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Abstract We present data and analysis of a set of balloon‐borne sounding profiles, which includes co‐located O3, CO, CH4, and particles, over the northern Tibetan Plateau during an Asian summer monsoon (ASM) season. These novel measurements shed light on the ASM transport behavior near the northern edge of the anticyclone. Joint analyses of these species with the temperature and wind profiles and supported by back trajectory modeling identify three distinct transport processes that dominate the vertical chemical structure in the middle troposphere, upper troposphere (UT), and the tropopause region. The correlated changes in profile structures in the middle troposphere highlight the influence of the strong westerly jet. Elevated constituent concentrations in the UT identify the main level of convective transport at the upstream source regions. Observed higher altitude maxima for CH4 characterize the airmasses' continued ascent following convection. These data complement constituent observations from other parts of the ASM anticyclone.

Summary: The Hunga Tonga-Hunga Ha’apai (HTHH) volcano eruption received worldwide attention due to its magnitude and potential effects on environment and climate. However, the operational sulfur dioxide (SO2) products mis-estimated SO2 emissions under volcanic conditions due to large uncertainties in the assumptions of SO2 plume altitude. That might have occurred in previous volcanic eruptions and misled understanding of the evolution of sulfate aerosols in the atmosphere and their impact on global climate. Here, we simultaneously retrieved the volcanic SO2 and its plume altitude from the Troposphere Monitoring Instrument (TROPOMI) and the Environment Monitoring Instrument-2 (EMI-2), exploring the SO2 burden, distribution, and evolution from January 14 to 17. We captured multiple eruptions with the second eruption emitting far more SO2 than the first. Total emissions exceeded 900 kt, significantly higher than those from operational products. Our inferred emission fluxes and injection heights offer valuable references for climate modeling and submarine volcano studies.

The Asian summer monsoon (ASM) region is a key region transporting air to the upper troposphere (UT), significantly influencing the distribution and concentration of trace gases, including methane (CH _4 ), an important greenhouse gas. We investigate the seasonal enhancement of CH _4 in the UT over the ASM region, utilizing retrievals from the Atmospheric Infrared Sounder (AIRS), model simulations and in-situ measurements. Both the AIRS data and model simulation reveal a substantial enhancement in CH _4 concentrations within the active monsoon region of up to 3%, referring to the zonal means, and of up to 6% relative to the pre-monsoon season. Notably, the spatial distribution of the CH _4 plume demonstrates a southwestward shift in the AIRS retrievals, in contrast to the model simulations, which predict a broader enhancement, including a significant increase to the east. A cross-comparison with in-situ measurements, including AirCore measurements over the Tibetan Plateau and airline sampling across the ASM anticyclone (ASMA), favors the enhancement represented by model simulation. Remarkable CH _4 enhancement over the west Pacific is also evidenced by in-situ data and simulation as a dynamical extension of the ASMA. Our findings underscore the necessity for cautious interpretation of satellite-derived CH _4 distributions, and highlight the critical role of in-situ data in anchoring the assimilation of CH _4 .

TanSat-2, the next-generation Chinese greenhouse gas monitoring satellite for measuring carbon dioxide (CO2), has a new city-scale observing mode. We assess the theoretical capability of TanSat-2 to quantify integrated urban CO2 emissions over the cities of Beijing, Jinan, Los Angeles, and Paris. A high-resolution emission inventory and a column-averaged CO2 (XCO2) transport model are used to build an urban CO2 inversion system. We design a series of numerical experiments describing this observing system to evaluate the impacts of sampling patterns and XCO2 measurement errors on inferring urban CO2 emissions. We find that the correction in systematic and random flux errors is correlated with the signal-to-noise ratio of satellite measurements. The reduction in systematic flux errors for the four cities are sizable, but are subject to unbiased satellite sampling and favorable meteorological conditions (i.e., less cloud cover and lower wind speed). The corresponding correction to the random flux error is 19–28%. Even though clear-sky satellite data from TanSat-2 have the potential to reduce flux errors for cities with high CO2 emissions, quantifying urban emissions by satellite-based measurements is subject to additional limitations and uncertainties.

The COVID-19 pandemic has stopped many human activities, which has had significant impact on emissions of greenhouse gases. Here, the authors present daily estimates of country-level CO2 emissions for different economic sectors and show that there has been a 8.8% decrease in global CO2 emissions in the first half of 2020.

