Air Mass Factor Research Articles

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.

Improved retrieval of SO2 plume height from TROPOMI using an iterative Covariance-Based Retrieval Algorithm

Abstract. Knowledge of sulfur dioxide layer height (SO2 LH) is important to understand volcanic eruption processes, the climate impact of SO2 emissions and to mitigate volcanic risk for civil aviation. However, the estimation of SO2 LH from ground-based instruments is challenging in particular for rapidly evolving and sustained eruptions. Satellite wide-swath nadir observations have the advantage to cover large-scale plumes and the potential to provide key information on SO2 LH. In the ultraviolet, SO2 LH retrievals leverage the fact that, for large SO2 columns, the light path and its associated air mass factor (AMF) depends on the SO2 absorption (and therefore on the vertical distribution of SO2), and SO2 LH information can be obtained from the analysis of measured back-scattered radiances coupled with radiative transfer simulations. However, existing algorithms are mainly sensitive to SO2 LH for SO2 vertical columns of at least 20 DU. Here we develop a new SO2 LH algorithm and apply it to observations from the high-spatial-resolution TROPOspheric Monitoring Instrument (TROPOMI). It is based on an SO2 optical depth look-up table and an iterative approach. The strength of this scheme lies in the fact that it is a Covariance-Based Retrieval Algorithm (COBRA; Theys et al., 2021). This means that the SO2-free contribution of the measured optical depth is treated in an optimal way, resulting in an improvement of the SO2 LH sensitivity to SO2 columns as low as 5 DU, with a precision better than 2 km. We demonstrate the value of this new data through a number of examples and comparison with satellite plume height estimates (from IASI and CALIOP), and back-trajectory analyses. The comparisons indicate an SO2 LH accuracy of 1–2 km, except for some difficult observation conditions, in particular for optically thick ash plumes or partially SO2-filled scenes.

Polarization performance simulation for the GeoXO atmospheric composition instrument: NO2 retrieval impacts

Abstract. NOAA's Geostationary Extended Observations (GeoXO) constellation will continue and expand on the capabilities of the current generation of geostationary satellite systems to support US weather, ocean, atmosphere, and climate operations. It is planned to consist of a dedicated atmospheric composition instrument (ACX) to support air quality forecasting and monitoring by providing capabilities similar to missions such as TEMPO (Tropospheric Emission: Monitoring Pollution), currently planned to launch in 2023, as well as OMI (Ozone Monitoring Instrument), TROPOMI (TROPOspheric Monitoring Instrument), and GEMS (Geostationary Environment Monitoring Spectrometer) currently in operation. As the early phases of ACX development are progressing, design trade-offs are being considered to understand the relationship between instrument design choices and trace gas retrieval impacts. Some of these choices will affect the instrument polarization sensitivity (PS), which can have radiometric impacts on environmental satellite observations. We conducted a study to investigate how such radiometric impacts can affect NO2 retrievals by exploring their sensitivities to time of day, location, and scene type with an ACX instrument model that incorporates PS. The study addresses the basic steps of operational NO2 retrievals: the spectral fitting step and the conversion of slant column to vertical column via the air mass factor (AMF). The spectral fitting step was performed by generating at-sensor radiance from a clear-sky scene with a known NO2 amount, the application of an instrument model including both instrument PS and noise, and a physical retrieval. The spectral fitting step was found to mitigate the impacts of instrument PS. The AMF-related step was considered for clear-sky and partially cloudy scenes, for which instrument PS can lead to errors in interpreting the cloud content, propagating to AMF errors and finally to NO2 retrieval errors. For this step, the NO2 retrieval impacts were small but non-negligible for high NO2 amounts; we estimated that a typical high NO2 amount can cause a maximum retrieval error of 0.25×1015 molec. cm−2 for a PS of 5 %. These simulation capabilities were designed to aid in the development of a GeoXO atmospheric composition instrument that will improve our ability to monitor and understand the Earth's atmosphere.

