scholarly journals Monitoring Global Tropospheric OH Concentrations using Satellite Observations of Atmospheric Methane

2018 ◽  
Author(s):  
Yuzhong Zhang ◽  
Daniel J. Jacob ◽  
Joannes D. Maasakkers ◽  
Melissa P. Sulprizio ◽  
Jian-Xiong Sheng ◽  
...  
Keyword(s):  
Methane Emissions ◽  
Satellite Observations ◽  
Atmospheric Methane ◽  
Replacement Method ◽  
Methyl Chloroform ◽  
Methane Budget ◽  
Interhemispheric Difference ◽  
Shortwave Infrared ◽  
Observing System Simulation Experiment ◽  
Better Than

Abstract. The hydroxyl radical (OH) is the main tropospheric oxidant and is the largest sink for atmospheric methane. The global abundance of OH has been monitored for the past decades with the methyl chloroform (CH3CCl3) proxy. This approach is becoming ineffective as atmospheric CH3CCl3 concentrations decline. Here we propose that satellite observations of atmospheric methane in the shortwave infrared (SWIR) and thermal infrared (TIR) can provide an effective replacement method. The premise is that the atmospheric signature of the methane sink from oxidation by OH is distinct from that of methane emissions. We evaluate this method in an observing system simulation experiment (OSSE) framework using synthetic SWIR and TIR satellite observations representative of the TROPOMI and CrIS instruments, respectively. The synthetic observations are interpreted with a Bayesian inverse analysis optimizing both gridded methane emissions and global OH concentrations with detailed error accounting, including errors in meteorological fields and in OH distributions. We find that the satellite observations can constrain the global tropospheric OH concentrations with a precision better than 1 % and an accuracy of about 3 % for SWIR and 7 % for TIR. The inversion can successfully separate contributions from methane emissions and OH concentrations to the methane budget and its trend. We also show that satellite methane observations can constrain the interhemispheric difference in OH. The main limitation to the accuracy is uncertainty in the spatial and seasonal distribution of OH.

scholarly journals Monitoring global tropospheric OH concentrations using satellite observations of atmospheric methane

2018 ◽  
Vol 18 (21) ◽  
pp. 15959-15973 ◽  
Author(s):  
Yuzhong Zhang ◽  
Daniel J. Jacob ◽  
Joannes D. Maasakkers ◽  
Melissa P. Sulprizio ◽  
Jian-Xiong Sheng ◽  
...  
Keyword(s):  
Simulation Experiment ◽  
Short Wave ◽  
Methane Emissions ◽  
Satellite Observations ◽  
Atmospheric Methane ◽  
The Past ◽  
Methyl Chloroform ◽  
Systematic Component ◽  
Observing System Simulation Experiment ◽  
Better Than

Abstract. The hydroxyl radical (OH) is the main tropospheric oxidant and the main sink for atmospheric methane. The global abundance of OH has been monitored for the past decades using atmospheric methyl chloroform (CH3CCl3) as a proxy. This method is becoming ineffective as atmospheric CH3CCl3 concentrations decline. Here we propose that satellite observations of atmospheric methane in the short-wave infrared (SWIR) and thermal infrared (TIR) can provide an alternative method for monitoring global OH concentrations. The premise is that the atmospheric signature of the methane sink from oxidation by OH is distinct from that of methane emissions. We evaluate this method in an observing system simulation experiment (OSSE) framework using synthetic SWIR and TIR satellite observations representative of the TROPOMI and CrIS instruments, respectively. The synthetic observations are interpreted with a Bayesian inverse analysis, optimizing both gridded methane emissions and global OH concentrations. The optimization is done analytically to provide complete error accounting, including error correlations between posterior emissions and OH concentrations. The potential bias caused by prior errors in the 3-D seasonal OH distribution is examined using OH fields from 12 different models in the ACCMIP archive. We find that the satellite observations of methane have the potential to constrain the global tropospheric OH concentration with a precision better than 1 % and an accuracy of about 3 % for SWIR and 7 % for TIR. The inversion can successfully separate the effects of perturbations to methane emissions and to OH concentrations. Interhemispheric differences in OH concentrations can also be successfully retrieved. Error estimates may be overoptimistic because we assume in this OSSE that errors are strictly random and have no systematic component. The availability of TROPOMI and CrIS data will soon provide an opportunity to test the method with actual observations.

