Three Years of Greenhouse Gas Column-Averaged Dry Air Mole Fractions Retrieved from Satellite - Part 2: Methane

Abstract. Carbon dioxide (CO2) and methane (CH4) are the two most important anthropogenic greenhouse gases. SCIAMACHY on ENVISAT is the first satellite instrument whose measurements are sensitive to concentration changes of the two gases at all altitude levels down to the Earth's surface where the source/sink signals are largest. We have processed three years (2003-2005) of SCIAMACHY nearinfrared nadir measurements to simultaneously retrieve vertical columns of CO2 (from the 1.58µm absorption band), CH4 (1.66µm) and oxygen (O2 A-band at 0.76µm) using the scientific retrieval algorithm WFM-DOAS.We show that the latest version of WFM-DOAS, version 1.0, which is used for this study, has been significantly improved with respect to its accuracy compared to the previous versions while essentially maintaining its high processing speed (1 min per orbit, corresponding to 6000 single measurements, and per gas on a standard PC). The greenhouse gas columns are converted to dry air column-averaged mole fractions, denoted XCO2 (in ppm) and XCH4 (in ppb), by dividing the greenhouse gas columns by simultaneously retrieved dry air columns. For XCO2 dry air columns are obtained from the retrieved O2 columns. For XCH4 dry air columns are obtained from the retrieved CO2 columns because of better cancellation of light path related errors compared to using O2 columns retrieved from the spectrally distant O2 Aband. Here we focus on a discussion of the XCH4 data set. The XCO2 data set is discussed in a separate paper (Part 1). For 2003 we present detailed comparisons with the TM5 model which has been optimally matched to highly accurate but sparse methane surface observations. After accounting for a systematic low bias of 2% agreement with TM5 is typically within 1¿2%. We investigated to what extent the SCIAMACHY XCH4 is influenced by the variability of atmospheric CO2 using global CO2 fields from NOAA¿s CO2 assimilation system CarbonTracker. We show that the CO2 corrected and uncorrected XCH4 spatio-temporal pattern are very similar but that agreement with TM5 is better for the CarbonTracker CO2 corrected XCH4. In line with previous studies (e.g., Frankenberg et al., 2005b) we find higher methane over the tropics compared to the model. We show that tropical methane is also higher when normalizing the CH4 columns with retrieved O2 columns instead of CO2. In consistency with recent results of Frankenberg et al. (2008b) it is shown that the magnitude of the retrieved tropical methane is sensitive to the choice of the spectroscopic line parameters of water vapour. Concerning inter-annual variability we find similar methane spatio-temporal pattern for 2003 and 2004. For 2005 the retrieved methane shows significantly higher variability compared to the two previous years, most likely due to somewhat larger noise of the spectral measurements.JRC.H.2-Air and Climat

Remote sensing of fugitive methane emissions from oil and gas production in North American tight geologic formations

In the past decade, there has been a massive growth in the horizontal drilling and hydraulic fracturing of shale gas and tight oil reservoirs to exploit formerly inaccessible or unprofitable energy resources in rock formations with low permeability. In North America, these unconventional domestic sources of natural gas and oil provide an opportunity to achieve energy self-sufficiency and to reduce greenhouse gas emissions when displacing coal as a source of energy in power plants. However, fugitive methane emissions in the production process may counter the benefit over coal with respect to climate change and therefore need to be well quantified. Here we demonstrate that positive methane anomalies associated with the oil and gas industries can be detected from space and that corresponding regional emissions can be constrained using satellite observations. On the basis of a mass-balance approach, we estimate that methane emissions for two of the fastest growing production regions in the United States, the Bakken and Eagle Ford formations, have increased by 990 ± 650 ktCH4 yr−1 and 530 ± 330 ktCH4 yr−1 between the periods 2006–2008 and 2009–2011. Relative to the respective increases in oil and gas production, these emission estimates correspond to leakages of 10.1% ± 7.3% and 9.1% ± 6.2% in terms of energy content, calling immediate climate benefit into question and indicating that current inventories likely underestimate the fugitive emissions from Bakken and Eagle Ford

CH4_4 Fluxes Derived from Assimilation of TROPOMI XCH4_4 in CarbonTracker Europe-CH4_4: Evaluation of Seasonality and Spatial Distribution in the Northern High Latitudes

