Life-Cycle Assessment of Conventional and Alternative Fuels for Road Vehicles

Raymond R. Tan, MSa and Alvin B. Culaba, RME, PhDb

aChemical Engineering Department, De La Salle University – Manila

bMechanical Engineering Department, De La Salle University – Manila

 

ABSTRACT

Results of the life-cycle assessment (LCA) of several conventional and alternative motor vehicle fuels are discussed.  The analysis was accomplished using the composite program EDIP-GREET, which is based on the Danish EDIP impact assessment and the American GREET 1.5a fuel-cycle models.  The options evaluated included conventional fuels (gasoline and diesel), biofuels (bioethanol and biodiesel) and natural gas derivatives (LNG, CNG and methanol), with the analysis being limited to air pollution and resource depletion impacts.  Sensitivity analysis was also used to determine the effect of electrical power generation mix on total environmental impacts.  The model outputs indicate no significant over-all benefits resulting from the substitution of natural gas-based fuels for gasoline.  On the other hand, the use of bioethanol and biodiesel in place of gasoline and diesel, respectively, is expected to yield significant gains particularly with respect to greenhouse gas emissions and fossil fuel depletion.

 

Keywords:             Life-cycle assessment (LCA), alternative fuels

 

Introduction

Automotive transport is a major contributor to local and global air pollution as well as fossil fuel resource depletion.  In the Philippines, for example, road vehicles accounted for 13% of the country’s primary energy consumption in the late 1990s, as well as a proportionate share of the  estimated 63 ΄ 106 ton per annum national CO2 emission inventory (World Resources Institute, 2000).  Alternative propulsion systems are considered to be the most promising long-term solution to the environmental impacts resulting from road vehicle use (Poulton, 1994).  For the Philippines in particular, there is significant potential for the use of biofuels and natural gas derivatives as petroleum substitutes for vehicles with spark ignition (SI) and compression ignition (CI) engines.

 

In the aftermath of the oil shocks of the 1970s, the Philippines explored liquid biofuels as a means of insulating her economy from volatile petroleum prices.  One of the fuels identified for development was bioethanol derived for sugarcane, which was used in gasoline blends called alcogas (Lorilla, 1982; Del Rosario et al., 1985).  The other fuel was biodiesel derived from coconut oil, or cocodiesel.  The alcogas and cocodiesel programs were also meant to provide alternative markets to revitalize the country’s sugar and coconut agricultural sectors (Eala, 1985).  Both biofuel programs were abandoned in the mid-1980s due in part to domestic political turmoil, and in part to stable World oil prices.  Today biofuels merit reconsideration, but for environmental rather than economic considerations.

 

The development of the commercially viable Camago-Malampaya natural gas (NG) deposits in the western Philippines has stimulated interest in the utilization of this relatively clean-burning fuel for various applications.  Although near-term plans focus on the use of NG for power generation, other applications will also be explored in the long run.  There is particular interest in using NG as an environment-friendly alternative transportation fuel (Philippine Department of Energy, 2000).  NG can be used directly in liquefied (LNG) or compressed form (CNG) in vehicles with modified.  Alternatively, it can be converted to methanol, which requires significantly less engine modification.

 

Life-Cycle Assessment

Life-cycle assessment (LCA) is a conceptual framework and methodology for the assessment of environmental impacts of product systems on a cradle-to-grave basis.  The LCA approach is a departure from conventional assessments which tend to focus either on product manufacturing or end-of-life disposal.  Analysis of a system under LCA encompasses the extraction of raw materials and energy reseources from the environment, the conversion of these resources into the desired product, the utilization of the product by the consumer, and finally the disposal, reuse, or recycle of the product after its service life.  The LCA approach is an effective way to introduce environmental considerations in process and product design or selection (Azapagic, 1999).

 

Modern LCA methodology is based on standards developed in the 1990s by the Society of Environmental Toxicology and Chemistry (1991) and the International Organisation for Standardisation (ISO, 1997; 1998; 2000a; 2000b).  The latter’s LCA standards are known as the ISO 14040 series and fall under the general framework of the ISO 14000 environmental management standards. 

 

LCA consists of four components:

 

§         Goal and Scope Definition – specifies the objective of the assessment as well as the assumptions under which all subsequent analysis is done.  Under the SETAC framework, also specifies conditions for subsequent sensitivity and scenario analysis.

§         Inventory Analysis – involves the quantification of environmentally relevant material and energy flows of a system using various sources of data.

§         Impact Assessment – analyzes and compares the environmental burdens associated with the material and energy flows determined in the previous phase through classification, normalization, and weighting.

