Marco Pandolfi

Institute of Environmental Assessment and Water Research (IDAEA-CSIC), Barcelona, Spain

Quality control of environmental data is closely linked to the entire air quality monitoring process, from the choice of site, choice of instrumentation, calibration and maintenance processes, data storage, and retrieval and analysis systems. For air quality monitoring, quality control is used to ensure that the final product (ambient air quality monitoring data) is consistent and reliable. The data validation process involves a critical review of all information relating to a particular data set in order to verify, amend or reject the data. A robust and reliable handling of environmental data is especially important nowadays given that the amount of monitoring data available worldwide is substantial and increasing mostly thanks to the establishment of international monitoring networks (e.g. ACTRIS – the European Research Infrastructure for the observation of Aerosol, Clouds, and Trace gases, GAW – WMO Global Atmosphere Watch, EMEP – The European Monitoring and Evaluation Programme, NOAA/ESRL Federated Aerosol Network, among other). Here we mostly focus on different approaches to handling, process and present environmental data and we will go through the steps of the data validation process which include for example: the correct application of check and calibration factors, multi-data (contaminants and meteorology) analysis to highlight anomalies, removal of data known to be spurious or collected during calibration and maintenance, treatment of negative or out-of-range data, among other. With this aim we will use ambient data collected with different instruments widely used to study the aerosol particle properties important for air quality and climate. Moreover, for a reliable quality control of data it is important to have access to specialist software that might be necessary to carry out all but the most simple types of analysis. Here we will also present some useful software packages to handle environmental data.