This study analyzes decarbonization efforts of 1,095 European firms, identifying six key strategic pathways—ranging from risk diagnosis to supply chain redesign—and uses a systems dynamics approach to reveal how these interconnected strategies influence climate risk performance. The findings offer valuable tools for managers and policymakers to coordinate supply chain actions more effectively, fostering continuous innovation and improved sustainability outcomes.

Metalloproteins have evolved through the selective, strong, and precise interactions between metal ions and polypeptides.

As the latest annual flagship report in the series, it details synergistic pathways for simultaneous pollution control and carbon reduction to drive green economic growth in China, offering highly actionable policy insights and real-world experience for advancing national climate goals.

Denitrification using Pd-based catalysts converts N-oxyanions into harmless products. However, the metal cost and scarcity are barriers to application.

The global challenge of water security is intensifying, driven by rapid population growth, industrialisation and climate change, making sustainable water reclamation and reuse an essential strategy

With an estimated 2 billion people worldwide suffering from iron deficiency — a condition linked to anemia, impaired childhood brain development, and higher infant mortality — researchers are racing to find more effective nutritional interventions. MIT scientists have developed a promising solution: tiny crystalline particles known as metal-organic frameworks (MOFs) that can be used to fortify everyday foods and beverages, mixed into foods such as bread or sprinkled directly into drinks like coffee or tea.

The study finds that Chinese listed companies' increasing carbon footprints, primarily from value chain emissions, are associated with higher expected returns, indicating a carbon damage risk premium recognized by investors.

The lifestyles and worldviews of indigenous communities have long been deeply intertwined with natural resources, particularly water.

This study explores the integration of Generative Artificial Intelligence (GenAI) in water distribution networks, identifying opportunities for enhancing information retrieval, improving water quality management, implementing predictive maintenance, and optimizing operations, while also addressing challenges related to data quality, scalability, and the need for expertise in both engineering and AI, ultimately providing insights for water utilities and policymakers on leveraging GenAI responsibly.