A sensitivity study has been performed to estimate detection limits of various atmospheric trace gases achievable by a Mars‐orbiting solar occultation Fourier transform infrared (FTIR) spectrometer. ...This was accomplished by first computing realistic limb transmittance spectra based on a model (T, P, VMR, and dust profiles) of the Mars atmosphere and adding appropriate noise and systematic errors based on assumed instrument design/configuration/performance. We then performed spectral fits to the resulting synthetic spectra to derive slant column abundances and their uncertainties. A profile retrieval was performed to infer limits of detection. This methodology was applied to a Mars‐orbiting FTIR solar occultation spectrometer covering the 850–4,300 cm−1 spectral region at 0.025‐cm−1 resolution. We conclude that most gases can be retrieved with a single‐occultation sensitivity of 20–100 ppt. But this sensitivity varies considerably with the dust loading, especially for gases whose strongest absorption bands are toward higher wavenumbers where scattering is large. We conclude that for CH4, the ν4 band centered at 1,305 cm−1, despite being more than 2 times weaker than the ν3 band centered at 3,015 cm−1, offers better sensitivity due to its close spectral proximity to the dust extinction minimum. We also conclude that for the purpose of CH4 detection, a high‐resolution (0.025 cm−1) broadband instrument would have a substantial advantage over a medium‐resolution (0.15 cm−1) instrument, despite the latter having a much larger signal‐to‐noise ratio.
Plain Language Summary
We have estimated whether an infrared spectrometer might have enough sensitivity to measure minute amounts of gases (e.g., CH4, N2O, HCN, and OCS) in the Martian atmosphere that might arise due to life or volcanic activity. We conclude that by viewing the Sun at sunset and sunrise, many gases would be detectable at the 20–100 ppt level which would reduce current upper limits of several gases, some by factors of more than a hundred (e.g., N2O). But airborne dust is a major impediment to detecting gases in the lowest few kilometers of the atmosphere, close to their likely sources.
Key Points
The solar occultation technique provides high (ppt) sensitivity to many atmospheric trace gases, due to the long atmospheric paths and the brightness of the Sun
Dust extinction is a major obstacle in the lower Mars atmosphere to detecting trace gases without strong absorption bands at wavenumbers less than 2,400 cm−1 or for spectrometers without coverage at wavenumbers less than 2,400 cm−1
High spectral resolution (0.025 cm−1) offers significant advantages over medium‐resolution spectrometers (0.15 cm−1) for detecting trace gases (e.g., CH4) whose absorptions are overlapped by much stronger interfering absorptions (e.g., from CO2 or H2O)
Motivated by a satellite remote sensing mission, this article proposes a multivariable errors-in-variables (EIV) regression model with heteroscedastic errors for relating the satellite data products ...to similar products from a well-characterized but globally sparse ground-based dataset. In the remote sensing setting, the regression model is used to estimate the global divisor for the satellite data. The error structure of the proposed EIV model comprises two components: A random-error component whose variance is inversely proportional to sample size of underlying individual observations which are aggregated to obtain the regression data, and a systematic-error component whose variance remains the same as the underlying sample size increases. In this article, we discuss parameter identifiability for the proposed model and obtain estimates from two-stage parameter estimation. We illustrate our proposed procedure through both simulation studies and an application to validating measurements of atmospheric column-averaged CO
2
from NASA's Orbiting Carbon Observatory-2 (OCO-2) satellite. The validation uses coincident target-mode OCO-2 data that are temporally and spatially sparse and ground-based measurements from the Total Carbon Column Observing Network (TCCON) that are spatially sparse but more accurate. Supplementary materials for the article are available online.
Methane (CH4) is a potent greenhouse gas and ozone precursor. Quantifying methane emissions is critical for projecting and mitigating changes to climate and air quality. Here we present CH4 ...observations made from space combined with Earth‐based remote sensing column measurements. Results indicate the largest anomalous CH4 levels viewable from space over the conterminous U.S. are located at the Four Corners region in the Southwest U.S. Emissions exceeding inventory estimates, totaling 0.59 Tg CH4/yr 0.50–0.67; 2σ, are necessary to bring high‐resolution simulations and observations into agreement. This underestimated source approaches 10% of the EPA estimate of total U.S. CH4 emissions from natural gas. The persistence of this CH4 signal from 2003 onward indicates that the source is likely from established gas, coal, and coalbed methane mining and processing. This work demonstrates that space‐based observations can identify anomalous CH4 emission source regions and quantify their emissions with the use of a transport model.
