Life cycle assessment of lignocellulosic bioethanol: Environmental impacts and energy balance

Renewable and Sustainable Energy Reviews 42 (2015) 1349–1361

Contents lists available at ScienceDirect

Renewable and Sustainable Energy Reviews journal homepage: www.elsevier.com/locate/rser

Life cycle assessment of lignocellulosic bioethanol: Environmental impacts and energy balance Marjorie Morales a,b, Julián Quintero a,b, Raúl Conejeros a,b, Germán Aroca a,b,n a b

School of Biochemical Engineering, Pontificia Universidad Católica de Valparaiso, Av. Brasil 2085, Valparaiso, Chile Bioenercel S.A. Barrio Universitario s/n, Ideaincuba Building, Concepción, Chile

art ic l e i nf o

a b s t r a c t

Article history: Received 23 April 2014 Received in revised form 17 September 2014 Accepted 28 October 2014

A high number of life cycle assessment of the production of lignocellulosic bioethanol have been published to evaluate or to demonstrate its environmental benefits, in most of the cases the comparison of results and conclusions is difficult due the different methodological approaches of the analysts. The aim of this review is to synthesize and to analyze the available and updated information concerning to life cycle assessment (LCA) of lignocellulosic bioethanol and to compare its environmental impacts with conventional fossil fuels and the first-generation bioethanol. This review analyzes more than one hundred case studies reported in the last decade, whose main focus were the energy balance and the green house gas (GHG) emissions, considering the methods of analysis, assumptions and the most used impact categories. The studies showed a clear reduction in GHG emissions and ozone layer depletion, while results in other impact categories, such as acidification, eutrophication, human health and photochemical smog showed to be positively or negatively affected. The LCA results of the bioethanol production are highly influenced by the bioethanol proportion in the gasoline– bioethanol blend and by the source of raw material: GHG emissions reduction is less than 10% for E10 blend and higher than 40% for E85 and upper blends. When comparing raw materials for E100 blend, the highest GHG reduction per distance traveled were obtained for agricultural residues, with reductions between 82 and 91%. In the case of switchgrass and wood, the reduction values were between 53–93% and 50–62%, respectively. Most of the reviewed studies found that lignocellulosic bioethanol production is energetically sustainable, being this result dependent on the possibility of using by-products as fuel in a cogeneration system. It has been shown that lignocellulosic bioethanol have lower impacts in most of the categories and a positive energy balance compared with first generation bioethanol and gasoline. & 2014 Elsevier Ltd. All rights reserved.

Keywords: Life-cycle-assessment Lignocellulosic bioethanol Greenhouse gas emissions Energy balance Impacts categories

Contents 1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2. Bioethanol from lignocellulosic materials. . . . . . . . . . . . . . . . . . . . . . . . . . . . 3. Life cycle assessment methodology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4. Description of case studies analyzed . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5. Analysis of case studies considering greenhouse gases emissions. . . . . . . . . 6. Analysis of case studies considering energy balance and NET energy value 7. Other environmental impacts . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8. Key methodological issues . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9. Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Acknowledgments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

n

. . . . . . . . . . .

. . . . . . . . . . .

. . . . . . . . . . .

. . . . . . . . . . .

. . . . . . . . . . .

. . . . . . . . . . .

. . . . . . . . . . .

. . . . . . . . . . .

. . . . . . . . . . .

. . . . . . . . . . .

. . . . . . . . . . .

. . . . . . . . . . .

. . . . . . . . . . .

. . . . . . . . . . .

. . . . . . . . . . .

. . . . . . . . . . .

. . . . . . . . . . .

. . . . . . . . . . .

. . . . . . . . . . .

. . . . . . . . . . .

. . . . . . . . . . .

. . . . . . . . . . .

. . . . . . . . . . .

. . . . . . . . . . .

. . . . . . . . . . .

. . . . . . . . . . .

. . . . . . . . . . .

. . . . . . . . . . .

. . . . . . . . . . .

. . . . . . . . . . .

. . . . . . . . . . .

. . . . . . . . . . .

. . . . . . . . . . .

. . . . . . . . . . .

. . . . . . . . . . .

. . . . . . . . . . .

. . . . . . . . . . .

. . . . . . . . . . .

. . . . . . . . . . .

. . . . . . . . . . .

. . . . . . . . . . .

. . . . . . . . . . .

. . . . . . . . . . .

. . . . . . . . . . .

. . . . . . . . . . .

. . . . . . . . . . .

. . . . . . . . . . .

Corresponding author at: School of Biochemical Engineering, Pontificia Universidad Católica de Valparaiso, Av. Brasil 2085, Valparaiso, Chile. Tel.: þ 56322273755. E-mail address: [email protected] (G. Aroca).

http://dx.doi.org/10.1016/j.rser.2014.10.097 1364-0321/& 2014 Elsevier Ltd. All rights reserved.

. . . . . . . . . . .

. . . . . . . . . . .

. . . . . . . . . . .

. . . . . . . . . . .

. . . . . . . . . . .

1350 1350 1351 1351 1352 1354 1356 1357 1358 1359 1359

1350

M. Morales et al. / Renewable and Sustainable Energy Reviews 42 (2015) 1349–1361

1. Introduction Nowadays there is general consensus that climate change is mainly caused by anthropogenic activities due to the use of fossil fuels as primary energy source. In OECD countries the transport sector is responsible for at least 23% of global CO2 emissions with an increasing rate [1]. Global CO2 emissions reached 34 billion tons in 2011, a value 3% higher than the previous year, and higher than the annual average increase of 2.7% in the last decade [2]. The European Environment Agency (EEA) established a 5.2% reduction in CO2 emissions for 2012, considering as a base the emissions in 1990, to meet the agreements established in the Kyoto Protocol, though which is expected that biofuels will provide 27% of the total transport fuel by 2050 [3]. However, a report from the Bioethanol for Sustainable Transport Project (BEST) suggests that additional agreements are needed to meet the goal of the European Commission of 20% emissions reduction by 2020 [4]. Actions like blending mandates, tax incentives, and purchasing policies have been essential for the development of the production of biofuels in Europe, Asia, United States of America, Brazil and other countries. In USA a framework for biofuels have been implemented, it includes the U.S. Renewable Fuels Standard (RFS) and the Energy Independence and Security Act of 2007 [5] aiming to promote the use of biofuels in the transport sector. In the European Union the European Renewable Energy Directive was announced in 2009 [6]. Bioethanol is one of the leading candidates to replace a fraction of liquid fuels produced from oil. It can be used in mixtures up to 10% in gasoline without modification of the engines and also it can be used in higher proportion in the so-called flexi-fuel vehicles, able to use up to 85% alcohol in mixtures with gasoline, it is also possible to use 100% bioethanol in specially designed engines [7– 9]. Bioethanol is mainly produced from sugars and starch-rich materials around the world. USA and Brazil produce bioethanol from corn and sugarcane, respectively, meanwhile in Europe and China cereals are used as raw materials [7,10,11]. USA and Brazil are the leading bioethanol producers in the world, with the 89% of the total global production [12]. Although corn-based and sugarcane-based ethanol are promising substitutes to gasoline, the current production replace a minimal portion of the 3,8 trillion liters of fossil fuel consumed worldwide in the transport sector [12] and their production is under scrutiny due to the competition of the raw materials in the food market and the direct competition with land use for agriculture, affecting food security globally. In addition, the price of first generation bioethanol is uncertain due to the prices variations of the fossil fuels and the agricultural markets [13]. Many efforts have been carried out in the last decades to develop a commercial process for producing second generation bioethanol using lignocellulosic biomass, such as: crop residues (cane bagasse, corn stover, wheat straw, rice straw, rice husk, barley straw, sweet sorghum bagasse, olive stones and pulp), hardwood (aspen, poplar), softwood (pine, spruce), cellulose wastes (newsprint, waste office paper, recycled paper sludge), herbaceous biomass (alfalfa, hay, switchgrass, reed canary grass, coastal bermudagrass, thimothy grass), and municipal solid wastes [14]. Currently the most abundant lignocellulosic feedstocks derived from crop residues in USA, South America, Asia and Europe are corn stover, sugarcane bagasse, rice straw and wheat straw, respectively. Lignocellulosic biomass is a potential source of raw material to produce biofuels [12], but the sustainability of the processes must be shown. Hence, the selection or design of the biofuel production process must consider environmental and social criteria [15] in addition to process and capital costs that allow its economic feasibility, and a positive energy balance, Some organizations like:

the Global Bioenergy Partnership [16], the Roundtable on Sustainable Biofuels [17] and the International Organization for Standardization through the project ISO/PC 248 [18] have established a set of sustainability indexes for bioenergy production and use. A number of studies have been published in the last years related to the assessment of the environmental performance for the production and use of lignocellulosic bioethanol. The main purpose has been to compare the environmental impact of bioethanol produced from lignocellulose with bioethanol produced from sugar or corn, and gasoline, being the life cycle assessment (LCA) one of the most commonly used methodology. The environmental performance of the proposed processes is still unclear due to the scarce number of large-scale production facilities. LCA would allow to identify potential impacts at an early stage of process design, and provide the opportunity for making decisions and improve the process regarding its sustainability before to be scaled up or implemented [19]. Many reports have been published about LCA of lignocellulosic bioethanol production, in most of the cases it is not possible a direct comparison of the results due to differences on the focus and/or assumptions made by the LCA analysts [20]. The aim of this review is to analyze and synthesize the available and latest information concerning LCA of lignocellulosic bioethanol production and to compare its environmental impacts with conventional fossil fuels and first-generation bioethanol, by analyzing case studies regarding geographical location, feedstock, functional unit, allocations, assumptions, methods of analysis, and impact categories.

