ASPO effect (Preventive and Compulsory Social Isolation) in the atmosphere of the southwest of the province of Buenos Aires, Argentina

In 2020, Argentina implemented Preventive and Compulsory Social Isolation (ASPO) in the context of the global pandemic caused by the COVID-19 virus. This historical event has led to a decline in economic activities and the movement of the population. Current studies show a decrease in greenhouse gases harmful to health in the atmosphere due to health measures applied to contain the virus. Southwest Buenos Aires (Argentine Republic) is not exempt from these effects. The article aims to analyze the variations of the NO2 levels in pre-pandemic scenarios and during the pandemic. These results indicated a gradual decrease of NO2 related to the decrease in traffic and anthropogenic activities throughout the region, with a significant impact in big cities.

Changes in the Distribution of Air Pollutants (Carbon Monoxide) during the Control of the COVID-19 Pandemic in Jakarta, Surabaya, and Yogyakarta, Indonesia

The condition of the Coronavirus Disease 2019 (COVID-19) pandemic in 2020 characterizing DKI Jakarta, Surabaya, and Yogyakarta Provinces which have a high population density in 2019, necessitates implementing Large-Scale Social Restrictions (LSSR) to control or break the chain of the spread of COVID-19. The LSSR policy that limits community activities, be it business activities, transportation, and the industrial sector, will impact social activities and the environment due to the reduced intensity of community activities. Therefore, this study aimed to determine changes in the carbon monoxide (CO) levels in Jakarta, Surabaya and Yogyakarta during the prepandemic and during the pandemic. The method used is the tropospheric CO concentration extracted from the Sentinel-5P satellite data. The CO data were retrieved and calculated using Google Earth Engine. The COVID-19 pandemic reduced CO level by 19.7%, 14.9%, and 21%, respectively. The paired t-test shows no significant difference from before the COVID-19 pandemic, with a significance of 0.05. The highest pre-pandemic average and total CO concentration levels were 0.042 and 1.0198 mol/m2 in Yogyakarta, respectively, whereas the lowest during the pandemic were 0.02845 and 0.6828 mol/m2 in Surabaya. Overall, the three cities have a weak relationship between CO level and precipitation as well as temperatures and CO level © 2023, Journal of Ecological Engineering.All Rights Reserved.

Evaluating TROPOMI and MODIS performance to capture the dynamic of air pollution in São Paulo state: A case study during the COVID-19 outbreak.

Atmospheric pollutant data retrieved through satellite sensors are continually used to assess changes in air quality in the lower atmosphere. During the COVID-19 pandemic, several studies started to use satellite measurements to evaluate changes in air quality in many different regions worldwide. However, although satellite data is continuously validated, it is known that its accuracy may vary between monitored areas, requiring regionalized quality assessments. Thus, this study aimed to evaluate whether satellites could measure changes in the air quality of the state of São Paulo, Brazil, during the COVID-19 outbreak; and to verify the relationship between satellite-based data [Tropospheric NO2 column density and Aerosol Optical Depth (AOD)] and ground-based concentrations [NO2 and particulate material (PM; coarse: PM10 and fine: PM2.5)]. For this purpose, tropospheric NO2 obtained from the TROPOMI sensor and AOD retrieved from MODIS sensor data by using the Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm were compared with concentrations obtained from 50 automatic ground monitoring stations. The results showed low correlations between PM and AOD. For PM10, most stations showed correlations lower than 0.2, which were not significant. The results for PM2.5 were similar, but some stations showed good correlations for specific periods (before or during the COVID-19 outbreak). Satellite-based Tropospheric NO2 proved to be a good predictor for NO2 concentrations at ground level. Considering all stations with NO2 measurements, correlations >0.6 were observed, reaching 0.8 for specific stations and periods. In general, it was observed that regions with a more industrialized profile had the best correlations, in contrast with rural areas. In addition, it was observed about 57% reductions in tropospheric NO2 throughout the state of São Paulo during the COVID-19 outbreak. Variations in air pollutants were linked to the region economic vocation, since there were reductions in industrialized areas (at least 50% of the industrialized areas showed >20% decrease in NO2) and increases in areas with farming and livestock characteristics (about 70% of those areas showed increase in NO2). Our results demonstrate that Tropospheric NO2 column densities can serve as good predictors of NO2 concentrations at ground level. For MAIAC-AOD, a weak relationship was observed, requiring the evaluation of other possible predictors to describe the relationship with PM. Thus, it is concluded that regionalized assessment of satellite data accuracy is essential for assertive estimates on a regional/local level. Good quality information retrieved at specific polluted areas does not assure a worldwide use of remote sensor data.

