Department of Geosciences, Middle Tennessee State University, P.O. Box 9, Murfreesboro, TN, 37132, USA.
Department of Geography, University of Tennessee, Knoxville, Knoxville, TN, USA.
Int J Biometeorol. 2022 Jul;66(7):1339-1348. doi: 10.1007/s00484-022-02280-8. Epub 2022 Apr 4.
Wearable sensors have been used to collect information on individual exposure to excessive heat and humidity. To date, no consistent diurnal classification method has been established, potentially resulting in missed opportunities to understand personal diurnal patterns in heat exposure. Using individually experienced temperatures (IET) and heat indices (IEHI) collected in the southeastern United States, this work aims to determine whether current methods of classifying IETs and IEHIs accurately characterize "day," which is typically the warmest conditions, and "night," which is typically the coolest conditions. IET and IEHI data from four locations were compared with the closest hourly weather station. Different day/night classifications were compared to determine efficacy. Results indicate that diurnal IET and IEHI ranges are higher than fixed-site ranges. Maximum IETs and IEHIs are warmer and occur later in the day than ambient conditions. Minimum IETs are lower and occur earlier in the day than at weather stations, which conflicts with previous assumptions that minimum temperatures occur at night. When compared to commonly used classification methods, a method of classifying day and night based on sunrise and sunset times best captured the occurrence of maximum IETs and IEHIs. Maximum IETs and IEHIs are often identified later in the evening, while minimum IETs and IEHIs occur throughout the day. These findings support future research focusing on nighttime heat exposure, which can exacerbate heat-related health issues, and diurnal patterns of personal exposure throughout the entire day as individual patterns do not necessarily follow the diurnal pattern seen in ambient conditions.
可穿戴传感器已被用于收集个体暴露于过度热和湿环境中的信息。迄今为止,尚未建立一致的昼夜分类方法,这可能导致错失了解个人热暴露昼夜模式的机会。本研究使用在美国东南部收集的个体经历温度(IET)和热指数(IEHI),旨在确定当前分类 IET 和 IEHIs 的方法是否能准确描述“白天”(通常是最温暖的条件)和“夜晚”(通常是最凉爽的条件)。来自四个地点的 IET 和 IEHI 数据与最近的每小时气象站进行了比较。比较不同的昼夜分类,以确定其功效。结果表明,昼夜 IET 和 IEHI 范围高于固定站点范围。最大 IET 和 IEHI 比环境条件更温暖,且出现在一天中的较晚时间。最低 IET 比气象站更低,且出现在一天中的较早时间,这与先前假设的最低温度发生在夜间相矛盾。与常用的分类方法相比,基于日出和日落时间的昼夜分类方法最能捕捉到最大 IET 和 IEHI 的发生。最大 IET 和 IEHI 通常在晚上较晚时间被识别,而最低 IET 和 IEHI 则全天发生。这些发现支持未来的研究重点关注夜间热暴露,这可能会加剧与热相关的健康问题,以及个人全天的昼夜暴露模式,因为个体模式不一定遵循环境条件下的昼夜模式。