MANUAL FOR ESTIMATION OF GHG ... - ksdl.karnataka.gov.in

MANUAL FOR ESTIMATION OF GHG REMOVALS BY FORESTRY ACTIVITIES

competing uses or if leakage emerges after a project has begun, steps can be taken to mitigate it or to revise net carbon estimates. Strategies have emerged from pilot projects and they include:

Providing socio-economic benefits to local people that create incentives to maintain the project and its carbon benefits, and Using transferable technologies that help avoid leakage because they allow project benefits

to be duplicated outside project boundaries (Brown et al., 1997). The following leakage tree (Figure J.1) identifies whether leakage is likely to occur and what form leakage might take.

Figure J.1: Decision tree for identifying leakage

J.3 Methods for Estimation of Leakage of Carbon Benefits The method and approach to be adopted for estimating leakage will depend on the causes of leakage. The focus here is on changes in aboveground biomass stock. Two approaches for understanding land use pattern and dependence of communities on the land demarcated for the project are, i) compilation of historical records, and ii) Participatory Rural Appraisal.

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PART - I

Compilation of records Participatory Rural Appraisal (PRA) Obtain records of past land use, land conversion and felling from the forest department, land survey books and maps, satellite imageries

Procure village level maps

Compile data Contact local village body or leader and arrange for a meeting with local stakeholders, especially village elders

Validate records obtained through field visits and group discussions

Obtain information on land use pattern and extent of conversion from local stakeholders

Plot a graph indicating trends in land use and land use change

Identify locations of biomass extraction, within and outside project boundary

Below we outline steps to be adopted for estimating leakage resulting from biomass extraction and land conversion. Leakage due to biomass extraction - Non-sustainable extraction from outside the project boundary as a result of project activities leads to leakage of carbon benefits. This requires estimation of carbon stocks and following are the steps to be adopted. Step 1: Procure land use maps Step 2: Locate land use systems currently subjected to biomass extraction Step 3: Estimate and locate on map area likely to be subjected to biomass extraction outside the project boundary in different land use systems Step 4: Estimate the extent of land likely to be subjected to extraction of biomass, outside the project boundary due to project activities and regulations using PRA approach Step 5: Estimate carbon stock for ‘Base-year’ using ‘Plot method’ in; i) areas being subjected to biomass extraction and ii) areas not subjected to biomass extraction Step 6: Estimate the net loss of carbon stock (in tC/ha), using carbon stock estimates of ‘Base-year’ in; i) areas subjected to biomass extraction and ii) areas not subjected to biomass extraction Step 7: Estimate leakage or aggregate carbon emission using area data obtained through PRA and net carbon stock loss obtained through field studies

Leakage due to land conversion - To estimate the quantity of carbon leakage from land conversion, it is necessary to estimate the ‘Base-year’ C-stock in different land use systems. Step 1: Estimate area under different land use in ‘Base-year’ through land survey Step 2: Estimate carbon stock in different land use systems using ‘plot method’ for i) areas subjected to conversion and ii) areas not yet subjected to conversion Step 3: Estimate the potential rates of land conversion of different land use systems outside the project boundary through PRA Step 4: Estimate net loss of carbon using estimates of carbon stock for ‘Base-year’ for i) areas subjected to conversion and ii) areas not yet subjected to conversion Step 5: Estimate leakage or aggregate carbon emission using area data obtained through PRA and net carbon stock loss obtained through field studies

EQUATION-J1

∑=

+=n

iiiii CBCALeakage

1

where: Ai = Area converted in land use system ‘i’ to ‘n’ Bi = Area subjected to biomass extraction for land use system ‘i’ to ‘n’

Ci = Carbon stock change per ha for land use system ‘i’ to ‘n’

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K ESTIMATING NET ANTHROPOGENIC GHG REMOVALS BY SINKS

“Net anthropogenic greenhouse gas removals by sinks” is the actual net GHG removals by sinks minus the baseline net greenhouse gas removals by sinks minus leakage. The net anthropogenic GHG removals by sinks is the actual additional carbon sinks due to the project activity. Methods to estimate baseline GHG, actual GHG removal by sinks due to project activity and leakage is described in Sections H, I and J, respectively. Estimation of net anthropogenic GHG removal by sinks is as follows: Net anthropogenic GHG removals by sinks (tCO2) = (Actual net GHG removals by sinks) - (Baseline GHG removals by sinks) - (Leakage)

EQUATION-K1 Net anthropogenic GHG removals by sinks (tCO2) ∆Cco2 = [CPL-CBL] – Leakage

where: CPL = Actual net GHG removals by sinks (tCO2) for the project area from Equation I1 CBL = Baseline GHG removals by sinks (tCO2) for the project area from Equation H1 Leakage from Equation J1

Net GHG removals by sinks for a selected period:

∆Cnet = ∑n

1 [(∆Cco2)time 1 + (∆Cco2)time 2 +……. (∆Cco2)time n

where: ∆Cnet (tCO2/ha)= Net anthropogenic GHG removals by sinks for the selected period

∆Cco2 = Net anthropogenic GHG removals by sinks at time ‘i’ to ‘n’ Model approach Peer-reviewed simulation models (e.g., CO2Fix — Masera et al., 2003; CENTURY—Parton et al., 1987; PROCOMAP-Ravindranath et al., (2005) or a locally developed model) project the changes in carbon stocks of components to be measured in the project case in each land-use category over time, and in some cases, non-CO2 GHG emissions too. It is recommended that these models be used to simulate changes in the selected carbon stocks and non-CO2 greenhouse gas emissions without the project activity at the start of the project. The selected carbon pools and non-CO2 greenhouse gases are measured and monitored over time in the control areas. Data from the control areas can also be used in combination with the models in the previous step to improve the simulation results.

41

PART - I

L CONSIDERATIONS AND FREQUENCY FOR THE MONITORING PLAN

The monitoring plan consists of measurements of various parameters that determine the net GHG removal by sinks due to the project activity and emissions of non-CO2 greenhouse gases over time. Monitoring plan depends on the project area, which could be one contiguous parcel consisting of few land owners or small land parcels with many land owners. Each parcel of land cannot be monitored and it is essential to develop indicators that can be monitored at the parcel and project level. Monitoring the changes in carbon stocks and non-CO2 greenhouse gas emissions and removals when projects are constituted by multiple small-scale landholders will require monitoring systems at project as well as parcel level (IPCC GPG, 2003): Project level: For each activity to be implemented within the project area, the following needs to be developed:

A technical description; management objectives; the species; the soil, climatic and vegetation conditions suitable for the activity; the expected inputs in terms of materials and labour; and the expected outputs in terms of growth and yield of products. Prepare ready tables regarding measured indicators at the parcel level. For example DBH,

height, etc. to estimate carbon stocks. Establish a number of sample plots within the project area to maintain and improve the

calibration of these tables. Each technical description should also include a set of parameters used to determine the

baseline carbon stocks, against which the carbon uptake is to be measured. A similar set of indicators that are readily measured at the plot level should be tabulated

against baseline carbon stocks. Parcel level: Within each parcel the following measurements can then be taken:

Cross-check to determine whether the activity implemented in the parcel falls within the parameters set out in the technical description (e.g., correct species, planting density, climate, etc) Baseline indicators Activity indicators

The changes in carbon stocks are then estimated with reference to the tables in the relevant technical descriptions. Quality assurance procedures (Section M) should examine the data collection procedures at both levels within such projects.

L.1 Frequency of Carbon Monitoring The frequency of monitoring should take into consideration the carbon dynamics of the project and costs involved. In the tropics, changes in the carbon stock in trees and soils in an afforestation/reforestation project can be detected with measurements at intervals of about 3 years or less. In the temperate zone, given the dynamics of forest processes, they are generally measured at 5-year intervals (e.g., many national forest inventories). For carbon pools that respond more slowly, such as soil, even longer periods could be used. Thus, it is recommended that for carbon accumulating in the trees, the frequency of monitoring should be defined in accordance with the rate of change of the carbon stock, and be in accordance with the rotation length (for plantations) and cultivation cycle (for croplands and grazing lands). Some of the indicators to be monitored along with key parameters and frequency of monitoring are listed in Table L.1.

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Table L.1: Frequency of monitoring of key parameters and indicators for ecological, environmental and socio-economic impact assessment

Indicator Parameter Method Frequency

Number of seedlings - Survival rate Quadrats - counting Annual for initial 3 years

DBH and height Basal area - Biomass growth Quadrats - measurement

3-5 years (depending on forest type)

Soil organic carbon - Soil carbon Field methods Soil sampling Laboratory estimation

5 years

Biodiversity - Number of species/ha Quadrat 3-5 years (depending on forest type)

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PART - I

M QUALITY ASSURANCE AND QUALITY CONTROL PLAN The quality assurance (QA) and quality control (QC) steps provided by GPG (2003) should be followed. The plan should become part of project documentation and cover procedures as described below: Step 1: Collect reliable field measurements

• Develop Standard Operating Procedures (SOPs) for each step of the field measurement, which should be adhered to at all times

• Field-team members should be fully cognisant of all procedures and the importance of collecting data as accurately as possible

• Field teams should install test plots if needed in the field and measure all pertinent components using the SOPs

• All field measurements should be checked by a qualified person in cooperation with the field team and correct any errors in techniques

• A document should be filed with the project documents that show that these steps have been followed

• The document should list all names of the field team and the project leader should certify that the team is trained.