The influence of snow cover on Ozone Monitor Instrument formaldehyde observations

Formaldehyde (HCHO) is measured from space using backscattered ultraviolet sun-light. Because of HCHO’s short lifetime, space-based observations of HCHO can serve as a proxy for volatile organic compounds, helping to characterize their global emissions and distributions. HCHO satellite observations rely on Air Mass Factor (AMF) calculations to transform fitted slant columns into vertical column densities. Most HCHO satellite products do not explicitly consider the presence of snow on the ground during the calculation of AMFs. In this study, we leverage information from the MODIS bidirectional reflectance distribution function (BRDF), MODIS snow cover information, and the Interactive Multisensor Snow and Ice Mapping System to evaluate the impact of ground snow on Ozone Monitoring Instrument (OMI) HCHO retrievals. We focus our analysis on the year 2005. We compare AMFs computed using daily MODIS BRDF to AMFs computed using OMI’s surface reflectance climatology, the baseline for NASA’s OMHCHO product. Over snow-covered regions, both sets of AMFs show significant differences. We observe two different behaviors. Regions with permanent snow cover (Greenland and Antarctica) show smaller AMFs calculated with MODIS BRDF than with the OMI climatology resulting in a 6% median annual increase of HCHO VCDs. Over regions with seasonal snow cover, the situation is more complex with more variability in the differences during the year. For example, a February 2005 case study over Europe shows that the NASA OMHCHO VCDs (calculated using the OMI Lambertian climatology) are on average 16% larger than HCHO columns retrieved using daily MODIS BRDF information.

Influence of convection on the upper-tropospheric O<sub>3</sub> and NO<sub><i>x</i></sub> budget in southeastern China

Abstract. Thunderstorms can significantly influence the air composition via strong updraft and lightning nitrogen oxides (LNOx). In this study, the ozonesondes and TROPOMI (TROPOspheric Monitoring Instrument) nitrogen dioxide (NO2) observations for two cases are combined with a model to investigate the effects of typical strong convection on vertical redistribution of air pollutants in Nanjing, southeastern China. The ozonesonde observations show higher O3 and water vapor mixing ratios in the upper troposphere (UT) after convection, indicating the strong updraft transporting lower-level air masses into the UT and the possible downward O3-rich air near the top of UT over the convective period. During the whole convection life cycle, the UT O3 production is driven by the chemistry (5–10 times the magnitude of dynamic contribution) and reduced by the LNOx (−40 %). Sensitivity tests demonstrate that neglecting LNOx in standard TROPOMI NO2 products causes overestimated air mass factors over fresh lightning regions and the opposite for outflow and aged lightning areas. Therefore, a new high-resolution retrieval algorithm is applied to estimate the LNOx production efficiency. Our work shows the demand for high-resolution modeling and satellite observations on LNOx emissions of both active and dissipated convection, especially small-scale storms.

Ground-Based MAX-DOAS Measurements of Tropospheric Aerosols, NO2, and HCHO Distributions in the Urban Environment of Shanghai, China

Aerosol extinction profiles at 550 nm were retrieved by applying multi-axis differential optical absorption spectroscopy (MAX-DOAS) and lookup table. Then the tropospheric NO2 and HCHO vertical column densities were retrieved using a two-step method from 28 July to 5 August of 2015 in Shanghai. The retrieved results were compared with the satellite products, and then their diurnal variation was observed. A consistency check was performed before the inversion to obtain a correction factor. Based on the sensitivity of geometric angles to oxygen dimer air mass factor (O4 AMF, AMF is the ratio of the slanted column density to the vertical column density), the parameterization scheme of geometric angles in the lookup table is optimized. The results show that the aerosol increased significantly in the afternoon. The diurnal variation of tropospheric NO2 and HCHO vertical column densities (VCDs) are bimodal and unimodal patterns respectively, and their values are higher than those of GOME-2 and OMI satellite products. A process of aerosol reduction and recovery are related to ground particulates and meteorological elements. The chemical sensitivity of local ozone production also has a clear diurnal variation.

Impact of 3D cloud structures on the atmospheric trace gas products from UV–Vis sounders – Part 1: Synthetic dataset for validation of trace gas retrieval algorithms

