Abstract

Abstract. In this article we describe the implementation of an online-coupled gas-phase chemistry model in the turbulence-resolving PALM model system 6.0 (formerly an abbreviation for Parallelized Large-eddy Simulation Model and now an independent name). The new chemistry model is implemented in the PALM model as part of the PALM-4U (PALM for urban applications) components, which are designed for application of the PALM model in the urban environment (Maronga et al., 2020). The latest version of the Kinetic PreProcessor (KPP, 2.2.3) has been utilized for the numerical integration of gas-phase chemical reactions. A number of tropospheric gas-phase chemistry mechanisms of different complexity have been implemented ranging from the photostationary state (PHSTAT) to mechanisms with a strongly simplified volatile organic compound (VOC) chemistry (e.g. the SMOG mechanism from KPP) and the Carbon Bond Mechanism 4 (CBM4; Gery et al., 1989), which includes a more comprehensive, but still simplified VOC chemistry. Further mechanisms can also be easily added by the user. In this work, we provide a detailed description of the chemistry model, its structure and input requirements along with its various features and limitations. A case study is presented to demonstrate the application of the new chemistry model in the urban environment. The computation domain of the case study comprises part of Berlin, Germany. Emissions are considered using street-type-dependent emission factors from traffic sources. Three chemical mechanisms of varying complexity and one no-reaction (passive) case have been applied, and results are compared with observations from two permanent air quality stations in Berlin that fall within the computation domain. Even though the feedback of the model's aerosol concentrations on meteorology is not yet considered in the current version of the model, the results show the importance of online photochemistry and dispersion of air pollutants in the urban boundary layer for high spatial and temporal resolutions. The simulated NOx and O3 species show reasonable agreement with observations. The agreement is better during midday and poorest during the evening transition hours and at night. The CBM4 and SMOG mechanisms show better agreement with observations than the steady-state PHSTAT mechanism.

Highlights

  • More than half of the world’s population lives in cities, and the number is expected to exceed two-thirds by the year 2050 (United Nations, 2014)

  • In this article we describe the implementation of an online-coupled gas-phase chemistry model in the turbulence-resolving PALM model system 6.0

  • A number of tropospheric gas-phase chemistry mechanisms of different complexity have been implemented ranging from the photostationary state (PHSTAT) to mechanisms with a strongly simplified volatile organic compound (VOC) chemistry and the Carbon Bond Mechanism 4 (CBM4; Gery et al, 1989), which includes a more comprehensive, but still simplified VOC chemistry

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Summary

Introduction

More than half of the world’s population lives in cities, and the number is expected to exceed two-thirds by the year 2050 (United Nations, 2014). Most of the LES-based pollutant dispersion studies investigated the flow and ventilation characteristics in street canyons (Liu et al, 2002; Walton et al, 2002; Walton and Cheng, 2002; Baker et al, 2004; Cui et al, 2004; Li et al, 2008; Moonen et al, 2013; Keck et al, 2014; Toja-Silva et al, 2017) or other idealized structures These studies indicated that LES coupled air pollution models can help to explain microscale urban features and observed pollutant transport characteristics in cities (Han et al, 2019).

PALM and PALM-4U
The chemistry model
Prognostic equations
Gas-phase chemistry implementation
Photolysis frequencies
Coupling to SALSA aerosol module
Deposition
SMOG 8 CBM4
Traffic emissions
Initial and boundary conditions
Chemistry model application
Modelled episode and modelling domain
Observational data
Model configuration and initialization
Results and discussion
Meteorology
Vertical mixing of NO2 and O3
Spatial distribution of pollutants
Comparison of the three chemical mechanisms
Comparison of pollutant concentrations with observations
Computational efficiency
Concluding remarks

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