§         Improvement Analysis (SETAC, 1991) or Interpretation (ISO, 1997; 2000) – utilizes the results of the preceding stages to generate a decision or plan of action.  Under the ISO framework, this component also includes sensitivity analysis.

 

Objective

This purpose of this study was to assess the environmental impacts of biofuels (bioethanol and biodiesel) and natural gas derivatives (LNG, CNG and methanol) relative to conventional automotive fuels (gasoline and diesel), taking into account life-cycle considerations, in order to identify the best environmental option.

 

Model Description

The components of the EDIP-GREET LCA model are:

 

§         The GREET fuel-cycle inventory submodel.  The GREET (Greenhouse Gases, Regulated Emissions and Energy Use in Transportation) model was developed by Argonne National Laboratory in the mid-1990s for the United States Department of Energy (Wang, 1996).  This public-domain model can be downloaded from the Argonne website (www.transportation.anl.gov).  GREET version 1.5a (Wang, 1999) was used as the inventory submodel of EDIP-GREET.  It is coded in Microsoft Excel and Visual Basic, and its modular structure allows users to create new fuel pathways or modify existing ones.  The most recent version of this model is GREET 1.6, which is enhanced with graphic user interfaces (GUIs) and Monte Carlo simulation capability (Wang, 2001).  GREET simulations are limited to the following environmental flows: greenouse gas emissions (CO2, CH4 and N2O); miscellaneous air emissions (VOC, CO, NOx, PM10 and SOx); and energy usage (total, fossil and petroleum energy).

§         The EDIP impact assessment submodel.  The EDIP (Environmental Design of Industrial Products) method was developed in the mid-1990s by a consortium that included the Technological University of Denmark, the Confederation of Danish Industries, the Danish Environmental Protection Agency and private-sector partners.  The impact assessment procedure specified under the EDIP framework  relies on classification under predefined environmental impact categories, characterization using equivalency factors, and normalization with weighting using the concept of the person-equivalent (Hauschild and Wenzel, 1997; Wenzel et al, 1997).  In this study the EDIP impact assessment method was coded onto the GREET 1.5a spreadsheet to allow comprehensive analysis based on environmental impact themes (rather than just inventory flows) to be performed. Only eight impact categories are applicable to the inventory outputs of the GREET submodel: global warming (GWP), acidification (AP), photochemical ozone formation (POFP), nutrification (NP), human toxicity via inhalation (HTP), and resource depletion (RDP) of oil, coal and natural gas.

 

Description of Fuel Life Cycles

The fuel life cycles simulated in this study were:

 

§         Bioethanol – assumed to be produced from cellulosic agricultural waste using enzymatic hydrolysis and fermentation (Wang, 1999). 

§         Biodiesel – assumed to be coconut oil methyl ester (COME), which is produced by transesterification of coconut oil with methanol derived from NG (Tan et al., 2002). 

§         Liquefied Natural Gas (LNG) – assumed to be liquefied in centralized processing facilities and subsequently transported in cryogenic tanks to refueling sites.

§         Compressed Natural Gas (CNG) – assumed to be distributed by pipeline to refueling sites and compressed prior to sale.

§         Methanol – assumed to be produced from NG through steam methane reforming (Wang, 1999).

 

Simulation Parameters and Assumptions

In this study the following principal modifications were made in the GREET and EDIP submodels:

 

§         Assessments are normalized on a per vehicle-km basis.

§         Three different electricity generation scenarios were used for the marginal power requirements of the fuel life cycles.  Scenario A was based on the Philippine Department of Energy (2000) projections for the year 2009.  Scenarios B and C assumed that the marginal power demand was supplied using natural gas and renewables (e.g., solar or wind energy), respectively.  The three scenarios are summarized in Table 1.

Table 1  Marginal Power Generation Scenarios

 

Power Mix Scenario

A

B

C

Coal

45%

0%

0%

Oil 

10%

0%

0%

Natural Gas

16%

100%

0%

Others

29%

0%

100%

 

§         The natural gas specifications shown in Table 2 were used in place of the default properties embedded in GREET 1.5a.  These are based on the properties of Camago-Malampaya natural gas (Philippine DOE, 2000).

Table 2  Properties of Camago-Malampaya Natural Gas

Property

Specification

Net Heating Value

46 MJ/kg

Carbon Emission Factor

0.054 kg CO2/MJ

Sulfur Emission Factor

0

 

§         Fuel economy assumptions for vehicles are conservative.  Vehicles powered by bioethanol, LNG, CNG and methanol are assumed to be similar in efficiency to gasoline-powered units.  Diesel and biodiesel are also assumed to give identical fuel economies. 

§         The sulfur content of diesel was assumed to be .05% or 500 ppm by weight, based on the long-term targets specified by the guidelines of the Philippine Clean Air Act (Philippine DENR, 2000).  The default value in GREET 1.5a is .025% or 250 ppm.

