Comparative environmental life cycle assessment of conventional vehicles with different fuel options, plug-in hybrid and electric vehicles for a sustainable transportation system in Brazil

Accepted Manuscript Comparative environmental life cycle assessment of conventional vehicles with different fuel options, plug-in hybrid and electric vehicles for a sustainable transportation system in Brazil Lidiane La Picirelli de Souza, Electo Eduardo Silva Lora, José Carlos Escobar Palacio, Mateus Henrique Rocha, Maria Luiza Grillo Renó, Osvaldo José Venturini PII:

S0959-6526(18)32585-X

DOI:

10.1016/j.jclepro.2018.08.236

Reference:

JCLP 14020

To appear in:

Journal of Cleaner Production

Received Date: 28 January 2018 Revised Date:

21 August 2018

Accepted Date: 22 August 2018

Please cite this article as: de Souza LLP, Lora EES, Palacio JoséCarlosEscobar, Rocha MH, Renó MLG, Venturini OsvaldoJosé, Comparative environmental life cycle assessment of conventional vehicles with different fuel options, plug-in hybrid and electric vehicles for a sustainable transportation system in Brazil, Journal of Cleaner Production (2018), doi: 10.1016/j.jclepro.2018.08.236. This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

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Comparative environmental life cycle assessment of conventional vehicles with different fuel options, plug-in hybrid and electric vehicles for a sustainable transportation system in Brazil Lidiane La Picirelli de Souzaa*, Electo Eduardo Silva Loraa, José Carlos Escobar Palacioa, Mateus a

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Henrique Rochaa, Maria Luiza Grillo Renóa, Osvaldo José Venturinia NEST – Excellence Group in Thermal Power and Distributed Generation, Institute of Mechanical Engineering, Federal University of Itajubá (UNIFEI), Av. BPS 1303, Itajubá, Minas Gerais State, CEP: 37500-903, Brazil. *

Corresponding author: [email protected] (L.L.P. de Souza), [email protected] (M.H. Rocha),

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ABSTRACT

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[email protected] (E.E.S. Lora).

The principal motivation of this work is to evaluate the existing fuel use (gasoline or ethanol) and new alternative source of power supply (electricity) for vehicles in Brazil, and to assess potential to consume less petroleum and nonrenewable fuels, in order to reduce the air pollution and greenhouse gas emissions. In the literature, there are several relevant published works which focus on this topic for developed countries, and other countries, such as Brazil are not fully investigated; therefore this gap was a motivation for this study. The methods consider the fuel production, electricity generation and powertrain production, the vehicle use phase stages and powertrain end of life only, which

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includes the recycling of vehicles and batteries. The goal and scope of this study is to evaluate and to compare the environmental impacts of vehicles in the Brazilian context. A life cycle assessment is carried out in this paper to assess the well-to-wheels for different scenarios of fuels consumption and powertrains configurations for a vehicle. The five analyzed scenarios are: conventional internal combustion engine vehicle fueled by gasoline, conventional internal

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combustion engine vehicle fueled by hydrous ethanol, conventional internal combustion engine vehicle fueled by a mixture of gasoline and hydrous ethanol (flex-fuel vehicle), plug-in hybrid electric vehicle and battery electric vehicle. The common functional unit assumed for the analysis was 1.0 km traveled. The results show that the scenarios that use

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ethanol as fuel have higher environmental impacts for the categories of acidification, eutrophication and photochemical oxidation. The scenarios using gasoline have the higher impacts for abiotic depletion, fossil fuels abiotic depletion potential and global warming potential. Vehicles using lithium ions batteries have the highest impacts for human toxicity. The battery electric vehicle has smallest environmental impacts in general way, followed by vehicles using ethanol. The Brazilian government should increase its investment and develop the use of electric vehicles, since the country’s electric mix is renewable, as well as further encourage the use of ethanol, since it generates less environmental impacts than gasoline.

Keywords: Life cycle assessment; Environmental impact assessment; Automotive fuel; Internal combustion engine vehicle; Plug-in hybrid electric vehicle; Battery electric vehicle.

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HIGHLIGHTS

Engines fueled by ethanol are environmental favorable in four impact categories.

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Ethanol engines have the worst environmental performance in three impact categories.

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Electric vehicles yield higher human toxicity values due to the electricity generation.

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Electric vehicles can reduce the greenhouse gas emissions compared to combustion vehicles.

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Vehicles use phase have the greatest environmental impacts in all analyzed categories.

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Abbreviations

Acrylonitrile Butadiene Styrene

ACP

Acidification Potential

ADP

Abiotic Depletion Potential

BEV

Battery Electric Vehicle

BOD

Biochemical Oxygen Demand

CFCs

Chlorofluorocarbons

CML

Institute of Environmental Science (CML) of Leiden University

COD

Chemical Oxygen Demand

EOL

Endo-of-Life

ERM

Environmental Resources Management Limited

ETP

Eutrophication Potential

EUCM

European Union Council of Ministers

EVs

Electric Vehicles

FETP

Freshwater Aquatic Ecotoxicity Potential

FCEV

Fuel Cell Electric Vehicle

FDP

Fossil Fuels Depletion Potential

FFVs

Flex Fuel Vehicles

FU

Functional Unit

GHG

Greenhouse Gases

GWP

Global Warming Potential

HBFCs

Hydrobromofluorocarbons

HCFCs

Hydrochlorofluorocarbons

HEV

Hybrid Electric Vehicle

HTP

Human Toxicity Potential

ICE

Internal Combustion Engine

ICEV

Internal Combustion Engine Vehicle

ICEVe

Internal Combustion Engine Vehicle fueled by hydrous ethanol

ICEVf

Internal Combustion Engine Vehicle fueled by a mixture of Gasoline C and anhydrous ethanol

ICEVg

Internal Combustion Engine Vehicle fueled by Gasoline C

ISO

International Organization for Standardization

LCI LCIA

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LCA

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ABS

Life Cycle Assessment

Life Cycle Inventory Life Cycle Impact Assessment

LHV

Lower Heating Value

Li-ion

Lithium-ion Battery

NER

Net Energy Ratio

NMVOCs

Non-Methane Volatile Organic Compounds

ODP

Ozone Depletion Potential

PAHs

Polycyclic Aromatic Hydrocarbons

PHEV

Plug-in Hybrid Electric Vehicle

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Photochemical Oxidant Formation Potential

ppm

Parts per million

Proalcool

Brazilian Alcohol Program

TEP

Terrestrial Ecotoxicity Potential

VOCs

Volatile Organic Compounds

WTWs

Well-to-Wheels

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POP

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1. Introduction

Climate scientists have observed that CO2 concentrations in the atmosphere have been increasing significantly over the past century, compared to the pre-industrial era (about 280 ppm). In October of 2016 the CO2 concentration (402.31 ppm) was about 42% higher than in the midoccurred in the level of CH4 and of N2O (Igliński and Babiak, 2017).

