Evaluating Seasonal Model Simulations of Ozone in Northern Italy View Full Text


Ontology type: schema:Chapter     


Chapter Info

DATE

2004

AUTHORS

Guido Pirovano , Cesare Pertot , Veronica Gabusi , Marialuisa Volta

ABSTRACT

High concentrations of tropospheric ozone are quite usual in Mediterranean areas during summer seasons and cause adverse effects on human health and natural ecosystems. In order to capture ozone climatological behaviour and select effective reduction strategies, long-term simulations can be performed. Several authors (Hogrefe et al., 2001; Schmidt et al., 2001; Kasibihatla et al., 2000) present seasonal simulations on regional scale performed by photochemical systems. Usually models are run with a spatial resolution ranging from 36 km to 0.5° over domains extending up to 2–3000 km in each direction. In this paper an urban scale long-term simulation is evaluated. The simulation domain is located in Northern Italy, including Milan metropolitan area. It is characterised by complex terrain, high urban and industrial emissions and a close road network. Due to the presence of the Alps, winds are often weak and circulation shows very heterogeneous patterns. Besides, during anticyclonic stable conditions breeze can develop causing daily circulation of polluted air masses between urban and rural areas. The critical anthropogenic emissions, the frequent stagnating meteorological conditions and the solar radiation regularly cause high ozone level episodes. Due to the described meteorological features, pollutants can give raise to a complex spatial distribution, that is difficult to describe by means of mathematical models even using a detailed spatial resolution. Moreover, in several cases, spatial variability can induce a representativeness reduction of measurement stations, making critical the comparison with model results. More... »

PAGES

171-178

Book

TITLE

Air Pollution Modeling and Its Application XVI

ISBN

978-1-4613-4697-5
978-1-4419-8867-6

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/978-1-4419-8867-6_16

DOI

http://dx.doi.org/10.1007/978-1-4419-8867-6_16

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1028117782


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