For a food, beverage, or agribusiness company, Category 1 — purchased goods and services — is almost never a diversified problem. It is usually one problem: the emissions embedded in a small number of high-impact commodities, and within that, one sub-source that dwarfs the rest — land-use change.
Why land-use change is different from other emissions
Most Scope 3 categories are about energy: fuel burned, electricity used, materials processed. Land-use change is different. When forest, grassland, or peatland is converted to cropland or pasture, decades or centuries of stored carbon are released — sometimes in a single clearing event, sometimes gradually as soil carbon depletes over subsequent years of cultivation.
For commodities like beef, palm oil, soy, and cocoa grown on recently converted land, land-use change emissions can be several times larger than every other emission source in that product's footprint combined — cultivation, processing, and transport included. A packaged food company can spend years optimizing its factory energy use and its logistics network and move its total footprint by a few percent, while a shift in where its soy or palm oil is sourced from moves it by an order of magnitude.
Why the numbers stay so uncertain
Three structural problems keep land-use change accounting rough, even for companies genuinely trying to get it right:
Attribution is probabilistic, not observed. Most companies do not know with certainty whether the specific hectare that grew their soy was forest five years ago. Land-use change accounting typically relies on regional deforestation risk statistics and traceability data, not confirmed field-level history — so the number is a modeled estimate, not a direct measurement, even in the best programs.
The amortization period changes the answer. GHG Protocol guidance (and frameworks like the GHG Protocol Land Sector and Removals Guidance) generally amortize a land conversion event's emissions over 20 years. A company sourcing from land cleared 19 years ago books a small annual charge; land cleared last year books a large one — for what might be the same underlying volume of commodity.
Traceability drops off fast beyond tier one. Direct farm relationships are traceable. Once a commodity passes through a regional aggregator, a crushing plant, or a commodity trader before reaching a branded company, land-of-origin data frequently disappears entirely, which is exactly where most global soy, palm, and cocoa trade actually happens.
What better practice looks like
Companies making real progress on this category tend to do three things differently: they map deforestation risk by sourcing region using satellite-based monitoring rather than self-reported supplier attestations; they prioritize traceability investment on the two or three commodities that dominate their footprint rather than spreading it thin; and they treat land-use change as a sourcing-strategy question, not just a reporting one — because unlike most Scope 3 categories, this is one where switching origin, not switching suppliers, is usually the fastest reduction lever available.
For any food or agribusiness company building a credible Scope 3 inventory, land-use change deserves disproportionate scrutiny relative to its line-item size in a spreadsheet — because in this category more than almost any other, the number that looks smallest on first estimate is often the one most in need of a second look.