A study of dispersion in complex terrain under winter conditions using high-resolution mesoscale and Lagrangian particle models

Abstract

Abstract. A mesoscale model (MM5), a dispersive Langrangian particle model (FLEXPART), and intensive meteorological and COrrelation SPECtrometer (COSPEC) measurements from a field campaign are used to examine the advection and turbulent diffusion patterns associated with interactions and forcings between topography, synoptic atmospheric flows and thermally-driven circulations. This study describes the atmospheric dispersion of emissions from a power plant with a 343-meter-tall chimney, situated on very complex terrain in the North-East of Spain, under winter conditions. During the field campaign, the plume was transported with low transversal dispersion and deformed essentially due to the effect of mechanical turbulence. The main surface impacts appeared at long distances from the emission source (more than 30 km). The results show that the coupled models (MM5 and FLEXPART) are able to predict the plume integral advection from the power plant on very complex terrain. Integral advection and turbulent dispersion are derived from the dispersive Lagrangian model output for three consecutive days so that a direct quantitative comparison has been made between the temporal evolution of the predicted three-dimensional dispersive conditions and the COSPEC measurements. Comparison between experimental and simulated transversal dispersion shows an index of agreement between 80% and 90%, within distance ranges from 6 to 33 km from the stack. Linked to the orographic features, the simulated plume impacts on the ground more than 30 km away from the stack, because of the lee waves simulated by MM5.

Seasonal differences in SO2 ground-level impacts from a power plant plume on complex terrain

“…The results presented are complementary to previous studies describing the atmospheric dispersion of the plume aloft emitted during the same field campaigns used in the study presented in this paper (Pérez-Landa et al 2002;Palau et al 2006). By experimentation and modelling, this study attempts to characterise the patterns observed in the ground-level impacts at distances from a few kilometres to more than 80 km around the power plant under two recurrent and extreme meteorological situations representing typical summer and winter conditions.…”

“…The winter campaign took place on 26, 27 and 28 November 2001, and it has been selected as representative of the most recurrent winter scenarios in the area (winter Northwest advection; Palau 2003). The climatological representativity of both meteorological scenarios has already been justified and published (Palau 2003;Palau et al 2004bPalau et al , 2006.…”

“…The power plant selected, with a 343-m-tall chimney, is located in the Northeast of the Iberian Peninsula (labelled APP in Fig. 1) and the SO 2 plume emitted is affected by mesoscale forcings of the wind flow (Palau et al 2001(Palau et al , 2006Pérez-Landa et al 2002;Palau 2003). Previous studies in the area showed that Gaussian regulatory dispersion models cannot be applied under the most recurrent meteorological conditions because of the limitations assumed (Millán 1987;Palau et al 2001Palau et al , 2004aPerez-Landa et al 2002).…”

“…A general feature is the presence of very high gradients within a few kilometres, directly linked to terrain heterogeneities (Fast 1995;Zaremba and Carroll 1999); in this sense, the spatial representativity of the measurement data can be assessed by employing validated mesoscale models (COST-710 1998;Palau et al 2006) that take into account the terrain height variance within the simulated domain (Salvador et al 1999) and the meteorological interactions between the different scales (Palau et al 2005).…”

Urban Aerosol Characteristics during the World Expo 2010 in Shanghai

“…FLEXPART releases so-called tracer particles at emission sources or receptors and calculates their trajectories using the mean winds interpolated from the meteorological input fields, plus random motions representing turbulence. This model has been widely used in the analysis of data for atmospheric chemistry experiments to investigate the influence of various meteorological processes on pollution transport, such as tracing the long-range transport of biomass burning emissions (Fiebig et al, 2009), sources attribution (local or regional) (Quinn et al, 2006) and dispersion over complex terrains (De Foy et al, 2006;Palau et al, 2006). A special feature of FLEXPART is the possibility of running it backward in time to produce information on the spatial distribution of sources contributing to a particular measurement (Stohl et al, 2003;Seibert et al, 2004).…”