Accurate measurements of the vertical distribution of carbon dioxide (CO2) in the atmosphere are critical to validate the vertical columns recorded by satellite and ground-based spectrometers and to estimate sources and sinks of CO2. This work describes an in-situ air-sampler system (Aircore). Profiles of CO2 and carbon monoxide (CO) were retrieved from two soundings of this system in Xilin Hot on 13 and 14 June 2018, and compared with observations from the Tropospheric Monitoring Instrument (TROPOMI), Orbiting Carbon Observatory-2 (OCO-2), and Copernicus Atmosphere Monitoring Service (CAMS). The column-averaged mixing ratio of CO (XCO) monitored by TROPOMI agreed well with that calculated from the in-situ CO profile, with a small mean difference of 5 ± 1.89 ppb. The column-averaged mixing ratio of CO2 (XCO2) monitored by OCO-2 also agreed well with that calculated from the in-situ CO2 profile, with a slight bias of 0.4 ± 0.6 ppm. The OCO-2 a posteriori profile had an obvious bias compared with the in-situ CO2 profile on 13 June, with an underestimation between 600 hPa and 250 hPa and an overestimation below 600 hPa. CAMS also had the same bias compared with the in-situ CO profile; however, CAMS agreed well with the in-situ CO profile on 14 June in the troposphere because a weak cold vortex passed Xilin Hot on 13 June and disappeared on 14 June. In the stratosphere, there were significant biases in the vertical degradation. The striking agreement between the column-averaged mixing ratios and the differences in the vertical distribution suggests new exciting applications for the profile product.

The unique geographical location and high altitude of the Tibetan Plateau can greatly influence regional weather and climate. In particular, the Asian summer monsoon (ASM) anticyclone circulation system over the Tibetan Plateau is recognized to be a significant transport pathway for water vapor and pollutants to enter the stratosphere. To improve understanding of these physical processes, a multi-location joint atmospheric experiment was performed over the Tibetan Plateau from late July to August in 2018, funded by the five-year (2018–2022) STEAM (stratosphere and troposphere exchange experiment during ASM) project, during which multiple platforms/instruments—including long-duration stratospheric balloons, dropsondes, unmanned aerial vehicles, special sounding systems, and ground-based and satellite-borne instruments—will be deployed. These complementary methods of data acquisition are expected to provide comprehensive atmospheric parameters (aerosol, ozone, water vapor, CO2, CH4, CO, temperature, pressure, turbulence, radiation, lightning and wind); the richness of this approach is expected to advance our comprehension of key mechanisms associated with thermal, dynamical, radiative, and chemical transports over the Tibetan Plateau during ASM activity.

A series of carbon dioxide (CO2) emission inventories with high spatial resolutions covering China have been developed in the last decade, making it possible to assess not only the anthropogenic emissions of large administrational units (countries; provinces) but also those of small administrational units (cities; counties). In this study, we investigate three open-source gridded CO2 emission inventories (EDGAR; MEIC; PKU-CO2) and two statistical data-based inventories (CHRED; CEADs) covering the period of 2000–2020 for 16 prefecture-level cities in Shandong province in order to quantify the cross-inventory uncertainty and to discuss potential reasons for it. Despite ±20% differences in aggregated provincial emissions, all inventories agree that the emissions from Shandong increased by ~10% per year before 2012 and that the increasing trend slowed down after 2012, with a quasi-stationary industrial emission proportion being observed during 2008–2014. The cross-inventory discrepancies increased remarkably when downscaled to the city level. The relative differences between two individual inventories for half of the cities exceeded 100%. Despite close estimations of aggregated provincial emissions, the MEIC provides relatively high estimates for cities with complex and dynamic industrial systems, while the CHRED tends to provide high estimates for heavily industrial cities. The CHRED and MEIC show reasonable agreement regarding the evolution of city-level emissions and the city-level industrial emission ratios over 2005–2020. The PKU-CO2 and EDGAR failed to capture the emissions and their structural changes at the city level, which is related to their point-source database stopping updates after 2012. Our results suggest that cross-inventory differences for city-level emissions exist not only in their aggregated emissions but also in their changes over time.

Monitoring the atmospheric CO2 columns inside and around a city is of great importance to understand the temporal–spatial variation of XCO2 near strong anthropogenic emissions. In this study, we use two FTIR CO2 column measurements in Beijing (Bruker EM27/SUN) and Xianghe (Bruker IFS 125HR) between 2019 and 2021 to investigate the differences of XCO2 between Beijing (urban) and Xianghe (suburb) in North China and to validate the OCO-2 and OCO-3 satellite XCO2 retrievals. The mean and standard deviation (std) of the ΔXCO2 between Beijing and Xianghe (Beijing–Xianghe) observed by two FTIR instruments are 0.206 ± 1.736 ppm, which has a seasonal variation and varies with meteorological conditions (wind speed and wind direction). The mean and std of the XCO2 differences between co-located satellite and FTIR measurements are −0.216 ± 1.578 ppm in Beijing and −0.343 ± 1.438 ppm in Xianghe for OCO-2 and 0.637 ± 1.594 ppm in Beijing and 1.206 ± 1.420 ppm in Xianghe for OCO-3. It is found that the OCO-3 snapshot area mode (SAM) measurements can capture the spatial gradient of XCO2 between urban and suburbs well. However, the FTIR measurements indicate that the OCO-3 SAM measurements are about 0.9–1.4 ppm overestimated in Beijing and Xianghe.