Step 2: Verify methods used to collect field data

At the end of the field work, check independently 10-20% of the plots Re-measure independently every 8-10 permanent plots, compare the measurements to check

for errors and resolve, correct and record the errors Express errors as a percentage of all plots that have been rechecked to provide an estimate

of the measurement error. Step 3: Verifying data entry and analysis techniques

• Reliable carbon estimates require proper entry of data into the data analyses spreadsheets. Possible errors in this process can be minimised if the entry of both field data and laboratory data are reviewed using expert judgement

• Comparison with independent data should be taken up to ensure that the data are realistic • Communication between all personnel involved in measuring and analysing data should be

used to resolve any apparent anomalies before the final analysis of the monitoring data is completed

• If there are any problems with the monitoring plot data that cannot be resolved, the plot should not be used in the analysis.

Step 4: Data maintenance and archiving

Data archiving should take several forms and copies of all data should be provided to each project participant Copies (electronic and/or paper) of all field data, data analyses, and models; estimates of the

changes in carbon stocks and non-CO2 greenhouse gases and corresponding calculations and models used; any GIS products; and copies of the measuring and monitoring reports should all be stored in a dedicated and safe place, preferably offsite The electronic copies of the data and report be updated periodically or converted to a format

that could be accessed by any future software application. If after implementing QA/QC plan, it is found that targeted precision level is not met, then additional field measurements need to be conducted to achieve the targeted precision level.

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N DATA MAINTENANCE AND STORAGE Forestry projects are of relatively long-term nature. Hence data maintenance and storage is an important component of the project. Data archiving should take several forms and copies of all data should be provided to each project participant. Maintenance of information system:

In order to ensure integrity of data over long periods, only reputable organizations with fully audited balance sheets and a history of either rural development activity or afforestation activity or other public projects involving the management of data for large numbers of families or landholdings should be considered as project participants for forestry projects Either a UNIX based or WINDOWS ACCESS DATABASE or other computerized data

management system must be used to record the information on the basis of both project and parcel level The information regarding current and historical land use patterns and system for land use

classification for the project area should be collected from reliable sources i.e. government records, GIS, etc. and archived. Depending on the reliability of the data supplementary information may have to be collected The records of sampled data for biomass and soil organic carbon should be documented in a

way to ensure consistency of time series data. The methods for interpolating of samples and years should be done using spreadsheets The field data at parcel level consisting of various sizes and types has to be aggregated into

homogenous groups and estimations done for each of the stratum to provide the final comprehensive monitoring report.

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PART - I

O UNCERTAINTY REDUCTION To reduce uncertainty, it is essential to derive confidence intervals by applying a quantitative method to existing data. Confidence intervals at given confidence levels provide a minimum basis for a simple quantitative estimate of uncertainty. To remain consistent with GPG (2000), uncertainties should be estimated at 95% confidence limits. Uncertainty arises due to sampling, measurement and model error. The following table (Table O.1) can be the suggested allowable limits for measurement error in permanent plots. Table O.1: Allowable limits for measurement error in permanent plots

Measurement Allowable error Missed or extra trees No error within the plot Tree species or groups No error Breast height ±5 cm of the true height (1.3 m) DBH ±0.1 cm or 1% whichever is greater Circular plot radius ± 1% of horizontal Source: MacDicken, 1997 Determination of soil organic carbon has great uncertainty. The sources of uncertainty in estimating CO2 emission/removal from soils, characteristics and treatment is given in Table O.2. Table O.2: Sources of uncertainty in estimating CO2 emission/removals from soils

Uncertainty source Characteristics Treatment

Lack of proper stratification

Land use not stratified according to variables that most contribute

to overall variability

Enhance the power of the sampling design through improved stratification

Bulk density (BD)

Bulk density not measured in all sampling sites, inaccurate bulk density values, especially in compact or dense sub-soils

Use additional data from literature or databases to identify systematic error in BD and supplement missing data, by carrying out representative measurements

Coarse fragments

No assessment of the volume or mass of coarse fragments

Use additional data from literature or databases to identify systematic error in coarse fragment; calibrate and standardize the assessment of the coarse fragment content during sampling campaigns

Carbon concentration

Analytical methods for carbon analyses have changed

Avoid changing analytical methods if possible; develop correction factors from comparative lab studies, or published studies

Source: IPCC GPG, 2003

O.1 Calculating Uncertainty There are two methods for calculating the total uncertainty for a project activity. The first method uses simple error propagation through the root of the sum of the squares of the component errors. The second method uses Monte Carlo simulations to propagate errors. The first method, which is simple to use is described here. The overall uncertainty for actual net GHG removals by sinks can be assessed as follows (IPCC GPG, 2003):

46


222

21 ... ntotal UUUU ++=

where: Utotal = percentage uncertainty in the product of the quantities (half the 95% confidence interval divided by the total, expressed as % Ui = percentage uncertainties associated with each of the quantities, i = 1, …, n

Step 1: The plot level results of increment of biomass for living and standing dead trees, above- and belowground in permanent plots are averaged to give mean and 95% confidence intervals for the stratum. Step 2: Where temporary plots are used for trees, or the pools in soils, lying dead wood, forest floor, and non-tree vegetation are included the uncertainty has to be calculated differently. The confidence interval is calculated as:

22

21 %95%95%95 TimeTime ClClClTotal +=

where: [95%CItime1] = 95% confidence interval for time 1 and [95%CItime2] = 95% confidence interval for time 2. Step 3: The total confidence interval is calculated as follows:

22222 %95%95%95%95%95%95 NTVFFDDWsoilveg CICICICICICITotal ++++=⋅⋅

where: [95%CIveg] = 95% confidence interval for vegetation, [95%CIsoil] = 95% confidence interval for soil etc. DDW = lying dead wood, FF = Forest floor, NTV = non-tree vegetation. Step 4: Ideally, the baseline will also have a 95 % CI in which case the confidence interval after the

subtraction of means will equal: 22 %95%95%95 BaselineStocksCarbon CICICI +=⋅⋅ ⋅Total

Step 5: If the project has multiple strata then the new confidence interval for the combined strata would be estimated as follows:

222

21 %95%95%95%95 snss CICICICITotal ⋅⋅⋅⋅⋅+=⋅⋅

where: [95%CIs1] = 95% confidence interval for stratum 1, stratum 2, etc. for all strata measured in the project. Step 6: Finally the total uncertainty in carbon stocks per unit area is then multiplied by the area of the project or entity to produce an estimate of the total change in carbon. Step 7: The total is then converted to tons of CO2 equivalent by multiplying by 3.67

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PART - I

P APPENDIX Appendix P.1: Examples of generic aboveground biomass estimation equations for tropical forest types

Forest type Equation R2/

sample size

DBH range (cm)

Moist hardwoods Y= EXP[-2.289+2.694LN(DBH)-0.021(LN(DBH))2] 0.98/226 5-148 Wet hardwoods Y= 21.297- 6.953(DBH)+ 0.740(DBH)2 0.92/176 4-112 Pines* Y= 0.887+[(10486(DBH)2.84/(DBH2.84)+376907] 0.98/137 0.6-56 Source: GPG, 2003, *also applicable to temperate pines, Y= dry biomass in kg/tree; DBH= diameter at breast height; LN= natural log; EXP= "e raised to the power of", Y= biomass in kg/tree; HT= height of trunk (m); LN= natural log Appendix P.2: Examples of regression equations for root biomass estimation in different forest types

Forest type Equation Temperate BGB = exp (-1.0587 + 0.8836 x ln AGB + 0.2840) Tropical BGB = exp (-1.0587 + 0.8836 x ln AGB)

All forests BGB = exp (-1.085 + 0.9256 x ln AGB) BGB = exp (-1.3267 + 0.8877 x ln AGB) + (0.1045 x ln age)

BGB = belowground biomass in tonnes/hectare and AGB = aboveground biomass in tonnes/ha Appendix P.3: Default values for parameters

FracBURN 0.25 in developing countries and 0.10 or less in developed countries (kg N/kg crop-N) FracR 0.45 kg N/kg crop-N FracFUEL 0.0 kg N/kg N excreted FracGASF 0.1 kg NH3-N + N)x-N/kg of synthetic fertilizer N applied FracGASM 0.2 kg NH3-N + NOx-N/kg of N excreted by livestock FracNCRBF 0.03 kg N/kg of dry biomass FracNCR0 0.015 kg N/kg of dry biomass FracGRAZ Country estimate Appendix P.4: Tentative default values for nitrogen excretion per head of animal per region (kg/animal/yr)

Regions Non-dairy cattle

Dairy cattle Poultry Sheep Swine Other

animals

North America 70 100 0.6 16 20 25 Western Europe 70 100 0.6 20 20 25 Eastern Europe 50 70 0.6 16 20 25 Oceania 60 80 0.6 20 16 25 Latin America 40 70 0.6 12 16 40 Africa 40 60 0.6 12 16 40 Near East & Mediterranean 50 70 0.6 12 16 40 Asia and Far East 40 60 0.6 12 16 40 Source: Revised IPCC 1996 guidelines

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Appendix P.5: Enteric fermentation emission factors (Kg per head per year)

Livestock Developed countries Developing countries Buffalo 55 55 Sheep 8 5 Goats 5 5 Camels 46 46 Horses 18 18 Mules and Asses 10 10 Swine 1.5 1.0 Poultry Not estimated Not estimated All estimates are ± 20% Source: Revised 1996 IPCC Guidelines for National GHG Inventories Reference Manual (Volume 3)

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PART - I

Q DATA FORMATS Q.1 General Site Description and Land Use History FIELD SHEETS AND APPENDICES A1

Use this form to record general site characteristics for the initial site condition

