Thesis Title: Including biodiversity conservation into climate change decision making
Thesis Committee:
Dr. Valerie Thomas (Advisor), School of Industrial and Systems Engineering, Georgia Institute of Technology
Dr. Arthur Delarue, School of Industrial and Systems Engineering, Georgia Institute of Technology
Dr. Santanu Dey, School of Industrial and Systems Engineering, Georgia Institute of Technology
Dr. Dima Nazzal, School of Industrial and Systems Engineering, Georgia Institute of Technology
Dr. Matthew Oliver, School of Economics, Georgia Institute of Technology
Date and Time:
Thursday, June 22nd, 2023 at 11:00 am- 1:00 pm ET
In-person location:
Groseclose 404
Online meeting link:
https://gatech.zoom.us/j/98803085011?pwd=U2RuMjBCTjhXT3d6S2V4S0YvR0o0dz09
Meeting ID: 988 0308 5011
Passcode: 381589
Abstract:
Climate change and biodiversity loss are two of the major environmental problems that humans are facing today. Bioenergy with and without carbon capture and storage remains as one of the most important technologies to be used for climate change mitigation. Because of the large scale requirements for land in future bioenergy deployment scenarios, there is concern about the potential biodiversity impacts, suggesting a potential trade-off between climate change mitigation and biodiversity conservation. Decision making optimization models used to support climate change mitigation policy do not include the associated biodiversity impacts. In this thesis I focus on incorporating biodiversity impacts into optimization models for land use change and forest management. The objective is to improve decision making models to estimate the magnitude of the trade-off and identify mechanisms that could alleviate it.
In Chapter 1, I focus on the concept of biodiversity, what it is, how we can measure it, and I propose a methodology to incorporate biodiversity impacts into optimization models. For this, I chose the Countryside Species-Area Relationship (cSAR) ecologic model and because of its non-linearity, I propose three methods that can be used to integrate the chosen ecologic model into an optimization model. I also discuss the ethical assumptions behind the way biodiversity is incorporated via a constraint or via an objective function. Because of the computational advantages and representation of the nonlinear relation between habitat loss and biodiversity loss, the piecewise linear approximation (LaP) method is chosen.
In Chapter 2, I start with a land use change model and I focus on the trade-offs between transformation costs and biodiversity impacts. This is explored for a scenario that guarantees an exogenous amount of woody biomass supply, consistent with the target of keeping warming under 2ºC, compared to pre-industrial levels. I analyze the outcomes when we prioritize biodiversity versus when we prioritize costs, and assess the feasibility of the best case for biodiversity under this large-scale deployment of bioenergy.
One of the limitations of Chapter 2 is that it does not consider market dynamics, assuming that future demands for agricultural land, pastures and wood products are fixed. To address this and to explore how forest management decisions can be improved by accounting for its biodiversity impacts, in Chapter 3 I integrate a partial equilibrium economic model (GLOBIOM forest) for the forest industry with the cSAR ecologic model. I find that forest management decisions can be used to alleviate the potential trade-offs between biodiversity conservation and climate change mitigation using bioenergy.
With these studies, I exemplify how the integration of environmental models, economic models, and operations research can be used to improve solutions and support policymaking in complex problems such as climate change and biodiversity loss. Also, in this way, I am demonstrating how industrial engineering tools can be used for decisions beyond the private sector and even become an essential contribution to addressing global sustainability problems.