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1.
Sci Total Environ ; 859(Pt 1): 159997, 2022 Nov 09.
Article in English | MEDLINE | ID: covidwho-2105903

ABSTRACT

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.

2.
ACS Environmental Au ; 2(5):441-454, 2022.
Article in English | Scopus | ID: covidwho-2062151

ABSTRACT

NO2and O3simulations have great uncertainties during the COVID-19 epidemic, but their biases and spatial distributions can be improved with NO2assimilations. This study adopted two top-down NOXinversions and estimated their impacts on NO2and O3simulation for three periods: the normal operation period (P1), the epidemic lockdown period following the Spring Festival (P2), and back to work period (P3) in the North China Plain (NCP). Two TROPOspheric Monitoring Instrument (TROPOMI) NO2retrievals came from the Royal Netherlands Meteorological Institute (KNMI) and the University of Science and Technology of China (USTC), respectively. Compared to the prior NOXemissions, the two TROPOMI posteriors greatly reduced the biases between simulations with in situ measurements (NO2MREs: prior 85%, KNMI -27%, USTC -15%;O3MREs: Prior -39%, KNMI 18%, USTC 11%). The NOXbudgets from the USTC posterior were 17-31% higher than those from the KNMI one. Consequently, surface NO2levels constrained by USTC-TROPOMI were 9-20% higher than those by the KNMI one, and O3is 6-12% lower. Moreover, USTC posterior simulations showed more significant changes in adjacent periods (surface NO2: P2 vs P1, -46%, P3 vs P2, +25%;surface O3: P2 vs P1, +75%, P3 vs P2, +18%) than the KNMI one. For the transport flux in Beijing (BJ), the O3flux differed by 5-6% between the two posteriori simulations, but the difference of NO2flux between P2 and P3 was significant, where the USTC posterior NO2flux was 1.5-2 times higher than the KNMI one. Overall, our results highlight the discrepancies in NO2and O3simulations constrained by two TROPOMI products and demonstrate that the USTC posterior has lower bias in the NCP during COVD-19. © 2022 American Chemical Society. All rights reserved.

3.
Remote Sensing ; 14(18):N.PAG-N.PAG, 2022.
Article in English | Academic Search Complete | ID: covidwho-2055348

ABSTRACT

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.)

4.
Environ Sci Pollut Res Int ; 2022 Oct 01.
Article in English | MEDLINE | ID: covidwho-2048486

ABSTRACT

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.

5.
Frontiers in Environmental Science ; 10, 2022.
Article in English | Web of Science | ID: covidwho-2022690

ABSTRACT

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).

6.
Environ Monit Assess ; 194(10): 714, 2022 Oct.
Article in English | MEDLINE | ID: covidwho-2014247

ABSTRACT

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.


Subject(s)
Air Pollutants , Air Pollution , COVID-19 , Air Pollutants/analysis , Air Pollution/analysis , COVID-19/epidemiology , Communicable Disease Control , Environmental Monitoring , Humans , Nitrogen Dioxide/analysis , SARS-CoV-2
7.
Atmospheric Environment ; 289, 2022.
Article in English | Web of Science | ID: covidwho-2014913

ABSTRACT

Nitrogen dioxide (NO2) is an important target for monitoring atmospheric quality. Deriving ground-level NO2 concentrations with much finer resolution, it requires high-resolution satellite tropospheric NO2 column as input and a reliable estimation algorithm. This paper aims to estimate the daily ground-level NO2 concentrations over China based on machine learning models and the TROPOMI NO2 data with high spatial resolution. In this study, four tree-based algorithm machine learning models, decision trees (DT), gradient boost decision tree (GBDT), random forest (RF) and extra-trees (ET), were used to estimate ground-level NO2 concentrations. In addition to considering many influencing factors of the ground-level NO2 concentrations, we especially introduced simplified temporal and spatial information into the estimation models. The results show that the extra-trees with spatial and temporal information (ST-ET) model has great performance in estimating ground-level NO2 concentrations with a cross-validation R-2 of 0.81 and RMSE of 3.45 mu g/m(3) in test datasets. The estimated results for 2019 based on the ST-ET model achieves a satisfactory accuracy with a cross-validation R-2 of 0.86 compared with the other models. Through time-space analysis and comparison, it was found that the estimated high-resolution results were consistent with the ground observed NO2 concentrations. Using data from January 2020 to test the prediction power of the models, the results indicate that the ST-ET model has a good performance in predicting ground-level NO2 concentrations. Taking four ground-level NO2 concentrations hotspots as examples, the estimated ground-level NO2 concentrations and ground-based observation data during the coronavirus disease (COVID-19) pandemic were lower compared with the same period in 2019. The findings offer a solid solution for accurately and efficiently estimating ground-level NO2 concentrations by using satellite observations, and provide useful information for improving our understanding of the regional atmospheric environment.

