| 英文摘要 |
To develop the control strategy for fine particle(PM2.5) in Taiwan, the contents for this project include literature review, analysis of water soluble ionic species for samples from the Taiwan FRM sampling networks, field measurements of sulfate, nitrate and secondary organic aerosol formation rates, simulation of impacts of various kinds of emission sources by using three-dimensional air quality model CMAQ, and cost/benefit assessment for various control scenarios. The dominant ionic species of fine particle is sulfate whose fraction is greater than 20% at all sites; the fraction of ammonia is about 12% to 18% and that for nitrate varies between 4% to 20% from site to site. Except for eastern Taiwan, the values of J are all greater than one, implying the abundance of gaseous NH3. The type of distribution for all mass concentrations in 2014 is Gamma distribution of (9.6,2.496). Therefore, it is (3.54,4.24) to meet the national ambient air quality standard of PM2.5.
Field campaigns were conducted at nine different sites in southern Taiwan from 19th to 28th November, 2014 simultaneously in order to study the formation rates of secondary aerosol. The time duration for each sample was six hours in order to differentiate the daytime and nighttime. The three-dimensional meteorological conditions were simulated by using WRF and the back-trajectory analyses were performed by using HYSPLIT. The upwind concentration was determined by interpolation among all measurement sites for each six-hour trajectory and the effects of dispersion and dry deposition were adjusted by using ventilation factor and potassium, respectively. The measurement results show that the formation rates for sulfate, nitrate, and SOA are 5.09±3.25%/hr, 1.91±1.68%/hr, and 0.50±0.30%/hr, respectively.
The contributions of various kinds of emissions sources to the ambient fine particle concentrations were simulated by using the three-dimensional grid air quality model CMAQ with the zero-out method. Thirty-one different kinds of emission sources have been simulated with the emission data from TEDS8.1. For primary fine particle, the contribution from cooking and restaurant is the greatest of 10.0% for every ten thousand of PM2.5 emitted, followed by bus of 9.3% and commercial burning of 9.1%. For NOx, the contribution from clothes industry is the greatest of 0.53% for every ten of NOx emitted, followed by glass industry and electronic industry of 0.52% both. For SO2, the contribution from bus is the greatest of 1.1% for every ten thousand of SO2 emitted, followed by commercial burning of 0.93% and electronic industry of 0.89%. Significant differences have been found in the cost/benefit analysis whether the existing control efficiency is taken into account. For adding control measures into the existing emission sources, the maximum reduction efficiency is 27% and the annual cost is 230 billion NT$.
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