Atmospheric dispersion modelling calculates how methane released from a source spreads through the surrounding air, allowing analysts to work backwards from measured concentration data to estimate the actual emission rate at the source. Without this step, concentration readings alone are essentially meaningless for quantification purposes. The sections below unpack how the modelling works, which approaches are most common, and why airborne measurement technology makes the whole process significantly more reliable.
How does atmospheric dispersion modelling calculate emission rates from detected methane?
Atmospheric dispersion modelling calculates emission rates by combining measured downwind methane concentrations with real-time meteorological data, particularly wind speed and direction, atmospheric stability, and turbulence. The model simulates how a plume of gas would spread from a point source under those conditions, then solves backwards to find the source strength that best explains the observed concentration pattern.
In practice, this involves fitting a mathematical description of the plume, typically a Gaussian spread function, to the measured data. The model accounts for how the atmosphere dilutes the gas as it travels downwind, how terrain and surface roughness affect turbulence, and how atmospheric stability classes change dispersion behaviour under different weather conditions. When the modelled plume matches the observed concentrations, the emission rate at the source is the output.
This inverse modelling approach is what transforms raw sensor readings into source-level methane emission factors that regulators and operators actually need. It is the critical bridge between detection and quantification.
Why can’t concentration measurements alone tell you how much methane is leaking?
Concentration measurements alone cannot tell you how much methane is leaking because the same emission rate produces very different concentration readings depending on wind speed, atmospheric stability, and distance from the source. A strong wind dilutes the plume rapidly, making a large leak appear small. Calm conditions concentrate the gas, making a small leak appear large.
Think of it this way: if you smell gas strongly, you know there is a leak nearby, but you cannot know whether it is a minor seep or a serious breach without understanding the atmospheric conditions at that moment. Concentration is a symptom; the emission rate is the underlying cause. Quantifying methane emissions accurately requires knowing both the concentration and the physical context in which that concentration was measured.
This is why operators who need to measure methane emissions for regulatory reporting cannot rely on point-in-time sensor readings without pairing them with a rigorous dispersion analysis.
What are the main types of dispersion models used in methane emission studies?
The main types of dispersion models used in methane emission studies are Gaussian plume models, Lagrangian particle models, and computational fluid dynamics (CFD) models. Each offers different trade-offs between computational speed, accuracy, and suitability for different source types and terrain conditions.
Gaussian plume models
Gaussian models are the most widely used in operational emission surveys. They assume that the methane plume spreads in a bell-curve pattern both horizontally and vertically as it travels downwind. They are computationally fast, well-validated, and well-suited to open terrain with relatively steady wind conditions. Their main limitation is that they perform less reliably in complex terrain or under highly variable wind conditions.
Lagrangian and CFD models
Lagrangian particle models track the movement of individual „packets“ of gas through a simulated atmosphere, making them better suited to variable wind fields and more complex environments. CFD models solve the full equations of fluid motion and offer the highest physical accuracy, but they are computationally intensive and typically reserved for detailed site-level studies rather than wide-area pipeline surveys. For most operational methane emission quantification work, Gaussian models remain the practical standard, with Lagrangian approaches used when conditions demand greater flexibility.
How does dispersion modelling support EU Methane Regulation compliance?
Dispersion modelling supports EU Methane Regulation compliance by providing the quantitative emission data that operators are legally required to report. Under EU Methane Regulation 2024/1787, operators of fossil energy infrastructure must not only detect leaks but quantify methane emissions at both the source and site level, report them annually, and have those figures verified by independent third parties. Dispersion modelling is the method that makes source-level quantification technically credible.
The regulation distinguishes between simply knowing that a leak exists and knowing how much methane it is releasing. Operators who rely only on detection surveys without quantification cannot satisfy their reporting obligations. Dispersion modelling closes that gap by converting measured plume data into the emission rate figures that compliance reports require.
