based clustering provides a foundation when built upon can describe the spatiotemporal variability of atmospheric trace gasesA clustering algorithm entitled CLustering of Atmospheric Satellite Products (CLASP) is presented to describe observations of trace gasesCLASP is applied to TROPOspheric Monitoring Instrument NO2 observations for event identification, plume variability, and source identification [ABSTRACT FROM AUTHOR]

Copyright of Journal of Remote Sensing is the property of Editorial Office of Journal of Remote Sensing & Science Publishing Co. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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In this study, the changes in nitrogen dioxide (NO2), carbon monoxide (CO) and sulfur dioxide (SO2) pollutant gases were examined between June 2019 and June 2021 during the COVID-19 pandemic period. For this purpose, monthly and annual averages of Sentinel-5P TROPOspheric Monitoring Instrument (TROPOMI) values were calculated on the Google Earth Engine (GEE) platform. According to the results obtained using the GEE platform, the average column density values of NO2, CO, and SO2 in the Marmara Region between the selected dates were calculated as 8.40E-05 mol/m2, 3.23E-02 mol/m², and 3.75E-04 mol/m², respectively. During the lockdown, these values decreased to 7.84E-05 mol/m2 , 3.05E-02 mol/m² and 2.75E-04 mol/m² respectively. According to TROPOMI data, these three gas column density values showed a decreasing trend during the COVID-19 pandemic lockdown period. However, in a 25-month examination in general, these three gas values showed an increasing trend due to population growth, industrialization, and increasing traffic density. [ABSTRACT FROM AUTHOR]

Governments around the world took unprecedented measures, such as social distancing and the minimization of public/industrial activity, in response to the COVID-19 pandemic in 2020. This provided a unique chance to assess the relationships between key air pollutant emissions and track the reductions in these emissions in various countries during the lockdown. This study considers atmospheric air pollution in the 78 largest Russian cities (with populations over 250,000) in March–June of 2019–2021. This is the first such study for the largest cities in Russia. The initial data were the TROPOMI measurements (Sentinel-5P satellite) of such pollutants as carbon monoxide (CO), formaldehyde (HCHO), nitrogen dioxide (NO2), and sulfur dioxide (SO2), which are the main anthropogenic pollutants. The data were downloaded from the Google Earth Engine's cloud-based geospatial data platform. This provided L3-level information for subsequent analysis. The TROPOMI data indicated a decrease in the atmospheric content of the air pollutants in the largest Russian cities during the lockdown compared to the pre-pandemic and post-pandemic periods. The reduced economic activity due to the COVID-19 pandemic had the greatest impact on NO2 concentrations. The average reduction was −30.7%, while the maximum reduction was found within Moscow city limits that existed before 01.07.2012 (−41% with respect to the 2019 level). For sulfur dioxide, the average decrease was only 7%, with a further drop in 2021 (almost 20% relative to 2019). For formaldehyde and carbon monoxide, there were no reductions during the 2020 lockdown period (99.4% and 100.9%, respectively, with respect to 2019). The identified impacts of the COVID-19 lockdown on NO2, SO2, HCHO, and CO NO2 concentrations in major Russian cities generally followed the patterns observed in other industrialized cities in China, India, Turkey, and European countries. The COVID-19 pandemic had a local impact on NO2 concentration reductions in major Russian cities. The differences leveled off over time, and the baseline pollution level for each pollutant was restored. [ABSTRACT FROM AUTHOR]

The lockdowns from the coronavirus disease of 2019 (COVID-19) have led to a reduction in anthropogenic activities and have hence reduced primary air pollutant emissions, which were reported to have helped air quality improvements. However, air quality expressed by the air quality index (AQI) did not improve in Shanghai, China, during the COVID-19 outbreak in the spring of 2022. To better understand the reason, we investigated the variations of nitrogen dioxide (NO2), ozone (O3), PM2.5 (particular matter with an aerodynamic diameter of less than 2.5 μm), and PM10 (particular matter with an aerodynamic diameter of less than 10 μm) by using in situ and satellite measurements from 1 March to 31 June 2022 (pre-, full-, partial-, and post-lockdown periods). The results show that the benefit of the significantly decreased ground-level PM2.5, PM10, and NO2 was offset by amplified O3 pollution, therefore leading to the increased AQI. According to the backward trajectory analyses and multiple linear regression (MLR) model, the anthropogenic emissions dominated the observed changes in air pollutants during the full-lockdown period relative to previous years (2019–2021), whereas the long-range transport and local meteorological parameters (temperature, air pressure, wind speed, relative humidity, and precipitation) influenced little. We further identified the chemical mechanism that caused the increase in O3 concentration. The amplified O3 pollution during the full-lockdown period was caused by the reduction in anthropogenic nitrogen oxides (NOx) under a VOC-limited regime and high background O3 concentrations owing to seasonal variations. In addition, we found that in the downtown area, ground-level PM2.5, PM10, and NO2 more sensitively responded to the changes in lockdown measures than they did in the suburbs. These findings provide new insights into the impact of emission control restrictions on air quality and have implications for air pollution control in the future. [ABSTRACT FROM AUTHOR]