The Chinese carbon dioxide measurement satellite (TanSat) has collected a large number of measurements in the solar calibration mode. To improve the accuracy of XCO2 retrieval, the Instrument Line Shape (ILS, also known as the slit function) must be accurately determined. In this study, we characterized the on-orbit ILS of TanSat by fitting measured solar irradiance from 2017 to 2018 with a well-calibrated high-spectral-resolution solar reference spectrum. We used various advanced analytical functions and the stretch/sharpen of the tabulated preflight ILS to represent the ILS for each wavelength window, footprint, and band. Using super Gaussian+P7 and the stretch/sharpen functions substantially reduced the fitting residual in O2 A-band and weak CO2 band compared with using the preflight ILS. We found that the difference between the derived ILS width and on-ground preflight ILS was up to −3.5% in the weak CO2 band, depending on footprint and wavelength. The large amplitude of the ILS wings, depending on the wavelength, footprint, and bands, indicated possible uncorrected stray light. Broadening ILS wings will cause additive offset (filling-in) on the deep absorption lines of the spectra, which we confirmed using offline bias correction of the solar-induced fluorescence retrieval. We estimated errors due to the imperfect ILS using simulated TanSat spectra. The results of the simulations showed that XCO2 retrieval is sensitive to errors in the ILS, and 4% uncertainty in the full width of half maximum (FWHM) or 20% uncertainty in the ILS wings can induce an error of up to 1 ppm in the XCO2 retrieval.

Records and projections of increasing global average temperature call for improvements of global stocktake inputs, which are vital to achieving targets of intergovernmental agreements on climate change. Unmanned Aerial Vehicle (UAV)-based atmospheric observation of greenhouse gas (GHG) concentrations is an upcoming addition to the top-down measurement methods due to its advantageous spatial-temporal resolutions, greater coverage area and lower costs. Hence, we developed and tested a lightweight UAV payload enclosure integrating a non-dispersive diffusion infrared (NDIR) spectrometer and two electrochemical sensors for measurements of carbon dioxide (CO2), carbon monoxide (CO) and nitrogen dioxide (NO2). To achieve higher response times and maintain measurement qualities, we designed a custom air inlet on the rotor-facing side of the enclosure to reduce measurement fluctuations caused by rotor downwash airflow. To validate the payload design, we conducted a controlled test for comparing chambered and chamber-less NDIR spectrometer measurements. From the test we observed a reduction of 0.48 hPa in terms of standard deviation of pressure measurements and minimised downwash-flow-induced anomalous biases (+0.49 ppm and +0.08 hpa for chambered compared to −1.33 ppm and −1.05 hpa for chamber-less). We also conducted an outdoor in-situ measurement test with multiple flights reaching 500 m above ground level (ABGL). The test yielded high resolution results representing vertical distributions of mole fraction concentrations of three types of gases via two types of flight trajectory planning methods. Therefore, we provide an alternative UAV payload integration method for NDIR spectrometer CO2 measurements that complement existing airborne GHG observation methodologies. Additionally, we also introduced an aerodynamic approach in reducing measurement noises and biases for a low response time sensor configuration.

We estimated CO _2 emissions from the Beijing region of China using differential ground-based observations of the column-averaged dry air mole fractions of CO _2 ( $\Delta X{\text{C}}{{\text{O}}_{2,{\text{ obs}}}}$ ; urban minus upwind background column observations) in winter (1 November 2020–1 March 2021). Beijing is one of the most world’s populated cities and the CO _2 emissions from this region contain large uncertainties in different bottom-up anthropogenic inventories. Differential measurements are potentially able to capture urban signals over Beijing (3.46 ± 2.35 ppm). The simulated X CO _2 enhancements were calculated ( $\Delta X{\text{C}}{{\text{O}}_{2,{\text{ sim}}}}$ ) based on three emission inventories (the Open-source Data Inventory for Anthropogenic CO _2 (ODIAC), Multiresolution Emission Inventory for China (MEIC) and Emissions Database for Global Atmospheric Research (EDGAR) datasets) for Beijing. The $\Delta X{\text{C}}{{\text{O}}_{2,{\text{ sim}}}}$ values based on the ODIAC dataset were much higher than the observations, whereas the values from the EDGAR dataset were much lower and the MEIC dataset was more consistent. We performed a Lagrangian inversion framework based on Bayesian theory. The average and uncertainty of a priori estimates (12.18 ± 8.0, 7.09 ± 7.5 and 3.53 ± 11.4 μ mol (m ^2 s) ^−1 ) were optimized to the posterior emissions (9.44 ± 5.7, 7.13 ± 4.9 and 7.15 ± 5.7 μ mol (m ^2 s) ^−1 ), suggesting that the three posterior estimates tended to converge to become more consistent, transport errors (especially the horizontal transport errors) and the spatially uneven corrections in Beijing were the main reason for the differences between the posterior estimates. Sensitivity tests suggested that the prescribed spatial and temporal structures affected up to about 12.9%, 4.9% and 20.8%, respectively, of the three inventories.

