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Estimating the carbon footprint of milk in dual-purpose dairy production systems: Influence of animal productivity, functional unit, and emission allocation and quantification methods
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DOI：10.3168/jds.2025-27448.png)
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Abstract
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Our objective was to estimate the effects of productivity gain, functional units (FU), quantification and allocation methods of greenhouse gas emission on milk carbon footprint (CF) in dual-purpose dairy production system in Bangladesh. An attributional cradle-to-farmgate life cycle assessment (LCA) was conducted following ISO-14040/14044 and FAO guidelines, including feed production, enteric emissions, manure management, and farm energy in system boundary. Foreground data including herd structure, milk yield and composition, diets, manure management, and farm energy from Bangladesh Agricultural University Dairy Farm (2018–2023) were used to build LCA model. Enteric methane (CH4), manure CH4, and nitrous oxide emissions were estimated using Intergovernmental Panel on Climate Change Tier-1 and Tier-2 methods. FU compared were 1 kg fat-and-protein corrected milk (FPCM), 100-kcal energy, and 100-g protein. Emissions were allocated between milk and meat using no allocation assumption, biophysical, or economic methods when FPCM was used as FU. Across 5 years, average CF was 5.18 ± 1.03 kg CO2-eq kg−1 FPCM under the no-allocation IPCC Tier 2 approach, and milk CF declined by 37% (6.89 to 4.34 kg CO2-eq kg−1 FPCM) as productivity increased by 63% (3.53 to 5.76 kg cow−1 d−1). Tier 2 method, using system-specific factors, had 27% lower CF than Tier 1. Productivity gain had similar reduction effects on CF when using 100-kcal energy or 100 g protein as FU. Biophysical and economic allocation reduced CF by 47% and 36%, respectively, compared with no allocation. Uncertainty analysis showed wide CF variation across years, and sensitivity analysis identified milk yield and herd structure as the most influential drivers. Enteric fermentation was the dominant emission source (48%), followed by feed (24%), manure (20%), and farm energy (8%). These findings highlight the importance of productivity improvement and methodological choices for shaping CF estimates and evaluating sustainable dairy production in low-input dual-purpose systems.
Keywords:
Carbon footprint
dual-purpose dairy
life cycle assessment
functional unit
allocation methods
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