This document provides an abstract for a 4th National Research Conference on Climate Change held at the Indian Institute of Technology Madras from October 26-27, 2013. It includes the detailed program for the two-day conference covering sessions on climate change science and impacts, mitigation, and adaptation. The first day's program includes three sessions with oral presentations on topics like glacial changes in the Himalayas, climate impacts on agriculture, and climate change adaptation strategies. It also includes a session on high-resolution regional climate modeling and a poster session on adaptation projects. The abstracts provided give an overview of the research presented at the conference on assessing climate impacts and developing mitigation and adaptation solutions for India.

12. www.wca2014.org
COMPENDIUM
OF ABSTRACTS

13. capturing C (127.74 kg C/tree) and removing CO2 from the atmosphere (46.83 kg/tree/year) while, A.
pendula was the least with corresponding carbon (8.22kg C/tree) and CO2 (3.01kg/tree/year),
respectively. Positive correlation existed between carbon content and tree growth attributes (height and
dbh).
Keywords: agroforestry, carbon mitigation, CO2 removal efficiency, tree-biomass
AD2.1.3. Climate change in agriculture in the hilly region of Himachal Pradesh and the role
of agroforestry
M S. Pathania1
1
Agricultural economics, CSKHPKV, Palampur, India
The impact of climate change is most seriously felt in mountain regions because of the most vulnerable
ecosystems. Evidence of climate change could be clearly observed by changes in receding snowfall in
the Himalayas, disrupted rainfall patterns and increasing temperature. Agricultural production system
is affected by short and long-term climate changes. The study observed that different factors
responsible for climate change in the state indicated a decreasing trend in the amount of precipitation,
decrease of snowfall and decreasing trend of flow of water in different rivers. The forest and pasture
area decline over a period indicate negative signal to environment. The productivity of different crops is
less than their production potential. The study revealed that significant numbers of farmers believe that
temperatures have increased and precipitation has declined along with the late onset and early
withdrawal of monsoon with long dry spells which need to adjust to the cropping pattern with a
changing trend of climatic factors and the development of crop varieties that will be resistant to climate
change. The age, farming experience, education level, innovativeness, consciousness to environment
and exposures to mass media had a positive and significant relationship with farmer perceptions to
climate change. Adaptations made by farmers revealed that use of water conservation techniques and
agroforestry were the important adaptations in response to climatic change. They were in agreement
about adoption of a combination of tree plantations with crops to reduce the pressure of climate change
and increase crop productivity. There is need to develop suitable resistant crops to climate change and
planting trees with crops helps to reduce adverse climatic changes and increase crop productivity. Both
short term and long term strategies need to cope with climate change.
Keywords: none
AD2.1.4. Carbon sequestration assessment of block plantations at JSW Steel Limited
Ajit Gupta1*
, S K Dhyani1
, A K Handa1
, K B Sridhar1
, Amit Jain1
, Uma Gupta1
, P Sasindran2
, M
Kaza2
, R Sah2
, S M R Prasad2
, K Sriram2
1
National Research Centre for Agroforestry (NRCAF), Jhansi 2
JSW Steel Limited, Vijayanagar Works,
Toranagallu, Bellary, Karnataka, India
JSW Steel Ltd. is one of the premier steel producers in India with a current capacity of 10 MTPA at its
Vijayanagar Works in the Bellary district of Karnataka, India. As the fastest growing steel company in
India, it aims at quantifying the CO2 sequestered through green belt development activities in its
349 | P a g e

14. campus. T h e National Research Centre for Agroforestry (NRCAF), Jhansi simulated the CO2
sequestered under the existing greenbelt using CO2FIX model. The block plantations assessed across
the steel plant are 4MT (303 ha), 7MT (81 ha), 10MT (81 ha) and Township (101 ha). The soil of the
site is reddish/brown in colour and clayey loam in texture. The average annual rainfall of the plantation
area is 667 mm. The number of existing trees per hectare in the green belt of four assessed plant
areas varied from 475 to 934. The dominant tree species observed were Eucalyptus tereticornis
(38.69%), Leucaena leucocephala (31.39%) and Pithecellobium dulce (24.82%) in 7MT area;
Leucaena leucocephala (20.36%), Azadirachta indica (14.51%) and Peltophorum ferrugineum
(13.15%) in 4MT area; Cassia siamea (26.31%), Pongamia pinnata (23.68%), Azadirachta indica
(15.78%) and Acacia auriculiformis (13.15 %) in 10MT area; Leucaena leucocephala (29.37%) and
Eucalyptus tereticornis (14.75%) in the township areas. The carbon sequestration potential of
existing green belt in 4MT, 7MT, 10MT and township areas of JSW campus has been estimated to
the tune of 2.65, 1.63, 3.01 and 3.7 tonnes CO2ha-1
.yr-1
(or equivalently 9.71, 5.97, 11.03 and
13.60 tons CO2ha-1
.yr-1
). Overall, the carbon sequestration potential of the existing plantations
varied from 1.63 to 3.71 tons C.ha-1
.yr-1
.
Keywords: block plantations, carbon sequestration, steel plan
AD2.1.5. Carbon sequestration potential of mixed tree species existing on agricultural lands
in Bundelkhand regions of India
Ram Newaj1*
, S K Dhyani2
, Badra Alam2
, Ajit Ajit2
, Ramesh Singh2
, A K Handa2
, Anil Kumar2
,
Ankur Jha2
1
National Research Centre for Agroforestry, Jhansi (Uttar Pradesh), India, 2
National Research Centre for
Agroforestry, Jhansi, India
Carbon (C) sequestration through agroforestry is a potential viable option to mitigate climate change.
The amount of C storage by trees, crops and soil depends on the nature of the tree, tree density,
environmental and socioeconomic factors. Bundelkhand region has 13 districts and the total
geographical area is 7.06 m ha out of which 3.88 m ha is agricultural land. A field survey was conducted
through transect walk during 2009-2012 in 10 districts at village level (six village in each block). All
trees more than 1.5 m in height and more than 5.0 cm diameter at breast height (dbh) were enumerated.
The data was obtained for the number of trees for each tree species and dbh for each tree. In this way the
data was generated for different tree species and their density for a particular village. The tree species
were classified as slow, medium and fast growing based on the growth rate of stem volume for example;
slow growing < 10 m3
ha-1
yr-1
, medium growing 10-20 m3
ha-1
yr-1
and fast growing >20 m3
ha-1
yr-1
.
Specific species or generic volume equations were used to convert dbh in to volume (m3
ha-1
).
Simulation of above- and below-ground biomass of trees and crops, soil carbon and total C was done
using CO2FIX 3.1 model. The most common trees in the region are: A. nilotica, A. catechu, Zizyphus
mauritiana, Azadirachta indica, Butea monosperma, Madhuca latifolia, Acacia leucophloea, Inga
dulcis and Leucaena leucocephala. The results indicated that the value of biomass (tree + crop), soil C
and C sequestered were 29.61, 9.34, 23.13 t ha-1
, respectively in base year (2010) and the corresponding
values for 2030 would be 41.38, 18.38 and 37.84 t ha-1
respectively over baseline.
Keywords: field survey, transect walk, biomass, soil carbon, CO2FIX 3.1 model
350 | P a g e