The increase in atmospheric greenhouse gas concentrations of CO2 and CH4, due to human activities, is the main driver of the observed increase in surface temperature by more than 1 °C since the pre-industrial era. At the 2015 United Nations Climate Change Conference held in Paris, most nations agreed to reduce greenhouse gas emissions to limit the increase in global surface temperature to 1.5 °C. Satellite remote sensing of CO2 and CH4 is now well established thanks to missions such as NASA’s OCO-2 and the Japanese GOSAT missions, which have allowed us to build a long-term record of atmospheric GHG concentrations from space. They also give us a first glimpse into CO2 and CH4 enhancements related to anthropogenic emission, which helps to pave the way towards the future missions aimed at a Monitoring & Verification Support (MVS) capacity for the global stock take of the Paris agreement. China plays an important role for the global carbon budget as the largest source of anthropogenic carbon emissions but also as a region of increased carbon sequestration as a result of several reforestation projects. Over the last 10 years, a series of projects on mitigation of carbon emission has been started in China, including the development of the first Chinese greenhouse gas monitoring satellite mission, TanSat, which was successfully launched on 22 December 2016. Here, we summarise the results of a collaborative project between European and Chinese teams under the framework of the Dragon-4 programme of ESA and the Ministry of Science and Technology (MOST) to characterize and evaluate the datasets from the TanSat mission by retrieval intercomparisons and ground-based validation and to apply model comparisons and surface flux inversion methods to TanSat and other CO2 missions, with a focus on China.

The COVID-19 pandemic has led to ongoing reductions in economic activity and anthropogenic emissions. Beijing was particular badly affected by lockdown measures during the early months of the COVID-19 pandemic. It has significantly reduced the CO2 emission and toxic air pollution (CO and NO2). We use column-averaged dry-air mole fractions of CO2 and CO (XCO2 and XCO) observed by a ground-based EM27/SUN Fourier transform spectrometer (FTS), the tropospheric NO2 column observed by MAX-DOAS and satellite remote sensing data (GOSAT and TROPOMI) to investigate the variations in anthropogenic CO2 emission related to COVID-19 lockdown in Beijing. The anomalies describe the spatio-temporal enhancement of gas concentration, which relates to the emission. Anomalies in XCO2 and XCO, and XNO2 (ΔXCO2, ΔXCO, and ΔXNO2) for ground-based measurements were calculated from the diurnal variability. Highly correlated daily XCO and XCO2 anomalies derived from FTS time series data provide the ΔXCO to ΔXCO2 ratio (the correlation slope). The ΔXCO to ΔXCO2 ratio in Beijing was lower in 2020 (8.2 ppb/ppm) than in 2019 (9.6 ppb/ppm). The ΔXCO to ΔXCO2 ratio originating from a polluted area was significantly lower in 2020. The reduction in anthropogenic CO2 emission was estimated to be 14.2% using FTS data. A comparable value reflecting the slowdown in growth of atmospheric CO2 over the same time period was estimated to be 15% in Beijing from the XCO2 anomaly from GOSAT, which was derived from the difference between the target area and the background area. The XCO anomaly from TROPOMI is reduced by 8.7% in 2020 compared with 2019, which is much smaller than the reduction in surface air pollution data (17%). Ground-based NO2 observation provides a 21.6% decline in NO2. The NO2 to CO2 correlation indicates a 38.2% decline in the CO2 traffic emission sector. Overall, the reduction in anthropogenic CO2 emission relating to COVID-19 lockdown in Beijing can be detected by the Bruker EM27/SUN Fourier transform spectrometer (FTS) and MAX-DOAS in urban Beijing.

A Correction to this paper has been published: https://doi.org/10.1038/s41467-020-20254-5

Satellite measurements and model simulations indicate the existence of the Asian tropopause aerosol layer (ATAL)—an enhanced aerosol layer in the upper troposphere and lower stratosphere (UTLS) associated with the Asian summer monsoon (ASM)—although it has rarely been evidenced by snapshots of balloon-borne in situ measurements. To better understand how the ATAL evolves, a portable optical particle counter (POPS) onboard a stratospheric balloon was released over the Tibetan Plateau (TP) during the ASM period of 2019. The POPS detected the ATAL in the UTLS during the ascending, descending periods, as well as during its quasi-horizontal floating periods. The aerosol number density in the ATAL showed obvious vertical variability. The peak aerosol number density in the ATAL was 180 cm ^−3 around the tropopause during the ascending and descending period and the maximum aerosol number density was 290 cm ^−3 around the tropopause during the floating period. And the aerosol concentration observed over the TP in the 2019 summer was approximately five times larger than that in the 2018 summer. Lagrangian simulations reveal that the minority of the observed aerosol particles were directly elevated in a region of uplift south of the Himalayas, and the majority of the particles were transported from the UTLS region situated approximately between the isentropic surfaces of 370 and 460 K. Up to 14% of the observed aerosol particles were directly influenced by the volcanic plumes from the eruption of the volcano Raikoke in June 2019.