For underground equipment in particular, the regulation sets high sensitivity requirements for Type 2 surveys. Meeting those requirements demands measurement technologies and analytical methods capable of detecting and quantifying even low-level fugitive emissions accurately, which is where the choice of both sensor technology and modelling approach becomes decisive.
What factors affect the accuracy of atmospheric dispersion modelling results?
The accuracy of atmospheric dispersion modelling results is primarily affected by the quality of meteorological input data, the spatial resolution and precision of the concentration measurements, the complexity of the terrain, and how well the chosen model matches the physical conditions of the survey. Errors in any of these inputs propagate directly into the estimated emission rate.
- Wind speed and direction accuracy: Small errors in wind measurements have an outsized effect on the calculated source strength, because wind is the primary driver of plume dilution.
- Atmospheric stability classification: The degree of atmospheric turbulence determines how quickly the plume spreads. Misclassifying stability conditions leads to systematic over- or underestimation of emission rates.
- Measurement height and spatial coverage: Ground-level measurements capture only part of the plume cross-section. Incomplete sampling of the plume leads to underestimation of total mass flux.
- Terrain and surface roughness: Complex terrain, buildings, and vegetation all disturb airflow in ways that simple Gaussian models do not capture well.
- Source characterisation: Knowing whether a source is a point leak, a diffuse area source, or a combination of both affects which modelling approach is most appropriate.
How does airborne DIAL technology improve dispersion modelling compared to ground-based methods?
Airborne Differential Absorption LIDAR (DIAL) technology improves dispersion modelling by providing full vertical and horizontal cross-sections of the methane plume rather than isolated point measurements at ground level. This complete plume profile allows analysts to calculate mass flux directly from the data, reducing dependence on model assumptions and significantly improving the accuracy of the resulting emission rate estimates.
Ground-based sensors, whether handheld detectors or vehicle-mounted systems, sample the plume at a single height and location. To reconstruct the full plume from those readings, the dispersion model must make many assumptions about how the gas is distributed vertically, assumptions that introduce uncertainty. Airborne DIAL eliminates much of that uncertainty by measuring the actual three-dimensional concentration field as the aircraft traverses the plume.
The practical advantages for emission quantification are substantial. Airborne surveys can cover large pipeline networks rapidly, capturing plume cross-sections under consistent meteorological conditions rather than stitching together measurements taken at different times and wind states. The result is emission rate data that is both more precise and more defensible for regulatory reporting purposes.
How ADLARES helps you quantify methane emissions with confidence
We combine airborne DIAL measurement with rigorous dispersion analysis to deliver source-level and site-level methane emission quantification that meets the requirements of EU Methane Regulation 2024/1787. Our CHARM® technology is the world’s only DVGW-approved airborne gas remote detection system, and it has been used to inspect over 250,000 km of gas pipelines across Europe. Here is what we bring to your emission quantification programme:
- Full plume cross-section measurement: CHARM® captures complete vertical and horizontal plume profiles from helicopter altitude, providing the high-quality data that accurate dispersion modelling requires.
- High sensitivity for underground infrastructure: Our system detects leakage rates from 150 litres per hour, meeting the sensitivity thresholds required for EU Methane Regulation Type 2 surveys of underground equipment.
- Rapid wide-area coverage: Surveys are conducted at speeds of up to 180 km/h, allowing large pipeline networks and facility sites to be covered efficiently in a single campaign.
- Regulatory-grade reporting: Results are delivered through a secure Web GIS platform, providing the documented, verifiable emission data that independent third-party verifiers and regulators expect.
- Site-level emission quantification: Beyond leak detection, we quantify total methane emissions from compressor stations, landfills, LNG terminals, and other facilities, supporting complete LDAR compliance reporting.
If your organisation needs to measure methane emissions accurately and meet its obligations under the EU Methane Regulation, we are ready to help. Learn more about our methane emission quantification services or get in touch with our team to discuss your specific survey requirements.