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This study describes the application of a regional Earth system model with updated parameterizations for selected land–atmosphere exchange processes and multiplatform, multidisciplinary observations. We estimate reactive nitrogen (Nr = NO y+ NHx) emissions from various sources, surface and column nitrogen dioxide (NO2), and total and speciated Nr dry and wet deposition during 2018–2023 over the northeastern and mid-Atlantic US where nitrogen-oxide-limited or transitional chemical regimes dominate. The estimated Nr concentrations and deposition fluxes are related to ozone (O3) in terms of spatiotemporal variability and its key drivers as well as possible ecosystem impacts. Modeled surface O3 persistently agrees well with observations, with root mean square errors staying within 4–7 ppbv for individual years in May–June–July. Model-based surface O3–NO2 column correlation, which shows a dependency on column formaldehyde / NO2, is higher in 2020 (r=0.62) than in other years (r=0.47 –0.56). Ozone vegetative uptake overall dropped by ∼10% from 2018 to 2023, displaying clearer downward temporal changes than total Nr deposition as declining NOy emission and deposition competed with increasing NHx fluxes. It is highlighted that temporal variabilities of Nr and O3 concentrations and fluxes on subregional to local scales respond to hydrological variability that can be influenced by precipitation and controllable human activities like irrigation. Deposition and biogenic emissions that are highly sensitive to interconnected environmental and plant physiological conditions, plus extra-regional sources (e.g., O3-rich stratospheric air and dense wildfire plumes from upwind regions), have been playing increasingly important roles in controlling pollutant budgets as local emissions decline owing to effective emission regulations and COVID lockdowns. [ABSTRACT FROM AUTHOR]

Formaldehyde (HCHO) in the atmosphere is an intermediate product from the oxidation of methane and non-methane volatile organic compounds. In remote marine regions, HCHO variability is closely related to atmospheric oxidation capacity, and modeled HCHO in these regions is usually added as a global satellite HCHO background. Thus, it is important to understand and validate the levels of satellite HCHO over the remote oceans. Here we intercompare three satellite retrievals of total HCHO columns from the Ozone Monitoring Instrument Smithsonian Astrophysical Observatory (OMI SAO (v004)) algorithm, Ozone Mapping and Profiler Suite on Suomi National Polar-orbiting Partnership Smithsonian Astrophysical Observatory (OMPS-NPP SAO) algorithm, and Ozone Monitoring Instrument Belgian Institute for Space Aeronomy (OMI BIRA) algorithm and validate them against in situ observations from the NASA Atmospheric Tomography Mission (ATom) mission. All retrievals are correlated with ATom-integrated columns over remote oceans, with OMI SAO (v004) showing the best agreement. This is also reflected in the mean bias (MB) for OMI SAO (- 0.73 ± 0.87) × 1015 molec. cm−2, OMPS SAO (- 0.76 ± 0.88) × 1015 molec. cm−2, and OMI BIRA (- 1.40 ± 1.11) × 1015 molec. cm−2. We recommend the OMI-SAO (v004) retrieval for remote-ocean atmosphere studies. Three satellite HCHO retrievals and in situ ATom columns all generally captured the spatial and seasonal distributions of HCHO in the remote-ocean atmosphere. Retrieval bias varies by latitude and season, but a persistent low bias is found in all products at high latitudes, and the general low bias is most severe for the OMI BIRA product. Examination of retrieval components reveals that slant column corrections have a larger impact on the retrievals over remote marine regions, while AMFs play a smaller role. This study informs us that the potential latitude-dependent biases in the retrievals require further investigation for improvement and should be considered when using marine HCHO satellite data, and vertical profiles from in situ instruments are crucial for validating satellite retrievals. [ABSTRACT FROM AUTHOR]