Key Points
Four Corners exhibits largest CH4 anomaly seen from spaceEmissions of >0.5 Tg CH4/yr have persisted since 2003Space‐ and ground‐based CH4 identify missing emissions from fossil fuel extraction
Column-averaged concentrations of carbon dioxide (XCO2) and methane (XCH4) were retrieved from spectra observed by the Greenhouse gases Observing SATellite (GOSAT) using the so-called Photon path ...length Probability Density Function-Simultaneous (PPDF-S) retrieval method, which explains cloud/aerosol effects in terms of light path modification. The PPDF-S data, as well as the standard products for General Users (GU) of XCO2 and XCH4 retrieved using the full physics (FP) method, were validated through comparison with Total Carbon Column Observing Network (TCCON) data. Results show that bias and its standard deviation of XCO2 over the land are 0.73 and 1.83 ppm for the PPDF-S data, and −0.32 and 2.16 ppm for GU products. For XCH4, they are 1.4 and 14.1 ppb, and −1.9 and 12.5 ppb, respectively. Although the magnitude relations between XCO2 and XCH4 retrieved by the PPDF-S and GU products are identical over the land, they differ over the ocean. This fact emphasizes the importance of additional validation data over the ocean. Results also show that 68% of FP data that were screened out through an Aerosol Optical Thickness (AOT) test passed all screening tests for the PPDF-S method, implying the applicability of the PPDF-S method to denser aerosol conditions.
Satellite remote sensing platforms can collect measurements on a global scale within a few days, which provides an unprecedented opportunity to characterize and understand the spatio-temporal ...variability of environmental variables. Because of the additional challenges of making precise and accurate measurements from space, it is essential to validate satellite remote sensing datasets with highly precise and accurate ground-based measurements. The focus of this article is on two sets of measurements: Atmospheric column-averaged carbon dioxide (CO2) collected by the Orbiting Carbon Observatory-2 (OCO-2) mission in its target mode of operation; and ground-based data used for validation from the Total Carbon Column Observing Network (TCCON). The current statistical modeling of the relationship between the less-precise OCO-2 satellite data (Y) and the more-precise TCCON ground-based data (X) assumes a linear regression and heteroscedastic measurement errors that reside in both the OCO-2 data and the TCCON data. To obtain consistent estimates of the regression coefficients, it is critical to determine the error variance of each datum in the regression. In this article, a rigorous statistical procedure is presented for obtaining these error variances through modeling the spatial and/or temporal dependence structure in the OCO-2 and TCCON datasets. Numerical results for analyzing data at the Lamont TCCON station and the corresponding OCO-2 target-mode data (orbit number 3590) illustrate our procedure.
For methane emission reduction strategies in urban areas to be effective, large emitters must be identified. Recent studies in U.S. cities have highlighted the contribution of methane emissions from ...natural gas distribution networks and end use. We present a methane emission source identification and quantification method for the Greater Toronto Area (GTA), the largest metropolitan area in Canada, using mobile gas monitoring systems. From May 2018 to August 2019, we collected 77 surveys of methane mixing ratios, covering a distance of about 6400 km, and sampled emission plumes from sources such as closed landfills, natural gas compressor stations, and waterways. Our results indicate that inactive landfills emit less than inventory estimates. Despite this discrepancy, we confirm that the waste sector is the largest methane emitter in the GTA. We also report that the frequency of methane leaks from the local distribution system ranges between 4 and 22 leaks per 100 km of roadway in downtown Toronto, which is comparable to the range observed in U.S. cities, which have invested in modern natural gas distribution infrastructure. Last, we find that engineered waterways, whose emissions are currently not reported in inventories, may be a significant source of methane.
The Global Methane Budget 2000–2017 Saunois, Marielle; Stavert, Ann R.; Poulter, Ben ...
Earth system science data,
07/2020, Letnik:
12, Številka:
3
Journal Article
Recenzirano
Odprti dostop
Understanding and quantifying the global methane (CH4) budget is important for assessing realistic pathways to mitigate climate change. Atmospheric emissions and concentrations of CH4 continue to ...increase, making CH4 the second most important human-influenced greenhouse gas in terms of climate forcing, after carbon dioxide (CO2). The relative importance of CH4 compared to CO2 depends on its shorter atmospheric lifetime, stronger warming potential, and variations in atmospheric growth rate over the past decade, the causes of which are still debated. Two major challenges in reducing uncertainties in the atmospheric growth rate arise from the variety of geographically overlapping CH4 sources and from the destruction of CH4 by short-lived hydroxyl radicals (OH). To address these challenges, we have established a consortium of multidisciplinary scientists under the umbrella of the Global Carbon Project to synthesize and stimulate new research aimed at improving and regularly updating the global methane budget. Following Saunois et al. (2016), we present here the second version of the living review paper dedicated to the decadal methane budget, integrating results of top-down studies (atmospheric observations within an atmospheric inverse-modelling framework) and bottom-up estimates (including process-based models for estimating land surface emissions and atmospheric chemistry, inventories of anthropogenic emissions, and data-driven extrapolations).
