中國塵霾長程傳輸對臺灣細懸浮微粒(PM2.5)濃度的影響

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徐慧淳(Hui-Chun Hsu) 查詢紙本館藏

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論文名稱

中國塵霾長程傳輸對臺灣細懸浮微粒(PM2.5)濃度的影響
(The Effects of Long-range Transported Haze from China on the PM2.5 levels in Taiwan)

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摘要(中)

每年秋末至春初期間，源自西伯利亞的北方高壓逐漸增強向太平洋移動，臺灣盛行風向由西南轉為東北，來自中國的高濃度細懸浮微粒(PM2.5)隨著東北風傳輸到臺灣，影響臺灣的空氣品質。為了探究中國長程傳輸污染物對臺灣本地空氣品質的影響，本文參考Junker et al. (2009)及Chuang et al. (2008a)從2006年1月至2015年12月環保署萬里、基隆、宜蘭、冬山、淡水空品測站污染物監測資料及中央氣象局每日地面天氣圖資料，篩選出日平均風速? 3.7 m s-1、PM2.5 ? 25 μg m-3的長程傳輸事件日(Long Range Transport – Event, LRT – Event)、日平均風速> 3.7 m s-1、PM2.5 < 25 μg m-3的一般長程傳輸日(Long Range Transport – Ordinary, LRT – Ordinary)、日平均風速< 3.7 m s-1的混合型(LRT/LP (Local Pollution) Mix)或當地污染(Pure LP)。由各年污染類型統計結果得知，LRT – Ordinary發生頻率最高(好發於秋季至春季間)，其次為LRT – Event (好發於冬季至春初間)及LRT/LP Mix or Pure LP(各季發生頻率平均)。
本文利用CMAQ模式模擬2010年1月至5月未含臺灣的東亞排放源影響，推估LRT – Event (n = 13)、LRT – Ordinary (n =32)、LRT/LP Mix or Pure LP (n = 14)對臺灣西部八個都會區測站的長程傳輸PM2.5濃度變化比例，取代表北、中、南部的新莊、忠明、小港站，並以萬里站為對比站(比例為1)，三站LRT – Event比例為0.83、0.62、0.53，LRT –Ordinary (n =32)比例為0.72、0.67、1.44，LRT/LP Mix or Pure LP (n = 14)比例為0.91、1.10、1.72，受到大氣環境氣流不同變化機制影響，不同污染類型在各地影響比例差異甚大。
將模擬的2010年1月至5月期間三種長程傳輸類型在各站PM2.5濃度影響比例，代入2006年1月至2015年12月篩選出三種長程傳輸類型監測資料，用以估算長程傳輸與當地PM2.5濃度(包含臺灣本島其他地區傳輸濃度)，最後得出臺灣北(新莊)、中(忠明)、南(小港)地區的長程傳輸與當地PM2.5濃度貢獻量分別為14 μg m-3 (53%)與11 μg m-3 (47%)、12 μg m-3 (37%)與21 μg m-3 (63%)、18 μg m-3 (36%)與36 μg m-3 (64%)，北部PM2.5濃度主要受長程傳輸影響，中、南部地區雖受當地污染影響較高，但長程傳輸影響仍不容忽視。
以前述方法推估不同年度長程傳輸與當地污染影響PM2.5濃度，發現2013年以後，中國長程傳輸在臺灣西部各地PM2.5濃度影響逐漸下降，當地PM2.5濃度在新竹以北變動幅度小，但中部以南十年間有明顯的下降趨勢。本文分析指出：在東北季風情況下，來自中國長程傳輸的PM2.5在臺灣北部已經相當接近年平均空品標準，但持續降低當地污染源排放仍然是改善PM2.5空氣品質的有效途徑。

摘要(英)

The high PM2.5 air masses from northern China usually deteriorated the air quality in Taiwan via long-range transport (LRT) from the late autumn to early spring every year. The reason is that Taiwan is located in the downwind area of Asian continent under prevailing northeasterly wind. In order to understand the impact of pollutants from LRT on the air quality in Taiwan, this study analyzed long-term air quality and meteorological data in northern Taiwan (including Wanli, Keelung, Yilang, Dongshan, and Tamsui stations) from 2006 to 2015 especially when the prevailing wind is northeasterly. The outcome of analysis referring to the method of Junker et al. (2009) and Chuang et al. (2008a) results in three types of pollution. The present study defined the first type as LRT – Event with the conditions of the daily-average wind speed ? 3.7 m s-1 and the daily-average PM2.5 ? 25 μg m-3. The second type is LRT – Ordinary when the daily-average wind speed ? 3.7 m s-1 and the daily average PM2.5 < 25 μg m-3, and the third type is LRT/LP Mix (Local Pollution) or the Pure LP when the daily-average wind speed < 3.7 m s-1. According to the statistics, LRT – Ordinary type is the most frequent occurring one usually from autumn to next spring, followed by LRT – Event also from autumn to early spring, and the LRT/LP Mix or the Pure LP appearing in every season.
This study applied the Community Multi-scale Air Quality Model (CMAQ) model to simulate a short-term (January to May 2010) scenario with emissions geographically covering the whole East Asia but excluding Taiwan. From such a simulation, this study estimated the variation ratios of LRT PM2.5 concentration in major metropolises to Wanli station, the northern tip of Taiwan. Based on this estimation, the variation ratios of LRT PM2.5 concentration over Wanli in the northern (Hsinchuang station), central (Zongming station), and southern (Xiaogang station) metropolises are 0.83, 0.62, and 0.53, respectively, for the LRT – Event type (n=13). For the LRT – Ordinary type (n=32), the variation ratios of LRT PM2.5 concentrations over Wanli in the three metropolis are 0.72, 0.67, and 1.44, respectively. As to the LRT/LP Mix or the Pure LP type (n=14), the variation ratios of LRT PM2.5 concentration over Wanli are 0.91, 1.10, and 1.72, respectively. Due to complicated mechanisms of atmospheric condition, these three types of pollution have different variation ratios in various regions.
Using 10-year air quality data and the variation ratios of the three types of pollution, the present study made estimates on the PM2.5 concentrations of LRT and LP at different metropolises. The results show that the average contributions of LRT and LP in northern, central, and southern metropolises are at 14 μg m-3 (53%) and 11 μg m-3 (47%), 12 μg m-3 (37%) and 21 μg m-3 (63%), and 18 μg m-3 (36%) and 36 μg m-3 (64%), respectively. The contribution of PM2.5 in northern Taiwan is mainly from LRT. Although the impact of LP is higher in central and southern Taiwan, the present study suggests that the contribution of LRT is not ignorable.
In terms of the contributions of LRT and LP to various stations, the PM2.5 concentrations from LRT in the western Taiwan had gradually decreased since 2013. The annual variations of PM2.5 concentration from LP were not obvious in stations north from Hsinchu, but there was a significantly downward trend in the central and southern Taiwan during the last ten years. Compared to yearly PM2.5 standard (15 μg m-3), the LRT contribution from China to PM2.5 is already near the yearly standard in northern Taiwan. However, it is practical to reduce the PM2.5 contribution from LP sources than expecting reduction of LRT contribution to meet PM2.5 daily standard (35 μg m-3).

