"Indian methane emissions during 2010-2015"

Center for Climate Change Research (CCCR)

Yogesh K. Tiwari

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Associates: Dr. Supriyo Chakraborty, Dr. Vinu Valsala, Mr. Amey Datye

Research Team: Ms. Smrati Gupta (Sc-B); Mr. Santanu Halder (JRF); Dr. Tania Guha (former Post doc);

Dr. K. Ravi Kumar (former PhD student & Post doc, now Assistant Professor at IIT Delhi);

and various other M.Sc and M.Tech project students

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Ref: IPCC, AR5

Why Methane (CH4)?

- Radiative forcing

- Global warming potential

- CH4 life time

(1750 – 2011)

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CH4 observations started during late 2009 by the CCCR-IITM Pune

GHGs monitoring at Sinhagad (2009 onward)

Wet condition (around

October)

Dry condition (during

March, April)

Sinhagad Mountain table top

Sinhagad Tower for GHGs obs.

Sinhagad (SNG) site started in late 2009 by the CCCR-IITM Pune

• CSIRO Australia, NIO Goa - Cape Rama (CRI), 50 m amsl (discontinued , Jan 2013)

• Univ. of Bristol, Bose Institute Kolkata – Darjeeling (DJI), 2194 m amsl

CRI

DJI

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Monthly coverage from GOSAT retrievals (purple), CARIBIC flight path (light blue),

Other Institutional efforts on CH4 observation

Background and Objectives

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• India is currently thought to have the second largest CH4 emissions of any

country, but emissions have not been quantified from the top-down using

atmospheric observations from within the country and a high-resolution

modelling approach.

• We used a combination of satellite, aircraft and surface observations

between 2010 and 2015 to quantify CH4 emissions from India and to

investigate sources of discrepancies between the top-down derived emissions

and two inventories, EDGAR2010 (Emissions Database for Global Atmospheric

Research v4.2 FT 2010) and India’s BUR (First Biennial Update Report to its

National Communications) to UNFCCC

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(10 Oct. 2017)

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Comparison of India’s top-down CH4 emissions and seasonal cycle with bottom-up inventories. a Indian CH4 emissions (as Tg yr−1) for the prior inventories (orange, solid line) and for the top-down estimated here (dark blue line). The prior was comprised by EDGAR2010 (excluding rice), Yan et al. rice and GFED v3.1 biomass burning. For comparison, the dashed orange line corresponds to EDGAR2010 (including rice) and GFED. The turquoise line and shading indicates a 12-month running mean of the top-down emissions (uncertainties assuming full correlation between months). The black line and grey shading correspond to 2010 emissions submitted to the UNFCCC (BUR) and uncertainties (based on percentage uncertainties for the year 2000, the last year for which uncertainties were published: 50% enteric fermentation, 8% rice, 125% fossil fuel, 150% waste). b Average prior (orange) and top-down (blue) seasonal cycle. In all panels, shading corresponds to 5th–95th percentile uncertainties. The monsoon season is highlighted in pink bars

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Differences in emissions between seasons. a) Difference between the average summer (June–Sept) or b) average winter (Jan–Feb) peak emission periods, and the average of spring/autumn minimum emission periods (March–May, October–December) in gm−2 s−1.

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Prior emissions in gm−2 s−1 by source sector. a) Yan et al.17 average rice emissions for June–September. b) Yan et al.17, average rice emissions for March–May and October–December. c) EDGAR v4.2FT2010 anthropogenic emissions excluding rice and ruminants

(28 Nov. 2017)

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Measured and LMDz model simulated CH4 concentration at a) SNG (Sinhagad) and SEY (Seychelles), and b) CRI (Cape Rama) and SEY (Seychelles).

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(a) CARIBIC flight track from Frankfurt to Chennai on 16th Jan., 2012, rectangular boxes show oceanic sector and continental sector; (b) Longitudinal variation of CH4 concentration (model minus observed) over oceanic sector, vertical black line represents continental boundary; and (c) Vertical profile of CH4 concentration (model minus observed) over continental sector. 13

Model simulated vertical profile of CH4 over (a) Arabian Sea and (b) Indian subcontinent during summer (Jul, Aug) and winter (Dec, Jan) months.

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Vertical profile of model simulated

CH4 concentration averaged over

longitude bands 60oE-80oE and

during 2006 to 2013.

