Inverse modeling of CH4 emissions for 2010 - 2011 using different satellite retrieval products from GOSAT and SCIAMACHY

Beginning in 2009 new space-borne observations of dry-air column-averaged mole fractions of atmospheric methane (XCH4) became available from the Thermal And Near infrared Sensor for carbon Observations - Fourier Transform Spectrometer (TANSO-FTS) instrument onboard the Greenhouse Gases Observing SATellite (GOSAT). Until April 2012 concurrent CH4 measurements were provided by the SCanning Imaging Absorption spectroMeter for Atmospheric CartograpHY (SCIAMACHY) instrument onboard ENVISAT. The GOSAT and SCIAMACHY XCH4 retrievals can be directly compared during their circa 32-month period of overlap. We estimate monthly average CH4 emissions between January 2010 and December 2011, using the TM5-4DVAR inverse modeling system. Additionally, high-accuracy measurements from the National Oceanic and Atmospheric Administration Earth System Research Laboratory (NOAA ESRL) global air sampling network are used, providing strong constraints of the remote surface atmosphere. We discuss five inversion scenarios that make use of different GOSAT and SCIAMACHY XCH4 retrieval products, including two sets of GOSAT proxy retrievals processed independently by the Netherlands Institute for Space Research (SRON) / Karlsruhe Institute of Technology (KIT), and the University of Leicester (UL), and the RemoTeC "Full-Physics" (FP) XCH4 retrievals available from SRON/KIT. 2-year average emission maps show a good overall agreement among all GOSAT-based inversions, but also compared to the SCIAMACHY-based inversion, with consistent flux adjustment patterns, particularly across Equatorial Africa and North America. The inversions are validated against independent shipboard and aircraft observations, and XCH4 measurements available from the Total Carbon Column Observing Network (TCCON). All GOSAT and SCIAMACHY inversions show very similar validation performance.JRC.H.2-Air and Climat

Copernicus Climate Change Service (C3S) Global Satellite Observations of Atmospheric Carbon Dioxide and Methane

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Design of production technology of specified component for conditions of workshop at IME FME Brno university of technology

Diplomová práce se zabývá návrhem a realizací technologie výroby součásti zadané firmou Frentech Aerospace s.r.o. pro podmínky dílny ÚST FSI VUT v Brně (laboratoře C2). Získaných poznatků je využito k návrhu inovované technologie výroby s využitím nástrojů firmy Pramet Tools, s.r.o. Technologie výroby součásti pro dílnu ÚST jsou zpracovány pro duralový materiál EN AW 6082. Součástí práce je technicko-ekonomické zhodnocení všech popsaných technologií výroby. Oba technologické postupy navržené pro podmínky laboratoře C2 jsou zhodnoceny společně a technologický postup firmy Frentech Aerospace s.r.o. je zhodnocen odděleně z důvodu zpracování technologie pro odlišný materiál polotovaru.Diploma thesis deals with design and implementation of manufacturing technology of a part which was given by company Frentech Aerospace s.r.o. Manufacturing technology is prepared for conditions of workshop of Department of Machining FME Brno UT (laboratory C2). Acquired knowledges are used for design of innovative manufacturing technology with cutting tools from company Pramet Tools, s.r.o. Manufacturing technologies of gained part are designed for alloy blank EN AW 6082. Technical-economical assessment of all manufacturing technologies is part of this thesis. Both of manufacturing technologies designed for laboratory C2 are assessed together and manufacturing technology given by company Frentech Aerospace s.r.o. is assessed alone due to using different blank material.

Computation and analysis of atmospheric carbon dioxide annual mean growth rates from satellite observations during 2003-2016