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1800s, with an average growth of 2 ppm/year in the last ten years. Significant increases have also

Nowadays, road transport is responsible for a significant and growing share of global anthropogenic emissions of CO2 (Offer et al., 2010). The main cause is the dependence on petroleum-based fuels (Bauer et al., 2015). The tendency is to increase with the growth of fleet of

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vehicles. According to the Brazilian Automotive Industry Association between 2003 and 2015 the fleet of vehicles gets duplicated. In 2007 the Brazilian passenger vehicles fleet were around 30

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million automobiles, which got to 50 million vehicles in 2015 (Rodrigues et al., 2018). As the result of the increases of the automobile fleet other problems intensified corresponding to the environmental charges, as a consequence of the energetic consumption, emissions, discharges and wastes volumes (Lombardi et al., 2017). At the time the automotive industry is facing huge challenges in relation to the performance of its traditional technology, based on the Internal Combustion Engine Vehicle (ICEV) that is criticized for being unsustainable at middle and long

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range, basically due to the emission of polluting gases in the combustion process and because it is also a low efficiency engine devices (Arena et al., 2013). In addition, to this that industry is also suffering a strong pressure from the regulatory

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agencies, which demand actions for the diminishing of the environmental impacts caused by the vehicles. In this way, many aspects related to the sustainability, originally related to academic researchers and industrial manufacturers are getting the general public attention driving the

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consumers to change their opinion and the buying patterns (Karaaslan et al., 2018). To encounter answers to climate change and to the dependence on petroleum fuels (accompanied by their fluctuating prices) engineers and policy makers are looking for sustainable alternatives of fuels and vehicles, which are less harmful and have the ability to use limited resources at higher efficiencies (Ramachandran and Stimming, 2015). Along sustainable fuels are the biofuels. These have been used for years as a way to increase energy self-sufficiency, reduce import costs and strengthen domestic agricultural development. Since 2000, the global biofuels supply has increased by a factor of 4% of the world’s transport fuels in 2015. This significant rise is attributed to policies such as blending mandates, which foster greater utilization and may partly insulate biofuels during times of oil price (Araújo et al., 2017). 5

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In 2015, Brazil and United States produced approximately 70% of the global biofuel supply, consisting primarily of sugarcane-based and corn-based ethanol, respectively. European Union and Asia represent emergent markets that have developed in the last two decades. European Union focuses on biodiesel from oil waste and fats, soybean, rapeseed and palm oil. In Asia, the biofuel feedstock is centered on sugarcane, corn, wheat and cassava for the formation of an international biofuel commodities market (Joshi et al., 2017).

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The biofuel has been evolved from the first to the fourth generation which is primarily differed in the feedstocks and production technologies. The primary first generation biofuel are biodiesel and bioethanol. For these biofuels, there are technological advancements in feedstock production as highlighted by Maroušek (2014) which developed a novel technique for continuous

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disintegration of oilseeds for biodiesel production. The operating principle consists of gasification of deshelled oilseeds mash using small amounts of gas. These were subsequently subjected to the

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pressure waves generated externally by underwater high-voltage discharges, which are then followed by expansion of the water plasma.

Maroušek and Kwan (2013) performed a technical study of another non-thermal oil extraction technology for biodiesel production. This technology is performed in the apparatus, which allows subjecting the flow of the phytomass to the pressure shockwaves that are being transmitted in the liquid medium. The pressure shockwaves (50–60 MPa) are following the rapid expansion of water

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plasma, which is initiated by a high voltage discharge as traceable.

Maroušek et al. (2013) carried out a study to evaluate statistically the kinetic data regarding the intensity of maceration and subsequent pretreatment of Jatropha curcas L. seeds with pressure shockwaves (50 MPa–60 MPa) in order to obtain vegetable oil for biodiesel production.

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The same procedure was followed by Maroušek et al. (2012). The authors concluded that the application of pressure shock waves produced by under-water high-voltage discharges on unground

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and inadequately soaked seeds of Jatropha curcas L. has a negligible impact on oil extraction. However, the impact increases after husks are ground and intensively macerated in an excess of an organic solvent such as methanol. The depth of penetration of the solvent and the number of shock waves seem to be very important and may increase the oil yield up to 94%. For the second generation biofuels, the lignocellulosic biomass is identified as the main feedstock. The potential feedstocks are herbaceous and woody plants, agricultural and forestry residues, municipal and industrial solid wastes. The main advantage of this technology is that the lignocellulosic biomass does not require usage of agricultural land (Liew et al., 2014). Third and fourth generation biofuel is mainly derived from algae. Recent research activities have been focused on the search for ideal combination of algal species with high lipid content and their optimum growth conditions (Dutta et al., 2014). 6

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Other alternative to reduce CO2 emissions from road transport are the Electric Vehicles (EVs) (Figenbaum, 2017). The Germany is a country that has invested in this technology. The Germany’s Federal Council approved in 2016 a resolution on banning ICEV fueled by fossil fuels from 2030 onward. Germany has a carbon reduction goal of 95% by 2050, which will likely require significant levels of vehicle electrification. According that resolution, automobiles with Internal Combustion Engines (ICEs) sold up to 2030 must only be driven until the year 2050, since after that date will

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not allowed the circulation of any type of car with ICE running in Germany, only EVs. However, should be noted that this resolution does not have the force of law and it is unclear how the country will move to forbid ICEVs sales in opposition to the Germany’s powerful automotive manufacturing industry (Heinrichs and Jochem, 2016).

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China leads the world in EV usage, with about 649,000 EVs on its roads and an ambitious plan to deploy 5 million EVs by 2020. The U.S. ranks second globally, with fewer than 565,000

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EVs. Japan ranks third globally, with 152,000 EVs on its road, Norway is the fourth country in the world having 135,000 EVs and the Netherlands has the fifth position with 115,000 EVs on its road. Currently, Norway have joined the Netherlands intends to phase out all fossil fuel powered automobiles by 2025. In 2016, only 2 million EVs and Hybrid Electric Vehicles (HEVs) were on the road worldwide, about 0.2% of the global fleet (Cecere et al., 2018). However, some key issues remain unanswered, such as, whether there will be sufficient

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renewable energy supplies to power vast new fleets of EVs and also whether lithium and cobalt reserves will be sufficient to meet the demand for these minerals in construction of new batteries. Besides that, if EVs are charged with fossil fuel generated electricity, the obtained results in relation to the reduction of Greenhouse Gases (GHG) emissions will not be very significant (Ruiz et al.,

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2018).

Therefore, it is important to evaluate the environmental impacts of the different alternative

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scenarios of fuels consumption and vehicles’ configurations in Brazilian conditions. Thus, this work represents an important scientific and technological novelty considering that according to Teixeira and Sodré (2018) for replacement of 5% of the Brazilian vehicle fleet by EVs would require an increase of 26.65 GWh/day (9.73 TWh/year), representing 1.10% of the energy consumption. Furthermore, if 100% of the Brazilian fleet were replaced by EVs, the increase in daily demand would be 533 GWh/day (194.55 TWh/year), equivalent to an increase of 19.40% in electricity consumption. However, the increase in electric power energy consumption caused by the increase in the number of EVs in the Brazilian fleet could be environmentally positive and favorable, since the Brazilian electric energy matrix was composed of 84.5% of electricity from renewable energy sources in 2016 (71% hydropower, 7% biomass, 6% wind energy and 0.5% solar energy), while the 7

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electricity from renewable energy sources in the rest of the world was only 23.65% in 2016 (Almeida et al., 2018). Moreover, even considering the use of liquid fuels, Brazil has a more renewable and sustainable energy matrix than the rest of the world due to the use of sugarcane ethanol, as fuel in ICEs. Sugarcane ethanol has the potential to promote the environmental sustainability due to the positive energy balance, considering that the energy ratio for its production is of the order of 9.0

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times (renewable energy/fossil energy). Also, sugarcane ethanol has a significant potential to reduce more than 80% of the GHG emissions, when compared with the corresponding substituted fossil fuel (gasoline) (Lora et al., 2014).