Spatiotemporal Variation of Nitrogen Dioxide and Nighttime Light Dataset of Iranian Metropolises in the COVID-19 Outbreak

COVID-19 lockdown has caused a reduction in traffic volume and industrial activities which are the main sources of air pollution in whole of the world. As tropospheric NO2 pollutant and nighttime light (NTL) are the representative of human activities, this study focused to quantify the annual and monthly change of NO2 concentration and NTL in 14 metropolises of Iran before, during and after the lockdown months such as March, April, October and November. TROPOMI images of Sentinel-5p were used for investigation of NO2 column density in 2019, 2020 and 2021, and the variation of NTL was monitored by VIIRS images. The findings showed the majority of metropolises have an increase of NO2 concentration in March and October and a decrease in April and November in 2020 but a significant increase in 2021. The similar pattern of NTL change as NO2 was observed in the most metropolises. The correlation coefficient between NO2 concentration and NTL was calculated from 0.66 to 0.75. So, in majority of metropolises, the reduction of NO2 was observed with reduction of NTL. According to the results, reducing traffic volume as mobile source does not has an effective contribution in NO2 emission in some metropolises of Iran which the stationary sources are dominant such as Isfahan. Tehran as the capital of Iran showed the highest annual mean NO2 reduction in lockdown, this finding showed the important role of traffic volume on air quality of Tehran compared to industrial activities. The integrated application of TROPOMI and NTL data will help to better decision making for controlling and managing of air quality in country's urban area.

Air Quality Improvement Following COVID-19 Lockdown Measures and Projected Benefits for Environmental Health

Many regions worldwide suffer from heavy air pollution caused by particulate matter (PM2.5) and nitrogen dioxide (NO2), resulting in a huge annual disease burden and significant welfare costs. Following the outbreak of the COVID-19 global pandemic, enforced curfews and restrictions on human mobility (so-called periods of 'lockdown') have become important measures to control the spread of the virus. This study aims to investigate the improvement in air quality following COVID-19 lockdown measures and the projected benefits for environmental health. China was chosen as a case study. The work projects annual premature deaths and welfare costs by integrating PM2.5 and NO2 pollutant measurements derived from satellite imagery (MODIS instruments on Terra and Aqua, and TROPOMI on Sentinel-5P) with census data archived by the Organization for Economic Co-operation and Development (OECD). A 91-day timeframe centred on the initial lockdown date of 23 January 2020 was investigated. To perform the projections, OECD data on five variables from 1990 to 2019 (mean population exposure to ambient PM2.5, premature deaths, welfare costs, gross domestic product and population) were used as training data to run the Autoregressive Integrated Moving Average (ARIMA) and multiple regression models. The analysis of the satellite imagery revealed that across the regions of Beijing, Hebei, Shandong, Henan, Xi'an, Shanghai and Hubei, the average concentrations of PM2.5 decreased by 6.2, 30.7, 14.1, 20.7, 29.3, 5.5 and 17.3%, while the NO2 decreased by 45.5, 54.7, 60.5, 58.7, 63.6, 50.5 and 66.5%, respectively, during the period of lockdown restrictions in 2020, as compared with the equivalent period in 2019. Such improvements in air quality were found to be beneficial, reducing in 2020 both the number of premature deaths by approximately 97,390 and welfare costs by over USD 74 billion.

Impact of COVID-19 restrictions on air quality and surface urban heat island effect within the main urban area of Urumqi, China.

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 NO2 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 NO2 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.

