110-111年度能見度監測系統操作維護及資料解析計畫
| 中文摘要 | 本計畫執行環保署能見度監測網板橋、西屯、小港三測站能見度設備操作與維護，定期完成資料品質保證與品質管制(QA/QC，Quality assurance / Qaulity control)作業，整合能見度監測網與環保署空氣品質測站等監測資料，並提供光學監測儀器監測結果應用及解析。結果顯示：(一) 相對濕度是提高推估消光係數精確度的重要因子，透過繪製不同能見度條件下PM2.5 ((Particulate Matter < 2.5 μm in diameter, 細懸浮微粒) 和RH (Relative Humidity, 相對濕度) 的出現頻率圖，可以提供人們概略且直接地判斷霧或霾對能見度衰減影響的參考。(二) 在吸光係數的應用上，藉由EPA (Environmental Protection Administration, 環境保護署) 公告污染事件驗證CO/NOx (Carbon monoxide / Nitrogen Oxides, 一氧化碳與氮氧化物比值)、AAE (Absorption Ångström Exponent, 吸收波長指數) 與BC/PM2.5 (Black Carbon / PM2.5, 黑炭與細懸浮微利的比值) 三維指標應用於辨別境外傳輸、境內污染與交通排放的事件特徵。(三) 使用ISORROPIA模式推估低濕低PM2.5環境下的氣膠含水量，由於硝酸鹽的潮解點低於硫酸鹽，而小港測站的硝酸鹽濃度通常高於其他站，因此引起對能見度衰減更多關注。(四) 臺中盆地設置的LPV-4 能見度儀低空和高空兩條光徑和LiDAR (Light Detection and Ranging, 光學探測與測距、雷射雷達、光達) 儀器進行測量結果顯示，在適當的大氣條件下，LPV-4和光達的觀測相互對應，通過掃描式光達儀器的三維監測與低空和高空照片可說明大氣邊界層的波動會導致人眼觀測與儀器測量之間的差異。(五) 透過PMF (Positive Matrix Factorization, 正矩陣因子法)解析三測站的污染源，顯示硝酸鹽污染源管制對於改善能見度政策的重要性。 | ||
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| 中文關鍵字 | 消光係數、散光係數、PM2.5化學成分、相對濕度 | ||
基本資訊
| 專案計畫編號 | 經費年度 | 110 | 計畫經費 | 2660 千元 | |
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| 專案開始日期 | 2021/10/14 | 專案結束日期 | 2022/09/30 | 專案主持人 | 張士昱 |
| 主辦單位 | 監資處 | 承辦人 | 陳誼 | 執行單位 | 中山醫學大學 |
成果下載
| 類型 | 檔名 | 檔案大小 | 說明 |
|---|---|---|---|
| 期末報告 | 能見度監測系統操作維護及資料解析計畫_成果報告.pdf | 23MB |
Plan of visibility monitoring system operating maintenance and data analysis
| 英文摘要 | The work projects of this plan included maintaining and operating the EPA (Environmental Protection Administration) visibility monitoring network (VMN) in Banqiao, Xitun, and Xiaogang stations, implementing the data quality assurance and quality control, investigating the measured information between EPA air quality monitoring stations and VMN, and providing the analysis and application of the VMN optical monitoring data. After the analysis of the data provided from this project, several results were investigated. First, the method to evaluate the visibility from the concentration of PM2.5 (Particulate Matter < 2.5 μm in diameter) and the RH (Relative Humidity) was established in this project. The evaluated visibility by this method could offer an easy and direct reference in order to determine the decreasing of the visibility for people. Second, in the application of the absorbance coefficient, the three-dimensional indicators of CO/NOx (Carbon monoxide / Nitrogen Oxides), AAE (Absorption Ångström Exponent) and BC/PM2.5 (Black Carbon / PM2.5) are verified by the pollutant events of EPA announcements to identify the characteristics of long-range transport pollutants, local pollutants, and traffic emissions. Third, the aerosol liquid water content (ALWC) simulated by the ISORROPIA model in the low humidity and PM2.5 environment correlated better with the nitrate than with the sulfate at Xiaogang station. The possible reason could be that the deliquescence relative humidity of nitrate was lower than sulfate. The great amount of ALWC after deliquescence caused the visibility degradation even at RH < 65%. The concentrations of nitrate were usually higher at Xiaogang station than other stations, which raised more attention on visibility degradation. Therefore, the concentration of nitrate was suggested to be concerned in pollution control policies in order to improve the visibility. Forth, in order to investigate the vertical variations of visibility, two optical paths of LPV-4 at low and high altitude, and LiDAR (Light Detection and Ranging) instrument were set up to measure in Taichung basin. Under the proper atmospheric conditions, the observations of LPV-4 transmissometers and the LiDAR instrument corresponded to each other. The fluctuations of atmospheric boundary layers would cause discrepancies between the human eye observations and the instrument measurements, which could be illustrate by the three-dimensional monitoring of the scanning LiDAR instrument and photos at low and high altitude. Fifth, the positive matrix factorization (PMF) was used at three stations for source apportionment of pollution. The results highlight the importance of nitrate pollution source control in improving visibility policies. To sum up, the visibility could be roughly evaluated from the PM2.5 and the RH through the method established in this project. The LiDAR instrument could offer a better result for the three-dimensional atmosphere monitoring which is able to explain how the fluctuations of atmospheric boundary layers effect the visibility monitoring, and it is correlated to the result observed from the LPV-4 under proper conditions. According to results derived from the ISORROPIA model and the PMF method, the reducing of nitrate pollutant source is recognized as an important factor to improve the visibility. | ||
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| 英文關鍵字 | Extinction coefficient, Scattering coefficient, PM2.5 chemical component, Relative humidity | ||