清洁的空气与居民的日常生活密切相关，是城市居民生活质量的重要影响因素。当前我国空气污染问题严重，对城市居民生活质量和主观幸福感造成不良影响，已经成为关系国计民生的重要社会问题。虽然当前已有大量的研究评估了空气污染对居民健康带来负面影响（健康成本），然而受数据获取手段等方面的限制，对居民行为模式和情绪影响（我们称之为“社会成本”）的研究仍非常缺乏。随着可以表征居民行为特征的时空大数据的出现，给系统分析空气污染的社会成本带来了新的手段。为此，本研究将侧重空气污染的社会成本度量这一论题，回答如何利用时空大数据，借助新兴的空间社会计算方法，研究空气污染对城市居民行为特征和情感的影响，综合测算空气污染的社会成本并对未来情景进行模拟。研究希望能够发展基于时空大数据的环境变化对人类影响评估新方法，促进人地关系研究并为环境效益评估提供科学决策。

China has experienced rapid economic growth in the last three decades, accompanied by significant environmental degradation such as escalating air pollution. In contrast to previous studies on the direct health, cognition, and productivity effects, our research instead draws attention to the broader social costs of air pollution by examining the effects of air pollution on social activities, the social interactions embodied in such activities, and urbanites’ subjective well-being in Chinese cities. China’s serious air pollution, growing urban population, and changing social-economic and spatial structure provide us with a unique “lab” to study these topics. This research builds upon our existing work on air pollution externality, and is the first to link the behavioral changes with subjective well-being and consumer welfare, and further estimate the associated social cost of air pollution with respect to these two aspects. Our study combines urban economics, behavior science, and environmental studies approaches to connect individual-level human behaviors with aggregate-level social welfare estimates with a handful of unique spatial-temporal big data sources in China. More importantly, we will perform causal analysis, rather than simple correlation analysis, using instrumental variables technique. The results will provide insights into the social cost of air pollution in China, and suggest socially responsible policies aimed at mitigating air pollution and promoting social activities and interactions in cities.