The growth rate of atmospheric carbon dioxide (CO2) reflects the net effect of emissions and uptake resulting from anthropogenic and natural carbon sources and sinks. Annual mean CO2 growth rates have been determined from satellite retrievals of column-averaged dry-air mole fractions of CO2, i.e. XCO2, for the years 2003 to 2016. The XCO2 growth rates agree with National Oceanic and Atmospheric Administration (NOAA) growth rates from CO2 surface observations within the uncertainty of the satellite-derived growth rates (mean difference +/- standard deviation: 0.0 +/- 0.3 ppm year(-1);R: 0.82). This new and independent data set confirms record-large growth rates of around 3 ppm year(-1) in 2015 and 2016, which are attributed to the 2015-2016 El Nino. Based on a comparison of the satellite-derived growth rates with human CO2 emissions from fossil fuel combustion and with El Nino Southern Oscillation (ENSO) indices, we estimate by how much the impact of ENSO dominates the impact of fossil-fuel-burning-related emissions in explaining the variance of the atmospheric CO2 growth rate. Our analysis shows that the ENSO impact on CO2 growth rate variations dominates that of human emissions throughout the period 2003-2016 but in particular during the period 2010-2016 due to strong La Nina and El Nino events. Using the derived growth rates and their uncertainties, we estimate the probability that the impact of ENSO on the variability is larger than the impact of human emissions to be 63 % for the time period 2003-2016. If the time period is restricted to 2010-2016, this probability increases to 94%

Evaluation and Analysis of the Seasonal Cycle and Variability of the Trend from GOSAT Methane Retrievals

Methane (CH_4) is a potent greenhouse gas with a large temporal variability. To increase the spatial coverage, methane observations are increasingly made from satellites that retrieve the column-averaged dry air mole fraction of methane (XCH_4). To understand and quantify the spatial differences of the seasonal cycle and trend of XCH_4 in more detail, and to ultimately help reduce uncertainties in methane emissions and sinks, we evaluated and analyzed the average XCH_4 seasonal cycle and trend from three Greenhouse Gases Observing Satellite (GOSAT) retrieval algorithms: National Institute for Environmental Studies algorithm version 02.75, RemoTeC CH_4 Proxy algorithm version 2.3.8 and RemoTeC CH_4 Full Physics algorithm version 2.3.8. Evaluations were made against the Total Carbon Column Observing Network (TCCON) retrievals at 15 TCCON sites for 2009–2015, and the analysis was performed, in addition to the TCCON sites, at 31 latitude bands between latitudes 44.43°S and 53.13°N. At latitude bands, we also compared the trend of GOSAT XCH_4 retrievals to the NOAA’s Marine Boundary Layer reference data. The average seasonal cycle and the non-linear trend were, for the first time for methane, modeled with a dynamic regression method called Dynamic Linear Model that quantifies the trend and the seasonal cycle, and provides reliable uncertainties for the parameters. Our results show that, if the number of co-located soundings is sufficiently large throughout the year, the seasonal cycle and trend of the three GOSAT retrievals agree well, mostly within the uncertainty ranges, with the TCCON retrievals. Especially estimates of the maximum day of XCH_4 agree well, both between the GOSAT and TCCON retrievals, and between the three GOSAT retrievals at the latitude bands. In our analysis, we showed that there are large spatial differences in the trend and seasonal cycle of XCH_4. These differences are linked to the regional CH_4 sources and sinks, and call for further research

Validation of TANSO-FTS/GOSAT XCO2 and XCH4 glint mode retrievals using TCCON data from near-ocean sites

The thermal And near infrared sensor for carbon observations Fourier transform spectrometer (TANSO-FTS) on board the Greenhouse Gases Observing Satellite (GOSAT) applies the normal nadir mode above the land ( land data ) and sun glint mode over the ocean ( ocean data ) to provide global distributions of column-averaged dry-air mole fractions of CO2 and CH4, or XCO2 and XCH4. Several algorithms have been developed to obtain highly accurate greenhouse gas concentrations from TANSO-FTS/GOSAT spectra. So far, all the retrieval algorithms have been validated with the measurements from ground-based Fourier transform spectrometers from the Total Carbon Column Observing Network (TCCON), but limited to the land data. In this paper, the ocean data of the SRPR, SRFP (the proxy and full-physics versions 2.3.5 of SRON/KIT\u27s RemoTeC algorithm), NIES (National Institute for Environmental Studies operational algorithm version 02.21) and ACOS (NASA\u27s Atmospheric CO2 Observations from Space version 3.5) are compared with FTIR measurements from five TCCON sites and nearby GOSAT land data. For XCO2, both land and ocean data of NIES, SRFP and ACOS show good agreement with TCCON measurements. Averaged over all TCCON sites, the relative biases of ocean data and land data are −0.33 and −0.13 % for NIES, 0.03 and 0.04 % for SRFP, 0.06 and −0.03 % for ACOS, respectively. The relative scatter ranges between 0.31 and 0.49 %. For XCH4, the relative bias of ocean data is even less than that of the land data for the NIES (0.02 vs. −0.35 %), SRFP (0.04 vs. 0.20 %) and SRPR (−0.02 vs. 0.06 %) algorithms. Compared to the results for XCO2, the XCH4 retrievals show larger relative scatter (0.65-0.81 %)

