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Trace gas and energy flux measurement at micro-meteorological scales

Measurement of the exchange of trace gases, w'ater vapor, and energy between the atmosphere and Earth’s surface has seen extensive development in the research community for several decades, driven mainly by technological developments in wind velocity measurement due to advances in ultrasonic anemometry. The significantly improved frequency response in 2 and 3 dimensions up to к 100 Hz has advanced the development of the eddy covariance (EC) measurement technique. EC quantifies exchange fluxes of trace gases, water vapor, particulates, and sensible heat energy between the surface and the PBL via the constant flux layer communicating with surface processes. EC measurement has been important to better understand ecosystems and the processes forming their function and to the field of micro-meteorology with industrial applications, e.g., in agriculture (Parker, 2015), being an important research element. The information and insights provided by the EC and related methods is an important means of testing ecosystem, crop, and land surface models useful in predicting response both to changes in average values of climate-related parameters, and to their anticipated extremes.

The eddy covariance technique is based on the measurement of atmospheric turbulence properties. A fundamental assumption is that of homogenous and fully turbulent atmospheric transport in the region of interest at and near the surface. Primarily driven by circular eddy structures in the lower atmosphere, these eddies transport atmospheric constituents primarily horizontally but with vertical components that carry gases or energy fr om the surface into the PBL via a constant flux layer. Mathematically the vertical flux, or net ecosystem exchange, F (in units of mol in"2 s'1), can be represented as the covariance of the vertical velocity and dry air molar density of the species of interest, e.g., CO: (Burba, 2013; Gu, 2012).

where: F = vertical flux or net ecosystem exchange (mol m~2 s"1),

cd = mean dry molar density (mol in'3),

w' = instantaneous deviation from the mean of the vertical velocity

(turbulent component),

s' = instantaneous deviation from the mean of the species of interest dry

ah' mole fraction, and

ir’s' = mean of the instantaneous deviations of the vertical velocity and dry ah mole fraction covariance.

This simple mathematical relation rests on numerous assumptions. Some of the primary ones are the following.

  • • Homogenous and fully turbulent atmospheric flow with mean vertical flow assumed to be small to negligible (in some theoretical treatments).
  • • No sources or sinks sufficient to interrupt this homogeneity exist in the domain.
  • • Ah density fluctuations are negligible, i.e., ah density is constant or closely so over the period of the observations, generally on the order of a few minutes to hours.
  • • The species of interest are chemically stable during the time of the observations.

Experimental conditions must also account for these assumptions; some of these are the following:

  • • Terrain over which the flow is established is homogenous.
  • • Observations at the measurement site are representative of an area upwind, i.e., a fetch or footprint (this chapter hr a larger geographical sense, sec 5.2.1.3, and in the next section).
  • • Wind velocity, atmospheric temperature, and pressure instrumentation must be sensitive to small changes at high frequencies.
  • • Mean air flow and turbulence at the measurement point are not appreciably distorted by the observing installation structure or the instruments themselves.
  • 6.5.1 Obsen’atioiis and footprint modeling—the field of view

In the eddy covariance technique, nricrometeorological instruments are usually placed on a tower at a height chosen for sensitivity to the region of interest. Instrumentation generally includes ultrasonic anemometers, positioned to measure the three atmospheric velocity components, ah' temperature and pressure, and specific auxiliary parameters pertinent to the investigation. Frequency response of the instruments observing EC-related parameters should be comparable to that of the anemometry, if possible, they should have similar frequency response. Because this may not be the case, correction methods have been developed to account for these effects in the analyzing observations (Horst, 2000). Observations are usually taken over hourly or sub-lrourly periods when atmospheric dynamics are relatively constant, such that the EC assumptions of constant mean air density and atmospheric velocity are met. The term “footprint” summarizes the concept of the region, or effective fetch, that influences data at the observation station. Much like the influence or sensitivity functions discussed previously (sec 5.2.1.3) which determine the location of sources or sinks that influence or enhance the signals observed in the much taller towers associated with urban networks. Footprint models seek to describe the originating locations of EC signals. Several footprint modeling approaches have been developed in order to establish formal connections between micrometeorological flux measurements of trace gases above a vegetation region and their mass conservation in a surface-vegetation-atmospheric context. Footprint modelling is a means of investigating limitation of the concept, particularly in the design and analysis of experimental arrangements (Schmid, 2002; Vesala. 2008).

6.5.2 EC applications in carbon management

Although in many cases carbon management focuses on emissions, one should keep in mind that, on a global scale, approximately one half of yearly anthropogenic emissions are removed from carbon sinks, either by the oceans or the land. EC methods have been widely utilized as a critical resource to increase our knowledge of vegetative exchanges with the atmosphere, i.e., CO, uptake or removals. For example, agricultural applications use EC methods to better quantify greenhouse gas emissions from cropped and grazed soils under ctment management practices and to identify and further develop improved management practices that will enhance carbon sequestration in soils, decrease emissions and uptake of CO, due to crop and soil photosynthetic activity. Methane emissions from various livestock-related process, and N.O emissions, e.g., from fertilization process, are also investigated using EC methods. This information can promote sustainability and provide a sound scientific basis for carbon credits and GHG trading programs (Follet, 2010).