The tropospheric NO2 column from Sentinel-5P/TROPOMI (2018–2020) and Aura/OMI (2010–2020) over Poland, notably for 7 major Polish cities, was used to assess the annual variability and the COVID-19 lockdown effect. On a national scale, during lockdown (March–June 2020), strong sources of pollution were found in Katowice and Warszawa, as well as at the power plant in Bełchatów. A gradual drop in OMI NO2 values between March and June was found for all cities and the entire domain of Poland, this being a part of the annual NO2 cycle derived for every year from 2010 to 2020. In fact, the gradual drop of NO2 in the lockdown year was within the typical monthly and annual variability. In March 2020, Kraków showed the highest NO2 reduction rate. A reduction of NO2 was observed in Gdańsk, Wrocław, and Warszawa during every month of the lock-down period. Several factors, including wind speed and direction, temperature, and increased emission sources, can limit the dispersion and removal of NO2. Although meteorological conditions have a significant impact on the annual cycle of NO2 in Poland, it is important to note that anthropogenic emissions remain the primary driver of NO2 concentrations. Therefore, the study concludes that the effect of COVID-19 restrictions on NO2 pollution was negligible and clarifies the current understanding of the COVID-19 effect over Poland, with an emphasis on hotspots in the major Polish cities and their vicinity. This is consistent with our understanding that the reduction of NO2 pollution is seen in cities due to reduced traffic (domestic, municipal, and airborne).

The first case of COVID-19 in Iran was reported on 19 February 2020, 1 month before the Nowruz holidays coincided with the global pandemic, leading to quarantine and lockdown. Many studies have shown that environmental pollutants were drastically reduced with the spread of this disease and the decline in industrial activities. Among these pollutants, nitrogen dioxide (NO2) and carbon monoxide (CO) are widely caused by anthropogenic and industrial activities. In this study, the changes in these pollutants in Iran and its four metropolises (i.e., Tehran, Mashhad, Isfahan, and Tabriz) in three periods from 11 March to 8 April 2019, 2020, and 2021 were investigated. To this end, timeseries of the Sentinel-5P TROPOMI and in situ data within the Google Earth Engine (GEE) cloud-based platform were employed. It was observed that the results of the NO2 derived from Sentinel-5P were in agreement with the in situ data acquired from ground-based stations (average correlation coefficient = 0.7). Moreover, the results showed that the concentration of NO2 and CO pollutants in 2020 (the first year of the COVID-19 pandemic) was 5% lower than in 2019, indicating the observance of quarantine rules, as well as people’s initial fear of the coronavirus. Contrarily, these pollutants in 2021 (the second year of the COVID-19 pandemic) were higher than those in 2020 by 5%, which could have been due to high vehicle traffic and a lack of serious policy- and law-making by the government to ban urban and interurban traffic. These findings are essential criteria that might be used to guide future manufacturing logistics, traffic planning and management, and environmental sustainability policies and plans. Furthermore, using the COVID-19 scenario and free satellite-derived data, it is now possible to investigate how harmful gas emissions influence air quality. These findings may also be helpful in making future strategic decisions on how to cope with the virus spread and lessen its negative social and economic consequences.