關鍵字(中)

★ 細懸浮微粒(PM2.5)
★ 長程傳輸
★ 當地污染
★ CMAQ

關鍵字(英)

★ PM2.5
★ Long range transport (LRT)
★ Local pollutant (LP)
★ CMAQ

論文目次

目錄
摘要 V
ABSTRACT VII
致謝 IX
目錄 X
圖目錄 XIII
表目錄 XVI
第一章前言 1
1.1 研究緣起 1
1.2 研究目的 2
第二章文獻回顧 3
2.1 細懸浮微粒(PM2.5)的重要性 3
2.1.1 PM2.5來源及特性 3
2.1.2 PM2.5化學成分 5
2.1.3 PM2.5對大氣環境及健康的影響 6
2.2 臺灣PM2.5的特性 9
2.3 中國塵霾的重要性 11
2.3.1 中國塵霾的定義 11
2.3.2 中國塵霾的形成及演化 13
2.4 中國PM2.5化學成分及來源 16
2.5 中國長程傳輸對臺灣的影響 20
2.5.1 長程傳輸綜觀天氣型態 20
2.5.2 長程傳輸污染物特性 22
2.6 模式模擬應用 25
第三章研究方法 27
3.1 研究流程圖 27
3.2 觀測資料分析方法 27
3.2.1 污染物傳輸假設 27
3.2.2 污染類型分類 31
3.2.3 小時降雨量與PM2.5濃度的關係 33
3.2.4 長程傳輸事件日判定驗證 34
3.2.5 以監測資料推估長程傳輸及當地PM2.5濃度 36
3.3模式模擬方法 39
3.3.1 模擬時間 39
3.3.2 氣象模擬 – ARW-WRF 39
3.3.3 排放資料處理-SMOKE 43
3.3.4 化學模式-CMAQ 45
3.4 模式模擬資料評估方法 47
3.4.1 氣象及污染物濃度資料 47
3.4.2 WRF-CAMQ氣象評估 49
3.4.3 WRF-CAMQ污染物評估 50
3.4.4 長程傳輸PM2.5濃度平均變化比例推估 51
3.5 推估長程傳輸及當地PM2.5濃度十年變化趨勢 52
第四章結果與討論 53
4.1 臺灣東北季風下污染類型界定 53
4.1.1 背景測站選擇 53
4.1.2 污染類型界定分析 57
4.1.3 當地PM2.5 推估曲線 64
4.1.4 長程傳輸事件日判定驗證 65
4.2 臺灣各年東北季風下污染類型特性 68
4.3 未修正的監測資料推估臺灣西部都會區長程傳輸及當地PM2.5濃度 73
4.4 臺灣西部都會區不同污染類型長程傳輸PM2.5濃度變化特性 76
4.4.1 模擬與觀測資料評估結果 76
4.4.2 不同污染類型的長程傳輸PM2.5濃度變化比例 84
4.4.3 不同污染類型的長程傳輸PM2.5濃度變化比例個案分析 92
4.5 臺灣西部都會區長程傳輸及當地PM2.5濃度推估探討 107
4.5.1 利用長程傳輸PM2.5濃度變化比例修正監測資料推估 107
4.5.2 探討監測資料及模式模擬推估長程傳輸與當地PM2.5濃度的差異 112
4.5.3長程傳輸與當地PM2.5逐年變化分析 115
4.5.4 不同污染類型PM2.5濃度貢獻 121
第五章結論與建議 123
5.1 結論 123
5.2 建議 125
第六章文獻回顧 126
附錄一氣流軌跡判定與MODIS – AOD空間分布圖 135
附錄二 WRF氣象場風向評估結果 146
附錄三長程傳輸PM2.5與風場空間分布圖(未含臺灣的東亞排放源模擬結果) 161
附錄四監測資料與模擬資料推估長程傳輸及當地PM2.5濃度時序圖 179
附錄五口試委員意見答覆 187

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指導教授

李崇德、莊銘棟(Chung-Te Lee Ming-Tung Chuang)

審核日期

2017-1-23

推文