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适用于美国的适应性热应激补偿能力分类的发展。

The development of an adaptive heat stress compensability classification applied to the United States.

作者信息

Guzman-Echavarria Gisel, Middel Ariane, Vecellio Daniel J, Vanos Jennifer

机构信息

School of Geographical Sciences and Urban Planning, Arizona State University, P.O. Box 875302, Tempe, AZ, 85287-5302, USA.

School of Arts, Media and Engineering, Arizona State University, Tempe, AZ, 85287-5802, USA.

出版信息

Int J Biometeorol. 2024 Sep 16. doi: 10.1007/s00484-024-02766-7.

Abstract

Traditional climate classification and weather typing systems are not designed to understand and prevent heat illness, or to design effective cooling strategies during extreme heat. Thus, we developed the Heat Stress Compensability Classification (HSCC) combining open-source historical weather data (2005-2020) with biophysical modeling of a standard human, in the sun or shade, during peak city-specific hot hours on the top 10th percentile hottest days in 96 U.S. cities. Four categories of uncompensable heat stress (UHS)--which can result in rising core temperature--were established based on the relative constraints of dry and evaporative heat exchanges for achieving heat balance in proportion to constant metabolic heat production (112Wm). Results show that 88.7% of these peak-hot hours meet the UHS criterion, and 41% present a dry heat gain of 70 to 150Wm while allowing a maximum evaporative loss between 90 and 140Wm. Evaporative heat loss constraints dominate the eastern U.S. Dry heat gain was widespread, yet particularly high in the south and southwest. Full shade reduces UHS frequency to 7.6%, highlighting the importance of quality shade access and accounting for radiative load in heat stress assessments. Although there are five distinct categories (one compensable and four UHS), the HSCC is dynamic and customizable, providing actionable information on thermal variations within a given category. These variations depict the reason for UHS (e.g., limited evaporative cooling) and, thus, how to concentrate cooling efforts, particularly at the limits of physiological adaptability. Findings facilitate developing targeted criteria for heat stress reduction with potential global applications.

摘要

传统的气候分类和天气分型系统并非旨在理解和预防热疾病,也不是为了在极端高温期间设计有效的降温策略。因此,我们开发了热应激可补偿性分类(HSCC),它将开源历史天气数据(2005 - 2020年)与标准人体在阳光下或阴凉处、美国96个城市第10百分位数最热日的特定城市高峰炎热时段的生物物理模型相结合。基于干热交换和蒸发热交换的相对限制,建立了四类不可补偿热应激(UHS),这些限制是为了在与恒定代谢产热(112W/m²)成比例的情况下实现热平衡。结果表明,这些高峰炎热时段的88.7%符合UHS标准,41%呈现70至150W/m²的干热增益,同时允许最大蒸发损失在90至140W/m²之间。蒸发散热限制在美国东部占主导地位。干热增益普遍存在,但在南部和西南部尤其高。完全阴凉可将UHS频率降低至7.6%,突出了优质阴凉处的重要性以及在热应激评估中考虑辐射负荷的重要性。尽管有五个不同类别(一个可补偿类别和四个UHS类别),但HSCC是动态且可定制的,提供了给定类别内热变化的可操作信息。这些变化描述了UHS的原因(例如,蒸发冷却有限),从而说明了如何集中降温努力,特别是在生理适应能力的极限处。研究结果有助于制定针对性的热应激降低标准,并具有潜在全球应用价值。

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