目標：大氣細懸浮微粒（fine particulate matter, PM2.5）濃度可能受交通污染源的影響，本 研究以台灣雲嘉南地區為研究地區，探討大氣PM2.5與交通污染源的關係。方法：分析行政院環 境保護署空氣品質監測站之PM2.5數據及機動車密度登記資料。研究區域為雲林縣、嘉義縣市與 台南市。以敘述性統計（平均值、中位數、最小值和最大值）分析PM2.5濃度、氣象因子與機 動車密度；以斯皮爾曼等級相關（Spearman’s Rank Correlation Coefficient）探討PM2.5濃度、氣 象因子與機動車密度的相關性；以複迴歸分析機動車密度對PM2.5濃度的影響。資料分析期間 為2015年1至12月。結果：2015年雲嘉南地區PM2.5平均濃度為26.4 μg/m3，冷季（11~4月，35.0 μg/m3）高於熱季（5~10月，17.8 μg/m3）。機動車平均密度分別為380.1（汽車）與734.8（機 車）輛/平方公里。機動車密度雖與PM2.5濃度呈正向關係但未達統計顯著，溫度為影響雲嘉南 地區PM2.5濃度之重要因子。機動車密度對PM2.5的影響可能存在區域差異性。台南市：汽車密 度每增加1輛/平方公里，PM2.5增加0.762 μg/m3。嘉義市：機車密度每增加1輛/平方公里，PM2.5 增加0.362 μg/m3。嘉義縣：汽車密度每增加1輛/平方公里，PM2.5增加0.977 μg/m3。雲林縣：汽 車密度每增加1輛/平方公里，PM2.5增加1.030 μg/m3。結論：溫度為影響雲嘉南地區大氣PM2.5濃 度的重要因子。交通污染源對雲嘉南地區PM2.5的影響可能存在區域差異性，值得後續深入探 討。（台灣衛誌 2019；38(1)：19-30）

Objectives: Levels of atmospheric fine particulate matter (PM2.5) may be affected by the traffic sources. This article explores correlations between the PM2.5 level and traffic sources in Yun-Chia-Nan area in Taiwan. Methods: Data regarding PM2.5 levels and motor vehicle density in 2015 were obtained from Environmental Protection Administration monitoring stations and Environmental Resource Database, respectively. The study area covers four southwestern districts of Taiwan: Yunlin County, Chiayi City, Chiayi County, and Tainan City. Mean, median, minimum, and maximum values for PM2.5 levels, meteorological variables, and motor vehicle densities were calculated. The relationship between PM2.5, meteorological variables, and motor vehicle density was estimated using the Spearman’s rank correlation coefficient. A multiple linear regression model was used to explore the associations of PM2.5 with motor vehicle density. The study duration was January–December 2015. Results: In 2015, the annual mean PM2.5 level was 26.4 μg/m3; PM2.5 levels were higher in the colder season (November–April; 35.0 μg/m3) than in the hotter season (May–October; 17.8 μg/m3). The motor vehicle densities were 380.1 car/km2 and 734.8 motorcycle/km2. The relationship between motor vehicle density and PM2.5 level was positive, but nonsignificant. Temperature was the major factor influencing the PM2.5 levels. Moreover, the effects of motor vehicle density on the PM2.5 level varied geographically: for every 1-car/km2 increase, the PM2.5 level increased by 0.762, 0.362, 0.977, and 1.030 μg/m3 in Tainan City, Chiayi City, Chiayi County, and Yunlin County, respectively. Conclusions: Temperature is the major factor influencing PM2.5 levels in Yun-Chia-Nan area in Taiwan. The effect of traffic sources on PM2.5 level might have geographic variation. Further relevant research is warranted. (Taiwan J Public Health. 2019;38(1):19-30)