CAMx-LPiG (Comprehensive Air Quality Model with Extensions-Linear Plume in Grid) is an online hybrid model based on the Chemistry and Transport Model (CTM) CAMx, which includes a sub-grid scale module to simulate the dispersion of linear road traffic emissions called LPiG. LPiG is a plume in grid module specifically developed by extending the capabilities of the Lagrangian puff sub-grid model available in CAMx. The online integration of the local scale model within the Eulerian CTM allows for a multiscale simulation of air quality from the regional scale to the urban scale, preserving a coherent description of the chemical state of the atmosphere at all spatial scales and avoiding any double counting of the emissions simulated by the sub-grid module. In this work, the model is presented and evaluated against measured NO2 concentrations for the city of Milan for the month of January 2017. The model can introduce road traffic-induced gradient in NO2 concentration at sub-grid resolution. Moreover, CAMx-LPiG has been shown to reduce bias compared to CAMx stand-alone simulations.

Development and evaluation of the online hybrid model CAMx-LPiG

G. Lonati;
2025-01-01

Abstract

CAMx-LPiG (Comprehensive Air Quality Model with Extensions-Linear Plume in Grid) is an online hybrid model based on the Chemistry and Transport Model (CTM) CAMx, which includes a sub-grid scale module to simulate the dispersion of linear road traffic emissions called LPiG. LPiG is a plume in grid module specifically developed by extending the capabilities of the Lagrangian puff sub-grid model available in CAMx. The online integration of the local scale model within the Eulerian CTM allows for a multiscale simulation of air quality from the regional scale to the urban scale, preserving a coherent description of the chemical state of the atmosphere at all spatial scales and avoiding any double counting of the emissions simulated by the sub-grid module. In this work, the model is presented and evaluated against measured NO2 concentrations for the city of Milan for the month of January 2017. The model can introduce road traffic-induced gradient in NO2 concentration at sub-grid resolution. Moreover, CAMx-LPiG has been shown to reduce bias compared to CAMx stand-alone simulations.
2025
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/1309315
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