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Since long-term exposure to PM2.5 is a growing concern in Taiwan, therefore, our study aimed to investigate the association between different PM2.5 concentrations and cause-specific mortalities, as well as explore the influence of demographic, socio-economic, and geographic determinants on mortality. Utilizing a Distributed Lag Non-Linear Model (DLNM), we estimated the PM2.5-attributable mortality burden among the elderly population (above 65 years) in Taiwan from 2005 to 2018. Our analysis considered various thresholds defined by the World Health Organization (WHO) to assess the impact of PM2.5 concentrations, ranging from standard Air Quality Guidelines (AQG) levels (0–15 μg/m3) to higher interim targets (up to 80 μg/m3). Our study reveals that achieving AQG levels (< 15 μg/m3) in Taiwan could potentially prevent 5571 elderly deaths, including 889 deaths from CVDs, 934 deaths from RTIs, and 680 deaths from chronic diseases. We observed a rapid increase in attributable deaths at lower PM2.5 concentrations, with a subsequent marginal increase at higher levels of exposure. We also identified several factors that modify the effects of PM2.5 exposures among elderly. For example, we found that higher elderly population ratios and high-income households were associated with an elevated risk of PM2.5-related deaths. In contrast, higher social welfare expenditure, better availability of medical practitioners per square kilometer, and higher forest-to-land ratios were associated with positive effects, indicating their potential in reducing mortality risk. This study fills a knowledge gap by examining the health consequences of varying PM2.5 levels and explored the complex interplay between demographic, socio-economic, and geographic factors in relation to PM2.5-related mortality. [ABSTRACT FROM AUTHOR]