TROPOspheric Monitoring Instrument NO2 Research Articles

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%.

Airborne observation with a low-cost hyperspectral instrument: retrieval of NO2 vertical column densities (VCDs) and the satellite sub-grid variability over industrial point sources

Abstract. High-spatial-resolution NO2 vertical column densities (VCDs) were retrieved from airborne observations using the low-cost hyperspectral imaging sensor (HIS) at three industrial areas (i.e., Chungnam, Jecheon, and Pohang) in South Korea, where point sources (i.e., power plant, petrochemical complex, steel yard, and cement kiln) with significant NO2 emissions are located. An innovative and versatile approach for NO2 VCD retrieval, hereafter referred to as the modified wavelength pair (MWP) method, was developed to overcome the excessively variable radiometric and spectral characteristics of the HIS attributed to the absence of temperature control during the flight. The newly developed MWP method was designed to be insensitive to broadband spectral features, including the spectral dependency of surface and aerosol reflectivity, and can be applied to observations with relatively low spectral resolutions. Moreover, the MWP method can be implemented without requiring precise radiometric calibration of the instrument (i.e., HIS) by utilizing clean-pixel data for non-uniformity corrections and is also less sensitive to the optical properties of the instrument and offers computational cost competitiveness. In the experimental flights using the HIS, NO2 plumes emitted from steel yards were particularly conspicuous among the various NO2 point sources, with peak NO2 VCDs of 2.0 DU (Dobson unit) at Chungnam and 1.8 DU at Pohang. Typical NO2 VCD uncertainties ranged between 0.025–0.075 DU over the land surface and 0.10–0.15 DU over the ocean surface, and the discrepancy can be attributable to the lower signal-to-noise ratio over the ocean and higher sensitivity of the MWP method to surface reflectance uncertainties under low-albedo conditions. The NO2 VCDs retrieved from the HIS with the MWP method showed a good correlation with the collocated Tropospheric Monitoring Instrument (TROPOMI) data (r=0.73, mean absolute error equals 0.106 DU). However, the temporal disparities between the HIS frames and the TROPOMI overpass, their spatial mismatch, and their different observation geometries could limit the correlation. The comparison of TROPOMI and HIS NO2 VCDs further demonstrated that the satellite sub-grid variability could be intensified near the point sources, with more than a 3-fold increase in HIS NO2 VCD variability (e.g., difference between 25th and 75th quantiles) over the TROPOMI footprints with NO2 VCD values exceeding 0.8 DU compared to footprints with NO2 VCD values below 0.6 DU.

An Observing System Simulation Experiment Analysis of How Well Geostationary Satellite Trace‐Gas Observations Constrain NOx Emissions in the US

AbstractWe investigate the benefit of assimilating high spatial‐temporal resolution nitrogen dioxide (NO2) measurements from a geostationary (GEO) instrument such as Tropospheric Emissions: Monitoring of Pollution (TEMPO) versus a low‐earth orbit (LEO) platform like TROPOspheric Monitoring Instrument (TROPOMI) on the inverse modeling of nitrogen oxides (NOx) emissions. We generated synthetic TEMPO and TROPOMI NO2 measurements based on emissions from the COVID‐19 lockdown period. Starting with emissions levels prior to the lockdown, we use the Weather Research and Forecasting Model coupled with Chemistry/Data Assimilation Research Testbed (WRF‐Chem/DART) to assimilate these pseudo‐observations in Observing System Simulation Experiments to adjust NOx emissions and quantify how well the assimilation of TEMPO versus TROPOMI measurements recovers the lockdown‐induced emissions changes. We find that NOx emission biases can be ameliorated using half as many simulation days when assimilating GEO observations, and the estimated NOx emissions in 23 out of 29 major urban regions in the US are more accurate. The root mean square error and coefficient of determination of posterior NOx emissions are reduced by 12.5%–41.5% and 1.5%–17.1%, respectively, across different regions. We conduct sensitivity experiments that use different data assimilation (DA) configurations to assimilate synthetic GEO observations. Results demonstrate that the temporal width of the DA window introduces −10% to −20% biases in the emissions inversion and constraining both NOx concentrations and emissions simultaneously yields the most accurate NOx emissions estimates. Our work serves as a valuable reference on how to appropriately assimilate GEO observations for constraining NOx emissions in future studies.

