Development of a fast, urban chemistry metamodel for inclusion in global models

Abstract

A reduced form metamodel has been produced to simulate the effects of physical, chemical, and meteorological processing of highly reactive trace species in urban areas, which is capable of efficiently simulating the urban concentration, surface deposition, and net export flux of these species. A polynomial chaos expansion and the probabilistic collocation method have been used to develop the metamodel, and its coefficients, so that it is 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 nature of the surrounding environment (background concentrations of species). The metamodel development involved using probability distribution functions (PDFs) of the inputs 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. It was determined that the deviations between the metamodel and the parent mode for many important species (O[subscript 3], CO, NO[subscript x], and black carbon (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. In these cases, the complexity and non-linearity of the physical, chemical, and meteorological processing is too large for the third order metamodel to give an accurate fit. Finally, 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 ozone, CO, formaldehyde, BC, and PM[subscript 10] 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 global climate.