Tropospheric Vertical Column Densities Research Articles

Propagation of NO2 originated in intense fires in the Paraná River Delta analyzed from satellite observations

Wildfires in the Paraná River Delta started to be a common situation in the year 2008 and during the first years of the 2020́s decade: 2020, 2021, 2022. These fires affected natural areas, primarily the islands within the delta, situated in front of Rosario city (32.95 °S, 60.67 °W, 25 meters above sea level (m.a.s.l.)), Argentina. They mostly occur during the period between June and September each year and are more intense when a strong La Niña event is present. The aim of this study is to examine the association between the propagation of high intensity nitrogen dioxide (NO2) plumes and the significant fire events that occurred in the Paraná River Delta from 6 to 17 September 2022. Satellite data of NO2 obtained from the TROPOspheric Monitoring Instrument (TROPOMI) on board the European Space Agency (ESA) Sentinel-5 Precursor satellite, air mass forward trajectories performed with The Hybrid Single-Particle Lagrangian Integrated Trajectory model (HYSPLIT), Fire Radiative Power (FRP) data provided by Visible Infrared Imaging Radiometer Suite (VIIRS) on board The National Oceanic and Atmospheric Administration - 20 (NOAA-20) and Suomi National Polar-orbiting Partnership (S-NPP) satellites, Aerosol Optical Depth (AOD) from VIIRS S-NPP and Smoke Injection Height from Multi-Angle Implementation of Atmospheric Correction (MAIAC) Thermal Technique were employed. The trajectories followed by the air masses coming from the major fire sources locations nearby Rosario city and its surrounding area, were analyzed at altitudes of 20, 500, 1000, 1500 and 2000 m above ground level (AGL) in order to evaluate the impact of the NO2 clouds present in the atmosphere and carried by the winds, at different sites of Rosario and its adjacent region. The NO2 plumes has the potential to pose a significant health risk for this region, inhabited by an approximate population of one and a half million individuals. This risk is contingent upon the altitude where the highest levels of NO2 in the tropospheric column are found. Tropospheric vertical column densities (VCDs) of NO2 in the range of 4.68×1014 to 1.66×1016 molecules/cm2 were determined. The results indicate a robust correlation between elevated tropospheric NO2 VCD values and intense fires, as characterized by their FRP. Additionally, high tropospheric NO2 VCDs were observed to impact cities and towns located in close proximity to the fires. In particular, the unusually high tropospheric NO2 VCDs determined for the towns of Fighiera and Pueblo Esther, situated along the coast and near the Paraná River Delta, are noteworthy. This is uncommon considering they are small towns in rural areas that typically have good air quality. The results regarding FRP, provided by VIIRS on board NOAA-20 and S-NPP satellites, indicate that the fire characterization of hotspots during the considered period had a mean value in the range of 20.17-21.47 MW. On specific days (12, 13 and 16 September 2022), the cumulative (total) daily values were very high, ranging from 2000 to 10000 MW. Furthermore, on 12 and 13 September 2022, the smoke aerosols did not reach significant altitudes in the atmosphere, remaining within the range of 0 to 1500 m AGL. During the fire period, AOD values close to 1 were observed within the fire plume. Notably, Puerto San Martín (0.27), San Lorenzo (0.22), and Ibarlucea (0.20) recorded higher average AOD values compared to other sites. The remaining sites generally exhibited lower average AOD values, with a slight distinction between rural locations (Pueblo Esther: 0.14 and Fighiera: 0.14) and the city center of Rosario (0.09).