16. 4th National Research Conference on Climate Change
Indian Institute of Technology, Madras
October 26-27, 2013
Organized jointly by IIT Madras, IIT Delhi, IISc Bangalore and
Centre for Science and Environment, New Delhi
DETAILED PROGRAMME
DAY 1: OCTOBER 26, 2013
REGISTRATION AND TEA – 08.00 to 09.00
(VENUE: CENTRAL LECTURE THEATRE HALL, HUMANITIES AND SOCIAL SCIENCES BUILDING)
INTRODUCTION – 09:00 TO 10:00
(VENUE: CENTRAL LECTURE THEATRE HALL, HUMANITIES AND SOCIAL SCIENCES BUILDING)
Sudhir Chella Rajan Professor and Head, Humanities and Social Sciences, IIT Madras
Bhaskar Ramamurthi Director, IIT Madras
M S Swaminathan Founder and Chairman, MS Swaminathan Research Foundation
Chandra Bhushan Deputy Director General, Centre for Science and Environment
SESSION I - 10:15 TO 12:15
SCIENCE & IMPACTS (VENUE: ICSR BUILDING, LT 1) Chair: N R Patel
Rajiv Kumar Chaturvedi Glacial mass balance changes in Karakoram and Himalaya based on multi-model projections
Ajay Singh Identifying imprint of ENSO on rice yield in India
Anubhab Pattanayak Weather sensitivity of rice yield: Evidence from India
Nitin Patil Interannual variability in monsoon rainfall and relation to aerosol effects using GCM simulations
Ashwini Kulkarni High resolution climate change scenarios in India
N R Patel Simulating impact of climate change on productivity, carbon sequestration and erosion process in
an agricultural landscape
CLIMATE CHANGE MITIGATION (VENUE: ICSR BUILDING, LT 2) Chair: Dilip Ahuja
M Sridevi Karpagavalli Wetland in climate mitigation: A case study of organic carbon profile of Pallikaranai Wetland, Chennai
Himangana Gupta Environmental impact of private sector CDM forestry projects in India
Prerna Prabhakar Analysis of resistances to intra regional trade of low carbon goods and services (LCGS) in an RTA:
A comparative analysis of SAFTA and AFTA
Ajit Gupta Assessing mitigation potential of existing agroforestry systems in some districts of Indo-Gangetic plains in India
Dilip Ahuja All states stand to save electricity were IST to be advanced
N H Ravindranath Climate change and forests
CLIMATE CHANGE ADAPTATION (VENUE: ICSR BUILDING, LT 3) Chair: A Nambi
Sujit Sarjerao Satpute Adaptive cropping policy for Mahanadi basin under climate change scenarios
Anoma Basu MGNREGA’s contribution to adaptation and mitigation of climate change impacts: A study in four districts of Madhya Pradesh
Chandra Kant Dhakal Determinants of livestock holders' adaptive capacity to climate change in Gandaki river basin, Nepal
A Ramachandran Changing climate and need of community based adaptation strategies
Naresh Kumar Adaptation of agriculture to climate change – opportunities, limits and limitations

17. SESSION II - 12:15 TO 12:45
CORDEX SOUTH ASIA: HIGH RESOLUTION CLIMATE DATA FOR IMPACT ASSESSMENTS
(VENUE: ICSR BUILDING LT 2) Chair: G Bala
Ramesh Vellore Scientist D, Indian Institute of Tropical Meteorology, Pune
SESSION III - 12.45 TO 1.15
POSTERS ON ADAPTATION (VENUE: ICSR BUILDING, LT 2)
(See Appendix for details)
LUNCH (VENUE: ICSR BUILDING DINING AREA) - 13.15-13.45
POSTER VIEWING ADAPTATION (VENUE: ICSR BUILDING FOYER) - 13.45-14.30
SESSION IV - 14.30 TO 16.30
SCIENCE AND IMPACTS(VENUE: ICSR BUILDING, LT 1) Chair: Sachchidanand Tripathi
Rajiv Kumar Chaturvedi Trends and variability of satellite-derived NPP in India
Prateek Gantayat Estimating volume of glacier stored ice using surface velocities and slope
K G Misra Climate change and stream flow variability in western Himalaya, India
Soumendra Nath Bhanja Satellite based estimates of groundwater storage depletion and its connection to climate change over Indian region
Sachchidanand Tripathi Secondary organic aerosols over Gangetic plains: Formation mechanisms, hygroscopic and optical properties
RENEWABLE ENERGY (VENUE: ICSR BUILDING, LT 2) Chair: Chandra Bhushan
Charith Konda Financing renewable deployment in India: Implications for policy
S S Krishnan Integrating renewable energy research and rapid deployment through policy analysis in the Indian context
O S Sastry Solar Photovoltaic technology for energy requirements of India
Srinivas Murthy Sustainability of solar thermal energy: Role of polygeneration
Srinivas Reddy Thermal technologies for sustainable development
CLIMATE CHANGE ADAPTATION (VENUE: ICSR BUILDING, LT 3) Chair: Sujatha Byravan
Ashish Chaturvedi Community based climate change adaptation: The 3P model
Archana Patankar Extreme weather events, uninsured losses and informal sector vulnerability: A case study of Mumbai, India
T Rajaram Use of participatory cognitive mapping to understand the socio-ecological dynamics and climate change
adaptation strategies in an agro-ecosystem: A case study from central Tamil Nadu
A Nambi Climate change and urban agriculture
Ahana Lakshmi Climate change in coastal ecosystems
SESSION V - 16.30 TO 17.15
POSTERS ON CLIMATE CHANGE MITIGATION AND CLIMATE POLICY (VENUE: ICSR BUILDING LT 2)
(See Appendix for details)
POSTER VIEWING MITIGATION AND POLICY (VENUE: ICSR BUILDING FOYER) - 17.15 to 18.15
LAUNCH OF CENTRE FOR SCIENCE AND ENVIRONMENT'S CLIMATE TALKIES EXHIBITION
(VENUE: ICSR BUILDING) - 18:30 to 19:30
DINNER (VENUE: ICSR BUILDING DINING AREA) - 19:30 to 22:00

18. DAY 2: OCTOBER 27, 2013
SESSION I - 9:00 TO 10:00
PANEL DISCUSSION ON NEW SCIENCE FINDINGS IN THE IPCC FIFTH ASSESSMENT REPORT
(VENUE: ICSR BUILDING AUDITORIUM) Chair: Sanjay Mishra
Govindasamy Bala Associate Professor, Centre for Atmospheric and Oceanic Studies, IISc
Krishna Achuta Rao Associate Professor, Centre for Atmospheric Sciences, IIT Delhi
Prashant Goswami Chief Scientist, Council for Scientific and Industrial Research Fourth Paradigm Institute (CSIR 4PI), Bangalore
SESSION II - 10.15 TO 12.15
SCIENCE AND IMPACTS (VENUE: ICSR BUILDING, LT 1) Chair: Anil Kulkarni
Nishi Srivastava Comparative study of anthropogenic aerosol fraction estimation over India
N K Indira Continuous GHG measurements in India
Shamal Date Tropical Indian Ocean SST variability in different CMIP5 scenarios
Kanhu Charan Pattnayak Projection of Indian summer monsoon for the 21st Century using RegCM4.3 with GFDL forcing
V K Gaur Outstanding research questions in climate change science and India’s contributions towards
global carbon flux estimations
SCIENCE AND IMPACTS (VENUE: ICSR BUILDING, LT 3) Chair: C Balaji
Balaji Narasimhan Hydrological assessment of sustaining rice production in a changing climate:
A case study of Krishna river basin, India
Monami Dutta How well do the IPCC-AR4 models simulate the observed 20th century warming as well as its future
projections over the Western Himalayan region of India?
M R Ramesh Kumar Monsoons and cyclones: Role of climate change
Vimal Mishra Climate change impacts on urban energy and infrastructure demands
Sagnik Dey Climate change & human health: Recent advances and challenges ahead
CLIMATE CHANGE MITIGATION (VENUE: ICSR BUILDING, LT 2) Chair: Ajit Kolar
Soumyananda Dinda Climate change and emerging opportunities in South Asia
Hippu Salk Kristle Nathan Solar PV microgrid–‘tragedy of commons’ or ‘community wisdom’ –
A case study of electrification projects in Komna
Anshu Ogra A study of climate policy integration in the state action plans on climate change
Avipsa Mahapatra Climate-friendly alternatives to HFCs: Energy efficiency co-benefits
Ajit Kolar Advance coal power generation systems with CO2 capture
Surender Kumar Climate shocks and production efficiency
SESSION III - 12:15 TO 13:30
POSTERS ON SCIENCE AND IMPACTS (VENUE: ICSR BUILDING, LT 3)
(See Appendix for details)
LUNCH (VENUE: ICSR BUILDING DINING AREA) - 13.30 to 14.15
POSTER VIEWING: SCIENCE AND IMPACTS (VENUE: ICSR BUILDING FOYER) - 14.15 to 17.00

