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The growth-associated protein GAP-43 (B-50) and the transcription factor C-Jun are involved in regeneration of the injured nervous system. In this study, we investigated the possibility of the induction of GAP-43 and C-Jun in axotomized neurons of Clarke's nucleus (CN) in adult rats, of which a large population undergoes degeneration several weeks after a low thoracic lateral funiculotomy of the spinal cord.In situhybridization and immunohistochemistry revealed a transient up-regulation of GAP-43 mRNA, C-Jun protein, and its activated, phosphorylated form, peaking around 7 days after injury in preferentially large diameter CN-neurons ipsilateral and caudal to the lesion. Our results document that some populations of axotomized central nervous system neurons, similar to axotomized regenerating neurons of the peripheral nervous system, can up-regulate GAP-43 and C-Jun, even if they are destined to degenerate. This might reflect a transient regenerative capacity, which fails over time.

This study describes the digitization and calibration of historically significant solar absorption spectra recorded at the Jungfraujoch International Scientific Station in the 1950s. Using a homemade Pfund-type grating spectrometer, these spectra were recorded on paper rolls to study the solar spectrum which was then used to compile a solar atlas between 2.8 and 23.7 µm (421 to 3571 cm−1) that, in particular, later contributed to the development of the HITRAN (High-Resolution Transmission Molecular Absorption Database) database. We have now digitized these analogue recorded spectra to make them available for atmospheric studies. Our approach involves image-processing techniques, including colour masking for digitization and peak detection for accurate wavenumber calibration against a synthetic spectrum. We have also developed a validation method by re-digitizing degraded Fourier transform infrared (FTIR) spectra to the same resolution as the old spectra to evaluate the digitization accuracy. Furthermore, we have studied the influence of line thickness on the digitization error. The number of spectra transformed into a machine-readable format is 106 (freely available for download), with an average digitization error of 1.55 % and a wavenumber shift standard deviation of 0.075 cm −1. These digitized and calibrated spectra now offer a valuable resource for atmospheric studies, providing essential historical data for atmospheric research. This work not only helps to preserve scientific heritage but also enhances the utility of historical data in contemporary research.

Axons undergo Wallerian degeneration distal to a point of injury. Experimental investigations have documented many of the cellular and molecular events that underlie this behaviour. Since relatively little is known about such events in human CNS pathologies and current experimental intervention strategies indicate the possibility of significant axon regeneration along the original degenerated fibre tract, we performed an immunohistochemical investigation of the dynamics of Wallerian degeneration in post mortem spinal cords of patients who died 2 days to 30 years after either cerebral infarction or traumatic spinal cord injury. Neurofilament (NF) staining demonstrated a spatio-temporal pattern of axonal loss within degenerating descending nerve fibre tracts that could be detected close to the lesion as early as 12 days after injury and progressed to an almost complete loss of NF immunoreactivity at survival times of 1 year and longer. Immunohistochemistry for glial fibrillary acidic protein revealed a late astrocytic reaction starting at 4 months after injury in the degenerating tracts, leading to the long-term deposition of a dense astrocytic scar. These events were accompanied by the gradual reduction of myelin basic protein in affected nerve fibre tracts, leading to almost complete loss by 3 years after injury. Since the extracellular matrix molecule chondroitin sulphate proteoglycan (CSPG) is known to be strongly inhibitory for axonal regeneration and to be a major component of gliotic scar tissues, we investigated the possible deposition of CSPG within the degenerating nerve fibre tracts. Apart from a local up-regulation close to the lesion site, our results show no enhanced CSPG expression within degenerated tracts at any survival time. This suggests that despite the apparent lack of CSPG in Wallerian degeneration, the slow reduction of CNS myelin and the long-term deposition of a dense astrocytic scar may present an environment that is non-supportive for axon regrowth

Soil carbon monoxide (CO) fluxes represent a net balance between biological soil CO uptake and abiotic soil and (senescent) plant CO production. Studies largely from temperate and boreal forests indicate that soils serve as a net sink for CO, but uncertainty remains about the role of tropical rainforest soils to date. Here we report the first direct measurements of soil CO fluxes in a tropical rainforest and compare them with estimates of net ecosystem CO fluxes derived from accumulation of CO at night under stable atmospheric conditions. Furthermore, we used laboratory experiments to demonstrate the importance of temperature on net soil CO fluxes. Net soil surface CO fluxes ranged from −0.19 to 3.36 nmol m−2 s−1, averaging ∼1 nmol CO m−2 s−1. Fluxes varied with season and topographic location, with the highest fluxes measured in the dry season in a seasonally inundated valley. Ecosystem CO fluxes estimated from nocturnal canopy air profiles, which showed CO mixing ratios that consistently decreased with height, ranged between 0.3 and 2.0 nmol CO m−2 s−1. A canopy layer budget method, using the nocturnal increase in CO, estimated similar flux magnitudes (1.1 to 2.3 nmol CO m−2 s−1). In the wet season, a greater valley ecosystem CO production was observed in comparison to measured soil valley CO fluxes, suggesting a contribution of the valley stream to overall CO emissions. Laboratory incubations demonstrated a clear increase in CO production with temperature that was also observed in field fluxes, though high correlations between soil temperature and moisture limit our ability to interpret the field relationship. At a common temperature (25 °C), expected plateau and valley senescent-leaf CO production was small (0.012 and 0.002 nmol CO m−2 s−1) in comparison to expected soil material CO emissions (∼ 0.9 nmol CO m−2 s−1). Based on our field and laboratory observations, we expect that tropical rainforest ecosystems are a net source of CO, with thermal-degradation-induced soil emissions likely being the main contributor to ecosystem CO emissions. Extrapolating our first observation-based tropical rainforest soil emission estimate of ∼ 1 nmol m−2 s−1, global tropical rainforest soil emissions of ∼ 16.0 Tg CO yr−1 are estimated. Nevertheless, total ecosystem CO emissions might be higher, since valley streams and inundated areas might represent local CO emission hot spots. To further improve tropical forest ecosystem CO emission estimates, more in situ tropical forest soil and ecosystem CO flux measurements are essential.

The Total Carbon Column Observing Network (TCCON) measures column-average mole fractions of several greenhouse gases (GHGs), beginning in 2004, from over 30 current or past measurement sites around the world using solar absorption spectroscopy in the near-infrared (near-IR) region. TCCON GHG data have been used extensively for multiple purposes, including in studies of the carbon cycle and anthropogenic emissions, as well as to validate and improve observations from space-based sensors. Here, we describe an update to the retrieval algorithm used to process the TCCON near-IR solar spectra and to generate the associated data products. This version, called GGG2020, was initially released in April 2022. It includes updates and improvements to all steps of the retrieval, including but not limited to the conversion of the original interferograms into spectra, the spectroscopic information used in the column retrieval, post hoc air mass dependence correction, and scaling to align with the calibration scales of in situ GHG measurements. All TCCON data are available through https://tccondata.org/ (last access: 22 April 2024) and are hosted on CaltechDATA (https://data.caltech.edu/, last access: 22 April 2024). Each TCCON site has a unique DOI for its data record. An archive of all the sites' data is also available with the DOI https://doi.org/10.14291/TCCON.GGG2020 (Total Carbon Column Observing Network (TCCON) Team, 2022). The hosted files are updated approximately monthly, and TCCON sites are required to deliver data to the archive no later than 1 year after acquisition. Full details of data locations are provided in the “Code and data availability” section.

