Integrated Climate Action Planning (ICLAP) in Asia-Pacific Cities: Analytical Modelling for Collaborative Decision Making

Mahendra Sethi*, Li Jing Liu, Eva Ayaragarnchanakul, Aki Suwa, Ram Avtar, Akhilesh Surjan, Shilpi Mittal

*Corresponding author for this work

    Research output: Contribution to journalArticlepeer-review

    2 Citations (Scopus)

    Abstract

    While climate change has global causations and impacts, there is growing consensus on addressing the 2 °C challenge through local actions. However, at the local level, there is disintegrated knowledge on the following: (a) short-, mid-and long-term climate vulnerability, (b) economy and GHG structures and their future pathways, and (c) useful mitigation and adaptation undertaken elsewhere. We evaluate these gaps through a comprehensive review of scientific literature and policy approaches of urban-climate studies in the Asia-Pacific Region. Based on the research findings, we develop a collaborative research framework of an integrated climate action planning (ICLAP) model for evidence-based decision-making tool. It adopts an innovative methodology integrating knowledge and data from diverse analytics, as follows: (a) spatial: downscaling global/regional climate scenarios to forecast local climate variability (50 km × 50 km) for 2030 (SDG target) and 2050; (b) statistical: a meta-analysis of 49 five-million-plus cities to forecast economic, energy and GHG scenarios; (c) bibliometric: a systematic review of global urban climate interventions from Google Scholar that collectively aid cities on policy inputs for mid-term climate variability, GHG profiles and available solutions at their disposal. We conclude with a discussion on scientific and policy relevance of such a tool in fostering overall urban, regional and global sustainability.

    Original languageEnglish
    Article number247
    JournalAtmosphere
    Volume13
    Issue number2
    DOIs
    Publication statusPublished - Feb 2022

    Keywords

    • Asia-Pacific
    • Climate action planning
    • Decision making
    • Integrated model
    • Urban climate

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