The Flex Fuel Vehicles (FFVs) were launched in 2003 in Brazil, in such a way that they have

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achieved commercial success since their launch and over the following years, the matter took on importance as average ethanol prices became significantly lower than those of gasoline. Nowadays,

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increased the ethanol blend in gasoline has been from 25% to 27%, and the consumers can also use 100% ethanol (E100) to fill up their FFVs. The FFVs represent more than 90% of new cars sold today in the Brazilian fleet, and due to consumer demand these vehicles now make up about half of the country’s entire light vehicle fleet (Sozinho et al., 2018).

Therefore, this study demonstrate the important application of Life Cycle Assessment (LCA) to a strategic sector in the Brazilian economy, which allows vehicle designers and manufacturers,

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fuel producers and distributors, as well as, policy makers, to make informed decisions regarding the environmental consequences in the entire production and supply chain, especially when novelty is extreme or high in relation to the state-of-the-art. Environmental effects are more difficult to assess beforehand, as they encompass more variables, uncertainties and interactions. Additionally, new

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regulations would probably allow the use of technical novelties that contribute to improve in terms of sustainability the urban transportation flow.

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Among the various vehicle alternatives, the Battery Electric Vehicles (BEVs) and the Plug-in Hybrid Electric Vehicle (PHEVs) are often considered as better options than ICEVs in terms of GHG emissions and energy consumption. In reality, however, making a decision favouring these vehicle options is not so straightforward due to temporal and spatial variations, such as, regional driving profiles and the sources of the electricity used (Onat et al., 2015). Otherwise, BEVs coupled with low-carbon electricity sources, such as biofuels, and natural gas are more sustainable from a life cycle perspective (Hawkins et al., 2012). In this sense, the main purpose of this paper is to perform an attributional LCA study of the different alternative scenarios of fuels consumption of five compact passenger vehicles (light-duty vehicles) in Brazil, and to quantify and compare the environmental impacts caused by the studied systems. The types of the environmental impacts that are studied in the Life Cycle Impact 8

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Assessment (LCIA) includes: Ozone Depletion Layer Potential (ODP), Abiotic Depletion Potential (ADP), Fossil Fuels Abiotic Depletion Potential (FDP), Global Warming Potential (GWP), Human Toxicity Potential (HTP), Photochemical Oxidant Formation Potential (POP), Acidification Potential (ACP) and Eutrophication Potential (ETP) among the different vehicle scenarios: conventional ICEV fueled by conventional E25 gasoline (ICEVg), ICEV fueled by hydrous ethanol (ICEVe), ICEV fueled by mixture of E25 gasoline and hydrous ethanol (ICVEf), PHEV and BEV.

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A very strong justification of the needs for this work is the necessity of performing adequate studies related to the automotive systems that allow elaborating tools able to support the decision makers guiding a real reduction of the environmental impact of the automotive vehicles.

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2. Literature Review

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A comprehensive literature review is undertaken to compare the scope and main focus of various studies addressing the environmental impacts of ICEVg, ICEVe, ICVEf, PHEV and BEV. In total, 14 different peer-reviewed articles, mainly LCA studies, are evaluated based on their scope, investigated vehicle technologies and selected environmental impact categories. The initial studies related to the LCA referred to the automotive systems were started in the 1970s, with the purpose of obtaining a lower dependence from crude oil products. Afterward the searching of eco-efficiency

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and sustainable products has stimulated a higher interest on the studies of the development and application of the LCA methodology.

According to van Lier and Macharis (2014) next to large economic and social benefits,

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transport services also cause significant, mostly negative environmental impacts. A rather impressive list of environmental impacts is associated with transport activities, caused by interferences in the ecological system such as: non-renewable resources consumption, emissions of

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polluting substances (climate change effects, photochemical smog formation, ozone layer destruction, acid rain, local air pollution, etc.), soil contamination, water eutrophication, ecotoxicity damages, accidents, noise and scrapping of vehicles and infrastructure. Generally, cost benefit analysis is carried out to assess the economic aspects of the environmental regulations, whereas the LCA is carried out to assess the impact of the products and services throughout its useful life. Hence, these analytical tools are very important assessment techniques for the development of low carbon economy. In this sense, this work has high environmental benefits for greening of transportation sector, which was responsible for 32.5% of the energy consumption and 46.3% of the GHG emissions in Brazil in the year 2014. Besides, as indicate the estimates of recent years, the transport sector has the highest growth rates of energy 9

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consumption (4.42% per year between 2002 and 2012). The CO2 emissions rose from 84 million tons in 1990 to 204 million in 2012 (Silva et al., 2018a). Therefore, this work provides overall criterion for development of new insights for reducing the climate change and environmental problems of transportation systems, which would make the transportation system more sustainable and environmentally friendly. The reduction of GHG emissions contributes to lowering the impact of climate change effects, which has huge social

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benefits.

To achieve the true sustainability, it is necessary to implement a paradigms change in the society in all of the aspects, since the institution of new technologies (PHEV and BEV) that consume less non-renewable resources, and are more efficient, and emit less polluting substances,

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until the introduction of changes in the society collective thinking regarding to such technologies. Thus, the environmental impact assessment information provided by this work is extremely

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important in educating the consuming public to the environmental issues facing Brazil. In the future, it could be possible to quantitatively assess these people benefits, using the social LCA guidelines and results.

The transportation sector is nowadays one of the most important emitters of pollutants and GHG and passenger cars make-up a very large share of these emissions. According Röder et al. (2003) recommendations to reduce these emissions do not only comprise the optimization of the

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existing technology (better engine efficiency, lower driving resistance, more efficient pollutant control) but also the introduction of alternative fuels or new powertrain concepts. The alternative fuels may be, for example, mainly based on natural gas, renewable energy sources like biofuels (bioethanol, biodiesel, biomethanol, biogas, etc.) or solar energy. The new powertrain concepts may

Vehicle (FCEV).

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include hybrid vehicles (PHEV), electric drivetrains with batteries (BEV) or a Fuel Cell Electric

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Urban air quality improvement, climate change concerns, and a reluctance to depend on nonrenewable sources have been the main motivations for the development of new technologies of powertrains for automobiles and their respective applications. The principal motivation to evaluate the existing fuel use (gasoline or ethanol) and eventual new alternative source of power supply (electricity) is to assess the potential to consume less petroleum and non-renewable fuels, in order to reduce the air pollution and GHG emissions. To evaluate the environmental impact of a transportation system, it is necessary to consider the correct energy pathway. In assessing a vehicle system should be considered a vehicle’s LCA comprised of two cycles: (i) vehicle life cycle that includes vehicle assembly, maintenance, dismantling and recycling and (ii) fuel life cycle that also referred to as the Well-to-Wheels (WtWs) 10

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cycle that includes the following steps: fuel extraction, processing, distribution, storage and use (Gao and Winfield, 2012). The use of LCA is recommended to identify the environmental impacts along the complete life cycle of products. In this sense, Table 1 summarizes a recent literature review on the use of LCA in transportation sector. A more complete revision of environmental impacts of different types of vehicles can be found at Nördelof et al. (2014). It has been described in the literature that most of

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the environmental impacts of the vehicle manufacturing companies are associated with the vehicle’s use phase, mainly due to the GHG emissions and energy demand (fuel consumption). It is for this reason that LCA in this field are crucial and the results are an important contribution to coming studies. Despite the important number of international works reported in Table 1, neither of them

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focuses on a particular Brazilian national context. It was found only three works that address the use of the LCA for automotive sector in the Brazilian conditions, but none of the three studies dealing

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with this specific issue that is being emphasized in this paper.

