1030323

103

4,860,000 千元

2014/04/22

2015/04/21

張簡國平

嘉義市政府環境保護局

王辰文

正修科技大學

大氣空氣、環境監測及檢測

細懸浮微粒、化學成分分析、空氣品質模式模擬、管制策略

PM2.5, Chemical Analysis, Air Quality Modeling, Control Strategy

林聖倫；袁中新

林聖倫

07-7358800#2605

sllin100@gcloud.csu.edu.tw

本計畫透過四季人工採樣進行嘉義市周界大氣PM2.5質量濃度及成分分析，採樣分別訂於七~八月、十月、十二月、及二~三月。運用採樣分析結果進行CMB受體模式模擬以推估各類污染源貢獻比例，並佐以逆軌跡模式模擬以支持污染源方向。於本市污染源所產生之原生性PM2.5及衍生性前驅物對於本市空氣中PM2.5濃度影響，本計畫透過空品模式Model-3/CMAQ進行嘉義市總體排放貢獻模擬，使用三個環保署建議案例區間，另使用ISC ST3進行本市轄區內原生性污染源排放模擬，具體完成內容如下： 1.春季PM2.5濃度33~61 μg/m3，PM2.5/PM10比例45.9~58.0%，落於一般都會區間。春季盛行西北及北風，於本市東北及西北均出現較高濃度值，有氣團經過本市轄區後於下風處粒狀物近山累積現象。水溶性離子比例58.7%、碳含量14.4%、金屬5.1%。離子成分以NO3- (22.4%)最多，SO42- (16.8%)次之，NH4+ (14.3%)第三，碳成分以OC (10.1%) > EC (4.9%)。 2.夏季PM2.5濃度9~22 μg/m3，PM2.5/PM10為33.3~42.9%，低於一般高濃度季節，顯示本季周界空氣環境較佳，推測乃因歇性降雨出現。水溶性離子39.1%、碳含量18.0%、金屬13.0%。離子成分以SO42- (21.8%)最多，NH4+ (8.8%)次之，NO3- (7.2%)第三，碳成分以OC (10.6%) > EC (7.4%)。 3.秋季PM2.5濃度21~74 μg/m3之間，本季103年11月1日出現高濃度74 μg/m3，為103年嘉義測站秋季最高濃度。PM2.5/PM10為34.9~59.1%，高於前述夏季結果，推測因氣溫下降、垂直對流高度壓縮，偏北風導致轄區外移入加強等影響。水溶性離子54.2%、碳含量10.2%、金屬7.5%。離子成分以SO42- (21.9%)最多，NO3- (16.6%)次之，NH4+ (11.0%)第三，碳成分以OC (6.4%) > EC (3.8%)。 4.冬季PM2.5濃度29~69 μg/m3之間。本季有四日公告警戒日，測站濃度分別為31~50 μg/m3，其中一日預報高估，其餘均超過法規。