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Spatiotemporal Dynamics of Urban Population Based on Mobile Signaling Data and Its Correlation With Wastewater
Chenguang Fan1, Kai He2, Penghui Li1
1School of Environmental Science and Safety Engineering, Tianjin University of Technology, Tianjin, China.
Abstract:
Urban population dynamics play a critical role in wastewater management; however, traditional estimation methods fail to capture the necessary spatial and temporal resolution. This study introduces an innovative approach using mobile signaling data (MSD) to construct a high-resolution spatiotemporal population model for Zhuhai City. The model quantifies the correlation between dynamic population patterns and key wastewater parameters across 12 catchments, thereby demonstrating the potential for improved operational control in wastewater treatment. The MSD-derived population model revealed significant spatial heterogeneity, with notable day-night shifts, and some catchments exhibited nighttime populations exceeding daytime levels by approximately 22,000 individuals, reflecting residential dominance. Correlation analyses showed that MSD-derived populations were significantly associated with organic and nutrient loads (particularly BOD) in predominantly residential and commercial catchments, whereas the performance of individual hydrochemical proxies (e.g., NH3-N) was catchment-dependent. Overall, MSD-based estimates exhibited substantially lower temporal variability (RSD 0.98%-4.91%) than hydrochemical proxy-based estimates, whose variability was notably higher and more context-sensitive. This study underscores MSD's transformative potential for precise urban wastewater management, offering a robust methodology to enhance the predictive control and optimization of wastewater infrastructure in rapidly urbanizing contexts.
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