This entry describes the methods used to quantify methane emissions from either point or area sources using downwind methods. The methods described could be used as a practical guide to quantify emissions of any trace gas type from either a point or area emission source. Methane is a relatively strong greenhouse gas, its GWP is 25 times larger than CO2 over a 100-year period, and an increase in methane anthropogenic emissions has been correlated to a changing global climate. Emission estimates that are calculated and used for national inventories are usually derived from bottom-up approaches, however there is now an increasing pressure for these to be validated by direct measurement. Calculating emission rates from downwind measurements has proven to be a versatile and relatively simple approach for direct measurement. Downwind measurement method descriptions are presented here as a practicable guide to quantifying point and area source emissions. Emission quantification is a two-stage process where methane concentration and meteorological data must be measured downwind of a source and then converted to emissions using an atmospheric dispersion model. Only four technology types currently measure in the range typical of downwind methane concentrations: metal oxide sensors, non-dispersive infrared sensors, tunable diode laser absorption spectrometers and optical cavity instruments. The choice of methane measurement is typically determined by the size of the emission source, location and the budget of the project. Meteorological data are essential to quantifying emissions, especially regarding wind speed and direction. In most cases, simple atmospheric dispersion approaches can be used to quantify both area and point emissions using these downwind measurements. Emissions can be generated using limited data (only methane concentration, wind speed, wind direction, and locations are necessary), but quantification uncertainty can be reduced using more input data. Site selection and location of instrument deployment are essential because quantification approaches assume a flat fetch (no aerodynamic obstructions) and constant wind fields. When modeling assumptions are violated, quantification uncertainty can range between +250% and −100% of the actual emission rate. At present there, is no happy medium between modeling complexity and computational time, and this remains the biggest challenge for downwind emission quantification.
This entry describes the methods used to quantify methane emissions from either point or area emission sources using downwind measurements. The description of methods could be used as a practical guide to quantify emissions of any trace gas type (e.g., carbon dioxide, hydrogen, nitrous oxide) as gases tend to become very dilute after emission (from ~0.1% to ppm-levels after distances ~1 m) and different gases have negligible buoyancy differences when diluted
[1]. Here, methane is used as the example trace gas as it has practical importance to emissions from the energy, waste, agriculture and natural sectors.
Over the past decade, it has become accepted that the changing global climate is a response to the increase in atmospheric gas species’ concentration
[2][3][4][2,3,4]. This has largely been attributed to an increase in gas emissions from anthropogenic activities, which have resulted from changes to industrial manufacturing, agricultural processes and energy demand
[2]. Due to their absorption of infrared radiation, several gases have been identified as greenhouse gases (GHGs), e.g., carbon dioxide, methane, nitrous oxide and sulfur hexafluoride. Each gas type has the capacity to absorb a different amount of infrared radiation, typically standardized against carbon dioxide, which has a global warming potential (GWP) of one, and more heat is trapped in atmosphere with a larger abundance of atmospheric GHGs.
Methane is a relatively strong greenhouse gas as its GWP is 25 times larger than CO
2 over a 100-year period
[2][4][2,4]. The 100-year GWP (GWP100) is universally accepted as the standard GWP metric for comparison between gases
[5]. Until recently, most GHG emissions at site, region and national levels have been calculated using bottom-up methods, where emissions are calculated by multiplying the number of emission activities within the area of study by an emission factor
[6]. Emission factors are a quantitative assessment of how emissive a source is; units are typically “grams of gas per unit time”, and usually derived from a measurement study. More recently, it has become apparent that there are significant differences between bottom-up emission estimates and the amount of gas that has been emitted
[7][8][9][10][11][12][7,8,9,10,11,12], with the discrepancy largely attributed to incorrect or inaccurate emission factors
[10][13][14][15][10,13,14,15].
