Decarbonizing hard-to-abate sectors is critical to achieve climate change goals given the unique and often fossil fuel-based manufacturing processes. For developed and emerging economies, evaluating power and heavy industry sectors are pertinent given the immense growth expected in the upcoming decades. This presentation will focus on cost and emission models that have been developed and evaluated using the Sesame platform. Specifically, case studies for Hydrogen, Iron and Steel, and Power will be presented demonstrating the impact of technology options, supply chain choices and regional differences. In addition to the plant-level analysis, a system view will be taken to estimate emissions and energy consumption for the entire fleet. By comparing the various technology routes on a cost and emission basis, potential decarbonization strategies, marginal abatement cost, and sensitivities to fuel and other operational costs will be analyzed. The sectoral analysis indicates the immense increase in energy consumption and corresponding infrastructure support for industrial decarbonization. A combination of resource efficiency and technology improvements will be important for reducing emissions from a business-as-usual operation. Overall, the analysis indicates the role of system analysis in evaluating plant-level and system level changes in legacy sectors that are expanding and will be transitioning from traditional production methods. This study is timely as the global community sets climate goals and must consider hard-to-abate sectors, during the energy transition. Using system analysis provides insight to future plant-level and sectoral-level emission and cost challenges.
Ronald Spangler Program Director, MIT Corporate Relations Emre Gençer Research Scientist, MIT Energy Initiative Jacquelyn Pless Fred Kayne (1960) Career Development Professor of Entrepreneurship Assistant Professor, Technological Innovation, Entrepreneurship, and Strategic Management, MIT Sloan School of Management
There are three major complexities facing those who manage last-mile distribution: increasing density in megacities, increasing fragmentation of urban demand, and ever-increasing customer expectations. How can technology and data improve last-mile logistics? What unique challenges do managers face? How can you understand shifting consumer expectations and the evolution of omni-channel retail and delivery in city environments? Join Matthias Winkenbach to explore how companies can reach customers on their own terms, where they live, work, shop, or play, anywhere on the globe.
Rapid urbanization and increasing population density in megacities poses unique challenges for last-mile distribution in many of the world’s largest emerging markets. Meeting these challenges requires understanding shifting consumer expectations and the evolution of omni-channel retail and delivery in city environments. These insights can help companies leverage logistics big data analytics for last-mile network design and planning to reach customers on their own terms, where they live, work, shop, or play, anywhere on the globe.
AI and Society: Computational, Economic, and Legal Perspectives
Manish Raghavan Drew Houston (2005) Career Development Professor and Assistant Professor of Information Technology, MIT Sloan School of Management
MIT Data Center Day will be a high-energy, insight-rich forum focused on the real-world challenges of building next-generation compute infrastructure. MIT faculty and researchers will share practical strategies on topics ranging from AI workloads and energy integration to modular design and sustainability.
Contact