Gas Retrievals Research Articles

Emisi Metana (CH4) pada Beberapa Metode Pengelolaan Limbah Sawah di Kecamatan Anjir Pasar Kabupaten Barito Kuala

Paddy fields for all of Indonesia are 8.1 million ha, about 43% are in Java and about 57% are outside Java. Paddy fields are part of the wetlands. Paddy fields control the global climate through the gases they produce and have a greenhouse effect. One of the greenhouse gases is methane, therefore the purpose of this study was to determine the effect of rice field waste management on methane emissions and the population of methanogenic microorganisms. The research method used is one-factor Completely Randomized Design (RAL). The factor tested was the method of managing rice waste before planting rice with five treatments namely: A = Rice field waste was slashed and then lifted into the mound after a few days of being returned to the field; B = Rice field waste is carried out management slashed, rolled up, reversed, and stretched; C = Rice field waste is slashed, planted with traces and then slashed again after the trace is transferred to land outside the research plot; D = Rice field waste sprayed with herbicide 2 times; E = Ricefield waste sprayed with herbicide 1 time and then soil in the tractor. Each treatment was repeated four times so 20 units of the experimental. CH4 gas retrieval used the hood method while the microorganism population used the MPN (most probable Number) method. The results showed that the rice field waste management method had an effect on methane emissions and populations of methanogen microorganisms in the planting and vegetative phases, while the generative phase had no effect.

Greenhouse gas retrievals for the CO2M mission using the FOCAL method: first performance estimates

Abstract. The Anthropogenic Carbon Dioxide Monitoring (CO2M) mission is a constellation of satellites currently planned to be launched in 2026. CO2M is planned to be a core component of a Monitoring and Verification Support (MVS) service capacity under development as part of the Copernicus Atmosphere Monitoring Service (CAMS). The CO2M radiance measurements will be used to retrieve column-averaged dry-air mole fractions of atmospheric carbon dioxide (XCO2), methane (XCH4) and total columns of nitrogen dioxide (NO2). Using appropriate inverse modelling, the atmospheric greenhouse gas (GHG) observations will be used to derive United Nations Framework Convention on Climate Change (UNFCCC) COP 21 Paris Agreement relevant information on GHG sources and sinks. This challenging application requires highly accurate XCO2 and XCH4 retrievals. Three different retrieval algorithms to derive XCO2 and XCH4 are currently under development for the operational processing system at EUMETSAT. One of these algorithms uses the heritage of the FOCAL (Fast atmOspheric traCe gAs retrievaL) method, which has already successfully been applied to measurements from other satellites. Here, we show recent results generated using the CO2M version of FOCAL, called FOCAL-CO2M. To assess the quality of the FOCAL-CO2M retrievals, a large set of representative simulated radiance spectra has been generated using the radiative transfer model SCIATRAN. These simulations consider the planned viewing geometry of the CO2 instrument and corresponding geophysical scene data (including different types of aerosols and varying surface properties), which were taken from model data for the year 2015. We consider instrument noise and systematic errors caused by the retrieval method but have not considered additional error sources due to, for example, instrumental issues, spectroscopy or meteorology. On the other hand, we have also not taken advantage in this study of CO2M's MAP (multi-angle polarimeter) instrument, which will provide additional information on aerosols and cirrus clouds. By application of the FOCAL retrieval to these simulated data, confidence is gained that the FOCAL method is able to fulfil the challenging requirements for systematic errors for the CO2M mission (spatio-temporal bias ≤ 0.5 ppm for XCO2 and ≤ 5 ppb for XCH4).

The GeoCarb greenhouse gas retrieval algorithm: simulations and sensitivity to sources of uncertainty

