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Integrating monitoring networks to obtain estimates of ground-level ozone concentrations --a proof of concept in Tuscany (central Italy)
Authors:Ferretti Marco  Andrei Sara  Caldini Gabriella  Grechi Daniele  Mazzali Cristina  Galanti Emilio  Pellegrini Marco
Affiliation:Linnaeambiente Ricerca Applicata Srl, Via G. Sirtori 37, I-50137 Firenze, Italy. ferretti@terradata.it
Abstract:Prior to 2000 a network of conventional ozone (O3) analysers existed in the Province of Firenze (Tuscany, central Italy). Between 2000 and 2004 the network was extended to incorporate a newly designed bioindicator network of tobacco plants (Nicotiana tabacum Bel W3). The objective was to set-up an integrated monitoring system to obtain estimates of ground-level O3 concentrations over the whole study area (3513 km2) in order to fill data gaps and cover reporting requirements. The existing conventional monitors were purposefully located mainly in urban areas. A total of 45 biomonitoring sites were selected using a systematic design to cover the target area. Two to five additional biomonitoring sites were co-located with conventional O3 analysers for calibration purposes, and five more sites for independent validation of modelled O3 concentrations. Visible Leaf Injury Index (LII) on the tobacco plants was significantly correlated (P: 0.018/0.0014) with a series of O3 exposure variables (mean of weekly 1-hour maxima, M1; mean of 7-hour means, M7; 24-hour mean, M24; and weekly AOT40). LII was found to be a significant predictor of weekly means of the O3 exposure variables with a standard error of estimates between 13.6 and 24.3 microg m(-3) (absolute values). LII was mapped with an ad-hoc spatial model over the study area at a 22 km grid resolution, and mapped values were used to predict O3 concentrations by means of a first order linear model. Results showed that high estimates of O3 (up to 188 microg m(-3) as mean of weekly maxima, M1) occurred more frequently in hilly and mountainous areas, with a spatial pattern changing on an annual basis. Predicted O3 concentrations were not significantly different from the measured concentrations (P: 0.34), although marked differences were observed for individual sites and years. The study provided evidence that integration of monitoring networks using different methods can be a viable option to obtain estimates of O3 concentrations over large areas.
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