The present study investigates the reduction in nitrogen dioxide (NO2) levels using satellite-based (Sentinel-5P TROPOMI) and ground-based (Central Pollution Control Board) observations of 2020. The lockdown duration, monthly, seasonal and annual changes in NO2 were assessed comparing the similar time period in 2019. The study also examines the role of atmospheric parameters like wind speed, air temperature, relative humidity, solar radiation and atmospheric pressure in altering the monthly and annual values of the pollutant. It was ascertained that there was a mean reduction of ~ 61% (~ 66.5%), ~ 58% (~ 51%) in daily mean NO2 pollution during lockdown phase 1 when compared with similar period of 2019 and pre-lockdown phase in 2020 from ground-based (satellite-based) measurements. April month with ~ 57% (~ 57%), summer season with ~ 48% (~ 32%) decline and an annual reduction of ~ 20% (~ 18%) in tropospheric NO2 values were observed (p < 0.001) compared to similar time periods of 2019. It was assessed that the meteorological parameters remained almost similar during various parts of the year in 2019 and 2020, indicating a negligent role in reducing the values of atmospheric pollution, particularly NO2 in the study area. It was concluded that the halt in anthropogenic activities and associated factors was mainly responsible for the reduced values in the Delhi conglomerate. Similar work can be proposed for other pollutants to holistically describe the pollution scenario as an aftermath of COVID-19-induced lockdown. [ABSTRACT FROM AUTHOR]

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

Lockdowns imposed across the world to combat the spread of the COVID-19 pandemic also reduced the anthropogenic emissions. This study investigates the changes in the anthropogenic and natural pollution levels during the lockdown over the Arabian Peninsula (AP), a region where natural pollutants (mineral dust) dominate. In-situ and satellite observations, reanalysis products, and Weather Research and Forecasting model (WRF) coupled with Chemistry module (WRF-Chem) simulations were analyzed to investigate the influence of COVID−19 lockdown on the aerosols (PM2.5, PM10, and AOD) and trace gases (NO2 and SO2). WRF-Chem reasonably reproduced the satellite and in-situ measurements during the study period, with correlation coefficients varying between 0.6–0.8 (0.3–0.8) for PM10 (NO2 and SO2) at 95% confidence levels. During the lockdown, WRF-Chem simulations indicate a significant reduction (50–60%) in the trace gas concentrations over the entire AP compared to the pre-lockdown period. This is shown to be mostly due to a significant reduction in the emissions and an increase in the boundary layer height. An increase in the aerosol concentrations over the central and northern parts of the AP, and a decrease over the north-west AP, Red Sea, and Gulf of Aden regions are noticeable during the lockdown. WRF-Chem simulations suggest that the increase in particulate concentrations over the central and northern AP during the lockdown is mainly due to an increase in dust concentrations, manifested by the stronger convergence and upliftment of winds and warmer surface temperatures (15–25%) over the desert regions. The restricted anthropogenic activities drastically reduced the trace gas concentrations, however, the reduction in particulate concentration levels is offset by the increase in the natural processes (dust emissions).

Nitrogen dioxide (NO2) is one of the main air pollutants, formed due to both natural and anthropogenic processes, which has a significant negative impact on human health. The COVID-19 pandemic has prompted countries to take various measures, including social distancing or stay-at-home orders. This study analyzes the impact of COVID-19 lockdown measures on nitrogen dioxide (NO2) changes in Central Asian countries. Data from TROPOspheric Monitoring Instrument (TROPOMI) on the Sentinel-5 Precursor satellite, as well as meteorological data, make it possible to assess changes in NO2 concentration in countries and major cities in the region. In particular, the obtained satellite data show a decreased tropospheric column of NO2. Its decrease during the lockdown (March 19–April 14) ranged from − 5.1% (Tajikistan) to − 11.6% (Turkmenistan). Based on the obtained results, it can be concluded that limitations in anthropogenic activities have led to improvements in air quality. The possible influence of meteorology is not assessed in this study, and the implied uncertainties cannot be quantified. In this way, the level of air pollution is expected to decrease as long as partial or complete lockdown continues. [ABSTRACT FROM AUTHOR]

