Automated Detection and Estimation of Methane Emissions at Site and Regional Scales Based on Lidar Sparse Tomographic Data

The GreenLITE™ system designed to autonomously monitor trace gas emissions over extended ares of interest is comprised of two elements: onsite data collection and offsite cloud-based data processing and analytics subsystems. The data collection system consists of the laser transceivers, retroreflectors, scanning hardware and data capture subsystems which provide the measurements of differential optical depth. The data processing/analytics subsystem converts observed differential optical depth values into path-averaged CH₄ or CO₂ concentrations (xCH₄ or xCO₂), constructs 2-D views of trace gas distributions for a horizontal plane over the area of interest, and estimates emission rates. Once installed and calibrated, GreenLITE™ is designed to run autonomously, scanning the area of interest on a 24-hour per day basis and providing 2-D maps of trace gas (CH₄/CO₂) concentration and emission, as well as other custom analytics, via standard secure web/network-based protocols. These products and supporting analytics are accessible via a standard web browser.

This work will focus on the data processing and analytics infrastructure design, developed and performance characteristics, whose primary functions are to convert observed differential transmission/optical depth values into xCH₄ or xCO₂ chord concentrations, to compute 2-D distributions of gas concentrations, to estimate flow rates/fluxes, and to distribute these products via standard open-source network-based protocols. GreenLITE™ instrument data, along with local weather and numerical weather prediction (NWP) model data, are ingested and cataloged in a common set of database services. These services provides data access to downstream computation elements as well as tailored web-based applications accessed worldwide via standard web browsers, tablets, and smart phones. These applications that run in a lightweight service-oriented architecture construct data products, e.g. trace gas concentrations and flow rates, as well as system and environmental analytics. The baseline set of computational services is composed of four basic elements: 1) conversion of observed optical depths into integrated column concentration values of xCH₄/xCO₂ along individual chords, 2) computation of 2-D distributions of trace gas concentrations using sparse tomography, 3) real-time estimation of flow/leak rate, and 4) construction of system and application specific analytics. The nominal data flow is illustrated in the figure below.

In 2017, GreenLITE™ demonstrated the ability to quantify and map the location of controlled CH₄ releases as well as other sources during our testing at the Total 2017 Gas Detection and Quantification test campaign. In addition, the preliminary GreenLITE^TM estimates of emissions rates were within a factor of 2 of the known release rates. An overview of these results will be presented as part of this presentation.

Finally, this work will outline how this technology may be extended to include application for assessing the daily bulk emission, including fugitive emissions, from large scale industrial sites, i.e. tailing ponds and other traces gases of interest from both a health/safety and emission monitoring perspective.