scholarly journals Quantifying Time-Averaged Methane Emissions from Individual Coal Mine Vents with GHGSat-D Satellite Observations

2020 ◽  
Vol 54 (16) ◽  
pp. 10246-10253 ◽  
Author(s):  
Daniel J. Varon ◽  
Daniel J. Jacob ◽  
Dylan Jervis ◽  
Jason McKeever
Keyword(s):  
Coal Mine ◽  
Methane Emissions ◽  
Satellite Observations

Quantifying Methane Emissions from Super-emitter Coal Mines using TROPOMI Observations

2021 ◽  
Author(s):  
Pankaj Sadavarte ◽  
Sudhanshu Pandey ◽  
Joannes D. Maasakkers ◽  
Alba Lorente ◽  
Tobias Borsdorff ◽  
...  
Keyword(s):  
Greenhouse Gas ◽  
Coal Mine ◽  
Greenhouse Gas Emission ◽  
Coal Mines ◽  
Oil And Gas Industry ◽  
Methane Emissions ◽  
Point Sources ◽  
Satellite Observations ◽  
Intergovernmental Panel ◽  
Bottom Up

<p>In the context of the Paris Agreement goal of limiting global warming to below 2 degrees Celsius, the Representative Concentration Pathways (RCP) 2.6 of the Intergovernmental Panel on Climate Change (IPCC) have framed greenhouse gas emission scenarios emphasizing a sharp reduction in methane (CH<sub>4</sub>) emissions with the current increasing trend. Recent studies have shown that satellite observations of atmospheric methane can be used to detect and quantify localized methane sources on a facility-level for the oil and gas industry. We use satellite observations from TROPOMI to understand the high and persistent methane signals from ventilation shafts in the coal mining industry.  Even the bottom-up and top-down global estimates infer coal mine methane responsible for ~12% of the anthropogenic methane emissions. TROPOMI onboard Sentinel-5P has a ground pixel resolution of 5 × 7 km<sup>2</sup> at nadir, which allows detection of large local to point sources. With its daily global coverage, we identify high methane emission sources over coal mine regions in Australia during 2018 and 2019 and quantify methane emissions using the fast data-driven cross-sectional flux method. Our initial results show that TROPOMI estimates are higher than bottom-up global emission inventories. We will present emission estimates using satellite-based quantification for super-emitter coal mines and evaluate its implication on national greenhouse gas reporting.</p>

scholarly journals Bottom-Up Estimates of Coal Mine Methane Emissions in China: A Gridded Inventory, Emission Factors, and Trends

2019 ◽  
Vol 6 (8) ◽  
pp. 473-478 ◽  
Author(s):  
Jianxiong Sheng ◽  
Shaojie Song ◽  
Yuzhong Zhang ◽  
Ronald G. Prinn ◽  
Greet Janssens-Maenhout
Keyword(s):  
Coal Mine ◽  
Methane Emissions ◽  
Emission Factors ◽  
Bottom Up ◽  
Coal Mine Methane

scholarly journals Monitoring global tropospheric OH concentrations using satellite observations of atmospheric methane

2018 ◽  
Vol 18 (21) ◽  
pp. 15959-15973 ◽  
Author(s):  
Yuzhong Zhang ◽  
Daniel J. Jacob ◽  
Joannes D. Maasakkers ◽  
Melissa P. Sulprizio ◽  
Jian-Xiong Sheng ◽  
...  
Keyword(s):  
Simulation Experiment ◽  
Short Wave ◽  
Methane Emissions ◽  
Satellite Observations ◽  
Atmospheric Methane ◽  
The Past ◽  
Methyl Chloroform ◽  
Systematic Component ◽  
Observing System Simulation Experiment ◽  
Better Than

