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Overview of PM10, PM2.5 and BC and Their Dependent Relationships with Meteorological Variables in an Urban Area in Northwestern Morocco

202325 citationsOpen accessIbn Tofail University

In plain language

Measurements taken across four seasons in Kenitra, Morocco, show how particulate matter and black carbon concentrations fluctuate alongside weather conditions over time. Particulate pollution reached its peak in autumn, with average concentrations of 61.4 micrograms per cubic metre for PM10 and 21.2 micrograms per cubic metre for PM2.5. The lowest levels occurred in winter for PM10 and summer for PM2.5, while black carbon concentrations reached their highest levels during summer. Statistical modelling of meteorological lag-effects demonstrated that conditions from preceding days substantially influenced pollutant levels. Relative humidity recorded one to two days prior was negatively correlated with particulate levels across most seasons. Temperature from one to three days earlier showed mixed seasonal correlations with fine particles and PM10, while wind speed had varying immediate and lagged associations depending on the season.

Key takeaways

  • Airborne particulate matter peaked during autumn in Kenitra, whilst black carbon reached its highest average concentrations in summer.
  • Relative humidity measured one to two days earlier was negatively associated with particulate matter concentrations in all seasons except winter.
  • Temperature from one to three days prior correlated negatively with PM2.5 in winter and summer, but positively with PM10 in autumn.
  • Wind speed displayed distinct seasonal lag-effects, reducing PM10 levels on the same day in winter and three days earlier in summer.

Why it matters

Urban air quality is shaped not only by current weather but also by meteorological conditions occurring days in advance. Understanding these delayed relationships helps improve local environmental monitoring and pollution forecasting. Identifying seasonal peaks in particulate matter and black carbon assists environmental managers in anticipating when urban populations face the highest exposure to harmful airborne pollutants.

Commercialisation angle

The abstract does not indicate an application pathway or commercialisation route for this early-stage observational research.

AI-generated from the published abstract. Always read the original work before citing.

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.

Research topics

  • Air Quality and Health Impacts
  • Atmospheric chemistry and aerosols
  • Air Quality Monitoring and Forecasting

Sustainable Development Goals

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DOI: 10.3390/atmos14010162

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