Aerosols significantly affect carbon dioxide (CO2) retrieval accuracy and precision by modifying the light path. Hyperspectral measurements in the near infrared and shortwave infrared (NIR/SWIR) bands from the generation of new greenhouse gas satellites (e.g., the Chinese Global Carbon Dioxide Monitoring Scientific Experimental Satellite, TanSat) contain aerosol information for correction of scattering effects in the retrieval. Herein, a new approach is proposed for optimizing the aerosol model used in the TanSat CO2 retrieval algorithm to reduce CO2 uncertainties associated with aerosols. The weighting functions of hyperspectral observations with respect to elements in the state vector are simulated by a forward radiative transfer model. Using the optimal estimation method (OEM), the information content and each component of the CO2 column-averaged dry-air mole fraction (XCO2) retrieval errors from the TanSat simulations are calculated for typical aerosols which are described by Aerosol Robotic Network (AERONET) inversion products at selected sites based on the a priori and measurement assumptions. The results indicate that the size distribution parameters (reff, veff), real refractive index coefficient of fine mode (arf) and fine mode fraction (fmf) dominate the interference errors, with each causing 0.2−0.8 ppm of XCO2 errors. Given that only 4−7 degrees of freedom for signal (DFS) of aerosols can be obtained simultaneously and CO2 information decreases as more aerosol parameters are retrieved, four to seven aerosol parameters are suggested as the most appropriate for inclusion in CO2 retrieval. Focusing on only aerosol-induced XCO2 errors, forward model parameter errors, rather than interference errors, are dominant. A comparison of these errors across different aerosol parameter combination groups reveals that fewer aerosol-induced XCO2 errors are found when retrieving seven aerosol parameters. Therefore, the model selected as the optimal aerosol model includes aerosol optical depth (AOD), peak height of aerosol profile (Hp), width of aerosol profile (Hw), effective variance of fine mode aerosol (vefff), effective radius of coarse mode aerosol (reffc), coefficient a of the real part of the refractive index for the fine mode and coarse mode (arf and arc), with the lowest error of less than 1.7 ppm for all aerosol and surface types. For marine aerosols, only five parameters (AOD, Hp, Hw, reffc and arc) are recommended for the low aerosol information. This optimal aerosol model therefore offers a theoretical foundation for improving CO2 retrieval precision from real TanSat observations in the future.

The variation in tropospheric ozone over East Asia was analyzed using tropospheric column ozone data measured by the Global Ozone Monitoring Experiment (GOME) satellite. An empirical orthogonal function (EOF) analysis was carried out to derive the dominant modes of the variation in the tropospheric ozone volume-mixing ratio (TOVMR). The EOF1 mode, which explained 61.5% of the total variance, showed a same-sign distribution over all of East Asia, with a belt of enhanced ozone concentrations around 40°N. The principal component of EOF1 (PC1) suggested that photochemical ozone production together with Brewer-Dobson circulation and subtropical westerly jet plays important roles in modulating the seasonal variation of the TOVMR; ozone-rich air produced by photochemical processes was transported from the stratosphere to the troposphere by BD circulation and this ozone-rich air was then blocked by the subtropical westerly jet and accumulated north of the jet. The EOF2 mode explained 29.2% of the total variance with an opposite-sign pattern on the north and south side of 35°N. When anticyclonic circulation transported ozone-poor air from the upwelling area over the Bay of Bengal towards the Tibetan Plateau during the onset of the Asian summer monsoon, tropospheric ozone in this region decreased dramatically.

Aerosol scattering is an important source of error in CO2 retrievals from satellite. This paper presents an analysis of aerosol information content from the Cloud and Aerosol Polarimetric Imager (CAPI) onboard the Chinese Carbon Dioxide Observation Satellite (TanSat) to be launched in 2016. Based on optimal estimation theory, aerosol information content is quantified from radiance and polarization observed by CAPI in terms of the degrees of freedom for the signal (DFS). A linearized vector radiative transfer model is used with a linearized Mie code to simulate observation and sensitivity (or Jacobians) with respect to aerosol parameters. In satellite nadir mode, the DFS for aerosol optical depth is the largest, but for mode radius, it is only 0.55. Observation geometry is found to affect aerosol DFS based on the aerosol scattering phase function from the comparison between different viewing zenith angles or solar zenith angles. When TanSat is operated in target mode, we note that multi-angle retrieval represented by three along-track measurements provides additional 0.31 DFS on average, mainly from mode radius. When adding another two measurements, the a posteriori error decreases by another 2%–6%. The correlation coefficients between retrieved parameters show that aerosol is strongly correlated with surface reflectance, but multi-angle retrieval can weaken this correlation.