The novel coronavirus (COVID-19) infectious respiratory disease becomes a global pandemic in few weeks from its start in December 2019 to early 2020. Various countries across the world including China went to lockdown and several caution were implemented to reduce the further spread of this infectious disease. Wuhan (China) was the first city to impose the lockdown for controlling the impact of COVID-19. The lockdown unexpectedly gives the scientific community a chance to investigate the influence of the human activity on air pollution in real world scenario. The present study attempted to investigate the impact of lockdown during the ongoing viral disease on the changes of fine particulate matters and some unhealthy gases i.e. PM2.5, PM10, SO2, CO, O3, AQI and NO2 over Hubei province of China, by using ground station data and TROPOMI satellite data. The air pollutants were compared as, (i) pre COVID-19 period (i.e. October-December 2019), (ii) throughout the lockdown in Hubei province (i.e. January 2020-March 2020) and Post lockdown duration (i.e. April 2020-June 2020). Results clearly showed that air quality was not secured due to high emission of CO, SO2, NO2, O3, PM2.5, and PM10 on Pre COVID-19 times, but under the lockdown continuously decrease in NO2 from (54 mg/cm3 to 26 mg/cm3), SO2 (10.5 mg/cm3 to 7.77 mg/cm3) PM2.5 (49.22 mg/cm3 to 44.34 mg/cm3), PM10 concentrations (80.83 mg/cm3 to 57.04 mg/cm3) and AQI (72.95 mg/cm3 to 49.64 mg/cm3) has been observed. Because lockdown shuts all anthropogenic activities like industrial work, traffic vehicles and various socio-economic activities, which developed a healthy change on air quality. Emission of unhealthy gases and particulates were quite clear during the lockdown but again increase after finishing the lockdown period. However, we don’t support the lockdown as a measure for the betterment of air quality as this has severely posed negative impacts on the socio-economic processes and progress, but changes in human behavior of using industries and vehicles can help us to improve the air quality.

The SARS-CoV-2 (Severe Acute Respiratory Syndrome-related Coronavirus 2) and its concomitant disease COVID-19 (Coronavirus Disease 2019), discovered at the end of December 2019, have spread around the world, becoming a global public health problem. To prevent the spread of COVID-19, the Chinese government took strict lockdown measures in early 2020 in many cities. The purpose of this study was to evaluate changes in air quality in Shanghai, China's most populous city during the lockdown. Lockdown measures led to a decrease in anthropogenic activity and a concomitant reduction in air pollutant emissions, which led to a temporary improvement in air quality. Mean daily concentrations of PM2.5, PM10, SO2 and NO2 during a 2-week portion of the lockdown period (24 January–6 February) were respectively reduced by −19.2%, −44.7%, −21.5% and −33.6% compared to the same period in 2019. Even with the decrease in PM2.5 and PM10 concentrations, they were still more than four times higher than the World Health Organization standards (10 μg/m3 and 20 μg/m3, respectively). This study provides data useful for evaluating existing environmental policy, as it showed how the control of pollution sources can affect air quality. [ABSTRACT FROM AUTHOR]

The lockdowns from the coronavirus disease of 2019 (COVID-19) have led to a reduction in anthropogenic activities and have hence reduced primary air pollutant emissions, which were reported to have helped air quality improvements. However, air quality expressed by the air quality index (AQI) did not improve in Shanghai, China, during the COVID-19 outbreak in the spring of 2022. To better understand the reason, we investigated the variations of nitrogen dioxide (NO2), ozone (O3), PM2.5 (particular matter with an aerodynamic diameter of less than 2.5 μm), and PM10 (particular matter with an aerodynamic diameter of less than 10 μm) by using in situ and satellite measurements from 1 March to 31 June 2022 (pre-, full-, partial-, and post-lockdown periods). The results show that the benefit of the significantly decreased ground-level PM2.5, PM10, and NO2 was offset by amplified O3 pollution, therefore leading to the increased AQI. According to the backward trajectory analyses and multiple linear regression (MLR) model, the anthropogenic emissions dominated the observed changes in air pollutants during the full-lockdown period relative to previous years (2019–2021), whereas the long-range transport and local meteorological parameters (temperature, air pressure, wind speed, relative humidity, and precipitation) influenced little. We further identified the chemical mechanism that caused the increase in O3 concentration. The amplified O3 pollution during the full-lockdown period was caused by the reduction in anthropogenic nitrogen oxides (NOx) under a VOC-limited regime and high background O3 concentrations owing to seasonal variations. In addition, we found that in the downtown area, ground-level PM2.5, PM10, and NO2 more sensitively responded to the changes in lockdown measures than they did in the suburbs. These findings provide new insights into the impact of emission control restrictions on air quality and have implications for air pollution control in the future.