Table 1

An overview of recent LCA studies (2012–2018) of conventional internal combustion engines vehicles, fuel cell vehicles, hybrid electric and pure electric vehicles. Abbreviations are explained

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right below the Table.

Regarding to the previous studies of environmental assessment of automotive industry from Brazil context it should be highlighted the works of Silva et al. (2018b), Choma and Ugaya (2017) and Flórez-Orrego et al. (2015).

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Silva et al. (2018b) carried out a paper to evaluate a cradle-to-grave LCA for automotive engine valves produced in Brazil, identifying environmental hotspots and suggesting cleaner

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production scenarios to reduce life cycle environmental impacts by improving manufacturing resources efficiency of the valves. Choma and Ugaya (2017) performed a study to identify and contribute to reducing the environmental impacts of the adoption of BEVs in the Brazilian lightweight fleet using the methodology of LCA. The authors have used a decisional approach and the analysis was focused on the use phase, including energy consumption, whereas attributional data were used for the vehicle production stage. The BEV considered was better for ADP, GWP, ODP, Freshwater Aquatic Ecotoxicity Potential (FETP) and Terrestrial Ecotoxicity Potential (TEP). Flórez-Orrego et al. (2015) performed a study to assess and compare the exergy and environmental performance of the end use of vehicle fuels for the Brazilian condition. The analysis comprised the petroleum and natural gas derivatives (including hydrogen), biofuels (ethanol, and 11

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biodiesel) and their mixtures, besides of the electricity generated in the Brazilian electricity mix, intended to be used in plug in electric vehicles. It is important to remark that publications from Table 1 are from U.S., China, Canada and European countries, and other countries’ such as Brazil are not fully investigated; therefore this gap was a motivation for this study. Thus, the knowledge gap is the principal motivation in this paper that present results of the LCA carried out for five different scenarios of powertrains and their

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respective power supply (gasoline, ethanol or electricity). This work considers the fuel production, electricity generation and powertrain production, the vehicle use phase stages and powertrain Endof-Life (EOL), which includes the recycling of vehicles and batteries. The potential environmental benefits of adopting EVs will depend on several factors such as electricity generation matrix, the

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use of vehicles and the manufacturing phase, i.e., depends on the whole life cycle.

This study looks to build on previous published work made by the same authors (Souza et al.,

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2016), which have already examined the concept of sustainability applied to different scenarios of fuels consumption and powertrains configurations for a compact passenger vehicle, outlining the main issues to be considered, and the selection of the main indicators and tools.

3. Materials and methods

Goal and scope of this study

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The goal definition is the first phase of the LCA in which the purpose of the study is

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described. It identifies and defines the object of the assessment. The goal of this study is to compare, on an attributional life cycle perspective, the environmental performances of different

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types of electrical and conventional passenger vehicles. A comparative LCA based on a cradle-tograve attributional analysis was carried out to assess the health and environmental impacts of vehicles/fuels systems. The vehicles are differentiated into five types of powertrains, as indicated by: •

Scenario 1: Internal Combustion Engine Vehicle fueled by gasoline (ICEVg).

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Scenario 2: Internal Combustion Engine Vehicle fueled by a mixture of ethanol (E25) and ethanol (FFVs) (ICEVf).

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Scenario 3: Internal Combustion Engine Vehicle Fueled by ethanol (ICEVe).

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Scenario 4: Plug-in Hybrid Electric Vehicle (PHEV).

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Scenario 5: Pure Battery Electric Vehicle (BEV). 12

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A cradle-to-grave product system was considered in this study. Thereby for these different types of vehicles the following phases of the life cycle are considered: vehicle manufacturing phase, vehicle use phase (operation and maintenance) and vehicle EOL phase (recycling and final disposal). The vehicle category is a compact passenger automobile, based on a Volkswagen Golf A4 platform with a weight of 1181 kg, as stated by Schweimer and Levin (2000). As described by Nördelof et al. (2014), LCA of vehicles usually compares vehicles belonging to the same class or

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segment, which is defined in terms of vehicle weight/size and vehicle powertrain. Therefore, it is considered that the chassis designed by PHEV and BEV will be the same used in vehicles that have internal combustion engines (ICEVg, ICEVf and ICEVe), the only difference is related to powertrain and power supply (battery).

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The data used for the preparation of the inventory correspond to average data of conventional Brazilian technology at the present time. However, in some cases, as in the BEVs manufacturing,

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battery production and final disposal will be used data from other countries, which have been adapted to the Brazilian reality. Some data quality requirements were considered in this study, that is: (i) the analysis considered geographic boundaries of the data used (representative data from Brazil regarding temporal and technological development); (ii) representative databases from Brazilian conditions, based on the adjustment of the representative international production technologies; (iii) the analysis considered more recent data found in the international literature; (iv)

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finally, when none of the previous options was possible, global averages were used. The characterization factors reported by the CML 2 Baseline 2000 (v 2.03) model, developed by Institute of Environmental Science (CML) of Leiden University were applied as a default characterization method for life cycle assessment stage. More detailed information about the CML

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method can be found in Guinée et al. (2002). This environmental impact assessment method is available in SimaPro 7.0.1 software (Jolliet et al., 2016), which was used for the computational

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implementation of the Life Cycle Inventories (LCI), as well as, the characterization of the impacts. The following impact categories were evaluated: Ozone Depletion Layer Potential (ODP), Abiotic Depletion Potential (ADP), Fossil Fuels Abiotic Depletion Potential (FDP), Global Warming Potential (GWP), Human Toxicity Potential (HTP), Photochemical Oxidant Formation Potential (POP), Acidification Potential (ACP) and Eutrophication Potential (ETP).

3.2

Functional Unit (FU)

According Nördelof et al. (2014) the Functional Unit (FU) of complete LCAs is defined as a vehicle life cycle, which is specified by a total number of driven kilometers. The distance traveled 13

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can vary largely, both in terms of total driving distance and years of operation. A common total drive distance is often stipulated, although in reality there might be differences between study objects. Nevertheless, the assumptions made for the total amount of kilometers driven are very important to the outcome of the work and the choice of FU in LCA studies should be mandatory. Several studies which focus the environmental performance of current and future vehicles based on the LCA have “1 km” as the selected FU, as indicated in Table 1. In this study, the FU is

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defined as driving 1 kilometer (km) under Brazilian average conditions. The FU takes all life cycle stages of the vehicle into account and assumes an average occupation of 1.6 persons, with a lifespan of 14 years and a total life traveled distance 160,000 km. The total life time refers to the age of the

System boundaries

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3.3

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average vehicle going to the EOL treatment in Brazil.

3.3.1 Internal combustion engine vehicle fuelled by gasoline (ICEVg) Scenario 1 under study is comprised by a vehicle with ICE which uses E25 gasoline as fuel (Fig. 1). In Brazil, automotive commercial gasoline is known as E25 gasoline, which corresponds a mixture of gasoline (100%) and anhydrous ethanol (25%).

