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城市健康与福祉的气候行动:使用机器学习方法系统开发同行评审研究数据库的方案

Climate action for health and wellbeing in cities: a protocol for the systematic development of a database of peer-reviewed studies using machine learning methods.

作者信息

Belesova Kristine, Callaghan Max, Minx Jan C, Creutzig Felix, Turcu Catalina, Hutchinson Emma, Milner James, Crane Melanie, Haines Andy, Davies Michael, Wilkinson Paul

机构信息

Department of Public Health, Environments and Society and Centre on Climate Change and Planetary Health, London School of Hygiene and Tropical Medicine, London, WC1H 9SH, UK.

Mercator Research Institute on Global Commons and Climate Change, Berlin, 10829, Germany.

出版信息

Wellcome Open Res. 2021 Mar 5;6:50. doi: 10.12688/wellcomeopenres.16570.1. eCollection 2021.

Abstract

Cities produce more than 70% of global greenhouse gas emissions. Action by cities is therefore crucial for climate change mitigation as well as for safeguarding the health and wellbeing of their populations under climate change. Many city governments have made ambitious commitments to climate change mitigation and adaptation and implemented a range of actions to address them. However, a systematic record and synthesis of the findings of evaluations of the effect of such actions on human health and wellbeing is currently lacking. This, in turn, impedes the development of robust knowledge on what constitutes high-impact climate actions of benefit to human health and wellbeing, which can inform future action plans, their implementation and scale-up. The development of a systematic record of studies reporting climate and health actions in cities is made challenging by the broad landscape of relevant literature scattered across many disciplines and sectors, which is challenging to effectively consolidate using traditional literature review methods. This protocol reports an innovative approach for the systematic development of a database of studies of climate change mitigation and adaptation actions implemented in cities, and their benefits (or disbenefits) for human health and wellbeing, derived from peer-reviewed academic literature. Our approach draws on extensive tailored search strategies and machine learning methods for article classification and tagging to generate a database for subsequent systematic reviews addressing questions of importance to urban decision-makers on climate actions in cities for human health and wellbeing.

摘要

城市产生的温室气体排放量占全球总量的70%以上。因此,城市采取行动对于缓解气候变化以及在气候变化背景下保障城市居民的健康和福祉至关重要。许多城市政府已对缓解和适应气候变化做出了雄心勃勃的承诺,并采取了一系列行动来应对这些问题。然而,目前缺乏对这些行动对人类健康和福祉影响的评估结果进行系统记录和综合分析。这反过来又阻碍了关于哪些是对人类健康和福祉有益的高影响力气候行动的可靠知识的发展,而这些知识可以为未来的行动计划及其实施和扩大规模提供参考。由于相关文献广泛分布在许多学科和领域,利用传统文献综述方法难以有效整合,因此要系统记录有关城市气候与健康行动的研究颇具挑战性。本方案报告了一种创新方法,用于系统开发一个数据库,该数据库收录了城市实施的缓解和适应气候变化行动的研究,以及这些行动对人类健康和福祉的益处(或不利影响),这些信息来源于同行评审的学术文献。我们的方法采用了广泛的定制搜索策略和机器学习方法进行文章分类和标记,以生成一个数据库,用于后续的系统综述,解决城市决策者在城市气候行动对人类健康和福祉方面的重要问题。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8737/8022210/76b2a03a2ee1/wellcomeopenres-6-18260-g0000.jpg

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