An unprecedented city-wide lockdown took place in Shanghai from April to May 2022 to curb the spread of COVID-19, which caused socio-economic disruption but a significant reduction of anthropogenic emissions in this metropolis. However, the ground-based monitoring data showed that the concentration of ozone (O3) remained at a high level. This study applied Tropospheric Monitoring Instrument (TROPOMI) observations to examine changes in tropospheric vertical column density (VCD) of nitrogen dioxide (NO2) and formaldehyde (HCHO), which are precursors of O3. Compared with the same period in 2019–2021, VCDs of NO2 and HCHO decreased respectively by ~50% and ~20%. Multiple regression analysis showed that the lockdown effect played a dominant role in this dramatic decline rather than meteorological impacts. Using the exponentially-modified Gaussian method, this study quantified nitrogen oxides (NOX) emission in Shanghai as 32.60 mol/s with a decrease of 50–80%, which was mainly contributed by the transportation and industrial sectors. The significant reduction of NOX emission in Shanghai is much higher than that of volatile organic compounds (VOCs), which led to dramatic changes in formaldehyde-to-nitrogen dioxide ratio (HCHO/NO2, FNR). Thus, when enforcing regulation on NOx emission control in the future, coordinately reducing VOCs emission should be implemented to mitigate urban O3 pollution.

Since its first confirmed case in December 2019, coronavirus disease 2019 (COVID-19) has become a worldwide pandemic with more than 90 million confirmed cases by January 2021. Countries around the world have enforced lockdown measures to prevent the spread of the virus, introducing a temporal change of air pollutants such as nitrogen dioxide (NO2) that are strongly related to transportation, industry, and energy. In this study, NO2 variations over regions with strong responses to COVID-19 are analysed using datasets from the Global Ozone Monitoring Experiment-2 (GOME-2) sensor aboard the EUMETSAT Metop satellites and TROPOspheric Monitoring Instrument (TROPOMI) aboard the EU/ESA Sentinel-5 Precursor satellite. The global GOME-2 and TROPOMI NO2 datasets are generated at the German Aerospace Center (DLR) using harmonized retrieval algorithms; potential influences of the long-term trend and seasonal cycle, as well as the short-term meteorological variation, are taken into account statistically. We present the application of the GOME-2 data to analyze the lockdown-related NO2 variations for morning conditions. Consistent NO2 variations are observed for the GOME-2 measurements and the early afternoon TROPOMI data: regions with strong social responses to COVID-19 in Asia, Europe, North America, and South America show strong NO2 reductions of ∼ 30–50% on average due to restriction of social and economic activities, followed by a gradual rebound with lifted restriction measures. [ABSTRACT FROM AUTHOR]

Most countries around the world, including the United States, took actions to control COVID‐19 spread that led to an abrupt shift in human activity. On‐road NOx emissions from light and heavy‐duty vehicles decreased by 9%–19% between February and March at the onset of the lockdown period in the middle of March in most of the US; between March and April, the on‐road NOx emissions dropped further by 8%–31% when lockdown measures were most stringent. These precipitous drops in NOx emissions correlated well (r = 0.75) with tropospheric NO2 column amount observed by the Sentinel 5 Precursor TROPOspheric Monitoring Instrument (S5P TROPOMI). Furthermore, the changes in TROPOMI tropospheric NO2 column amount across continental US between 2020 and 2019 correlated well with the changes in on‐road NOx emissions (r = 0.68) but correlated weakly with changes in emissions from the power plants (r = 0.35). At the height of lockdown‐related unemployment in the second quarter of 2020, the tropospheric NO2 column values decreased at the rate of 0.8 µmoles/m2 per unit percentage increase in the unemployment rate. Despite the lifting of lockdown measures, parts of the US continued to have ∼20% below normal on‐road NOx emissions. To achieve this new normal urban air quality in the US, continuing remote work policies that do not impede economic growth may become one of the many options. Plain Language Summary: This study documents the different phases of COVID‐19 lockdown in 2020 and how traffic emissions changed accordingly across the US, particularly in five different cities, namely Los Angeles, San Francisco, San Joaquin Valley, New York City, and Atlanta. Analysis of data for these cities from measurements on the ground and satellites indicate that a downturn in the economy and telework policies reduced the number of cars and trucks on the road in March and April due to which air quality got better. The recovery of traffic emissions after the lockdowns was lifted was slow and below normal emissions were observed even at the end of 2020. While the cities in the east reached near normal levels, the west coast showed below normal traffic emissions. The air quality in 2020 provided a window into the future as to how improvements can be achieved. Key Points: COVID‐19 lockdown‐related reductions in on‐road NOx emissions tracked by TROPOspheric Monitoring Instrument (TROPOMI) tropospheric nitrogen dioxide column observationsOn‐road NOx emissions continued to be ∼20% below normal through December 2020 in parts of the US even after lockdowns were lifted in the USIncrease in the unemployment rate in the second quarter of 2020 correlated negatively with TROPOMI tropospheric nitrogen dioxide column amount [ABSTRACT FROM AUTHOR]