2. Bioethanol from lignocellulosic materials Bioethanol is named first or second generation according to the feedstock used for its production. First generation is that produced from feedstocks used for food and feed, such as cereals, tubers, high sugar content plants and agro-industrial processing coproducts. Second generation bioethanol is produced from nonfood raw material, such as: wood, tall grasses, crop residues, paper residues and other lignocellulosics materials [11]. Lignocellulose is mainly composed by cellulose, hemicellulose, lignin, extractives and ashes [8]. Cellulose is a homopolymer of glucose, while hemicellulose is composed by a variety of monomers of five and six carbons. Lignin is a complex amorphous aromatic polymer of high molecular weight and it is tightly bound to cellulose and hemicellulose [21,22]. Sugars in lignocellulosics are not easily available, due to this tight structure, and requires a previous pretreatment to make the hydrocarbon polymers available to saccharification and fermentation [9,11]. Processes for lignocellulosic bioethanol production consider the following steps: pretreatment, saccharification, fermentation, distillation and dehydration. The purpose of the pretreatment stage is to modify the macroscopic and microscopic structure of the material in such a way that the cellulose will be accessible to the action of acids or enzymes in the following step of saccharification or hydrolysis [23]. The saccharification of the cellulose is made by an acidic or enzymatic hydrolysis. Bacteria or yeasts carry out the fermentation of the sugars to bioethanol. The most common yeast used is Saccharomyces cerevisiae, which metabolize hexoses but it is not able to ferment pentoses such as xylose. Xylose is the second most abundant sugar in nature after glucose and it is an important fraction of the hemicellulose, which accounts up to one-third of the sugars in the lignocellulose [12]. Xylose fermentation and the presence of inhibitors are challenges to be overcome for increasing the economic feasibility of the processes. Nowadays there are important advances in the development of recombinant yeasts able to resist the harsh condition of

M. Morales et al. / Renewable and Sustainable Energy Reviews 42 (2015) 1349–1361

industrial operations [24] and also it has been discovered yeasts with the natural ability to ferment both sugars [25]. Key issues of the commercial production are: the selection of the operations for pretreatment and optimization of its conditions for making available as much carbohydrates present in the raw material as possible, to decrease the cost of the enzyme, to maximize the conversion of sugars to ethanol including pentoses, to valorize the use of lignin as co-product or energy source, and to minimize the energy and water demand. All these aspects have important impacts in the economic feasibility and environmental sustainability of the processes [26,27].

3. Life cycle assessment methodology The LCA is a process of compilation and evaluation of inputs (energy and material), outputs (product, by-products, pollutant and emissions) to determine the potential environmental impacts of a product system throughout its life cycle. This methodology was created to generate comparable information about the impacts of a product, process or service as a support mechanism for generating environmental awareness in the consumers, companies and governments [28,29]. LCA methodology can be applied to assess product improvement, product design or product comparison. It considers four methodological phases: (1) To define objective and limits of the system, (2) to determine life cycle inventory, (3) to quantify life cycle impacts categories, and (4) interpretation of the results. The system boundary (also called limit) is defined as a set of criteria specifying which unit processes are part of a product system [28], while the life cycle inventory is a list of inputs and outputs components of each step of the production process. The amount of each component is defined according to a metric called “functional unit“. Environmental impacts categories aims to quantify the effect of the emissions on defined environmental processes, i.e.: global warming, photochemical oxidation, ozone depletion, acidification, and others. [30]. Impact factors, as its name suggest, are used to quantify the environmental impacts, these are calculated through established formulas (methods) that convert inventory data into a common unit defined for each impact category, e.g.: “CO2 equivalent” for global warming. A number of software have been developed for helping in the LCA, most of them include database from many economic sectors that may differ in extension and quality. These software are free or commercial, and calculate environmental impacts from the provided inventory data. Table 1 shows the most used and reported software for LCA. The methods to carry out a LCA are classified, according to the aim of the study, in endpoint and midpoint. Endpoint methods are focused on the damage. They quantify the effects of the emissions on the objective to be protected: ecosystem, human health and

1351

resource availability. Midpoint methods are oriented to the impacts: human toxicity, ozone layer depletion, global warming, eutrophication, and others. The impact evaluated in midpoint methods can be further used to determine the damage categories in endpoint methods [28]. In the case of biofuels production, the limits of the systems are generally defined as “well to wheel” (WTW), where the impacts are evaluated considering the extraction or production of raw materials from the “well”, its transformation, distribution and final use: the “wheels”. Other approaches, such as “well to tank” (WTT) considers only raw material production and bioethanol production process, and “tank to wheel” (TTW) in which the improvement on the impacts factors are evaluated considering the use of the bioethanol in the engines [31,32]. In general, the analysis have been focused on upstream activities i.e.: agricultural or forestry, and downstream activities, i.e.: use in engines, with low emphasis on the bioethanol production process [33]. Fig. 1 illustrate the main components of the LCA methodology: Definition and limits of the study, life cycle inventory, quantification of life cycle impacts categories and analysis of the results. Also the components of the system boundaries of the life cycle of lignocellulosic bioethanol are agricultural stage, bioethanol production stage, and distribution and use.

4. Description of case studies analyzed Sixty case studies concerning LCA for bioethanol production, using different lignocellulosic raw materials, were selected from the available scientific literature in the last thirteen years, including papers, reviews and technical reports. Tables 2 and 3 synthesize the key issues and general considerations of each study. The reviewed studies cover a wide spectrum of raw materials: energy crops, agriculture residues, mainly wheat straw and corn stover, other lignocellulosic residues, such as forest residues, and municipal waste. The distribution of the studies, according to the type of raw material, is shown in Fig. 2. Most of the LCA were carried out in Europe and North America (see Fig. 3). These studies cover a wide variety of lignocellulosics feedstock and impact categories (see Table 2). Regarding the studies in Asia, these are mainly from Philippines [39], Thailand [72], India [40], China and Japan [50]. In Africa only one study has been carried out, it was done in South Africa [80]. There are a few LCA reported in Latin America, some of the most relevant are from Colombia [56], Cuba [70] and Brazil [81,82]. The reported LCAs consider both limits: WTT and WTW. In WTT analysis, the bioethanol energy content; measured in MJ, and mass; measured in kg of bioethanol, have been commonly used as functional unit, while in WTW analyses, the functional

Table 1 Some of the most known life cycle assessment software. Software

Developer

Country

Web site

SimaPro GaBi Bousted LCAmanager OpenLCA WRATE REGIS Euklid WISARD TEAM Umberto

Pré-consultants PE Europe GmbH Bousted Consulting SIMPPLE GreenDeltaTC UK Enviromental Agency Sinum AG Frauenhofer Institut Pricewaterhouse Coopers Ecobilan-Pricewaterhouse Coopers Ifeu-Institut

Holland Germany England Spain Germany England Switzerland Germany France France Germany

www.pre.nl www.gabi-software.com www.boustead-consulting.co.uk www.simpple.com www.greendeltatc.com www.enviroment-agency.gov.uk/wrate www.sinum.com www.ivv.fhg.de www.ecobilan.eu www.pwcglobal.com www.ifeu.de/umberto

1352

M. Morales et al. / Renewable and Sustainable Energy Reviews 42 (2015) 1349–1361

Fig. 1. System components of the life cycle of lignocellulosic bioethanol.

