Identifying publicly perceived high temperature thresholds across Chinese cities using geotagged social media data

• Published in: Sustainable cities and society 2025-02, Vol.119, p.106115, Article 106115
• Main Authors: Xu, Rui, Yi, Jiawei, Qi, Wei, Du, Yunyan, Huang, Sheng, Wang, Nan, Qian, Jiale, Tu, Wenna, Hu, Dingchen, Ma, Ting, Dewan, Ashraf
• Format: Article
• Language: English
• Subjects: Exposure; Heat perception; High temperature; Meteorological standards; Social media; Thresholds
• ISSN: 2210-6707
• DOI: 10.1016/j.scs.2024.106115

•Ensemble approach identifies heat perception thresholds using social media data.•Climate and socioeconomic factors shape city-specific heat perception thresholds.•Heat exposure risks exceed current warning standards in many Chinese cities. Over recent decades, there has been a marked increase in the frequency and intensity of high temperature events (HTEs) at a global scale, posing profound impacts on human society and on the ecological environment. Recognizing the variability in public perception of high temperatures across different regions is critical for developing localized heat adaptation and mitigation measures. This study developed an ensemble approach to investigate the geographical variations in public perception of high temperatures across 351 Chinese cities using geotagged microblogs. The results revealed that the perceived high temperature thresholds were significantly lower than the heat warning standard, and apparent temperature thresholds exhibited greater variability and better characterize perceived thermal discomfort across cities. The thresholds are significantly associated with climatic factors such as mean temperature and warming trend, as well as socio-economic factors including population density, electricity consumption, green space, and nighttime urban heat island intensity. The research findings also revealed the potential underestimation of exposure to heat risk in many cities, particularly in northeastern and southwestern China. This study demonstrated the value of social media data in understanding public perception of heat and emphasized the importance of considering local adaptability in developing effective heat warning and mitigation strategies.