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

Satellite HCHO data are widely used as a reliable proxy of non‐methane volatile organic compounds (NMVOCs) to constrain underlying emissions and chemistry. Here, we examine global significant changes in HCHO columns at the early stage of the COVID‐19 pandemic (January–April 2020) compared with the same period in 2019 with observations from the TROPOspheric Monitoring Instrument (TROPOMI). HCHO columns decline (11.0%) in the Northern China Plain (NCP) because of a combination of meteorological impacts, lower HCHO yields as NOx emission plunges (by 36.0%), and reduced NMVOC emissions (by 15.0%) resulting from the lockdown. HCHO columns change near Beijing (+8.4%) due mainly to elevated hydroxyl radical as NOx emission decreases in a NOx‐saturated regime. HCHO columns change in Australia (+17.5%), Northeastern Myanmar of Southeast Asia (+14.9%), Central Africa (+7.8%), and Central America (+18.9%), consistent with fire activities. Our work also points to other changes related to temperature and meteorological variations. Plain Language Summary: We use satellite observations to examine global significant changes in HCHO columns at the early stage of the COVID‐19 pandemic compared with the same period in 2019. HCHO columns decreased in the Northern China Plain caused by a joint effect of meteorology, reduced anthropogenic NOx, and decreased non‐methane volatile organic compound emissions during the lockdown. The impact of temperature and meteorology on HCHO columns is observed in Northwestern China, India, Southern Africa, Eastern Brazil, Southern Cone, and Northeastern Thailand of Southeast Asia. Regional changes in Southeastern Australia, Northeastern Myanmar of Southeast Asia, Central Africa, and Central America are likely driven by open fire activities. Key Points: We detect significant changes in HCHO columns worldwide at the early stage of the COVID‐19 pandemicWe see evidence of changing atmospheric oxidizing capacity and NMVOC emissions in the Northern China Plain due to the massive lockdownBesides anthropogenic emission, temperature and open fires are vital factors dominating variations in HCHO columns [ABSTRACT FROM AUTHOR]

The TROPOspheric Monitoring Instrument (TROPOMI) aboard the Sentinel-5 Precursor satellite has been used to detect the atmospheric environment since 2017, and it is of great significance to investigate the accuracy of its products. In this work, we present comparisons between TROPOMI tropospheric NO2 and total SO2 products against ground-based MAX-DOAS at a single site (Xianghe) and OMI products over a seriously polluted region (North China Plain, NCP) in China. The results show that both NO2 and SO2 data from three datasets exhibit a similar tendency and seasonality. In addition, TROPOMI tropospheric NO2 columns are generally underestimated compared with collocated MAX-DOAS and OMI data by about 30–60%. In contrast to NO2, the monthly average SO2 retrieved from TROPOMI is larger than MAX-DOAS and OMI, with a mean bias of 2.41 (153.8%) and 2.17 × 1016 molec cm−2 (120.7%), respectively. All the results demonstrated that the TROPOMI NO2 as well as the SO2 algorithms need to be further improved. Thus, to ensure reliable analysis in NCP area, a correction method has been proposed and applied to TROPOMI Level 3 data. The revised datasets agree reasonably well with OMI observations (R > 0.95 for NO2, and R > 0.85 for SO2) over the NCP region and have smaller mean biases with MAX-DOAS. In the application during COVID-19 pandemic, it showed that the NO2 column in January-April 2020 decreased by almost 25–45% compared to the same period in 2019 due to the lockdown for COVID-19, and there was an apparent rebound of nearly 15–50% during 2021. In contrast, a marginal change of the corresponding SO2 is revealed in the NCP region. It signifies that short-term control measures are expected to have more effects on NO2 reduction than SO2; conversely, we need to recognize that although the COVID-19 lockdown measures improved air quality in the short term, the pollution status will rebound to its previous level once industrial and human activities return to normal.