19. SESSION IV - 15:00 TO 17:00
SCIENCE AND IMPACTS (VENUE: ICSR BUILDING LT 1) Chair: Anil Kulkarni
Princy Jain Impact of climate change on the Indian economy: Evidence from rice yields
Sibananda Senapati Assessment of socio-economic vulnerability due to climate change among fish dependent
community from Mumbai, India
Abhishek Nair Climate change vulnerability assessment for sustainable livelihoods using fuzzy
cognitive mapping approach
Amarnath Tripath Farmers’ vulnerability to climate change in Uttar Pradesh, India: Measurement and correlates
R C Dhiman Climate change and vector borne diseases
Balaji Chakravarty Towards better tracking of storms in the Bay of Bengal
CLIMATE CHANGE ADAPTATION (VENUE: ICSR BUILDING LT 2) Chair: K Kavi Kumar
Rucha Dande Traditional community management system as an adaptation strategy to climate variability:
Case of common property resources in western Rajasthan
Chandra Sekhar Bahinipati The damages from climatic extremes: Do generic adaptation measures matter?
K Ravi Shankar Understanding farmers’ knowledge, attitude and adaptation measures towards climate change
in Anantapur District of Andhra Pradesh
K Kavi Kumar Weather variability, agriculture and migration in India
SESSION V - 17:00 TO 18:00
VALEDICTORY SESSION (VENUE: ICSR AUDITORIUM)
Sanjay Mishra Advisor/Scientist-G, Head - Climate Change Programme, Department of Science and Technology,
Ministry of Science and Technology
Chandra Bhushan Deputy Director General, CSE
G Bala Associate Professor, Center for Atmospheric and Oceanic Studies, IISc
Krishna Achutarao Associate Professor, Center for Atmospheric Studies, IIT - Delhi
Ambuj Sagar Professor, Humanities and Social Science, IIT - Delhi
Sudhir Chella Rajan Professor, Humanities and Social Science, IIT - Madras
REIMBURSEMENTS AND CERTIFICATE DISTRIBUTION ALONG WITH HIGH TEA
(VENUE: ICSR AUDITORIUM LT 1)- 18:00 to 18:30

20. APPENDIX: POSTER PRESENTERS AND TITLES
ADAPTATION
Divya Subash Kumar Climate exposure index for dengue in Chennai
Falendra Kumar Sudan Climate change, food and livelihood security, and human mobility: Evidence and lessons learnt from
cold desert of Leh in north-west Himalaya
Pradipta Halder Climate change perceptions among local communities in India and their responses towards adaptation
Priya Dutta Vulnerability to heat stress among indoor working population
Aradhana Singh Untamed element: Gendered challenges and responses in natural disasters, Uttarakhand experience
Mrutyunjay Swain Effects of institutional support system on households’ resilience: The case of drought risk management
in Bolangir district, Odisha
Arun Jyoti Nath Promoting traditional management of Barringtonia forest as a strategy for livelihood security and climate change
mitigation
Chinmai Hemani Vulnerability assessment and adaptation strategies for coastal rural communities – a case of Western India
Jagadish Thaker Perceptions of changes in rainfall and extreme events among the Indian public
Jyoti Upadhyay Climate variation and food security: A case study of Karnataka
MITIGATION AND CLIMATE POLICY
Karthik Ganesan Residential CO2 emissions in India: The latent story of affluent rural households as written in the NSS 68th round
Rajesh Kumar Renewable energy technology : A sustainable means to mitigate greenhouse gases
Hippu Salk Kristle Nathan Solar PV for rural electricity– A misplaced emphasis for mitigating climate change
T Sekar Estimation of stored above ground biomass and carbon sequestration of Albizia saman in Chennai metropolitan city
J S I Rajkumar Sequestering of atmospheric carbon through fodder cultivation - A measure for mitigating global warming
Rani Tyagi Economic valuation of climate change adaptation in developing countries
Rajesh Kumar Quantifying the CO2 emissions in e-learning through LCA methodology
Naseer M Jaffer Economic growth and environmental protection - Race to the top?
Janani Venkatesh Production of algal bio-energy from ocean carbon dioxide by adsorption and desorption of carbon dioxide using
molecular sieves
CH Sreenivas Assessment of carbon mitigation potential of biogas technology in India
Binod Prasad Shah Green climate and climate resilient city in Nepal
Tapas Sudan Climate change and prospects and challenges of shale gas reserves in India: Lessons learnt from United States
SCIENCE AND IMPACTS
M Naresh Kumar Predicting climate variability over the Indian region using data mining strategies
Nimisha Agarwal Future climate analogue of current wheat production zones in India
Naresh Kumar Temporal and spatial variation in extreme temperatures over western Himalayan region
Anurag Kandya Simulating the impact of urban canopies on multi-meteorological properties: A case study of megacity Delhi using
WRF-GIS modelling
Chandan Roy Impact of climate change on poverty and food security: A case study of Indian Sundarbans
G Vinay Kumar Estimation of black carbon effect on snow reflectance in the accumulation area of glaciers in Baspa basin,
Himachal Pradesh, India
Sirisha Kalidindi Does turning down the solar constant have same climatic effect as prescribing aerosols into the stratosphere?
N R Patel Simulating impact of climate change on productivity, carbon sequestration and erosion process in an
agricultural landscape
Angshuman Modak Existence of regional disparities in precipitation due to the atmospheric circulation in a geoengineered world
Vijay Kumar V A Estimating the uncertainty in climate impact projections for Indian terrestrial ecosystem using DGVM (LPJ) with
CMIP5 climate models
Madhura Ranade Kane Changes in western disturbances over western Himalayas in a warming environment
Smriti Basnett Influence of supra and moraine-dammed lakes on the glacier retreat in Sikkim Himalaya

21. Gurjot Singh Bangalore carbon mapping study – Assessing cities’ potential for carbon storage and sequestration
V B Sakhare Physio-chemical parameters of a minor reservoir-Harini (Katgaon) in relation to fisheries
Apoorva Pandey Estimation of climate impact of energy-use activities in traditional industries
Kshitij Jayakrishnan Seasonal variability in black carbon aerosols over India using regional model simulations
Ramesh Vellore Are extreme precipitation events increasing over the Himalayas?
Nishanth T Long term variation of total and tropospheric ozone column over India
Mohammad Mahbubul Karim Effects of climate on dengue incidence in Dhaka: 2000-2011 – A GAM analysis
Ram Singh Quantifying uncertainty in future sea level change over the Indian Ocean region
Mathew KA Isotopic signatures of migration in butterflies: Reflection of climate shift
Jitendra Kumar Meher Long-term past and future rainfall change scenarios over western Himalayan region of India
Prashant Dave Path analysis based validation of mechanisms of aerosol-precipitation interactions
P Rahul Isotopic signature in paper cellulose; a man-made archive recording climate change
Yogesh Karyakarte Decadal snow cover change in Parbati basin, Himachal Pradesh, India
Jitendra Sangwai Experimental investigations on the formation of CO2 clathrate hydrates in porous media for efficient CO2 sequestration
Arunabh Choudhury Temporal variability of precipitation in NE India: 1901-2002
Madhushree Sarkar Climate and clean air impact of ozone precursor emissions from energy-use activities
Rajeev S Kurup Monsoon - ENSO teleconnections in the CMIP5 models
Devaraju N Effect of tropical deforestation on energy balance and climate
Ananya Rao Trends and variability in terrestrial carbon stocks and fluxes for the South Asian region