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Therefore, in order to avoid doubts about the concepts presented in this paper, it should be highlighted that in Brazil Gasoline A is free of oxygenated components, while Gasoline C is produced by blending Gasoline A with anhydrous ethanol. Gasoline A is not sold at the gas station

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in Brazil. Instead, Gasoline C, which is the blend of 27% anhydrous ethanol and 73% of Gasoline A by volume, is used. Pure Gasoline A is indicated by E0 and different gasoline-ethanol blends are indicated by the same nomenclature, for example: in the U.S. 10% of the pure gasoline is blended in

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ethanol (E10), in Spain, Germany, and Italy the pure gasoline is blended with 5% of ethanol (E5) and in Brazil the commercial gasoline is comprised by a mixture of 73% of pure gasoline (Gasoline A) and 27% of anhydrous ethanol (E27). The compulsory use of ethanol blended to gasoline has been mandatory since 1977, when legislation required a 4.5% blend of ethanol to gasoline. According to the current Brazilian legislation, the ethanol blend can vary from 18% to 27.5%, and is currently set at 27% volume/volume, by means of presidential decree. The engine does not need any special modifications to use this fuel mixture. This mixture has the objective of increasing the efficiency and drivability of the vehicle, as well as reducing the emission of GHG. Ethanol and gasoline do not

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contain the same energy content per volume. A rule of thumb in Brazil is that ethanol contains about 70% of the energy of gasoline (Bennertz and Rip, 2018).

Fig. 1. Scheme of the system boundary of the Scenario 1 (ICEVg) and Scenario 2 (ICEVf).

gasoline (flex fuel vehicles) (ICEVf)

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3.3.2 Internal combustion engine vehicle fuelled by a mixture of ethanol and

The manufacturers of automobiles in Brazil provided the major testing ground for investing in the new flexible fuel technology. The long experience with ethanol in Brazil and the maturity of its

account for over 90% of new car sales in Brazil.

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supply and end-use infrastructure facilitated rapid consumer uptake of the FFVs, which now

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The popularity of FFVs resulted in the consumption of ethanol exceeding gasoline in Brazil as of 2009 due to the long experience with ethanol in Brazil and the maturity of its supply and end use infrastructure facilitated rapid consumer uptake of the new FFVs (Johnson and Silveira, 2014). Besides that mainly due to the low price of ethanol, in which differences tributaries were adopted at that time, making the fuel more attractive to the final consumer (Bennertz and Rip, 2018). It should be noted that the Fig. 1 also shows the system boundaries relating to the Scenario 2

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(ICEVf) because it differentiates only by the amount of ethanol and gasoline for each scenario. The FFV can run on gasoline or ethanol in any content. The Scenario 2 of this study represents a vehicle with ICE that uses E25 gasoline and hydrous ethanol in different proportions, according with the preference of the consumer. The selection of this type of fuel is variable and according with specific

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factors of the economy of the country, such as, the price, the accessibility or the inherent to the environment’s impact of the fuel. For this work the following proportions were considered: 75% of

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E25 gasoline and 25% of hydrous ethanol, it means that the vehicles use 56.25% of pure gasoline and 43.75% of ethanol (anhydrous+hydrous).

3.3.3 Internal combustion engine fuelled by ethanol (ICEVe) The Scenario 3 (ICEVe) is comprised by a vehicle with an ethanol fuelled ICE (Fig. 2). Scenario 3 considers that the engines are designed specially to work purely on hydrous ethanol (6% water). In addition, to the identification as renewable fuels, in Brazil the ethanol is a conventional fuel, used by a great amount of the vehicle fleet. The demand of the consumers for ethanol is growing steadily and today it can be used in FFVs (the user can decide to use 100% of hydrous 15

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ethanol as fuel or 100% E25 gasoline). It should be noted that the FFVs began to be sold in Brazil in 2003. Vehicles fuelled with purely on hydrous ethanol was sold by the Brazilian manufacturers until 2007 and, since this date they only produce automobiles fuelled with E25 gasoline and FFVs.

3.3.4 Plug-in Hybrid Electric Vehicle (PHEV)

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Fig. 2. Scheme of the system boundary of the Scenario 3 (ICEVe).

Scenario 4 (PHEV) includes a HEV having an electric motor and an ICE fuelled with gasoline (Fig. 3). PHEV scenario adopts a similar configuration to the conventional HEV, but it differs from

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the HEV due to its higher battery energy capacity, the utilization of an external power source to recharge the batteries, and the different battery management strategy. It is considered that the PHEV

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is equipped with an ICE and an electric motor, as well as, a battery that can be charged from an external power source. Two main PHEV operating modes can be distinguished: charge depleting and charge sustaining. Charge depleting mode occurs when the engine is off and the vehicle propelled by the electric motor with electricity stored in the battery. When the battery reaches its minimum state of charge, the engine switches on and the charge sustaining mode starts its operation. Being only partly dependent on battery power, PHEVs have lower requirements on

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battery performance and smaller battery capacity than BEVs, restricting their all-electric driving range to some 50–80 km. In this study it was considered that the vehicle’s autonomy reaches 80 km (considering only electric device).

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Fig. 3. Scheme of the system boundary of the Scenario 4 (PHEV).

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3.3.5 Pure Battery Electric Vehicle (BEV) Scenario 5 (BEV) is comprised by an automobile equipped with an electric motor that propels the vehicle, an energy storage system of batteries and as energy source electricity (Fig. 4). However, the commercialization and the use of EVs are still very small, in the developed countries there is a great opportunity for the introduction of such vehicles in the automobile market. In the Brazilian market BEVs are not widely available, so that there are uncertainties in predicting possible capacity for BEV powertrain for the future. It is considered that the electricity from an external power source is stored in a battery that provides enough power to reach the desired top speed and acceleration. It is assumed that an electricity mix for the BEV use is representative of the 16

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Brazilian electricity grid. The BEV can recuperate in regeneration phases and store the energy in the battery for later use. Due to the large speed and torque range of the electric motor a single speed transmission is sufficient to reach all performance requirements. BEVs typically use lithium ion batteries (Li-ion batteries), while nickel-metal hydride batteries (Ni–MH) are generally preferred to power HEVs due to their relatively lower costs. For this study, is considered that BEV uses a Li-ion battery. The BEV category includes vehicles

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propelled entirely by externally produced electricity, with a driving range span of 120–160 km. In this study, it was considered autonomy of 160 km. Table 2 shows a summary of the different proportions of gasoline, ethanol and electricity used in the five different scenarios previously

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described, both for the entire life cycle of vehicles, and for the FU adopted in this work.

Table 2

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Fig. 4. Scheme of the system boundary of the Scenario 5 (BEV).

Summary of the different proportions of gasoline, ethanol and electricity used in the five different scenarios analysed in this work.

Life cycle inventory (LCI) analysis

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3.4

LCI data can be divided into foreground and background data. Foreground data represent processes being directly part of vehicle manufacturing phase, use phase, EOL phase and fuel supply chains. The background data represent the rest of the economic system, i.e. products and processes

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required as inputs in the foreground system. LCI analysis was conducted in accordance with the ISO 14040 standard (ISO, 2006a) including the data collection and the procedures used to quantify

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the inputs (materials, fuels and energy flows) and outputs (energy flows, atmospheric gases emissions, liquid effluents and solid wastes) during the whole life cycle of the product.