8.
Atmospheric Environment ; : 119310, 2022.
Article in English | ScienceDirect | ID: covidwho-1977053

ABSTRACT

Nitrogen dioxide (NO2) is an important target for monitoring atmospheric quality. Deriving ground-level NO2 concentrations with much finer resolution, it requires high-resolution satellite tropospheric NO2 column as input and a reliable estimation algorithm. This paper aims to estimate the daily ground-level NO2 concentrations over China based on machine learning models and the TROPOMI NO2 data with high spatial resolution. In this study, four tree-based algorithm machine learning models, decision trees (DT), gradient boost decision tree (GBDT), random forest (RF) and extra-trees (ET), were used to estimate ground-level NO2 concentrations. In addition to considering many influencing factors of the ground-level NO2 concentrations, we especially introduced simplified temporal and spatial information into the estimation models. The results show that the extra-trees with spatial and temporal information (ST-ET) model has great performance in estimating ground-level NO2 concentrations with a cross-validation R2 of 0.81 and RMSE of 3.45 μg/m3 in test datasets. The estimated results for 2019 based on the ST-ET model achieves a satisfactory accuracy with a cross-validation R2 of 0.86 compared with the other models. Through time-space analysis and comparison, it was found that the estimated high-resolution results were consistent with the ground observed NO2 concentrations. Using data from January 2020 to test the prediction power of the models, the results indicate that the ST-ET model has a good performance in predicting ground-level NO2 concentrations. Taking four ground-level NO2 concentrations hotspots as examples, the estimated ground-level NO2 concentrations and ground-based observation data during the coronavirus disease (COVID-19) pandemic were lower compared with the same period in 2019. The findings offer a solid solution for accurately and efficiently estimating ground-level NO2 concentrations by using satellite observations, and provide useful information for improving our understanding of the regional atmospheric environment.

9.
Heliyon ; 8(8): e09978, 2022 Aug.
Article in English | MEDLINE | ID: covidwho-1936477

ABSTRACT

This work analyzes nitrogen dioxide (NO2) pollution over a set of cities in the Po Valley in northern Italy, using satellite and in situ observations. The cities include Milan, Bergamo, and Brescia, the first area of the COVID-19 outbreak and diffusion in Italy, with a higher mortality rate than in other parts of Italy and Europe. The analysis was performed for three years, from May 2018 to April 2021, including the period of first-wave diffusion of COVID-19 over the Po Valley, that is, January 2020-April 2020. The study aimed at giving a more general picture of the NO2 temporal and spatial variation, possibly due to the lockdown adopted for the pandemic crisis containment and other factors, such as the meteorological conditions and the seasonal cycle. We have mainly investigated two effects: first, the correlation of NO2 pollution with atmospheric parameters such as air and dew point temperature, and second the possible correlation between air quality and COVID-19 deaths, which could explain the high mortality rate. We have found a good relationship between air quality and temperature. In light of this relationship, we can conclude that the air quality improvement in March 2020 was primarily because of the lockdown adopted to prevent and limit virus diffusion. We also report a good correlation between NO2 pollution and COVID-19 deaths, which is not seen when considering a reference city in the South of Italy. The critical factor in explaining the difference is the persistence of air pollution in the Po Valley in wintertime. We found that NO2 pollution shows a seasonal cycle, yielding a non-causal correlation with the COVID-19 deaths. However, causality comes in once we read the correlation in the context of current and recent epidemiological evidence and leads us to conclude that air pollution may have acted as a significant risk factor in boosting COVID-19 fatalities.

