EPA-105-FA18-03-A171

105

6,400 千元

空氣品質管理

2016/04/08

2017/04/07

吳義林

空保處

江勝偉

財團法人成大研究發展基金會

環境監測及檢測、大氣空氣、環境影響評估

空氣品質指標、成分分析、模式模擬、成本效益

AQI, chemical compositions, CMAQ, cost/benefit analysis

賴信志；蔡德明

邱慧真

06-2386764#

niki@cs.ncku.edu.tw

本計畫之工作內容包括分析細懸浮微粒與臭氧等空氣污染物之空氣品質特性、分析手動測站細懸浮微粒之水溶性離子成分、分析各行業對細懸浮微粒及臭氧之貢獻量和以成本效益研擬細懸浮微粒管制策略。 分析環保署之移動平均值預測紫爆發生之正確率，北部與東部之正確率較高，可達99%左右，往南部有下降趨勢，正確率最低之空品區出現在雲嘉南地區，為97.4%，紫爆預報正確率在下午一點及兩點最高，凌晨十二點時最低。整理分析103、104年AQI指標不良時之主要指標污染物，AQI大於100及150主要指標污染物為PM2.5、O3 8小時，大於200主要為O3 8小時，103年全台AQI大於100站日數比率為25.4%、大於150為7.0%、大於200為0.14%，104年AQI大於100站日數比率為20. 5%、大於150為4.5%、大於200為0.05%。 使用離子層析儀分析PM2.5中水溶性離子成分之分析結果，全台監測站皆以SO42-佔比例最高，且皆超過20%，NH4+與NO3-次之，NH4+約佔9%～14%，NO3-全台變化較大，約佔3%～12%，其餘離子皆不足5%。有機酸佔細懸浮微粒比例，全台監測站中，除了陽明站以外皆為草酸鹽佔比例最高約0.7%～0.9%，甲酸鹽其次約0.2%～0.7%，其餘離子皆不足0.3%。北部及花東空品區I值小於2時段佔多數，其餘空品區則以大於2時段佔多數，各空品區J值普遍小於1，顯示氨氣不足以中和硝酸鹽。以草酸鹽與鉀鹽比例推估生質燃燒貢獻之草酸鹽，台灣各空品區皆於6月及10月～12月，草酸鹽受到生質燃燒影響較大，全台平均貢獻比例約12%～17%；全年平均空間貢獻量分布，台灣本島貢獻量在7.5%～12.5%，朴子、彰化、新竹等地區受影響較大，約10.5～12.5%。103年北中南部之有機酸變化，草酸濃度中南部皆大於北部，且皆有夏低冬高的情形。103年挑選新營站醣類之分析，除了左旋葡萄糖外，其餘皆小於0.5%，而左旋葡萄糖明顯呈現夏低冬高，尤其是十一月中至十二月底期間之高濃度與高比例。以左旋葡萄糖推估103年生質燃燒對PM2.5之貢獻，7月4日中部空品區生質燃燒有較高的貢獻比例(2～8%)；12月22日中部(5～19%)和雲嘉南(7～18%)空品區有較高的貢獻比例；新營站全年則以冬季為大，貢獻比例可至20%。 以Models-3/CMAQ模式模擬全台行業別空污排放對全台PM2.5之影響，每萬噸PM2.5排放，以餐飲業之貢獻比例最高，為6.85%，其次為鋪面車行揚塵(5.88%)與自用小客車(5.62%)；每萬噸SOx排放，以非金屬礦物製品製造業之2.2%最高，其次為塑膠製品製造業(1.23%)與紡織業(1.21%)；每噸NOx排放，以印刷電路板-面源之貢獻比例最高，為5.32%，其次為餐飲業 (3.83%)與二行程機車(1.03%)； NMHC的部分於模擬結果中，發現對衍生性PM2.5並無明顯的貢獻情形。使用CMAQ模擬台中電廠對全台PM2.5之影響，結果顯示PM2.5濃度大於35 μg/m3時，台中電廠於中部及雲嘉南地區有較高的貢獻比例，最高為朴子站之3.81%；PM2.5濃度大於50 μg/m3時，北部及中部有明顯高貢獻比例的產生，其發生站為大園站之6.05%及南投站之6.30%。由CMAQ之模擬結果，分析2013年1、4、7及10月之臭氧敏感度，中部以南地區主要為NOx控制的日數較多，東部地區及北部地區則偏向於VOC控制。其中1、4及10月與年平均趨勢相同，VOC控制集中在北部及東部地區，而7月則是集中於中部地區。 以全台灣細懸浮微粒濃度(基準年：2013年，周界年平均濃度24m/m3)減量5%、10%、15%、20%以及25% 五個情境進行模擬，於25%減量情境時，粒狀物、硫氧化物及氮氧化物減量比例皆接近最大控制效率，總成本為467億元，污染物減量應優先去除粒狀物，再去除硫氧化物，最後再去除氮氧化物。