Tropospheric ozone results from in situ chemical formation and stratosphere–troposphere exchange (STE), with the latter being more important in the middle and upper troposphere than in the lower troposphere. Ozone photochemical formation is nonlinear and results from the oxidation of methane and non-methane hydrocarbons (NMHCs) in the presence of nitrogen oxide (NO x= NO + NO2). Previous studies showed that O3 short- and long-term trends are nonlinearly controlled by near-surface anthropogenic emissions of carbon monoxide (CO), volatile organic compounds (VOCs), and nitrogen oxides, which may also be impacted by the long-range transport (LRT) of O3 and its precursors. In addition, several studies have demonstrated the important role of STE in enhancing ozone levels, especially in the midlatitudes. In this article, we investigate tropospheric ozone spatial variability and trends from 2005 to 2019 and relate those to ozone precursors on global and regional scales. We also investigate the spatiotemporal characteristics of the ozone formation regime in relation to ozone chemical sources and sinks. Our analysis is based on remote sensing products of the tropospheric column of ozone (TrC-O3) and its precursors, nitrogen dioxide (TrC-NO2), formaldehyde (TrC-HCHO), and total column CO (TC-CO), as well as ozonesonde data and model simulations. Our results indicate a complex relationship between tropospheric ozone column levels, surface ozone levels, and ozone precursors. While the increasing trends of near-surface ozone concentrations can largely be explained by variations in VOC and NOx concentration under different regimes, TrC-O3 may also be affected by other variables such as tropopause height and STE as well as LRT. Decreasing or increasing trends in TrC-NO2 have varying effects on TrC-O3, which is related to the different local chemistry in each region. We also shed light on the contribution of NOx lightning and soil NO and nitrous acid (HONO) emissions to trends of tropospheric ozone on regional and global scales. [ABSTRACT FROM AUTHOR]

The Geostationary Environment Monitoring Spectrometer (GEMS) on board the GEO-KOMPSAT-2B satellite is the first geostationary satellite launched to monitor the environment. GEMS conducts hourly measurements during the day over eastern and southeastern Asia. This work presents glyoxal (CHOCHO) vertical column densities (VCDs) retrieved from GEMS, with optimal settings for glyoxal retrieval based on sensitivity tests involving reference spectrum sampling and fitting window selection. We evaluated GEMS glyoxal VCDs by comparing them to the TROPOspheric Monitoring Instrument (TROPOMI) and multi-axis differential optical absorption spectroscopy (MAX-DOAS) ground-based observations. On average, GEMS and TROPOMI VCDs show a spatial correlation coefficient of 0.63, increasing to 0.87 for northeastern Asia. While GEMS and TROPOMI demonstrate similar monthly variations in the Indochinese Peninsula regions (R > 0.67), variations differ in other areas. Specifically, GEMS VCDs are higher in the winter and either lower or comparable to TROPOMI and MAX-DOAS VCDs in the summer across northeastern Asia. We attributed the discrepancies in the monthly variation to a polluted reference spectrum and high NO2 concentrations. When we correct GEMS glyoxal VCDs as a function of NO2 SCDs, the monthly correlation coefficients substantially increase from 0.16–0.40 to 0.45–0.72 in high NO2 regions. When averaged hourly, GEMS and MAX-DOAS VCDs exhibit similar diurnal variations, especially at stations in Japan (Chiba, Kasuga, and Fukue). [ABSTRACT FROM AUTHOR]

We use formaldehyde (HCHO) vertical column measurements from the Scanning Imaging Absorption spectrometer for Atmospheric Chartography (SCIAMACHY) and Ozone Monitoring Instrument (OMI), and a nested-grid version of the GEOS-Chem chemistry transport model, to infer an ensemble of top-down isoprene emission estimates from tropical South America during 2006, using different model configurations and assumptions in the HCHO air-mass factor (AMF) calculation. Scenes affected by biomass burning are removed on a daily basis using fire count observations, and we use the local model sensitivity to identify locations where the impact of spatial smearing is small, though this comprises spatial coverage over the region. We find that the use of the HCHO column data more tightly constrains the ensemble isoprene emission range from 27-61 Tg C to 31-38 Tg C for SCIAMACHY, and 45-104 Tg C to 28-38 Tg C for OMI. Median uncertainties of the top-down emissions are about 60-260% for SCIAMACHY, and 10-90% for OMI. We find that the inferred emissions are most sensitive to uncertainties in cloud fraction and cloud top pressure (differences of ±10%), the a priori isoprene emissions (±20%), and the HCHO vertical column retrieval (±30%). Construction of continuous top-down emission maps generally improves GEOS-Chem's simulation of HCHO columns over the region, with respect to both the SCIAMACHY and OMI data. However, if local time top-down emissions are scaled to monthly mean values, the annual emission inferred from SCIAMACHY are nearly twice those from OMI. This difference cannot be explained by the different sampling of the sensors or uncertainties in the AMF calculation. Key Points Satellite HCHO data constrain range of uncertainty in Amazon isoprene emissions Top-down emissions are sensitive to prior isoprene inventory and HCHO retrieval Top-down emissions from SCIAMACHY are about twice those derived from OMI © 2013. American Geophysical Union. All Rights Reserved.

