本文選題：道路交通 + PM_(2.5)��； 參考：《福建農林大學》2017年碩士論文

【摘要】：近年來,PM2.5(細顆粒物)已經成為我國空氣質量的首要影響因素。而交通活動造成的顆粒物排放已成為城市大氣污染的重要來源之一。本研究擬以莆田市8座環(huán)境監(jiān)測站數據為基礎,利用GIS對莆田市8座監(jiān)測站數據進行空間插值,對莆田市主城區(qū)顆粒物濃度空間分布情況進行分析。以不同的道路綠化模式的典型路段為研究對象,對這些道路路側環(huán)境中的顆粒物、氣象參數以及路段車量等進行監(jiān)測。在此基礎上,通過對不同綠化模式、不同車流量條件下的道路環(huán)境顆粒物污染的對比,尋找不同車流量條件下道路環(huán)境顆粒物污染的規(guī)律,同時為探討一種較好的道路綠化模式提供科學依據。主要研究結果如下:(1)莆田市城區(qū)全年顆粒物濃度均處于較低水平;春、冬兩季的PM10(可吸入顆粒物)和PM2.5的平均濃度值明顯高于夏、秋兩季;荔城區(qū)監(jiān)測點位顆粒物污染最為嚴重;東圳水庫監(jiān)測點位顆粒物濃度最低;遠離城區(qū)、綠化和植被覆蓋好,及鄰近水域的地區(qū)顆粒物濃度較低;風速與PM10濃度呈正相關性,而與PM2.5濃度之間存在強烈的負相關性;溫度與PM10和PM2.5濃度均呈現(xiàn)明顯的負相關關系;相對濕度與PM10和PM2.5濃度呈負相關性。(2)本文分別使用傳統(tǒng)車流量以及基于排放因子的車流量計算方式對車流量進行統(tǒng)計,發(fā)現(xiàn)基于排放因子的標準化車流量與顆粒物濃度的相關性更好;PM2.5的濃度與車流量的相關性較好,而PM1(可入肺顆粒物)、PM10和TSP(總懸浮顆粒物)的濃度與車流量的相關性較差;對車流量及顆粒物濃度的時間分布進行分析,發(fā)現(xiàn)由于顆粒物的擴散需要一定的時間,顆粒物濃度的變化相對交通量有一定的延后性;根據監(jiān)測站周邊交通量大小以及繁華度從高到低將8座空氣自動監(jiān)測子站分為三類,發(fā)現(xiàn)顆粒物污染較嚴重的區(qū)域的主要特征為交通發(fā)達、人類活動頻繁;對于不同等級道路,PM10及TSP濃度呈現(xiàn)出主干道次干道支路;而PM1及PM2.5的濃度呈現(xiàn)出次干道主干道支路;莆田市城區(qū)節(jié)假日與工作日顆粒物濃度變化情況有很大的區(qū)別,而車流量在節(jié)假日明顯降低,平均降幅達到了 13.44%;顆粒物濃度水平也有明顯的降低,特別是PM10和TSP,降幅分別達到了 35.36%和39.09%,呈現(xiàn)出明顯的"節(jié)假日效應"。(3)"喬-灌-草"配置模式的道路路側綠化帶對各個粒徑顆粒物濃度的削減作用最高;PM1和PM2.5的污染源相似,而PM10和TSP則是來自于另外的相似污染源;道路路側綠化帶對不同粒徑的顆粒物的削減率不同,大小依次為:TSPPM10PM2.5PM1。道路路側綠化帶對粒徑較大的顆粒物有較好的阻擋及吸附作用,"喬-灌-草"模式對PM10和TSP的削減率達到了 44.9%和43.7%。而對小粒徑顆粒物的凈化效果較差。
[Abstract]:In recent years, PM2.5 (fine particulate matter) has become the primary influence factor of air quality in China. Particulate matter emissions caused by traffic activities have become one of the important sources of urban air pollution. Based on the data of 8 environmental monitoring stations in Putian City, the spatial distribution of particulate matter concentration in Putian City is analyzed by using GIS to interpolate the data of 8 stations in Putian City. Taking typical road sections with different road greening models as the research object, the particles, meteorological parameters and traffic volume of these road side environments were monitored. On this basis, through the comparison of road environmental particulate pollution under different greening modes and different vehicle flow conditions, the laws of road environmental particulate pollution under different traffic flow conditions are explored. At the same time, it provides a scientific basis for exploring a better road greening mode. The main results are as follows: (1) the average concentrations of PM10 (respirable particulate matter) and PM2.5 in spring and winter were significantly higher than those in summer and autumn. The concentration of particulate matter was the lowest in Dongzhen Reservoir, far away from the urban area, the greening and vegetation coverage was good, and the concentration of particulate matter in the adjacent waters was lower, and the wind speed was positively correlated with the concentration of PM10. However, there was a strong negative correlation between temperature and PM2.5 concentration, and there was a significant negative correlation between temperature and PM10 and PM2.5 concentration. There is a negative correlation between relative humidity and PM10 and PM2.5 concentration. (2) in this paper, the traditional traffic flow and the calculation method based on emission factor are used to calculate the traffic flow. The results showed that the correlation between the concentration of PM2.5 and the concentration of PM _ (2.5) was better than that of the concentration of PM _ (1) and tsp (total suspended particulate matter). By analyzing the time distribution of vehicle flow and particle concentration, it is found that the change of particle concentration has a certain delay because the diffusion of particulate matter takes a certain time. According to the traffic volume around the monitoring station and the degree of prosperity from high to low, eight air automatic monitoring sub-stations can be divided into three categories. It is found that the main characteristics of the area with serious particulate pollution are developed traffic and frequent human activities. The concentration of PM10 and tsp in different grades of roads showed sub-trunk roads, while the concentrations of PM1 and PM2.5 showed sub-trunk roads, and the concentration of particulate matter in Putian city was different from that in working days. On the other hand, the traffic flow significantly decreased during the holidays, with an average drop of 13.44%. The level of particulate matter concentration also decreased significantly. Especially for PM10 and TSPs, the decreases were 35.36% and 39.09%, respectively, showing obvious "holiday effect". (3) the pollution sources of PM1 and PM2.5 were similar to those of "Arbor, Irrigation and Grass" allocation mode. But PM10 and tsp come from other similar pollution sources, and the road side green belt has different reduction rate of different particle size, the order is: TSPPM10PM2.5PM1. The green belt on the side of the road has a good blocking and adsorption effect on the larger particle size. The reduction rates of PM10 and tsp in the "Joe Irrigation Grass" model have reached 44.9% and 43.7% respectively. However, the purifying effect of small particle size was poor.
【學位授予單位】：福建農林大學
【學位級別】：碩士
【學位授予年份】：2017
【分類號】：X513;X73

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