§         Human toxicity potential of PM10 emissions was assumed to be 6.7 ΄ 103 m3/g, based on the ambient concentration limit of 150 mg/m3 specified in the implementing guidelines of the Philippine Clean Air Act (Philippine DENR, 2000).  No default value is specified in the EDIP model.

§         In this study the EDIP human toxicity potential of toluene (2.5΄ 103 m3/g) was used as a representative value for mixed volatile organic compounds (VOCs). 

 

Results and Discussion

Environmental impacts associated with air emissions and fossil fuel usage for Power Scenario A are shown in Figures 1 and 2, respectively.  Total impacts for bioethanol and biodiesel are significantly lower than those of gasoline and diesel, primarily due to sharp reductions in CO2 emissions (and GWP) and fossil fuel consumption.  Impacts of the two biofuels in other impact categories remain roughly comparable to those of conventional fuels.  Cumulative air emission impacts from CNG and methanol are slightly lower than those of gasoline.  LNG is actually the worst environmental option of the seven fuels evaluated.  In general, all three NG derivatives produce more total impacts than diesel.  As might be expected, the depletion impacts of LNG, CNG and methanol are skewed towards NG resource consumption. 

 

Air emission impacts and fossil fuel depletion scores for Power Scenario B are shown in Figures 3 and 4, respectively.  Corresponding data for Power Scenario C are given in Figures 5 and 6.  These two scenarios represent progressively cleaner grid electricity.  In general, the impacts of the liquid fuels show little sensitivity to power mix.  However, the environmental impacts LNG and CNG improve slightly relative to the other five fuels as electricity generation becomes cleaner.  This is attributable to the fact that significant electrical inputs are required for NG liquefaction, pipeline transmission and compression; reduction in impacts per kW-h of electricity also translate to reduced impacts for these two fuel cycles.  Total resource depletion impacts for Power Scenario C are also lower than those from the previous two scenarios because of the use of renewable energy for power generation. 

 

 

 

 

 

 

 

 

 

 

 

 

 


Figure 1  Air Emission Impacts of Alternative Fuels (Power Scenario A)

 

 

 

 

 

 

 

 

 

 

 

 

 


Figure 2  Resource Depletion Impacts of Alternative Fuels (Power Scenario A)

 

 

 

 

 

 

 

 

 

 

 

 

 


Figure 3  Air Emission Impacts of Alternative Fuels (Power Scenario B)

 

 

 

 

 

 

 

 

 

 

 

 

 


Figure 4  Resource Depletion Impacts of Alternative Fuels (Power Scenario B)

 

 

 

 

 

 

 

 

 

 

 

 

 


Figure 5  Air Emissions Impacts of Alternative Fuels (Power Scenario C)

 

 

 

 

 

 

 

 

 

 

 

 

 


Figure 6  Resource Depletion Impacts of Alternative Fuels (Power Scenario C)

Conclusions

Based on the specified assumptions, the results of this study indicate little or no environmental benefit from the use of NG as an automotive fuel.  Of the three options available for NG utilization, the environmentally optimal alternative is CNG.  In terms of total environmental impact, the methanol conversion pathway gives only marginal improvements relative to gasoline, while LNG fails to yield any gains at all.  The biofuel options, bioethanol and biodiesel, yield benefits primarily with respect to global warming and fossil fuel resource depletion; impacts in other categories are roughly comparable to those of conventional fuels.

 

These findings imply that alternative-fueled vehicles must be optimized to take advantage of specific fuel properties in order for potential environmental benefits to be realized; mere conversion of existing vehicle engines will most likely result in mediocre emissions reduction.  For example, bioethanol, LNG, CNG and methanol have high octane ratings that allow for higher compression ratios.  Engines designed specifically for these fuels can take advantage of their anti-knock properties.  They will have higher thermal efficiencies, resulting in improved fuel economy and reduced emissions on a per km basis.  

 

References

Azapagic, A. (1999).  Life Cycle Assessment and its Application to Process Selection, Design and Optimization.  Chemical Engineering Journal 73: 1 – 21.

Del Rosario, E. J., Chay, P. B., See, T. S., Deocadez, E. J., Moran, D. G. (1985).  Ethanol Production from Sugarcane and Sweet Sorghum.  Proceedings of the National Symposium on Renewable Energy Technologies, Manila, Philippines.

Eala, F. (1985). A Possible Long-Term Strategy for the Philippine Sugar Industry. Proceedings of the National Symposium on Renewable Energy Technologies, Manila, Philippines.

Hauschild, M. and Wenzel, H. (1997).  Environmental Assessment of Products.  Vol. 2: Scientific Background.  Chapman & Hall, London.