Abstract. The Geostationary Carbon Cycle Observatory (GeoCarb) was selected as NASA's second Earth Venture Mission (EVM-2). The scientific objectives of GeoCarb were to advance our knowledge of the carbon cycle, in particular, land–atmosphere fluxes of the greenhouse gases carbon dioxide (CO2) and methane (CH4) and the effects of these fluxes on the Earth's radiation budget. GeoCarb would retrieve column-integrated dry-air mole fractions of CO2 (XCO2), CH4 (XCH4) and CO (XCO), important for understanding tropospheric chemistry), in addition to solar-induced fluorescence (SIF), from hyperspectral resolution measurements in the O2 A-band at 0.76 µm, the weak CO2 band at 1.6 µm, the strong CO2 band at 2.06 µm, and a CH4/CO band at 2.32 µm. Unlike its predecessors (OCO-2/3, GOSAT-1/2, TROPOMI), GeoCarb would be in a geostationary orbit with a sub-satellite point centered over the Americas. This orbital configuration combined with its high-spatial-resolution imaging capabilities would provide an unprecedented view of these quantities on spatial and temporal scales accurate enough to resolve sources and sinks to improve land–atmosphere CO2 and CH4 flux calculations and reduce the uncertainty of these fluxes. This paper will present a description of the GeoCarb instrument and the L2 retrieval algorithms which will be followed by simulation experiments to determine an error budget for each target gas. Several sources of uncertainty will be explored, including that from the instrument calibration parameters for radiometric gain, the instrument line shape (ILS), the polarization, and the geolocation pointing, in addition to forward model parameters including meteorology and spectroscopy, although there are some other instrument-related sources of uncertainty that are left out for this study, including that from “smile”, the keystone effect, stray light, detector persistence, and scene inhomogeneity. The results indicate that the errors (1σ) are less than the instrument's multi-sounding precision requirements of 1.2 ppm, 10 ppb, and 12 ppb (10 %), for XCO2, XCH4, and XCO, respectively. In particular, when considering the sources of uncertainty separately and in combination (all sources included), we find overall RMSEs of 1.06 ppm for XCO2, 8.2 ppb for XCH4, and 2.5 ppb for XCO, respectively. Additionally, we find that, as expected, errors in XCO2 and XCH4 are dominated by forward model and other systematic errors, while errors in XCO are dominated by measurement noise. It is important to note that the GeoCarb mission was canceled by NASA; however, the instrument is still in development and will be delivered to NASA, in full, with the hope that it will eventually be adopted in a future mission proposal.

Development and analysis of pH-sensitive surfactants for enhancing foam drainage gas retrieval

In this study, a novel surfactant with pH-responsive properties was developed to address the challenges associated with balancing foaming and defoaming properties in traditional foam drainage gas recovery processes. The surfactant was created by employing primary amine and aldehyde monomers based on the principles of reversible dynamic covalent bonds. Optimal synthesis conditions were determined through an extensive analysis of foaming performance: a molar reaction ratio of primary amine to aldehyde at 10:0.8, a 20-minute reaction time, and a stirring speed of 300 r/min.The formation of dynamic imine bonds was confirmed through infrared spectroscopy. Surface tension measurements revealed that at pH = 8, the surfactant achieved a minimum surface tension of 31.1 mN/m, while at pH = 3, the surface tension exceeded 40 mN/m. Particle size analysis demonstrated a 26.5-fold reduction in particle size as the pH decreased from 8 to 3. Zeta potential tests indicated excellent dispersion stability within the pH range of 3–8, with Zeta potential consistently exceeding 25 mV.Furthermore, the surfactant displayed remarkable foaming and foam stabilizing effects at pH = 8, with initial and 5-minute foam heights reaching 168 mm and 132 mm, respectively. When the pH dropped below 6, the surfactant exhibited rapid defoaming. After six cycles of alternating acid-base environments, it maintained excellent foaming performance, achieving a 5-minute foam height of up to 138 mm. Importantly, it retained its foaming capabilities in formation water solutions with a mineralization degree of 200 g/L.These findings hold significant implications for the development of intelligent environmental response treatments for foam drainage and gas production, enhancing the overall efficiency of drainage and gas production operations.

Analyzing the Impact of Evolving Combustion Conditions on the Composition of Wildfire Emissions Using Satellite Data

AbstractWildfires have become larger and more frequent because of climate change, increasing their impact on air pollution. Air quality forecasts and climate models do not currently account for changes in the composition of wildfire emissions during the commonly observed progression from more flaming to smoldering combustion. Laboratory measurements have consistently shown decreased nitrogen dioxide (NO2) relative to carbon monoxide (CO) over time, as they transitioned from more flaming to smoldering combustion, while formaldehyde (HCHO) relative to CO remained constant. Here, we show how daily ratios between column densities of NO2 versus those of CO and HCHO versus CO from the Tropospheric Monitoring Instrument (TROPOMI) changed for large wildfires in the Western United States. TROPOMI‐derived emission ratios were lower than those from the laboratory. We discuss reasons for the discrepancies, including how representative laboratory burns are of wildfires, the effect of aerosols on trace gas retrievals, and atmospheric chemistry in smoke plumes.

