Sai Liang was a postdoctoral research fellow at SNRE of the University of Michigan. He was selected as a Dow Sustainability Postdoctoral Fellow during September, 2013 – August, 2015. He is interested in understanding the complex interdependence of economic and environmental systems and the implications on policymaking. His research focuses on how the economies of the global trade network are likely to be impacted by future environmental challenges, specifically focusing on a country’s availability of freshwater. An interdisciplinary approach is required for the research by integrating methods and tools in environmental systems analysis, risk analysis, statistical physics, and macroeconomics. He investigated ther impacts of water scarcity risks on the global trade network.
- Developing a Spatially-Explicit Agent-Based Life Cycle Analysis Framework for Improving the Environmental Sustainability of Bioenergy Systems
- Integrated Energy-Economy-Environment (3E) Modeling for Clean Vehicle Development in China
- M-CUBED 2.0: Uncovering the Food-Energy-Water Nexus for Urban Sustainability
- M-CUBED: Influence of global trade on the human health impacts of particulate matter
- Water Scarcity Risk for the Global Trade Network
- A Dual Strategy for Controlling Energy Consumption and Air Pollution in China’s Metropolis of Beijing
- Betweenness-Based Method to Identify Critical Transmission Sectors for Supply Chain Environmental Pressure Mitigation
- Big Data and Industrial Ecology
- CO2 emissions embodied in interprovincial electricity transmissions in China
- Consumption-based human health impacts of primary PM2.5: The hidden burden of international trade
- Decoupling Analysis and Socioeconomic Drivers of Environmental Pressure in China
- Developing the Chinese Environmentally Extended Input-Output (CEEIO) Database
- Emerging challenges and opportunities for the food-energy-water nexus in urban systems
- Final production-based emissions of regions in China
- Forecast Modelling via Variations in Binary Image-Encoded Information Exploited by Deep Learning Neural Networks
- Global Drivers of Russian Timber Harvest
- Greenhouse gas emission factors of purchased electricity from interconnected grids
- Life cycle assessment of biodiesel production in China
- Life Cycle Assessment of High Speed Rail in China
- Reference and Functional Unit Can Change Bioenergy Pathway Choices
- Revisiting Drivers of Energy Intensity in China During 1997-2007: A Structural Decomposition Analysis
- Scaling of Global Input-Output Networks
- Socioeconomic Drivers of Greenhouse Gas Emissions in the United States
- Socioeconomic Drivers of Mercury Emissions in China from 1992 to 2007
- Structure of the Global Virtual Carbon Network: Revealing Important Sectors and Communities for Emission Reduction
- Temporal and Spatial Variations in Consumption-Based Carbon Dioxide Emissions in China
- The Disposal and Willingness to Pay for Residents' Scrap Fluorescent Lamps in China: A Case Study of Beijing
- Unintended consequences of bioethanol feedstock choice in China
- Unintended Environmental Consequences and Co-Benefits of Economic Restructuring
- Virtual Atmospheric Mercury Emission Network in China
- Virtual Scarce Water Embodied in Inter-Provincial Electricity Transmission in China
- Waste oil derived biofuels in China bring brightness for global GHG mitigation