We use a nested-grid version of the GEOS-Chem chemistry transport model, constrained by isoprene emissions from the Model of Emissions of Gases and Aerosols from Nature (MEGAN), and the Lund-Potsdam-Jena General Ecosystem Simulator (LPJ-GUESS) bottom-up inventories, to evaluate the impact that surface isoprene emissions have on formaldehyde (HCHO) air-mass factors (AMFs) and vertical column densities (VCDs) over tropical South America during 2006, as observed by the Scanning Imaging Absorption Spectrometer for Atmospheric Chartography (SCIAMACHY) and Ozone Monitoring Instrument (OMI). Although the large-scale seasonal variability of monthly mean HCHO VCDs is typically unaffected by the choice of bottom-up inventory, large relative differences of up to ±45% in the HCHO VCD can occur for individual regions and months, but typically most VCD differences are of order ±20%. These relative changes are comparable to those produced by other sources of uncertainty in the AMF including aerosols and surface albedo, but less than those from clouds. In a sensitivity test, we find that top-down annual isoprene emissions inferred from SCIAMACHY and OMI HCHO vertical columns can vary by as much as ±30-50% for each instrument respectively, depending on the region studied and the a priori isoprene emissions used. Our analysis suggests that the influence of the a priori isoprene emissions on HCHO AMFs and VCDs is therefore non-negligible and must be carefully considered when inferring top-down isoprene emissions estimates over this, or potentially any other, region. © 2012. American Geophysical Union.

We present an evaluation of a nested high-resolution Goddard Earth Observing System (GEOS)-Chem chemistry transport model simulation of tropospheric chemistry over tropical South America. The model has been constrained with two isoprene emission inventories: (1) the canopy-scale Model of Emissions of Gases and Aerosols from Nature (MEGAN) and (2) a leaf-scale algorithm coupled to the Lund-Potsdam-Jena General Ecosystem Simulator (LPJ-GUESS) dynamic vegetation model, and the model has been run using two different chemical mechanisms that contain alternative treatments of isoprene photo-oxidation. Large differences of up to 100 Tg C yr-1 exist between the isoprene emissions predicted by each inventory, with MEGAN emissions generally higher. Based on our simulations we estimate that tropical South America (30-85°W, 14°N-25°S) contributes about 15-35% of total global isoprene emissions. We have quantified the model sensitivity to changes in isoprene emissions, chemistry, boundary layer mixing, and soil NOx emissions using ground-based and airborne observations. We find GEOS-Chem has difficulty reproducing several observed chemical species; typically hydroxyl concentrations are underestimated, whilst mixing ratios of isoprene and its oxidation products are overestimated. The magnitude of model formaldehyde (HCHO) columns are most sensitive to the choice of chemical mechanism and isoprene emission inventory. We find GEOS-Chem exhibits a significant positive bias (10-100%) when compared with HCHO columns from the Scanning Imaging Absorption Spectrometer for Atmospheric Chartography (SCIAMACHY) and Ozone Monitoring Instrument (OMI) for the study year 2006. Simulations that use the more detailed chemical mechanism and/or lowest isoprene emissions provide the best agreement to the satellite data, since they result in lower-HCHO columns. Copyright © 2011 by the American Geophysical Union.

