The Use of Biofilters to Reduce Atmospheric Methane Emissions from Landfills: Part I. Biofilter Design

Abstract. Methane emissions from natural wetlands and rice paddies constitute a large proportion of atmospheric methane, but the magnitude and year-to-year variation of these methane sources are still unpredictable. Here we describe and evaluate the integration of a methane biogeochemical model (CLM4Me; Riley et al., 2011) into the Community Land Model 4.0 (CLM4CN) in order to better explain spatial and temporal variations in methane emissions. We test new functions for soil pH and redox potential that impact microbial methane production in soils. We also constrain aerenchyma in plants in always-inundated areas in order to better represent wetland vegetation. Satellite inundated fraction is explicitly prescribed in the model, because there are large differences between simulated fractional inundation and satellite observations, and thus we do not use CLM4-simulated hydrology to predict inundated areas. A rice paddy module is also incorporated into the model, where the fraction of land used for rice production is explicitly prescribed. The model is evaluated at the site level with vegetation cover and water table prescribed from measurements. Explicit site level evaluations of simulated methane emissions are quite different than evaluating the grid-cell averaged emissions against available measurements. Using a baseline set of parameter values, our model-estimated average global wetland emissions for the period 1993–2004 were 256 Tg CH4 yr−1 (including the soil sink) and rice paddy emissions in the year 2000 were 42 Tg CH4 yr−1. Tropical wetlands contributed 201 Tg CH4 yr−1, or 78% of the global wetland flux. Northern latitude (>50 N) systems contributed 12 Tg CH4 yr−1. However, sensitivity studies show a large range (150–346 Tg CH4 yr−1) in predicted global methane emissions (excluding emissions from rice paddies). The large range is sensitive to (1) the amount of methane transported through aerenchyma, (2) soil pH (±100 Tg CH4 yr−1), and (3) redox inhibition (±45 Tg CH4 yr−1). Results are sensitive to biases in the CLMCN and to errors in the satellite inundation fraction. In particular, the high latitude methane emission estimate may be biased low due to both underestimates in the high-latitude inundated area captured by satellites and unrealistically low high-latitude productivity and soil carbon predicted by CLM4.

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Methane emissions by alpine plant communities in the Qinghai–Tibet Plateau

Biology Letters ◽

10.1098/rsbl.2008.0373 ◽

2008 ◽

Vol 4 (6) ◽

pp. 681-684 ◽

Cited By ~ 67

Author(s):

Guangmin Cao ◽

Xingliang Xu ◽

Ruijun Long ◽

Qilan Wang ◽

Changting Wang ◽

...

Keyword(s):

Plant Communities ◽

Methane Emissions ◽

Tibet Plateau ◽

The Tibetan Plateau ◽

Atmospheric Methane ◽

Closed Chamber ◽

Methane Budget ◽

Alpine Plant Communities ◽

Regional Basis ◽

Qinghai Tibet Plateau

For the first time to our knowledge, we report here methane emissions by plant communities in alpine ecosystems in the Qinghai–Tibet Plateau. This has been achieved through long-term field observations from June 2003 to July 2006 using a closed chamber technique. Strong methane emission at the rate of 26.2±1.2 and 7.8±1.1 μg CH 4 m −2 h −1 was observed for a grass community in a Kobresia humilis meadow and a Potentilla fruticosa meadow, respectively. A shrub community in the Potentilla meadow consumed atmospheric methane at the rate of 5.8±1.3 μg CH 4 m −2 h −1 on a regional basis; plants from alpine meadows contribute at least 0.13 Tg CH 4 yr −1 in the Tibetan Plateau. This finding has important implications with regard to the regional methane budget and species-level difference should be considered when assessing methane emissions by plants.

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Quantifying methane point sources from fine-scale (GHGSat) satellite observations of atmospheric methane plumes

10.5194/amt-2018-171 ◽

2018 ◽

Author(s):

Daniel J. Varon ◽

Daniel J. Jacob ◽

Jason McKeever ◽

Dylan Jervis ◽

Berke O. A. Durak ◽

...

Keyword(s):