Simultaneous decreases in NO2 levels and disparities in California during the COVID-19 pandemic

This study investigated the changes in nitrogen dioxide (NO2) air pollution levels and their disparities in California, U.S. during the pandemic of coronavirus disease 2019 (COVID-19). From pre-COVID (February 11–March 10, 2020) to peri-COVID (March 22–April 21, 2020) periods, ground-level measured NO2 concentrations decreased by 6.9 ppb (54.2%) on average across California. Our novel statistical approach showed that the meteorology-adjusted NO2 concentrations declined to a smaller extent (4.3 ppb, 34.4%), implying that the meteorological parameters helped reduce NO2 concentrations along with lockdown-related NOx emission reductions. In addition, satellite TROPOspheric Monitoring Instrument (TROPOMI) tropospheric NO2 data demonstrated substantial decreases in NO2 levels in urban (49.7% versus 16.5% in rural areas) and high-traffic (50.1%) areas. On average, 32.8%, 62.8%, and 14.9% higher TROPOMI NO2 levels were identified for socially vulnerable populations, as defined by the CalEnviroScreen 3.0, race/ethnicity, and educational attainment, respectively. The NO2 exposure differences generally decreased as average TROPOMI NO2 levels decreased during the pandemic (Pearson correlations = 0.61–0.95). From pre- to peri-COVID periods, the decreasing NO2 disparities were pronounced in relation to race/ethnicity [from 39.0 (78.6%) to 10.4 (36.7%) μmol/m2]. Despite the remaining NO2 disparities during the pandemic, our findings indicated that the mitigation of NO2 disparities (particularly racial inequity) would be achievable by the continued regulatory actions emphasizing the reduction of traffic-related NOx emissions such as electrification of passenger cars and diesel trucks.

TROPOMI NO2 Sentinel-5P data in the Community of Madrid: A detailed consistency analysis with in situ surface observations

Excess reactive nitrogen emissions from anthropogenic activities can negatively impact the natural environment. The sensor TROPOspheric Monitoring Instrument (TROPOMI) onboard the Sentinel-5 Precursor (Sentinel-5P) satellite is capable of providing data on tropospheric NO2 vertical column densities (VCDs). This work investigates NO2 data retrieved from TROPOMI to study the spatial and temporal patterns of NO2 pollution compared with surface-level concentration measurements in the Community of Madrid in 2022. A high linear correlation coefficient (r) was obtained by comparing daily Level-3 tropospheric TROPOMI NO2 data with ground-based data from air quality monitoring stations at satellite overpass time (r = 0.78). Since the overpasses of Sentinel-5P over the region consistently occur between 12:00 and 4:00 p.m. local time, a second correlation analysis was carried out by averaging all available data from both sources within that interval, resulting in an even higher coefficient (r = 0.81). Results showed a lower correlation at rural sites compared to urban and suburban sites. Examining the monthly and weekly variations of NO2 concentration from satellite data and in situ measurements, similar tendencies in NO2 concentration were observed from both sources. In agreement with previous studies, the cold months and weekdays exhibited higher NO2 concentrations. It was concluded that TROPOMI NO2 data and in situ measurements yield a strong correlation for the Community of Madrid target area, and TROPOMI data can be further investigated to propose pollution mitigation policies.

