This study evaluates the health effects of long-term exposure to PM10 in Seoul. Building on the preliminary model Shin and Bithell (2019), an in-silico agent-based model (ABM) is used to simulate the travel patterns of individuals according to their origins and destinations. During the simulation, each person, with their inherent socio-economic attributes and allocated origin and destination location, is assumed to commute to and from the same places for 10 consecutive years. A nominal measure of their health is set to decrease whenever the concentration of PM10 exceeds the national standard. Sensitivity analysis on calibrated parameters reveals increased vulnerability among certain demographic groups, particularly those aged over 65 and under 15, with a significant health decline associated with road proximity. The study reveals a substantial health disparity after 7,000 simulation ticks (equivalent to 10 years), especially under scenarios of a 3% annual increase in pollution levels. Long-term exposure to PM10 has a significant impact on health vulnerabilities, despite initial resilience being minimal. The study emphasises the importance of future research that takes into account different pollution thresholds as well as more detailed models of population dynamics and pollution generation in order to better understand and mitigate the health effects of air pollution on diverse urban populations.

翻译：本研究评估了首尔长期暴露于PM10对健康的影响。基于Shin和Bithell（2019）的初步模型，采用计算机模拟的基于智能体模型模拟个体根据其出发地与目的地的出行模式。在模拟过程中，每个个体以其固有的社会经济属性及分配的出发地与目的地位置，假定连续10年在相同地点间通勤往返。当PM10浓度超过国家标准时，其名义健康指标将相应降低。对校准参数的敏感性分析显示，特定人口群体（尤其是65岁以上及15岁以下人群）脆弱性增加，且道路邻近性与显著健康衰退相关。研究表明，在模拟运行7000步（相当于10年）后，特别是在污染水平年均增长3%的情景下，健康差距显著扩大。尽管初始抵抗力极小，长期PM10暴露仍对健康脆弱性产生重大影响。本研究强调未来研究需考虑不同污染阈值以及更精细的人口动态与污染生成模型，以更好地理解并减轻空气污染对多样化城市人口的健康影响。