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Air Quality, Atmosphere & Health

, Volume 11, Issue 1, pp 61–68 | Cite as

Investigating PM10 episodes using levoglucosan as tracer

  • Alexandra MonteiroEmail author
  • Sónia Gouveia
  • Manuel Scotto
  • Sandra Sorte
  • Carla Gama
  • Vorne L. Gianelle
  • Cristina Colombi
  • Célia Alves
Article

Abstract

The present study aims to investigate the role/contribution of residential combustion (using levoglucosan as a tracer of biomass combustion) during PM10 episode days registered over the Porto urban area (Portugal), in order to support air quality plans that need to be developed for this particular region. The levoglucosan and PM10 concentration values, together with the meteorological conditions (namely temperature), measured during an experimental field campaign performed in 2013, were used in this study. To this end, a wavelet-based approach is applied to (a) better quantify the coherence and dependency of these variables and (b) assess the strength of the connection between the two pollutants species (PM and levoglucosan) at different time scales. Results evidenced a high coherence/dependency between PM10 and levoglucosan values for the episodes selected (periods with exceedances of the PM10 limit values), suggesting the contribution of biomass combustion sources. The highest coherence (normalised covariance) is observed for the winter episodes and time periods of 5–10 days, which is related to the duration of the episodes selected. The summertime episode, which exhibits a negligible observed correlation between temperature and levoglucosan, is explained by the influence of forest fires that occurred within this period and region.

Keywords

Levoglucosan Temperature Particulate matter Episodes Wavelet analysis 

Notes

Acknowledgements

The authors wish to thank the financial support from AIRUSE LIFE+ (ENV/ES/584) EU project. This work was partially supported by the Portuguese Foundation for Science and Technology (FCT), with national (MEC) and European structural funds through the programmes FEDER, under the partnership agreement PT2020—within IEETA/UA project UID/CEC/00127/2013 (Instituto de Engenharia Electrónica e Informática de Aveiro, IEETA/UA, Aveiro), CIDMA/UA project UID/MAT/04106/2013 (Centro de Investigação e Desenvolvimento em Matemática e Aplicações, CIDMA/UA, Aveiro) and CESAM (UID/AMB/50017-POCI-01-0145-FEDER-007638) within the PT2020 Partnership Agreement and Compete 2020. S. Gouveia and C. Gama acknowledge the postdoctoral and doctoral grants by FCT (SFRH/BPD/87037/2012 and SFRH/BD/87468/2012, respectively).

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Copyright information

© Springer Science+Business Media B.V. 2017

Authors and Affiliations

  1. 1.CESAM and Department of Environment and PlanningUniversity of AveiroAveiroPortugal
  2. 2.Institute of Electronics and Informatics Engineering of Aveiro (IEETA) and Center for R&D in Mathematics and Applications (CIDMA)University of AveiroAveiroPortugal
  3. 3.CEMAT and Department of MathematicsIST University of LisbonLisbonPortugal
  4. 4.Environmental Monitoring SectorArpa LombardiaMilanItaly

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