implicatio implica tion n of of bio biofue fuel pr prod oduc - - PowerPoint PPT Presentation

Wate ter r qu quan antity tity an and d qu quality ality implica implicatio tion n of

• f bio

biofue fuel pr prod

• duc

uctio tion: n: A A ca case se stu study dy of

• f t

the he Khlon Khlong Phlo Phlo Wate tersh shed ed in in Tha hail ilan and d

• Prof. MUKAND S. BABEL

Asian Institute of Technology (AIT), Thailand and Kyoto University (KU), Japan msbabel@ait.asia and msbabel@gmail.com

What is Biofuel?

2

• Biofuels: solid, liquid or gaseous fuels derived

from organic matter/biomass

• Biofuels: primary and secondary
• Primary: fuel wood in unprocessed form used

for heating, cooking or electricity production

• Secondary: bioethanol and biodiesel

produced by processing biomass and used in vehicles and various industrial processes

• Secondary biofuels categorized: first, second

and third generation based on

• type of processing technology, type of feedstock
• r their level of development

What is Biofuel?

3

(Dragone et al., 2010 modified from Nigam and Singh, 2010)

Why Biofuels?

4

• Biofuels are promoted by many countries

(USA, Brazil, China, India, Thailand, Malaysia etc.) to:

• cut down fossil fuel consumption,
• decrease oil imports,
• reduce greenhouse gas emission, and
• reduce the poverty level of rural

communities.

5

Bio-ethanol production statistics

Country Bio-ethanol production Energy share in gasoline (million litres) type fuel use (%) 2009-11 2021 2009-2011 2021 averagea averagea United States 47,617 82,610 5.4 10.9 Brazil 25,331 51,305 47.1 64.3 China 8,094 10,058 1.8 1.3 EU27 6,424 15,747 2.7 8.3 India 1,976 4,194 Canada 1,565 1,992 2.6 3.4 Thailand 777 2,102 Japan 102 104 Rest of the world 6,333 12,290 Total 98,219 180,402 5.9 10.8

Source: OECD/FAO (2012); a estimated value

Bio-ethanol production statistics

6

Source: OECD/FAO (2012); Bnl means Billion Liters

Main producers: USA, Brazil, EU & in developing countries: China and India

7

Bio-diesel production statistics

Country Biodiesel production Energy share in diesel (million litres) type fuel use (%) 2009-11 2021 2009-11 2021 averagea averagea EU27 10,436 19,864 5.1 8.5 United States 2,834 5,083 0.9 1.5 Australia 641 727 3.1 3.1 Argentina 2,231 4,204 3.2 4 Brazil 2,015 3,205 4 4.6 Thailand 664 1,339 Malaysia 563 956 India 330 1,297 Columbia 431 917 Canada 147 552 0.7 1.6 Rest of the world 1,030 3,451 Total 21,322 41,595 2.5 3.8

Source: OECD/FAO (2012); a estimated value

8

Bio-diesel production statistics

Source: OECD/FAO (2012); Bnl means Billion Liters

Main producer: EU & other players: Argentina, USA, Brazil, Thailand and Indonesia

Biofuels production by 2021

9

Source: OECD/FAO (2012)

Ethanol: Apart from USA, Brazil & EU, China, India and Thailand are expected to contribute to world production by 2-3% each by 2021

• Expanding biofuel sector absorbs larger share
• f crop production

10

Food/feed and biofuel use

Source: OECD/FAO (2012)

11

Land-use change and Biofuels

Biofuel policies in Thailand

12

• Plans to increase the share of renewable

energy in the total energy consumption from 0.5% in 2002 to 20.3% (4.1% from biofuel) by 2022

• Plans of expanding the oil palm land cover to

1.6 million ha by 2023 (Siriwardhana et al., 2009).

• Orchard replacement by oil palm for biofuel

already happening in the northern, northeastern, eastern and southern regions

Rationale

13

• Biofuel “as an alternative to fossil fuel”
• 57 billion L to 221 billion L in 2021
• Thailand: 5 billion L by 2022
• Land use change for biofuel

production

• Impact on water resources and the

aquatic environment, esp. nutrient cycle and water quality leading to eutrophication

• Severe impacts on hydrological

processes but the quantification is complex

• Need of scientific assessment of

regional feedstock production implication for sustainability

Before After

14

Objectives

Analyze the potential impact of land use change due to biofuel production on the hydrology and water quality of watershed

Specific objectives:

• Estimate water footprints of biofuel and

biofuel energy

• Evaluate impact on annual and seasonal

water balance

• Quantify impact on water quality

15

Study Area

Location:

• Khlong Prasae
• Rayong
• 12057’-13010’N
• 101035’-101045’E

Area: 202.8 km2 Rainfall: 1,734 mm Temp.: 27 to 310 Humidity: 69 to 83% Elevation: 13 to 72 m msl Land use: Agri. (66%) Forest (33%) Soils: S – Cl - L S – L

Khlong Phlo Watershed

16

Water footprint: Methodology

Climatic Parameters Crop Coefficient Effective Rainfall Reference crop ET Crop ET Green WFCP Irrigation requirement Pollutant emission Agreed water quality

Step 1: Water footprint of crops (WFCP)

Blue WFCP Grey WFCP Biofuel conversion rate Green WFCP Blue WFCP Grey WFB Grey WFCP Step 2: Water footprint of biofuel (WFB) Green WFB Blue WFB Energy

• f biofuel

Green WFB Blue WFB Grey WFBE Grey WFB Step 3: Water footprint of biofuel energy (WFBE) Green WFBE Blue WFBE

Formulae used for water footprint (WF)

Green WF = min (Evapotranspiration, Effective Rain) Blue WF = Irrigation requirement Grey WF = max (Pollutant released/Permissible limit) WFCP = Water use for crop production / crop yield WFB = WFCP/ biofuel conversion rate WFBE = WFB/ energy per liter biofuel Energy /L biofuel = HHV X density

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HHV: higher heating value

18

Impact on water balance and water quality: Methodology (SWAT), Pre-processing Phase

& & & & & & & & & & & & & & &

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

DEM Drainage Soil Land use Sub-watersheds

Hydrological Response Units

19

Impact on water balance and water quality: Methodology (SWAT), Processing Phase

Meteorological data Model calibration and validation Scenarios simulation Land use change scenarios Evaluation

• Water balance
• Water quality

Hydrological Response Units Management data Model evaluation

20

Data collected

Data Frequen uency Perio iod Source ce Rainfall Daily 1984-2006 RID/TMD Temperature Daily 1984-2006 TMD Wind speed Daily 1984-2006 TMD Relative Humidity Daily 1984-2006 TMD Sunshine duration Daily 1984-2006 TMD Discharge Daily 1984-2006 RID Sediment load Daily 1997-2005 RID Data Type Source ce DEM 30 m resolution http://www.gdem.aster. or.jp Land use map 1:25,000 m LDD Soil map 1:100,000 m LDD Drainage map RID Data Source ce Soil properties LDD, www.iiasa.ac.at Fertilizer use DOA, www.fao.org/ag/agl/fertistat/fst.fubc.en.asap Cropping pattern Farmers , DOA of Thailand

Meteorological data: Spatial data: Additional data:

21

Land use (2006)

Code Land Use Area Perce cent km km

2

3 Rice 1.82 0.90 8 Cashew Nut 4.84 2.39 9 Cassava 9.88 4.87 21 Evergreen Forest 66.36 32.73 27 Deciduous Forest 0.05 0.03 41 Institutional Land 0.51 0.25 43 Water bodies 0.89 0.44 47 Residential 0.28 0.14 57 Wet Land 0.01 0.01 64 Orchard 27.96 13.79 67 Oil Palm 1.12 0.55 70 Rubber 85.12 41.98 82 Range grass 1.83 0.90 89 Sugarcane 2.11 1.04

Total

202.80 100.00

22

Land use change scenarios

• A. Oil Palm expansion (Biodiesel)

Scenario A1

• Orchard to Oil

Palm

• Oil Palm <1 to

17% Scenario A2

• Rubber to Oil

Palm

• Oil Palm <1 to

43% Scenario A3

• Orchard + Rubber to Oil

Palm

• Oil Palm < 1 to 59%

Scenario A4

• Forest to Oil Palm
• Oil Palm <1 to

33% Scenario A5

• Orchard +

Rubber+ Forest to Oil Palm

• Oil Palm <1 to

91%

• B. Cassava expansion (Bio-ethanol)

Scenario B1

• Orchard to

Cassava

• Cassava 5 to 21%

Scenario B2

• Rubber to

Cassava

• Cassava 5 to 47%

Scenario B3

• Orchard + Rubber to

Cassava

• Cassava 5 to 63%

Scenario B4

• Forest to Cassava
• Cassava 5 to 38%

Scenario B5

• Orchard +

Rubber+ Forest to Cassava

• Cassava 5 to 96%

23

Land use change scenarios

• D. Combined expansion

Scenario D1

• Orchard to Oil Palm +

Cassava

Scenario D2

• Rubber to Oil Palm +

Cassava

Scenario D3

• Orchard to Cassava +

Sugarcane

Scenario D4

• Rubber to Cassava +

Sugarcane

• C. Sugarcane expansion (Bio-ethanol)