scholarly journals A study of synthetic <sup>13</sup>CH<sub>4</sub> retrievals from TROPOMI and Sentinel 5/UVNS Part 1: non scattering atmosphere

2019 ◽  
Author(s):  
Edward Malina ◽  
Haili Hu ◽  
Jochen Landgraf ◽  
Ben Veihelmann
Keyword(s):  
A Priori ◽  
Atmospheric Methane ◽  
Clear Sky ◽  
Methane Budget ◽  
Highly Sensitive ◽  
Temporal Averaging ◽  
Temperature And Pressure ◽  
Shortwave Infrared ◽  
Better Than ◽  
Averaging Techniques

Abstract. Retrievals of methane isotopologues have the potential to differentiate between natural and anthropogenic methane sources types, which can provide much needed information about the current global methane budget. We investigate the feasibility of retrieving the second most abundant isotopologue of atmospheric methane (13CH4, roughly 1.1 % of total atmospheric methane) from the Shortwave Infrared (SWIR) channels of the future Sentinel 5/UVNS and current Copernicus Sentinel 5 Precursor TROPOMI instruments. With the intended goal of calculating the δ13C ratio, we assume that a δ13C uncertainty of better than 10 ‰ is sufficient to differentiate between source types, which corresponds to a 13CH4 uncertainty of <0.2 ppb. Using the well established Information Content analysis techniques and assuming clear sky, non-scattering conditions, we find that the SWIR3 (2305–2385 nm) channel on the TROPOMI instrument can achieve a mean uncertainty of <1 ppb, while the SWIR1 channel (1590–1675 nm) on the Sentinel 5 UVNS instrument can achieve <0.68 ppb. These uncertainties combined with modest spatial and/or temporal averaging techniques can reduce δ13C uncertainty to the target magnitude or better. However, we find that 13CH4 retrievals are highly sensitive to errors in a priori knowledge of temperature and pressure, and accurate knowledge of these profiles are required before 13CH4 retrievals can be performed on TROPOMI and future Sentinel 5/UVNS data.

scholarly journals Methane emissions by alpine plant communities in the Qinghai–Tibet Plateau

2008 ◽  
Vol 4 (6) ◽  
pp. 681-684 ◽  
Author(s):  
Guangmin Cao ◽  
Xingliang Xu ◽  
Ruijun Long ◽  
Qilan Wang ◽  
Changting Wang ◽  
...  
Keyword(s):  
Plant Communities ◽  
Methane Emissions ◽  
Tibet Plateau ◽  
The Tibetan Plateau ◽  
Atmospheric Methane ◽  
Closed Chamber ◽  
Methane Budget ◽  
Alpine Plant Communities ◽  
Regional Basis ◽  
Qinghai Tibet Plateau

For the first time to our knowledge, we report here methane emissions by plant communities in alpine ecosystems in the Qinghai–Tibet Plateau. This has been achieved through long-term field observations from June 2003 to July 2006 using a closed chamber technique. Strong methane emission at the rate of 26.2±1.2 and 7.8±1.1 μg CH 4 m −2  h −1 was observed for a grass community in a Kobresia humilis meadow and a Potentilla fruticosa meadow, respectively. A shrub community in the Potentilla meadow consumed atmospheric methane at the rate of 5.8±1.3 μg CH 4 m −2  h −1 on a regional basis; plants from alpine meadows contribute at least 0.13 Tg CH 4 yr −1 in the Tibetan Plateau. This finding has important implications with regard to the regional methane budget and species-level difference should be considered when assessing methane emissions by plants.

scholarly journals Investigation of the global methane budget over 1980–2017 using GFDL-AM4.1

2019 ◽  
Author(s):  
Jian He ◽  
Vaishali Naik ◽  
Larry W. Horowitz ◽  
Ed Dlugokencky ◽  
Kirk Thoning
Keyword(s):  
Atmospheric Chemistry ◽  
Latitudinal Gradient ◽  
Methane Emissions ◽  
Anthropogenic Emissions ◽  
Atmospheric Methane ◽  
Recent Past ◽  
Methane Budget ◽  
Global Trend ◽  
Emission Changes ◽  
Global Emissions