Comparative Study of the Atmospheric Gas Composition Detection Capabilities of FY-3D/HIRAS-I and FY-3E/HIRAS-II Based on Information Capacity

Fengyun-3E (FY-3E)/Hyperspectral Infrared Atmospheric Sounder-II (HIRAS-II) is an extension Fengyun-3D (FY-3D)/HIRAS-I. It is crucial to fully explore and analyze the detection capabilities of these two instruments for atmospheric gas composition. Based on the observed spectral data from the infrared hyperspectral detection instruments FY-3D/HIRAS-I and FY-3E/HIRAS-II, simulated radiance data and Jacobian matrices are obtained using the Rapid Radiative Transfer Model RTTOV (Radiative Transfer for TOVS (TIROS Operational Vertical Sounder)). By perturbing temperature (T), surface temperature (Tsurf), water vapor (H2O), ozone (O3), carbon dioxide (CO2), methane (CH4), carbon monoxide (CO), and nitrous oxide (N2O), the brightness temperature differences before and after the perturbations are calculated to analyze the sensitivity of temperature and various atmospheric gas components. The Improved Optimal Sensitivity Profile (OSP) algorithm is used to select the channels for atmospheric gas retrieval. The observation error covariance and background error covariance matrices are calculated, and then the information capacity is calculated, specifically the degrees of freedom for signal(DFS) and the entropy reduction (ER). Based on this, a comparative analysis is conducted on the information capacity of atmospheric water vapor and ozone components contained in the hyperspectral detection data from HIRAS-I and HIRAS-II instruments, respectively, to explore the retrieval capabilities of the two instruments for atmospheric gas components. We selected clear-sky data from the African oceanic region and the Chinese Yangtze River Delta terrestrial region for quantitative analysis of the information capacity of HIRAS-I and HIRAS-II. The results show that FY-3D/HIRAS-I and FY-3E/HIRAS-II exhibit different sensitivities to atmospheric gas components. In different experimental regions, temperature and water vapor show the most dramatic sensitivity changes, followed by ozone, methane, and nitrous oxide, while carbon monoxide and carbon dioxide exhibit the lowest variability. Regarding channel selection, HIRAS-II identifies more gas channels compared to HIRAS-I. The experiments concluded that HIRAS-II has a significantly higher information capacity than HIRAS-I, and the information capacity of atmospheric gas components varies across different experimental regions. Water vapor and ozone exhibit the highest information capacity, followed by nitrous oxide and methane, while carbon monoxide and carbon dioxide demonstrate the lowest capacity. The H2O ER (DFS) contained in FY-3E/HIRAS-II is 1.51 (0.35) higher than that in FY-3D/HIRAS-I, the O3 ER (DFS) in FY-3E/HIRAS-II is 1.51 (0.36) higher than that in FY-3D/HIRAS-I, while the N2O ER (DFS) in FY-3E/HIRAS-II is 0.17 (0.19) higher and the CH4 ER (DFS) is 0.07 (0.04) higher than that in FY-3D/HIRAS-I.

Decoupling in the vertical shape of HCHO during a sea breeze event: The effect on trace gas satellite retrievals and column-to-surface translation

The effect of sea breeze circulation on stratification of the vertical formaldehyde (HCHO) concentration vertical profiles is explored using a regional atmospheric chemical transport model (CTM) for three synoptically stagnant days focused on the east coast of the U.S in June 2018. During this event, a significant thermal contrast between the Atlantic Ocean and the terrestrial regions (12–17 °C), observed by moderate resolution imaging spectroradiometer (MODIS) and well-captured by the WRF-CMAQ model (15–18 °C), is conducive to monsoon-like flow, perpendicular to the shorelines, carrying clean marine air masses over the land within a few hundreds of meters above the surface. In contrast, the westerly continental polluted air masses prevail in higher altitudes. These two conflicting flows result in atypical vertical shapes of HCHO concentrations increasing with altitude. This decoupling pattern is so pronounced that we observe total column HCHO negatively correlate with surface concentrations. Comparisons of an accredited global model, GEOS-CF, to surface wind measurements and MODIS skin temperature indicate its poor representation of the sea breeze timing and strength, resulting in GEOS-CF HCHO vertical shapes being drastically different from the WRF-CMAQ. Based on radiative transfer calculations, the differences in the vertical distribution of HCHO between the WRF-CMAQ and that of GEOS-CF in the first 3 km are sufficient to induce a 20–30% error in air mass factors (thus total vertical HCHO column abundances). Through an experiment involving converting HCHO total columns to surface mixing ratios, we demonstrate that GEOS-CF allocates noticeably more HCHO molecules (40–150%) to the surface layer due to the misrepresentation of the vertical shape of HCHO during the sea breeze event. It is known that a significant fraction of the human population lives in coastal areas prone to detrimental effects caused by air pollution, and elevated pollutant concentrations usually occur in synoptically stagnant atmospheric conditions when local circulation patterns come into play; accordingly, our experiments emphasize the importance of the effect a priori profiles can have on satellite-derived applications under such conditions. To ensure that the quantitative representation of satellite-based trace gas retrievals on a daily basis is trustworthy and useable for air quality applications, atmospheric models providing a priori profiles for satellite retrievals should be well-tuned to reproduce complex local circulation such as sea-land breezes.