Since the COVID-19 outbreak in 2020, China’s air pollution has been significantly affected by control measures on industrial production and human activities. In this study, we analyzed the temporal variations of NO2 concentrations during the COVID-19 lockdown and post-epidemic era in 11 Chinese megacities by using satellite and ground-based remote sensing as well as in situ measurements. The average satellite tropospheric vertical column density (TVCD) of NO2 by TROPOMI decreased by 39.2–71.93% during the 15 days after Chinese New Year when the lockdown was at its most rigorous compared to that of 2019, while the in situ NO2 concentration measured by China National Environmental Monitoring Centre (CNEMC) decreased by 42.53–69.81% for these cities. Such differences between both measurements were further investigated by using ground-based multi-axis differential optical absorption spectroscopy (MAX-DOAS) remote sensing of NO2 vertical profiles. For instance, in Beijing, MAX-DOAS NO2 showed a decrease of 14.19% (versus 18.63% by in situ) at the ground surface, and 36.24% (versus 36.25% by satellite) for the total tropospheric column. Thus, vertical discrepancies of atmospheric NO2 can largely explain the differences between satellite and in situ NO2 variations. In the post-epidemic era of 2021, satellite NO2 TVCD and in situ NO2 concentrations decreased by 10.42–64.96% and 1.05–34.99% compared to 2019, respectively, possibly related to the reduction of the transportation industry. This study reveals the changes of China’s urban NO2 pollution in the post-epidemic era and indicates that COVID-19 had a profound impact on human social activities and industrial production.

During the COVID‐19 lockdown (24 January–20 March) in China low air pollution levels were reported in the media as a consequence of reduced economic and social activities. Quantification of the pollution reduction is not straightforward due to effects of transport, meteorology, and chemistry. We have analyzed the NOx emission reductions calculated with an inverse algorithm applied to daily NO2 observations from TROPOMI onboard the Copernicus Sentinel‐5P satellite. This method allows the quantification of emission reductions per city and the analysis of emissions of maritime transport and of the energy sector separately. The reductions we found are 20–50% for cities, about 40% for power plants, and 15–40% for maritime transport depending on the region. The reduction in both emissions and concentrations shows a similar timeline consisting of a sharp reduction (34–50%) around the Spring festival and a slow recovery from mid‐February to mid‐March. Plain Language Summary: During the COVID‐19 lockdown in China, air quality had strongly improved. Here we study what sources were reduced and how much the reduction per city was. We used TROPOMI observations of the Sentinel‐5P satellite, which monitors the Earth's atmosphere daily. We focused on observations of the pollutant "nitrogen dioxide," an important precursor of air pollution in the atmosphere. With our novel methodology we are able to calculate the pollution back to the sources of the emissions, whether these are big cities, industrial regions, power plants, or busy shipping lanes. We applied this method to East China, where the 36 biggest Chinese cities are located. Almost all those cities showed strong emission reductions of 20–50% during the lockdown in February 2020. Besides urban China, we found an average emission reduction of 40% over coal power plants and a reduction in maritime transport by 15–40% depending on the region. The period of reduced emissions lasted until around the end of February, and the emissions slowly returned to normal during the month March 2020. Exception is the region Wuhan, the center of the COVID‐19 crisis, where emissions started to rebound since 8 April, the end of their lockdown period. Key Points: NOx emissions derived from TROPOMI observations show reductions for individual Chinese cities of about 35% due to the COVID‐19 lockdownEmissions of coal power plants and maritime transport show strong reductions (25–40%) during the lockdownUrban emissions rebound in March to levels before the lockdown, while emissions of power plants and maritime transport take longer to recover [ABSTRACT FROM AUTHOR]

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.

