Global mitigation potential and costs of reducing agricultural non-CO<sub>2</sub>greenhouse gas emissions through 2030

Beach, Robert; Creason, Jared; Ohrel, Sara; Ragnauth, Shaun; Ogle, Stephen M.; Li, Changsheng; Ingraham, Pete; Salas, William

doi:10.1080/1943815x.2015.1110183

Cited by 76 publications

(63 citation statements)

References 20 publications

(17 reference statements)

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“…The GAINSv4 model results add to a limited number of independently developed bottom-up estimates of technical abatement potentials and costs to reduce global CH 4 emissions in the 2050 timeframe (Lucas et al 2007, Harmsen et al 2019. Similar efforts have been presented for the 2030 timeframe, e.g., Höglund-Isaksson (2012) estimated marginal abatement cost curves using an earlier version of the GAINS model and USEPA (2006,2012) presented corresponding cost curves for all non-CO 2 greenhouse gases with (Beach et al 2015, Beach et al 2008 and Frank et al (2018) presenting results specifically for the agricultural sector.…”

Section: Introductionmentioning

confidence: 74%

Technical potentials and costs for reducing global anthropogenic methane emissions in the 2050 timeframe –results from the GAINS model

Höglund-Isaksson

Gómez-Sanabria

Klimont

et al. 2020

Environ. Res. Commun.

133

113

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Methane is the second most important greenhouse gas after carbon dioxide contributing to humanmade global warming. Keeping to the Paris Agreement of staying well below two degrees warming will require a concerted effort to curb methane emissions in addition to necessary decarbonization of the energy systems. The fastest way to achieve emission reductions in the 2050 timeframe is likely through implementation of various technical options. The focus of this study is to explore the technical abatement and cost pathways for reducing global methane emissions, breaking reductions down to regional and sector levels using the most recent version of IIASA's Greenhouse gas and Air pollution Interactions and Synergies (GAINS) model. The diverse human activities that contribute to methane emissions make detailed information on potential global impacts of actions at the regional and sectoral levels particularly valuable for policy-makers. With a global annual inventory for 1990-2015 as starting point for projections, we produce a baseline emission scenario to 2050 against which future technical abatement potentials and costs are assessed at a country and sector/technology level. We find it technically feasible in year 2050 to remove 54 percent of global methane emissions below baseline, however, due to locked in capital in the short run, the cumulative removal potential over the period 2020-2050 is estimated at 38 percent below baseline. This leaves 7.7 Pg methane released globally between today and 2050 that will likely be difficult to remove through technical solutions. There are extensive technical opportunities at low costs to control emissions from waste and wastewater handling and from fossil fuel production and use. A considerably more limited technical abatement potential is found for agricultural emissions, in particular from extensive livestock rearing in developing countries. This calls for widespread implementation in the 2050 timeframe of institutional and behavioural options in addition to technical solutions.

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Section: Introductionmentioning

confidence: 74%

Technical potentials and costs for reducing global anthropogenic methane emissions in the 2050 timeframe –results from the GAINS model

Höglund-Isaksson

Gómez-Sanabria

Klimont

et al. 2020

Environ. Res. Commun.

133

113

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“…Agriculture is responsible for 53% of global non-CO 2 emissions, and therefore, it has essential mitigation potential and costs of reducing GHG emissions (Beach et al 2016;Gerber et al 2016;Johnson et al 2007;Smith et al 2008). Due to meteorological conditions, development level and many other factors, the share of agricultural emissions is not the same around the world.…”

Section: Introductionmentioning

confidence: 99%

High-resolution spatial distribution and associated uncertainties of greenhouse gas emissions from the agricultural sector

