Impact of wind turbulence on thermal perception in the urban microclimate

https://doi.org/10.1016/j.jweia.2021.104714Get rights and content

Highlights

  • The effect of wind flow turbulence on thermal perception under outdoor conditions has been examined though a human subject experiment in the wind tunnel.

  • The increased turbulence intensity enhances perceived coolness by reducing the skin temperature.

  • The previously published thermal comfort models may underestimate the mean skin temperature decrement by 30% and 50% for standing and cycling conditions respectively.

  • Appling a recent manikin-derived convective heat transfer coefficient formula in the existing thermal comfort models can improve the accuracy of the mean skin temperature prediction.

Abstract

Ongoing urbanization has led to complexities in the urban terrain, increasing roughness length within the atmospheric surface layer, and introduced highly turbulent wind flow at pedestrian height. This research aims to explicitly examine the effect of wind flow turbulence on thermal perception under outdoor conditions. A wind tunnel with passive grid was used to introduce turbulence into simulated wind conditions. Thermal physiological (skin temperature) and perceptual (questionnaire) responses were collected from 20 college-age subjects during the exposures to various simulated urban wind conditions. Results confirm that increased turbulence intensity enhances perceived coolness by reducing the skin temperature. We updated the convective heat transfer coefficient in a numerical skin thermoreceptor model and also Gagge's two-node thermophysiological model so that they both reflect more accurately the effects of turbulence intensity on skin temperature. Skin temperatures simulated with the modified models were in good agreement with experimental observations, and corrected the un-modified model's 30% and 50% underestimation of mean skin temperature decrement for standing and cycling conditions respectively. These findings contribute to the broader goal of a thermal comfort model for application to urban microclimate.

Introduction

A sedentary lifestyle negatively impacts health, increasing the risk of cardiovascular diseases, diabetes, and obesity (Godbey, 2009). To compensate for diminished activity, communities are encouraged to spend more time engaged in outdoor activities. However, in warm-to-hot climate zones where the rate of urbanisation is greatest, the urban heat island effect not only suppresses outdoor activities, but also deters citizens from walking to everyday destinations – shops, public transport hubs, and schools (Asimakopoulus and Santamouris, 2012). City designers, landscape architects, and engineers efforts to manage urban warming are focusing on performance testing various cooling strategies including artificial and natural shading (Lin et al., 2013) and enhancing air movement between buildings (Xie et al., 2018).

Compared with retrofitting environmental remediation based user feedback, it would be more efficient to design urban cooling strategies in the planning phase. Predictive thermal comfort models represent a useful tool in this endeavour. Such models link urban microclimatic characteristics to pedestrians' thermal perceptions, usually expressed on a 7-point thermal sensation scale (−3 = cold, −2 = cool, −1 = slightly cool, 0 = neutral, 1 = slightly warm, 2 = warm, 3 = hot) (ASHRAE, 2017). Thermal environmental parameters (i.e., air temperature, mean radiant temperature, relative humidity, wind velocity), taken together with expected clothing insulation and activity intensity are the main inputs to a thermophysiological model that mathematically describes the heat exchanges at the body's surface, inside the body (passive system), and the thermal regulation process (active system) that those effects in the passive system would induce. Based on the calculated physiological parameters, thermal sensation model can then predict people's thermal perception.

Substantive improvements have been made since the simple two-node thermoregulatory model was first developed half a century ago (Stolwijk, 1971) in two distinct directions. First is the anatomy of the body, which has evolved from the simplistic single sphere of the two-node model (Gagge, 1971; Givoni and Goldman, 1972) into a multi-segment humanoid form with each segment comprising four layers: skin, fat, muscle, and core, each with its own thermal properties (Stolwijk, 1971). The second major evolution in numerical thermal regulation models related to the movement of blood between these multiple nodes, upgraded from a constant-temperature central blood compartment to an intricate system of arteries and veins capable of simulating counter-current heat exchanges between blood and the tissues through which it flows (Huizenga et al., 2001a; Kingma, 2012; Kingma et al., 2012; Zhang et al., 2001).

Despite refinements in the active system the heat exchanges between the passive system and its thermal environment remain oversimplified, ignoring the highly turbulent condition of the atmospheric boundary layer. Wind is represented by mean velocity only, with its fluctuating characteristics being filtered out. However, experimental (i.e. wind tunnel testing, field measurement) and numerical simulation studies (Assimakopoulos et al., 2003; Niachou et al., 2008; Oke, 1987; Stathopoulos, 2006; Scaperdas and Colvile, 1999) have confirmed the complex flow characteristics of the pedestrian-level wind environment. In the urban canopy layer, wind is easily governed by terrain surface characteristics and the immediate surroundings. Therefore, the unrealistic characterisation of air flowing over the surface of contemporary thermoregulation models may be one of the explanations of a persistent discrepancy between comfort model predictions and field observations (Xie et al., 2018, 2020).