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

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

AIR QUALITY DURING ISOLATION PERIODS DUE TO COVID-19 PANDEMIC: NITROGEN DIOXIDE ANALYSIS IN COLOMBIAN CITIES

This study analyses air quality behavior by considering nitrogen dioxide (NO2) as a reference parameter during atypical conditions associated with the COVID-19 pandemic. NO2 concentrations in 31 departmental capital cities of Colombia (South America) were evaluated during four periods according to government dispositions to face the pandemic: (I) before isolation (normal conditions), (II) mandatory isolation (significant traffic and industrial activity reduction), (III) intelligent isolation (return of some commercial activities), and (IV) selective isolation (Increase of authorized commercial activities). A good fit between ground data and satellite information is observed. Results indicate that most of the cities (45%) present a counterintuitive behavior with concentration increments for Period II with respect to Period I. © 2022, Rasayan Journal of Chemistry, c/o Dr. Pratima Sharma. All rights reserved.

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

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

Spatio-Temporal Analysis of Air Pollutants Changes During The COVID-19 Using Sentinel-5P in Google Earth Engine (Case Study: Java Island)

COVID-19 or Coronavirus Disease 2019 has become a global pandemic until several countries have implemented social distancing in restrictions on human activities. The Indonesian Government, in early 2020, set a PSBB (Large-Scale Social Restriction) policy. Still, as the COVID-19 Pandemic progressed, the Indonesian Government finally changed the PSBB and implemented the PPKM (Enforcement of Community Activity Restrictions) policy. COVID-19 has an impact on decreasing human and industrial activities. On the other hand, this will be beneficial due to a decrease in air pollutants. Pollutants come from motor vehicle fumes or other industrial activities. The types of pollutants carried out in this research are Carbon Monoxide (CO), Ozone (O3), Sulfur Dioxide (S02), and Nitrogen Dioxide (NO2). Using Sentinel-5P Imagery, which can record pollutant activity with the daily temporal resolution, the effect of the number of pollutants on the COVID-19 Pandemic can be investigated using the Google Earth Engine and the correlation test method to relate the effect of pollutant concentrations to BMKG meteorological data. The correlation test of pollutant data on sentinel 5P images with BMKG data shows a strong correlation of 0.5045 and 0.795 in Central Java. In addition, changes in the decrease in CO, NO2, and O3 gases occurred in November 2020 - December 2020. Monitoring of pollutants in Java During the COVID-19 Pandemic was packaged in the Website and Google Earth Engine. According to users, the application obtained a usability test result of 89%

A Remote Sensing based study of Tropospheric Ozone Concentration amid COVID-19 Lockdown over India using Sentinel-5P Satellite Data

Amid the COVID-19 crisis, governments all over the world, and not excluding India, took to lockdown measures to deaccelerate the spread of the COVID-19 virus. This led to reduction of atmospheric pollution by declining the harmful Nitrogen and Sulphur Oxide (NOX and SOX) concentrations. However, one hand while the stratospheric Ozone (O3) showed repair, the lower atmospheric O3 concentrations demonstrated a remarkable increase during lockdown phase over India. This study aims to estimate the O3 concentration during the Covid-19 lockdown over Pune city in India using freely available Sentinel-5P satellite datasets. The study makes use of the Ordinary Least Squares (OLS) and Random Forest (RF) regressions and compares the findings of the two algorithms based on estimation results. This study utilizes lower atmospheric O3 concentration data from Sentinel-5P satellite of the European Space Agency (ESA) over the Indian mainland for a month of lockdown scenario (March 22nd, 2020, to April 25th, 2020) and shows the remarkable increase in concentration of O3 gas as a pollutant. Despite the complete lockdown over India during this given time frame, there has been enough emission of O3 precursors from other sources such as stubble burning. The estimates of tropospheric O3 concentration for May 2020 for Pune city, using OLS and RF Regressions, have been validated with May 2020 data. The results have provided a RMSE of 1.05 and 1.23 with R2-statistics of 0.90 and 0.857 in training and testing phases for OLS and RMSE of 0.98 and MAE of 1.07 with R2-statistics of 0.968 and 0.895 in training and testing phases of the RF. The outcome of this study has proven that O3 gas concentrations in the atmosphere depends upon various other causative factors apart from the precursor gases. The study also shows that the remotely sensed Sentinel-5P datasets, supplemented with ground-based sensor data can help in time and cost saving estimation of O3 concentrations in the troposphere with considerable accuracy. [ FROM AUTHOR] Copyright of Geocarto International is the property of Taylor & Francis Ltd 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 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 . (Copyright applies to all s.)