Abstract. Retrievals of trace gas concentrations from satellite observations are mostly performed for clear regions or regions with low cloud coverage. However, even fully clear pixels can be affected by clouds in the vicinity, either by shadowing or by scattering of radiation from clouds in the clear region. Quantifying the error of retrieved trace gas concentrations due to cloud scattering is a difficult task. One possibility is to generate synthetic data by three-dimensional (3D) radiative transfer simulations using realistic 3D atmospheric input data, including 3D cloud structures. Retrieval algorithms may be applied on the synthetic data, and comparison to the known input trace gas concentrations yields the retrieval error due to cloud scattering. In this paper we present a comprehensive synthetic dataset which has been generated using the Monte Carlo radiative transfer model MYSTIC (Monte Carlo code for the phYSically correct Tracing of photons In Cloudy atmospheres). The dataset includes simulated spectra in two spectral ranges (400–500 nm and the O2A-band from 755–775 nm). Moreover it includes layer air mass factors (layer-AMFs) calculated at 460 nm. All simulations are performed for a fixed background atmosphere for various sun positions, viewing directions and surface albedos. Two cloud setups are considered: the first includes simple box clouds with various geometrical and optical thicknesses. This can be used to systematically investigate the sensitivity of the retrieval error on solar zenith angle, surface albedo and cloud parameters. Corresponding 1D simulations are also provided. The second includes realistic three-dimensional clouds from an ICON large eddy simulation (LES) for a region covering Germany and parts of surrounding countries. The scene includes cloud types typical of central Europe such as shallow cumulus, convective cloud cells, cirrus and stratocumulus. This large dataset can be used to quantify the trace gas concentration retrieval error statistically. Along with the dataset, the impact of horizontal photon transport on reflectance spectra and layer-AMFs is analysed for the box-cloud scenarios. Moreover, the impact of 3D cloud scattering on the NO2 vertical column density (VCD) retrieval is presented for a specific LES case. We find that the retrieval error is largest in cloud shadow regions, where the NO2 VCD is underestimated by more than 20 %. The dataset is available for the scientific community to assess the behaviour of trace gas retrieval algorithms and cloud correction schemes in cloud conditions with 3D structure.

TROPOspheric Monitoring Instrument observations of total column water vapour: Algorithm and validation

In this paper, we present the total column water vapour (TCWV) retrieval for the TROPOspheric Monitoring Instrument (TROPOMI) observations in the visible blue spectral band. The TROPOMI TCWV algorithm is being optimized and validated in the framework of the Sentinel 5 Precursor Product Algorithm Laboratory (S5P-PAL) project from the European Space Agency (ESA). The retrieval was first developed to retrieve TCWV from the Global Ozone Monitoring Experiment 2 (GOME-2). We have optimized the settings of the retrieval to adapt it for TROPOMI observations. The TROPOMI TCWV algorithm follows the typical two step approach, using spectral fit retrieval of slant columns, and conversion of the slant columns to vertical columns using air mass factors (AMFs). An iterative optimization algorithm is developed to dynamically find the optimal a priori water vapour profile for the AMF calculation. Further optimizations on the spectral retrieval, air mass factor calculations as well as a new surface albedo retrieval approach are implemented.The TCWV retrieval algorithm is applied to TROPOMI observations from May 2018 to May 2021. The results are validated by comparing them to ERA5 reanalysis data, GOME-2, MODerate resolution Imaging Spectroradiometer (MODIS) and Special Sensor Microwave Imager Sounder (SSMIS) satellite observations. TCWV derived from TROPOMI observations agree well with the other data sets with Pearson correlation coefficient (R) ranging from 0.96 to 0.99. The mean bias between TROPOMI and ERA5 data is −1.24 kg m−2 for measurements over land and 0.73 kg m−2 for measurements over water. The comparison to MODIS observations show similar results with small dry bias of 1.51,kg m−2 for measurements over land and a small wet bias of 1.25 kg m−2 for measurements over water. Slightly larger dry bias of 1.98 kg m−2 for measurements over land and 1.74 kg m−2 for measurements over water are found when compared to GOME-2 obserations. Compared to SSMIS data over water, TROPOMI observations are bias low by 3.25 kg m−2. The small discrepancies found between TROPOMI and reference data sets are related to the differences in measurement technique, measurement time, surface albedo issue, as well as cloud and aerosol contamination. This study demonstrates that the algorithm can provide stable and consistent results on a global scale and can be applied to generate operational TCWV products from TROPOMI and the forthcoming Copernicus missions Sentinel-4 and Sentinel-5. We have also demonstrated the capability of retrieving fine scale water vapour structures in a case study over the Amazon. This indicates that the TROPOMI data set is also useful for local and regional climate studies.