Revised estimates of NO2 reductions during the COVID-19 lockdowns using updated TROPOMI NO2 retrievals and model simulations

The TROPOspheric Monitoring Instrument (TROPOMI) observed unprecedented declines in NO2 vertical column densities (VCD) over the world's most densely populated cities during the 2020 COVID-19 lockdowns. These favorable changes in NO2 air quality were correlated with sharp reductions in traffic volume and economic activity during the lockdowns. In this comprehensive global study, we provide revised estimates of the declines in anthropogenic emissions for 36 megacities using a novel methodology for disentangling the anthropogenic emissions from the meteorological transport and natural variability. We further quantify the uncertainty associated with changes in the a priori profile shape information during the lockdowns due to reduced emissions. Satellite NO2 retrieval techniques calculate an air mass factor that requires a priori NO2 profile shape information representative of the local atmosphere. This information, which is typically obtained from a chemical transport model (CTM), was not available for the early studies. This study also accounts for the satellite sampling errors resulting from the selective sampling of non-cloudy scenes during the study period. For our analysis, we used CTM simulations that were generated with and without COVID-impacted emissions. We perform retrievals of tropospheric NO2 columns with the NASA NO2 algorithm, and then use observed and simulated data to disentangle the meteorological transport from the contribution due anthropogenic emissions. We found that the meteorological transport was most significant source of variability ranging between −35% and 22% of the change total tropospheric VCD. We also find that not accounting for changes in the a priori NO2 profile shape information during the lockdowns resulted in systematic retrieval errors that were up to 12% of the estimated decline, and the elimination of cloud contaminated scenes resulted in sampling errors that in general ranged between varied ±15%.

The variability of NO2 concentrations over China based on satellite and influencing factors analysis during 2019–2021

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

Remote Sensing Measurements at a Rural Site in China: Implications for Satellite NO2 and HCHO Measurement Uncertainty and Emissions From Fires

AbstractNitrogen dioxide (NO2) and formaldehyde (HCHO) play vital roles in atmospheric photochemical processes. Their tropospheric vertical column density (TVCD) distributions have been monitored by satellite instruments. Evaluation of these observations is essential for applying these observations to study photochemistry. Assessing satellite products using observations at rural sites, where local emissions are minimal, is particularly useful due in part to the spatial homogeneity of trace gases. In this study, we evaluate OMI and TROPOMI NO2 and HCHO TVCDs using multi‐axis differential optical absorption spectroscopy (MAX‐DOAS) measurements at a rural site in the east coast of the Shandong province, China in spring 2018 during the Ozone Photochemistry and Export from China Experiment (OPECE) measurement campaign. On days not affected by local burning, we found generally good agreement of NO2 data after using consistent a priori profiles in satellite and MAX‐DOAS retrievals and accounting for low biases in scattering weights in one of the OMI products. In comparison, satellite HCHO products exhibited weaker correlations with MAX‐DOAS data, in contrast to satellite NO2 products. However, TROPOMI HCHO products showed significantly better agreement with MAX‐DOAS measurements compared to OMI data. Furthermore, case studies of the vertical profiles measured by MAX‐DOAS on burning days revealed large enhancements of nitrous acid (HONO), NO2, and HCHO in the upper boundary layer, accompanied with considerable variability, particularly in HONO enhancements.

Ground-based Multi-AXis Differential Optical Absorption Spectroscopy (MAX-DOAS) observations of NO2 and H2CO at Kinshasa and comparisons with TROPOMI observations

