INVERSE AIR-POLLUTION MODELING OF URBAN-SCALE CARBON-MONOXIDE EMISSIONS

A new recursive least-squares technique is developed to give spatial a nd temporal definition to the adjustments necessary in an emission inv entory, to fit ambient concentration observations optimally. The CIT P hotochemical Airshed Model is used to compute CO concentration distrib utions arising from 29 separate source domains in the South Coast Air Basin of California. A Kalman filter integrated within the model match es predictions with CO observations at 27 locations by superposing the computed distributions with optimal weighting factors. The filter str ucture allows control of the extent to which adjusted emission invento ries are allowed to deviate from a base-case, which already has high s patial and temporal definition. Applied to the Southern California Air Quality Study, 27-29 August 1987, strong temporal dependence was note d in the necessary adjustment to the available CO emission inventory, with a peak factor of 3.0 at midday on weekdays. The spatial resolutio n of the technique revealed new high-emission zones for CO in a corrid or between Pasadena and San Bernardino, in the Riverside-Corona area, and along the Pacific coast on Saturday. In this first such applicatio n to an urban environment, some success was also achieved in correctin g the phasing of emissions for errors arising from the neglect of sour ce-receptor lags in the inverse modelling technique.