APFoam 1.0: integrated computational fluid dynamics simulation of O ₃–NO _x–volatile organic compound chemistry and pollutant dispersion in a typical street canyon

Urban air quality issues are closely related to human health and economic development. In order to investigate street-scale flow and air quality, this study developed the atmospheric photolysis calculation framework (APFoam 1.0), an open-source computational fluid dynamics (CFD) code based on OpenFOAM, which can be used to examine microscale reactive pollutant formation and dispersion in an urban area. The chemistry module of APFoam has been modified by adding five new types of reactions, which can implement the atmospheric photochemical mechanism (full Oinline-formula₃–NOinline-formula_x–volatile organic compound chemistry) coupled with a CFD model. Additionally, the model, including the photochemical mechanism (CS07A), air flow, and pollutant dispersion, has been validated and shows good agreement with SAPRC modeling and wind tunnel experimental data, indicating that APFoam has sufficient ability to study urban turbulence and pollutant dispersion characteristics. By applying APFoam, Oinline-formula₃–NOinline-formula_x–volatile organic compound (VOC) formation processes and dispersion of the reactive pollutants were analyzed in an example of a typical street canyon (aspect ratio inline-formula $M7inlinescrollmathmlH/W=\mathrm{normal\; 1}$ 45pt14ptsvg-formulamathimgd0e7f4a98d63957985a8b6c793eb6bee gmd-14-4655-2021-ie00001.svg45pt14ptgmd-14-4655-2021-ie00001.png ). The comparison of chemistry mechanisms shows that Oinline-formula₃ and NOinline-formula₂ are underestimated, while NO is overestimated if the VOC reactions are not considered in the simulation. Moreover, model sensitivity cases reveal that 82 %–98 % and 75 %–90 % of NO and NOinline-formula₂, respectively, are related to the local vehicle emissions, which is verified as the dominant contributor to local reactive pollutant concentration in contrast to background conditions.

In addition, a large amount of NOinline-formula_x emissions, especially NO, is beneficial to the reduction of Oinline-formula₃ concentrations since NO consumes Oinline-formula₃. Background precursors (NOinline-formula_x/VOCs) from boundary conditions only contribute 2 %–16 % and 12 %–24 % of NO and NOinline-formula₂ concentrations and raise Oinline-formula₃ concentrations by 5 %–9 %. Weaker ventilation conditions could lead to the accumulation of NOinline-formula_x and consequently a higher NOinline-formula_x concentration but lower Oinline-formula₃ concentration due to the stronger NO titration effect, which would consume Oinline-formula₃. Furthermore, in order to reduce the reactive pollutant concentrations under the odd–even license plate policy (reduce 50 % of the total vehicle emissions), vehicle VOC emissions should be reduced by at least another 30 % to effectively lower Oinline-formula₃, NO, and NOinline-formula₂ concentrations at the same time. These results indicate that the examination of the precursors (NOinline-formula_x and VOCs) from both traffic emissions and background boundaries is the key point for understanding Oinline-formula₃–NOinline-formula_x–VOCs chemistry mechanisms better in street canyons and providing effective guidelines for the control of local street air pollution.