scholarly journals Using satellites to uncover large methane emissions from landfills

2021 ◽  
Author(s):  
Joannes Maasakkers ◽  
Daniel Varon ◽  
Aldís Elfarsdóttir ◽  
Jason McKeever ◽  
Dylan Jervis ◽  
...  
Keyword(s):  
High Resolution ◽  
Hot Spots ◽  
Buenos Aires ◽  
Methane Emissions ◽  
Emission Sources ◽  
Emission Inventories ◽  
Atmospheric Methane ◽  
Target Mode ◽  
Facility Level ◽  
Methane Concentrations

As atmospheric methane concentrations increase at record pace, it is critical to identify individual emission sources with high potential for mitigation. Landfills are responsible for large methane emissions that can be readily abated but have been sparsely observed. Here we leverage the synergy between satellite instruments with different spatiotemporal coverage and resolution to detect and quantify emissions from individual landfill facilities. 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 ‘tip and cue’ approach, we detect and analyze strongly emitting landfills (3-29 t hr−1) in Buenos Aires (Argentina), Delhi (India), Lahore (Pakistan), and Mumbai (India). We find that city-level emissions are 1.6-2.8 times larger than reported in commonly used emission inventories and that the landfills contribute 5-47% of those emissions. Our work demonstrates how complementary satellites enable global detection, identification, and monitoring of methane super-emitters at the facility-level.

scholarly journals Simulations of atmospheric methane for Cape Grim, Tasmania, to constrain southeastern Australian methane emissions

2015 ◽  
Vol 15 (1) ◽  
pp. 305-317 ◽  
Author(s):  
Z. M. Loh ◽  
R. M. Law ◽  
K. D. Haynes ◽  
P. B. Krummel ◽  
L. P. Steele ◽  
...  
Keyword(s):  
Climate Models ◽  
Atmospheric Model ◽  
Methane Emissions ◽  
Atmospheric Methane ◽  
Austral Spring ◽  
Southeastern Australia ◽  
Australian Continent ◽  
The Impact ◽  
Methane Concentrations ◽  
Cape Grim

Abstract. This study uses two climate models and six scenarios of prescribed methane emissions to compare modelled and observed atmospheric methane between 1994 and 2007, for Cape Grim, Australia (40.7° S, 144.7° E). The model simulations follow the TransCom-CH4 protocol and use the Australian Community Climate and Earth System Simulator (ACCESS) and the CSIRO Conformal-Cubic Atmospheric Model (CCAM). Radon is also simulated and used to reduce the impact of transport differences between the models and observations. Comparisons are made for air samples that have traversed the Australian continent. All six emission scenarios give modelled concentrations that are broadly consistent with those observed. There are three notable mismatches, however. Firstly, scenarios that incorporate interannually varying biomass burning emissions produce anomalously high methane concentrations at Cape Grim at times of large fire events in southeastern Australia, most likely due to the fire methane emissions being unrealistically input into the lowest model level. Secondly, scenarios with wetland methane emissions in the austral winter overestimate methane concentrations at Cape Grim during wintertime while scenarios without winter wetland emissions perform better. Finally, all scenarios fail to represent a~methane source in austral spring implied by the observations. It is possible that the timing of wetland emissions in the scenarios is incorrect with recent satellite measurements suggesting an austral spring (September–October–November), rather than winter, maximum for wetland emissions.

scholarly journals Updated Global Fuel Exploitation Inventory (GFEI) for methane emissions from the oil, gas, and coal sectors: evaluation with inversions of atmospheric methane observations

2021 ◽  
Author(s):  
Tia R. Scarpelli ◽  
Daniel J. Jacob ◽  
Shayna Grossman ◽  
Xiao Lu ◽  
Zhen Qu ◽  
...  
Keyword(s):  
Climate Change ◽  
Methane Emissions ◽  
Emission Inventories ◽  
Atmospheric Methane ◽  
Intergovernmental Panel ◽  
Gas Emissions ◽  
The Us ◽  
Prior Estimate ◽  
Future Evaluation ◽  
Oil Gas

