A Hybrid Multi-Path Optical Remote Sensing System for Monitoring Fugitive Areal Emission of Methane

甲烷是导致气候变化的第二大温室气体，仅次于二氧化碳。尽管垃圾填埋场、农业和油气作业的逃逸排放占总排放量的大部分，但由于高度不均匀的浓度分布和大空间尺度上高度可变的通量，在表征和量化此类排放方面存在挑战。此外，常规甲烷排放监测技术在捕获大规模、非均匀逃逸排放方面存在固有限制，其中一些技术在恶劣天气条件下或偏远地区的适用性极其有限。 此外，由于缺乏监测技术，已进入排放清单的排放因素对于逃逸源具有很大的不确定性，这对艾伯塔省尾矿库和采矿工作面等不常见的源尤其具有挑战性。油砂地区的排放系数是不完整的，甚至是不可用的，尽管它们是巨大的甲烷来源，因此必须纳入加拿大的甲烷排放清单。 这项研究旨在开发一种新的、混合的、多路径的光学遥感(ORS)方法和系统，以克服现有技术的局限性，并将新方法应用于开发艾伯塔省独特但重要的来源的排放系数，例如尾矿库和垃圾填埋场。近期目标是建立一种方法，将ORS技术测量的二维浓度分布与反弥散模拟相结合，生成实时的排放通量分布。最终，可以量化排放总量，定位排放热点。中长期目标是应用这一方法研究研究区(艾伯塔省)典型的主要逃逸排放源，如农业污染源，以表征甲烷排放动态，并制定这些排放源的排放系数，在此基础上制定更准确和更全面的排放清单。 这项研究的结果预计将为排放监测界带来立竿见影的好处，因为它提供了一种经济而强大的工具，以应对对逃逸、大规模、异质和高度可变的甲烷来源的监测挑战。它还将为气候模拟研究人员提供油砂设施中独特的逃逸源的排放因子/动力学特征的新数据，以研究能源开发对区域气候的影响。当ORS传感器被这些气体的传感器取代时，这项技术可以很容易地转移到其他气体上，从而允许在战剂检测、应急响应和排放管理方面的其他潜在应用，这反过来将减少工业排放对加拿大环境和公众健康的影响。

Methane is the 2nd most important greenhouse gas contributing to climate change after CO2. Despite the fact that fugitive emissions from landfills, agriculture, and oil & gas operations contribute most of the total emission, challenges are present in characterizing and quantifying such emissions due to highly heterogeneous concentration distribution, and highly variable flux over large spatial scales. Furthermore, conventional methane emission monitoring technologies have inherent limitations for capturing large-scale, heterogeneous fugitive emissions, and the applicability of some of the technologies is extremely limited under harsh weather conditions or at remote locations. Besides, the emission factors that have been entered into the emission inventories are of large uncertainties for fugitive sources due to the lack of monitoring technologies, which is particularly challenging for uncommon sources such as tailings ponds and mining face in Alberta. Emissions factors are incomplete or even unavailable for the oil sands area, despite that they are large methane sources and hence have to be included in developing the Canadian emission inventory for methane. This research aims to develop a novel, hybrid, multi-path optical remote sensing (ORS) method and system to overcome the limitations of existing technologies, and apply the new method for developing emission factors for the unique but important sources in Alberta, e.g., tailings ponds, as well as landfills. The near-term objective is to establish the method by integrating the measurement of 2-D concentration distribution using ORS technology with inverse dispersion modeling to generate the real-time emission flux distribution. Eventually, the total emission can be quantified and the emission hot spots can be located. The mid- and long-term objectives are to apply this approach to study typical major fugitive emission sources in the study area (Alberta) such as agricultural sources, to characterize the methane emission dynamics and develop emission factors for those sources, based on which a more accurate and comprehensive emission inventory could be developed. The outcome of this research is anticipated to bring immediate benefit to the emission monitoring community by providing an economical and powerful tool to address the monitoring challenges for fugitive, large scale, heterogeneous, and highly variable sources of methane. It will also provide the climate modeling researchers new data of emission factors/dynamical characteristics for the unique fugitive sources in oil sands facilities to study the impact of energy development on the regional climate. The technology can be readily transferred to other gases when the ORS sensor is replaced with the ones for those gases, allowing other potential applications in warfare agent detection, emergency response, and emission management, which in return, would reduce the impact of industry emissions on environment and public health in Canada.