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Lagrangian plume and puff models account for chemical processes by simple linear transformations in time. These models can track individual source impacts, thus enabling user to outline source specific air pollution control strategies. Considerable differences are observed when concentrations are compared in time and space because of uncertainties in the characterization of the direction of transport that are of the order of the actual plume width. The observed and simulated concentrations for fixed receptors, give estimates of maximum concentration values within a factor of two or three of those observed.

207-220 Srivastava, Anjali ; ‘Source apportionment of ambient VOCS in Mumbai city Atmospheric Environment’ , Volume 38, Issuey39, December2004, pp. , Bourdeau, P. ), 1995. Office for Publications of the European Communities, Luxemburg. A. Schlosser, S. Dutkiewicz, S. W. , 2008: Sensitivity of the urbanized MM5 (uMM5) to perturbations in surface properties in Houston Texas. Boundary-Layer Meteorology, pp. , 1973. A model for the dynamics of the inversion above a convective boundary layer. 550–567 34 Air Quality - Models and Applications THOR - an Integrated Air Pollution Forecasting and Scenario Management System.

Not undergoing any chemical reactions,  transformation or decay. The spatial dynamics of pollution dispersion is described by the following type of equation in a Gaussian model: C ( x , y , z ; He )  Q  2 u y z    z  He 2    z  He 2    y 2        exp   2   exp     exp  2 y      2 z2  2 z2          (2) Where C(x, y, z) : pollutant concentration at. , in the wind direction and cross-wind, in meters; Q: is the emission strength (g/s) He: is the effective stack height, see below.