Cohan, Daniel S.2011-07-252011-07-252010Tang, Wei. "Influence of uncertainties in vertical mixing algorithms on an air quality model." (2010) Master’s Thesis, Rice University. <a href="https://hdl.handle.net/1911/62085">https://hdl.handle.net/1911/62085</a>.https://hdl.handle.net/1911/62085Vertical diffusion of trace pollutants is a very important physical process that influences pollutant concentrations. However, there are large uncertainties in the numerical modeling of this process, which could affect model predictions of pollutant levels and their responsiveness to emission controls. Uncertainties could result from the formulation of vertical diffusion schemes or from errors in eddy diffusivity and dry deposition velocity parameters associated with this process. Inter-comparisons between different model configurations and sensitivity analysis of model parameters can be used to help quantify these uncertainties. In this study, a comprehensive evaluation of two vertical diffusion schemes, EDDY and ACM2, was performed by comparing ground-level concentrations and vertical profiles generated using the CMAQ model with measurement data from the Texas Air Quality Study II. In addition, new capabilities of conducting sensitivity analysis to dry deposition velocity and eddy diffusivity were implemented into the CMAQ-DDM model. The results show that the ACM2 scheme tends to predict larger secondary pollutant concentrations and smaller primary pollutant concentrations at the surface compared to the EDDY scheme. Differences between the two vertical diffusion schemes and uncertainties in dry deposition velocity may cause temporal variations in the responsiveness of ozone to both NOx and VOC control respectively.application/pdfengCopyright is held by the author, unless otherwise indicated. Permission to reuse, publish, or reproduce the work beyond the bounds of fair use or other exemptions to copyright law must be obtained from the copyright holder.Atmospheric sciencesEnvironmental engineeringInfluence of uncertainties in vertical mixing algorithms on an air quality modelThesisTHESIS C.E. 2010 TANG