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The Arctic and boreal regions are experiencing a rapid increase in temperature, resulting in a changing cryosphere, increasing human activity, and potentially increasing high-latitude methane emissions. Satellite observations from Sentinel-5P TROPOMI provide an unprecedented coverage of a column-averaged dry-air mole fraction of methane (XCH4) in the Arctic, compared to previous missions or in situ measurements. The purpose of this study is to support and enhance the data used for high-latitude research through presenting a systematic evaluation of TROPOMI methane products derived from two different processing algorithms: the operational product (OPER) and the scientific product (WFMD), including the comparison of recent version changes of the products (OPER, OPER rpro, WFMD v1.2, and WFMD v1.8). One finding is that OPER rpro yields lower XCH4 than WFMD v1.8, the difference increasing towards the highest latitudes. TROPOMI product differences were evaluated with respect to ground-based high-latitude references, including four Fourier Transform Spectrometer in the Total Carbon Column Observing Network (TCCON) and five EM27/SUN instruments in the Collaborative Carbon Column Observing Network (COCCON). The mean TROPOMI–TCCON GGG2020 daily median XCH4 difference was site-dependent and varied for OPER rpro from −0.47 ppb to 22.4 ppb, and for WFMD v1.8 from 1.2 ppb to 19.4 ppb with standard deviations between 13.0 and 20.4 ppb and 12.5–15.0 ppb, respectively. The TROPOMI–COCCON daily median XCH4 difference varied from −26.5 ppb to 5.6 ppb for OPER rpro, with a standard deviation of 14.0–28.7 ppb, and from −5.0 ppb to 17.2 ppb for WFMD v1.8, with a standard deviation of 11.5–13.0 ppb. Although the accuracy and precision of both TROPOMI products are, on average, good compared to the TCCON and COCCON, a persistent seasonal bias in TROPOMI XCH4 (high values in spring; low values in autumn) is found for OPER rpro and is reflected in the higher standard deviation values. A systematic decrease of about 7 ppb was found between TCCON GGG2014 and GGG2020 product update highlighting the importance of also ensuring the reliability of ground-based retrievals. Comparisons to atmospheric profile measurements with AirCore carried out in Sodankylä, Northern Finland, resulted in XCH4 differences comparable to or smaller than those from ground-based remote sensing. [ABSTRACT FROM AUTHOR]

Despite the importance of understanding the urban emission characteristics of greenhouse gases (GHGs) and air pollutants, few studies have conducted integrated assessments across diverse urban environments. Herein, we conducted a comprehensive evaluation of the emission characteristics of GHGs and air pollutants in seven cities in the Northern Hemisphere using ground‐based Fourier transform spectrometers. Our analysis primarily focused on emission ratios of excess column‐averaged dry‐air mole fractions of carbon monoxide (CO) to carbon dioxide (CO2) (∆XCO:∆XCO2) and those of methane (CH4) to CO2 (∆XCH4:∆XCO2). We found that the emission ratios varied significantly across cities. Xianghe (China) and Pasadena (USA), known for severe air pollution, showed the highest emission ratios. Notably, Seoul (South Korea) showed lower ∆XCO:∆XCO2 (3.32 ± 0.10 ppb/ppm) but relatively higher ∆XCH4:∆XCO2 (4.85 ± 0.04 ppb/ppm), which was comparable to the ∆XCH4:∆XCO2 value of Xianghe (5.15 ± 0.10 ppb/ppm), suggesting that targeted CH4 reduction strategies may be required for climate change mitigation in Seoul. Plain Language Summary: Many cities experience significant greenhouse gas and air pollutant emissions. We comprehensively analyzed the characteristics of these emissions using ground‐based solar‐viewing Fourier transform spectrometers (FTSs) in Northern Hemisphere cities including Seoul (South Korea), Thessaloniki (Greece), Tsukuba (Japan), Karlsruhe (Germany), Xianghe (China), Pasadena (USA), and Paris (France). First, we focused on variations in carbon dioxide (CO2), methane (CH4), and carbon monoxide (CO). Based on these variations, their emission ratios were estimated in terms of excess column‐averaged dry‐air mole fractions of CO to CO2 (∆XCO:∆XCO2) and CH4 to CO2 (∆XCH4:∆XCO2) in urban sites. We found that the emission ratios differed across cities. For example, Xianghe and Pasadena, which generally exhibit high levels of air pollution, had the highest emission ratios. However, Seoul had lower emission ratios of ∆XCO:∆XCO2, but higher levels of ∆XCH4:∆XCO2. This study suggests that ground‐based Fourier transform spectrometer measurements can be used as a tool for comprehensively evaluating the emission characteristics of greenhouse gases and air pollutants in urban environments. Furthermore, extending our study to longer periods and more sites could further aid in formulating effective mitigation strategies for climate change. Key Points: We comprehensively assessed the emission characteristics of greenhouse gases and air pollutants in seven cities in the Northern HemisphereGround‐based Fourier transform spectrometers offers a comprehensive analysis of the urban emission characteristics of greenhouse gases and air pollutantsOur results can further support effective strategies for mitigating climate change [ABSTRACT FROM AUTHOR]