Recent advances in satellite observations of methane provide increased opportunities for inverse modeling. However, challenges exist in the satellite observation optimization and retrievals for high latitudes. In this study, we examine possibilities and challenges in the use of the total column averaged dry-air mole fractions of methane (XCH$_4$) data over land from the TROPOspheric Monitoring Instrument (TROPOMI) on board the Sentinel 5 Precursor satellite in the estimation of CH4 fluxes using the CarbonTracker Europe-CH$_4$ (CTE-CH$_4$) atmospheric inverse model. We carry out simulations assimilating two retrieval products: Netherlands Institute for Space Research’s (SRON) operational and University of Bremen’s Weighting Function Modified Differential Optical Absorption Spectroscopy (WFM-DOAS). For comparison, we also carry out a simulation assimilating the ground-based surface data. Our results show smaller regional emissions in the TROPOMI inversions compared to the prior and surface inversion, although they are roughly within the range of the previous studies. The wetland emissions in summer and anthropogenic emissions in spring are lesser. The inversion results based on the two satellite datasets show many similarities in terms of spatial distribution and time series but also clear differences, especially in Canada, where CH$_4$ emission maximum is later, when the SRON’s operational data are assimilated. The TROPOMI inversions show higher CH$_4$ emissions from oil and gas production and coal mining from Russia and Kazakhstan. The location of hotspots in the TROPOMI inversions did not change compared to the prior, but all inversions indicated spatially more homogeneous high wetland emissions in northern Fennoscandia. In addition, we find that the regional monthly wetland emissions in the TROPOMI inversions do not correlate with the anthropogenic emissions as strongly as those in the surface inversion. The uncertainty estimates in the TROPOMI inversions are more homogeneous in space, and the regional uncertainties are comparable to the surface inversion. This indicates the potential of the TROPOMI data to better separately estimate wetland and anthropogenic emissions, as well as constrain spatial distributions. This study emphasizes the importance of quantifying and taking into account the model and retrieval uncertainties in regional levels in order to improve and derive more robust emission estimates

A scientific algorithm to simultaneously retrieve carbon monoxide and methane from TROPOMI onboard Sentinel-5 Precursor

Carbon monoxide (CO) is an important atmospheric constituent affecting air quality, and methane (CH$_{4}$) is the second most important greenhouse gas contributing to human-induced climate change. Detailed and continuous observations of these gases are necessary to better assess their impact on climate and atmospheric pollution. While surface and airborne measurements are able to accurately determine atmospheric abundances on local scales, global coverage can only be achieved using satellite instruments. The TROPOspheric Monitoring Instrument (TROPOMI) onboard the Sentinel-5 Precursor satellite, which was successfully launched in October 2017, is a spaceborne nadirviewing imaging spectrometer measuring solar radiation reflected by the Earth in a push-broom configuration. It has a wide swath on the terrestrial surface and covers wavelength bands between the ultraviolet (UV) and the shortwave infrared (SWIR), combining a high spatial resolution with daily global coverage. These characteristics enable the determination of both gases with an unprecedented level of detail on a global scale, introducing new areas of application. Abundances of the atmospheric column-averaged dry air mole fractions XCO and XCH$_{4}$ are simultaneously retrieved from TROPOMI’s radiance measurements in the 2:3 μm spectral range of the SWIR part of the solar spectrum using the scientific retrieval algorithm Weighting Function Modified Differential Optical Absorption Spectroscopy (WFMDOAS). This algorithm is intended to be used with the operational algorithms for mutual verification and to provide new geophysical insights. We introduce the algorithm in detail, including expected error characteristics based on synthetic data, a machine-learning-based quality filter, and a shallow learning calibration procedure applied in the post-processing of the XCH$_{4}$ data. The quality of the results based on real TROPOMI data is assessed by validation with ground-based Fourier transform spectrometer (FTS) measurements providing realistic error estimates of the satellite data: the XCO data set is characterised by a random error of 5:1 ppb (5:8 %) and a systematic error of 1:9 ppb (2:1 %); the XCH$_{4}$ data set exhibits a random error of 14:0 ppb (0:8 %) and a systematic error of 4:3 ppb (0:2 %). The natural XCO and XCH$_{4}$ variations are well-captured by the satellite retrievals, which is demonstrated by a high correlation with the validation data (R = 0:97 for XCO and R D 0:91 for XCH$_{4}$ based on daily averages). We also present selected results from the mission start until the end of 2018, including a first comparison to the operational products and examples of the detection of emission sources in a single satellite overpass, such as CO emissions from the steel industry and CH$_{4}$ emissions from the energy sector, which potentially allows for the advance of emission monitoring and air quality assessments to an entirely new level

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%

Ensemble-based satellite-derived carbon dioxide and methane column-averaged dry-air mole fraction data sets (2003-2018) for carbon and climate applications

