A risk-integrated framework for industrial air quality assessment linking dispersion modeling and health-based environmental pressure indicators.

The textile industry is a major contributor to Indonesia's manufacturing sector and a significant source of industrial air pollution. However, approaches that integrate pollutant dispersion with health-oriented environmental indicators remain limited. A risk-integrated framework for air quality assessment is developed by linking Gaussian plume dispersion modeling with a health-weighted Atmospheric Environmental Pressure Index (AEPI). The framework combines modeled pollutant concentrations with hazard quotient (HQ)-based normalization to evaluate cumulative environmental pressure in relation to potential health implications. The approach was applied to a textile manufacturing facility in Central Java, Indonesia, using emission inventory data, ERA5 meteorological datasets (2015-2024), and ambient measurements from six receptor locations. The results indicate that predicted pollutant concentrations comply with Indonesia's National Ambient Air Quality Standards (Government Regulation No. 22/2021), while PM2.5 levels exceed World Health Organization (WHO, 2021) guideline values. AEPI values of 0.06 (baseline), 0.08 (predicted), and an incremental increase of 0.02 fall within the "very low atmospheric pressure" category, with particulate matter (PM2.5 and PM10) identified as the dominant contributor. These findings suggest that compliance with national standards does not necessarily reflect health-based air quality conditions. By linking dispersion modeling with risk-weighted indexing, the proposed framework provides a more nuanced interpretation of pollutant contributions and environmental pressure. Rather than aiming for broad generalization, this study demonstrates the applicability of a transferable modeling index framework for predictive and health-oriented air quality assessment, particularly in data-limited industrial settings.