Validation of air pollution biomonitoring networks and related data modelling: a geostatistical approach

Abstract

This paper describes a geostatistical approach for environmental data modeling based on value descriptive analysis, variographic analysis, estimation method and validation. It shows an application related to atmospheric pollutant dispersion (ozone) detected by active biomonitoring in the province of Livorno (Italy). This work proposes a two-stage approach based on: the computation of an index on an exploratory and geostatistical data analysis to assess whether a monitoring network is well distributed in space and allows us to get reliable information about the whole study area; the derivation of a continuous representation of the variable (the Cotyledonous Damage Index) from punctual measurements. The geostatistical approach proposed is useful to define in a structured way the possible problems in a monitoring network, to control the data estimation error in the points not sampled. The case study analysed underlines that the biomonitoring network outline does not have a representative sample station distribution of the study area introducing significant errors related to the territorial generalization of the derived information. The proposed approach allows us to elaborate on the obtained data to carry out the data spatialization associating an error to them and to the evaluation model.