環保專案成果報告查詢系統

專案計畫編號
經費年度	100
計畫經費	11,980 千元
專案開始日期	2011/07/01
專案結束日期	2012/06/30
專案主持人	許珮蒨
主辦單位	新北市政府環境保護局
承辦人	林育寬
執行單位	中興工程顧問股份有限公司
專案分類	大氣空氣
中文關鍵字	細懸浮微粒、空氣品質、成分分析、管制策略
英文關鍵字	Fine Particulate Matter (PM2.5), air quality, composition analysis, control strategy
協同主持人
共同主持人
計畫聯絡人	曹志宏
計畫聯絡電話	02-27698388#20866
計畫聯絡信箱	ah4491@ntpc.gov.tw

中文摘要	本計畫針對北部空品區細懸浮微粒長期監測數據進行分析、執行短期採樣及成分分析、並以CMB受體模式與三維光化模式進行模擬及研究工作，以提出合理有效的防制策略方向。 (一)北部空品區長期PM2.5變化北部空品區各縣市民國95 ~ 100 年PM2.5 年平均濃度約在20 ~32 μg/m3 左右，以臺北市最高，年平均濃度接近30 μg/m3。桃園縣約28 μg/m3 次之、新北市約25 μg/m3 又次之，而基隆市最低，年平均濃度約22 μg/m3。值得注意的是，臺北都會區及基隆市之PM2.5/PM10 比值高於桃園縣。可能因桃園縣粗顆粒(PM2.5-10)濃度確實較高，其次臺北都會區及基隆市機動車輛等細粒污染排放量大，亦是可能原因，顯示都會區機動車輛排放管制工作，確實不容忽視。都會區內測站(中山、萬華、古亭、松山、土城、板橋、新莊)之PM2.5 濃度相對較高，其中以中山站最高，再次證明機動車輛的可能影響。然近年各測站PM10 皆有改善趨勢，其中以臺北都會區外圍之林口、淡水與桃園站改善較多，都會區內測站改善較少。 (二)採樣結果分析由縣市同步採樣之光化(SO42-、NH4+、NO3-)、碳成分(OC、EC)、海水飛沫(Na+、Cl-、Mg2+)及揚塵(Fe、Al、Ca)等成分比例與背景之差異(採樣點－萬里)，顯示北部空品區之碳成分應為主要改善對象。另外揚塵比例雖不高，但各採樣點皆較萬里站高，顯示街道、裸露地或營建工地等揚塵管制，亦不容忽視。交通密集區域採樣結果成分比例與縣市同步採樣成分比例差異顯示，特定區域PM2.5 不僅高出環境甚多，且OC、EC 及Ca2+比例偏高，應與車輛排氣及車行揚塵有關。 (三)空氣污染管制策略研擬以機車、小客車及柴油車作為減量管制策略，以空氣品質模式模擬評估減量成效顯示，O3 小時值或8 小時值最大減少成效區域大多位於臺北市與新北市區。衍生性粒狀物24 小時值最大減少區域位於污染源下風地區，如北部地區之桃園新竹濱海地區及桃園復興鄉等，其濃度並不顯著。相對而言，原生性粒狀物24 小時值最大減少區域，則以臺北市區、板橋、新莊、高速公路、縱貫省道等線形地區，為減量成效較為顯著之區域。由本計畫採樣結果顯示，不同採樣點之碳成分差異明顯；比較超級測站OC、EC逐時變化亦顯示，不論任何季節晨間OC、EC皆有高峰值，顯示機動車輛之貢獻不小。另由CMB之分析結果，與以不同O3區間之PM2.5濃度變化分析結果，光化來源比例平均分別為38%及21%。顯示PM2.5管制除原生性污染排放外，亦需兼顧光化來源管制。因此整體管制方向將分為車輛排放管制與光化前趨物(NOx、NMHC)管制，由排放量資料顯示車輛仍是主要NOx來源；NMHC則除汽機車外，主要來自於點源。
中文關鍵字	細懸浮微粒、空氣品質、成分分析、管制策略

