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Atmospheric dispersion modelling of particulate and gaseous pollutants affecting the trans-Manche region

Atmospheric dispersion modelling of particulate and gaseous pollutants affecting the trans-Manche region

Plainiotis, Stylianos (2006) Atmospheric dispersion modelling of particulate and gaseous pollutants affecting the trans-Manche region. PhD thesis, University of Greenwich.

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This thesis describes the development of a methodology to determine large-scale and meso-scale atmospheric dispersion patterns. The research is only concerned with outdoor exposure to atmospheric pollutants and aims to identify pollution sources using dispersion modelling with the assistance of ground level measurements from British, French and other monitoring stations and remote sensing technology.

Lagrangian Particle Dispersion (LPD) models compute trajectories of a large number of notional particles and can be used to numerically simulate the dispersion of a pollutant (passive tracer) in the planetary boundary layer. Two widely used atmospheric dispersion models were employed: the Hybrid Single Particle Lagrangian Integrated Trajectory (HYSPLIT) model by R. Draxler, and the model FLEXPART by Stohl et al. Both models possess forward tracking and inverse (or receptor-based) modes. Meteorological data output from the PSU/NCAR Mesoscale model (known as MM5), or datasets from the European Centre of Medium-range Weather Forecast (ECMWF) are used to drive the dispersion models. Linkage routines were developed to interpret the LPD codes with the required meteorological information.

This study aims to determine whether current approaches and practice for atmospheric dispersion modelling are reliable, consistent and up-to-date. An intercomparison of the models FLEXPART and HYSPLIT is performed for known episodes to determine their accuracy, ease of use, effect of source specification and to investigate their sensitivity to input data and mesh resolution, and in particular the effect of different model formulations and assumptions followed by the models.

The possibility of identifying emission sources in the near and far field is investigated, by modelling dispersion backwards in time, in particular the discrimination of multiple sources from receptor data is discussed. The effect of meteorological data resolution on the output of LPD models was evaluated and the most suitable methodology for better source definition was determined for different modelling scales, ranging from the intercontinental transport of airborne pollutants to simulating pollution episodes caused by local sources.

Item Type: Thesis (PhD)
Additional Information:
Uncontrolled Keywords: atmospheric dispersion modelling, mathematical modelling, Lagrangian Particle Dispersion, LPD, emissions, meteorological data,
Subjects: Q Science > QA Mathematics
Q Science > QC Physics
Pre-2014 Departments: School of Computing & Mathematical Sciences
School of Computing & Mathematical Sciences > Department of Mathematical Sciences
Last Modified: 17 Jan 2019 15:44

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