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The role of everyday mobility in adaptation to air pollution hazard: A mixed-method approach combining big and traditional data
Global Environmental Change ( IF 8.6 ) Pub Date : 2024-08-27 , DOI: 10.1016/j.gloenvcha.2024.102914 Chang Xia
Global Environmental Change ( IF 8.6 ) Pub Date : 2024-08-27 , DOI: 10.1016/j.gloenvcha.2024.102914 Chang Xia
The empirical study aims to examine how residents perceive and respond to air pollution in their daily lives, whether they use mobility as an adaptation strategy to avoid or mitigate their exposure, and how socioeconomic and demographic factors modify such responses in mobility. To this end, this study conducts an analysis in the city of Chengdu using a mixed-method approach combining surveys and large-scale mobile phone data. It is found that most at-risk individuals take protective measures, and some choose to change mobility patterns to protect themselves from exposure to air pollution. Regression results suggest that engagement with air quality information and the perceived effectiveness of protective measures are the most important predictors of human mobility changes in response to air pollution. The use of mobility as an adaptation strategy occurs despite the availability of in-situ strategies in general, while low-cost and effective in-situ adaptation choices and high-cost mobility strategies are considered as substitutes. Using changes in origin–destination trips in Sichuan generated from 5,393,739 cellphone users in Chengdu, this study reveals that an increase in the difference of the air quality index at origin versus at destination is associated with more trips from the origin to the destination, and travelers are more sensitive to air quality at origin that drives them to escape from the polluted areas. The findings suggest the (re)production of inequality and marginalization of some population groups in hazard adaptation.
中文翻译:
日常出行在适应空气污染危害中的作用:结合大数据和传统数据的混合方法
该实证研究旨在研究居民在日常生活中如何看待和应对空气污染,他们是否使用流动性作为避免或减轻暴露的适应策略,以及社会经济和人口因素如何改变流动性的这种反应。为此,本研究采用调查与大规模手机数据相结合的混合方法,对成都市进行了分析。研究发现,大多数高危人群采取了保护措施,有些人选择改变出行方式以保护自己免受空气污染的影响。回归结果表明,对空气质量信息的参与和对防护措施有效性的感知是因空气污染而导致的人员流动性变化的最重要预测因素。尽管一般存在就地策略,但仍将流动性用作适应策略,而低成本且有效的就地适应选择和高成本流动性策略被认为是替代品。这项研究利用成都 5,393,739 名手机用户生成的四川出发地 - 目的地行程的变化,表明出发地与目的地空气质量指数差异的扩大与从出发地到目的地的旅行增加有关,并且旅行者对原产地空气质量更加敏感,这促使他们逃离污染地区。研究结果表明,一些人口群体在灾害适应过程中(重新)产生了不平等和边缘化。
更新日期:2024-08-27
中文翻译:
日常出行在适应空气污染危害中的作用:结合大数据和传统数据的混合方法
该实证研究旨在研究居民在日常生活中如何看待和应对空气污染,他们是否使用流动性作为避免或减轻暴露的适应策略,以及社会经济和人口因素如何改变流动性的这种反应。为此,本研究采用调查与大规模手机数据相结合的混合方法,对成都市进行了分析。研究发现,大多数高危人群采取了保护措施,有些人选择改变出行方式以保护自己免受空气污染的影响。回归结果表明,对空气质量信息的参与和对防护措施有效性的感知是因空气污染而导致的人员流动性变化的最重要预测因素。尽管一般存在就地策略,但仍将流动性用作适应策略,而低成本且有效的就地适应选择和高成本流动性策略被认为是替代品。这项研究利用成都 5,393,739 名手机用户生成的四川出发地 - 目的地行程的变化,表明出发地与目的地空气质量指数差异的扩大与从出发地到目的地的旅行增加有关,并且旅行者对原产地空气质量更加敏感,这促使他们逃离污染地区。研究结果表明,一些人口群体在灾害适应过程中(重新)产生了不平等和边缘化。