Solar-induced chlorophyll fluorescence (SIF) is emitted during photosynthesis in plant leaves. It constitutes a small additional offset to reflected radiance and can be observed by sensitive instruments. The Chinese global carbon dioxide monitoring satellite (TanSat), as its mission, acquires greenhouse gas column density. The advanced technical characteristics of the hyper-spectrum grating spectrometer (ACGS) onboard TanSat enable SIF retrieval from space observations in the O2-A band. In this study, one-year SIF data was processed from Orbiting Carbon Observatory-2 (OCO-2) and TanSat using a physical-based algorithm. A comparison between the SIF retrieved from OCO-2 and its official product shows their strong linear relationship (R²>0.85) and suggests the reliability of the algorithm. The global distribution showed that the SIF retrieved from the two satellites shared the same spatial pattern for all seasons with the grided SIF difference less than 0.3W m-2 µm-1 sr-1, and they also agreed with the official OCO-2 SIF product. The retrieval uncertainty of seasonal-grided TanSat SIF is less than 0.03W m-2 µm-1 sr-1 whereas the uncertainty of each sounding ranges from 0.1 to 0.6W m-2 µm-1 sr-1. The relationship between SIF and terrestrial gross primary productivity was also estimated for data quality testing. The spatiotemporal consistency between TanSat and OCO-2 and their comparable data quality make the comprehensive usage of the two mission products possible. Data supplemented by TanSat observations are expected to contribute to the development of global SIF maps with more spatiotemporal detail, which will advance global research on vegetation photosynthesis. [ABSTRACT FROM AUTHOR]

Tropospheric ozone is both a major pollutant and a short-lived greenhouse gas and has therefore attracted much concern in recent years. The ozone profile in the troposphere and lower stratosphere over Beijing has been observed since 2002 by ozonesondes developed by the Institute of Atmospheric Physics. Increasing concentrations of tropospheric ozone from 2002 to 2010 measured by these balloon-based observations have been reported previously. As more observations are now available, we used these data to analyze the long-term variability of ozone over Beijing during the whole period from 2002 to 2018. The ozonesondes measured increasing concentrations of ozone from 2002 to 2012 in both the troposphere and lower stratosphere. There was a sudden decrease in observed ozone between 2011 and 2012. After this decrease, the increasing trend in ozone concentrations slowed down, especially in the mid-troposphere, where the positive trend became neutral. We used the Chemical Lagrangian Model of the Stratosphere (CLaMS) to determine the influence of the transport of ozone from the stratosphere to the troposphere on the observed ozone profiles. CLaMS showed a weak increase in the contribution of stratospheric ozone before the decrease in 2011-2012 and a much more pronounced decrease after this time. Because there is no tropospheric chemistry in CLaMS, the sudden decrease simulated by CLaMS indicates that a smaller downward transport of ozone from the stratosphere after 2012 may explain a significant part of the observed decrease in ozone in the mid-troposphere and lower stratosphere. However, the influence of stratospheric ozone in the lower troposphere is negligible in CLaMS and the hiatus in the positive trend after 2012 can be attributed to a reduction in ozone precursors as a result of stronger pollution control measures in Beijing. [ABSTRACT FROM AUTHOR]

In this study, ship-based Multi-Axis Differential Optical Absorption Spectroscopy (MAX-DOAS) measurements were performed in the Eastern China Sea (ECS) area in June 2017. The tropospheric Slant Column Densities (SCDs) of nitrogen dioxide (NO2), sulfur dioxide (SO2), and formaldehyde (HCHO) were retrieved from the measured spectra by the Differential Optical Absorption Spectroscopy (DOAS) technique. Using the simple geometric approach, the SCDs of different trace gases observed at 15° elevation angle were adopted to convert into tropospheric Vertical Columns Densities (VCDs). During this campaign, the averaged VCDs of NO2, SO2, and HCHO in the marine environment over ECS area are 6.50×1015moleccm−2, 4.28×1015moleccm−2 and 7.39×1015moleccm−2, respectively. In addition, the ship-based MAX-DOAS trace gases VCDs were compared with satellite observations of Ozone Monitoring Instrument (OMI) and Ozone Mapping and Profiler Suite (OMPS). The daily OMI NO2 VCDs agree well with ship-based MAX-DOAS measurements showing the correlation coefficient R of 0.83. Besides, the good agreements of SO2 and HCHO VCDs between the OMPS satellite and ship-based MAX-DOAS observations were also found with correlation coefficient R of 0.76 and 0.69. The vertical profiles of these trace gases are achieved from the measured Differential Slant Column Densities (DSCDs) at different elevation angles using optimal estimation method. The retrieved profiles displayed the typical vertical distribution characteristics, which exhibits the low concentrations of <3, <3, and <2ppbv for NO2, SO2, and HCHO in clean area of the marine boundary layer far from coast of the Yangtze River Delta (YRD) continental region. Interestingly, elevated SO2 concentrations can be observed intermittently along the ship routes, which is mainly attributed to the vicinal ship emissions in the view of the MAX-DOAS measurements. Combined with the on-board ozone lidar measurements, the ozone (O3) formation was discussed with the vertical profile of HCHO/NO2 ratio, which is sensitive to the increases of NO2 concentration. This study provided further understanding of the main air pollutants in the marine boundary layer of the ECS area and also benefited to formulate the policies regulating the shipping emissions in such costal area like YRD region. [ABSTRACT FROM AUTHOR]