10.
Geophys Res Lett ; 47(17): e2020GL089269, 2020 Sep 16.
Article in English | MEDLINE | ID: covidwho-1931317

ABSTRACT

TROPOMI satellite data show substantial drops in nitrogen dioxide (NO2) during COVID-19 physical distancing. To attribute NO2 changes to NO x emissions changes over short timescales, one must account for meteorology. We find that meteorological patterns were especially favorable for low NO2 in much of the United States in spring 2020, complicating comparisons with spring 2019. Meteorological variations between years can cause column NO2 differences of ~15% over monthly timescales. After accounting for solar angle and meteorological considerations, we calculate that NO2 drops ranged between 9.2% and 43.4% among 20 cities in North America, with a median of 21.6%. Of the studied cities, largest NO2 drops (>30%) were in San Jose, Los Angeles, and Toronto, and smallest drops (<12%) were in Miami, Minneapolis, and Dallas. These normalized NO2 changes can be used to highlight locations with greater activity changes and better understand the sources contributing to adverse air quality in each city.

11.
2021 IEEE India Geoscience and Remote Sensing Symposium, InGARSS 2021 ; : 320-323, 2021.
Article in English | Scopus | ID: covidwho-1922714

ABSTRACT

In the present study, the atmospheric concentrations of Carbon Monoxide (CO) over India during COVID-19 (2020) were studied by comparing it with 2019 and 2021. COVID-19 has created an undesirable impact all over the world. However, as a blessing in disguise, these measures have a positive effect on the environment due to closing the mass gathering places. The work has undergone using the TROPOMI instrument, on-board Sentinel-5 Precursor. The results, evidence that human activities like transportation in Delhi, Industrial activities near Indo-Gangetic Plain have sharply fallen during the lockdown phase. On Contrary, there is a sharp increment in the area of Thermal power plants being coal-based. On the whole, the mean concentration of CO over India has minimal change due to long lifetime (1~2 months), indicating the duration of the (68 days) lockdown did not capture prompt and short-term atmospheric change. © 2021 IEEE.

12.
2021 XIX WORKSHOP ON INFORMATION PROCESSING AND CONTROL (RPIC) ; 2021.
Article in English | Web of Science | ID: covidwho-1909256

ABSTRACT

Air quality is assessed by determining criteria pollutant levels in the atmosphere. While the most significant measurements are ground based, satellite remote sensing is rising as a complementary technique to reveal spatial distribution of pollutants in the integrated tropospheric column. In this work we present a new CONAE's value-added monthly product of nitrogen dioxide (NO2) for South America, derived from the tropospheric NO2 column density estimated by TROPOMI/Sentinel5p (ESA) data. Dataset generation of monthly mean, median, standard deviation and quantity of data used per pixel, along with distribution formats of downloading and visualizing data, are explained in order to provide to different users their characteristics and access. In addition, a spatial and temporal analysis is made for the Buenos Aires, Santiago and Sao Paulo cities along with ground measurements, for the august 2018 to may 2021 period and on a monthly basis. For this matter, higher values of nitrogen dioxide were observed in wintertime for the three cities, due to a greater quantity of stagnation episodes. While satellite derived data follows the temporal profile of ground-based concentrations, Santiago was the city of higher levels and bigger contrast to the summer levels. COVID-19 pandemic restrictions to traffic circulation is also noticed in the diminishing of NO2 in the two datasets, as it was also reported in previous studies. The publication of this new dataset holds the objective of supporting air quality monitoring in South America, helping non specialized users to freely access to interoperational data.

13.
Atmosphere ; 13(5):840, 2022.
Article in English | ProQuest Central | ID: covidwho-1871343

ABSTRACT

In this article, we aim to show the capabilities, benefits, as well as restrictions, of three different air quality-related information sources, namely the Sentinel-5Precursor TROPOspheric Monitoring Instrument (TROPOMI) space-born observations, the Multi-Axis Differential Optical Absorption Spectroscopy (MAX-DOAS) ground-based measurements and the LOng Term Ozone Simulation-EURopean Operational Smog (LOTOS-EUROS) chemical transport modelling system simulations. The tropospheric NO2 concentrations between 2018 and 2021 are discussed as air quality indicators for the Greek cities of Thessaloniki and Ioannina. Each dataset was analysed in an autonomous manner and, without disregarding their differences, the common air quality picture that they provide is revealed. All three systems report a clear seasonal pattern, with high NO2 levels during wintertime and lower NO2 levels during summertime, reflecting the importance of photochemistry in the abatement of this air pollutant. The spatial patterns of the NO2 load, obtained by both space-born observations and model simulations, show the undeniable variability of the NO2 load within the urban agglomerations. Furthermore, a clear diurnal variability is clearly identified by the ground-based measurements, as well as a Sunday minimum NO2 load effect, alongside the rest of the sources of air quality information. Within their individual strengths and limitations, the space-borne observations, the ground-based measurements, and the chemical transport modelling simulations demonstrate unequivocally their ability to report on the air quality situation in urban locations.

