臺灣交通源空氣污染物之排放特徵與排放特性描述：以自強隧道實驗為例

Characteristics of Traffic Pollutants in Ziqiang Tunnel, Taiwan

洪伯彰(Po-Chang Hung)

指導教授 ： 蕭大智

國立臺灣大學/工學院/環境工程學研究所/碩士(2020年)

https://doi.org/10.6342/NTU202003999

摘要

隨著都市化的發展，民眾對於交通的需求量也逐漸增加，導致交通排放已成為大氣環境中粒狀污染物排放的主要來源之一。根據行政院環保署的空氣排放清冊(TEDS 10.0)所示，交通車輛的排放占細懸浮微粒(PM2.5)總排放量的26.29%。根據公共衛生的相關文獻指出若長期暴露於高濃度的PM2.5環境中會導致呼吸道疾病、氣喘及心血管疾病發生，甚至會提高死亡風險。由此可知分析交通污染源的排放特徵、建立及更新交通污染源的排放清單及評估其PM的毒性等，對於政府機關未來建立相關交通污染排放管制政策、法規或更新空氣污染物排放清單極其重要。
本研究藉由調查臺北市自強隧道的污染物，了解臺灣交通源空氣污染物之排放特徵與排放特性。自強隧道長度為819公尺，屬於臺北市公路中最長的隧道。本研究使用簡易空氣品質量測儀(Low-Cost Sensor, LCS)、七波段氣膠吸光儀(Aethalometer, Magee, AE33)以及口袋型微粒黑碳監測儀（MicroAeth®MA350）來量測隧道進、出口的微粒與等效黑碳(equivalent Black Carbon, eBC)的質量濃度。這些儀器皆具有高時間解析度，可以觀察隧道內部污染物隨著時間的變化趨勢。除此之外，本研究還建立了一套移動式系統，用於量測污染物隨著自強隧道下風處距離的變化趨勢。同時也使用PM2.5採樣器來進行濾紙採樣，並且透過ROS實驗，以DTT反應速率推定氧化潛勢，進一步分析交通源PM的潛在毒性。
根據研究結果顯示，在自強隧道內重型車車流會主導PM1.0與eBC濃度的變化，而轎車和機車則是會主導隧道內CO與CO2的濃度變化，其主要原因在於柴油與汽油引擎的燃燒機制不同而導致。而在eBC的分析數據中，本研究所建立的出口端AAE指數約在1.1~1.3之間，並且發現AAE的變化與隧道內重型車的占比之間具有中度的相關性(R=0.49)，且遠高於其他兩類車種。在移動式系統的實驗過程，我們發現eBC的濃度具有明顯的濃度衰減作用，但在氣狀污染物(CO、CO2)方面卻沒有該現象產生，此可歸因於隧道內涵洞所產生的微粒損失機制。
在排放因子的計算中，本研究所建立的排放因子相對於其他隧道略低，這可能與地理環境、年代、車種不同抑或是隧道內涵洞的作用…等因素所導致。除此之外，自強隧道中具有較高的CO排放因子，這可能是因為自強隧道中機車車流的占比很高，而機車通常會排放出更高濃度的CO。而在多元線性迴歸中，本研究發現重型車的PM1.0與eBC的排放因子最大，而轎車與機車的CO、CO2排放因子則高於重型車，此數據與濃度和車流的相關性分析結果吻合。
最後在ROS的實驗分析當中，本研究透過OPDTT作為PM毒性指標，在OPDTTv數值在出口端大於入口端，但是OPDTTm卻相反，我們推測可能是因為新鮮的交通污染物其毒性較低進而導致出口端的OPDTTm較低，但因出口端的PM2.5濃度較高使得整體OPDTTv依舊上升。而在OPDTTV的多元線性迴歸中，重型車為最大貢獻者，其可能原因分別為：(1)重型車往往能釋放出更高的PM2.5質量濃度；(2)柴油引擎所釋放的PAHs與n-alkanes碳鏈較短、分子量較低，因此較容易溶於水形成WSOC進而使OPDTTv上升。但若以整體上來敘述，我們也可以發現轎車與重型車的毒性排放貢獻卻是相近的，可說明轎車的毒性排放也是不可忽視的一環。

關鍵字

隧道 ； 交通源空氣污染物 ； 排放因子 ； 多元線性迴歸 ； PM毒性指標

並列摘要

The emission of traffic pollution sources is one of the main reasons for the generation of aerosol particles in the atmospheric environment. According to TEDS 10.0, the emissions of transportation vehicles account for 26.29% of the total emissions of fine particle matter (PM2.5). Public health studies have indicated that if long-term exposure in the high concentration of PM2.5, it will cause adverse to human health, sush as：cardiovascular disease, respiratory tract disease, asthma and increase the risk of death. Therefore, analying the emission characteristics、uqdate emission factors (EFs) and evaluate the toxicity of PM of traffic pollution sources is extremely important for government agencies to establish relevant traffic pollution emission control policies, regulations or update air pollutant emission datas in the future.
The objective of this research is to investigate the characteristics of traffic pollution in the Ziqiang tunnel which is the longest highway tunnel in the Taipei city (not included the freeway tunnel). We used the low-cost sensor 、 Aethalometer (Mangee, AE33) and The microAeth ® MA350 to measure the particle matter mass concentration and equivalent black carbon (eBC) at the entrance and exit of tunnel. These instruments have good time resolution can completely see the trend of pollutants concentration in the tunnel over the time. At the same time, we also employed the PM2.5 samplers to do filter sampling and did the ROS experiment. In addition to this, we also builded the mobile system which start up in the morning、afternoon and night to analyze the relationship between the concentration of pollutant and the downwind distance of tunnel.
The results indicate that the heavy duty vehicles dominated the PM1.0 and eBC concentration variation in the Ziqiang Tunnel. But in the concentration variation of CO and CO2 the automobile and motorcycle are the main contributor. This results can be explained by the difference combustion mechanism between diesel and gasoline engines. The AAE was established by 1.1~1.3, and found that the proportion of heavy duty vehicle in the traffic fleet have moderately correlated to the AAE variation. In the mobile system, we observed the eBC concentration will be markedly decreased in front of adits but the opposite of gaseous pollutants which showed a steady concentration growth with the tunnel distance. This can be attributed to the particle loss mechanism produced by the adits of the tunnel.
The EF for the Ziqiang Tunnel was slightly lower than other tunnels, which may be associated with the differences of country、vehicle fleets、tunnel environment and the concentration loss by adits. Additionally, the higher EFCO was be found in the Ziqiang Tunnel because of the proportion of motorcycle was more than other tunnel study. In the multiple linear regression, we found theat the EFPM1.0 and EFeBC of heavy duty vehicles are the largest, while the EFCO and EFCO2 of automobiles and motorcycle are higher than that of heavy duty vehicles. It is consistent with paragraph three result.
In the ROS analysis, we discovered the toxicity of PM probable decrease with the tunnel distance. It caused the OPDTTm at the exit was lower than entrance OPDTTm, however the exit OPDTTv still higher than entrance value because of the difference of PM concentration. Finally, the EF of OPDTTv indicate that the heavy duty vhicle is the main contributor. There are two points worth attention：(1) Heavy duty vehicles tend to emission higher PM2.5 mass concentration；(2) PAHs and n-alkanes released by diesel engine have shorter carbon chains, they are easier to dissolve in water to form water soluble organic carbon (WSOC) and will be responsible for transform to OPDTTv. However we can find that the total toxic emission contributions of automobile and heavy duty vehicle are similar.

並列關鍵字

Tunnel ； Traffic pollution ； Emission factor ； Multiple linear regression ； ROS

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