Abstract. Changes in atmospheric methane abundance have implications for both chemistry and climate as methane is both a strong greenhouse gas and an important precursor for tropospheric ozone. A better understanding of the drivers of trends and variability in methane abundance over the recent past is therefore critical for building confidence in projections of future methane levels. In this work, the representation of methane in the atmospheric chemistry model AM4.1 is improved by optimizing total methane emissions (to an annual mean of 576 ± 32 Tg yr−1) to match surface observations over 1980–2017. The simulations with optimized global emissions are in general able to capture the observed global trend, variability, seasonal cycle, and latitudinal gradient of methane. Simulations with different emission adjustments suggest that increases in methane sources (mainly from energy and waste sectors) balanced by increases in methane sinks (mainly due to increases in OH levels) lead to methane stabilization (with an imbalance of 5 Tg yr−1) during 1999–2006, and that increases in methane sources combined with little change in sinks (despite small decreases in OH levels) during 2007–2012 lead to renewed methane growth (with an imbalance of 14 Tg yr−1 for 2007–2017). Compared to 1999–2006, both methane emissions and sinks are greater (by 31 Tg yr−1 and 22 Tg yr−1, respectively) during 2007–2017. Our results also indicate that the energy sector is more likely a major contributor to the methane renewed growth after 2006 than wetland, as increases in wetland emissions alone are not able to explain the renewed methane growth with constant anthropogenic emissions. In addition, a significant increase in wetland emissions would be required starting in 2006, if anthropogenic emissions declined, for wetland emissions to drive renewed growth in methane, which is a less likely scenario. Simulations with varying OH levels indicate that 1 % change in OH levels could lead to an annual mean of ~ 4 Tg yr−1 difference in the optimized emissions and 0.08 year difference in the estimated tropospheric methane lifetime. Continued increases in methane emissions along with decreases in tropospheric OH concentrations during 2008–2015 prolong methane lifetime and therefore amplify the response of methane concentrations to emission changes. Uncertainties still exist in the partitioning of emissions among individual sources and regions.

A novel sampling system for radiocarbon measurements of atmospheric methane 

2021 ◽  
Author(s):  
Giulia Zazzeri ◽  
Xiaomei Xu ◽  
Heather Graven
Keyword(s):  
Molecular Sieves ◽  
Nuclear Power ◽  
Power Plants ◽  
Methane Emissions ◽  
Measurement Precision ◽  
Imperial College ◽  
Atmospheric Methane ◽  
Sampling System ◽  
Mass Spectrometry Facility ◽  
Better Than

&lt;p&gt;Radiocarbon in atmospheric methane (&amp;#916;&lt;sup&gt;14&lt;/sup&gt;CH&lt;sub&gt;4&lt;/sub&gt;) is a powerful tracer of fossil methane emissions and can be used to attribute methane emissions to fossil or biogenic sources. However, few &amp;#916;&lt;sup&gt;14&lt;/sup&gt;CH&lt;sub&gt;4 &lt;/sub&gt;measurements are reported since 2000&lt;sup&gt;1,2&lt;/sup&gt;, due to challenges in sampling enough carbon for &lt;sup&gt;14&lt;/sup&gt;C measurements and in assessing the influence of &lt;sup&gt;14&lt;/sup&gt;C emissions from nuclear power plants on the &lt;sup&gt;14&lt;/sup&gt;C observations.&lt;/p&gt;&lt;p&gt;At Imperial College London we addressed the sampling limitation by developing a unique sampling system that separates carbon at the point of sampling and uses small traps of molecular sieves. Collection of a sample is made by three main steps: 1) removal of CO&lt;sub&gt;2&lt;/sub&gt; and CO from air, 2) combustion of CH&lt;sub&gt;4&lt;/sub&gt; into CO&lt;sub&gt;2&lt;/sub&gt; and 3) adsorption of the combustion-derived CO&lt;sub&gt;2&lt;/sub&gt; onto the molecular sieve trap. &lt;sup&gt;14&lt;/sup&gt;C analysis of our samples was carried out at the accelerator mass spectrometry facility at UCI. This novel system has been used for collection of samples in central London and has been made portable for collection of samples in different settings.&amp;#160;&lt;/p&gt;&lt;p&gt;Here we describe the system and report the evaluation of the measurement uncertainty and the processing blank. We achieved a measurement precision of 6 &amp;#8240;, which is similar to or better than the reported precision of the most recent observations&lt;sup&gt;1,3&lt;/sup&gt;.&lt;/p&gt;&lt;p&gt;&lt;sup&gt;1&lt;/sup&gt; Townsend&amp;#8208;Small et al JGR 117(D7) 2012&lt;/p&gt;&lt;p&gt;&lt;sup&gt;2&lt;/sup&gt; Sparrow et al Sci. Adv 4(1) 2018&lt;/p&gt;&lt;p&gt;&lt;sup&gt;3&lt;/sup&gt; Espic et al Radiocarbon 61( 5) 2019&lt;/p&gt;

scholarly journals Four-dimensional variational data assimilation for inverse modelling of atmospheric methane emissions: method and comparison with synthesis inversion

