Tropospheric Column Research Articles

Large discrepancy between observed and modeled wintertime tropospheric NO2 variabilities due to COVID-19 controls in China

Recent studies demonstrated the difficulties to explain observed tropospheric nitrogen dioxide (NO2) variabilities over the United States and Europe, but thorough analysis for the impacts on tropospheric NO2 in China is still lacking. Here we provide a comparative analysis for the observed and modeled (Goddard Earth Observing System-Chem) tropospheric NO2 in early 2020 in China. Both ozone monitoring instrument and surface NO2 measurements show marked decreases in NO2 abundances due to the 2019 novel coronavirus (COVID-19) controls. However, we find a large discrepancy between observed and modeled NO2 changes over highly polluted provinces: the observed reductions in tropospheric NO2 columns are about 40% lower than those in surface NO2 concentrations. By contrast, the modeled reductions in tropospheric NO2 columns are about two times higher than those in surface NO2 concentrations. This discrepancy could be driven by the combined effects from uncertainties in simulations and observations, associated with possible inaccurate simulations of lower tropospheric NO2, larger uncertainties in the modeled interannual variabilities of NO2 columns, as well as insufficient consideration of aerosol effects and a priori NO2 variability in satellite retrievals. In addition, our analysis suggests a small influence from free tropospheric NO2 backgrounds in E. China in winter. This work demonstrates the challenge to interpret wintertime tropospheric NO2 changes in China, highlighting the importance of integrating surface NO2 observations to provide better analysis for NO2 variabilities.

Variability of nitrogen oxide emission fluxes and lifetimes estimated from Sentinel-5P TROPOMI observations

Abstract. Satellite observations of the high-resolution TROPOspheric Monitoring Instrument (TROPOMI) on Sentinel-5 Precursor can be used to observe nitrogen dioxide (NO2) at city scales to quantify short time variability of nitrogen oxide (NOx) emissions and lifetimes on a daily and seasonal basis. In this study, 2 years of TROPOMI tropospheric NO2 columns, having a spatial resolution of up to 3.5 km × 5.5 km, have been analyzed together with wind and ozone data. NOx lifetimes and emission fluxes are estimated for 50 different NOx sources comprising cities, isolated power plants, industrial regions, oil fields, and regions with a mix of sources distributed around the world. The retrieved NOx emissions are in agreement with other TROPOMI-based estimates and reproduce the variability seen in power plant stack measurements but are in general lower than the analyzed stack measurements and emission inventory results. Separation into seasons shows a clear seasonal dependence of NOx emissions with in general the highest emissions during winter, except for isolated power plants and especially sources in hot desert climates, where the opposite is found. The NOx lifetime shows a systematic latitudinal dependence with an increase in lifetime from 2 to 8 h with latitude but only a weak seasonal dependence. For most of the 50 sources including the city of Wuhan in China, a clear weekly pattern of NOx emissions is found, with weekend-to-weekday ratios of up to 0.5 but with a high variability for the different locations. During the Covid-19 lockdown period in 2020, strong reductions in the NOx emissions were observed for New Delhi, Buenos Aires, and Madrid.

The Impact of Springtime‐Transported Air Pollutants on Local Air Quality With Satellite‐Constrained NOx Emission Adjustments Over East Asia

