# Site-Dependent Dynamic Life Cycle Assessment of Human Health Impacts from Industrial Air Pollutants: Inhalation Exposure to NOx, SO2, and PM2.5 in PVC Window Manufacturing

## TL;DR

This paper introduces a new method to assess health risks from air pollutants in PVC window manufacturing by considering local conditions and exposure patterns.

## Contribution

A site-dependent dynamic LCA framework integrating ESPA and atmospheric modeling to capture exposure-driven health impacts.

## Key findings

- The framework identifies hotspots and periods of elevated exposure to NOx, SO2, and PM2.5.
- Health impacts are quantified in DALYs, showing populations at greatest risk.
- The method improves LCA accuracy for industrial planning and operations.

## Abstract

Industrial air emissions are major contributors to human exposure to toxic pollutants, posing significant health risks. Life cycle assessment (LCA) is increasingly used to quantify human toxicity impacts from industrial processes. Conventional LCA often overlooks spatial and temporal variability, limiting its ability to capture actual inhaled doses and exposure-driven impacts. To address this, we developed a site-dependent dynamic LCA (SdDLCA) framework that integrates conventional LCA with Enhanced Structural Path Analysis (ESPA) and atmospheric dispersion modeling. Applied to the production of double-glazed PVC windows for a residential project, the framework generates high-resolution, site-specific emission inventories for three key pollutants: nitrogen oxides (NOx), sulfur dioxide (SO2), and fine particulate matter (PM2.5). Local concentration fields are compared with World Health Organization (WHO) air quality thresholds to identify hotspots and periods of elevated exposure. By coupling these fields with the ReCiPe 2016 endpoint methodology and localized demographic and meteorological data, SdDLCA quantifies human health impacts in Disability-Adjusted Life Years (DALYs), providing a direct measure of inhalation toxicity. This approach enhances LCA’s ability to capture exposure-driven effects, identifies populations at greatest risk, and offers a robust, evidence-based tool to guide industrial planning and operations that minimize health hazards from air emissions.