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Tropentag, September 14 - 16, 2022, Prague

"Can agroecological farming feed the world? Farmers' and academia's views."


Quantitative assessment of scenarios for greenhouse gas mitigation from livestock systems

Armando Rivera1, Marius Gilbert1, Alessandra Falcucci2, Giuseppe Tempio2, Dominik Wisser2, Aimable Uwizeye2, Giuseppina Cinardi2, Camillo De Camillis2, Saskia Reppin2, Monica Rulli2, Henning Steinfeld2, Timothy Robinson2

1Université Libre de Bruxelles, Belgium
2Food and Agriculture Organization of the United Nations, Italy


Abstract


Global demand for livestock products is projected to double by 2050 in developing countries and to grow by 10 percent in developed countries, increasing pressure on ecosystems that are already stretched. FAO estimated that in 2011 almost 32 percent of land was already degraded by conventional agricultural systems that have prioritised productivity over environmental services and sustainability. To estimate the environmental impacts of livestock systems, FAO has developed the Global Livestock Environmental Assessment Model (GLEAM, version 4 - 2019 IPCC guidelines). GLEAM is a computational model based on a Tier-2 life cycle assessment, that uses spatial data to generate baselines of greenhouse gasses emissions (GHG) from livestock systems and to evaluate mitigation scenarios related to the production, processing, and transport of livestock related products. The model produces global estimates and has also been used by several countries for environmental impact assessments in relation to greenhouse emissions. The research seeks to improve the model integration with global data on feed production and trade, from sources such as FAOSTAT, to quantify the global GHG impact of different scenarios of mitigation actions, such as substitutions of different feed ingredients over a range of time scales and changing husbandry practices such as feeding, genetics and animal health. A second objective is to adapt and test GLEAM to work at a farm level. Several collaborations are being established to carry out analyses of individual farm data – for example in Kenya, Costa Rica, China and Ecuador – to adapt the model to estimate baseline emissions and mitigation potential for individual farms. Additionally, uncertainty analysis of GLEAM will be conducted, using Monte Carlo simulations to determine the spread of errors due uncertainties in the model and the data. Finally, the research will generate sensitivity analysis to determine, through modelling, the uncertainty associated with each of the individual input parameters. This will point to priority areas for data collection and model improvement.


Keywords: Climate change, emissions, gleam, greenhouse, life cycle, livestock


Contact Address: Armando Rivera, Université Libre de Bruxelles, Brussels, Belgium, e-mail: armando.rivera.moncada@ulb.be


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