Development and application of paleolimnological methods to assess pollution of aquatic ecosystems downstream of the Alberta oilsands

开发和应用古湖泊学方法来评估艾伯塔省油砂下游水生生态系统的污染

基本信息

批准号：
RGPIN-2016-03630
负责人：
Hall, Roland
金额：
$ 2.11万
依托单位：
University of Waterloo
依托单位国家：
加拿大
项目类别：
Discovery Grants Program - Individual
财政年份：
2020
资助国家：
加拿大
起止时间：
2020-01-01 至 2021-12-31
项目状态：
已结题

来源：
https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=708827
关键词：
Development application paleolimnological methods assess

项目摘要

In recent years, societal concerns have escalated over cumulative effects of rapidly-growing oilsands development on downstream ecosystems in the lower Athabasca River watershed. Based on expert-panel reports, current monitoring programs are inadequate to address the growing apprehension about releases of pollution from oilsands development via air and water. Key locations include the lower Athabasca River, Lake Athabasca, Peace-Athabasca Delta and community of Ft. Chipewyan where worries have been expressed for human and ecosystem health. Of particular concern are metals and organic pollutants. Studies of snowpack and lake sediments show that oilsands development is polluting at least a 50-km radius via the air. However, disentangling the roles of natural processes versus industrial development on contaminant supply via the Athabasca River remains a key scientific challenge, because systematic monitoring began 30 years after oilsands development. Thus, real-time measurements of pre-disturbance contaminant levels are not known and cannot be produced retroactively. Also, the river naturally erodes oil-bearing strata along >100 km of riverbank, which further confounds interpretation of existing monitoring data. The proposed research will develop and apply a scientifically-rigorous paleolimnological approach at three strategically-selected locations (Athabasca River downstream of oilsands, Peace-Athabasca Delta, lower Peace River) to provide key missing information on pre-industrial baseline levels of metal contaminants of concern carried by the Athabasca and Peace rivers. This approach, a product of 15 years of prior research, will use analyses of contaminants in sediments deposited into floodplain lakes by river floodwaters before industrial development to determine the natural range of sediment contaminant concentrations in the river, as baseline' to evaluate long-term river monitoring data for evidence of pollution by oilsands development and other human activities. A novel aspect is use of pre-disturbance sediments from flood-prone lakes to assess pollution of rivers. A key outcome will be generation of methods and data that can be used in ongoing and future river-quality monitoring to ensure there are minimal downstream cumulative effects from oilsands development. Ultimately, we aim to use the methodology to determine relative roles of natural processes versus industrial activity on contaminant levels at other rivers in Canada and elsewhere in the world where insufficient pre-impact data impede an ability to detect pollution, and to adapt the methodology for other types of contaminants (e.g., polycyclic aromatic compounds). Three PhD and 12 undergraduate students will be trained in sought-after skills in environmental assessment.

近年来，由于迅速增长的油砂开发对下阿萨巴斯卡河下游生态系统的累积影响，社会问题逐渐升级。根据专家面板的报告，当前的监测计划不足以解决人们对通过空气和水的油砂开发释放污染的越来越多的担忧。关键地点包括下阿萨巴斯卡河下部，阿萨巴斯卡湖，和平的阿巴巴斯加三角洲和英尺社区。 Chipewyan为人类和生态系统健康表达了担忧。特别关注的是金属和有机污染物。对积雪和湖泊沉积物的研究表明，油砂开发的空气至少污染了50公里的半径。但是，解散自然过程与工业发展对通过阿萨巴斯卡河的污染物供应的作用仍然是一个关键的科学挑战，因为系统监测始于石油制成后30年。因此，尚不清楚烟气前污染物水平的实时测量，不能追溯产生。此外，河流自然侵蚀了沿河岸> 100公里的含油地层，这进一步混淆了对现有监测数据的解释。拟议的研究将在三个战略性选择的地点（油砂下游，和平 - 阿巴巴斯加三角洲，下和平河下游）开发并应用科学上的古杂色方法，以提供有关阿萨巴斯卡和和平河流携带的金属污染物的主要工业基线污染物水平的重要信息。这种方法是15年的先前研究的产物，将在工业发展前对河流洪水沉积到洪泛区湖中的污染物的分析，以确定河流中的沉积物污染物浓度的自然污染物污染物的自然范围，以评估长期的河流监测数据，以证明石油污染和其他人类活动的污染和其他人类活动。一个新的方面是使用容易洪水的湖泊中的扰动前沉积物来评估河流的污染。一个关键的结果将是生成可用于持续和未来的河流质量监测的方法和数据，以确保油砂开发产生的下游累积效应最少。最终，我们旨在使用该方法来确定自然过程与工业活动的相对作用与加拿大其他河流和世界其他地方的污染物水平的相对作用，在这些河流中不足，在这些河流中不足的前IMPACT数据妨碍了检测污染的能力，并适应了其他类型的污染物的方法（例如，多碳酸性的芳香族芳烃化合物）。三名博士学位和12名本科生将接受培训的环境评估技能。