To fight climate change, it is crucial to have a precise knowledge of greenhouse gas (GHG) concentrations in the atmosphere and to monitor sources and sinks of GHGs. On global scales, satellites are an appropriate monitoring tool. For the validation of the satellite measurements and to tie them to the World Meteorological Organization (WMO) trace gas scale, ground-based Fourier transform infrared (FTIR) networks are used, which provide reference data. To ensure the highest-quality validation data, the network must be scaled to the WMO trace gas scale and have a very small site-to-site bias. Currently, the Total Carbon Column Observing Network (TCCON) is the de facto standard FTIR network for providing reference data. Ensuring a small site-to-site bias is a major challenge for the TCCON. In this work, we describe the development and application of a new method to evaluate the site-to-site bias by using a remotely controlled portable FTIR spectrometer as a travel standard (TS) for evaluating the consistency of columnar GHG measurements performed at different TCCON stations, and we describe campaign results for the TCCON sites in Tsukuba (Japan), East Trout Lake (Canada) and Wollongong (Australia). The TS is based on a characterized portable EM27/SUN FTIR spectrometer equipped with an accurate pressure sensor which is operated in an automated enclosure. The EM27/SUN is the standard instrument of the Collaborative Carbon Column Observing Network (COCCON). The COCCON is designed such that all spectrometers are referenced to a common reference unit located in Karlsruhe, Germany. To evaluate the long-term stability of the TS instrument, it is placed side-by-side with the TCCON instrument in Karlsruhe (KA) and the COCCON reference unit (the EM27/SUN spectrometer SN37, which is operated permanently next to the TCCON-KA site) between deployments to collect comparing measurements. At each of the visited TCCON sites, the TCCON spectrometers collected low-resolution (LR) (0.5 cm-1) and high-resolution (HR) (0.02 cm-1) measurements in an alternating manner. Based on the TS as a portable standard, the measurements are compared to the Karlsruhe site as a common reference. For Tsukuba and Wollongong, the agreement with the reference in Karlsruhe found for XCO2 is on the 0.1 % level for both the LR and HR measurements. For XCH4 , the agreement is at the 0.2 % level, with the low-resolution measurements showing a low bias at both sites and for both gases. For XCO , the deviations are up to 7 %. The reason for this is likely to be a known issue with the CO a priori profiles used by the TCCON over source regions. In East Trout Lake (ETL), the TCCON spectrometer broke down while the TS was en route to the station. Hence, no side-by-side comparison was possible there. An important auxiliary value for FTIR retrievals is the surface pressure. Using the pressure sensor in the TS, the surface pressure measurements at each site are also compared. The surface pressure analysis reveals excellent agreement (0.027, 0.135 and 0.094 hPa) for the Tsukuba, ETL and Wollongong sites. [ABSTRACT FROM AUTHOR]

China stands out as a major contributor to anthropogenic methane (CH 4) emissions, with coal mine methane (CMM) playing a crucial role. To control and reduce CH 4 emissions, China has made a dedicated commitment and formulated an ambitious mitigation plan. To verify the progress made, the consistent acquisition of independent CH 4 emission data is required. This paper aims to implement a wind-assigned anomaly method for the precise determination of regional-scale CMM emissions within the coal-rich Shanxi province. We use the TROPOspheric Monitoring Instrument (TROPOMI) CH 4 observations from May 2018 to May 2023, coupled with ERA5 wind and a bottom-up inventory dataset based on the IPCC (Intergovernmental Panel on Climate Change) Tier 2 approach covering the Changzhi, Jincheng, and Yangquan regions of the Shanxi province. The derived emission strengths are 8.4 × 10 26 molec. s -1 (0.706 Tg yr -1 , ± 25 %), 1.4 × 10 27 molec. s -1 (1.176 Tg yr -1 , ± 20 %), and 4.9 × 10 26 molec. s -1 (0.412 Tg yr -1 , ± 21 %), respectively. Our results exhibit biases of - 18 %, 8 %, and 14 %, respectively, when compared to the IPCC Tier 2 bottom-up inventory. Larger discrepancies are found when comparing the estimates to the Copernicus Atmosphere Monitoring Service global anthropogenic emissions (CAMS-GLOB-ANT) and Emissions Database for Global Atmospheric Research (EDGARv7.0) inventories (64 %–176 %), suggesting that the two inventories may be overestimating CH 4 emissions from the studied coal mining regions. Our estimates provide a comprehensive characterization of the regions within the Shanxi province, contribute to the validation of emission inventories, and provide additional insights into CMM emission mitigation. [ABSTRACT FROM AUTHOR]