Scenario C1

• Orchard to

Sugarcane

• Sugarcane 1 to

17% Scenario C2

• Rubber to

Sugarcane

• Sugarcane 1 to

43% Scenario C3

• Orchard + Rubber to

Sugarcane

• Sugarcane 1 to 59%

Scenario C4

• Forest to

Sugarcane

• Sugarcane 1 to

34% Scenario C5

• Orchard +

Rubber+ Forest to Sugarcane

• Sugarcane 1 to

92%

Results and Discussion

25

Water footprint of crops (WFCP)

Oil Palm Cassava Sugarcane

775 m3/t 420 m3/t 85 m3/t 306 m3/t 106 m3/t 42 m3/t 142 m3/t 80 m3/t 12 m3/t

• Sugarcane has low water footprint due to higher yield
• WFCP sensitive to yield

26

Water footprint of biofuel (WFB)

• 5800 L for oil palm = 1 L of biodiesel
• 2500 L for cassava and 3400L for sugarcane = 1 L of bio-ethanol
• Grey water contributes 5-17% for cassava, 3-9% for sugarcane and

3-12% for oil palm

100 200 300 400 500 600 700 800 5% 10% 15% 20% L of Grey water/L of biofuel Pollutant Loading to surface water Oil Palm Cassava Sugarcane 1000 2000 3000 4000 5000 6000

Oil Palm Cassava Sugarcane

L of water/ L of biofuel

Grey WF Blue WF Green WF

27

Water footprint of biofuel energy (WFBE)

• 177, 103 & 140 m3 for oil palm, cassava & sugarcane ( under 5%

leaching nitrogen scenario)

• The most water

er-effici icient ent crop p for the study y area is cassa sava a and the water footprint for bio-ethanol energy is less than for biodiesel

• Biofuel production utilizing cassa

sava a as feedstoc dstock k would ld have e less s impact act on the water er resour

• urce

ces s of the studied watershed as compared to sugarcane and oil palm. 50 100 150 200 Oil Palm Cassava Sugarcane m3/ GJ of energy Grey WF Blue WF Green WF

28

Water footprint of biofuel energy (WFBE)

Gerb rbens ns Leene nes et al. (2008)

Crop

Green n WFBE

BE

Blue WFBE

BE

Green n WFBE

BE

Blue WFBE

BE

m3/ GJ of Energy gy m3/ GJ of Energy gy m3/ GJ of Energy gy m3/ GJ of Energy gy

Cassava

72 25 79 8

Sugarcane

87 49 64 55

WFBE comparison with a study by Gerbens-Leenes et al. (2008).

• Sugar 13% and cassava 10% less
• Difference in crop water requirement (CWR) and yield
• CWR sensitive to climatic data and starting of growing period
• Nakhon Ratchasima for sugarcane and Chaing Mai for cassava
• Yield 3 production years (2006-2008)(OAE) vs 5 production years

(1997-2001)(FAO)

• Water footprint for biofuel energy is sensitive to the location
• The impact on the components of water balance would vary from

place to place, thereby requiring localized studies.

29

Water footprint under various land use change scenarios

• Increase in cultivation area of biofuel crops would increase the

blue water requirement which means increased irrigation withdrawals.

• Significant effect on the water resources availability in the

studied watershed.

5 10 15 20 25 BC A1 A2 A3 A4 A5 B1 B2 B3 B4 B5 C1 C2 C3 C4 C5 D1 D2 D3 D4 Scenario/Base case Scenario

Blue water (base case ) = 20.3 mm

30

Water footprint under various land use change scenarios

• Expansion of biofuel crops in the studied watershed would

increase the grey water requirement = reduced fresh water availability due to contamination

• Decrease in grey water requirement for orchard replacement

scenarios is negligible hence ideal land use change would be to replace orchard with biofuel crops.

