Natural Gas Midstream
Remote methane sensor for emissions from pipelines and compressor stations using Chirped-laser Dispersion Spectroscopy Last Reviewed
November 2017


The goal of the project is to develop, test, and field demonstrate a remote sensing methane (CH4) detector for use on aircraft and vehicles to detect leaks along midstream infrastructure of the natural gas supply chain.

Princeton University, Princeton, NJ 08544
American Aerospace Technologies, Inc., Conshohocken, PA 19428

Fugitive methane leaks from the natural gas supply chain to the atmosphere mitigate the climatic benefits of switching away from other fossil fuel sources, but large measurement challenges exist in identifying and quantifying CH4 leak rates along the vast number and type of components in the natural gas supply chain. This is particularly true of the "midstream" components of gathering, processing, compression, transmission, and storage. In contrast to sampling well pads where spatial length scales are on the order of 10 m, the length scales of midstream components are immense. Nearly 500,000 km of transmission pipelines form a complex network across the US. Distributed at various points along these networks are another 700,000 km of gathering pipelines, 600 processing plants, 1,400 transmission compressor stations, and 400 underground storage units nationwide.

The large areal and linear extents of midstream infrastructure creates sampling challenges. Mobile laboratories are limited to the road network and favorable (downstream) wind directions when, for example, sampling processing/compressor stations. Ground‐based measurements and tracer approaches also require favorable meteorological conditions. Because significant amounts of CH4 are emitted into the compressor station exhaust, the warmer and more buoyant plumes often will not be captured by ground‐based techniques.

To address the plume lofting and large length scales for midstream sampling, this project will develop and deploy a novel remote sensing CH4 sensor from either light aircraft or a mobile laboratory. This will involve sensor refinement, field testing, and algorithm development; validation experiments on a vehicle and then aircraft with controlled releases of methane; and flights along pipeline corridors in the Mid‐Atlantic and Marcellus Shale region to demonstrate technologies for commercial readiness.

Research to be performed is divided into seven major tasks that shall be conducted over a three year period and that are designed to achieve the research objectives in the most efficient and cost‐effective way. These include:

  • Development of a heterodyne enhanced chirp modulated chirped laser absorption spectroscopy (HE‐CM‐CLaDS) system for remote methane detection.
  • Laboratory testing of system parameters including methane sensitivity, spectroscopic drift, and evaluation of the heterodyne‐enhancement approach range‐finding capabilities. Different target materials shall be tested to determine the system limitations in hard‐target remote sensing schemes. In addition, comparison of the HE‐CM‐CLaDS system with that of conventional systems based on direct optical detection will be performed and detection limits will be determined.
  • Demonstrate system performance outside in a field environment with a goal of quantifying precision, accuracy, and range resolution. An outdoor calibration facility will be constructed to accurately determine a known amount of CH4 along a pre‐defined optical path.
  • Investigate two approaches to convert field-based, range‐resolved CH4 concentrations into leak rate measurements: an inverse Gaussian approach and a mass balance approach. The agreement between the two approaches will be used to assess data quality, sampling protocol, and meteorological limitations, as well as the remote, range‐resolved CH4 concentrations and approximate flux estimates.
  • Conduct vehicle-mounted backscatter measurements from roadways along pipelines and other midstream gas/oil infrastructure.
  • Develop and test a micro‐drone (i.e., hand‐sized, ~ 200 gram) system capable of following and hovering ~ 30 feet above the vehicle-mounted sensor. The micro-drone shall support back‐reflection for vertically‐integrated measurements via light‐weight retro‐reflectors.
  • Sensor integration on a light manned aircraft (e.g., Cessna 210), conduct test flights, and detection of CH4 leaks along a pipeline corridor.


The key innovation is HE‐CM‐CLaDS, an approach that uses optical dispersion rather than absorption to detect atmospheric CH4. Instead of detecting changes in light intensity as in an absorption-based measurement like all existing optical sensors, HE‐CM‐CLaDS detects the phase shift of laser light resulting from optical dispersion. One of the key advantages to this approach is its strong signal intensity, a feature that is critical for a backscattered approach where near‐infrared light is collected from a wide range of surfaces and ground cover. Remote standoff detection means the technique will be capable of deployment on a vehicle or aircraft for large area scanning such as an overflight of a pipeline corridor or around gathering or compressor stations. Finally, HE‐CM-CLaDS provides a range‐resolved signal that allows for 3D tomographic images with appropriate sampling/scanning design.

Because the HE‐CM‐CLaDS sensor can be used to send trained personnel to a specific, targeted pipeline site to fix a given leak, the anticipated benefits are saved labor and travel costs, improved pipeline safety, and reduced pipeline explosions, resulting in fewer injuries/deaths and less property damage. This will benefit pipeline companies and operators by mitigating costs associated with fines, liability, and legal fees. In addition, industry will benefit from system-wide recovery of otherwise lost product. Finally, by providing a remote sensing leak detection technology for companies, leaks along the natural gas supply chain will be mitigated more efficiently and less CH4 (and other associated hydrocarbons) will escape into the atmosphere, resulting in improved air quality and a reduced climatic footprint.

Accomplishments (most recent listed first)

  • Design is underway of the collecting optics to maximize power collection and allow auto-refocusing and optimal reflected signal from a moving target on an unmanned autonomous vehicle. The lens design will be integrated with the collecting optics for conventional CLaDS and the HE-CLaDS systems.
    Collecting optics for a) CLaDS and b) HE-CLaDS with auto-focusing signal provided by the camera. (click to enlarge)
  • Implemented ranging capability using a field-programmable gate array (FPGA), which will be used to integrate all functions of the CLaDS system in a single data acquisition and control system. Laboratory testing of the ranging capability has been initiated to test its compatibility with various CLaDS techiques.

Current Status (November 2017)
Current efforts are focused on developing the heterodyne‐enhancement to the existing, novel CM‐CLaDS sensor to improve back-scatter signal as well as development of range‐finding capabilities. In addition, a robust opto‐mechanical design of the system shall be initiated that will be later used for mobile platforms.

Project Start: October 1, 2016
Project End: February 29, 2020

DOE Contribution: $1,141,204
Performer Contribution: $285,299

Contact Information
NETL – Robert Vagnetti ( or 304-285-1334)
Princeton, University – Dr. Mark A. Zondlo ( or 609-258-5037)

Additional Information:

Quarterly Research Progress Report [PDF] October - December, 2017

Quarterly Research Progress Report [PDF] July - September, 2017

Quarterly Research Progress Report [PDF] April - June, 2017