The Ozone Monitoring Instrument (OMI) has been successfully measuring the Earth's atmospheric composition since 2004, but the on-orbit behavior of its slit functions has not been thoroughly characterized. Preflight measurements of slit functions have been used as a static input in many OMI retrieval algorithms. This study derives on-orbit slit functions from the OMI irradiance spectra assuming various function forms, including standard and super-Gaussian functions and a stretch to the preflight slit functions. The on-orbit slit functions in the UV bands show U-shaped cross-track dependences that cannot be fully represented by the preflight ones. The full widths at half maximum (FWHM) of the stretched preflight slit functions for detector pixels at large viewing angles are up to 30% larger than the nadir pixels for the UV1 band, 5% larger for the UV2 band, and practically flat in the VIS band. Nonetheless, the on-orbit changes of OMI slit functions are found to be insignificant over time after accounting for the solar activity, despite of the decaying of detectors and the occurrence of OMI row anomaly. Applying the derived on-orbit slit functions to ozone-profile retrieval shows substantial improvements over the preflight slit functions based on comparisons with ozonesonde validations. [ABSTRACT FROM AUTHOR]

We validate the Ozone Monitoring Instrument (OMI) Ozone Profile (PROFOZ) product from October 2004 through December 2014 retrieved by the Smithsonian Astrophysical Observatory (SAO) algorithm against ozonesonde observations. We also evaluate the effects of OMI row anomaly (RA) on the retrieval by dividing the dataset into before and after the occurrence of serious OMI RA, i.e., pre-RA (2004-2008) and post-RA (2009-2014). The retrieval shows good agreement with ozonesondes in the tropics and midlatitudes and for pressure <~50 hPa in the high latitudes. It demonstrates clear improvement over the a priori down to the lower troposphere in the tropics and down to an average of ~550 (300) hPa at middle (high) latitudes. In the tropics and midlatitudes, the profile mean biases (MBs) are less than 6%, and the standard deviations (SDs) range from 5 to 10% for pressure <~50 hPa to less than 18% (27%) in the tropics (midlatitudes) for pressure >~50 hPa after applying OMI averaging kernels to ozonesonde data. The MBs of the stratospheric ozone column (SOC, the ozone column from the tropopause pressure to the ozonesonde burst pressure) are within 2% with SDs of <5% and the MBs of the tropospheric ozone column (TOC) are within 6% with SDs of 15%. In the high latitudes, the profile MBs are within 10% with SDs of 5-15% for pressure <~50 hPa but increase to 30% with SDs as great as 40% for pressure >~50 hPa. The SOC MBs increase up to 3% with SDs as great as 6% and the TOC SDs increase up to 30%. The comparison generally degrades at larger solar zenith angles (SZA) due to weaker signals and additional sources of error, leading to worse performance at high latitudes and during the midlatitude winter. Agreement also degrades with increasing cloudiness for pressure>~100 hPa and varies with cross-track position, especially with large MBs and SDs at extreme off-nadir positions. In the tropics and midlatitudes, the post-RA comparison is considerably worse with larger SDs reaching 2% in the stratosphere and 8% in the troposphere and up to 6% in TOC. There are systematic differences that vary with latitude compared to the pre-RA comparison. The retrieval comparison demonstrates good long-term stability during the pre-RA period but exhibits a statistically significant trend of 0.14-0.7%year-1 for pressure<~80 hPa, 0.7DUyear-1 in SOC, and -0.33DUyear-1 in TOC during the post-RA period. The spatiotemporal variation of retrieval performance suggests the need to improve OMI's radiometric calibration especially during the post-RA period to maintain the long-term stability and reduce the latitude/season/SZA and cross-track dependency of retrieval quality. [ABSTRACT FROM AUTHOR]

We validate the Ozone Monitoring Instrument (OMI) ozone profile (PROFOZ) product including ozone profiles between 0.22-261hPa and Stratospheric Ozone Columns (SOCs) down to 100, 215, and 261hPa from October 2004 through December 2014 retrieved by the Smithsonian Astrophysical Observatory (SAO) algorithm against the latest Microwave Limb Sound (MLS) v4.2x data. We also evaluate the effects of OMI row anomaly (RA) on the retrieval by dividing the data set into before and after the occurrence of serious RA, i.e., pre-RA (2004-2008) and post-RA (2009-2014). During the pre-RA period, OMI ozone profiles agree very well with MLS data. Tthe global mean biases (MBs) are within 3% between 0.22-100 hPa and negative 3-9% for lower layers, and the standard deviations (SDs) are 3.5-5% from 1-40 hPa, 6-10% for upper layers and 5-20% for lower layers, after applying OMI averaging kernels to MLS data. OMI shows latitude and solar zenith angle (SZA) dependent biases, but MBs and SDs are mostly within 10% except for low/high altitudes of high latitudes/SZAs. During the post-RA period, OMI retrievals degrade slightly between 5-261hPa with MBs and SDs typically larger by 2-5%, and degrade much more, with larger MBs by up to 8% and SDs by up to 15% for pressure less than ~5hPa, where the MBs are larger by 10-15% south of 40 °N due to the blockage effect of RA and smaller by 15-20% north of 40 °N due to the solar contamination effect of RA. The much worse comparison at high altitudes indicates the UV-1 channel of pixels that are not flagged as RA is still affected by the RA. During the pre-RA period, OMI SOCs show very good agreement with MLS data with global mean MBs within 0.6% and SDs of 1.9% for SOCs down to 215 and 261hPa and of 2.30% for SOC down to 100hPa. Despite clearly worse ozone profile comparison during the post-RA period, OMI SOCs only slightly degrade, with SDs larger by 0.4-0.6% mostly due to looser spatial coincidence criterion as a result of missing data from RA and MBs larger by 0.4-0.7%. The retrieval comparison indicates significant bias trends, especially during the post-RA period. The spatiotemporal variation of the retrieval performance suggests the need to improve OMI's radiometric calibration to maintain the long-term stability and spatial consistency of the PROFOZ product. The good comparison with SOC down to 261hPa supports that MLS ozone at 261hPa, recommended for further evaluation by the MLS team, is suitable for scientific use. [ABSTRACT FROM AUTHOR]