While turbulence effects have not yet been incorporated into numerical thermoregulation models, they have long been recognised in the context of human perception of draught, defined as unwanted local cooling, in indoor settings (Fanger et al., 1988). The statistical draft risk model (Fanger et al., 1988) predicts the percentage of dissatisfaction caused by draught PD, as a function of the air temperature Ta, mean air velocity v, and the turbulence intensity TI of the air flow.

More recently research attention has shifted away from unpleasant draft effects in cool-to-neutral thermal environments (negative alliesthesia) towards the pleasant breeze effects of airflow in warm-than-neutral environments (Xia et al., 2000), termed positive alliesthesia (Huang et al., 2012; Parkinson and de Dear, 2016; Tanabe and Kimura, 1989; Zhou et al., 2010). Among those studies which not only collected the subjective responses but also measured the skin temperature simultaneously, Parkinson and de Dear (2016) found that the frequency and amplitude of skin temperature fluctuation followed the pattern of air movement. Fanger et al. (1988) also long maintained the importance of fluctuations in skin temperature in eliciting sensations of draft discomfort, which is simply a synonym for negative alliesthesia.

But despite these significant research efforts into wind turbulence effects on subjective thermal comfort, its effect on convective heat loss has not been included in the exiting thermal regulation models. Mayer (1987) first to connected turbulence intensity to convective heat transfer at the skin surface, measuring it indirectly through the thermal boundary layer around an artificially heated manikin head, with the turbulence intensity ranging from 14% to 55% at mean wind velocity below 0.5 m/s. The experimental results proved that convective heat loss increases with turbulence intensity. His manikin studies were followed by a series of human subject experiments, with skin temperature differences investigated at average wind speeds between 0.1 m/s and 0.6 m/s and turbulence levels between 15% and 70%. Griefahn et al. (2000) experimental findings indicated that with a velocity range from still air up to 0.5 m/s the skin temperature differences between turbulence levels were almost indistinguishable from measurement error. Wang et al. (2011) suggested that the variation of skin temperature reduction at local sites only become noticeable between different turbulence intensities (15% and 30%) when the mean wind velocity exceeded 0.3 m/s. However, the highest wind speed been tested in the previous studies (1 m/s) was far too low compared to typical outdoor pedestrian-level wind conditions.

Meanwhile, a recent study in which a thermal manikin was exposed to an outdoor air velocity range (0.7–6.9 m/s) confirmed that ignoring turbulence intensity of 30% resulted in convective heat transfer at the manikin's skin surface being underestimated by as much as 50% (Yu et al., 2020). Discrepancies of this magnitude emphasise that the effects of turbulence intensity cannot be dismissed as negligible, and therefore should be incorporated into contemporary thermal regulation models and their associated comfort predictions.

This study aims to verify the recent manikin-derived convective heat transfer coefficient formula, using physiological and psychological responses collected from the human subjects, tested under diverse combinations of metabolic rate, wind speed, and wind direction.

Section snippets

Materials and methods

The experiments were conducted in the Boundary Layer Wind Tunnel (BLWT) in the School of Civil Engineering at The University of Sydney. The tunnel is 20 m long, 2.5 m wide and 2 m high. The incoming air velocity was controlled through the rotational speed of the wind tunnel fan, and a coarse grid at the inlet (Fig. 1a, see Yu et al., 2020 for a detailed description of the facility)was used to simulate outdoor urban wind environments with realistic turbulence intensity ranges (Zou et al., 2021).

The effect of turbulence intensity on whole-body thermal perception

The participants were required to report their thermal sensation vote by filling in a questionnaire on their mobile device as soon as they felt the wind. This process took up to an average of 25 s over all the participants. Previous studies have suggested that the subjective sensation under a dynamic thermal stimulation is directly proportional to the impulse accumulated by the thermoreceptors within the first 20 s (de Dear et al., 1993). Therefore, we here adopted the skin temperature change

Conclusions

This study confirms the impact of turbulence-induced cooling on both physiological and perceptual responses of human subjects to wind. When directly facing the wind, the subjects could almost instantly feel the difference between two levels of turbulence intensity (35% and 17%), which was reflected by the proportional change of skin temperature. The mean skin temperature difference between two turbulence levels continues to increase, and reached statistically significant after 10-min under all

CRediT authorship contribution statement

Yichen Yu: Methodology, Visualization, Validation, Writing – original draft. Richard de Dear: Conceptualization, Methodology, Visualization, Validation, Writing – review & editing, Supervision. Kapil Chauhan: Visualization, Writing – review & editing, Supervision. Jianlei Niu: Conceptualization, Writing – review & editing, Supervision.

Declaration of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Acknowledgement

This research was supported by the School of Architecture, Design and Planning, and the School of Civil Engineering, both at The University of Sydney. The authors wish to thank Mr Zachary Benitez, Mr Theo Gresley-Daines, and Mr Jiwei Zou for their technical support and assistance with the wind tunnel experiments.

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