A reduced form metamodel has been produced to simulate the effects of physical, chemical, and meteorological processing of highly reactive trace species in hypothetical urban areas, which is capable of efficiently simulating the urban concentration, surface deposition, and net mass flux of these species. A polynomial chaos expansion and the probabilistic collocation method have been used for the metamodel, and its coefficients were fit so as to be applicable under a broad range of present-day and future conditions. The inputs upon which this metamodel have been formed are based on a combination of physical properties (average temperature, diurnal temperature range, date, and latitude), anthropogenic properties (patterns and amounts of emissions), and the surrounding environment (background concentrations of certain species).

Probability Distribution Functions (PDFs) of the inputs were used to run a detailed parent chemical and physical model, the Comprehensive Air Quality Model with Extensions (CAMx), thousands of times. Outputs from these runs were used in turn to both determine the coefficients of and test the precision of the metamodel, as compared with the detailed parent model. The deviations between the metamodel and the parent mode for many important species (O3, CO, NOx, and BC) were found to have a weighted RMS error less than 10% in all cases, with many of the specific cases having a weighted RMS error less than 1%. Some of the other important species (VOCs, PAN, OC, and sulfate aerosol) usually have their weighted RMS error less than 10% as well, except for a small number of cases. These cases, in which the highly non-linear nature of the processing is too large for the third order metamodel to give an accurate fit, are explained in terms of the complexity and non-linearity of the physical, chemical, and meteorological processing. In addition, for those species in which good fits have not been obtained, the program has been designed in such a way that values which are not physically realistic are flagged.

Sensitivity tests have been performed, to observe the response of the 16 metamodels (4 different meteorologies and 4 different urban types) to a broad set of potential inputs. These results were compared with observations of O3, CO, formaldehyde, BC, and PM10 from a few well observed urban areas, and in most of the cases, the output distributions were found to be within ranges of the observations.

Overall, a set of efficient and robust metamodels have been generated which are capable of simulating the effects of various physical, chemical, and meteorological processing, and capable of determining the urban concentrations, mole fractions, and fluxes of species, important to human health and the climate.

The point of developing these computationally efficient metamodels of urban processing is so that they can be used in the context of global modeling efforts. In specific, urban-scale processing has long been excluded in global 3D chemical transport models due to its large computational demands. In this thesis, the metamodel is used to simulate this processing, and compare a set of results against the more traditional approach of dilution of emissions into large grid boxes. This metamodel provides a tool to simulate, in a global 3D model, the effects of cities around the world on aerosol chemistry, physics, and radiative effects at the global scale.

It is then demonstrated that a significant Bias Error = (Dilution Approach - Urban Processing) / Urban Processing is incurred due to the ignoring of urban processing. Specifically, the globally averaged monthly minimum, monthly maximum, and monthly average bias error caused by ignoring urban processing on the total aerosol surface concentration (+0.23, +0.28, and +0.26), the total aerosol column abundance (+0.43, +0.61, and +0.51), the AOD (+0.35, +0.50, and +0.42), and the AAOD (+0.01, +0.18, and +0.09), respectively. This leads to a significant Error = (Dilution Approach - Urban Processing) for the globally averaged monthly minimum, monthly maximum, and monthly average error for the top of the atmosphere radiative forcing (−0.414, −0.168, and −0.272 W/m2), the surface radiative forcing (−1.02, −0.352, and −0.448 W/m2), and the atmospheric radiative forcing (−0.004, +0.849, and +0.176 W/m2), respectively. These results show that failure to consider urban scale processing leads to significantly more negative aerosol radiative forcing in the dilution case, as compared to when detailed urban scale processing is considered.

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