Abstract. We present a database of MAX-DOAS (Multi-AXis Differential Optical Absorption Spectroscopy) ground-based observations of NO2 and H2CO tropospheric vertical column densities (VCDtropo) performed for the first time in the city of Kinshasa. These measurements were conducted between November 2019 and July 2021 and processed using the standardized inversion tools developed in the ESA FRM4DOAS (Fiducial Reference Measurements for Ground-Based DOAS Air-Quality Observations) project. The retrieved geophysical quantities are used to validate column observations from the TROPOspheric Monitoring Instrument (TROPOMI) over Kinshasa. In the validation, we experiment with three different comparison cases of increasing complexity. In the first case, a direct comparison between MAX-DOAS observations (hourly average of MAX-DOAS VCDtropo at overpass) and TROPOMI shows an underestimation of TROPOMI with a median bias of −38 % for NO2 and −39 % for H2CO based on monthly comparison. The second case takes into account the different vertical sensitivities of the two instruments and the a priori profile. We note significant changes in the median bias for both compounds: −12 % for NO2 and +11 % for H2CO. The third case builds on the second case by considering also the direction of sight of the MAX-DOAS. For this third case, we find a median bias of +44 % for NO2 and a median bias of +4 % for H2CO. However this case is impacted by low sampling and is considered less reliable. The findings from this study underscore the significance of employing a realistic a priori profile in TROPOMI column extraction, particularly within heavily polluted urban zones like Kinshasa. The investigation also highlights the necessity for prudence when integrating the MAX-DOAS line of sight due to the noise generated during subsampling and the limited horizontal sensitivity of MAX-DOAS observations. Importantly, the study further reveals the pronounced pollution levels of NO2, H2CO and aerosols in both the city of Kinshasa and its adjacent regions, underscoring the imperative for consistent monitoring and effective regulatory measures by local authorities.

Validation of Sentinel-5P TROPOMI tropospheric NO2 products by comparison with NO2 measurements from airborne imaging DOAS, ground-based stationary DOAS, and mobile car DOAS measurements during the S5P-VAL-DE-Ruhr campaign

Abstract. Airborne imaging differential optical absorption spectroscopy (DOAS), ground-based stationary DOAS, and car DOAS measurements were conducted during the S5P-VAL-DE-Ruhr campaign in September 2020. The campaign area is located in the Rhine-Ruhr region of North Rhine-Westphalia, western Germany, which is a pollution hotspot in Europe comprising urban and large industrial sources. The DOAS measurements are used to validate spaceborne NO2 tropospheric vertical column density (VCD) data products from the Sentinel-5 Precursor (S5P) TROPOspheric Monitoring Instrument (TROPOMI). Seven flights were performed with the airborne imaging DOAS instrument for measurements of atmospheric pollution (AirMAP), providing measurements that were used to create continuous maps of NO2 in the layer below the aircraft. These flights cover many S5P ground pixels within an area of 30 km × 35 km and were accompanied by ground-based stationary measurements and three mobile car DOAS instruments. Stationary measurements were conducted by two Pandora, two Zenith-DOAS, and two MAX-DOAS instruments. Ground-based stationary and car DOAS measurements are used to evaluate the AirMAP tropospheric NO2 VCDs and show high Pearson correlation coefficients of 0.88 and 0.89 and slopes of 0.90 ± 0.09 and 0.89 ± 0.02 for the stationary and car DOAS, respectively. Having a spatial resolution of about 100 m × 30 m, the AirMAP tropospheric NO2 VCD data create a link between the ground-based and the TROPOMI measurements with a nadir resolution of 3.5 km × 5.5 km and are therefore well suited to validate the TROPOMI tropospheric NO2 VCD. The observations on the 7 flight days show strong NO2 variability, which is dependent on the three target areas, the day of the week, and the meteorological conditions. The AirMAP campaign data set is compared to the TROPOMI NO2 operational offline (OFFL) V01.03.02 data product, the reprocessed NO2 data using the V02.03.01 of the official level-2 processor provided by the Product Algorithm Laboratory (PAL), and several scientific TROPOMI NO2 data products. The AirMAP and TROPOMI OFFL V01.03.02 data are highly correlated (r=0.87) but show an underestimation of the TROPOMI data with a slope of 0.38 ± 0.02 and a median relative difference of −9 %. With the modifications in the NO2 retrieval implemented in the PAL V02.03.01 product, the slope and median relative difference increased to 0.83 ± 0.06 and +20 %. However, the modifications resulted in larger scatter and the correlation decreased significantly to r=0.72. The results can be improved by not applying a cloud correction for the TROPOMI data in conditions with high aerosol load and when cloud pressures are retrieved close to the surface. The influence of spatially more highly resolved a priori NO2 vertical profiles and surface reflectivity are investigated using scientific TROPOMI tropospheric NO2 VCD data products. The comparison of the AirMAP campaign data set to the scientific data products shows that the choice of surface reflectivity database has a minor impact on the tropospheric NO2 VCD retrieval in the campaign region and season. In comparison, the replacement of the a priori NO2 profile in combination with the improvements in the retrieval of the PAL V02.03.01 product regarding cloud heights can further increase the tropospheric NO2 VCDs. This study demonstrates that the underestimation of the TROPOMI tropospheric NO2 VCD product with respect to the validation data set has been and can be further significantly improved.

