University of Aberdeen and the International Maize and Wheat Improvement Center (CIMMYT) have been collaborating to use the CGIAR Research Program on Climate Change, Agriculture and Food Security (CCAFS) Mitigation Options Tool (CCAFS-MOT) to estimate greenhouse gas emissions from Indian farming and identifies cost-effective mitigation options. Sylvia Vetter has presented a poster with preliminary results of this project at EGU – European Geosciences Union General Assembly in Vienna in April 2016. Authors: Sylvia Vetter, Diana Feliciano, Jon Hillier, Clare Stirling, Tek Bahdur, Pete Smith.

1. GHG Yield N P T Total emissions
tonnes/
ha
kg/ha mm grad C kg/ha kg/kg
Legume 0.37 0.99 426.9 25.12 257.27 0.43
Wheat 4.44 161.99 543.11 24.97 1289.8 0.29
Millet 1.71 55.48 475.26 25.16 817.58 0.43
Sugarcane 56.1 184.8 1076.23 24.2 2039.3 0.04
Coconut, Cotton,
Sesamum
1.79 88.26 432 25.12 669.25 0.41
Rice 3.72 161.13 612.33 24.68 3080.91 1.22
GHG emissions and mitigation potential in Indian agriculture
Sylvia H. Vetter1,*, Diana Feliciano1, Jon Hillier1, Clare M. Stirling2, Tek Bahdur2, Pete Smith1
1 Institute of Biological and Environmental Sciences, University of Aberdeen, Aberdeen AB24 3UU, UK; 2 International Maize and Wheat Improvement Center (CIMMYT)
Introduction
India is one of the world’s largest greenhouse gas (GHG)
emitter, accounting for about 5% of global emissions with
further increases expected in the future. The Government of
India aims to reduce emission intensities by 20-25% by 2020
compared with the 2005 level. In a recent departure from
past practice the reconvened Council on Climate Change
stated that climate change in agriculture would include a
component that would focus on reducing emissions in
agriculture, particularly methane and nitrous oxide emissions.
Method
The CCAFS Mitigation Option Tool (CCAFS-MOT) estimates
GHG emissions from various crops (e.g. barley, maize,
sugarcane), crop groups (e.g. vegetables, legumes) and
livestock production in different regions. By bringing together
several different empirical models to estimate GHG emissions,
CCAFS-MOT provides policy-makers across the globe with the
reliable information needed to make informed decisions about
emissions reductions within agriculture.
An excel version of the CCAFS-MOT can be downloaded:
https://ccafs.cgiar.org/mitigation-option-tool-
agriculture#.VpTnWL826d4
For the presented analysis the Tool was programmed in
MATLAB to allow spatial modelling and a comprehensive
analysis.
Input: soil (texture, organic C, pH, bulk density, N content)
and climate (annual precipitation, temperature) information;
management (crop, yield, fertiliser, tillage practice, residue
management) and for rice additional water management
information
Output: GHG emissions are estimated in terms of carbon
dioxide equivalent per hectare (kg CO2eq ha-1) and carbon
dioxide equivalent per unit of product (kg CO2eq kg-1).
Mitigation potential for multiple options in kg CO2eq ha-1
Data: Plot level data on crop yield and fertilizer application
was obtained from Directorate of Economics and Statistics of
the government of India: http://eands.dacnet.nic.in/Plot-
Level-Summary-Data.htm. Data on temperature and rainfall
were obtained from Global Climate data:
http://worldclim.org/. Soil data corresponding to GPS location
were obtained from The Global Soil dataset for Earth System
Modelling: http://globalchange.bnu.edu.cn/research/soilw.
Mitigation options:
Option 1: no tillage
Option 2: no tillage (rice)
Option 3: Planting basins
Option 4: Legume intercropping/rotation with legumes
Option 5: Residue incorporation
Option 6: improved water management (general)
Option 8: Use of cover crops
GHG emissions for crops in India
• Lowest GHG emissions per hectare are produced by
legumes, followed by cereals
• Highest emissions per hectare are produced by paddy
rice, sugarcane, potato and onions
• Emissions per kg yield show a different order with lowest
GHG emissions for coconut, sugarcane, onions, barley
and potato. The lower emissions per kg yield result from
the higher yield that is produced on one hectare for
these crops
• Paddy rice shows in both lists the highest GHG
emissions. The GHG emissions of rice management differ
immensely with the water management (single drainage,
multiple drainage).
