Assessing equity in heat mitigation ecosystem services of urban green space in Singapore

IF 6.1 2区 环境科学与生态学 Q1 ECOLOGY
Ronghua Xu , Perrine Hamel , Aikeen Youu Ming Lim , Tingting He
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Abstract

Urban green space provides ecosystem services such as heat mitigation, which are associated with improved resident health and welfare. While estimating the disparity in ecosystem services is essential to improve equity, little guidance is available as to which indices and indicators should be used. Here, we assess the distributional equity in heat mitigation benefits as measured by two indicators – land surface temperature reduction and wet-bulb temperature reduction – in the city-state of Singapore, and compare three inequality indices: Gini coefficient (GC), Atkinson index (AI), and Theil entropy index (TE). We include scenarios with and without migrant construction workers to test the changes in inequality indices when considering marginalized groups, and explore the influence of income subgroups and other socio-demographic factors. Results suggest that heat mitigation ecosystem services are inequitably distributed in Singapore, as shown by all inequality indices, except AI applied to wet-bulb temperature. Compared to GC, the increase in AI and TE clearly reflects the exacerbation of inequity under scenario with migrant construction workers. Lower-income subgroups typically contribute more to heat mitigation inequity than wealthier communities. The decomposability of AI and TE provided policy-relevant insights; AI helped evaluating inequity differences between heat indicators, while TE proved better at detecting inequity changes across scenarios. We discuss the strengths and limitations of each index, paving the way for improved guidance on analytical approaches to assessing environmental equity.
新加坡城市绿地减热生态系统服务公平性评估
城市绿地提供生态系统服务,如减少热量,这与改善居民健康和福利有关。虽然估计生态系统服务的差异对改善公平至关重要,但对于应该使用哪些指数和指标却几乎没有指导。在这里,我们通过两个指标(陆地表面温度降低和湿球温度降低)来评估新加坡城市国家热减排效益的分配公平性,并比较了三个不平等指数:基尼系数(GC)、阿特金森指数(AI)和泰尔熵指数(TE)。我们采用有和没有外来建筑工人的情景来检验在考虑边缘群体时不平等指数的变化,并探讨收入亚群体和其他社会人口因素的影响。结果表明,除人工智能应用于湿球温度外,所有不平等指数都表明,新加坡的热缓解生态系统服务分布不公平。与GC相比,AI和TE的增加清楚地反映了外来建筑工人情景下不平等的加剧。与富裕社区相比,低收入亚群体通常对缓解热量不平等的贡献更大。AI和TE的可分解性提供了与政策相关的见解;人工智能有助于评估热量指标之间的不平等差异,而人工智能在检测不同情况下的不平等变化方面表现更好。我们讨论了每个指数的优势和局限性,为改进对评估环境公平的分析方法的指导铺平了道路。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Ecosystem Services
Ecosystem Services ECOLOGYENVIRONMENTAL SCIENCES&-ENVIRONMENTAL SCIENCES
CiteScore
14.90
自引率
7.90%
发文量
109
期刊介绍: Ecosystem Services is an international, interdisciplinary journal that is associated with the Ecosystem Services Partnership (ESP). The journal is dedicated to exploring the science, policy, and practice related to ecosystem services, which are the various ways in which ecosystems contribute to human well-being, both directly and indirectly. Ecosystem Services contributes to the broader goal of ensuring that the benefits of ecosystems are recognized, valued, and sustainably managed for the well-being of current and future generations. The journal serves as a platform for scholars, practitioners, policymakers, and other stakeholders to share their findings and insights, fostering collaboration and innovation in the field of ecosystem services.
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