Ozone Pollution of Megacity Shanghai during City-Wide Lockdown Assessed Using TROPOMI Observations of NO2 and HCHO

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

Investigating Changes in Ozone Formation Chemistry during Summertime Pollution Events over the Northeastern United States.

Understanding the local-scale spatial and temporal variability of ozone formation is crucial for effective mitigation. We combine tropospheric vertical column densities (VCDTrop) of formaldehyde (HCHO) and nitrogen dioxide (NO2), referred to as HCHO-VCDTrop and NO2-VCDTrop, retrieved from airborne remote sensing and the TROPOspheric Monitoring Instrument (TROPOMI) with ground-based measurements to investigate changes in ozone precursors and the inferred chemical production regime on high-ozone days in May-August 2018 over two Northeast urban domains. Over New York City (NYC) and Baltimore/Washington D.C. (BAL/DC), HCHO-VCDTrop increases across the domain, but higher NO2-VCDTrop occurs mainly in urban centers on ozone exceedance days (when maximum daily 8 h average (MDA8) ozone exceeds 70 ppb at any monitor in the region). The ratio of HCHO-VCDTrop to NO2-VCDTrop, proposed as an indicator of the sensitivity of local surface ozone production rates to its precursors, generally increases on ozone exceedance days, implying a transition toward a more NOx-sensitive ozone production regime that should lead to higher efficacy of NOx controls on the highest ozone days in NYC and BAL/DC. Warmer temperatures and enhanced influence from emissions in the local boundary layer on the high-ozone days are accompanied by slower wind speeds in BAL/DC but stronger, southwesterly winds in NYC.

Comparison of S5P/TROPOMI Inferred NO2 Surface Concentrations with In Situ Measurements over Central Europe

The aim of this paper is to evaluate the surface concentration of nitrogen dioxide (NO2) inferred from the Sentinel-5 Precursor Tropospheric Monitoring Instrument (S5P/TROPOMI) NO2 tropospheric column densities over Central Europe for two time periods, summer 2019 and winter 2019–2020. Simulations of the NO2 tropospheric vertical column densities and surface concentrations from the Long-Term Ozone Simulation–European Operational Smog (LOTOS-EUROS) chemical transport model are also applied in the methodology. More than two hundred in situ air quality monitoring stations, reporting to the European Environment Agency (EEA) air quality database, are used to carry out comparisons with the model simulations and the spaceborne inferred surface concentrations. Stations are separated into seven types (urban traffic, suburban traffic, urban background, suburban background, rural background, suburban industrial and rural industrial) in order to examine the strengths and shortcomings of the different air quality markers, namely the NO2 vertical column densities and NO2 surface concentrations. S5P/TROPOMI NO2 surface concentrations are inferred by multiplying the fraction of the satellite and model NO2 vertical column densities with the model surface concentrations. The estimated inferred TROPOMI NO2 surface concentrations are examined further with the altering of three influencing factors: the model vertical leveling scheme, the versions of the TROPOMI NO2 data and the air mass factors applied to the satellite and model NO2 vertical column densities. Overall, the inferred TROPOMI NO2 surface concentrations show a better correlation with the in situ measurements for both time periods and all station types, especially for the industrial stations (R > 0.6) in winter. The calculated correlation for background stations is moderate for both periods (R~0.5 in summer and R > 0.5 in winter), whereas for traffic stations it improves in the winter (from 0.20 to 0.50). After the implementation of the air mass factors from the local model, the bias is significantly reduced for most of the station types, especially in winter for the background stations, ranging from +0.49% for the urban background to +10.37% for the rural background stations. The mean relative bias in winter between the inferred S5P/TROPOMI NO2 surface concentrations and the ground-based measurements for industrial stations is about −15%, whereas for traffic urban stations it is approximately −25%. In summer, biases are generally higher for all station types, especially for the traffic stations (~−75%), ranging from −54% to −30% for the background and industrial stations.

