Methane Detection Framework

– Quantitative Concentration Measurement versus Emissions Rate Estimates

Figure 1.  Methane monitoring technologies include satellite, airborne, drone-based, and walking SEM (Surface Emissions Monitoring). 

These technologies all measure and characterize spatial concentrations of methane at or above background levels and vary in deployment modality from satellite to aircraft to drone and localized measurements (Figure 1). While the principle of concentration measurement is consistent across all measurement technologies, the units reported for methane emissions can be shared as geolocated methane concentrations ([CH4]) or as an emission rate (volume or mass emitted per unit time). The difference between these reported values causes some confusion amongst non-experts, particularly in regards to their relative value to operators and impact on regulations. This technical brief seeks to educate and clarify the differences in these measurement units.

Ambient methane concentration measurements in air are obtained using a gas analyzer

to measure the volumetric fraction of methane in an air sample by interrogating the air sample itself. The in situ sensor technologies for direct concentration measurement, including optical techniques (TDLAS, NDIR), flame ionization (FID), and selective thin-film measurement, all quantify in terms of parts-per-billion-by volume (ppbv) or parts-per-million by volume (ppmv). These measurements detect the absolute concentration of methane in air at an exact measurement location. High performance in situ methane concentration sensors have been miniaturized and are typically fielded in handheld configurations, or as payloads in aircraft, vehicles, or small drones.

Comparing Alternate Methods for Remote Sensing

Alternate methods for methane detection rely on remote sensing whereby there is no requirement to directly interrogate an air sample, rather spectroscopic methods are used to quantify the total absorption, due to a gas such as methane, across an optical pathlength. The photons required for these spectroscopic methods can be sourced from solar irradiation (passive remote sensing) or a synthetic source such as a laser (active remote sensing). These approaches quantify the total methane enhancement within the total pathlength from photon source to the detector. Satellite remote sensing instruments utilize photons from the sun for passive spectroscopy where the total pathlength is the round trip from the sun through the atmosphere (including the return through the atmosphere) before the satellite sensor measures the upwelling solar irradiation. This is similar for aircraft technologies with passive sensors where the solar photons travel through the entire atmospheric column, reflect off the earth’s surface, and return as upwelling solar irradiation to the aircraft sensor flying at a specified altitude. 

For active remote sensing payload, typically deployed on aircraft or drones, a laser tuned specifically for methane is emitted from the sensor where it reflects off of the earth’s surface and returns to the sensor. Thus the total pathlength for this synthetic photon source is 2x the above ground level (AGL) flight altitude. All of these remote sensing approaches, including the active and passive methods, detect methane concentration enhancements in units of parts-per-million-meter (ppm-m, Figure 2).

Figure 2. Concentration Pathlength (CPL) measurement principle. Shown are examples demonstrating the detection of a CPL value of 100 ppm-m whereby the finding is non-deterministic in terms of plume characterization. For instance, if a passive remote sensor is measuring enhancements at 1km AGL, a 100 ppm-m value could reflect several scenarios: (A) 5 ppm enhancement across the entire 20 m column, (B) 20 ppm enhancement across the bottom 5 m of column, or (C) 50 ppm enhancement in the bottom 2 m of the column. This non-unique solution makes interpretation difficult.

While these Concentration Pathlength Sensors (CPL) detect methane enhancements on a per-pixel basis in terms of ppm-m, the ultimate reporting unit is the amount of methane released from a leak location per unit time, also known as “methane emissions flux rate”, in units of kilograms of methane per hour (kg CH4 / hr), or a volumetric flux rate, in standard cubic feet per minute (SCFM CH4). This translation requires models to correlate the plume pixel methane concentration map to emissions rate estimates. Additionally, wind calculations can add uncertainty to achieving mass flow rate. 

Direct Concentration Measurement

Direct concentration measurement data is most useful for the exemplar use case of source detection and localization. When these data are collected across a large area, such as a landfill or renewable natural gas facility, the concentrations enhancements clearly identify the areas where there is proximal leakage. Thus, accurate leak location information can be used by the operator to directly mitigate sources. The methane enhancement pixel maps can be used in similar fashion, although because the techniques are remote sensing measurements, they are not as sensitive and often have high error rates associated with these methane Concentration Pathlength (CPL) measurements, error which is further compounded by ill-constrained model parameters.