Satellite gravimetry is used to study the global hydrological cycle. It is a key component in the investigation of groundwater depletion on the Indian subcontinent. Terrestrial mass loss caused by river sediment transport is assumed to be below the detection limit in current gravimetric satellites of the Gravity Recovery and Climate Experiment Follow-On mission. Thus, it is not considered in the calculation of terrestrial water storage (TWS) from such satellite data. However, the Ganges and Brahmaputra rivers, which drain the Indian subcontinent, constitute one of the world's most sediment-rich river systems. In this study, we estimate the impact of sediment mass loss within their catchments on local trends in gravity and consequential estimates of TWS trends. We find that for the Ganges–Brahmaputra–Meghna catchment sediment transport accounts for (4 ± 2) % of the gravity decrease currently attributed to groundwater depletion. The sediment is mainly eroded from the Himalayas, where correction for sediment mass loss reduces the decrease in TWS by 0.22 cm of equivalent water height per year (14 %). However, sediment mass loss in the Brahmaputra catchment is more than twice that in the Ganges catchment, and sediment is mainly eroded from mountain regions. Thus, the impact on gravimetric TWS trends within the Indo–Gangetic Plain – the main region identified for groundwater depletion – is found to be comparatively small (< 2 %).

The tropical western Pacific is recognized as an important region for stratosphere–troposphere exchange but lies in a data-sparse location that had a measurement gap in the global ozone sounding network. The Palau Atmospheric Observatory (PAO, approx. 7.3∘ N, 134.5∘ E) was established to study the atmospheric composition above the remote tropical western Pacific with a comprehensive instrumental setup. Since 2016, two laboratory containers in Palau host a Fourier transform infrared spectrometer; a lidar (micro-lidar until 2016, cloud and aerosol lidar from 2018); a Pandora 2S photometer; and laboratory space for weather balloon soundings with ozone, water vapor, aerosol, and radiosondes. In this analysis, we focus on the continuous, fortnightly ozone sounding program with electrochemical concentration cell (ECC) ozonesondes. The aim of this study is to introduce the PAO and its research potential, present the first observation of the typical seasonal cycle of tropospheric ozone in the tropical western Pacific based on a multiannual record of in situ observations, and investigate major drivers of variability and seasonal variation from January 2016 until December 2021​​​​​​​ related to the large-scale atmospheric circulation. We present the PAO ozone (O3) volume mixing ratios (VMR) and relative humidity (RH) time series complemented by other observations. The site is exposed to year-round high convective activity reflected in dominating low O3 VMR and high RH. In 2016, the impact of the strong El Niño is evident as a particularly dry, ozone-rich episode. The main modulator of annual tropospheric O3 variability is identified as the movement of the Intertropical Convergence Zone (ITCZ), with the lowest O3 VMR in the free troposphere during the ITCZ position north of Palau. An analysis of the relation of O3 and RH for the PAO and selected sites from the Southern Hemispheric Additional Ozonesondes (SHADOZ) network reveals three different regimes. Palau's O3 / RH distribution resembles the one in Fiji, Java and American Samoa but is unique in its seasonality and its comparably narrow Gaussian distribution around low O3 VMR and the evenly distributed RH. A previously found bimodal distribution of O3 VMR and RH could not be seen for the full Palau record but only during specific seasons and years. Due to its unique remote location, Palau is an ideal atmospheric background site to detect changes in air dynamics imprinted on the chemical composition of the tropospheric column. The efforts to establish, run and maintain the PAO have succeeded to fill an observational gap in the remote tropical western Pacific and give good prospects for ongoing operations. The ECC sonde record will be integrated into the SHADOZ database in the near future.

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.

The Tropospheric Monitoring Instrument (TROPOMI) on board the Sentinel-5 Precursor (S5P) satellite is part of the latest generation of trace gas monitoring satellites and provides a new level of spatio-temporal information with daily global coverage, which enables the calculation of daily globally averaged CH4 concentrations. To investigate changes in atmospheric methane, the background CH4 level (i.e. the CH4 concentration without seasonal and short-term variations) has to be determined. CH4 growth rates vary in a complex manner and high-latitude zonal averages may have gaps in the time series, and thus simple fitting methods do not produce reliable results. In this paper we present an approach based on fitting an ensemble of dynamic linear models (DLMs) to TROPOMI data, from which the best model is chosen with the help of cross-validation to prevent overfitting. This method is computationally fast and is not dependent on additional inputs, allowing for fast and continuous analysis of the most recent time series data. We present results of global annual methane increases (AMIs) for the first 4.5 years of S5P/TROPOMI data, which show good agreement with AMIs from other sources. Additionally, we investigated what information can be derived from zonal bands. Due to the fast meridional mixing within hemispheres, we use zonal growth rates instead of AMIs, since they provide a higher temporal resolution. Clear differences can be observed between Northern Hemisphere and Southern Hemisphere growth rates, especially during 2019 and 2022. The growth rates show similar patterns within the hemispheres and show no short-term variations during the years, indicating that air masses within a hemisphere are well-mixed during a year. Additionally, the growth rates derived from S5P/TROPOMI data are largely consistent with growth rates derived from Copernicus Atmospheric Monitoring Service (CAMS) global-inversion-optimized (CAMS/INV) data, which use surface observations. In 2019 a reduction in growth rates can be observed for the Southern Hemisphere, while growth rates in the Northern Hemisphere stay stable or increase. During 2020 a strong increase in Southern Hemisphere growth rates can be observed, which is in accordance with recently reported increases in Southern Hemisphere wetland emissions. In 2022 the reduction in the global AMI can be attributed to decreased growth rates in the Northern Hemisphere, while growth rates in the Southern Hemisphere remain high. Investigations of fluxes from CAMS/INV data support these observations and suggest that the Northern Hemisphere decrease is mainly due to the decrease in anthropogenic fluxes, while in the Southern Hemisphere, wetland fluxes continued to rise. While the continued increase in Southern Hemisphere wetland fluxes agrees with existing studies about the causes of observed methane trends, the difference between Northern Hemisphere and Southern Hemisphere methane increases in 2022 has not been discussed before and calls for further research.

This study evaluates tropospheric columns of methane, carbon monoxide, and ozone in the Arctic simulated by 11 models. The Arctic is warming at nearly 4 times the global average rate, and with changing emissions in and near the region, it is important to understand Arctic atmospheric composition and how it is changing. Both measurements and modelling of air pollution in the Arctic are difficult, making model validation with local measurements valuable. Evaluations are performed using data from five high-latitude ground-based Fourier transform infrared (FTIR) spectrometers in the Network for the Detection of Atmospheric Composition Change (NDACC). The models were selected as part of the 2021 Arctic Monitoring and Assessment Programme (AMAP) report on short-lived climate forcers. This work augments the model–measurement comparisons presented in that report by including a new data source: column-integrated FTIR measurements, whose spatial and temporal footprint is more representative of the free troposphere than in situ and satellite measurements. Mixing ratios of trace gases are modelled at 3-hourly intervals by CESM, CMAM, DEHM, EMEP MSC-W, GEM-MACH, GEOS-Chem, MATCH, MATCH-SALSA, MRI-ESM2, UKESM1, and WRF-Chem for the years 2008, 2009, 2014, and 2015. The comparisons focus on the troposphere (0–7 km partial columns) at Eureka, Canada; Thule, Greenland; Ny Ålesund, Norway; Kiruna, Sweden; and Harestua, Norway. Overall, the models are biased low in the tropospheric column, on average by −9.7 % for CH4, −21 % for CO, and −18 % for O3. Results for CH4 are relatively consistent across the 4 years, whereas CO has a maximum negative bias in the spring and minimum in the summer and O3 has a maximum difference centered around the summer. The average differences for the models are within the FTIR uncertainties for approximately 15 % of the model–location comparisons.

