Validation of a Lagrangian dispersion model implementing different kernel methods for density reconstruction

Vitali, Lina; Monforti, F.; Bellasio, Roberto; Bianconi, Roberto; Sachero, V.; Mosca, Sonia; Zanini, Gabriele

doi:10.1016/j.atmosenv.2006.06.056

Cited by 15 publications

(7 citation statements)

References 14 publications

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“…Essentially model results are consistent with the observations and performance indexes are quite good, compared to what obtained by analogous modelling systems (e.g. Vitali et al, 2006;Brzozowska, 2013), in particular by SPRAY (e.g. Anfossi et al, 2010) especially when applied in a similar context (Gariazzo et al, 2007;Morabito et al, 2013).…”

Section: Evaluation Of Concentration Fieldssupporting

confidence: 80%

A Lagrangian modelling approach to assess the representativeness area of an industrial air quality monitoring station

Vitali

Morabito

Adani

et al. 2016

Atmospheric Pollution Research

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Section: Evaluation Of Concentration Fieldssupporting

confidence: 80%

A Lagrangian modelling approach to assess the representativeness area of an industrial air quality monitoring station

Vitali

Morabito

Adani

et al. 2016

Atmospheric Pollution Research

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“…To interpret changes in the community composition among samples and during possible transitions between offshore and coastal phases, we computed the difference between the VPPs release time at LTER-MC and the first-entry time (T A ) of VPPs in the origin zones. In particular, we computed the T A of the particles in an area neighbouring the VPPs centre mass (C m ( x c , y c )), reinterpreting the receptor-based method discussed elsewhere 53 . For each simulation, the neighbourhood area around C m was defined as the region enclosing the 1/20 th closest particles by the end of the run.…”

Section: Methodsmentioning

confidence: 99%

Disentangling physical and biological drivers of phytoplankton dynamics in a coastal system

Cianelli

D’Alelio

Uttieri

et al. 2017

Sci Rep

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This proof-of-concept study integrates the surface currents measured by high-frequency coastal radars with plankton time-series data collected at a fixed sampling point from the Mediterranean Sea (MareChiara Long Term Ecological Research site in the Gulf of Naples) to characterize the spatial origin of phytoplankton assemblages and to scrutinize the processes ruling their dynamics. The phytoplankton community generally originated from the coastal waters whereby species succession was mainly regulated by biological factors (life-cycle processes, species-specific physiological performances and inter-specific interactions). Physical factors, e.g. the alternation between coastal and offshore waters and the horizontal mixing, were also important drivers of phytoplankton dynamics promoting diversity maintenance by i) advecting species from offshore and ii) diluting the resident coastal community so as to dampen resource stripping by dominant species and thereby increase the numerical importance of rarer species. Our observations highlight the resilience of coastal communities, which may favour their persistence over time and the prevalence of successional events over small time and space scales. Although coastal systems may act differently from one another, our findings provide a conceptual framework to address physical–biological interactions occurring in coastal basins, which can be generalised to other areas.

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“…Kernel functions are used in many Lagrangian particle dispersion models to reconstruct the concentrations. The advantages of using kernel functions instead of simple box models to reconstruct the concentrations are highlighted in Haan, (1999) and Vitali et al, (2006). The two-dimensional space is discretised in square cells with a width of τ .…”

Section: Exposure Analysismentioning

confidence: 99%

Emission estimation based on traffic models and measurements

Tsanakas

2019

Linköping Studies in Science and Technology. Licentiate Thesis

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Validation of a Lagrangian dispersion model implementing different kernel methods for density reconstruction

Cited by 15 publications

References 14 publications

A Lagrangian modelling approach to assess the representativeness area of an industrial air quality monitoring station

A Lagrangian modelling approach to assess the representativeness area of an industrial air quality monitoring station

Disentangling physical and biological drivers of phytoplankton dynamics in a coastal system

Emission estimation based on traffic models and measurements

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