To new heights by flying low: comparison of aircraft vertical NO2 profiles to model simulations and implications for TROPOMI NO2 retrievals

Abstract. The sensitivity of satellites to air pollution close to the sea surface is decreased by the scattering of light in the atmosphere and low sea surface albedo. To reliably retrieve tropospheric nitrogen dioxide (NO2) columns using the TROPOspheric Monitoring Instrument (TROPOMI), it is therefore necessary to have good a priori knowledge of the vertical distribution of NO2. In this study, we use an aircraft of the Royal Belgian Institute of Natural Sciences equipped with a sniffer sensor system to measure NOx (= NO + NO2), CO2 and SO2. This instrumentation enabled us to evaluate vertical profile shapes from several chemical transport models and to validate TROPOMI tropospheric NO2 columns over the polluted North Sea in the summer of 2021. The aircraft sensor observes multiple clear signatures of ship plumes from seconds after emission to multiple kilometers downwind. Besides that, our results show that the chemical transport model Transport Model 5, Massively Parallel version (TM5-MP), which is used in the retrieval of the operational TROPOMI NO2 data, tends to underestimate surface level pollution – especially under conditions without land outflow – while overestimating NO2 at higher levels over the study region. The higher horizontal resolution in the regional CAMS (Copernicus Atmosphere Monitoring Service) ensemble mean and the LOTOS-EUROS (Long Term Ozone Simulation European Operational Smog) model improves the surface level pollution estimates. However, the models still systematically overestimate NO2 levels at higher altitudes, indicating exaggerated vertical mixing and overall too much NO2 in the models over the North Sea. When replacing the TM5 a priori NO2 profiles with the aircraft-measured NO2 profiles in the air mass factor (AMF) calculation, we find smaller recalculated AMFs. Subsequently, the retrieved NO2 columns increase by 20 %, indicating a significant negative bias in the operational TROPOMI NO2 data product (up to v2.3.1) over the North Sea. This negative bias has important implications for estimating emissions over the sea. While TROPOMI NO2 negative biases caused by the TM5 a priori profiles have also been reported over land, the reduced vertical mixing and smaller surface albedo over sea make this issue especially relevant over sea and coastal regions.

S‐5P/TROPOMI‐Derived NOx Emissions From Copper/Cobalt Mining and Other Industrial Activities in the Copperbelt (Democratic Republic of Congo and Zambia)

AbstractWe have analyzed Sentinel‐5 Precursor TROPOspheric Monitoring Instrument (TROPOMI) data over the Copperbelt mining region (Democratic Republic of Congo and Zambia). Despite high background values, annual 2019–2022 means of TROPOMI NO2 (nitrogen dioxide) show local enhancements consistent with six point sources (four copper/cobalt mines, two cities) where high‐emission industrial activities take place. We have quantified annual NOx (nitrogen oxides) emissions from these point sources, identified temporal trends in emissions, and found strong correlations with production data from colocated mines and one oil refinery. The Copernicus Atmosphere Monitoring Service Global Anthropogenic (CAMS‐GLOB‐ANT) version 5 inventory underpredicts TROPOMI‐derived emissions and lacks the temporal trends observed in TROPOMI and mine/refinery production. These results demonstrate the potential for satellite monitoring of mining and other industrial activities, often unreported or underestimated, which impact the air quality of local communities. This is particularly important for Africa, where mining is increasing aggressively.

Remotely sensed and surface measurement- derived mass-conserving inversion of daily NOx emissions and inferred combustion technologies in energy-rich northern China

Abstract. This work presents a new model-free inversion estimation framework (MFIEF) using daily TROPOspheric Monitoring Instrument (TROPOMI) NO2 columns and observed fluxes from the continuous emission monitoring system (CEMS) to quantify 3 years of daily scale emissions of NOx at 0.05∘×0.05∘ over Shanxi Province, a major world-wide energy-producing and energy-consuming region. The NOx emissions, day-to-day variability, and uncertainty on a climatological basis are computed to be 1.86, 1.03, and 1.05 Tg yr−1 respectively. The highest emissions are concentrated in the lower Fen River valley, which accounts for 25 % of the area, 53 % of the NOx emissions, and 72 % of CEMS sources. Two major forcing factors (10th to 90th percentile) are horizontal transport distance per day (63–508 km) and lifetime of NOx (7.1–18.1 h). Both of these values are consistent with NOx emissions to both the surface layer and the free troposphere. The third forcing factor, the ratio of NOx/NO2, on a pixel-to-pixel basis, is demonstrated to correlate with the combustion temperature and energy efficiency of large energy consuming sources. Specifically, thermal power plants, cement, and iron and steel companies have a relatively high NOx/NO2 ratio, while coking, industrial boilers, and aluminum oxide factories show a relatively lower ratio. Variance maximization is applied to daily TROPOMI NO2 columns, which facilitates identification of three orthogonal and statistically significant modes of variability, and successfully attributes them both spatially and temporally to (a) this work's computed emissions, (b) remotely sensed TROPOMI ultraviolet aerosol index (UVAI), and (c) computed transport based on TROPOMI NO2.

