Assessment of Wastewater Treatment Efficiency in Changsha Using Principal Component Analysis and Cluster Analysis: A Five-Year Study (2020–2024)

To assess the treatment efficiency and spatio-temporal variation characteristics of urban wastewater treatment plants, this study analyzed influent and effluent water quality data, including pH, COD, BOD5, SS, NH3–N, TN, and TP, as well as treatment volume data from 19 plants in Changsha from 2020 to 2024. The results revealed significant fluctuations in influent water quality across different plants, though effluent quality generally complied with discharge standards. Removal rates of SS, NH3–N, and BOD5 all exceeded 80%, while that of TN ranged between 63% and 79%. The COD/BOD5 ratios in the influent mostly exceeded 0.3, indicating generally good biodegradability of the municipal wastewater. However, 79% of the plants exhibited SS/BOD5 > 1.5, and 83.2% had BOD5/TN < 4, suggesting a widespread carbon deficiency for denitrification. Principal component analysis (PCA) demonstrated that both influent and effluent quality indicators were suitable for dimensionality reduction, with pH, COD, NH3–N, and TN identified as core evaluation factors. Cluster analysis (CA) indicated phased increases in influent concentrations, while effluent quality showed progressive annual improvement from 2020 to 2024. Urban WWTPs’ influent pollution loads were hydrological period-dependent, with high-flow effluent fluctuations and controllable low-flow loads. This study provides data support for operational optimization of wastewater treatment plants in Changsha.