unit usually is vehicle-km. Fig. 4 shows the number of publications according to the functional unit used. Concern on global warming and climate change due to the gaseous emissions, and the debate on energy balance of liquid biofuels, have influenced the impacts categories that analysts consider in their studies. The number of publication addressing these aspects demonstrates this, all the reviewed papers consider greenhouse gases (GHG) emission, and almost all include energy balance, only 25 of the studies include other impact categories (see Table 4). Acidification (AC) and Eutrophication (EP) potentials were included in 40% of the studies, while Ozone Layer Depletion (OLD), Photochemical Smog (PS) and Human Toxicity (HT) were included in less than 20% of the studies. Fifteen studies reported impacts on Abiotic Resources Depletion (AD). Any attempt to classify the case studies by impact categories is hampered by the differences in objectives and scope, databases used, assumptions, and methodology. Taking into consideration this limitation, in this review, the impacts categories were classified in Greenhouse Gases Emissions, Energy Balance and Other Impact Categories. Most of the industrial processes have multiple input and output streams. However, normally only one of the outputs is of interest for the LCA and the analyst needs to determine how much of the inputs (material and energy) and the emissions associated to the process should be allocated for the production of each co-product [108]. Allocation method can be applied to bioethanol production using different criteria: volume allocation, mass allocation, energy allocation or economic allocation [107]. Allocations may represent a limiting factor of the LCA due to the ambiguity of the results when using different allocation methods [64]. Therefore, there is a high probability of getting substantial differences in the environmental impacts for a specific system depending on the allocation considered. Cherubini et al. [65] proposed the use of a sensitivity analysis of the variables involved in the allocation on the environmental impacts, which should take into account the variability of the assumed parameters, e.g.: use or destination of co-products, source or technology for energy supply. The ISO 14040 recommend avoiding allocation whenever is possible, either through division of the whole process into subprocesses related to co-products or by expanding the system boundaries to include the additional functions related to them. It is denominated system expansion or substitution [71]. It considered that the co-product can replace another input with an equivalent function, e.g.: the electricity produced in the process could replace all or part of the electric energy required by the process, or the solid residues generated, e.g.: stillage from distillation or ashes from boilers, can be used as soil amendment or

fertilizer [87]. Detailed information about Allocation Methods has been published elsewhere [108–111]. Table 2 shows that most of the reviewed cases (53%) did not consider allocation, but when it was included, 30% of the studies used substitution approach, e.g.: some studies assumed that the electricity produced from wastes was consumed in the bioethanol and enzyme production facilities. On the other hand, economic allocation was considered in 7% of the studies. 8% of the studies considered mass allocation, and energy allocation was used in only one study.

5. Analysis of case studies considering greenhouse gases emissions. The global transportation sector is responsible for 25% of the world’s greenhouse gas emissions, and this percentage is rising [11]. The production and use of biofuels produced from agricultural wastes or lignocellulosic material has the potential to reduce those emissions.[11]. According to Quirin et al. [32], the GHG emission sources in the life cycle of bioethanol are: the agricultural stage, the transport of supplies, the bioethanol production stage, and the distribution and use stages. The main GHG emissions are CO2, N2O and CH4. The nitrous oxide emissions come mainly from the application of nitrogen-based fertilizers and from the decomposition of the organic matter. The nitrogen from the N-fertilizer is emitted to the atmosphere as N2O. These emissions varies depending on the soil type, weather, crop type, agricultural practices, fertilizer types and application frequency [112]. Moreover, CH4 emissions are related to the nitrogenated fertilizer used, crop type and the decomposition of the organic material. Also NH4þ and/or NH3 released to the environment, and they can inhibit the oxidation of CH4 by methanotrophs [113,114], decreasing the CH4 consumption in soils and increasing its concentration in the atmosphere. A common conclusion from the reviewed studies (see Table 2) was the significant reduction of emissions compared to fossil fuels. These differences were dependent on the raw material and the bioethanol proportion in the blend gasoline–bioethanol, as can be seen in Fig. 5. When comparing different blending proportion, it was found that GHG reduction were less than 10% for blends with bioethanol content less than 10% (E10). While emissions reductions were higher than 40% and 50% for E85 and E100 blends, respectively. These results can be extended for different raw materials. The determination of the most contributing stage in GHG emissions depends on the bioethanol blend content, e.g.: 85% of the total GHG emissions in a E10 blend are due to the vehicle

Table 2 Main characteristics and impact categories considered of the reviewed publications. Location

Feedstock

Functional unit

GWP Energy AD AC EP OLD PS TH Fossil Software/model/database

Allocation

Refs

1999 2000 2000 2001 2001 2002 2002 2002 2002 2002 2003 2003 2003 2004 2004 2004 2005 2005

USA Switzerland Canada USA USA Philippine India Europe USA Europe England England Canada USA Global USA USA USA, Japan, China, Germany USA USA Global Canada Global USA Europe Colombia USA USA

Wood crop and switchgrass Industrial waste Switchgrass, corn stover, wheat straw Lignocellulosic (wood and herbaceous) Wood and herbaceous Corn stover Sugarcane bagasse Forest waste and agricultural waste Switchgrass Wood chips and wood crop Wood crop Wood chips y wheat straw Woods chips and lignocellulosic Lignocellulosic Wood, forest waste and agricultural waste Corn stover Lignocellulosic Wood crop and lignocellulosic

km L EtOH BTU; mile % Mile km Ton biomass km mg biomass km GJ Feedstock MJ EtOH km Ton dry biomass Ha, km km km km

x x x x x x x x x x x x x x x x x x

x x x x x

Corn stover Lignocellulosic Lignocellulosic Corn stover and switchgrass Wood crop, Forest waste and lignocellulosic Switchgrass Forest waste, agricultural waste and wheat straw Lignocellulosic Wood chips, switchgrass and lignocellulosic Wood crop (poplar)

x x x x x x x x x x

x x x x x x x x x

x x

x

x

x

x x x

2005 2005 2005 2005 2006 2006 2007 2007 2007 2007

Switchgrass

2007 2008 2008 2009

USA France Europe Spain

Switchgrass, wood (poplar) and forest waste Agricultural waste Forest waste and lignocellulosic Wood (poplar)

Mile Ha km km

x x x x

2009 2009 2009 2009 2009 2009 2009 2010

Spain Global Germany USA England USA Cuba USA

kg EtOH; km Ha; km 1000 kg biomass L Bioethanol MJ Fuel eq MJ EtOH 216 t sugar/d L EtOH

x x x x x x x x

2010 2010 2010 2010 2010 2010 2011 2011 2011

Thailand Austria Austria USA England Spain England USA South Africa

Herbaceous crops Wood crop and lignocellulosic Agricultural waste Forest waste, switchgrass and corn stover Biodegradable waste Wood crop By-products of sugar cane Wood chips, wheat straw, corn stover and industrial waste Lignocellulosic Switchgrass Agricultural waste Corn stover and switchgrass Wood (willow) Wood (poplar) and herbaceous Wood (willow) Wood chips (maple, beech and birch) Sugarcane Bagasse

L EtOH Per year Per year L EtOH Ton EtOH km Ton dry biomass 4 m3 dry wood MJ

x x x x x x x x x

x

x x x x x x x x x

x

x x

x x

x

x

x

x

x

x x

x x

x

x

x

x

x

x

x

x

x

x

x x x x x x x x x x x x x x x x x x

GREET Own author and literature US DOE in ExcelTM model GREET 1.6 GREET EDIP-GREET TEAM E2 database LBST model N.D. N.D. N.D. N.D. SimaPro GREET N.D. TEAM model DEAM database GREET NREL

N.A. Economic N.A. N.A. N.A. N.A. Substitution N.A. N.A. N.A. N.C. Economic N.C. N.A. N.A. N.C. N.A. N.C.

[34] [35] [36] [37] [38] [39] [40] [41] [42] [43] [44] [45] [46] [47] [32] [48] [49] [50]

x x x x x x x

EPA-TRACI GREET N.D. GREET GREET 1.6 EBAMM ADVISOR-NREL, TES SimaPro GREET NREL database

Substitution Substitution N.A. N.A. Substitution Substitution N.C. N.C. N.A N.C.