22. 4th National Research Conference on Climate Change
Indian Institute of Technology Madras
October 26-27, 2013
Organized jointly by IIT Madras, IIT Delhi, IISc Bangalore and
Centre for Science and Environment, New Delhi
INTRODUCTION
Sudhir Chella Rajan Professor and Head, Humanities and Social Sciences,
IIT Madras
Email: scrajan@iitm.ac.in
Bhaskar Ramamurthi Director, IIT Madras
Email: director@iitm.ac.in
MS Swaminathan Emeritus Chairman and Chief Mentor, MS Swaminathan
Research Foundation, Chennai
Email: swami@mssrf.res.in
Chandra Bhushan Deputy Director General, Center for Science and Environment
Email: chandra@cseindia.org
SESSION I
SCIENCE & IMPACTS
Rajiv K Chaturvedi IISc Bangalore
Email: chaturvedi.rajiv@gmail.com
Ajay Singh IIT Mumbai
Email: ajayvs@iitb.ac.in
Anubhab Pattanayak Madras School of Economics
Email: anubhab.pattanayak@gmail.com
Nitin Patil IIT Mumbai
Email: nupatil@iitb.ac.in
Ashwini Kulkarni Scientist, Indian Institute of Tropical Meteorology, Pune
Email: ashwini@tropmet.res.in
NR Patel Scientist SF, Indian Institute of Remote Sensing, Indian Space
Research Organization, Dehradun
Email: pnatoo@gmail.com
CLIMATE CHANGE MITIGATION
M Sridevi Karpagavalli Anna University, Chennai
Email: sridevi.cc@gmail.com
Himangana Gupta Panjab University, Chandigarh
Email: himangana@gmail.com
Prerna Prabhakar University of Delhi
Email: prernaprabhakar12@gmail.com
Ajit Gupta National Research Centre for Agroforestry, Jhansi
Email: umaajitgupta123@gmail.com
Dilip Ahuja Professor, School of Natural Sciences and Engineering,
National Institute of Advanced Sciences, IISc Bangalore
Email: drahuja@gmail.com
NH Ravindranath Professor, Centre for Sustainable Technologies, IISc Bangalore
Email: ravi@ces.iisc.ernet.in
CLIMATE CHANGE ADAPTATION
Sujit Sarjerao Satpute IIT Mumbai
Email: sujit.satpute@gmail.com
Anoma Basu FRI University, Indian Institute of Forest Management
Research Center, Bhopal
Email: anomabasu@yahoo.com
Chandra Kant Dhakal Institute of Agriculture and Animal Science, Nepal
Email: dhakalck@yahoo.com
A Ramachandran Director, Centre for Climate Change and Adaptation
Research,Anna University, Chennai
Email: ram7@annauniv.edu
Naresh Kumar Principal Scientist, Indian Agricultural Research Institute,
New Delhi
Email: nareshkumar@iari.res.in
A Nambi Director, Climate Change Program, M S Swaminathan
Research Foundation, Chennai
Email: arnambi@yahoo.com
SESSION II
CORDEX SOUTH ASIA: HIGH RESOLUTION CLIMATE DATA FOR
IMPACT ASSESSMENTS
Ramesh Vellore Indian Institute of Tropical Meteorology, Pune
Email: rameshv@tropmet.res.in
G Bala Associate Professor, Center for Atmospheric and Oceanic
Studies, IISc Bangalore
Email: gbala@caos.iisc.ernet.in
SESSION III
POSTERS ON ADAPTATION
Divya Subash Kumar Anna University, Chennai
Email: divyasubashkumar@gmail.com
Falendra Kumar Sudan University of Jammu, Jammu
Email: fk_sud@rediffmail.com
Pradipta Halder University of Eastern Finland
Email: pradipta.halder@uef.fi
Priya Dutta Indian Institute of Public Health Gandhinagar
Email: priyadutta@iiphg.org
Aradhana Singh Garhwal University, Uttarakhand
Email: aradhanasingh.830@rediffmail.com
Mrutyunjay Swain Sardar Patel University, Gujarat
Email: mrutyunjay77@gmail.com
Arun Jyoti Nath Assam University, Silchar,Assam
Email: arunjyotinath@gmail.com
Chinmai Hemani Independent Researcher and Climate Change Consultant
Email: chinmayhemani@gmail.com
Jagadish Thaker National University of Singapore
Email: jthaker@nus.edu.sg
Jyoti Upadhyay Institute for Social and Economic Change, Bangalore
Email: jyotiupadhyay11@gmail.com
SESSION IV
SCIENCE AND IMPACTS
Rajiv Kumar Chaturvedi IISc Bangalore
Email: chaturvedi.rajiv@gmail.com
Prateek Gantayat IISc Bangalore
Email: prateek@caos.iisc.ernet.in
PARTICIPANTS' DETAILS
DAY 1: OCTOBER 26, 2013

