Revisiting China’s methane emissions from coal sector

2021 ◽  
Author(s):  
Duo Cui
Keyword(s):  
Global Climate ◽  
Grid Cell ◽  
High Growth ◽  
Methane Emissions ◽  
High Growth Rate ◽  
Abandoned Mines ◽  
Top Down ◽  
Bottom Up ◽  
China Rose ◽  
Gosat Satellite

<p>Methane emissions associated with human activities contributes significantly to global climate change. China is the world largest methane emitter and the coal mining sector is the largest contributor. Recent atmospheric inversion by Miller et al. using spaceborne column CH<sub>4</sub> concentration measurements inferred that emissions in China rose by more than 1.0 Tg CH<sub>4</sub> yr<sup>−1</sup> from 2010 to 2017 due to the contribution of fossil fuel, especially from coal sector. Here we revisit methane emissions from the coal sector in China by comparing a sectorial bottom up emission inventory (2005-2019) with the results from another ensemble of CH<sub>4</sub> inversions using GOSAT satellite data during 2011-2017. During that period, the bottom up inventory gives an average emission of 17.9 Tg CH4 yr-1 and the median of all inversions of 18.6 Tg CH4 yr-1, with a range of [10.8, 25.6] corresponding to the min-max of all inversions and the use of two gridded maps of emissions to separate the coal sector from total emissions in each inversion grid cell. We confirm the upward trend in methane emissions from the coal sector from 2005 to 2019 observed by Miller et al. In addition, we show that trend accelerated after 2016 as consistently found in the bottom-up inventory and top-down inversions approaches. However, during the period of 2010-2017, the bottom-up inventory and top-down inversions showed opposite trends in emissions. Especially during the period of 2014-2016, emissions from coal sector decreased at a rate of 0.8 Tg CH4 yr-1 using bottom up inventory, while emissions from top-down inversions maintained a relatively high growth rate at 0.4 Tg CH4 yr-1. Suggesting possible underestimation of the emission by bottom up inventories. In addition, we estimates the contribution of abandoned mines to the growth of methane emissions from coal sector was around 20%, we also show a COVID-19 pandemic related sharp dip in methane emission from the coal sector in Feb 2020 and rebound since in April 2020 based on the estimation of monthly bottom-up inventory.</p>

scholarly journals Climate Dialog, Climate Action: Can Democracy Do the Job?

2021 ◽  
Author(s):  
Fred Young Phillips ◽  
LaVonne Reimer ◽  
Rebecca Turner
Keyword(s):  
Large Scale ◽  
Global Climate ◽  
Environmental Issues ◽  
Top Down ◽  
Bottom Up ◽  
Psychological Mechanisms ◽  
Ipcc Report ◽  
Climate Action

The latest IPCC report forcefully states that immediate, decisive, and large-scale actions are needed to avert climate catastrophe. This essay presumes that democratic governments are best and most desirably positioned to take these actions. Yet in the countries most pivotal to global climate, significant voting blocs are uninterested in environmental issues. The essay urges adding bottom-up dialog between environmental and anti-environmental voters, to current and future top-down technocratic “solutions.” To make this combination result in a unified pro-environment electorate, we must understand: religious objections to environmentalism; the capital-vs.-knowledge strife that slows polluting corporations’ green transitions; and the psychological mechanisms that can make inter-group dialog fruitful.

scholarly journals Variability and quasi-decadal changes in the methane budget over the period 2000–2012

2017 ◽  
Author(s):  
Marielle Saunois ◽  
Philippe Bousquet ◽  
Benjamin Poulter ◽  
Anna Peregon ◽  
Philippe Ciais ◽  
...  
Keyword(s):  
Biomass Burning ◽  
Methane Emissions ◽  
Data Driven ◽  
Atmospheric Methane ◽  
Top Down ◽  
Bottom Up ◽  
Ch4 Emissions ◽  
Ensemble Mean ◽  
The Mean ◽  
The Tropics