AbstractTo quantify the impact of transported air pollutants on local air quality, this study applies an inverse modeling technique with tropospheric nitrogen dioxide column retrievals from TROPOspheric Monitoring Instrument, and the CMAQ‐ISAM model, which computes source attribution over six regions of interest in spring 2019 over East Asia. Satellite‐constrained nitrogen oxides (NOx) emissions successfully improve model performance by significantly reducing the normalized mean bias of concentrations of NOx, Ozone (O3), and PM2.5 from most regions in China and South Korea. Anticyclones over the Yellow Sea transport air pollutants and increase the contribution of emissions from adjacent regions to local air quality. Fluxes of air pollutants with posterior emissions showed notable enhancements in their magnitude by 3%–24% for NOy, O3, and PM2.5. The contributions of emissions from neighboring regions on local NOx and O3 budgets in the planetary boundary layer were 22.96%–35.24% and 24.23%–42.26%. The contribution of emissions from North Korea was notable despite its comparably lower emission rates. Regarding the impact of external influences on local air quality, the enhanced chemical loss of NOx compensated for increases by transport. Also, the increased vertical gradient of maximum daily 8‐hr average O3 amplified vertical transport and dry deposition processes in the opposite direction along with slight changes in the chemical net O3 production rate. This study shows the nonlinear response of local air quality to changes in the transport of air pollutants, which could be further investigated concerning changes in emissions and climatological factors that would modify the inflow of air pollutants.

Air quality in the New Delhi metropolis under COVID-19 lockdown

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 (SO), ozone (O), nitrogen dioxide (NO), 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 NO, and 88% for CO, after the lockdown period. Such studies would pave the path for implementing future air pollution control measures by environmentalists.

Understanding China's resumption of work and production during the critical period of COVlD‐19 based on multi‐source data

AbstractMonitoring the resumption of work and production (RWP) is of great significance to the restoration of social order and the economy after the coronavirus disease 2019 (COVID‐19) epidemic. In this study, the most critical period of epidemic prevention and control and economic recovery was divided into four phases according to the changes in emergency response levels during the epidemic in China, and based on VIIRS I‐Band 375‐m active fire data (VNP14IMG), NO2 tropospheric vertical column density (TVCD) data, and intracity travel intensity data, the density‐based spatial clustering of applications with the noise logistic regression industrial heat source identification model, NO2 difference model, and urban relative recovery index were constructed to analyze work resumption at different phases. The results indicate that: (1) the production intensity of China's heat source enterprises decreased first and then exceeded the epidemic period compared with the same period in history. From phases 1 to 3, the heat source enterprise production intensity was lower than the same period in 2019 (the production intensities were 19,562.79, 22,462.57, and 38,466.89, respectively), and the reduction rates of production intensity were 27.5, 26.1, and 22.7%, respectively. In phase 4, enterprise production intensity achieved an increase of 7%. (2) The process of the RWP in China is closely related to NO2 TVCD. In the first three phases, significantly decreased emission sources of NO2 reduced the total value of NO2 by varying degrees in most provinces of the country. Correspondingly, in phase 4, the NO2 TVCD in some provinces recovered to the value of the same period in 2019, including typical industrial bases (Shandong, Hebei, Shanxi, etc.) and economically developed coastal areas (Jiangsu, Guangdong, Zhejiang, etc.). (3) In phase 3, the intracity travel intensity in all cities improved, and the city relative recovery index (RRI) rose across the board. In particular, the western cities were better than the eastern cities. Among them, the RRIs of most cities in southwest China (Sichuan, Yunnan) and northwest China (Gansu) were more than 90%. Notably, the recovery situation exhibited an obvious “siege phenomenon,” and the recovery of core cities required a longer period. Overall, the sudden COVID‐19 epidemic seriously affected the production of Chinese enterprises. However, benefitting from rapid and effective epidemic prevention and control measures, the resumption of work and production has been a success. Our study provides guidance for economic recovery strategies during post‐pandemic stages.

Spatiotemporal Variations and Influent Factors of Tropospheric Ozone Concentration over China Based on OMI Data

