Effects of Chemical Feedbacks on Decadal Methane Emissions Estimates

Nguyen, Newton H.; Turner, Alexander J.; Yin, Yi; Prather, Michael J.; Frankenberg, Christian

doi:10.1029/2019gl085706

Cited by 27 publications

(18 citation statements)

References 54 publications

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“…increase in OH primary production is mainly due to an increase in tropospheric water vapor and O3 burden during El Niño events ( Fig.S3 and S12 in Nicely et al (2020)), while the increase in OH secondary production is caused by enhanced NOx emissions (Fig.S3) and O3 formation (Nicely et al (2020) related to biomass burning as well as more HO2 formation by CO+OH. As a result, the OH year-to-year variations found here are much smaller than those estimated by Nguyen et al (2020), who mainly considered the response of OH to CO. The positive anomaly OH primary production (0.2±0.5Tmol yr -1 ) is not significant during 1991-1992 El Niño event, maybe due to reduction of tropospheric water vapor ( Fig.S3 in Nicely et al (2020)) after the eruption of Mount Pinatubo (Soden et al, 2020).…”

Section: Factors Controlling Oh Trends and Year-to-year Variabilitycontrasting

confidence: 87%

“…The responses of OH to changes in biomass burning, ozone, water vapor, and lightning NOx emissions during El Niño years have been recognized by previous studies (Holmes et al, 2013;Murray et al, 2014;Turner et al, 2018;Rowlinson et al, 2019;Nguyen et al, 2020). Here, the consistent temporal variations of CCMI OH fields increase our confidence in the model simulated response of OH to ENSO as a result of several nonlinear chemical processes.…”

Section: Conclusion and Discussionsupporting

confidence: 74%

“…The El Niño-Southern Oscillation (ENSO) has proven to influence [OH] by perturbing CO emissions from biomass burning (Rowlinson et al 2019) and NOx emissions from lightning (Turner et al, 2018), but the detailed mechanisms behind present OH variations and their impact on the CH4 budget remain poorly understood. Nguyen et al (2020) estimated the impact of the chemical feedback induced by CO and CH4 changes on the top-down estimates of CH4 emissions using a box model approach. However, they account neither for the heterogeneous distribution of atmospheric reactive species in space nor for the chemical feedback related to OH production processes that vary over time.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

On the role of trend and variability of hydroxyl radical (OH) in the global methane budget

Zhao¹,

Saunois²,

Bousquet³

et al. 2020

Preprint

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Abstract. Decadal trends and interannual variations in the hydroxyl radical (OH), while poorly constrained at present, are critical for understanding the observed evolution of atmospheric methane (CH4). Through analyzing the OH fields simulated by the model ensemble of the Chemistry–Climate Model Initiative (CCMI), we find (1) the negative OH anomalies during the El Niño years mainly corresponding to the enhanced carbon monoxide (CO) emissions from biomass burning and (2) a positive OH trend during 1980–2010 dominated by the elevated primary production and the reduced loss of OH due to decreasing CO after 2000. Both two-box model inversions and variational 4D inversions suggest that ignoring the negative anomaly of OH during the El Niño years leads to a large overestimation of the increase in global CH4 emissions by up to 10 Tg yr−1 to match the observed CH4 increase over these years. Not accounting for the increasing OH trends given by the CCMI models leads to an underestimation of the CH4 emission increase by ~ 23 Tg yr−1 from 1986 to 2010. The variational inversion estimated CH4 emissions show that the tropical regions contribute most to the uncertainties related to OH. This study highlights the significant impact of climate and chemical feedbacks related to OH on the top-down estimates of the global CH4 budget.

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Section: Factors Controlling Oh Trends and Year-to-year Variabilitycontrasting

confidence: 87%

Section: Conclusion and Discussionsupporting

confidence: 74%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

On the role of trend and variability of hydroxyl radical (OH) in the global methane budget

Zhao¹,

Saunois²,

Bousquet³

et al. 2020

Preprint

View full text Add to dashboard Cite

show abstract

“…S1 in the Supplement). The CCMI models consistently simulated a positive OH trend during 2000-2010, mainly due to more OH production by NO than loss by CO over East and Southeast Asia and a positive trend of water vapor over the tropical regions (Zhao et al, 2019;Nicely et al, 2020). More details can be found in Zhao et al (2019) and the literature cited herein.…”