Wind Speed ◽

Methane Emissions ◽

Point Sources ◽

Small Scale ◽

Atmospheric Methane ◽

Flux Method ◽

Pixel Resolution ◽

Cross Sectional ◽

Source Rate ◽

The Cross

Abstract. Anthropogenic methane emissions originate from a large number of relatively small point sources. The planned GHGSat satellite fleet aims to quantify emissions from individual point sources by measuring methane column plumes over selected ~ 10 × 10 km2 domains with ≤ 50 × 50 m2 pixel resolution and 1–5 % measurement precision. Here we develop algorithms for retrieving point source rates from such measurements. We simulate a large ensemble of instantaneous methane column plumes at 50 × 50 m2 pixel resolution for a range of atmospheric conditions using the Weather Research and Forecasting model (WRF) in large eddy simulation (LES) mode and adding instrument noise. We show that standard methods to infer source rates by Gaussian plume inversion or source pixel mass balance are prone to large errors because the turbulence cannot be properly parameterized on the small scale of instantaneous methane plumes. The integrated mass enhancement (IME) method, which relates total plume mass to source rate, and the cross-sectional flux method, which infers source rate from fluxes across plume transects, are better adapted to the problem. We show that the IME method with local measurements of the 10-m wind speed can infer source rates with error of 0.07–0.17 t h−1 + 5–12 % depending on instrument precision (1–5 %). The cross-sectional flux method has slightly larger errors (0.07–0.26 t h−1 + 8–12 %) but a simpler physical basis. For comparison, point sources larger than 0.5 t h−1 contribute more than 75 % of methane emissions reported to the U.S. Greenhouse Gas Reporting Program. Additional error applies if local wind speed measurements are not available, and may dominate the overall error at low wind speeds. Low winds are beneficial for source detection but not for source quantification.

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Variability and quasi-decadal changes in the methane budget over the period 2000–2012

10.5194/acp-2017-296 ◽

2017 ◽

Cited By ~ 2

Author(s):

Marielle Saunois ◽

Philippe Bousquet ◽

Benjamin Poulter ◽

Anna Peregon ◽

Philippe Ciais ◽

...

Keyword(s):

Biomass Burning ◽

Methane Emissions ◽

Data Driven ◽

Atmospheric Methane ◽

Top Down ◽

Bottom Up ◽

Ch4 Emissions ◽

Ensemble Mean ◽

The Mean ◽

The Tropics

Abstract. Following the recent Global Carbon project (GCP) synthesis of the decadal methane (CH4) budget over 2000–2012 (Saunois et al., 2016), we analyse here the same dataset with a focus on quasi-decadal and inter-annual variability in CH4 emissions. The GCP dataset integrates results from top-down studies (exploiting atmospheric observations within an atmospheric inverse-modelling frameworks) and bottom-up models, inventories, and data-driven approaches (including process-based models for estimating land surface emissions and atmospheric chemistry, inventories of anthropogenic emissions, and data-driven extrapolations). The annual global methane emissions from top-down studies, which by construction match the observed methane growth rate within their uncertainties, all show an increase in total methane emissions over the period 2000–2012, but this increase is not linear over the 13 years. Despite differences between individual studies, the mean emission anomaly of the top-down ensemble shows no significant trend in total methane emissions over the period 2000–2006, during the plateau of atmospheric methane mole fractions, and also over the period 2008–2012, during the renewed atmospheric methane increase. However, the top-down ensemble mean produces an emission shift between 2006 and 2008, leading to 22 [16–32] Tg CH4 yr−1 higher methane emissions over the period 2008–2012 compared to 2002–2006. This emission increase mostly originated from the tropics with a smaller contribution from mid-latitudes and no significant change from boreal regions. The regional contributions remain uncertain in top-down studies. Tropical South America and South and East Asia seems to contribute the most to the emission increase in the tropics. However, these two regions have only limited atmospheric measurements and remain therefore poorly constrained. The sectorial partitioning of this emission increase between the periods 2002–2006 and 2008–2012 differs from one atmospheric inversion study to another. However, all top-down studies suggest smaller changes in fossil fuel emissions (from oil, gas, and coal industries) compared to the mean of the bottom-up inventories included in this study. This difference is partly driven by a smaller emission change in China from the top-down studies compared to the estimate in the EDGARv4.2 inventory, which should be revised to smaller values in a near future. Though the sectorial partitioning of six individual top-down studies out of eight are not consistent with the observed change in atmospheric 13CH4, the partitioning derived from the ensemble mean is consistent with this isotopic constraint. At the global scale, the top-down ensemble mean suggests that, the dominant contribution to the resumed atmospheric CH4 growth after 2006 comes from microbial sources (more from agriculture and waste sectors than from natural wetlands), with an uncertain but smaller contribution from fossil CH4 emissions. Besides, a decrease in biomass burning emissions (in agreement with the biomass burning emission databases) makes the balance of sources consistent with atmospheric 13CH4 observations. The methane loss (in particular through OH oxidation) has not been investigated in detail in this study, although it may play a significant role in the recent atmospheric methane changes.

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High rates of anaerobic methane oxidation in freshwater wetlands reduce potential atmospheric methane emissions

Nature Communications ◽

10.1038/ncomms8477 ◽

2015 ◽

Vol 6 (1) ◽

Cited By ~ 106

Author(s):

K. E. A. Segarra ◽

F. Schubotz ◽

V. Samarkin ◽

M. Y. Yoshinaga ◽

K-U Hinrichs ◽

...

