Two biological processes, one accounting problem
For any food or beverage company with dairy, meat, or animal feed in its supply chain, the largest slice of its carbon footprint usually isn't in its own factories or trucks. It's on farms it doesn't own, arising from processes it has no direct control over: enteric fermentation and manure management. Understanding what these are, biologically, is the first step to understanding why they're so hard to account for under the GHG Protocol.
Enteric fermentation
Ruminant animals — cattle, sheep, goats, buffalo — digest fibrous plant material using microbes in a specialized stomach chamber called the rumen. That microbial fermentation process is what lets a cow turn grass into milk and muscle, but it also produces methane as a byproduct, which the animal releases mostly through belching. This is enteric fermentation: it is a normal part of ruminant digestion, not a malfunction or an inefficiency that can be engineered away entirely, though it can be reduced through diet, breeding, and feed additives.
Methane matters disproportionately in climate accounting because of its global warming potential. On a 100-year timeframe, the IPCC's widely cited figure puts methane at roughly 28 times more warming potential than an equivalent mass of CO2, and its short-term (20-year) potency is even higher. That means a dairy or beef supply chain can carry a large climate impact even when the absolute tonnage of gas released looks small next to a factory's CO2 emissions.
Manure management
The second source is what happens to animal waste after it leaves the animal. How manure is stored and treated determines what it emits. Manure stored in liquid form in lagoons or pits, without oxygen, decomposes anaerobically and produces methane, similar in principle to what happens in a landfill. Manure that is handled as a solid, spread on fields, or composted with airflow tends to decompose aerobically, producing far less methane but more nitrous oxide, another potent greenhouse gas. The management system — not just the animal count — is what drives the emissions profile, which is one reason average, herd-size-based estimates can be misleading.
Where this lands in a company's inventory
For a livestock producer, enteric fermentation and manure management are counted directly in Scope 1, since the emissions occur at facilities and operations under their control. But for a downstream food or retail company — a dairy processor, a cheese brand, a fast-food chain, a grocery retailer — these emissions occur upstream, at the farm level, before the company ever takes possession of the milk, meat, or feed ingredient. Under the GHG Protocol's Corporate Value Chain (Scope 3) Standard, that places them in Category 1: Purchased Goods and Services.
This is a defining feature of agricultural Scope 3 accounting. A beverage company reporting its Category 1 footprint for dairy ingredients is, in effect, reporting a rolled-up estimate of enteric fermentation and manure emissions from thousands of farms it has never visited, aggregated through however many processors and cooperatives sit between the farm gate and its purchase order.
Why the data quality hierarchy matters here more than most categories
The GHG Protocol's data quality hierarchy — spend-based, average-data, hybrid, supplier-specific, from weakest to strongest — is relevant everywhere, but livestock supply chains are one of the sharpest illustrations of why it matters.
A spend-based estimate applies an emissions factor to the dollars spent on dairy or meat inputs. It's fast to produce and almost useless for identifying reduction opportunities, because it can't distinguish between a supplier using anaerobic lagoons and one using a covered digester that captures methane for energy. An average-data approach improves on this by applying regional or sector-average emissions factors per unit of product (per liter of milk, per kilogram of beef), which at least reflects some production-method reality if the averages are well constructed. Supplier-specific, primary data — herd management practices, manure handling systems, feed composition, actual farm-level output — gives the most accurate picture, but is expensive and slow to collect across a supply base that may include family farms, cooperatives, and large-scale operations with very different levels of record-keeping.
Most food companies start at the spend-based or average-data end of the hierarchy simply because that's what's available in year one. The meaningful work is moving toward hybrid or supplier-specific data for the highest-volume, highest-impact ingredients first, rather than trying to upgrade the entire supply base at once.
Why this is becoming harder to ignore
The regulatory pressure on this kind of disclosure is increasing, even where the specific rules don't single out agriculture. The EU's CSRD and ESRS E1 push companies toward comprehensive Scope 3 disclosure under a double materiality lens, and can reach non-EU companies with large enough EU operations. California's SB 253 requires Scope 3 disclosure, with assurance requirements phasing in over time, for large companies doing business in the state regardless of where they're headquartered. Neither of these rules was written with dairy farms in mind, but any food or beverage company subject to them will find that livestock-related Category 1 emissions are among the largest and least precise numbers in their inventory, and therefore among the first places auditors and stakeholders will ask hard questions.
What actually moves the number
For a purchasing company, the practical levers are less about accounting technique and more about supplier engagement: working with dairy and livestock suppliers on feed formulation, methane-reducing feed additives, manure capture and digestion systems, and herd management practices that improve productivity per animal. None of that shows up in a spend-based estimate, which is exactly the point. If the measurement system can't detect an improvement a supplier makes, it can't reward it, and the incentive to make that improvement weakens. Getting Category 1 data quality right for livestock ingredients isn't just a reporting exercise — it's what makes supplier engagement programs capable of showing results at all.