South Asian methane emissions, inferred from surface, aircraft and satellite observations

Lead Research Organisation: University of Bristol
Department Name: Geographical Sciences

Abstract

Methane is a powerful Kyoto Protocol regulated greenhouse gas and has the second largest radiative forcing after carbon dioxide. Globally, a large fraction of methane emissions are naturally occurring from sources such as wetlands and termites. In South Asia, natural wetlands are a smaller but still significant source of methane compared to the larger anthropogenic sources such as rice paddies, ruminants, fossil fuel emissions and biomass burning. Global average emissions of methane are generally well constrained but in order to specifically quantify emissions from South Asia, measurements taken in close proximity of South Asian sources are required. To fulfill this objective, a measurement site in Darjeeling, India was established in 2011 to measure methane on-site and collects over 70 measurements per day. In this project, methane emissions from each source sector (fossil fuel, wetlands, cattle, etc) will be quantified using surface, aircraft and satellite observations of methane concentration over South Asia.

Satellites currently measure methane concentrations around the globe and are powerful tools because of their global coverage, while surface sites only measure at one location. The main limitation with satellites is because they can be prone to errors in areas where clouds and dust can mask the methane signal. One of the avenues of research that will be done in this proposal is to combine all of the surface, aircraft and satellite measurements together and use the combined data to provide information on the quality of the satellite observations over South Asia. This will help to better understand how these satellite observations can be used over this region in the future.

One of the main sources of atmospheric methane in India comes from rice paddies, also known as anthropogenic wetlands. The process that governs these emissions is similar to that occurring in natural wetlands. When water covers the surface of the soil, oxygen is deprived to lower layers of the soil. In these "anoxic" zones, bacteria metabolize organic matter in the soil through a pathway that leads to methane production. However, the human influence on water management, fertilizer use and other agricultural practices makes rice paddy methane production a very different problem from a naturally driven wetland process. For example, humans artificially alter the water table level through the use of irrigation. Farmers also add additional nutrients into the soil, providing more organic matter and nitrogen for bacteria to utilize than would be found in a natural wetland. Furthermore, rice paddies are often created in areas that wouldn't otherwise contain wetland and thus are artificially introduced.

One of the main objectives of this research is to improve our understanding of the processes that drive methane emissions from wetland sources in India (from both natural wetlands and rice paddies). I will employ a "wetland" model, modified to include agricultural practices, to simulate emissions from the ground as well as a model of atmospheric transport to link the processes producing methane in the soil to the measurements that we make in the atmosphere. These atmospheric observations will be used to improve the processes in the wetland model. Using this tool, I will produce the most accurate and up-to-date methane emissions estimates, from all sources, from the Indian subcontinent. Finally, I will project emissions of methane from rice agriculture in India to the year 2100 using projected rice-growth and future climate scenarios such as those used in the Intergovernmental Panel on Climate Change Fifth Assessment Report (IPCC AR5).

Planned Impact

Who Will Benefit?

Several academic and societal groups have been identified as beneficiaries of the proposed research. (1) The multidisciplinary research proposed here will benefit and link groups in atmospheric science, climate science, biogeochemistry and statistics. (2) The scientific community benefits from long-term operation of the Darjeeling station and in the collection of long-term data. (3) This project benefits NERC, which recently funded a large multi-institute project to quantify UK emissions, the Greenhouse gAs Uk and Global Emissions (GAUGE) project using terrestrial models and atmospheric data. (4) Students in India will benefit from proposed educational activities (5) The UK Department of Energy and Climate Change (DECC) will benefit through the incorporation of the new inverse method used in this project into the software used for UK emissions estimation and reporting to the United Nations Framework Convention on Climate Change. (6) Students in the UK will directly benefit from the proposed outreach activities (7) The public will benefit from research results disseminated to a general audience via the University of Bristol and my personal website.

How will they benefit?

This research has several important academic and economic/societal impacts, as outlined by the Research Councils UK (RCUK).

