Emissions from vehicular sources are a major contribution to air pollution in every country. Air quality models are being used to study the impact of such emissions. The CAL3QHC emissions model was developed by the U.S. Environmental Protection Agency based on California's CAL3Q model. One area of concern with modeling results is uncertainty in input data, in model calculations, and in natural atmospheric processes. The focus of the study is uncertainty in input data for the CAL3QHC roadway model. Two practical methods--the ASTM approach and the least rigid approach--are used to perform the sensitivity analysis on the input parameters. The two important areas in which CAL3QHC requires sensitivity discussions are the emissions source strength of the vehicles in the queue and the link length (which represents the number of vehicles in a queue). The variability of these two parameters results in a nonlinear relationship between the source strengths and the predicted concentrations. Sensitivity analysis of the CAL3QHC model is carried out for a simple roadway intersection with two traffic lanes and two receptor locations (at the corner of the intersection and midblock). With results from the ASTM method, sensitivity indices are calculated for signal timing, traffic volume, number of traffic lanes, and wind speed. Among all indices, wind speed shows the maximum sensitivity on predicted carbon monoxide concentrations. The model needs no calibration because none of the parameters studied show Type IV sensitivity using ASTM results.
Abstract