It must be emphasized that all of the approaches derive a flux rate from a methane concentration product. Translation of these methane concentration data products into emissions rates are all dependent on advanced atmospheric dispersion modeling. These model outputs are highly sensitive to model inputs such as wind speed and direction, other atmospheric conditions (e.g. turbulence), and estimated source locations. In order to obtain emission rate data from the concentration measurement techniques, including the ppbv / ppmv or Integrated pathlength enhancements, inverse models must be used to translate the plume enhancements to emission rates. These quantitative methane emissions flux rates can be calculated by several different methods (Figure 3).

Figure 3. Three common methods for calculating methane flux rates from methane concentration measurements:

(a) Integrated Mass Enhancement (IME) is calculated from airborne remote sensing methods from the total methane enhancement using a concentration map of methane enhancements (ppm-m) across an area of the landfill or area of  interest, combined with windspeed.

(b) Vertical Flux Plane (VFP) approach integrates the 2D ambient air methane concentration data, collected in a downwind vertical plane (e.g. curtain raster pattern) at various altitudes, with wind speed and direction to estimate the amount of methane per unit time passing through the downwind VFP.

(c) At-surface measurements, collected via a walking drone surface emissions monitoring survey (SEM) or using a drone (DSEM) can be used to estimate methane emissions flux rates assuming gaussian distribution and integration across detected sources. These data are then modeled using a characterization approach which models the at-surface concentration data to virtual sources to estimate the total landfill site emissions (e.g. SEM2FLUX.

This contemporary focus on methane emissions rate quantification, expressed in terms of mass or volume of methane released per unit time, is valuable to operators to understand how much product they’re losing, however, when inverse models are applied to these concentration data, the errors are often very high due to the uncertainties in environmental conditions, including wind speed and direction, and the complexity of the models. Often errors can range from 15% (industry leading) to 50% or greater based on the quality of the methane concentration data and the accuracy of the environmental parameters. Landfills in general are difficult environments in which to constrain the environmental conditions largely due to the topographic complexity of these environments which are not captured by advanced atmospheric models like NOAA’s High Resolution Rapid Refresh (HRRR) at 3km resolution.

For these reasons, models vary in terms of uncertainties and results often differ between different inverse atmospheric dispersion models. This high uncertainty is also the reason why these passive remote sensing methods (satellite, airborne, drone) are not appropriate for inventory purposes.

Value to Customer – Actionable Data

The priority for the operator is to understand the presence of emissions, and their accurate locations, in order to eliminate loss pathways. The more accurate the emissions location the better for the operator to make site improvements. The sensitivity and resolution of the approach is also critical in evaluating utility of a method for operational deployment at a landfill or RNG site. There is typically an inverse correlation between sensitivity and the area coverage per day where satellites remote sensing provides the largest area coverage at the lowest sensitivity, or in the case of drones which provide data up to 200 acres per day at the highest sensitivity (Table 2).

Regarding localization accuracy, the Ground Sample Distance (GSD) is a critical parameter where course spatial resolution sensors can show that there is a problem on a particular landfill or RNG site, but more granularity is needed to make these data truly actionable for the operator. Satellite approaches exhibit resolutions (or ground sample distance, GSD) of approximately 30m per pixel, which is considered low resolution lacking granularity. Aircraft passive remote sensing approaches can do better at ~5m per pixel but none is as useful in granularity compared to drone approaches which are accurate to 2m* or better GSD, thus providing the highest fidelity leak localization capabilities.

The landfill and renewable natural gas (RNG) industries have a primary need for detection and localization of leaks so that the operators can take mitigative action. The value for RNG companies is underscored by the fact that the value of biogas product is enhanced based on federal and state subsidies that increase the value of this renewable energy source. RNG customers are also interested in estimates of emissions rates because they can assess the business case for additional gas capture via GCCS expansion or modification. RNG operators utilize standard-cubic-feet-per-minute (SCFM) as the standard unit for methane emissions flux rate and even estimates with 15-30% uncertainties can inform the potential for additional gas capture to drive revenue streams.