Integrating NASA Aqua AIRS in a Real‐Time NUCAPS Science‐To‐Applications System to Support Severe Weather Forecasting

AbstractIn recent years, National Oceanic and Atmospheric Administration (NOAA) Unique Combined Atmospheric Processing System (NUCAPS) hyperspectral infrared satellite sounding retrievals derived from Joint Polar Satellite System (JPSS) polar‐orbiting satellites have been documented as observations that add value to weather forecasting applications. NUCAPS is currently the operational algorithm delivering JPSS satellite sounding retrievals to the NOAA National Weather Service (NWS) and is based on the heritage Atmospheric Infrared Sounder (AIRS) Science Team algorithm for processing vertical temperature, moisture, and trace gas retrievals. For the Special Collection on “Twenty Years of Observations from AIRS,” we highlight the methodology we implemented to develop a prototype science‐to‐applications system to enable real‐time processing of AIRS satellite sounding retrievals through the NUCAPS algorithm (i.e., NUCAPS‐Aqua) to support weather forecasting applications. The addition of NUCAPS‐Aqua to experimental real‐time pathways alongside operational JPSS NUCAPS soundings, facilitated assessment of NUCAPS‐Aqua at the 2022 Hazardous Weather Testbed (HWT) Spring Experiment. Development of NUCAPS‐Aqua described in this technical report includes preservation of microwave observations and calculation of a‐priori regression coefficients. Additionally, the real‐time processing and challenges with implementing a science‐to‐applications system are discussed. Two illustrative pre‐convective forecasting examples analyzed by NWS forecasters during the 2022 HWT Spring Experiment are highlighted to demonstrate the benefit of NUCAPS‐Aqua as (a) special afternoon soundings, (b) an additional observation to assess temporal trends using multiple satellites, and (c) a complement to observational and model analysis.

Volcanic Clouds Characterization of the 2020–2022 Sequence of Mt. Etna Lava Fountains Using MSG-SEVIRI and Products’ Cross-Comparison

From December 2020 to February 2022, 66 lava fountains (LF) occurred at Etna volcano (Italy). Despite their short duration (an average of about two hours), they produced a strong impact on human life, environment, and air traffic. In this work, the measurements collected from the Spinning Enhanced Visible and InfraRed Imager (SEVIRI) instrument, on board Meteosat Second Generation (MSG) geostationary satellite, are processed every 15 min to characterize the volcanic clouds produced during the activities. In particular, a quantitative estimation of volcanic cloud top height (VCTH) and ash/ice/SO2 masses’ time series are obtained. VCTHs are computed by integrating three different retrieval approaches based on coldest pixel detection, plume tracking, and HYSPLIT models, while particles and gas retrievals are realized simultaneously by exploiting the Volcanic Plume Retrieval (VPR) real-time procedure. The discrimination between ashy and icy pixels is carried out by applying the Brightness Temperature Difference (BTD) method with thresholds obtained by making specific Radiative Transfer Model simulations. Results indicate a VCTH variation during the entire period between 4 and 13 km, while the SO2, ash, and ice total masses reach maximum values of about 50, 100, and 300 Gg, respectively. The cumulative ash, ice, and SO2 emitted from all the 2020–2022 LFs in the atmosphere are about 750, 2300, and 670 Gg, respectively. All the retrievals indicate that the overall activity can be grouped into 3 main periods in which it passes from high (December 2020 to March 2021), low (March to June 2021), and medium/high (June 2021 to February 2022). The different products have been validated by using TROPOspheric Monitoring Instrument (TROPOMI) polar satellite sensor, Volcano Observatory Notices for Aviation (VONA) bulletins, and by processing the SEVIRI data considering a different and more accurate retrieval approach. The products’ cross-comparison shows a generally good agreement, except for the SO2 total mass in case of high ash/ice content in the volcanic cloud.

