Data and Methodological Limitations This study is based on theoretical modeling and literature-derived parameters ra-ther than on newly collected experimental measurements. Therefore, the uncertainty coefficients, correction parameters, and operational assumptions used in the framework should be considered analytical estimates that require validation through local calibra-tion campaigns. In addition, the spatial coverage and cost assessments rely on simpli-fied scenario assumptions that may differ from real deployment conditions. Technical and Measurement Limitations Mobile monitoring systems based on low-cost sensors present inherent technical constraints, including sensor drift, cross-sensitivity, aging effects, and nonlinear re-sponses. Although the proposed correction framework incorporates temperature, hu-midity, vehicle speed, and vibration effects, the complexity of these interactions may not be fully captured by the simplified analytical model. Other engineering factors, such as airflow stability, inlet design, power supply, and GPS accuracy, were also not explicitly modeled. Geographical and Temporal Limitations The proposed framework was specifically developed for Mohammedia, and its direct transferability to other cities should therefore be considered with caution. Dif-ferences in urban structure, industrial activity, traffic patterns, and meteorological conditions may influence both monitoring performance and deployment strategy. In addition, seasonal variability, long-term pollutant trends, and exceptional events were not explicitly included in the scenario-based analysis. Despite these limitations, the proposed framework provides a useful analytical basis for assessing the feasibility of mobile air quality monitoring and may be adapted to other medium-sized cities facing similar environmental and financial constraints, pro-vided that local calibration and validation data are incorporated.

Data and Methodological Limitations This research relies on theoretical models and parameters drawn from existing literature instead of new experimental data collection. The uncertainty factors, adjustment parameters, and operational assumptions within the framework represent analytical estimates that need verification through local calibration studies. Additionally, the spatial coverage and cost evaluations depend on simplified scenario assumptions that might not match actual deployment situations. Technical and Measurement Limitations Low-cost sensor-based mobile monitoring systems have built-in technical restrictions, such as sensor drift, interference from other substances, deterioration over time, and non-linear behavior. While the suggested correction framework accounts for temperature, humidity, vehicle speed, and vibration impacts, the simplified analytical model may not completely represent how these factors interact with each other. Other engineering considerations like airflow consistency, inlet configuration, power systems, and GPS precision were not specifically included in the modeling. Geographical and Temporal Limitations The framework was created specifically for Mohammedia, so applying it directly to other cities requires careful consideration. Variations in city layout, industrial operations, traffic flow, and weather patterns could affect both monitoring effectiveness and deployment approaches. Furthermore, the scenario-based analysis did not account for seasonal changes, long-term pollution trends, or unusual events. Even with these constraints, the framework offers a valuable analytical foundation for evaluating mobile air quality monitoring feasibility and can be modified for other medium-sized cities with comparable environmental and budget challenges, as long as local calibration and validation information is included.