Methane（CH₄）It is the second most important anthropogenic greenhouse gas, and it plays an important role in the chemical process of the atmospheric environment. But there are huge uncertainties in the global budget of methane, especially the stocks of large facility sources, such as landfills, cattle herds, and oil and gas extraction infrastructure, which together contribute enormous amounts of energy to global emissions. influences.

Infrared cameras are relatively inexpensive leak detection tools, but they do not provide measurementsCH₄ Quantitative information required for throughput. In addition, remote sensing methods of tracer gas diffusion can be used to quantify fugitive emissions, relying on controlled release of tracer gases at the source, combined with concentration measurements of tracer and target gas plumes. However, this method requires expensive equipment and is relatively difficult to implement. For example, where access to the site to release the tracer is not possible, or where the plume may be suspended, the tracer approach may have limitations.

Facility-scale emission fluxes can be rapidly derived from near-field sampling (less than 500 meters from the source), which can be obtained from unmanned aerial vehicle (UAV) platforms. Drones are cheap, versatile and relatively easy to use. They can fly near the source and can be guided automatically using road signs for uniform and unbiased spatial sampling. However, measuring methane using sensors with ppm-level sensitivity of limited precision and accuracy imposes significant limitations on accurate source identification and flux quantification.

ABB's latest model of laser-based off-axis integrated cavity output spectroscopy (OA-ICOS) trace gas analyzer addresses this limitation and is ideal for fast and precise drone sampling. They are light enough to perform in situ with ppb-level sensitivityCH₄ Measurement.

Attached article"Testing the near-field Gaussian plume inversion flux quantification technique using unmanned aerial vehicle sampling"

Article link:https://doi.org/10.5194/amt-13-1467-2020

The work in the article was coordinated by a group of scientists at the University of Manchester who worked through the release ofTwo DJI Spreading Wings S1000+ octa-rotor UAVs were flown in the wind, and the application of near-field Gaussian plume inversion (NGI) method was used for unbiased UAV sampling control CH₄ Emission source.

The first drone (UAV1) was connected to the LGR-ICOS MGGA (older model of the GLA131-GPC Micro Methane Emissions Analyzer) on the ground using a 150m PFA tube. Samples were taken from the MGGA via tubing using a micropump. The sampling lag time between the air entering the air intake of the drone and the air entering the MGGA cavity was 25 seconds. Both the MGGA and the pump are powered by a 12V lead acid battery.

A new compact (3kg) LGR-ICOS GLA133-GGA UAV Greenhouse Gas Analyzer (called in the article) with a carbon fiber casing mounted on the second drone (UAV2)"pMGGA"）prototype. The sampling lag time between the air entering the external air inlet and the air entering the pMGGA cavity was 2 seconds.

▲ Left picture ：GLA131-GPC miniature portable methane emission analyzer;▲Right: GLA133-GGA drone-based greenhouse gas analyzer installed on a DJI S1000+ octa-rotor drone

The drone sampling method for source identification and flux quantification using the LGR-ICOS instrument was tested in two fields near a natural gas extraction facility in Lancashire, with sampling over five days prior to drilling or hydraulic fracturing. Methane was released from 0.25 meters above the ground at one of two controlled flux rates within the job site, and two drones were flown downwind of the release point for a total of 22 flight surveys of 8-9 minutes each (UAV1 flew 7 times, UAV2 flew 15 times). During flux analysis, the exact location of the flux rate and time-invariant plume is not disclosed, allowing true unbiased measurements.

▲Picture: Photographs of UAV1 (connected to MGGA on the ground) and UAV2 (connected to pMGGA mounted on the frame), showing the location of the air intake relative to the UAV base. (Shah et al.)

The location of the UAV and the controlled release and its sampling path are determined every day based on the public wind direction forecast and on-site wind direction measurement, so that the flight trajectory of each UAV is in the horizontal center in the downwind direction of the controlled release. The UAV1 operates using pre-programmed waypoints and ramps up. Each UAV1 flight survey consisted of two parts: one flight to the right of the source (projected onto the sampling plane, perpendicular to the mean wind direction), and one flight to the left. At the same time, each UAV No. 2 flight survey consists of a single flight to conduct a horizontal cross-section survey. The height of each cross-section is basically fixed, about 100 meters laterally from the take-off position.

▲Picture: The site used for drone sampling, the controlled release point is marked with an X (Shah et al.)

Both LGR-ICOS instruments were characterized and calibrated using standards certified by the World Meteorological Organization. The effects of cell pressure and cell temperature were evaluated, and water vapor correction factors were calculated specifically for each instrument. Using the NGI least squares flux quantification technique, the CH measured for each flight survey was calculated₄ Flux Density, which uses Gaussian statistics to account for changes in turbulent winds to derive emission fluxes.

The flux quantification method was experimentally demonstrated to be successful, and the authors observed that most NGI fluxes were in good agreement with known controlled emission fluxes. They observed that 19 of the 22 fluxes were adequately summarized in the UAV-derived flux uncertainty, validating this innovative approach to measuring facility-scale point source plume emission fluxes, which Methods Emission sources were relatively unchanged during drone sampling.

While the authors acknowledge that more precise flux estimates can be obtained using other methods, such as the tracer diffusion method, they emphasize that the method has been adapted for rapid flux analysis rather than precise flux measurements for inventories. A key advantage of this method is its ability to sample downwind of the pollution source to obtain off-site CH₄ Flux measurement. This sampling allows for CH₄Emissions conduct independent and portable studies without the need for heavy infrastructure, special permits, site access or prior notice. This method is well suited for regulatory leak detection and source isolation, as well as measuring the severity of flux leaks for subsequent investigation using other methods.

In summary, the Studies have shown that drone sampling combined with the LGR-ICOS compact trace gas analyzer can actually yield unbiased snapshots of emission sources and fluxes with NGI methods, with ppb-level accuracy, by measuring in a plane perpendicular to the wind direction. Upsampling, at least ~50m from the source. Going forward, the authors expect to combine UAV sampling with tracer release, taking advantage of UAV vertical sampling to simultaneously measure target gas and alternative tracers downwind, CH for large facilities as a powerful tool in the future₄ Accurate flux quantification of emission sources such as hard-to-access oil and gas extraction infrastructure, livestock and landfills.

This UAV solution can measure CO synchronously₂、CH₄、H₂O。