90 (r = 0.03), and minimum noise (r = 0.02), and also maximum noise with ultraviolet radiation (r = -0.03). The ANOVA results showed significant differ- ences from various sources of variation (Table 3). Tree coverage and time of day showed significant dif- ferences in the variables, with the exception of the noise level data. Season showed significant differ- ences for all variables. Maximum noise and ultraviolet radiation did not show any interactions between the sources of varia- tion, such that the results from the Tukey multiple comparison test for these variables indicate that these variables can be analyzed separately, depending on the source of variation (Table 4). In the remaining variables, any interactions evident are merely for ref- erence. For example, if maximum PM10 is analyzed according to tree coverage, time of day, and season of year, it was observed that the maximum values for canopy coverage of 20%, 100%, and 40% were found in autumn, spring, and summer, respectively. In autumn as in spring, the maximum values are reached in the morning, whereas in summer the maximum values were recorded at midday (Table 4). The Tukey multiple comparison test showed the differences detected by the ANOVA. In the case of canopy coverage, significant differences were found of the variables show a linear relationship between themselves (grey cells), however, weak relationships (r < 0.60) dominate the results, the exceptions being the relationship between temperatures (r = 0.97), fol- lowed by relative humidity with temperature at 1.5 m (r = -0.86) and with temperature at ground level (r = -0.85), and finally between particulate matter. The variables that didn’t show a linear relationship with tree coverage are maximum PM10 PM10 (r = 0.00), average Ponce-Donoso et al: Urban Trees and Environmental Variables for noise, temperature at ground level, and ultraviolet radiation, showing that larger tree coverage can be characterized by lower average values. This tendency is likewise visible in the remaining variables, even though there is no evidence of significant differences with the exception of relative humidity (RH), which has an inverse relationship (Table 4). This result con- firms that tree coverage has a role in reducing the amplitude of these recorded variables, making cities more habitable by reducing the undesirable effects of these negative variables. The time of day showed significant differences for all variables except for maximum noise. The behavior of the variables that showed significant differences was dissimilar. The highest values were observed in the mornings for maximum and average particulate matter, minimum noise, and relative humidity, whereas temperatures reached maximums at midday. Analyzing the season variable established that maxi- mum values, with the exception of temperature and ultraviolet radiation, were recorded in autumn. DISCUSSION Even though the particulate matter values show sig- nificant differences (Tables 3 and 4) when considering the tree coverage, no clear tendency is visible in the relationship between particulate matter and tree cov- erage. According to Liu et al. (2015), the canopy cov- erage directly influences the concentration of particulate matter. This relationship was also con- firmed in this study, even though canopy coverage did not necessarily lead to a reduction in particulate matter. Another aspect that justifies these results is the spatial extent of the study. The distance between the furthest pair of spatially separated points was no more Table 3. Probability of ANOVA by variable and source of variation. Variables Source of variation A: Coverage B: Time of day C: Season Interaction ABC PM10 (mg/m3 Max 0.0176 0.0000 0.0000 0.0055 ) Avg 0.0008 0.0000 0.0000 0.0001 The data with significant differences are marked in grey. ©2020 International Society of Arboriculture Noise (dBA) Max 0.0000 0.1133 0.0448 0.8636 Min 0.3973 0.0000 0.0000 0.0207 Ground 0.0000 0.0000 0.0000 0.0157 Temperature (°C) 1.5 m 0.0000 0.0000 0.0000 0.0000 UV (nm) RH (%) 0.0012 0.0000 0.0000 0.2861 0.0000 0.0000 0.0000 0.0011
March 2020
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