COMPARISON OF SIGMA-SCHEMES FOR ESTIMATION OF AIR POLLUTANT DISPERSION IN LOW WINDS

The dispersion coefficients are key parameters in most of the air qual ity models and their use in low wind speed conditions involves some de gree of uncertainty. Various estimates of dispersion parameters are di scussed for low wind conditions. Specifically, schemes viz., standard, split sigma, split sigma theta, segmented plume (I) and (II), short-t erm averaging and U-min approach are studied through intercomparison. The concentration formula used in this intercomparison is obtained fro m the steady-state advection-diffusion equation. The results show that with hourly data of wind velocity and standard deviation of horizonta l wind direction (sigma(theta)), split sigma and split sigma theta sch emes perform much better than the traditional standard method as they take into account the wind direction fluctuations for the horizontal d ispersion. On the other hand, with high-frequency data of wind velocit y and sigma(theta), schemes like segmented plume (I) and (II) and shor t-term averaging simulate the observations much better especially in t erms of the multiple peak nature of the concentration distribution. Th e influence of wind fluctuations from instantaneous plumes is captured by the high-frequency data. Further, short-term averaging scheme has the advantage of not requiring sigma(theta) and still performing well. The difference in these results and those obtained from the Gaussian plume solution has been found to be marginal.