EPJ Web Conf.
Volume 176, 2018The 28th International Laser Radar Conference (ILRC 28)
|Number of page(s)||4|
|Section||Lidars applications in atmospheric structure and composition: Aerosols, clouds, trace gases|
|Published online||13 April 2018|
Modelling of pollen dispersion in the atmosphere: evaluation with a continuous 1β+1δ lidar
Remote Sensing Laboratory, Universitat Politècnica de Catalunya, Barcelona, Spain
2 Ciències i Tecnologies de l'Espai - Centre de Recerca de l'Aeronàutica i de l'Espai / Institut d'Estudis Espacials de Catalunya (CTE-CRAE / IEEC), Universitat Politècnica de Catalunya, Barcelona, Spain
3 Departament de Física, Universitat Politècnica de Catalunya, Barcelona, Spain
4 Departament de Biologia Animal, Biologia Vegetal i Ecologia, Universitat Autònoma de Barcelona, Bellaterra, Spain
5 Institut de Ciencia i Tecnología Ambientals (ICTA), Universitat Autònoma de Barcelona, Bellaterra, Spain
6 Earth Sciences Department, Barcelona Supercomputing Center – Centro Nacional de Supercomputación, Barcelona, Spain
7 Environmental Modeling Laboratory, Technical University of Catalonia, Barcelona, Spain
* Email: email@example.com
Published online: 13 April 2018
Pollen allergenicity plays an important role on human health and wellness. It is thus of large public interest to increase our knowledge of pollen grain behavior in the atmosphere (source, emission, processes involved during their transport, etc.) at fine temporal and spatial scales. First simulations with the Barcelona Supercomputing Center NMMB/BSC-CTM model of Platanus and Pinus dispersion in the atmosphere were performed during a 5-day pollination event observed in Barcelona, Spain, between 27 – 31 March, 2015. The simulations are compared to vertical profiles measured with the continuous Barcelona Micro Pulse Lidar system. First results show that the vertical distribution is well reproduced by the model in shape, but not in intensity, the model largely underestimating in the afternoon. Guidelines are proposed to improve the dispersion of airborne pollen by numerical prediction models.
© The Authors, published by EDP Sciences, 2018
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (http://creativecommons.org/licenses/by/4.0/).
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