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 (1σ) % 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 (1σ) % 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 (1σ) %, 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.

Two global networks of ground-based Fourier transform spectrometers are measuring abundances of atmospheric trace gases that absorb in the near infrared and mid-infrared: the Network for the Detection of Atmospheric Composition Change (NDACC) and the Total Carbon Column Observing Network (TCCON). The first lacks a CO2 product; therefore, this study focuses on developing an xCO2 retrieval method for NDACC from a spectral window in the 4800 cm−1 region. This retrieval will allow extending ground-based measurements back in time, which we will demonstrate with historical data available from Ny-Ålesund, Svalbard. At this site, both TCCON and NDACC measurements are routinely performed, which is an advantage for collocated comparisons. The results are compared with collocated TCCON measurements of column-averaged dry-air mole fractions of CO2 (denoted by xCO2) in Ny-Ålesund, Svalbard, and only TCCON in Burgos, Philippines. We found that it is possible to retrieve xCO2 from NDACC spectra with a precision of 0.2 %. The comparison between the new retrieval and TCCON showed that the sensitivity of the new retrieval is high in the troposphere and lower in the upper stratosphere, similar to TCCON, as seen in the averaging kernels, and that the seasonality is well captured as seen in the retrieved time series. Additionally, we have included a retrieval strategy suggestion to improve the quality of the xCO2 product.

The tropical western Pacific (TWP) plays an important role in global stratosphere–troposphere exchange and is an active region of the interhemispheric transport (IHT). Common indicators for transport between the hemispheres like the tropical rain belt are too broad or lack precision in the TWP. In this paper, we provide a method to determine the atmospheric chemical equator (CE), which is a boundary for air mass transport between the two hemispheres in the tropics. This method used the model output from an artificial passive tracer simulated by the chemical transport model GEOS-Chem in the troposphere. We investigated the movement of the CE in the tropics, which indicates the migration of atmospheric circulation systems and air mass origins. Our results show the CE on different timescales, suggesting that the different features of the IHT in different regions are highly related to the variation in the circulation systems. We compared the CE with the tropical wind fields, indicating that the region of IHT does not coincide with the convergence of the 10 m wind fields in the tropical land sectors and the TWP region. We compared the CE with the atmospheric composition such as satellite data of CH4 and model simulation of sulfur hexafluoride (SF6). The results show that the CE and north–south gradient of CH4 in the Indian Ocean in January are well consistent with each other, which indicates the CE has good potential to estimate the IHT inferred by observations. We discussed the vertical extent and the meridional extent of the IHT. We find that the vertical structure above 2 km has a slight northern tilt in the Northern Hemisphere (NH) winter season and a southern tilt in the NH summer, meaning the seasonality of the migration of the CE at the lower altitude is larger than that at the higher altitude. The meridional extent of the CE indicates a narrow transition zone where IHT happens throughout the year. We find that the meridional extent above South America is larger compared to other regions. The distribution of the land–sea contrast plays an important role in the meridional extent of IHT. We focus on the TWP region and further compared the tropical rain belt with the CE. There is a broad region of high precipitation occurring in the TWP region, and it is difficult to determine the IHT by the rain belt. In the NH winter, the CE is not consistent with the tropical rain belt in the TWP but is confined to the southern branch of the peak of the rain belt. For the other seasons, both indicators of IHT agree.

Atmospheric carbon dioxide (CO2) accounts for the largest radiative forcing among anthropogenic greenhouse gases. There is, therefore, a pressing need to understand the rate at which CO2 accumulates in the atmosphere, including the interannual variations (IAVs) in this rate. IAV in the CO2 growth rate is a small signal relative to the long-term trend and the mean annual cycle of atmospheric CO2, and IAV is tied to climatic variations that may provide insights into long-term carbon–climate feedbacks. Observations from the Orbiting Carbon Observatory-2 (OCO-2) mission offer a new opportunity to refine our understanding of atmospheric CO2 IAV since the satellite can measure over remote terrestrial regions and the open ocean, where traditional in situ CO2 monitoring is difficult, providing better spatial coverage compared to ground-based monitoring techniques. In this study, we analyze the IAV of column-averaged dry-air CO2 mole fraction (XCO2) from OCO-2 between September 2014 and June 2021. The amplitude of the IAV, which is calculated as the standard deviation of the time series, is up to 1.2 ppm over the continents and around 0.4 ppm over the open ocean. Across all latitudes, the OCO-2-detected XCO2 IAV shows a clear relationship with El Niño–Southern Oscillation (ENSO)-driven variations that originate in the tropics and are transported poleward. Similar, but smoother, zonal patterns of OCO-2 XCO2 IAV time series compared to ground-based in situ observations and with column observations from the Total Carbon Column Observing Network (TCCON) and the Greenhouse Gases Observing Satellite (GOSAT) show that OCO-2 observations can be used reliably to estimate IAV. Furthermore, the extensive spatial coverage of the OCO-2 satellite data leads to smoother IAV time series than those from other datasets, suggesting that OCO-2 provides new capabilities for revealing small IAV signals despite sources of noise and error that are inherent to remote-sensing datasets.

Arctic amplification, the phenomenon that the Arctic is warming faster than the global mean, is still not fully understood. The Transregional Collaborative Research Centre “TRR 172: ArctiC Amplification: Climate Relevant Atmospheric and SurfaCe Processes, and Feedback Mechanisms (AC)3” program, funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation), contributes towards this research topic. For the purpose of measuring aerosol components, a Fourier transform infrared spectrometer (FTIR), for measuring downwelling emission (in operation since 2019), and a Raman lidar are operated at the joint Alfred Wegener Institute for Polar and Marine Research and Paul Emile Victor Institute (AWIPEV) research base in Ny-Ålesund, Spitsbergen (79∘ N, 12∘ E). To carry out aerosol retrieval using measurements from the FTS, the LBLDIS retrieval algorithm, based on a combination of the Line-by-Line Radiative Transfer Model (LBLRTM) and the DIScrete Ordinate Radiative Transfer (DISORT) algorithm, is modified for different aerosol types (dust, sea salt, black carbon, and sulfate), aerosol optical depth (AOD), and effective radius (Reff). Using lidar measurement, an aerosol and cloud classification method is developed to provide basic information about the distribution of aerosols or clouds in the atmosphere and is used as an indicator to perform aerosol or cloud retrievals with the FTS. Therefore, a two-instrument joint-observation scheme is designed and subsequently used on the data measured from 2019 to the present. In order to introduce this measurement technique in detail, an aerosol-only case study is presented using data from 10 June 2020. In the aerosol-only case, the retrieval results show that sulfate is the dominant aerosol throughout the day (τ900cm-1 = 0.007 ± 0.0027), followed by dust (τ900cm-1 = 0.0039 ± 0.0029) and black carbon (τ900cm-1 = 0.0017 ± 0.0007). Sea salt (τ900cm-1 = 0.0012 ± 0.0002), which has the weakest emission ability in the infrared wave band, shows the lowest AOD value. Such proportions of sulfate, dust, and BC also show good agreement with Modern-Era Retrospective analysis for Research and Applications version 2 (MERRA-2) reanalysis data. Additionally, comparison with a Sun photometer (AErosol RObotic NETwork – AERONET) shows the daily variation in the AOD retrieved from FTS to be similar to that retrieved by Sun photometer. Using this method, long-term observations (from April to August 2020) are retrieved and presented. We find that sulfate is often present in the Arctic; it is higher in spring and lower in summer. Similarly, BC is also frequently observed in the Arctic, with less obvious seasonal variation than sulfate. A BC outburst event is observed each spring and summer. In spring, sulfate and BC are dominant, whereas sea salt and dust are relatively low. In addition, a sea salt enhancement event is observed in summertime, which might be due to the melting of sea ice and emissions from nearby open water. From the retrieved results over a long time period, no clear correlations are found; thus, the aforementioned species can be retrieved independently of one another.