14.
2021 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2021 ; : 711-713, 2021.
Article in English | Scopus | ID: covidwho-1861121

ABSTRACT

Since the onset of the COVID-19 pandemic in early 2020, many countries worldwide implemented a series of social distancing and containment measures as an attempt to limit its spread. Those measures have led to a significant slowing down of economic activities, drastic drops in road and air traffic, and strong reductions of industrial activities in nonessential sectors, which in turn affected atmospheric emissions and air quality worldwide. Concentrations of short-lived pollutants, such as nitrogen dioxide, are indicators of changes in economic slowdowns and are comparable to changes in emissions. Nitrogen oxides are mainly produced by human activity and the combustion of (fossil) fuels, such as road traffic, ships, power plants and other industrial facilities. Nitrogen Dioxide can have a significant impact on human health, both directly and indirectly through the formation of ozone and small particles. The Copernicus Sentinel-5P satellite nitrogen dioxide concentrations measurements have been used to investigate COVID-19 impact on air quality from space. Global maps of Copernicus Sentinel-5P tropospheric Nitrogen Dioxide measurements have been included – together with other Sentinel measurements – into an on-line tool (dashboard) to provide investigations/results about changes to the Earth environment caused by the COVID-19 pandemic to the public: race.esa.int. © 2021 IEEE.

15.
Aerosol and Air Quality Research ; 21(11), 2021.
Article in English | ProQuest Central | ID: covidwho-1771483

ABSTRACT

We studied the impact of COVID-19 (coronavirus disease 2019) lockdown on the air quality over the Atlanta area using satellite and ground-based observations, meteorological reanalysis data and traffic information. Unlike other cities, we found the air quality has improved slightly over the Atlanta area during the 2020 COVID-19 lockdown period (March 14–April 30, 2020), compared to the analogous period of 2019 (March 14-April 30, 2019). Ground NO2 concentrations have decreased slightly 10.8% and 8.2% over the near-road (NR) and urban ambient (UA) stations, respectively. Tropospheric NO2 columns have reduced 13%-49% over the Atlanta area from space-borne observations of TROPOspheric Monitoring Instrument (TROPOMI). Ground ozone and PM2.5 have decreased 15.7% an ~5%, respectively. This slight air quality improvement is primarily caused by the reduced human activities, as COVID-19 lockdowns have reduced ~50% human activities, measured by traffic volume. Higher wind speed and precipitations also make the meteorological conditions favorable to this slight air quality improvement. We have not found a significant improvement in Atlanta amid the lockdown when human activities have reduced ~50%. Further studies are needed to understand the impacts of reduced human activities on atmospheric chemistry. We also found TROPOMI and ground measurements have disagreements on NO2 reductions, as collocated TROPOMI observations revealed ~23% and ~21% reductions of tropospheric NO2 columns over NR and UA stations, respectively. Several factors may explain this disagreement: First, tropospheric NO2 columns and ground NO2 concentrations are not necessarily the same, although they are highly correlated in the afternoon;Second, meteorological conditions may have different impacts on TROPMI and ground measurements. Third, TROPOMI may underestimate tropospheric NO2 due to uncertainties from air mass factors. Fourth, the uncertainties of chemiluminescence NO2 measurements used by ground stations. Consequently, studies using space-borne tropospheric NO2 column and ground NO2 measurements should take these factors into account.

