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  • Title: Storm runoff differentially influences the nutrient concentrations and microbial contamination at two distinct beaches in northern China.
    Author: He Y, He Y, Sen B, Li H, Li J, Zhang Y, Zhang J, Jiang SC, Wang G.
    Journal: Sci Total Environ; 2019 May 01; 663():400-407. PubMed ID: 30716630.
    Abstract:
    With the escalating coastal development and loss of vegetated landscape, the volume of storm runoff increases significantly in Chinese coastal cities. To protect human health and valuable recreational resources, it is necessary to develop a quantitative understanding of coastal pollution. Here we studied the influence of storm runoff on the nutrients and microbial pathogens at two popular bathing beaches in northern China. Dongshan Beach, located near the mouth of an urban river, is influenced by non-point source pollution while Tiger-Rock Beach, a coastal beach, is primarily influenced by a point source from a storm drain outfall. Storm runoff significantly (P < 0.001) decreased the salinity and Chl a post-storm at both the beaches, but only reduced the concentration of dissolved inorganic N at Tiger-Rock Beach. Escherichia coli decreased by 68.7% at Dongshan Beach, possibly due to the dilution effect of the stormflow, contradicting the notion of elevated fecal contamination in coastal beaches from storm runoff. Vibrio parahaemolyticus increased at both beaches post-storm, by 155.7% at Dongshan Beach and 136.7% at Tiger-Rock Beach. Regardless of storm impact, both E. coli and V. parahaemolyticus were much higher at Dongshan Beach than that at Tiger-Rock, suggesting the influence of different surrounding topographies. Lastly, the statistical models developed based on the environmental and microbial parameters regression showed predictive power (adjusted R2 > 0.5) to estimate the concentration of E. coli at Dongshan Beach and V. parahaemolyticus at Tiger-Rock Beach. Overall, the results suggest the unique role of the individual beaches in attenuating the effect of rainfall on the concentration of microbial pathogens in bathing water quality and provide unique predictive models for recreational water management and public health protection.
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