Predicting Methane Emissions from Alberta Oil Sands Territories Using a Holistic Model and Monitoring System

阿尔伯塔省石油行业的温室气体（GHG）排放量每年约为7000万吨，而且没有限制。这些排放大部分来自甲烷的生物生成，这是由生活在油砂尾矿池和尾坑湖中的细菌产生的。由于产甲烷细菌在这个问题上的重要性，对油砂尾矿产生的温室气体排放量的准确预测可以帮助估计具体的排放限制，以减少气候变化的影响。此外，这些细菌产生的甲烷会伤害生活在尾坑湖和周围地区的动物，破坏土地复垦战略。因此，我们打算确定产甲烷菌对它们所在地区的整体影响。我们将建立数学模型，预测甲烷菌的温室气体排放作为许多不同的生态和气象协变量的函数。这些模型将以机器学习和机械技术为特色，因此结合了高预测能力、可分析性和明确的因果关系指示。这些模型将利用实验室实验的结果来构建，在实验室实验中，在不同的模拟环境条件下，在受控环境中观察甲烷菌的活性。我们的合作伙伴南非空气质量监测联盟提供了一系列空气质量传感器，我们将在尾矿池和尾坑湖内及其周围部署这些传感器，它们将适合使用这些传感器的大量现场数据。来自这些传感器的数据将使用人工智能方法进行实时分析。我们还将进行实验室实验，调查甲烷对模式生物的健康和行为的影响，以及沥青的影响（通过甲烷菌活动的间接影响，尾坑湖物种会遇到沥青）。我们将通过创建一个应用程序来传播我们的发现，使利益相关者能够估计任何特定地点甲烷菌的排放，我们在阿尔伯塔环境和保护区的合作伙伴将利用我们的结果来制定油砂土地复垦和自然资源管理的政策。我们的项目将促进艾伯塔省油砂基础设施的改善，并改善全省的空气质量。

Greenhouse gas (GHG) emissions from the oil sector in Alberta total about 70 Mt annually, with no limit in place. Much of these emissions derive from methane biogenesis, which is done by bacteria that live in oil sands tailings ponds and end-pit lakes. Because of the importance of methanogenic bacteria in this matter, accurate predictions of GHG emissions derived from oil sands tailings can aid in estimating specific emissions limits to reduce the effects of climate change. Also, methane produced by these bacteria can harm the animals living in end-pit lakes and the surrounding areas, foiling land reclamation strategies. We therefore intend to determine the holistic effects of methanogens on the areas they are found in. We will build mathematical models predicting GHG emissions by methanogens as a function of many different ecological and meteorological covariates. These models will feature both machine learning and mechanistic techniques, and hence combine high predictive power with analyzability and clear indications of causality. The models will be constructed by utilizing the results of lab experiments where methanogen activity will be observed in a controlled setting under different simulated environmental conditions. They will be fit using large amounts of field data from an array of air quality sensors, provided by our partners in the South African Consortium of Air Quality Monitoring, that we will deploy in and around tailings ponds and end-pit lakes. The data from these sensors will be analyzed in real time using AI methods. We will also perform lab experiments investigating the effects of methane on the health and behaviour of model organisms, as well as those of bitumen (which end-pit lake species encounter via indirect effects of methanogen activity). We will disseminate our findings by creating an app enabling stakeholders to estimate emissions by methanogens in any given location, and our partners in Alberta Environment and Protected Areas will use our results to shape policy on oil sands land reclamation and natural resource stewardship. Our project will facilitate improvements in Alberta's oil sands infrastructure and better air quality provincewide.