Academic Impacts:
(1) Enhancing the knowledge economy through scientific advancement - The proposed research uses a novel modeling framework and data from multiple sources to advance the state-of-the-art knowledge about methane emissions from South Asia. This framework could potentially be applied to other regions and globally. (2) Worldwide academic advancement to address issues of importance in other countries or globally - This research is critical for quantifying emissions of a potent greenhouse gas, methane, from a rapidly growing developing country and has wide ranging implications for global and Indian climate policies. A multinational and multidisciplinary team of scientists has been selected to target South Asian methane emissions in greater detail than has been done before. (3) Development of new and innovative methodologies, and cross-disciplinary approaches - I propose to develop a new and innovative method to deduce 'top-down' constraints on methane production in South Asia, using a novel "inverse" methodology and data from a variety of sources around South Asia. The project is fundamentally inter-disciplinary as it bridges atmospheric modeling, terrestrial wetland modeling and climate science and explores the synergies between the fields.

Economic and Societal Impact:
(1) Contributing towards evidence based policy-making - As evidenced by top-down emissions estimates of other gases, most bottom-up inventories, from which many policies are based, are often underestimated and have large uncertainties. The ultimate goal of this research is to provide the most up-to-date 'top-down' emissions estimates for methane, from various source sectors in South Asia, using all of the atmospheric observations available from the region. The results will be used to inform policy-makers in the UK and in India through the proposed impact activities. (2) Contributing toward environmental, sustainability, protection and impact reduction - The effect of wetland and rice paddy emissions on climate will be investigated to the year 2100. This will help to inform policymakers of the effect that these emissions will have on global climate. Furthermore, one of the goals of this research is to better understand the effect of agricultural practices on methane emissions from rice paddies in India. This improved understanding will help to inform where research should be targeted.

Publications

10 25 50
 
Description I have been involved in several publications using satellite column methane data to quantify surface fluxes. I have contributed novel atmospheric modeling and statistical tools to quantify uncertainties in satellite-based data. I have quantified the first high-resolution methane emissions estimates from South Asia using data from satellites, aircraft and surface stations. This is the first time that this approach has been applied to column methane mole fractions from satellite data and the first time that this approach has been used in South Asia. Our key finding is that India's methane emissions are consistent with India's inventory reports to the United Framework Convention on Climate Change but substantially less than the emissions catalogued by global inventories. This work has been incorporated into India's 2018 submission to the United Nations Framework Convention on Climate Change.

This technique was then applied to assessing Brazil's methane emissions. We found that Brazil's wetland emissions could be lower than previously thought when accounting for biases between satellite and surface data.

I have also been involved in a high-profile study to use methane isotopologue data to understand what drivers may have been responsible for the observed variations in the atmospheric methane record. We found that wetlands are likely responsible for the increase in global atmospheric methane in the last decade. I have also been involved in a study using methane concentrations and isotopologue data to show that changes in the main methane sink, the hydroxyl radical, could have equally also been responsible for these observed signals. These two studies show that there is still much work to do to understand changes in atmospheric methane concentrations.

I have been involved in further developing a hierarchical Bayesian inverse modeling framework, which has now been extended to a reversible-jump MCMC model to quantify uncertainties associated with the choice of basis function.

Our model of methane's soil sink has incorporated new data from the last decade to improve our representation of how soils consume methane from the atmosphere. Our key finding has been that while the global total sink has not changed significantly from previous estimates, there is a significant shift away from the topics and toward the high-latitudes. We also find the drivers of changes in the soil sink from 1900-2100 and show that after 1990, temperature becomes the major driver of change in amount of methane taken up by soils.

I am further developing a collaboration with statisticians to develop new and improved inverse modeling methodologies (Dr Andrew Zammit Mangion and Prof Noel Cressie, University of Wollongong, Australia) and have extended these methods to use data from the Orbiting Carbon Observatory-2.

I developed collaborations to be involved in NERC-FAAM's flight campaign to India (Monsoon) in July 2016. As part of this, I was responsible for greenhouse gas measurements from a suite of instruments (CH4, N2O, synthetic greenhouse gases). The key findings from our publication are that India has emissions of several major HCFCs and HFCs and that India is in the process of transitioning between HCFC and HFC usage in air conditioning.

I am a co-investigator on the NERC Highlight Topic 'Closing the global methane budget,' which seeks to gain new observations and develop new modeling tools to understand why atmospheric methane concentrations are changing. We have created a spatial map of wetland methane isotope source signatures to be used in global atmospheric inverse modeling studies. The key findings of this study are that spatial variations in d13C-CH4 source signatures significantly can impact how methane emissions are retrieved. Because of the small signals in d13C-CH4 observations, not including these important source signature variations has the ability to skew the conclusions that can be derived.