Hydrogen cyanide (HCN) is an important tracer of biomass burning, but there are significant uncertainties in its atmospheric budget, especially its photochemical and ocean sinks. Here we use a tracer version of the TOMCAT global 3-D chemical transport model to investigate the physical and chemical processes driving the abundance of HCN in the troposphere and stratosphere over the period 2004–2016. The modelled HCN distribution is compared with version 4.1 of the Atmospheric Chemistry Experiment Fourier transform spectrometer (ACE-FTS) HCN satellite data, which provide profiles up to around 42 km, and with ground-based column measurements from the Network for the Detection of Atmospheric Composition Change (NDACC). The long-term ACE-FTS measurements reveal the strong enhancements in upper-tropospheric HCN due to large wildfire events in Indonesia in 2006 and 2015. Our 3-D model simulations confirm previous lower-altitude balloon comparisons that the currently recommended NASA Jet Propulsion Laboratory (JPL) reaction rate coefficient of HCN with OH greatly overestimates the HCN loss. The use of the rate coefficient proposed by Kleinböhl et al. (2006) in combination with the HCN oxidation by O(1D) gives good agreement between ACE-FTS observations and the model. Furthermore, the model photochemical loss terms show that the reduction in the HCN mixing ratio with height in the middle stratosphere is mainly driven by the O(1D) sink with only a small contribution from a reaction with OH. From comparisons of the model tracers with ground-based HCN observations we test the magnitude of the ocean sink in two different published schemes (Li et al., 2000, 2003). We find that in our 3-D model the two schemes produce HCN abundances which are very different to the NDACC observations but in different directions. A model HCN tracer using the Li et al. (2000) scheme overestimates the HCN concentration by almost a factor of 2, while a HCN tracer using the Li et al. (2003) scheme underestimates the observations by about one-third. To obtain good agreement between the model and observations, we need to scale the magnitudes of the global ocean sinks by factors of 0.25 and 2 for the schemes of Li et al. (2000) and Li et al. (2003), respectively. This work shows that the atmospheric photochemical sinks of HCN now appear well constrained but improvements are needed in parameterizing the major ocean uptake sink.

Accurate accounting of emissions and removals of CO2 is critical for the planning and verification of emission reduction targets in support of the Paris Agreement. Here, we present a pilot dataset of country-specific net carbon exchange (NCE; fossil plus terrestrial ecosystem fluxes) and terrestrial carbon stock changes aimed at informing countries' carbon budgets. These estimates are based on “top-down” NCE outputs from the v10 Orbiting Carbon Observatory (OCO-2) modeling intercomparison project (MIP), wherein an ensemble of inverse modeling groups conducted standardized experiments assimilating OCO-2 column-averaged dry-air mole fraction (XCO2) retrievals (ACOS v10), in situ CO2 measurements or combinations of these data. The v10 OCO-2 MIP NCE estimates are combined with “bottom-up” estimates of fossil fuel emissions and lateral carbon fluxes to estimate changes in terrestrial carbon stocks, which are impacted by anthropogenic and natural drivers. These flux and stock change estimates are reported annually (2015–2020) as both a global 1∘ × 1∘ gridded dataset and a country-level dataset and are available for download from the Committee on Earth Observation Satellites' (CEOS) website: https://doi.org/10.48588/npf6-sw92 (Byrne et al., 2022). Across the v10 OCO-2 MIP experiments, we obtain increases in the ensemble median terrestrial carbon stocks of 3.29–4.58 Pg CO2 yr−1 (0.90–1.25 Pg C yr−1). This is a result of broad increases in terrestrial carbon stocks across the northern extratropics, while the tropics generally have stock losses but with considerable regional variability and differences between v10 OCO-2 MIP experiments. We discuss the state of the science for tracking emissions and removals using top-down methods, including current limitations and future developments towards top-down monitoring and verification systems.

In 2022, South Africa faced devastating flooding which resulted in the loss of at least 425 lives and widescale destruction of property. Using qualitative methods, we describe the gendered impact of the floods on homes and lives of women and men from very low-income housing areas. We conducted 16 in-depth interviews with women, and eight single-sex narrative group discussions and with 35 women and 15 men from flood-affected areas. The women were research participants in a project that commenced prior to the floods, and the men were recruited for this study. The floods were described by many as ‘heart-breaking’, as neighbouring homes collapsed, children were swept away, and people known to them lost their lives. However, other participants asserted that the floods ‘didn’t affect them much’, before describing considerable, impact on their houses, families, possessions, neighbourhoods, jobs, and other aspects of their lives. After the initial struggle to secure their homes, and rescue family and possessions from the floods, participants were faced with extensive interruption to water supply and electricity, which severely exacerbated stress, especially for women. We describe how the impact of the flooding unfolded and largely followed the contours of gender relations, rather than disrupting them. Most women did not describe violence against women (VAW) as escalating after the floods, but for those who did, the pathway followed the impact of the floods on men’s access to the central tenets of successful masculinity, notably the provider/protector role, and lashing out response. Participants also emphasised that their lives continued much as before once the immediate aftermath of floods was past, and in so doing demonstrated significant resilience, which is not described in existing models of disaster impact on VAW.

Background: Survivors of sexual violence are at higher risk of adverse mental health outcomes compared to those exposed to other interpersonal traumas. Objective: To examine the trajectory of both post-traumatic stress disorder (PTSD) and depression as well as the role of early counselling over 24 months among rape survivors. Method: The South African Rape Impact Cohort Evaluation (RICE) study enrolled women aged 16–40 years attending post-rape care services within 20 days of a rape incident (n = 734), and a comparison group (n = 786) was recruited from primary health care. Women were followed for 24 months; the main study outcomes were depression and PTSD. Reports of early supportive counselling by the exposed group were also included. The analysis included an adjusted joint mixed model with linear splines to account for correlated observations between the outcomes. Results: At 24 months, 45.2% of the rape-exposed women met the cut-off for depression and 32.7% for PTSD. This was significantly higher than levels found among the unexposed. Although a decline in depression and PTSD was seen at 3 months among the women who reported a rape, mean scores remained stable thereafter. At 24 months mean depression scores remained above the depression cut-off (17.1) while mean PTSD scores declined below the PTSD cut-off (14.5). Early counselling was not associated with the trajectory of either depression or PTSD scores over the two years in rape-exposed women with both depression and PTSD persisting regardless of early counselling. Conclusion: The study findings highlight the importance to find and provide effective mental health interventions post-rape in South Africa.

