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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]

Propane (C3H8) is an important trace gas in the atmosphere, as it is a proxy for oil and gas production and has a significant impact on atmospheric chemical reactions related to the hydroxyl radical and tropospheric ozone formation. In this study, solar direct absorption spectra near 2967 cm−1 recorded by a ground-based Fourier Transform InfraRed spectrometer (FTIR) are applied to retrieve C3H8 total columns between June 2018 and July 2022 at Xianghe in North China. The systematic and random uncertainties of the C3H8 column retrieval are estimated to be 18.2 % and 18.1 %, respectively. The mean and standard deviation of the C3H8 columns derived from the FTIR spectra at Xianghe are 1.80±0.81(1 σ) × 1015 molecules / cm 2. Good correlations are found between C3H8 and other non-methane hydrocarbons, such as C2H6 (R=0.84) and C2H2 (R=0.79), as well as between C3H8 and CO (R=0.72). However, the correlation between C3H8 and CH4 is relatively weak (R=0.45). The FTIR C3H8 measurements are also compared against two atmospheric chemical transport model simulations (the Whole Atmosphere Community Climate Model (WACCM) and the Copernicus Atmosphere Monitoring Service (CAMS)). We find that the C3H8 columns from both models have different seasonal variations as compared to the FTIR measurements. Moreover, the mean C3H8 columns derived from the WACCM and CAMS models are about 68 % larger than the FTIR retrievals. The new FTIR measurements at Xianghe provide us an insight into the C3H8 column variations and underlying processes in North China. [ABSTRACT FROM AUTHOR]

Carbon dioxide (CO2) is the most important long-lived greenhouse gas and can be retrieved using solar absorption spectra recorded by a ground-based Fourier-transform infrared spectrometer (FTIR). In this study, we investigate the CO2 retrieval strategy using the Network for the Detection of Atmospheric Composition Change–Infrared Working Group (NDACC–IRWG) type spectra between August 2018 and April 2022 (~4 years) at Xianghe, China, aiming to find the optimal observed spectra, retrieval window, and spectroscopy. Two spectral regions, near 2600 and 4800 cm−1, are analyzed. The differences in column-averaged dry-air mole fraction of CO2 (XCO2) derived from spectroscopies (ATM18, ATM20, HITRAN2016, and HITRAN2020) can be up to 1.65 ± 0.95 ppm and 7.96 ± 2.02 ppm for NDACC-type 2600 cm−1 and 4800 cm−1 retrievals, respectively, which is mainly due to the CO2 differences in air-broadened Lorentzian HWHM coefficient (γair) and line intensity (S). HITRAN2020 provides the best fitting, and the retrieved CO2 columns and profiles from both 2600 and 4800 cm−1 are compared to the co-located Total Column Carbon Observing Network (TCCON) measurements and the greenhouse gas reanalysis dataset from the Copernicus Atmosphere Monitoring Service (CAMS). The amplitude of XCO2 seasonal variation derived from the NDACC-type (4800 cm−1) is closer to the TCCON measurements than that from the NDACC-type (2600 cm−1). Moreover, the NDACC-type (2600 cm−1) retrievals are strongly affected by the a priori profile. For tropospheric XCO2, the correlation coefficient between NDACC-type (4800 cm−1) and CAMS model is 0.73, which is higher than that between NDACC-type (2600 cm−1) and CAMS model (R = 0.56). [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]

