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降水对河流中微生物污染的影响:滞后结构与季节效应修正

Precipitation effects on microbial pollution in a river: lag structures and seasonal effect modification.

作者信息

Tornevi Andreas, Bergstedt Olof, Forsberg Bertil

机构信息

Occupational and Environmental Medicine, Department of Public Health and Clinical Medicine, Umeå University, Sweden.

Department of Civil and Environmental Engineering, Water Environment Technology, Chalmers University of Technology, Gothenburg, Sweden.

出版信息

PLoS One. 2014 May 29;9(5):e98546. doi: 10.1371/journal.pone.0098546. eCollection 2014.

Abstract

BACKGROUND

The river Göta Älv is a source of freshwater for 0.7 million swedes. The river is subject to contamination from sewer systems discharge and runoff from agricultural lands. Climate models projects an increase in precipitation and heavy rainfall in this region. This study aimed to determine how daily rainfall causes variation in indicators of pathogen loads, to increase knowledge of variations in river water quality and discuss implications for risk management.

METHODS

Data covering 7 years of daily monitoring of river water turbidity and concentrations of E. coli, Clostridium and coliforms were obtained, and their short-term variations in relation with precipitation were analyzed with time series regression and non-linear distributed lag models. We studied how precipitation effects varied with season and compared different weather stations for predictive ability.

RESULTS

Generally, the lowest raw water quality occurs 2 days after rainfall, with poor raw water quality continuing for several more days. A rainfall event of >15 mm/24-h (local 95 percentile) was associated with a three-fold higher concentration of E. coli and 30% higher turbidity levels (lag 2). Rainfall was associated with exponential increases in concentrations of indicator bacteria while the effect on turbidity attenuated with very heavy rainfall. Clear associations were also observed between consecutive days of wet weather and decreased water quality. The precipitation effect on increased levels of indicator bacteria was significant in all seasons.

CONCLUSIONS

Rainfall elevates microbial risks year-round in this river and freshwater source and acts as the main driver of varying water quality. Heavy rainfall appears to be a better predictor of fecal pollution than water turbidity. An increase of wet weather and extreme events with climate change will lower river water quality even more, indicating greater challenges for drinking water producers, and suggesting better control of sources of pollution.

摘要

背景

约塔河是70万瑞典人的淡水水源。该河流受到下水道系统排放和农田径流的污染。气候模型预测该地区降水量和暴雨将增加。本研究旨在确定每日降雨如何导致病原体负荷指标的变化,以增加对河流水质变化的了解,并讨论其对风险管理的影响。

方法

获取了7年的河水浊度以及大肠杆菌、梭状芽孢杆菌和大肠菌群浓度的每日监测数据,并通过时间序列回归和非线性分布滞后模型分析了它们与降水相关的短期变化。我们研究了降水效应如何随季节变化,并比较了不同气象站的预测能力。

结果

一般来说,降雨后2天原水水质最差,较差的原水水质会持续数天。24小时内降雨量超过15毫米(当地第95百分位数)的降雨事件会使大肠杆菌浓度增加两倍,浊度水平升高30%(滞后2天)。降雨与指示菌浓度呈指数增长相关,而对浊度的影响在暴雨时减弱。连续几天的潮湿天气与水质下降之间也存在明显关联。降水对指示菌水平升高的影响在所有季节都很显著。

结论

降雨全年都会增加这条河流和淡水水源的微生物风险,并是水质变化的主要驱动因素。暴雨似乎比水体浊度更能预测粪便污染情况。随着气候变化,潮湿天气和极端事件的增加将进一步降低河流水质,这给饮用水生产商带来了更大挑战,并表明需要更好地控制污染源。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6d42/4038599/a5bf5a097797/pone.0098546.g001.jpg

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