16.
Aerosol and Air Quality Research ; 22(4):10, 2022.
Article in English | Web of Science | ID: covidwho-1753822

ABSTRACT

COVID-19 lockdown resulted in the revival of the environment due to reduced emissions of various pollutants globally. In particular, aerosols, NOx and SO2 showed significant reductions at most places. However, the greenhouse gases are not necessarily following this reduction everywhere. In most areas, a decrease in NOx increases methane (CH4) concentration by enhancing the lifetime, but also results in decreased concentrations with reduced emissions. Analyzing the atmospheric CH4 variations during the COVID-19 lockdown over India is crucial as India is one of the regions with high seasonal variability of CH4. The present study has analyzed the tropospheric CH4 trends over India during the pre-monsoon season (March-May) for 2003-2021 using AIRS data. The study analyzed the lockdown variations (24 March-31 May) of tropospheric CH4 over India with the same period of 2019 and 2021 using TROPOMI to find the changes in CH4 concentrations over different regions of India due to lockdown. Our results capture the undeviating north (low)-south (high) gradient in the CH4 concentration with anticipated regional intensifications, likely, in the eastern and western coastal regions, with more comprehensive details than it ever has been presented before.

17.
2021 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2021 ; 2021-July:1553-1555, 2021.
Article in English | Scopus | ID: covidwho-1746063

ABSTRACT

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.

18.
Urban Climate ; 43:101150, 2022.
Article in English | ScienceDirect | ID: covidwho-1740248

ABSTRACT

In this study, TROPOspheric Monitoring Instrument (TROPOMI) observations were resampled to obtain 0.01° × 0.01° NO2 VCD (vertical column density) over Yangtze River Delta (YRD), China. Based on this high spatial resolution satellite observations, NO2 VCDs in megacities cluster of YRD region were examined with a reduction of ~35% during COVID-19 lockdown. The adjusted Exponentially-Modified Gaussian (EMG) model was used to estimate the NOX emission in typical cities under regionally polluted YRD region. Taking 100 km of mass integration interval as an example, during 2018–2019, the averaged NOX emission of Shanghai, Hangzhou, Nanjing, and Ningbo is 139.65 mol/s, 84.49 mol/s, 79.87 mol/s and 88.73 mol/s, respectively. This estimation has a good correlation with Multi-resolution Emission Inventory for China (MEIC) emission with R more than 0.9 but lower results mainly due to the underestimation of NO2 VCD by TROPOMI in polluted areas. It was also found that the NOX emissions of Ningbo are higher than expected, which is closely related to massive ship emissions. This study indicates that this approach based on adjusted EMG model can enhance the ability to quantify NOX emissions at city level by utilizing the high spatial resolution observations of TROPOMI.

19.
Systems and Soft Computing ; 4:200035, 2022.
Article in English | ScienceDirect | ID: covidwho-1671117

ABSTRACT

Air pollution has been on continuous rise with increase in industrialization in metropolitan cities of the world. Several measures including strict climate laws and reduction in the number of vehicles were implemented by several nations. The COVID-19 pandemic provided a great opportunity to understand the daily human activities effect on air pollution. Majority nations restricted industrial activities and vehicular traffic to a large extent as a measure to restrict COVID-19 spread. In this paper, we analyzed the impact of such COVID19-induced lockdown on the air quality of the city of New Delhi, India. We analyzed the average concentration of common gaseous pollutants viz. sulfur dioxide (SO2), ozone (O3), nitrogen dioxide (NO2), and carbon monoxide (CO). These concentrations were obtained from the tropospheric column of Sentinel-5P (an earth observation satellite of European Space Agency) data. We observed that the city observed a significant drop in the level of atmospheric pollutant’s concentration for all the major pollutants as a result of strict lockdown measure. Such findings are also validated with pollutant data obtained from ground based monitoring stations. We observed that near-surface pollutant concentration dropped significantly by 50% for PM2.5, 71.9% for NO2, and 88% for CO, after the lockdown period. Such studies would pave the path for implementing future air pollution control measures by environmentalists.

20.
Journal of Environmental Sciences ; 2022.
Article in English | ScienceDirect | ID: covidwho-1620822

ABSTRACT

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 (NO2) tropospheric vertical column density (TVCD) in 2020. The NO2 TVCD reveals a sharp drop, followed by a stable fluctuation and then a strong rebound when compared to 2019. By the end of 2020, the annual average NO2 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 NO2 TVCD is mainly caused by the rapid recovery of economy especially in the fourth quarter, when contribution of industry and power plant on NO2 TVCD continues to rise. This revenge bounce of NO2 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.

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