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The conference publication “Interactive Optimization for Urban Carbon Neutrality Through Renewable Energy and Nature-Based Solutions,” authored by Júlia Sánchez-Martínez, Nicos Komninos, Elisavet Gkitsa, and Anastasia Panori, received the Best Paper Award at the 14th International Conference on Distributed, Ambient and Pervasive Interactions. The conference was part of the Human–Computer Interaction International 2026, held in Montreal, Canada, from 26 to 31 July 2026.
The paper presents a replicable, data-driven model for optimising combinations of renewable energy systems (RES) and nature-based solutions (NBS) for urban decarbonisation. In the context of accelerating climate change, reducing urban CO₂ emissions has become a major strategic priority for cities worldwide. The proposed model was tested within the ReGenWest project in Thessaloniki, Greece, a pilot initiative supporting the objectives of the EU Mission for Climate-Neutral and Smart Cities.
Developed on the NetLogo platform, the model enables users to define a specific intervention area according to stakeholder boundaries, ownership structures, and local priorities. Each area is treated as a single optimisation block, reflecting the distinct decision-making context of the site. The methodology combines NetLogo-based simulations with Python optimisation tools to assess feasible RES–NBS configurations at the level of fundamental spatial decision units. It includes an exhaustive-search option for evaluating alternative configurations. The optimisation problem was also formulated and solved as a Multiple-Choice Knapsack Problem using Google OR-Tools.
The results reveal significant trade-offs between intervention costs and CO₂ reduction. These trade-offs are shaped by non-linear dynamics arising from real-world constraints, including economies of scale. Their incorporation produces non-linear Pareto frontier curves that more accurately represent the complexity of urban decarbonisation interventions.
The model provides a transparent and interactive decision-support tool for identifying cost-efficient and spatially feasible combinations of renewable energy and nature-based solutions. Its structure and methodology are also replicable and adaptable to other urban contexts.
The full paper is available through SpringerLink,