Tropospheric Nitrogen Dioxide Increases Past Pre-Pandemic Levels Due to Economic Reopening in India

This paper analyzes the spatiotemporal patterns of nitrogen dioxide (NO2) tropospheric vertical column densities (TVCDs) before and during the second wave of COVID-19 in India. The results indicate that the NO2 columns increase significantly in the reopening period before the second wave (Mar. 1 ∼ Apr. 20) in 2021, which exceed the levels of the same period in 2019. The relative difference from the mean of 2010–2019 is 18.76% higher in 2021 than that of 2019, during the reopening. The paper identifies Odisha, Madhya Pradesh, Chhattisgarh, Jharkhand and West Bengal as the five states with the largest increases in relative difference from 2019 to 2021, which are 33.81%, 29.83%, 23.86%, 30.01%, and 25.48% respectively. As illustrated by trends in the indices of industrial production (IIP), these unexpected increases in tropospheric NO2 can be attributed to reopening as well as elevated production across various sectors including electricity, manufacturing and mining. Analysis of NO2 TVCD levels alongside IIPs indicate a marked increase in industrial activity during the reopening period in 2021 than in the same time period in 2019. After the beginning of the second wave of COVID-19 (Apr. 21 ∼ Jun. 21), India re-implemented lockdown policies to mitigate the spread of the pandemic. During this period, the relative difference of total NO2 columns declined in India as well as in most individual study regions, when compared to 2019, due to the pandemic mitigation policies. The relative declines are as follows: 6.43% for the whole country and 14.25%, 22.88%, 4.57% and 7.89% for Odisha, Madhya Pradesh, Chhattisgarh and Jharkhan, respectively, which contain large industrial clusters. The change in relative difference in West Bengal from 2019 to 2021 is not significant during the re-lockdown period with a 0.04% increase. As with the first wave, these decreases in NO2 TVCD mainly due to the mitigation policies during the second wave.

Impact of 3D cloud structures on the atmospheric trace gas products from UV–Vis sounders – Part 3: Bias estimate using synthetic and observational data

Abstract. Three-dimensional (3D) cloud structures may impact atmospheric trace gas products from ultraviolet–visible (UV–Vis) sounders. We used synthetic and observational data to identify and quantify possible cloud-related bias in NO2 tropospheric vertical column density (TVCD). The synthetic data were based on high-resolution large eddy simulations which were input to a 3D radiative transfer model. The simulated visible spectra for low-earth-orbiting and geostationary geometries were analysed with standard retrieval methods and cloud correction schemes that are employed in operational NO2 satellite products. For the observational data, the NO2 products from the TROPOspheric Monitoring Instrument (TROPOMI) were used, while the Visible Infrared Imaging Radiometer Suite (VIIRS) provided high-spatial-resolution cloud and radiance data. NO2 profile shape, cloud shadow fraction, cloud top height, cloud optical depth, and solar zenith and viewing angles were identified as the metrics being the most important in identifying 3D cloud impacts on NO2 TVCD retrievals. For a solar zenith angle less than about 40∘ the synthetic data show that the NO2 TVCD bias is typically below 10 %, while for larger solar zenith angles the NO2 TVCD is low-biased by tens of percent. The horizontal variability of NO2 and differences in TROPOMI and VIIRS overpass times make it challenging to identify a similar bias in the observational data. However, for optically thick clouds above 3000 m, a low bias appears to be present in the observational data.