Abstract. The hydroxyl radical (OH) is the main tropospheric oxidant and the main sink for atmospheric methane. The global abundance of OH has been monitored for the past decades using atmospheric methyl chloroform (CH3CCl3) as a proxy. This method is becoming ineffective as atmospheric CH3CCl3 concentrations decline. Here we propose that satellite observations of atmospheric methane in the short-wave infrared (SWIR) and thermal infrared (TIR) can provide an alternative method for monitoring global OH concentrations. The premise is that the atmospheric signature of the methane sink from oxidation by OH is distinct from that of methane emissions. We evaluate this method in an observing system simulation experiment (OSSE) framework using synthetic SWIR and TIR satellite observations representative of the TROPOMI and CrIS instruments, respectively. The synthetic observations are interpreted with a Bayesian inverse analysis, optimizing both gridded methane emissions and global OH concentrations. The optimization is done analytically to provide complete error accounting, including error correlations between posterior emissions and OH concentrations. The potential bias caused by prior errors in the 3-D seasonal OH distribution is examined using OH fields from 12 different models in the ACCMIP archive. We find that the satellite observations of methane have the potential to constrain the global tropospheric OH concentration with a precision better than 1 % and an accuracy of about 3 % for SWIR and 7 % for TIR. The inversion can successfully separate the effects of perturbations to methane emissions and to OH concentrations. Interhemispheric differences in OH concentrations can also be successfully retrieved. Error estimates may be overoptimistic because we assume in this OSSE that errors are strictly random and have no systematic component. The availability of TROPOMI and CrIS data will soon provide an opportunity to test the method with actual observations.

Methane emissions from coal mines ventilation shafts in Upper Silesia, Poland

2020 ◽  
Author(s):  
Mila Stanisavljevic ◽  
Jaroslaw Nęcki ◽  
Piotr Korbeń ◽  
Hossein Maazallahi ◽  
Malika Menoud ◽  
...  
Keyword(s):  
Isotopic Composition ◽  
Mole Fraction ◽  
Coal Mine ◽  
Meteorological Data ◽  
Coal Mines ◽  
Isotope Ratio Mass Spectrometry ◽  
Global Scale ◽  
Methane Emissions ◽  
Atmospheric Methane ◽  
Isotopic Characterization

<p>Atmospheric methane is the second most important anthropogenic greenhouse gas after carbon dioxide. On the global scale, methane emissions are reasonably well constrained but the contributions from individual sources are highly uncertain (Saunois, 2016). According to bottom-up estimates, methane emissions from underground coal mining excavation contribute 11% to all anthropogenic methane sources (Saunois, 2016). However, there is a lack of in situ measurement to verify these estimates. Here we present results from measurements of the methane mole fraction over the Polish part of the Upper Silesian Coal Basin (USCB). Methane mole fraction was measured using vehicles equipped with high precision laser-based instruments (Picarro G2201-i CRDS, Picarro G2301- CRDS). Basic meteorological data (wind speed, wind direction) and GPS location data were collected on the roof of the vehicles. In order to obtain emission estimates, we attempted to cross the plumes from the coal mine shafts using public roads approximately perpendicular to plume downwind from the source. When possible, the plumes were intersected several times at different distances in order to have a closer look at uncertainties. A Gaussian plume model was used to calculate the release rate from the methane single source.</p><p>In addition to methane mole fraction measurements, we collected air samples for isotopic characterization (δ<sup>13</sup>C and δD) using isotope ratio mass spectrometry. We observed significant variation in measured methane isotopic composition over USCB (the results are in a range of -321 to -142 ‰ SMOW for δD and -31 to -58 ‰ VPDB for δ<sup>13</sup>CH<sub>4</sub>). The results indicated a much larger variability of the isotopic composition of methane emitted from coal mines than assumed previously, which may complicate the distinction of methane emissions from different sources by isotopic characterization.</p><p><strong>Keywords</strong>: Methane, Greenhouse Gases, Clime Change, Coal Mine Ventilation Shafts, Methane Isotopic Compositions</p><p>Reference:</p><p>Saunois, M., Bousquet, P., Poulter, B., et al., 2016a. The global methane budget, 2000–2012. Earth Syst. Sci. Data 8, 697–751. https://doi.org/10.5194/essd-8-697-2016. www.earth-syst-sci-data.net/8/697/2016/.</p><p>This work is part of the Marie Sklodowska-Curie Initial Training Network MEMO2 , which enable us to extend these measurements to other European locations</p>

scholarly journals Concurrent variation in oil and gas methane emissions and oil price during the COVID-19 pandemic

