# A Model Chain Application to Estimate Mixing Layer Height Related to PM10 Dispersion Processes

## TL;DR

This paper uses a modeling system to estimate mixing layer height and its impact on PM10 pollution in a region of Italy.

## Contribution

A novel modeling approach combining WRF-ARW and CALMET to assess MLH and PM10 dispersion.

## Key findings

- Modelled MLH, along with rainfall and wind speed, identifies conditions for PM10 accumulation.
- Local emissions are key during critical PM10 events despite favorable meteorological conditions.
- Orography significantly influences local weather dynamics affecting MLH.

## Abstract

The mixing layer height (MLH) is a crucial parameter in order to investigate the near surface concentrations of air pollutants. The MLH can be estimated by measurements of some atmospheric variables, by indirect estimates based on trace gases concentration or aerosol, or by numerical models. Here, a modelling approach is proposed. The developed modelling system is based on the models WRF-ARW and CALMET. This system is applied on Firenze-Prato-Pistoia area (Central Italy), during 2010, and it is compared with in situ measurements. The aim of this work is to evaluate the use of MLH model estimates to characterize the critical episodes for PM10 in a limited area. In order to find out the meteorological conditions predisposing accumulation of PM10 in the atmosphere's lower level, some indicators are used: daily mean wind speed, cumulated rainfall, and mean MLH estimates from CALMET model. This indicator is linked to orography, which has important consequences on local weather dynamics. However, during critical events the local emission sources are crucial to the determination of threshold exceeding of PM10. Results show that the modelled MLH, together with cumulative rainfall and wind speed, can identify the meteorological conditions predisposing accumulation of air pollutant at ground level.