Effect of dust morphology on chemical transport and UV-Vis trace gas retrieval models

Effect of dust morphology on chemical transport and UV-Vis trace gas retrieval models

SCIATRAN software package (V4.6): update and further development of aerosol, clouds, surface reflectance databases and models

Abstract. Since the initiation of development at the Institute of Environmental Physics (IUP), University of Bremen, in 1994, the radiative transfer model SCIATRAN (formerly GOMETRAN) has been continuously improved and new versions have been released (Rozanov et al., 1997, 2002, 2005, 2014, 2017). In the course of development, the SCIATRAN software package became capable of simulating radiative transfer processes through the Earth's atmosphere or coupled atmosphere–ocean system with a variety of approaches to treat the sphericity of the atmosphere (plane-parallel, pseudo-spherical, approximately spherical and full-spherical solutions) in both scalar and vector modes. Supported by a variety of built-in databases and parameterizations, these capabilities made SCIATRAN widely used for various remote-sensing applications related to the retrieval of atmospheric trace gases and characteristics of aerosols, clouds and surfaces. This paper presents an overview of the cloud, aerosol and surface (CAS) databases and models implemented in the SCIATRAN software package (V4.6) and provides some recommendations on their usage. The new implementations offer potential users a flexible interface to perform radiative transfer simulations: (1) accounting for multilayer liquid water, ice and mixed-phase clouds; (2) employing typical aerosol-type parameterizations (including vertical variability) used in the satellite and model communities as well as updated databases; (3) including various surface bidirectional reflectance distribution function (BRDF) and albedo models for land, vegetation, ocean, snow and melt ponds on sea ice. The most recent version of the radiative transfer model SCIATRAN is freely available at the website of the IUP, University of Bremen: http://www.iup.physik.uni-bremen.de/sciatran (last access: November 2022).

Using portable low-resolution spectrometers to evaluate Total Carbon Column Observing Network (TCCON) biases in North America

Abstract. EM27/SUN devices are portable solar-viewing Fourier transform spectrometers (FTSs) that are being widely used to constrain measurements of greenhouse gas emissions and validate satellite trace gas measurements. On a 6-week-long campaign in the summer of 2018, four EM27/SUN devices were taken to five Total Carbon Column Observing Network (TCCON) stations in North America, to measure side by side, to better understand their durability, the accuracy and precision of retrievals from their trace gas measurements, and to constrain site-to-site bias among TCCON sites. We developed new EM27/SUN data products using both previous and current versions of the retrieval algorithm (GGG2014 and GGG2020) and used coincident AirCore measurements to tie the gas retrievals to the World Meteorological Organization (WMO) trace gas standard scales. We also derived air-mass-dependent correction factors for the EM27/SUN devices. Pairs of column-averaged dry-air mole fractions (denoted with an X) measured by the EM27/SUN devices remained consistent compared to each other during the entire campaign, with a 10 min averaged precision of 0.3 ppm (parts per million) for XCO2, 1.7 ppb (parts per billion) for XCH4, and 2.5 ppb for XCO. The maximum biases between TCCON stations were reduced in GGG2020 relative to GGG2014 from 1.3 to 0.5 ppm for XCO2 and from 5.4 to 4.3 ppb for XCH4 but increased for XCO from 2.2 to 6.1 ppb. The increased XCO biases in GGG2020 are driven by measurements at sites influenced by urban emissions (Caltech and the Armstrong Flight Research Center) where the priors overestimate surface CO. In addition, in 2020, one EM27/SUN instrument was sent to the Canadian Arctic TCCON station at Eureka, and side-by-side measurements were performed in March–July. In contrast to the other TCCON stations that showed an improvement in the biases with the newer version of GGG, the biases between Eureka's TCCON measurements and those from the EM27/SUN degraded with GGG2020, but this degradation was found to be caused by a temperature dependence in the EM27/SUN oxygen retrievals that is not apparent in the GGG2014 retrievals.

