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New Study Reveals Accurate Carbon Footprint of Milk in Bangladesh
Confirmed
In Short: A new study from the University of Connecticut has determined a more accurate measure of the carbon footprint of milk produced in Bangladesh, highlighting the importance of farm-specific data in environmental impact assessments.
A new study from the lab of Elias Uddin, assistant professor of animal science at the University of Connecticut, has determined a more accurate measure of the carbon footprint of milk produced in Bangladesh. The study, published on September 16, 2026, in UConn Today, found that on average, during a five-year period, the carbon footprint of milk on the farm was 5.18 kilograms per kilogram of milk.
Anna Zarra Aldrich, from the College of Agriculture, Health and Natural Resources, explained, 'This study demonstrated that using farm-specific data helps more accurately measure the environmental impact of creating and delivering milk. Every product or service has a “carbon footprint,” a measure of the environmental impact of creating or delivering it.
The research underscores the significance of precise data in understanding the environmental impact of agricultural products. By focusing on farm-specific data, the study provides a more nuanced understanding of the carbon footprint of milk, which can inform better environmental practices and policies.
While the study focuses on milk in Bangladesh, the methodology and findings can be applied to other regions and agricultural products. The accurate measurement of carbon footprints can help farmers and policymakers make informed decisions to reduce environmental impacts and promote sustainable practices.
What's confirmed
- A new study from the lab of Elias Uddin, assistant professor of animal science at the University of Connecticut, has determined a more accurate measure of the carbon footprint of milk produced in Bangladesh. The study, published on September 16, 2026, in UConn Today, found that on average, during a five-year period, the carbon footprint of milk on the farm was 5.18 kilograms per kilogram of milk.
- Anna Zarra Aldrich, from the College of Agriculture, Health and Natural Resources, explained, 'This study demonstrated that using farm-specific data helps more accurately measure the environmental impact of creating and delivering milk. Every product or service has a “carbon footprint,” a measure of the environmental impact of creating or delivering it.
- The research underscores the significance of precise data in understanding the environmental impact of agricultural products. By focusing on farm-specific data, the study provides a more nuanced understanding of the carbon footprint of milk, which can inform better environmental practices and policies.
- While the study focuses on milk in Bangladesh, the methodology and findings can be applied to other regions and agricultural products. The accurate measurement of carbon footprints can help farmers and policymakers make informed decisions to reduce environmental impacts and promote sustainable practices.
What's still developing
- In addition to battery electric power that produces zero tailpipe emissions, it has been developed with a focus on keeping its carbon footprint to a minimum across the complete vehicle lifecycle.
- United Nations University Institute for Water, Environment and Health (UNU-INWEH), Richmond Hill, Ontario, Canada. doi: 10.53328/INR26RMA002 This report, Environmental Cost of Artificial Intelligence: Carbon, Water and Land Footprints, by the United Nations University Institute for Water, Environment and Health (UNU-INWEH) on its 30th anniversary, examines one of the most underexplored consequences of AI’s rapid expansion: the environmental footprints of the energy required to power it.
- The report also shows that AI’s footprint is shaped by both major infrastructure trends, including the rapid growth of data centers, and everyday use patterns, including model choice, output length, modality, and the growing use of text, image, and video generation.
- The report moves beyond a carbon-only lens by quantifying the carbon, water, and land footprints associated with the electricity used to train, deploy, and operate AI systems at scale.
- Every kilowatt-hour used by AI carries carbon, water, and land implications, and these footprints do not always move in the same direction: low-carbon electricity is not automatically low-water or low-land.
- Importantly, the report frames AI’s environmental footprint as a governance and justice challenge, not only a technical problem.