Gang He, Toon Vandyck, Mengqi Zhao

Quantifying the cost savings of global solar photovoltaic supply chains

John Paul Helveston, Department of Engineering Management & Systems Engineering, George Washington University
Gang He, Department of Technology and Society, College of Engineering and Applied Sciences, Stony Brook University
Michael R. Davidson, Department of Mechanical and Aerospace Engineering, University of California San Diego

Achieving global carbon neutrality relies on the deployment of renewable energy at unprecedented speed and scale, yet countries sometimes implement policies that increase costs by restricting the free flow of capital, talent, and innovation and localizing benefits in terms of growth, employment, and trade surpluses. This paper contributes to the conversation on this dilemma by quantifying the implications of nationalistic policies for domestically manufacturing solar photovoltaic (PV) modules. Using detailed historical capacity, component, and input material price data of solar photovoltaic (PV) deployment in the U.S., Germany, and China, we develop a two-factor learning model to assess the savings of a globalized solar PV supply chain in terms of the cost of module deployment to achieve ambitious low-carbon goals. We estimate that the globalized PV module market has saved PV installers in the U.S. $24 ($19 – $31) billion, Germany $7 ($5 – $9) billion, and China $36 ($26 – $45) billion from 2008 to 2020 compared to a counterfactual scenario where domestic manufacturers supply an increasing proportion of installed capacities in each country over a 10-year period. In projecting the same scenario forward from 2020, we estimate that 2030 unit solar module prices would be approximately 20-25% higher in each country compared to a future with globalized supply chains. International climate policy benefits from a globalized low-carbon value chain, and these results point to the need for complementary policies to mitigate welfare distribution effects and potential impacts on technological crowding-out.

The global and regional air quality impacts of dietary change

Marco Springmann, Oxford Martin Programme on the Future of Food and Nuffield Department of Population Health, University of Oxford
Rita Van Dingenen, European Commission, Joint Research Centre (JRC)
Toon Vandyck, European Commission, Joint Research Centre (JRC)
Catharina Latka, Institute for Food and Resource Economics, University of Bonn
Peter Witzke, Institute for Food and Resource Economics, University of Bonn
Adrian Leip, European Commission, DG Research & Innovation

Shifting to healthy and sustainable diets can bring significant benefits for human health and a range of environmental outcomes, including climate change. Recent evidence points to potential benefits for air quality, but a comprehensive and global assessment is lacking. Here we combine models of the food system, air quality, human health and the economy to show that dietary changes could lead to significant reductions in air pollution. We find that dietary changes to flexitarian, vegetarian, and vegan dietary patterns would be associated with 134,000-237,000 (3-6%) less premature deaths from air pollution globally, with enhanced productivity increasing economic output by 0.8-1.2%.

Representing Reservoir Storage in an Integrated Model of Global Energy-Water-Land Dynamics

Mengqi Zhao, Pacific Northwest National Laboratory
Thomas Wild, Joint Global Change Research Institute at Pacific Northwest National Laboratory
Son Kim, Joint Global Change Research Institute at Pacific Northwest National Laboratory
Neal Graham, Joint Global Change Research Institute at Pacific Northwest National Laboratory
AFM Kamal Chowdhury, University of Maryland

Reservoirs represent a small component of the global water balance but play a significant role in modifying the natural water cycle to meet human demands. The increasing connections of Energy-Water-Land (EWL) systems and climate change at the global scale pose challenges for reservoirs to reliably meet water demands and attenuate droughts. Appropriate representation of reservoir water storage in global models of EWL dynamics is the key to understanding the future dynamics of water demand and supply driven by multisectoral interactions. In this study, we implement a representation of global water storage in the Global Change Analysis Model (GCAM) to explore the future role (e.g., expansion) of reservoir water storage globally in meeting demands and evolving in response to interactions with the energy and land systems. GCAM represents 235 global water basins, operates at 5-year time steps, and uses supply curves to capture economic competition of supplying water through reservoirs, groundwater, and desalination. Our approach consists of developing a generic Linear Programming (LP) model that is dynamically linked with GCAM. The LP model uses the concept of virtual reservoirs to lump distributed reservoir storage in each basin into a single storage unit. It then dynamically updates each basin’s supply curve to reflect evolving monthly patterns of hydrologic inflows to reservoirs and water demand patterns, and provides this information to GCAM in each model period. The updated supply curve enables GCAM to leverage the levelized cost of reservoirs to capture water storage deficits, forecast reservoir storage capacity expansion potential, and evaluate the impact of increased storage capacity on multisectoral feedback through an economic lens. This modeling framework allows us to explore diverse water storage questions previously unexplored by GCAM (and similar tools), such as the implications of climate impacts on reservoir water supply, and what this will mean for groundwater and associated electricity usage and emissions. Overall, this work investigates what effects future expansion of reservoir storage capacity could have on the evolution of global EWL systems through the development of increasingly robust projection tools.