Performance simulations for a spaceborne methane lidar mission

Kiemle, Christoph; Kawa, S. R.; Quatrevalet, Mathieu; Browell, E. V.

doi:10.1002/2013jd021253

Cited by 43 publications

(44 citation statements)

References 33 publications

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“…However, the optimal usage of satellite data remains limited by systematic errors in satellite retrievals (Bergamaschi et al, 2009;Locatelli et al, 2015). The development of low-bias observations system from space, such as active lidar technics, is promising to overcome these issues (Kiemle et al, 2014). The partition of regional emissions by processes remains very uncertain today, waiting for the development or consolidation of measurements of more specific tracers, such as methane isotopes or ethane, dedicated to constrain the different methane sources or groups of sources (e.g.…”

Section: Introductionmentioning

confidence: 99%

The global methane budget 2000–2012

Saunois

Bousquet

Poulter

et al. 2016

Earth Syst. Sci. Data

934

733

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Abstract. The global methane (CH 4 ) budget is becoming an increasingly important component for managing realistic pathways to mitigate climate change. This relevance, due to a shorter atmospheric lifetime and a stronger warming potential than carbon dioxide, is challenged by the still unexplained changes of atmospheric CH 4 over the past decade. Emissions and concentrations of CH 4 are continuing to increase, making CH 4 the second most important human-induced greenhouse gas after carbon dioxide. Two major difficulties in reducing uncertainties come from the large variety of diffusive CH 4 sources that overlap geographically, and from the destruction of CH 4 by the very short-lived hydroxyl radical (OH). To address these difficulties, we have established a consortium of multi-disciplinary scientists under the umbrella of the Global Carbon Project to synthesize and stimulate research on the methane cycle, and producing regular (∼ biennial) updates of the global methane budget. This consortium includes atmospheric physicists and chemists, biogeochemists of surface and marine emissions, and socio-economists who study anthropogenic emissions. Following Kirschke et al. (2013), we propose here the first version of a living review paper that integrates results of top-down studies (exploiting atmospheric observations within an atmospheric inverse-modelling framework) and bottom-up models, inventories and data-driven approaches (including process-based models for estimating land surface emissions and atmospheric chemistry, and inventories for anthropogenic emissions, data-driven extrapolations). . Top-down inversions consistently infer lower emissions in China (∼ 58 Tg CH 4 yr −1 , range 51-72, −14 %) and higher emissions in Africa (86 Tg CH 4 yr −1 , range 73-108, +19 %) than bottom-up values used as prior estimates. Overall, uncertainties for anthropogenic emissions appear smaller than those from natural sources, and the uncertainties on source categories appear larger for top-down inversions than for bottom-up inventories and models.The most important source of uncertainty on the methane budget is attributable to emissions from wetland and other inland waters. We show that the wetland extent could contribute 30-40 % on the estimated range for wetland emissions. Other priorities for improving the methane budget include the following: (i) the development of process-based models for inland-water emissions, (ii) the intensification of methane observations at local scale (flux measurements) to constrain bottom-up land surface models, and at regional scale (surface networks and satellites) to constrain top-down inversions, (iii) improvements in the estimation of atmospheric loss by OH, and (iv) improvements of the transport models integrated in top-down inversions.

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Section: Introductionmentioning

confidence: 99%

The global methane budget 2000–2012

Saunois

Bousquet

Poulter

et al. 2016

Earth Syst. Sci. Data

934

733

View full text Add to dashboard Cite

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“…GOSAT-2, a successor of GOSAT featuring higher precision, is scheduled for launch in 2018. The MERLIN lidar instrument (Kiemle et al, 2011(Kiemle et al, , 2014 is scheduled for launch in 2020. Additional instruments are currently being planned or proposed.…”

Section: Introductionmentioning

confidence: 99%

Satellite observations of atmospheric methane and their value for quantifying methane emissions

