透過您的圖書館登入
IP:18.119.157.134
  • 期刊

風速與污染物濃度頻率分布之關係

The relationship between the frequency distribution of air pollutants and wind speed

摘要


空氣污染物濃度會受到風速的影響。空氣污染物濃度分布與風速之分布有一個簡單的統計模式。當空氣污染物濃度及風速為對數常態分布(lognormal)且幾何標準差(σ_g)相差不大,其關係式為K=CP*u_((100-P)),其中K為一個定值,C_p 為在累積機率為p時之空氣污染物濃度,u_((100-P))為在累積機率為100-p 時之風速。本研究選取1995~2000年忠明站的監測資料,並利用type V Pearson、Weibull及lognormal三種理論分布分別模擬SO_2、CO、PM_(10)及PM_(2.5)濃度及風速之頻率分布,並以Kolmogorov-Smirnov (K-S) test來判斷何種理論分布較符合實際分布。此外本研究並驗證風速與污染物濃度分布之統計關係式是否成立,進而求出污染物之K值和排放量變化率。結果顯示出污染物和風速大多較符合lognormal分布,而污染物與風速的σ_g相差不大,在累積機率20 ~ 80之間時,其C_p與U_*((100-p))乘積接近一常數。顯示K=CP*u_((100-p))之關係成立,而求得之K值在1999年分別為K=_(CO)=1.4m/s *ppm, K_(PM10)=95.2m/s *ppm, K_(PM2.5)=45.6m/s*ppm及.K_(SO2)=5.0 m/s *ppm。而1999~2000年忠明站污染物的排放變化率(EV)分別為EV_(CO)= 3.43%, EV_(PM10)=-1.68%, EV_(PM2.5)=22.08%, EV_(SO2)=1.64%。

關鍵字

排放量變化率

並列摘要


The frequency distribution of air pollutant concentration is influenced by wind speed. When the distributions of air pollutant and wind speed are all lognormal and both of the geometric standard deviations are the same, there exists a simple model, which relates the statistic of the wind speed and air pollution data. The concentration of air pollutant, C, at cumulative probability, p, is inverse proportional to the wind speeds, u, at probability of (100-p). The relationship is K=C_pu_((100-p)). K is constant. In this study, three distributions (lognormal, Weibull and type V Pearson distribution) are taken to fit the PM_(10), PM_(2.5), SO_2, CO and wind speed distribution at Chung-Min stations. The K-S test is used to judge which type of distribution is appropriate to represent the actual air pollutant and wind speed distribution. Moreover, the simple model is demonstrated in this study. The constant K value is calculated and source emission change rate of air pollutant is estimated crudely by this simple model. The results show that the lognormal distribution is the best one distribution to represent the air pollutant concentration and wind speed. It is found that K values of air pollutants are constant when the cumulative probability between 20 ~80%. Therefore, the simple model is held. The K values of CO, PM_(10), PM_(2.5) and SO_2 are 1.4 m/s ppm, 95.2 m/s ppm, 45.6m/s ppm and 5.0 m/s ppm, respectively. Moreover, it is found that the estimated values of emission change rate are about 34%, 20.6 % and 17.4% for PM_(10), SO_2 and CO at Chung-Min station from 1999 to 2000, respectively.

參考文獻


Mage, D. T. and Ott, W. R. (1984) An Evaluation of the Method of Fractiles, Moments and Maximum Likedlihood for Estimating Parameters when Sampling Air Quality Data from a Stationary Lognormal Distribution Atmospheric Environment 18, 163-171.
Mage, D. T., and Ott, W. R. (1978) Refinements of the Lognormal Probability Model for Analysis of Aerometric Data J. Air Pollut. Control Ass. 28, 796-798.
Kao, A. S. and Friedlander, S. K. (1985) Frequency Distributions of PM10 Chemical Components and Their Sources Environ. Sci. and Technol. 29, 19-28.
Georgopoulos, P. G. and Seinfeld, J. H. (1982) Statistical Distribution of Air Pollutant Concentration Environ. Sci. and Technol. 16, 401A-416A.
Morel, B., S. Yen and Cifuentes, L. (1999) Statistical Distribution for Air Pollutant Applied to the Study of Particulate Problem in Santiago Atmospheric Environment 33, 2575-2585.

延伸閱讀