Biomass burning nitrogen dioxide emissions derived from space with TROPOMI: methodology and validation

Abstract. Smoke from wildfires is a significant source of air pollution, which can adversely impact air quality and ecosystems downwind. With the recently increasing intensity and severity of wildfires, the threat to air quality is expected to increase. Satellite-derived biomass burning emissions can fill in gaps in the absence of aircraft or ground-based measurement campaigns and can help improve the online calculation of biomass burning emissions as well as the biomass burning emissions inventories that feed air quality models. This study focuses on satellite-derived NOx emissions using the high-spatial-resolution TROPOspheric Monitoring Instrument (TROPOMI) NO2 dataset. Advancements and improvements to the satellite-based determination of forest fire NOx emissions are discussed, including information on plume height and effects of aerosol scattering and absorption on the satellite-retrieved vertical column densities. Two common top-down emission estimation methods, (1) an exponentially modified Gaussian (EMG) and (2) a flux method, are applied to synthetic data to determine the accuracy and the sensitivity to different parameters, including wind fields, satellite sampling, noise, lifetime, and plume spread. These tests show that emissions can be accurately estimated from single TROPOMI overpasses. The effect of smoke aerosols on TROPOMI NO2 columns (via air mass factors, AMFs) is estimated, and these satellite columns and emission estimates are compared to aircraft observations from four different aircraft campaigns measuring biomass burning plumes in 2018 and 2019 in North America. Our results indicate that applying an explicit aerosol correction to the TROPOMI NO2 columns improves the agreement with the aircraft observations (by about 10 %–25 %). The aircraft- and satellite-derived emissions are in good agreement within the uncertainties. Both top-down emissions methods work well; however, the EMG method seems to output more consistent results and has better agreement with the aircraft-derived emissions. Assuming a Gaussian plume shape for various biomass burning plumes, we estimate an average NOx e-folding time of 2 ±1 h from TROPOMI observations. Based on chemistry transport model simulations and aircraft observations, the net emissions of NOx are 1.3 to 1.5 times greater than the satellite-derived NO2 emissions. A correction factor of 1.3 to 1.5 should thus be used to infer net NOx emissions from the satellite retrievals of NO2.

An improved TROPOMI tropospheric NO<sub>2</sub> research product over Europe

Abstract. Launched in October 2017, the TROPOspheric Monitoring Instrument (TROPOMI) aboard Sentinel-5 Precursor provides the potential to monitor air quality over point sources across the globe with a spatial resolution as high as 5.5 km × 3.5 km (7 km × 3.5 km before 6 August 2019). The DLR nitrogen dioxide (NO2) retrieval algorithm for the TROPOMI instrument consists of three steps: the spectral fitting of the slant column, the separation of stratospheric and tropospheric contributions, and the conversion of the slant column to a vertical column using an air mass factor (AMF) calculation. In this work, an improved DLR tropospheric NO2 retrieval algorithm from TROPOMI measurements over Europe is presented. The stratospheric estimation is implemented using the STRatospheric Estimation Algorithm from Mainz (STREAM), which was developed as a verification algorithm for TROPOMI and does not require chemistry transport model data as input. A directionally dependent STREAM (DSTREAM) is developed to correct for the dependency of the stratospheric NO2 on the viewing geometry by up to 2×1014 molec./cm2. Applied to synthetic TROPOMI data, the uncertainty in the stratospheric column is 3.5×1014 molec./cm2 in the case of significant tropospheric sources. Applied to actual measurements, the smooth variation of stratospheric NO2 at low latitudes is conserved, and stronger stratospheric variation at higher latitudes is captured. For AMF calculation, the climatological surface albedo data are replaced by geometry-dependent effective Lambertian equivalent reflectivity (GE_LER) obtained directly from TROPOMI measurements with a high spatial resolution. Mesoscale-resolution a priori NO2 profiles are obtained from the regional POLYPHEMUS/DLR chemistry transport model with the TNO-MACC emission inventory. Based on the latest TROPOMI operational cloud parameters, a more realistic cloud treatment is provided by a Clouds-As-Layers (CAL) model, which treats the clouds as uniform layers of water droplets, instead of the Clouds-As-Reflecting-Boundaries (CRB) model, in which clouds are simplified as Lambertian reflectors. For the error analysis, the tropospheric AMF uncertainty, which is the largest source of NO2 uncertainty for polluted scenarios, ranges between 20 % and 50 %, leading to a total uncertainty in the tropospheric NO2 column in the 30 %–60 % range. From a validation performed with ground-based multi-axis differential optical absorption spectroscopy (MAX-DOAS) measurements, the new DLR tropospheric NO2 data show good correlations for nine European urban/suburban stations, with an average correlation coefficient of 0.78. The implementation of the algorithm improvements leads to a decrease of the relative difference from −55.3 % to −34.7 % on average in comparison with the DLR reference retrieval. When the satellite averaging kernels are used to remove the contribution of a priori profile shape, the relative difference decreases further to ∼ −20 %.