ISO 14040 (1997).  Environmental Management – Life Cycle Assessment – Principles and Framework.  International Organisation for Standardisation, Geneva.

ISO 14041 (1998).  Environmental Management – Life Cycle Assessment – Goal and Scope Definition and Inventory Analysis.  International Organisation for Standardisation, Geneva.

ISO 14042 (2000a).  Environmental Management – Life Cycle Assessment – Life Cycle Impact Assessment International Organisation for Standardisation, Geneva.

ISO 14043 (2000b).  Environmental Management – Life Cycle Assessment – Life Cycle Interpretation.  International Organisation for Standardisation, Geneva.

Lorilla, F. (1982).  The Philippine Alcogas Program.  Proceedings of the Regulatory Workshop on the Technology of Fuel Alcohol Production, Los Banos, Laguna, Philippines.

Philippine Department of Energy (2000).  Philippine Energy Plan 2000 – 2009.  Manila.

Philippine Department of Environment and Natural Resources (2000).  Implementing Rules and Regulations of Republic Act 8749 – Clean Air Act of 1999.  Manila.

Poulton, M. L. (1994).  Alternative Fuels for Road Vehicles.  Computational Mechanics Publications, Southampton.

SETAC (1991).  A Technical Framework for Life Cycle Assessments.  Society for Environmental Toxicology and Chemistry, Washington, D.C.

SETAC (1999).  Streamlined Life-Cycle Assessment: A Final Report from the SETAC North America Streamlined LCA Workgroup. Society for Environmental Toxicology and Chemistry, Washington, D.C.

Tan, R. R., Culaba, A. B. and Purvis, M. R. I. (2002b).  Land Use and Carbon Balance Implications of Coconut Biodiesel Utilization in the Philippine Automotive Transport Sector.  To be published.

Wang, M. (1996).  GREET 1.0 – Transportation Fuel Cycles Model: Methodology and Use.  Final Report ANL/ESD-33, Argonne National Laboratory, U.S.A.

Wang, M. (1999).  GREET 1.5 – Transportation Fuel Cycle Model.  Final Report ANL/ESD-39, Argonne National Laboratory, U.S.A.

Wang, M. (2001).  Development of GREET 1.6 Fuel Cycle Model for Transportation Fuels and Vehicle Technologies.  Final Report ANL/ESD/TM-163, Argonne National Laboratory, U.S.A.

Wenzel, H., Hauschild, M. and Alting, L. (1997).  Environmental Assessment of Products.  Vol. 1: Methodology, Tools and Case Studies in Product Development.  Chapman & Hall, London.

World Resources Institute (2000).  World Resources 2000 – 2001.  People and Ecosystems: The Fraying Web of Life.  Washington, D.C.

ABOUT THE AUTHORS

 

Raymond R. Tan is an Assistant Professor and former Vice-Chairman of the Chemical Engineering Department of De La Salle University – Manila.  He holds B.S. and M.S. degrees in Chemical Engineering from DLSU – Manila, and is a candidate for a Ph.D. in Mechanical Engineering.  He placed second in the November 1994 Chemical Engineering Board Exam, and then worked briefly as a Plant Engineer for the food processing conglomerate, Universal Robina Corporation, before joining De La Salle University in 1997.  He has since assumed a wide range of administrative and academic duties, including an assignment as a Visiting Lecturer and Researcher at the University of Portsmouth in the United Kingdom during the winter of 2001.  His current research interests include Environmental Systems Modeling, Life Cycle Assessment (LCA) and Environmental Decision Support Systems. 

 

Dr. Alvin B. Culaba is an Associate Professor and former Chair of the Mechanical Engineering Department and director of Graduate Studies of the College of Engineering, De La Salle University – Manila.  He has over fifteen years of experience in teaching, research, and consultancy.  His research interests include Life Cycle Assessment (LCA), Environmental Impact Analysis of Manufacturing Processes, Knowledge-Based Systems applications, Environmental Management Systems (EMS), Cleaner Production Technology, and Renewable Energy Systems.  His research outputs have been read in international and local conferences and were published in proceedings and international refereed journals.  He continues to sit as a member of the environment and energy planning/review committees of the Department of Science and Technology (DOST) and the Department of Environment and Natural Resources – Environmental Management Bureau (DENR – EMB).  He is an environment and energy consultant for various companies in the Philippines and currently, the EMS specialist of the International Initiative for a Sustainable Environment (IISE), a USAID-funded project of the government of the Philippines implemented by the DENR and DTI, and managed by Chemonics International.  He holds a Ph.D. in Mechanical/Environmental Engineering from the University of Portsmouth in the United Kingdom.