Accurately characterizing the instrument line shape (ILS) of the Orbiting Carbon Observatory-2 (OCO-2) is challenging and highly important due to its high spectral resolution and requirement for retrieval accuracy (0:25%) compared to previous spaceborne grating spectrometers. Onorbit ILS functions for all three bands of the OCO-2 instrument have been derived using its frequent solar measurements and high-resolution solar reference spectra. The solar reference spectrum generated from the 2016 version of the Total Carbon Column Observing Network (TCCON) solar line list shows significant improvements in the fitting residual compared to the solar reference spectrum currently used in the version 7 Level 2 algorithm in the O2 A band. The analytical functions used to represent the ILS of previous grating spectrometers are found to be inadequate for the OCO-2 ILS. Particularly, the hybrid Gaussian and super-Gaussian functions may introduce spurious variations, up to 5% of the ILS width, depending on the spectral sampling position, when there is a spectral undersampling. Fitting a homogeneous stretch of the preflight ILS together with the relative widening of the wings of the ILS is insensitive to the sampling grid position and accurately captures the variation of ILS in the O2 A band between decontamination events. These temporal changes of ILS may explain the spurious signals observed in the solar-induced fluorescence retrieval in barren areas. [ABSTRACT FROM AUTHOR]

Accurately characterizing the instrument line shape (ILS) of the Orbiting Carbon Observatory-2 (OCO-2) is challenging and highly important due to its high spectral resolution and requirement for retrieval accuracy (0.25%) compared to previous space-borne grating spectrometers. On-orbit ILS functions for all three bands of the OCO-2 instrument have been derived using its frequent solar measurements and high-resolution solar reference spectra. The solar reference spectrum generated from the 2016 version of the TCCON solar line list shows significant improvements in the fitting residual compared to the solar reference spectrum currently used in the v7 L2 algorithm in the O2 A band. The analytical functions used to represent the ILS of previous grating spectrometers are found to be inadequate for the OCO-2 ILS. Particularly, the hybrid Gaussian and Super Gaussian functions may introduce spurious variations, up to 5% of the ILS width, depending on the spectral sampling position, when there is a spectral undersampling. Fitting a homogeneous stretch of the preflight ILS together with the relative widening of the wings of the ILS is insensitive to the sampling grid position and accurately captures the variation of ILS in the O2 A band between decontamination events. These temporal changes of ILS may explain the spurious signals observed in the solar-induce fluorescence retrieval in barren areas. [ABSTRACT FROM AUTHOR]

The atmospheric carbon dioxide (CO2) concentration has increased to more than 405 parts per million (ppm. 1ppm=10-6m/s2) in 2017 due to human activities such as deforestation, land-use change and burning of fossil fuels. Although there is broad scientific consensus on the damaging consequences of the change in climate associated with increasing concentrations of greenhouse gases, fossil CO2 emissions have continued to increase in recent years mainly from rapidly developing economies and China is now the largest emitter of CO2 generating about 30% of all emissions globally. To allow more reliable forecast of the future state of the carbon cycle and to support the efforts for mitigation greenhouse gas emissions, a better understanding of the global and regional carbon budget is needed. Space-based measurements of CO2 can provide the necessary observations with dense coverage and sampling to provide improved constrains on of carbon fluxes and emissions. The Chinese Global Carbon Dioxide Monitoring Scientific Experimental Satellite (TanSat) was established by the National High Technology Research and Development Program of China with the main objective of monitoring atmospheric CO2 and CO2 fluxes at the regional and global scale. TanSat has been successfully launched in December 2016 and as part of the Dragon programme of ESA and the Ministry of Science and Technology (MOST), a team of researchers from Europe (UK and Finland) and China has evaluated early TanSat data and contrast it against data from the GOSAT mission and models. In this manuscript, we report on retrieval intercomparisons of TanSat data using two different retrieval algorithms, on validation efforts for the Eastern Asia region using GOSAT CO2 data and first assessments of TanSat and GOSAT CO2 data against model calculations using the GEOS-Chem model.