Nature-based climate solutions? Companies are key.
The impact of agricultural supply chains.
In the context of growing global population and increasing demand for agricultural products, the joint goals of avoiding dangerous climate change and reversing the ongoing decline in the state of nature will require significant changes to many aspects of society. Agriculture, forestry, and land use change account for 23% of global greenhouse gas emissions (IPCC), while pressure from agriculture, deforestation, and land degradation is a dominant driver of biodiversity decline on land (IPBES). Agricultural land covered 37% of the global land surface area in 2019. Of this area, approximately one-third were croplands and two-thirds used for raising livestock (FAO 2021). This suggests that meeting growing food needs while reducing the environmental impacts of agriculture is one of the foremost challenges of the 21st century (Tim Searchinger et al. 2019).
Companies with agricultural commodities in their supply chains play a key role in mitigating environmental and social impacts and in contributing to nature-based climate solutions. The business case for companies to identify and reduce these impacts is growing. In part, this stems from regulation. For example, in 2021 the European Commission proposed regulation on deforestation-free products and in 2022 proposed a Directive on corporate sustainability due diligence in company value chains. The UK has also adopted the Environment Act, Schedule 17, which focuses on deforestation risks from commodities linked to commercial activities. While the U.S. is also considering legislation to minimize the environmental impacts of international trade.
How can companies assess environmental impacts?
Despite the urgency of the sustainability challenge, the availability of generally applicable, accurate, and practical tools for assessing the environmental impacts of agricultural supply chains remains limited. Life Cycle Assessment (LCA) approaches have been critical for assessing a product’s or service’s potential environmental impacts (Hellweg and Milà i Canals 2014). A recent consolidated and standardized dataset of typical environmental impacts (greenhouse gas emissions, pollution) for a range of agricultural products has been derived using LCA approaches (Poore and Nemecek 2018) and has become a standard resource for footprinting analysis (e.g. Foundation Earth). This LCA approach provides information on characteristic environmental impacts associated with a particular production system in a specific geography, such as nations.
However, environmental impacts can be very sensitive to precisely where and how a commodity is produced (Godar et al. 2016; Lathuillière et al. 2021). For example, Poore and Nemecek (2018) estimate the range of greenhouse gas emissions associated with agricultural products and find huge variability across producers and across products. The emissions arising from 100g of beef protein sourced from a beef herd range from around 20 up to 105 kg-CO2 equivalents (these are values for the 10th and 90th percentiles so exclude extreme low and high emission estimates). The context dependency of impacts is amplified for land use change, water use and biodiversity, for which it really matters where the impacts occur. In the case of water, for some watersheds and locations within them, there is already scarcity, so further water withdrawals are likely more impactful than elsewhere (Gleick and Palaniappan 2010). Likewise for land use change, loss of intact tropic forest ecosystems can have a much more detrimental biodiversity impact than loss of plantation forestry ecosystems in the northern hemisphere (Newbold et al. 2015).
In response, tools have been developed that use more precise spatially explicit information on production and the supply chain links to consumption. The platform ‘Trase’ for instance compiles and links production and trade data with transportation cost optimization to trace commodity flows back to production landscapes. For Brazilian soy, Trase combines municipally reported soy production statistics with supply chain, logistics and international trade data to identify the footprint of consumption in other countries (Godar et al. 2016; Green et al. 2019).
Developments in remote sensing and cloud computing are transforming capabilities to observe deforestation or other environmental impacts (Taylor et al. 2020). For example, the Global Forest Watch Pro tool uses these techniques to help companies identify deforestation events or risks, in and around the supply areas of the mills, silos or slaughterhouses from which they source (Amaral and Lloyd 2019).
The scale of agriculture’s footprint and the diversity of its production systems and supply chains indicate the urgent need for new and comprehensive tools for assessing the impacts of supply chains. For instance, Trase provides excellent, detailed traceability information, however, this is for a specific subset of commodities and countries. Global Forest Watch Pro provides detailed information about deforestation impacts but does not provide information about supply chains or sourcing locations. These gaps arise primarily because of the uncertainties and time lags in global agricultural supply chain and production data. In this environment of limited information, the LandGriffon framework enables agricultural supply chain companies to evaluate, plan, and mitigate impacts arising from diverse supply chains.
The LandGriffon approach.
The LandGriffon methodology starts from the presumption that many supply chains are difficult to track and manage. While some companies within agricultural supply chains have direct relationships with the farms and processors that produce their raw materials, in many cases they only have a rough idea of who and where their materials are ultimately sourced from. This is mostly due to the aggregation of resources, geographic distance, and processing steps from commodity production (zu Ermgassen et al. 2022). Although this lack of supply chain knowledge is particularly the case for companies furthest downstream in the supply chain, it is frequently true for manufacturers, traders, and other intermediaries. Nonetheless, the need remains for companies to make decisions despite the imperfect information they may currently possess.
The past decade has seen an explosion in global, high-resolution environmental monitoring products derived from satellite remote sensing and global modeling approaches. These data are particularly relevant to managing impacts and risks associated with agricultural production. Yet they remain minimally used by companies seeking to improve their environmental performance, partly because of the difficulty of tracing where materials are ultimately sourced from (David Patterson et al. 2022).
LandGriffon is inspired by the need to move beyond life-cycle assessment approaches and provide spatially explicit information on agricultural supply chain impacts. It addresses the challenge of a lack of traceability by providing a framework for companies to spatialize agricultural supply chain information and evaluate impacts as accurately as possible. We estimate supply chain impacts using a hierarchical approach. When little information is available, we use a probabilistic model to identify likely sourcing regions and estimate impacts. When companies know more about their suppliers and sourcing locations, this information is used to improve the quality and accuracy of estimates. When field-level impact assessments are available, these data can supersede LandGriffon estimates.
Given the urgent need for companies to take action to evaluate, plan, and mitigate environmental impacts, we believe that the LandGriffon framework fills an essential gap in enabling companies to act in environments of limited information.
For companies with agricultural supply chains, we believe there is currently a gap in tools that can be applied globally to agricultural commodities, integrate with current supply chain systems, and help explore pathways to reduce impacts and associated risks to their businesses.
LandGriffon aims to address these and other gaps by having the following properties:
- Ability to integrate with diverse company supply chain data and systems.
- Is spatially explicit.
- Generally applicable for all agricultural commodities at global scale.
- Extendable so that it works with currently available data but can readily incorporate newer data and indicators as these become available.
- Allows companies to explore various pathways to reduce impacts by evaluating the effects of actions such as changing recipes or sourcing locations or reducing the environmental impacts of producers.
- Promotes greater precision in supply chain traceability by rewarding this with more accurate impact estimates.
- Aligns with the needs of companies in implementing the draft guidelines proposed by the Science Based Targets Network (SBTN) and the Taskforce on Nature-related Financial Disclosures (TNFD), (TNFD 2022). This is manifested in the features and baseline impact indicators already implemented and under development in the tool.
Interested in what LandGriffon could do for your company?
Contact us now at hello@landgriffon.com
LandGriffon is developed by Satelligence and Vizzuality, and advised by the Stockholm Environment Institute and their Trase Initiative.
Thank you Mike Harfoot, Elena Palao, Francis Gassert and Rens Masselink for preparing the methodology.
