Modelling dynamics and uncertainty in assessment of quality standards for fine particulate matters

In order to assess compliance with air quality standards, European regulations prescribe to monitoring the concentration of particulate matters and to control both annual and daily averages. The measurement accuracy varies according to monitor type, temperature and pollution level, often in a complex nonlinear manner. Consequently, comparisons, threshold exceedances interpretation and compliance assessment are often difficult. In this paper, we consider the displaced dynamical calibration (DDC) model which is able to calibrate biased readings by using displaced data obtained by reference instruments. Moreover, we discuss the uncertainty of annual averages of daily concentrations. An application to the Northern Italy air quality network allows us to draw some empirical conclusions.In order to assess compliance with air quality standards, European regulations prescribe to monitoring the concentration of particulate matters and to control both annual and daily averages. The measurement accuracy varies according to monitor type, temperature and pollution level, often in a complex nonlinear manner. Consequently, comparisons, threshold exceedances interpretation and compliance assessment are often difficult. In this paper, we consider the displaced dynamical calibration (DDC) model which is able to calibrate biased readings by using displaced data obtained by reference instruments. Moreover, we discuss the uncertainty of annual averages of daily concentrations. An application to the Northern Italy air quality network allows us to draw some empirical conclusions.