Carbon footprint of coffee production: the case study of Indian Robusta coffee
Title | Carbon footprint of coffee production: the case study of Indian Robusta coffee |
Publication Type | Journal Article |
Year of Publication | 2025 |
Authors | Iglesias SP, Karka Pb., Posada Jc A, Lindeboom REF, van den Broek M, Gopi G, al. et |
Journal | Energy Nexus |
Volume | Volume 18 |
Date Published | 06/2025 |
Keywords | Carbon footprint; LCA; Robusta coffee; Green coffee; Roasted coffee; Ground coffee |
Abstract | Coffee processing encompasses the conversion of coffee cherries into marketable products, including the removal of outer layers to produce green coffee and, in extended chains, their roasting into roasted coffee, and grinding into ground coffee. Calculating the carbon footprint (CF) in coffee processing is crucial for identifying and mitigating key sources of greenhouse gas (GHG) emissions. Utilizing the Life Cycle Assessment (LCA) methodology, the current study quantifies the CF associated with Robusta dry coffee processing by collecting primary data through interviews with coffee producers and visits to coffee processing units, roasting, and grinding facilities in Wayanad, India. The study identifies GHG emission hotspots across two scenarios. Scenario A includes transportation of dried coffee beans from farm to coffee processing unit, green coffee production, packaging, roasting, and grinding at a local unit, while Scenario B covers local transportation of green coffee beans from India to The Netherlands, green coffee production, packaging, and its transportation from India to The Netherlands. Cultivation and harvesting of coffee cherries, consumer-level preparation and use, and disposal of coffee products are outside the scope of this study. The functional unit is defined as 1 kg of green coffee for both scenarios. Findings show that the CF equals 0.62 and 0.38 kg CO2eq per kg of green coffee for scenarios A and B, respectively. Roasting (78 % of CF), and sea transportation (66 % of CF) emerged as the main hotspots of GHG emissions for scenario A, and scenario B, respectively. |
URL | https://www.sciencedirect.com/science/article/pii/S277242712500097X |
DOI | 10.1016/j.nexus.2025.100456 |