Overview of PM₁₀, PM_2.5 and BC and Their Dependent Relationships with Meteorological Variables in an Urban Area in Northwestern Morocco

Abstract

At an urban site in Kenitra, Morocco, two aerosol size fractions (PM2.5 and PM10) were sampled for four seasons to characterize the seasonal trends of particulate (PM) and carbonaceous (BC) aerosols. An in-depth statistical analysis of the lag-effects of meteorology on collected data was investigated using uni- and multivariate linear regression analyses. The results revealed significant seasonal trends for PM10, PM2.5, and BC. PM concentrations showed the maximum values in autumn (61.4 ± 24.5 µg/m3 for PM10 and 21.2 ± 8.2 µg/m3 for PM2.5), while the minimum was observed in winter (40.2 ± 17.1 µg/m3) for PM10 and in summer (14.3 ± 3.3 µg/m3) for PM2.5. High BC concentrations were recorded in summer (6.3 ± 4.2 μg/m3, on average). The relative humidity 1–2 days earlier showed a higher negative correlation with the PM concentrations (except in winter), and the temperature 1–3 days earlier showed a negative correlation with the PM2.5 in winter and summer and a positive one with the PM10 in autumn. Wind speed was negatively associated with PM10 on the current day in winter and 3 days earlier in summer. However, diverse effects of wind speed on PM2.5 were observed (negative in summer and positive in spring). These results confirm the important role of meteorology in the formation of urban air pollution with pronounced variations in different seasons.

Keywords

• urban aerosols
• PM₁₀
• PM_2.5
• black carbon
• meteorological variables
• multivariate linear regression