The Copernicus Atmosphere Monitoring Service (CAMS) is providing daily analyses and forecasts of the composition of the atmosphere, including the reactive gases such as O3, CO, NO2, HCHO, SO2, aerosol species and greenhouse gases. The global CAMS analysis system (IFS-COMPO) is based on the ECMWF Integrated Forecast System (IFS) for numerical weather prediction (NWP), and assimilates a large number of composition satellite products on top of the meteorological observations ingested in IFS. The CAMS system receives regular upgrades, following the upgrades of IFS. The last upgrade, Cy48R1, operational since 27 June 2023, was major with a large number of code changes, both for COMPO and for NWP. The main COMPO innovations include the introduction of full stratospheric chemistry, a major update of the emissions, of the aerosol model, including the representation of secondary organic aerosol, several updates of the dust life cycle and optics, inorganic chemistry in the troposphere, and the assimilation of VIIRS AOD and TROPOMI CO. The CAMS Cy48R1 upgrade was validated using a large number of independent measurement datasets, including surface in situ, surface remote sensing, routine aircraft and balloon and satellite observations. In this paper we present the validation results for Cy48R1 by comparing with the skill of the previous operational system (Cy47R3), with the independent observations as reference, for the period October 2022 to June 2023 during which daily forecasts from both cycles are available. Major improvements in skill are found for the ozone profile in the lower-middle stratosphere and for stratospheric NO2 due to the inclusion of full stratospheric chemistry. Stratospheric trace gases compare well with ACE-FTS observations between 10–200 hPa, with larger deviations between 1–10 hPa. The impact of the updated emissions is especially visible over East Asia and is beneficial for the trace gases O3, NO2, and SO2. The CO column assimilation is now anchored by IASI instead of MOPITT which is beneficial for most of the CO comparisons, and the assimilation of TROPOMI CO data improves the model CO field in the troposphere. In general the aerosol optical depth has improved globally, but the dust evaluation shows more mixed results. The results of the 47 comparisons are summarised in a score card, which shows that 83 % of the evaluation datasets show a neutral or improved performance of Cy48R1 compared to the previous operational CAMS system, while 17 % indicate a (slight) degradation. This demonstrates the overall success of this upgrade. [ABSTRACT FROM AUTHOR]

Long-term ground-based ozone measurements are crucial to study the recovery of stratospheric ozone as well as the trends of tropospheric ozone. This study is performed in the context of the LOTUS (Long-term Ozone Trends and Uncertainties in the Stratosphere) and TOAR-II (Tropospheric Ozone Assessment Report, phase II) initiatives. We perform an intercomparison study of total column ozone and multiple partial ozone columns between the ground-based measurements available at the Lauder station from 2000 to 2022, which are the Fourier transform infrared (FTIR) spectrometer, Dobson Umkehr, ozonesonde, lidar, and the microwave radiometer. We compare partial columns, defined to provide independent information: one tropospheric and three stratospheric columns. The intercomparison is analyzed using the median of relative differences (the bias) of FTIR with each of the other measurements, the scaled Median Absolute deviation (MAD s ), and a trend of these differences (measurement drift). The total column shows a bias and strong scatter well within the combined systematic and random uncertainties respectively. There is however a drift of 0.6±0.5 %/decade if we consider the full time series. In the troposphere we find a low bias of -1.9 % with the ozonesondes. No drift is found between the three instruments in the troposphere, which is good for trend studies within TOAR-II. In both the lower and upper stratosphere, we get a negative bias for all instruments with respect to FTIR (between -1.2 % and -6.8 %), but all are within the range of the systematic uncertainties. In the middle stratosphere we seem to find a negative bias of around -5.2 to -6.6 %, pointing towards too high values for FTIR in this partial column. We find no significant drift in the stratosphere between ozonesonde and FTIR for all partial columns. We do observe drift between the FTIR and Umkehr partial columns in the lower and upper stratospheres (2.6±1.1 %/decade and -3.2±0.9 %/decade), with lidar in the midle and upper stratosphere (2.1±0.8 %/decade and -3.7±1.2 %/decade), and with MWR in the midle stratosphere (3.1±1.7 %/decade). These drifts point to the fact that the different observed trends in LOTUS are not due to different sampling, vertical sensitivity or time periods and gaps. However, the difference in trends in LOTUS is reduced by applying a new FTIR retrieval strategy, which changes inputs such as the choice of microwindows, spectroscopy from HITRAN2008 to HITRAN2020, and the regularization method. [ABSTRACT FROM AUTHOR]