With climate goal deadlines looming, there has been an increased demand for the validation of emission estimates
[16][17][18][16,17,18]. Typically, this has been adopted as “Measurement, Monitoring, Reporting and Verification Frameworks”, which require greenhouse gas emissions to be verified through direct measurement. Direct measurement can be made in a number of ways: enclosing the source in a chamber; summing individual sources within an area; inferring emissions from downwind measurements; using tracer flux; making eddy covariance measurements; applying a mass balance approach; or remotely sensing the plume using aircraft or satellite
[7][19][20][21][22][23][24][25][26][27][28][29][7,19,20,21,22,23,24,25,26,27,28,29]. The advantages and disadvantages of these methods are described in a number of papers
[23][30][23,30] but are often limited by either high quantification thresholds—10+ kg CH
4 h
−1 for aircraft
[22] and 100+ kg CH
4 h
−1 for satellites
[7][11][31][7,11,31]—or the need for direct access to the emission source.
Inferring emissions from downwind measurements does not suffer from these shortcomings and has proved to be a versatile and relatively robust approach for quantifying emissions. Sources can either be point or area sources and emissions can be calculated using relatively little data, e.g., methane concentration and wind speed, at a minimum. Uncertainty in quantification decreases with an increase in input data quality. Downwind methods have been used to quantify methane emissions from onshore oil and gas facilities
[27][32][27,32], offshore oil and gas facilities
[33][34][33,34], landfill
[29][35][36][29,35,36], agriculture
[37][38][39][40][37,38,39,40], and natural sources
[37], with emission ranging from 10 g CH
4 h
−1 to 100 kg CH
4 h
−1 [33].
Methane concentration data are essential for calculating the emission. The size of the concentration observed is a function of distance downwind, the size of the emission, the wind speed and atmospheric stability. Typically, expected downwind methane concentrations are less than 20 parts per million by volume (ppm)
[27][37][38][41][27,37,38,41]. Background methane concentrations are also required; these are typically measured upwind of the source and usually observed to be ~1.8 ppm
[12][37][42][43][12,37,42,43]. Coupled with concentration data, meteorological data are also required with wind speed being essential. This can be measured using a standard rotating-cup anemometer, but better quantification accuracy can be achieved using a 3D sonic anemometer. Other meteorological data are desirable but not essential, including wind direction, temperature, relative humidity atmospheric pressure, and solar irradiance. Similarly, micrometeorological data are desirable but emissions can be quantified without quantitative data. These data are usually measured by a 3D sonic anemometer but can also be derived from lower-tech instruments. Details are provided in full below.
Point sources are defined as a single identifiable source of emission, e.g., a crack in a pipe, while an area source is a group of sources emitted over a finite region. There is a degree of fluidity between how a source may be defined, point or area, and this is usually a function of observation distance. For example, a landfill can be considered an assemblage of individual point sources when measuring on-site, an area source at a middle distance, and a single-point source when observed from even farther away. The distance at which the source transitions between types is dependent on the size and distribution of the sources and needs to be determined for each individual emission scenario. Emissions are typically presented as the emission rate in units of “grams of gas per unit time” for point sources or as a flux in units of “grams of gas per unit area per unit time” for area sources.
As mentioned above, quantification uncertainty depends on the quality of the input data. For very far-field measurements, up to 10 km away, the uncertainty has been estimated at plus/minus a factor of two (+100%, −50%)
[33]. For nearer measurements (less than 1 km), downwind methods’ quantification uncertainty has been measured at ±60%
[37][44][37,44] using controlled releases. At even closer distances (<5 m), downwind methods’ quantification uncertainty has been measured at less than ±15%
[20][30][20,30]. The main cause of uncertainty at small distances is parameterizing the lateral dispersion of the plume, and this can be overcome by measuring directly downwind of the emission source.
In recent years, many publications have described methods that use downwind measurements to quantify methane emissions. In this entry, method descriptions are presented as a practicable guide to quantifying point and area source emissions with the inclusion of suggestions that could be used to work around missing data or overcome instrumentation shortcomings.
