Area fugitive emission measurements of methane & carbon dioxide

Testing Fugitive Emissions Quantification Methods

Approved for funding in ERA’s Methane Challenge in 2017, Canadian Natural Resources Limited (CNRL) partnered with Alberta-based LuxMux, Boreal Laser, RWDI Air, SAIT, the University of Alberta, and others to conduct a comprehensive program to improve detection, monitoring, and quantification of fugitive methane and carbon dioxide emissions from area sources such as mine faces and tailings ponds. By its completion in 2020, the project obtained sufficient data covering several different emissions assessment technologies.

CNRL and project partners set out to field validate solutions that quantify fugitive methane and carbon dioxide emissions from large industrial area sources. Surface mining operationsgreenhouse gas (GHG) emissions include methane and carbon dioxide production from fluid tailings ponds. This project involved testing different measurement techniques for estimating fugitive emissions at the Horizon oil sands facility mine pits and tailings ponds. These areas involve complex terrain and heterogenous air emissions zones, making emissions management more challenging.

The assessed techniques aimed to offer improved spatial and temporal coverage, which is a limitation of the current standard technique to measure and model air emissions called “flux chambers”, as required by the Government of Alberta. Compared to the existing flux chamber measurement approach, the project demonstrated five technologies: inverse dispersion modelling (IDM), fixed sensors including smart poles, open path systems, drones, and satellites. The project aimed to help the oil and gas industry develop a holistic system of sensors and models to achieve more accurate quantification of methane and carbon dioxide emissions, to enable more targeted reduction strategies.

Alternative measurement technologies may be superior to conventional methods

Project results showed that all alternatives tested during the technologies were an improvementover the flux chamber industry standard. They proved to be technically sound, more representative of true emissions, and more cost effective. The project found the following recommendations for emissions measurements at tailings ponds and mine areas:

• The eddy-covariance (EC) method for fugitive emissions characterization – a well-established and well-regarded meteorological approach for measuring gas fluxes above an emitting surface – is best for small area sources.
• Inverse dispersion modelling (IDM) with Las Gatos Research (LGR) portable, fixed-point GHG analyzers, based on cavity ring-down spectroscopy to obtain gas concentrations,are best for conducting emissions measurements at tailings ponds.
• The WindTrax (IDM) model, a backward Lagrangian stochastic approach using concentration measurement taken upwind and downwind of the emitting surface, is most effective for characterizing emissions from sources with simple terrain and wind flow patterns i.e. tailings ponds.
• CALPUFF IDM, which simulates the movement and dispersion of individual puffs emitted in each time step and overlays the puffs for each pre-selected receptor location and IDM,takes observed data to find an emission rate that best explains the observation. This method is best for complicated terrain.
• Air mass balance is best for conducting emissions surveys at mine areas, although it has logistical and cost challenges.
• The optimal approach for conducting emissions measurements from mine areas is the IDM method with LGR GHG analyzers.

What’s next? 

The study results provided learnings about alternative measurement methods and supporting recommendations that can be adopted. The current flux chamber technology mandated by the Government of Alberta does not provide a true picture of emissions, especially in the case of methane. Alternative methods of emissions quantification can be applied for approval by Alberta Environment and Protected Areas (AEPA).

Additionally, the project resulted in recommendations for monitoring of CO₂ emissions that prove to be a challenge at tailings ponds and mine sites. CO₂ emissions are difficult to characterize due to interference in natural emissions, therefore the study recommendation is to monitor CO₂ emissions by applying filters to the CO₂ emission results. Laser path technologies, such as S3’s GreenLITE coupled with IDM, are the most promising to obtain emissions estimates, as they can scan across large areas both horizontally and vertical in real time and under remote control.