Topic: AI-Driven Carbon Footprint and Decarbonization of Water Systems under Climate Change

Climate change is intensifying pressure on water systems while simultaneously increasing their energy demand and associated greenhouse gas emissions. Processes across water supply, treatment, distribution, and wastewater management are increasingly recognized as significant contributors to carbon footprints in urban and regional systems.

Concurrently, advances in artificial intelligence (AI) and data-driven approaches provide new opportunities to quantify, monitor, and reduce emissions in water systems.

This Special Issue focuses on carbon footprints, greenhouse gas emissions, and the decarbonization of water systems in the context of climate change, with particular emphasis on AI-enabled modeling, optimization, and decision-support tools. We welcome studies that integrate life cycle assessment (LCA), carbon accounting, and digital technologies to improve the sustainability, efficiency, and resilience of water systems.

This issue aims to bridge the gap between water system management and carbon mitigation by providing insights for policymakers, water utilities, engineers, and researchers. Ultimately, it seeks to support the development of low-carbon and climate-resilient water infrastructure and management strategies.

Proposed topics include, but are not limited to:

● Carbon footprint assessment of water supply and wastewater systems;

● Greenhouse gas emissions from water infrastructure and treatment processes;

● AI-driven carbon accounting and monitoring in water systems;

● Energy-water-carbon nexus analysis;

● Decarbonization strategies for urban and agricultural water systems;

● LCAof water technologies and infrastructure;

● Low-carbon optimization of water allocation and distributionsystems;

● Digital twins for carbon-aware water system management;

● Climate change impacts on water-related emissions;

● Integration of renewable energy intowater systems;

● Policy and governance for low-carbon water management;

● Uncertainty quantification and explainable AI in carbon modeling of water systems.

Carbon footprint, water systems, greenhouse gas emissions, decarbonization, artificial intelligence (AI), Life cycle assessment (LCA), energy-water nexus, climate change, smart water management