NO2 emissions from oil refineries in the Mississippi Delta

Of the >17,943 thousand barrels per calendar day (bbl/d) of oil refining capacity located in the US, the Petroleum Administration for Defense District 3 (PADD-3) region has the largest number of refineries and accounts for >53 % (or 9607 tbbl/d) of all US oil refining capacity. Processing facilities in this area are mainly located on the Gulf of Mexico coast in Texas and Louisiana. This study selected a sub-region for analysis within the Mississippi River delta in the state of Louisiana between the cities of New Orleans and Baton Rouge. This region is characterized by intensive industrial activity connected with oil refining and related activities. The TROPOspheric Monitoring Instrument (TROPOMI) detected highly localized NO2 vertical column densities (VCDs) over the two largest US refineries in Baton Rouge (503,000 bbl/d) and Garyville (578,000 bbl/d). TROPOMI NO2 VCD over these stations were 100 μmol/m2 and 80 μmol/m2, respectively. A high correlation coefficient (r = 0.65, p < 0.05) was also found between TROPOMI NO2 and population density. Data from the National Emissions Inventory (NEI) showed high NOx emissions from refineries and other industries including coal-fired power generation, chemical, and aluminum processing plants. The results of the NO2 analysis are of practical interest for a comparative assessment of air pollution, as well as for the exchange of best practices in the field of low-waste fuel combustion technologies.

Measurement report: MAX-DOAS measurements characterise Central London ozone pollution episodes during 2022 heatwaves

Abstract. Heatwaves are a substantial health threat in the UK, exacerbated by co-occurrence of ozone pollution episodes. Here we report on the first use of retrieved vertical profiles of nitrogen dioxide (NO2) and formaldehyde (HCHO) over Central London from a newly installed multi-axis differential optical absorption spectroscopy (MAX-DOAS) instrument coincident with two of three heatwaves for the hottest summer on record. We evaluate space-based sensor observations routinely used to quantify temporal changes in air pollution and precursor emissions over London. Collocated daily mean tropospheric column densities from the high-spatial-resolution space-based TROPOspheric Monitoring Instrument (TROPOMI) and MAX-DOAS, after accounting for differences in vertical sensitivities, are temporally consistent for NO2 and HCHO (both R = 0.71). TROPOMI NO2 is 27 %–31 % less than MAX-DOAS NO2, as expected from horizontal dilution of NO2 by TROPOMI pixels in polluted cities. TROPOMI HCHO is 20 % more than MAX-DOAS HCHO, greater than differences in past validation studies but within the range of systematic errors in the MAX-DOAS retrieval. The MAX-DOAS near-surface (0–110 m) retrievals have similar day-to-day and hourly variability to the surface sites for comparison of NO2 (R ≥ 0.7) and for MAX-DOAS HCHO versus surface site isoprene (R ≥ 0.7) that oxidises to HCHO in prompt and high yields. Daytime ozone production, diagnosed with MAX-DOAS HCHO-to-NO2 tropospheric vertical column ratios, is mostly limited by availability of volatile organic compounds (VOCs), except on heatwave days. Temperature-dependent biogenic VOC emissions of isoprene increase exponentially, resulting in ozone concentrations that exceed the regulatory standard for ozone and cause non-compliance at urban background sites in Central London. Locations in Central London heavily influenced by traffic remain in compliance, but this is likely to change with stricter controls on vehicle emissions of NOx and higher likelihood of heatwave frequency, severity, and persistence due to anthropogenic climate change.

