(181c) Optimization Framework for Sustainable Land Management

As a part of its “Valuing Nature” goal [1] for 2025, Dow is committed to deliver $1 billion NPV through business-driven projects that enhance nature. In addition to this, Dow’s “Carbon Neutrality” [2] goal for 2050 requires swift action to attain these ambitious targets. Land-use transformations have the potential to supplement the technological systems like CO₂ capture to help meeting these goals. These land-use transformations include reforestation, restoration, remediation, wetland, pond construction, etc., each capable of providing natural-capital and environmental benefits. Since Dow owns numerous land properties and there are several possible land-use transformations, it is impossible to manually analyze each solution. Systems engineering and mathematical optimization approaches can effectively explore all the feasible solutions and recommend the best land management strategy.

In this talk, we will present an optimization framework for sustainable land management that can help in making informed decisions. We have developed a unique methodology to leverage geographic information system (GIS) capabilities in a mathematical optimization setting. Using this framework, we have developed a tool that has the capabilities to: i) analyze environmental risk of global Dow locations and identify priority sites for implementing nature-based solutions ii) optimize land-use transformation strategies at a selected site for maximizing value from ecosystem services. Examples of environmental metrics considered include water stress indicators [3], biodiversity hotspots [4], air quality measurements [5], and 2040 temperature projections [6]. On a site level we leverage county level land parcel data and national land cover database (NLCD) [7] to characterize the land types and identify the best land transformation strategies using mathematical optimization. We will conclude the talk with a case study showcasing how these capabilities are integrated and developed into a decision-making platform that leverages advanced mathematical optimization techniques.

References:

[1] Dow Corporate. Valuing nature; accessed 2022/01/31. Link: https://corporate.dow.com/en-us/science-and-sustainability/2025-goals/nature.html

[2] Dow Corporate. Accelerating our sustainability commitments; accessed 2022/01/03. Link: https://corporate.dow.com/en-us/science-and-sustainability/commits-to-reduce-emissions-and-waste.html

[3] Hofste, RUTGER W., Samantha Kuzma, Sara Walker, Edwin H. Sutanudjaja, Marc FP Bierkens, Marijn JM Kuijper, Marta Faneca Sanchez et al. "Aqueduct 3.0: Updated decision-relevant global water risk indicators." World Resources Institute: Washington, DC, USA (2019).

[4] Hrdina, Ales, and Romportl, Dusan. "Evaluating global biodiversity hotspots–Very rich and even more endangered." Journal of Landscape Ecology 10, no. 1 (2017): 108-115.

[5] OpenAQ: A Platform to Aggregate and Freely Share Global Air Quality Data, volume 2015, 2015.

[6] Hack, J. J., B. A. Boville, J. T. Kiehl, P. J. Rasch, and D. L. Williamson. "Climate statistics from the National Center for Atmospheric Research community climate model CCM2." Journal of Geophysical Research: Atmospheres 99, no. D10 (1994): 20785-20813.

[7] Collin Homer, Jon Dewitz, Limin Yang, Suming Jin, Patrick Danielson, George Xian, John Coulston, Nathaniel Herold, James Wickham, and Kevin Megown. Completion of the 2011 national land cover database for the conterminous United States representing a decade of land cover change information. Photogrammetric Engineering & Remote Sensing, 81(5):345{354, 2015.