Effects of AT and NT surface temperate on player’s thermal stress (continued from page 19)
Te impact of AT and NT surface temperature on players' thermal stress was estimated using a statistical modeling procedure called multiple linear regression, where time of day and day of week were considered. Two sets of models were developed for players on each field type—physiological thermal stress and perceived thermal stress. Te Figure 5 graphic showing this data in on the previous page. Particular attention was given to (1) the comparison of the impact of turf surface temperature on different types of thermal stress, as well as to (2) investigate the explanatory capacity of turf surface temperature as a proxy of thermal stress. Upper plots showed the predicted changes in physiological thermal stress (W/m2
) by an increase in one Fahrenheit degree of AT and
NT surface temperature, whereas the bottom plot indicated the predicted shifts in perceived thermal stress. All models were statistically significant, indicating that both field types affect physiological and perceived thermal stress significantly.
Te impact of surface temperature on athletes' thermal stress is higher on NT than AT. Te coefficient slope of NT is 11.6 for physiological thermal stress, meaning that the one-degree F increase in surface temperature led to 11.6 growth in energy budget values (W/m2
). Te coefficient
slope of AT was 6.9 which was three times less than NT. Interestingly, a similar outcome was found in perceived thermal stress, where NT's coefficient slope (0.014) was higher than AT’s (0.008). Tese findings indicate that both the perceived and physiological thermal stress of the players are more sensitive when they are performing on NT. We assume that this is mainly due to the higher thermal stress level on AT that may result in the reduced performance (or amount of activity) and lower metabolic rates leading to decreases in thermal stress of players compared to NT.
Explanatory power of surface temperature for thermal stress varies on the types of thermal stress. In this study, explanatory power indicates the ability on how much variations in players' thermal stress can be explained by the surface temperature. Overall, the surface temperatures showed better performance in explaining athletes’ physiological thermal stress than the perceived thermal stress model. In the physiological thermal stress model, the explanatory power (or adjusted r-squared) values are 57 percent and 49 percent for AT and NT respectively, which are around 30 percent higher than the perceived thermal stress model. Tis implies that, considering their high explanatory power of around 50 percent, surface temperature can be considered a superior proxy when it is used for measuring the physiological thermal stress of soccer players.
Conclusion
Tis study compared the perceived and physiological thermal stress of soccer players performing on AT and NT. Microclimate was measured on each field type during four hot, sunny, summer days in 2021. Questionnaire surveys and the COMFA model were adopted to measure perceived and physiological thermal stress, respectively. Our findings confirmed that surface temperature is the main driving factor that leads to an increase in both perceived and physiological thermal stress of the soccer players in summer daytime. Te highlights of the key findings are as follows:
• Mean AT-NT difference in surface temperature was over 68.0 degrees F (20 degrees C), which tends to be more pronounced when the direct solar beam is stronger, and the time reaches solar noon at around 1:00 PM CST
• Athletes performing on AT had higher perceived and physiological thermal stress than those on NT. Compared to AT, NT can reduce the physiological thermal stress by up to 20 percent in a setting of a clear, hot, and sunny day.
Te findings of this study are useful for biometeorology and sports field management to enhance the athletes’ safety from heat stress and increase their match performance. Future studies need to address how the difference in thermal stress induced by AT and NT affects the athlete’s physical performance and physiological body changes, such as hydration.
REFERENCES
Francis, R. A. (2018). Artificial lawns: Environmental and societal considerations of an ecological simulacrum. Urban Forestry & Urban Greening, 30, 152-156.
Guyer, H. (2020). Athletic Surfaces’ Influence on the Termal Environment: An Evaluation of Wet Bulb Globe Temperature in the Phoenix Metropolitan Area. Arizona State University, Temple, AZ
Harlan, S. L., Brazel, A. J., Prashad, L., Stefanov, W. L., & Larsen, L. (2006). Neighborhood microclimates and vulnerability to heat stress. Social science & medicine, 63(11), 2847-2863.
Jim, C. Y. (2017). Intense summer heat fluxes in artificial turf harm people and environment. Landscape and Urban Planning, 157, 561-576.
Kenny, N. A., Warland, J. S., Brown, R. D., & Gillespie, T. G. (2009). Part A: Assessing the performance of the COMFA outdoor thermal comfort model on subjects performing physical activity. International Journal of Biometeorology, 53(5), 415-428.
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TPI Turf News September/October 2022
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