2020 ◽  
Author(s):  
David R. Lyon ◽  
Benjamin Hmiel ◽  
Ritesh Gautam ◽  
Mark Omara ◽  
Kate Roberts ◽  
...  
Keyword(s):  
Natural Gas ◽  
Commodity Prices ◽  
Oil Prices ◽  
The United States ◽  
Methane Emissions ◽  
Gas Production ◽  
Satellite Observations ◽  
Permian Basin ◽  
Natural Gas Production ◽  
Oil And Natural Gas

Abstract. Methane emissions associated with the production, transport, and use of oil and natural gas increase the climatic impacts of energy use; however, little is known about how emissions vary temporally and with commodity prices. We present airborne and ground-based data, supported by satellite observations, to measure weekly to monthly changes in total methane emissions in the United States’ Permian Basin during a period of volatile oil prices associated with the COVID-19 pandemic. As oil prices declined from ~$ 60 to $ 20 per barrel, emissions changed concurrently from 3.4 % to 1.5 % of gas production; as prices partially recovered, emissions increased back to near initial values. Concurrently, total oil and natural gas production only declined by a maximum of ~10 % from the peak values seen in the months prior to the crash. Activity data indicate that a rapid decline in well development and subsequent effects on associated gas flaring and midstream infrastructure throughput are the likely drivers of temporary emission reductions. Our results, along with past satellite observations, suggest that under more typical price conditions, the Permian Basin is in a state of overcapacity in which rapidly growing natural gas production exceeds midstream capacity and leads to high methane emissions.

scholarly journals Four-dimensional variational data assimilation for inverse modelling of atmospheric methane emissions: method and comparison with synthesis inversion

2008 ◽  
Vol 8 (21) ◽  
pp. 6341-6353 ◽  
Author(s):  
J. F. Meirink ◽  
P. Bergamaschi ◽  
M. C. Krol
Keyword(s):  
Data Assimilation ◽  
Transport Model ◽  
Time Window ◽  
Methane Emissions ◽  
Satellite Observations ◽  
Inverse Modelling ◽  
Model Parameters ◽  
Full Potential ◽  
Atmospheric Methane ◽  
Assimilation System

Abstract. A four-dimensional variational (4D-Var) data assimilation system for inverse modelling of atmospheric methane emissions is presented. The system is based on the TM5 atmospheric transport model. It can be used for assimilating large volumes of measurements, in particular satellite observations and quasi-continuous in-situ observations, and at the same time it enables the optimization of a large number of model parameters, specifically grid-scale emission rates. Furthermore, the variational method allows to estimate uncertainties in posterior emissions. Here, the system is applied to optimize monthly methane emissions over a 1-year time window on the basis of surface observations from the NOAA-ESRL network. The results are rigorously compared with an analogous inversion by Bergamaschi et al. (2007), which was based on the traditional synthesis approach. The posterior emissions as well as their uncertainties obtained in both inversions show a high degree of consistency. At the same time we illustrate the advantage of 4D-Var in reducing aggregation errors by optimizing emissions at the grid scale of the transport model. The full potential of the assimilation system is exploited in Meirink et al. (2008), who use satellite observations of column-averaged methane mixing ratios to optimize emissions at high spatial resolution, taking advantage of the zooming capability of the TM5 model.

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.

Sign in / Sign up

Export Citation Format

Share Document