3.4.1 Vehicle/battery manufacturing phase 3.4.1.1

Automobile manufacturing phase

The vehicle is composed by several units, which can be divided in smaller units up to the single component. For the vehicle, manufacturer datasheets are available in the literature, which include a list of the main materials composition. The LCI of the vehicle was based on the most 17

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promising and most popular commercial vehicles currently sold on the market. The vehicle is composed by many systems that can be separated in sub-systems up to single parts. The two main larger systems that were considered in the vehicle models are the powertrain (electric engine and battery system for the BEV and ICE for the ICEV) and the glider. The data used for the LCI of the vehicle manufacturing and maintenance were calculated and adapted from the basis of an LCA of the Volkswagen Golf A4 (Schweimer and Levin, 2000), with the most recent data dating from

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2000, which is compatible with the scenarios under study, because it is a vehicle belonging to the Brazilian vehicular fleet. Table S1 from Electronic Supplementary Material shows the main materials and energy requirements for assembling of 1.0 automobile.

Li–ion batteries production for BEV and PHEV vehicles

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3.4.1.2

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The battery LCI was based on an existing study of Majeau-Bettez et al. (2011) and the database for this was built using a mix of average and commercial data supplied by the battery manufacturing company. The powertrain of the BEV includes all the units of the BEV, excluding the glider. The battery pack is the core of the BEV. This is comprised by four units: the cooling system, the battery cell, the packing and the battery management system. To make a comparison in the production and uses of batteries for EV, the alternative was taken to maintain the inventory of

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the Golf automobiles, adding the LCI of a Li-ion battery. To simplify the analysis of the LCI it was considered the same battery for the PHEV and BEV technologies. In practice, those batteries present different electrochemical and material properties. However, several studies, such as, Sullivan and Gaines (2012) that combine the inventories to get general data representing both

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technologies. The main LCI data of materials and energy consumption for manufacturing the Li–ion

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battery are reported in Table S2 from the Electronic Supplementary Material.

3.4.2 Vehicle use phase The distance adopted for the use phase of vehicles under study was based on the mean useful life of an automobile in Brazil that is 160,000 km. With this figure and with the mean specific consumption (km/l) of vehicles, Scenarios 1, 2 and 3, it is possible to determine the total quantity of gasoline and ethanol consumed, as shown in Table 3. The emission data used in this stage for Scenarios 1, 2 and 3 were the emissions to air originated by the combustion of gasoline and ethanol, obtained from Cavalett et al. (2012). The use phase for the BEV and PHEV is directly related to a certain amount of charge/discharge cycles, but there is no certain agreement regarding the unit of lifetime of batteries 18

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because of the uncertainties in use patterns and user behavior, which can directly affect the charge/discharge cycles. Another important source of variability is that the studies compared are within the last 15 years, whereas battery technology has significantly improved in recent years (Onat et al., 2015). The charge/discharge cycles are directly related to the distance traveled by the vehicle, and the energy used for the heating and cooling system. All the data related about the LCI of the BEV

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and PHEV, in terms of energy consumption, were taken from Faria et al. (2013). Table S3 from the Electronic Supplementary Material shows data related to the use phase of Scenario 4 (PHEV) and Scenario 5 (BEV). The calculated data based on Table S3 related to Scenario 4 and Scenario 5 is

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shown in Table 4.

Table 3

Table 4

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Total quantity of fuels used in the Scenario 1, Scenario 2 and Scenario 3.

Calculated energy consumption of Scenario 4 and Scenario 5.

Gasoline production

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3.4.2.1

The stages included in the LCI analysis of type A gasoline were: oil extraction and transport, refining, gasoline transport and use. Within this subsystem is included a production and final product streams of the gasoline fabrication, but inputs associated to construction facilities, i.e.

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manufacturing, machinery, buildings, etc., were not included the LCI. There was considered that the crude oil used for the production of gasoline in Brazil has two origins, fixing that 50% of the crude

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oil will come from international sources and 50% from the Brazilian sources. The data related to the transport distance of crude oil by maritime oil tankers between Middle East and Brazil were taken from Borges (2004). Table S4 (Electronic Supplementary Material) shows the LCI for gasoline production.

3.4.2.2

Ethanol production

The LCI of ethanol starts in the agriculture stage involving the indirect use of energy for seeds, fertilizers and agrochemicals (pesticides, herbicides, etc.) in addition to the energy used directly in the processes. In the life cycle of ethanol production the agricultural stage is fully integrated to the industrial production. In the agricultural system boundary of ethanol production the 19

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use of fuels, fertilizers, herbicides, insecticides, lime and seeds is considered (Rocha et al., 2010). It is common to use stillage and other ethanol industry co-products (filter cake and ashes) as a complement of chemical fertilizers (Rocha et al., 2008). The industrial step includes sugarcane milling, juice clarification and treatment, fermentation, distillation, purification of ethanol and generation of energy (steam and electricity) used in the mill (Rocha et al., 2014). The data used to evaluate the ethanol production process were collected from

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Cavalett et al. (2013). The data referred to the nitrogen (urea) fertilizer production were taken from Ribeiro (2009). The data concerned to the phosphate (P2O5) fertilizer production, calcium oxide (CaO), lime, insecticides and sulfuric acid (H2SO4) were taken from Viana (2008) and the data regarding to the lubricants production were taken from Borges (2004).

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The appropriate information about the emissions produced by the diesel combustion in the agricultural tractors and the emissions from the sugarcane on-farm agricultural practices were taken

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from Wang et al. (2013) and Nemecek and Kägi (2007), respectively. Table S5 provided in Electronic Supplementary Material presented the inputs/outputs of the agricultural stage of the ethanol production and Table S6 shows the main materials and products to produce 1926 MJ (corresponding to 1.0 ton of sugarcane) of hydrous ethanol. For anhydrous ethanol production the same data that the one for the hydrous ethanol was used with the addition of 0.069 kg of cyclohexane/1000 kg of processed sugarcane. In order to remove water from a heterogeneous

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azeotropic ethanol/water mixture, cyclohexane is added in the dehydration stage to produce anhydrous ethanol and a vapor mixture of water and cyclohexane (Cavalett et al., 2012).

Electricity generation

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3.4.2.3

It is known that Brazil has an interconnected electricity grid mix therefore the electric energy

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production and delivery must be evaluated in a manner so as to reflect the average situation throughout all the Brazilian territory. In order to determinate the impact of the production and use of electricity on the environment, different processes of energy conversion that integrate the Brazilian energy matrix should be evaluated. Table S7 (Electronic Supplementary Material) shows the internal electricity offer in Brazil for the year 2013. In a general way, the technologies that use fossil fuels for electricity generation are related with the direct GHG emissions, mainly during the operation phase of the industrial installations. In contrast to fossil fuel technologies, the great amount of GHG emissions from renewable energy technologies occur upstream of the plant operation, typically for the production and construction of the technology and/or its supporting infrastructure (Weisser, 2007). 20

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Therefore, the data used for the LCI of electricity production are retrieved from the Ecoinvent database because it is one of the most comprehensive international LCI databases. The references of the LCI data for electricity generation are: electricity generation in hydroelectric power stations (Bauer et al., 2007), electricity generation in natural gas-fired power plants (Faist-Emmenegger et al., 2007), electricity from sugarcane bagasse (Jungbluth et al., 2007), electricity generation from diesel-fuelled thermal power plants (Jungbluth, 2007), electricity generation from thermal power

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plants coal fired (Röder et al., 2007), electricity generation in nuclear power plants (Dones, 2007) and electricity generation with wind power in eolic plants (Burger and Bauer, 2007).