Evaluation of TROPOMI and OMI Tropospheric NO2 Products Using Measurements from MAX-DOAS and State-Controlled Stations in the Jiangsu Province of China

The tropospheric vertical column density of NO2 (Trop NO2 VCD) can be obtained using satellite remote sensing, but it has been discovered that the Trop NO2 VCD is affected by uncertainties such as the cloud fraction, terrain reflectivity, and aerosol optical depth. A certain error occurs in terms of data inversion accuracy, necessitating additional ground observation verification. This study uses surface NO2 mass concentrations from the China National Environmental Monitoring Center (CNEMC) sites in Jiangsu Province, China in 2019 and the Trop NO2 VCD measured by MAX-DOAS, respectively, to verify the Trop NO2 VCD product (daily and monthly average data), that comes from the TROPOspheric Monitoring Instrument (TROPOMI) and Ozone Monitoring Instrument (OMI). The results show that the spatial distributions of NO2 in TROPOMI and OMI exhibit a similar tendency and seasonality, showing the characteristics of being high in spring and winter and low in summer and autumn. On the whole, the concentration of NO2 in the south of Jiangsu Province is higher than that in the north. The Pearson correlation coefficient (r) between the monthly average TROPOMI VCD NO2 and the CNEMC NO2 mass concentration is 0.9, which is greater than the r (0.78) between OMI and CNEMC; the r (0.69) between TROPOMI and the MAX-DOAS VCD NO2 is greater than the r (0.59) between OMI and the MAX-DOAS. As such, the TROPOMI is better than the previous generation of OMI at representing the spatio-temporal distribution of NO2 in the regional scope. On the other hand, the uncertainties of the satellite products provided in this study can constrain regional air quality forecasting models and top-down emission inventory estimation.

Sentinel-5P TROPOMI NO<sub>2</sub> retrieval: impact of version v2.2 improvements and comparisons with OMI and ground-based data

Abstract. Nitrogen dioxide (NO2) is one of the main data products measured by the Tropospheric Monitoring Instrument (TROPOMI) on the Sentinel-5 Precursor (S5P) satellite, which combines a high signal-to-noise ratio with daily global coverage and high spatial resolution. TROPOMI provides a valuable source of information to monitor emissions from local sources such as power plants, industry, cities, traffic and ships, and variability of these sources in time. Validation exercises of NO2 v1.2–v1.3 data, however, have revealed that TROPOMI's tropospheric vertical column densities (VCDs) are too low by up to 50 % over highly polluted areas. These findings are mainly attributed to biases in the cloud pressure retrieval, the surface albedo climatology and the low resolution of the a priori profiles derived from global simulations of the TM5-MP chemistry model. This study describes improvements in the TROPOMI NO2 retrieval leading to version v2.2, operational since 1 July 2021. Compared to v1.x, the main changes are the following. (1) The NO2-v2.2 data are based on version-2 level-1b (ir)radiance spectra with improved calibration, which results in a small and fairly homogeneous increase in the NO2 slant columns of 3 % to 4 %, most of which ends up as a small increase in the stratospheric columns. (2) The cloud pressures are derived with a new version of the FRESCO cloud retrieval already introduced in NO2-v1.4, which led to a lowering of the cloud pressure, resulting in larger tropospheric NO2 columns over polluted scenes with a small but non-zero cloud coverage. (3) For cloud-free scenes a surface albedo correction is introduced based on the observed reflectance, which also leads to a general increase in the tropospheric NO2 columns over polluted scenes of order 15 %. (4) An outlier removal was implemented in the spectral fit, which increases the number of good-quality retrievals over the South Atlantic Anomaly region and over bright clouds where saturation may occur. (5) Snow/ice information is now obtained from ECMWF weather data, increasing the number of valid retrievals at high latitudes. On average the NO2-v2.2 data have tropospheric VCDs that are between 10 % and 40 % larger than the v1.x data, depending on the level of pollution and season; the largest impact is found at mid and high latitudes in wintertime. This has brought these tropospheric NO2 closer to Ozone Monitoring Instrument (OMI) observations. Ground-based validation shows on average an improvement of the negative bias of the stratospheric (from −6 % to −3 %), tropospheric (from −32 % to −23 %) and total (from −12 % to −5 %) columns. For individual measurement stations, however, the picture is more complex, in particular for the tropospheric and total columns.