Spatiotemporal changes in tropospheric nitrogen dioxide hotspot due to emission switch-off condition in the view of lockdown emergency in India.

The COVID-19 outbreak has elicited forced lockdown conditions for all anthropogenic emissions across the globe. It has brought an opportunity for the researchers to sort out the relative contribution of the environmental pollutants which are emerged from the coal-based thermal power plants and other industrial sectors. In countries like India, some industrial sectors and thermal power plants coexist; henceforth, they mutually produce NO2 concentration canopy in the upper atmosphere in raised form. Focusing on this issue, the present work intends to explore the NO2 emission hot-spots' foci using switch-off conditions in consequence of emergency lockdown. Our results indicate that stable ( C V low and NO 2 max ) and large NO2 concentration canopy is noticeable in the inter-state border areas among Chhattisgarh, Bihar, Madhya Pradesh, and Jharkhand (around "Govind Ballabh Part Sagar" reservoir) where a cluster of thermal power plant is located. The "OFF" situation also proposes a close correspondence between the NO2 richness column and installed capacity (R 2 value > 0.7 with 0.0002 p value). States that are situated in the eastern part of the country and megacities like Delhi and Kolkata represent a crucial role in NO2 emission while in certain regions of south India are more or less safe from NO2 emission. As a consequence, the lockdown has created a temporary pollution baseline for tropospheric NO2 that offers research prospects to think of alternate sources of energy that can maintain environmental health as well as human well-being.

Changes in temporal pattern and spatial distribution of environmental pollutants in 8 Asian countries owing to COVID-19 pandemic.

This study investigated the changes in air pollutant's concentration, spatio-temporal distribution and sensitivity of changes in air pollutant's concentration during pre and post COVID-19 outbreak. We employed Google Earth Engine Platform to access remote sensing datasets of air pollutants across Asian continent. Air pollution and cumulative confirmed-COVID cases data of Asian countries (Afghanistan, Bangladesh, China, India, Iran, Iraq, Pakistan, and Saudi Arabia) have been collected and analyzed for 2019 and 2020. The results indicate that aerosol index (AI) and nitrogen dioxide (NO2) is significantly reduced during COVID outbreak i.e. in year 2020. In addition, we found significantly positive (P < 0.05, 95% confidence interval, two-tailed) correlation between changes in AI and NO2 concentration for net active-COVID case increment in almost each country. For other atmospheric gases i.e. carbon monoxide (CO), formaldehyde (HCHO), ozone (O3), and Sulfur dioxide (SO2), insignificant and/or significant negative correlation is also observed. These results suggest that the atmospheric concentration of AI and NO2 are good indicators of human activities. Furthermore, the changes in O3 shows significantly negative correlation for net active-COVID case increment. In conclusion, we observed significant positive environmental impact of COVID-19 restrictions in Asia. This study would help and assist environmentalist and policy makers in restraining air pollution by implementing efficient restrictions on human activities with minimal economic loss.

Air and Water Quality Improvement during COVID-19 Lockdown

COVID-19 pandemic forced many countries to adopt lockdown measures, temporarily closing factories, diminish maritime traffic and reducing the mobility of people in the cities. Analysis from the Tropospheric Monitoring Instrument (TROPOMI) and Ocean and Land Colour Instrument (OLCI) on board Europe's Sentinel-5P, 3A/B respectively, for the first wave of the COVID-19, have shown a substantial improvement in air and water quality. More specifically, since COVID-19 lockdown until the end April, Lisbon and Porto were at their lowest PM10 levels of about 20% and a drop of 33% in 2 years, while Madrid had a significant drop since lockdown with vales significantly below 2018 levels but still close to 2019 levels. In terms of NO2 levels, Lisbon had an historical minimum of the last 2 years, dropping more than 40% during most of April 2020. Finally, Madrid had 2-year lowest level of more than 30% since lockdown. Concerning the water quality in the Portuguese coastal waters, it was verified an increase in water transparency since confinement started until May, accordingly to the Total Suspended Matter (TSM) indicator. From February to March, March to April and April to May there was a reduction in TSM levels of 17%, 37% and 53% respectively.

