Polluted air models

Air pollution meteorology came of age and, by 1980, mathematical models of the pollution of the atmosphere were being energetically developed. A start had been made in elucidating the photochemistry of air pollution. Air quality monitoring systems became operational throughout the world. A wide variety of measuring instruments became available. 

Killus, J. P., Meyer, J. P., Durran, D. R., Anderson, G. E., Jerskey, T. N., and Whitten, G. Z., "Continued Research in Mesoscale Air Pollution Simulation Modeling," Vol. V, "Refinements in Numerical Analysis, Transport, Chemistry, and Pollutant Removal," Report No. ES77-142. Systems Applications, Inc., San Rafael, CA, 1977. 

Air pollution dispersion models derived from the UNAMAP6 stationary source models and other specialized dispersion models. Uses more than 20 models. Requires 512K memory and 132 column printer. 

In this context, it is important to note that a model test simulating the operation of an air pollution control scheme can also be modeled in water. For some air pollution problems, an air model might become quite large in order to ensure modeling the turbulent nature of the prototype flow rate. For some applications, a water model can be used which will give a reasonable scale size. 

PEM (Pollution Episodic Model) is an urban scale air pollution model capable of predicting short-term average surface concentrations and deposition fluxes of two gaseous or particulate pollutants. 

Uncertainties in Photochemical Models. The ability of photochemical models to accurately predict HO concentrations is undoubtedly more reliable in clean vs. polluted air, since the number of processes that affect [HO ] and [H02 ] is much greater in the presence of NMHC. Logan et al (58) have obtained simplified equations for [HO ] and [HO2 ] for conditions where NMHC chemistry can be ignored. The equation for HO concentration is given in Equation E6. The first term in the numerator refers to the fraction of excited oxygen atoms formed in R1 that react to form HO J refers to the photodissociation of hydrogen peroxide to form 2 HO molecules other rate constants refer to numbered reactions above. 

We note several areas of potential concern regarding polluted air chemical models. 

Figure 5. Diurnal HO profiles as predicted by 20 polluted air chemical models. From Hough (165) see that reference for model identities.

Air pollution dispersion modeling, for odor impacts, 26 725 Air preheater, 19 512 Air products and chem systems, methanol process, 26 310-311 Air quality... 

Odor evaluation, in perfumes, 18 379 Odor impacts, air pollution dispersion modeling for, 26 725 Odorous compounds controlling, 10 75 in wastewater, 26 723t Odor panels, 26 724 Odor pollution, 26 669 Odor removal, adsorbents for, 1 611 Odors... 

McRae, G. J., Goodin, W. R., and Seinfeld, J. H. (1982). Development of a second-generation mathematical model for urban air pollution. I. Model formulation. Atmos. Environ. 16, 679-696. 

This brief description of oxidant formation in polluted air is based on our current understanding of the chemistry involved. It is evident fix>m an examination of the detailed mechanism that many of the important reactions have not been well studied. For example, the sequences of degradation reactions for the hydrocarbons are only poorly understood. As a result of these uncertainties, it is not possible to make accurate predictions of photochemical oxidant concentrations. However, with another 5 yr of progress similar to the last 5, it should be possible to construct chemical models that will permit ozone predictions accurate to within... 

The time-series analysis results of Merz et were expressed in first-order empirical formulas for the most part. Forecasting expressions were developed for total oxidant, carbon monoxide, nitric oxide, and hydrocarbon. Fitting correlation coefficients varied from 0.547 to 0.659. As might be expected, the best results were obtained for the primary pollutants carbon monoxide and nitric oxide, and the lowest correlation was for oxidant. This model relates one pollutant to another, but does not relate emission to air quality. For primary pollutants, the model expresses the concentrations as a function of time. 

Egan, B. A., and J. R. Mahoney. Applications of a numerical air pollution transport model to dispersion in the atmospheric boundary layer. J. Appl. Meteorol. 11 1023-1039, 1972. 

Nappo, C. J., Jr. A method for evaluating the accuracy of air pollution prediction models, pp. 325-329. In Preprints. Symposium on Atmospheric Diffusion and Air Pollution of the American Meteorological Sodety, Santa Barbara, California, September 9-13, 1974. Boston American Meteorological Sodety, 1974. 

Trijonis, J. C. Economic air pollution control model for Los Angeles County in 1975. General least cost-air quality model. Environ. Sci. Technol. 8 811-826, 1974. 

While such calculations can be carried out in principle, they are in fact rarely possible in the detail needed for developing reliable air quality/emission source relationships for particulate pollution. Dispersion modeling however, is necessary to predict the air quality effects of a new source which is to be located in a region where air quality/emission source relationships are poorly understood. 

Sander, R., and P. Crutzen, Model Study Indicating Halogen Activation and Ozone Destruction in Polluted Air Masses Transported to the Sea, J. Geophys. Res., 101, 9121-9138 (1996). 

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