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A Bayesian risk assessment framework for microcystin violations of drinking water and recreational standards in the Bay of Quinte, Lake Ontario, Canada

机译:贝叶斯风险评估框架微囊杆菌侵犯床湾湖泊湖,安大略湖,加拿大湖湾饮用水和娱乐标准

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Freshwater ecosystems can experience harmful algal blooms, which negatively impact recreational uses, aesthetics, taste, and odor in drinking water. Cyanobacterial toxins can have dire repercussions on aquatic wildlife and human health, and the most ubiquitous worldwide are the hepatotoxic compounds known as microcystins. The factors that influence the occurrence and magnitude of cyanobacteria blooms and toxin production vary in space and time and remain poorly understood. It is within this context that we present a suite of statistical models, parameterized with Bayesian inference techniques, to link the retrospective analysis of important environmental factors with the probability of exceedance of threshold microcystin levels. Our modelling framework is applied to the Bay of Quinte, Lake Ontario, Canada; a system with a long history of eutrophication problems. Collectively, 16.1% of the samples of the system collected during the study period (2003-2016) exceeded the drinking water guideline of 1.5 mu gL(-1), while approximately 3% of recorded values exceeded the recommended recreational threshold of 20 mu gL(-1). Using a segmented regression model with a stochastic breakpoint of microcystin concentrations estimated at 0.54 mu g L-1, we demonstrate that the environmental conditions associated with increased probability of exceedance of the drinking water standard are chlorophyll a concentration (3)(7) mu g L-1, water temperature (3)20 degrees C, ammonium concentration = 40 mu gL(-1), total phosphorus concentration (3)25 mu g L-1, and wind speed = 37 km h(-1). Considering the multitude of factors that can influence the ambient levels of toxins, our study argues that the adoption of probabilistic water quality criteria offers a pragmatic approach to accommodate the associated uncertainty by permitting a realistic frequency of violations. In this context, we present a framework to evaluate the confidence of compliance with probabilistic standards that stipulate less than 10% violations of microcystin threshold ambient levels. (C) 2019 Elsevier Ltd. All rights reserved.
机译:淡水生态系统可以体验有害的藻类绽放,对饮用水中的娱乐使用,美学,味道和气味产生负面影响。蓝藻毒素可以对水生野生动物和人类健康有可怕的影响,并且全球最无处不在的全球性是称为微囊藻蛋白的肝毒性化合物。影响蓝藻盛开和毒素生产的发生和程度的因素在空间和时间内各不等,并且仍然清晰地理解。在这种情况下,我们提供了一套统计模型,与贝叶斯推理技术参数化,以将重要环境因素的回顾性分析与阈值微胱氨酸水平的概率联系起来。我们的建模框架适用于加拿大安大略湖Quinte湾;具有富营养化问题历史悠久的系统。统称,在研究期间收集的系统样本的16.1%超过了1.5 mu gl(-1)的饮用水指南,而大约3%的记录值超过了20 mu gl的推荐休闲阈值(-1)。使用分段的回归模型估计在0.54μg1-1的微囊藻浓度随机断裂点,我们证明与超越饮用水标准的概率增加相关的环境条件是叶绿素A浓度(3)(7)μg L-1,水温(3)20℃,铵浓度<=40μg1(-1),总磷浓度(3)25μmg l-1,风速<= 37 km h(-1) 。考虑到可能影响毒素的环境水平的众多因素,我们的研究认为,采用概率水质标准提供了一种务实的方法,可以通过允许侵犯逼真的频率来适应相关的不确定性。在这种情况下,我们提出了一个框架,以评估遵守概率标准的置信度,违反10%的侵犯微囊藻阈值环境水平的概率标准。 (c)2019 Elsevier Ltd.保留所有权利。

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