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.

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.

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.

A New Separation Methodology for the Maritime Sector Emissions over the Mediterranean and Black Sea Regions

The aim of this paper is to apply a new lane separation methodology for the maritime sector emissions attributed to the different vessel types and marine traffic loads in the Mediterranean and the Black Sea defined via the European Marine and Observation Data network (EMODnet), developed in 2016. This methodology is implemented for the first time on the Copernicus Atmospheric Monitoring Service Global Shipping (CAMS-GLOB-SHIP v2.1) nitrogen oxides (NOX) emissions inventory, on the Sentinel-5 Precursor Tropospheric Monitoring Instrument (TROPOMI) nitrogen dioxide (NO2) tropospheric vertical column densities, and on the LOTOS-EUROS (Long Term Ozone Simulation—European Operational Smog) CTM (chemical transport model) simulations. By applying this new EMODnet-based lane separation method to the CAMS-GLOB-SHIP v2.1 emission inventory, we find that cargo and tanker vessels account for approximately 80% of the total emissions in the Mediterranean, followed by fishing, passenger, and other vessel emissions with contributions of 8%, 7%, and 5%, respectively. Tropospheric NO2 vertical column densities sensed by TROPOMI for 2019 and simulated by the LOTOS-EUROS CTM have been successfully attributed to the major vessel activities in the Mediterranean; the mean annual NO2 load of the observations and the simulations reported for the entire maritime EMODnet-reported fleet of the Mediterranean is in satisfactory agreement, 1.26 ± 0.56 × 1015 molecules cm−2 and 0.98 ± 0.41 × 1015 molecules cm−2, respectively. The spatial correlation of the annual maritime NO2 loads of all vessel types between observation and simulation ranges between 0.93 and 0.98. On a seasonal basis, both observations and simulations show a common variability. The wintertime comparisons are in excellent agreement for the highest emitting sector, cargo vessels, with the observations reporting a mean load of 0.98 ± 0.54 and the simulations of 0.81 ± 0.45 × 1015 molecules cm−2 and correlation of 0.88. Similarly, the passenger sector reports 0.45 ± 0.49 and 0.39 ± 0.45 × 1015 molecules cm−2 respectively, with correlation of 0.95. In summertime, the simulations report a higher decrease in modelled tropospheric columns than the observations, however, still resulting in a high correlation between 0.85 and 0.94 for all sectors. These encouraging findings will permit us to proceed with creating a top-down inventory for NOx shipping emissions using S5P/TROPOMI satellite observations and a data assimilation technique based on the LOTOS-EUROS chemical transport model.

Lockdowns Save People from Air Pollution: Evidence from Daily Global Tropospheric NO2 Satellite Data

Motivated by the global fear of the Coronavirus-19 (COVID-19) pandemic, we investigated whether lockdowns save people from air pollution, notably from Nitrogen Dioxide (NO2). Using daily satellite data from the National Aeronautics and Space Administration (NASA), we first found that the global NO2 tropospheric vertical column density (TVCD) decreased by 16.5% after the Coronavirus-19 (COVID-19) outbreak. Then, we calculated the global health benefits, as the monetized value of life, using the value of a statistical life (VSL). The total global health benefits were approximately 8.73 trillion USD, accounting for 10% of the global GDP; such benefits would be the largest in China, followed by the United States, Japan and Germany. Our results suggest that lockdowns may bring benefits to countries that policy interventions cannot easily bring, thus highlighting the importance of social distancing.

