Abstract
Trees can reduce heat radiation for adjacent farmhouses, achieving cooling and energy-saving effects in summer. However, there is still a lack of research on the quantitative influence of trees’ parameters and their spatial orientation on the cooling load of farmhouses. This knowledge gap hampers the scientific greening of residences from an energy-efficiency perspective and leads to wasted ecological benefits. Taking Gao Hong Town’s residences in China as an example, by comprehensively applying remote sensing technology, frequency statistics, and numerical simulation, the representative tree-farmhouse information model was constructed. The ENVI-met software was used to simulate and extract the temperatures of external walls under 54 scenarios. The Radiant Time Series Method (RTSM) was then used to calculate peak cooling load with trees under different scenarios. Sensitivity analysis indicates that trees on the south side have the most significant impact on the disturbance rate of peak cooling load of trees to farmhouses (PCLTD), reaching up to 4.4 %, followed by the west, east, and north sides with PCLTD of 1.6 %, 1.1 %, and 0.8 %, respectively. According to the sensitivity of the minimum distance between wall and tree canopy (DW-T) to PCLTD, the 1 m-5 m range of DW-T can be divided into three zones: high-sensitivity (1 m-2 m), medium-sensitivity (2 m-4 m), and low-sensitivity (4 m-5 m).For trees on the south side with leaf area density (LAD) of 1 m2/m3, 2 m2/m3, and 3 m2/m3, the corresponding PCLTD are 3.4 %, 4.4 %, and 4.9 %; for Diameter of Tree Canopy (DC) of 5 m, 7 m, and 9 m, the respective PCLTD are 4.4 %, 6.2 %, and 8.3 %.To maximize the energy-saving effects of trees on farmhouses, it is recommended that the DW-T for trees on the south be less than 3 m, and for trees on the west and east, less than 2 m.These findings support optimizing tree planting strategies adjacent to rural residences in China from an energy-saving perspective, contributing to the improvement of thermal environments and the assessment of energy efficiency.
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