scholarly journals Quantification of methane emissions from hotspots and during COVID-19 using a global atmospheric inversion

2022 ◽  
Author(s):  
Joe McNorton ◽  
Nicolas Bousserez ◽  
Anna Agustí-Panareda ◽  
Gianpaolo Balsamo ◽  
Richard Engelen ◽  
...  
Keyword(s):  
Atmospheric Chemistry ◽  
Energy Sector ◽  
Satellite Observations ◽  
Regional Studies ◽  
Atmospheric Methane ◽  
Global System ◽  
Ch4 Emissions ◽  
Forecasting System ◽  
Future Work ◽  
Uncertainty Information

Abstract. Concentrations of atmospheric methane (CH4), the second most important greenhouse gas, continue to grow. In recent years this growth rate has increased further (2020: +14.7 ppb), the cause of which remains largely unknown. Here, we demonstrate a high-resolution (~80 km), short-window (24-hour) 4D-Var global inversion system based on the ECMWF Integrated Forecasting System (IFS) and newly available satellite observations. The largest national disagreement found between prior (63.1 Tg yr−1) and posterior (59.8 Tg yr−1) CH4 emissions is from China, mainly attributed to the energy sector. Emissions estimated form our global system agree well with previous basin-wide regional studies and point source specific studies. Emission events (leaks/blowouts) >10 t hr−1 were detected, but without accurate prior uncertainty information, were not well quantified. Our results suggest that global anthropogenic CH4 emissions for 2020 were 5.7 Tg yr−1 (+1.6 %) higher than for 2019, mainly attributed to the energy and agricultural sectors. Regionally, the largest 2020 increases were seen from China (+2.6 Tg yr−1, 4.3 %), with smaller increases from India (+0.8 Tg yr−1, 2.2 %) and Indonesia (+0.3 Tg yr−1, 2.6 %). Results show the rise in emissions, and subsequent atmospheric growth, would have occurred with or without the COVID-19 slowdown. During the onset of the global slowdown (March–April, 2020) energy sector CH4 emissions from China increased; however, during later months (May–June, 2020) emissions decreased below expected pre-slowdown levels. The accumulated impact of the slowdown on CH4 emissions from March–June 2020 is found to be small. Changes in atmospheric chemistry, not investigated here, may have contributed to the observed growth in 2020. Future work aims to develop the global IFS inversion system and to extend the 4D-Var window-length using a hybrid ensemble-variational method.

scholarly journals Evaluation of anthropogenic CH<sub>4</sub> emissions over China using bottom-up inventories

2020 ◽  
Author(s):  
Xiaohui Lin ◽  
Wen Zhang ◽  
Monica Crippa ◽  
Shushi Peng ◽  
Pengfei Han ◽  
...  
Keyword(s):  
Waste Treatment ◽  
Comprehensive Evaluation ◽  
Energy Sector ◽  
Atmospheric Methane ◽  
Activity Data ◽  
Bottom Up ◽  
Average Growth ◽  
Ch4 Emissions ◽  
Source Contributions ◽  
Change Mitigation

Abstract. Atmospheric methane (CH4) is a potent greenhouse gas that is strongly influenced by several human activities. China, as one of the major agricultural and energy production countries, e.g., rice cultivation, ruminant feeding and coal production, contributes considerably to the global anthropogenic CH4 emissions. Understanding the characteristics of China's CH4 emissions is necessary for interpreting source contributions and for further climate change mitigation. However, the scarcity of data from some sources or years and spatially explicit information pose great challenges to completing an analysis of CH4 emissions. This study provides a comprehensive evaluation of China's anthropogenic CH4 emissions by synthesizing most of the currently available data (12 inventories). The results show that anthropogenic CH4 emissions differ widely among inventories, with values ranging from 41.9–57.5 Tg CH4 yr−1 in 2010. The discrepancy primarily resulted from the energy sector (27.3–60.0 % of total emissions), followed by the agricultural (26.9–50.8 %), and waste treatment (8.1–21.2 %) sectors. Temporally, emissions among inventories stabilized in the 1990s, but increased significantly thereafter, with annual average growth rates (AAGRs) of 1.8–3.9 % during 2000–2010, but slower AAGRs of 0.5–2.2 % during 2011–2015. Spatially, the growth of CH4 emissions could be attributed mostly to an increase in emissions from the energy sector (mainly from coal mining) in the northern and central inland regions, followed by waste treatment in the southern and eastern regions. The availability of detailed activity data for sectors or subsectors and the use of region-specific emission factors play important roles in understanding source contributions, and reducing the uncertainty of bottom-up inventories.