Retrieval of atmospheric trace gases from satellite infrared limb sounding data

The Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) instrument which operated in the near-to-mid infrared on the Envisat satellite from 2002–2012 is a Fourier-transform spectrometer for the measurement of high-resolution atmospheric emission spectra at the Earth’s limb. The initial operational products are profiles of temperature, H2O, O3, CH4, N2O, HNO3, and NO2, and this list is extended to include the important GHG (greenhouse gases) and ODS (ozone depleting substances) species using MORSE (orbital retrieval processor). This paper discusses retrievals of minor trace species of HCFC-22, HOCl, OCS, C2H6, COF2, HCN, CF4, SF6, and CCl4. Preliminary zonal mean results of these retrievals are satisfactory except for HCN and CF4 species. We then use MIPAS to estimate the total F and Cl budget in the atmosphere. Comparisons with SLIMCAT are also discussed, with the results consistent. Finally, we focus on improving the retrieval method for minor trace species, COF2, by adjusting correlation length and a priori constraint, as well as the chi-square method introduced to analyze noise. Tests have shown that our improvement could get more information from the measurements.

Cloud parameter retrieval for Environmental trace gases Monitoring Instrument (EMI) using the O2-O2 absorption band

This study proposes an improved cloud parameter retrieval algorithm for the existing cloud parameter algorithm of the Environmental trace gases Monitoring Instrument (EMI) using the collision complex of the oxygen (O2-O2) absorption feature. The main improvements are the evaluation of the impact of temperature on the O2-O2 slant column densities (SCDs), and the well-corrected EMI measured reflectance. The cloud parameters will help improve the accuracy of EMI trace gas retrievals. The O2-O2 SCDs were fitted based on EMI-observed radiances and solar irradiance, and the impact of temperature on the O2-O2 SCD was evaluated. A simulated reflectance look-up table (LUT), as well as the O2-O2 SCD LUT, were established through the SCIATRAN radiative transfer model. Reflectance and O2-O2 SCD LUTs are functions of effective cloud fraction (ECF) and cloud pressure (CP), which can be inverted to ECF and CP LUTs. On this basis, the EMI ECF and CP were obtained using the EMI observation geometric information, EMI measured reflectance, and O2-O2 SCD to interpolate the ECF and CP LUTs. To evaluate the results, we performed an inter-comparison between the EMI cloud parameters, TROPOspheric Monitoring Instrument (TROPOMI) cloud products, Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) CP, and ground-based lidar cloud altitude. Of them, the one-day global ECF and CP of EMI and TROPOMI exhibited good agreement; the correlation coefficients were 0.925 and 0.866, respectively. Additionally, EMI was closer to the CALIOP results when the cloud pressure was >600 hPa. The comparison with the ground-based lidar cloud altitude also yielded good agreement during the continuous observation period from September 21 to November 10, 2019. The results prove that the improved EMI cloud retrieval algorithm could provide effective cloud products for EMI trace gas inversion.

Quantification and evaluation of atmospheric emissions from crop residue burning constrained by satellite observations in China during 2016–2020

In rural regions of China, crop residue burning (CRB) is the major biomass burning activity, which can result in massive emissions of atmospheric particulate, greenhouse gas, and trace gas pollutants. Based on Himawari-8 satellite fire radiative power and agricultural statistics data, we implemented a daily inventory of agricultural fire emissions in 2016–2020 with a 2-km spatial resolution, including atmospheric pollutants such as CO2, CH4, CO, N2O, NOX, NH3, SO2, PM10, PM2.5, Hg, OC, EC, and NMVOCs. Our inventory constrained by geostationary satellite monitoring is more consistent with the actual CRB emissions in China, as many flaring events occur surreptitiously in the early morning and late evening to avoid regulation, which may be overlooked by polar-orbiting satellites. The spatiotemporal characterizations of various CRB emissions are found to be consistent with multiple satellite trace gas retrievals. We also assessed the effectiveness of field burning bans in China. Combined with other relevant datasets, it was found that although China has been advocating for a long time not to burn straw in the open field, CRB emissions was not successfully controlled nationwide until 2016. We estimated that the cumulative reduction of CO2 CRB emissions alone amounts to 809 ± 651 (2σ) teragram (Tg) during the 13th Five-Year Plan period (2016–2020), with an average value equivalent to 1.2 times the total annual territorial CO2 emissions by fossil fuels from Germany in 2021 (675 Tg, ranked 1st in EU27 and 7th in the world). Our inventory also suggests that continuous, long-term controls are necessary. Otherwise, CRB emissions may only be delayed on a seasonal scale, rather than reduced.

