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Chen Zhang, Hua Liao, Fang-Zhi Wang, and Ru Li

Abstract

Human behaviors are believed to be sensitive to environmental conditions. However, little is known about the role of temperature in individual daily behaviors. We examine the links between temperature and food intake using nearly one million purchasing records from China. The results show that a 1°C increase in temperature would cause a 0.11% decrease in food intake, which amounts to USD 4.2 million of daily food expenditures nationwide. Moreover, females appear to be more sensitive to the temperature in their food intake than males. In addition, we observe a U-shaped relationship between the temperature and the willingness to order a takeout online, and this observation is robust under multiple alternative estimations. Our results indicate that a higher temperature would reduce energy demand for body thermoregulation, resulting in less food intake. Both extreme high and low temperatures can cause disutility. Therefore, the consumers who still want to satisfy their needs for food intake feel compelled to alter their willingness to pay under the extreme temperature events. The quantitative analysis can provide helpful references for modeling the climate–consumer relationship in integrated assessment models. Thus, it is an interesting avenue for future research to bridge the climate and consumers to identify welfare loss and inequality due to climate change.

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Yuyao Cao, Qinghong Zhang, Juanzhen Sun, Rumeng Li, Yaohai Huang, Jing Zhuang, Jun Xu, and Yun Chen

Abstract

Understanding when weather information is required by the public is essential for evaluating and improving user-oriented weather services. Due to the popularity of smartphones, most people can easily access weather information via smartphone applications. In this study, we analyzed usage data for the Moji Weather smartphone application in 2017 and 2018, and devised a demand index to determine how often the weather information was used by the public under different weather conditions. Using hourly observations of surface temperature, wind intensity, precipitation, and visibility, we quantified the relationship between the demand for weather information and weather conditions in different regions of China. Generally, the demand index increased with increases in local hourly precipitation or surface wind intensity in all regions; however, there were notable regional differences in the increasing trends. Extreme hot weather was found to increase the demand index in Northern China, Xinjiang, and the Sichuan Basin, while in Southern China it increased more in response to extreme cold weather. We quantified the relationships between the demand index and weather conditions by performing a polynomial regression analysis for each weather element and region. The high-demand thresholds were found to vary among regions, suggesting the need for customized weather services for users in different geographical regions. The study also revealed the contribution of weather warnings to weather information demand in two megacities, and showed that warnings were effective for conveying information regarding weather-related risks.

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