Satellite retrievals of column-averaged dry-air mole fractions of carbon dioxide (CO₂) and methane (CH₄), denoted XCO₂ and XCH₄, respectively, have been used in recent years to obtain information on natural and anthropogenic sources and sinks and for other applications such as comparisons with climate models. Here we present new data sets based on merging several individual satellite data products in order to generate consistent long-term climate data records (CDRs) of these two Essential Climate Variables (ECVs). These ECV CDRs, which cover the time period 2003–2018, have been generated using an ensemble of data products from the satellite sensors SCIAMACHY/ENVISAT and TANSO-FTS/GOSAT and (for XCO₂) for the first time also including data from the Orbiting Carbon Observatory 2 (OCO-2) satellite. Two types of products have been generated: (i) Level 2 (L2) products generated with the latest version of the ensemble median algorithm (EMMA) and (ii) Level 3 (L3) products obtained by gridding the corresponding L2 EMMA products to obtain a monthly 5∘×5∘ data product in Obs4MIPs (Observations for Model Intercomparisons Project) format. The L2 products consist of daily NetCDF (Network Common Data Form) files, which contain in addition to the main parameters, i.e., XCO₂ or XCH₄, corresponding uncertainty estimates for random and potential systematic uncertainties and the averaging kernel for each single (quality-filtered) satellite observation. We describe the algorithms used to generate these data products and present quality assessment results based on comparisons with Total Carbon Column Observing Network (TCCON) ground-based retrievals. We found that the XCO₂ Level 2 data set at the TCCON validation sites can be characterized by the following figures of merit (the corresponding values for the Level 3 product are listed in brackets) – single-observation random error (1σ): 1.29 ppm (monthly: 1.18 ppm); global bias: 0.20 ppm (0.18 ppm); and spatiotemporal bias or relative accuracy (1σ): 0.66 ppm (0.70 ppm). The corresponding values for the XCH₄ products are single-observation random error (1σ): 17.4 ppb (monthly: 8.7 ppb); global bias: −2.0 ppb (−2.9 ppb); and spatiotemporal bias (1σ): 5.0 ppb (4.9 ppb). It has also been found that the data products exhibit very good long-term stability as no significant long-term bias trend has been identified. The new data sets have also been used to derive annual XCO₂ and XCH₄ growth rates, which are in reasonable to good agreement with growth rates from the National Oceanic and Atmospheric Administration (NOAA) based on marine surface observations. The presented ECV data sets are available (from early 2020 onwards) via the Climate Data Store (CDS, https://cds.climate.copernicus.eu/, last access: 10 January 2020) of the Copernicus Climate Change Service (C3S, https://climate.copernicus.eu/, last access: 10 January 2020)

Auswertung und Interpretation von Satellitenmessungen im nahinfraroten Spektralbereich: Atmosphärisches Kohlenstoffdioxid und Methan

Carbon dioxide (CO2) and methane (CH4) are the two most important anthropogenic greenhouse gases. SCIAMACHY on ENVISAT is the first satellite instrument whose measurements are sensitive to concentration changes of the two gases at all altitude levels down to the Earth's surface where the source/sink signals are largest. Three years (2003-2005) of SCIAMACHY near-infrared nadir measurements have been processed to simultaneously retrieve vertical columns of CO2, CH4, and oxygen using the scientific retrieval algorithm WFM-DOAS. The latest version of WFM-DOAS, version 1.0, which was developed within the scope of this thesis, has been significantly improved with respect to its accuracy compared to the previous versions while essentially maintaining its high processing speed. The greenhouse gas columns are converted to column-averaged dry air mole fractions, denoted XCO2 and XCH4, by dividing the greenhouse gas columns by simultaneously retrieved dry air columns. For XCO2 dry air columns are obtained from the retrieved O2 columns. For XCH4 dry air columns are obtained from the retrieved CO2 columns because of better cancellation of light path related errors compared to using O2 columns retrieved from the spectrally distant O2 A-band.The satellite CO2 data set is compared with ground based Fourier Transform Spectroscopy (FTS) measurements and results from the global assimilation system CarbonTracker showing good agreement concerning the annual increase as well as the seasonal cycle over the northern hemisphere. However, for the southern hemisphere, where significantly less data are available for averaging, the amplitude and phase of the seasonal cycle show systematic differences arising partially from the O2 normalisation most likely caused by unconsidered scattering effects due to subvisual cirrus clouds. Based on the error analysis and on the comparison with the reference data it can be concluded that the XCO2 data set can be characterised by a single measurement retrieval precision (random error) of 1-2%, a systematic low bias of about 1.5%, and by a relative accuracy of about 1-2% for monthly averages at a spatial resolution of about 7°x7°. Averaging the retrieved XCO2 over all three years provides elevated CO2 over densely populated and industrialised source regions indicating that strong regional anthropogenic CO2 emissions can be potentially detected from space.The satellite CH4 data set is compared with global model simulations based on the TM5 model optimised versus high-accuracy surface measurements from the NOAA/ESRL network. After accounting for a systematic low bias of circa 2% agreement with TM5 is typically within 1-2%. The single measurement retrieval precision of XCH4 is estimated to be 1.5-1.7%. It is investigated to what extent the SCIAMACHY XCH4 is influenced by the variability of atmospheric CO2 using global CO2 fields from CarbonTracker showing that agreement with TM5 is better for the CarbonTracker CO2 corrected XCH4. In line with other studies higher methane over the tropics is found compared to the model. Tropical methane is also higher when normalising the CH4 columns with retrieved O2 columns instead of CO2. However, the magnitude of the retrieved tropical methane enhancement is sensitive to changes in spectroscopy and possible inaccuracies in the spectroscopic parameters can thus contribute to a potential overestimation of the tropical methane. First inverse modelling results for methane surface fluxes are presented for the year 2004 performed at the European Commission's Joint Research Centre (EC-JRC) by Peter Bergamaschi