Improved knowledge of the chemistry and drivers of surface ozone over the Qinghai-Tibet Plateau (QTP) is significant for regulatory and control purposes in this high-altitude region in the Himalayas. In this study, we investigate the processes and drivers of surface ozone anomalies (defined as deviations of ozone levels relative to their seasonal means) between 2015 and 2020 in urban areas over the QTP. We separate quantitatively the contributions of anthropogenic emissions and meteorology to surface ozone anomalies by using the random forest (RF) machine-learning model-based meteorological normalization method. Diurnal and seasonal surface ozone anomalies over the QTP were mainly driven by meteorological conditions, such as temperature, planetary boundary layer height, surface incoming shortwave flux, downward transport velocity and inter-annual anomalies were mainly driven by anthropogenic emission. Depending on region and measurement hour, diurnal surface ozone anomalies varied over −27.82 to 37.11 µg m−3, whereas meteorological and anthropogenic contributions varied over −33.88 to 35.86 µg m−3 and −4.32 to 4.05 µg m−3 respectively. Exceptional meteorology drove 97 % of surface ozone non-attainment events from 2015 to 2020 in the urban areas over the QTP. Monthly averaged surface ozone anomalies from 2015 to 2020 varied with much smaller amplitudes than their diurnal anomalies, whereas meteorological and anthropogenic contributions varied over 7.63 to 55.61 µg m−3 and 3.67 to 35.28 µg m−3 respectively. The inter-annual trends of surface ozone in Ngari, Lhasa, Naqu, Qamdo, Diqing, Haixi and Guoluo can be attributed to anthropogenic emissions in 95.77 %, 96.30 %, 97.83 %, 82.30 %, 99.26 % and 87.85 %, and meteorology in 4.23 %, 3.70 %, 2.17 %, 3.19 %, 0.74 % and 12.15 % respectively. The inter-annual trends of surface ozone in other cities were fully driven by anthropogenic emission, whereas the increasing inter-annual trends would have larger values if not for the favorable meteorological conditions. This study can not only improve our knowledge with respect to spatiotemporal variability of surface ozone but also provide valuable implications for ozone mitigation over the QTP.

In order to establish a creditable greenhouse gas (GHG) monitoring network to support the goals of carbon peak/neutrality, it is necessary to know what we have done and what we have to do in the future. In this study, we summarize an overview of the status and perspective of GHG monitoring in China. With decades of effort, China has made a great breakthrough in GHG monitoring capacity and steadily improved the performance of homemade GHG monitoring instruments. However, most GHG monitoring studies have been research-oriented, temporal, sparse, and uncoordinated. It is suggested to take full advantage of various monitoring technologies, monitoring platforms, numerical simulations, and inventory compilation techniques to form a creditable GHG stereoscopic monitoring and assessment system at an operational level. We envisage that this system can routinely quantify GHGs on national, provincial, regional, and even individual scales with high spatiotemporal resolution and wide coverage to support low-carbon policy in China.

The Sentinel-5 Precursor (S5P) mission was launched on October 2017 and has since provided data with high spatio-temporal resolution using its remote sensing instrument, the TROPOspheric Monitoring Instrument (TROPOMI). The latter is a nadir viewing passive grating imaging spectrometer. The mathematical inversion of the TROPOMI data yields retrievals of different trace gas and aerosol data products. The column-averaged dry air mole fraction of methane (XCH4) is the product of interest to this study. The daily global coverage of the atmospheric methane mole fraction data enables the analysis of the methane distribution and variation on large scales and also to estimate surface emissions. The spatio-temporal high-resolution satellite data are potentially particularly valuable in remote regions, such as the Arctic, where few ground stations and in-situ measurements are available. In addition to the operational Copernicus S5P total-column averaged dry air mole fraction methane data product developed by SRON, the scientific TROPOMI/WFMD algorithm data product v1.5 (WFMD product) was generated at the Institute of Environmental Physics at the University of Bremen. In this study we focus on the assessment of both S5P XCH4 data products over Greenland and find that spatial maps of both products show distinct features along the coast lines. Anomalies up to and exceeding 100 ppb are observed and stand out in comparison to the otherwise smooth changes in the methane distribution. These features are more pronounced for the operational product compared to the WFMD product. The spatial patterns correlate with the difference between the GMTED2010 digital elevation model (DEM) used in the retrievals and a more recent topography data set indicating that inaccuracies in the assumed surface elevation are the origin of the observed features. These correlations are stronger for the WFMD product. In order to evaluate the impact of the topography dataset on the retrieval we reprocess the WFMD product with updated elevation data. We find a significant reduction of the localized features when GMTED2010 is replaced by recent topography data over Greenland based on ICESat-2 data. This study shows the importance of the chosen topography data on retrieved dry air mole fractions. The use of an accurate and as up-to-date as possible DEM is advised for all S5P data products as well as for future missions which rely on DEM as input data. A modification based on this study is planned to be introduced in the next version of the WFMD data product.

We show new results from an updated version of the Fast atmOspheric traCe gAs retrievaL (FOCAL) retrieval method applied to measurements of the Greenhouse gases Observing SATellite (GOSAT) and its successor GOSAT-2. FOCAL was originally developed for estimating the total column carbon dioxide mixing ratio (XCO2) from spectral measurements made by the Orbiting Carbon Observatory-2 (OCO-2). However, depending on the available spectral windows, FOCAL also successfully retrieves total column amounts for other atmospheric species and their uncertainties within one single retrieval. The main focus of the current paper is on methane (XCH4; full-physics and proxy product), water vapour (XH2O) and the relative ratio of semi-heavy water (HDO) to water vapour (δD). Due to the extended spectral range of GOSAT-2, it is also possible to derive information on carbon monoxide (XCO) and nitrous oxide (XN2O) for which we also show first results. We also present an update on XCO2 from both instruments. For XCO2, the new FOCAL retrieval (v3.0) significantly increases the number of valid data compared with the previous FOCAL retrieval version (v1) by 50 % for GOSAT and about a factor of 2 for GOSAT-2 due to relaxed pre-screening and improved post-processing. All v3.0 FOCAL data products show reasonable spatial distribution and temporal variations. Comparisons with the Total Carbon Column Observing Network (TCCON) result in station-to-station biases which are generally in line with the reported TCCON uncertainties. With this updated version of the GOSAT-2 FOCAL data, we provide a first total column average XN2O product. Global XN2O maps show a gradient from the tropics to higher latitudes on the order of 15 ppb, which can be explained by variations in tropopause height. The new GOSAT-2 XN2O product compares well with TCCON. Its station-to-station variability is lower than 2 ppb, which is about the magnitude of the typical N2O variations close to the surface. However, both GOSAT-2 and TCCON measurements show that the seasonal variations in the total column average XN2O are on the order of 8 ppb peak-to-peak, which can be easily resolved by the GOSAT-2 FOCAL data. Noting that only few XN2O measurements from satellites exist so far, the GOSAT-2 FOCAL product will be a valuable contribution in this context.

Southeast Asian peatlands represent a globally significant carbon store that is destabilized by land-use changes like deforestation and the conversion into plantations, causing high carbon dioxide (CO2) emissions from peat soils and increased leaching of peat carbon into rivers. While this high carbon leaching and consequentially high DOC concentrations suggest that CO2 emissions from peat-draining rivers would be high, estimates based on field data suggest they are only moderate. In this study, we offer an explanation for this phenomenon by showing that carbon decomposition is hampered by the low pH in peat-draining rivers. This limits CO2 production in and emissions from these rivers. We find an exponential pH limitation that shows good agreement with laboratory measurements from high-latitude peat soils. Additionally, our results suggest that enhanced input of carbonate minerals increases CO2 emissions from peat-draining rivers by counteracting the pH limitation. As such inputs of carbonate minerals can occur due to human activities like deforestation of river catchments, liming in plantations, and enhanced weathering application, our study points out an important feedback mechanism of those practices.