23. KG Misra Birbal Sahni Institute of Palaeobotany, Lucknow
Email: krishbsip@gmail.com
Soumendra Nath Bhanja IIT Kharagpur
Email: soumendrabhanja@gmail.com
Sachchidanand Tripathi Professor, Department of Civil Engineering, IIT Kanpur
Email: snt@iitk.ac.in
RENEWABLE ENERGY
Charith Konda Climate Policy Initiative, Hyderabad
Email: kg.charith@gmail.com
SS Krishnan Principal Research Scientist, C-STEP, Bangalore
Email: ssk@cstep.in
OS Sastry SEC (Solar Energy Centre), Ministy of New and
Renewable Energy, Delhi
Email: sastry284@yahoo.in
Srinivas Murthy Refrigeration and Airconditioning Lab, Department of
Mechanical Engineering, IIT Madras
Email: ssmurthy@iitm.ac.in
Srinivas Reddy Heat Transfer and Thermal Power Lab, Department of
Mechanical Engineering, IIT Madras
Email: ksreddy@iitm.ac.in
Chandra Bhushan Deputy Director General, CSE, New Delhi
Email: chandra@cseindia.org
CLIMATE CHANGE ADAPTATION
Ashish Chaturvedi GIZ, New Delhi
Email: ashish.chaturvedi@giz.de
Archana Patankar KJ Somaiya Institute of Management Studies and
Research, Mumbai
Email: archanapatankar@somaiya.edu
T Rajaram M A M College of Engineering,Tamil Nadu
Email: rajaenviro@gmail.com
A Nambi Director, Climate Change Program, M S Swaminathan
Research Foundation, Chennai
Email: arnambi@yahoo.com
Ahana Lakshmi Senior Scientific Consultant, National Centre for Sustain-
able Coastal Management,Anna University, Chennai
Email: ahanalakshmi@gmail.com
Sujatha Byravan Former Senior Fellow at Center for Development Finance
Email: sbyravan@yahoo.com
SESSION V
POSTERS ON CLIMATE CHANGE MITIGATION AND CLIMATE POLICY
Karthik Ganesan Council on Energy, Environment and Water, New Delhi
Email: karthik.ganesan@ceew.in
Rajesh Kumar Madurai Kamaraj University,Tamil Nadu
Email: rajeshkumarac@gmail.com
Hippu Salk K Nathan IISc Bangalore
Email: hsknathan@nias.iisc.ernet.in
T Sekar Pachaiyappa’s College, Chennai
Email: tsekar_bot@yahoo.com
J S I Rajkumar Madras Veterinary College, Chennai
Email: drjsirajkumar@gmail.com
Rani Tyagi H.R. College of Commerce and Economics, Mumbai
Email: ranityagi@gmail.com
Rajesh Kumar Sri Padampat Singhania University, Udaipur
Email: rajesh.kumar@spsu.ac.in
Naseer M Jaffer Xavier Institute of Management and Entrepreneurship,
Bangalore
Email: crystalauora@gmail.com
Janani Venkatesh SRM University,Tamil Nadu
Email: jananiv1993@gmail.com
CH Sreenivas IIT Mumbai
Email: cnu.biotech@gmail.com
Binod Prasad Shah Himalayan Alliance for Climate Change, Nepal
Email: envbinod@gmail.com
Tapas Sudan Thapar University, Patiala, Punjab
Email: tapassudan1994@gmail.com
SESSION I
PANEL DISCUSSION ON NEW SCIENCE FINDINGS IN THE
IPCC FIFTH ASSESSMENT REPORT
Govindasamy Bala Associate Professor, Center for Atmospheric and Oceanic
Studies, IISc Bangalore
Email: gbala@caos.iisc.ernet.in
Krishna Achuta Rao Associate Professor, Center for Atmospheric Sciences,
IIT Delhi
Email: akrishna@cas.iitd.ernet.in
Prashant Goswami Chief Scientist, Council of Scientific and Industrial
Research Fourth Paradigm Research Institute (CSIR 4PI),
Bangalore
Email: goswami@cmmacs.ernet.in
Sanjay Mishra Advisor/Scientist-G, Head - Climate Change Programme,
Department of Science and Technology, Ministry of Science
and Technology
Email: sanjaykr.mishra@nic.in
SESSION II
SCIENCE AND IMPACTS
Nishi Srivastava Birla Institute of Technology, Mesra
Email: nishi.bhu@gmail.com
NK Indira Scientist, CSIR 4PI Bangalore
Email: indira@csir4pi.in
Shamal Date Indian Institute of Tropical Meteorology,Pune
Email: shamal@tropmet.res.in
Kanhu Charan Pattnayak IIT Delhi
Email: kcpattnayak@gmail.com
VK Gaur Honorary Scientist, CSIR 4PI, Bangalore
Email: gaur@cmmacs.ernet.in
M R Ramesh Kumar Chief Scientist, National Institute of Oceanography, Goa
Email: kramesh@nio.org
Anil Kulkarni Distinguished visiting Scientist, Divecha Center for Climate
Change, IISc Bangalore
Email: anilkulkarni@caos.iisc.ernet.in
SCIENCE AND IMPACTS
Balaji Narasimhan IIT Mumbai
Email: nbalaji@iitm.ac.in
Monami Dutta Bidhan Chandra Krishi Viswavidyalaya,West Bengal
Email: monamidutta2509@gmail.com
Vimal Mishra Assistant Professor,Water and Climate Lab,
IIT Gandhinagar
Email: vmishra@iitgn.ac.in
Sagnik Dey Assistant Professor, Center for Atmospheric Studies,
IIT Delhi
Email: sagnik@cas.iitd.ac.in
C Balaji Scientist, Heat Transfer and Thermal Power Lab,
Department of Mechanical Engineering, IIT Madras
Email: balaji@iitm.ac.in
CLIMATE CHANGE MITIGATION
Soumyananda Dinda SKB University, Purulia
Email: sdinda@gmail.com
Hippu Salk K Nathan IISc Bangalore
Email: hsknathan@nias.iisc.ernet.in
Anshu Ogra Jawaharlal Nehru University, New Delhi
Email: anshuogra@gmail.com
Avipsa Mahapatra Environmental Investigation Agency,Washington DC
Email: amahapatra@eia-global.org
Ajit Kolar Professor, Heat Transfer and Thermal Power Lab,
Department of Mechanical Engineering, IIT Madras
Email: kolar@iitm.ac.in
Surender Kumar Professor of Economics, Department of Business
Economics, University of Delhi
Email: surender672@gmail.com
DAY 2: OCTOBER 27, 2013

24. SESSION III
POSTERS ON SCIENCE AND IMPACTS
M Naresh Kumar ISRO, Hyderabad
Email: nareshkumar_m@nrsc.gov.in
Nimisha Agarwal IISc Bangalore
Email: nimisha2902@gmail.com
Naresh Kumar India Meteorological Department, New Delhi
Email: naresh.nhac@gmail.com
Anurag Kandya Nirma University,Ahmedabad
Email: akandya@yahoo.com
Chandan Roy Jadavpur University, Kolkata
Email: chandanroyju@gmail.com
G Vinay Kumar IISc Bangalore
Email: gaddam_vinay@ymail.com
Sirisha Kalidindi IISc Bangalore
Email: sirishakalidindi@caos.iisc.ernet.in
N R Patel ISRO, Dehradun
Email: nrpatel@iirs.gov.in
Angshuman Modak IISc Bangalore
Email: amatcaos@caos.iisc.ernet.in
Vijay Kumar V A IISc Bangalore
Email: va.vijaykumar9@gmail.com
Madhura Ranade Kane Indian Institute of Tropical Meteorology, Pune
Email: madhura@trop.met.res.in
Smriti Basnett IISc Bangalore
Email: smritibas@gmail.com
Gurjot Singh IISc Bangalore
Email: gurjotbmc@gmail.com
V B Sakhare Yogeshwari Mahavidyalaya,Ambajogai
Email: vbsakhare@rediffmail.com
Apoorva Pandey IIT Mumbai
Email: p1231@iitb.ac.in
Kshitij Jayakrishnan IIT Mumbai
Email: kshitij.jayakrishnan@gmail.com
Ramesh Vellore Indian Institute of Tropical Meteorology, Pune
Email: rameshv@tropmet.res.in
Nishanth T Kannur Univeristy, Kerala
Email: nisthu.t@gmail.com
Mohammad M Karim Centre for Population, Urbanization and Climate Change,
Dhaka
Email: mshossain@icddrb.org
Ram Singh IIT Delhi
Email: rambhari0123@gmail.com
Mathew KA IISc Bangalore
Email: mathew.ka@ceas.iisc.ernet.in
Jitendra Kumar Meher Bidhan Chandra Krishi Viswavidyalaya,West Bengal
Email: jitendra.meher29@gmail.com
Prashant Dave IIT Mumbai
Email: daveprashant@iitb.ac.in
P Rahul IISc Bangalore
Email: rahulp@ceas.iisc.ernet.in
Yogesh Karyakarte IISc Bangalore
Email: yogeshkaryakarte@gmail.com
Jitendra Sangwai IIT Madras
Email: jitendrasangwai@iitm.ac.in
Arunabh Choudhury National Institute of Technology, Karnataka
Email: arunav.choudhury@gmail.com
Madhushree Sarkar IIT Mumbai
Email: madhusreesarkar@yahoo.co.in
Rajeev S Kurup IIT Delhi
Email: rajeevsk369@gmail.com
Devaraju N IISc Bangalore
Email: dev@caos.iisc.ernet.in
Ananya Rao IISc Bangalore
Email: ananyasrao@gmail.com
SESSION IV
SCIENCE AND IMPACTS
Princy Jain University of Delhi
Email: pj1909@gmail.com
Sibananda Senapati National Institute of Industrial Engineering,
Mumbai
Email: sibanandaeco@gmail.com
Abhishek Nair Institute of Rural Management, Gujarat
Email: pramod@irma.ac.in
Amarnath Tripath Institute of Economic Growth, New Delhi
Email: amarnath@iegindia.org
RC Dhiman Scientist, National Institute of Malaria Research,
New Delhi
Email: dhimanrc@icmr.org.in
C Balaji Scientist, Heat Transfer and Thermal Power Lab,
Department of Mechanical Engineering, IIT Chennai
Email: nbalaji@iitm.ac.in
Anil Kulkarni Distinguished visiting Scientist, Divecha Center for Climate
Change, IISc Bangalore
Email: anilkulkarni@caos.iisc.ernet.in
CLIMATE CHANGE ADAPTATION
Rucha Dande Axykno Capital Services, Nagpur
Email: ar.rucha.dande@gmail.com
Chandra S Bahinipati Gujarat Institute of Development Research,Ahmedabad
Email: chandrasekharbahinipati@gmail.com
K Ravi Shankar Central Research Institute for DrylandAgriculture, Hyderabad
Email: krshankar@crida.in
KS Kavi Kumar Professor, Madras School of Economics
Email: kavi@mse.ac.in
SESSION V
VALEDICTORY SESSION
Sanjay Mishra Advisor/Scientist-G, Head - Climate Change Programme,
Department of Science and Technology, Ministry of Science
and Technology
Email: sanjaykr.mishra@nic.in
Chandra Bhushan Deputy Director General, CSE
Email: chandra@cseindia.org
G Bala Associate Professor, Center for Atmospheric and Oceanic
Studies, IISc Bangalore
Email: gbala@caos.iisc.ernet.in
Krishna Achutarao Associate Professor, Center for Atmospheric Studies,
IIT Delhi
Email: akrishna@cas.iitd.ernet.in
Ambuj Sagar Professor, Humanities and Social Science, IIT Delhi
Email: asagar@hss.iitd.ac.in
Sudhir Chella Rajan Professor, Humanities and Social Science, IIT Madras
Email: scrajan@iitm.ac.in