Keyword(s):

Methane Oxidation ◽

Methane Emissions ◽

Freshwater Wetlands ◽

Anaerobic Methane Oxidation ◽

Atmospheric Methane

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Advances in representing interactive methane in ModelE2-YIBs (version 1.1)

10.5194/gmd-2018-85 ◽

2018 ◽

Author(s):

Kandice L. Harper ◽

Yiqi Zheng ◽

Nadine Unger

Keyword(s):

Climate Model ◽

Climate Modeling ◽

Optimization Procedure ◽

Relative Difference ◽

Methane Emissions ◽

Optimization Process ◽

Sink Strength ◽

Mixing Ratio ◽

Atmospheric Methane ◽

Tight Coupling

Abstract. Methane (CH4) is both a greenhouse gas and a precursor of tropospheric ozone, making it an important focus of chemistry–climate interactions. Methane has both anthropogenic and natural emission sources, and reaction with the atmosphere's principal oxidizing agent, the hydroxyl radical (OH), is the dominant tropospheric loss process of methane. The tight coupling between methane and OH abundances drives indirect linkages between methane and other short-lived air pollutants and prompts the use of interactive methane chemistry in global chemistry–climate modeling. In this study, an updated contemporary inventory of natural methane emissions and the soil sink is developed using an optimization procedure that applies published emissions data to the NASA GISS ModelE2-Yale Interactive terrestrial Biosphere (ModelE2-YIBs) global chemistry–climate model. Methane observations from the global surface air-sampling network of the Earth System Research Laboratory (ESRL) of the U.S. National Oceanic and Atmospheric Administration (NOAA) are used to guide refinement of the natural methane inventory. The optimization process indicates global annual wetland methane emissions of 140 Tg CH4 y−1. The updated inventory includes total global annual methane emissions from natural sources of 181 Tg CH4 y−1 and a global annual methane soil sink of 60 Tg CH4 y−1. An interactive-methane simulation is run using ModelE2-YIBs, applying dynamic methane emissions and the updated natural methane emissions inventory that results from the optimization process. The simulated methane chemical lifetime of 10.4 ± 0.1 years corresponds well to observed lifetimes. The simulated year 2005 global-mean surface methane concentration is 1.1 % higher than the observed value from the NOAA ESRL measurements. Comparison of the simulated atmospheric methane distribution with the NOAA ESRL surface observations at 50 measurement locations finds that the simulated annual methane mixing ratio is within 1 % (i.e., +1 % to −1 %) of the observed value at 76 % of locations. Considering the 50 stations, the mean relative difference between the simulated and observed annual methane mixing ratio is a model overestimate of only 0.5 %. Comparison of simulated annual column-averaged methane concentrations with SCIAMACHY satellite retrievals provides an independent post-optimization evaluation of modeled methane. The comparison finds a slight model underestimate in 95 % of grid cells, suggesting that the applied methane source in the model is slightly underestimated or the model's methane sink strength is slightly too strong outside of the surface layer. Overall, the strong agreement between simulated and observed methane lifetimes and concentrations indicates that the ModelE2-YIBs chemistry–climate model is able to capture the principal processes that control atmospheric methane.

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Monitoring global tropospheric OH concentrations using satellite observations of atmospheric methane

Atmospheric Chemistry and Physics ◽

10.5194/acp-18-15959-2018 ◽

2018 ◽

Vol 18 (21) ◽

pp. 15959-15973 ◽

Cited By ~ 8

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.

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

Atmospheric Chemistry and Physics ◽

10.5194/acp-15-305-2015 ◽

2015 ◽

Vol 15 (1) ◽

pp. 305-317 ◽

Cited By ~ 6

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.

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Review of “High-resolution inversion of methane emissions in the Southeast US using SEAC4RS aircraft observations of atmospheric methane: anthropogenic and wetland source” by Sheng et al.

10.5194/acp-2017-1151-rc1 ◽

2018 ◽

Author(s):

Anonymous

Keyword(s):

High Resolution ◽

Methane Emissions ◽

Atmospheric Methane ◽

Aircraft Observations ◽

Southeast Us

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

10.5194/egusphere-egu2020-15165 ◽

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

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.In addition to methane mole fraction measurements, we collected air samples for isotopic characterization (&#948;13C and &#948;D) 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 &#8240; SMOW for &#948;D and -31 to -58 &#8240; VPDB for &#948;13CH4). 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.Keywords: Methane, Greenhouse Gases, Clime Change, Coal Mine Ventilation Shafts, Methane Isotopic CompositionsReference:Saunois, M., Bousquet, P., Poulter, B., et al., 2016a. The global methane budget, 2000&#8211;2012. Earth Syst. Sci. Data 8, 697&#8211;751. https://doi.org/10.5194/essd-8-697-2016. www.earth-syst-sci-data.net/8/697/2016/.This work is part of the Marie Sklodowska-Curie Initial Training Network MEMO2 , which enable us to extend these measurements to other European locations

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