[51] [52] [7] [53] [54] [55] [10] [56] [57] [58]

Monte Carlo LCA model, EERE y USDA database GREET 1.7 BioFit project data N.D Own author and literature

Substitution

[59] [60] [61] [62] [63]

CMLCA N.D. Umberto Version 5, Ecoinvent – GaBi, WRATE, EASEWASTE, GREET modified: CA-GREET SimaPro-Ecoindicator SimaPro

N.A. Mass N.A. Mass and Economic Substitution N.A. Substitution N.A. N.C. N.A. Substitution Substitution

[64] [65] [66] [67] [68] [69] [70] [71]

CML 2000 SimaPro CML 2000 SimaPro CML 2000 GaBi 4.2 database EDIP 2003 CML UK data published by FSC Eco-indicator 99 SimaPro Impact 2002 þ

N.C. N.A. Substitution Substitution Substitution Mass N.A. Mass Substitution

[72] [73] [74] [75] [76] [77] [78] [79] [80]

x

x

x

x x x

x

x

x

x

x

x

x

x

x

x

x

x

x x

x x

x x x x x x

x x

x

x

x

x

x

x x x

x x x

x x x

x x x

x x x

x x x

x

x

x

x

x x

x

x x x x x x x x x

x x

x

x x

x x x x x

1353

2007 USA

Ha km km km km MJ EtOH;L EtOH km kg EtOH BTU EtOH MJ EtOH; ton dry biomass MJ Bioethanol

x x

x

M. Morales et al. / Renewable and Sustainable Energy Reviews 42 (2015) 1349–1361

Year

x x x x x x x x x

Wood Chips (willow) Herbaceous Wood (eucalyptus, black locust and poplar) Wood (eucalyptus) Wood Chips Cereal straws Sweden Spain Global Spain Global Italy

GWP: global warming potential, Energy: includes energy balance, AD: abiotic depletion, AC: acidification, EP: eutrophication, OLD: ozone layer depletion, PS: photochemical smog, HT: human ecotoxicity, Fossil: comparison with fossil fuel, EtOH: bioethanol, N.D.: not determined, N.A.: not apply, N.C.: not considered.

[85] [86] [87] [88] [89] [90] Economic Mass N.C. Substitution N.C. Substitution x x x x

x x x x x x x x x x x

x x x x x x

x

2012 2012 2012 2012 2012 2013

x x x x x x

x

x

x x x x

SimaPro 7.3 ecoinvent database Own author and literature NREL CMLCA NREL database /EFRAT y SimaPro 7.1 SimaPro and GWP 100

Energy Substitution Mass Substitution SUMMA SimaPro y CML 2 SimaPro ReCiPe Midpoint SimaPro and CML baseline 2000 v2.05 x

x x x x x x x x x x x x x x x x x

Ton EtOH kg EtOH km; kg Ethanol kg Ethanol; kg of waste paper Ha kg EtOH (variable value) kg EtOH; km km Per year Ton EtOH Sugarcane Bagasse Sugarcane bagasse and urban waste Wheat straw Waste papers 2012 2012 Brazil 2012 England 2012 England

x x x x

Allocation GWP Energy AD AC EP OLD PS TH Fossil Software/model/database Functional unit Feedstock Location Year

Table 2 (continued )

[81] [82] [83] [84]

M. Morales et al. / Renewable and Sustainable Energy Reviews 42 (2015) 1349–1361

Refs

1354

operation (combustion in the engine), as a result of the high gasoline proportion [10], while in a lower or zero gasoline proportion (E85 and E100) the main source of emissions is the production stage, followed by the bioethanol use stage [34,63]. Considering that usually high gasoline proportion blends are used in most of the countries, the vehicle engine is a technological key issue to be analyzed to decrease the GHG emissions. When comparing different raw material, differences in GHG emissions can be clearly observed at the same blend proportion, highest GHG reduction per distance traveled were obtained for agricultural residues, such as corn stover and wheat straw, with reductions between 82 and 91% for E100. In the case of other raw material, such as switchgrass and wood, 53–93% and 50–62% reduction are reported, respectively. Considering other bioethanol proportion blends, the highest GHG reduction for bioethanol production from wood were obtained by GBEP [16] for E90 blend and by Wang et al. [34] for E95 blend, with values of 107% and 105%, respectively. Percentage reduction greater than 100% were also reported for corn stover in a E85 blend by Sheehan et al. [48] with a 106% reduction by 1 km driven. The percentages over 100% indicates that the CO2 transferred from the atmosphere to the biomass is higher than the CO2 released from the production and use stages, hence the net balance of CO2 of the life cycle is negative. Pont [60] stated that a system for bioethanol production from lignocellulosic material with WTT boundaries, implicitly considers carbon captures by the raw material from the environment, leading to a negative net GHG emission. While in the case of TTW boundary, GHG emissions are positive due to the release of carbon during blend combustion, which is influenced by the engine considered. [35,38,41,60,63]. Other authors consider “zero CO2 equivalent emission” in some life cycle stages (production and/or usage stages), assuming that exactly the same amount of CO2 absorbed from the atmosphere, by the plants through photosynthesis, is released through bioethanol production and/or combustion, resulting in an almost closed CO2 cycle [32,34,58]. Fertilizer use is the most important parameter in the estimation of GHG from the agricultural stage [7]. While in the production stage, by-products disposal is one of the most relevant, even when including electricity production from wastes in a cogeneration unit. Alternative uses of co-product have been identified as one of the causes of the differences in GHG estimation. i.e.: when energy co-generation, using the solids residues from the process, is included in the bioethanol production stage, GHG emissions are significantly reduced compared with the possibility of using electricity from a coal power-station. Zhi Fu et al. [46] compared different wood sources from dendroenergetic crops and forestry residues, with or without energy cogeneration from lignin, they found that the GHG decrease 8% in cases with co-generation, compared to the cases using electricity from fossil fuels.

6. Analysis of case studies considering energy balance and NET energy value A high output (‘return’) of biofuel energy per unit of fossil energy used is desirable: the output/input energy ratio (briefly “energy ratio”) is used as an indicator of energy efficiency [115]. Energy ratio aims to evaluate the capacity of bioethanol to substitute non-renewable energy resources. It determines if bioethanol produced contains more useful energy than the required for its production. In general, the energy ratio, also called “energy balance” is defined as the ratio of the heat content of the fuel (in MJ/kg) to the non-renewable primary energy consumed to produce 1 kg of that fuel, considering the entire life cycle of the fuel [116]. This ratio is one of the most reported indicators concerning the performance of the bioethanol production and

M. Morales et al. / Renewable and Sustainable Energy Reviews 42 (2015) 1349–1361

1355

Table 3 GHG emissions and energy balance for LCA bioethanol cases. Feedstock

g CO2 eq/MJ

g CO2 eq/L

MJ/MJb

MJ/Lc

Co-generation

Reference

Corn

–  25a 90 – – 71–90 72 – – – 30–106 40  20a

– – – – – – – – – 557.1 – – – – – – – – – – – – 2863 1402 – – – – – – – 250 – – – – – – – – – – 270–290 – – – – – – – – – 515.8 – – – – – 754 150

1.38–2.51 0.5 1.25 1.3 0.3 – – 1.40 0,77 2.5 1.4–2.1 0.496 2.5 2 2.5 9.2–11.2 4.4 1.1 2.1–2.8 1.9 6.3–7.7 8.3–10.2 0.85 1.11 – 1–1.2 0.464 6.6–9.2 2.2.–2.6 2.62 5.82–8.55 – 1.5 1.48 0.55–0.56 1.23–2.2 3 1.94 1.3–2 8.10 3.25 0.64 – 0.78–1.79 1.34–2.33 – 5.2 – 5.6 1.08 2.23 4.7–4.8 2.5 1–1.5 – 13.1 11.31 0.69 1.4 –

– – – – – 3.8–7.2 7.2 – – – – – – – – – – – – – – – – – 3.5–6.3 – – – – – – 2.5 – – – – – – – – – – 2.3–3.3 –

✓ ✓ ✓ X X X ✓ ✓ X ✓ ✓ N.S. N.S. X N.S. ✓ ✓ X ✓ X X ✓ X ✓ X ✓ N.S. ✓ X ✓ ✓ ✓ ✓ X X ✓ N.S. N.S. ✓ ✓ ✓ X ✓ X ✓ N.S. X X ✓ X ✓ ✓ ✓ ✓ X N.S. ✓ X ✓ ✓

[91] [38] [58] [92] [38] [59] [59] [93] [94] [35] [44] [45] [43] [92] [41] [95] [96] [96] [97] [98] [99] [100] [72] [72] [101] [44] [45] [102] [102] [91] [58] [71] [69] [69] [44] [44] [41] [7] [38] [103] [104] [94] [71] [44] [44] [45] [92] [59] [105] [105] [93] [96] [35] [38] [59] [106] [93] [94] [35] [71]

