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

监测甲烷无组织区域排放的混合多路光学遥感系统

• 批准号: RGPIN-2020-05223
• 负责人: Du, Ke
• 金额: $ 1.89万
• 依托单位: University of Calgary
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2022
• 资助国家: 加拿大
• 起止时间: 2022-01-01 至 2023-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=764669
• 关键词: Hybrid; Multi; Path; Optical; Remote

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.

甲烷是继二氧化碳之后导致气候变化的第二大温室气体。尽管来自垃圾填埋场、农业和石油和天然气作业的无组织排放占总排放量的大部分，但由于高度不均匀的浓度分布以及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，传统的甲烷排放监测技术在捕获大规模、异质的逸散性排放方面具有固有的局限性，并且某些技术的适用性在恶劣天气条件下或偏远地区受到极大限制。此外，由于缺乏监测技术，进入排放清单的排放因子对于无组织源来说具有很大的不确定性，这对于艾伯塔省的尾矿库和采矿工作面等不常见源来说尤其具有挑战性。尽管油砂地区是大量甲烷来源，但其排放因子并不完整，甚至无法获得，因此必须将其纳入加拿大甲烷排放清单的制定中。本研究旨在开发一种新颖的混合多路径光学遥感（ORS）方法和系统，以克服现有技术的局限性，并应用新方法来开发艾伯塔省独特但重要的排放源（例如尾矿池和垃圾填埋场）的排放因子。近期目标是建立一种方法，将使用 ORS 技术进行的二维浓度分布测量与逆色散建模相结合，生成实时排放通量分布。最终，可以量化总排放量并定位排放热点。中长期目标是应用该方法研究研究区（艾伯塔省）农业源等典型主要无组织排放源，表征甲烷排放动态并制定这些源的排放因子，在此基础上制定更准确、更全面的排放清单。 这项研究的成果预计将通过提供一种经济而强大的工具来解决逃逸、大规模、异质和高度可变的甲烷来源的监测挑战，从而为排放监测界带来直接利益。它还将为气候建模研究人员提供油砂设施中独特逃逸源的排放因子/动态特征的新数据，以研究能源开发对区域气候的影响。当 ORS 传感器被替换为其他气体的传感器时，该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中进行其他潜在应用，从而减少工业排放对加拿大环境和公共健康的影响。