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Blue-green algae mitigation strategies for urban lakes

Blue-green algae mitigation strategies for urban lakes
城市湖泊蓝绿藻缓解策略
批准号:
566271-2021
负责人:
McBean, Edward
金额:
$4.08万
依托单位:
依托单位国家:
加拿大
项目类别:
Alliance Grants
财政年份:
2021
资助国家:
加拿大
项目状态:
已结题
起止时间:
2021-01-01 至 2022-12-31

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中文摘要
翻译
蓝藻,俗称蓝绿藻,是一种自然存在的微生物,可能会将蓝藻毒素释放到淡水系统中。这些毒素会造成严重的公共卫生风险,因为通过皮肤接触、摄入湖水或受污染的饮用水或食物接触可能会导致影响动物(牲畜和宠物)和人类的症状。这些风险从轻微的刺激到更严重的疾病,在最坏的情况下,可能是致命的。蓝藻出现在世界各地,在平静,营养丰富的水域,允许藻类繁殖。这些水华可能在一年中的任何时候发生,但在夏季和初秋更常见,产生难闻的气味,水变色,在水面上积聚成浮渣,并释放可能对人类和水生生物有害的毒素。人们预计,由于气候变化导致的气温升高,城市湖泊的水华频率和持续时间将会增加。随着蓝藻毒素发生率的增加,人们的兴趣集中在了解导致蓝藻毒素形成的因素途径,以及最终管理城市湖泊的机会,从而减少藻华发生的可能性(例如管理/减少营养负荷,考虑物理和化学活动来减少藻华,以及使用现代技术(如微生物源跟踪)发展科学知识)。并创造工具来评估它们的规模和潜力)。目前,缺乏专门预测有害藻类成分和毒性的模型,需要提高对可能的控制措施有效性的认识。本研究将集中于神仙湖的案例研究应用,神仙湖是安大略省哈尔顿镇的一个26公顷的省级重要湿地,那里的藻类生长大量,并且有相当多的历史数据可用。仙女湖是这项研究的理想选择,考虑到有兴趣的各方,附近允许相对容易的访问,以及拟议的研究团队的专业知识。
英文摘要
Cyanobacteria, commonly known as blue-green algae, are naturally occurring microscopic organisms that may release cyanotoxins into freshwater systems. These toxins pose a serious public health risk as exposure through skin contact, ingestion of lake water, or contaminated drinking water or food may cause symptoms impacting both animals (livestock and pets) and humans. These risks range from minor irritation to more serious illness and, in worst case scenarios, can be fatal.Cyanobacteria occur worldwide, in calm, nutrient-rich waters, allowing algal blooms. These blooms may occur at any time of year but are more common during summer and early fall, creating bad odors, water discoloration, accumulate as a scum on the surface of the water, and releasing toxins that may be harmful to humans and aquatic biota. The expectations are that blooms will increase in frequency and duration in urban lakes due to warming temperatures associated with climate change.With the increasing incidence of cyanotoxins, interest is focusing on understanding the pathways of factors which contribute to formation of cyanotoxins and ultimately, opportunities to manage urban lakes and hence insights to decrease the potential for algal blooms to occur (e.g. manage/decrease nutrient loads, consider physical and chemical activities to reduce the blooms, and develop scientific knowledge using modern techniques such as microbial source tracking, and create tools to assess their magnitude and potential). Currently, models to specifically predict harmful algal composition and toxicity are lacking and improved knowledge of the effectiveness of possible control measures are needed.This research will focus on a case study application to Fairy Lake, a 26 ha Provincially Significant Wetland in the Town of Halton, Ontario where the algal growths are substantial and a considerable history of data are available. Fairy Lake is ideal for this research, given the interested parties, the proximity allowing relatively easy access, and the expertise within the proposed research team.
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Improved Infrastructure Assessments of Water Main Breaks Using Data Mining and Machine Learning Algorithms
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  • 财政年份:
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  • 负责人:
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  • 依托单位:
Improved Infrastructure Assessments of Water Main Breaks Using Data Mining and Machine Learning Algorithms
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    2021
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  • 财政年份:
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  • 负责人:
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  • 依托单位:
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