Several publications have come out describing ozone-depleting compounds from China. Three publications describe emissions of CFC-11, carbon tetrachloride and chloroform. The key findings are that emissions from China have increased in recent years.
Exploitation Route The methodologies developed in this work can be used for other trace gas inversion projects. This hierarchical Bayesian inversion framework is already being used by groups around the world. The results of the emissions estimation work in South Asia has been incorporated into India's 2018 submission to the United Nations Framework Convention on Climate Change. The results of the methane soil sink project and the methane wetland source signature project have been compiled into files (netcdf format) that are on the web for researchers to download and use. The work on ozone-depleting substances from China has been communicated to colleagues and representatives in China, with the goal that the country will reduce these emissions. My work with statisticians is now being applied to carbon dioxide data from the Orbiting Carbon Observatory 2 (OCO-2).
Sectors Environment

 
Description My work on India's methane emissions has been communicated to the teams in India that are responsible for submission of greenhouse gas inventory to the United Nations Framework Convention on Climate Change. The results of this work have now been included in the 2018 Biennial Update Report to the UNFCCC by India. The methodologies created in Ganesan et al., Nature Communications, 2017 have been included in the Intergovernmental Panel on Climate Change's 2019 Refinement to the 2006 Guidelines. Our work in discovering new emissions of the banned CFC-11 from China has led to the closure of some illegal facilities. This work has been communicated at the highest levels to the overseeing body of the international Montreal Protocol.
Sector Environment
Impact Types Policy & public services

 
Description NERC Highlight Topic
Amount £4,000,000 (GBP)
Funding ID NE/N016548/1 
Organisation Natural Environment Research Council 
Sector Public
Country United Kingdom
Start 05/2016 
End 04/2020
 
Description NERC Highlight Topic Detection and Attribution of Regional Emissions
Amount £3,200,000 (GBP)
Funding ID NE/S003606/1 
Organisation Natural Environment Research Council 
Sector Public
Country United Kingdom
Start 06/2019 
End 05/2023
 
Description Newton Fund
Amount £180,000 (GBP)
Organisation Meteorological Office UK 
Sector Academic/University
Country United Kingdom
Start 04/2018 
End 03/2020
 
Description Atmospheric methane community 
Organisation Royal Holloway, University of London
Department Department of English
Country United Kingdom 
Sector Academic/University 
PI Contribution I work with Prof Euan Nisbet on understanding the observed variations of atmospheric methane. I provide modelling expertise to this partnership and a modeller involved in the NERC Highlight Topic (Closing the global methane budget) led by Prof Nisbet.
Collaborator Contribution Prof Nisbet provides atmospheric 13CH4 data (the main isotope of CH4) which I use with atmospheric models to provide an interpretation of the variations seen in the observations.
Impact Nisbet, E...Ganesan, A, 2016, 'Rising atmospheric methane: 2007-14 growth and isotopic shift'. Global Biogeochemical Cycles, vol 30., pp. 1356-1370
Start Year 2016
 
Description Land-surface modellers 
Organisation UK Centre for Ecology & Hydrology
Country United Kingdom 
Sector Public 
PI Contribution We have begun this collaboration to develop the methane module within the land-surface model JULES to include methane isotopes. I am bringing in expertise on atmospheric methane, atmospheric methane observations and inverse modelling.
Collaborator Contribution My collaborators contribute expertise on the JULES model.
Impact None yet Disciplines involved: Atmospheric chemistry, biogeochemistry, inverse modelling
Start Year 2016
 
