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.
Highlights
The year 2020 was one of the three warmest years on record, despite a cooling La Niña event
The integrated climate action planning (ICLAP) tool adopts advanced modelling of synthesizing three different knowledge domains/analytics, building on specific and accepted research methods in the respective domains of climate adaptation, mitigation and data science, as elaborated below: 1. Spatial—downscaling climate scenarios and GIS mapping of variability: in order to ensure that the research can be used for multi-disciplinary applications, our study focuses on demonstrating fundamental climate variability scenarios over the space than defines vulnerability class, weight assignment and/or mapping vulnerability
The literature review and evidence collected from five Asia-Pacific countries in this research demonstrates that an ICLAP framework makes the process of data integrationbased decision making even more scientific, realistic and verifiable
Summary
The year 2020 was one of the three warmest years on record, despite a cooling La Niña event. 2011–2020 was the warmest decade on record, in which the six years since. The climate change phenomenon has global greenhouse gas (GHG) contributions and implications; yet there is a growing and unequivocal consensus that the 2 ◦ C global warming challenge can be dealt with concerted local actions [2,3,4]. Climate Week 2021 sends a strong signal to how the Asia-Pacific region presents some unique challenges in achieving global climate mitigation and adaptation goals. In terms of climate vulnerability, of 100 cities facing the greatest environmental risks, 99 are in Asia, including 37 in China and 43 in India [7]. The risks are from a combination of pollution, extreme heat stress, natural hazards and vulnerability to climate change, and are concomitant with growing GHGs
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