This study reviewed four widely used air quality models and concluded that simple Gaussian dispersion models, ISCST3 and AERMOD, are not suitable for modeling N deposition because they fail to represent chemical and phase transformations of nitrogen oxides (NOX) and ammonia (NH3) emissions. It reviewed two models that do represent chemical speciation and formation of aerosols: CALPUFF and the Community Multiscale Air Quality (CMAQ) model. CALPUFF is a trajectory model that adopts several simplifications that raise important concerns regarding its accuracy. CMAQ is a photochemical grid model and includes state-of-the-art science algorithms. The study performed simulations using each model to assess nitrogen (N) deposition from a power plant. CALPUFF predicted slightly lower deposition rates than did CMAQ, and the spatial features of CALPUFF were poorly resolved. For CMAQ, the study simulated calendar year 2002 to develop baseline N deposition estimates throughout California, and then performed a sensitivity simulation with the new power plant to calculate the change in N deposition. The CMAQ predicted higher deposition rates than the CALPUFF model and provided finer spatial resolution. However, the CMAQ model exhibited numerical noise. The authors recommend exploring other photochemical grid models that might have less numerical noise than CMAQ. Perhaps the most significant outcome of this work is the CMAQ model-simulated baseline annual N deposition for a 4-kilometer resolution grid on a domain that includes much of California. These data have also been converted into an ASCII format that can be readily imported into ArcGIS or other GIS software and used in future ecosystem studies of the effects of N deposition and soil nitrification