1 2 3 BC A1 A2 A3 A4 A5 B1 B2 B3 B4 B5 C1 C2 C3 C4 C5 D1 D2 D3 D4 Scenario/Base case Scenario

Grey water (base case) =37.2mm

y = 0.8613x + 13.243 R² = 0.8088 100 200 300 400 500 100 200 300 400 500 Simulated flow (mm) Observed flow (mm) Calibration Best fit line

50 100 150 200 1996/1 1997/1 1998/1 1999/1 2000/1 Stream flow (mm) Observed Simulated 50 100 150 200 250 300 350 400 450 1986/1 1987/1 1988/1 1989/1 1990/1 1991/1 1992/1 1993/1 1994/1 1995/1 Stream flow (mm) Observed Simulated

31

Monthly flow calibration and validation

Calibration Validation

Mean and SD < 10%, NS>0.5, R2>0.6 Mean and SD < 10%, NS>0.5, R2>0.6

y = 0.7309x + 8.8996 R² = 0.6311 50 100 150 200 50 100 150 200 Simulated flow (mm) Observed flow (mm) Validation Best fit line

0.00 0.10 0.20 0.30 0.40 0.50 1997/1 1998/1 1999/1 2000/1 Sediment yield (t/ha) Observed Simulated

32

Sediment yield calibration and validation

Total average annual sediment yield:

• Modeled with error 5.13% [0.60 t/ha (Sim) vs. 0.57 t/ha (Obs)]

Monthly sediment yield:

Calibration Validation

Calibration: Mean and SD < 10%, NS>0.5, R2>0.6 Validation: Mean > 10% and SD < 10%, NS< 0.5, R2<0.6

y = 0.7804x + 0.0088 R² = 0.6859 y = 0.7229x - 0.0022 R² = 0.5365 0.00 0.10 0.20 0.30 0.40 0.50 0.00 0.10 0.20 0.30 0.40 0.50 Simulated sediment yield (t/ha) Observed sediment yield (t/ha) Calibation Validation Linear (Calibation) Linear (Validation)

33

Scenario analysis for impacts on water balance components

• Oil palm
• change in total water yield

and ET negligible

• Cassava and sugarcane
• effect all components
• Increased surface runoff

and total water yield, decreased baseflow and ET.

• Combined expansion
• combined expansion of

biofuel crops has relatively less impacts on water resources

34

Effect of land use change on monthly water yield

Differences in monthly water yield from land use change scenarios to baseline: Forest replace

• 5

5 10 15 20 J F M A M J J A S O N D Difference from base case (mm) Scenario A4 Scenario B4 Scenario C4

35

Effect of gradual land use change on water yield

Differences in annual average water balance components for different gradual expansion scenarios compared to the base case: Cassava expansion case

• 10

10 20 30 25 50 75 100 Difference from baseline (%) Percent Change Surface runoff Baseflow Total water yield Evapotranspiration

• Oil palm expansion were negligible
• Cassava and sugarcane
• Increased surface runoff, total water yield and decreased

baseflow and ET

36

Scenario analysis for impacts on water quality

Differences in non-point source pollutants for different scenarios compared to the base case, (a) Oil palm expansion; (b) Cassava expansion; (c) Sugarcane expansion; (d) Combined expansion.

Conclusions and Recommendations

38

Conclusions

• Water footprint of bio-ethanol is less than

biodiesel and cassava would have less impact on water resources

• The use of biofuel crops requiring less

irrigation and less fertilizer would be an appropriate strategy

• Biodiesel no impact on water balance
• Forest conversion will affect the water balance
• Bio-ethanol production will affect the water

balance

39

Conclusions

• Biodiesel production will effect the water

quality due to increased nitrate loading

• Expansion of oil palm area would have a

significantly adverse impact on the water quality due to increased nitrate loading

• Conversion of orchard showed less water quality

impact

• Bio-ethanol production will also have impact
• n water quality
• Biofuel production will have negative impact
• n the environment

40

Recommendations

• Cassava to be promoted in water scarce areas but the

environmental impacts must be considered

• Replacement of orchard for oil palm would have minimum

impacts on both WR and WQ which is in line with the govt. policy to promote biodiesel replacing orchards

• Conversion of rubber: no impact on water balance but

will affect water quality

• Forest in no case should be replaced
• Orchard may be replaced for biofuel crops from water

resources and water quality perspective

• Land use management plans like combined oil palm and

cassava expansion and assessing threshold areas for expansion of biofuel crops should be implemented to safeguard against or mitigate any potential adverse consequences on water resources

For the Government of Thailand:

41

Recommendations

For further study:

• A research at a large scale at basin level with

several options on bio-fuel crops, bringing into consideration the physical, socio-economic and environmental aspects, is recommended for developing suitable water and energy policies.

THANK YOU

This presentation is based on the published Paper: Babel, M.S., Shrestha, B., Perret, S.R., 2011. Hydrological impact

• f biofuel production on hydrology: A case study of Khlong Phlo

Watershed in Thailand. Agricultural Water Management 101:8 -26. msbabel@ait.asia and msbabel@gmail.com