Livestock methane emission and its perspective in the global methane cycle

Over the past three centuries, the atmospheric methane burden has grown 2.5-fold, reaching levels unprecedented in at least 650 000 years. Agricultural expansion has played a large part in this anthropogenic signal, with enterically fermented methane emitted by farmed ruminant livestock accounting for about one quarter of all anthropogenic emissions. This paper summarises the range of measurements that give confidence in estimates of the emission per animal and per unit feed intake and in their extrapolation to national and global emission inventories, while noting also some of the inherent uncertainties. Global emissions are discussed in the context of the evolving global methane cycle.

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A global anthropogenic emission inventory of atmospheric pollutants from sector- and fuel-specific sources (1970–2017): An application of the Community Emissions Data System (CEDS)

10.5194/essd-2020-103 ◽

2020 ◽

Author(s):

Erin E. McDuffie ◽

Steven J. Smith ◽

Patrick O'Rourke ◽

Kushal Tibrewal ◽

Chandra Venkataraman ◽

...

Keyword(s):

Emission Inventory ◽

Data System ◽

Atmospheric Pollutants ◽

Emission Inventories ◽

Anthropogenic Emission ◽

Fuel Type ◽

Road Transportation ◽

Activity Data ◽

Global Emission ◽

Global Emissions

Abstract. Global anthropogenic emission inventories remain vital for understanding the fate and transport of atmospheric pollution, as well as the resulting impacts on the environment, human health, and society. Rapid changes in today’s society require that these inventories provide contemporary estimates of multiple atmospheric pollutants with both source sector and fuel-type information to understand and effectively mitigate future impacts. To fill this need, we have updated the open-source Community Emissions Data System (CEDS) (Hoesly et al., 2019) to develop a new global emission inventory, CEDSGBD-MAPS. This inventory includes emissions of seven key atmospheric pollutants (NOx, CO, SO2, NH3, NMVOCs, BC, OC) over the time period from 1970–2017 and reports annual country-total emissions as a function of 11 anthropogenic sectors (agriculture, energy generation, industrial processes, transportation (on-road and non-road), residential, commercial, and other sectors (RCO), waste, solvent use, and international-shipping) and four fuel categories (total coal, solid biofuel, and the sum of liquid fuels and natural gas combustion, plus remaining process-level emissions). The CEDSGBD-MAPS inventory additionally includes global gridded (0.5°×0.5°) emission fluxes with monthly time resolution for each compound, sector, and fuel-type to facilitate their use in earth system models. CEDSGBD-MAPS utilizes updated activity data, updates to the core CEDS default calibration procedure, and modifications to the final procedures for emissions gridding and aggregation to retain sector and fuel-specific information. Relative to the previous CEDS data released for CMIP6 (Hoesly et al., 2018), these updates extend the emission estimates from 2014 to 2017 and improve the overall agreement between CEDS and two widely used global bottom-up emission inventories. The CEDSGBD-MAPS inventory provides the most contemporary global emission estimates to-date for these key atmospheric pollutants and is the first to provide global estimates for these species as a function of multiple fuel-types across multiple source sectors. Dominant sources of global NOx and SO2 emissions in 2017 include the combustion of oil, gas, and coal in the energy and industry sectors, as well as on-road transportation and international shipping for NOx. Dominant sources of global CO emissions in 2017 include on-road transportation and residential biofuel combustion. Dominant global sources of carbonaceous aerosol in 2017 include residential biofuel combustion, on-road transportation (BC only), as well as emissions from waste. Global emissions of NOx, SO2, CO, BC, and OC all peak in 2012 or earlier, with more recent emission reductions driven by large changes in emissions from China, North America, and Europe. In contrast, global emissions of NH3 and NMVOCs continuously increase between 1970 and 2017, with agriculture serving as a major source of global NH3 emissions and solvent use, energy, residential, and the on-road transport sectors as major sources of global NMVOCs. Due to similar development methods and underlying datasets, the CEDSGBD-MAPS emissions are expected to have consistent sources of uncertainty as other bottom-up inventories, including uncertainties in the underlying activity data and sector- and region-specific emission factors. The CEDSGBD-MAPS source code is publicly available online through GitHub: https://github.com/emcduffie/CEDS/tree/CEDS_GBD-MAPS. The CEDSGBD-MAPS emission inventory dataset (both annual country-total and global gridded files) is publicly available and registered under: https://doi.org/10.5281/zenodo.3754964 (McDuffie et al., 2020).