Toward Global Mapping of Methane With TROPOMI: First Results and Intersatellite Comparison to GOSAT

The TROPOspheric Monitoring Instrument (TROPOMI), launched on 13 October 2017, aboard the Sentinel‐5 Precursor satellite, measures reflected sunlight in the ultraviolet, visible, near‐infrared, and shortwave infrared spectral range. It enables daily global mapping of key atmospheric species for monitoring air quality and climate. We present the first methane observations from November and December 2017, using TROPOMI radiance measurements in the shortwave infrared band around 2.3 μm. We compare our results with the methane product obtained from the Greenhouse gases Observing SATellite (GOSAT). Although different spectral ranges and retrieval methods are used, we find excellent agreement between the methane products acquired from the two satellites with a mean difference of 13.6 ppb, standard deviation of 19.6 ppb, and Pearson's correlation coefficient of 0.95. Our preliminary results capture the latitudinal gradient and show expected regional enhancements, for example, in the African Sudd wetlands, with much more detail than has been observed before

Evaluation and Analysis of the Seasonal Cycle and Variability of the Trend from GOSAT Methane Retrievals

Methane (CH4) is a potent greenhouse gas with a large temporal variability. To increase the spatial coverage, methane observations are increasingly made from satellites that retrieve the column-averaged dry air mole fraction of methane (XCH4). To understand and quantify the spatial differences of the seasonal cycle and trend of XCH4 in more detail, and to ultimately help reduce uncertainties in methane emissions and sinks, we evaluated and analyzed the average XCH4 seasonal cycle and trend from three Greenhouse Gases Observing Satellite (GOSAT) retrieval algorithms: National Institute for Environmental Studies algorithm version 02.75, RemoTeC CH4 Proxy algorithm version 2.3.8 and RemoTeC CH4 Full Physics algorithm version 2.3.8. Evaluations were made against the Total Carbon Column Observing Network (TCCON) retrievals at 15 TCCON sites for 2009-2015, and the analysis was performed, in addition to the TCCON sites, at 31 latitude bands between latitudes 44.43°S and 53.13°N. At latitude bands, we also compared the trend of GOSAT XCH4 retrievals to the NOAA\u27s Marine Boundary Layer reference data. The average seasonal cycle and the non-linear trend were, for the first time for methane, modeled with a dynamic regression method called Dynamic Linear Model that quantifies the trend and the seasonal cycle, and provides reliable uncertainties for the parameters. Our results show that, if the number of co-located soundings is sufficiently large throughout the year, the seasonal cycle and trend of the three GOSAT retrievals agree well, mostly within the uncertainty ranges, with the TCCON retrievals. Especially estimates of the maximum day of XCH4 agree well, both between the GOSAT and TCCON retrievals, and between the three GOSAT retrievals at the latitude bands. In our analysis, we showed that there are large spatial differences in the trend and seasonal cycle of XCH4. These differences are linked to the regional CH4 sources and sinks, and call for further research

An Islamist Party, Constraints, Opportunities and Transformation to Post-Islamism: The Tajik Case

Year-to-year variations in the atmospheric methane (CH4) growth rate show significant correlation with climatic drivers. The second half of 2010 and the first half of 2011 experienced the strongest La Niña since the early 1980s, when global surface networks started monitoring atmospheric CH4 mole fractions. We use these surface measurements, retrievals of column-averaged CH4 mole fractions from GOSAT, new wetland inundation estimates, and atmospheric δ13C-CH4 measurements to estimate the impact of this strong La Niña on the global atmospheric CH4 budget. By performing atmospheric inversions, we find evidence of an increase in tropical CH4 emissions of ∼6–9 TgCH4 yr−1 during this event. Stable isotope data suggest that biogenic sources are the cause of this emission increase. We find a simultaneous expansion of wetland area, driven by the excess precipitation over the Tropical continents during the La Niña. Two process-based wetland models predict increases in wetland area consistent with observationally-constrained values, but substantially smaller per-area CH4 emissions, highlighting the need for improvements in such models. Overall, tropical wetland emissions during the strong La Niña were at least by 5% larger than the long-term mean