Sentinel-5 Precursor (S5P)衛星發射時間為2017年，屬於新一代環境衛星。其觀測目標在於空氣品質與環境監測，並提供較高解析度的氣膠、微量氣體等反演資料以利未來進行研究分析使用。但近幾年來較少研究人員使用S5P衛星上的酬載儀器TROPOMI所反演出來的產品進行臺灣污染物的相關分析。因此本篇研究使用TROPOMI所反演出的對流層二氧化氮(Nitrogen Dioxide, NO2) 與地面觀測近地表二氧化氮進行驗證及比較。二氧化氮屬於主要的都市地區污染物並且為二次性氣膠及臭氧的前驅物。其中二次性氣膠是引發極端空氣污染事件的成因之一，因此為了監測空氣品質，分析前驅氣體的時空變化趨勢顯得相當重要。此篇研究採用2018年6月至2019年5月的每日及每月平均資料進行相關性統計。使用日資料分析時，北部 (新北市/臺北市/基隆市)、雲林、嘉義、臺南及高雄屬於高度相關(r ≥ 0.5);低度相關(r < 0.3) 則出現在宜蘭、新竹、桃園。因污染物濃度日變化包含了許多複雜因素，如大氣環流不同、排放源強度不一、化學物質轉變及觀測時間上的誤差等，因此使用月平均資料分析，結果顯示各地區相關係數值較日資料增加許多，代表由兩儀器所觀測出來的資料相關性提升到中度、甚至高度相關，同時意味著對流層二氧化氮及近地表二氧化氮濃度變化趨勢相似，因此可證明TROPOMI所反演出的二氧化氮產品可使用在臺灣相關污染物研究中。
從時空分布角度來看，臺灣東側通常污染物平均濃度較低；都市地區則因排放量較多，濃度偏高。根據不同季節，臺灣冬季擁有最高平均濃度值;夏季則是最低。此結果也能瞭解到濃度變化與氣象場有一定的關聯性，因此結合再分析場並特別針對高濃度污染事件進行探討。極端污染事件一般出現在各縣市盛行北或東風、低風速及大氣較為穩定的情況下，因污染物擴散不易所造成。而當冬季邊界層高度相較於月平均低、溫度及相對濕度則相較於月平均時高，則極端越值地區 (Extreme Threshold Area, 如:桃園、臺中、彰化、高雄) 易有高濃度污染產生。除此之外，地面測站提供了近地表的污染物濃度觀測，藉由濃度變化可分析區域排放的影響; S5P衛星上的TROPOMI則可提供較大範圍 (包含都市、郊區與山區)、高解析度 (3.5×7.0 km2)、垂直層濃度 (近地表與高層) 的觀測，去理解大環境污染物的變化並增加地面測站所無法提供出的高層二氧化氮與季節之間的相關特性說明，同時驗證高層污染物對於空氣污染事件是不可忽略的重要因子。

Sentinel-5 Precursor (S5P) is a new generation environmental satellite and provides products regarding trace gases concentrations along with cloud and aerosol information in global scale. This study focuses on nitrogen oxide (NOx), the main air pollutant in urban areas and the precursor of secondary aerosols and ozone, under the regional scale. As NOx is primary in the form of Nitrogen dioxide (NO2), this study aims to understand the spatiotemporal feature of NO2 in Taiwan. Tropospheric NO2 data retrieved from the TROPOMI onboard S5P and surface NO2 data collected by surface instruments from the Environmental Protection Administration (EPA) of Taiwan are used for analysis. The analyzed temporal period spans from June 2018 to May 2019, and surface observation is collocated with a daily revisit of S5P spatiotemporally. Those data are analyzed in 15 sub-regions in Taiwan to understand the relationship between tropospheric vertical column and surface concentration of NO2.
The preliminary results reveal high correlations between surface and tropospheric NO2 concentration in North (Taipei/ New Taipei City/ Keelung), Yunlin, Chiayi, Tainan, and Kaohsiung in S5P’s daily revisit rate, while Yilan, Taoyuan, and Hsinchu shows relatively low correlations. The mean concentration of NO2 on the monthly scale is analyzed to avoid possible impacts due to high-frequency variation in environmental factors. Results indicate there are high correlations in most counties between ground-based and space-borne observations. In other words, the tendency of surface NO2 is similar to the tropospheric NO2 in most countries in Taiwan, particularly on the monthly scale. Therefore, to monitor and analyze NO2 concentration, spaceborne TROPOMI on S5P might be an alternative option for conducting related research in Taiwan.
From the aspect of spatiotemporal characteristic analysis, Eastern Taiwan often has the lowest concentration; there is a higher concentration in the urban area because of the abundant emission sources. Moreover, during winter the concentration tends to be higher than summer, indicating certain connections between the environment and air pollutants. The NCEP reanalysis data, which represents the meteorological factors, is also applied in this study for investigating the uncertainty sources, revealing a strong correlation between wind direction and pollution concentration. The result shows that higher NO2 concentrations are usually under lower planetary boundary height (PBL), lower wind speed, lower tropospheric stability (LTS), lower 975 hPa temperature, and higher 975 hPa Relative humidity (RH), and this feature is enhanced in summer and spring.
An analysis of the collected data demonstrates that ground-based observation represents the local effect; satellite observation can represent the state of the environmental pollution, offering certain characteristics that cannot be identified by surface observation because of its ability to provide coverage of large area (urban, suburban and ocean) and observe total column density (near-surface and higher-level NO2). This study also proves that pollutants at higher altitudes play an important role in extreme air pollution events.

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