| 英文摘要 |
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.
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