Potential of TROPOMI for understanding spatio-temporal variations in surface NO2 and their dependencies upon land use over the Iberian Peninsula

Abstract. In orbit since late 2017, the Tropospheric Monitoring Instrument (TROPOMI) is offering new outstanding opportunities for better understanding the emission and fate of nitrogen dioxide (NO2) pollution in the troposphere. In this study, we provide a comprehensive analysis of the spatio-temporal variability of TROPOMI NO2 tropospheric columns (TrC-NO2) over the Iberian Peninsula during 2018–2021, considering the recently developed Product Algorithm Laboratory (PAL) product. We complement our analysis with estimates of NOx anthropogenic and natural soil emissions. Closely related to cloud cover, the data availability of TROPOMI observations ranges from 30 %–45 % during April and November to 70 %–80 % during summertime, with strong variations between northern and southern Spain. Strongest TrC-NO2 hotspots are located over Madrid and Barcelona, while TrC-NO2 enhancements are also observed along international maritime routes close the strait of Gibraltar, and to a lesser extent along specific major highways. TROPOMI TrC-NO2 appear reasonably well correlated with collocated surface NO2 mixing ratios, with correlations around 0.7–0.8 depending on the averaging time. We investigate the changes of weekly and monthly variability of TROPOMI TrC-NO2 depending on the urban cover fraction. Weekly profiles show a reduction of TrC-NO2 during the weekend ranging from −10 % to −40 % from least to most urbanized areas, in reasonable agreement with surface NO2. In the largest agglomerations like Madrid or Barcelona, this weekend effect peaks not in the city center but in specific suburban areas/cities, suggesting a larger relative contribution of commuting to total NOx anthropogenic emissions. The TROPOMI TrC-NO2 monthly variability also strongly varies with the level of urbanization, with monthly differences relative to annual mean ranging from −40 % in summer to +60 % in winter in the most urbanized areas, and from −10 % to +20 % in the least urbanized areas. When focusing on agricultural areas, TROPOMI observations depict an enhancement in June–July that could come from natural soil NO emissions. Some specific analysis of surface NO2 observations in Madrid show that the relatively sharp NO2 minimum used to occur in August (drop of road transport during holidays) has now evolved into a much broader minimum partly de-coupled from the observed local road traffic counting; this change started in 2018, thus before the COVID-19 outbreak. Over 2019–2021, a reasonable consistency of the inter-annual variability of NO2 is also found between both datasets. Our study illustrates the strong potential of TROPOMI TrC-NO2 observations for complementing the existing surface NO2 monitoring stations, especially in the poorly covered rural and maritime areas where NOx can play a key role, notably for the production of tropospheric O3.

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.

Spaceborne Observations of Lightning NO2 in the Arctic.

The Arctic region is experiencing notable warming as well as more lightning. Lightning is the dominant source of upper tropospheric nitrogen oxides (NOx), which are precursors for ozone and hydroxyl radicals. In this study, we combine the nitrogen dioxide (NO2) observations from the TROPOspheric Monitoring Instrument (TROPOMI) with Vaisala Global Lightning Dataset 360 to evaluate lightning NO2 (LNO2) production in the Arctic. By analyzing consecutive TROPOMI NO2 observations, we determine the lifetime and production efficiency of LNO2 during the summers of 2019-2021. Our results show that the LNO2 production efficiency over the ocean is ∼6 times higher than over continental regions. Additionally, we find that a higher LNO2 production efficiency is often correlated with lower lightning rates. The summertime lightning NOx emission in the Arctic (north of 70° N) is estimated to be 219 ± 116 Mg of N, which is equal to 5% of anthropogenic NOx emissions. However, for the span of a few hours, the Arctic LNO2 density can even be comparable to anthropogenic NO2 emissions in the region. These new findings suggest that LNO2 can play an important role in the upper-troposphere/lower-stratosphere atmospheric chemical processes in the Arctic, particularly during the summer.