We perform Empirical Orthogonal Function (EOF) analysis on 12 years of global GOME and SCIAMACHY formaldehyde (HCHO) column observations to determine the most significant spatial and temporal HCHO variations. In most regions, we find that HCHO variability is predominantly driven by seasonal variations of biogenie emissions and biomass burning. However, unusually low HCHO columns are consistently observed over the Amazon rainforest during the transition from the wet-to-dry seasons. We use MODIS leaf area and enhanced vegetation indices, to show variations in vegetation are consistent with the observed decrease in HCHO during this period (correlations of 0.69 and 0.67, respectively). Based on this evidence, we suggest isoprene emitting vegetation experience widespread leaf flushing (new leaf growth) prior to the dry season, resulting in a large-scale annual shutdown of Amazonian isoprene emissions. © 2009.

The Geostationary Environment Monitoring Spectrometer (GEMS) on board GEO-KOMPSAT-2B was launched in February 2020 and has been monitoring atmospheric chemical compositions over Asia. We present the first evaluation of the operational GEMS formaldehyde (HCHO) vertical column densities (VCDs) during and after the in-orbit test (IOT) period (August–October 2020) by comparing them with the products from the TROPOspheric Monitoring Instrument (TROPOMI) and Fourier-transform infrared (FTIR) and multi-axis differential optical absorption spectroscopy (MAX-DOAS) instruments. During the IOT, the GEMS HCHO VCDs reproduced the observed spatial pattern of TROPOMI VCDs over the entire domain (r= 0.62) with high biases (10 %–16 %). We found that the agreement between GEMS and TROPOMI was substantially higher in Northeast Asia (r= 0.90), encompassing the Korean Peninsula and east China. GEMS HCHO VCDs captured the seasonal variation in HCHO, primarily driven by biogenic emissions and photochemical activities, but showed larger variations than those of TROPOMI over coastal regions (Kuala Lumpur, Singapore, Shanghai, and Busan). In addition, GEMS HCHO VCDs showed consistent hourly variations with MAX-DOAS (r= 0.77) and FTIR (r= 0.86) but were 30–40 % lower than ground-based observations. Different vertical sensitivities of GEMS and ground-based instruments caused these biases. Utilizing the averaging kernel smoothing method reduces the low biases by approximately 10 % to 15 % (normalized mean bias (NMB): - 47.4 % to - 31.5 % and - 38.6 % to - 26.7 % for MAX-DOAS and FTIR, respectively). The remaining discrepancies are due to multiple factors, including spatial collocation and different instrumental sensitivities, requiring further investigation using inter-comparable datasets. [ABSTRACT FROM AUTHOR]

This study applies a regional Earth system model (NASA-Unified Weather Research and Forecasting with online chemistry) with updated parameterizations for selected land-air exchange processes and multi-platform observations, to first estimate reactive nitrogen (Nr = oxidized NOy + reduced NHx) emissions from anthropogenic and natural sources, nitrogen dioxide (NO2) column densities and surface concentrations, total and speciated Nr dry or/and wet deposition fluxes during 2018-2023 over the northeastern and Mid-Atlantic US most of which belong to nitrogen oxides-limited or transitional chemical regimes. The estimated multi-year Nr concentrations and deposition fluxes are then compared with and related to ozone (O3), in terms of their spatiotemporal variability and key drivers as well as possible ecosystem impacts. Finally, through three sets of case studies, we identify and discuss about 1) the capability of land data assimilation (DA) to reduce the uncertainty in modeled land surface states at daily-to-interannual timescales, that can propagate into atmospheric chemistry fields; 2) the impacts of irrigation on land surface and atmospheric fields as well as pollutants' ecosystem uptake and impacts; and 3) the impacts of transboundary air pollution during selected extreme events on pollutants' budgets and ecosystem impacts. With the updated model parameterizations and anthropogenic emission inputs, the eastern US surface O3 modeled by this tool persistently agrees better with observations (i.e., with root-mean-square errors staying within 4-7 ppbv for the individual years' May-June-July) than those in literature where model errors often exceed 20 ppbv. Based on model calculations, surface O3 correlates more strongly with early afternoon NO2 columns than formaldehyde columns (r=0.54 and 0.40, respectively). The O3 vegetative uptake overall dropped by ~10% from 2018 to 2023, displaying clearer downward temporal changes than the total Nr deposition due to the declining NOy emission and deposition fluxes competing with the increasing NHx fluxes. It is highlighted that, temporal variability of Nr and O3 concentrations and fluxes on subregional-to-local scales respond to hydrological variability that can be influenced by precipitation and controllable human activities such as irrigation. Deposition processes and biogenic emissions that are highly sensitive to interconnected environmental and plants' physiological conditions, as well as extra-regional sources (e.g., O3-rich stratospheric air and dense wildfire plumes from upwind regions), have been playing increasingly important roles in controlling pollutants' budgets in this area as local emissions go down owing to effective emission regulations and COVID lockdowns. To better inform the design of mitigation and adaptation strategies, it is recommended to continue evaluating and improving the model parameterizations and inputs relevant to these processes in seamlessly coupled multiscale Earth system models using laboratory and field experiments in combination with satellite DA which would in turn benefit remote sensing communities. [ABSTRACT FROM AUTHOR]