中文摘要

本計畫針對北部空品區細懸浮微粒長期監測數據進行分析、執行短期採樣及成分分析、並以CMB受體模式與三維光化模式進行模擬及研究工作，以提出合理有效的防制策略方向。 (一)北部空品區長期PM2.5變化北部空品區各縣市民國95 ~ 100 年PM2.5 年平均濃度約在20 ~32 μg/m3 左右，以臺北市最高，年平均濃度接近30 μg/m3。桃園縣約28 μg/m3 次之、新北市約25 μg/m3 又次之，而基隆市最低，年平均濃度約22 μg/m3。值得注意的是，臺北都會區及基隆市之PM2.5/PM10 比值高於桃園縣。可能因桃園縣粗顆粒(PM2.5-10)濃度確實較高，其次臺北都會區及基隆市機動車輛等細粒污染排放量大，亦是可能原因，顯示都會區機動車輛排放管制工作，確實不容忽視。都會區內測站(中山、萬華、古亭、松山、土城、板橋、新莊)之PM2.5 濃度相對較高，其中以中山站最高，再次證明機動車輛的可能影響。然近年各測站PM10 皆有改善趨勢，其中以臺北都會區外圍之林口、淡水與桃園站改善較多，都會區內測站改善較少。 (二)採樣結果分析由縣市同步採樣之光化(SO42-、NH4+、NO3-)、碳成分(OC、EC)、海水飛沫(Na+、Cl-、Mg2+)及揚塵(Fe、Al、Ca)等成分比例與背景之差異(採樣點－萬里)，顯示北部空品區之碳成分應為主要改善對象。另外揚塵比例雖不高，但各採樣點皆較萬里站高，顯示街道、裸露地或營建工地等揚塵管制，亦不容忽視。交通密集區域採樣結果成分比例與縣市同步採樣成分比例差異顯示，特定區域PM2.5 不僅高出環境甚多，且OC、EC 及Ca2+比例偏高，應與車輛排氣及車行揚塵有關。 (三)空氣污染管制策略研擬以機車、小客車及柴油車作為減量管制策略，以空氣品質模式模擬評估減量成效顯示，O3 小時值或8 小時值最大減少成效區域大多位於臺北市與新北市區。衍生性粒狀物24 小時值最大減少區域位於污染源下風地區，如北部地區之桃園新竹濱海地區及桃園復興鄉等，其濃度並不顯著。相對而言，原生性粒狀物24 小時值最大減少區域，則以臺北市區、板橋、新莊、高速公路、縱貫省道等線形地區，為減量成效較為顯著之區域。由本計畫採樣結果顯示，不同採樣點之碳成分差異明顯；比較超級測站OC、EC逐時變化亦顯示，不論任何季節晨間OC、EC皆有高峰值，顯示機動車輛之貢獻不小。另由CMB之分析結果，與以不同O3區間之PM2.5濃度變化分析結果，光化來源比例平均分別為38%及21%。顯示PM2.5管制除原生性污染排放外，亦需兼顧光化來源管制。因此整體管制方向將分為車輛排放管制與光化前趨物(NOx、NMHC)管制，由排放量資料顯示車輛仍是主要NOx來源；NMHC則除汽機車外，主要來自於點源。

中文關鍵字

細懸浮微粒、空氣品質、成分分析、管制策略

類型	檔名	檔案大小	說明	最新版公開日期
期末報告	摘要.pdf	53MB	摘要	2013/2/1 上午 12:00:00

摘要	The main tasks of this project includes: long-term air quality data analysis for fine particulate matter (PM2.5) in the north Air Quality Control Area, short-term sampling and composition analyzing, and modeling and research works by using the CMB and CAMx models. Reasonable and effective strategies for air quality control were finally concluded. 1. Long-term variation of PM2.5 in the north air quality control area The annual concentration of PM2.5 in the north air quality control area is about 20-32 μg/m3 from 2006 to 2011 in average. The highest concentration presented in the Taipei city, which was about 30μg/m3. The second and the third highest concentration occurred in the Taoyuan County and the New Taipei City, which were 28 μg/m3 and 25 μg/m3. The lowest consentation which happened in the Keelung city was 22 μg/m3. It is notable that the ratio of PM2.5 to PM10 in the Taipei-Keelung metropolitan area is higher than in the Taoyuan County. It may because the PM2.5-10 concentration in Taoyuan County is much higher. On the other hand, the higher emission of fine particles from motor vehicles in the Taipei-Keelung metropolitan area might be another reason. The result indicates that motor vehicles emission control is critical in the downtown area. Among the monitoring sites within the downtown area (such as Zhongshan, Wanhua, Guting, Songshan, Tucheng, Banqiao and Xinzhuang air quality observation station), the PM2.5 concentration is comparatively higher. The highest record occured is in the Zhongshan station, which proves the impact due to motor vehicles on PM2.5 again. However, the PM10 concentration of all the monitoring sites was generally improved. 2. Sampling and composition analysis The simultaneous sampling of photochemical(SO42-, NH4+, NO3-), carbon(OC, EC), sea spray (Na+, Cl-, Mg2+), fugitive dust (Fe, Al, Ca) in the Taipei city and the New Taipei city was executed in this project. The composition analysis result comparing to the background (Wanli station) shows that the composition of carbon should be the main target to be improved in the north air quality control area. Besides, fugitive dust emission control at street、exposed area and construction site is critical as well since the fugitive dust at every sampling site was higher than the background concentraion. According to the difference analysis of the sampling results in heavy traffic zone and the simultaneous sampling among cities, heavy traffic zone has not only higher PM2.5 emission but also higher OC、EC and Ca2+ emission. It may cause from the exhaust gas of motor vehicles and fugitive dust of the traffic. 3. Proposal of air pollution control strategy Taking scooters、motor vehicles and diesel vehicles into consideration of emission reduction, it shows that hourly and 8-hour-average maximum reduction area of O3 occurred mostly in the Taipei and New Taipei city by examing air quality simulation model. The daily average maximum reduction area presents in the leeward places againt the pollution souces, such as the coastal area in the Hsinchu and Taoyuan County. The daily average maximum reduction of the primary particles locates in the Taipei city, Panchia district, Xinzhuang district, and the linear area like freeway and highway. Based on our sampling data and analysis results, the composition of carbon is significantly different at varios sites. It shows that the OC and EC concentration have peak in the morning at supersite by the comparison of their hourly average value. It may cause from the distribution of motor vehicles. According to the result of CMB analysis and the concentration assessment of PM2.5 at two O3 intervals, the impacts caused by photochemical were 38% and 21%. It represents that not only direct emission sources but photochemical sources should be reduced for PM2.5 control. Overall, the two key aspects are the exhaust gas of motor vehicles and photochemical precursor (NOx, NMHC) control. Generally, the sources of NOx emission are still motor vehicles, and the sources of NMHCemission are stationary pollution sources besides motor vehicles.
英文關鍵字	Fine Particulate Matter (PM2.5), air quality, composition analysis, control strategy

