Project Description

Due to erosion processes, huge quantities of soil-derived particles are entrained into the atmosphere and transported away from the source, impacting air quality and affecting the Earth’s radiative budget. This thesis addresses those land-atmosphere interactions, dealing with atmospheric mineral aerosol, with a main objective of improving the assessment of longrange transport of African dust focusing on Cape Verde and Portugal. To achieve the objective, dust modelling is employed and combined with observations, including size distributed particle concentrations and optical properties. Three different modelling systems are used, namely BSCDREAM8b, the NMMB/BSC-Dust model and WRF-CHIMERE, with distinct dust production models. In order to improve characterization of the dust size distribution at emission, a new parametrization is tested in this work, leading to a decrease in the emission fine fractions and an increase in the coarser ones, which has an impact in modelled downwind concentrations and optical parameters. Aerosol cycles are characterized and different methods to estimate the contribution of Saharan dust to regional PM levels are implemented and assessed.

Significant dust intrusions from North West Africa severely affect Cape Verde PM surface concentrations during winter. In the summer dust is transported towards the region at higher altitudes, yielding high aerosol optical depths. On a yearly basis, and according to the methodology employed, roughly 42% of the PM10 mass observed in Cape Verde is associated with dust transported from North African deserts. Desert dust outbreaks are less severe in Portugal. Nevertheless, during 2016, at least two dust episodes, occurring in February and October, are responsible for regional exceedances of the PM10 daily limit value defined in the Air Quality Directive.

This study intends to improve the scientific knowledge on processes and sources responsible for mineral dust loading into the atmosphere and to provide new means and valuable information for science-based decision making.

Research Team

University of Aveiro

• Carla Gama da Silva
• Casimiro Pio (supervisor)

CITTA

• Oxana Tchepel (supervisor)

Polytechnic University of Catalonia

• José María Baldasano (supervisor)

Financial Support

• FCT

Stage of Progress

• Finished in 2018