scholarly journals A comparative study of anthropogenic CH<sub>4</sub> emissions over China based on the ensembles of bottom-up inventories

2021 ◽  
Vol 13 (3) ◽  
pp. 1073-1088
Author(s):  
Xiaohui Lin ◽  
Wen Zhang ◽  
Monica Crippa ◽  
Shushi Peng ◽  
Pengfei Han ◽  
...  
Keyword(s):  
Waste Treatment ◽  
Energy Sector ◽  
Coal Production ◽  
Atmospheric Methane ◽  
Activity Data ◽  
Bottom Up ◽  
Average Growth ◽  
Ch4 Emissions ◽  
Source Contributions ◽  
Comprehensive Comparison

Abstract. Atmospheric methane (CH4) is a potent greenhouse gas that is strongly influenced by several human activities. China, as one of the major agricultural and energy production countries, contributes considerably to the global anthropogenic CH4 emissions by rice cultivation, ruminant feeding, and coal production. Understanding the characteristics of China's CH4 emissions is necessary for interpreting source contributions and for further climate change mitigation. However, the scarcity of data from some sources or years and spatially explicit information pose great challenges to completing an analysis of CH4 emissions. This study provides a comprehensive comparison of China's anthropogenic CH4 emissions by synthesizing the most current and publicly available datasets (13 inventories). The results show that anthropogenic CH4 emissions differ widely among inventories, with values ranging from 44.4–57.5 Tg CH4 yr−1 in 2010. The discrepancy primarily resulted from the energy sector (27.3 %–60.0 % of total emissions), followed by the agricultural (26.9 %–50.8 %) and waste treatment (8.1 %–21.2 %) sectors. Temporally, emissions among inventories stabilized in the 1990s but increased significantly thereafter, with annual average growth rates (AAGRs) of 2.6 %–4.0 % during 2000–2010 but slower AAGRs of 0.5 %–2.2 % during 2011–2015, and the emissions became relatively stable, with AAGRs of 0.3 %–0.8 %, during 2015–2019 because of the stable emissions from the energy sector (mainly coal production). Spatially, there are large differences in emissions hotspot identification among inventories, and incomplete information on emission patterns may mislead or bias mitigation efforts for CH4 emission reductions. The availability of detailed activity data for sectors or subsectors and the use of region-specific emission factors play important roles in understanding source contributions and reducing the uncertainty in bottom-up inventories. Data used in this article are available at https://doi.org/10.6084/m9.figshare.12720989 (Lin et al., 2021).

scholarly journals Accelerating methane growth rate from 2010 to 2017: leading contributions from the tropics and East Asia

2020 ◽  
Author(s):  
Yi Yin ◽  
Frederic Chevallier ◽  
Philippe Ciais ◽  
Philippe Bousquet ◽  
Marielle Saunois ◽  
...  
Keyword(s):  
Growth Rate ◽  
Carbon Monoxide ◽  
Satellite Observations ◽  
Anthropogenic Emissions ◽  
Atmospheric Methane ◽  
Sources And Sinks ◽  
Ch4 Emissions ◽  
Significant Acceleration ◽  
Oxidation Chain ◽  
The Tropics

Abstract. After stagnating in the early 2000s, the atmospheric methane growth rate has been positive since 2007 with a significant acceleration starting in 2014. While causes for previous growth rate variations are still not well determined, this recent increase can be studied with dense surface and satellite observations. Here, we use an ensemble of six multi-tracer atmospheric inversions that have the capacity to assimilate the major tracers in the methane oxidation chain – namely methane, formaldehyde, and carbon monoxide – to simultaneously optimize both the methane sources and sinks at each model grid. We show that the recent surge of the atmospheric growth rate between 2010–2013 and 2014–2017 is most likely explained by an increase of global CH4 emissions by 17.5 ± 1.5 Tg yr−1 (mean ± 1σ), while variations in CH4 sinks remained small. The inferred emission increase is consistently supported by both surface and satellite observations, with leading contributions from the tropics wetlands (~ 35 %) and anthropogenic emissions in China (~ 20 %). Such a high consecutive atmospheric growth rate has not been observed since the 1980s and corresponds to unprecedented global total CH4 emissions.

