Seoul, the capital city of Korea with over 10 million residents, has been experiencing serious air pollution problems. Previous studies on source apportionment of PM2.5 in Seoul are based on measurements of chemical compositions of PM2.5 from a single monitoring site. In this paper, we analyse PM2.5 concentration data collected from multiple sites in 24 districts of Seoul and estimate regional source profiles using Bayesian multivariate receptor model. The regional source profiles provide information for the identification of major PM2.5 sources as well as the regions relatively more seriously affected by each source than other regions. These regional characteristics relevant to PM2.5 can help establish effective, customised, region-specific PM2.5 control strategies for each region rather than general strategies that apply to every region of Seoul.

拥有超过 1000 万居民的韩国首都首尔一直面临着严重的空气污染问题。之前关于首尔 PM2.5 来源分配的研究是基于对单个监测点 PM2.5 化学成分的测量。在本文中，我们分析了从首尔 24 个地区的多个地点收集的 PM2.5 浓度数据，并使用贝叶斯多元受体模型估计区域源概况。区域源概况为识别主要 PM2.5 源以及受每个源影响比其他区域相对更严重的区域提供信息。这些与 PM2.5 相关的区域特征有助于为每个地区制定有效的、定制的、针对特定地区的 PM2.5 控制策略，而不是适用于首尔每个地区的通用策略。