Several research networks that use EC as a central method for the study of ecosystem processes har e been established. In the U.S., NSF’s National Ecological Observatory Network (NEON) (Batelle,

2011) has been designed to collect data that characterize and quantify complex, rapidly changing ecological processes across the continental U.S. The Ameriflux research network relies upon principal investigator-managed sites uses EC methods to measure ecosystem fluxes of CO„ water, and energy in North, Central, and South America (Amenflux/DOE, 2015). The FluxNet network is a global network of micrometeorological tower sites that use eddy covariance methods to measure the exchanges of carbon dioxide, water vapor, and energy between terrestrial ecosystems and the atmosphere (ORNL DAAC, 2002). The Integrated Carbon Observing System Research Infrastructure (ICOS, 2008) aims to provide long-term, continuous observations of greenhouse gas sources and sinks. ICOS is a pan-European research organization focused on carbon cycle science, greenhouse gas budgets, and the perturbation thereof. The EC technique is a principal method in the national ICOS observing stations that span applications to ecology studies and atmospheric and ocean stations. To ensure consistency in data and analysis, ICOS has established a system of standards and instrumental configurations primarily for atmospheric stations (Rebmaun. 2018).

Mass balance and tracer gas methods for emissions determination

Mass balance flux estimation methods are usually conducted using measurements of trace gas mole fraction and horizontal wind velocity to estimate emissions flux using a conservation of mass between upwind and downwind observation points of the atmosphere. Wind vector information can be obtained using either direct measurement, often the case with airborne experiments, or simulated values obtained fr om Numerical Weather Prediction Models. The method has been applied to atmospheric trace gases of interest to both the air qualify and greenhouse gas measurement communities. The mass balance method is based on measurement of the difference in flux entering and leaving a region and has been applied to cities (Salmon, 2018), to large sources within urban areas (Conley, 2017), and more generally to individual or small groups of sources (EPA GHGRP, 2015; White, 1976). The method may be applied to individual emission processes or facilities or to defined geographical domains using either fixed or mobile observing methods located on the surface or from airborne platforms. Flux quantification from a source, such as a city or an isolated emission source, e.g., power plant located far from other sources, using this approach is a difference measurement based on mole fraction observations taken both upwind and downwind of the source using various types of mobile platforms.

6.6.1 Airborne platforms

Aircraft-based greenhouse gas mass balance measurements are quite useful for obtaining a snapshot of emissions from domains over which an aircraft can fly multiple transects in and out of the source’s concentration plume. Measurements of the trace gas concentration are made in real-time of air typically pulled into a sampling port as the aircraft transits the region. The spatial resolution and transect length of such measurements depends on the aircraft’s speed and the instrument sampling time. Given the variability in wind direction and speed over the area flown, instantaneous aircraft velocity measurement and trajectory information are required in order to determine complementary wind vector values during the course of an observation. The use of aircraft GPS instrumentation or fast-response wind probes has improved the accuracy and reliability of these measurements in recent decades.

As shown in Figure 13, flight planning is used to orient flight paths to be as near perpendicular to the wind direction as practicable. Figure 10 shows a diagram of a domain around the Baltimore-Washington D.C. region with CO, mole fraction measurement over multiple horizontal and vertical transects. These snapshots of mole fraction spatial distribution are taken both horizontally and vertically in the planetary boundary layer where emission plumes, to some degree, remain intact as they move vertically through it. The variation in mole fraction both horizontally and vertically is sampled, clearly showing the downwind plume from the urban areas. In this case, both upwind and downwind transects are used to determine the flux difference due to city emissions. In some cases, horizontal downwind transects that sample the atmosphere well away from the urban plume may be used, as they are perhaps more representative of background conditions (Karion. 2015; Cambaliza, 2014).

The data shown in Figure 13 illustrates the requirements placed upon mole fraction measuring instrument response, sensitivity, and accuracy in this application. Here, the CO, mole fraction range is 10 gmol/mol to 15 pmol/mol. To support these accuracy requirements, airborne instrumentation measurement strategies often include the use of on-board reference gas standards to characterize instrument performance and accuracy before, after, and at times dining a flight.

6.6.2 Surface mobile platforms

Observations of emissions using ground vehicles have been used to characterize emissions of methane from the oil and gas production, transportation, and delivery systems. Similar in concept to airborne methods, IR imagers and mole fraction measurement instruments mounted on cars and trucks are used to observe trace gas plumes downwind of point sources. These mobile sensing approaches have been used extensively to identify emission sources and fugitive emissions, and to characterize known emission sources (Albertson, 2016; Yacovitch. 2017; Weller, 2018). Unlike airborne platforms, where the vertical extent of a plume can be observed, surface vehicle-based surveys are limited in altimde to a few meters above ground level. Wind speed determinations are made with auemometry, either at a fixed location near the point of investigation or mounted on the vehicles involved. In the latter case, compensation for vehicle motion relative to wind direction and speed is required.

Another technique often combined with mobile observing platforms uses a surrogate gas that can be observed experimentally as a tracer to infer the emission rate of another gas not measured directly. Tracer experiments often involve releasing tracer gases at measured rates near a suspected emission location. A mobile measuring vehicle transits downwind of the locations of interest, observing the enhancements of the tracer gases. Given that the ratios of measured species to non-measured species mixing ratios are known, these combined with measured tracer gas release rate(s) provide the means to determine emission rates (Yacovitch. 2017).

 
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