Spaceborne formaldehyde (HCHO) measurements constitute an excellent proxy for the sources of non-methane volatile organic compounds (NMVOCs). Past studies suggested substantial overestimations of NMVOC emissions in state-of-the-art inventories over major source regions. Here, the QA4ECV (Quality Assurance for Essential Climate Variables) retrieval of HCHO columns from OMI (Ozone Monitoring Instrument) is evaluated against (1) FTIR (Fourier-transform infrared) column observations at 26 stations worldwide and (2) aircraft in situ HCHO concentration measurements from campaigns conducted over the USA during 2012–2013. Both validation exercises show that OMI underestimates high columns and overestimates low columns. The linear regression of OMI and aircraft-based columns gives ΩOMI=0.651Ωairc+2.95×1015 molec.cm-2 , with ΩOMI and Ωairc the OMI and aircraft-derived vertical columns, whereas the regression of OMI and FTIR data gives ΩOMI=0.659ΩFTIR+2.02×1015 molec.cm-2. Inverse modelling of NMVOC emissions with a global model based on OMI columns corrected for biases based on those relationships leads to much-improved agreement against FTIR data and HCHO concentrations from 11 aircraft campaigns. The optimized global isoprene emissions (∼445Tgyr-1) are 25% higher than those obtained without bias correction. The optimized isoprene emissions bear both striking similarities and differences with recently published emissions based on spaceborne isoprene columns from the CrIS (Cross-track Infrared Sounder) sensor. Although the interannual variability of OMI HCHO columns is well understood over regions where biogenic emissions are dominant, and the HCHO trends over China and India clearly reflect anthropogenic emission changes, the observed HCHO decline over the southeastern USA remains imperfectly elucidated. [ABSTRACT FROM AUTHOR]

Volatile organic compounds (VOCs) are key precursors of particulate matter and tropospheric ozone. Although the terrestrial biosphere is by far the largest source of VOCs into the atmosphere, the emissions of biogenic VOCs remain poorly constrained at the regional scale. In this work, we derive top-down biogenic emissions over Europe using weekly averaged TROPOMI formaldehyde (HCHO) data from 2018 to 2021. The systematic bias of the TROPOMI HCHO columns is characterized and corrected for based on comparisons with FTIR data at seven European stations. The top-down fluxes of biogenic, pyrogenic, and anthropogenic VOC sources are optimized using an inversion framework based on the MAGRITTEv1.1 chemistry transport model and its adjoint. The inversion leads to strongly increased isoprene emissions with respect to the MEGAN–MOHYCAN inventory over the model domain (from 8.1 to 18.5 Tgyr-1), which is driven by the high observed TROPOMI HCHO columns in southern Europe. The impact of the inversion on biomass burning VOCs (+ 13 %) and anthropogenic VOCs (- 17 %) is moderate. An evaluation of the optimized HCHO distribution against ground-based remote sensing (FTIR and MAX-DOAS) and in situ data provides generally improved agreement at stations below about 50 ∘ N but indicates overestimated emissions in northern Scandinavia. Sensitivity inversions show that the top-down emissions are robust with respect to changes in the inversion settings and in the model chemical mechanism, leading to differences of up to 10 % in the total emissions. However, the top-down emissions are very sensitive to the bias correction of the observed columns, as the biogenic emissions are 3 times lower when the correction is not applied. Furthermore, the use of different a priori biogenic emissions has a significant impact on the inversion results due to large differences among bottom-up inventories. The sensitivity run using CAMS-GLOB-BIOv3.1 as a priori emissions in the inversion results in 30 % lower emissions with respect to the optimization using MEGAN–MOHYCAN. In regions with large temperature and cloud cover variations, there is strong week-to-week variability in the observed HCHO columns. The top-down emissions, which are optimized at weekly increments, have a much improved capability of representing these large fluctuations than an inversion using monthly increments. [ABSTRACT FROM AUTHOR]

