許多研究已證實空氣污染會對人類造成嚴重的健康危害，特別是對社會經濟弱勢族群的影響往往特別嚴重。歐洲及美國的研究也表明在不同種族、族裔或地區之間的空污暴露差異或不平等現象，並沒有隨著現今污染物濃度的降低而減少，反而持續存在或擴大。然而，在亞洲，探討臺灣空污不平等的量化研究相當稀少，並且缺乏準確的空污推估模型來進行分析。近年來，受惠於人工智慧技術的進展與電腦運算能力的大幅提升，地理人工智慧(Geospatial-Artificial Intelligence, Geo-AI)成為空氣污染推估的新興方法。
因此，本研究以Geo-AI模型所推估之日間臭氧(Ozone, O3)、二氧化氮(Nitrogen Dioxide, NO2)、細懸浮微粒(Fine Particulate Matter, PM2.5)之時空模擬結果為基礎，探討2012年至2019年雲嘉南三縣市不同社會經濟人口群體所暴露的空污濃度差異，並且使用吉尼係數、平均對數偏差、絕對不平等和相對不平等指標來分析不平等趨勢。除此之外，我們也使用時空立方體(Space-Time Cube)和新興熱區分析(Emerging Hot Spot Analysis)來視覺化空氣污染的長期冷熱區變化趨勢。研究結果發現社會經濟人口較弱勢的群體暴露較高的日間O3濃度，但暴露在較低的NO2與PM2.5濃度；社會經濟人口較優勢的群體暴露較低的日間O3濃度，但暴露在較高的NO2與PM2.5濃度。此外，空污不平等的趨勢並沒有隨著濃度下降而降低。研究成果將有助於政府相關單位制訂更精準的空污減排策略。

Many studies have confirmed that air pollution poses serious health risks to humans, and its impacts are often particularly severe on socioeconomically disadvantaged groups. However, in Asia, quantitative studies on air pollution inequality in Taiwan are relatively scarce. Our study uses spatiotemporal simulation results of daytime ozone (O3), nitrogen dioxide (NO2), and fine particulate matter (PM2.5) estimated by the Geo-AI model to examine the differences in air pollution exposure among socioeconomic population groups in Yunlin, Chiayi, and Tainan counties from 2012 to 2019. Inequality trends are further analyzed using the Gini coefficient, mean log deviation, slope index of inequality, and relative index of inequality. In addition, we apply the Space-Time Cube and Emerging Hot Spot Analysis to visualize the long-term variations of air pollution hot and cold spots. In the results of the Emerging Hot Spot Analysis, we found that daytime O3 exhibited multiple long-term hot spots in coastal areas. NO2 displayed several long-term hot spots in urban areas. The analysis of air pollution exposure inequality further revealed that socioeconomically disadvantaged groups are exposed to higher daytime O3 concentrations but lower NO2 and PM2.5 concentrations, while socioeconomically advantaged groups are exposed to lower daytime O3 concentrations but higher NO2 and PM2.5 concentrations. Moreover, exposure inequality did not decline in parallel with reductions in pollutant concentrations. These findings provide critical insights to support governmental agencies' development of more targeted air pollution control strategies.

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