The Cost of CO2 Transport and Storage in Global Integrated Assessment Modeling by Erin E. Environmental Science University of California, Berkeley, 2015 SUBMITTED TO THE INSTITUTE FOR DATA, SYSTEMS, AND SOCIETY IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF SCIENCE IN TECHNOLOGY AND POLICY AT THE MASSACHUSETTS INSTITUTE OF TECHNOLOGY JUNE 2021 © 2021 Massachusetts Institute of Technology. All rights reserved. Signature of Author: ____________________________________________________________ Technology and Policy Program May 14, 2021 Certified by: ___________________________________________________________________ Howard Herzog Senior Research Engineer, MIT Energy Initiative Certified by: ___________________________________________________________________ Sergey Paltsev Deputy Director, MIT Joint Program on the Science and Policy of Global Change Senior Research Scientist, MIT Energy Initiative Accepted by: __________________________________________________________________ Dr.
Noelle Selin Director, Technology and Policy Program Associate Professor, Institute for Data, Systems, and Society and Department of Earth, Atmospheric, and Planetary Science 1 The Cost of CO2 Transport and Storage in Global Integrated Assessment Modeling by Erin E. Smith Submitted to the Institute for Data, Systems, and Society on May 14, 2021, in partial fulfilment of the requirements for the degree of Master of Science in Technology and Policy Abstract Carbon capture and storage (CCS) is one of many critical tools to mitigate global climate change. Much analytic work has been dedicated to evaluating the cost and performance of various CO2 capture technologies, but less attention has been paid to evaluating the cost of CO2 transport and storage. This paper assesses the range of CO2 transport and storage costs and evaluates their impact on economy- wide modelling results of decarbonization pathways.
Many integrated assessment modeling studies assume a combined cost for CO2 transport and storage that is uniform in all regions of the world, commonly estimated at $10/tCO2. Realistically, the cost of CO2 transport and storage is not fixed at $10/tCO2 and varies across geographic, geologic, and institutional settings. I surveyed the literature to identify key sources of variability in transport and storage costs and developed a method to quantify and incorporate these elements into a cost range. I find that onshore pipeline transport and storage costs vary from $4 to 45/tCO2 depending on key sources of variability including transport distance, scale (i.
quantity of CO2 transported and stored), monitoring assumptions, reservoir geology, and transport cost variability such as pipeline capital costs. Using the MIT Economic Projection and Policy Analysis (EPPA) model, I examined the impact of variability in transport and storage costs by applying a range of uniform costs in all geographic regions in a future where global temperature rise is limited to 2°C. I then developed several modeling cases where transport and storage costs vary regionally. In these latter cases, global cumulative CO2 captured and stored through 2100 ranges from 290 to 377 Gt CO2, compared to 425 Gt CO2 when costs are assumed to be uniformly $10/t CO2 in all regions.
I conclude that the widely used assumption of $10/tCO2 for the transport and storage of CO2 is reasonable in some regions, but not in others. Moreover, CCS deployment is more sensitive to transport and storage costs in some regions than others, particularly China. Several transport and storage options should be taken into account when modeling large-scale deployment of CCS in decarbonization pathways. However, cost data are scarce and there is still a significant amount of uncertainty and variability in available transport and storage costs.
Thesis Supervisor: Howard Herzog Title: Senior Research Engineer, MIT Energy Initiative Thesis Supervisor: Sergey Paltsev Title: Deputy Director, MIT Joint Program on the Science and Policy of Global Change Senior Research Scientist, MIT Energy Initiative 2 Acknowledgments I’m very grateful for the guidance and support of my advisors Sergey Paltsev, Howard Herzog, and Jennifer Morris throughout my time at MIT. The analysis in this thesis would not have been possible without them. I am a better energy economist, public speaker, teammate, and thinker because of their mentorship. I also want to thank Haroon Kheshgi, Gary Teletzke, Bryan Mignone, and Edward Corcoran for their continued support and guidance throughout the completion of this thesis.
My findings are better and more durable thanks to their insight and expertise. Ultimately, I’m here because of the love and support of my spectacular friends and family. I’m lucky enough to be surrounded by people who are awe-inspiring and who make the good days better and the bad days easier. I came to MIT excited but anxious about the challenges I would face, and I leave proud of what I have accomplished because it took not only hard work, but also a village.
And I have a damn good village. To mom, dad, Kindon, and my grandparents – I am who I am because of you. You embody the love, strength, humor, open-mindedness, and kindness that I try to emulate. You love me unconditionally, see my potential when I doubt it, and ceaselessly root for me.
I would be lesser without you and will never be able to sufficiently thank you. To Mom, who encouraged me to ask questions, stay open minded, give others the benefit of the doubt, trust my gut, stand up for myself as a woman in the world, and so much more. To Dad, who taught me to work hard, treat others with grace and mercy, give back to my community, laugh loudly, forgive easily, and to be a team player wherever I go. To Kindon, who even as my little brother showed me a thing or two about how to be thoughtful and generous with those I love, be patient, assert my voice, stand up for what I believe in, and find humor in the randomness of life.
And to my grandparents, whose nurturing hands have held mine throughout my childhood and adulthood. Words can’t capture my love and gratitude for you. To my fellow TPPers, especially Sade Nabahe and Nina Peluso – you are gems who are not only exceptionally bright, but also compassionate, patient, hilarious, and kind. I could not have asked for better people with whom to weather the highs and lows of graduate school.
You have been the calm in the storm and created space for others to feel safe and be vulnerable. You work hard while also embracing joy and laughter, and I’m grateful to not only share a cohort with you but also a friendship that I’m lucky enough to take with me after MIT. You are goddesses through and through. 3 To my close friends Oren, Sumner, Serena, Justin, Jessica, and the Bearcoons – I am a better person for knowing you, and my life is exponentially better with you in it.
