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: 2021
• 资助国家: 加拿大
• 起止时间: 2021-01-01 至 2022-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=740463
• 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第二大导致气候变化的温室气体。尽管来自垃圾填埋场、农业和石油天然气作业的逃逸性排放占总排放量的大部分，但由于高度异质的浓度分布和大空间尺度上高度可变的通量，因此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、异质散逸性排放方面具有固有的局限性，其中一些技术在恶劣天气条件下或在偏远地区的适用性极为有限。此外，由于缺乏监测技术，已输入排放清单的排放因子对于易散性来源具有很大的不确定性，这对于阿尔伯塔的尾矿池和采矿工作面等不常见来源尤其具有挑战性。排放系数是不完整的，甚至无法获得的油砂区，尽管他们是大的甲烷来源，因此必须包括在制定加拿大的甲烷排放清单。本研究旨在开发一种新的、混合的、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阿尔伯塔独特但重要的源的排放因子，例如，尾矿池以及垃圾填埋场。近期目标是建立将ORS技术的二维浓度分布测量与逆弥散模型相结合以生成实时排放通量分布的方法。最终，可以量化总排放量并定位排放热点。中期和长期目标是应用这种方法来研究典型的主要无组织排放源在研究区域（阿尔伯塔），如农业源，表征甲烷排放动态和开发这些源的排放因子，在此基础上，可以开发一个更准确和全面的排放清单。 这项研究的结果预计将带来直接的好处，排放监测社区提供了一个经济和强大的工具，以解决监测的挑战，逃犯，大规模，异构，高度可变的甲烷来源。它还将为气候模拟研究人员提供油砂设施中独特逃逸源的排放因子/动力学特征的新数据，以研究能源开发对区域气候的影响。该技术可以很容易地转移到其他气体，当ORS传感器被替换为这些气体的传感器时，允许在战剂检测，应急响应和排放管理中的其他潜在应用，这反过来将减少工业排放对加拿大环境和公共健康的影响。