A dataset of microphysical cloud parameters from optically thin clouds, retrieved from infrared spectral radiances measured in summer 2017 in the Arctic, is presented. Measurements were performed using a mobile Fourier-transform infrared (FTIR) spectrometer which was carried by RV Polarstern. The dataset contains retrieved optical depths and effective radii of ice and liquid water, from which the liquid water path and ice water path are calculated. The water paths and the effective radii retrieved from the FTIR measurements are compared with derived quantities from a combined cloud radar, lidar and microwave radiometer measurement synergy retrieval, called Cloudnet. The purpose of this comparison is to benchmark the infrared retrieval data against the established Cloudnet retrieval. For the liquid water path, the data correlate, showing a mean bias of 2.48 g m−2 and a root-mean-square error of 10.43 g m−2. It follows that the infrared retrieval is able to determine the liquid water path. Although liquid water path retrievals from the Cloudnet retrieval data come with an uncertainty of at least 20 g m−2, a root-mean-square error of 9.48 g m−2 for clouds with a liquid water path of at most 20 g m−2 is found. This indicates that the liquid water paths, especially of thin clouds, of the Cloudnet retrieval can be determined with higher accuracy than expected. Apart from this, the dataset of microphysical cloud properties presented here allows researchers to perform calculations of the cloud radiative effects when the Cloudnet data from the campaign are not available, which was the case from 22 July 2017 until 19 August 2017. The dataset is published at PANGAEA (https://doi.org/10.1594/PANGAEA.933829, Richter et al., 2021).

Abstract We validate formaldehyde (HCHO) vertical column densities (VCDs) from Ozone Mapping and Profiler Suite Nadir Mapper (OMPS‐NM) instruments onboard the Suomi National Polar‐orbiting Partnership (Suomi NPP) satellite for 2012–2020 and National Oceanic and Atmospheric Administration‐20 (NOAA‐20) satellite for 2018–2020, hereafter referred to as OMPS‐NPP and OMPS‐N20, with ground‐based Fourier‐Transform Infrared (FTIR) observations of the Network for the Detection of Atmospheric Composition Change (NDACC). OMPS‐NPP/N20 HCHO products reproduce seasonal variability at 24 FTIR sites. Monthly variability of OMPS‐NPP/N20 has a very good agreement with FTIR, showing correlation coefficients of 0.83 and 0.88, respectively. OMPS‐NPP (N20) biases averaged over all sites are −0.9 (4) ± 3 (6)%. However, at clean sites (with VCDs 4.0 × 1015 molecules cm−2, negative biases of −15% ± 4% appear for OMPS‐NPP, but OMPS‐N20 shows smaller bias of 0.5% ± 6% due to its smaller ground pixel footprints. Therefore, smaller satellite footprint sizes are important in distinguishing small‐scale plumes. In addition, we discuss a bias correction and provide lower limit for the monthly uncertainty of OMPS‐NPP/N20 HCHO products. The total uncertainty for OMPS‐NPP (N20) at clean sites is 0.7 (0.8) × 1015 molecules cm−2, corresponding to a relative uncertainty of 32 (30)%. In the case of HCHO VCDs > 4.0 × 1015 molecules cm−2, however, the relative uncertainty in HCHO VCDs for OMPS‐NPP (N20) decreases to 31 (18)%.

Nitrogen dioxide (NO2) is mainly affected by local emission and meteorology rather than long-range transport. Accurate knowledge of its long-term variabilities and drivers is significant for understanding the evolution of economic and social development, anthropogenic emission, and the effectiveness of pollution control measures on a regional scale. In this study, we quantity the long-term variabilities and the underlying drivers of NO2 from 2005–2020 over the Yangtze River Delta (YRD), one of the most densely populated and highly industrialized city clusters in China, using OMI spaceborne observations and the multiple linear regression (MLR) model. We have compared the spaceborne tropospheric results to surface in situ data, yielding correlation coefficients of 0.8 to 0.9 over all megacities within the YRD. As a result, the tropospheric NO2 column measurements can be taken as representative of near-surface conditions, and we thus only use ground-level meteorological data for MLR. The inter-annual variabilities of tropospheric NO2 vertical column density (NO2 VCDtrop) from 2005–2020 over the YRD can be divided into two stages. The first stage was from 2005–2011, which showed overall increasing trends with a wide range of (1.91 ± 1.50) to (6.70 ± 0.10) × 1014 molec. cm−2 yr−1 (p<0.01) over the YRD. The second stage was from 2011–2020, which showed overall decreasing trends of (−6.31 ± 0.71) to (−11.01 ± 0.90) × 1014 molec. cm−2 yr−1 (p<0.01) over each of the megacities. The seasonal cycles of NO2 VCDtrop over the YRD are mainly driven by meteorology (81.01 %–83.91 %), except during winter when anthropogenic emission contributions are pronounced (16.09 %–18.99 %). The inter-annual variabilities of NO2 VCDtrop are mainly driven by anthropogenic emission (69.18 %–81.34 %), except for a few years such as 2018 which are partly attributed to meteorology anomalies (39.07 %–91.51 %). The increasing trends in NO2 VCDtrop from 2005–2011 over the YRD are mainly attributed to high energy consumption associated with rapid economic growth, which causes significant increases in anthropogenic NO2 emission. The decreasing trends in NO2 VCDtrop from 2011–2020 over the YRD are mainly attributed to the stringent clean air measures which either adjust high-energy industrial structure toward low-energy industrial structure or directly reduce pollutant emissions from different industrial sectors.

The Thermal And Near infrared Sensor for carbon Observation – Fourier Transform Spectrometer (TANSO-FTS) on the Japanese Greenhouse gases Observing SATellite (GOSAT) has been returning data since April 2009. The version 9 (v9) Atmospheric Carbon Observations from Space (ACOS) Level 2 Full Physics (L2FP) retrieval algorithm (Kiel et al., 2019) was used to derive estimates of carbon dioxide (CO2) dry air mole fraction (XCO2) from the TANSO-FTS measurements collected over its first 11 years of operation. The bias correction and quality filtering of the L2FP XCO2 product were evaluated using estimates derived from the Total Carbon Column Observing Network (TCCON) as well as values simulated from a suite of global atmospheric inversion systems (models) which do not assimilate satellite-derived CO2. In addition, the v9 ACOS GOSAT XCO2 results were compared with collocated XCO2 estimates derived from NASA's Orbiting Carbon Observatory-2 (OCO-2), using the version 10 (v10) ACOS L2FP algorithm. These tests indicate that the v9 ACOS GOSAT XCO2 product has improved throughput, scatter, and bias, when compared to the earlier v7.3 ACOS GOSAT product, which extended through mid 2016. Of the 37 million soundings collected by GOSAT through June 2020, approximately 20 % were selected for processing by the v9 L2FP algorithm after screening for clouds and other artifacts. After post-processing, 5.4 % of the soundings (2×106 out of 37×106) were assigned a “good” XCO2 quality flag, as compared to 3.9 % in v7.3 ( ×106 out of 24×106). After quality filtering and bias correction, the differences in XCO2 between ACOS GOSAT v9 and both TCCON and models have a scatter (1σ) of approximately 1 ppm for ocean-glint observations and 1 to 1.5 ppm for land observations. Global mean biases against TCCON and models are less than approximately 0.2 ppm. Seasonal mean biases relative to the v10 OCO-2 XCO2 product are of the order of 0.1 ppm for observations over land. However, for ocean-glint observations, seasonal mean biases relative to OCO-2 range from 0.2 to 0.6 ppm, with substantial variation in time and latitude. The ACOS GOSAT v9 XCO2 data are available on the NASA Goddard Earth Science Data and Information Services Center (GES-DISC) in both the per-orbit full format (https://doi.org/10.5067/OSGTIL9OV0PN, OCO-2 Science Team et al., 2019b) and in the per-day lite format (https://doi.org/10.5067/VWSABTO7ZII4, OCO-2 Science Team et al., 2019a). In addition, a new set of monthly super-lite files, containing only the most essential variables for each satellite observation, has been generated to provide entry level users with a light-weight satellite product for initial exploration (CaltechDATA, https://doi.org/10.22002/D1.2178, Eldering, 2021). The v9 ACOS Data User's Guide (DUG) describes best-use practices for the GOSAT data (O'Dell et al., 2020). The GOSAT v9 data set should be especially useful for studies of carbon cycle phenomena that span a full decade or more and may serve as a useful complement to the shorter OCO-2 v10 data set, which begins in September 2014.

