AN EVALUATION OF DISPERSION COEFFICIENTS FOR USE IN AIR
QUALITY MODELS
MANJU MOHAN and T. A. SIDDIQUI1
Centre for Atmospheric Sciences, Indian Institute of Technology, New Delhi-16, India
(Received in final form 24 September, 1996)
Abstract. Standard deviations of concentration in horizontal and vertical directions i.e. y and z
have been estimated by using five different schemes based on empirical (due to Pasquill and Briggs)
schemes and sophisticated methods (due to Irwin, Draxler, Taylor, Hanna et al.). The five schemes are
discussed at length. The purpose of this study is to make use of meteorological observations which
are routinely available, to test all the above methods and intercompare the results with one another
and observations so that the sensitivity of each scheme under various atmospheric stability conditions
could be assessed. It has been found that the existing schemes are good enough to provide reasonable
estimates of dispersion coefficient (y) during highly unstable conditions (Pasquill stability classes
A and B). However, the same is not true for the case when the stability increases from C to F and
turbulence decreases, specifically during stable atmospheric conditions, when the observed values
were found to be much higher than all the existing schemes. This suggests that while we continue
to use the current methods of estimating the dispersion parameters, a rigorous search is required
for methods which give predictions which are close-to-reality during such conditions which are
represented by low levels (in terms of magnitude) of atmospheric turbulence leading to higher levels
of pollution.
As one of the sophisticated methods requires the use of v and w (standard deviations of wind
velocity fluctuation in y and z directions), these have been estimated and validated with observed
data (field experiments conducted by EPRI at Kincaid). Statistical evaluation of v and w based on
performance measures indicate a good performance of the parameterisations adopted in this study. In
the case of w during unstable conditions a comparison of three different schemes with observations