Estimating Spectral Effects of Absorbing Aerosols on Backscattered UV Radiation

AbstractWe examine the spectral effects of tropospheric absorbing aerosol types on backscattered UV radiation from 300 to 400 nm. First, using satellite observations, we show a non‐linear spectral dependence below 340 nm for scenes with significant aerosol absorption. Lambert‐equivalent reflectivity also follows a non‐linear behavior and may become negative, therefore non‐physical, at shorter wavelengths. We then present radiative transfer calculations of UV radiances accounting for ozone and aerosol attenuation. The effects are quantified as spectral residuals, calculated by comparing radiances simulated with aerosols to those with a molecular atmosphere assuming spectrally independent Lambert‐equivalent surface reflectivity. Simulations are carried out for carbonaceous smoke and mineral dust aerosols using the present‐day optical models applied successfully in the Ozone Monitoring Instrument aerosol algorithm, OMAERUV. The spectral residual has a complex dependence on wavelength, aerosol optical and physical properties, and surface conditions. In all simulated cases, the spectral residual has a maximum around 320 nm and then diminishes rapidly at shorter wavelengths due to increased photon absorption by ozone in the stratosphere. However, we find the relationship between the spectral residual and that at 340 nm nearly linear for a wide range of these conditions. The relationship depends somewhat on the total column ozone. The theoretical results presented offer a means for correcting the effects of UV‐absorbing aerosols in trace gas retrievals without a priori knowledge of aerosol and surface properties. Since our technique of estimating spectral effects of aerosols applies to radiance residuals, and not a specific retrieval algorithm, it may be used broadly to correct the effects in various retrieval algorithms.

Intercomparison of Sentinel-5P TROPOMI cloud products for tropospheric trace gas retrievals

Abstract. Clouds have a strong impact on satellite measurements of tropospheric trace gases in the ultraviolet, visible, and near-infrared spectral ranges from space. Therefore, trace gas retrievals rely on information on cloud fraction, cloud albedo, and cloud height from cloud products. In this study, the cloud parameters from different cloud retrieval algorithms for the Sentinel-5 Precursor (S5P) TROPOspheric Monitoring Instrument (TROPOMI) are compared: the Optical Cloud Recognition Algorithm (OCRA) a priori cloud fraction, the Retrieval Of Cloud Information using Neural Networks (ROCINN) CAL (Clouds-As-Layers) cloud fraction and cloud top and base height, the ROCINN CRB (Clouds-as-Reflecting-Boundaries) cloud fraction and cloud height, the Fast Retrieval Scheme for Clouds from the Oxygen A-band (FRESCO) cloud fraction, the interpolated FRESCO cloud height from the TROPOMI NO2 product, the cloud fraction from the NO2 fitting window, the O2–O2 cloud fraction and cloud height, the Mainz Iterative Cloud Retrieval Utilities (MICRU) cloud fraction, and the Visible Infrared Imaging Radiometer Suite (VIIRS) cloud fraction. Two different versions of the TROPOMI cloud products OCRA/ROCINN, FRESCO, and the TROPOMI NO2 product are included in the comparisons (processor version 1.x and 2.x). Overall, the cloud parameters retrieved by the different algorithms show qualitative consistency in version 1.x and good agreement in version 2.x with the exception of the VIIRS cloud fraction, which cannot be directly compared to the other data. Differences between the cloud retrievals are found especially for small cloud heights with a cloud fraction threshold of 0.2, i.e. clouds that are particularly relevant for tropospheric trace gas retrievals. The cloud fractions of the different version 2 cloud products primarily differ over snow- and ice-covered pixels and scenes with sun glint, for which only MICRU includes an explicit treatment. All cloud parameters show some systematic problems related to the across-track dependence, where larger values are found at the edges of the satellite view. The consistency between the cloud parameters from different algorithms depends strongly on how the data are filtered for the comparison, for example, what quality value is used or whether snow- and ice-covered pixels are excluded from the analysis. In summary, clear differences were found between the results of various algorithms, but these differences are reduced in the most recent versions of the cloud data.