2008 ◽  
Vol 8 (21) ◽  
pp. 6341-6353 ◽  
Author(s):  
J. F. Meirink ◽  
P. Bergamaschi ◽  
M. C. Krol
Keyword(s):  
Data Assimilation ◽  
Transport Model ◽  
Time Window ◽  
Methane Emissions ◽  
Satellite Observations ◽  
Inverse Modelling ◽  
Model Parameters ◽  
Full Potential ◽  
Atmospheric Methane ◽  
Assimilation System

Abstract. A four-dimensional variational (4D-Var) data assimilation system for inverse modelling of atmospheric methane emissions is presented. The system is based on the TM5 atmospheric transport model. It can be used for assimilating large volumes of measurements, in particular satellite observations and quasi-continuous in-situ observations, and at the same time it enables the optimization of a large number of model parameters, specifically grid-scale emission rates. Furthermore, the variational method allows to estimate uncertainties in posterior emissions. Here, the system is applied to optimize monthly methane emissions over a 1-year time window on the basis of surface observations from the NOAA-ESRL network. The results are rigorously compared with an analogous inversion by Bergamaschi et al. (2007), which was based on the traditional synthesis approach. The posterior emissions as well as their uncertainties obtained in both inversions show a high degree of consistency. At the same time we illustrate the advantage of 4D-Var in reducing aggregation errors by optimizing emissions at the grid scale of the transport model. The full potential of the assimilation system is exploited in Meirink et al. (2008), who use satellite observations of column-averaged methane mixing ratios to optimize emissions at high spatial resolution, taking advantage of the zooming capability of the TM5 model.

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

2016 ◽  
Vol 16 (22) ◽  
pp. 14371-14396 ◽  
Author(s):  
Daniel J. Jacob ◽  
Alexander J. Turner ◽  
Joannes D. Maasakkers ◽  
Jianxiong Sheng ◽  
Kang Sun ◽  
...  
Keyword(s):  
Regional Scale ◽  
Methane Emissions ◽  
Point Sources ◽  
Satellite Observations ◽  
Anthropogenic Sources ◽  
Emission Inventories ◽  
Atmospheric Methane ◽  
High Quality ◽  
Spatial Coverage ◽  
Wide Range

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.

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

2016 ◽  
Author(s):  
Daniel J. Jacob ◽  
Alexander J. Turner ◽  
Joannes D. Maasakkers ◽  
Jianxiong Sheng ◽  
Kang Sun ◽  
...  
Keyword(s):  
Methane Emissions ◽  
Point Sources ◽  
Satellite Observations ◽  
Anthropogenic Sources ◽  
Satellite Measurement ◽  
Emission Inventories ◽  
Atmospheric Methane ◽  
High Quality ◽  
Spatial Coverage ◽  
Wide Range

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, down to the scale of point sources and in combination with suborbital (surface and aircraft) data. Current observations from GOSAT are of high quality but have sparse spatial coverage. They provide limited information to quantify methane emissions on a regional (100–1000 km) scale. TROPOMI to be launched in late 2016 is expected to quantify daily emissions on the regional scale and will also effectively detect large point sources. Future satellite instruments with much higher spatial resolution, such as the recently launched GHGSat with 50 × 50 m2 resolution over targeted viewing domains, have the potential to detect a wide range of methane point sources. Geostationary observation of methane, still in the proposal stage, will have unique capability for mapping source regions with high resolution while also detecting transient "super-emitter" point sources. Exploiting the 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 understand methane emission processes and from there to inform climate policy.

scholarly journals Investigation of the global methane budget over 1980–2017 using GFDL-AM4.1

