Calculation of external climate costs for food highlights inadequate pricing of animal products

The paper investigates how to quantify and monetize greenhouse gas (GHG) externalities from agricultural production, with the goal of revealing the gap between current producer prices and the true social and environmental costs of food. Existing market prices do not include external climate damages, leading to distortions and welfare losses. The study aims to develop a differentiated, bottom-up method to calculate food-category-specific external costs, distinguishing between conventional and organic systems and major food categories (plant-based, animal-based, dairy) in Germany. This is important because animal agriculture is a major source of CO2, CH4, and N2O emissions, and prior analyses have not linked category- and system-specific emissions with monetized costs. By applying life-cycle assessment (LCA) and meta-analytic estimates of organic–conventional differences and monetizing with a damage cost rate, the study evaluates necessary price surcharges to internalize climate externalities and inform policy consistent with the polluter-pays principle.

Earlier external cost assessments of agriculture (e.g., Pretty et al. for the UK; analogous studies for the USA and Germany) used top-down approaches and did not link specific emission sources to costs. Later, bottom-up methods were developed for specific pollutants, such as reactive nitrogen, and applied to sectors like Dutch pig production. Numerous studies quantify food-category-specific GHG footprints and compare conventional versus organic systems, but monetization has been limited to select categories without an encompassing linkage across categories and farming systems. Carbon pricing varies widely: market prices for emissions allowances were low in the study’s reference period, while damage cost estimates recommended by the German Federal Environment Agency (UBA) increased from 80 €/tCO2eq (2010) to 180 €/tCO2eq (2019), aligning with IPCC assessments (~173.5 €/tCO2eq). The literature also projects rising necessary carbon prices (>400 $/t by mid-century). This context motivates a comprehensive, category- and system-specific monetization of GHG externalities.

Study scope and system boundary: Germany, reference year 2016; system boundary cradle-to-farmgate. Two-step framework: (1) quantification of category-specific GHG emissions; (2) monetization to derive external costs and percentage price surcharges relative to producer prices. Quantification: Food items are grouped into broad categories (plant-based, animal-based, dairy) and narrow categories (plant-based: vegetables, fruits, cereals, root crops, legumes, oilseed; animal-based: eggs, poultry, ruminants, pork; dairy: milk only). Baseline food-specific emission data for conventional production are sourced from the GEMIS LCA database (German-focused), originally for 2010 and adjusted to 2016 using linear regression on German agricultural emission trends (2000–2015 UBA data). Emissions include CO2, CH4, and N2O with 100-year GWPs of 28 and 265 for CH4 and N2O. Land-use change (LUC) emissions are not in GEMIS; these are calculated separately for conventional production following Ponsioen and Blonk using trade and land-use statistics. Given German arable area has been decreasing and organic feed is largely locally/regionally sourced per EU organic regulations, LUC is assumed negligible for organic production in Germany. LUC is primarily attributed to imported soymeal used in conventional feed; country-specific late LUC factors for Argentina and Brazil are weighted by import shares (result: 2.54 kg CO2eq/kg soymeal) and allocated to soymeal inputs of relevant products. Aggregation: Food-specific conventional emissions are aggregated to narrow and broad categories by weighting with German 2016 production volumes used for human consumption (Destatis, AMI). Only conventional production quantities are used for weighting to enable consistent comparison; ratios are applied to derive category means. Organic–conventional differentiation: GEMIS provides conventional data; organic emission factors are derived by applying meta-analytically estimated emission differences between systems and adjusting for yield/productivity gaps to express results per kg product. For plant-based products, a yield gap (conventional 117% of organic) is applied; for animal-based and dairy, productivity gaps (179% and 152%, respectively) are used. A set of European studies (Germany and comparable EU contexts) is synthesized using a quality-weighting scheme based on publication year, citations/year, and journal rank (no standard errors available). Resulting emission difference ratios (organic vs conventional, per kg) are: plant-based 57%, animal-based 150%, dairy 96% (before adding LUC). These ratios are applied to the aggregated conventional category emissions to derive organic category emissions. Monetization: External costs are obtained by multiplying category-specific emission intensities by the damage cost rate of 180 €/tCO2eq recommended by UBA (consistent with IPCC). Producer prices at farmgate are calculated as total producer proceeds divided by total production quantity per category (Destatis/AMI). Percentage surcharges are computed as the ratio of external costs to producer prices, indicating the additional price needed to internalize GHG externalities. LUC-related costs are reported separately for conventional categories where applicable.