Impact of 3D cloud structures on the atmospheric trace gas products from UV–Vis sounders – Part 2: Impact on NO2 retrieval and mitigation strategies

Abstract. Operational retrievals of tropospheric trace gases from space-borne spectrometers are based on one-dimensional radiative transfer models. To minimize cloud effects, trace gas retrievals generally implement a simple cloud model based on radiometric cloud fraction estimates and photon path length corrections. The latter relies on measurements of the oxygen collision pair (O2–O2) absorption at 477 nm or on the oxygen A-band around 760 nm to determine an effective cloud height. In reality however, the impact of clouds is much more complex, involving unresolved sub-pixel clouds, scattering of clouds in neighbouring pixels, and cloud shadow effects, such that unresolved three-dimensional effects due to clouds may introduce significant biases in trace gas retrievals. Although clouds have significant effects on trace gas retrievals, the current cloud correction schemes are based on a simple cloud model, and the retrieved cloud parameters must be interpreted as effective values. Consequently, it is difficult to assess the accuracy of the cloud correction only based on analysis of the accuracy of the cloud retrievals, and this study focuses solely on the impact of the 3D cloud structures on the trace gas retrievals. In order to quantify this impact, we study NO2 as a trace gas example and apply standard retrieval methods including approximate cloud corrections to synthetic data generated by the state-of-the-art three-dimensional Monte Carlo radiative transfer model MYSTIC. A sensitivity study is performed for simulations including a box cloud, and the dependency on various parameters is investigated. The most significant bias is found for cloud shadow effects under polluted conditions. Biases depend strongly on cloud shadow fraction, NO2 profile, cloud optical thickness, solar zenith angle, and surface albedo. Several approaches to correct NO2 retrievals under cloud shadow conditions are explored. We find that air mass factors calculated using fitted surface albedo or corrected using the O2–O2 slant column density can partly mitigate cloud shadow effects. However, these approaches are limited to cloud-free pixels affected by surrounding clouds. A parameterization approach is presented based on relationships derived from the sensitivity study. This allows measurements to be identified for which the standard NO2 retrieval produces a significant bias and therefore provides a way to improve the current data flagging approach.

Polarization performance simulation for the GeoXO atmospheric composition instrument: NO2 retrieval impacts

Abstract. NOAA's Geostationary Extended Observations (GeoXO) constellation will continue and expand on the capabilities of the current generation of geostationary satellite systems to support US weather, ocean, atmosphere, and climate operations. It is planned to consist of a dedicated atmospheric composition instrument (ACX) to support air quality forecasting and monitoring by providing capabilities similar to missions such as TEMPO (Tropospheric Emission: Monitoring Pollution), currently planned to launch in 2023, as well as OMI (Ozone Monitoring Instrument), TROPOMI (TROPOspheric Monitoring Instrument), and GEMS (Geostationary Environment Monitoring Spectrometer) currently in operation. As the early phases of ACX development are progressing, design trade-offs are being considered to understand the relationship between instrument design choices and trace gas retrieval impacts. Some of these choices will affect the instrument polarization sensitivity (PS), which can have radiometric impacts on environmental satellite observations. We conducted a study to investigate how such radiometric impacts can affect NO2 retrievals by exploring their sensitivities to time of day, location, and scene type with an ACX instrument model that incorporates PS. The study addresses the basic steps of operational NO2 retrievals: the spectral fitting step and the conversion of slant column to vertical column via the air mass factor (AMF). The spectral fitting step was performed by generating at-sensor radiance from a clear-sky scene with a known NO2 amount, the application of an instrument model including both instrument PS and noise, and a physical retrieval. The spectral fitting step was found to mitigate the impacts of instrument PS. The AMF-related step was considered for clear-sky and partially cloudy scenes, for which instrument PS can lead to errors in interpreting the cloud content, propagating to AMF errors and finally to NO2 retrieval errors. For this step, the NO2 retrieval impacts were small but non-negligible for high NO2 amounts; we estimated that a typical high NO2 amount can cause a maximum retrieval error of 0.25×1015 molec. cm−2 for a PS of 5 %. These simulation capabilities were designed to aid in the development of a GeoXO atmospheric composition instrument that will improve our ability to monitor and understand the Earth's atmosphere.

Retrieval of greenhouse gases from GOSAT and GOSAT-2 using the FOCAL algorithm

Abstract. 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.