Crop farms emit less, livestock farms lead in GHG emissions

Polish researchers have introduced a detailed methodology for estimating greenhouse gas (GHG) emissions at the individual farm level. Their findings lay the groundwork for precision-based climate policy within the European Union’s agricultural sector, addressing longstanding challenges in emissions accounting across diverse farming systems.

The study, titled “Farm Greenhouse Gas Emissions as a Determinant of Sustainable Development in Agriculture—Methodological and Practical Approach” and published in Sustainability (2025, 17, 6452), presents an original and replicable strategy for evaluating farm-level emissions using Poland’s Farm Accountancy Data Network (FADN), grounded in Intergovernmental Panel on Climate Change (IPCC) methodologies. The authors aim to offer a robust tool that supports both climate action and policy targeting, bridging critical data gaps that have hampered efforts to decarbonize agriculture.

How can farm-level emissions be accurately calculated?

The study aimed to develop a comprehensive and replicable method to calculate GHG emissions from individual farms, using existing agricultural accounting databases. The researchers utilized data from 11,029 Polish farms in the 2023 FADN dataset, applying a layered IPCC-compliant model to quantify emissions of carbon dioxide (CO₂), methane (CH₄), and nitrous oxide (N₂O). These were converted to a standard carbon dioxide equivalent (CO₂-eq) using the Global Warming Potential (GWP) index.

Six main emission sources were examined: livestock emissions, direct and indirect soil emissions, field burning of crop residues, fuel combustion, and electricity consumption. Notably, the methodology distinguishes itself by its granularity and transparency. The researchers documented calculation steps, data limitations, and assumptions with such precision that the model can be adopted or adapted by other EU countries using their own FADN datasets.

Livestock-related emissions, particularly methane from enteric fermentation and manure management, were found to be dominant contributors. Soil emissions, especially from synthetic nitrogen fertilizers, were also significant. Where FADN data lacked direct inputs, such as precise quantities of lime or urea, indirect market-based estimates were used. While emissions from land use and land-use change (LULUCF) were excluded due to data unavailability, energy use from fuel and electricity was factored in, revealing its varying weight across farm types.

What are the emission patterns across farm types?

The study categorized farms using the European Community Typology of Agricultural Holdings into seven types (excluding wine farms): field crops, horticulture, permanent crops, milk, other grazing livestock, granivores, and mixed farms. The analysis revealed stark disparities in emissions, largely tied to production focus, land size, and livestock density.

Milk-producing farms emerged as the highest emitters, averaging 224 tonnes of CO₂-eq per year, more than double the emissions of the average Polish farm. Granivore and other grazing livestock farms also registered elevated emissions, at 147 and 109 tonnes respectively. By contrast, farms focused on horticulture, permanent crops, and field crops had the lowest emissions, with some averaging as little as 12 tonnes annually.

The structure of emissions also varied sharply. In dairy farms, over 70% of GHG output stemmed from livestock, whereas in horticultural systems, energy use played a dominant role, contributing nearly 40% of total emissions. Crop-specialized farms were heavily impacted by soil emissions, accounting for roughly 40% of their total footprint. Across most farm types, emissions from crop residues and indirect nitrogen loss via volatilization and leaching added meaningful weight.

When normalized per livestock unit or hectare of utilized agricultural area (UAA), efficiency dynamics shifted. Granivore farms demonstrated the lowest emissions per livestock unit, benefiting from the relatively low GHG output of pigs and poultry compared to cattle. In contrast, dairy farms were the most emission-intensive per animal. Similarly, horticultural, granivore, and milk farms showed higher emissions per hectare, indicating intensive input use. Permanent crop farms, on the other hand, had the lowest land-use emissions per hectare, reinforcing their sustainability advantage.

What are the implications for policy and climate action?

By quantifying emissions at the micro-level and correlating them with production types, land use, and energy consumption, the research opens the door to targeted climate interventions. The authors argue that generic climate policies risk being ineffective or misdirected unless they consider the heterogeneous nature of agricultural emissions.

Their findings suggest that strategic public aid should prioritize high-emission farm types such as dairy and granivore systems, while tailoring mitigation measures to specific emission sources within each type. For instance, reductions in livestock numbers or changes in manure management may yield large benefits in ruminant-heavy operations, whereas precision fertilization and energy efficiency could be more impactful in crop-focused or horticultural systems.

The research also underscores critical gaps in existing data infrastructures. While FADN provides a robust platform, its limitations, such as the exclusion of small farms and incomplete environmental data, hinder comprehensive emissions tracking. The authors note that the recent transformation of FADN into the Farm Sustainability Data Network (FSDN) is a step forward, but additional data on land-use practices, renewable energy adoption, and urban fertilizer use is still needed.

Despite these limitations, the proposed methodology offers an immediate path forward for enhancing the precision of climate action in agriculture. It provides a blueprint not only for Polish policymakers but also for other EU nations seeking to align agricultural practices with their 2050 climate neutrality goals.