Charkovska

Horabik-Pyzel

Bun

et al. 2018

Mitig Adapt Strateg Glob Change

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Agricultural activity plays a significant role in the atmospheric carbon balance as a source and sink of greenhouse gases (GHGs) and has high mitigation potential. The agricultural emissions display evident geographical differences in the regional, national, and even local levels, not only due to spatially differentiated activity, but also due to very geographically different emission coefficients. Thus, spatially resolved inventories are important for obtaining better estimates of emission content and design of GHG mitigation processes to adapt to global carbon rise in the atmosphere. This study develops a geoinformation approach to a highresolution spatial inventory of GHG emissions from the agricultural sector, following the categories of the United Nations Intergovernmental Panel on Climate Change guidelines. Using the Corine Land Cover data, a digital map of emission sources is built, with elementary areal objects that are split up by administrative boundaries. Various procedures are developed for disaggregation of available emission activity data down to a level of elementary emission objects, conditional on covariate information, such as land use, observable in the elementary object scale. Among them, a statistical scaling method suitable for spatially correlated areal emission sources is applied. As an example of implementation of this approach, the spatial distribution of methane (CH 4 ) and Nitrogen Oxide (N 2 O) emissions was obtained for areal China University of Mining and Technology, Beijing, China emission sources in the agriculture sector in Poland with a spatial resolution of 100 m. We calculated the specific total emissions for different types of animal and manure systems as well as the total emissions in CO 2 -equivalent. We demonstrated that the emission sources are located highly nonuniformly and the emissions from them vary substantially, so that average data may provide insufficient approximation. In our case, over 11% smaller emission was estimated using spatial approach as compared with the national inventory report where average data were used. In addition, we quantified uncertainties associated with the developed spatial inventory and analysed the dominant components in total emission uncertainties in the agriculture sector. We used the activity data from the lowest possible (municipal) level. The depth of disaggregation of these data to the level of arable lands is minimal, and hence, the relative uncertainty of spatial inventory is smaller when comparing with traditional gridded emissions. The proposed technique allows us to discuss factors driving the geographical distribution of GHG emissions for different categories of the agricultural sector. This may be particularly useful in high-resolution modelling of GHG dispersion in the atmosphere.Mitig Adapt Strateg Glob Change https://doi.org/10.1007/s11027-017-9779-3 Electronic supplementary material

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“…A set of US Environmental Protection Agency mitigation studies also developed global marginal abatement cost (MAC) curves for agriculture. These studies incorporated results from DAYCENT (a daily version of the CENTURY model) simulations for non-rice crops and DeNitrification-DeComposition (DNDC) simulations for rice with economic data to generate estimates of the costs and potential mitigation associated with a suite of non-CO2 GHG mitigation options for the agricultural sector (US Environmental Protection Agency, 2006;Beach et al, 2008;US Environmental Protection Agency, 2013;Beach et al, 2015).…”

Section: Examplesmentioning

confidence: 99%

Developing Climate-Smart Agriculture Policies: The Role of Economic Modeling

Crouch¹,

Lapidus²,

Beach³

et al. 2017

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This PDF document was made available from www.rti.org as a public service of RTI International. More information about RTI Press can be found at http://www.rti.org/rtipress. RTI International is an independent, nonprofit research organization dedicated to improving the human condition by turning knowledge into practice. The RTI Press mission is to disseminate information about RTI research, analytic tools, and technical expertise to a national and international audience. RTI Press publications are peerreviewed by at least two independent substantive experts and one or more Press editors.

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Global mitigation potential and costs of reducing agricultural non-CO₂greenhouse gas emissions through 2030

Cited by 76 publications

References 20 publications

Technical potentials and costs for reducing global anthropogenic methane emissions in the 2050 timeframe –results from the GAINS model

Technical potentials and costs for reducing global anthropogenic methane emissions in the 2050 timeframe –results from the GAINS model

High-resolution spatial distribution and associated uncertainties of greenhouse gas emissions from the agricultural sector

Developing Climate-Smart Agriculture Policies: The Role of Economic Modeling

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Global mitigation potential and costs of reducing agricultural non-CO2greenhouse gas emissions through 2030

Cited by 76 publications

References 20 publications

Technical potentials and costs for reducing global anthropogenic methane emissions in the 2050 timeframe –results from the GAINS model

Technical potentials and costs for reducing global anthropogenic methane emissions in the 2050 timeframe –results from the GAINS model

High-resolution spatial distribution and associated uncertainties of greenhouse gas emissions from the agricultural sector

Developing Climate-Smart Agriculture Policies: The Role of Economic Modeling

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Product

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Global mitigation potential and costs of reducing agricultural non-CO₂greenhouse gas emissions through 2030