1. Date: dd/mm/yyyy

2. Type of land: Wasteland/Degraded forest land/fallow land/others

3. Location: ________________________________________________________________

4. Land title details: __________________________________________________________

5. Reference location: Easting: ______________________E Northing ________________N

6. Datum used on map: Map zone: __________________ (refer to relevant topographic maps)

6. Assessing organisation: ______________________________________________________

7. Team members: ____________________________________________________________

8. Time spent overall on initial condition assessment: ____________________ (person hours)

9. Average annual rainfall: ________________________________________________ (mm)

10. Previous land use history: ___________________________________________________

Note significant land-use or vegetation changes and when they occurred (e.g. removal of

native vegetation or woody weeds, cropping, fertiliser, pasture improvement)

11. Current land-use: __________________________________________________________

16. Other comments on the site: _________________________________________________

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Q.2 Data format for tree (Stems with GBH >10 cm are considered trees)

METHOD: __________________ SIZE OF THE PLOT: _____ Length X _____ Breadth (In Mts) Or _____ M (Radius, If Circular Plot) NO. OF PLOTS: __________ TOTAL AREA SAMPLED: _______ Sq.mts Location: Date of measurement: Land use system: Sub-strata: Tree plot no: Team members: Time in: Time out: S. No Species

(1)

Tree number

(2)

Stem number (including dead

stem) (3)

GBH (cm)

(4)

Height (m)

(5)

Planted or regenerated

(6)

Remarks

(7) 1 2 3 4 5 6 7 GBH: Girth at breast height (130 cm above ground); For small trees, DBH (diameter at breast height) can be taken at 130 cm above ground. Q.3 Data format for shrub quadrats (young trees or seedlings with < 5 cm DBH or ___ GBH)

Location: Date of measurement: Area of plot: Land use system: Tree plot no: Shrub plot no:

Diameter (cm) S. No.

Species DBH1 DBH2 DBH3

Height (m) Biomass – Fresh weight (kg)

1 2 3 4 5

Q.4 Data format for herb plots

Location: Date of measurement: Area of plot: Land use system: Forest Tree plot no: Shrub plot no: Herb plot no:

Species No. of plants Fresh weight (kg)

Notes: Fresh weight; taken after harvesting the herb plants in herb plot

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PART - I

Q.5. Data Format for woody litter

In tree quadrat, estimate kgs of woody litter - fallen twigs, branches etc. Collect all fallen twigs and branches and take the fresh weight.

Quadrat Weight of woody litter (kgs) 1. 2. 3. 4.

Note: If there is a fallen tree; record the length and diameter to estimate the volume Q.6. Household Questionnaire form for collecting information on leakage due to project activity

Name of the Village Name of the Household Occupation (Main) Land holding (in acre / ha /or any local unit)

a. Irrigated: b. Rainfed: c. Others: TOTAL: _____________

Do you use fuelwood for household requirements? Yes / No

If yes, what is the total quantity required per season / year / month / day?

_________ kg / ton / cart loads or cycle loads?

How frequently do you go for fuelwood collection?

No. of trips _____ / week (or) ____ / month (or) _____ / season (rainy, summer)

What % of annual fuelwood used comes from

a. Degraded commons (proposed for the project): b. Natural forest: c. Plantations: d. Agricultural lands: e. Other sources (specify):

Do you collect small timber or poles for household requirements? A 1 Yes / No

If yes, where do you collect? Degraded commons / Plantation / Forest / Others What % of small timber/poles comes from

a. Degraded commons (proposed for the project)(%): b. Natural forest (%): c. Plantations (%): d. Other sources (%):

What quantity of small timber/poles is gathered every year?

______ No. of poles

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R REFERENCES

1. Avery and Burkhart, 1983. Forest Measurements, 3rd edition, Eds. T.E. Avery and H.E. Burkhart (New York: McGraw-Hill, 1983).

2. Brown et al., 2000. Project Based Activities. In: Land Use, Land-Use Change and Forestry. Special Report of the Intergovernmental Panel on Climate Change Robert T. Watson, Ian R. Noble, Bert Bolin, N. H. Ravindranath, David J. Verardo and David J. Dokken (Eds.).

3. Brown, P. 1998. Climate, Biodiversity and Forests. Issues and Opportunities Emerging from the Kyoto Protocol. World Resources Institute, Washington, DC.

4. Brown, P., Cabarle, B. and Livernash, R. 1997. Carbon Counts: Estimating Climate Change Mitigation in Forestry Projects. World Resources Institute, Washington, DC.

5. Brown, S. 1997. Estimating Biomass and Biomass Change of Tropical Forests: A Primer. UN FAO Forestry Paper 134, Rome. 55 pp.

6. Brown, S., A. J. R. Gillespie and A. E. Lugo, 1989. Biomass estimations for tropical forests with applications to forest inventory data, Forest Science, 35 (4): 881-902.

7. Brown, S., J. Sathaye, M. Cannell, and P. Kauppi. 1996. Management of forests for mitigation of greenhouse gas emissions. Chapter 24 in R. T. Watson, M.C. Zinyowera, and R.H. Moss (eds.), Climate Change 1995: Impacts, Adaptations and Mitigation of Climate Change: Scientific-Technical Analyses. Contribution of Working Group II to the Second Assessment Report of the Intergovernmental Panel on Climate Change, Cambridge University Press, Cambridge and New York.

8. Cairns, M. A., S. Brown, E. H. Helmer, and G. A. Baumgardner. 1997. Root biomass allocation in the world’s upland forests. Oecologia 111: 1-11.

9. Dawkins, H.C. 1957. Some results of stratified random sampling of tropical high forest. Seventh British Commonwealth Forestry Conf. Item 7 (iii).

10. GPG, 2000 http://www.ipcc-nggip.iges.or.jp/public/gpglulucf/gpglulucf.htm

11. GPG, 2003 Good Practice Guidance for Land Use, Land-Use Change and Forestry (Eds: Jim Penman, Michael Gytarsky, Taka Hiraishi, Thelma Krug, Dina Kruger, Riitta Pipatti, Leandro Buendia, Kyoko Miwa, Todd Ngara, Kiyoto Tanabe and Fabian Wagner). Institute for Global Environmental Strategies (IGES), Japan for the Intergovernmental Panel for Climate Change.

12. IPCC (1996) Land Use Change and Forestry, In: Revised 1996 IPCC-Guidelines for National Greenhouse Gas Inventories: Reference Manual. Intergovernmental Panel on Climate Change.

13. Kauppi, P. and Sedjo, R. (2001) Technical and Economic Potential of Options to Enhance, Maintain and Manage Biological Carbon Reservoirs and Geo-Engineering, In: Climate Change 2001: Mitigation, Intergovernmental Panel on Climate Change, Cambridge University Press, Cambridge, UK.

14. Kirschbaum,. M. U. F., Bullock, P., Evans, J. R., Goulding, K., Jarvis, P.G., Noble, I.R., Rounsevell, M., Sharkey, T.D., 1996. Ecophysiological, Ecological, and Soil processes in terrestrial ecosystems: A Primer on general concepts and relationships. In: Climate change 1995, Impacts, Adaptation and Mitigation of climate change: Scientific-Technical Analyses. Cambridge University Press.

15. MacDicken K.G. (1997). A Guide to Monitoring Carbon Storage in Forestry and Agroforestry Projects. Winrock International, Arlington, VA, USA, 87 pp, available at: http://www.winrock.org/REEP/PDF_Pubs/carbon.pdf.

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PART - I

16. Masera O.R., Garza-Caligaris J.F., Kanninen M., Karjalainen T., Nabuurs G.J., Pussinen A., de Jong B.J., and Mohren F. (2003). Modeling Carbon Sequestration in Afforestation and Forest Management Projects: The CO2Fix V.2 Approach. Ecological Modelling 3237, pp. 1-23.

17. Noble I., Michael Apps, Richard Houghton, Daniel Lashof, Willy Makundi, Daniel Murdiyarso, Brian Murray, Wim Sombroek, and Riccardo Valentini. Implications of Different Definitions and Generic Issues, 2000 in Watson, R T., Noble, I R., Bolin, B., Ravindranath, N, H., Verardo, D, J., and Dokken, D J. (2000) Land-Use, Land-Use Change and Forestry, A Special report of the Intergovernmental Panel on Climate Change, Cambridge University Press, Cambridge.

18. Oren, R., D. S. Ellsworth, K. H. Johnsen, et al. 2001. Soil fertility limits carbon sequestration by forest ecosystems in a CO2-enriched atmosphere. Nature 411: 469-472.

19. Parton W.J., Schimel D.S., Cole C.V., and Ojima D.S. (1987). Analysis of factors controlling soil organic matter levels in Great Plains grasslands. Soil Science Society of America Journal 51: pp. 1173-1179.

20. Ravindranath N H., Murthy I. K., Sudha, P., Ramprasad V., Nagendra, M.D.V., Sahana, C.A., Khan, H. and Srivathsa, K.G. Methodological Issues In Forestry Mitigation Projects: A Case Study of Kolar District, Accepted for Publication in “Mitigation and Adaptation Strategies for Global Change”

21. Schimel, D., D. Alves, I. Enting, M. Heimann, F. Joos, D. Raynaud, T. Wigley, M. Prather, R. Derwent, D. Ehhalt, P. Fraser, E. Sanhueza, X. Zhou, P. Jonas, R. Charlson, H. Rodhe, S. Sadasivan, K.P. Shine, Y. Fouquart, V. Ramaswamy, S. Solomon, J. Srinivasan, D. Albritton, I. Isaksen, M. Lal, and D. Wuebbles, 1996: Radiative forcing of climate change. In: Climate Change 1995. The Science of Climate Change. Contribution of Working Group I to the Second Assessment Report of the Intergovernmental Panel on Climate Change [Houghton, J.T., L.G. Meira Filho, B.A. Callander, N. Harris, A. Kattenberg, and K. Maskell (eds.)]. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, pp. 65–131.

22. Sokal R.R. and Rohlf F.J. (1995). Biometry: the principles and practice of statistics in biological research. 3rd Edition. W. H. Freeman and Co., New York.

