Model quality objectives based on measurement uncertainty. Part II: NO2 and PM10.

Abstract: Estimating measurement uncertainty for NO2 and PM10 is a complex issue that is normally addressed by experimentalists specifically for every type of instrument and measurement. On the other hand, an estimate of the maximum expected measurement uncertainty is needed when a numerical model is to be evaluated against observations, as proposed in Thunis et al. (2012, referred to as T2012). In a companion paper (Thunis et al., 2013, referred to as T2013) a simplified formulation of the measurement uncertainty in function of the measured concentration is proposed and applied to the simpler case of Ozone. In this paper the same approach is applied for NO2 and PM10, but using different techniques for the uncertainty estimation. For NO2 the Guide to the expression of Uncertainty in Measurement JCGM (2008, referred to as GUM) approach is used and applied on each urban AirBase (1997) measurement over the year 2009. For PM10, the method of the Guide for the Demonstration of Equivalence (ECWG, 2010) is used on data obtained with two different PM samplers used in parallel either during specific monitoring campaign or as available within the AirBase database. The resulting concentration dependent measurement uncertainties are then used to update the MQO (Model Quality Objective) and MPC (Model Performance Criteria) proposed in T2012. An estimate of the measurement uncertainty for annual means is proposed as well. [Copyright &y& Elsevier]