Spatiotemporal Variations and Future Trends of Sucralose Contamination in Major Rivers of Zhejiang, China: An Emerging Concern and Sustainability Challenge

The environmental persistence of sucralose (SUC), a recalcitrant artificial sweetener, has raised significant ecological concerns owing to its notable resistance to both thermal and biological degradation. This study focused on the eight major river basins in Zhejiang Province and used the LC-MS/MS external standard method to systematically detect the environmental occurrence of SUC. Significant spatial variations were observed. The highest concentration recorded in the river was 6.60 μg/L in the Beijing-Hangzhou Grand Canal. In contrast, the Ou River showed almost no detectable concentration. Higher contamination levels were consistently found in urban-adjacent areas, particularly near Hangzhou metropolitan region. Distinct seasonal patterns were also identified, with peak concentrations occurring during summer months. Through the application of the seasonal Kendall trend analysis, an increasing trend was projected for seven of the eight river systems studied, with the Ou River being the sole exception. Furthermore, the accuracy of the model’s prediction results was verified by comparing the data from the 2024 experimental tests with the model’s predicted results. By comparing the data from the experimental tests in 2024 with the model’s predictions, the results showed that, except for the Beijing-Hangzhou Grand Canal, the relative deviations of the other rivers were all less than 5.00%. This indicates that the model had a high accuracy in predicting the changing trend of concentrations. This study provided fundamental data for understanding sucralose’s environmental behavior in the Yangtze River Delta watersheds, serving as a critical baseline data for ecological risk assessments and contributing to water resource sustainability. And the ecological or toxicological implications of SUC pollution require further study. Furthermore, this study developed a transferable methodological framework for monitoring artificial sweetener contamination across diverse aquatic ecosystems.