The temporal variability of both surface concentrations and column abundances of CO2, CH4 and CO at the Xianghe site in China are analyzed with the Weather Research and Forecast model coupled with Chemistry (WRF-Chem). Simulations of these in situ (PICARRO) and remote sensing (TCCON-affiliated) measurements are produced by the model's passive tracer option, called WRF-GHG, from September 2018 until September 2019. Our analysis found a good model performance with correlation coefficients between observations and simulations up to 0.85 for CO2 and 0.69 for CO. Key source sectors for every gas are revealed by tracking the anthropogenic fluxes in separate tracer fields. While there are slight variations in the relative impacts of these source sectors between surface and column observations, owing to differences in the sensitivity footprint of each observation type, the primary sectors influencing the various species are evident. For CO2 the industry, energy and biosphere sectors are found to be the primary contributors to the total simulated concentration, whereas CH4 concentrations are predominantly attributed to the energy, agriculture and residential & waste sectors. For CO, industry is the largest contributing sector at Xianghe, followed by residential and transportation sources. Differences among the various observation types were particularly visible in the contributions of the biosphere to CO2 and the energy sector to CH4, as their largest sources are located further away from Xianghe. Further, the influence of meteorological factors on the variability observed in the different time series was analyzed. We found that southwest winds typically bring polluted air masses from the North China Plain to the site, while northern winds are associated with cleaner conditions. Variability in surface measurements is primarily driven by the daily cycle of accumulation and atmospheric mixing linked with the planetary boundary layer height. Furthermore, the study demonstrates the ability to detect strong regional sources at Xianghe depending on wind direction. To address inconsistencies between the simulations and observations of CH4, we looked at TROPOspheric Monitoring Instrument (TROPOMI) satellite observations. We found that the model underestimation of CH4 in summer and overestimation in winter may result from a combination of a similar bias in the lateral boundary conditions and an incorrect monthly variation of the CH4 emissions in the agriculture and/or waste sectors of the CAMS-GLOB-ANT inventory over north China. Additionally, WRF-GHG simulations indicated a possible overestimation of coal mine emissions nearby Tangshan, which could not be confirmed nor contradicted by the TROPOMI observations. In summary, our findings highlight the value of WRF-GHG to interpret both surface and column observations at Xianghe, offering source sector attribution and insights in the link with local and large-scale winds based on the simultaneously computed meteorological fields. However, given the long lifetime of the considered species and the fact that WRF-GHG is a regional model, accurate initial and lateral boundary conditions remain crucial. The dependence on precise input emission data on the other hand, can be used to evaluate the existing bottom-up inventories. [ABSTRACT FROM AUTHOR]

Nitrous oxide (N2O) and methane (CH4) are two important greenhouse gases in the atmosphere. In 2019, mid-infrared (MIR) solar absorption spectra were recorded by a Bruker VERTEX 70 spectrometer and a Bruker IFS 125HR spectrometer at Sodankylä, Finland, at spectral resolutions of 0.2 and 0.005 cm-1 , respectively. The N2O and the CH4 retrievals from high-resolution MIR spectra have been well investigated within the Network for the Detection of Atmospheric Composition Change (NDACC) but not for MIR spectra gathered with instruments operating at low spectral resolution. In this study, N2O and CH4 retrieval strategies and retrieval uncertainties from the VERTEX 70 MIR low-resolution spectra are discussed and presented. The accuracy and precision of the VERTEX 70 N2O and CH4 retrievals are assessed by comparing them with the coincident 125HR retrievals and AirCore measurements. The relative differences between the N2O total columns retrieved from 125HR and VERTEX 70 spectra are - 0.3 ± 0.7 (1 σ) % with a correlation coefficient (R) of 0.93. Regarding the CH4 total column, we first used the same retrieval microwindows for 125HR and VERTEX 70 spectra, but there is an underestimation in the VERTEX 70 retrievals, especially in summer. The relative differences between the CH4 total columns retrieved from the 125HR and VERTEX 70 spectra are -1.3±1.1 (1 σ) % with a R value of 0.77. To improve the VERTEX 70 CH4 retrievals, we propose alternative retrieval microwindows. The relative differences between the CH4 total columns retrieved from the 125HR and VERTEX 70 spectra in these new windows become 0.0±0.8 (1 σ) %, along with an increase in the R value to 0.87. The coincident AirCore measurements confirm that the VERTEX 70 CH4 retrievals using the latter window choice are better, with relative mean differences between the VERTEX 70 CH4 retrievals and AirCore measurements of - 1.9 % for the standard NDACC microwindows and of 0.13 % for the alternative microwindows. This study provides insight into the N2O and CH4 retrievals from the low-resolution (0.2 cm-1) MIR spectra observed with a VERTEX 70 spectrometer, and it demonstrates the suitability of this kind of instrument for contributing to satellite validation, model verification, and other scientific campaigns with the advantage of its transportability and lower cost compared to standard NDACC-type Fourier-transform infrared (FTIR) instruments. [ABSTRACT FROM AUTHOR]