Contour lines indicates model

CH4 concentration values.

High frequency observations using online monitoring system 1) GHGs observations at the surface 2) GHGs observations during aircraft campaigns

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Recent developments on observational front

•The atmospheric CO2 budget estimated from both the top-down and bottom-up approaches suffers

from large uncertainty (Patra et a., 2013). One of the primary reasons of this uncertainty is the lack of

monitoring of CO2 at high temporal and spatial resolution •Especially monitoring the CO2 variability over an urban station which is the hot spots of

anthropogenic emission is crucial •Understanding the CO2 variability at a finer temporal scale like hourly variation can add up to the

understanding of the sudden emission episodes from a region and also transport driven mixing

•Installed at IITM in January,

2016 •At the terrace of IITM main

building •Currently running •Dry mol-fraction of CO2 •Dry mol-fraction of CH4 •CO •Water vapor concentration •Calibration of instrument

with NOAA cylinder at

regular time intervals

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1) Diurnal variation of CO2 (ppm) during different seasons (year 2016) at the IITM campus

18 Time (hours) Time (hours)

2) GHGs monitoring during aircraft campaigns

Ref: GHGs monitoring during CAIPEEX airplane campaigns 2014 , 2015

Credits: Dr. Thara Prabhakaran

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2014 2015

Airborne GHGs monitoring: 2014, 2015

• Instrumentation

• Picarro 2401-m, for measuring CO2, CH4, CO, H2O concentrations

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Calibrations:

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Flights over: “Kolhapur-Arabian sea-Solapur” (July 2015)

(Flight observations)

(LMDZ Model Simulations)

(Case study with different model)

23 CH4 (ppb)

Altitu

de

in

me

ters

(Flight observations)

(ACTM Model Simulations)

Flights over: “Kolhapur-Arabian sea-Solapur” (July 2015)

Easterly flow

Convection

5 km

8 km

2 km

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2 Km 5 km

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Flights over: “Ganga Basin – at Varanasi base” (Sept. 2014)

(Flight observations)

(LMDZ Model Simulations)

model simulated CH4 (ppb),

900 mb 800 mb 650 mb

500 mb 550 mb

July 2015

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Upcoming Project: (tall tower observatory)

(India’s tallest tower for GHGs monitoring) GHGs, its isotope, and CO2 flux monitoring observatory at Sagar University campus, Sagar, M.P

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• GHGs profiling at 72 meter tall tower

• Fully automatic observatory: real time data transfer, data display at the IITM Pune,

1. CO2,CH4,CO,H2O,delta 13C of CO2

&CH4 2. Eddy Covariance system (3-D

ultrasonic anemometer-thermometer, open path CO2-H2O analyzer, Data acquisition system)

3. Soil CO2 flux system 4. Soil heat flux plate at 2 levels 5. Multi-component weather sensors 6. Infrared thermometer (continuous

recording type) 7. Photosynthetic Active Radiation (PAR)

sensor, Line-PAR sensor 8. Net radiometer (with separate

shortwave and longwave components) 9. Integrated sensor for water content,

electrical conductivity and soil temperature

10. Datalogger

(72 meter) Sagar Tall Tower GHGs Observatory

Field work at Sagar University campus:

Actual site for tall tower

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Major conclusions

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• These findings demonstrate the need for more robust bottom-up accounting, using

country-specific data and more advanced accounting methodologies. They also

highlight the value of top-down evaluations of emissions inventories for regions of the

world that are critical for global climate and policy, but like India, are under-studied

and are therefore poorly quantified contributors to climate change.

• We estimate average emissions over the period 2010–2015 to be 22.0 (19.6–24.3)

Tg yr−1. These emissions are consistent with India’s reports to the United Nations

Framework Convention on Climate Change (UNFCCC), but are ~ 30% smaller than

the most widely used global CH4 inventory, EDGAR and ~ 40% smaller than

previous atmospheric inversion studies over India14. We also find that annual

emissions did not change significantly between 2010 and 2015 (0.2 ± 0.7 Tg yr−1),

suggesting that the major CH4 sources, including ruminants, rice paddies, waste

and fossil fuels, did not vary appreciably during this period.

Thanks for continuous support:

1) Prof. Ravi S. Nanjundiah, Director IITM

2) Dr. R. Krishnan, Executive Director, CCCR

Thank You !!

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