We describe a method for removing systematic biases of column-averaged dry air mole fractions of CO2 (XCO2) and CH4 (XCH4) derived from short-wavelength infrared (SWIR) spectra of the Greenhouse gases Observing SATellite (GOSAT). We conduct correlation analyses between the GOSAT biases and simultaneously retrieved auxiliary parameters. We use these correlations to bias correct the GOSAT data, removing these spurious correlations. Data from the Total Carbon Column Observing Network (TCCON) were used as reference values for this regression analysis. To evaluate the effectiveness of this correction method, the tnzuncorrected/corrected GOSAT data were compared to independent XCO2 and XCH4 data derived from aircraft measurements taken for the Comprehensive Observation Network for TRace gases by AIrLiner (CONTRAIL) project, the National Oceanic and Atmospheric Administration (NOAA), the US Department of Energy (DOE), the National Institute for Environmental Studies (NIES), the Japan Meteorological Agency (JMA), the HIAPER Pole-to-Pole observations (HIPPO) program, and the GOSAT validation aircraft observation campaign over Japan. These comparisons demonstrate that the empirically derived bias correction improves the agreement between GOSAT XCO2/XCH4 and the aircraft data. Finally, we present spatial distributions and temporal variations of the derived GOSAT biases.

Precise estimates of greenhouse gas (GHG) emissions and sinks are critical for understanding the carbon cycle and identifying key factors in the human-induced climate change feedback. Recent efforts were focused on reconciling bottom-up and top-down GHG emissions estimates, in particular on the city scale, using both space-based and ground-based atmospheric composition measurements that still show serious discrepancies. In this study, we explore the variability of the CO and CO2 emissions from the Mexico City Metropolitan Area (MCMA) from long-term time-resolved total column measurements using solar absorption Fourier Transform Infrared Spectroscopy (FTIR). Measurements were performed at three stations, two of them located in the urban area at two opposite sides of Mexico City center and the third in a mountainous background site. Using a simple model and the mixed layer height from a ceilometer, the GHG concentration in the mixed layer and the CO/CO2 ratio were determined from the total column observations and compared to surface measurements using Cavity ring-down spectroscopy (CRDS). Finally, combining the ground-based total column and space-based TROPOMI CO measurements, we estimate the annual CO and CO2 MCMA emissions based on a simple model, i.e.: without recourse to complex transport models. By this way, we study the inter-annual variability of the CO and CO2 MCMA anthropogenic emissions, and relate it to the main natural or anthropogenic changes occurring during the last decade, such as the 2015–2016 El Niño period or the COVID-19 lock-down event. [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]