23. Timothy Pearson, Sarah Walker and Sandra Brown. (2005). Source Book for LULUCF Projects. Winrock International.http://carbonfinance.org/biocarbon/Router.cfm?Page=DocLib&Dtype=50

24. Watson, R, T., Noble, I, R., Bolin, B., Ravindranath, N, H., Verardo, D, J., and Dokken, D, J. (2000) Land Use, Land-Use Change and Forestry, A Special report of the Intergovernmental Panel on Climate Change, Cambridge University Press, Cambridge.

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MANUAL FOR ESTIMATION OF EMISSION REDUCTION IN BIOENERGY SECTOR

A INTRODUCTION The combustion of fossil fuels is the most significant source of global anthropogenic Green

House Gases (GHG) emissions and the combustion of fossil fuels for energy generation contributes nearly 40% of the total GHG emissions in the world. Fossil fuels like coal, diesel, kerosene, LPG used in the electricity generation, industrial use and domestic consumptions are the major source of GHG emissions. The GHG emission reduction projects including renewable energy like biomass based energy generation; fuel switches to replace the fossil fuels have tremendous potentialities in reducing the GHG emissions. The BERI project intends to bring about GHG emission reduction through fossil fuel substitution by bioenergy, namely

Utilization of Biogas for heating purpose Electricity for household lighting and irrigation set Methane emissions through waste management

To arrive at specific methodology for the BERI project, various methodologies were reviewed including the IPCC Guidelines, the GHG indicator: UNEP Guidelines for calculating GHG emissions for businesses and non-commercial organizations and Manual for calculating GHG benefits of GEF projects. In this section of the manual, efforts have been made to describe the methods to estimate the GHG emissions from various types of fuel types used in the energy production.

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PART II

B BROAD GUIDELINES TO MEASURE GHG EMISSIONS FOR BIOENERGY

PROJECT B.1 How to Calculate the GHG emissions from the fuel combustions for a bioenergy

project?

The flow chart showing the steps in calculating GHG emissions for a bioenergy project is given below

ba

ee

L

Define Project

boundary

Estimate seline of GHG

(without project scenario)

Total fuel consumption

Emission factor

Total GHG emission in baselineX =

Estimate mission of GHG

(with project scenario)


Emission factor

Total GHG emission in project scenarioX =

Estimate GHG

reductionsTotal GHG emission in

project scenarioTotal GHG emission in

baseline -

Total GHG emission reduction

=

Estimate eakage of GHG

in project scenario


Emission factor

Total Leakage of GHG in project scenarioX =

Estimate mission of GHG

(with project scenario)


Emission factor

Total GHG emission in project scenarioX =

Total Leakage GHG in project scenario-

B.2 Define Project Boundary

The project boundary is to be defined before the GHG estimations are carried out. Usually the project boundary is limited to the physical project activity. For bioenergy projects, the project boundary encompasses the physical, geographical site of the renewable generation source.

In case of BERI also, the project boundary encompasses the physical, geographical site of the renewable generation source.

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B.3 Estimation of Base line of GHG (without project scenario)

A baseline is the scenario that reasonably represents the anthropogenic emissions by source of GHGs that would occur in the absence of the proposed project activity. A baseline deemed reasonable represents the anthropogenic GHG emissions by sources that would occur in the absence of the proposed project activity. Different scenarios may have to be narrated as potential evolutions of the situations existing before the proposed project activity. The continuation of the current activity could be one of them. A base line methodology must confirm the following:

• Baselines should be precise transparent, comparable and workable, • Should avoid overestimation, • The methodology for determination of baseline should be homogeneous and reliable, • System boundaries of baseline should be clearly defined, • Role of externalities should be brought out (social, economical, and environmental), • Should include historical emission data –sets wherever available, • Lifetime of the project cycle must be clearly avoided.

For any GHG mitigation project, for the baseline estimation, the project proponent needs to calculate the GHG emissions from fuels used to meet the energy demand. Since there is no accurate data available on the fuel consumptions, the task of computing the emission is most cumbersome and challenging. In Indian situation, in a typical bioenergy project, the following types of energy consumptions can be seen.

• Electricity (lighting / irrigation), • Coal (cooking / cogeneration), • Wood (cooking / heating / brick making), • Kerosene (heating / lighting / cooking),

• Gas/Diesel (cooking / electricity generation),

• Dung Cakes / Bio-gas (cooking / heating).

B.3.1 Steps to estimate baseline GHG emissions

(a) Estimation of emission from the Grid. In India, as the major fossil fuel based energy is the electricity, the emissions from electricity needs to be estimated. This can be estimated in the following way.

( )GWh

factorEmissionGWhyelectricitfromestimationGHG ×=

For the electricity consumption estimation (GWh), data can be collected from the following source. • Utility provider. • Electrical bills. • Invoices for fuel deliveries. • Meter readings. • Gas bills.

• Pipeline measurements. • Energy management

software’s.

Most frequently, for a village, household surveys would be useful to retrieve the data from the above-mentioned sources.

The estimation of emission factor for “electricity from grid” needs to be carried out for different regions in the country as the emissions may vary. Region-wise emission may be estimated using a method-involving estimation of the average emissions of all the electricity generation plants excluding renewable energy emissions for the last three years and dividing it by the total electricity generation. The average emissions can be obtained as follows. - Operating margin plants include thermal, coal based co-generations, hydro, and

electricity imports from the national grid, excluding the renewable energy sources

- Build margin includes the average of 20% or 5 of the most recently established or 5 recent plants added to the expansion

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PART II

- The average of both operating margin and build margin gives the emission for the region or state.

For India, the default IPCC guidelines’ emission factor for electricity is 890 kg CO2 /MWh. For different regions in the country, the emission factors have to be estimated. For the BERI project the average emission factor has been estimated at 1072 kg CO2 /MWh.

(b) Combustion of fuels. To calculate GHG emissions from combustion of fuels, IPCC guidelines makes use of an activity statistics (eg. annual fuel consumption in tonnes) and an emission factor (tonnes of CO2 per tonne of fuel combusted). The non-electricity energy source emissions like kerosene, gas, wood and other types are to be estimated in the base line scenario by multiplying the quantity of fuels consumed with their corresponding emission factors.

( ) (∑ ×= factorEmissionConsumedFuelcombustionfuelfromestimationGHG )

Carbon dioxide has been taken as primary GHG gas for the estimating the total GHG emissions along with CH4 and N2O for estimating CO2 equivalent emissions from wood and dung cakes. The IPCC guidelines provide default values of emission factors for different fossil fuels. Some of the emission factors for various fuels are given in the Table B.1 below. The emission factors have been estimated for different countries.

Table B.1: Default values of fuels as per IPCC guidelines. Refined Petroleum Products

tCO2/ therm

tCO2/ litre

tCO2/ KWh

tCO2/ tonne

COAL (DEFAULT) 0.0003413 1.84 Gasoline 0.00222 0.0002496 3.07 Natural Gas 0.005919 0.0002020 2.93 Gas/Diesel Oil 0.00268 0.0002667 3.19 Residual Fuel Oil 0.00300 0.0002786 3.08 LPG 0.006654 0.00165 0.0002271 2.95 Jet Kerosene 0.00258 0.0002575 3.17 Shale Oil 0.0002218 2.61 Ethane 0.0002641 2.90 Naphtha 0.00224 0.0002905 3.27 Bitumen 0.0002641 3.21 Lubricants 0.00263 0.0003631 2.92 Petroleum Coke 0.0002641 3.09 Refinery Feedstock 0.0002641 3.25 Refinery Gas 0.007041 0.0002603 2.92 Other Oil Products 0.00254 0.0002641 2.92

Emission from the coal varies according to net calorific value (NCV), coal type, as well as from country to country. For India, the emission factor for coal is 1.53 tonnes of CO2 / tonne of coal. Non-carbon dioxide green house gases generated by fuel combustion are mainly methane (CH4) and nitrous oxide (N2O). Emissions of these gases are difficult to quantify and according to IPCC their warming contribution is probably minor, compared to that of CO2. However, the CO2 equivalent emissions from CH4 and N2O from wood and dung cakes need to be accounted for. Rough estimates of CH4 and N2O contributions from the combustion of coal, natural gas and oil were calculated to be in the region of 1%. Further, research will need to be done towards this issue. In the present case the methane emission arising out of the burning of the fuel wood has been calculated by using the IPCC default value. For BERI project the most frequently used fuels including coal, kerosene, diesel, dung cakes, biogas, LPG have been considered for the estimation and the emission factors for India have been taken for calculations.

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B.4 Estimation of the emissions in project scenario.

Bioenergy projects which are normally considered emission neutral do not have any emissions during the project as they are expected to use renewable energy sources. However, due to the following activities, emissions may occur which needs to be estimated:

(a) On site construction activity: Due to the setup / establishment of the plant there would be fossil fuel energy which needs to be estimated as done in the baselines.

(b) Transport of waste: In many of the bioenergy projects there would be use of waste or biomass for the plant through a transport system using fossil fuel that needs to be estimated as done for the baseline.

(c) In co-generation plants there will be fossil fuel usage which needs to be accounted during in emission estimation.

(d) Reduction in the GHG emission due to best practices are to be accounted. For example, in BERI case the use of drip irrigation plant is expected to reduce the GHG emission, which is accounted in reduction in electricity generation or usage.

B.5 Leakage.

Leakages of GHG emissions due to some of the project activities have an impact on areas outside the project and thus need to be accounted. For example, the use of biomass in the project area for electricity generation may result in non availability of biomass in the neighboring areas leading to increased felling outside the project area. The quantity of biomass over harvested multiplied by the emission factor will give leakage estimation.