Comparing Sentinel-5P TROPOMI NO2 column observations with the CAMS regional air quality ensemble

Abstract. The Sentinel-5P TROPOspheric Monitoring Instrument (TROPOMI) instrument, launched in October 2017, provides unique observations of atmospheric trace gases at a high resolution of about 5 km, with near-daily global coverage, resolving individual sources like thermal powerplants, industrial complexes, fires, medium-scale towns, roads, and shipping routes. Even though Sentinel-5P (S5P) is a global mission, these datasets are especially well suited to test high-resolution regional-scale air quality (AQ) models and provide valuable input for emission inversion systems. In Europe, the Copernicus Atmosphere Monitoring Service (CAMS) has implemented an operational regional AQ forecasting capability based on an ensemble of several European models, available at a resolution of 0.1∘ × 0.1∘. In this paper, we present comparisons between TROPOMI observations of nitrogen dioxide (NO2) and the CAMS AQ forecasts and analyses of NO2. We discuss the different ways of making these comparisons and present quantitative results in the form of maps for individual days, summer and winter months, and a time series for European subregions and cities between May 2018 and March 2021. The CAMS regional products generally capture the fine-scale daily and averaged features observed by TROPOMI in much detail. In summer, the comparison shows a close agreement between TROPOMI and the CAMS ensemble NO2 tropospheric columns with a relative difference of up to 15 % for most European cities. In winter, however, we find a significant discrepancy in the column amounts over much of Europe, with relative differences up to 50 %. The possible causes for these differences are discussed, focusing on the possible impact of retrieval and modeling errors. Apart from comparisons with the CAMS ensemble, we also present results for comparisons with the individual CAMS models for selected months. Furthermore, we demonstrate the importance of the free tropospheric contribution to the estimation of the tropospheric column and thus include profile information from the CAMS configuration of the ECMWF's (European Centre for Medium-Range Weather Forecasts) global integrated model above 3 km altitude in the comparisons. We also show that replacing the global 1∘ × 1∘ a priori information in the retrieval by the regional 0.1∘ × 0.1∘ resolution profiles of CAMS leads to significant changes in the TROPOMI-retrieved tropospheric column, with typical increases at the emission hotspots up to 30 % and smaller increases or decreases elsewhere. As a spinoff, we present a new TROPOMI NO2 level 2 (L2) data product for Europe, based on the replacement of the original TM5-MP generated global a priori profile by the regional CAMS ensemble profile. This European NO2 product is compared with ground-based remote sensing measurements of six Pandora instruments of the Pandonia Global Network and nine Multi-AXis Differential Optical Absorption Spectroscopy (MAX-DOAS) instruments. As compared to the standard S5P tropospheric NO2 column data, the overall bias of the new product for all except two stations is 5 % to 12 % smaller, owing to a reduction in the multiplicative bias. Compared to the CAMS tropospheric NO2 columns, dispersion and correlation parameters with respect to the standard data are, however, superior.

Quantifying daily NOx and CO2 emissions from Wuhan using satellite observations from TROPOMI and OCO-2

Abstract. Quantification and control of NOx and CO2 emissions are essential across the world to limit adverse climate change and improve air quality. We present a new top-down method, an improved superposition column model to estimate day-to-day NOx and CO2 emissions from the large city of Wuhan, China, located in a polluted background. The latest released version 2.3.1 TROPOMI (TROPOspheric Monitoring Instrument) NO2 columns and version 10r of the Orbiting Carbon Observatory-2 (OCO-2)-observed CO2 mixing ratio are employed. We quantified daily NOx and CO2 emissions from Wuhan between September 2019 and October 2020 with an uncertainty of 31 % and 43 %, compared to 39 % and 49 % with the earlier v1.3 TROPOMI data, respectively. Our estimated NOx and CO2 emissions are verified against bottom-up inventories with minor deviations (&lt;3 % for the 2019 mean, ranging from −20 % to 48 % on a daily basis). Based on the estimated CO2 emissions, we also predicted daily CO2 column mixing ratio enhancements, which match well with OCO-2 observations (&lt;5 % bias, within ±0.3 ppm). We capture the day-to-day variation of NOx and CO2 emissions from Wuhan in 2019–2020, which does not reveal a substantial “weekend reduction” but does show a clear “holiday reduction” in the NOx and CO2 emissions. Our method also quantifies the abrupt decrease and slow NOx and CO2 emissions rebound due to the Wuhan lockdown in early 2020. This work demonstrates the improved superposition model to be a promising new tool for the quantification of city NOx and CO2 emissions, allowing policymakers to gain real-time information on spatial–temporal emission patterns and the effectiveness of carbon and nitrogen regulation in urban environments.

