Estimating Livestock Emissions to Unlock Climate Financing

Key Messages

• The livestock sector is pivotal to reducing greenhouse gas emissions.
• In low-and middle-income countries, livestock plays a multifunctional role supporting livelihoods and nutrition.
• The livestock sector offers pathways to help communities respond to climate impacts.
• Reducing livestock sector emissions helps to mitigate the sector’s contribution to climate change.
• There is untapped potential for climate finance to support mitigation and adaptation measures in the livestock sector.
• To qualify for climate finance, countries and projects will need to quantify the livestock sector’s mitigation opportunities.
• This brief explores the recognised methodologies for calculating greenhouse gas emissions from livestock production.
• It offers an introduction to the science-based calculations used in emissions quantification, the data requirements and how to interpret modelled results.

This brief, aimed at both finance applicants and financiers themselves, gives a high-level overview of the methodologies available to calculate greenhouse gas emissions from livestock production, with the objective to improve understanding and confidence in the methods themselves and the evidence they provide.

Models to estimate livestock greenhouse gas emissions have common calculations at their core

The Intergovernmental Panel on Climate Change (IPCC) has developed detailed methodologies for calculating emissions from the main societal sectors, including energy, transport, industry, agriculture and waste. This common approach is designed to ensure that emissions are estimated in a consistent way by different sectors and are comparable between countries. The science-based guidelines are regularly updated, reflecting advances in knowledge, by an international group of scientists relevant to each sector. The latest update was published in 2019.

Tier 1 or Tier 2 calculations?

The IPCC methodologies include different tiers of calculation, representing increasing levels of complexity. Tier 1 calculations are the most basic, requiring few input data points (namely livestock populations) combined with default emission factors. If the requirement is to judge the order of magnitude of livestock emissions, Tier 1 results are fit-for-purpose. However, if there is a requirement to explore a change in emissions due to a change in management practices or input resources available (such as animal diets, genetics or health) Tier 2 calculations should be used. Tier 2 calculations require significantly more input data points; fundamentally, they replace the use of default emission factors by calculating more specific factors for specific scenarios.

Scope of analysis

Livestock-associated emissions are generated along value chains, so to capture the full potential for mitigation, lifecycle assessments (LCAs) are advisable. LCAs consider activities and emissions from inputs to production (for instance feed), through animal production, transportation, processing, to the retail of animal sourced foods. If the focus is solely on changes to on-farm emissions or to specific emission sources such as enteric methane, a narrower scope may be appropriate but should not be the default. The IPCC guidelines provide the consistent set of calculations that can be selected from for an appropriate scope of analysis. Mitigation of direct and indirect emissions should be considered alongside other system parameters, such as livestock adaptation and resilience. There are frameworks to guide users through the application of the IPCC guidelines. For instance, the AMS- III.BK methodology, ‘Strategic feed supplementation in smallholder dairy sector to increase productivity’, supports the assessment of scenarios in relation to methane and feed supplementation changes in smallholder dairy systems. The methodology outlines specific data needs for baseline measurement and verification. This is a globally recognised methodology for determining system GHG emissions, developed by the United Nations Framework Convention on Climate Change (UNFCC) and approved by the Clean Development Mechanism Executive board in 2014. The methodology has also been accepted for use in verifying carbon credits.

Measured or assumed input data points

Tier 2 calculations require enough input data to accurately reflect the details of the production system. It is not practical or resource-effective to empirically assess all input data points required for Tier 2 calculations from the livestock systems of interest. Instead, there is distinction between those data points where assumptions will suffice, and those that need more real (granular) measured data. This varies depending on the livestock species and interventions being explored.

For instance, for cattle, sheep and goats, the greatest share of emissions comes from enteric fermentation, a digestion process within the animal’s rumen (Figure 1). As such, having a good livestock inventory (including herd/flock structures and body weights) and diet data (both quantity, quality and nutritional composition) is important. For pigs and poultry, feed production and manure management are the main emission sources, so key data includes where and how feed is produced and how manure is managed.