Spatiotemporal distribution of atmospheric pollutants has been a hot topic in the field of environmental science in recent years. Rapid economic development, urbanization, and industrialization have resulted in a significant increase in ozone emissions, and China is facing the issue of air pollution with high ozone concentrations in the ambient air. The Aura ozone monitoring instrument (OMI), can provide long-term and large-scale dynamic monitoring of tropospheric column ozone (TCO). The TCO concentrations over China were extracted and analyzed from 2005 to 2019. The results showed that the spatiotemporal distribution of ozone concentration decreased from northeast to southeast in China. The seasonal variations of ozone concentration were spring’s concentration is greater than winter’s concentration, winter’s concentration is greater than summer’s concentration, summer’s concentration is greater than autumn’s concentration. The monthly variation showed a cyclical trend, with low values observed from June to November and high values from December to May. In addition, the spatiotemporal distribution of ozone concentration was affected by natural factors and anthropogenic factors. Regarding natural factors, TCO concentration was positively correlated with temperature, wind field, and vegetation coverage, but negatively with precipitation in southwest China. Regarding anthropogenic factors, TCO concentration showed a significant positive correlation with regional GDP, oxides of nitrogen (NOx), and volatile organic compounds (VOCs) in most areas of China. Clustering of backward air trajectories revealed that northwest and southeast airflows led to a higher TCO concentration in northeast China. These further indicate that the variation of TCO concentration was affected by many factors, but temperature, wind field, and the emissions of NOx and VOCs were the key factors.

Measurement report: Long-term variations in surface NO<sub><i>x</i></sub> and SO<sub>2</sub> mixing ratios from 2006 to 2016 at a background site in the Yangtze River Delta region, China

Abstract. China has been experiencing rapid changes in emissions of air pollutants in recent decades. Increased emissions of primary particulates and reactive gases caused severe haze in several polluted regions including the Yangtze River Delta (YRD). Measures implemented in recent years for improving air quality have reduced the emissions of NOx, SO2, etc. The emission changes in these gases are reflected by tropospheric columns from satellite observations and surface measurements of surface concentrations from urban sites. However, little is known about the long-term variations in regional background NOx and SO2. In this study, we present NOx and SO2 measurements from the Lin'an station (LAN; 30∘18' N, 119∘44′ E; 138.6 m a.s.l.), one of the Global Atmosphere Watch (GAW) stations in China. We characterize the seasonal and diurnal variations and study the long-term trends of NOx and SO2 mixing ratios observed at LAN from 2006 to 2016. We also interpret the observed variations and trends in terms of changes in meteorological conditions as well as emission of these gases. The overall average mixing ratios of NOx (NO2) and SO2 during 2006–2016 were 13.6 ± 1.2 ppb (12.5 ± 4.6) and 7.0 ± 4.2 ppb, respectively. The averaged seasonal variations showed maximum values of NOx and SO2 in December (23.5 ± 4.4 ppb) and January (11.9 ± 6.2 ppb), respectively, and minimum values of 7.1 ± 0.8 and 2.8 ± 2.3 ppb (both in July), respectively. The average diurnal variation characteristics of NOx and SO2 differed considerably from each other, though the daily average mixing ratios of both gases were significantly correlated (R2=0.29, P<0.001). The annual average mixing ratio of NOx increased during 2006–2011 and then decreased significantly at 0.78 ppb/yr (−5.16 %/yr, P<0.01). The annual 95th and 5th percentiles of hourly NOx mixing ratios showed upward trends until 2012 and 2014, respectively, before a clear decline. The annual average mixing ratio of SO2 decreased significantly at 0.99 ppb/yr (−8.27 %/yr, P<0.01) from 2006–2016. The annual 95th and 5th percentiles of hourly SO2 mixing ratios all exhibited significant (P<0.001) downward trends at 3.18 and 0.19 ppb/yr, respectively. Changes in the total NOx and SO2 emissions as well as the industrial emissions in the YRD region were significantly correlated with the changes in annual NOx and SO2 mixing ratios. The significant decreases in NOx from 2011 to 2016 and SO2 from 2006 to 2016 highlight the effectiveness of relevant control measures on the reduction in NOx and SO2 emissions in the YRD region. A decrease in annual SO2 / NOx ratio was found, suggesting a better efficacy in the emission reduction in SO2 than NOx. We found gradual changes in average diurnal patterns of NOx and SO2, which could be attributed to increasing contributions of vehicle emissions to NOx and weakening impacts of large sources on the SO2 concentration. This study reaffirms China's success in controlling both NOx and SO2 in the YRD but indicates at the same time a necessity to strengthen the NOx emission control.

