4.7 Article

A comparison of reanalysis techniques: Applying optimal interpolation and Ensemble Kalman Filtering to improve air quality monitoring at mesoscale

期刊

SCIENCE OF THE TOTAL ENVIRONMENT
卷 458, 期 -, 页码 7-14

出版社

ELSEVIER SCIENCE BV
DOI: 10.1016/j.scitotenv.2013.03.089

关键词

Data assimilation; Optimal interpolation; Ensemble Kalman Filter; Particulate matter

资金

  1. Italian Ministry of University and Research (MIUR)
  2. Regione Lombardia
  3. CILEA Consortium through a LISA Initiative (Laboratory for Interdisciplinary Advanced Simulation) grant

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To fulfill the requirements of the 2008/50 Directive, which allows member states and regional authorities to use a combination of measurement and modeling to monitor air pollution concentration, a key approach to be properly developed and tested is the data assimilation one. In this paper, with a focus on regional domains, a comparison between optimal interpolation and Ensemble Kalman Filter is shown, to stress pros and drawbacks of the two techniques. These approaches can be used to implement a more accurate monitoring of the long-term pollution trends on a geographical domain, through an optimal combination of all the available sources of data. The two approaches are formalized and applied for a regional domain located in Northern Italy, where the PM10 level which is often higher than EU standard limits is measured. (C) 2013 Elsevier B.V. All rights reserved.

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