Spaceborne formaldehyde (HCHO) measurements constitute an excellent proxy for the sources of non-methane volatile organic compounds (NMVOCs). Past studies suggested substantial overestimations of NMVOC emission in state-of-the-art inventories over major source regions. Here, the QA4ECV (Quality Assurance for Essential Climate Variables) retrieval of HCHO columns from OMI (Ozone Monitoring Instrument) are evaluated against (1) FTIR (Fourier-transform infrared) column observations at 26 stations worldwide, and (2) aircraft in situ HCHO concentration measurements from campaigns conducted over the U.S. in 2012-2013. Both validation exercises show that OMI underestimates high columns and overestimates low columns. The linear regression of OMI and aircraft-based columns gives OMI = 0.651 airc +2.95 · 1015 molec.cm-2, with OMI and airc the OMI and aircraft-derived vertical columns, whereas the regression of OMI and FTIR data gives OMI = 0.659 FTIR +2.02 · 1015 molec.cm-2. Inverse modelling of NMVOC emissions with a global model based on OMI columns corrected for biases based on those relationships leads to much-improved agreement against FTIR data and HCHO concentrations from 11 aircraft campaigns. The optimized global isoprene emissions (- 445Tg yr-1) are 25% higher than those obtained without bias correction. The optimized isoprene emissions bear both striking similarities and differences with recently published emissions based on spaceborne isoprene columns from the CrIS (Cross-track Infrared Sounder) sensor. Although the interannual variability of OMI HCHO columns is well understood over regions where biogenic emissions are dominant, and the HCHO trends over China and India clearly reflect anthropogenic emission changes, the observed HCHO decline over the Southeastern U.S. remains imperfectly elucidated. [ABSTRACT FROM AUTHOR]

Volatile organic compounds (VOCs) are key precursors of particulate matter and tropospheric ozone. Although the terrestrial biosphere is by far the largest source of VOCs into the atmosphere, the emissions of biogenic VOCs remain poorly constrained at regional scale. In this work, we derive top-down biogenic emissions over Europe using weekly-averaged TROPOMI formaldehyde (HCHO) data from 2018 to 2021. The systematic bias of the TROPOMI HCHO columns is characterized and corrected for based on comparisons with FTIR data at seven European stations. The top-down fluxes of biogenic, pyrogenic, and anthropogenic VOC sources are optimized using an inversion framework based on the MAGRITTEv1.1 chemistry transport model and its adjoint. The inversion leads to strongly increased isoprene emissions with respect to the MEGAN-MOHYCAN inventory over the model domain (from 8.1 to 18.5 Tg yr−1 ) which is driven by the high observed TROPOMI HCHO columns in southern Europe. The impact of the inversion on biomass burning VOCs (+13%) and anthropogenic VOCs (−17%) is moderate. An evaluation of the optimized HCHO distribution against ground-based remote sensing (FTIR and MAX-DOAS) and in situ data provides generally improved agreement at stations below about 50° N, but indicates overestimated emissions in northern Scandinavia. Sensitivity inversions show that the top-down emissions are robust with respect to changes in the inversion settings and in the model chemical mechanism. However, the top-down emissions are very sensitive to the bias correction of the observed columns. Furthermore, the use of different a priori emissions has a significant impact on the inversion results due to large differences among bottom-up inventories. In regions with variable meteorology, there is strong week-to-week variability in the observed HCHO columns. The top-down emissions, which are optimized at weekly increments, have a much improved capability of representing these large fluctuations than an inversion using monthly increments. [ABSTRACT FROM AUTHOR]