B.6 Total GHG Emission reduction.

This may be calculated as follows.

leakagesscenarioprojectinEmissionEmissionBaselineGHGinduction −−=Re

B.7 Monitoring and validation.

The GHG emission reductions are to be monitored systematically using validated methodology. The reductions in emissions can be monitored using metered readings of energy consumption both at input and output sources. Logbooks, meter readings, accounts and other verifiable logbooks will be the basis for monitoring.

B.8 Assumption adopted in the BERI project

The following points were considered while developing the methodologies o The project boundary is taken as the physical, geographical site of the renewable generation

source (as per the Appendix B of the simplified modalities and procedures for small-scale CDM project activities for all Type I- Renewable Energy Projects)

o It is envisaged that entire electricity from the grid will be substituted with electricity from gasifiers in the project area.

o As per the “UNEP Guidelines for calculating GHG emissions for businesses and non-commercial organizations”, for India, the default emission factor for electricity mix is 890 tCO2/GWh. However, for this study, the emission factor for electricity mix for the Southern Grid was used as reference and the average of “approximate operating margin” and “build margin”, was calculated to arrive at the emission factor of 1072 tCO2/GWh.

o Drip irrigation introduced during the project intervention will be result in decrease in the consumption of electricity. This will be reflected in the amount of electricity consumed during the household survey.

o Carbon emissions are calculated for household cooking (heating) purposes for fossil fuels like kerosene, LPG, gas/diesel and coal. Within the energy module, carbon emissions due to biomass consumption is assumed to equal to its regrowth, hence not accounted. Also, for the BERI project the firewood/crops residues are from within the project area.

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PART II

o Non-carbon dioxide green house gases generated by fossil fuel combustion are mainly CH4 and N2O and according to IPCC their warming contribution is probably minor, compared to that of CO2. However, the CH4 and N2O emissions from the biomass based fuels like wood / wood waste, charcoal, and dung cakes need to be accounted for as per the IPCC guidelines. The default values for CH4 and N2O emission from burning of various fuels used in residential sector (1996 IPPC Guidelines) have been taken into account for baseline estimations.

o The CH4 and N2O emissions from the biogas plants are however not taken into account for two reasons, firstly CH4 is not released as it is but is converted to CO2 when burnt which in turn is of natural origin and secondly N2O release from Biogas plants is very miniscule.

o Fuel efficiency in the project area through improved chulhas during the project period will be captured by estimating the efficiency levels in the chulhas. This will be reflected in the decrease in quantity of firewood required and this saving of firewood has been accounted for in GHG emissions due to project activity.

60


C METHODOLOGY TO ESTIMATE BASELINE FOR BIOENERGY PROJECT For the activities to be carried out in the BERI project area, baseline methodology for the

following activities is discussed in this section Electricity from grid for household lighting and irrigation pump set Utilization of various fuels for cooking (heating) purpose (including kerosene, LPG,

dung cakes, coal, etc.)

C.1 Estimation of CO2 baseline emissions due to “electricity from grid” (without project scenario)

This CO2 baseline estimation is for supply of electricity from the grid. Following are the steps involved in the estimation of CO2 baseline emissions1.

Step 1: Estimate the “approximate operating margin” and the “build margin” 2 (Refer Annexure C1.) Note: Calculations for BERI project has already been carried out and given in Annexure C1

Step 2: Calculate the average emission factor (Refer Annexure C1) Note: Calculations for BERI project has already been carried out and given in Annexure C1

Step 3: Calculate the electricity supplied through grid to the project area Use Annexure C2 for filling in data from Taluka Panchayat

Or Use Annexure C3 for filling in data from Household survey

Or Use Annexure C4 for filling in data from Electricity Bills

Step 4: Calculate CO2 emissions due to electricity supplied through grid to the project area Use Equation C1 (given below) Alternatively use the Estimation Table C1 for calculating the emissions

EQUATION- C1 [ ]21072 COtEG EE ×=

EG = GHG emissions in the project area due to electricity from the grid [ ]2COt

EE = Total electricity from the grid [GWh] 1072 = Carbon emission factor calculated [tCO2/GWh] 3

C.2 Estimation of CO2, CH4, & N2O baseline emissions due to consumption of fuel for heating (without project scenario)

This baseline estimation of CO2, CH4, & N2O is for various fuels like kerosene, LPG, wood, dung, charcoal and biogas presently being used in the project area as household fuel consumption.

1 The baseline methodology is adopted from the AMS I-D of the Appendix B1 of the simplified modalities and procedures for small-scale CDM project activities 2 The KPTCL and the Southern Region’s grid is used as the reference region for estimating the current generation mix for BERI project 3 For the calculation of the baseline, the average of the “approximate operating margin” and the “build margin” of Southern Region’s grid was calculated to arrive at the emission factor of 1072 tCO2/GWh (Refer Annexure C1 for calculations)

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PART II

Following are the steps involved in the baseline emissions calculations for household fuel consumption4.

Step 1: Estimate the quantity of various fuels used by households in the project area through survey (Refer Section I for Sampling Strategy) (Refer Annexure C5. Fill in the data from household survey on monthly basis Add up for all the months to get the yearly fuel consumption in the project area for cooking purpose)

Step 2: Calculate the average emission factor for C, CH4, & N2O for each fuel type (Refer Annexure C6) Note: Calculations for BERI project has already been carried out based on the IPCC default values

Step 3: Calculate the C, CH4, & N2O emissions due to various fuels used in the households in the project area and derive the CO2 equivalent emissions Use Equation C2 (given below) Alternatively use the Estimation Table C2 for calculating the emissions. Add any other type of fuel which has not been included here

EQUATION-C2

( ) ( ) ( ) ( )( )

( ) ( ) ( ) ( )( )[ ]

( ) ( ) ( ) ( )( )[ ]310048.003.006.0023.0

216.30.65.49362.4

12448.4169.8657.8093.868

2222

4444

××+×+×+×+

××+×+×+×+

××+×+×+×=

OdNOchNOwNOcN

dCHchCHwCHcCH

cCgClCkCH

EEEE

EEEE

EEEEG

HG = GHG emissions in the project area due to consumption of fuel for cooking [ ] 2COt

kE = Consumption of kerosene in metric tonnes5

lE = Consumption of LPG in metric tonnes

gE = Consumption of gas/diesel in metric tonnes

cE = Consumption of coal in metric tonnes6

4 The baseline methodology is adopted from the AMS I-C of the Appendix B1 of the simplified modalities and procedures for small-scale CDM project activities. For renewable energy technologies that displace technologies using fossil fuels, the simplified baseline is the fuel consumption of the technologies that would have been used in the absence of the project activity times an emission coefficient for the fossil fuel displaced. IPCC default values for emission coefficients may be used. 5 Default values for carbon emission from burning of various fuels used in residential sector

Fuel Type Net Calorific Value1

Emission Factor2

Carbon Unoxidised3

Calculation Factor [B x C x D]

A B C D E Gas/Diesel Oil 43.3 20.2 0.99 865.9 Kerosene 44.75 19.6 0.99 868.3 LPG 47.31 17.2 0.995 809.7 Coal 16.454 25.85 0.98 416.8

kT

TJtCkT

TJ

1. IPCC Guidelines Vol. 2 Table 1-3 2. IPCC Guidelines Vol. 2 Table 1-2 3. IPCC Guidelines Vol. 2 Table 1-4 6 Default values for CH4 and N2O emission from burning of various fuels used in residential sector (1996 IPPC Guidelines)

Fuel Net Calorific Value

Emission Factors for CH4

in kg/TJ

Calculation Factor for CH4

B x C

Emission Factors for N2O in kg/TJ

Calculation Factor for N2O

B x E A B C D E F

Coal 16.454 300 4.9362 1.4 0.023 Wood / Wood Waste 15.0 300 4.5 4 0.06

TJ kT

kTT

62


wE = Consumption of wood / wood waste in metric tonnes

chE = Consumption of charcoal in metric tonnes

dE = Consumption of dung cakes in metric tonnes.

1244 = Conversion factor from Carbon to CO2

21 = Green House Warming Potential of methane 310 = Green House Warming Potential of nitrous oxide The subscript C is for carbon emissions CH4 is for methane emissions and N2O is for nitrous oxide emissions

C.3 Estimation of the total GHG baseline emissions (without project scenario)

Total GHG baseline emissions in the project area are due to electricity from grid and due to fuel consumption in households. Following are the steps involved in the total GHG baseline emissions calculations:

Step 1: Take the estimated CO2, emission due to electricity consumption from grid from Section C1 and CO2 (equivalent) emissions due to use of various fuels in the households from Section C2 in the project area and add the two. Use Equation C3 (given below)

EQUATION – C3

[ ]2COtGGG HEtotalB +=

totalBG = Total GHG emissions in the project area were the project to not take place

[ ]2COt

EG = GHG emissions in the project area due to electricity from the grid [ ] 2COt

HG = GHG emissions in the project area due to consumption of fuel for cooking

[ ]2COt

Step 2: Calculate the total CO2 equivalent emissions in baseline scenario. Use the Estimation Table C3 for calculating the emissions

Charcoal 30.0 200 6.0 1 0.03 Other Biomass & Wastes 12.0 300 3.6 4 0.048

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PART II

D METHODOLOGY TO ESTIMATE EMISSIONS DUE TO BIOENERGY PROJECT For the emission reduction activities to be carried out in the project area, the GHG emissions

that would occur due to project activities are to be estimated as outlined below. In the BERI project, the following activities are to be taken up which are expected to reduce GHG emissions by replacement of fossil fuels

Electricity generation from gasifier to replace grid supply Generation of biogas through biogas plants for cooking (heating) purpose

D.1 Estimation of CO2, CH4, & N2O emissions from the gasifier plant

The emissions from gasifiers include carbon emission from start up diesel used and some amount of methane and nitrous oxide are expected as emissions from wood / wood waste (IPCC Guideline, 1996).

