108年臺中市細懸浮微粒(PM2.5)成分分析及空品預報計畫
| 中文摘要 | 本研究有大氣PM2.5化學組成調查，排放管道PM2.5濃度檢測以及公車站PM2.5濃度量測。另一重點是空品預報，當未來48小時空氣品質有惡化(AQI>150)之虞時，提前通知環保局採取應變措施。 后里、大里及東大站PM2.5化學成分中有機碳含量介於19.2~24.9%、硫酸根20.0~23.3%、銨根4.9~7.9%、元素碳6.2~8.9%，硝酸根占比3.5~6.5%，金屬成分占比2.8~9.9%。台中電廠管道PM2.5108年檢測結果顯示FPM介於0.7 mg/Nm3~1.85 mg/Nm3，CPM介於11.9 mg/Nm3~24.4 mg/Nm3。 公車站早、中、晚三次PM2.5量測結果顯示，晨峰期的濃度最高，昏峰期濃度最低，濃度變化未能反應交通流量的變化，但可發現公車站PM2.5變化趨勢與大氣測站相似，顯示公車站PM2.5受大氣背景濃度影響得幅度高於車輛數的影響。 AQI值預測準確率在4月份55%，5月份達73%。4月準確率較低的原因是受到春季的天氣系統變化快速影響，氣象預報誤差大間接影響空氣品質預測準確性，9月份起，因加入ECMWF空氣品質預報模式輔助CMAQ預報，以及採用類神經網絡輔助修正預測數值，預測準確度大幅且穩定上升，10月份達到77%。 | ||
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| 中文關鍵字 | PM2.5化學成分、管道過濾性微粒、管道凝結性微粒、空氣品質預報 | ||
基本資訊
| 專案計畫編號 | 經費年度 | 108 | 計畫經費 | 12500 千元 | |
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| 專案開始日期 | 2019/01/23 | 專案結束日期 | 2019/12/31 | 專案主持人 | 程萬里 |
| 主辦單位 | 臺中市政府環境保護局 | 承辦人 | 張詠雅 | 執行單位 | 台灣綠仕科技有限公司 |
成果下載
| 類型 | 檔名 | 檔案大小 | 說明 |
|---|---|---|---|
| 期末報告 | 定稿_R1.pdf | 8MB |
Composition Analysis of PM2.5 and Air Quality Forecasting for Taichung City in 2019
| 英文摘要 | This study covers the analysis of atmospheric PM2.5 chemical composition, measurement of PM2.5 mass concentration in flue gas, monitoring of PM2.5 concentration near bus stops, as well as the forecast of air quality in Taichung. Whenever the air quality tends to deteriorate with Air Quality Index (AQI) higher than 150 within the next 48 hours, the Environmental Protection Bureau (EPB) of Taichung City Government will be notified in advance to take emergency measures. The chemical composition of PM2.5 at Houli, Dali, and THU sites is analyzed. The ranges of relative amount for each component in PM2.5 are organic carbon (19.2-24.9%), sulfate (20.0-23.3%), ammonium (4.9-7.9%), elemental carbon (6.2-8.9%), nitrate (6.2-8.9%), and metallic elements (2.8-9.9%). The result of measuring PM2.5 in flue gas from Taichung Power Plant in 2019 shows that the mass concentrations of filterable particulate matters (FPM) and condensable particulate matters (CPM) fall in the ranges of 0.7-1.85 mg/Nm3 and 11.9-24.4 mg/Nm3, respectively. The concentrations of PM2.5 are monitored at bus stops in the morning, at noon, and in the evening. The result indicates that the concentration of PM2.5 is highest during the commuting rush hours in the morning while that of PM2.5 is lowest during the heavy traffic in the evening, implying that the diurnal variation of PM2.5 cannot reflect the change in the volume of traffic flow. However, the trend of PM2.5 at bus stops is similar to that at ambient monitoring sites, which means that the influence of background atmosphere on the PM2.5 concentration at bus stops is more significant than that of the volume of vehicles. The accuracy of air quality forecast is 55% in April and 73% in May. The relatively lower accuracy in April was due to the capricious weather systems in spring along with the higher uncertainty of the weather forecast. The Community Multiscale Air Quality Modeling System (CMAQ) is integrated with the air quality forecasting model of the European Centre for Medium-Range Weather Forecasts (ECMWF) and adopts neural network to assist with the forecasting and correct the predicted numerical values since September. Afterwards, the accuracy of air quality forecast steadily increases and reaches 77% in October. | ||
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| 英文關鍵字 | Composition of PM2.5、Filterable Particulate Matter (FPM)、Condensable Particulate Matter (CPM)、Air Quality Forecast | ||