Abstract. We present an updated version of the Global Fuel Exploitation Inventory (GFEI) for methane emissions and evaluate it with results from global inversions of atmospheric methane observations from satellite (GOSAT) and in situ platforms (GLOBALVIEWplus). GFEI allocates methane emissions from oil, gas, and coal sectors and subsectors to a 0.1° × 0.1° grid by using the national emissions reported by individual countries to the United Nations Framework Convention on Climate Change (UNFCCC) and mapping them to infrastructure locations. Our updated GFEI v2 gives annual emissions for 2010–2019 that incorporate the most recent UNFCCC national reports, new oil/gas well locations, and improved spatial distribution of emissions for Canada, Mexico, and China. Russia's oil/gas emissions decrease by 83 % in its latest UNFCCC report while Nigerian emissions increase sevenfold, reflecting changes in assumed emission factors. Global gas emissions in GFEI v2 show little net change from 2010 to 2019 while oil emissions decrease and coal emissions slightly increase. Global emissions in GFEI v2 are lower than the EDGAR v6 and IEA inventories for all sectors though there is considerable variability in the comparison for individual countries. GFEI v2 estimates higher emissions by country than the Climate TRACE inventory with notable exceptions in Russia, the US, and the Middle East. Inversion results using GFEI as a prior estimate confirm the lower Russian emissions in the latest UNFCCC report but Nigerian emissions are too high. Oil/gas emissions are generally underestimated by the national inventories for the highest emitting countries including the US, Venezuela, Uzbekistan, Canada, and Turkmenistan. Offshore emissions in GFEI tend to be overestimated. Our updated GFEI v2 provides a platform for future evaluation of national emission inventories reported to the UNFCCC using the newer generation of satellite instruments such as TROPOMI with improved coverage and spatial resolution. It responds to recent aspirations of the Intergovernmental Panel on Climate Change (IPCC) to integrate top-down and bottom-up information into the construction of national emission inventories.

scholarly journals Seasonal and interannual variability in wetland methane emissions simulated by CLM4Me' and CAM-chem and comparisons to observations of concentrations

2015 ◽  
Vol 12 (13) ◽  
pp. 4029-4049 ◽  
Author(s):  
L. Meng ◽  
R. Paudel ◽  
P. G. M. Hess ◽  
N. M. Mahowald
Keyword(s):  
Interannual Variability ◽  
Spatial Patterns ◽  
Methane Emission ◽  
Methane Concentration ◽  
Methane Emissions ◽  
Data Availability ◽  
Latitudinal Gradients ◽  
Atmospheric Methane ◽  
Seasonal And Interannual Variability ◽  
Methane Concentrations

Abstract. Understanding the temporal and spatial variation of wetland methane emissions is essential to the estimation of the global methane budget. Our goal for this study is three-fold: (i) to evaluate the wetland methane fluxes simulated in two versions of the Community Land Model, the Carbon-Nitrogen (CN; i.e., CLM4.0) and the Biogeochemistry (BGC; i.e., CLM4.5) versions using the methane emission model CLM4Me' so as to determine the sensitivity of the emissions to the underlying carbon model; (ii) to compare the simulated atmospheric methane concentrations to observations, including latitudinal gradients and interannual variability so as to determine the extent to which the atmospheric observations constrain the emissions; (iii) to understand the drivers of seasonal and interannual variability in atmospheric methane concentrations. Simulations of the transport and removal of methane use the Community Atmosphere Model with chemistry (CAM-chem) model in conjunction with CLM4Me' methane emissions from both CN and BGC simulations and other methane emission sources from literature. In each case we compare model-simulated atmospheric methane concentration with observations. In addition, we simulate the atmospheric concentrations based on the TransCom wetland and rice paddy emissions derived from a different terrestrial ecosystem model, Vegetation Integrative Simulator for Trace gases (VISIT). Our analysis indicates CN wetland methane emissions are higher in the tropics and lower at high latitudes than emissions from BGC. In CN, methane emissions decrease from 1993 to 2004 while this trend does not appear in the BGC version. In the CN version, methane emission variations follow satellite-derived inundation wetlands closely. However, they are dissimilar in BGC due to its different carbon cycle. CAM-chem simulations with CLM4Me' methane emissions suggest that both prescribed anthropogenic and predicted wetlands methane emissions contribute substantially to seasonal and interannual variability in atmospheric methane concentration. Simulated atmospheric CH4 concentrations in CAM-chem are highly correlated with observations at most of the 14 measurement stations evaluated with an average correlation between 0.71 and 0.80 depending on the simulation (for the period of 1993–2004 for most stations based on data availability). Our results suggest that different spatial patterns of wetland emissions can have significant impacts on Northern and Southern hemisphere (N–S) atmospheric CH4 concentration gradients and growth rates. This study suggests that both anthropogenic and wetland emissions have significant contributions to seasonal and interannual variations in atmospheric CH4 concentrations. However, our analysis also indicates the existence of large uncertainties in terms of spatial patterns and magnitude of global wetland methane budgets, and that substantial uncertainty comes from the carbon model underlying the methane flux modules.

