After a decade of stable or slightly decreasing global methane concentrations, ground‐based in situ data show that CH4 began increasing again in 2007 and that this increase continued through 2009. So far, space‐based retrievals sensitive to the lower troposphere in the time period under consideration have not been available. Here we report a long‐term data set of column‐averaged methane mixing ratios retrieved from spectra of the Scanning Imaging Absorption Spectrometer for Atmospheric Cartography (SCIAMACHY) instrument onboard Envisat. The retrieval quality after 2005 was severely affected by degrading detector pixels within the methane 2ν3 absorption band. We identified the most crucial problems in SCIAMACHY detector degradation and overcame the problem by applying a strict pixel mask as well as a new dark current characterization. Even though retrieval precision after the end of 2005 is invariably degraded, consistent methane retrievals from 2003 through 2009 are now possible. Regional time series in the Sahara, Australia, tropical Africa, South America, and Asia show the methane increase in 2007–2009, but we cannot yet draw a firm conclusion concerning the origin of the increase. Tropical Africa even seems to exhibit a negative anomaly in 2006, but an impact from changes in SCIAMACHY detector degradation cannot be excluded yet. Over Assakrem, Algeria, we observed strong similarities between SCIAMACHY measurements and ground‐based data in deseasonalized time series. We further show long‐term SCIAMACHY xCH4 averages at high spatial resolution that provide further insight into methane variations on regional scales. The Red Basin in China exhibits, on average, the highest methane abundance worldwide, while other localized features such as the Sudd wetlands in southern Sudan can also be identified in SCIAMACHY xCH4 averages.

Methane emissions due to accidents in the oil and natural gas sector are very challenging to monitor, and hence are seldom considered in emission inventories and reporting. One of the main reasons is the lack of measurements during such events. Here we report the detection of large methane emissions from a gas well blowout in Ohio during February to March 2018 in the total column methane measurements from the spaceborne Tropospheric Monitoring Instrument (TROPOMI). From these data, we derive a methane emission rate of 120 ± 32 metric tons per hour. This hourly emission rate is twice that of the widely reported Aliso Canyon event in California in 2015. Assuming the detected emission represents the average rate for the 20-d blowout period, we find the total methane emission from the well blowout is comparable to one-quarter of the entire state of Ohio’s reported annual oil and natural gas methane emission, or, alternatively, a substantial fraction of the annual anthropogenic methane emissions from several European countries. Our work demonstrates the strength and effectiveness of routine satellite measurements in detecting and quantifying greenhouse gas emission from unpredictable events. In this specific case, the magnitude of a relatively unknown yet extremely large accidental leakage was revealed using measurements of TROPOMI in its routine global survey, providing quantitative assessment of associated methane emissions.

Abstract. The effects of three important SCIAMACHY near-infrared instrument calibration issues on the retrieved methane (CH4) and carbon monoxide (CO) total columns have been investigated: the effects of the growing ice layer on the near-infrared detectors, the effects of the orbital variation of the instrument dark signal, and the effects of the dead/bad detector pixels. Corrections for each of these instrument calibration issues have been defined. The retrieved CH4 and CO total columns including these corrections show good agreement with CO measurements from the MOPITT satellite instrument and with CH4 model calculations by the chemistry transport model TM3. Using a systematic approach, it is shown that all three instrument calibration issues have a significant effect on the retrieved CH4 and CO total columns, although the impact on the CH4 total columns is more pronounced than for CO. Results for three different wavelength ranges are compared and show good agreement. The growing ice layer and the orbital variation of the dark signal show a systematic, but time-dependent effect on the retrieved CH4 and CO total columns, whereas the dead/bad pixels show a more random effect. The importance of accurate corrections for each of these instrument calibration issues is illustrated using examples where inaccurate corrections lead to a wrong interpretation of the results.

Abstract. The near-infrared spectra measured with the SCIAMACHY instrument on board the ENVISAT satellite suffer from several instrument calibration problems. The effects of three important instrument calibration issues on the retrieved methane (CH 4 ) and carbon monoxide (CO) total columns have been investigated: the effects of the growing ice layer on the near-infrared detectors, the effects of the orbital variation of the instrument dark signal, and the effects of the dead/bad detector pixels. Corrections for each of these instrument calibration issues have been defined. The retrieved CH 4 and CO total columns including these corrections show good agreement with CO measurements from the MOPITT satellite instrument and with CH 4 model calculations by the chemistry transport model TM3. Using a systematic approach, it is shown that all three instrument calibration issues have a significant effect on the retrieved CH 4 and CO total columns. However, the impact on the CH 4 total columns is more pronounced than for CO, because of its smaller variability. Results for three different wavelength ranges are compared and show good agreement. The growing ice layer and the orbital variation of the dark signal show a systematic, but time-dependent effect on the retrieved CH 4 and CO total columns, whereas the effect of the dead/bad pixels is rather unpredictable: some dead pixels show a random effect, some more systematic, and others no effect at all. The importance of accurate corrections for each of these instrument calibration issues is illustrated using examples where inaccurate corrections lead to a wrong interpretation of the results.Correspondence to: A. M. S. Gloudemans (a.gloudemans@sron.nl)

As atmospheric methane concentrations increase at record pace, it is critical to identify individual emission sources with high potential for mitigation. Here, we leverage the synergy between satellite instruments with different spatiotemporal coverage and resolution to detect and quantify emissions from individual landfills. We use the global surveying Tropospheric Monitoring Instrument (TROPOMI) to identify large emission hot spots and then zoom in with high-resolution target-mode observations from the GHGSat instrument suite to identify the responsible facilities and characterize their emissions. Using this approach, we detect and analyze strongly emitting landfills (3 to 29 t hour −1 ) in Buenos Aires, Delhi, Lahore, and Mumbai. Using TROPOMI data in an inversion, we find that city-level emissions are 1.4 to 2.6 times larger than reported in commonly used emission inventories and that the landfills contribute 6 to 50% of those emissions. Our work demonstrates how complementary satellites enable global detection, identification, and monitoring of methane superemitters at the facility level.