Multi-factor coupled optimization of indoor air quality and human health exposure in traditional dwellings based on passive strategies

Abstract People spend approximately 90% of their time in indoor environments, making indoor air quality (IAQ) a critical factor influencing human health and overall well-being. However, traditional dwellings in western Sichuan, China, still rely heavily on biomass combustion as the primary source of heating. This practice leads to elevated concentrations of indoor pollutants and generally poor IAQ, posing considerable health risks to residents, particularly during the cold and transitional seasons. To address this issue, the present study adopts a passive design perspective and employs an interdisciplinary research framework that integrates field measurements with computational simulation modeling. The objective is to systematically identify the key passive factors affecting IAQ and to develop an effective multi-factor coupled optimization strategy. Three representative passive variables were examined, and the results indicate that the window-to-wall ratio is the most influential factor governing indoor CO 2 levels. Furthermore, the analysis shows that optimizing any single factor provides only limited improvement, whereas a multi-factor coupled strategy yields a substantial reduction in indoor CO 2 concentration—up to 64%. Based on these findings, the study proposes a passive IAQ optimization approach specifically tailored to traditional Banbi-style dwellings in northwest Sichuan. This approach demonstrates significant potential for improving IAQ, and the methodology offers valuable guidance for passive environmental optimization in traditional buildings located in regions with similar climatic and socioeconomic conditions.