Air Quality Predictions of the Urban Airshed Model Containing Improved Advection and Chemistry Algorithms

Abstract

We have carried out an extensive study on the effect of replacing the advection and chemistry algorithms of the Urban Airshed Model (UAM) with more accurate algorithms, using the SCAQS episode of August 26−28, 1987, and input data supplied by the California Air Resources Board. Replacing the UAM chemistry solver by the implicit−explicit hybrid solver (IEH) tends to lower the afternoon ozone concentrations somewhat, the afternoon PAN concentrations more noticeably, and the H2O2 concentrations significantly. IEH is also much less likely to have a convergence failure than the UAM solver. Replacing the Smolarkiewicz scheme by the forward Euler Taylor Galerkin scheme (FETG) yields a greater impact. The replacement increases the local peak NO concentrations and lowers the local peak ozone and CO concentrations significantly. Replacing both chemistry and advection algorithms lowers the peak ozone, PAN, and H2O2 concentrations quite noticeably. For example, the predicted peak ozone for August 28 is reduced from 234 to 200 ppb. The complicated wind field for this episode generates two high-ozone subdomains in the modelone in the east and one in the northwest. Reducing the NOx emission by 50% shifts the predicted domainwide peak ozone from the east to the northwest. If we disregard this shift, then the use of more accurate modules in the UAM leads to a 50% increase in the domainwide peak ozone while the original UAM yields a 27% increase. Both the original and improved UAM versions give a 20% increase in peak hourly ozone and a 30% increase in peak 8-h ozone in the eastern subdomain, but much greater and vastly different increases for each of the peak 1-h and peak 8-h ozone concentrations in the northwestern subdomain. The best available numerical methods should be used in modeling a complex system like air quality so that potential hidden errors may be identified and the design of air quality control may be more reliable.