The Geostationary Environment Monitoring Spectrometer (GEMS) onboard GEO-KOMPSAT 2B was successfully launched in February 2020 and has monitored Asia. We present the first evaluation of the operational GEMS formaldehyde (HCHO) vertical column densities (VCDs) during the in-orbit test period (IOT) (August–October 2020) and onward by comparing them with the products from Tropospheric Monitoring Instrument (TROPOMI), Fourier-Transform Infrared (FTIR), and Multi-Axis Differential Optical Absorption Spectroscopy (MAX-DOAS) instruments. During the in-orbit test period, the GEMS HCHO VCDs reproduced the observed spatial pattern of TROPOMI VCDs over the whole domain (r=0.62) with high biases (10–16 %). In the afternoon, GEMS VCDs were too high over the west side of the tropics. We corrected this issue by adding polarization sensitivity vectors of the GEMS instrument as an additional fitting parameter in the retrieval algorithm. Using observed radiances from clear-sky pixels as the reference spectrum in the spectral fitting significantly contributed to reducing artifacts in radiance references, resulting in 10–40 % lower HCHO VCDs over the latitude including cloudy areas in the updated GEMS product. We find that the agreement between the two is much higher in Northeast Asia (r=0.90), including the Korean peninsula and East China. GEMS HCHO VCDs well captured the seasonal variation of HCHO mainly driven by biogenic emissions and photochemical activities but showed larger variations than those of TROPOMI over coastal regions (Kuala Lumpur, Singapore, Shanghai, and Busan). In addition, GEMS HCHO VCDs showed consistent hourly variations with MAX-DOAS (r=0.79) and FTIR (r=0.85) but were lower by 30–40 % relative to the ground based observations. Different vertical sensitivities between GEMS and ground-based instruments caused these systematic biases. The use of averaging kernel smoothing method reduces the low biases by about 10 to 15 % (NMB: -48.5 % to -32.4 %, -39.1 % to -27.3 % for MAX-DOAS and FTIR, respectively). The remaining discrepancies are due to multiple factors, including spatial colocation and different instrumental sensitivities, which need further investigation using inter-comparable datasets. [ABSTRACT FROM AUTHOR]

We present a database of MAX-DOAS (Multi-AXis Differential Optical Absorption Spectroscopy) ground-based observations of NO2 and H2CO 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) in Kinshasa. In the validation, we experiment three different comparison cases of increasing complexity. In the first case, a direct comparison between MAX-DOAS observations (average +/- 60 minutes around overpass) and TROPOMI shows an underestimation of TROPOMI with a median bias of -40 % (s=0.26 and R=0.41) for NO2 and -26 % (s=0.24 and R=0.28) for H2CO. The second case takes into account the different vertical sensitivities of the two instruments and the apriori profile. We note a slight decrease of the biases and a strong improvement of the linear regression parameter, about -35 % (s=0.72 and R=0.74) for NO2 and 1 % (s=1.01 and R=0.66) for H2CO. The third case, which is considered more realistic than the first two, builds on the second case by considering also the direction of sight of the MAX-DOAS. For this third case, we find a bias of -2 % (s= 1.09; R= 0.59) for NO2 and 13 % (s= 1.51; R= 0.60) for H2CO. Those results indicate a large impact of the vertical sensitivity and horizontal heterogeneity in this validation process at this site. In order to evaluate the capability of the GEOS-Chem model in this region, we performed the comparisons between TROPOMI and the simulations made for 2020. We found a bias of 16 % (s= 0.42 and R = 0.80) for NO2 and bais of 61 % (s= 0.05 and R = 0.24) for H2CO. [ABSTRACT FROM AUTHOR]