Abstract
Against the backdrop of accelerating population aging, urban green spaces have become primary venues for elderly daily activities, with their winter thermal comfort emerging as a critical determinant of senior wellbeing. However, existing studies lack quantitative guidelines on how plant characteristics affect thermal comfort, limiting age-friendly design. Thirty representative landscape space sites (waterfront, square, dense forest, and sparse forest) in Beijing’s Zizhuyuan and Taoranting Parks were analyzed through microclimate measurements, 716 questionnaires, and scoring evaluations, supplemented by PET field data and ENVI-met simulations. A scoring system was developed based on tree density, plant traits (height, crown spread), and spatial features (canopy closure, structure, enclosure, and evergreen coverage). Key findings: (1) Sparse forests showed the best overall thermal comfort. Square building spaces were objectively comfortable but subjectively poor, while waterfront spaces showed the opposite. Dense forests performed worst in both aspects. (2) Wind speed and humidity were key drivers of both subjective and objective thermal comfort, and differences in plant configurations and landscape space types shaped how these factors were perceived. (3) Differentiated optimal scoring thresholds exist across the four landscape space types: waterfront (74 points), square building (52 points), sparse forest (61 points), and dense forest (88 points). (4) The landscape space design prioritizes sparse forest spaces, with moderate retention of waterfront and square areas and a reduction in dense forest zones. Optimization should proceed by first controlling enclosure and shading, then adjusting canopy closure and evergreen ratio, and finally refining tree traits to improve winter thermal comfort for the elderly. This study provides quantitative evidence and optimization strategies for improving both subjective and objective thermal comfort under diverse plant configurations.