Step 1: Estimate the diesel consumed by the gasifiers on monthly basis (Refer Annexure D1.)

Step 2: Calculate the Carbon emission factor for Diesel (Refer Annexure C6) Note: Calculations for BERI project has already been carried out and given in Annexure D1

Step 3: Estimate the wood consumed by the gasifiers on monthly basis (Refer Annexure D1.)

Step 4: Calculate the CH4, & N2O emission factor for Wood (Refer Annexure C6) Note: Calculations for BERI project has already been carried out and given in Annexure D2

Step 5: Calculate the CO2, and CO2 equivalent of CH4, & N2O emission factor for diesel and wood Use Equation D1 (given below) Use the Estimation Table D1 for calculating the emissions

EQUATION-D1

( ) ( )[ ] ( )[ ]31006.0215.412449.865 24 ××+××+

××= OwPNwPCHgPCEP EEEG

EPG = GHG emissions in the project area due to electricity from the gasifier [ ]2COt

gPE = Consumption of gas/diesel in metric tonnes7

wPE = Consumption of wood / wood waste in metric tonnes8

7 Default values for carbon emission from burning of various fuels used in residential sector


kTTJ

Emission Factor2

Carbon

Unoxidised3 Calculation Factor

[B x C x D]

A B C D E Gas/Diesel Oil 43.3 20.2 0.99 0.8659

TJtC

1. IPCC Guidelines Vol. 2 Table 1-3 2. IPCC Guidelines Vol. 2 Table 1-2 3. IPCC Guidelines Vol. 2 Table 1-4 8 Default values for CH4 and N2O emission from burning of various fuels used in residential sector (1996 IPPC Guidelines)

Fuel Net Calorific Value

Emission Factors for CH4 in kg/TJ


kT

B x C

Emission Factors for N2O in kg/TJ


kTT

B x E A B C D E F

Wood / Wood Waste 15.0 300 4.5 4 0.06

kTTJ

64



21 = Green House Warming Potential of methane 310 = Green House Warming Potential of nitrous oxide The subscript C is for carbon emissions CH4 is for methane emissions and N2O is for nitrous oxide emissions

D.2 To estimate emissions due to consumption of fuel for cooking with installation of Biogas plants

Emissions from the Biogas plant are the following

1. Methane (CH4) that is generated is collected and used as fuel. The fuel is combusted in household for heating purpose and gets converted into CO2. This CO2 is not taken into account as it is of natural and renewable origin.

2. Nitrous Oxide (N2O) emissions from the biogas plants. The N2O release from biogas plants is also not taken into account as it is negligible.

3. Methane (CH4) from the biogas slurry is emitted when the slurry is applied to the fields as compost. This emission is accounted in the sink estimations of LULUCF section.

For the BERI project, the emissions due to consumption of fuel for cooking with installation of Biogas plants is zero.

D.3 To estimate emissions due to installation of improve chullas for cooking

With improvised chullas being installed in the project area there would be saving in the quantity of firewood consumption, which would result in reduction in CO2 emissions.

D.4 To estimate the total emissions in presence of project

The total GHG emissions in the project area due to the project activity are due to emissions from gasifiers. Following are the steps involved in the total GHG emissions calculations in presence of project:

Step 1: Take the estimated CO2, emission due to electricity generation from gasifier from Section D1 and CO2 (equivalent) emissions due to use of various fuels in the households from Section D2 in the project area and add the two. Use Equation D3 (given below)

EQUATION-D3

[ ]2COtGGG HPEPtotalP +=

totalPG = Total GHG emissions in the project area during the project [ ]2COt

EPG = GHG emissions in the project area due to electricity from the gasifier [ ] 2COt

HPG = GHG emissions in the project area due to biogas [ ] 2COt

In this case BERI project the emissions from the biogas is zero

Step 2: Calculate the total CO2 equivalent emissions in project scenario. Use the Estimation Table D3 for calculating the emissions

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PART II

E METHODOLOGY TO ESTIMATE EMISSION REDUCTIONS IN ABSENCE OF

PROPOSED BIOENERGY PROJECT Emission reduction that would have occurred in the absence of the proposed bioenergy

project includes on-site and off-site emissions. Following are the emission reductions:

E.1 On-site emissions

E.1.1 Construction of gasifier

The first direct on-site emissions occur during the construction of gasifier. The total energy consumed in the form of electricity and diesel is a one time emission.

EQUATION-E1

[ ] ( )

××+×=

12449.8651072 dcggcgg EEG

gG = GHG emissions in the project area due to use of electricity and diesel for construction of the

gasifier [ ] 2COt

gcgE = Consumption of electricity for construction of gasifier in metric tonnes

dcgE = Consumption of gas/diesel for construction of gasifier in metric tonnes9

1072 = Carbon emission factor calculated [tCO2/GWh] 10


E.1.2 Storage of biomass

The storage of biomass could lead to emissions. The biomass used in the gasifier is the hardy dry variety that would not undergo any anaerobic digestion in the stipulated storage period (say six months of storage). Hence, no substantial emission of CH4 is anticipated and hence not accounted for.

E.1.3 Consumption of Electricity by the gasifiers Auxiliary consumption refers to the small portion of the generated electricity that is

consumed for own use, which is very small and can be safely not taken into account.

E.1.4 Use of grid electricity in case of maintenance / shut down of the gasifiers

The gasifier sub-project is envisaged to substitute grid power entirely and is a CO2 neutral biomass-based power plant designed to supply electricity to the grid. Therefore, no additional carbon emissions due to the project activity is expected to be generated within the project boundary. However, some emission may arise in case of total shut down of the gasifier and usage of grid power occasionally. Also, some small amount electricity may be used while maintaining the plant which needs to be accounted. This consumption can be reflected in the equation below

EQUATION-E2

[ ]1072×= gmgm EG

9 Default values for carbon emission from burning of various fuels used in residential sector


kTTJ

Emission Factor2

TJtC

Carbon Unoxidised3



1. IPCC Guidelines Vol. 2 Table 1-3 2. IPCC Guidelines Vol. 2 Table 1-2 3. IPCC Guidelines Vol. 2 Table 1-4 10 For the calculation of the baseline, the average of the “approximate operating margin” and the “build margin” of Southern Region’s grid was calculated to arrive at the emission factor of 1072 tCO2/GWh

66


gmG = GHG emissions in the project area due to use of electricity during maintenance and shut down of

the gasifier [ ] 2COt

gmE = Consumption of electricity during maintenance and shut down of gasifier in metric tonnes

1072 = Carbon emission factor calculated [tCO2/GWh] 11

E.1.5 Construction of biogas plant

The first direct on-site emissions occur during the construction of biogas plants. The total energy consumed in the form of electricity and diesel is a one time emission.

EQUATION-E3

[ ] ( )

××+×=

12449.8651072 dcbgcbb EEG

bG = GHG emissions in the project area due to use of electricity and diesel for construction of the

biogas plant [ ] 2COt

gcbE = Consumption of electricity for construction of biogas plant in metric tonnes

dcbE = Consumption of gas/diesel for construction of biogas plant in metric tonnes12 1072 = Carbon emission factor calculated [tCO2/GWh] 13


E.2 Off-site emissions

E.2.1 Transport of biomass:

Direct off-site emissions in the proposed project arise from transporting the biomass by tractor-trolleys. In the project area, in case the transport of the biomass is done using truck or tractors consuming fossil fuel then emissions need to be accounted for. However, on an average, the distance over which fuels have to be transported will be substantially larger for fossil fuel-fired power stations because of the larger distance to coal mines and ports than for the proposed projects. Therefore, transport emissions in the baseline will be larger than the transport emissions related to the proposed project. This also provides a conservative estimate of emission reductions. If the transportation is carried out using bullock carts or hand driven carts then also the emissions need not be accounted for.

E.2.2 Savings in electricity due to prevention of distribution and transmission losses

Saving in the electricity due distribution and transmission losses for the amount of electricity generated due to the project activity. However, because it forms only a small part of the total electricity consumption no leakage is taken into account.

E.3 Emission Reductions in Absence of Proposed Bioenergy Project

The total GHG emissions reduction in the project area in the absence of proposed project activity are due to the emissions from gasifiers. Following are the steps involved in the total GHG emissions calculations in presence of project:

11 For the calculation of the baseline, the average of the “approximate operating margin” and the “build margin” of Southern Region’s grid was calculated to arrive at the emission factor of 1072 tCO2/GWh

12 Default values for carbon emission from burning of various fuels used in residential sector Fuel Type Net Calorific Value1

kTTJ

Emission Factor2

TJtC

Carbon Unoxidised3 Calculation Factor [B x C x D]


1. IPCC Guidelines Vol. 2 Table 1-3 2. IPCC Guidelines Vol. 2 Table 1-2 3. IPCC Guidelines Vol. 2 Table 1-4 13 For the calculation of the baseline, the average of the “approximate operating margin” and the “build margin” of Southern Region’s grid was calculated to arrive at the emission factor of 1072 tCO2/GWh

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PART II

Step 1: Take the estimated CO2 emissions due to 1. Electricity and diesel consumption for construction of gasifier from Section E.1.1 2. Electricity used from grid during maintenance and shut down of gasifier from Section

E.1.4 3. Electricity and diesel consumption for construction of biogas plant from Section E.1.5

Add the three by using the Equation E4 (given below) EQUATION-E4

[ ]2COtGGGG bgmgER ++=

ERG = GHG emission reduction in the project area in the absence of proposed project activity

gG = GHG emissions in the project area due to use of electricity and diesel for construction of the

gasifier [ ] 2COt

gmG = GHG emissions in the project area due to use of electricity during maintenance and shut down

of the gasifier [ ]2COt

bG = GHG emissions in the project area due to use of electricity and diesel for construction of the

biogas plant [ ] 2COt

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F METHODOLOGY TO ESTIMATE LEAKAGES

Leakage is defined in the Appendix B of the simplified modalities and procedures for small-scale CDM project activities for all Type I- Renewable Energy Projects as “If the energy generating equipment is transferred from another activity or if the existing equipment is transferred to another activity, leakage is to be considered”. In the BERI project, all the gasifier and biogas plants would be installed new and no transfer of equipment is expected. Hence, there is no leakage in BERI project. However, to calculate the leakage following is the equation

Step 1: Calculate the leakage in the project area the using the Equation F4 (given below)

EQUATION-F4

[ ]EfEG LL ×=

LG = Leakage of GHG in the project area

LE = Energy consumed in transferring the energy generating equipment Ef = Emission factor of the energy consumed

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PART II

G METHODOLOGY TO ESTIMATE REDUCTION OF GHG The difference between emissions during baseline and project implementation & leakages

during that period represents the emissions reductions due to the project activity during a given period.