In this study, we carried out an independent validation of two methane retrieval algorithms using spectra from the Infrared Atmospheric Sounding Interferometer (IASI) onboard the Meteorological Operational satellite programme-A (MetOp-A) since 2006. Both algorithms, one developed by the Laboratoire de Météorologie Dynamique (LMD), called the non-linear inference scheme (NLISv8.3), the other by the Rutherford Appleton Laboratory (RAL), referred to as RALv2.0, provide longterm global CH4 concentrations using distinctively different retrieval approaches (Neural Network vs. Optimal Estimation, respectively). They also differ with respect to the vertical range covered, where LMD provides mid-tropospheric dry air mole fractions (mtCH4) and RAL provides mixing ratio profiles from which we can derive total column-averaged dry air mole fractions (XCH4) and potentially 2 partial column layers (qCH4). We compared both CH4 products using the Copernicus Atmospheric Monitoring Service (CAMS) model, in situ profiles (range extended using CAMS model data) and ground-based Fourier transform infrared (FTIR) remote sensing measurements. The average difference in mtCH4 with respect to in situ profiles for LMD ranges between -0.3 and 10.9 ppb while for RAL the XCH4 difference ranges between -10.2 and -4.6 ppb. The standard deviation (stdv) of the observed differences between in situ and RAL retrievals is 14.5-23.0 ppb, which is consistently smaller than that between in situ and LMD retrievals about 15.2-30.6 ppb. By comparing with ground-based FTIR sites, the mean difference is within ±10 ppb for both RAL and LMD retrievals. However, the stdv of the differences at the ground-based FTIR stations show significantly lower values for RAL (11-16 ppb) than those for LMD (about 25 ppb). The long-term stability and seasonal cycles of CH4 derived from the LMD and RAL products are further investigated and discussed. The seasonal variation of XCH4 derived from RAL is consistent with the seasonal variation observed by the groundbased FTIR measurements. However, the overall 2007-2015 XCH4 trend derived from RAL measurements is underestimated if not adjusted for an anomaly occurring on 16 May 2013 due to a L1 calibration change. For LMD, we see very good agreement at the (sub)tropics (<35°N-35°S), but notice deviations of the seasonal cycle (both in the amplitude and phase) and an underestimation of the long-term trend with respect to the RAL and reference data at higher latitude sites. [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 overestimation 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) are evaluated against (1) FTIR (Fourier-transform infrared) column observations at 26 stations worldwide, and (2) aircraft in situ HCHO 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 ΩOMI = 0.651 Ωairc + 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 givesΩOMI = 0.659 ΩFTIR + 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 (~445 Tg 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 Southeastern U.S. remains imperfectly elucidated. [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]