NO2 Correlation Using Sentinel-5P Images and on-site Measurements during the Evolution of COVID-19 and its Influence in the Metropolitan District of Quito, Ecuador

Since the first outbreak of coronavirus disease (COVID-19) reported in Wuhan (China) on December 31, 2019, countries all over the world have decreed different security measures such as lockdowns and confinement, resulting in reduced levels of air pollution. The present study explores the correlation of the levels of nitrogen dioxide (NO2) measured using two different source data as Sentinel - 5P images and the on-site database of three monitoring stations belonging to the Environmental Monitoring Network in the Metropolitan District of Quito, within three periods of time during the progression of COVID-19. The result of this analysis shows an overall correlation of ninety-three percent of the levels of NO2 for both measurements in the period January to June 2020. During the lockdown and confinement measures from March to April 2020 a reduction of forty-nine percent was found, but when confinement measures were reduced within the period May to June 2020, an increase in NO2 concentration was again observed and the reduction was only thirteen percent;thus, the reduction in NO2 concentrations may be attributed partly due to the significant reduction in vehicle exhaust gas emissions. From the correlation of the results obtained, it can be concluded that this methodology, using Sentinel-5P image analysis may be used to measure the NO2 concentrations in the atmosphere in cities where there is no on-site air quality monitoring network. © 2022. International Journal on Advanced Science, Engineering and Information Technology.All Rights Reserved

Revealing the Declining Trend of NO2and SO2Concentration in Indian Cities during Pandemic Lockdown

The highly polluted Indian cities are retained their normal state during COVID-19 pandemic lockdown. Thus, the study aims to analysis the lockdown impact on NO2 and SO2 in the selected cities. So, the lockdown relative changes (C) are calculated based on baseline and pre-lockdown, for which the ground (Central Pollution Control Board data) and satellite (Sentinel 5P data) measured NO2 and SO2 data were utilised. The study reveals that the average pollutants concentration of NO2 and SO2 is declined to below-average level and indicates that the average dropdown level of NO2 and SO2 are -45.4% and -30.2% for ground pollutants;-45.1% and -43.4% for satellite pollutants respectively. The pandemic lockdown has restricted industrial, vehicular emission, and other anthropogenic activities which resulted in a positive effect on air quality. © 2021 IEEE.

Tracing out the effect of transportation infrastructure on NO2 concentration levels with Kernel Density Estimation by investigating successive COVID-19-induced lockdowns.

This study aims to investigate the effect of transportation infrastructure on the decrease of NO2 air pollution during three COVID-19-induced lockdowns in a vast region of France. For this purpose, using Sentinel-5P satellite data, the relative change in tropospheric NO2 air pollution during the three lockdowns was calculated. The estimation of regional infrastructure intensity was performed using Kernel Density Estimation, being the predictor variable. By performing hotspot-coldspot analysis on the relative change in NO2 air pollution, significant spatial clusters of decreased air pollution during the three lockdowns were identified. Based on the clusters, a novel spatial index, the Clustering Index (CI) was developed using its Coldspot Clustering Index (CCI) variant as a predicted variable in the regression model between infrastructure intensity and NO2 air pollution decline. The analysis revealed that during the three lockdowns there was a strong and statistically significant relationship between the transportation infrastructure and the decline index, CCI (r = 0.899, R2 = 0.808). The results showed that the largest decrease in NO2 air pollution was recorded during the first lockdown, and in this case, there was the strongest inverse correlation with transportation infrastructure (r = -0.904, R2 = 0.818). Economic and population predictors also explained with good fit the decrease in NO2 air pollution during the first lockdown: GDP (R2 = 0.511), employees (R2 = 0.513), population density (R2 = 0.837). It is concluded that not only economic-population variables determined the reduction of near-surface air pollution but also the transportation infrastructure. Further studies are recommended to investigate other pollutant gases as predicted variables.