Variations of Urban NO2 Pollution during the COVID-19 Outbreak and Post-Epidemic Era in China: A Synthesis of Remote Sensing and In Situ Measurements

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.

Year-round changes in tropospheric nitrogen dioxide caused by COVID-19 in China using satellite observation

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 small fluctuations 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.

Comparison between economic growth and satellite-based measurements of NO2 pollution over northern Italy

The aim of this study is to investigate to what extent spatiotemporal fluctuations in the tropospheric NO2 column concentration can map variations in economic output. To do so satellite based tropospheric NO2 column measurements obtained from the ERS-2, ENVISAT, MetOp-A, and MetOp-B satellite missions covering the period from 1996 to 2017 over the Po valley in northern Italy is analyzed. A harmonic analysis is carried out in order to exclude influences such as the annual or semi-annual cycle. Afterwards the residues of the tropospheric NO2 time series are further investigated by means of a wavelet analysis method. The result is a spectrogram which implies the NO2 variability for the study area between 1996 and 2017. Therefore, the gross domestic product (GDP) is used as an indicator for economic performance and thus, as an approximation, of anthropogenically induced NO2 pollution. Clear conspicuous signatures occurred almost simultaneously both within the temporal development of the GDP growth rate and the spectral characteristic of the NO2 variability during the studied period. The comparison of the temporal course of the GDP shows that the period of systematically reduced spectral intensity in NO2 coincides strikingly well with the period of the global financial crisis in 2008 which was then followed by a second crisis in 2014. The economic growth decreased by 7.9% between 2007 and 2009 and by 5.2% between 2011 and 2014 in comparison to the same quarter of the previous year. It is found that during the crises (2007–2013) the variability of NO2 is reduced by about 80%.

Modeling of spatial and temporal variations of ozone-NOx-VOC sensitivity based on photochemical indicators in China

Comprehensive air quality model with extensions (CAMx)-decoupled direct method (DDM) was used to simulate ozone-NOx-VOCs sensitivity of for May–November in 2016–2018 in China. Based on the relationship between the simulated ozone (O3) sensitivity values and the ratio of formaldehyde (HCHO) to NO2 (FNR) and the ratio of production rate of hydrogen peroxide (H2O2) to production rate of nitric acid (HNO3) (PH2O2/PHNO3), the localized range of FNR and PH2O2/PHNO3 thresholds in different regions in China were obtained. The overall simulated FNR values are about 1.640–2.520, and PH2O2/PHNO3 values are about 0.540–0.830 for the transition regime. Model simulated O3 sensitivities or region specific FNR or PH2O2/PHNO3 thresholds should be applied to ensure the accurate local O3 sensitivity regimes. Using the tropospheric column FNR values from ozone monitoring instrument (OMI) satellite data as an indicator with the simulated threshold values, the spatial distributions of O3 formation regimes in China are determined. The O3 sensitivity regimes from eastern to central China are gradually from VOC-limited, transition to NOx-limited spatially, and moving toward to transition or NOx-limited regime from 2005 to 2019 temporally.

Assessment of the Performance of TROPOMI NO2 and SO2 Data Products in the North China Plain: Comparison, Correction and Application

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.

“Novel 2019 Coronavirus Outbreak” through the Eyes of GNSS Signal

Besides the global crisis of the novel COVID-19 outbreak, we have presented the other side towards an environmental perspective. Due to the economic shutdown of major cities, the novel COVID-19 outbreak has significantly influenced air quality in the atmosphere and also affected the tropospheric refraction on Global Navigation Satellite System GNSS signal propagation in the horizontally stratified column. We suggest that GNSS signal propagation and variation in Zenith Tropospheric Delay (ZTD) in the tropospheric column can be used as a proxy for the pollution-monitoring tool in the future. Although we have presented a case study from mainland China, the hypothesis can be tested globally.

