AGU Session on Sustainable Agriculture under Climate Change

[Bin Peng]

Dear colleagues,

Hope you are doing great in this pandemic and sorry if this is cross posting. 

I am now writing to invite your submissions to our AGU2020 session on monitoring and modeling soil organic carbon and greenhouse gas emissions for sustainable agriculture and climate change mitigation/adaptation. The deadline for submitting an abstract is 29 July, 2020. Due to the COVID-19, AGU fall meeting in this year will be mostly virtual, which means we don't need to worry about VISA or travel issues.

Here is the full description of our session and you can submit your abstract directly through clicking the following link. Also, we would appreciate any help to promote our session through your own channels.

https://agu.confex.com/agu/fm20/prelim.cgi/Session/103300

GC070 - Sustainable agriculture and climate change: monitoring and modeling the soil organic carbon and greenhouse gas emission of agroecosystems

Climate change and land-use intensification have presented humanity with great challenges in maintaining food security and environmental sustainability. Cropland carbon sequestration achieved through conservative management practices is promising for enhancing soil organic carbon (SOC) and health, reducing greenhouse gas (GHG) emissions, and finally mitigating climate change. Improved modeling and monitoring capacities to track SOC changes and GHG emissions at granular scales are urgently needed in both academia and industry. We invite submissions focusing on: (1) developing scalable and cost-effective monitoring capacities to track SOC changes and GHG emissions; (2) synthesis of multi-source observations to infer cropland SOC changes and GHG emissions, including those from near-surface/airborne/satellite remote sensing, ground surveys, long-term agricultural experiments, and intensive sensor networks; (3) multi-scale process-based modeling of crop, management, environmental, and economic aspects of the agricultural system; and (4) systematic model-data integration to support decision-making for improved farming practice, policy design, and economic returns.

Thanks a lot and hope to see you virtually during AGU2020.

Bin Peng (UIUC), Zhenong Jin (UMN), Jinyun Tang (LBNL), and Kaiyu Guan (UIUC)