Inferring and evaluating satellite-based constraints on NOx emissions estimates in air quality simulations

Abstract. Satellite observations of tropospheric NO2 columns can provide top-down observational constraints on emissions estimates of nitrogen oxides (NOx). Mass-balance-based methods are often applied for this purpose but do not isolate near-surface emissions from those aloft, such as lightning emissions. Here, we introduce an inverse modeling framework that couples satellite chemical data assimilation to a chemical transport model. In the framework, satellite-constrained emissions totals are inferred using model simulations with and without data assimilation in the iterative finite-difference mass-balance method. The approach improves the finite-difference mass-balance inversion by isolating the near-surface emissions increment. We apply the framework to separately estimate lightning and anthropogenic NOx emissions over the Northern Hemisphere for 2019. Using overlapping observations from the Ozone Monitoring Instrument (OMI) and the Tropospheric Monitoring Instrument (TROPOMI), we compare separate NOx emissions inferences from these satellite instruments, as well as the impacts of emissions changes on modeled NO2 and O3. OMI inferences of anthropogenic emissions consistently lead to larger emissions than TROPOMI inferences, attributed to a low bias in TROPOMI NO2 retrievals. Updated lightning NOx emissions from either satellite improve the chemical transport model's low tropospheric O3 bias. The combined lighting and anthropogenic emissions updates improve the model's ability to reproduce measured ozone by adjusting natural, long-range, and local pollution contributions. Thus, the framework informs and supports the design of domestic and international control strategies.

Derivation of Emissions From Satellite‐Observed Column Amounts and Its Application to TROPOMI NO2 and CO Observations

AbstractA unified framework that connects emissions with satellite‐observed column amounts is derived from first principles. The emission information originates from the inner product of the horizontal wind and the gradient of column amount, which is more accurate than the horizontal flux divergence as used in previous studies. Additionally, the topographical and chemical effects are accounted for through fitted scale height and chemical lifetime. This framework is applied to derive NOx and CO emissions over the CONUS from TROPOspheric Monitoring Instrument NO2 and CO observations. High‐resolution (0.04°) emission mapping over the CONUS reveals unprecedented details, including CO emissions in major cities and NOx emissions from large cities, power plants, and major roadways. Monthly resolved NOx emissions show decrease and rebound after the COVID‐19 pandemic. This framework is integrated with the physical oversampling algorithm and can be readily applied to other products from the new‐generation satellite instruments.

Intercomparison of Sentinel-5P TROPOMI cloud products for tropospheric trace gas retrievals

Abstract. Clouds have a strong impact on satellite measurements of tropospheric trace gases in the ultraviolet, visible, and near-infrared spectral ranges from space. Therefore, trace gas retrievals rely on information on cloud fraction, cloud albedo, and cloud height from cloud products. In this study, the cloud parameters from different cloud retrieval algorithms for the Sentinel-5 Precursor (S5P) TROPOspheric Monitoring Instrument (TROPOMI) are compared: the Optical Cloud Recognition Algorithm (OCRA) a priori cloud fraction, the Retrieval Of Cloud Information using Neural Networks (ROCINN) CAL (Clouds-As-Layers) cloud fraction and cloud top and base height, the ROCINN CRB (Clouds-as-Reflecting-Boundaries) cloud fraction and cloud height, the Fast Retrieval Scheme for Clouds from the Oxygen A-band (FRESCO) cloud fraction, the interpolated FRESCO cloud height from the TROPOMI NO2 product, the cloud fraction from the NO2 fitting window, the O2–O2 cloud fraction and cloud height, the Mainz Iterative Cloud Retrieval Utilities (MICRU) cloud fraction, and the Visible Infrared Imaging Radiometer Suite (VIIRS) cloud fraction. Two different versions of the TROPOMI cloud products OCRA/ROCINN, FRESCO, and the TROPOMI NO2 product are included in the comparisons (processor version 1.x and 2.x). Overall, the cloud parameters retrieved by the different algorithms show qualitative consistency in version 1.x and good agreement in version 2.x with the exception of the VIIRS cloud fraction, which cannot be directly compared to the other data. Differences between the cloud retrievals are found especially for small cloud heights with a cloud fraction threshold of 0.2, i.e. clouds that are particularly relevant for tropospheric trace gas retrievals. The cloud fractions of the different version 2 cloud products primarily differ over snow- and ice-covered pixels and scenes with sun glint, for which only MICRU includes an explicit treatment. All cloud parameters show some systematic problems related to the across-track dependence, where larger values are found at the edges of the satellite view. The consistency between the cloud parameters from different algorithms depends strongly on how the data are filtered for the comparison, for example, what quality value is used or whether snow- and ice-covered pixels are excluded from the analysis. In summary, clear differences were found between the results of various algorithms, but these differences are reduced in the most recent versions of the cloud data.

