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This study presents a proof-of-concept agent-based model (ABM) of health vulnerability to long-term exposure to airborne particulate pollution, specifically to particles less than 10 micrometres in size (PM10), in Seoul, Korea. We estimated the differential effects of individual behaviour and social class across heterogeneous space in two districts, Gwanak and Gangnam. Three scenarios of seasonal PM10 change (business as usual: BAU, exponential increase: INC, and exponential decrease: DEC) and three scenarios of resilience were investigated, comparing the vulnerability rate both between and within each district. Our first result shows that the vulnerable groups in both districts, including those aged over 65, aged under 15, and with a low education level, increased sharply after 5,000 ticks (each tick corresponding to 1 day). This implies that disparities in health outcomes can be explained by socioeconomic status (SES), especially when the group is exposed over a long period. Additionally, while the overall risk population was larger in Gangnam in the AC100 scenarios, the recovery level from resilience scenarios decreased the risk population substantially, for example from 7.7% to 0.7%. Our second finding from the local-scale analysis indicates that most Gangnam sub-districts showed more variation both spatially and in different resilience scenarios, whereas Gwanak areas showed a uniform pattern regardless of earlier prevention. The implication for policy is that, while some areas, such as Gwanak, clearly require urgent mitigating action, areas like Gangnam may show a greater response to simpler corrections, but aggregating up to the district scale may miss particular areas that are more at risk. Future work should consider other pollutants as well as more sophisticated population and pollution modelling, coupled with explicit representation of transport and more careful treatment of individual doses and the associated health responses.

An Agent-Based Assessment of Health Vulnerability to Long-Term Particulate Exposure in Seoul Districts