scholarly journals Accelerating methane growth rate from 2010 to 2017: leading contributions from the tropics and East Asia

2021 ◽  
Vol 21 (16) ◽  
pp. 12631-12647
Author(s):  
Yi Yin ◽  
Frederic Chevallier ◽  
Philippe Ciais ◽  
Philippe Bousquet ◽  
Marielle Saunois ◽  
...  
Keyword(s):  
Growth Rate ◽  
Satellite Observations ◽  
Anthropogenic Emissions ◽  
Atmospheric Methane ◽  
Tropical Wetlands ◽  
Sources And Sinks ◽  
Ch4 Emissions ◽  
Significant Acceleration ◽  
Oxidation Chain ◽  
The Tropics

Abstract. After stagnating in the early 2000s, the atmospheric methane growth rate has been positive since 2007 with a significant acceleration starting in 2014. While the causes for previous growth rate variations are still not well determined, this recent increase can be studied with dense surface and satellite observations. Here, we use an ensemble of six multi-species atmospheric inversions that have the capacity to assimilate observations of the main species in the methane oxidation chain – namely, methane, formaldehyde, and carbon monoxide – to simultaneously optimize both the methane sources and sinks at each model grid. We show that the surge of the atmospheric growth rate between 2010–2013 and 2014–2017 is most likely explained by an increase of global CH4 emissions by 17.5±1.5 Tg yr−1 (mean ± 1σ), while variations in the hydroxyl radicals (OH) remained small. The inferred emission increase is consistently supported by both surface and satellite observations, with leading contributions from the tropical wetlands (∼ 35 %) and anthropogenic emissions in China (∼ 20 %). Such a high consecutive atmospheric growth rate has not been observed since the 1980s and corresponds to unprecedented global total CH4 emissions.

scholarly journals Spatial scale-dependent land–atmospheric methane exchanges in the northern high latitudes from 1993 to 2004

2014 ◽  
Vol 11 (7) ◽  
pp. 1693-1704 ◽  
Author(s):  
X. Zhu ◽  
Q. Zhuang ◽  
X. Lu ◽  
L. Song
Keyword(s):  
Spatial Heterogeneity ◽  
Spatial Scale ◽  
Water Table ◽  
Spatial Scales ◽  
Grid Cell ◽  
High Latitudes ◽  
Atmospheric Methane ◽  
Ch4 Emissions ◽  
Biogeochemical Models ◽  
Macro Scale

Abstract. Effects of various spatial scales of water table dynamics on land–atmospheric methane (CH4) exchanges have not yet been assessed for large regions. Here we used a coupled hydrology–biogeochemistry model to quantify daily CH4 exchanges over the pan-Arctic from 1993 to 2004 at two spatial scales of 100 km and 5 km. The effects of sub-grid spatial variability of the water table depth (WTD) on CH4 emissions were examined with a TOPMODEL-based parameterization scheme for the northern high latitudes. We found that both WTD and CH4 emissions are better simulated at a 5 km spatial resolution. By considering the spatial heterogeneity of WTD, net regional CH4 emissions at a 5 km resolution are 38.1–55.4 Tg CH4 yr−1 from 1993 to 2004, which are on average 42% larger than those simulated at a 100 km resolution using a grid-cell-mean WTD scheme. The difference in annual CH4 emissions is attributed to the increased emitting area and enhanced flux density with finer resolution for WTD. Further, the inclusion of sub-grid WTD spatial heterogeneity also influences the inter-annual variability of CH4 emissions. Soil temperature plays an important role in the 100 km estimates, while the 5 km estimates are mainly influenced by WTD. This study suggests that previous macro-scale biogeochemical models using a grid-cell-mean WTD scheme might have underestimated the regional CH4 emissions. The spatial scale-dependent effects of WTD should be considered in future quantification of regional CH4 emissions.

scholarly journals Denitrification, dehydration and ozone loss during the Arctic winter 2015/2016

