Modelling high particulate matter and ozone episodes in the Trans-Manche region

There is concern in the Cross-Channel region of Nord-Pas-de-Calais (France) and Kent (Great Britain), regarding the extent of atmospheric pollution detected in the area from emitted gaseous (VOC, NOx, S02)and particulate substances. In particular, the air quality of the Cross-Channel or "Trans-Manche" region is highly affected by the heavily industrial area of Dunkerque, in addition to transportation sources linked to cross-channel traffic in Kent and Calais, posing threats to the environment and human health. In the framework of the cross-border EU Interreg IIIA activity, the joint Anglo-French project, ATTMA, has been commissioned to study Aerosol Transport in the Trans-Manche Atmosphere. Using ground monitoring data from UK and French networks and with the assistance of satellite images the project aims to determine dispersion patterns. and identify sources responsible for the pollutants. The findings of this study will increase awareness and have a bearing on future air quality policy in the region. Public interest is evident by the presence of local authorities on both sides of the English Channel as collaborators. The research is based on pollution transport simulations using (a) Lagrangian Particle Dispersion (LPD) models, (b) an Eulerian Receptor Based model. This paper is concerned with part (a), the LPD Models. Lagrangian Particle Dispersion (LPD) models are often used to numerically simulate the dispersion of a passive tracer in the planetary boundary layer by calculating the Lagrangian trajectories of thousands of notional particles. In this contribution, the project investigated the use of two widely used particle dispersion models: the Hybrid Single Particle Lagrangian Integrated Trajectory (HYSPLIT) model and the model FLEXPART. In both models forward tracking and inverse (or·. receptor-based) modes are possible. Certain distinct pollution episodes have been selected from the monitor database EXPER/PF and from UK monitoring stations, and their likely trajectory predicted using prevailing weather data. Global meteorological datasets were downloaded from the ECMWF MARS archive. Part of the difficulty in identifying pollution sources arises from the fact that much of the pollution outside the monitoring area. For example heightened particulate concentrations are to originate from sand storms in the Sahara, or volcanic activity in Iceland or the Caribbean work identifies such long range influences. The output of the simulations shows that there are notable differences between the formulations of and Hysplit, although both models used the same meteorological data and source input, suggesting that the identification of the primary emissions during air pollution episodes may be rather uncertain.

Airborne transport of Saharan dust to the Mediterranean and to the Atlantic

The Sahara desert is a significant source of particulate pollution not only to the Mediterranean region, but also to the Atlantic and beyond. In this paper, PM 10 exceedences recorded in the UK and the island of Crete are studied and their source investigated, using Lagrangian Particle Dispersion (LPD) methods. Forward and inverse simulations identify Saharan dust storms as the primary source of these episodes. The methodology used allows comparison between this primary source and other possible candidates, for example large forest fires or volcanic eruptions. Two LPD models are used in the simulations, namely the open source code FLEXPART and the proprietary code HYSPLIT. Driven by the same meteorological fields (the ECMWF MARS archive and the PSU/NCAR Mesoscale model, known as MM5) the codes produce similar, but not identical predictions. This inter-model comparison enables a critical assessment of the physical modelling assumptions employed in each code, plus the influence of boundary conditions and solution grid density. The outputs, in the form of particle concentrations evolving in time, are compared against satellite images and receptor data from multiple ground-based sites. Quantitative comparisons are good, especially in predicting the time of arrival of the dust plume in a particular location.