Improved spatial representation of a highly resolved emission inventory in China: evidence from TROPOMI measurements

Emissions in many sources are estimated in municipal district totals and spatially disaggregated onto grid cells using empirically selected spatial proxies such as population density, which might introduce biases, especially in fine spatial scale. Efforts have been made to improve the spatial representation of emission inventory, by incorporating comprehensive point source database (e.g. power plants, industrial facilities) in emission estimates. Satellite-based observations from the TROPOspheric Monitoring Instrument (TROPOMI) with unprecedented pixel sizes (3.5 × 7 km2) and signal-to-noise ratios offer the opportunity to evaluate the spatial accuracy of such highly resolved emissions from space. Here, we compare the city-level NO x emissions from a proxy-based emission inventory named the Multi-resolution Emission Inventory for China (MEIC) with a highly resolved emission inventory named the Multi-resolution Emission Inventory for China - High Resolution (MEIC-HR) that has nearly 100 000 industrial facilities, and evaluate them through NO x emissions derived from the TROPOMI NO2 tropospheric vertical column densities (TVCDs). We find that the discrepancies in city-level NO x emissions between MEIC and MEIC-HR are influenced by the proportions of emissions from point sources and NO x emissions per industrial gross domestic product (IGDP). The use of IGDP as a spatial proxy to disaggregate industrial emissions tends to overestimate NO x emissions in cities with lower industrial emission intensities or less industrial facilities in the MEIC. The NO x emissions of 70 cities are derived from one year TROPOMI NO2 TVCDs using the exponentially modified Gaussian function. Compared to the satellite-derived emissions, the cities with higher industrial point source emission proportions in MEIC-HR agree better with space-constrained results, indicating that integrating more point sources in the inventory would improve the spatial accuracy of emissions on city scale. In the future, we should devote more efforts to incorporating accurate locations of emitting facilities to reduce uncertainties in fine-scale emission estimates and guide future policies.

Evaluation of the coupled high-resolution atmospheric chemistry model system MECO(n) using in situ and MAX-DOAS NO<sub>2</sub> measurements

Abstract. We present high spatial resolution (up to 2.2×2.2 km2) simulations focussed over south-west Germany using the online coupled regional atmospheric chemistry model system MECO(n) (MESSy-fied ECHAM and COSMO models nested n times). Numerical simulation of nitrogen dioxide (NO2) surface volume mixing ratios (VMRs) are compared to in situ measurements from a network with 193 locations including background, traffic-adjacent and industrial stations to investigate the model's performance in simulating the spatial and temporal variability of short-lived chemical species. We show that the use of a high-resolution and up-to-date emission inventory is crucial for reproducing the spatial variability and resulted in good agreement with the measured VMRs at the background and industrial locations with an overall bias of less than 10 %. We introduce a computationally efficient approach that simulates diurnal and daily variability in monthly-resolved anthropogenic emissions to resolve the temporal variability of NO2. MAX-DOAS (Multiple AXis Differential Optical Absorption Spectroscopy) measurements performed at Mainz (49.99∘ N, 8.23∘ E) were used to evaluate the simulated tropospheric vertical column densities (VCDs) of NO2. We propose a consistent and robust approach to evaluate the vertical distribution of NO2 in the boundary layer by comparing the individual differential slant column densities (dSCDs) at various elevation angles. This approach considers details of the spatial heterogeneity and sensitivity volume of the MAX-DOAS measurements while comparing the measured and simulated dSCDs. The effects of clouds on the agreement between MAX-DOAS measurements and simulations have also been investigated. For low elevation angles (≤8∘), small biases in the range of −14 % to +7 % and Pearson correlation coefficients in the range of 0.5 to 0.8 were achieved for different azimuth directions in the cloud-free cases, indicating good model performance in the layers close to the surface. Accounting for diurnal and daily variability in the monthly-resolved anthropogenic emissions was found to be crucial for the accurate representation of time series of measured NO2 VMR and dSCDs and is particularly critical when vertical mixing is suppressed, and the atmospheric lifetime of NO2 is relatively long.