This study applied Monte Carlo analysis with Latin hypercube sampling to evaluate the effects of uncertainty in air parcel trajectory paths, emissions, rate constants, deposition affinities, mixing heights, and atmospheric stability on predictions from a vertically resolved photochemical trajectory model. Uncertainties in concentrations of ozone and other secondary compounds and in predicted changes due to 25% reductions in motor vehicle nonmethane organic compound (NMOC) and nitrogen oxide (NO x ) emissions were examined. Surface wind measurements were interpolated over the modeling domain, and uncertainties were quantified using data withholding. The resulting wind fields and uncertainties were used to generate ensembles of trajectories ending at four Southern California air quality monitoring sites. A motor vehicle emissions inventory and associated uncertainties were derived from remote sensing and fuel sales data. Uncertainties in chemical rate parameters were obtained from expert reviews. Estimated uncertainties in O 3 range across the four sites from 24% to 57% (1 standard deviation (1σ) relative to the mean). Seven variables contribute almost 80% of this uncertainty. Reductions in motor vehicle NMOC reduce O 3 from 10 ( 10% (1σ) to 28 ( 10%. With reductions in motor vehicle (NO x ) emissions, the change in O 3 ranges from an increase of 14 ( 14% to a decrease of 6.6 ( 6.2%.

Attempts to characterize ozone formation as sensitive to either volatile organic compounds (VOC) or NOx within a region oversimplify a problem that shows spatial and temporal variation. California's Central Valley has some of the highest ozone levels in the country and a rapidly growing population, and air quality problems in this region can be influenced by interbasin transport of ozone and its precursors. An Eulerian photochemical airshed model is applied to the region for the period 3–6 August 1990. This episode spans a weekend, and the emission inventory incorporates revised motor vehicle emissions with day‐specific activity patterns. Compared with the baseline inventory, the revised inventory contains higher VOC and lower NOx emissions from motor vehicles and different temporal patterns of these emissions. Revised estimates of biogenic emissions are greatly reduced. The baseline emission inventory used in previous modeling efforts appears to contain compensating errors, with high biogenic emissions making up for low motor vehicle emissions of VOC. Results suggest that heavily urbanized areas around and downwind of the San Francisco Bay and Sacramento are VOC‐sensitive, while the more rural areas are NOx‐sensitive. Ozone formation in the San Joaquin Valley, where progress in reducing ambient ozone concentrations has been slow, exhibits sensitivity to emissions of both VOC and NOx, and is influenced by emissions from the San Francisco Bay Area during this modeling episode.