Comparison of TROPOMI NO2, CO, HCHO, and SO2 data against ground‐level measurements in close proximity to large anthropogenic emission sources in the example of Ukraine

AbstractThe TROPOspheric Monitoring Instrument (TROPOMI) significantly improved the quality of air pollution monitoring. The comparison against other data sources showed acceptable results and good correlation. However, highly polluted areas remain the reason for large uncertainties. In our study, we compared TROPOMI NO2, CO, HCHO, and SO2 data against ground‐level measurements from Ukrainian monitoring sites, which could be considered rather unusual due to their close location to large anthropogenic emission sources. These sites were established in the former USSR to reflect the maximal air pollution levels. TROPOMI detected all cities with huge anthropogenic emissions in 2019–2020 and qualitatively reflected air pollution in Ukraine. However, direct comparison against individual monitoring sites showed mainly insignificant correlation, which was not much improved with cloudiness filtering, spatial averaging, and considering boundary layer height. We show that on an hour‐to‐daily scale, differences appear when remote sensing at a particular time cannot catch the elevated pollution levels in the boundary layer after air mass transportation. On a seasonal scale, the correlation decreases because of the differences in seasonality between near‐surface and column pollutants' content. We discuss that the relationship between TROPOMI and ground‐level measurements depends on the season, the continuance of industrial emissions, and the features of individual emission sources.

Daily Satellite Observations of Nitrogen Dioxide Air Pollution Inequality in New York City, New York and Newark, New Jersey: Evaluation and Application.

Urban air pollution disproportionately harms communities of color and low-income communities in the U.S. Intraurban nitrogen dioxide (NO2) inequalities can be observed from space using the TROPOspheric Monitoring Instrument (TROPOMI). Past research has relied on time-averaged measurements, limiting our understanding of how neighborhood-level NO2 inequalities co-vary with urban air quality and climate. Here, we use fine-scale (250 m × 250 m) airborne NO2 remote sensing to demonstrate that daily TROPOMI observations resolve a major portion of census tract-scale NO2 inequalities in the New York City-Newark urbanized area. Spatiotemporally coincident TROPOMI and airborne inequalities are well correlated (r = 0.82-0.97), with slopes of 0.82-1.05 for relative and 0.76-0.96 for absolute inequalities for different groups. We calculate daily TROPOMI NO2 inequalities over May 2018-September 2021, reporting disparities of 25-38% with race, ethnicity, and/or household income. Mean daily inequalities agree with results based on TROPOMI measurements oversampled to 0.01° × 0.01° to within associated uncertainties. Individual and mean daily TROPOMI NO2 inequalities are largely insensitive to pixel size, at least when pixels are smaller than ∼60 km2, but are sensitive to low observational coverage. We statistically analyze daily NO2 inequalities, presenting empirical evidence of the systematic overburdening of communities of color and low-income neighborhoods with polluting sources, regulatory ozone co-benefits, and worsened NO2 inequalities and cumulative NO2 and urban heat burdens with climate change.