Sorted by
Emissions per
ha
Emissions per
yield
crop kg/ha crop kg/kg
Masur,Lentil 260.25 Coconut 0.00029
Soyabean 321.83 Sugarcane 0.06096
Groundnut 344.04 Onion 0.09504
Urad,Blackgram 352.09 Barley 0.18034
Coconut 363.34 Potato 0.18535
Arhar,Redgram 422.91 Soyabean 0.24911
Gram 444.06 Groundnut 0.30568
Mustard,Rapeseed 481.42 Wheat 0.31254
Jowar 494.95 Maize 0.31485
Peas 504.33 Masur,Lentil 0.33134
Barley 561.18 Bajra 0.37672
Moong,Greengram 597.69 Peas 0.38471
Bajra 636.50 Mustard,Rapeseed 0.39680
Ragi 751.45 Ragi 0.47289
Safflower 751.65 Arhar,Redgram 0.51275
Maize 797.50 Gram 0.54047
Sunflower 826.24 Jute 0.59166
Wheat 947.71 Jowar 0.60071
Sesamum 1416.62 Urad,Blackgram 0.63021
Jute 1483.59 cotton 1.12294
Onion 1610.65 Sunflower 1.12646
cotton 1656.79 Moong,Greengram 1.33883
Potato 4210.67 Safflower 1.61506
Sugarcane 5083.94 Sesamum 2.12707
Paddy Rice 7593.74 Paddy Rice 4.70139
Haryana
Example Sugarcane:
Bihar
GHG yield N P T Total emissions
tonnes/
ha
kg/ha mm grad C kg/ha
kg/kg
yield
Legume 0.88 21.85 1021.41 26.02 319.79 0.38
Maize 3.29 106.94 1031.54 25.67 930.08 0.26
Wheat 2.47 111.6 1043.78 25.63 867.69 0.36
Potato 15.33 104.06 994.98 25.82 1607.98 0.1
Coconut, Cotton,
Sesamum
1.32 54.22 1084.33 25.47 978.36 0.8
Rice 2.13 91.59 1050.29 25.57 2015.98 1.68
Example: Maize:
• Precipitation is nearly twice as high in Bihar compared with Haryana
• Legumes result in a lower yield (tonnes/ha) in Bihar even if the fertilizer amounts are much higher than in Haryana
• For wheat and rice: yield and fertilizer use is much higher in Haryana than in Bihar, what results in higher GHG emissions
per hectare but the emissions per kg yield are lower because of the higher yield in Haryana
Mitigation Scenario Bihar:
• Increase in all fertiliser to increase yield
• Residue is less burned and more incorporated
• No till increases soil organic carbon (SOC)
Mitigation Scenario Haryana:
• Synthetic fertiliser ↓; organic fertiliser ↑
• Residue is less burned and more incorporated
• No till increases soil organic carbon (SOC)
Mitigation Scenarios:
Stakeholder meetings provided a wide range of possible and definite scenarios (management, policy, technology, costs, etc.)
for the future to mitigate emissions in agriculture as well as how to increase productivity. In a first analysis the sum of the
given mitigation options for Haryana and Bihar is calculated.
*Contact: Sylvia Vetter
School of Biological Sciences, University of Aberdeen,
23 St Machar Drive, Aberdeen AB24 3UU, Scotland, UK
E-mail: sylvia.vetter@abdn.ac.uk
State analysis
GHG emissions calculated for crops of two different states in India and general mitigation potential for different single options
Conclusion
• GHG emissions are highest for rice management
• Management differs widely over India what results in a wide
range of GHG emissions and a need for different mitigation
options for different regions/states
• Mitigation potential is high in rice production due to a
change of water management
• Mitigation potential is high in fertiliser management,
depending on region a decrease or increase of fertiliser can
decreases GHG emissions per kg yield and influence
production positively