25. Assessing mitigation potential of existing agroforestry systems in some districts of Indo-
gangetic plains in India
Ajit, S.K.Dhyani, Ramnewaj, A.K.Handa, Badre Alam, Rajender Prasad, R.H.Rizvi, Amit Jain and
Uma
National Research Centre for Agroforestry (NRCAF),
(Indian Council of Agricultural Research)
Gwalior Road, Near Pahuj Dam
JHANSI-284003 (UP), India
Corresponding Author: Ajit , Principal Scientist, NRCAF, Jhansi
e-mail: umaajitgupta123@gmail.com, umaajitgupta@yahoo.co.in
Office(O):0510-2730213/2730214 , FAX: 0510-2730364 Mobile: 09415092880
ABSTRACT
The Indo-gangetic plains (IGP) in India occupy 13% of the total geographical area and produces
50% of total food grain of the country. Dynamic CO2FIX model v3.1 has been used to assess the
baseline carbon and to estimate the carbon sequestration potential (CSP) of agroforestry
systems (AFS) for a simulation period of thirty years in three districts of IGP. The estimated
u ers of trees existi g i far er’s field o per he tare asis i these distri ts were 37.95,
6.14 and 6.20, respectively. The baseline standing biomass in the tree components varied from
2.45 to 2.88 Mg DM ha-1
and the total biomass (tree+crop) from 11.14 to 25.97 Mg DM ha-1
in
the three districts. The soil organic carbon in the baseline ranged from 8.13 to 9.12 Mg C ha-1
and is expected to increase from 8.63 to 24.51 Mg C ha-1
. The CSP of existing AFS has been
estimated to the tune of 0.111, 0.126 and 0.551 Mg C ha-1
yr-1
and accordingly the mitigation
potential as 0.407, 0.462 and 2.021 Mg CO2 ha-1
yr-1
for Sultanpur, Dinajpur and Ludhiana
districts of IGP, respectively. Model validation results revealed that average percent bias in
standing tree biomass prediction was less than 6%.
Available On line:
http://www.indiaenvironmentportal.org.in/files/file/Ajit%20Gupta.pdf

26. Assessing mitigation potential of existing agroforestry systems in
g g p g g y y
some districts of Indo‐gangetic plains (IGP) in India
Ajit, S.K.Dhyani, Ramnewaj, A.K.Handa, Badre Alam, Rajender Prasad, R.H.Rizvi,
Amit Jain and Uma
National Research Centre for Agroforestry (NRCAF),
(Indian Council of Agricultural Research)
Gwalior Road Near Pahuj Dam
Gwalior Road, Near Pahuj Dam
JHANSI‐284003 (UP), India
Corresponding Author: AJIT , Principal Scientist, NRCAF, Jhansi
e‐mail: umaajitgupta123@gmail.com, umaajitgupta@yahoo.co.in
Office(O):0510‐2730213/2730214 FAX: 0510‐2730364 Mobile: 09415092880

27. About the Project
• This study on
Mitigation potential of existing
agroforestry systems on farmers field
was initiated in 2011 under the NICRA Project
(N ti l I iti ti Cli t R ili t A i lt )
(National Initiative on Climate Resilient Agriculture),
launched by the Indian Council of Agricultural Research
(ICAR), Ministry of Agriculture, Government of India, New
Delhi (www.nicra‐icar.in).
• The basic objective of this study was
The basic objective of this study was
to simulate the CSP of existing AFS on
farmer’s field
farmer s field

28. For simulating the carbon sequestration potential of existing agroforestry
systems in various districts of IGP we have used CO2FIX model
CO2FIX model
• The CO2FIX model V 3.1 was developed at Centro
Agronómico Tropical de Investigación y Enseñenza
systems in various districts of IGP , we have used CO2FIX model
Agronómico Tropical de Investigación y Enseñenza
(CATIE), Wageningen, Netherland under the
CASFOR II (Carbon Sequestration in Forested
Landscapes) project.
p ) p j
• CASFOR II was financed through the European
Commission INCO2-programme. Additional funding
was received from the Dutch Ministry of
was received from the Dutch Ministry of
Agriculture, Nature Management and Fisheries under
the North-South programme, and by the Mexican
National Council of Science and Technology.
gy
• The software can be downloaded free of cost from site
http://www.efi.fi/projects/casfor

29. Why CO2FIX
• Ravindranath and Ostwald (2008) have compiled and compared different models
Ravindranath and Ostwald (2008) have compiled and compared different models
used in estimating changes in carbon stock for forestry and plantation projects.
• CO2FIX was preferred over others (viz PROCOMAP, CENTURY and ROTH) for the
present study since only CO2FIX can simulate the carbon dynamics of single
/multiple species simultaneously, and can handle trees with varied ages and
agroforestry systems (AFS).
• Moreover, CO2FIX outputs the biomass and C separately in above and below
d t t h t i (i i i ) i dditi t il b
ground tree components cohorts wise (i.e species wise) in addition to soil carbon
dynamics.
• In this study, we are estimating the carbon sequestration potential of existing
agroforestry systems at farmers’ fields in different district of Indogangetic plains
agroforestry systems at farmers fields in different district of Indogangetic plains
and it was anticipated to observe varying tree species existing at farmers’ fields.
Accordingly CO2FIX was more appropriate to handle multiple species
simultaneously in addition to field crops.
• Nair et al. (2005) has also mentioned that CO2FIX is a user friendly model for
dynamically estimating the carbon sequestration potential of forest management
and afforestation project and is readily adaptable for agroforestry.

30. CO2FIX in nut‐shell
• In CO2FIX model, the biomass and carbon credits are simulated
at the hectare scale with time steps of one year
at the hectare scale with time steps of one year.
• The biomass module converts volumetric net annual increment
data to the annual carbon stock of the biomass compartment.
• Turnover and harvest parameter drive the fluxes from biomass to
soil. The model has a soil module known as YASOO, which takes
into account the initial litter quality and the effect of climate on
into account the initial litter quality and the effect of climate on
decomposition. Litter enters the soil module based on the size of
the litter and is then dissociated into contents of different classes
f i d Th lidit f it il b ti t
of organic compounds. The validity of its soil carbon estimates,
mass loss estimates and ability to appropriately describe the
effects of climate on decomposition rates has been tested within
a wide range of environments.

