The analytical framework is specifically contextualized to Mohammedia, a medi-um-sized industrial coastal city with an estimated area of 33 km². The industrial struc-ture, traffic configuration, and urban morphology of Mohammedia may differ signifi-cantly from those of larger metropolitan areas or rural regions. Consequently, the gen-eralizability of the conclusions may be limited. Seasonal variations, diurnal pollutant cycles, long-term emission trends, and ex-treme or unexpected events (such as industrial incidents or meteorological anomalies) were not explicitly incorporated into the scenario modeling. Future studies integrating longitudinal monitoring data would be necessary to validate temporal robustness. Despite these limitations, the framework provides a structured basis for evaluating mobile monitoring feasibility and may serve as a preliminary decision-support tool pending empirical validation.

This analytical approach focuses specifically on Mohammedia, an industrial coastal city of moderate size covering approximately 33 km². The industrial makeup, traffic patterns, and urban layout of Mohammedia could vary considerably from larger metropolitan centers or rural areas. This means the findings might not apply broadly to other locations. The scenario modeling did not account for seasonal changes, daily pollution patterns, long-term emission shifts, or unusual events like industrial accidents or weather extremes. To confirm how well this approach works over time, future research would need to include ongoing monitoring data. Even with these constraints, this framework offers an organized method for assessing whether mobile monitoring is practical and could function as an initial decision-making resource until real-world testing confirms its effectiveness.