Alternative Models for Air Pollutant Effects on Visibility

Abstract

Air pollution causes visibility reduction in urban areas such as Los Angeles as well as in national parks and wilderness areas. In this work, alternative mathematical models are formulated that relate air pollutant emissions or ambient air pollutant concentrations to visual range or to changes in the appearance of a scenic vista. The first model examined connects continuous measurements of airborne particle size distributions to resulting effects on visibility via Mie scattering calculations. The model is tested by application to data taken during the 1987 Southern California Air Quality study. The time series of measured light scattering coefficient values is reproduced well when redundant nephelometer measurements are available to assure that the measured light scattering coefficient values are not in doubt. A source-oriented model for air pollutant effects on visibility next is assembled that computes light scattering directly from data on gas-phase and primary particle-phase air pollutant emissions from sources. Airborne particle mass concentrations are predicted accurately. The model predictions generally match the measured aerosol size distribution and chemical composition. Good agreement is attained between model predictions and measurements of atmospheric light scattering coefficient values. An image processing-based visibility model is presented that displays model calculations as synthetic color photographs having the appearance of a smog event. Beginning with a digitized clear day photograph of the scene of interest, a theoretically based model for light scattering and absorption is used to recalculate sky color and skylight addition between the observer and objects in the field of view in order to predict the appearance of the scene in the presence of heavy smog. Model verification data are collected experimentally, including photographs of chosen vistas and measurements of the atmospheric aerosol chemical composition and size distribution. The model performs well, producing representations of the sky color and objects in the field of view that are close to those seen in actual photographs. This model also is adapted to begin with data on landscape features taken from earth-orbiting satellites combined with digital terrain elevation data, such that the model could be applied on a global scale.