31. Input Parameters required for the model
• The main input parameters relevant to CO2FIX model are the cohort wise values for the
• stem‐CAI (current annual increment in m3 ha‐1 yr‐1) over
years;
years;
• relative growth of the foliage, branches, leaf and root with
respect to the stem growth over years;
• turnover rates for foliage, branches and roots;
• and climate data of the site ( annual precipitation in mm and
monthly values of minimum and maximum temperatures in 0C )
monthly values of minimum and maximum temperatures in 0C ).
• Other inputs to the model includes initial surface soil organic carbon (Mg
C ha‐1), rotation length for the tree species, per cent carbon contents in
different tree parts wood density and initial values of baseline carbon (Mg
different tree parts, wood density and initial values of baseline carbon (Mg
C ha‐1) in different tree parts, when the simulation are being carried out
for the existing tree plantations as in the present case.

32. The CO2FIX modules considered are:
• Biomass
Methodology adopted
• These Modules requires primary as well as secondary
Biomass
• Soil and
• Carbon accounting modules.
Methodology adopted
q p y y
data on tree and crop components (called ‘cohorts’ in
CO2FIX terminology).
District Level Data
Primary data
1. Name of existing tree species
under agroforestry systems
Secondary data
1. Total Area of District (in ha).
2. i) Agril. Land (in ha), ii) Non Agril. Land
(in ha) iii)Forest Land (in ha) iv)Waste land
g y y
2. Frequency of existing tree spp.
under agroforestry system
3. DBH of Maximum 10 plants
(including smaller medium and large
(in ha), iii)Forest Land (in ha), iv)Waste land
(in ha).
3. Name and No. of blocks In District
4. Area of blocks (in ha) and total no. of
villages in district
7
(including smaller, medium and large
size tree ).
g
5. Major crops with their productivity (q/ha)
and Area under crop (in ha)
6. District map(Block wise)
7. Block map(village wise)

33. Tree Cohorts
• The tree species being grown on farmland were classified
Tree Cohorts
into three categories/cohort’s viz slow, medium and fast
growing trees as per the nature of the tree species.
• DBH of the surveyed trees was used to approximately find
• DBH of the surveyed trees was used to approximately find
out the age of the standing trees. To derive the incremental
data of tree stem growth, the volume equations published in
g , q p
State Forest Report-2009 were used as the secondary data.
• DBH (m) and stem volume (m3/tree) datasets were generate
for the species found in survey. The individual species wise
generated data sets were then clubbed into single files for
the slow medium and fast growing species separately
the slow, medium and fast growing species separately.
8

34. • These three data sets pertaining to slow, medium and fast
growing species were independently used to fit non-
g g p p y
linear functions for stem volume-DBH relationships.
These tree wise absolute stem volume-DBH
relationships were then converted into hectare wise
relationships were then converted into hectare wise
stem volume-DBH relationships, by multiplying tree
wise stem volume from the average number of trees
f d i ill i ifi d
found in a village in a specified category
(slow/medium/fast).
• DBH was transformed back into age to obtain
DBH was transformed back into age to obtain
hectare wise stem volume–age relationships.
Ultimately, these absolute stem volume values were
converted into CAI (current annual increment in
converted into CAI (current annual increment in
m3/ha/yr). Thus, we obtained the CAI equations for
stem-volume-age for the three categories/cohorts of
slow, medium and fast growing trees in a given district.
9

35. Crop Cohort
• In order to simulate the crop component, the crop was considered as a ‘tree’
with a very small stem volume, no branches and a lot of foliage and roots.
• The stem part is needed since allocation to foliage and roots are driven by
• The stem part is needed, since allocation to foliage and roots are driven by
stem increment. In order to keep the influence of the stem compartment as
small as possible, a very small increment was specified, in our case 0.01 m3 ha‐
1 yr‐1.
y
• The foliage (grain and straw) and root compartment receive a very high
relative increment (w.r.t. stem), say for example set as 8657 and 865
respectively for Ludhiana district. When the wood density has been set at
p y y
‘0.09’, the aboveground production is 8657*0.09*0.01 = 7.79 Mg DM ha‐1 (dry
matter per hectare). Similarly, belowground production is 0.77 Mg DM ha‐1 for
Ludhiana district.
• Additionally, it was presumed for CO2FIX model that 5% of the above ground
crop biomass (grain and straw) incorporates into the soil, while 95% is
exported out from the system. Likewise, 30% of the below ground crop
biomass is incorporated into the soil.

36. Soil parameterization
• The district wise climatic data on monthly temperature and precipitation was
obtained from IMD (Indian Meteorological Department) and was fed as the
p
general parameters for the soil compartment of the model.
•The dynamic soil carbon model YASSO describes decomposition and
dynamics of soil carbon in well drained soils
dynamics of soil carbon in well‐drained soils.
•The soil module consists of three litter compartments (non‐woody, coarse‐
woody and fine‐woody) and five decomposition compartments (extractives,
cellulose, lignin like compound, humus‐1 and humus‐2).
•Litter is produced in the biomass module through biomass turnover. For the
soil carbon module the litter is grouped as non‐woody litter (foliage and fine
soil carbon module, the litter is grouped as non woody litter (foliage and fine
roots), fine woody litter (branches and coarse roots) and coarse woody litter
(stems and stumps).
11

37. Statistical analysis of data:
Statistical analysis of data:
• The Statistical analysis of data has been done using
SAS‐9.3 (SAS Institute’s Inc. @ 2011, Cary, North
Carolina‐27513, USA).
Carolina 75 3, USA).
• proc‐UNIVARIATE was used for computing the basic
descriptive statistics and proc NLIN was used for fitting
descriptive statistics and proc‐NLIN was used for fitting
the nonlinear equations to the data.
• proc–SGPLOT was used for plotting the graphs to the
observed and modeled biomass along with the residuals.

38. /
Example of Ludhiana district
Site characteristics, dominant tree/crops and climatic data of the study area
Attributes Ludhiana
Location 300 4’ N and 750 5’ E
Rainfall (mm), climate 681, Semiarid
( ), ,
Soil type Sandy, Clayey Loam, Alkaline
Region Upper Gangetic plains
Region Upper‐Gangetic plains
Dominant crops Rice, Wheat and Maize
Dominant agroforestry trees Populus deltoides, Eucalyptus tereticornis,
Melia azedarach

39. Input parameter used in CO2FIX model for simulating tree biomass components
in various tree cohorts (uniform for all three districts)
Cohorts Slow growing
trees a
Medium growing
trees b
Fast growing trees c
Rotation (year) 90 50 10
Wood density (Mg DM/m3) 0.67 0.65 0.61
Carbon content (% dry weight) 48 48 48
Turnover rate foliage 0.5 0.5 0.6
Turnover rate branch 0 02 0 04 0 02
Turnover rate branch 0.02 0.04 0.02
Turnover rate root 0.02 0.1 0.2
Product allocation for Thinning
harvesting*
Stem log wood 0.8 0.8 0.8
Stem slash 0.2 0.2 0.2
Branch log wood 0.8 0.8 0.2
Branch slash 0.2 0.2 0.8
Foliage slash 1 1 1
Foliage slash soil 0.7 0.7 0.7
Estimated from a Negi (1984); Kumar et al. (2011); b Jha (1995); c Bargali et al. (1992); *Haripriya (2001)

40. Cohorts Ludhiana
Primary survey results for the tree species observed in the district
Slow growing
tree
Medium
growing
Fast growing
Estimated average
Estimated average
number of trees per
hectare
0.17 1.0 36.78
Estimated age of
existing trees (years) 40 16 3
Observed average
DBH of existing trees
(cm)
29.2 25.28 7.5
(cm)

41. Slow Growing Medium Growing Fast Growing
Current Annual Increment (CAI) of the stem volume growth (m3 ha‐1yr‐1) over years for three
tree cohorts
Age CAI Age CAI Age CAI Age CAI
0 0.010 55 0.040 0 0.025 1.0 0.000
5 0.010 60 0.047 5 0.028 2.0 0.004
10 0.010 65 0.054 10 0.037 2.5 0.031
15 0.012 70 0.060 15 0.053 3.0 0.249
20 0.014 75 0.068 20 0.076 3.5 0.447
25 0.016 80 0.072 25 0.106 4.0 0.677
30 0.018 85 0.085 30 0.155 4.5 0.912
35 0.022 90 0.091 35 0.217 5.0 1.318
40 0.025 95 0.092 40 0.279 5.5 1.469
45 0.030 100 0.087 45 0.292 6.0 1.584
50 0.034 50 0.119 6.5 1.665
55 0.021 7.0 1.740
7.5 1.744
8.0 1.731
8.5 1.706
9.0 1.628
9.5 1.581