et al. 2016

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Abstract. Methane is a greenhouse gas emitted by a range of natural and anthropogenic sources. Atmospheric methane has been measured continuously from space since 2003, and new instruments are planned for launch in the near future that will greatly expand the capabilities of space-based observations. We review the value of current, future, and proposed satellite observations to better quantify and understand methane emissions through inverse analyses, from the global scale down to the scale of point sources and in combination with suborbital (surface and aircraft) data. Current global observations from Greenhouse Gases Observing Satellite (GOSAT) are of high quality but have sparse spatial coverage. They can quantify methane emissions on a regional scale (100-1000 km) through multiyear averaging. The Tropospheric Monitoring Instrument (TROPOMI), to be launched in 2017, is expected to quantify daily emissions on the regional scale and will also effectively detect large point sources. A different observing strategy by GHGSat (launched in June 2016) is to target limited viewing domains with very fine pixel resolution in order to detect a wide range of methane point sources. Geostationary observation of methane, still in the proposal stage, will have the unique capability of mapping source regions with high resolution, detecting transient "super-emitter" point sources and resolving diurnal variation of emissions from sources such as wetlands and manure. Exploiting these rapidly expanding satellite measurement capabilities to quantify methane emissions requires a parallel effort to construct high-quality spatially and sectorally resolved emission inventories. Partnership between top-down inverse analyses of atmospheric data and bottom-up construction of emission inventories is crucial to better understanding methane emission processes and subsequently informing climate policy.

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“…Use of the standard atmosphere described in Section 2 simplifies the simulations, making the weighting function (Equation (3)) as well as its vertical integral (Equation (2)) a constant only dependent on the selected on-/offline pair from Table 1. Typical variations in aerosol load and climate conditions have minor influence on the IPDA Lidar performance [24], in the absence of clouds [33]. Our analysis does not include systematic errors (measurement biases), extensively discussed in [24] and found to be sufficiently smaller than the single-measurement noise errors presented here below.…”

Section: Instrument: Space Ipda Lidar Setup For Plume Measurementsmentioning

confidence: 92%

“…We limit our Lidar sizing analysis to pulsed, direct detection systems with two wavelengths (on-and offline), using knowledge gained during the planning and design phase of airborne [18] and spaceborne IPDA Lidars [20,24,25,27,33]. Alternative Lidar methodologies might likewise be applicable [19,22,34].…”

Section: Instrument: Space Ipda Lidar Setup For Plume Measurementsmentioning

confidence: 99%

“…This yields overlapping footprints separated by 14 m for a low-earth orbit with typical satellite velocity v SAT ≈ 7 km/s, as the separation between two footprints equals the ratio v SAT /PRF. We use a model developed and described in [25,33] to assess the performance of IPDA Lidar for a baseline set of instrument, platform and environmental parameters listed in Table 2 that influence the precision (random instrument noise; Equation (4)) of space-based Lidar measurements. Use of the standard atmosphere described in Section 2 simplifies the simulations, making the weighting function (Equation (3)) as well as its vertical integral (Equation (2)) a constant only dependent on the selected on-/offline pair from Table 1.…”

Section: Instrument: Space Ipda Lidar Setup For Plume Measurementsmentioning

confidence: 99%

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Potential of Spaceborne Lidar Measurements of Carbon Dioxide and Methane Emissions from Strong Point Sources

et al. 2017

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Abstract:Emissions from strong point sources, primarily large power plants, are a major portion of the total CO 2 emissions. International climate agreements will increasingly require their independent monitoring. A satellite-based, double-pulse, direct detection Integrated Path Differential Absorption (IPDA) Lidar with the capability to actively target point sources has the potential to usefully complement the current and future GHG observing system. This initial study uses simple approaches to determine the required Lidar characteristics and the expected skill of spaceborne Lidar plume detection and emission quantification. A Gaussian plume model simulates the CO 2 or CH 4 distribution downstream of the sources. A Lidar simulator provides the instrument characteristics and dimensions required to retrieve the emission rates, assuming an ideal detector configuration. The Lidar sampling frequency, the footprint distance to the emitting source and the error of an individual measurement are of great importance. If wind speed and direction are known and environmental conditions are ideal, an IPDA Lidar on a 500-km orbit with 2 W average power in the 1.6 µm CO 2 absorption band, 500 Hz pulse repetition frequency, 50 m footprint at sea level and 0.7 m telescope diameter can be expected to measure CO 2 emission rates of 20 Mt/a with an average accuracy better than 3% up to a distance of 3 km away from the source. CH 4 point source emission rates can be quantified with comparable skill if they are larger than 10 kt/a, or if the Lidar pulse repetition frequency is augmented.

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Performance simulations for a spaceborne methane lidar mission

Cited by 43 publications

References 33 publications

The global methane budget 2000–2012

The global methane budget 2000–2012

Satellite observations of atmospheric methane and their value for quantifying methane emissions

Potential of Spaceborne Lidar Measurements of Carbon Dioxide and Methane Emissions from Strong Point Sources

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