Retrieval of O3, NO2, BrO and OClO Columns from Ground-Based Zenith Scattered Light DOAS Measurements in Summer and Autumn over the Northern Tibetan Plateau

Ground-based zenith scattered light differential optical absorption spectroscopy (DOAS) measurements were performed in summer and autumn (27 May–30 November) 2020 at Golmud (94°54′ E, 36°25′ N; 2807.6 m altitude) to investigate the abundances and temporal variations of ozone (O3) and its depleting substances over the northern Tibetan Plateau (TP). The differential slant column densities (dSCDs) of O3, nitrogen dioxide (NO2), bromine monoxide (BrO), and chlorine dioxide (OClO) were simultaneously retrieved from scattered solar spectra in the zenith direction during the twilight period. The O3 vertical column densities (VCDs) were derived by applying the Langley plot method, for which we investigated the sensitivities to the chosen wavelength, the a-priori O3 profile and the aerosol extinction profile used in O3 air mass factor (AMF) simulation as well as the selected solar zenith angle (SZA) range. The mean O3 VCDs from June to November 2020 are 7.21 × 1018 molec·cm−2 and 7.18 × 1018 molec·cm−2 at sunrise and sunset, respectively. The derived monthly variations of the O3 VCDs, ranging from a minimum of 6.9 × 1018 molec·cm−2 in October to 7.5 × 1018 molec·cm−2 in November, well matched the OMI satellite product, with a correlation coefficient R = 0.98. The NO2 VCDs at SZA = 90°, calculated by a modified Langley plot method, were systematically larger at sunset than at sunrise as expected with a pm/am ratio of ~1.56. The maximum of the monthly NO2 VCDs, averaged between sunrise and sunset, was 3.40 × 1015 molec·cm−2 in July. The overall trends of the NO2 VCDs were gradually decreasing with the time and similarly observed by the ground-based zenith DOAS and OMI. The average level of the BrO dSCD90°–80° (i.e., dSCD between 90° and 80° SZA) was 2.06 × 1014 molec·cm−2 during the period of June–November 2020. The monthly BrO dSCD90°–80° presented peaks in August and July for sunrise and sunset, respectively, and slowly increased after October. During the whole campaign period, the OClO abundance was lower than the detection limit of the instrument. This was to be expected because during that season the stratospheric temperatures were above the formation temperature of polar stratospheric clouds. Nevertheless, this finding is still of importance, because it indicates that the OClO analysis works well and is ready to be used during periods when enhanced OClO abundances can be expected. As a whole, ground-based zenith DOAS observations can serve as an effective way to measure the columns of O3 and its depleting substances over the TP. The aforementioned results are helpful in investigating stratospheric O3 chemistry over the third pole of the world.

Impact of 3D radiative transfer on airborne NO<sub>2</sub> imaging remote sensing over cities with buildings

Abstract. Airborne imaging remote sensing is increasingly used to map the spatial distribution of nitrogen dioxide (NO2) in cities. Despite the small ground-pixel size of the sensors, the measured NO2 distributions are much smoother than one would expect from high-resolution model simulations of NO2 over cities. This could partly be caused by 3D radiative transfer effects due to observation geometry, adjacency effects and effects of buildings. Here, we present a case study of imaging a synthetic NO2 distribution for a district of Zurich using the 3D MYSTIC (Monte carlo code for the phYSically correct Tracing of photons In Cloudy atmospheres) solver of the libRadtran radiative transfer library. We computed NO2 slant column densities (SCDs) using the recently implemented 3D-box air mass factors (3D-box AMFs) and a new urban canopy module to account for the effects of buildings. We found that for a single ground pixel (50 m × 50 m) more than 50 % of the sensitivity is located outside of the pixel, primarily in the direction of the main optical path between sun, ground pixel, and instrument. Consequently, NO2 SCDs are spatially smoothed, which results in an increase over roads when they are parallel to the optical path and a decrease otherwise. When buildings are included, NO2 SCDs are reduced on average by 5 % due to the reduced sensitivity to NO2 in the shadows of the buildings. The effects of buildings also introduce a complex pattern of variability in SCDs that would show up in airborne observations as an additional noise component (about 12 µmol m−2) similar to the magnitude of typical measurement uncertainties. The smearing of the SCDs cannot be corrected using 1D-layer AMFs that assume horizontal homogeneity and thus remains in the final NO2 map. The 3D radiative transfer effects by including buildings need to be considered to compute more accurate AMFs and to reduce biases in NO2 vertical columns obtained from high-resolution city-scale NO2 remote sensing.