Abstract. Following the recent Global Carbon project (GCP) synthesis of the decadal methane (CH4) budget over 2000–2012 (Saunois et al., 2016), we analyse here the same dataset with a focus on quasi-decadal and inter-annual variability in CH4 emissions. The GCP dataset integrates results from top-down studies (exploiting atmospheric observations within an atmospheric inverse-modelling frameworks) and bottom-up models, inventories, and data-driven approaches (including process-based models for estimating land surface emissions and atmospheric chemistry, inventories of anthropogenic emissions, and data-driven extrapolations). The annual global methane emissions from top-down studies, which by construction match the observed methane growth rate within their uncertainties, all show an increase in total methane emissions over the period 2000–2012, but this increase is not linear over the 13 years. Despite differences between individual studies, the mean emission anomaly of the top-down ensemble shows no significant trend in total methane emissions over the period 2000–2006, during the plateau of atmospheric methane mole fractions, and also over the period 2008–2012, during the renewed atmospheric methane increase. However, the top-down ensemble mean produces an emission shift between 2006 and 2008, leading to 22 [16–32] Tg CH4 yr−1 higher methane emissions over the period 2008–2012 compared to 2002–2006. This emission increase mostly originated from the tropics with a smaller contribution from mid-latitudes and no significant change from boreal regions. The regional contributions remain uncertain in top-down studies. Tropical South America and South and East Asia seems to contribute the most to the emission increase in the tropics. However, these two regions have only limited atmospheric measurements and remain therefore poorly constrained. The sectorial partitioning of this emission increase between the periods 2002–2006 and 2008–2012 differs from one atmospheric inversion study to another. However, all top-down studies suggest smaller changes in fossil fuel emissions (from oil, gas, and coal industries) compared to the mean of the bottom-up inventories included in this study. This difference is partly driven by a smaller emission change in China from the top-down studies compared to the estimate in the EDGARv4.2 inventory, which should be revised to smaller values in a near future. Though the sectorial partitioning of six individual top-down studies out of eight are not consistent with the observed change in atmospheric 13CH4, the partitioning derived from the ensemble mean is consistent with this isotopic constraint. At the global scale, the top-down ensemble mean suggests that, the dominant contribution to the resumed atmospheric CH4 growth after 2006 comes from microbial sources (more from agriculture and waste sectors than from natural wetlands), with an uncertain but smaller contribution from fossil CH4 emissions. Besides, a decrease in biomass burning emissions (in agreement with the biomass burning emission databases) makes the balance of sources consistent with atmospheric 13CH4 observations. The methane loss (in particular through OH oxidation) has not been investigated in detail in this study, although it may play a significant role in the recent atmospheric methane changes.

scholarly journals Assessment of the Effectiveness of Global Climate Policies Using Coupled Bottom-Up and Top-Down Models

2015 ◽  
Author(s):  
Maryse Labriet ◽  
Laurent Drouet ◽  
Marc Vielle ◽  
Richard Loulou ◽  
Amit Kanudia ◽  
...  
Keyword(s):  
Global Climate ◽  
Top Down ◽  
Bottom Up ◽  
Climate Policies

scholarly journals Trends and inter-annual variability of methane emissions derived from 1979-1993 global CTM simulations

2003 ◽  
Vol 3 (1) ◽  
pp. 73-88 ◽  
Author(s):  
F. Dentener ◽  
M. van Weele ◽  
M. Krol ◽  
S. Houweling ◽  
P. van Velthoven
Keyword(s):  
Transport Model ◽  
Meteorological Data ◽  
Stratospheric Ozone ◽  
Methane Emissions ◽  
Anthropogenic Emission ◽  
Top Down ◽  
Bottom Up ◽  
Annual Variability ◽  
The Difference ◽  
Ozone Precursor