Comparing scenarios

To qualify for climate finance, there is generally a requirement to quantify a change in emissions, through either comparing a business-as-usual (BAU) production scenario to an improved production efficiency scenario; or comparing to a scenario in a past reference year. As such, at least two production scenarios are modelled and the emission estimations compared. It is important to have appropriate evidence to support any changes between these scenarios. For example, to demonstrate the mitigation potential of improving dairy cattle nutrition, feed ration data and subsequent milk yield impacts are essential. Comparing these scenarios then shows you the potential to reduce emissions.

More productive animals generally reduce emissions per kg of product. Comparing the emission intensity (kg CO₂ equivalent per unit of product) in the two scenarios demonstrates the potential to reduce emissions associated with the increased production of food. For example, in a scenario without investment, the emission intensity of a litre of milk is 10 kg CO₂ equivalent. In a scenario where intervention has taken place, the emission intensity is 5 kg CO₂ equivalent. As a result, for every litre produced in the future with the intervention, 5 kg CO₂ equivalent are averted. If mitigation measures are coupled with efforts to limit herd growth, absolute emissions can be reduced, or their increase can be slowed. 

Interpreting the results of models

Biological systems are inherently complex and interconnected. This can make it difficult to predict the quantitative effects of mitigation measures. The level of confidence in the estimate depends on which intervention is being assessed. For instance, improving ruminant nutrition is likely to reduce enteric methane emissions. However, this intervention may also increase feed intake and alter feed sourcing, highlighting the need for using lifecycle assessments. Other mitigation opportunities, such as carbon sequestration through changes in land use practices, can be highly effective. However, their potential can vary significantly due to many biological factors. Estimates of mitigation should ideally communicate their level of confidence quantitatively or, when this is not possible, at least explain key uncertainties qualitatively. For example, one approach is to identify the data input points that the modelled results are most sensitive to, then perform an analysis (such as a Monte Carlo simulation) to explore how this uncertainty can propagate through to the modelled emissions estimations (put simply, this explores if an input parameter is wrong, how wrong will the modelled results be).

Conclusion

If recognised methods are followed and appropriate input data available, then we can be confident that assessments are sufficiently robust and potential GHG emission reductions associated with changes in animal herds or management practices will be reliably quantified. Livestock has a key role to play in reducing global GHG emissions and ensuring the growing global population, especially in LMICs, are properly nourished.

This document is the result of a collaborative effort of the LD4D Solutions Group on Climate Finance & Livestock. Lead authors: Gareth Salmon (SEBI-Livestock, University of Edinburgh), Danielle Niedermaier (Land O’Lakes Venture37), and Frances Siobhàn Ryan (SEBI-Livestock, University of Edinburgh). We gratefully acknowledge the feedback of Michael Macleod (Scotland’s Rural College), Leah Arabella Germer (World Bank), Ben Henderson (World Bank), Anne Mottet (International Fund Agricultural Development), An Notenbaert (Alliance of Bioversity International and CIAT) and Kurt Rockeman (RuMeth International Ltd).

The LD4D Climate Finance & Livestock Solutions Group brings together decision-makers and experts to generate evidence-based insights that help livestock development projects access climate finance. The group aims to unlock much-needed funding for a sector that is currently underrepresented in climate finance - despite its crucial role in adaptation and mitigation.

Livestock Data for Decisions (LD4D) is a worldwide community of over 1,000 members and partners working to improve livestock data and evidence in low- and middle-income countries. LD4D aims to support the transition to more sustainable and inclusive livestock systems by mobilizing trusted livestock data for better policies, investments, and strategies. Learn more at livestockdata.org.

This work is licensed under Creative Commons Attribution-NonCommercial- NoDerivatives 4.0 International. To view a copy of this license, visit https://creativecommons.org/licenses/by-nc-nd/4.0/. September 2024.

We welcome your feedback. Please contact us with any feedback or suggestions. If you are interested in supporting our work and exploring partnership opportunities, please visit livestockdata.org/partnership.