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Aerial view of harvested palm oil nuts

Carbon Accounting: Why emissions vary widely from farm to farm

  • Date: 09 May 2024
  • Author: Emily Moberg

This is the third in a series of blog posts on carbon accounting standards. The first post provided an overarching explanation of carbon accounting and its inherent challenges. The second post examined variability in companies’ “Scope 3” emissions—that is, emissions that originate from upstream and downstream activities, which often constitute 90% or more of companies’ emissions. Here we discuss factors behind the variability of emissions across farms and regions.

The variability in greenhouse gas (GHG) emissions per unit of product across the agricultural sector is striking, even when comparing identical products. Understanding this variability is crucial, particularly when assessing the complexities of supply chains. This variability manifests at multiple scales—from individual farms to regions—and significantly impacts both corporate strategy and policy formulation.

At the farm level, differences in emissions can be profound, even among neighboring farms that are both practicing conventional agriculture. For instance, two farms growing the same row crops can exhibit up to a twofold difference in emissions. Similar variability exists in aquaculture, where shrimp production emissions can vary by as much as five times. These discrepancies are often due to the efficiency of input use, influenced by factors such as soil quality, farmer skill, and local weather conditions. Such variability within a farm itself can result in certain areas being more profitable than others.

Farms employing different agricultural practices can show even more dramatic contrasts in emissions—sometimes differing by 10 to 50 times. For example, differences in application of fertilizers, pesticides, and other inputs in coffee can lead to a fivefold increase in on-farm emissions. Likewise, palm oil grown on drained organic soils can generate 4-20 times more on-farm emissions than average.

Regionally, although there is a wide range of practices and efficiencies among producers, the average performance blends the results from the best and the worst producers, thus masking critical variations between producers that must be addressed.

Environmental variability also contributes to this variability in emissions. Soil conditions, rainfall patterns, and other climatic factors differ not just from one farm to another but also from one field to another. These natural resource variations influence efficiency even when the same practices are used. They also encourage the adoption of farming practices tailored to local condition

Climate change will continue to amplify these variations and make them more unpredictable, heightening the challenges farmers face. This means we need to pay attention to changes in practices over time. And if farmers are unable to adapt to changing conditions, we must be aware of the impacts of persisting with outdated practices.

These “embedded” differences in carbon emissions grow more when agricultural outputs are used as feed or processed into other products. For example, the conversion ratios for livestock feed vary significantly: poultry may require two kilograms of feed per kilogram of meat, whereas beef might need between six to eight kilograms for the same output. Similarly, cheese production might use four to five kilograms of milk to produce just one kilogram of cheese. So, if a feed ingredient starts with a five-fold difference in carbon footprint, depending on the animal consuming it, we could easily have a 10-fold or more difference in the animal’s footprint. These figures highlight how agricultural emissions can escalate when products undergo further processing or are used in different production contexts.

Often, we try to characterize GHG performance at a larger scale still—national or continental scale averages. Again, by grouping performance of the best and worst in a way that mixes the causes of that variability, we frequently can miss opportunities for mitigation and engagement. Both the mitigation strategies and their costs differ greatly for the better and worse performers; in general, mitigating the worst has outsized benefits.

To address this variability, companies need to transform how they track and manage it—and that means rethinking traditional approaches to traceability and transparency. Companies far downstream of farms or aggregators cannot access this information without upstream cooperation. By identifying the least efficient practices and focusing on elevating their performance, we can significantly reduce the overall environmental footprint of the agricultural sector, without jeopardizing the amount of food produced.

Emily Moberg is Director of Scope 3 Carbon Measurement and Mitigation, on the Markets team at WWF.

For more information on the variability of production emissions, check out these 10 commodity-specific case studies.