Estimating the Carbon Footprint of Milk in Dual-Purpose Dairy Production System: Influence of Animal Productivity, Functional Unit, and Emission Allocation and Quantification Methods

This dataset contains five years (2018–2023) of comprehensive herd, feed, manure, and farm operation data collected from a dual-purpose dairy production system in Bangladesh, used to estimate the carbon footprint of milk following IPCC Tier 1 and Tier 2 methodologies. It includes annual herd structure and Animal Units, breed composition, body weight measurements, milk yield and FPCM production, and full milk composition profiles. Detailed ration formulations for all animal categories are provided for each year, along with nutrient composition, feed production inputs (fertilizers, pesticides, diesel, irrigation, machinery), and transportation details. The dataset also includes IPCC equations for enteric methane, manure methane, manure nitrous oxide, nitrogen excretion, and feed-related emissions, as well as farm energy use (electricity and diesel). Annual greenhouse gas emissions by source (enteric fermentation, manure management, feed production, and farm energy) are presented alongside carbon footprint results under three allocation approaches (no allocation, biophysical, and economic) and three functional units (kg FPCM, 100-kcal energy, and 100-g protein). Uncertainty analysis results based on 1,000 Monte Carlo simulations per year are included, providing mean values, standard deviations, and 68% and 95% confidence intervals. The complete field questionnaire used for data collection—covering farm characteristics, feeding, reproduction, manure management, feed production, water and energy use, and historical system changes—is also provided, along with supplementary figures depicting emission flows and Monte Carlo distributions.