Speaker
Description
Systematic ambient air pollution data is essential to conduct epidemiological studies aimed at mitigating the impact of air pollution on human health in the dust belt region. However, a lack of data plagues the regions most affected by low air quality, owing to daunting challenges in monitoring air quality. These challenges include the need for reference-grade air quality monitoring stations that require a stable alternating-current electric power supply, expensive reference-grade analyzers, and frequent calibration and maintenance. Meeting these standards is a significant challenge in Africa.
Numerical models play a crucial role in understanding the behavior and estimating the concentrations of various pollutants in the atmosphere. In this conference, we present maximum 8-hour daily average ozone concentrations for the city of Marrakech during Winter 2009 and Summer 2015. These concentrations result from simulations using CHIMERE-WRFv2021, utilizing a detailed spatialized inventory.
Our results, compared to observations from two local monitoring stations, indicate that the model accurately simulates MDA8 (maximum daily average) ozone concentrations at the JEF Station, albeit with a slight overestimation of 16% in Summer (average: 45 ppb) and 37% in Winter (average: 33 ppb). However, at MHD Station, which is less affected by significant changes in anthropogenic activity, the model overestimates ozone concentrations by 91% in Summer (average: 49 ppb) and by 50% in Winter (average: 38 ppb).
Looking at the diurnal average concentrations of ozone, the CHIMERE model system overestimates both daytime and nighttime surface ozone concentrations by up to 91% (NMB) in Summer. Pearson's correlation coefficient (r) based on MDA8 ozone concentrations was found to be less than 0.5 (S: 0.46, W: -0.07) for LOCAL/ON (S: 0.33, W: 0.21) with the MEMSD inventory and (S: 0.36, W: 0.29) with the CAMS inventory. This indicates that the model does not accurately reproduce temporal variability in Marrakech.