To fight climate change it is crucial to have a precise knowledge of Greenhouse Gas (GHG) concentrations in the atmosphere and to monitor sources and sinks of GHGs. On global scales, satellites are an appropriate monitoring tool. For the validation of the satellite measurements, and to tie them to the World Meteorological Organization (WMO) trace gas scale, ground based Fourier Transform Infrared (FTIR) networks are used, which provide reference data. To ensure the highest quality validation data, the network must be scaled to the WMO trace gas scale and have a very small site-to-site bias. Currently, the Total Carbon Column Observing Network (TCCON) is the de-facto standard FTIR network for providing reference data. To ensure a small site-to-site bias is a major challenge for the TCCON. In this work we describe the development and application of a new method to evaluate the site-to-site bias by using a remotely controlled portable FTIR spectrometer as a Travel Standard (TS) for evaluating the consistency of columnar GHG measurements performed at different TCCON stations and we describe campaign results for the TCCON sites in Tsukuba (Japan), East Trout Lake (Canada) and Wollongong (Australia). The TS is based on a characterized portable EM27/SUN FTIR spectrometer equipped with an accurate pressure sensor which is operated in an automated enclosure. The EM27/SUN is the standard instrument of the Collaborative Carbon Column Observing Network (COCCON). The COCCON is designed such that all spectrometers are referenced to a common reference unit located in Karlsruhe, Germany. To evaluate the long-term stability of the TS instrument, it is placed side-by-side with the TCCON instrument in Karlsruhe and the COCCON reference unit (the EM27/SUN spectrometer SN37, which is operated permanently next to the TCCON-KA site) between deployments to collect comparing measurements. At each of the visited TCCON sites, the TCCON spectrometers collected low-resolution (LR) (0.5 cm-1) and high-resolution (HR) (0.02 cm-1) measurements in an alternating manner. In East Trout Lake (ETL), the TCCON spectrometer broke down while the TS was en route to the station. Hence, no side-by-side comparison was possible there. For Tsukuba and Wollongong the agreement found for XCO2 is on the 0.1 % level. For XCH4 the agreement is at the 0.2 % level, with the low-resolution measurements showing a low bias at both sites and for both gases. For XCO the deviations are up to 7 %. The reason for this is likely to be an known issue with the CO a priori profiles used by TCCON over source regions. The pressure analysis reveals excellent agreement (0.027 hPa, 0.135 hPa, and 0.094 hPa) for the Tsukuba, ETL, and Wollongong sites. [ABSTRACT FROM AUTHOR]

Monitoring the atmospheric concentrations of the greenhouse gases (GHG) carbon dioxide (CO2) and methane (CH4) is a key ingredient for fostering our understanding of the mechanisms behind the sources and sinks of these gases and for verifying and quantitatively attributing their anthropogenic emissions. Here, we present the instrumental setup and performance evaluation of an open-path GHG observatory in the city of Heidelberg, Germany. The observatory measures path-averaged concentrations of CO2 and CH4 along a 1.55 km path in the urban boundary layer above the city. We combine these open-path data with local in situ measurements to evaluate the representativeness of these observation types on the kilometer scale. This representativeness is necessary to accurately quantify emissions, since atmospheric models tasked with this job typically operate on kilometer-scale horizontal grids. For the operational period between 8 February and 11 July 2023, we find a precision of 2.7 ppm (0.58 %) and 18 ppb (0.89 %) for the dry-air mole fractions of CO2 (xCO2) and CH4 (xCH4) in 5 min measurements, respectively. After bias correction, the open-path measurements show excellent agreement with the local in situ data under atmospheric background conditions. Both datasets show clear signals of traffic CO2 emissions in the diurnal xCO2 cycle. However, there are particular situations, such as under southeasterly wind conditions, in which the in situ and open-path data reveal distinct differences up to 20 ppm in xCO2 , most likely related to their different sensitivity to local emission and transport patterns. Our setup is based on a Bruker IFS 125HR Fourier transform spectrometer, which offers a spacious and modular design providing ample opportunities for future refinements of the technique with respect to finer spectral resolution and wider spectral coverage to provide information on gases such as carbon monoxide and nitrogen dioxide. [ABSTRACT FROM AUTHOR]

Urban areas are responsible for more than 40 % of global energy-related carbon dioxide (CO 2) emissions. The Tokyo metropolitan area (TMA), Japan, one of the most populated regions in the world, includes various emission sources, such as thermal power plants, automobile traffic, and residential facilities. In order to infer a top–down emission estimate, we conducted an intensive field campaign in the TMA from February to April 2016 to measure column-averaged dry-air mole fractions of CO 2 (XCO 2) with three ground-based Fourier transform spectrometers (one IFS 125HR and two EM27/SUN spectrometers). At two urban sites (Saitama and Sodegaura), measured XCO 2 values were generally larger than those at a rural site (Tsukuba) by up to 9.5 ppm, and average diurnal variations increased toward evening. To simulate the XCO 2 enhancement (Δ XCO 2) resulting from emissions at each observation site, we used the Stochastic Time-Inverted Lagrangian Transport (STILT) model driven by meteorological fields at a horizontal resolution of ∼1 km from the Weather Research and Forecasting (WRF) model, which was coupled with anthropogenic (large point source and area source) CO 2 emissions and biogenic fluxes. Although some of the diurnal variation of Δ XCO 2 was not reproduced and plumes from nearby large point sources were not captured, primarily because of a transport modeling error, the WRF–STILT simulations using prior fluxes were generally in good agreement with the observations (mean bias, 0.30 ppm; standard deviation, 1.31 ppm). By combining observations with high-resolution modeling, we developed an urban-scale inversion system in which spatially resolved CO 2 emission fluxes at >3 km resolution and a scaling factor of large point source emissions were estimated on a monthly basis by using Bayesian inference. The XCO 2 simulation results from the posterior CO 2 fluxes were improved (mean bias, -0.03 ppm; standard deviation, 1.21 ppm). The prior and posterior total CO 2 emissions in the TMA are 1.026 ± 0.116 and 1.037 ± 0.054 Mt-CO 2 d -1 at the 95 % confidence level, respectively. The posterior total CO 2 emissions agreed with emission inventories within the posterior uncertainty, demonstrating that the EM27/SUN spectrometer data can constrain urban-scale monthly CO 2 emissions. [ABSTRACT FROM AUTHOR]