2020 ◽  
Vol 20 (2) ◽  
pp. 805-827 ◽  
Author(s):  
Jian He ◽  
Vaishali Naik ◽  
Larry W. Horowitz ◽  
Ed Dlugokencky ◽  
Kirk Thoning
Keyword(s):  
Atmospheric Chemistry ◽  
Latitudinal Gradient ◽  
Sharp Decrease ◽  
Methane Emissions ◽  
Anthropogenic Sources ◽  
Anthropogenic Emissions ◽  
Atmospheric Methane ◽  
Methane Budget ◽  
Emission Changes ◽  
Global Emissions

Abstract. Changes in atmospheric methane abundance have implications for both chemistry and climate as methane is both a strong greenhouse gas and an important precursor for tropospheric ozone. A better understanding of the drivers of trends and variability in methane abundance over the recent past is therefore critical for building confidence in projections of future methane levels. In this work, the representation of methane in the atmospheric chemistry model AM4.1 is improved by optimizing total methane emissions (to an annual mean of 580±34 Tg yr−1) to match surface observations over 1980–2017. The simulations with optimized global emissions are in general able to capture the observed trend, variability, seasonal cycle, and latitudinal gradient of methane. Simulations with different emission adjustments suggest that increases in methane emissions (mainly from agriculture, energy, and waste sectors) balanced by increases in methane sinks (mainly due to increases in OH levels) lead to methane stabilization (with an imbalance of 5 Tg yr−1) during 1999–2006 and that increases in methane emissions (mainly from agriculture, energy, and waste sectors) combined with little change in sinks (despite small decreases in OH levels) during 2007–2012 lead to renewed growth in methane (with an imbalance of 14 Tg yr−1 for 2007–2017). Compared to 1999–2006, both methane emissions and sinks are greater (by 31 and 22 Tg yr−1, respectively) during 2007–2017. Our tagged tracer analysis indicates that anthropogenic sources (such as agriculture, energy, and waste sectors) are more likely major contributors to the renewed growth in methane after 2006. A sharp increase in wetland emissions (a likely scenario) with a concomitant sharp decrease in anthropogenic emissions (a less likely scenario), would be required starting in 2006 to drive the methane growth by wetland tracer. Simulations with varying OH levels indicate that a 1 % change in OH levels could lead to an annual mean difference of ∼4 Tg yr−1 in the optimized emissions and a 0.08-year difference in the estimated tropospheric methane lifetime. Continued increases in methane emissions along with decreases in tropospheric OH concentrations during 2008–2015 prolong methane's lifetime and therefore amplify the response of methane concentrations to emission changes. Uncertainties still exist in the partitioning of emissions among individual sources and regions.

scholarly journals Technical Note: Four-dimensional variational data assimilation for inverse modelling of atmospheric methane emissions: method and comparison with synthesis inversion

2008 ◽  
Vol 8 (3) ◽  
pp. 12023-12052 ◽  
Author(s):  
J. F. Meirink ◽  
P. Bergamaschi ◽  
M. C. Krol
Keyword(s):  
Data Assimilation ◽  
Transport Model ◽  
Time Window ◽  
Methane Emissions ◽  
Satellite Observations ◽  
Inverse Modelling ◽  
Model Parameters ◽  
Full Potential ◽  
Atmospheric Methane ◽  
Assimilation System

Abstract. A four-dimensional variational (4D-var) data assimilation system for inverse modelling of atmospheric methane emissions is presented. The system is based on the TM5 atmospheric transport model. It can be used for assimilating large volumes of measurements, in particular satellite observations and quasi-continuous in-situ observations, and at the same time it enables the optimization of a large number of model parameters, specifically grid-scale emission rates. Furthermore, the variational method allows to estimate uncertainties in posterior emissions. Here, the system is applied to optimize monthly methane emissions over a 1-year time window on the basis of surface observations from the NOAA-ESRL network. The results are rigorously compared with an analogous inversion by Bergamaschi et al. (2007), which was based on the traditional synthesis approach. The posterior emissions as well as their uncertainties obtained in both inversions show a high degree of consistency. At the same time we illustrate the advantage of 4D-Var in reducing aggregation errors by optimizing emissions at the grid scale of the transport model. The full potential of the assimilation system is exploited in Meirink et al. (2008), who use satellite observations of column-averaged methane mixing ratios to optimize emissions at high spatial resolution, taking advantage of the zooming capability of the TM5 model.

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