42. Slow growing a Medium growing b Fast growing c
Foliage Age Rates Age Rates Age Rates
Relative growth of various tree components with respect to stem growth for tree cohorts (over years)
0 1 1 0.26 0 0.30
10 0.50 5 0.63 2 0.44
20 0.73 15 0.50 3 0.40
30 0.64 20 0.38 4 0.38
40 1.02 25 0.32 5 0.37
40 1.02 25 0.32 5 0.37
50 1.12 30 0.50 6 0.32
60 0.98 7 0.56
70 0.91 8 0.58
Branch Age Rates Age Rates Age Rates
0 0 20 1 0 44 0 0 25
0 0.20 1 0.44 0 0.25
10 0.18 5 0.44 2 0.22
20 0.15 15 0.33 3 0.18
30 0.16 20 0.38 4 0.18
40 0.16 25 0.32 5 0.21
50 0.15 30 0.32 6 0.28
60 0.14 7 0.43
70 0.14 8 0.58
Root Age Rates Age Rates Age Rates
0 0 40 0 0 44 0 0 30
0 0.40 0 0.44 0 0.30
10 0.40 5 0.48 2 0.43
20 0.39 15 0.63 3 0.58
30 0.30 20 0.60 4 0.49
40 0.31 25 0.77 5 0.36
50 0.31 30 0.82 6 0.31
60 0.29 7 0.47
70 0.27 8 0.37

43. Simulation results for the
three districts of IGP’s at
Biomass accumulated in the tree/crop
components and carbon sequestered
under existing AFS
three districts of IGP’s at
a glance
under existing AFS
Sultanpur
(6.14 trees/ha)
Ludhiana
(37.95 trees/ha)
Dinajpur
(6.20 trees/ha)
Tree Biomass (above and Baseline 2 56 2 88 2 45
Tree Biomass (above and
below ground )
Mg DM ha‐1
Baseline
Biomass
2.56 2.88 2.45
Simulated 8.24 4.67 8.22
Total Biomass (tree+
crop) Mg DM ha‐1
Baseline 11.14 25.97 12.10
Simulated 17 05 28 41 17 59
crop) Mg DM ha 1 Simulated 17.05 28.41 17.59
Soil carbon
(Mg C ha‐1)
Baseline
C b
8.13 9.12 8.16
Simulated 8.63 24.51 9.28
Biomass carbon
(Mg C ha‐1)
Baseline 4.92 11.21 5.33
Simulated 7 75 12 45 8 00
Carbon
(Mg C ha 1) Simulated 7.75 12.45 8.00
Total carbon
(biomass + soil)
(Mg C ha‐1)
Baseline 13.05 20.43 13.49
Simulated 16.38 36.96 17.28
Net carbon sequestered in agroforestry
Net carbon sequestered in agroforestry
systems over the simulated period of thirty
years
(Mg C ha‐1) Carbon
3.33 16.53 3.79
Estimated annual carbon sequestration sequestered
Estimated annual carbon sequestration
potential of agroforestry system in different
districts of Indo‐Gangetic Plains
(Mg C ha‐1yr‐1)
0.111 0.551 0.126

44. Location Agroforestry
System
Tree species No. of
tree per
hectare
Age (year) CSP
(Mg C ha‐1yr‐1)
References
SBS Nagar,
Punjab
Agrisilviculture P. deltoids 740 7 9.4 Chauhan
et al. 2010
Dehradun, Silviculture E. tereticornis 2500 3.5 4.4 Dhyani
Uttarakhand et al. 1996
2777* 2.5 5.9
Kurukkhetra,
Haryana
Silvipasture A. nilotica 1250 7 2.81 Kaur
et al. 2002
D. sissoo 1250 7 5.37
P juliflora 1250 7 6 5
P. juliflora 1250 7 6.5
Chandigarh Agrisilviculture L.
leucocephala
10666 6 10.48 Mittal and
Singh 1989
Tripura** Silviculture T. grandis 444 20 3.32 Negi
et al. 1990
G. arborea 452 20 3.95
Tarai central
d i i **
Silviculture T. grandis 570 10 3.74 Negi
l
devision **
Uttarakhand
et al. 1995
500 20 2.25
494 30 2.87
Jhansi, Uttar
Pradesh
Agrisilviculture A. procera 312 7 3.7 Ramnewaj
et al 2008
Pradesh et al. 2008
Jhansi, Uttar
Pradesh
Agrisilviculture A. pendula 1666 5.3 0.43 Rai
et al. 2002

45. Location Agroforestry
System
Tree species No. of tree
per hectare
Age (year) CSP
(Mg C ha‐1yr‐1)
References
Jhansi,
Uttar Pradesh
Silviculture A. procera 312 10 1.79
A. amara 312 10 1.00
Rai et al. 2000
A. indica 312 10 0.72
A. pendula 312 10 0.95
D. sissoo 312 10 2.55
D. cinerea 312 10 1.05
E officinalis 312 10 1 55
E. officinalis 312 10 1.55
E. tereticornis 312 10 0.81
H. binata 312 10 0.58
L. leucocephala 312 10 1.62
M. azaderach 312 10 0.49
T j 312 10 0 99
T. arjuna 312 10 0.99
Hydarabad,
Andhra Pradesh
Silviculture L. leucocephala 2500 9 10.32
E. camaldulensis 2500 9 8.01
D. sissoo 2500 9 11.47
A. lebbeck 625 9 0.62
Rao et al.
2000
D. strictus 2500 9 0.58
A. albida 1111 9 0.82
A. tortilis 1111 9 0.39
A. auriculiformis 2500 9 8.64
A indica 625 9 0 72
A. indica 625 9 0.72
A. nilotica 1111 9 0.77
T. indica 1111 9 0.43
Hydarabad, Andhra
Pradesh
Agrisilviculture L. leucocephala 11111 4 2.77 Rao et al.
1991
6666 4 1.90
** hh h l l b d
Raipur, ** Chhattisgarh Agrisilviculture G. arborea 592 5 3.23 Swami and
Puri 2005
Coimbatore, ** Tamilnadu Agrisilviculture C. equisetifolia 833 4 1.57 Viswanath et
al. 2004
Kerala Home garden Mixed tree spp. 667 71 1.60 Saha et al.

46. Observed vs. CO2FIX simulated biomass for the independent validation data set along
with the prediction bias curve (predbio: modelled biomass, obsbio:observed biomass,
linfit: linear regression line fitted on modelled and observed biomass, resid:
g f ,
residual/error/bias in estimation)

47. Using paired t‐test for evaluating the significance of case‐wise differences between
the observed and CO2FIX modelled biomass for the validation data set (pred:
modelled biomass obs:observed biomass)
modelled biomass, obs:observed biomass)
The values of the t‐statistic comes out
to be 2.14 with p‐value as 0.0679,
to be 2.14 with p value as 0.0679,
indicating thereby that the differences
between the observed and the
modelled biomass are not significant at
5% l l f i ifi
5% level of significance.
The average value of the percent bias in prediction was 5.66%.

48. Generalized stem volume equations are used for
Simulating CSP of AFS using CO2FIX model
Simulating CSP of AFS using CO2FIX model
This rate of decomposition is
influenced by climatic factors
viz temperature and rainfall
Simulating the effect
of temp and rainfall
on
on
Carbon Sequestered

50. N
N
A
A
H
H K
K
N
N
A
A
H
H K
K
O
OU
U