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Investigation of the global methane budget over 1980–2017 using GFDL-AM4.1

10.5194/acp-2019-529 ◽

2019 ◽

Cited By ~ 1

Author(s):

Jian He ◽

Vaishali Naik ◽

Larry W. Horowitz ◽

Ed Dlugokencky ◽

Kirk Thoning

Keyword(s):

Atmospheric Chemistry ◽

Latitudinal Gradient ◽

Methane Emissions ◽

Anthropogenic Emissions ◽

Atmospheric Methane ◽

Recent Past ◽

Methane Budget ◽

Global Trend ◽

Emission Changes ◽

Global Emissions

Abstract. Changes in atmospheric methane abundance have implications for both chemistry and climate as methane is both a strong greenhouse gas and an important precursor for tropospheric ozone. A better understanding of the drivers of trends and variability in methane abundance over the recent past is therefore critical for building confidence in projections of future methane levels. In this work, the representation of methane in the atmospheric chemistry model AM4.1 is improved by optimizing total methane emissions (to an annual mean of 576 ± 32 Tg yr−1) to match surface observations over 1980–2017. The simulations with optimized global emissions are in general able to capture the observed global trend, variability, seasonal cycle, and latitudinal gradient of methane. Simulations with different emission adjustments suggest that increases in methane sources (mainly from energy and waste sectors) balanced by increases in methane sinks (mainly due to increases in OH levels) lead to methane stabilization (with an imbalance of 5 Tg yr−1) during 1999–2006, and that increases in methane sources combined with little change in sinks (despite small decreases in OH levels) during 2007–2012 lead to renewed methane growth (with an imbalance of 14 Tg yr−1 for 2007–2017). Compared to 1999–2006, both methane emissions and sinks are greater (by 31 Tg yr−1 and 22 Tg yr−1, respectively) during 2007–2017. Our results also indicate that the energy sector is more likely a major contributor to the methane renewed growth after 2006 than wetland, as increases in wetland emissions alone are not able to explain the renewed methane growth with constant anthropogenic emissions. In addition, a significant increase in wetland emissions would be required starting in 2006, if anthropogenic emissions declined, for wetland emissions to drive renewed growth in methane, which is a less likely scenario. Simulations with varying OH levels indicate that 1 % change in OH levels could lead to an annual mean of ~ 4 Tg yr−1 difference in the optimized emissions and 0.08 year difference in the estimated tropospheric methane lifetime. Continued increases in methane emissions along with decreases in tropospheric OH concentrations during 2008–2015 prolong methane lifetime and therefore amplify the response of methane concentrations to emission changes. Uncertainties still exist in the partitioning of emissions among individual sources and regions.

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Sensitivity analysis of methane emissions derived from SCIAMACHY observations through inverse modelling

Atmospheric Chemistry and Physics ◽

10.5194/acp-6-1275-2006 ◽

2006 ◽

Vol 6 (5) ◽

pp. 1275-1292 ◽

Cited By ~ 73

Author(s):

J. F. Meirink ◽

H. J. Eskes ◽

A. P. H. Goede

Keyword(s):