PM2.5/PM10為52.9~67.9%，顯示粒狀物高濃度季節其粒徑小之顆粒亦增高，對於市民健康具負面影響潛勢。水溶性離子59.2%、碳含量13.7%、金屬4.6%。離子成分以NO3- (20.7%)最多，SO42- (17.5%)次之，NH4+ (12.6%)第三，碳成分以OC (9.5%) > EC (3.9%)。 5.高濃度案例分析，本市PM2.5高濃度出現分為二種類型。 (1)其一為轄區外移入，如103年11月1日，嘉義測站濃度為74 μg/m3，屬本年度秋季最高值，由中部以南所有環保署測站濃度時間空間分布，出現PM2.5濃度峰值由中部向南傳輸至雲嘉南空品區，有近山累積現象發生，並匯集繼續南進傳輸經嘉義至下風處高屏地區，經本市人口及交通密集區後無累積現象發生。 (2)第二類為地區性排放累積104年1月18及21日，嘉義測站濃度分別為67及55 μg/m3，採樣期間中部以南各地PM2.5濃度峰值出現時間相同，PM2.5濃度並無順風向傳輸之明顯變化，當日低溫(17~19oC)導致氣團傳輸能力下降，高濃度值可能源於區域性排放累積，而出現以高雄(工業及城市)地區偏高之分布。 6.量化氣態前驅物、氣象條件對於PM2.5濃度之影響。利用不同氣象條件進行PM2.5「超標與否」之統計分析，其中於邏輯斯回歸分析式中，可回歸求得超標事件是否發生之機率，故藉由上述之春、夏、秋及冬季之四季邏輯斯回歸方程式，配合各因子數值帶入後即可求得不同條件下之發生PM2.5超標機率。若此法經環保署測站測值驗證可得良好之再現性，未來可衍生為使用前24小時平均參數進行隔日平均值之回歸，進而推演出可於24小時前預測隔日PM2.5超標機率之迴歸分析式。 7.受體模式模擬結果，春季污染源貢獻依序為衍生性硝酸鹽、交通源、衍生性硫酸鹽、土壤揚塵、石化業及農廢燃燒。夏季污染貢獻源依序為衍生性硫酸鹽、衍生性硝酸鹽、土壤揚塵、石化業、交通源、海水飛沫、水泥業及鋼鐵業。秋季污染貢獻源依序為衍生性硫酸鹽、衍生性硝酸鹽、交通源、石化業、土壤揚塵、農廢燃燒、海水飛沫、水泥業及鋼鐵業。冬季污染貢獻源依序為交通源、衍生性硝酸鹽、衍生性硫酸鹽、農廢燃燒、石化業、土壤揚塵、海水飛沫、鋼鐵業及水泥業。 8.推估嘉義市污染源對本身所造成的各季PM2.5增量影響如下表，可見本市自體貢獻以夏、秋季較高，冬、春季較低。本市總污染源貢獻：春季0.74%、夏季7.30%、秋季4.30%、冬季0.19%。 9.管制策略建議依照我國環保署施行大方向分為下列各點，詳見報告書第六章。 1.污染源減量管制措施 移動源管制對策 逸散源管制對策 固定源管制對策 宣導及防護 2.境外傳輸影響 3.空氣品質預警與應變 4.強化行政管制工具 5.加強政策與民眾溝通 6.推動跨局處合作