空氣品質指標、成分分析、模式模擬、成本效益

2016EPA final-公告版20170605.pdf

10MB

2017/7/1 上午 12:00:00

The purposes of this project include to evaluate the PM2.5 forecasting system, to analyze the water soluble chemical species in PM2.5, to evaluate the contributions of various sectors to PM2.5 and ozone based on TEDS9 and to evaluate the various control strategies based on cost/benefit analyses. The results show that the correct ratios of DAQI forecasting system for PM2.5 are the greatest, up to 99%, at northern and eastern Taiwan and are the least, about 97%, at Yuchinan air basin. The results of air quality index (AQI) shows that the major air pollutants are fine particles and ozone 8-hour average for AQI greater than 100. Note that the dominant pollutant for AQI greater than 200 is ozone 8-hour average. The concentrations of water soluble chemical species in PM2.5 are analyzed by ion chromatography. The results show that the major species are sulfate, ammonium, and nitrate. The fractions of sulfate are the greatest among all analyzed species and are greater than 20% at all sites; those of ammonium and nitrate are 9%～14% and 3%～12%, respectively. Among the analyzed water soluble organic species, the fractions of oxalate, 0.7%～0.9%, are the greatest except for the Yangmin site, followed by formate of 0.2%～0.7%. The concentrations of oxalate in southern Taiwan are greater than those in northern Taiwan and are greater in winter season. The contributions of biomass sources to oxalate are 7.5%～12.5% in Taiwan based on the ratios of oxalate and potassium and the greater contributions periods are in June and October to December, which are the major rice straw open burning periods in Taiwan. The concentrations of levoglucosan、mannosan、galactosan and threitol are greater in winter season, especially in November and December. Levoglucosan is also used as tracer to estimate the contributions of biomass sources to the ambient fine particle concentrations. The results show that the contributions of biomass sources to ambient fine particle concentrations are about 5～19% and 7～18% at central and Yuchinan air basins, respectively. The contributions of various sectors to the ambient fine particle and ozone concentrations are evaluated by Models-3/CMAQ. For every ten thousand tons of fine particles emitted, the contribution of cooking, 6.85%, is the greatest, followed by dust from paved road, 5.88%, and passenger car, 5.62%. For NOx, the contribution of printed circuit board,5.32%, is the greatest, followed by cooking, 3.83%, and two-stroke motorcylse, 1.03%. The annual average contribution of Taichung power plant to the ambient fine particle concentration is 2.3% in Taiwan based on the simulation by CMAQ. Note that the contribution to each site may be up to 6.3% at PM2.5 daily concentration greater than 50 μg/m3. The sensitivity analysis for ozone control has been conducted by observation based method using the ratio of H2O2 to HNO3. The results shows that VOC-control for northern Taiwan and NOx-control for central and southern Taiwan in ozone season. The cost/benefit analysis for fine particle control shows that the order of pollutant control is primary particle, SO2 and NOx. The amounts of primary fine particle, SO2 and NOx need to be reduced are 27300 tons, 89400 tons, and 178400 tons, respectively and these are 70.9%, 85.0%, and 51.9% of the emission of year 2013. However, these end-of-pipe control measures can only reduce the ambient fine particle concentration by 25%.

AQI, chemical compositions, CMAQ, cost/benefit analysis