Effects of COVID-19 pandemic lockdown: A satellite data-based appraisal of air quality in Guwahati, Assam

Moderate Resolution Imaging Spectroradiometer (MODIS) and Ozone Monitoring Instrument (OMI) based data are used to evaluate the effects of the COVID-19 lockdown on the concentrations of pollutants such as aerosol optical depth (AOD) and tropospheric columns of nitrogen dioxide (NO2) along with sulfur dioxide (SO2) respectively for the period of January 2017 to September 2021 over the capital city of Assam, Guwahati. In India lockdown due to COVID-19 was first imposed from 24th March to 14th April as phase I and then it extended from 15th April to 3rd May as phase II in the year 2020. The concentration of all pollutants was usually fall during the lockdown period as compared to their average during the 5-year period over the study area. The results showed that Pre-monsoon (March-May) seasonal AOD for the pandemic year 2020 was decreased by ∼ 23% after lockdown as compared to same season of normal years over the study location. The seasonally averaged AOD reached its peak value in pre-monsoon (0.78 ± 0.09), followed by winter (0.59 ± 0.10) and monsoon (0.52 ± 0.05), with the minimum taking place in post-monsoon (0.38 ± 0.08) season. The monthly average AOD varies from its highest value (0.82 ± 0.18) in May to its lowest value (0.36 ± 0.10) in October for the study period over Guwahati. Tropospheric column NO2 exhibits same seasonality as AOD with highest value (0.21 × 1016 molecules cm−2) in pre-monsoon and lowest value (0.13 × 1016 molecules cm−2) in post-monsoon season which may be due to same source of origination of both NO2 and AOD. Conversely, SO2 does not vary much from the five-year average value during the lockdown period. Significant reduction in PM2.5 mass concentration value during Covid-19 lockdown months has been observed which indicates short term improvement of air quality over Guwahati.

Variation in Aerosol Optical Depth (AOD), NO2 and Tropospheric Ozone Column during the Lockdown Period Amid COVID-19 Pandemic over India

With the emergence of COVID-19 in late December 2019 in China and its exponential spread around the globe, on 11th March 2020 WHO declared it global pandemic. The first case of novel coronavirus in India was reported on 30th January 2020 in Kerala state of India. India is currently experiencing the worst situation amid COVID-19 pandemic with its 3rd position having the highest number of confirmed cases amongst the countries around the world with huge social and economic losses. Many studies reported that there is an improvement in air quality around different parts of the world due to cessation of vehicular, industrial and anthropogenic activities. The present study highlights the impact of COVID-19 pandemic on air quality over India during the lockdown period amid COVID-19 pandemic. Results revealed the significant decline in NO2 and aerosol optical depth (AOD) all around in India except for ozone. There has been a considerable decline in air pollution because of restricted activities during COVID-19 pandemic over India. Meteorological factors may not be directly related to the number of outbreaks. Although the COVID-19 lockdown has a negative impact on economic aspects but it has a positive impact on air quality. The COVID-19 pandemic impacted the lives of millions and having numerous global implications made humans believe that nothing will be normal as earlier. The study may help authorities and policy makers on taking specific measures for the pandemic it can be helpful in future to frame policies to reduce air pollution by policy makers.

Impacts of Strategic Mobility Restrictions Policies during 2020 COVID-19 Outbreak on Brazil’s Regional Air Quality