Following a continuous increase in the surface ozone (O3) level from 2013 to 2019, the overall summertime O3 concentrations across China showed a significant reduction in 2020. In contrast to this overall reduction in surface O3 across China, unexpected surface O3 enhancements of 10.2 ± 0.8 ppbv (23.4 %) were observed in May–June 2020 (relative to 2019) over the Sichuan Basin (SCB), China. In this study, we use high-resolution nested-grid GEOS-Chem simulation, the eXtreme Gradient Boosting (XGBoost) machine learning method, and the exposure–response relationship to determine the drivers and evaluate the health risks due to the unexpected surface O3 enhancements. We first use the XGBoost machine learning method to correct the GEOS-Chem model–measurement O3 discrepancy over the SCB. The relative contributions of meteorology and anthropogenic emission changes to the unexpected surface O3 enhancements are then quantified with a combination of GEOS-Chem and XGBoost models. In order to assess the health risks caused by the unexpected O3 enhancements over the SCB, total premature mortalities are estimated. The results show that changes in anthropogenic emissions caused a 0.9 ± 0.1 ppbv O3 reduction, whereas changes in meteorology caused an 11.1 ± 0.7 ppbv O3 increase in May–June 2020 relative to 2019. The meteorology-induced surface O3 increase is mainly attributed to an increase in temperature and decreases in precipitation, specific humidity, and cloud fractions over the SCB and surrounding regions in May–June 2020 relative to 2019. These changes in meteorology combined with the complex basin effect enhance biogenic emissions of volatile organic compounds (VOCs) and nitrogen oxides (NOx), speed up O3 chemical production, and inhibit the ventilation of O3 and its precursors; therefore, they account for the surface O3 enhancements over the SCB. The total premature mortality due to the unexpected surface O3 enhancements over the SCB has increased by 89.8 % in May–June 2020 relative to 2019.

Satellite retrievals of XCO2 at northern high latitudes currently have sparser coverage and lower data quality than most other regions of the world. We use a neural network (NN) to filter Orbiting Carbon Observatory 2 (OCO-2) B10 bias-corrected XCO2 retrievals and compare the quality of the filtered data to the quality of the data filtered with the standard B10 quality control filter. To assess the performance of the NN filter, we use Total Carbon Column Observing Network (TCCON) data at selected northern high latitude sites as a truth proxy. We found that the NN filter decreases the overall bias by 0.25 ppm (∼ 50 %), improves the precision by 0.18 ppm (∼ 12 %), and increases the throughput by 16 % at these sites when compared to the standard B10 quality control filter. Most of the increased throughput was due to an increase in throughput during the spring, fall, and winter seasons. There was a decrease in throughput during the summer, but as a result the bias and precision were improved during the summer months. The main drawback of using the NN filter is that it lets through fewer retrievals at the highest-latitude Arctic TCCON sites compared to the B10 quality control filter, but the lower throughput improves the bias and precision.

Satellite-based observations of atmospheric carbon dioxide (CO2) provide measurements in remote regions, such as the biologically sensitive but undersampled northern high latitudes, and are progressing toward true global data coverage. Recent improvements in satellite retrievals of total column-averaged dry air mole fractions of CO2 (XCO2) from the NASA Orbiting Carbon Observatory 2 (OCO-2) have allowed for unprecedented data coverage of northern high-latitude regions, while maintaining acceptable accuracy and consistency relative to ground-based observations, and finally providing sufficient data in spring and autumn for analysis of satellite-observed XCO2 seasonal cycles across a majority of terrestrial northern high-latitude regions. Here, we present an analysis of XCO2 seasonal cycles calculated from OCO-2 data for temperate, boreal, and tundra regions, subdivided into 5∘ latitude by 20∘ longitude zones. We quantify the seasonal cycle amplitudes (SCAs) and the annual half drawdown day (HDD). OCO-2 SCAs are in good agreement with ground-based observations at five high-latitude sites, and OCO-2 SCAs show very close agreement with SCAs calculated for model estimates of XCO2 from the Copernicus Atmosphere Monitoring Services (CAMS) global inversion-optimized greenhouse gas flux model v19r1 and the CarbonTracker2019 model (CT2019B). Model estimates of XCO2 from the GEOS-Chem CO2 simulation version 12.7.2 with underlying biospheric fluxes from CarbonTracker2019 (GC-CT2019) yield SCAs of larger magnitude and spread over a larger range than those from CAMS, CT2019B, or OCO-2; however, GC-CT2019 SCAs still exhibit a very similar spatial distribution across northern high-latitude regions to that from CAMS, CT2019B, and OCO-2. Zones in the Asian boreal forest were found to have exceptionally large SCA and early HDD, and both OCO-2 data and model estimates yield a distinct longitudinal gradient of increasing SCA from west to east across the Eurasian continent. In northern high-latitude regions, spanning latitudes from 47 to 72∘ N, longitudinal gradients in both SCA and HDD are at least as pronounced as latitudinal gradients, suggesting a role for global atmospheric transport patterns in defining spatial distributions of XCO2 seasonality across these regions. GEOS-Chem surface contact tracers show that the largest XCO2 SCAs occur in areas with the greatest contact with land surfaces, integrated over 15–30 d. The correlation of XCO2 SCA with these land surface contact tracers is stronger than the correlation of XCO2 SCA with the SCA of CO2 fluxes or the total annual CO2 flux within each 5∘ latitude by 20∘ longitude zone. This indicates that accumulation of terrestrial CO2 flux during atmospheric transport is a major driver of regional variations in XCO2 SCA.