Transport and distribution stage

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3.4.2.4

Energy use and the resulting emissions in transportation depend on the carrying mode and

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distance. The study of the transport distribution stage of ethanol, automobile and battery was performed by the highway freight transport, through heavy trucks using data referred to emissions from diesel fuel combustion on-road transport in heavy trucks loading vehicles (Lloyd and Cackette 2001).

For the distribution of the fuels (gasoline and ethanol) and electricity, the energy demand for transportation of liquid fuels by trucks and electricity losses in the grid are taken into account. It is

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considered that the transportation distance of the ethanol between São Paulo and the distribution center is 430 km (São José Mill Colina/SP). It is assumed that the refinery (Cubatão Refinery) is situated at a distance of 50 km from São Paulo, hence the type A gasoline is transported to the facility where occur the compulsory mixture of ethanol with gasoline via pipelines. This stage

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considers the electricity consumption obtained from the work of D’Agosto (2004).

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3.4.3 Vehicle’s End-of-Life (EOL) phase 3.4.3.1

End-of-Life of vehicles and batteries

In general, the vehicle’s EOL phase shows a limited contribution in terms of environmental impacts (below 1%). The EOL of vehicle could include the recycling of all the vehicles materials, in particular metals and glass and the incineration with energy recovery of all the non-recyclable plastic parts (Bartolozzi et al., 2013). In this study, for the EOL of vehicle it was considered the recycling of the automobile itself and the Li–ion battery. The impacts associated with material recovery and disposal processes are allocated to the vehicle life cycle. Like for the manufacturing phase, the EOL phase has been modeled as a parameter which will be adapted to all the vehicles 21

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according to their weight. The EOL was modeled using state-of-the-art data of the Belgian recycling units because there were not data from Brazil. A general energy consumption of 66 kWh/ton (Boureima et al., 2009) was assumed for all the recycling process. A rate of recycling by type of material is shown in Table S8 provided in Electronic Supplementary Material.

Batteries recycling

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3.4.3.2

The recovering and recycling of the materials used in the batteries had increased significantly due to the high costs of the raw materials for their production and in some countries due to rigorous legislations (Gao and Winfield, 2012). The Li–ion batteries’ recycling is rarely included in the

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energetic and environment evaluations due to the poor availability of data, therefore for those processes are still in experimental stage. It is not the case of the lead-acid battery recycling, which

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is a consolidated recycling process. The Environmental Resources Management Limited (ERM) has studied the adoption by the European Union Council of Ministers (EUCM), of the proposed Directive on Batteries and Accumulators. This study used a LCA with a subsequent economic evaluation of battery management options between 2006 and 2030. The results of the study showed that the increase of battery recycling is beneficial to the environment due to the recovery of metals; however, it is done at a significant financial cost when compared with the elimination (Fisher et al.

batteries recycling.

Life Cycle Impact Assessment (LCIA)

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3.5

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2006). Table S9 (Electronic Supplementary Material) shows the main data related to the Li–ion

The stage of the LCIA was conducted in accordance with the ISO 14044 standard (ISO,

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2006b). The method applied in this work was the CML 2 Baseline 2000 (v 2.03) method that is an update from the CML 1992 method (Guinée et al., 2002). The software SimaPro 7.0.1 (developed by the Pré-Consultants) was used to make the calculations, analyses and comparisons of the environmental impacts in the analyzed scenarios, because it is a widely used LCA tool, both by professionals and researchers (Leme et al., 2014). The midpoint impact categories used to carry out the environmental impacts assessment of the analyzed scenarios are: ODP, ADP, FDP, GWP, HTP, POP, ACP and ETP. The justification for such selection is that those categories represent the main environmental impacts by the automotive sector. Several authors of automobile LCA studies have also opted for this method among them it is possible to highlight Bicer and Dincer (2018).

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The CML 2000 LCIA method aims to offer best practice for midpoint indicators, operationalizing the ISO 14040 series of standards (Cavallet et al., 2013). The methods follow midpoint oriented approaches that characterize the impact categories based on the impacts that are directly caused by emitted pollutants, that is the environmental impacts at intermittent stage of the cause-effect chain in the form of indicators like carbon dioxide (CO2), climate change, dioxide (SO2) for acidification, etc. (Rathore and Mondal, 2018).

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chlorofluorocarbon (CFC) for ozone depletion, nitrogen oxides (NOx) for eutrophication, sulfur According Bicer and Dincer (2018) both HTP and TEP have important role for decision of using clean transportation vehicles because there are vast amount of road vehicles in the cities, which can cause damages related to these environmental impacts. Moreover, as the world struggles

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with GHG emission reduction policies, so the GWP is the main characteristics to compare the total CO2 equivalent emission from the alternative vehicles. The selection of future vehicle options can

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strongly depend on the emission characteristics. ADP is the depletion of the availability of resources, both in the environment and the economy, which is calculated using the reserve based instead of the ultimate reserve estimation. FDP considers the depletion of the fossil fuels resources, which declines gradually, so this is significant category for LCA. ACP and ETP categories are also critical in the vehicles, which can cause severe effects to soil and water in the environment. In addition, it should be noted that the ODP and ETP categories are also important for the analysis of

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the environmental impacts of transportation systems. Therefore, these were the impact categories chosen to be evaluated in this study.

Sensitivity analysis

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3.6

Uncertainty is inherent element of LCA, which requires cautious examination before

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interpretation of results. In the LCA studies, the results vary due to choices of system boundary, coproduct accounting methods and comparison with reference system. By analyzing a range of key parameters, sensitivity analysis helps to avoid drawing false conclusions regarding LCA of any process or product.

Sensitivity analysis was conducted in order to identify and evaluate the process steps with maximum contributions on various impact categories as well as to find out the alternative options to decrease the impacts varying their input values. Fuel consumption rate is very dependent on road quality, geographic and climatic conditions, efficiency of the vehicle, lifetime and fuel use. Therefore, it was carried out a sensitivity analysis to evaluate the uncertainties related to the

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environmental impact assessment effects of modeling assumptions regarding to the fuel consumption rate.

4. Results and discussion Ozone Layer Depletion Potential (ODP)

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4.1

The dynamic balance between production and destruction determines the concentration and total amount of O3 in the stratosphere. ODP refers to the destruction of ozone gas in the upper

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atmosphere, which is mainly attributed to the use of Chlorofluorocarbons (CFCs) in aerosol products.