With the unexpected arrival of the COVID-19 pandemic, countries worldwide were forced to take measures to curb its transmission. Mobility restrictions policies were the primary preventive measures applied around the globe. In addition to reducing the disease spread, they resulted in air quality changes in urbanized areas. In this sense, this study aimed to investigate how the mobility restrictions imposed by public policies impacted the air quality in Brazil during the COVID-19 2020 outbreak. Therefore, air quality (CO, NO2, PM10, PM2.5, and O3) and urban mobility datasets available in five populous Brazilian states (São Paulo, Rio de Janeiro, Espírito Santo, Paraná, and Rio Grande do Sul) were analyzed. Variations in air pollutant concentrations were verified by comparing the period during mobility restrictions (2020) and the average concentrations found before the restrictions (2015–2019). In addition, spatial assessment of changes was evaluated using tropospheric NO2 column densities from the TROPOMI. Although there was no national regulation regarding mobility restrictions, the results show that the reduction in urban mobility was similar for all the analyzed states. Following the mobility behavior, reducing air pollutant concentrations were significant for the first 30 days of restrictions. During this period, the most substantial reductions were observed for CO in the State of Rio Grande do Sul (–53%), NO2 in Rio de Janeiro (–34%), and PM10 in Espírito Santo (–23%). The exception was observed for O3, which followed the world trend of increasing concentrations (e.g., 40% increase in Paraná). Spatially, it was possible to evidence that large urban centers (with a large vehicle fleet) were the ones that showed the most significant reduction in NO2. However, when analyzing longer periods (over 90 days), there is a trend towards an increase in the concentrations of primary pollutants and a consequent reduction in O3, reflecting the significant increase in mobility rates.

Change In Nitrogen Dioxide (No2 ) Concentration Due To The Lockdown Amid The Covid-19 Pandemic In India

The study aimed to examine the change in the concentration of nitrogen dioxide due to the lockdown amid the COVID-19 pandemic in India at the district level using Sentinel-5P TROPOMI. The spatio-temporal characteristics of the tropospheric column NO2 concentration during 45 days of the lockdown were compared with the same days of 2019. Further, to model spatially varying relationships of NO2 during the lockdown period, it was given as a dependent variable whereas NO2 during the pre-lockdown period was considered as an independent variable. Results show that the mean NO2 concentration was reduced from 0.00406 mol/m2 before the lockdown (2019-03-25 to 2019-05-10) to 0.0036 mol/m2 during the lockdown period (2020-03-25 to 2020-05-10). The maximum decline of NO2 concentration was observed in Gautam Buddha Nagar and Delhi. This indicates the high level of atmospheric pollution due to the excess use of fuel in human activities. The results of the Ordinary Least Squares (OLS) method show a strong positive relationship between both variables. Positive standard residuals indicate that the concentration of NO2 has reduced more than expected as per the OLS model. The z-score (24.11) was obtained from spatial autocorrelation. It indicates that residuals are highly clustered and there is less than a 1% likelihood that this clustered pattern could be a result of a random chance. The highest decrease was observed in districts/urban agglomerations of Gautam Buddha Nagar (-40%), Delhi (-37%), Greater Bombay (-31%), Hyderabad (-29%), Faridabad (-29%), Bangalore Urban (-28%), Gandhinagar (-27%), Chennai (-27%) and Gurgaon (-26%) respectively.

Tropospheric NO2: Explorative analyses of spatial variability and impact factors

In order to study spatial patterns of nitrogen dioxide (NO2) and its impact factors, consistent and area-wide information is essential. With TROPOMI aboard Sentinel-5 Precursor (S-5P), daily tropospheric NO2 observations have become available with an unprecedented spatial resolution of 3.5 km × 5.5 km. However, a systematic study of tropospheric NO2 patterns on a national scale and with preserved high spatial resolution is still pending. In addition, the increasing availability of area-wide, high-resolution data for large study areas presents new challenges for analyzing impact factors, such as spatial heterogeneity. Based on the annual mean tropospheric NO2 of Germany (September 2018 to August 2019) resampled to a 1 km × 1 km spatial resolution, the subject of this study was twofold: on the one hand a hot and cold spot analysis was performed, on the other hand, non-meteorological factors influencing tropospheric NO2 were investigated within spatial regimes of different land use / land cover (LU/LC) compositions. A total of 24 national hot spots were identified with the majority located in urban areas. The spatial regime-based impact factor analysis revealed that most correlation coefficients between LU/LC and tropospheric NO2 are highly dependent on the location. Some other factors, however, were found to have a strong impact on tropospheric NO2 independent of the location (impervious surfaces, population and road density). Although this study is based on tropospheric column data, and meteorology has not been considered yet, the analyses demonstrate the contribution of Sentinel-5P/TROPOMI data to a better understanding of the high-dimensional and complex relationship between NO2, the atmosphere and the composition of the land surface and its use.