The Sentinel-5 Precursor (S5P) mission with the TROPOspheric Monitoring Instrument (TROPOMI) on board has been measuring solar radiation backscattered by the Earth's atmosphere and surface since its launch on 13 October 2017. In this paper, we present for the first time the S5P operational methane (CH4) and carbon monoxide (CO) products' validation results covering a period of about 3 years using global Total Carbon Column Observing Network (TCCON) and Infrared Working Group of the Network for the Detection of Atmospheric Composition Change (NDACC-IRWG) network data, accounting for a priori alignment and smoothing uncertainties in the validation, and testing the sensitivity of validation results towards the application of advanced co-location criteria. We found that the S5P standard and bias-corrected CH4 data over land surface for the recommended quality filtering fulfil the mission requirements. The systematic difference of the bias-corrected total column-averaged dry air mole fraction of methane (XCH4) data with respect to TCCON data is -0.26±0.56 % in comparison to -0.68±0.74 % for the standard XCH4 data, with a correlation of 0.6 for most stations. The bias shows a seasonal dependence. We found that the S5P CO data over all surfaces for the recommended quality filtering generally fulfil the missions requirements, with a few exceptions, which are mostly due to co-location mismatches and limited availability of data. The systematic difference between the S5P total column-averaged dry air mole fraction of carbon monoxide (XCO) and the TCCON data is on average 9.22±3.45 % (standard TCCON XCO) and 2.45±3.38 % (unscaled TCCON XCO). We found that the systematic difference between the S5P CO column and NDACC CO column (excluding two outlier stations) is on average 6.5±3.54 %. We found a correlation of above 0.9 for most TCCON and NDACC stations. The study shows the high quality of S5P CH4 and CO data by validating the products against reference global TCCON and NDACC stations covering a wide range of latitudinal bands, atmospheric conditions and surface conditions.

Ethane (C2H6) is an important greenhouse gas and plays a significant role in tropospheric chemistry and climate change. This study first presents and then quantifies the variability, sources, and transport of C2H6 over densely populated and highly industrialized eastern China using ground-based high-resolution Fourier transform infrared (FTIR) remote sensing along with atmospheric modeling techniques. We obtained a retrieval error of 6.21 ± 1.2 (1σ)% and degrees of freedom (DOFS) of 1.47 ± 0.2 (1σ) in the retrieval of C2H6 tropospheric column-averaged dry-air mole fraction (troDMF) over Hefei, eastern China (32∘ N, 117∘ E; 30 ma.s.l.). The observed C2H6 troDMF reached a minimum monthly mean value of 0.36 ± 0.26 ppbv in July and a maximum monthly mean value of 1.76 ± 0.35 ppbv in December, and showed a negative change rate of −2.60 ± 1.34 % yr−1 from 2015 to 2020. The dependencies of C2H6 troDMF on meteorological and emission factors were analyzed using generalized additive models (GAMs). Generally, both meteorological and emission factors have positive influences on C2H6 troDMF in the cold season (December–January–February/March–April–May, DJF/MAM) and negative influences on C2H6 troDMF in the warm season (June–July–August/September–October–November, JJA/SON). GEOS-Chem chemical model simulation captured the observed C2H6 troDMF variability and was, thus, used for source attribution. GEOS-Chem model sensitivity simulations concluded that the anthropogenic emissions (fossil fuel plus biofuel emissions) and the natural emissions (biomass burning plus biogenic emissions) accounted for 48.1 % and 39.7 % of C2H6 troDMF variability over Hefei, respectively. The observed C2H6 troDMF variability mainly results from the emissions within China (74.1 %), where central, eastern, and northern China dominated the contribution (57.6 %). Seasonal variability in C2H6 transport inflow and outflow over the observation site is largely related to the midlatitude westerlies and the Asian monsoon system. Reduction in C2H6 abundance from 2015 to 2020 mainly results from the decrease in local and transported C2H6 emissions, which points to air quality improvement in China in recent years.

A better understanding of greenhouse gas surface sources and sinks is required in order to address the global challenge of climate change. Space-borne remote estimations of greenhouse gas atmospheric concentrations can offer the global coverage that is necessary to improve the constraint on their fluxes, thus enabling a better monitoring of anthropogenic emissions. In this work, we introduce the Adaptable 4A Inversion (5AI) inverse scheme that aims to retrieve geophysical parameters from any remote sensing observation. The algorithm is based on the Optimal Estimation algorithm, relying on the Operational version of the Automatized Atmospheric Absorption Atlas (4A/OP) radiative transfer forward model along with the Gestion et Étude des Informations Spectroscopiques Atmosphériques: Management and Study of Atmospheric Spectroscopic Information (GEISA) spectroscopic database. Here, the 5AI scheme is applied to retrieve the column-averaged dry air mole fraction of carbon dioxide (XCO2) from a sample of measurements performed by the Orbiting Carbon Observatory-2 (OCO-2) mission. Those have been selected as a compromise between coverage and the lowest aerosol content possible, so that the impact of scattering particles can be neglected, for computational time purposes. For air masses below 3.0, 5AI XCO2 retrievals successfully capture the latitudinal variations of CO2 and its seasonal cycle and long-term increasing trend. Comparison with ground-based observations from the Total Carbon Column Observing Network (TCCON) yields a bias of 1.30±1.32 ppm (parts per million), which is comparable to the standard deviation of the Atmospheric CO2 Observations from Space (ACOS) official products over the same set of soundings. These nonscattering 5AI results, however, exhibit an average difference of about 3 ppm compared to ACOS results. We show that neglecting scattering particles for computational time purposes can explain most of this difference that can be fully corrected by adding to OCO-2 measurements an average calculated–observed spectral residual correction, which encompasses all the inverse setup and forward differences between 5AI and ACOS. These comparisons show the reliability of 5AI as an optimal estimation implementation that is easily adaptable to any instrument designed to retrieve column-averaged dry air mole fractions of greenhouse gases.

Atmospheric pollutants over the Himalayas and Tibetan Plateau (HTP) have potential implications for accelerating the melting of glaciers, damaging air quality, water sources and grasslands, and threatening climate on regional and global scales. Improved knowledge of the variabilities, sources, drivers and transport pathways of atmospheric pollutants over the HTP is significant for regulatory and control purposes. In this study, we quantify the variability, source, and transport of CO in the urban areas over the HTP by using in situ measurement, GEOS-Chem model tagged CO simulation, and the analysis of meteorological fields. Diurnal, seasonal, and interannual variabilities of CO over the HTP are investigated with ∼ 6 years (January 2015 to July 2020) of surface CO measurements in eight cities over the HTP. Annual mean of surface CO volume mixing ratio (VMR) over the HTP varied over 318.3 ± 71.6 to 901.6 ± 472.2 ppbv, and a large seasonal cycle was observed with high levels of CO in the late autumn to spring and low levels of CO in summer to early autumn. The diurnal cycle is characterized by a bimodal pattern with two maximums in later morning and midnight, respectively. Surface CO VMR from 2015 to 2020 in most cities over the HTP showed negative trends. The IASI satellite observations are for the first time used to assess the performance of the GEOS-Chem model for the specifics of the HTP. The GEOS-Chem simulations tend to underestimate the IASI observations but can capture the measured seasonal cycle of CO total column over the HTP. Distinct dependencies of CO on a short lifetime species of NO2 in almost all cities over the HTP were observed, implying local emissions to be predominant. By turning off the emission inventories within the HTP in GEOS-Chem tagged CO simulation, the relative contribution of long-range transport was evaluated. The results showed that transport ratios of primary anthropogenic source, primary biomass burning (BB) source, and secondary oxidation source to the surface CO VMR over the HTP varied over 35 % to 61 %, 5 % to 21 %, and 30 % to 56 %, respectively. The anthropogenic contribution is dominated by the South Asia and East Asia (SEAS) region throughout the year (58 % to 91 %). The BB contribution is dominated by the SEAS region in spring (25 % to 80 %) and the Africa (AF) region in July–February (30 %–70 %). This study concluded that the main source of CO in urban areas over the HTP is due to local and SEAS anthropogenic and BB emissions and oxidation sources, which differ from the black carbon that is mainly attributed to the BB source from South-East Asia. The decreasing trends in surface CO VMR since 2015 in most cities over the HTP are attributed to the reduction in local and transported CO emissions in recent years.