Sugar beet

Sugarcane

Cassava

Wheat

Wood

Wood

Agricultural Waste

Switchgrass

Industrial Waste

 40a – 50.6–59.3 112.1–123.4 – – – 10 – – 65.5–73.8 56–77 29 – – – 2.42–3.55 – 1.6 9.1 4.0–40 4.0–40  30a –  90a – – – – 23–72 23–72 13 – 36 – – – 36.8–38.4 –  70a 2–6 – – – – –

– – 16.6 90.4 1.5 – – – – 19.1–20.6 21.5 – – – 2.3

N.S.: Not specified. a b c

Carbon sequestration during plant growth. Energy balance. Net energy value.

depends mainly on the limits of the system and the raw material due to the variation in composition and the amount of fossil fuel used in the cultivation, production of fertilizers and transport to the production facility. Therefore, the energy balance can be lower or higher than 1. Theoretically this value could approach infinity if only renewable energy is used in the raw material production, bioethanol production and distribution [11]. Other parameter

usually used is the Net Energy Value (NEV), which is the difference between the net energy outputs (energy content of bioethanol and electricity produced by co-generation) and the net energy inputs in the biofuel production cycle (both fossil and non-fossil), this is generally expressed in MJ/L Ethanol produced [101,105]. The EB and NEV values reported for bioethanol production of first and second generation are shown in Table 3. Most of the cases

1356

M. Morales et al. / Renewable and Sustainable Energy Reviews 42 (2015) 1349–1361

Fig. 2. Raw materials of studies.

Fig. 3. Location of studies.

analyzed for second-generation bioethanol concluded that energy ratio is higher than 1, in only four cases [44,94] this value was less than 1, these studies have in common that the lignin was not used for energy co-generation. Regarding cases for first-generation bioethanol production, 20% of the reported values are less than 1. In a number of studies, low values in the energy ratio may be due to the use of obsolete and inefficient technologies without energy co-generation systems [44]. Moreover, Zhi Fu et al. [46] compared the production of El0 blend considering different feedstock and energy sources with gasoline, concluding that the production of gasoline required more energy than the required for biomass processing, therefore bioethanol has a better energy balance, being not related with the inclusion or exclusion of a co-generation

system. Table 3 shows that, in most of the cases, the energy ratios are higher for lignocellulosic bioethanol than the ones for first generation bioethanol, due to use of lignin instead of fossil fuels for process energy [57].

7. Other environmental impacts Only a few of the reviewed studies include a wide range of environmental impacts indicators for second-generation bioethanol, less than half of the cases consider categories different to global warming and energy balance. Table 2 shows some of the most used impact categories in the LCA methodology: abiotic

M. Morales et al. / Renewable and Sustainable Energy Reviews 42 (2015) 1349–1361

1357

Fig. 4. Functional unit of studies. Table 4 Impact categories for lignocellulosic bioethanol in comparison with fossil fuels. Feedstock

Corn stover

Wood chips

Corn stover

Wood

Poplar

Switchgrass

Corn stover

Wheat straw

Wood chips

Eucalyptus

Black locust

Poplar

GWP AD AC EP OLD PS HT TE ME FE Ref.

↓ ↓ ↑ ↑ N.D. ↓ ↑ N.D. N.D. N.D. [39]

↓↑ N.D. ↑ ↑ ↓ N.D. ↑ N.D. N.D. N.D. [46]

↓ N.D. ↑ N.D. ↓ ↑ N.D. N.D. N.D. N.D. [48]

↓ N.D. ↑ ↑ N.D. ↓ N.D. N.D. N.D. N.D. [107]

↓ ↓ ↑ ↑ ↓ ↑ ↑ ↑ ↑ ↑ [77]

↓ ↓ ↑ ↑ ↓ ↑ ↑ ↑ ↑ ↑ [73]

↓ ↓ ↓ ↑ ↓ ↓ ↓ ↓ ↓ ↓ [74]

↓ ↓ ↓ ↑ ↓ ↓ ↓ ↓ ↓ ↓ [85]

↓ ↓ ↓ ↑ ↓ ↓ N.D. N.D. N.D. N.D.

↓ N.D. ↓ ↑ N.D. ↑ N.D. N.D. N.D. N.D. [87]

↓ N.D. ↓ ↓ N.D. ↑ N.D. N.D. N.D. N.D.

↓ N.D. ↑ ↑ N.D. ↑ N.D. N.D. N.D. N.D.

GWP: global warming potential. AD: abiotic depletion. AC: acidification. EP: eutrophication. OLD: ozone layer depletion. PS: photochemical smog. HT: human ecotoxicity. TE: terrestrial ecotoxicity. ME: marine aquatic ecotoxicity. FE: fresh water aquatic ecotoxicity. N.D.: not determined. ↓: decrease. ↑: increase.

depletion, acidification, eutrophication, ozone layer depletion, photochemical smog and different types of eco-toxicities. Nevertheless, depending on the impact method used, others environmental impacts categories, such as winter smog, summer smog, heavy metals and carcinogenic substances, are reported. Many cases reported the environmental impacts in a qualitative form, as shown in Table 4. The impact reported for abiotic depletion (AD) decreased for lignocellulosic bioethanol in relation to the value reported for gasoline, while acidification and eutrophication impacts increase for lignocellulosic bioethanol, due to the emissions of nitrogen compounds (NOx), sulfur compounds (SOx), the use of synthetic fertilizers and the sources of nitrogen used in the production of enzymes [10,32,46]. However, these impact categories need to be analyzed for each particular context, because they are highly influenced by the raw material, e.g.: the impacts obtained for the bioethanol production from organic residues could be lower than those obtained for cultivated crops [32,73,85]. In general, the impacts on the environment by the use of bioethanol, compared with the use of gasoline are lower in the impacts categories of heavy metals and ozone layer depletion, however, Zah et al. [107] and Lechon et al. [117] showed negative results for bioethanol in those categories. The carcinogenic

substances, considered in the different type of eco-toxicities categories, are important only when the raw material was an energy crop, therefore in the case of residues this impact is negligible [46]. Others studies, showed that bioethanol have a high impact on terrestrial toxicity and aquatic toxicity when energy is provided by a co-generation system using the residues of the process [56]. Due to the complexity of the determination of impacts on biodiversity and land use change there is not agreement on the calculation of these indicators. Neither have been established a clear definition of biodiversity [118,119]. However, Worldwatch [11] states that cellulosic bioethanol, produced from perennial grasses and trees, that protect vulnerable lands to erosion and restore lands degraded by overuse, can be positive on land use change and to increase biodiversity.

8. Key methodological issues The functional unit is one of the most important issues to take into account for accomplishing a comparative analysis of LCA due to its influence on the environmental impacts. In the reviewed literature, 6 types of functional units were identified (Fig. 4) and in

1358

M. Morales et al. / Renewable and Sustainable Energy Reviews 42 (2015) 1349–1361

Fig. 5. WTW studies: percent reduction GHG/distance for lignocellulosic bioethanol in comparison with gasoline. (A) Wood; (B) grass, corn stover and wheat straw.

some cases the final outcomes were documented in two different functional units. A well defined functional unit is important for comparing results allowing easier interpretations. One of the most appropriate is the energy content of the fuel, which allows a simple comparison between different bioethanol blends depending on the limits of the LCA. However, when the objective is related to the transport sector, the use of distance traveled seems to be more appropriate. Regarding reference system, 75% of the reviewed reports use the life cycle of the gasoline as reference system, however, assumptions and other considerations related to gasoline LCA are not well documented. Other studies use first-generation bioethanol or variations in the type of raw material, or a conversion process technology as reference system. The energy source used in the process is a key aspect for GHG emission and most of the studies included energy co-generation from the organic waste generated in the process. However, most of the studies do not provide detailed information of these systems, neither the environmental impact associated that could be incorporated as allocation. Another important issues are related to the CO2 balance. The most common methodological assumptions used considers a “closed carbon cycle”, also called “carbon neutrality”, which assumes that the CO2 absorbed from the atmosphere by the biomass, is released in the bioethanol production stage and its combustion. Other studies assumed that certain stages, such as bioethanol production or combustion, did not contribute with CO2

emissions. Other approaches assume that the CO2 consumed by the biomass growth is discounted from the CO2 released in further stages, which could result in negative or zero CO2 emissions. Those methodological assumptions should be verified by real measurement of atmospheric CO2 captured by the biomass, which is variable depending on the crop type and agricultural practices involved. The inclusion of concepts, such as “carbon cycle”, “carbon neutrality” or “carbon balance”, makes difficult the comprehension of the results obtained in the LCAs, due to multidisciplinary domain of this topic, that requires to establish a standardized terminology that can allow its understanding by all the stakeholders.

