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

阿尔伯塔省石油部门每年的温室气体排放总量约为7000万吨，没有限制。这些排放物大部分来自甲烷生物合成，这是由生活在油砂尾矿池和底坑湖泊中的细菌完成的。由于产甲烷细菌在这一问题上的重要性，准确预测油砂尾矿产生的温室气体排放量可以帮助估计特定的排放限值，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底坑湖泊和周边地区的动物，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。我们将建立数学模型，预测甲烷菌作为许多不同的生态和气象协变量的函数的温室气体排放量。这些模型将以机器学习和机械技术为特色，因此将联合收割机的高预测能力与可分析性和明确的因果关系指示相结合。将利用实验室实验的结果构建模型，其中将在不同模拟环境条件下的受控环境中观察产甲烷菌活性。它们将使用来自空气质量传感器阵列的大量现场数据，这些传感器由我们在南非空气质量监测联盟的合作伙伴提供，我们将在尾矿池和底坑湖泊及其周围部署。来自这些传感器的数据将使用AI方法进行真实的实时分析。我们还将进行实验室实验，研究甲烷对模式生物的健康和行为的影响，以及沥青的影响（底坑湖物种通过产甲烷菌活动的间接影响遇到）。我们将通过创建一个应用程序来传播我们的研究结果，使利益相关者能够估计任何特定位置的产甲烷菌的排放量，我们在阿尔伯塔环境和保护区的合作伙伴将使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。我们的项目将促进阿尔伯塔油砂基础设施的改善和全省范围内更好的空气质量。

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.