The extensive terrestrial ecosystems of tropical Africa are a significant store of carbon, and play a key but uncertain role in the atmospheric budgets of carbon dioxide and methane. As ground-based observations in the tropics are scarce compared with other parts of the world, recent studies have instead made use of satellite observations assimilated into atmospheric chemistry and transport models to conclude that methane emissions from this geographical region have increased since 2010 as a result of increased wetland extent, accounting for up to a third of global methane growth, and that the tropical Africa region dominates net carbon emission across the tropics. These studies rely critically on the accuracy of satellite datasets such as those from OCO-2, GOSAT, and Sentinel-5P TROPOMI, along with results from atmospheric transport models, over a geographical region where there are few independent data to test the robustness of published results. In this paper we present the first ground-based observations of greenhouse gas column concentrations over East Africa, obtained using a portable Bruker EM27/SUN FTIR spectrometer during a deployment covering the first few months of 2020 in Jinja, Uganda. We operated the instrument near-autonomously by way of an automated weatherproof enclosure, and observed total atmospheric column concentrations of the greenhouse gases carbon dioxide and methane, as well as carbon monoxide, a useful proxy for emissions from incomplete combustion processes in the region. We discuss the performance of the combined enclosure and spectrometer system that we deployed in Jinja to obtain this data, and show comparisons of our ground-based observations with satellite datasets from OCO-2 and OCO-3 for carbon dioxide, and Sentinel-5P TROPOMI for methane and carbon monoxide, whilst also comparing our results with concentration data from the GEOS-Chem and CAMS atmospheric inversions that provide a means of increasing spatial and temporal coverage where satellite data are not available. For our measurement period, we find statistically significant differences at the 95% confidence level between the EM27/SUN and OCO-2 XCO2 (OCO-2 lower by a mean of 1.20ppm, standard deviation 1.05ppm), and between the EM27/SUN and Sentinel-5P XCO (Sentinel-5P lower by a mean of 3.68ppb, standard deviation 7.00ppb), whilst we found that the differ-ences between the EM27/SUN and OCO-3 XCO2 (OCO-3 lower by a mean of 1.15ppm, standard deviation 1.61ppm), and between the EM27/SUN and Sentinel-5P XCH4 (Sentinel-5P lower by a mean of 8.33ppb, standard deviation 10.5ppb), were not statistically significant. With regards to the model comparisons, we also see statistically significant differences between the EM27/SUN and a global GEOS-Chem inversion for XCO2 (GEOS-Chem lower by a mean of 0.35ppm, standard deviation 1.08ppm), between the EM27/SUN and a high-resolution GEOS-Chem inversion for XCH4 (GEOS-Chem lower by a mean of 3.80ppb, standard deviation 12.5ppb), and between the EM27/SUN and CAMS global analysis XCO (CAMS lower by a mean of 11.7ppb, standard deviation 8.94ppb). Our results demonstrate the value of ground-based observations of total column concentrations, and show that the combined EM27/SUN and enclosure system employed would be suitable for acquisition of the longer-term observations needed to rigorously evaluate satellite observations and model calculations over tropical Africa. [ABSTRACT FROM AUTHOR]

