Issue 11, 2017

Seasonal variation and risk assessment of PM2.5 and PM2.5–10 in the ambient air of Kenitra, Morocco

Abstract

The seasonal and spatial variations of particulate matter (PM2.5–10 and PM2.5) and its chemical composition have been studied over a one-year period in Kenitra city (2007–2008). The samples were collected using Gent stacked filters and dichotomous samplers in two size fractions: below 2.5 μm (fine) and 2.5 to 10 μm (coarse). The chemical compositions of the collected filters were evaluated by using Total X-ray Fluorescence and Atomic Absorption Spectroscopy. The influence of atmospheric transport scenarios on the levels of PM was elaborated by means of air mass back-trajectories, using the HYSPLIT™ model. This study allowed identifying four main transport patterns: short local flows over the Kenitra region, Northwesterly flows over the Atlantic Ocean, Northerly flows, and Southern flows. The highest PM2.5–10 concentrations were observed in the summer and the lowest in the winter. However, no significant seasonal variations were discerned for PM2.5 particles. The enrichment factor and risk assessment code were calculated to distinguish between anthropogenic influences and the natural background levels and assess the environmental risks of metals in PM2.5–10 and PM2.5 particles. A comparison of PM and metal concentrations in Kenitra city and other African cities (reported in the literature) revealed that that the values obtained in Kenitra city are significantly higher than those recorded for the other African cities (that are the subject of the comparison).

Graphical abstract: Seasonal variation and risk assessment of PM2.5 and PM2.5–10 in the ambient air of Kenitra, Morocco

Article information

Article type
Paper
Submitted
23 Jun 2017
Accepted
15 Oct 2017
First published
16 Oct 2017

Environ. Sci.: Processes Impacts, 2017,19, 1427-1436

Seasonal variation and risk assessment of PM2.5 and PM2.5–10 in the ambient air of Kenitra, Morocco

M. Tahri, A. Benchrif, M. Bounakhla, F. Benyaich and Y. Noack, Environ. Sci.: Processes Impacts, 2017, 19, 1427 DOI: 10.1039/C7EM00286F

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