Analysis and interpretation of satellite measurements in the near-infrared spectral region: Atmospheric carbon dioxide and methane

Carbon dioxide (CO2) and methane (CH4) are the two most important anthropogenic greenhouse gases. SCIAMACHY on ENVISAT is the first satellite instrument whose measurements are sensitive to concentration changes of the two gases at all altitude levels down to the Earth's surface where the source/sink signals are largest. Three years (2003-2005) of SCIAMACHY near-infrared nadir measurements have been processed to simultaneously retrieve vertical columns of CO2, CH4, and oxygen using the scientific retrieval algorithm WFM-DOAS. The latest version of WFM-DOAS, version 1.0, which was developed within the scope of this thesis, has been significantly improved with respect to its accuracy compared to the previous versions while essentially maintaining its high processing speed. The greenhouse gas columns are converted to column-averaged dry air mole fractions, denoted XCO2 and XCH4, by dividing the greenhouse gas columns by simultaneously retrieved dry air columns. For XCO2 dry air columns are obtained from the retrieved O2 columns. For XCH4 dry air columns are obtained from the retrieved CO2 columns because of better cancellation of light path related errors compared to using O2 columns retrieved from the spectrally distant O2 A-band.The satellite CO2 data set is compared with ground based Fourier Transform Spectroscopy (FTS) measurements and results from the global assimilation system CarbonTracker showing good agreement concerning the annual increase as well as the seasonal cycle over the northern hemisphere. However, for the southern hemisphere, where significantly less data are available for averaging, the amplitude and phase of the seasonal cycle show systematic differences arising partially from the O2 normalisation most likely caused by unconsidered scattering effects due to subvisual cirrus clouds. Based on the error analysis and on the comparison with the reference data it can be concluded that the XCO2 data set can be characterised by a single measurement retrieval precision (random error) of 1-2%, a systematic low bias of about 1.5%, and by a relative accuracy of about 1-2% for monthly averages at a spatial resolution of about 7°x7°. Averaging the retrieved XCO2 over all three years provides elevated CO2 over densely populated and industrialised source regions indicating that strong regional anthropogenic CO2 emissions can be potentially detected from space.The satellite CH4 data set is compared with global model simulations based on the TM5 model optimised versus high-accuracy surface measurements from the NOAA/ESRL network. After accounting for a systematic low bias of circa 2% agreement with TM5 is typically within 1-2%. The single measurement retrieval precision of XCH4 is estimated to be 1.5-1.7%. It is investigated to what extent the SCIAMACHY XCH4 is influenced by the variability of atmospheric CO2 using global CO2 fields from CarbonTracker showing that agreement with TM5 is better for the CarbonTracker CO2 corrected XCH4. In line with other studies higher methane over the tropics is found compared to the model. Tropical methane is also higher when normalising the CH4 columns with retrieved O2 columns instead of CO2. However, the magnitude of the retrieved tropical methane enhancement is sensitive to changes in spectroscopy and possible inaccuracies in the spectroscopic parameters can thus contribute to a potential overestimation of the tropical methane. First inverse modelling results for methane surface fluxes are presented for the year 2004 performed at the European Commission's Joint Research Centre (EC-JRC) by Peter Bergamaschi