No City Left Behind: Building Climate Policy Bridges between the North and South

Mohamed Hachaichi
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Abstract

Cities are progressively heightening their climate aspirations to curtail urban carbon emissions and establish a future where economies and communities can flourish within the Earth’s ecological limits. Consequently, numerous climate initiatives are being launched to control urban carbon emissions, targeting various sectors, including transport, residential, agricultural, and energy. However, recent scientific literature underscores the disproportionate distribution of climate policies. While cities in the Global North have witnessed several initiatives to combat climate change, cities in the Global South remain uncovered and highly vulnerable to climate hazards. To address this disparity, we employed the Balanced Iterative Reducing and Clustering using the Hierarchies (BRICH) algorithm to cluster cities from diverse geographical areas that exhibit comparable socioeconomic profiles. This clustering strives to foster enhanced cooperation and collaboration among cities globally, with the goal of addressing climate change in a comprehensive manner. In summary, we identified similarities, patterns, and clusters among peer cities, enabling mutual and generalizable learning among worldwide peer-cities regarding urban climate policy exchange. This exchange occurs through three approaches: (i) inner-mutual learning, (ii) cross-mutual learning, and (iii) outer-mutual learning. Our findings mark a pivotal stride towards attaining worldwide climate objectives through a shared responsibility approach. Furthermore, they provide preliminary insights into the implementation of “urban climate policy exchange” among peer cities on a global scale.
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不让任何城市掉队:在南北之间建立气候政策桥梁
城市正在逐步提高他们的气候抱负,以减少城市碳排放,并建立一个经济和社区可以在地球生态极限内蓬勃发展的未来。因此,许多旨在控制城市碳排放的气候倡议正在启动,目标涉及交通、住宅、农业和能源等各个领域。然而,最近的科学文献强调了气候政策的不成比例分布。虽然全球北方的城市已经见证了一些应对气候变化的举措,但全球南方的城市仍然处于开放状态,极易受到气候灾害的影响。为了解决这一差异,我们采用平衡迭代减少和聚类使用层次(BRICH)算法对来自不同地理区域的城市进行聚类,这些城市表现出可比的社会经济概况。这一集群旨在促进全球城市之间加强合作与协作,目标是全面应对气候变化。总之,我们发现了同行城市之间的相似性、模式和集群,使全球同行城市之间能够在城市气候政策交流方面相互学习。这种交流通过三种方式发生:(i)内部相互学习,(ii)交叉相互学习,(iii)外部相互学习。我们的研究结果标志着通过共同承担责任的方式实现全球气候目标的关键一步。此外,它们还为在全球范围内同类城市之间实施“城市气候政策交流”提供了初步见解。
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