Satellite-based observations of free tropospheric water vapour isotopologue ratios (δ D) with good global and temporal coverage have become recently available. We investigate the potential of these observations for constraining the uncertainties of the atmospheric analyses fields of specific humidity (q), temperature (T), and δ D and of variables that capture important properties of the atmospheric water cycle, namely the vertical velocity (ω), the latent heating rate (Q 2), and the precipitation rate (Prcp). Our focus is on the impact of the δ D observations if used in addition to the observation of q and T , which are much easier to be observed by satellites and routinely in use for atmospheric analyses. For our investigations we use an Observing System Simulation Experiment, i.e. simulate the satellite observations of q , T , and δ D with known uncertainties, then use them within a Kalman filter based assimilation framework in order to evaluate their potential for improving the quality of atmospheric analyses. The study is made for low latitudes (30° S to 30° N) and for 40 days between mid-July and end of August 2016. We find that the assimilation of q and T observations alone well constrains the atmospheric q and T fields (analyses skills in the free troposphere of up to 60 %), and moderately constrains the fields of δ D, ω , Q 2, and Prcp (analyses skills of 20 %–40 %). The additional assimilation of δ D observations further improves the quality of the analyses of all variables. We use Q 2 as proxy for the presence of condensation and evaporation processes, and we show that the additional improvement is rather weak when evaporation or condensation are negligible (additional analyses skills of generally below 5 %), and strongest for high condensation rates (additional skills of about 15 % and above). The very high condensation rates (identified by large positive Q 2 values) are rare, but related to extreme events (very high ω and Prcp) that are not well captured in the analyses (for these extreme events also the analyses uncertainties of ω , Q 2, and Prcp are very large), i.e. the additional assimilation of δ D observations significantly improves the analyses of the water cycle related variables for the events when an improvement is most important. In real world satellite datasets δ D observations affected by such strong latent heating events are frequently available, suggesting that the here demonstrated additional δ D impact for the simulated world is also a realistic scenario for a real world data assimilation. [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]

China stands out as a major contributor to anthropogenic methane (CH4) emissions, with coal mine methane (CMM) playing a crucial role. To control and reduce CH4 emissions, China has made a dedicated commitment and formulated an ambitious mitigation plan. To verify the process made, the consistent acquisition of independent CH4 emission data is required. This paper aims to implement a wind-assigned anomaly method for the precise determination of regional-scale CMM emissions within the coal-rich Shanxi province. We use the TROPOspheric Monitoring Instrument (TROPOMI) CH4 observations from May 2018 to May 2023, coupled with ERA5 wind covering the Changzhi, Jincheng and Yangquan regions. The derived emission strengths are 8.4× 1026 ± 1.6 × 1025 molec. s-1 (0.706 ± 0.013 Tg yr-1), 1.4 × 1027 ± 1.9 × 1025 molec. s-1 (1.176 ± 0.016 Tg yr-1), and 4.9 × 1026± 1.8 × 1025 molec. s-1 (0.412 ± 0.015 Tg yr-1), respectively. Our results exhibit biases of -18 %, 8 %, and 14 % when compared to the bottom-up inventory. Larger discrepancies are found when comparing the estimates to the CAMS-GLOB-ANT and EDGARv7.0 inventories. This suggests that the two inventories may be overestimating the CH4 emissions in the Jincheng and Yangquan regions. Our estimates provide a comprehensive characterization of the regions within the Shanxi province, contribute to the validation of emission inventories, and help to develop climate mitigation strategies. [ABSTRACT FROM AUTHOR]

China stands out as a major contributor to anthropogenic methane (CH4) emissions, with coal mine methane (CMM) playing a crucial role. To control and reduce CH4 emissions, China has made a dedicated commitment and formulated an ambitious mitigation plan. To verify the process made, the consistent acquisition of independent CH4 emission data is required. This paper aims to implement a wind-assigned anomaly method for the precise determination of regional-scale CMM emissions within the coal-rich Shanxi province. We use the TROPOspheric Monitoring Instrument (TROPOMI) CH4 observations from May 2018 to May 2023, coupled with ERA5 wind covering the Changzhi, Jincheng and Yangquan regions. The derived emission strengths are 8.4× 1026 ± 1.6 × 1025 molec. s-1 (0.706 ± 0.013 Tg yr-1), 1.4 × 1027 ± 1.9 × 1025 molec. s-1 (1.176 ± 0.016 Tg yr-1), and 4.9 × 1026± 1.8 × 1025 molec. s-1 (0.412 ± 0.015 Tg yr-1), respectively. Our results exhibit biases of -18%, 8%, and 14% when compared to the bottom-up inventory. Larger discrepancies are found when comparing the estimates to the CAMS-GLOB-ANT and EDGARv7.0 inventories. This suggests that the two inventories may be overestimating the CH4 emissions in the Jincheng and Yangquan regions. Our estimates provide a comprehensive characterization of the regions within the Shanxi province, contribute to the validation of emission inventories, and help to develop climate mitigation strategies. [ABSTRACT FROM AUTHOR]