Understanding systems.
Discovering possibilities.
Connecting environmental data, life cycle science and artificial intelligence to make sustainable futures possible.

Includes member career and collaborative works; 5 preprints listed separately.
From methods to real-world systems

Life cycle assessment
Using life cycle inventories, impact assessment and industrial ecology to reveal environmental tradeoffs in products and industrial systems.

AI & environment
Combining environmental data science, machine learning and large language models to advance evidence, modeling and decision support.

Energy & climate
Accounting for carbon across energy and consumption systems, and examining low-carbon technologies and transition pathways.

Water & resources
Connecting water quality, resource availability and economic networks to understand environmental risks and sustainable management.

Materials & circularity
Tracing material stocks, supply chains and waste flows to assess resource efficiency and circular economy transitions.
Ideas grounded in evidence
China’s unfinished buildings have created stranded assets with substantial resource and socioeconomic costs
Towards a unified principal indicator system for global water quality assessment
China material stocks and flows account for 1978–2018
A closer look at the research
Open data & life cycle assessmentTrustworthy Life Cycle Assessment Starts with Transparent Data
Behind an environmental footprint, can we trace the sources, boundaries and assumptions?
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AI & environmentFrom Generated Answers to Reliable Environmental Analysis
Bring environmental knowledge into models—and subject their outputs to domain-specific scrutiny.
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Circular economy & systems decisionsAvoiding Burden Shifting in Circular and Low-Carbon Solutions
Compare options across life cycles, connected systems and multiple environmental impacts.
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