Abstract

Mean radiant temperature (Tmrt) is a frequently-used measure of outdoor radiant heat conditions. Excessive Tmrt, linked especially to clear and warm days, have negative effect on human well-being. Highest Tmrt on such days is found in sunlit areas, whereas shaded areas have significantly lower values. One way of alleviating high Tmrt is by planting trees to provide shade in exposed areas. To achieve the most efficient mitigation of excessive Tmrt by tree shade with multiple trees requires optimized positioning of the trees, which is a computationally extensive procedure. By utilizing metaheuristics, calculations can be reduced. Here, we present TreePlanter v1.0, which applies a metaheuristic hill climbing algorithm on input raster data of Tmrt and shadow patterns to position trees in complex urban areas. The hill climbing algorithm enables dynamic exploration of the input data to position trees, compared with very computationally demanding brute-force calculations. The results show that the algorithm, in relatively low model runtime, can find positions for several trees simultaneously that lowers Tmrt substantially. TreePlanter can assist in future research on optimization of tree planting in urban areas to increase thermal comfort. The current version can only position trees of equal tree characteristics (tree height, tree canopy and trunk height). Expected developments include positioning of trees with different tree characteristics.

Highlights

  • The increased risk of exposure to excessive heat in urban areas during extreme events as an effect of a modified urban climate can lead to excess mortality and morbidity (Dousset et al, 2010; Gabriel and Endlicher, 2011)

  • TreePlanter make use of output data generated by the SOlar and LongWave Environmental Irradiance Geometry (SOLWEIG) model (Lindberg et al, 2008)

  • Tree locations were determined from tree locations from a previous iteration. Their results showed that tree locations with the genetic algorithm had a higher mitigating effect compared to randomly positioned trees. This can be compared to the results found in this paper, where tree locations with a high potential mitigating effect are sometimes found with fewer iterations with the genetic algorithm compared to the random algorithm

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Summary

Introduction

The increased risk of exposure to excessive heat in urban areas during extreme events as an effect of a modified urban climate can lead to excess mortality and morbidity (Dousset et al, 2010; Gabriel and Endlicher, 2011). Mean radiant temperature (Tmrt, ◦C) is an important meteorological variable in the human energy balance and outdoor human thermal comfort, especially during clear and warm weather (Mayer and Höppe, 1987; Höppe, 1992; Mayer et al, 2008). Tmrt is the sum of all short- and longwave radiation fluxes (both direct and reflected) to which the human body is exposed, defined by ASHRAE (2001) as the “uniform temperature of an imaginary enclosure in which radiant heat transfer from the human body equals the radiant heat transfer in the actual nonuniform enclosure”. Thorsson et al (2014) showed that there is a higher correlation between Tmrt and mortality compared than between air temperature and mortality on hot days. High daytime Tmrt correlated with heat related mortality among people aged 80+, whereas high nighttime Tmrt correlated with heat related mortality among peopled aged 45–79

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