Industrial Ecology is a broad area that analyzes the interactions among industrial, human, and natural systems. We use life cycle assessment, input-output analysis, and material flow analysis to understand how industrial activities influence the environment and what are alternative actions for reducing adverse environmental impacts.
Sustainable Engineering integrates sustainability into engineering system design, operation, and improvement. We use engineering process-based simulation, techno-economic analysis, and engineering design to help engineers, designers, and manufacturing companies develop products and processes that can meet the needs of human beings without compromising the natural environment.
Data analysis enables our ability to generate, mine, analyze, and visualize comprehensive datasets to contribute to solving sustainability issues. It covers a large variety of powerful tools that we can utilize. We use machine learning, deep learning, agent-based modeling, and geographic information system to build a more digital, intelligent, and sustainable decision-making process.
Ecological modeling can translate the nature system into modeling language to test ecological hypotheses and predict future prospects upon changes. Ecological models can present quantitative data that can be utilized by other tools to generate insights of the coupled human-nature system. We use forest growth models, soil organic carbon models, and crop growth models to generate the insights of how our nature system behaves and reacts under various scenarios.