The availability of formaldehyde (HCHO) (a proxy for volatile organic compound reactivity) and nitrogen dioxide (NO 2) (a proxy for nitrogen oxides) tropospheric columns from ultraviolet–visible (UV–Vis) satellites has motivated many to use their ratios to gain some insights into the near-surface ozone sensitivity. Strong emphasis has been placed on the challenges that come with transforming what is being observed in the tropospheric column to what is actually in the planetary boundary layer (PBL) and near the surface; however, little attention has been paid to other sources of error such as chemistry, spatial representation, and retrieval uncertainties. Here we leverage a wide spectrum of tools and data to quantify those errors carefully. Concerning the chemistry error, a well-characterized box model constrained by more than 500 h of aircraft data from NASA's air quality campaigns is used to simulate the ratio of the chemical loss of HO 2 + RO 2 (LROx) to the chemical loss of NO x (LNOx). Subsequently, we challenge the predictive power of HCHO/NO2 ratios (FNRs), which are commonly applied in current research, in detecting the underlying ozone regimes by comparing them to LROx/LNOx. FNRs show a strongly linear (R2=0.94) relationship with LROx/LNOx , but only on the logarithmic scale. Following the baseline (i.e., ln(LROx/LNOx) = - 1.0 ± 0.2) with the model and mechanism (CB06, r2) used for segregating NOx -sensitive from VOC-sensitive regimes, we observe a broad range of FNR thresholds ranging from 1 to 4. The transitioning ratios strictly follow a Gaussian distribution with a mean and standard deviation of 1.8 and 0.4, respectively. This implies that the FNR has an inherent 20 % standard error (1σ) resulting from not accurately describing the ROx – HOx cycle. We calculate high ozone production rates (PO 3) dominated by large HCHO × NO 2 concentration levels, a new proxy for the abundance of ozone precursors. The relationship between PO 3 and HCHO × NO 2 becomes more pronounced when moving towards NOx -sensitive regions due to nonlinear chemistry; our results indicate that there is fruitful information in the HCHO × NO 2 metric that has not been utilized in ozone studies. The vast amount of vertical information on HCHO and NO 2 concentrations from the air quality campaigns enables us to parameterize the vertical shapes of FNRs using a second-order rational function permitting an analytical solution for an altitude adjustment factor to partition the tropospheric columns into the PBL region. We propose a mathematical solution to the spatial representation error based on modeling isotropic semivariograms. Based on summertime-averaged data, the Ozone Monitoring Instrument (OMI) loses 12 % of its spatial information at its native resolution with respect to a high-resolution sensor like the TROPOspheric Monitoring Instrument (TROPOMI) (> 5.5 × 3.5 km 2). A pixel with a grid size of 216 km 2 fails at capturing ∼ 65 % of the spatial information in FNRs at a 50 km length scale comparable to the size of a large urban center (e.g., Los Angeles). We ultimately leverage a large suite of in situ and ground-based remote sensing measurements to draw the error distributions of daily TROPOMI and OMI tropospheric NO 2 and HCHO columns. At a 68 % confidence interval (1σ), errors pertaining to daily TROPOMI observations, either HCHO or tropospheric NO 2 columns, should be above 1.2–1.5 × 10 16 molec. cm -2 to attain a 20 %–30 % standard error in the ratio. This level of error is almost non-achievable with the OMI given its large error in HCHO. The satellite column retrieval error is the largest contributor to the total error (40 %–90 %) in the FNRs. Due to a stronger signal in cities, the total relative error (< 50 %) tends to be mild, whereas areas with low vegetation and anthropogenic sources (e.g., the Rocky Mountains) are markedly uncertain (> 100 %). Our study suggests that continuing development in the retrieval algorithm and sensor design and calibration is essential to be able to advance the application of FNRs beyond a qualitative metric. [ABSTRACT FROM AUTHOR]

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Carbon monoxide (CO), acetylene (C2H2), ethane (C2H6), formaldehyde (H2CO), and hydrogen cyanide (HCN) are important trace gases in the atmosphere. They are highly related to biomass burning, fossil fuel combustion, and biogenic emissions globally, affecting air quality and climate change. However, the variations and correlations among these species are not well known in North China, due to limited measurements. In June 2018, we installed a new ground-based Fourier-transform infrared (FTIR) spectrometer (Bruker IFS 125HR) recording mid-infrared high spectral resolution solar-absorption spectra at Xianghe (39.75° N, 116.96° E), China. In this study, we use the latest SFIT4 code, together with advanced a priori profile and spectroscopy, to retrieve these five species from the FTIR spectra measured between June 2018 and November 2021. The retrieval strategies, retrieval information, and retrieval uncertainties are presented and discussed. For the first time, the time series, variations, and correlations of these five species are analyzed at a typical polluted site in North China. The seasonal variations of C2H2 and C2H6 total columns show a maximum in winter-spring and a minimum in autumn, whereas the seasonal variations of H2CO and HCN show a maximum in summer and a minimum in winter. Unlike the other four species, the FTIR measurements show that there is almost no seasonal variation in the CO column. The correlation coefficients (R) between the synoptic variations of CO and the other four species (C2H2, C2H6, H2CO, and HCN) are between 0.68 and 0.80, indicating that they are affected by common sources. Using the FLEXPART model backward simulations and satellite fire measurements, we find that the variations of CO, C2H2, C2H6, and H2CO columns are mainly dominated by the local anthropogenic emissions, while HCN column observed at Xianghe is a good tracer to identify fire emissions. [ABSTRACT FROM AUTHOR]