Fuzzy multi-objective optimization model for carbon emissions during water supply based on life cycle assessment

The rising global carbon emissions from energy use in the water sectors highlight the need to research water supply allocation focusing on carbon footprint. This study introduced a non-exact optimization method for water resource allocation, focusing on the relationship between water supply and carbon emissions of energy consumption. It aimed to balance carbon emission reduction and minimize water supply costs, particularly emphasizing the mitigation of carbon emissions from unconventional water sources. This method can handle uncertainties in the objective function and constraint conditions, and provide decision-makers with optimal water resource allocation strategies under different confidence levels (λ) and optimistic-pessimistic parameters (γ). The results showed that: (1) under different γ values, the water shortage of Weihai was [0.99, 1.13] × 10⁸ m³, but the degree of water shortage was greater under different λ values; (2) increasing local water availability can reduce carbon emissions in the water supply process more effectively than increasing the proportion of clean energy generation; (3) in an ideal situation, the carbon emissions per unit of seawater desalination can be reduced to around [0.68, 0.83] kg/m³. The model can provide reasonable management strategies for water supply systems and handle multiple uncertainties in the decision-making process.