以Caline模式模擬台北市高速公路行駛車輛空氣污染物之排放

Abstract

本研究以通過台北市區內的兩條高速公路為空氣污染釋放源，選定污染物為一氧化碳、二氧化氮及二氧化硫，研究分成兩部份： 第一部分依據93年度兩條國道的總車流量進行排放量推估，國道一號方面，一氧化碳年排放量為1394.3公噸，二氧化氮排放量為2274公噸，二氧化硫為48.91公噸；國道三號方面，一氧化碳排放量為1091公噸，二氧化氮為1521公噸，二氧化硫為37.35公噸。相對台北市而言，兩條國道所釋放出污染物所佔比例為：一氧化碳排放量佔全台北市排放量的3.2%，二氧化氮為23.3%，二氧化硫為5%。 第二部分使用CALINE4線源擴散模式，對國道一號及國道三號排放污染物進行擴散模擬，以國道附近國小為接受點，進行國小學童暴露評估，由於二氧化硫年排放量甚低，無法計算出擴散濃度，因此不予討論，在一氧化碳及二氧化氮的擴散模擬後，發現暴露最高值出現在1月及12月，最低值出現在4月、10月及11月。 研究中並以南港監測站為受體進行推估值與實測值比較，模擬後得到相關係數為0.81，推測國道交通流量與南港測站附近污染物濃度隨著時間變化而具有相關性。

This study defines the two freeways that pass through Taipei City as the air pollution sources with carbon monoxide, nitrogen dioxide and sulfur dioxide selected as the pollutants. This study is divided into two parts: The first part is an estimate of emissions based on the two national freeways’ total traffic volume for 2004. For National Freeway No. 1, the year’s total volume of carbon monoxide emissions was 1394.3 metric tons, the total volume of nitrogen dioxide emissions was 2274 metric tons and the total volume of sulfur dioxide emissions was 48.91 metric tons; for National Freeway No. 3, the total volume of carbon monoxide emissions was 1091 metric tons, the total volume of nitrogen dioxide emissions was 1521 metric tons and the total volume of sulfur dioxide emissions was 37.35 metric tons. For Taipei City, the pollutants released from the two national freeways make up the following proportions: the volume of carbon monoxide emissions make up 3.2% of all Taipei City emissions, nitrogen dioxide emissions make up 23.3% and sulfur dioxide emissions make up 5%. In the second part, the CALINE4 line source dispersion model was used to simulate the spread of pollutant emissions from National Freeway No. 1 and National Freeway No. 3. Elementary schools near the national freeways were used as the receptor points to evaluate the level of exposure experienced by elementary school students. As the total emission volume of sulfur dioxide for the year was extremely low, its dispersion concentration could not be calculated and so was not considered. After modeling the dispersion for carbon monoxide and nitrogen dioxide, it was discovered that the highest exposure rates occurred in January and December, with the lowest rates occurring in April, October and November. During the study the Nangang monitoring station was used as a receptor to compare the projected estimates against the actual measured values. The simulation’s correlation coefficient was 0.81, suggesting that the volume of traffic on the national freeways and the changes in pollutant concentration over time near the Nangang monitoring station are related.