細懸浮微粒、化學成分分析、空氣品質模式模擬、管制策略

103嘉義PM2.5_期末正式報告.pdf

16MB

2015/7/1 上午 12:00:00

This project focuses on the atmospheric fine particle (PM2.5) levels and compositions around Chiayi City. The samples were taken with four seasons, including July to August (summer), October (autumn), December (winter), and February to March (spring). The results of atmospheric PM2.5 concentration and chemical compositions during all sampling season were input to chemical mass balance (CMB) model to simulate the contributions from various emission sources. For determining the contributions of primary particles and secondary gaseous precursors from the various pollution sources, the Model-3/CMAQ was employed to analyze three periodical events suggested by Taiwan EPA. The summery of whole project is as follows: 1.In spring, the PM2.5 concentrations were 33-61 μg/m3. The PM2.5/PM10 ratios were 45.9-58.0%, which is among the levels of normal urban area. The main wind direction were NW and N, leading to the relatively higher PM2.5 levels around the east of Chiayi City. The particulate accumulation in valley or near-mountain location occurred. The mass concentration of PM2.5 were mainly composed of 58.7% water soluble ions 14.4% carbonates, and 5.1% metals. The ion contents were majorly composed of NO3- (22.4%), SO42- (16.8%), and NH4+ (14.3%). The average OC (10.1%) mass content was higher the EC (4.9%). 2.In summer, the PM2.5 concentrations were 9-22 μg/m3. The PM2.5/PM10 ratios were 33.3-42.9%, which is significantly lower than other seasons. This could be resulted from the inhibition of primary particles and secondary gaseous precursors by temporal precipitation. The mass concentration of PM2.5 were mainly composed of 39.1% water soluble ions 18.0% carbonates, and 13.0% metals. The ion contents were majorly composed of SO42- (21.8%), NH4+ (8.8%), and NO3- (7.2%). The average OC (10.6%) mass content was higher the EC (7.4%). 3.In fall, the PM2.5 concentrations were 21-74 μg/m3, when the seasonal highest PM2.5 level occurred (74 μg/m3) at November 11th, 2014. The PM2.5/PM10 ratios were 34.9-59.1%, which is higher than those in summer. This could be resulted from the reducing temperature and the height of atmospheric boundary layer, which further inhibited the diffusion and concentrate the PM2.5 pollution. Also, the immigration of PM2.5 was along with the N wind from other regions. The mass concentration of PM2.5 were mainly composed of 54.2% water soluble ions 10.2% carbonates, and 7.5% metals. The ion contents were majorly composed of SO42- (21.9%), NO3- (16.6%), and NH4+ (11.0%). The average OC (6.4%) mass content was higher the EC (3.8%). 4.In winter, the PM2.5 concentrations were 29-69 μg/m3. There were four forecasting PM alert dates with concentration by 31-50 μg/m3. The PM2.5/PM10 ratios were 52.9-67.9%, reporting the higher fine particle level with more potential harmful effects than other seasons. The mass concentration of PM2.5 were mainly composed of 59.2% water soluble ions 13.7% carbonates, and 4.6% metals. The ion contents were majorly composed of SO42- (20.7%), NO3- (17.5%), and NH4+ (12.6%). The average OC (9.5%) mass content was higher the EC (3.9%). 5.There were two types of higher PM2.5 period: immigrating and local emission. (1)Immigrating emission (November 1st, 2014). The 24h-average concentration of Chiayi site was 74 μg/m3, which was the highest level in fall in 2014. The peak value of PM2.5 concentration were moved from the mid of Taiwan to Yun-Chia-Nan air quality control region and further to Kao-Ping area. There were no significant accumulation when the atmospheric air stream flow by Chiayi City. (2)Local emission (January 18th and 21st, 2015). The 24h-average concentration of Chiayi site were 67 and 55μg/m3. The PM2.5 local peak values at all sites in Middle, Yun-Chia-Nan, and Kao-Ping air quality control regions occurred at the same date. This indicates the local emission might dominate the PM2.5 increments in this case, as well as the locally higher concentration were around the Kaohsiung area. 6.Quantifying the effects of precursors and meteorological factors to PM2.5 levels. The “possibility of exceeding standard” were calculated by Logistic multi-component regression. The precursors (NOx, SO2, NMHC, and O3) levels and meteorological factors (temperature, relatively humidity, and wind speed) record by the Chiayi site during 2005-2014 were inputted. The detail seasonal result equation were listed in this report. 7.The main contribution for locally atmospheric PM2.5 by CMB model were as follows (in order of contributions). Spring: secondary nitrate, traffic source, secondary sulfate, re-suspending soil particle, petrochemical industry, and agricultural open burning. Summer: secondary sulfate, secondary nitrate, re-suspending soil particle, petrochemical industry, traffic source, sea salt, cement industry, and metallurgical industry. Fall: secondary sulfate, secondary nitrate, traffic source, petrochemical industry, re-suspending soil particle, agricultural open burning, sea salt, cement industry, and metallurgical industry. Winter: traffic source, secondary nitrate, secondary sulfate, agricultural open burning, petrochemical industry, re-suspending soil particle, sea salt, cement industry, and metallurgical industry. 8.The Taiwan Emission Data System 8.1 (TEDS 8.1) was utilized as the input data to Model-3/CMAQ for modeling seasonal PM2.5 contributions from stationary, mobile, and area sources. Following results show the self-contributions were higher in summer and fall than in winter and spring. Total self-contribution: 0.74% in spring, 7.30% in summer, 4.30% in fall, and 0.19% in winter. 9.The recommendation PM2.5 control strategies for Chiayi City follows the PM2.5 control directions of Taiwan EPA. Please refer to Chapter 6 for detail. (1)Local pollution control Mobile source control strategies Area source control strategies Stationary source control strategies Advocacy and protection (2)The impact of immigrating PM2.5 (3)Air quality alert and emergency management (4)Enhance the administrative control system (5)Improve the public communication (6)Promote the inter-bureau cooperation (7)Continuous sampling, analyzing, modelling, and setting up the fingerprints of local emission sources

PM2.5, Chemical Analysis, Air Quality Modeling, Control Strategy