The proposed research, aligned with the United Nations Sustainable Development Goals (SDGs), addresses the urgent challenge of climate change and develops TÀLIA, an advanced digital decision-support tool for the identification, classification, and prioritization of mitigation and adaptation solutions in urban contexts. The platform guides planners in selecting the most appropriate strategies based on specific climatic impacts and associated risks, enhancing urban resilience against extreme weather events, floods, heatwaves, and other climate-related hazards. TÀLIA employs a structured classification system that considers intervention category, scope, type, and technical implementation, encompassing both new constructions and the retrofitting of existing buildings at building and urban scales. The taxonomy differentiates interventions by nature — superficial or localized — and operational modalities. A key feature lies in the distinction between adaptation and mitigation strategies, allowing solutions to be classified as Nature-Based Solutions (NBS) or Artificial Solutions (AS). Integrated with a parametric evaluation system based on “if–else” logic, TÀLIA automatically assigns each solution a priority score from 0 to 5, derived from a multi-criteria decision analysis (MCDA), ensuring systematic, objective, and quantitative assessment. The Plant Advisor module additionally facilitates the selection of plant species according to the Minimum Environmental Criteria (CAM) — including native species, low water requirements, and biodiversity promotion — and local climatic data, such as tolerance to heat, drought, and pollution. Designed for national-scale application, the methodology is also adaptable to international contexts, providing planners with a robust, evidence-based tool to strengthen urban resilience, reduce vulnerability, and promote adaptive transformation in cities facing climate change.
a ricerca proposta, in linea con gli Obiettivi di Sviluppo Sostenibile (SDGs) delle Nazioni Unite, affronta l’urgente sfida del cambiamento climatico e sviluppa TÀLIA, uno strumento digitale avanzato di supporto alle decisioni per l’individuazione, classificazione e prioritizzazione di soluzioni di mitigazione e adattamento in contesti urbani. Il tool orienta i pianificatori nella selezione delle strategie più adeguate in base agli impatti climatici e ai rischi correlati, potenziando la resilienza urbana di fronte a eventi meteorologici estremi, inondazioni, ondate di calore e altri rischi climatici. TÀLIA adotta un sistema di classificazione strutturato che considera categoria, ambito, tipologia e modalità tecnica degli interventi includendo sia nuove costruzioni sia la riqualificazione del patrimonio edilizio esistente, su scala edilizia e urbana. La tassonomia distingue gli interventi per natura — superficiale o puntuale — e modalità operative. Una caratteristica chiave consiste nella distinzione tra strategie di adattamento e di mitigazione, consentendo la classificazione delle soluzioni come Nature-Based Solutions (NBS) o Artificial Solutions (AS). Integrato con un sistema parametrico di valutazione basato sulle logiche “if–else”, TÀLIA attribuisce automaticamente a ciascuna soluzione un punteggio di priorità da 0 a 5 derivato da un’analisi multi-criterio (MCDA), garantendo una valutazione sistematica, oggettiva e quantitativa. Il modulo Plant Advisor consente inoltre la selezione di specie vegetali secondo i criteri CAM – Criteri Ambientali Minimi (specie autoctone, basso fabbisogno idrico, promozione della biodiversità) – e dati climatici locali (resistenza al calore, alla siccità e all’inquinamento). Progettata per applicazione su scala nazionale, la metodologia è adattabile anche a contesti internazionali, fornendo ai pianificatori uno strumento solido e basato su evidenze per rafforzare la resilienza urbana, ridurre la vulnerabilità e promuovere una trasformazione adattiva delle città di fronte al cambiamento climatico.
Metodologie e strumenti digitali per la definizione di strategie di mitigazione e adattamento ai cambiamenti climatici in contesti urbani
ZYLKA, CLAUDIA
2026
Abstract
The proposed research, aligned with the United Nations Sustainable Development Goals (SDGs), addresses the urgent challenge of climate change and develops TÀLIA, an advanced digital decision-support tool for the identification, classification, and prioritization of mitigation and adaptation solutions in urban contexts. The platform guides planners in selecting the most appropriate strategies based on specific climatic impacts and associated risks, enhancing urban resilience against extreme weather events, floods, heatwaves, and other climate-related hazards. TÀLIA employs a structured classification system that considers intervention category, scope, type, and technical implementation, encompassing both new constructions and the retrofitting of existing buildings at building and urban scales. The taxonomy differentiates interventions by nature — superficial or localized — and operational modalities. A key feature lies in the distinction between adaptation and mitigation strategies, allowing solutions to be classified as Nature-Based Solutions (NBS) or Artificial Solutions (AS). Integrated with a parametric evaluation system based on “if–else” logic, TÀLIA automatically assigns each solution a priority score from 0 to 5, derived from a multi-criteria decision analysis (MCDA), ensuring systematic, objective, and quantitative assessment. The Plant Advisor module additionally facilitates the selection of plant species according to the Minimum Environmental Criteria (CAM) — including native species, low water requirements, and biodiversity promotion — and local climatic data, such as tolerance to heat, drought, and pollution. Designed for national-scale application, the methodology is also adaptable to international contexts, providing planners with a robust, evidence-based tool to strengthen urban resilience, reduce vulnerability, and promote adaptive transformation in cities facing climate change.| File | Dimensione | Formato | |
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https://hdl.handle.net/20.500.14242/356960
URN:NBN:IT:UNIROMA1-356960