• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Risk analysis >Impact of Hydrometeorological Events for the Selection of Parametric Models for Protozoan Pathogens in Drinking-Water Sources
【24h】

Impact of Hydrometeorological Events for the Selection of Parametric Models for Protozoan Pathogens in Drinking-Water Sources

机译：水质气象事件对饮水源原生动物病原体参数模型选择的影响

获取原文
获取原文并翻译 | 示例
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

Temporal variations in concentrations of pathogenic microorganisms in surface waters are well known to be influenced by hydrometeorological events. Reasonable methods for accounting for microbial peaks in the quantification of drinking water treatment requirements need to be addressed. Here, we applied a novel method for data collection and model validation to explicitly account for weather events (rainfall, snowmelt) when concentrations of pathogens are estimated in source water. Online in situ beta-d-glucuronidase activity measurements were used to trigger sequential grab sampling of source water to quantify Cryptosporidium and Giardia concentrations during rainfall and snowmelt events at an urban and an agricultural drinking water treatment plant in Quebec, Canada. We then evaluate if mixed Poisson distributions fitted to monthly sampling data (n = 30 samples) could accurately predict daily mean concentrations during these events. We found that using the gamma distribution underestimated high Cryptosporidium and Giardia concentrations measured with routine or event-based monitoring. However, the log-normal distribution accurately predicted these high concentrations. The selection of a log-normal distribution in preference to a gamma distribution increased the annual mean concentration by less than 0.1-log but increased the upper bound of the 95% credibility interval on the annual mean by about 0.5-log. Therefore, considering parametric uncertainty in an exposure assessment is essential to account for microbial peaks in risk assessment.
机译：众所周知，表面水域中致病微生物浓度的时间变化是受水形气象事件的影响。需要解决在量化饮用水处理要求的量化中核算微生物峰的合理方法。在这里，我们应用了一种新的数据收集和模型验证方法，以明确占天气事件（降雨，雪花），当源水中估计病原体时。在网上原位β-D-葡萄糖醛酸酶活性测量用于引发源水的顺序抓取取样，以量化加拿大魁北克省魁北克市和农业饮用水处理厂的降雨和散户事件期间的水孢子虫和贾奈迪亚浓度。然后，我们评估适配于每月采样数据的混合泊松分布（n = 30个样本），可以在这些事件中准确地预测日常平均浓度。我们发现，使用常规或基于事件的监测测量的γ分布低估的高碱基和贾迪亚浓度。但是，对数正态分布准确地预测了这些高浓度。选择对数正态分布的优先于伽马分布增加年平均浓度小于0.1次，但增加了95％信誉间隔的上限，以约0.5日志。因此，考虑到曝光评估中的参数不确定性对于风险评估中的微生物峰来说是必要的。

著录项

  • 来源
    《Risk analysis》 |2021年第8期|1413-1426|共14页
  • 作者

    Sylvestre Emile; Burnet Jean-Baptiste; Dorner Sarah; Smeetsc Patrick; Medema Gertjan; Villion Manuela; Hachad Mounia; Prevost Michele;

  • 作者单位

    Polytech Montreal NSERC Ind Chair Drinking Water Dept Civil Geol & Min Engn Montreal PQ H3C 3A7 Canada|Polytech Montreal Canada Res Chair Source Water Dept Civil Geol & Min Engn Montreal PQ H3C 3A7 Canada;

    Polytech Montreal NSERC Ind Chair Drinking Water Dept Civil Geol & Min Engn Montreal PQ H3C 3A7 Canada|Polytech Montreal Canada Res Chair Source Water Dept Civil Geol & Min Engn Montreal PQ H3C 3A7 Canada;

    Polytech Montreal Canada Res Chair Source Water Dept Civil Geol & Min Engn Montreal PQ H3C 3A7 Canada;

    KWR Water Res Inst Groningenhaven 7 NL-3433 PE Nieuwegein Netherlands;

    Delft Univ Technol Sanit Engn Dept Water Management Fac Civil Engn & Geosci POB 5048 NL-2600 GA Delft Netherlands;

    Minist Environm & Lutte Changements Climat Ctr Expertise Anal Environm Quebec Montreal PQ Canada;

    Polytech Montreal NSERC Ind Chair Drinking Water Dept Civil Geol & Min Engn Montreal PQ H3C 3A7 Canada|Polytech Montreal Canada Res Chair Source Water Dept Civil Geol & Min Engn Montreal PQ H3C 3A7 Canada;

    Polytech Montreal NSERC Ind Chair Drinking Water Dept Civil Geol & Min Engn Montreal PQ H3C 3A7 Canada;

  • 收录信息
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Cryptosporidium; drinking water; Giardia; hydrometeorology; risk assessment;

    机译：隐孢子虫;饮用水;吉亚迪亚;水统计学;风险评估;

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号