EQUATION-G1

( )LERtotalPtotalGHG GGGGR −−−=

GHGR = Total GHG emissions reduction in the project area during a given period [ ]2COt

totalG = Total GHG emissions in the project area were the project to not take place [ ]2COt

totalPG = Total GHG emissions in the project area during the project [ ] 2COt

ERG = GHG emission reduction in the project area in the absence of proposed project activity

LG = Leakage of GHG in the project area [ ]2COt

70


H MONITORING The monitoring methodology as defined in Appendix B (UNFCCC, 2003b) for the category:

‘renewable electricity generation for a grid’ involves metering of the electricity generated by the renewable technology. Although the proposed project does not involve co-fired plants, the monitoring of the amount of biomass input and its energy content is included as well in the methodology. The proposed methodology provides measured data on the amount of electricity generated, the biomass input and the fossil fuel input. With this information, a reliable estimate of the amount of emission reductions can be made. The methodology involves monitoring of the following:

o Electricity generation from the proposed project activity,

o Annual determination of the emission factor of the grid (weighted average excluding zero-and low cost sources) to recalculate the operating margin with monitored data,

o Annual determination of the emission factor of the grid (weighted average of recently built plants—represented by the 5 most recent plants or the most 20% of the generating units built) to recalculate the build margin with monitored data,

o Annual determination of the combined margin,

o Correction of emission factors due to import/export of electricity or use of fossil fuels (if needed),

For biogas plants, the monitoring shall consist of metering the biogas consumption in the household as well as surveying the fuel consumption apart from the biogas consumption. Logbooks for dung input to biogas plants by the users will be used for monitoring. The methodology involves monitoring of the following:

o Annual installation of Biogas plants and working of Biogas plants

o Biogas production in Biogas plants and its consumption

o Correction of emission factors of various fuels (if needed)

For the activities to be carried out in the BERI project area, the monitoring needs to be carried out for the variables as given in the Table H.1. The data type needed, the input mode/ agency to obtain the data from, the method to be employed, the concerned agency which will collect / monitor the data, the frequency of measurement and the external agency for monitoring have been summarized in Table H.1

71

Part II

Table H.1: Monitoring variables in the project

SL. NO

DATA TYPE DATA FROM INPUT MODE

METHOD TO BE EMPLOYED

AGENCY TO MONITOR

FREQUENCY OF MEASUREMENT

EXTERNAL AGENCY MONITORING

FOR GASIFIER 1 Electricity from Grid (to calculate the

operating and build margin) KPTCL / Bills at Taluka Panchayat

Participatory Method

Village Energy Committee

Once a month Once a year

2 Wood Usage and Diesel Usage for Electricity generation from gasifier

Log Book Entry / Weighbridge log


3 Electricity generated from gasifier Production Register Once a month Once a year 4 Electricity supplied from gasifier Supply Register

Log Book Maintenance

Gasifier Operation Staff

Once a month Once a year 5 Electricity supplied to household Household Electricity

Bills Once a month Once a year

6 Electricity supplied to irrigation pumpsets

Electricity Bills




FOR BIOGAS PLANT 6 Biogas from Biogas Plant Meter Reading / Log

Book Entry Once a month Once a year

7 Usage of Fuels in household Household survey


Biogas User / Village Energy

Committee Once a month Once a year

72


I SAMPLING

As sampling the whole project area would lead to very high costs and manpower it would be ideal to obtain information about the entire project scenario through observation of a smaller / representative sample size. Hence, a representative sample of the entire project area needs to be identified. Though the principals of sampling design in Bioenergy sector are similar to that in Sink sector the type of samples and data to be collected along with the frequency of sampling vary. As given in the previous Part I on Sink Projects there are four options for sample design - complete enumeration, simple random sampling, systematic sampling and stratified random sampling. As in Part I here too, the Stratified random sampling is thought to be the most precise option. Stratified sampling could be done on the following basis:

o Size of households

o Annual Income of households

o Number of cattle

o Size of land holdings

The following sampling need to be carried out in the project Table I.1: Sampling variables in the project SL. NO

DATA TYPE DATA FROM INPUT MODE

SAMPLE SIZE AGENCY

1 Electricity from Grid (to calculate the operating and build margin)

KPTCL / Bills at Taluka Panchayat

100 % Village Energy Committee

2 Wood Usage and Diesel Usage for Electricity generation from gasifier

Log Book Entry / Weighbridge log

3 Electricity generated from gasifier Production Register 4 Electricity supplied from gasifier Supply Register

100% Gasifier Operation

Staff

5 Electricity supplied to household Household Electricity Bills

6 Electricity supplied to irrigation pumpsets

Electricity Bills

20 % in each strata

mentioned above


6 Biogas from Biogas Plant Meter Reading / Log Book Entry

7 Usage of Fuels in household Household survey

20 % in each strata

mentioned above

Biogas User / Village Energy

Committee

73

PART II

ANNEXURE C1 ESTIMATION OF EMISSION FACTOR FOR ELECTRICITY FROM GRID

The baseline scenario is that the total electricity supplied in the project area is from grid for household lighting and irrigation pump set. The baseline methodology is adopted from the AMS I-D of the Appendix B1 of the simplified modalities and procedures for small-scale CDM project activities. The baseline is the kWh produced by the renewable generating unit multiplied by an emission coefficient (measured in kg CO2equ/kWh) calculated in a transparent and conservative manner as:

(a) The average of the “approximate operating margin” and the “build margin”, where:

(i) The “approximate operating margin” is the weighted average emissions (in kg CO2equ/kWh) of all generating sources serving the system, excluding hydro, geothermal, wind, low-cost biomass, nuclear and solar generation;

(ii) The “build margin” is the weighted average emissions (in kg CO2equ/kWh) of recent capacity additions to the system, which capacity additions are defined as the greater (in MWh) of most recent 20% of existing plants or the 5 most recent plants.”;

Table1: KPCL generation in MUs for past five years Yearly Supply to Karnataka KPCL generation in

MUs (or GWh) 2003-04 2002-03 2001-02 2000-01 1999-2000 Thermal 11393 10292 8954 8904 7762 Hydro+Wind 7033 6835 9268 10544 11711 Total 18426 17138 18222 19448 19473

Table2: Southern grid supply to Karnataka in MUs for 2003-04

Southern Grid MW installed % 2003-04 supply to

Karnataka in MUs Thermal 14336 48.6 5940 Hydro 10555 35.7 4374 IPP 2783 9.4 1153 Gas 1043 3.5 432 Nuclear 780 2.6 323 Wind 28 0.1 12 29525 100.0 12234.0

Note: The data for total supply to Karnataka was obtained and based on the installed capacity was back calculated for the electricity mix

Table3: Default Emission Factors for Northern Grid Thermal Plants 1080 tCO2/GWh Gas Plants 493 tCO2/GWh

Table4: CO2 Emissions Calculated using the Electricity supplied and Default Emission Factors (Emission from KPTCL + Southern Grid)

Electricity Source CO2 Emissions

(tonnes) KPTCL (Thermal Generated x Default IPCC EF for Coal) 12304440

74


Southern Grid (Thermal Generated x Default Northern Grid for Coal) + (Gas Generated x Default IPCC Gas) 6628561 Total CO2 Emissions 18933001

Table5: Operating Margin Calculated

Not taking low operating costs energy like hydro, biomass, geothermal, wind, biomass, nuclear and solar generation into considerations

Operating Margin Calculated = (CO2 from KPTCL) + (CO2 from Southern Grid)/ (Electricity from thermal +Gas plant)

1065.72tCO2/GWh

Table 6: Recent Additions to the Electricity Grid requested for Build Margin calculation Most recent additions 2000-2001 supply in MUs

1 RTPS V 1333.9 2 RTPS VI 1297.8 3 Almatti Dam 713.0

Total MUs 3344.7

Total CO2 Emissions (Tonnes) 2842238

Table 7: Build Margin Calculated

Not taking low operating costs energy like hydro, biomass, geothermal, wind, biomass, nuclear and solar generation into considerations

Build Margin Calculated = (CO2 from KPTCL)/ Total Electricity {Not taking low operating costs energy} 1080.0 tCO2/GWh

Calculation of Average Emission Factor

Calculating the emission factor as given below

Average of OM {Not taking low operating costs energy} + BM {Not taking low operating costs energy}