- Emission intensities (kg CO2eq/kg product) by broad category: animal-based conventional 8.90 without LUC, 13.38 with LUC; organic 13.39. Dairy conventional 1.09 (1.33 with LUC); organic 1.05. Plant-based conventional 0.20; organic 0.11. - Narrow category emission intensities (kg CO2eq/kg): ruminants 24.84 (36.95 with LUC) conventional; 37.37 organic. Poultry 13.16 (15.81 with LUC) conventional; 19.80 organic. Pork 5.54 (9.56 with LUC) conventional; 8.34 organic. Eggs 1.17 (1.18 with LUC) conventional; 1.76 organic. Legumes 0.03 conventional; 0.02 organic (lowest among all). - External costs (€/kg product) and relative surcharges (% of producer price): • Broad categories: animal-based conventional C = 1.60 €/kg (2.41 with LUC), Δ = 97% (146% with LUC); animal-based organic C = 2.41 €/kg, Δ = 71%. Dairy (milk) conventional C = 0.20 €/kg (0.24 with LUC), Δ = 75% (91% with LUC); dairy organic C = 0.19 €/kg, Δ = 40%. Plant-based conventional C = 0.04 €/kg, Δ = 25%; plant-based organic C = 0.02 €/kg, Δ = 6%. • Narrow categories conventional (Δ without/with LUC): eggs 17% (18%); poultry 138% (165%); ruminants 132% (197%); pork 74% (128%). Organic: eggs 9%; poultry 154%; ruminants 173%; pork 42%. - Absolute external costs: animal-based products have the highest absolute external costs at 2.41 €/kg, around 10 times higher than dairy and approximately 68.5 times higher than plant-based products (depending on category comparison and LUC treatment). - Organic advantages by broad category: after accounting for LUC, organic plant-based and dairy have lower emissions per kg than conventional (−43% and −21% respectively), while organic animal-based is slightly higher per kg on average; however, percentage surcharges are consistently lower for organic due to higher producer prices. - LUC is a major driver of higher emissions and costs for conventional animal-based products via imported soymeal feed.

The findings demonstrate that animal-based products, particularly ruminant meat, impose the largest climate externalities due to inefficient feed conversion, enteric methane, manure management, and energy use. Secondary animal products (milk, eggs) show lower emissions per kg than meat due to higher lifetime output per animal. Organic systems generally reduce emissions for plant-based and dairy categories through prohibition of mineral N fertilizers, lower indirect emissions from fertilizer production, more careful nutrient management, greater reliance on grazing, and reduced imported feed, which avoids LUC emissions. However, organic animal products can have higher per-kg emissions due to lower productivity, longer lifespans, and greater land requirements per animal; within animal products, the magnitude of LUC from soymeal feed inputs shapes the advantage, with pork showing relatively better performance for organic due to high LUC shares in conventional feed. Monetized, these differences translate into large necessary price surcharges for animal-based foods, especially conventional, supporting policies to internalize externalities. Internalization could shift consumption towards lower-carbon foods (organic plant-based), reduce food waste via higher valuation, and confer health co-benefits, while revenues could fund farmer transitions and social compensation, improving allocative efficiency and fairness under the polluter-pays principle.

This study develops and applies a bottom-up framework to quantify and monetize GHG externalities for German food categories, differentiating by farming system. It reveals substantial underpricing of animal-based products relative to their climate damages and smaller surcharges for plant-based and dairy products, with organic production generally performing better for plant-based and dairy. The method is transferable to other regions and to additional externalities (e.g., nitrogen losses, energy use) given LCA databases and production/price data. Future work should refine product-specific LUC estimation, extend analysis beyond farmgate to processing and logistics, and integrate uncertainty analyses and dynamic carbon pricing trajectories. Implementing even partial internalization could reduce market imperfections and enhance societal welfare by aligning prices with true costs.

- System boundary limited to cradle-to-farmgate; downstream stages (processing, distribution, retail, consumption) are not included. - LUC emissions are estimated primarily for soymeal in conventional systems and treated separately; product-specific and alternative LUC methodologies may yield different results. - Organic emission factors are derived via meta-analysis without reported standard errors; a proxy quality-weighting (year, citations, journal rank) was used, introducing uncertainty. - Assumes conventional production shares for weighting category aggregates due to data limitations for organic production shares. - GEMIS emissions anchored in 2010 and extrapolated to 2016 using trend regression; potential model/data uncertainties remain. - Focus on Germany (2016) limits generalizability to other geographies and time periods without re-parameterization. - Dairy category limited to milk; other dairy products not assessed due to processing beyond farmgate. - Damage cost rate (180 €/tCO2eq) is subject to debate and may evolve, affecting monetized costs and surcharges.