Methane Emission ◽

Measurement Errors ◽

Inverse Modelling ◽

Limiting Factor ◽

Atmospheric Methane ◽

Cloud Parameters ◽

Global Emission ◽

Spatial Coverage ◽

Methane Source ◽

The Impact

Abstract. Satellite observations of trace gases in the atmosphere offer a promising method for global verification of emissions and improvement of global emission inventories. Here, an inverse modelling approach based on four-dimensional variational (4D-var) data assimilation is presented and applied to synthetic measurements of atmospheric methane. In this approach, emissions and initial concentrations are optimised simultaneously, thus allowing inversions to be carried out on time scales of weeks to months, short compared with the lifetime of methane. Observing System Simulation Experiments (OSSEs) have been performed to demonstrate the feasibility of the method and to investigate the utility of SCIAMACHY observations for methane source estimation. The impact of a number of parameters on the error in the methane emission field retrieved has been analysed. These parameters include the measurement error, the error introduced by the presence of clouds, and the spatial resolution of the emission field. It is shown that 4D-var is an efficient method to deal with large amounts of satellite data and to retrieve emissions at high resolution. Some important conclusions regarding the SCIAMACHY measurements can be drawn. (i) The observations at their estimated precision of 1.5 to 2% will contribute considerably to uncertainty reduction in monthly, subcontinental (~500 km) methane source strengths. (ii) Systematic measurement errors well below 1% have a dramatic impact on the quality of the derived emission fields. Hence, every effort should be made to identify and remove such systematic errors. (iii) It is essential to take partly cloudy pixels into account in order to achieve sufficient spatial coverage. (iv) The uncertainty in measured cloud parameters may at some point become the limiting factor for methane emission retrieval, rather than the uncertainty in measured methane itself.

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Contribution of oxic methane production to surface methane emission in lakes and its global importance

Nature Communications ◽

10.1038/s41467-019-13320-0 ◽

2019 ◽

Vol 10 (1) ◽

Cited By ~ 15

Author(s):

Marco Günthel ◽

Daphne Donis ◽

Georgiy Kirillin ◽

Danny Ionescu ◽

Mina Bizic ◽

...

Keyword(s):

Surface Water ◽

Methane Emission ◽

Methane Production ◽

Surface Mixed Layer ◽

Atmospheric Methane ◽

Methane Cycle ◽

Surface Areas ◽

Balance Analysis ◽

Littoral Sediment ◽

Methane Source

AbstractRecent discovery of oxic methane production in sea and lake waters, as well as wetlands, demands re-thinking of the global methane cycle and re-assessment of the contribution of oxic waters to atmospheric methane emission. Here we analysed system-wide sources and sinks of surface-water methane in a temperate lake. Using a mass balance analysis, we show that internal methane production in well-oxygenated surface water is an important source for surface-water methane during the stratified period. Combining our results and literature reports, oxic methane contribution to emission follows a predictive function of littoral sediment area and surface mixed layer volume. The contribution of oxic methane source(s) is predicted to increase with lake size, accounting for the majority (>50%) of surface methane emission for lakes with surface areas >1 km2.

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Investigation of the global methane budget over 1980–2017 using GFDL-AM4.1

Atmospheric Chemistry and Physics ◽

10.5194/acp-20-805-2020 ◽

2020 ◽

Vol 20 (2) ◽

pp. 805-827 ◽

Cited By ~ 3

Author(s):

Jian He ◽

Vaishali Naik ◽

Larry W. Horowitz ◽

Ed Dlugokencky ◽

Kirk Thoning

Keyword(s):