1072.0 tCO2/GWh

75

PART II

ANNEXURE C2 ELECTRICITY SUPPLIED FROM TALUKA PANCHAYAT

Southern Grid Power Mix Year

Electricity Supplied to the project area

in GWh Hydro Thermal Nuclear Wind Solar

Distribution & Transmission

Losses 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005

76


ANNEXURE C3 ELECTRICITY CONSUMPTION FROM HOUSEHOLD SURVEY

Name of Gassifier Village Group Address

Log for household survey for the Month

Number of assets in households

Bulbs Tube lights CFL Fans Television Pump set

Sl. No Name of Household 0W

20W

40W

60W

100W

36W

40W

8W

12W

14W

16W

18W

22W

SF

BF

EF

TF

Ref

ridge

rato

r Ta

pe

Rec

orde

r V

Play

er

CD

/DVD

SC

BC

SB&W

BB&W

DTH

Mix

er

Grin

der

Emer

genc

y Li

ght

0.5H

P

1HP

3HP

5HP

Aver

age

Uni

ts o

f El

ectri

city

C

onsu

med

1 2 3 4 5 6 7 8 9

10 11 12 13 14 15

Total Nos of appliances in village

Average Time of usage Mutiplication Factor Consumption of Electricity / month (Units)

77

PART II

ANNEXURE C4 ELECTRICITY CONSUMPTION DATA FROM ELECTRICITY BILLS

Name of Gassifier Village Group

Address Log for household survey for the Month

Number of

Units Sl. No Name of

Household From To

Average Units of Electricity

Consumed 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 Total Unit Consumed

78


ESTIMATION TABLE C1 CO2 EMISSIONS FROM ELECTRICITY FROM GRID

An Excel Format for the Estimation Table is given along with the manual where the data can be entered directly and the amount of CO2 released estimated. Following is the hard copy of the Estimation Tables.

Sl. No

Project Area (Clusters)

Basic Unit (kWh)

Emission Factor (tCO2/GWh)*

Amount of Carbon dioxide released

1 X 1072 = 0.00 2 X 1072 = 0.00 3 X 1072 = 0.00 4 X 1072 = 0.00 5 X 1072 = 0.00

Total Amount of CO2 released in tonnes = 0.00

Step 1 Enter the amount of electricity used in (kWh) in each of the project cluster if available. If total amount electricity is available for the whole project area then enter the value in first row only Step 2 Multiply Column 1 by Column 2 and insert the total in Column 3. This is your total for CO2 from electricity

Note

* For the calculation of the baseline, the average of the “approximate operating margin” and the “build margin”, was calculated to arrive at the emission factor of 1072 tCO2/GWh. The Southern Region’s grid along with KPTCL data was used as the reference region for estimating the current generation mix

79

PART II

ANNEXURE C5 FUEL CONSUMPTION DATA FROM HOUSEHOLD SURVEY

Consumption of Fuels for Cooking / month Sl. No Name of Household Kerosene LPG Diesel Coke Wood Charcoal Biogas

Dung Cake

1 Kg Kg Kg Kg Kg Kg Kg Kg 2 Kg Kg Kg Kg Kg Kg Kg Kg 3 Kg Kg Kg Kg Kg Kg Kg Kg 4 Kg Kg Kg Kg Kg Kg Kg Kg 5 Kg Kg Kg Kg Kg Kg Kg Kg 6 Kg Kg Kg Kg Kg Kg Kg Kg 7 Kg Kg Kg Kg Kg Kg Kg Kg 8 Kg Kg Kg Kg Kg Kg Kg Kg 9 Kg Kg Kg Kg Kg Kg Kg Kg

10 Kg Kg Kg Kg Kg Kg Kg Kg 11 Kg Kg Kg Kg Kg Kg Kg Kg 12 Kg Kg Kg Kg Kg Kg Kg Kg 13 Kg Kg Kg Kg Kg Kg Kg Kg 14 Kg Kg Kg Kg Kg Kg Kg Kg 15 Kg Kg Kg Kg Kg Kg Kg Kg 16 Kg Kg Kg Kg Kg Kg Kg Kg 17 Kg Kg Kg Kg Kg Kg Kg Kg 18 Kg Kg Kg Kg Kg Kg Kg Kg 19 Kg Kg Kg Kg Kg Kg Kg Kg 20 Kg Kg Kg Kg Kg Kg Kg Kg

Total consumption of fuel/month* Kg Kg Kg Kg Kg Kg Kg Kg

*Consumption of various fuels for each month is calculated and added up to get the yearly consumption. Use the table given below to arrive at yearly fuel consumption for cooking

Consumption of Fuels for Cooking / month

Kerosene LPG Diesel Coal Wood Charcoal Biogas Dung Cake Sl.

No Month Kg Kg Kg Kg Kg Kg Kg Kg 1 January Kg Kg Kg Kg Kg Kg Kg Kg 2 February Kg Kg Kg Kg Kg Kg Kg Kg 3 March Kg Kg Kg Kg Kg Kg Kg Kg 4 April Kg Kg Kg Kg Kg Kg Kg Kg 5 May Kg Kg Kg Kg Kg Kg Kg Kg 6 June Kg Kg Kg Kg Kg Kg Kg Kg 7 July Kg Kg Kg Kg Kg Kg Kg Kg 8 August Kg Kg Kg Kg Kg Kg Kg Kg

80


9 September Kg Kg Kg Kg Kg Kg Kg Kg 10 October Kg Kg Kg Kg Kg Kg Kg Kg 11 November Kg Kg Kg Kg Kg Kg Kg Kg 12 December Kg Kg Kg Kg Kg Kg Kg Kg

Total fuel consumed in kg** Kg Kg Kg Kg Kg Kg Kg Kg

** Divide by 1000000 to convert the fuel consumed in kg to kilotons and use these values in estimating baseline emissions as well as for monitoring

81

PART II

ANNEXURE C6 EMISSION FACTORS FOR VARIOUS FUELS

Default values for carbon emission from burning of various fuels used in residential sector Fuel Type Net Calorific

Value1 kT

TJ

Emission Factor2

TJtC

Carbon Unoxidised3


A B C D E Gas/Diesel Oil 43.3 20.2 0.99 865.9 Kerosene 44.75 19.6 0.99 868.3 LPG 47.31 17.2 0.995 809.7 Coal 16.454 25.85 0.98 416.8

Note: 1. IPCC Guidelines Vol. 2 Table 1-3 2. IPCC Guidelines Vol. 2 Table 1-2 3. IPCC Guidelines Vol. 2 Table 1-4

Default values for CH4 and N2O emission from burning of various fuels used in residential sector (1996 IPPC Guidelines)

Fuel Net Calorific

Value kT

TJ

Emission Factors for

CH4 in kg/TJ


kTT

B x C

Emission Factors for

N2O in kg/TJ


kTT

B x E A B C D E F Coal 16.454 300 4.9362 1.4 0.023 Wood / Wood Waste 15.0 300 4.5 4 0.06 Charcoal 30.0 200 6.0 1 0.03 Other Biomass & Wastes

12.0 300 3.6 4 0.048

82


ESTIMATION TABLE C2 CO2 EMISSIONS FROM FUEL CONSUMPTION IN HOUSEHOLD SECTOR

An Excel Format for the Estimation Table is given along with the manual where the data can be entered directly and the amount of CO2 released estimated. Following is the hard copy of the Estimation Tables.

CO2 Emissions from fuels for cooking

Step 1 Enter the amount of fuel used in tonnes in the project area calculated from Format I-B (1). Step 2 Multiply Column 1 by Column 2 and Column 3 and insert the total in Column 4 for CO2, CH4 and N2O gases Step 3 Add up the totals in Column 4 and enter at the bottom of the Column 4. This is your total for CO2 equivalent emissions from fuel usage in households

Sl. No Fuel Types

Basic Unit (kT)

Calculation Factor (tC/kT)*

Conversion factor from Carbon to CO2

Amount of CO2 released

1 Kerosene X 868.3 X 3.67 = 0.00 2 LPG X 809.7 X 3.67 = 0.00 3 Diesel X 865.9 X 3.67 = 0.00 4 Coal X 416.8 X 3.67 = 0.00 5 Wood X X = 6 Charcoal X X = 7 Dung X X =

CH4 Emissions from fuels for cooking

Sl. No Fuel Types

Basic Unit (kT)

Calculation Factor (t/kT)**

Conversion factor from CH4 to CO2

Amount of CO2 equivalent released

1 Kerosene X X = 2 LPG X X = 3 Diesel X X = 4 Coal X 4.936 X 21 = 0.00 5 Wood X 4.5 X 21 = 0.00 6 Charcoal X 6 X 21 = 0.00 7 Dung X 3.6 X 21 = 0.00

83

PART II

N2O Emissions from fuels for cooking Sl. No Fuel Types

Basic Unit (kT)

Calculation Factor (t/kT)**

Conversion factor from N2O to CO2

Amount of CO2 equivalent released

1 Kerosene X X = 2 LPG X X = 3 Diesel X X = 4 Coal X 0.023 X 310 = 0.00 5 Wood X 0.06 X 310 = 0.00 6 Charcoal X 0.03 X 310 = 0.00 7 Dung X 0.048 X 310 = 0.00

Total Amount of CO2 equivalent released in tonnes = 0.00

84


ANNEXURE D1 ESTIMATION OF DIESEL CONSUMPTION BY GASIFIERS & EMISSION FACTOR

FOR GENERATION OF ELECTRICITY

Log Book for the Electricity Produced by ___________________Gassifier Village Group

Name of Gassifier Village Group

Address

Log for the Month for Electricity Produced

Sl. No Date

Biomass Used (Tons) Diesel Used (L)

Total Electricity Produced (MW)

1 2 3 4 5 6 7 8 9

10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31

Total

85

MANUAL FOR ESTIMATION OF GHG ... - ksdl.karnataka.gov.in

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