9. Conclusions This review reveled that the LCA methodology have been applied to the production of bioethanol from a wide range of lignocellulosic materials, most of them are residues generated from agro-industrial operations, mainly in Europe and North America. A number of functional unit and limits are used, however, depending on the system boundaries, energy content and travelled distance are the most common. The allocation method used generates variability in the LCA results and many authors selected the system boundaries expansion to avoid them. When comparing environmental impacts categories, Global Warming is the most used.

M. Morales et al. / Renewable and Sustainable Energy Reviews 42 (2015) 1349–1361

The studies showed a clear reduction in GHG emissions and ozone layer depletion, while results in other impact categories, such as acidification, eutrophication, human health and photochemical smog showed to be positively or negatively affected. The LCA results of the bioethanol production are highly influenced by the bioethanol proportion in the gasoline–bioethanol blend and by the source of raw material: GHG emissions reduction is less than 10% for E10 blend and higher than 40% for E85 and upper blends, being the main source the production stage. When comparing raw materials for E100 blend, the highest GHG reduction per distance traveled were obtained for agricultural residues such as corn stover and wheat straw, with reductions between 82 and 91%. In the case of switchgrass and wood, the reduction values were between 53–93% and 50–62%, respectively. Most of the authors shown that energy ratio was higher that one, and this ratio is highly dependent on the possibility of using by-products, such as lignin, as fuel in a cogeneration system. Consequently, co-generation using by-products is a key issue in the sustainability of bioethanol production. Even though a reduction in GHG emissions and a positive energy balance are achieved in the life cycle of lignocellulosic bioethanol, compared to fossil fuels alternatives, the assessment of other impact categories like acidification and eutrophication have not been intensively reported, probably because they become relevant only when intensive agricultural practices are required in the feedstock production, being the use of fertilizers the main contributors to those categories. The differences in keys methodological issues when applying LCA on lignocellulosic bioethanol make difficult the comparison of the environmental impacts of its production. However, it has been shown that lignocellulosic bioethanol have lower impacts in most of the categories and a positive energy balance compared with first generation bioethanol and gasoline.

Acknowledgments Financial support granted to M. Morales by CONICYT’s scholarship program (Comisión Nacional de Investigación Científica y Tecnológica) is gratefully acknowledged. This work was funded by Innova Chile Project 208-7320 Technological Consortium Bioenercel S.A. References [1] Seabra J, Macedo I, Chum H, Faroni C, Sarto C. Life cycle assessment of Brazilian sugarcane products: GHG emissions and energy use. Biofuels, Bioprod Biorefin 2011;5:519–32. [2] Olivier G, Janssens-Maenhout G, Peters J. Trends in global CO2 emissions. Netherlands: PBL Netherlands Environmental Assessment Agency, Insitute for Environment and Sustainability (IES) of the European Commission’s Joint Research Centre (JRC); 2012. [3] UNFCCC. Kyoto protocol reference manual. United Nations framework convention on climate change; 2008. [4] BEST. BioEthanol for sustainable transport: results and recommendations from the European BEST project, BEST project. Stockholm; 2009. [5] XVI of Public Law 110-140 (H.R.6). Energy independence and security act of 2007. USA; 2007. [6] Directive 2009/28/EC. Directive 2009/28/EC of the European parliament and of the council. 562009, Official Journal of the European Union. Strasbourg; 2009. [7] IEA. Biofuels for transport. An international perspective. International energy agency, France; 2005. p. 216. [8] Kumar D, Murthy G. Impact of pretreatment and downstream processing technologies on economics and energy in cellulosic ethanol production. Biotechnol Biofuels 2011;4:1–19. [9] Hamelinck C, Van Hooijdonk G, Faaij AP. Ethanol from lignocellulosic biomass: techno-economic performance in short-, middle- and long term. Biomass Bioenergy 2005;28:384–410. [10] Edwards R, Larivé J-F, Mahieu V, Rouveirolles P. Well-to-wheels analysis of future automotive fuels and powertrains in the European context. 2c ed. EU: CONCAWE, EUCAR and JRC; 2007. p. 88.

1359

[11] Worldwatch I. Biofuels for transportation. Global potential and implications for sustainable agriculture and energy in the 21st century. Washington DC: German Federal Ministry of Food, Agriculture and Consumer Protection (BMELV), Agency for Technical Cooperation (GTZ) and the Agency of Renewable Resources (FNR); 2006. [12] Limayem A, Ricke S. Lignocellulosic biomass for bioethanol production: current perspectives, potential issues and future prospects. Prog Energ Combust 2012;38:449–67. [13] FAO. Mercados de biocombustibles y efectos de las políticas. El estado mundial de la agricultura y la alimentación Biocombustibles: perspectivas, riesgos y oportunidades. Roma: División de Economía de las Naciones Unidas para la Agricultura y la Alimentación (ESA); 2008. [14] Cardona CA, Quintero JA, Paz IC. Production of bioethanol from sugarcane bagasse: status and perspectives. Bioresour Technol 2010;101:4754–66. [15] IEA. Technology roadmap. Biofuels for transport. France: International Energy Agency; 2011. [16] GBEP. Asociación Global para la Bioenergía. Indicadores de Sostenibilidad para la Bioenergía. Primera ed. GBEP, Italia; 2011. [17] RSB. The Roundtable on sustainable biofuels. Lausanne; 2012. [18] ISO. TC. 248 Project committee: sustainablilty criteria for bioenergy; 2009. [19] Quintero JA, Montoya MI, Sánchez OJ, Giraldo OH, Cardona CA. Fuel ethanol production from sugarcane and corn: comparative analysis for a Colombian case. Energy 2008;33:385–99. [20] Singh A, Pant D, Korres N, Nizami A-S, Prasad S, Murphy J. Key issues in life cycle assessment of ethanol production form lignocellulosic biomass: challenges and perspectives. Bioresour Technol 2010;101:5003–12. [21] Bhagwan G, Diptendu S, Rakesh C. Thermochemical conversion of biomass to liquids and gaseous fuels. Handbook of Plant Based Biofuels: Taylor & Francis Group LLC; 2009; 29–44 (Chapter 3). [22] Sarkar N, Kumar Ghosh S, Bannerjee S, Aikat K. Bioethanol production from agricultural wastes: an overview. Renewable Energy 2012;37:19–27. [23] Mosier N, Wyman C, Dale BE, Elander R, Lee YY, Holtzapple M, et al. Features of promising technologies for pretreatment of lignocellulosic biomass. Bioresour Technol 2005;96:673–86. [24] Hubmann G, Foulquie-́ Moreno M, Nevoigt E, Duitama J, Meurens N, Pais T, et al. Quantitative trait analysis of yeast biodiversity yields novel gene tools for metabolic engineering. Metab Eng 2013;17:68–81. [25] Nguyen NH, Suh S, Marshall C, Blackwell M. Morphological and ecological similarities: wood-boring beetles associated with novel xylose-fermenting yeasts, Spathaspora passalidarum gen. sp. nov. and Candida jeffriesii sp. nov. Mycol Res 2006;110:1232–41. [26] Davis S, Anderson-Teixeira K, DeLucia E. Life-cycle analysis and the ecology of biofuels. Trends Plant Sci 2009;14:140–6. [27] Margeot A, Hahn-Hagerdal B, Edlund M, Slade R, Monot F. New improvements for lignocellulosic ethanol. Curr Opin Biotechnol 2009;20:372–80. [28] ISO. 14040. Environmental management—life cycle assessment—principles and framworks. Switzerland: International Organization for Standardization; 2006. [29] ISO. 14044. Environmental management—life cycle assessment—requirement and guidelines. Switzerland: International Organization for Standardization; 2006. [30] Roy P, Tokuyasu K, Orikasa T, Nakamura N, Shiina T. Review: a review of life cycle assessment (LCA) of bioethanol from lignocellulosic biomass. Jpn Agric Res Q 2012;46:41–57. [31] Kaltschmitt M, Reinhardt G, Stelzer T. Life cycle analysis of biofuels under different environmental aspects. Biomass Bioenergy 1997;12:121–34. [32] Quirin M, Gärtner S, Pehnt M, Reinhardt GA. CO2 mitigation through biofuels in the transport sector. Status and perspectives. Germany: Institute for Energy and Environmental Research Heidelberg; 2004; 55. [33] MacLean HL, Spatari S. The contribution of enzymes and process chemicals to the life cycle of ethanol. Environ Res Lett 2009;4:1–10. [34] Wang M, Saricks C, Santini D. Effects of fuel ethanol use on fuel-cycle energy and greenhouse gas emissions. Illinois: Argonne National Laboratory; 1999; 32. [35] Fromentin A, Biollay F, Dauriat A, Lucas-Porta H, Marchand J-D, Sarlos G. Caractérisation de filières de production de bioéthanol dans le contexte helvétique. Lausanne: Laboratory de Systemes Energetiques and École Polytechnique Fédérale de Lausanne; 2000; 99. [36] Henderson S. Assessment of net emissions of greenhouse gases from ethanol-blended gasolines in Canada: lignocellulosic feedstocks. Richmond: Levelton Engineering and (S&T) Consultants; 2000. [37] Wang M. Development and use of GREET 1.6 fuel-cycle model for transportation fuels and vehicle technologies. Illinois: Argonne National Laboratory; 2001; 28. [38] GM/ANL. Well-to-wheel energy use and greenhouse gas emissions of advanced fuel/vehicle systems—North American Analysis. USA: General Motors Corporation, Argonne National Laboratory, BP, ExxonMobil and Shell; 2001. p. 34. [39] Tan R, Culaba A. Life-cycle assessment of conventional and alternative fuels for road vehicles. Manila: De La Salle University; 2002. [40] Kadam K. Environmental benefits on a life cycle basis of using bagassederived ethanol as a gasoline oxygenate in India. Energy Policy 2002;30: 371–84. [41] GM L, BP, ExxonMobil,Shell, TotalFinaElf. GM well-to-wheel analysis of energy use and greenhouse gas emissions of advanced fuel/vehicle systems —a European study. General Motors, L-B-Systemtechnik GmbH, BP, ExxonMobil, Shell, TotalFinaElf, Ottobrunn; 2002. p. 136.

