Increased government investment in climate change mitigation is prompting agricultural sectors to find reliable methods for measuring their contribution to climate change. With that in mind, a team led by scientists at the University of Illinois Urbana-Champaign proposed a supercomputing solution to help measure individual farm field-level greenhouse gas emissions.
, directed by natural resources and environmental sciences professor Kaiyu Guan, synthesized more than 25 of the group's previous studies to quantify greenhouse gas emissions produced by U.S. farmland.
"Artificial intelligence also plays a critical role in realizing our ambitious goals to quantify every field's carbon emission," said Zhenong Jin, a professor at the University of Minnesota who co-led the study.
Illinois natural resources and environmental sciences professor Kaiyu Guan says that there are many farming practices that can go a long way to reduce greenhouse gas emissions, but the scientific community has struggled to find a consistent method for measuring how well these practices work. His new study presents a comprehensive approach to help the stakeholders within the agricultural industry “speak the same language” when discussing greenhouse gas emissions.
The challenge of this work will be encouraging widespread adoption of the system, the researchers said.
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