Showing papers by "Arnoud Apituley published in 2014"

EARLINET: towards an advanced sustainable European aerosol lidar network

Abstract: The European Aerosol Research Lidar Network, EARLINET, was founded in 2000 as a research project for establishing a quantitative, comprehensive, and statistically significant database for the horizontal, vertical, and tempo- ral distribution of aerosols on a continental scale. Since then EARLINET has continued to provide the most extensive col- lection of ground-based data for the aerosol vertical distribu- tion over Europe. This paper gives an overview of the network's main de- velopments since 2000 and introduces the dedicated EAR- LINET special issue, which reports on the present innova- tive and comprehensive technical solutions and scientific re- sults related to the use of advanced lidar remote sensing tech- niques for the study of aerosol properties as developed within the network in the last 13 years. Since 2000, EARLINET has developed greatly in terms of number of stations and spatial distribution: from 17 sta- tions in 10 countries in 2000 to 27 stations in 16 countries in 2013. EARLINET has developed greatly also in terms of technological advances with the spread of advanced multi- wavelength Raman lidar stations in Europe. The develop- ments for the quality assurance strategy, the optimization of instruments and data processing, and the dissemination of data have contributed to a significant improvement of the net- work towards a more sustainable observing system, with an increase in the observing capability and a reduction of oper- ational costs. Consequently, EARLINET data have already been ex- tensively used for many climatological studies, long-range transport events, Saharan dust outbreaks, plumes from vol- canic eruptions, and for model evaluation and satellite data validation and integration. Future plans are aimed at continuous measurements and near-real-time data delivery in close cooperation with other ground-based networks, such as in the ACTRIS (Aerosols, Clouds, and Trace gases Research InfraStructure Network) www.actris.net, and with the modeling and satellite commu- nity, linking the research community with the operational world, with the aim of establishing of the atmospheric part of the European component of the integrated global observ- ing system.

Mapping atmospheric aerosols with a citizen science network of smartphone spectropolarimeters

Abstract: To assess the impact of atmospheric aerosols on health, climate, and air traffic, aerosol properties must be measured with fine spatial and temporal sampling. This can be achieved by actively involving citizens and the technology they own to form an atmospheric measurement network. We establish this new measurement strategy by developing and deploying iSPEX, a low-cost, mass-producible optical add-on for smartphones with a corresponding app. The aerosol optical thickness (AOT) maps derived from iSPEX spectropolarimetric measurements of the daytime cloud-free sky by thousands of citizen scientists throughout the Netherlands are in good agreement with the spatial AOT structure derived from satellite imagery and temporal AOT variations derived from ground-based precision photometry. These maps show structures at scales of kilometers that are typical for urban air pollution, indicating the potential of iSPEX to provide information about aerosol properties at locations and at times that are not covered by current monitoring efforts.

Cloud detection and classification based on MAX-DOAS observations

Abstract: . Multi-axis differential optical absorption spectroscopy (MAX-DOAS) observations of aerosols and trace gases can be strongly influenced by clouds. Thus, it is important to identify clouds and characterise their properties. In this study we investigate the effects of clouds on several quantities which can be derived from MAX-DOAS observations, like radiance, the colour index (radiance ratio at two selected wavelengths), the absorption of the oxygen dimer O4 and the fraction of inelastically scattered light (Ring effect). To identify clouds, these quantities can be either compared to their corresponding clear-sky reference values, or their dependencies on time or viewing direction can be analysed. From the investigation of the temporal variability the influence of clouds can be identified even for individual measurements. Based on our investigations we developed a cloud classification scheme, which can be applied in a flexible way to MAX-DOAS or zenith DOAS observations: in its simplest version, zenith observations of the colour index are used to identify the presence of clouds (or high aerosol load). In more sophisticated versions, other quantities and viewing directions are also considered, which allows subclassifications like, e.g., thin or thick clouds, or fog. We applied our cloud classification scheme to MAX-DOAS observations during the Cabauw intercomparison campaign of Nitrogen Dioxide measuring instruments (CINDI) campaign in the Netherlands in summer 2009 and found very good agreement with sky images taken from the ground and backscatter profiles from a lidar.