Impact of Using a New High-Resolution Solar Reference Spectrum on OMI Ozone Profile Retrievals

We evaluated a new high-resolution solar reference spectrum for characterizing space-borne Ozone Monitoring Instrument (OMI) measurements as well as for retrieving ozone profile retrievals over the ultraviolet (UV) wavelength range from 270 to 330 nm. The SAO2010 solar reference has been a standard for use in atmospheric trace gas retrievals, which is a composite of ground-based and balloon-based solar measurements from the Kitt Peak National Observatory (KPNO) and Air Force Geophysics Laboratory (AFGL), respectively. The new reference spectrum, called the TSIS-1 Hybrid Solar Reference Spectrum (HSRS), spans 202–2730 nm at a 0.01 to ~0.001 nm spectral resolution. The TSIS-1 HSRS in the UV region of interest in this study is a composite of AFGL and ground-based solar measurements from the Quality Assurance of Spectral Ultraviolet Measurements In Europe (QASUME) campaign, with a radiometric calibration that used the lower resolution Spectral Irradiance Monitor (SIM) instrument on the space-based Total and Spectral Solar Irradiance Sensor-1 (TSIS-1) mission. The TSIS-1 HSRS radiometric uncertainties were below 1% whereas those of SAO2010 ranged from 5% in the longer UV part to 15% in the shorter UV part. In deriving slit functions and wavelength shifts from OMI solar irradiances, the resulting fitting residuals showed significant improvements of 0.5–0.7% (relatively, 20–50%) due to switching from the SAO2010 to the TSIS-1 HSRS. Correspondingly, in performing ozone profile retrievals from OMI radiances, the fitting residuals showed relative improvements of up to ~5% in 312–330 nm with relative differences of 5–7% in the tropospheric layer column ozone; the impact on stratospheric ozone retrievals was negligible.

Impact of the COVID-19 pandemic related to lockdown measures on tropospheric NO<sub>2</sub> columns over Île-de-France

Abstract. The evolution of NO2, considered as a proxy for air pollution, was analyzed to evaluate the impact of the first lockdown (17 March–10 May 2020) over the Île-de-France region (Paris and surroundings). Tropospheric NO2 columns measured by two UV-Visible Système d'Analyse par Observation Zénithale (SAOZ) spectrometers were analyzed to compare the evolution of NO2 between urban and suburban sites during the lockdown. The urban site is the observation platform QualAir (48∘50′ N / 2∘21′ E) at the Sorbonne University Pierre and Marie Curie Campus in the center of Paris. The suburban site is located at Guyancourt (48∘46′N / 2∘03′E), Versailles Saint-Quentin-en-Yvelines University, 24 km southwest of Paris. Tropospheric NO2 columns above Paris and Guyancourt have shown similar values during the whole lockdown period from March to May 2020. A decade of data sets were filtered to consider air masses at both sites with similar meteorological conditions. The median NO2 columns and the surface measurements of Airparif (Air Quality Observatory in Île de France) during the lockdown period in 2020 were compared to the extrapolated values estimated from a linear trend analysis for the 2011–2019 period at each station. Negative NO2 trends of −1.5 Pmolec. cm−2 yr−1 (∼ −6.3 % yr−1) are observed from the columns, and trends of −2.2 µg m−3 yr−1 (∼ −3.6 % yr−1) are observed from the surface concentration. The negative anomaly in tropospheric columns in 2020 attributed to the lockdown (and related emission reductions) was found to be 56 % at Paris and 46 % at Guyancourt, respectively. A similar anomaly was found in the data of surface concentrations, amounting to 53 % and 28 % at the urban and suburban sites, accordingly.