scholarly journals Satellite-derived methane hotspot emission estimates using a fast data-driven method

2016 ◽  
Author(s):  
Michael Buchwitz ◽  
Oliver Schneising ◽  
Maximilian Reuter ◽  
Jens Heymann ◽  
Sven Krautwurst ◽  
...  
Keyword(s):  
Central Valley ◽  
Methane Emissions ◽  
Mitigation Strategies ◽  
Emission Sources ◽  
Fast Method ◽  
Atmospheric Methane ◽  
Near Surface ◽  
Uncertainty Estimates ◽  
Four Corners ◽  
Oil Gas

Abstract. Methane is an important atmospheric greenhouse gas and an adequate understanding of its emission sources is needed for climate change assessments, predictions and the development and verification of emission mitigation strategies. Satellite retrievals of near-surface-sensitive column-averaged dry-air mole fractions of atmospheric methane, i.e., XCH4, can be used to quantify methane emissions. Here we present a simple and fast method to estimate emissions of methane hotspots from satellite-derived XCH4 maps. We apply this method to an ensemble of XCH4 data products consisting of two products from SCIAMACHY/ENVISAT and two products from TANSO-FTS/GOSAT covering the time period 2003–2014. We obtain annual emissions of the source areas Four Corners in the southwestern USA, for the southern part of Central Valley, California, and for Azerbaijan and Turkmenistan. We find that our estimated emissions are in good agreement with independently derived estimates for Four Corners and Azerbaijan. For the Central Valley and Turkmenistan our estimated annual emissions are higher compared to the EDGAR v4.2 anthropogenic emission inventory. For Turkmenistan we find on average about 50 % higher emissions with our annual emission uncertainty estimates overlapping with the EDGAR emissions. For the region around Bakersfield in the Central Valley we find a factor of 6–9 higher emissions compared to EDGAR albeit with large uncertainty. Major methane emission sources in this region are oil/gas and livestock. Our findings corroborate recently published studies based on aircraft and satellite measurements and new bottom-up estimates reporting significantly underestimated methane emissions of oil/gas and/or livestock in this area in inventories.

scholarly journals Satellite observations of atmospheric methane and their value for quantifying methane emissions

2016 ◽  
Vol 16 (22) ◽  
pp. 14371-14396 ◽  
Author(s):  
Daniel J. Jacob ◽  
Alexander J. Turner ◽  
Joannes D. Maasakkers ◽  
Jianxiong Sheng ◽  
Kang Sun ◽  
...  
Keyword(s):  
Regional Scale ◽  
Methane Emissions ◽  
Point Sources ◽  
Satellite Observations ◽  
Anthropogenic Sources ◽  
Emission Inventories ◽  
Atmospheric Methane ◽  
High Quality ◽  
Spatial Coverage ◽  
Wide Range

Abstract. Methane is a greenhouse gas emitted by a range of natural and anthropogenic sources. Atmospheric methane has been measured continuously from space since 2003, and new instruments are planned for launch in the near future that will greatly expand the capabilities of space-based observations. We review the value of current, future, and proposed satellite observations to better quantify and understand methane emissions through inverse analyses, from the global scale down to the scale of point sources and in combination with suborbital (surface and aircraft) data. Current global observations from Greenhouse Gases Observing Satellite (GOSAT) are of high quality but have sparse spatial coverage. They can quantify methane emissions on a regional scale (100–1000 km) through multiyear averaging. The Tropospheric Monitoring Instrument (TROPOMI), to be launched in 2017, is expected to quantify daily emissions on the regional scale and will also effectively detect large point sources. A different observing strategy by GHGSat (launched in June 2016) is to target limited viewing domains with very fine pixel resolution in order to detect a wide range of methane point sources. Geostationary observation of methane, still in the proposal stage, will have the unique capability of mapping source regions with high resolution, detecting transient "super-emitter" point sources and resolving diurnal variation of emissions from sources such as wetlands and manure. Exploiting these rapidly expanding satellite measurement capabilities to quantify methane emissions requires a parallel effort to construct high-quality spatially and sectorally resolved emission inventories. Partnership between top-down inverse analyses of atmospheric data and bottom-up construction of emission inventories is crucial to better understanding methane emission processes and subsequently informing climate policy.