While we no longer live in the same city, our ability to stay connected across a distance means the world to me. You each exude a rare and perfect combination of strength, empathy, and playfulness. These are just a few things I love and admire about you in addition to the ways you are each uniquely beautiful, but they are traits you share and deserve to be celebrated. You constantly inspire me to be better and are simply the best.
To my mentors Addison Stark, Brad Townsend, and Blair Beasley - good mentors can be hard to find, yet each of you has taken the time to guide me with compassion, patience, and honesty over the years. You have paved the way for me to grow and seize new opportunities and have shaped my journey in countless ways. I admire and deeply respect each of you and cannot wait for the next time our paths cross. 4 Table of Contents ABSTRACT.
7 LIST OF FIGURES. 8 LIST OF TABLES. 12 PART I: QUANTIFYING CO2 TRANSPORT AND STORAGE COST RANGE. BACKGROUND ON CO2 TRANSPORT AND STORAGE COST ESTIMATES .Background on CO2 Transport and Storage in CCS Cost Analyses.
UNCERTAINTY AND VARIABILITY IN KEY COST COMPONENTS AND PARAMETERS. CO2 TRANSPORT COSTS. CO2 TRANSPORT OPTIONS. Rail and Truck.
CURRENT STATUS OF CO2 TRANSPORT COSTS. CO2 TRANSPORT COST RANGE. CO2 STORAGE COSTS. CO2 STORAGE OPTIONS.
Saline Aquifers and Depleted Oil and Gas Fields. Other Storage Reservoirs. CURRENT STATUS OF CO2 STORAGE COSTS. CO2 STORAGE COST RANGE.
COMBINED CO2 TRANSPORT AND STORAGE COST RANGE. COMBINED CO2 TRANSPORT AND STORAGE COST RANGE. KEY SOURCES OF VARIABILITY. 38 PART II: MODELING GLOBAL CLIMATE PATHWAYS WITH VARIABLE CO 2 TRANSPORT AND STORAGE COSTS.
BACKGROUND ON MODELING APPROACH. STRENGTHS AND LIMITATIONS OF INTEGRATED ASSESSMENT MODELS. ECONOMIC PROJECTION AND POLICY ANALYSIS (EPPA) MODEL. UNIFORM CO2 TRANSPORT AND STORAGE COSTS IN ALL REGIONS.
VARYING CO2 TRANSPORT AND STORAGE COSTS. RESULTS AND DISCUSSION. INSIGHT FOR POLICYMAKERS. 71 6 Acronyms CCS Carbon capture and storage CO2 Carbon dioxide EPPA MIT’s Economic Projection and Policy Analysis model IAM Integrated assessment model IPCC United Nations Intergovernmental Panel on Climate Change Mtpa Megatons per annum NETL National Energy Technology Lab operated by the U.
Department of Energy 7 List of Figures Figure 1. Summary of CO2 Transport and Storage Cost Components and Parameters. Pipeline Diameter as a function of CO 2 Flow Rate. Average pipeline construction costs in 2019$/mile as a function of CO 2 Flow Rate.
Comparison of Cost Indices for Price Escalation. Total CO2 transport costs for a 100-mile onshore pipeline in the United States in 2019 current dollars. CO2 storage cost range in current 2019$/tCO 2. Breakdown of CO2 transport and storage costs in current 2019$/tCO2 for various combinations of scale, transport distance, and monitoring assumptions in the United States.
Sensitivity of CO2 transport, storage and monitoring costs around the base case of 3.2 Mtpa CO2 being transported 100 miles. Description of 18 regions represented in MIT’s Economic Projection and Policy Analysis (EPPA). Cumulative Global CO2 captured and stored (2020-2100) under a scenario that limits global warming to 2°C and with uniform transport and storage costs in all regions. Reference Case is reflected by the square; endpoints of my cost range of $4 to $45/tCO2 is reflected by x’s.
Cumulative Regional CO2 captured and stored (2020-2100) under a scenario that limits global warming to 2°C and with uniform transport and storage costs in all regions. Cumulative global CO2 captured and stored (2020-2100) under a scenario that limits warming to 2°C. Annual CO2 captured and stored in the Reference Case (dashed lines) and Base Case (solid lines) under a scenario that limits warming to 2°C, by EPPA region. Annual electricity generation in Europe in the Base Case under a scenario that limits warming to 2°C.
Annual electricity generation in India in the Base Case under a scenario that limits warming to 2°C. Annual electricity generation in China in the Base Case under a scenario that limits warming to 2°C. Annual electricity generation in the United States in the Base Case under a scenario that limits warming to 2°C. Annual CO2 captured and stored in the CCS Networks and Clusters Case (dotted lines) and Base Case (solid lines) under a scenario that limits warming to 2°C, by EPPA region.
Annual CO2 captured and stored in Europe under a scenario that limits warming to 2°C, by modeling case. Annual Mt CO2 captured and stored in the United States for key sensitivities under a scenario that limits warming to 2°C. Annual Mt CO2 captured and stored in China for key sensitivities under a scenario that limits warming to 2°C. 65 9 List of Tables Table 1.
Capital cost factor range for onshore CO 2 pipelines in current 2019$/in-mi. Reservoir Properties from Szulczewski et al. (2013) and Grant et al. storage cost range (2008$/tCO2) under base monitoring assumptions (Low, Mean, and High columns) and extra monitoring assumptions (Mean with Extra Monitoring column.
USDOE (2017) model output reported here. storage cost range (2019$/tCO2) under base monitoring assumptions (Low, Mean, and High columns) and extra monitoring assumptions (Mean with Extra Monitoring column). USDOE (2017) model output escalated to 2019 dollars reported here.