1360

M. Morales et al. / Renewable and Sustainable Energy Reviews 42 (2015) 1349–1361

[42] McLaughlin SB, de la Torre Urgante DG, Garten CT, Lynd LR, Sanderson MA, Tolbert VR, et al. High-value renewable energy from prairie grasses. Environ Sci Technol 2002;36:2122–9. [43] Choudhury R, Weber T, Schindler J, Weindorf W, Wurster RGM. Well to wheel analysis of energy use and greenhouse gas emissions of advanced fuel/vehicle systems—a European study-results. Ottobrunn: LB Systemtechnik GmbH-LBST, General Motors-GM; 2002. [44] Woods J, Bauen A. Technology status review and carbon abatement potential of renewable transport fuels in the UK. London: Imperial College London; 2003; 88. [45] Elsayed MA, Matthews R, Mortimer ND. Carbon and energy balances for a range of biofuels options. UK: Sheffield Hallam University; 2003; 27. [46] Fu GZ, Chan A, Minns D. Life cycle assessment of bio-ethanol derived from cellulose. Int J Life Cycle Assess 2003;8:137–41. [47] Greene N. Growing energy: how biofuels can help end America’s oil dependence. USA: Natural Resources Defense Council; 2004. [48] Sheehan J, Aden A, Paustian K, Killian K, Brenner J, Walsh M, et al. Energy and environmental aspects of using corn stoves for fuel ethanol. J Ind Ecol 2004;7:117–46. [49] Wu M, Wu Y, Wang M. Mobility chains analysis of technologies for passanger cars and light-duty vehicles fueled with biofuels: applications of the GREET model to the role of biomass in America’s energy future (RBAEF) project. Illinois: Argonne National Laboratory; 2005; 68. [50] Delucchi M. A multi-country analysys of lifecycle emmisions from transportation fuels and motor vehicles. California: University of California and ITS UCDAVIS; 2005; 199. [51] Kim S, Dale BE. Life cycle assessment of various cropping systems utilized for producing biofuels: bioethanol and biodiesel. Biomass Bioenergy 2005;29:426–39. [52] Brinkman N, Wang M, Weber T, Darlington T. Well-to-wheels analysis of advanced fuel/vehicle systems—a North American study of energy use, greenhouse gas emissions, and criteria pollutant emissions. USA: General Motors Corporation, Argonne National Laboratory, Air Improvement Resoure Inc; 2005; 176. [53] Spatari S, Zhang Y, MacLean HL. Life cycle assessment of switchgrass- and corn stover-derived ethanol-fueled automobiles. Environ Sci Technol 2005;39:9750–8. [54] Fleming J, Habibi S, MacLean HL. Investigating the sustainability of lignocellulose-derived fuels for light-duty vehicles. Transp Res: Part D: Transport Environ 2006;11:146–59. [55] Farrell A, Plevin R, Turner B, Jones A, O’Hare M, Kammen D. Ethanol can contribute to energy and environmental goals. Science 2006;311:506–8. [56] Sánchez OJ, Cardona CA, Sánchez DL. Análisis de Ciclo de Vida y su Aplicación a la Producción de Bioetanol: Una Aproximación Cualitativa. Univ Eafit 2007;43:59–79. [57] Wang M, Wu M, Huo H. Life cycle energy and greenhouse gas emission impacts of different corn ethanol plant types. Environ Res Lett 2007;2:024001. [58] Huang J. Life cycle analysis of hybrid poplar trees for cellulosic ethanol. Massachusetts: Massachusetts Institute of Technology; 2007. [59] Groode T, Heywood J. Ethanol: a look ahead. Massachusetts, MA: Massachusetts Institute of Technology; 2007. [60] Pont J. Full fuel cycle assessment: well-to-wheels energy inputs, emissions, and water impacts. California, USA: TIAX LLC for California Energy Commission; 2007; 128. [61] Gabrielle B, Gagnaire N. Life-cycle assessment of straw use in bio-ethanol production: a case-study based on biophysical modelling. Biomass Bioenergy 2008;32:431–41. [62] Yuan J, Tiller K, Al-Ahmad H, Stewart N, Stewart C. Plants to power: bioenergy to fuel the future. Trends Plant Sci 2008;13:421–9. [63] González-García S, Gasol CM, Gabarrel X, Rieradevall J, Moreira MT, Feijoo G. Environmental profile of ethanol from poplar biomass as transport fuel in Southern Europe. Renewable Energy 2010;35:1014–23. [64] González-García S, Gasol CM, Gabarrel X, Rieradevall J, Moreira MT, Feijoo G. Environmental aspects of ethanol-based fuels from Brassica carinata: a case study of second generation ethanol. Renewable Sustainable Energy Rev 2009;13:2613–20. [65] Cherubini F, Bird ND, Cowie A, Jungmeier G, Schlamadinger B, WoessGallasch S. Energy- and greenhouse gas-based LCA of biofuel and bioenergy systems: key issues, ranges and recommendations. Resour Conserv Recycl 2009;53:434–47. [66] Uihlein A, Schebek L. Environmental impacts of a lignocellulose feedstock biorefinery system: an assessment. Biomass Bioenergy 2009;33:793–802. [67] Williams P, Inman D, Aden A, Heath G. Environmental and Sustainability Factors Associated With Next-Generation Biofuels in the United States: what Do We Really Know? Environ Sci Technol 2009;43:4763–75. [68] Stichnothe H, Azapagic A. Bioethanol from waste: life cycle estimation of the greenhouse gas saving potential. Resour Conserv Recycl 2009;53:624–30. [69] Prabhu A, Pham C, Glabe A, Duffy J. Detailed California-modified GREET pathway for cellulosic ethanol from farmed trees by fermentation. California, CA: California Environmental Protection Agency; 2009; 46. [70] Contreras A, Rosa E, Pérez M, Van Langenhove H, Dewulf J. Comparative life cycle assessment of four alternatives for using by-products of cane sugar production. J Cleaner Prod 2009;17:772–9. [71] Mu D, Seager T, Suresh RP, Zao F. Comparative life cycle assessment of lignocellulosic ethanol production: biochemical versus thermochemical conversion. Environ Manage 2010;46:565–78.

