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A simple urban air quality model [MODelo de Dispersión Atmosférica Ubana – Generic Reaction Set (DAUMOD-GRS)] was recently developed. One-hour peak O3 concentrations in the Metropolitan Area of Buenos Aires (MABA) during the summer estimated with the DAUMOD-GRS model have shown values lower than 20 ppb (the regional background concentration) in the urban area and levels greater than 40 ppb in its surroundings. Due to the lack of measurements outside the MABA, these relatively high ozone modelled concentrations constitute the only estimate for the area. In this work, a methodology based on the Monte Carlo analysis is implemented to evaluate the uncertainty in these modelled concentrations associated to possible errors of the model input data. Results show that the larger 1-h peak O3 levels in the MABA during the summer present larger uncertainties (up to 47 ppb). On the other hand, multiple linear regression analysis is applied at selected receptors in order to identify the variables explaining most of the obtained variance. Although their relative contributions vary spatially, the uncertainty of the regional background O3 concentration dominates at all the analysed receptors (34.4–97.6%), indicating that their estimations could be improved to enhance the ability of the model to simulate peak O3 concentrations in the MABA. © 2016 Elsevier Ltd


Documento: Artículo
Título:Uncertainty of modelled urban peak O3 concentrations and its sensitivity to input data perturbations based on the Monte Carlo analysis
Autor:Pineda Rojas, A.L.; Venegas, L.E.; Mazzeo, N.A.
Filiación:Centro de Investigaciones del Mar y la Atmósfera (CIMA/CONICET-UBA), DCAO/FCEN, UMI-IFAECI/CNRS, Ciudad Universitaria, Pabellón II, Piso 2. 1428, Buenos Aires, Argentina
Department of Chemical Engineering, Avellaneda Regional Faculty, National Technological University, CONICET, Av. Ramón Franco 5050, 1874, Avellaneda, Buenos Aires, Argentina
Palabras clave:Air quality; Model uncertainty; Monte Carlo analysis; Ozone; Sensitivity; Air quality; Input output programs; Linear regression; Monte Carlo methods; Ozone; Quality control; Regression analysis; Background concentration; Generic reaction set; Model uncertainties; Monte carlo analysis; Multiple linear regression analysis; Relative contribution; Sensitivity; Urban air quality; Uncertainty analysis; nitrogen oxide; oxygen; ozone; volatile organic compound; air quality; concentration (composition); data assimilation; error analysis; metropolitan area; Monte Carlo analysis; ozone; uncertainty analysis; air quality; air temperature; Article; controlled study; Monte Carlo method; multiple linear regression analysis; photolysis; priority journal; sensitivity analysis; solar radiation; titrimetry; urban area; wind; Argentina; Buenos Aires [Argentina]
Página de inicio:422
Página de fin:429
Título revista:Atmospheric Environment
Título revista abreviado:Atmos. Environ.
CAS:nitrogen oxide, 11104-93-1; oxygen, 7782-44-7; ozone, 10028-15-6


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---------- APA ----------
Pineda Rojas, A.L., Venegas, L.E. & Mazzeo, N.A. (2016) . Uncertainty of modelled urban peak O3 concentrations and its sensitivity to input data perturbations based on the Monte Carlo analysis. Atmospheric Environment, 141, 422-429.
---------- CHICAGO ----------
Pineda Rojas, A.L., Venegas, L.E., Mazzeo, N.A. "Uncertainty of modelled urban peak O3 concentrations and its sensitivity to input data perturbations based on the Monte Carlo analysis" . Atmospheric Environment 141 (2016) : 422-429.
---------- MLA ----------
Pineda Rojas, A.L., Venegas, L.E., Mazzeo, N.A. "Uncertainty of modelled urban peak O3 concentrations and its sensitivity to input data perturbations based on the Monte Carlo analysis" . Atmospheric Environment, vol. 141, 2016, pp. 422-429.
---------- VANCOUVER ----------
Pineda Rojas, A.L., Venegas, L.E., Mazzeo, N.A. Uncertainty of modelled urban peak O3 concentrations and its sensitivity to input data perturbations based on the Monte Carlo analysis. Atmos. Environ. 2016;141:422-429.