Assessment of three-dimensional, fine-granular measurement of particulate matter by a smart air quality network in urban area

Ground-based remote sensing by three ceilometers for mixing layer height detection over Augsburg as well as a Radio- Acoustic Sounding System (RASS) for temperature and wind profile measurements at the campus of Augsburg University are applied together with UAV height profiling with low-weight meteorological sensors and particle counter to monitor the three-dimensional dynamics of the lower atmosphere. Results about meteorological influences upon spatial variation of air pollution exposure are presented on this data basis which is more than one year long. Special focus is on the information about atmospheric layering as well as mixing and transport conditions for emitted particulate matter. Better understanding of these complex processes support knowledge about quality of air, which we breath, and especially high air pollution episodes and hot spot pollution regions.

[1]  Christoph Münkel Mixing height determination with lidar ceilometers results from Helsinki Testbed , 2007 .

[2]  K. Schäfer,et al.  Evaluation of the Interpretation of Ceilometer Data with RASS and Radiosonde Data , 2012, Boundary-Layer Meteorology.

[3]  Stefan Emeis,et al.  Atmospheric boundary-layer structure from simultaneous SODAR, RASS, and ceilometer measurements , 2004 .

[4]  Klaus Schäfer,et al.  Adding confidence levels and error bars to mixing layer heights detected by ceilometer , 2011, Remote Sensing.

[5]  Matthias Budde,et al.  SmartAQnet: remote and in-situ sensing of urban air quality , 2017, Remote Sensing.

[6]  W. Thomas,et al.  What is the benefit of ceilometers for aerosol remote sensing? An answer from EARLINET , 2014 .

[7]  Michael Schatzmann,et al.  Field measurements within a quarter of a city including a street canyon to produce a validation data set , 2005 .

[8]  Stefan Emeis,et al.  Surface-based remote sensing of the mixing-layer height a review , 2008 .

[9]  Stefan Emeis,et al.  Impact of meteorological conditions on airborne fine particle composition and secondary pollutant characteristics in urban area during winter-time , 2016 .

[10]  Stefan Emeis,et al.  Multiple atmospheric layering and mixing-layer height in the Inn valley observed by remote sensing , 2007 .

[11]  T. Riedel,et al.  Smart Air Quality Network for spatial high-resolution monitoring in urban area , 2018, Remote Sensing.

[12]  LAUS,et al.  Observation of the structure of the urban boundary layer with different ceilometers and validation by RASS data , 2009 .

[13]  Stefan Emeis,et al.  A measurement based analysis of the spatial distribution, temporal variation and chemical composition of particulate matter in Munich and Augsburg , 2011 .

[14]  Klaus Schäfer,et al.  Influence of mixing layer height on air pollutant concentrations in an urban street canyon , 2017 .

[15]  Karen Anderson,et al.  Lightweight unmanned aerial vehicles will revolutionize spatial ecology , 2013 .

[16]  Pascal Brisset,et al.  The Small Unmanned Meteorological Observer SUMO: A new tool for atmospheric boundary layer research , 2009 .

[17]  Stefan Emeis,et al.  Influence of mixing layer height upon air pollution in urban and sub-urban areas , 2006 .

[18]  Andreas Rauch,et al.  Determination of mixing layer heights from ceilometer data , 2004, SPIE Remote Sensing.