[72] Papong S, Malakul P. Life-cycle energy and environmental analysis of bioethanol production from cassava in Thailand. Bioresour Technol 2010;101:S112–8. [73] Cherubini F, Jungmeier G. LCA of a biorefinery concept producing bioethanol, bioenergy, and chemicals from switchgrass. Int J Life Cycle Assess 2010;15:53–66. [74] Cherubini F, Ulgiati S. Crop residues as raw materials for biorefinery systems —a LCA case study. Appl Energy 2010;87:47–57. [75] Spatari S, Bagley D, MacLean HL. Life cycle evaluation of emerging lignocellulosic ethanol conversion technologies. Bioresour Technol 2010;101:654–67. [76] Stephenson AL, Dupree P, Scott SA, Dennis JS. The environmental and economic sustainability of potential bioethanol from willow in the UK. Bioresour Technol 2010;101:9612–23. [77] González-García S, Moreira MT, Feijoo G. Comparative environmental performance of lignocellulosic ethanol from different feedstocks. Renewable Sustainable Energy Rev 2010:14. [78] Black MJ, Whittaker C, Hosseini SA, Diaz-Chavez R, Woods J, Murphy J. Life cycle assessment and sustainability methodologies for assessing industrial crops, processes and end products. Ind Crops Prod 2011;34:1332–9. [79] Neupane B, Halog A, Dhungel S. Attributional life cycle assessment of woodchips for bioethanol production. J Cleaner Prod 2011;19:733–41. [80] Melamu R, Von Blottnitz 2nd H. Generation biofuels a sure bet? A life cycle assessment of how things could go wrong J Cleaner Prod 2011;19:138–44. [81] Agostinho F, Ortega E. Energetic-environmental assessment of a scenario for Brazilian cellulosic ethanol. J Cleaner Prod 2012. [82] Dias M, Junqueira T, Cavalett O, Cunha M, Jesus C, Rossell C, et al. Integrated versus stand-alone second generation ethanol production from sugarcane bagasse and trash. Bioresour Technol 2012;103:152–61. [83] Borrion AL, McManus M, Hammond G. Environmental life cycle assessment of bioethanol production from wheat straw. Biomass Bioenergy 2012;47:9–19. [84] Wang L, Templer R, Murphy R. A life cycle assessment (LCA) comparison of three management options for waste papers: bioethanol production, recycling and incineration with energy recovery. Bioresour Technol 2012;120:89–98. [85] González-García S, Iribarren D, Susmozas A, Dufour J, Murphy R. Life cycle assessment of two alternative bioenergy systems involving Salix spp. biomass: bioethanol production and power generation. Appl Energy 2012;95:111–2. [86] González-García S, Luo L, Moreira MT, Gumersindo F, Huppes G. Life cycle assessment of hemp hurds use in second generation ethanol production. Biomass Bioenergy 2012;36:268–79. [87] González-García S, Moreira MT, Gumersindo F, Murphy J. Comparative life cycle assessment of ethanol production from fast-growing woods crops (black locust, eucalyptus and poplar). Biomass Bioenergy 2012;39:378–88. [88] González-García S, Moreira MT, Feijoo G. Environmental aspects of eucalytus based ethanol production and use. Sci Total Environ 2012;438:1–8. [89] Pawelzik P, Qiong Z. Evaluation of environmental impacts of cellulosic ethanol using life cycle assessment with technological advances over time. Biomass Bioenergy 2012;40:162–73. [90] Patrizi N, Caro D, Pulselli F, Bjerre AB, Bastianoni S. Environmental feasibility of partial substitution of gasoline with ethanol in the Province of Siena (Italy). J Cleaner Prod 2013;47:388–95. [91] Lorenz D, Morris D. How much energy does it take to make a gallon of ethanol? Minneapolis: Institute of Local-Self-Reliance; 1995; 8. [92] Von Blottnitz H, Curran MA. A review of assessment conducted on bioethanol as a transportation fuel from a net energy, greenhouse gas and environmental life cycle perspective. J Cleaner Prod 2007;15:607–19. [93] Vadas PA, Barnett KH, Undersander DJ. Economics and energy of ethanol production from alfalfa, corn, and switchgrass in the Upper Midwest, USA. Bioenergy Res 2008;1:44–55. [94] Pimentel D, Patzek T. Ethanol production using corn, switchgrass, and wood; biodiesel production using soybean and sunflower. Nat Resour Res 2005;14: 65–76. [95] Macedo I. Greenhouse gas emissions and energy balances in bio-ethanol production and utilization in Brazil. Biomass Bioenergy 1998;14:77–81. [96] García C, Fuentes A, Hennecke A, Riegelhaupt E, Manzini F, Masera O. Lifecycle greenhouse gas emissions and energy balances of sugarcane ethanol production in Mexico. Appl Energy 2011;88:2088–97. [97] Khan A, Fox R. Net energy analyses of ethanol production from sugarcane in Northeast Brazil. Biomass 1982;2:213–21. [98] Rosenschein AD, Hall DO. Energy analysis of ethanol production from sugarcane in Zimbabwe. Biomass Bioenergy 1991;1:241–6. [99] Turdera M. Energy balance, forecasting of bioelectricity generation and greenhouse gas emission balance in the ethanol production at sugarcane mills in the state of Mato Grosso do Sul. Renewable Sustainable Energy Rev 2013;19:582–8. [100] Coelho S, Goldemberg J, Lucon O, Guardabassi P. Brazilian sugarcane ethanol: lessons learned. Energy Sustainable Dev 2006;10:26–39. [101] Liu B, Wang F, Zhang B, Bi J. Energy balance and GHG emissions of cassavabased fuel ethanol using different planting modes in China. Energy Policy 2013;56:210–20. [102] Rosenberger A, Kaul HP, Senn T, Aufhammer W. Improving the energy balance of bioethanol production from winter cereals: the effect of crop production intensity. Appl Energy 2001;68:51–67. [103] Vande Walle I, Van Camp N, Van de Casteele L, Verheyen K, Lemeur R. Shortrotation forestry of birch, maple, poplar and willow in Flanders (Belgium) I— Biomass production after 4 years of tree growth. Biomass Bioenergy 2007;31:267–75.

M. Morales et al. / Renewable and Sustainable Energy Reviews 42 (2015) 1349–1361

[104] Fantozzi F, Buratti C. Life cycle assessment of biomass chains: wood pellet from short rotation coppice using data measured on a real plant. Biomass Bioenergy 2010:34. [105] Luo L, Van der Voet E, Huppes G. An energy analysis of ethanol from cellulosic feedstock—corn stover. Renewable Sustainable Energy Rev 2009;13:2003–11. [106] Schmer MR, Vogel KP, Mitchell RB, Perrin RK. Net energy of cellulosic ethanol from switchgrass. PNAS 2008;105:464–9. [107] Zah R, Böni H, Gauch M, Hischier R, Lehmann M, Wäger P. Life cycle assessment of energy products: environmental impacts assessments of biofuels. St. Gallen: Empa Technology and Society Lab; 2007. XVI. [108] Curran MA. Studying the effect on system preference by varying coproduct allocation in creating life-cycle inventory. Environ Sci Technol 2007;41: 7145–51. [109] Kodera K. Analysis of allocation methods of bioethanol LCA. Amsterdam: Leiden University; 2007. [110] Luo L, Van der Voet E, Huppes G. Udo de Haes HA. Allocation issues in LCA methodology: a case study of corn stover-based fuel ethanol. Int J Life Cycle Assess 2009;14:529–39. [111] Heijungs R, Guinée JB. Allocation and ‘what-if’ scenarios in life cycle assessment of waste management systems. Waste Manage 2007;27:997–1005. [112] Smeets EMW, Bouwman LF, Stehfest E, Van Vuuren DP, Posthuma A. Contribution of N2O to the greenhouse gas balance of first-generation biofuels. Global Change Biol. 2009;15:1–23.

1361

[113] Bronson KF, Mosier AR. Sppression of methane oxidation in aerobic soil by nitrogen fertilizers, nitrification inhibitors, and urease inhibitors. Biol Fertil Soils 1994;17:263–8. [114] Cáceres M, Gentina JC, Aroca G. Oxidation of methane by Methylomicrobium albun and Methylocystis sp. in the presence of H2S and NH3. Biotechnol Lett 2014;36:69–74. [115] Vries S, Van der Ven G, Van Ittersum M, Giller K. Resource use efficiency and environmental performance of nine major biofuel crops, processed by firstgeneration conversion techniques. Biomass Bioenergy 2010;34:588–601. [116] Gnansounou E, Dauriat A. Energy balance of bioethanol: a synthesis. European biomass conference. Paris, France; 2005. [117] Lechon Y, Cabal H, de la Rú a C, Lago C, Izquierdo L, Sáez R. Life cycle environmental aspects of biofuel goals in Spain. Scenarios 2010. In: 15th European biomass conference and exhibition—from research to market deployment. Berlin; 2007. [118] Koellner T, Scholz RW. Assessment of land use impacts on the natural environment. Part 2: Generic characterization factors for local species diversity in Central Europe. Int J Life Cycle Assess 2008;13:32–48. [119] Menichetti E, Otto M. Energy balance & greenhouse gas emissions of biofuels from a life cycle perspective. In:Biofuels: environmental consequences & implications of Changing land use. Gummersbach; 2008. p.81-109.