Observations of Lightning NOx Production From Tropospheric Monitoring Instrument Case Studies Over the United States

AbstractNitrogen oxides produced by lightning (LNOx) play an important role in determining mid‐ and upper‐tropospheric concentrations of the hydroxyl radical (OH), methane (CH4), and ozone (O3). The moles of NOx produced per flash was examined using nitrogen dioxide (NO2) columns and cloud properties from the Tropospheric Monitoring Instrument (TROPOMI) and flash counts from the Geostationary Lightning Mapper (GLM) aboard the Geostationary Operational Environmental Satellite‐16 (GOES‐16) and Earth Networks Total Lightning Network (ENTLN) for 29 convective systems over the United States that occurred during 2018 and 2019. For each of the case studies, the LNOx production efficiency (PE) was estimated using TROPOMI pixels over deep convection. First, the NOx columns associated with the TROPOMI NO2 columns were estimated using a specially derived air mass factor (AMF). The tropospheric column due to recent lightning was then determined by subtracting from the median NOx column a background representative of the NOx column due to sources other than recent lightning. Then, the PE was calculated by multiplying the LNOx column by the storm area and dividing by the number of flashes contributing to the column. For a three‐hour chemical lifetime, the mean PE was found to be 175 ± 100 mol per flash for optical flashes from GLM and 120 ± 65 mol per flash for radio‐wave‐detected flashes from ENTLN. The uncertainty associated with these values is mostly due to uncertainties in tropospheric background, AMF, and detection efficiency. GLM PE for individual systems was found to be positively correlated with optical energy.

Advancing Maritime Transparent Cirrus Detection Using the Advanced Baseline Imager “Cirrus” Band

AbstractWe describe a quantitative evaluation of maritime transparent cirrus cloud detection, which is based on Geostationary Operational Environmental Satellite – 16 (GOES-16) and developed with collocated Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) profiling. The detection algorithm is developed using one month of collocated GOES-16 Advanced Baseline Imager (ABI) Channel 4 (1.378 μm) radiance and CALIOP 0.532 μm column-integrated cloud optical depth (COD). First, the relationships between the clear-sky 1.378 μm radiance, viewing/solar geometry, and precipitable water vapor (PWV) are characterized. Using machine learning techniques, it is shown that the total atmospheric pathlength, proxied by airmass factor (AMF), is a suitable replacement for viewing zenith and solar zenith angles alone, and that PWV is not a significant problem over ocean. Detection thresholds are computed using the Ch. 4 radiance as a function of AMF. The algorithm detects nearly 50% of sub-visual cirrus (COD < 0.03), 80% of transparent cirrus (0.03 < COD < 0.3), and 90% of opaque cirrus (COD > 0.3). Using a conservative radiance threshold results in 84% of cloudy pixels being correctly identified and 4% of clear-sky pixels being misidentified as cirrus. A semi-quantitative COD retrieval is developed for GOES ABI based on the observed relationship between CALIOP COD and 1.378 μm radiance. This study lays the groundwork for a more complex, operational GOES transparent cirrus detection algorithm. Future expansion includes an over-land algorithm, a more robust COD retrieval that is suitable for assimilation purposes, and downstream GOES products such as cirrus cloud microphysical property retrieval based on ABI infrared channels.

Ozone Monitoring Instrument (OMI) Aura nitrogen dioxide standard product version 4.0 with improved surface and cloud treatments

Abstract. We present a new and improved version (V4.0) of the NASA standard nitrogen dioxide (NO2) product from the Ozone Monitoring Instrument (OMI) on the Aura satellite. This version incorporates the most salient improvements for OMI NO2 products suggested by expert users and enhances the NO2 data quality in several ways through improvements to the air mass factors (AMFs) used in the retrieval algorithm. The algorithm is based on the geometry-dependent surface Lambertian equivalent reflectivity (GLER) operational product that is available on an OMI pixel basis. GLER is calculated using the vector linearized discrete ordinate radiative transfer (VLIDORT) model, which uses as input high-resolution bidirectional reflectance distribution function (BRDF) information from NASA's Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) instruments over land and the wind-dependent Cox–Munk wave-facet slope distribution over water, the latter with a contribution from the water-leaving radiance. The GLER combined with consistently retrieved oxygen dimer (O2–O2) absorption-based effective cloud fraction (ECF) and optical centroid pressure (OCP) provide improved information to the new NO2 AMF calculations. The new AMFs increase the retrieved tropospheric NO2 by up to 50 % in highly polluted areas; these differences arise from both cloud and surface BRDF effects as well as biases between the new MODIS-based and previously used OMI-based climatological surface reflectance data sets. We quantitatively evaluate the new NO2 product using independent observations from ground-based and airborne instruments. The new V4.0 data and relevant explanatory documentation are publicly available from the NASA Goddard Earth Sciences Data and Information Services Center (https://disc.gsfc.nasa.gov/datasets/OMNO2_V003/summary/, last access: 8 November 2020), and we encourage their use over previous versions of OMI NO2 products.

