Vorapat Inkarojrit

Chiang Mai Old City, a cultural heritage site and major tourist destination in Thailand, has significant cultural capital but lacks a well-designed urban lighting system, limiting its nighttime development potential. This issue arises from the absence of an urban lighting master plan, a crucial tool for guiding the city’s growth. The challenge lies in reconciling the diverse perspectives of stakeholders to create a comprehensive lighting master plan that meets shared goals. This research proposes a system dynamics approach to analyze stakeholder complexity. A qualitative, multi-stage method was employed, through in-depth interviews and focus groups with 60 stakeholders from three groups: government, professionals, and end users, to prioritize critical factors. Causal Loop Diagrams (CLDs) were used to illustrate the interrelations among those factors, leading to alternative scenarios for the lighting master plan’s development. The findings demonstrate that safety and security is the top priority, followed by cultural and economic factors. Eleven reinforcing loops and two balancing loops are proposed through CLD visualization. This framework highlights the importance of a participatory process, advocating for a systematic and holistic approach where all stakeholders with diverse perspective collaborate side-by-side in the development of the urban lighting master plan for Chiang Mai Old City.

In Chiang Mai, Thailand, there has been an increasing demand for lighting design strategies that enhance tangible and intangible values of cultural heritage destinations. This research explores the role of lighting design in enhancing the cultural experiences and promoting the cultural tourism of Lanna Buddhist architecture. Suan Dok Temple was selected as a case study due to its historical, social, and cultural significance. This research uses qualitative approaches such as field surveys, photographic documentation, and interviews with temple authorities, cultural heritage experts and tourism professionals for the formulation of initial users’ requirements and lighting design criteria and concept. Data analysis suggested that cultural heritage and conservation, cultural tourism management, and operation and maintenance are important factors in heritage lighting design for cultural tourism. Realistic rendering images of lighting design scenes for the temple’s chedis and vihara are generated based on the concept of luminance layers representing the Buddhist cosmology idea. In addition, lighting operation and installation details are developed and presented to stakeholders for discussion on contextual and operational appropriateness. Finally, the study discusses critical lighting design factors for the development of lighting design solutions for heritage sites, particularly Lanna Buddhist temples, contributing to sustainable cultural tourism.

Capacity building for campus sustainability has been recognized as a process of strengthening the university stakeholders’ skills to minimize the negative impacts of current crises and emerging challenges. While many universities emphasize capacity building through research and education activities, most, if not all, neglect activities for non-academic staff. Without the necessary capacity, the universities might not be able to realize their development plans. To address this issue, Chulalongkorn University developed a capacity building program called “Beyond Leading Changes” in 2021 which consists of three modules. The first aims to provide SDGs knowledge and raise awareness on the local and global challenges. The second focuses on the design thinking process in which participants were asked to empathize, define, and ideate potential solutions to sustainability problems. The last module utilizes the project-based leaning approach in which the skills were developed through engaging projects set around real-world problems. 70 supporting staff from various units completed the program which resulted in many interesting pilot projects that cover a wide range of issues. Nevertheless, the challenge remains to make the program more accessible and inclusive.

The COVID-19 pandemic forced higher education institutions to switch to online learning for most of 2020 and 2021 for the safety of their students and staff, which significantly impacted campus resource consumption. This study aims to analyze the changes in electricity consumption in higher education buildings based on comparisons of three academic years to understand more about the energy implications of the post-COVID-19 era. The electricity data were collected from 181 samples of the electricity meter records at Chulalongkorn University, Thailand. When compared to the typical academic year in 2018, the results indicate that electricity consumption in 2019 and 2020 decreased by 20.92% and 35.50%, respectively. The academic and the library-type buildings marked the biggest change in electricity reduction. The smallest change was found in the research type as its essential work remained on campus. Only electricity consumption in the residence type increased due to the long periods of online learning policies. Finally, the findings suggest that teaching and learning activities have a strong influence on electricity consumption in higher education buildings. The facilities and learning methods related to these activities should be carefully discussed as elements of an effective strategy to manage electricity demands at the university level.

This study presents results from a window blind usage survey and field study that was conducted in California, USA during a period spanning from the vernal equinox to the winter solstice. A total of 113 office building occupants participated in the survey. Twenty-five occupants participated in the field study. In this study, 83 measurements of physical environmental conditions were cross-linked with participants' window blind controlling preferences. A total of 13 predictive window blind control bivariate and multivariate logistic models were derived. As hypothesised, the probability of a window blind closing event increased as the magnitude of physical environmental and confounding factors increased (p < 0.01). The main predictors were window/background luminance level and vertical solar radiation at the window. The confounding factors included MRT, direct solar penetration and participants' self-reported sensitivity to brightness. The results showed that the models correctly predict between 72–89% of the observed window blind control behaviour. This research extends the knowledge of how and why building occupants manually control window blinds in private offices, and provides results that can be directly implemented in energy simulation programs.