Abstract

Abstract. High-resolution modelling is needed to understand urban air quality and pollutant dispersion in detail. Recently, the PALM model system 6.0, which is based on large-eddy simulation (LES), was extended with the detailed Sectional Aerosol module for Large Scale Applications (SALSA) v2.0 to enable studying the complex interactions between the turbulent flow field and aerosol dynamic processes. This study represents an extensive evaluation of the modelling system against the horizontal and vertical distributions of aerosol particles measured using a mobile laboratory and a drone in an urban neighbourhood in Helsinki, Finland. Specific emphasis is on the model sensitivity of aerosol particle concentrations, size distributions and chemical compositions to boundary conditions of meteorological variables and aerosol background concentrations. The meteorological boundary conditions are taken from both a numerical weather prediction model and observations, which occasionally differ strongly. Yet, the model shows good agreement with measurements (fractional bias <0.67, normalised mean squared error <6, fraction of the data within a factor of 2 >0.3, normalised mean bias factor <0.25 and normalised mean absolute error factor <0.35) with respect to both horizontal and vertical distribution of aerosol particles, their size distribution and chemical composition. The horizontal distribution is most sensitive to the wind speed and atmospheric stratification, and vertical distribution to the wind direction. The aerosol number size distribution is mainly governed by the flow field along the main street with high traffic rates and in its surroundings by the background concentrations. The results emphasise the importance of correct meteorological and aerosol background boundary conditions, in addition to accurate emission estimates and detailed model physics, in quantitative high-resolution air pollution modelling and future urban LES studies.

Highlights

  • Exposure to outdoor air pollution is a major global threat resulting up to 0.8 million premature deaths in Europe (Lelieveld et al, 2019) and 3 million worldwide (Lelieveld et al, 2015; WHO, 2016) every year

  • As the observed wind speed at Kivenlahti and the one modelled by MetCoOp Ensemble Prediction System (MEPS) differ, we separately investigate the model sensitivity to the incoming wind direction

  • OMETOPSD and OWD,mastOPSD, for which the meteorological boundary conditions are taken from MEPS but the incoming wind direction is replaced with the one measured on the Kivenlahti mast, result in a similar pattern for the difference in the horizontal distribution of Ntot compared to MMETMPSD (Fig. 11a, c)

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Summary

Introduction

Exposure to outdoor air pollution is a major global threat resulting up to 0.8 million premature deaths in Europe (Lelieveld et al, 2019) and 3 million worldwide (Lelieveld et al, 2015; WHO, 2016) every year. Measurements from a single monitoring station nearest to the individual’s residence, hospital, or primary health care clinic have commonly been applied in air pollution exposure studies (Andersen et al, 2012; Adam et al, 2015), which can lead to notable errors Both the size and chemical composition of aerosol particles are of major importance when it comes to their health impacts (Kampa and Castanas, 2008; Kelly and Fussell, 2012). To further assess the performance of SALSA2.0 in the PALM model system 6.0 in simulating the spatial distribution of aerosol particle concentrations in an urban area and to examine the importance of meteorological and aerosol background boundary conditions, we will use observations made during an extensive measurement campaign in an urban neighbourhood in Helsinki, Finland, in summer and winter 2017.

Measurement campaign
Additional measurements
Model description
Model domain and morphological data
Meteorological boundary conditions
Air pollutant background concentrations
Air pollutant emissions
Model setup
Comparison of the modelled and observed boundary conditions
Performance measures
Horizontal distribution of total aerosol particle number concentration
Vertical profile of the lung-deposited surface area
Aerosol size distribution
Aerosol chemical composition
Background meteorological conditions
Findings
Discussion and conclusions
Full Text
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