Evaluation Methods and Optimization Strategies of Thermal Comfort in Pediatric Outpatient Departments of Hospitals in the Hot-Summer Cold-Winter Zone

Abstract

Children represent the future of humanity, and creating a healthy and comfortable medical environment for them has become a globally shared concern. Pediatric outpatient departments are among the busiest areas in hospitals, and a comfortable thermal environment is essential for stabilizing the emotions of pediatric patients and maintaining their health. Currently, commonly used thermal comfort evaluation models are primarily developed based on adult subjects and are often unsuitable for children. Moreover, hospital thermal environments are typically regulated by Heating, Ventilation and Air Conditioning (HVAC) systems, which account for the largest share of energy consumption in hospitals, presenting substantial energy-saving potential. Consequently, building energy efficiency and financial considerations are critical criteria when optimizing the thermal comfort of pediatric departments. The hot-summer cold-winter (HSCW) zone is one of the most densely populated areas in China with the highest medical demands. Its pronounced seasonal climate variations further exacerbate indoor thermal comfort challenges. It is therefore imperative to develop thermal comfort evaluation models specific to pediatric outpatient departments in the HSCW zone and formulate optimization strategies based on multi-criteria decision-making (MCDM). While existing studies have focused on children’s thermal comfort in educational buildings, research on hospital buildings is limited. Evaluation methods and optimization strategies for thermal comfort in pediatric outpatient departments are underdeveloped. This study took the pediatric outpatient department of Jiangsu Women and Children Health Hospital (JWCHH) as a case and followed the framework of "clarifying research objectives → developing evaluation models → identifying optimization measures → prioritizing optimization strategies" to conduct the research.

(1) Analyzing the progress and gaps in research on thermal comfort in pediatric outpatient departments in hospital buildings. A systematic literature review was conducted to analyzed 161 studies in three aspects, including evaluation of children's indoor thermal comfort, thermal comfort evaluation in hospital buildings, and thermal comfort optimization in hospital buildings. This analysis clarified the progress and gaps in existing research, providing a theoretical foundation for this study and identifying key issues that need to be addressed.

(2) Developing adaptive thermal comfort evaluation models for different occupant groups in the pediatric outpatient department. Based on differences in age, health status, and behavioral characteristics, the occupants in the pediatric outpatient department were categorized into preschool children, school children, adolescents, febrile children, visitors, and hospital staff. Clothing insulation and thermal response distributions were collected for these groups, and their metabolic rates were calculated. Adaptive thermal comfort evaluation models were then developed for each group, identifying the comfort temperature ranges of the outpatient department as 18.24°C–19.84°C during the heating season, 19.07°C–22.67°C during the transitional season, and 23.20°C–25.02°C during the cooling season.

(3) Developing a real-time individual thermal comfort evaluation model based on visual data. Using computer vision techniques, this study integrated infrared images and visible images of individual occupants wearing surgical masks to generate temperature features. These features, combined with indoor operative temperature (T_op) values, were used to develop a real-time individual thermal comfort evaluation model using random forest (RF), support vector machine (SVM), and k-nearest neighbors (KNN) algorithms. Among these, RF demonstrated the highest prediction accuracy for thermal responses.

(4) Identifying group-level and individual-level thermal comfort optimization measures for the pediatric outpatient department. Through literature review and Delphi method, thermal comfort optimization measures suitable for the pediatric outpatient department were identified at both group and individual levels. For group-level measures, Latin hypercube sampling was further conducted, followed by sensitivity and redundancy analyses of thermal comfort and building energy consumption indicators. The results selected changing cooling and heating setpoints of HVAC systems and adding ground insulation layer as key group-level optimization measures.

(5) Developing an MCDM model for prioritizing strategies integrating group-level and individual-level optimization measures. An evaluation indicators system for thermal comfort optimization strategies was constructed, incorporating thermal comfort, energy consumption, and financial dimensions. Evaluation indicator quantification methods for group-level and individual-level optimization measures were developed, and an AHP-Entropy-TOPSIS method was employed to construct the MCDM model. The results indicated that HVAC occupant-centric control (OCC) effectively optimized indoor thermal comfort, personal comfort systems (PCS) reduced inter-individual thermal sensation differences, and building envelope retrofitting should be combined with other optimization measures for effective implementation.

This study developed adaptive thermal comfort evaluation models for occupant groups, and constructed vision-based thermal comfort evaluation models for individual occupants in the pediatric outpatient department. Additionally, an MCDM model for prioritizing thermal comfort optimization strategies was established. The findings provide valuable insights for evaluating and optimizing thermal comfort in the pediatric outpatient departments of hospitals in the HSCW zone, contributing to the creation of comfortable and healthy medical environments for children.

Date of Award	28 Jul 2025
Original language	English
Awarding Institution	City University of Hong Kong
Supervisor	Shiu Tong Thomas NG (Supervisor) & Dezhi Li (External Supervisor)