Relevance to Regulations

While both the direct concentration measurement and CPL of these methods provide valuable data to inform on leak detection, localization, and quantification, they need to be evaluated for relevance to US federal and state regulations. The key metric to evaluate relevance to regulations include the accuracy of the method for leak detection and localization, the reproducibility of the method, and traceability to common scientific measurements. Direct concentration measurement techniques are reproducible using commercial-off-the-shelf sensors. All will perform similarly when measuring gas concentration at a particular location. For this reason ground and drone-based concentration measurements are incredibly reproducibly while analyzing air samples for methane trace gas concentration. Sensors can typically measure or register methane concentrations in air in the parts-per-million (“ppmv” or “ppm”) range to parts-per-billion (“ppbv” or “ppb”) range.

The large uncertainties of passive remote sensing for flux rate quantification make it unsuitable to use as a primary dataset for regulatory purposes. These high uncertainties, combined with the reliance on model input parameters means that no standards currently exist to calculate these emissions rates. Often these inverse models are also proprietary to those companies offering these services, which compounds the traceability of these techniques. 

While the methane satellite observation era has advanced dramatically over the last two years, in particular with the launch of Carbon Mapper Tanager-1 and MethaneSAT satellite instruments in August-2024, the CPL flux rate methods continue to be assessed for their respective accuracies for flux rate determination. Errors associated with these passive remote sensing approaches for flux rate estimates are commonly realized in the range of ±15-50%. This ensures that more repeatable and consistent measurement techniques should be maintained for compliance such as currently required under Method 21 Walking Survey SEM and OTM-51 DSEM. While these techniques are incredibly useful, they can’t be used as the sole regulatory technique and should be used as non-regulatory, qualitative metrics to indicate leakage in a particular area.

*Samples collected directly from the flight path. 

Landfills in the United States are governed by United States Environmental Protection Agency (US EPA) regulations requiring operators to measure surface methane emissions quarterly across the landfill at 30m spacing (or at tighter spacing, depending on the state). These regulations require landfill Surface Emissions Monitoring (SEM) via Method or via an approved Other Test Method (OTM). Method 21 surveys dictate measurement of methane concentrations across the entire landfill surface during a serpentine path walking survey. The required equipment includes a methane leak detector sampling within 5-10 centimeters (2-4 inches) of the landfill surface, and methane concentrations that meet or exceed 500ppmv are regulatory violations requiring remediation.

Summary

Sniffer Robotics provides a patent-protected,  methane emissions monitoring solution, providing quantitative methane concentration data to landfill and renewable natural gas (RNG) owners and operators.

The SnifferDRONE method, classified as Drone Surface Emissions Monitoring (DSEM), is the only method approved by the Environmental Protection Agency (EPA) for landfill Surface Emissions Monitoring (SEM) compliance under Other Test Method 51 (OTM-51), specifically granted to Sniffer Robotics as specified in Alternative Test Letter (ALT-150). The onset of satellite remote sensing in the commercial market, which data are useful for super-emitter detection, represent new capabilities utilized by regulators and SWF operators, often at no cost to the operator. While these regional and field-scale surveying approaches are useful for large emissions detection, their lack of sensitivity, low spatial resolution, and high quantification uncertainties render them typically ineffective to provide operational data for rapid mitigation. Higher spatial resolution is required for effective mitigation.

Please contact us if you have any questions regarding this technical brief and/or for further information about our solutions that help improve operations and our environment.

References

1.  Mohr, A.W., Barron, D., and Dorosz, K.A. Apparatus and method for collecting environmental samples. US 11175202B2, 2021.

2.  Figure 3 (A): Ayasse et al. (2019) Methane Mapping with Future Satellite Imaging Spectrometers.

3.  Figure 3 (B): Gålfalk et al. (2021); Shaw et al. (2021); Fosco et al. (2024)

4.  Figure 3 (C)  Abichou et al. (2023) Using Ground- and Drone-Based SEM Data to Locate Landfill Methane Emissions.