For the 2008–2017 decade, global methane emissions are estimated by atmospheric inversions (a top-down approach) to be 576 Tg CH4/yr (range 550–594, corresponding to the minimum and maximum estimates of the model ensemble). Of this total, 359 Tg CH4/yr or ∼ 60 % is attributed to anthropogenic sources, that is emissions caused by direct human activity (i.e. anthropogenic emissions; range 336–376 Tg CH4/yr or 50 %–65 %). The mean annual total emission for the new decade (2008–2017) is 29 Tg CH4/yr larger than our estimate for the previous decade (2000–2009), and 24 Tg CH4/yr larger than the one reported in the previous budget for 2003–2012 (Saunois et al., 2016). Since 2012, global CH4 emissions have been tracking the warmest scenarios assessed by the Intergovernmental Panel on Climate Change. Bottom-up methods suggest almost 30 % larger global emissions (737 Tg CH4/yr, range 594–881) than top-down inversion methods. Indeed, bottom-up estimates for natural sources such as natural wetlands, other inland water systems, and geological sources are higher than top-down estimates. The atmospheric constraints on the top-down budget suggest that at least some of these bottom-up emissions are overestimated. The latitudinal distribution of atmospheric observation-based emissions indicates a predominance of tropical emissions (∼ 65 % of the global budget, < 30° N) compared to mid-latitudes (∼ 30 %, 30–60° N) and high northern latitudes (∼ 4 %, 60–90° N). The most important source of uncertainty in the methane budget is attributable to natural emissions, especially those from wetlands and other inland waters.
Some of our global source estimates are smaller than those in previously published budgets (Saunois et al., 2016; Kirschke et al., 2013). In particular wetland emissions are about 35 Tg CH4/yr lower due to improved partition wetlands and other inland waters. Emissions from geological sources and wild animals are also found to be smaller by 7 Tg CH4/yr by 8 Tg CH4/yr, respectively. However, the overall discrepancy between bottom-up and top-down estimates has been reduced by only 5 % compared to Saunois et al. (2016), due to a higher estimate of emissions from inland waters, highlighting the need for more detailed research on emissions factors. Priorities for improving the methane budget include (i) a global, high-resolution map of water-saturated soils and inundated areas emitting methane based on a robust classification of different types of emitting habitats; (ii) further development of process-based models for inland-water emissions; (iii) intensification of methane observations at local scales (e.g., FLUXNET-CH4 measurements) and urban-scale monitoring to constrain bottom-up land surface models, and at regional scales (surface networks and satellites) to constrain atmospheric inversions; (iv) improvements of transport models and the representation of photochemical sinks in top-down inversions; and (v) development of a 3D variational inversion system using isotopic and/or co-emitted species such as ethane to improve source partitioning.
We present the Facility Level and Area Methane (CH4) Emissions inventory for the Greater Toronto Area (FLAME-GTA). We estimate that total emissions of CH4 in the GTA, the most populous metropolitan ...area in Canada, are about 86 ± 38 Gg/yr. The FLAME-GTA estimate is within uncertainty of, but lower in magnitude than the existing gridded inventories provided by the Emissions Database for Global Atmospheric Research (EDGAR v 5.0), and by Environment and Climate Change Canada's Air Quality Research Division (ECCC - AQRD) that estimate emissions of 96 ± 48 Gg/yr and 143 ± 71 Gg/yr in the GTA region, respectively. Using a Lagrangian transport model, we predict atmospheric mixing ratios based on different emission inventories and compare the predictions with in situ measurements available from an observatory within the GTA for January–March in both 2015 and 2016. Due to the strong influence of local sources on our observations only a subregion of our GTA inventory is evaluated. These results identify the need for a more extensive measurement network and an improved atmospheric transport modeling effort for further evaluation of the emission inventories.
•We develop a methane emission inventory for the Greater Toronto Area (GTA) with a high spatial resolution.•We compare our emission inventory to two other existing emission inventories (EDGAR v.5 and ECCC-AQRD).•A transport model is used to predict methane mixing ratios at a measurement site in the GTA.
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We estimate the overall CO2, CH4, and CO flux from the South Coast Air Basin using an inversion that couples Total Carbon Column Observing Network (TCCON) and Orbiting Carbon Observatory-2 (OCO-2) ...observations, with the Hybrid Single Particle Lagrangian Integrated Trajectory (HYSPLIT) model and the Open-source Data Inventory for Anthropogenic CO2 (ODIAC). Using TCCON data we estimate the direct net CO2 flux from the So-CAB to be 104±26 Tg CO2 yr(exp -1) for the study period of July 2013–August 2016. We obtain a slightly higher estimate of 120±30 Tg CO2 yr(exp -1) using OCO-2 data. These CO2 emission estimates are on the low end of previous work. Our net CH4 (360±90 Gg CH4 y(exp -1)) flux estimate is in agreement with central values from previous top-down studies going back to 2010 (342–440 Gg CH4 yr(exp -1)). CO emissions are estimated at 487±122 Gg CO yr(exp -1), much lower than previous top-down estimates (1440 Gg CO yr(exp -1)). Given the decreasing emissions of CO, this finding is not unexpected. We perform sensitivity tests to estimate how much errors in the prior, errors in the covariance, different inversion schemes, or a coarser dynamical model influence the emission estimates. Overall, the uncertainty is estimated to be 25%, with the largest contribution from the dynamical model. Lessons learned here may help in future inversions of satellite data over urban areas.
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