Unexpected Impact of COVID-19 Lockdown on the Air Quality in the Metro Atlanta, USA Using Ground-based and Satellite Observations

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

An improved TROPOMI tropospheric HCHO retrieval over China

Abstract. We present an improved TROPOspheric Monitoring Instrument (TROPOMI) retrieval of formaldehyde (HCHO) over China. The new retrieval optimizes the slant column density (SCD) retrieval and air mass factor (AMF) calculation for TROPOMI observations of HCHO over China. Retrieval of HCHO differential SCDs (DSCDs) is improved using the basic optical differential spectroscopy (BOAS) technique resulting in lower noise and smaller random error, while AMFs are improved with a priori HCHO profiles from a higher resolution regional chemistry transport model. Compared to the operational product, the new TROPOMI HCHO retrieval shows better agreement with ground-based Multi-AXis Differential Optical Absorption Spectroscopy (MAX-DOAS) measurements in Beijing. The improvements are mainly related to the AMF calculation with more precise a priori profiles in winter. Using more precise a priori profiles in general reduces HCHO vertical column densities (VCDs) by 52.37 % (± 27.09 %) in winter. Considering the aerosol effect in AMF calculation reduces the operational product by 11.46 % (± 1.48 %) and our retrieval by 17.61 % (± 1.92 %) in winter. The improved and operational HCHO are also used to investigate the spatial–temporal characteristics of HCHO over China. The result shows that both improved and operational HCHO VCDs reach maximum in summer and minimum in winter. High HCHO VCDs mainly located over populated areas, i.e., Sichuan Basin and central and eastern China, indicate a significant contribution of anthropogenic emissions. The hotspots are more obvious on the map of the improved HCHO retrieval than the operational product. The result indicates that the improved TROPOMI HCHO retrieval is more suitable for the analysis of regional- and city-scale pollution in China.

Evaluating Sentinel-5P TROPOMI tropospheric NO2 column densities with airborne and Pandora spectrometers near New York City and Long Island Sound.

Airborne and ground-based Pandora spectrometer NO2 column measurements were collected during the 2018 Long Island Sound Tropospheric Ozone Study (LISTOS) in the New York City/Long Island Sound region, which coincided with early observations from the Sentinel-5P TROPOspheric Monitoring Instrument (TROPOMI) instrument. Both airborne- and ground-based measurements are used to evaluate the TROPOMI NO2 Tropospheric Vertical Column (TrVC) product v1.2 in this region, which has high spatial and temporal heterogeneity in NO2. First, airborne and Pandora TrVCs are compared to evaluate the uncertainty of the airborne TrVC and establish the spatial representativeness of the Pandora observations. The 171 coincidences between Pandora and airborne TrVCs are found to be highly correlated (r2 =0.92 and slope of 1.03), with the largest individual differences being associated with high temporal and/or spatial variability. These reference measurements (Pandora and airborne) are complementary with respect to temporal coverage and spatial representativity. Pandora spectrometers can provide continuous long-term measurements but may lack areal representativity when operated in direct-sun mode. Airborne spectrometers are typically only deployed for short periods of time, but their observations are more spatially representative of the satellite measurements with the added capability of retrieving at subpixel resolutions of 250m×250m over the entire TROPOMI pixels they overfly. Thus, airborne data are more correlated with TROPOMI measurements (r2 = 0.96) than Pandora measurements are with TROPOMI (r2 = 0.84). The largest outliers between TROPOMI and the reference measurements appear to stem from too spatially coarse a priori surface reflectivity (0.5°) over bright urban scenes. In this work, this results during cloud-free scenes that, at times, are affected by errors in the TROPOMI cloud pressure retrieval impacting the calculation of tropospheric air mass factors. This factor causes a high bias in TROPOMI TrVCs of 4%–11%. Excluding these cloud-impacted points, TROPOMI has an overall low bias of 19%–33% during the LISTOS timeframe of June–September 2018. Part of this low bias is caused by coarse a priori profile input from the TM5-MP model; replacing these profiles with those from a 12 km North American Model–Community Multiscale Air Quality (NAMCMAQ) analysis results in a 12%–14% increase in the TrVCs. Even with this improvement, the TROPOMI-NAMCMAQ TrVCs have a 7%–19% low bias, indicating needed improvement in a priori assumptions in the air mass factor calculation. Future work should explore additional impacts of a priori inputs to further assess the remaining low biases in TROPOMI using these datasets.