Atmospheric Chemistry ◽

Latitudinal Gradient ◽

Sharp Decrease ◽

Methane Emissions ◽

Anthropogenic Sources ◽

Anthropogenic Emissions ◽

Atmospheric Methane ◽

Methane Budget ◽

Emission Changes ◽

Global Emissions

Abstract. Changes in atmospheric methane abundance have implications for both chemistry and climate as methane is both a strong greenhouse gas and an important precursor for tropospheric ozone. A better understanding of the drivers of trends and variability in methane abundance over the recent past is therefore critical for building confidence in projections of future methane levels. In this work, the representation of methane in the atmospheric chemistry model AM4.1 is improved by optimizing total methane emissions (to an annual mean of 580±34 Tg yr−1) to match surface observations over 1980–2017. The simulations with optimized global emissions are in general able to capture the observed trend, variability, seasonal cycle, and latitudinal gradient of methane. Simulations with different emission adjustments suggest that increases in methane emissions (mainly from agriculture, energy, and waste sectors) balanced by increases in methane sinks (mainly due to increases in OH levels) lead to methane stabilization (with an imbalance of 5 Tg yr−1) during 1999–2006 and that increases in methane emissions (mainly from agriculture, energy, and waste sectors) combined with little change in sinks (despite small decreases in OH levels) during 2007–2012 lead to renewed growth in methane (with an imbalance of 14 Tg yr−1 for 2007–2017). Compared to 1999–2006, both methane emissions and sinks are greater (by 31 and 22 Tg yr−1, respectively) during 2007–2017. Our tagged tracer analysis indicates that anthropogenic sources (such as agriculture, energy, and waste sectors) are more likely major contributors to the renewed growth in methane after 2006. A sharp increase in wetland emissions (a likely scenario) with a concomitant sharp decrease in anthropogenic emissions (a less likely scenario), would be required starting in 2006 to drive the methane growth by wetland tracer. Simulations with varying OH levels indicate that a 1 % change in OH levels could lead to an annual mean difference of ∼4 Tg yr−1 in the optimized emissions and a 0.08-year difference in the estimated tropospheric methane lifetime. Continued increases in methane emissions along with decreases in tropospheric OH concentrations during 2008–2015 prolong methane's lifetime and therefore amplify the response of methane concentrations to emission changes. Uncertainties still exist in the partitioning of emissions among individual sources and regions.

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Operation of the boreal peatland methane cycle across the past 16 k.y.

Geology ◽

10.1130/g46709.1 ◽

2019 ◽

Vol 48 (1) ◽

pp. 82-86 ◽

Cited By ~ 2

Author(s):

Yanhong Zheng ◽

Zhengkun Fang ◽

Tongyu Fan ◽

Zhao Liu ◽

Zhangzhang Wang ◽

...

Keyword(s):

Direct Evidence ◽

Ice Core ◽

Ice Cores ◽

Atmospheric Methane ◽

Last Deglaciation ◽

Methane Cycle ◽

The Past ◽

Stable Isotopic ◽

The Last Deglaciation

Abstract The role of boreal wetlands in driving variations in atmospheric methane (CH4) concentrations across the last deglaciation (20–10 ka) and the Holocene is debated. Most studies infer the sources of atmospheric methane via ice-core records of methane concentration and its light stable isotopic composition. However, direct evidence for variations in the methane cycle from the wetlands themselves is relatively limited. Here, we used a suite of biomarker proxies to reconstruct the methane cycle in the Chinese Hani peat across the past 16 k.y. We found two periods of enhanced methanogenesis, at ca. 15–11 ka and ca. 10–6 ka, whereas weak methanogenesis characterized the late Holocene. These periods of enhanced methanogenesis relate to periods of high/increasing temperatures, supporting a temperature control on the wetland methane cycle. We found no biomarker evidence for intense methanotrophy throughout the past 16 k.y., and, contrary to previous studies, we found no clear control of hydrology on the peatland methane cycle. Although the onset of methanogenesis at Hani at ca. 15 ka coincided with a negative shift in methane δ13C in the ice cores, there is no consistent correlation between changes in the reconstructed methane cycle of the boreal Hani peat and atmospheric CH4 concentrations.

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A global anthropogenic emission inventory of atmospheric pollutants from sector- and fuel-specific sources (1970–2017): an application of the Community Emissions Data System (CEDS)

Earth System Science Data ◽

10.5194/essd-12-3413-2020 ◽

2020 ◽

Vol 12 (4) ◽

pp. 3413-3442

Author(s):

Erin E. McDuffie ◽

Steven J. Smith ◽

Patrick O'Rourke ◽

Kushal Tibrewal ◽

Chandra Venkataraman ◽

...

Keyword(s):

