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    Please use this identifier to cite or link to this item: http://ir.lib.ncu.edu.tw/handle/987654321/73874


    Title: 雲林斗六PM2.5濃度變化與氣膠光學特性及氣象條件之關聯性研究
    Authors: 陳柏霖;Chen, Po-Ling
    Contributors: 大氣科學學系
    Keywords: 氣膠光學特性;光達;太陽光度計;垂直大氣穩定度
    Date: 2017-08-24
    Issue Date: 2017-10-27 12:28:10 (UTC+8)
    Publisher: 國立中央大學
    Abstract: 雲林縣近三年(2013-2015年)為全台灣污染最嚴重之縣市,轄區內之斗六地區污染源眾多,污染成因及氣膠種類複雜,因此本研究於較少受境外傳送污染影響之秋季,分析斗六及鄰近區域2005-2015年長期區域PM2.5濃度時空分布特性及與氣象因子相關性,於2015年秋季觀測期間進一步以氣膠光學儀器分析斗六地表和垂直氣柱氣膠光學特性,配合氣膠垂直分布及氣象條件資訊,希望解釋影響斗六地區地表氣膠濃度及特性之因素。

    分析2005-2015年秋季斗六、崙背、台西空品站PM2.5濃度日平均值顯示斗六PM2.5濃度最高,台西最低,但污染事件日PM2.5濃度增加比例以台西最多,斗六最少,三站PM2.5濃度逐年下降,斗六下降趨勢最為明顯,PM2.5濃度小時值顯示斗六PM2.5濃度於日間上升夜間下降,台西站於夜間上升日間下降,為海陸風環流造成之差異。斗六站PM2.5濃度日平均與相對濕度、風速、溫度、垂直大氣穩定度相關係數(r)值分別為-0.30、-0.29、-0.18、0.19,四變數線性回歸R2值為0.22,代表上述氣象條件變異對PM2.5濃度變化造成22 %之影響。

    由2015年觀測期間結果分析氣象條件對氣膠特性之影響,顯示相對濕度、風速、溫度與吸光性氣膠相關性較散光性氣膠佳,於污染事件日溫度與吸光係數r值達0.63,氣象條件於污染事件日時對氣膠粒徑有較大影響,r值分別為-0.60、0.50、0.56。分析垂直氣柱氣膠光學厚度(AOD)與地面PM2.5濃度相關性為正相關,但兩者於污染事件日為負相關,推測平時斗六地區主要污染源為當地排放和短程近地表傳送,污染事件日時可能有較多高空污染物影響地表,此現象可以由光達垂直氣膠分布發展特徵解析出來,而觀測期間PM2.5濃度與邊界層頂高度成正相關,亦說明垂直混和作用較強、地表與高空大氣交換較多時,PM2.5濃度較高。個案分析結果顯示,造成斗六地表污染PM2.5濃度提升之原因為:地表污染排放、海陸風環流輸入沿海地區污染物、夜間高空殘餘層於日間因對流作用下降至地表、垂直大氣穩定度高使污染物不易擴散,以上結果可作為日後地表污染預報及防治之參考。
    ;In the last three years (2013-2015), the most serious air pollution county in Taiwan is Yunlin. Douliu city, the capital of Yunlin, has many emission sources of particulate matter indicating complicated aerosol environment. In this study, we use 10 years (2005-2015) PM2.5 data of Douliu aera in autumn to analysis its temporal variation, spatial distribution and correlation with meteorology conditions. Aerosol data obtaining from an experiment in 2015 autumn at Douliu city has been used to further analyze aerosol vertical distribution and aerosol optical properties in both surface and vertical column. We try to use meteorology data, aerosol vertical distribution and the aerosol optics both at surface and vertical column to understand what the reason of aerosol concentration and the deterioration of air quality in Douliu city in autumn.

      The daily mean PM2.5 concentrations for Taixi, Lunbei, and Douliu from 11 years (2005-2015) fall season show the highest value for Douliu and the lowest value for Taixi. However, during polluted events, Taixi PM2.5 concentration growth rates is highest and Douliu is lowest. All three sites show decreasing trend of PM2.5 concentrations in the past ten years, especially for Douliu site. Hourly PM2.5 data reveal Douliu concentration increase at daytime and decrease at nighttime, whereas an opposite day-night trend for Taixi, suggesting it may in relation to the local land-sea breeze circulation. Correlation coefficients (R) between four meteorology conditions (relative humidity, wind speed, temperature, and vertical stability) and PM2.5 concentrations at Douliu are -0.30, -0.29, -0.18, 0.19, respectively. If we consider all of above meteorological parameters together with PM2.5 concentration, R-squared can reach 0.22. It suggests that 22 percent of PM2.5 concentration variation is associated with meteorology conditions.

    Results from 2015 field experiment showed that three meteorology parameters (relative humidity, wind speed and temperature) have better correlation coefficient with higher absorption aerosols (i.e. low single-scattering albedo). Correlation coefficient between temperature and absorption coefficient is 0.63 durning polluted event period. Higher correlation coefficient between meteological prameters and aerosol size are found to be -0.60, 0.50, 0.56 for RH, wind speed, and temperature, respectively. PM2.5 concentration shows positive correlation with AOD in the experimental period in general but shows a negative correlation durning polluted event period. This result implies the main sources of air pollution are local emissions and short-term near ground transport during the normal days. As contrast, lidar observation reveals high altitude aerosols downward transport to the ground durning polluted days. Positive correlation between PM2.5 concentration and PBL height also suggests that PM2.5 concentration will increase when atmospheric mixing is stronger. Results from case studies show that the increasing of surface air pollution in Douliu are due to local emission, aerosol transport by land-sea breeze circulation, nighttime residual layer downward to the surface by atmospheric vertical convection, and poor diffusion by high vertical stability. This study has implications on air quality diagnostic, forecast, as well as control policy making for the high PM2.5 area such as Douliu.
    Appears in Collections:[大氣物理研究所 ] 博碩士論文

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