Three-dimensional radiative transfer effects on airborne and ground-based trace gas remote sensing

Abstract. Air mass factors (AMFs) are used in passive trace gas remote sensing for converting slant column densities (SCDs) to vertical column densities (VCDs). AMFs are traditionally computed with 1D radiative transfer models assuming horizontally homogeneous conditions. However, when observations are made with high spatial resolution in a heterogeneous atmosphere or above a heterogeneous surface, 3D effects may not be negligible. To study the importance of 3D effects on AMFs for different types of trace gas remote sensing, we implemented 1D-layer and 3D-box AMFs into the Monte carlo code for the phYSically correct Tracing of photons In Cloudy atmospheres (MYSTIC), a solver of the libRadtran radiative transfer model (RTM). The 3D-box AMF implementation is fully consistent with 1D-layer AMFs under horizontally homogeneous conditions and agrees very well (<5 % relative error) with 1D-layer AMFs computed by other RTMs for a wide range of scenarios. The 3D-box AMFs make it possible to visualize the 3D spatial distribution of the sensitivity of a trace gas observation, which we demonstrate with two examples. First, we computed 3D-box AMFs for ground-based multi-axis spectrometer (MAX-DOAS) observations for different viewing geometry and aerosol scenarios. The results illustrate how the sensitivity reduces with distance from the instrument and that a non-negligible part of the signal originates from outside the line of sight. Such information is invaluable for interpreting MAX-DOAS observations in heterogeneous environments such as urban areas. Second, 3D-box AMFs were used to generate synthetic nitrogen dioxide (NO2) SCDs for an airborne imaging spectrometer observing the NO2 plume emitted from a tall stack. The plume was imaged under different solar zenith angles and solar azimuth angles. To demonstrate the limitations of classical 1D-layer AMFs, VCDs were then computed assuming horizontal homogeneity. As a result, the imaged NO2 plume was shifted in space, which led to a strong underestimation of the total VCDs in the plume maximum and an underestimation of the integrated line densities that can be used for estimating emissions from NO2 images. The two examples demonstrate the importance of 3D effects for several types of ground-based and airborne remote sensing when the atmosphere cannot be assumed to be horizontally homogeneous, which is typically the case in the vicinity of emission sources or in cities.

Total column water vapor retrieval for Global Ozone Monitoring Experience-2 (GOME-2) visible blue observations

Abstract. We present a new total column water vapor (TCWV) retrieval algorithm in the visible blue spectral band for the Global Ozone Monitoring Experience 2 (GOME-2) instruments on board the European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT) Metop satellites. The blue band algorithm allows the retrieval of water vapor from sensors which do not cover longer wavelengths, such as the Ozone Monitoring Instrument (OMI) and the Copernicus atmospheric composition missions Sentinel-5 Precursor (S5P), Sentinel-4 (S4) and Sentinel-5 (S5). The blue band algorithm uses the differential optical absorption spectroscopic (DOAS) technique to retrieve water vapor slant columns. The measured water vapor slant columns are converted to vertical columns using air mass factors (AMFs). The new algorithm has an iterative optimization module to dynamically find the optimal a priori water vapor profile. This makes it better suited for climate studies than usual satellite retrievals with static a priori or vertical profile information from the chemistry transport model (CTM). The dynamic a priori algorithm makes use of the fact that the vertical distribution of water vapor is strongly correlated to the total column. The new algorithm is applied to GOME-2A and GOME-2B observations to retrieve TCWV. The data set is validated by comparing it to the operational product retrieved in the red spectral band, sun photometer and radiosonde measurements. Water vapor columns retrieved in the blue band are in good agreement with the other data sets, indicating that the new algorithm derives precise results and can be used for the current and forthcoming Copernicus Sentinel missions S4 and S5.