2017 ◽  
Author(s):  
Farahnaz Khosrawi ◽  
Oliver Kirner ◽  
Björn-Martin Sinnhuber ◽  
Sören Johansson ◽  
Michael Höpfner ◽  
...  
Keyword(s):  
Atmospheric Chemistry ◽  
Stratospheric Ozone ◽  
Satellite Observations ◽  
The Arctic ◽  
Cold Pool ◽  
Polar Stratospheric Clouds ◽  
Airborne Measurements ◽  
Ozone Loss ◽  
Polar Stratosphere ◽  
Stratospheric Clouds

Abstract. The Arctic winter 2015/2016 was one of the coldest stratospheric winters in recent years. A stable vortex formed by early December and the early winter was exceptionally cold. Cold pool temperatures dropped below the Nitric Acid Trihydrate (NAT) existence temperature of about 195 K, thus allowing Polar Stratospheric Clouds (PSCs) to form. The low temperatures in the polar stratosphere persisted until early March allowing chlorine activation and catalytic ozone destruction. Satellite observations indicate that sedimentation of PSC particles led to denitrification as well as dehydration of stratospheric layers. Model simulations of the Arctic winter 2015/2016 nudged toward European Center for Medium-Range Weather Forecasts (ECMWF) analyses data were performed with the atmospheric chemistry–climate model ECHAM5/MESSy Atmospheric Chemistry (EMAC) for the Polar Stratosphere in a Changing Climate (POLSTRACC) campaign. POLSTRACC is a High Altitude and LOng Range Research Aircraft (HALO) mission aimed at the investigation of the structure, composition and evolution of the Arctic Upper Troposphere and Lower Stratosphere (UTLS). The chemical and physical processes involved in Arctic stratospheric ozone depletion, transport and mixing processes in the UTLS at high latitudes, polar stratospheric clouds as well as cirrus clouds are investigated. In this study an overview of the chemistry and dynamics of the Arctic winter 2015/2016 as simulated with EMAC is given. Further, chemical-dynamical processes such as denitrification, dehydration and ozone loss during the Arctic winter 2015/2016 are investigated. Comparisons to satellite observations by the Aura Microwave Limb Sounder (Aura/MLS) as well as to airborne measurements with the Gimballed Limb Observer for Radiance Imaging of the Atmosphere (GLORIA) performed on board of HALO during the POLSTRACC campaign show that the EMAC simulations are in fairly good agreement with observations. We derive a maximum polar stratospheric O3 loss of ~ 2 ppmv or 100 DU in terms of column in mid March. The stratosphere was denitrified by about 8 ppbv HNO3 and dehydrated by about 1 ppmv H2O in mid to end of February. While ozone loss was quite strong, but not as strong as in 2010/2011, denitrification and dehydration were so far the strongest observed in the Arctic stratosphere in the at least past 10 years.

scholarly journals Global stratospheric measurements of the isotopologues of methane from the Atmospheric Chemistry Experiment Fourier Transform Spectrometer

2015 ◽  
Vol 8 (10) ◽  
pp. 11171-11207
Author(s):  
E. M. Buzan ◽  
C. A. Beale ◽  
C. D. Boone ◽  
P. F. Bernath
Keyword(s):  
Fourier Transform ◽  
Atmospheric Chemistry ◽  
Climate Model ◽  
Fourier Transform Spectrometer ◽  
Atmospheric Methane ◽  
Community Climate Model ◽  
Atmospheric Sinks ◽  
Chemistry Experiment ◽  
Methane Concentrations ◽  
Balloon Measurements

Abstract. This paper presents an analysis of observations of methane and its two major isotopologues, CH3D and 13CH4 from the Atmospheric Chemistry Experiment (ACE) satellite between 2004 and 2013. Additionally, atmospheric methane chemistry is modeled using the Whole Atmospheric Community Climate Model (WACCM). ACE retrievals of methane extend from 6 km for all isotopologues to 75 km for 12CH4, 35 km for CH3D, and 50 km for 13CH4. While total methane concentrations retrieved from ACE agree well with the model, values of δD–CH4 and δ13C–CH4 show a bias toward higher δ compared to the model and balloon-based measurements. Calibrating δD and δ13C from ACE using WACCM in the troposphere gives improved agreement in δD in the stratosphere with the balloon measurements, but values of δ13C still disagree. A model analysis of methane's atmospheric sinks is also performed.