scholarly journals Satellite observations of atmospheric methane and their value for quantifying methane emissions

2016 ◽  
Author(s):  
Daniel J. Jacob ◽  
Alexander J. Turner ◽  
Joannes D. Maasakkers ◽  
Jianxiong Sheng ◽  
Kang Sun ◽  
...  
Keyword(s):  
Methane Emissions ◽  
Point Sources ◽  
Satellite Observations ◽  
Anthropogenic Sources ◽  
Satellite Measurement ◽  
Emission Inventories ◽  
Atmospheric Methane ◽  
High Quality ◽  
Spatial Coverage ◽  
Wide Range

Abstract. Methane is a greenhouse gas emitted by a range of natural and anthropogenic sources. Atmospheric methane has been measured continuously from space since 2003, and new instruments are planned for launch in the near future that will greatly expand the capabilities of space-based observations. We review the value of current, future, and proposed satellite observations to better quantify and understand methane emissions through inverse analyses, down to the scale of point sources and in combination with suborbital (surface and aircraft) data. Current observations from GOSAT are of high quality but have sparse spatial coverage. They provide limited information to quantify methane emissions on a regional (100–1000 km) scale. TROPOMI to be launched in late 2016 is expected to quantify daily emissions on the regional scale and will also effectively detect large point sources. Future satellite instruments with much higher spatial resolution, such as the recently launched GHGSat with 50 × 50 m2 resolution over targeted viewing domains, have the potential to detect a wide range of methane point sources. Geostationary observation of methane, still in the proposal stage, will have unique capability for mapping source regions with high resolution while also detecting transient "super-emitter" point sources. Exploiting the rapidly expanding satellite measurement capabilities to quantify methane emissions requires a parallel effort to construct high-quality spatially and sectorally resolved emission inventories. Partnership between top-down inverse analyses of atmospheric data and bottom-up construction of emission inventories is crucial to better understand methane emission processes and from there to inform climate policy.

Speleothem records of changes in tropical hydrology over the Holocene and possible implications for atmospheric methane

The Holocene ◽  
2011 ◽  
Vol 21 (5) ◽  
pp. 735-741 ◽  
Author(s):  
Stephen J. Burns
Keyword(s):  
Southern Hemisphere ◽  
Northern Hemisphere ◽  
Methane Production ◽  
Methane Emissions ◽  
Atmospheric Methane ◽  
Direct Response ◽  
The Holocene ◽  
Tropical Hydrology ◽  
The Tropics ◽  
Methane Concentrations

Recent speleothem records from the tropics of both hemispheres document a gradual decrease in the intensity of the monsoons in the Northern Hemisphere and increase in the Southern Hemisphere monsoons over the Holocene. These changes are a direct response of the monsoons to precession-driven insolation variability. With regard to atmospheric methane, this shift should result in a decrease in Northern Hemisphere tropical methane emissions and increase in Southern Hemisphere emissions. It is plausible that that overall tropical methane production experienced a minimum in the mid-Holocene because of decreased seasonality in rainfall at the margins of the tropics. Changes in tropical methane production alone might, therefore, explain many of the characteristics of Holocene methane concentrations and isotopic chemistry.

scholarly journals Satellite-derived methane hotspot emission estimates using a fast data-driven method

2017 ◽  
Vol 17 (9) ◽  
pp. 5751-5774 ◽  
Author(s):  
Michael Buchwitz ◽  
Oliver Schneising ◽  
Maximilian Reuter ◽  
Jens Heymann ◽  
Sven Krautwurst ◽  
...  
Keyword(s):  
Central Valley ◽  
Methane Emissions ◽  
Data Driven ◽  
Emission Sources ◽  
Atmospheric Methane ◽  
Near Surface ◽  
Source Regions ◽  
Uncertainty Estimates ◽  
Four Corners ◽  
Oil Gas

