Abstract

Abstract. Chemical and dynamical processes lead to the formation of aerosol layers in the upper planetary boundary layer (PBL) and above it. Through vertical mixing and entrainment into the PBL these layers may contribute to the ground-level particulate matter (PM); however, to date a quantitative assessment of such a contribution has not been carried out. This study investigates this aspect by combining chemical and physical aerosol measurements with WRF/Chem (Weather Research and Forecasting with Chemistry) model simulations. The observations were collected in the Milan urban area (northern Italy) during the summer of 2007. The period coincided with the passage of a meteorological perturbation that cleansed the lower atmosphere, followed by a high-pressure period favouring pollutant accumulation. Lidar observations revealed the formation of elevated aerosol layers and evidence of their entrainment into the PBL. We analysed the budget of ground-level PM2.5 (particulate matter with an aerodynamic diameter less than 2.5 μm) with the help of the online meteorology–chemistry WRF/Chem model, focusing in particular on the contribution of upper-level processes. Our findings show that an important player in determining the upper-PBL aerosol layer is particulate nitrate, which may reach higher values in the upper PBL (up to 30% of the aerosol mass) than in the lower PBL. The nitrate formation process is predicted to be largely driven by the relative-humidity vertical profile, which may trigger efficient aqueous nitrate formation when exceeding the ammonium nitrate deliquescence point. Secondary PM2.5 produced in the upper half of the PBL may contribute up to 7–8 μg m−3 (or 25%) to ground-level concentrations on an hourly basis. The residual aerosol layer above the PBL is also found to potentially play a large role, which may occasionally contribute up to 10–12 μg m−3 (or 40%) to hourly ground-level PM2.5 concentrations during the morning hours. Although the results presented here refer to one relatively short period in one location, this study highlights the importance of considering the interplay between chemical and dynamical processes occurring within and above the PBL when interpreting ground-level aerosol observations.

Highlights

  • We focus on the interplay between dynamical and chemical processes in the vertical direction in order to better understand the budget terms making up the ground-level particulate matter, a common measure to evaluate air quality

  • TNO emissions are adapted to WRF/Chem following the methodology used by Tuccella et al (2012), with minor changes derived from the second phase of the Air Quality Modelling Evaluation International Initiative (AQMEII) (Alapaty et al, 2012; Im et al, 2014a, b)

  • A plume of fresh emissions from the ground is dispersed in the growing convective boundary layer

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Summary

Introduction

A significant contribution to surface aerosol from entrainment and vertical dilution and chemical net production in the boundary layer has been pointed out in recent studies using single-column models (van Stratum et al, 2012; Ouwersloot et al, 2012). Surface and PBL total PM2.5 mass is calculated to be mainly produced by direct emissions and secondary formation by aerosol processes (e.g. condensation and absorption) and removed by horizontal and vertical transport and wet deposition (Zhang et al, 2009; Liu et al, 2011). The controlling processes are different for surface PM number, which is accumulated mainly by homogeneous nucleation and vertical transport, and it is lost mainly by dry deposition and coagulation (Zhang et al, 2010) For primary components such as black carbon (BC), the fate is similar to that of total PM2.5, while for secondary species it is more intricate.

The investigated area
Experimental set-up
Size-segregated aerosol composition
Lidar-ceilometer profiles
Description and set-up
Emissions
Preliminary analysis of the observations
Model verification against available observations
Insights into the budget of the aerosol vertical profile over Milan
Conclusions
Full Text
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