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

2020 ◽  
Vol 20 (21) ◽  
pp. 13011-13022
Author(s):  
Yuanhong Zhao ◽  
Marielle Saunois ◽  
Philippe Bousquet ◽  
Xin Lin ◽  
Antoine Berchet ◽  
...  
Keyword(s):  
Hydroxyl Radical ◽  
El Niño ◽  
Climate Model ◽  
El Nino ◽  
Interannual Variations ◽  
Atmospheric Methane ◽  
Tropical Regions ◽  
Ch4 Emissions ◽  
Methane Budget

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 ± 3 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 ± 9 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.

scholarly journals CUACE/Dust – an integrated system of observation and modeling systems for operational dust forecasting in Asia

2007 ◽  
Vol 7 (4) ◽  
pp. 10323-10342 ◽  
Author(s):  
S. L. Gong ◽  
X. Y. Zhang
Keyword(s):  
East Asia ◽  
Atmospheric Chemistry ◽  
Monitoring Network ◽  
Integrated System ◽  
Dust Aerosol ◽  
China Meteorological Administration ◽  
Source Regions ◽  
Operational Forecasts ◽  
Forecasting System ◽  
Aerosol Module

Abstract. An integrated sand and dust storm (SDS) forecasting system – CUACE/Dust (the Chinese Unified Atmospheric Chemistry Environment for Dust) has been developed, which consists of a comprehensive dust aerosol module with emission, dry/wet depositions and other atmospheric dynamic processes, and a data assimilation system (DAS) using observational data from the CMA (China Meteorological Administration) ground dust monitoring network and retrieved dust information from a Chinese geostationary satellite – FY-2C. This is the first time that a combination of surface network observations and satellite retrievals of the dust aerosol has been successfully used in the real time operational forecasts in East Asia through a DAS. During its application for the operational SDS forecasts in East Asia for spring 2006, this system captured the major 31 SDS episodes observed by both surface and satellite observations. Analysis shows that the seasonal mean threat score (TS) for 0–24 h forecast over the East Asia in spring 2006 increased from 0.22 to 0.31 by using the DAS, a 41% enhancement. The time series of the forecasted dust concentrations for a number of representative stations for the whole spring 2006 were also evaluated against the surface PM10 monitoring data, showing a very good agreement in terms of the SDS timing and magnitudes near source regions where dust aerosols dominate. This is a summary paper for a special issue of ACP featuring the development and results of the forecasting system.

scholarly journals Data assimilation of dust aerosol observations for CUACE/Dust forecasting system

2007 ◽  
Vol 7 (3) ◽  
pp. 8309-8332 ◽  
Author(s):  
T. Niu ◽  
S. L. Gong ◽  
G. F. Zhu ◽  
H. L. Liu ◽  
X. Q. Hu ◽  
...  
Keyword(s):  
Data Assimilation ◽  
Atmospheric Chemistry ◽  
Three Dimensional ◽  
System A ◽  
Source Regions ◽  
Operational Forecasts ◽  
Forecasting System ◽  
Dust Loading ◽  
Data Assimilation System ◽  
Assimilation System

Abstract. A data assimilation system (DAS) was developed for the Chinese Unified Atmospheric Chemistry Environment – Dust (CUACE/Dust) forecast system and applied in the operational forecasts of sand and dust storm (SDS) in spring 2006. The system is based on a three dimensional variational method (3D-Var) and uses extensively the measurements of surface visibility and dust loading retrieval from the Chinese geostationary satellite FY-2C. The results show that a major improvement to the capability of CUACE/Dust in forecasting the short-term variability in the spatial distribution and intensity of dust concentrations has been achieved, especially in those areas far from the source regions. The seasonal mean Threat Score (TS) over the East Asia in spring 2006 increased from 0.22 to 0.31 by using the data assimilation system, a 41% enhancement. The assimilation results usually agree with the dust loading retrieved from FY-2C and visibility distribution from surface meteorological stations, which indicates that the 3D-Var method is very powerful for the unification of observation and numerical modeling results.

Sign in / Sign up

Export Citation Format

Share Document