Emission Inventory ◽

Data System ◽

Atmospheric Pollutants ◽

Emission Inventories ◽

Anthropogenic Emission ◽

Fuel Type ◽

Road Transportation ◽

International Shipping ◽

Global Emission ◽

Global Emissions

Abstract. Global anthropogenic emission inventories remain vital for understanding the sources of atmospheric pollution and the associated impacts on the environment, human health, and society. Rapid changes in today's society require that these inventories provide contemporary estimates of multiple atmospheric pollutants with both source sector and fuel type information to understand and effectively mitigate future impacts. To fill this need, we have updated the open-source Community Emissions Data System (CEDS) (Hoesly et al., 2019) to develop a new global emission inventory, CEDSGBD-MAPS. This inventory includes emissions of seven key atmospheric pollutants (NOx; CO; SO2; NH3; non-methane volatile organic compounds, NMVOCs; black carbon, BC; organic carbon, OC) over the time period from 1970–2017 and reports annual country-total emissions as a function of 11 anthropogenic sectors (agriculture; energy generation; industrial processes; on-road and non-road transportation; separate residential, commercial, and other sectors (RCO); waste; solvent use; and international shipping) and four fuel categories (total coal, solid biofuel, the sum of liquid-fuel and natural-gas combustion, and remaining process-level emissions). The CEDSGBD-MAPS inventory additionally includes monthly global gridded (0.5∘ × 0.5∘) emission fluxes for each compound, sector, and fuel type to facilitate their use in earth system models. CEDSGBD-MAPS utilizes updated activity data, updates to the core CEDS default scaling procedure, and modifications to the final procedures for emissions gridding and aggregation. Relative to the previous CEDS inventory (Hoesly et al., 2018), these updates extend the emission estimates from 2014 to 2017 and improve the overall agreement between CEDS and two widely used global bottom-up emission inventories. The CEDSGBD-MAPS inventory provides the most contemporary global emission estimates to date for these key atmospheric pollutants and is the first to provide global estimates for these species as a function of multiple fuel types and source sectors. Dominant sources of global NOx and SO2 emissions in 2017 include the combustion of oil, gas, and coal in the energy and industry sectors as well as on-road transportation and international shipping for NOx. Dominant sources of global CO emissions in 2017 include on-road transportation and residential biofuel combustion. Dominant global sources of carbonaceous aerosol in 2017 include residential biofuel combustion, on-road transportation (BC only), and emissions from the waste sector. Global emissions of NOx, SO2, CO, BC, and OC all peak in 2012 or earlier, with more recent emission reductions driven by large changes in emissions from China, North America, and Europe. In contrast, global emissions of NH3 and NMVOCs continuously increase between 1970 and 2017, with agriculture as a major source of global NH3 emissions and solvent use, energy, residential, and the on-road transport sectors as major sources of global NMVOCs. Due to similar development methods and underlying datasets, the CEDSGBD-MAPS emissions are expected to have consistent sources of uncertainty as other bottom-up inventories. The CEDSGBD-MAPS source code is publicly available online through GitHub: https://github.com/emcduffie/CEDS/tree/CEDS_GBD-MAPS (last access: 1 December 2020). The CEDSGBD-MAPS emission inventory dataset (both annual country-total and monthly global gridded files) is publicly available under https://doi.org/10.5281/zenodo.3754964 (McDuffie et al., 2020c).

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The Global Methane Budget: 2000–2012

10.5194/essd-2016-25 ◽

2016 ◽

Cited By ~ 16

Author(s):

Marielle Saunois ◽

Philippe Bousquet ◽

Ben Poulter ◽

Anna Peregon ◽

Philippe Ciais ◽

...

Keyword(s):

