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Household energy use response to extreme heat with a biophysical model of temperature regulation: An Arizona case study [1]

['Halley B. Hughes', 'School Of Natural Resources', 'The Environment', 'University Of Arizona', 'Tucson', 'Az', 'United States Of America', 'W.A. Franke Honors College', 'David D. Breshears', 'Kimberly J. Cook']

Date: 2023-04

Rising temperatures associated with climate change are impacting household energy use. Many of today’s industrial-technological-urban humans thermoregulate in the face of varying temperatures using extra-metabolic energy use for heating and cooling our indoor microclimates. Previously, household energy use as a function of temperature change over seasons and time has been described using a three-part model of thermoregulation, the Extra-Metabolic Scholander-Irving model (EMSI), where energy use is lowest in the thermal neutral zone around room temperature and increases in colder and hotter temperatures. However, the EMSI model has only been evaluated for moderately warm cities to date, covering only two parts of the three-part model and lacking evaluation of data for extremely hot temperatures. We show that household energy use in Arizona, a U.S. state that includes hot semi-arid environments, varies across topography, and increases in response to the hottest summer months–exemplifying the third part of the EMSI model. Additionally, household energy use is lowest in the spring and fall and increases in response to colder temperatures in the winter. This relationship has hysteresis related to differences in household income; service regions with lower-income households delay the onset of extra-metabolic energy use for cooling. We use this model to gain predictive insights into energy use demand due to ongoing warming in the context of the desert city of Yuma, Arizona, where a relatively small increase in mean temperatures of ~1.5°C since the Industrial Revolution produced a 20-day increase (6%) in cooling days annually. Our study expands the EMSI model of thermal regulation to the previously missing hot part of the model, thereby gaining insights into the unique challenges of sustaining extra-metabolic thermoregulation in the face of global warming.

Funding: This work was funded by the Bridging Biodiversity and Conservation Science group at the University of Arizona via the Arizona Institutes for Resilience. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Data Availability: This study does not use original data. It is a synthesis of many publicly-available datasets which are all appropriately cited in the manuscript. The methodology section should provide amble guidance for both the replication and reproduction of this study.

Introduction

Addressing heat stress is one of the greatest challenges facing humans because climate change is increasing the frequency, intensity, and duration of hot extremes [1]. Several record-breaking heat events occurred around the globe in 2021 [2]. These heat events are unequivocally caused by climate change and in urban areas, their effects are compounded by the urban heat island (UHI) effect [3]. The UHI effect is caused by the planning, design, and mechanical operation of urban areas which results in increased temperatures compared with rural areas at their peripheries [4]. Cities in the U.S. are projected to be on average 5.55°C hotter in the afternoon and 7.77°C hotter at night by the end of the century [5]. Indicative of hotter locations around the globe, cities in the U.S. Southwest are getting hotter faster, illustrated by the fact that the top four fastest-warming cities are in the U.S. Southwest [6]. Despite clear climatic, regional, and scientific evidence of increasing heat stress in this region, there is a noticeable lag in heat planning and governance compared to other climate risks [7]. Thus, a better understanding of future energy consequences of heat in cities and inequities in heat mitigation and management efforts is needed as temperatures continue to increase [7].

To fully address the challenges affecting energy use in cities due to climate change and the UHI effect, we investigate the nexus of energy use and temperature to help inform heat planning and governance. Multiple frameworks can be used to assess energy use and temperature [8–10]. In this study, we link heat with temperature and energy use through an extended Scholander-Irving (S-I) model [11]. This approach has the advantage of being grounded in biophysical theory rather than being a statistical approach that adds socio-environmental variables as needed, while simultaneously contributing to a general understanding of energy use and temperature relationships. This biophysical model for thermoregulation in warm-blooded animals provides insights into the energetic cost of household thermoregulation in modern humans [12, 13]. Warm-blooded animals have evolved to maintain constant body temperatures (homeostasis) in the face of varying environmental temperatures by modulating biological metabolism regulated by the hypothalamus, and humans are no exception [14]. For example, humans use biological metabolism to sweat and cool themselves via evaporative cooling with increasing temperatures. Modern humans are unique, however, because they can also incorporate “extra-metabolic” energy using fossil fuels and renewable energy to thermoregulate our microhabitats in variable environments [15]. The functional role of the hypothalamus in maintaining homeostasis has been replaced mechanically by a thermostat [16]. Increasing or decreasing temperatures from a thermal neutral zone in the biological S-I models correspond with increasing biological energy demand. Despite a clear overlap between the S-I and EMSI, the EMSI extension has yet to be evaluated for hot temperatures in urban humans [12, 13].

Here, we build on this literature to evaluate the unique human relationship between “extra-metabolic” energy use and temperature by expanding the EMSI model with data for regions that experience high average temperatures and extreme heat events. We draw on the Scholander-Irving biophysical model for warm-blooded animals, which includes three parts: a zone of cold regulation, a thermal neutral zone, and a zone of heat regulation (Fig 1A), as seen in both the desert cottontail (Fig 1B) and humans (Fig 1C). Previous studies of cities have shown that the EMSI biophysical model for warm-blooded animals can be applied to the thermoregulation of households [Fig 1D, 12, 13, 16] for the cold and moderate parts of the three-part model. However, there is currently no study exploring the use of the EMSI model in cities that experience high annual temperatures–the third part of the model (Fig 1D). We studied Arizona, a state in the U.S. Southwest that includes seasonally hot cities in diverse hot semi-arid environments, to evaluate the third part–the hot temperatures on the right side–of the EMSI curve. Arizona is an ideal state to study for the third part of the curve as it has cities with monthly high temperature averages of 42.7°C.

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TIFF original image Download: Fig 1. The evolution of the Extra-Metabolic Scholander-Irving model. The Scholander-Irving model of metabolic energy use in thermoregulation in mammals is displayed through A) A conceptual/theory model, B) empirical data for desert cottontail rabbit (Sylvilagus audubonii) from Tucson, AZ which is modified from [17], C) Human biological metabolic data of naked humans adjusted from Hill et al. (2013). The human S-I curve lacks hot temperature data because of ethical research standards. The TNZ line is approximately the same width as cities and animals (10°C). Adding insulation measures, like clothing, to base human data would decrease the slope of the line left of the TNZ. (See Hill et. al 2013 for an in-depth explanation of the human S-I curve), and D) Extra-Metabolic Scholander-Irving model for a previous City study from Hill et al. (2013) modified to show a lack of hot data. Note the scale differences due to the data resolution (monthly vs. daily) and collection methods. https://doi.org/10.1371/journal.pclm.0000110.g001

We combine data for “extra-metabolic” energy use and temperatures from 2019 to i) develop empirical models of the household energy use response to temperatures to evaluate the hottest part of the EMSI model and ii) produce future projections of household energy use. We present results showing that the EMSI model applies to cities in hot climates and that there is spatial variability in household energy use between hot cities differing in income. We also demonstrate that heat waves and changing climate will affect household energy use. Finally, we discuss the benefits of this modeling system, and the broader implications that increased heat has on health and urban planning. We end with opportunities for extension and future studies. The 3-part EMSI model shown here bridges disciplinary divides by linking a foundational biophysical model of thermoregulation to the unique human ecology in the face of global change. The result is a holistic perspective on urban metabolism and heat vulnerability discourse in the face of rising temperatures.

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[1] Url: https://journals.plos.org/climate/article?id=10.1371/journal.pclm.0000110

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