摘要

The main tasks of this project includes: long-term air quality data analysis for fine particulate matter (PM2.5) in the north Air Quality Control Area, short-term sampling and composition analyzing, and modeling and research works by using the CMB and CAMx models. Reasonable and effective strategies for air quality control were finally concluded. 1. Long-term variation of PM2.5 in the north air quality control area The annual concentration of PM2.5 in the north air quality control area is about 20-32 μg/m3 from 2006 to 2011 in average. The highest concentration presented in the Taipei city, which was about 30μg/m3. The second and the third highest concentration occurred in the Taoyuan County and the New Taipei City, which were 28 μg/m3 and 25 μg/m3. The lowest consentation which happened in the Keelung city was 22 μg/m3. It is notable that the ratio of PM2.5 to PM10 in the Taipei-Keelung metropolitan area is higher than in the Taoyuan County. It may because the PM2.5-10 concentration in Taoyuan County is much higher. On the other hand, the higher emission of fine particles from motor vehicles in the Taipei-Keelung metropolitan area might be another reason. The result indicates that motor vehicles emission control is critical in the downtown area. Among the monitoring sites within the downtown area (such as Zhongshan, Wanhua, Guting, Songshan, Tucheng, Banqiao and Xinzhuang air quality observation station), the PM2.5 concentration is comparatively higher. The highest record occured is in the Zhongshan station, which proves the impact due to motor vehicles on PM2.5 again. However, the PM10 concentration of all the monitoring sites was generally improved. 2. Sampling and composition analysis The simultaneous sampling of photochemical(SO42-, NH4+, NO3-), carbon(OC, EC), sea spray (Na+, Cl-, Mg2+), fugitive dust (Fe, Al, Ca) in the Taipei city and the New Taipei city was executed in this project. The composition analysis result comparing to the background (Wanli station) shows that the composition of carbon should be the main target to be improved in the north air quality control area. Besides, fugitive dust emission control at street、exposed area and construction site is critical as well since the fugitive dust at every sampling site was higher than the background concentraion. According to the difference analysis of the sampling results in heavy traffic zone and the simultaneous sampling among cities, heavy traffic zone has not only higher PM2.5 emission but also higher OC、EC and Ca2+ emission. It may cause from the exhaust gas of motor vehicles and fugitive dust of the traffic. 3. Proposal of air pollution control strategy Taking scooters、motor vehicles and diesel vehicles into consideration of emission reduction, it shows that hourly and 8-hour-average maximum reduction area of O3 occurred mostly in the Taipei and New Taipei city by examing air quality simulation model. The daily average maximum reduction area presents in the leeward places againt the pollution souces, such as the coastal area in the Hsinchu and Taoyuan County. The daily average maximum reduction of the primary particles locates in the Taipei city, Panchia district, Xinzhuang district, and the linear area like freeway and highway. Based on our sampling data and analysis results, the composition of carbon is significantly different at varios sites. It shows that the OC and EC concentration have peak in the morning at supersite by the comparison of their hourly average value. It may cause from the distribution of motor vehicles. According to the result of CMB analysis and the concentration assessment of PM2.5 at two O3 intervals, the impacts caused by photochemical were 38% and 21%. It represents that not only direct emission sources but photochemical sources should be reduced for PM2.5 control. Overall, the two key aspects are the exhaust gas of motor vehicles and photochemical precursor (NOx, NMHC) control. Generally, the sources of NOx emission are still motor vehicles, and the sources of NMHCemission are stationary pollution sources besides motor vehicles.

英文關鍵字

Fine Particulate Matter (PM2.5), air quality, composition analysis, control strategy