comparison of biofuel life cycle assessment tools

Comparison of Biofuel Life Cycle Assessment Tools

Sugarcane ethanol production in Brazil

CTBE Team

Antonio Bonomi

Otavio Cavalett

Lucas Pereira

Mateus Chagas

Alexandre Souza

Bioenergy Conference 2016

Brisbane, Australia – November 14-16th, 2016

GREET GHGenius BioGrace

MOTIVATION

Targets for GHG emissions reductions have been set; however LCA

models with different results jeopardize their optimal use in the

policy context and may discredit the compliance of biofuels with the

targets established.

OBJECTIVE

Comparing LCA GHG regulatory models (GHGenius, GREET and

BioGrace), to identify and track the main reasons for discrepancy in the

results obtained by each model, depicting the main differences and

commonalities in methodological structures, calculation procedures,

and assumptions made.

BioGrace GHGenius GREET CTBE

Gasoline 83.8 95.0 90.2 87.5

Sugarcane ethanol 24.0 43.3 25.3 16.0

GHG savings 71% 54% 72% 82%

Greenhouse gases emissions [g CO2eq per MJ of fuel]

Most standards set a target of 50% reduction in GHG emissions for biofuels

The Greenhouse gases, Regulated Emissions and Energy in

Transportation

GREET 2015 (Graphic Interface) GREET1 Model (Excel)

Geography: US

Scope: Field-to-wheels

Timeframe: 1990-2020 (5-year span)

Case studies: petroleum, natural gas, ethanol (corn, sugarcane, switchgrass,

etc.), hydrogen (solar, nuclear, coal, etc.), biodiesel

User-friendliness: low (Excel) / high (Graphic Interface)

Harmonised Calculation of

Biofuel Greenhouse Gas emissions in Europe

Geography: EU

Scope: Field-to-pump

Timeframe: not defined

Case studies: ethanol (corn, wheat, sugarcane, etc.), biodiesel FAME and

HVO (soybean, palm, sunflower, etc.), biogas…

User-friendliness: high

GHGenius

Geography: Canada (national, regions, provinces), US (national and regions),

Mexico and India


Timeframe: 1995-2050

Case studies: coal, gasoline, crude oil, jet fuel, ethanol (corn, sugarcane,

wheat, etc.), biodiesel (canola, soy, etc.), methanol, bio oil…

User-friendliness: very low

Virtual Sugarcane Biorefinery (CTBE)

Geography: Brazil


Timeframe: 2015

Case study: sugarcane ethanol in Brazil

User-friendliness: not applicable (not designed for external users)

- Allocation criteria

- Default inputs/parameters

- N2O emissions

- Life cycle inventory (dataset)

- Upstream life cycle data

- Global Warming Potential (GWP) method

- Land Use-Change (LUC) (separate calculation within GREET (US

crops) and BioGrace (IPCC)) – not included in this study

Main sources of differences in GHG models identified:

The case of sugarcane ethanol in Brazil


Parameters BioGrace GHGenius GREET CTBE

Autonomous

CTBE

Annexed

50/50

Productivity (tonne/ha) 68.7

73.66 (2004)

+1.33%/yr

85.26 (2015)

86.7 (2008) 80.0 (2015) 80.0 (2015)

Ethanol yield (L/TC) 87.0 80.0 81.0 85.2 42.2

Sugar yield (kg/TC) - - - - 51.4

Surplus electricity (kWh/TC) - 10.7 75.0 (2015) 26.1 (2015) 26.1 (2015)

Parameters Data from NovaCana, Unica

and CTBE process simulation


Life cycle inventory

Main inputs BioGrace GHGenius GREET CTBE

per tonne of sugarcane

N fertilizer (kg) 0.91 1.08 0.80 1.23

P2O5 fertilizer (kg) 0.41 0.58 0.30 0.14

K2O fertilizer(kg) 1.08 1.47 1.00 1.31

Limestone (kg) 5.34 11.65 5.20 5.00

Diesel (machinery) 0.8 L 2.9 L 1.1 L 1.9 L

Sugarcane transportation (km) 20 20 19.3 27.3

Agricultural Macedo et al. 2004

Seabra et al. 2011

Macedo et al. 2008

Macedo et al. 2004 Wang et al. 2012:

Seabra et al. 2011

CTBE Agronomic

recommendation

Average

Seabra et al. (2011): 450 kg CaO per ha

Macedo et al. (2008): 1,900 kg CaO per ha

Macedo et al. (2004): 366 kg CaO per ha


GHG impacts

Agricultural

(unallocated)

5.2 kg/TC

5.3 kg/TC 367.0 kg/ha

11.7 kg/TC

5.0 kg/TC 400 kg/ha

GREET BioGrace GHGenius CTBE

g CO2eq per kg of limestone

(production + use) 236.0 129.5 790.0 131.6

Limestone


GHG impacts

Agricultural

(unallocated)

1.1 L diesel/TC (2.0 gCO2eq/MJ)

+ LPG, NG, gasoline,

electricity (2.6 gCO2eq/MJ)

0.8 L diesel/TC

2.9 L diesel/TC

1.9 L diesel/TC


g CO2eq per MJ of diesel

(production + combustion) 90.2 87.6 116.4 81.6

Diesel

Ecoinvent v2.2


GHG impacts

Agricultural

(unallocated)

14% burning for 140 kg of dry straw/TC

100% burning for 100 kg of dry straw/TC

0% burning

18.4% burning for 140 kg of dry straw/TC

User can choose the percentage of straw burning

GREET 2015 Straw burning 1995: 95% 2000: 86% 2005: 81% 2010: 54% 2015: 14%

Straw

burning


GHG impacts

Agricultural

(unallocated)

N = fertilizer (800 gN/TC)

N = fertilizer (910 gN/TC)

N = fertilizer (1077 gN/TC) + crop residues (1232 gN/TC)

+ soil + ind waste

N = fertilizer (1230 gN/TC) + ind waste + roots +

unburnt straw


N2O emission factor for sugarcane 1.220% 1.325% 1.575% 1.460%

g CO2eq per kg of N

(fertilizer production) 4.48 5.88 3.51 3.35

Fertilizer


Life cycle inventory

Inputs BioGrace GHGenius GREET CTBE

Autonomous

CTBE

Annexed

50/50

per L of ethanol

Sulfuric acid (kg) 16.06 7.40 - 4.94 4.93

Lime (kg) 17.97 11.00 10.85 7.48 15.84

Lubricants/Diesel (L) 0.258 0.640 1.92 0.153 0.243

NaOH (kg) - - - - -

Cyclohexane (kg) 1.06 - - 0.71 0.71

Phosphoric acid (g) - - - 2.70 4.28

Inorganic chemicals (g) - - - 0.044 0.062

Zeolites (g) - - - 0.047 0.047

Industrial

default

+40%

CTBE: model also includes steel, chromium steel, concrete for equipment and construction, and chemicals for water treatment


GHG impacts

WTW

(default allocation) Distributed

in the US

Distributed

in the US

Distributed

in Europe

Recommendations

For the calculation of GHG emissions associated with sugarcane ethanol in

Brazil:

- Updated inventory

- Transparent allocation method

- Calculation with a set of defined allocated methods

- Electricity as co-product

- Straw burning factor

- Consistency for diesel and nitrogen emissions

Thank you

Evaluation partners University of British Columbia (UBC)

Jack Saddler

Susan van Dyk

Anna Ringsred

National Renewable Energy Laboratory

(NREL)

Jim McMillan

Helena Chum

Ethan Warner

Yimin Zhang

Models developers Rijksdienst voor Ondernemend (RVO)

John Neeft

S&T Squared consultants

Don O’Connor

Argonne National Laboratory (ANL)

Jennifer Dunn

Michael Wang

Jeongwoo Han

Hao Cai

comparison of biofuel life cycle assessment tools

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