Lessons Learned from the COVID-19 Lockdown for Sustainable Northwestern Himalayan Region

This study tried to understand the changes in three air pollution parameters, namely absorbing aerosol index (AAI)—broadly referred to as dust and smoke, nitrogen dioxide (NO2) and carbon monoxide (CO) column number density in the Western Indian Himalayas during the COVID-19 lockdown. The study used Sentinel 5P data over a 50 km radius of 11 non-attainment cities (NACs) of Northwestern Indian Himalayan states (7 of Himachal Pradesh, 2 of Uttarakhand and 2 of Union Territory of Jammu and Kashmir) during the lockdown phase-1 (March 24–April 14, 2020) with respect to the pre-lockdown period (March 24–April 14, 2019). Ground-measured data on particulate matter (PM10) and nitrogen oxides (NOx) has also been used for only 7 NACs of Himachal Pradesh for the lockdown phase-1 and pre-lockdown period. The average values of AAI, NO2 and CO around 11 towns have been reduced by 55%, 19% and 7%, respectively, during lockdown phase-1, compared to the pre-lockdown period. The satellite observation is further complemented through ground-monitored data on air pollution. In the seven NACs of Himachal Pradesh, NOx and PM10 mass concentrations have been substantially reduced during the March and April months of 2020 compared to the same months of 2019. This study would give an idea to environmentalists and policymakers to plan a sustainable emission policy to reduce the adverse impacts of air pollution on the physical aspects (e.g. snow and glaciers) of the Northwestern Himalayan region under the climate change conditions. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

A MULTI-AGENCY COVID-19 DASHBOARD WITH SATELLITE AIR QUALITY DATA

After the initial COVID-19 lockdown in China during February 2020, NASA and ESA pollution monitoring satellite instruments quickly detected significant decreases in NO2 over the Wuhan region. This change was attributed to reductions in fossil fuel combustion from motor vehicles and industrial activity. The same phenomenon, the satellite measured reduction of NO2, happened next in northern Italy, and then in New York City as the coronavirus spread to these areas. Satellite remote sensing of NO2 has been a useful tool to document changes in fossil fuel combustion and associated economic activity as various countries or regions have implemented lockdowns as a means to try to contain the spread of the virus. In April 2020, ESA reached out to NASA and JAXA and suggested working together to construct an Earth Observing (EO) Dashboard to provide the public with information on the changes occurring within the environment due to the pandemic that are observable from satellites. Satellite air quality data - specifically, tropospheric NO2 - was one of the primary Earth observations provided by this tri-agency COVID-19 satellite data dashboard. © 2021 IEEE.

AIR QUALITY IMPROVEMENT DURING COVID-19 PANDEMIC: STUDY OF LAND AND MARITIME POLLUTION

COVID-19 pandemic forced many countries to adopt lockdown measures, temporarily closing factories, diminish maritime traffic and reducing the mobility of people in the cities. Analysis from the Tropospheric Monitoring Instrument (TROPOMI) on board Europe's Sentinel-5P and Copernicus Atmosphere Monitoring Service (CAMS), for the first wave of COVID-19 in 2020, have shown a substantial improvement in air quality. More specifically, since lockdown until the end of April, Lisbon and Porto were at their lowest PM10 levels in 2 years, while Madrid had a significant drop with values considerably below 2018 levels but still close to 2019 values. In terms of NO2 levels, Lisbon had an historical minimum of the last 2 years during most of April 2020 and Madrid had 2-year lowest level since lockdown. Finally, the commercial port of Ponta Delgada (São Miguel, Azores) had a decrease in cruise ship calls during the pandemic, which reduced the number of daily cases with significant NO2 concentrations, comparing to 2019. © 2021 IEEE