Description Satellite remote sensing community 
Organisation University of Leicester
Country United Kingdom 
Sector Academic/University 
PI Contribution i am currently working with the GOSAT column CH4 satellite product developed by the University of Leicester (Dr Hartmut Boesch and Dr Robert Parker). We are currently investigating the use of GOSAT for emissions estimation in India. I am also working with the OCO-2 science team (Dr Michael Gunson, Prof Noel Cressie, Dr Andrew Zammit-Mangion) in developing new statistical methods for using remotely sensed column CO2 data for quantifying the CO2 budget.
Collaborator Contribution Partners have provided data sets and guidance on how the data products were created. This has allowed us to develop new statistical methods for quantifying uncertainties in the satellite retrievals and propagate those uncertainties onto flux quantification.
Impact Zammit-Mangion, A, Cressie, N & Ganesan, A, 2016, 'Non-Gaussian bivariate modelling with application to atmospheric trace-gas inversion'. Spatial Statistics. Multi-disciplinary: Atmospheric Chemistry and Spatial Statistics Zammit-Mangion, A, Cressie, N, Ganesan, AL, O'Doherty, S & Manning, AJ, 2015, 'Spatio-temporal bivariate statistical models for atmospheric trace-gas inversion'. Chemometrics and Intelligent Laboratory Systems, vol 149., pp. 227-241 Multi-disciplinary: Atmospheric Chemistry and Spatial Statistics
Start Year 2016
 
Description Satellite remote sensing community 
Organisation University of Wollongong
Department School of Mathematics and Applied Statistics
Country Australia 
Sector Academic/University 
PI Contribution i am currently working with the GOSAT column CH4 satellite product developed by the University of Leicester (Dr Hartmut Boesch and Dr Robert Parker). We are currently investigating the use of GOSAT for emissions estimation in India. I am also working with the OCO-2 science team (Dr Michael Gunson, Prof Noel Cressie, Dr Andrew Zammit-Mangion) in developing new statistical methods for using remotely sensed column CO2 data for quantifying the CO2 budget.
Collaborator Contribution Partners have provided data sets and guidance on how the data products were created. This has allowed us to develop new statistical methods for quantifying uncertainties in the satellite retrievals and propagate those uncertainties onto flux quantification.
Impact Zammit-Mangion, A, Cressie, N & Ganesan, A, 2016, 'Non-Gaussian bivariate modelling with application to atmospheric trace-gas inversion'. Spatial Statistics. Multi-disciplinary: Atmospheric Chemistry and Spatial Statistics Zammit-Mangion, A, Cressie, N, Ganesan, AL, O'Doherty, S & Manning, AJ, 2015, 'Spatio-temporal bivariate statistical models for atmospheric trace-gas inversion'. Chemometrics and Intelligent Laboratory Systems, vol 149., pp. 227-241 Multi-disciplinary: Atmospheric Chemistry and Spatial Statistics
Start Year 2016
 
Description Statisticians 
Organisation University of Wollongong
Country Australia 
Sector Academic/University 
PI Contribution My collaboration with statisticians has led to a number of publications on improved methods for inverse modelling of atmospheric greenhouse gases. We provide atmospheric modelling and measurement capability and a thorough knowledge of the physical system we are modelling.
Collaborator Contribution Our collaborators provide the technical expertise on the statistical methods we are developing.
Impact Zammit-Mangion, A, Cressie, N & Ganesan, A, 2016, 'Non-Gaussian bivariate modelling with application to atmospheric trace-gas inversion'. Spatial Statistics. Multi-disciplinary: Atmospheric Chemistry and statistics Zammit-Mangion, N. Cressie, A.L. Ganesan, et al. (2015) Spatio-temporal bivariate statistical models for atmospheric trace-gas inversion, Chemometr. Intell. Lab, 149, 227-241, doi:10.1016/j.chemolab.2015.09.006. Multi-disciplinary: Atmospheric Chemistry and statistics Ganesan, A.L., Rigby, M., Zammit-Mangion, A., Manning, A.J., Prinn, R.G., Fraser, P.J., Harth, C.M., Kim, K.R., Krummel, P.B., Li, S., O'Doherty, S.J., Park, S., Salameh, P.K., Steele, L.P., and Weiss, R.F. (2014) Characterization of uncertainties in trace gas inversions using hierarchical Bayesian methods, Atmos. Chem. Phys., 14, 3855-3864, doi:10.5194/acp-14-3855-2014 Multi-disciplinary: Atmospheric chemistry, Atmospheric Physics, Statistics
Start Year 2014
 
Description Department of Energy and Climate Change 
Form Of Engagement Activity Participation in an activity, workshop or similar
Part Of Official Scheme? No
Geographic Reach National
Primary Audience Policymakers/politicians
Results and Impact I attend meetings with the Department of Energy and Climate Change, which funds the UK tall tower monitoring programme. I share the findings I have developed with methodologies for use in the UK.
Year(s) Of Engagement Activity 2015