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

艾伯塔省石油部门每年的温室气体(GHG)排放总量约为7000万吨，没有限制。这些排放很大程度上来自甲烷的生物生成，这是由生活在油砂尾矿池和尾矿湖中的细菌完成的。由于产甲烷细菌在这一问题上的重要性，对油砂尾矿产生的温室气体排放的准确预测有助于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末端坑湖和周围地区的动物，从而挫败土地开垦战略。因此，我们打算确定产甲烷菌对它们所在地区的整体影响。我们将建立预测甲烷菌温室气体排放量的数学模型，作为许多不同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，因此将高预测能力与可分析性和明确的因果关系迹象结合在一起。这些模型将利用实验室实验的结果来构建，这些实验将在不同的模拟环境条件下，在受控环境下观察甲烷菌的活性。他们将使用南非空气质量监测联盟的合作伙伴提供的一系列空气质量传感器提供的大量现场数据进行匹配，我们将在尾矿库和尾矿湖及其周围部署这些传感器。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(末端坑湖物种通过甲烷生成活动的间接影响而遇到的沥青)的影响。我们将通过创建一款应用程序来传播我们的发现，使利益相关者能够估计任何给定地点的甲烷菌排放量，我们在艾伯塔省环境和保护区的合作伙伴将利用我们的结果来制定关于油砂土地开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和全省更好的空气质量。

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.