車流量與空氣細懸浮微粒相關性分析

Exploring the Relationship between the Traffic Flow and the Ambient Particulate Matter 2.5 Concentration

張展維(Zhen-Wei Zheng)

指導教授 ： 戴榮賦

國立暨南國際大學/管理學院/資訊管理學系/碩士(2017年)

摘要

本研究有鑑於台灣空汙議題不斷地延燒，而專家指出有7成的污染都來自境內，但都無法明確的指出汙染源，所以本研究針對境內主要汙染源之一的車輛廢氣排放，來做偵測來研究車流量與PM2.5的相關性分析。本研究應用影像處理技術即時追蹤路上的車流量，並且同時偵測路上的PM2.5的濃度了解兩者的相關性。

不分組的整體數據呈現顯著中度相關，相關性r值為0.338，表示車流量對PM2.5有一定的影響力。根據環保署每日空氣品質指標(Daily Air Quality Index, DAQI)的細懸浮微粒(PM2.5)預警濃度分級，而24 μg/m3 - 35 μg/m3為第三級距，超過此級距以上就會達到警示標準，故以此級距來區分濃度分嶺的標準。將數據區分為高濃度與低濃度組時，高濃度組的相關性r值為0.433，較不分組時相關性更高，而低濃度組卻無顯著相關。低濃度組不相關的可能原因是，數據的收集時前一兩日有下過大雨，當時PM2.5數值都在10 μg/m3以下。

關鍵字

空汙 ； PM2.5 ； 影像處理 ； 車流量

並列摘要

The issue of air pollution continues in Taiwan. Experts have pointed out that 70% of the sources of pollution come within the territory, but they cannot be accurately identified. Therefore, this study detected the exhaust emissions of vehicles, one of the major sources of pollution in Taiwan, to adopt a correlation analysis of traffic flow and PM2.5. It applied image processing technique to supervise real-time traffic flow, and it also detected the PM2.5 concentration on the road to understand the correlation between the two.

The ungrouped overall data were of significant moderate correlation, and value R was 0.338, which showed that traffic flow had a certain impact on PM2.5. According to the PM2.5 Warning Concentration Grading Standard in the Daily Air Quality Index (DAQI) published by the Environmental Protection Administration, the third class interval was from 24 μg/m3 to 35 μg/m3. It would reach the warning standard once it was above the third class interval, which was therefore used as the standard to differentiate the concentration. After dividing the data into high concentration and low concentration, it was shown that the value R of the high concentration group was 0.433, which was higher than that of the ungrouped data, while the low concentration group did not show significant correlation. The possible reason to explain the non-correlation was that there had been heavy rain one or two days before data collection. The PM2.5 at that time was under 10 μg/m3.

並列關鍵字

Air pollution ； PM2.5 ； Image processing ； Traffic flow

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