| 摘要: | 本文於2017年1月9日至2017年2月14日在越南胡志明市，採集和分析PM2.5與PM10，研究越南都會區PM2.5 與PM10化學成份以及推估可能污染源， PM2.5與PM10樣本使用稱重方法來分析質量濃度，離子層析儀分析水溶性無機離子和碳分析儀器分析碳成份。研究結果顯示PM2.5與PM10平均質量濃度是31.8 µg m-3 和 65.8 µg m-3，碳成份占PM2.5、PM10是41%和14%，水溶性無機離子占PM2.5、PM10是26%和21%。本研究使用正矩陣因子法(Positive Matrix Factorization - PMF)推估貢獻因子(污染來源)，結果顯示有六種污染來源分別是二次硫酸(占PM2.5 14%, PM10 8%),汽油車(占PM2.5 21%, PM10 12%)，二次硝酸(占PM2.5 16%, PM10 11%)，建設活動(占PM2.5 5%, PM10 7%)，海鹽和塵土(占PM2.5 4%, PM10 5%)，農廢燃燒(占PM2.5 8%, PM10 8%)。最後使用條件機率函數(Conditional Probability Function - CPF)結合風向資料，推估當地污染源來向。;Atmospheric aerosols were collected from 9 January to 14 February 2017 in the urban area of Ho Chi Minh City (HCMC), Vietnam. Aerosol mass concentrations, carbonaceous contents, and water-soluble inorganic ions (WSIIs) of PM2.5 and PM10 were determined by gravimetrical weighing, thermal-optical reflectance method, and ion chromatography, respectively. The average mass concentration of PM2.5 and PM10 during the sampling period were 31.8 µg m-3 and 65.8 µg m-3, respectively. A mong various components, carbonaceous contents accounted for 41% and 24% of PM2.5 and PM10 mass, respectively. In contrast, WSIIs contributed 26% and 21% of PM2.5 and PM10 mass, respectively. In this study, positive matrix factorization (PMF) was used to investigate major contributing sources of PM2.5 and PM10 in HCMC. Six sources were identified from PMF modeling including secondary sulfate (14% of PM2.5, 8% of PM10), gasoline vehicles (21% of PM2.5, 12% of PM10), secondary nitrate (16% of PM2.5, 11% of PM10), construction activities (5% of PM2.5, 7% of PM10), sea salts and soils (4% of PM2.5, 5% of PM10), and biomass burning (8% of PM2.5, 8% of PM10). Conditional Probability Function was applied to help identify potential sources from local activities in HCMC. |