Carbon Dioxide ◽

Atmospheric Chemistry ◽

Land Surface ◽

Data Driven ◽

Anthropogenic Emissions ◽

Methane Cycle ◽

Modelling Framework ◽

Methane Budget ◽

The Individual ◽

Global Emissions

Abstract. The global methane (CH4) budget is becoming an increasingly important component for managing realistic pathways to mitigate climate change. This relevance, due to a shorter atmospheric lifetime and a stronger warming potential than carbon dioxide, is challenged by the still unexplained changes of atmospheric CH4 over the past decade. Emissions and concentrations of CH4 are continuing to increase making CH4 the second most important human-induced greenhouse gas after carbon dioxide. Two major difficulties in reducing uncertainties come from the large variety of diffusive CH4 sources that overlap geographically, and from the destruction of CH4 by the very short-lived hydroxyl radical (OH). To address these difficulties, we have established a consortium of multi-disciplinary scientists under the umbrella of the Global Carbon Project to synthesize and stimulate research on the methane cycle, and producing regular (~biennial) updates of the global methane budget. This consortium includes atmospheric physicists and chemists, biogeochemists of surface and marine emissions, and socio-economists who study anthropogenic emissions. Following Kirschke et al. (2013), we propose here the first version of a living review paper that integrates results of top-down studies (T-D, exploiting atmospheric observations within an atmospheric inverse-modelling framework) and bottom-up models, inventories, and data-driven approaches (B-U, including process-based models for estimating land surface emissions and atmospheric chemistry, and inventories for anthropogenic emissions, data-driven extrapolations). For the 2003–2012 decade, global methane emissions are estimated by T-D inversions at 558 Tg CH4 yr−1 (range [540–568]). About 60 % of global emissions are anthropogenic (range [50–65 %]). B-U approaches suggest larger global emissions (736 Tg CH4 yr−1 [596–884]) mostly because of larger natural emissions from individual sources such as inland waters, natural wetlands and geological sources. Considering the atmospheric constraints on the T-D budget, it is likely that some of the individual emissions reported by the B-U approaches are overestimated, leading to too large global emissions. Latitudinal data from T-D emissions indicate a predominance of tropical emissions (~64 % of the global budget,

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Effects of Sericea Lespedeza on Feed Intake, Digestion, and Ruminal Methane Emission in Hair Sheep

Journal of Animal Science ◽

10.1093/jas/skab096.075 ◽

2021 ◽

Vol 99 (Supplement_2) ◽

pp. 41-41

Author(s):

Luana L Ribeiro ◽

Ryszard Puchala ◽

Arthur L Goetsch

Keyword(s):

Methane Emission ◽

Feed Intake ◽

Dry Matter ◽

Coconut Oil ◽

Mixed Effects ◽

Repeated Measure ◽

Lespedeza Cuneata ◽

Hair Sheep ◽

Initial Body Weight ◽

Sericea Lespedeza

Abstract Eighteen Katahdin (initial body weight of 74 kg; SEM=1.8) and 18 St. Croix ewes (55 kg; SEM=1.3) were used in an experiment with four 6-wk periods to determine effects of dietary level of Sericea lespedeza (Lespedeza cuneata) containing 5.8% condensed tannins (dry matter; DM) and other supplemental ingredients on feed intake, digestion, and ruminal methane emission. Diets were consumed ad libitum and included a concentrate supplement at 0.45% BW (DM). Alfalfa was the basal forage for control (CON), ionophore (ION; lasalocid at 33 mg/kg DM), coconut oil (3%; CCO), and soybean oil (3%; SBO) diets, and forage in moderate- and high-lespedeza diets was a 1:1 mixture of alfalfa and lespedeza and all lespedeza, respectively (MSL and HSL, respectively). Data were analyzed with a 2 x 6 factorial arrangement of treatments, period as a repeated measure, and a mixed effects model. Digestion and methane emission were determined in weeks 4, 10, 16, and 22. Total DM intake was similar among treatments (P = 0.070) but numerically greatest for HSL (1,197, 1,297, 1,491, 1,203, 1,195, and 1,207 g/d; SEM=81.1), OM digestibility ranked (P < 0.05) CON, ION, CCO, and SBO > MSL > HSL (69.2, 57.6, 50.3, 66.3, 66.0, and 68.7%; SEM=1.57), and digestible OM intake was similar among treatments (P = 0.517; 697, 607, 589, 598, 635, and 690 g/d for CON, MSL, HSL, ION, CCO, and SBO, respectively; SEM=50.4). There were no interactions involving time in ruminal methane emission, which was greatest among treatments for CON (P < 0.05) in MJ/d (1.39, 0.93, 0.90, 0.92, 0.85, and 0.96; SEM=0.069) and relative to digestible energy intake (20.6, 15.7, 16.8, 16.1, 13.7, and 13.9% for CON, MSL, HSL, ION, CCO, and SBO, respectively; SEM=1.223). In conclusion, dietary inclusion of Sericea lespedeza may offer a natural and sustainable means of decreasing ruminal methane emission by hair sheep as previously shown in goats, with a magnitude of impact similar to that of some other supplemental dietary ingredients.

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