Movement restrictions were imposed in 2020 to mitigate the spread of Covid-19. These lock-down episodes provide a unique opportunity to study the sensitivity of urban photochemistry to temporary emission reductions and test air quality models. This study uses Tropospheric Monitoring Instrument (TROPOMI) nitrogen dioxide/carbon monoxide (NO 2 /CO) ratios in urban plumes in combination with an exponential fitting procedure to infer changes in the NOx lifetime (τ N O x) during Covid-19 lock-downs in the cities of Denver, Chicago, New York, Riyadh, Wuhan and Sao Paulo compared with the year before. The strict lockdown policy in Wuhan led to a 65–80% reduction in NO 2 , compared to 30–50% in the other cities that were studied. In New York and Wuhan, CO concentration was reduced by 10–15%, whereas over Riyadh, Denver, Chicago, and Sao Paulo the CO background concentration increased by 2–5 ppb. τ N O x has been derived for calm (0.0 < U (m/s) < 3.5) and windy (5.0 < U (m/s) < 8.5) days to study the influence of wind speed. We find reductions in τ N O x during Covid-19 lockdowns in all six megacities during calm days. The largest change in τ N O x during calm days is found for Sao-Paulo (31.8 ± 9.0%), whereas the smallest reduction is observed over Riyadh (22 ± 6.6%). During windy days, reductions in τ N O x are observed during Covid-19 lockdowns in New York and Chicago. However, over Riyadh τ N O x is almost similar for windy days during the Covid-19 lockdown and the year before. Ground-based measurements and the Chemistry Land-surface Atmosphere Soil Slab (CLASS) model have been used to validate the TROPOMI-derived results over Denver. CLASS simulates an enhancement of ozone (O 3) by 4 ppb along with reductions in NO (38.7%), NO 2 (25.7%) and CO (17.2%) during the Covid-19 lockdown in agreement with the ground-based measurements. In CLASS, decreased NO x emissions reduce the removal of OH in the NO 2 + OH reaction, leading to higher OH concentrations and decreased τ N O x . The reduction in τ N O x inferred from TROPOMI (28 ± 9.0%) is in agreement with CLASS. These results indicate that TROPOMI derived NO 2 /CO ratios provide useful information about urban photochemistry and that changes in photochemical lifetimes can successfully be detected. • The impact of Covid-19 lockdowns on the NOx lifetime is derived using TROPOMI retrieved NO 2 /CO ratios for six megacities. • Covid-19 lockdowns reduced the NOx lifetime compared to the year before across the six megacities. • TROPOMI derived reduction in NOx lifetime over Denver agrees with CLASS model intialized using ground-based observations. [ABSTRACT FROM AUTHOR]

Ports are major air pollution sources impacting downwind communities with emissions from port activities, nearby energy and other heavy industries, truck, train, and vessel traffic, and commuting traffic. The Ports of Los Angeles/Long Beach, denoted Ports, are the western hemisphere's largest, with plans for port electrification to reduce air pollution. The covid19 shutdown impacted the Ports, providing a real-world experiment on the effects of electrification on exposure to neighboring communities. Eight in situ surveys with a mobile air quality laboratory (14 trace gases, aerosols, and meteorology) were conducted spanning the covid19 shutdown to characterize the resultant air quality changes. These data were combed with time series (2015-) from six Port area air quality stations and TROPOMI satellite nitrogen dioxide NO 2 column XNO 2. In situ surveys showed dramatic NO 2 decreases from Jul. 2019 to May 2020 (during the shutdown), with NO 2 only returning towards pre-covid levels by Jul. 2022. Lesser covid19 NO 2 decreases were observed by the air quality station data and satellite XNO 2 for the Los Angeles Basin; both showed NO 2 decrease during the shutdown and an extended time for recovery to more normal concentration (and underlying economic activity) - until 2022 - far longer than the shutdown. Overall, ozone, O 3 increased, signifying that O 3 , formation is volatile organic hydrocarbons, VOH, limited, with the strongest O 3 source(s) arriving from offshore. This finding suggests efforts to purely address air quality by electrification without addressing area VOH emissions could potentially lessen, perhaps significantly, the expected air quality and health improvements in downwind communities. The Ports' area industrial sites were identified as driving these VOHs, as the inverse relationship between NO 2 and O 3 persisted during the shutdown when non-industrial VOH sources would have decreased. [Display omitted] • Mobile air quality surveyed the Los Angeles & Long Beach Ports during covid19. • Surveys, air quality station and satellite data found dramatic covid19 NO 2 decreases. • Recovery to normal pollution levels was slow - multiyear. • Ozone increased during covid19, indicating VOH-limited ozone formation. [ABSTRACT FROM AUTHOR]