Abstract. Methane is an important atmospheric greenhouse gas and an adequate understanding of its emission sources is needed for climate change assessments, predictions, and the development and verification of emission mitigation strategies. Satellite retrievals of near-surface-sensitive column-averaged dry-air mole fractions of atmospheric methane, i.e. XCH4, can be used to quantify methane emissions. Maps of time-averaged satellite-derived XCH4 show regionally elevated methane over several methane source regions. In order to obtain methane emissions of these source regions we use a simple and fast data-driven method to estimate annual methane emissions and corresponding 1σ uncertainties directly from maps of annually averaged satellite XCH4. From theoretical considerations we expect that our method tends to underestimate emissions. When applying our method to high-resolution atmospheric methane simulations, we typically find agreement within the uncertainty range of our method (often 100 %) but also find that our method tends to underestimate emissions by typically about 40 %. To what extent these findings are model dependent needs to be assessed. We apply our method to an ensemble of satellite XCH4 data products consisting of two products from SCIAMACHY/ENVISAT and two products from TANSO-FTS/GOSAT covering the time period 2003–2014. We obtain annual emissions of four source areas: Four Corners in the south-western USA, the southern part of Central Valley, California, Azerbaijan, and Turkmenistan. We find that our estimated emissions are in good agreement with independently derived estimates for Four Corners and Azerbaijan. For the Central Valley and Turkmenistan our estimated annual emissions are higher compared to the EDGAR v4.2 anthropogenic emission inventory. For Turkmenistan we find on average about 50 % higher emissions with our annual emission uncertainty estimates overlapping with the EDGAR emissions. For the region around Bakersfield in the Central Valley we find a factor of 5–8 higher emissions compared to EDGAR, albeit with large uncertainty. Major methane emission sources in this region are oil/gas and livestock. Our findings corroborate recently published studies based on aircraft and satellite measurements and new bottom-up estimates reporting significantly underestimated methane emissions of oil/gas and/or livestock in this area in EDGAR.

scholarly journals 2010–2015 North American methane emissions, sectoral contributions, and trends: a high-resolution inversion of GOSAT observations of atmospheric methane

2021 ◽  
Vol 21 (6) ◽  
pp. 4339-4356
Author(s):  
Joannes D. Maasakkers ◽  
Daniel J. Jacob ◽  
Melissa P. Sulprizio ◽  
Tia R. Scarpelli ◽  
Hannah Nesser ◽  
...  
Keyword(s):  
High Resolution ◽  
Analytical Solution ◽  
Oil And Gas ◽  
Oil Production ◽  
Methane Emissions ◽  
Gas Production ◽  
Anthropogenic Emissions ◽  
Atmospheric Methane ◽  
Oil And Gas Production ◽  
Best Estimate

Abstract. We use 2010–2015 Greenhouse Gases Observing Satellite (GOSAT) observations of atmospheric methane columns over North America in a high-resolution inversion of methane emissions, including contributions from different sectors and their trends over the period. The inversion involves an analytical solution to the Bayesian optimization problem for a Gaussian mixture model (GMM) of the emission field with up to 0.5∘×0.625∘ resolution in concentrated source regions. The analytical solution provides a closed-form characterization of the information content from the inversion and facilitates the construction of a large ensemble of solutions exploring the effect of different uncertainties and assumptions in the inverse analysis. Prior estimates for the inversion include a gridded version of the Environmental Protection Agency (EPA) Inventory of US Greenhouse Gas Emissions and Sinks (GHGI) and the WetCHARTs model ensemble for wetlands. Our best estimate for mean 2010–2015 US anthropogenic emissions is 30.6 (range: 29.4–31.3) Tg a−1, slightly higher than the gridded EPA inventory (28.7 (26.4–36.2) Tg a−1). The main discrepancy is for the oil and gas production sectors, where we find higher emissions than the GHGI by 35 % and 22 %, respectively. The most recent version of the EPA GHGI revises downward its estimate of emissions from oil production, and we find that these are lower than our estimate by a factor of 2. Our best estimate of US wetland emissions is 10.2 (5.6–11.1) Tg a−1, on the low end of the prior WetCHARTs inventory uncertainty range (14.2 (3.3–32.4) Tg a−1), which calls for better understanding of these emissions. We find an increasing trend in US anthropogenic emissions over 2010–2015 of 0.4 % a−1, lower than previous GOSAT-based estimates but opposite to the decrease reported by the EPA GHGI. Most of this increase appears driven by unconventional oil and gas production in the eastern US. We also find that oil and gas production emissions in Mexico are higher than in the nationally reported inventory, though there is evidence for a 2010–2015 decrease in emissions from offshore oil production.

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