Section: Oh Fieldsmentioning

confidence: 62%

“…Based on satellite observations, Gauber et al (2017) estimated that ∼ 20 % decrease in atmospheric CO concentrations during 2002-2013 led to an ∼ 8 % increase in atmospheric [OH]. The El Niño-Southern Oscillation (ENSO) has been proven to impact the tropospheric OH burden and CH 4 lifetime mainly through changes in CO emissions from biomass burning (Nicely et al, 2020;Nguyen et al, 2020) and in NO emission from lightning (Murray et al, 2013;Turner et al, 2018). The ENSO signal is weak during the early 2000s, resulting in small interannual variations of tropospheric OH burden (Zhao et al, 2019).…”

Section: Conclusion and Discussionmentioning

confidence: 99%

Influences of hydroxyl radicals (OH) on top-down estimates of the global and regional methane budgets

et al. 2020

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Abstract. The hydroxyl radical (OH), which is the dominant sink of methane (CH4), plays a key role in closing the global methane budget. Current top-down estimates of the global and regional CH4 budget using 3D models usually apply prescribed OH fields and attribute model–observation mismatches almost exclusively to CH4 emissions, leaving the uncertainties due to prescribed OH fields less quantified. Here, using a variational Bayesian inversion framework and the 3D chemical transport model LMDz, combined with 10 different OH fields derived from chemistry–climate models (Chemistry–Climate Model Initiative, or CCMI, experiment), we evaluate the influence of OH burden, spatial distribution, and temporal variations on the global and regional CH4 budget. The global tropospheric mean CH4-reaction-weighted [OH] ([OH]GM-CH4) ranges 10.3–16.3×105 molec cm−3 across 10 OH fields during the early 2000s, resulting in inversion-based global CH4 emissions between 518 and 757 Tg yr−1. The uncertainties in CH4 inversions induced by the different OH fields are similar to the CH4 emission range estimated by previous bottom-up syntheses and larger than the range reported by the top-down studies. The uncertainties in emissions induced by OH are largest over South America, corresponding to large inter-model differences of [OH] in this region. From the early to the late 2000s, the optimized CH4 emissions increased by 22±6 Tg yr−1 (17–30 Tg yr−1), of which ∼25 % (on average) offsets the 0.7 % (on average) increase in OH burden. If the CCMI models represent the OH trend properly over the 2000s, our results show that a higher increasing trend of CH4 emissions is needed to match the CH4 observations compared to the CH4 emission trend derived using constant OH. This study strengthens the importance of reaching a better representation of OH burden and of OH spatial and temporal distributions to reduce the uncertainties in the global and regional CH4 budgets.

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Merging TROPOMI and eddy covariance observations to quantify 5-years of daily CH4 emissions over coal-mine dominated region

Hu,

Qin,

et al. 2024

Int J Coal Sci Technol

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A simple and flexible mass balance approach was applied to observations of XCH4 from TROPOMI to estimate CH4 emissions over Shanxi Province, including the impacts of advective transport, pressure transport, and atmospheric diffusion. High-frequency eddy-covariance flux observations were used to constrain the driving terms of the mass balance equation. This equation was then used to calculate day-to-day and 5 km × 5 km grided CH4 emissions from May 2018 to July 2022 based on TROPOMI RPRO column CH4 observations. The Shanxi-wide emissions of CH4, 126 ± 58.8 ug/m2/s, shows a fat tail distribution and high variability on a daily time scale (the 90th percentile is 2.14 times the mean and 2.74 times the median). As the number of days in the rolling average increases, the change in the variation decreases to 128 ± 35.7 ug/m2/s at 10-day, 128 ± 19.8 ug/m2/s at 30-day and 127 ± 13.9 ug/m2/s at 90-day. The range of values of the annual mean emissions on coal mine grids within Shanxi for the years 2018 to 2022 was 122 ± 58.2, 131 ± 71.2, 111 ± 63.6, 129 ± 87.1, and 138 ± 63.4 ug/m2/s, respectively. The 5-year average emissions from TROPOMI are 131 ± 68.0 ug/m2/s versus 125 ± 94.6 ug/m2/s on the grids where the EDGAR bottom-up database also has data, indicating that those pixels with mines dominate the overall emissions in terms of both magnitude and variability. The results show that high-frequency observation-based campaigns can produce a less biased result in terms of both the spatial and temporal distribution of CH4 emissions as compared with approaches using either low-frequency data or bottom-up databases, that coal mines dominate the sources of CH4 in Shanxi, and that the observed fat tail distribution can be accounted for using this approach.

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Effects of Chemical Feedbacks on Decadal Methane Emissions Estimates

Cited by 27 publications

References 54 publications

On the role of trend and variability of hydroxyl radical (OH) in the global methane budget

On the role of trend and variability of hydroxyl radical (OH) in the global methane budget

Influences of hydroxyl radicals (OH) on top-down estimates of the global and regional methane budgets

Merging TROPOMI and eddy covariance observations to quantify 5-years of daily CH4 emissions over coal-mine dominated region

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