Abstract. The trend and interannual variability of methane sources are derived from multi-annual simulations of tropospheric photochemistry using a 3-D global chemistry-transport model. Our semi-inverse analysis uses the fifteen years (1979--1993) re-analysis of ECMWF meteorological data and annually varying emissions including photo-chemistry, in conjunction with observed CH4 concentration distributions and trends derived from the NOAA-CMDL surface stations. Dividing the world in four zonal regions (45--90 N, 0--45 N, 0--45 S, 45--90 S) we find good agreement in each region between (top-down) calculated emission trends from model simulations and (bottom-up) estimated anthropogenic emission trends based on the EDGAR global anthropogenic emission database, which amounts for the period 1979--1993 2.7 Tg CH4 yr-1. Also the top-down determined total global methane emission compares well with the total of the bottom-up estimates. We use the difference between the bottom-up and top-down determined emission trends to calculate residual emissions. These residual emissions represent the inter-annual variability of the methane emissions. Simulations have been performed in which the year-to-year meteorology, the emissions of ozone precursor gases, and the stratospheric ozone column distribution are either varied, or kept constant. In studies of methane trends it is most important to include the trends and variability of the oxidant fields. The analyses reveals that the variability of the emissions is of the order of 8Tg CH4 yr-1, and likely related to wetland emissions and/or biomass burning.

Seasonal and Long-Term Changes to Pavement Life Caused by Rising Temperatures from Climate Change

2019 ◽  
Vol 2673 (6) ◽  
pp. 267-278 ◽  
Author(s):  
Jayne F. Knott ◽  
Jo E. Sias ◽  
Eshan V. Dave ◽  
Jennifer M. Jacobs
Keyword(s):  
Climate Change ◽  
Temperature Rise ◽  
Climate Models ◽  
Global Climate ◽  
Global Climate Models ◽  
Climate Change Scenarios ◽  
Top Down ◽  
Bottom Up ◽  
Pavement Damage ◽  
The Impact

Pavements are vulnerable to reduced life with climate-change-induced temperature rise. Greenhouse gas emissions have caused an increase in global temperatures since the mid-20th century and the warming is projected to accelerate. Many studies have characterized this risk with a top-down approach in which climate-change scenarios are chosen and applied to predict pavement-life reduction. This approach is useful in identifying possible pavement futures but may miss short-term or seasonal pavement-response trends that are essential for adaptation planning. A bottom-up approach focuses on a pavement’s response to incremental temperature change resulting in a more complete understanding of temperature-induced pavement damage. In this study, a hybrid bottom-up/top-down approach was used to quantify the impact of changing pavement seasons and temperatures on pavement life with incremental temperature rise from 0 to 5°C at a site in coastal New Hampshire. Changes in season length, seasonal average temperatures, and temperature-dependent resilient modulus were used in layered-elastic analysis to simulate the pavement’s response to temperature rise. Projected temperature rise from downscaled global climate models was then superimposed on the results to determine the timing of the effects. The winter pavement season is projected to end by mid-century, replaced by a lengthening fall season. Seasonal pavement damage, currently dominated by the late spring and summer seasons, is projected to be distributed more evenly throughout the year as temperatures rise. A 7% to 32% increase in the asphalt-layer thickness is recommended to protect the base and subgrade with rising temperatures from early century to late-mid-century.

scholarly journals The challenge of reconciling bottom-up agricultural methane emissions inventories with top-down measurements

2018 ◽  
Vol 248 ◽  
pp. 48-59 ◽  
Author(s):  
R.L. Desjardins ◽  
D.E. Worth ◽  
E. Pattey ◽  
A. VanderZaag ◽  
R. Srinivasan ◽  
...  
Keyword(s):  
Methane Emissions ◽  
Top Down ◽  
Bottom Up ◽  
Emissions Inventories

scholarly journals Stable atmospheric methane in the 2000s: key-role of emissions from natural wetlands

2013 ◽  
Vol 13 (23) ◽  
pp. 11609-11623 ◽  
Author(s):  
I. Pison ◽  
B. Ringeval ◽  
P. Bousquet ◽  
C. Prigent ◽  
F. Papa
Keyword(s):  
South America ◽  
Process Model ◽  
Methane Emissions ◽  
Time Variability ◽  
Positive Trend ◽  
Tropical Wetlands ◽  
Top Down ◽  
Bottom Up ◽  
Natural Wetlands

