Why Us? >>

  • - Open Access
  • - Peer-reviewed
  • - Rapid publication
  • - Lifetime hosting
  • - Free indexing service
  • - Free promotion service
  • - More citations
  • - Search engine friendly

Free SCIRP Newsletters>>

Add your e-mail address to receive free newsletters from SCIRP.


Contact Us >>

WhatsApp  +86 18163351462(WhatsApp)
Paper Publishing WeChat
Book Publishing WeChat
(or Email:book@scirp.org)

Article citations


I. Rasool, M. Baldi, K. Wolter, T. N. Chase, J. Otterman and R. A. Pielke, “August 2003 Heat Wave in Western Europe, An Analysis and Perspectives, European Meterological Society (EMS),” 4th Annual Meeting—Part and Partner: 5th Conference on Applied Climatology (ECAC), Nice, 26-30 September 2004.

has been cited by the following article:

  • TITLE: Retrieval of PM10 Concentration from an AOT Passive Remote-Sensing Station between 2003 and 2007 over Northern France

    AUTHORS: Houda Yahi, Alain Weill, Michel Crepon, Antoni Ung, Sylvie Thiria

    KEYWORDS: Mass Concentration (PM10); Aerosol Optical Thickness (Sun Photometer); Competitive Neural Network; Self-Organizing Map (SOM); Weather Types

    JOURNAL NAME: Open Journal of Air Pollution, Vol.2 No.4, December 5, 2013

    ABSTRACT: A method of retrieving PM10 particles concentrations at the ground level from AOT (Aerosol Optical Thickness) measurements is presented. It uses data obtained among five years during 2003 to 2007 summers in the Lille region (northern France). As PM10 concentration strongly depends on meteorological variables, we clustered the meteorological situations provided by the MM5 meteorological model forced at the lateral boundaries by the operational NCEP model in eight classes (local weather types) for which a robust statistical relationship between AOT and PM10 was found. The meteorological situations were defined by the hourly vertical profiles of temperature and (zonal and meridian) wind components. The clustering of the weather types were obtained by a self-organizing map (SOM) followed by a hierarchical ascending classification (HAC). We were then able to retrieve the PM10 at the surface from the AERONET AOT measurements for each weather type by doing non linear regressions with dedicated SOMs. The method is general and could be extended to other regions. We analyzed the strong pollution event that occurred during August 2003 heat wave. Comparison of the results from our method with the output of the CHIMERE chemical-transport model showed the interest to tentatively combine these two pieces of information to improve particle pollution alert.