Abstract. Two atmospheric inversions (one fine-resolved and one process-discriminating) and a process-based model for land surface exchanges are brought together to analyse the variations of methane emissions from 1990 to 2009. A focus is put on the role of natural wetlands and on the years 2000–2006, a period of stable atmospheric concentrations. From 1990 to 2000, the top-down and bottom-up visions agree on the time-phasing of global total and wetland emission anomalies. The process-discriminating inversion indicates that wetlands dominate the time-variability of methane emissions (90% of the total variability). The contribution of tropical wetlands to the anomalies is found to be large, especially during the post-Pinatubo years (global negative anomalies with minima between −41 and −19 Tg yr−1 in 1992) and during the alternate 1997–1998 El-Niño/1998–1999 La-Niña (maximal anomalies in tropical regions between +16 and +22 Tg yr−1 for the inversions and anomalies due to tropical wetlands between +12 and +17 Tg yr−1 for the process-based model). Between 2000 and 2006, during the stagnation of methane concentrations in the atmosphere, the top-down and bottom-up approaches agree on the fact that South America is the main region contributing to anomalies in natural wetland emissions, but they disagree on the sign and magnitude of the flux trend in the Amazon basin. A negative trend (−3.9 ± 1.3 Tg yr−1) is inferred by the process-discriminating inversion whereas a positive trend (+1.3 ± 0.3 Tg yr−1) is found by the process model. Although processed-based models have their own caveats and may not take into account all processes, the positive trend found by the B-U approach is considered more likely because it is a robust feature of the process-based model, consistent with analysed precipitations and the satellite-derived extent of inundated areas. On the contrary, the surface-data based inversions lack constraints for South America. This result suggests the need for a re-interpretation of the large increase found in anthropogenic methane inventories after 2000.

scholarly journals Trends and inter-annual variability of methane emissions derived from 1979-1993 global CTM simulations

2002 ◽  
Vol 2 (2) ◽  
pp. 249-287 ◽  
Author(s):  
F. Dentener ◽  
M. van Weele ◽  
M. Krol ◽  
S. Houweling ◽  
P. van Velthoven
Keyword(s):  
Transport Model ◽  
Meteorological Data ◽  
Stratospheric Ozone ◽  
Regional Scale ◽  
Methane Emissions ◽  
Anthropogenic Emission ◽  
Top Down ◽  
Bottom Up ◽  
Annual Variability ◽  
The Difference

Abstract. The trend and interannual variability of methane sources are derived from multi-annual simulations of tropospheric photochemistry using a 3D global chemistry-transport model. Our semi-inverse analysis uses the fifteen years (1979 -1993) re-analysis of ECMWF meteorological data and annually varying including photo-chemistry, in conjunction with observed CH4 concentration distributions and trends derived from the NOAA-CMDL surface stations. Dividing the world in four zonal regions, (45-90 N, 0-45 N, 0-45 S; 45-90 S) we find good agreement in each region between (top-down) calculated emission trends from model simulations and (bottom-up) estimated anthropogenic emission trends based on the EDGAR global anthropogenic emission database, which amounts for the period 1979 -1993 2.7 Tg CH4 yr -1. Also the top-down determined total global methane emission compares well with the total of the bottom-up estimates. We use the difference between the bottom-up and top-down determined emission trends to calculate residual emissions. These residual emissions represent the inter-annual variability of the methane emissions. Simulations have been performed in which the year-to-year meteorology, the emissions of ozone precursor gases, and the stratospheric ozone column distribution are either varied, or kept constant. The analyses reveals that the variability of the emissions is of the order of 8 Tg CH4 yr -1, and most likely related to mid- and low-latitude wetland emissions and/or biomass burning. Indeed, a weak correlation is found between the residual emissions and regional scale temperatures.

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