The high ODP impact scores for the vehicles production are caused by emissions of

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halogenated compounds, including CFCs, carbon tetrachloride, methyl chloroform, halons, Hydrochlorofluorocarbons (HCFCs), Hydrobromofluorocarbons (HBFCs), Methyl bromide (CH3Br) and nitrous oxide (N2O). These substances are used as solvents, refrigerants, foam blowing agents, degreasing agents, aerosol propellants, fire extinguishers (halons) and agricultural pesticides (CH3Br) and are released during the production of materials such as steel, lead, aluminum, zinc,

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copper, platinum, lithium, nickel, plastics, rubbers and Acrylonitrile Butadiene Styrene (ABS), each of which is used in increased quantities in these vehicles. The majority of ODP emissions are generated during the vehicle manufacturing phase. Scenario 3 presented the best environmental result for the ODP impact category (7.36E-10 kg CFC-

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11–eq./km), followed by Scenario 2 (8.20E-10 kg CFC-11–eq./km), Scenario 1 (8.34E-10 kg CFC11–eq./km) and Scenario 4 (1.08E-09 kg CFC-11–eq./km). In relation of ODP impact category the

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worst case is represented by the Scenario 5 with a value of 1.39E-09 kg CFC-11–eq./km, as it can be seen in Fig. 5. The results are in agreement with Capitano (2015). Scenario 1 was the third place in the classification of the evaluated scenarios. The process that makes the greatest contribution to this scenario is the vehicle production with 85%, followed by the gasoline production (14%) and the ethanol production (1%). Scenario 2 was the second place in the ranking of the assessed scenarios. The process that makes the greatest contribution to this scenario is the vehicle production with 86%, followed by gasoline production (12%) and ethanol production (2%). The lowest impacts are referred to the Scenario 3, with value of 7.36E-10 kg CFC-11–eq./km, this corresponds to the fact that no direct emissions of are present in the use phase of ICEVe, only indirect emissions are present in the ethanol production, such as the use of fertilizers, insecticides, pesticides and herbicides (N2O and CH3Br emissions). 24

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Li–ion batteries production contributes with 28% and 35% of the CFC-11–eq./km emissions of the Scenario 4 and Scenario 5, respectively. The greatest percentage of those emissions comes from the use of polyfluoroethylene as dispersant/agglutinants of the electrodes paste, which emit ethane halogenated in their reactions. Its production is responsible for more than 85% of the CFC11–eq./km emissions, mostly due to the halogenated emissions of this value chain. The extraction and processing of metals, specifically aluminum (used in the cathode and passive cooling system)

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and steel (used in the battery pack housing and battery management system) are key drivers of ODP impacts.

The use of electricity from the grid has also an important role on the ODP impact category (2% for Scenario 4 and 14% for Scenario 5), therefore in the future, when the EV are considered a

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consolidated technology, it is recommended to ensure the maximum use of the renewable energy in the energy matrix. In the reuse, recycling and energy recovery of vehicles and the batteries, the

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avoided pollutant emissions would cause a positive impact on the environment. As recycling of materials like iron, aluminum, lithium, nickel, copper, lead, plastics, rubber, etc. could offer great economic and environmental benefits, therefore the values of some environmental impact categories are negative. The environmental benefits brought about by recycling mainly come from the resource and energy savings in the upstream production. The great benefit of recycling for the ODP category is presented by the Scenario 4 with 29%, followed by Scenario 3 (26%), Scenario 5 (23%), Scenario

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2 (22%) and Scenario 1 (21%).

Fig. 5. Ozone Layer Depletion Potential (ODP) for vehicles under Brazilian conditions.

Abiotic Depletion Potential (ADP)

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4.2

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In 2013, abiotic depletion was divided in two other indicators in the CML method: resources abiotic depletion (non-renewable resources, elements, ultimate reserves) and fuels abiotic depletion (fossil fuels) (Jolliet et al., 2016). ADP is an indicator for potential negative impacts on the availability of mineral resources. It aggregates the demand of metal and mineral resources according to their currently estimated global reserves and rate of de-accumulation, relative to the reference substance: Antimony (Sb). Concerning about ADP, the material acquisition covers a large portion of impact because of the consumption of abiotic compounds involved in the vehicle manufacturing and components replaced in maintenance. Environmental impacts categories related to resources are more complex. For

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instance, improvements in LCIA characterization methods are needed for ADP, as there are data gaps regarding several metals and dependency on old data. In relation to the ADP impact category all the analyzed scenarios have the same environmental performance with 2.78E-02 kg Sb–eq./km, since the same materials are assumed for all the analyzed scenarios. According to Fig. 6 the vehicles under study show similar results due to the fact that the stage which makes the biggest contribution for this category of impact is the vehicle

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production, in which the use of mineral resources is more significant, being responsible for more than 99% of the total environmental impacts on the ADP category. The production of batteries contributes to this impact due the extraction of the specific raw materials used in their production. Mostly HEV presently rely on Ni–MH batteries; however, in the near future Li–ion batteries are

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expected to dominate the market, especially with the rise of PHEV and BEV.

Although lithium occurs in average concentrations lower than 0.01% in the Earth’s crust and

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hence can be considered to be a geochemically scarce metal, assessment with ADP does not result in a high impact for the lithium components, since it is the base for the cathode active material production (Notter et al., 2010).

Compared to other components the ADP of lithium resources does not seem to be critical because its characterization factor in the CML 2 baseline 2000 (v 2.03) method is very low (1.15E05 kg Sb–eq./kg), in comparison with the gold (5.20E+01 kg Sb–eq./kg), silver (1.18E+00 kg Sb–

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eq./kg), palladium (5.71E-01 kg Sb–eq./kg) and cadmium (1.57E-01 kg Sb–eq./kg). In contrast, the characterization factor for metals most frequently used in the vehicle’s manufacturing is also small, such as, lead (6.34E-03 kg Sb–eq./kg), cooper (1.37E-03 kg Sb–eq./kg), zinc (5.38E-04 kg Sb– eq./kg), iron (5.24E-08 kg Sb–eq./kg) and aluminum (1.00E-09 kg Sb–eq./kg).

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The electricity production has a contribution to the ADP impact category due to the copper filaments and the cables for the electric distribution. In ethanol production the agricultural stage has

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the highest impacts on ADP, due to the large consumption of mineral fertilizers (based on nitrogen, phosphorus and potassium) and lime during sugarcane production, being the most expressive stage for this impact category. The recovery of materials in the phase of vehicle recycling and battery recycling was found to decrease the consumption of raw resources, contributing to reduce the potential negative impacts, but in less extent (<1%).

Fig. 6. Abiotic Depletion Potential (ADP) for vehicles under Brazilian conditions.

4.3

Fossil Fuel Abiotic Depletion Potential (FDP)

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The environmental impact category of FDP refers to the use of non-renewable fossil fuels such as coal, petroleum based fuels and natural gas. The Scenario 3 presented the best environmental result for the FDP impact category (2.57E-01 MJ–eq./km), followed by Scenario 5 (1.13E+00 MJ–eq./km), Scenario 4 (2.94E+00 MJ–eq./km) and Scenario 2 (3.22E+00 MJ–eq./km). In relation to FDP, the worst case is represented by the Scenario 1 (3.77E+00 MJ–eq./km), as expected, because of the huge consumption of fossil fuel (Gasoline A).

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According to presented analysis, the most expressive results of the FDP category are for the vehicles that use predominantly fossil fuels as energy sources, as presented in Fig. 7. The ICEVg shows the higher impacts for the FDP impact category. The largest contributing process that increased the impact of FDP was the gasoline production for Scenario 1 (93%), Scenario 2 (92%)

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and Scenario 4 (84%). The minor values of FDP correspond to the ICEVe, as a result of obtaining a renewable fuel with high output–input energy ratio (energy use efficiency). For instance, the

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sugarcane ethanol production has a Net Energy Ratio (NER) about of 8.0–12.0 MJrenewable/MJfossil (Rocha et al., 2014). NER is the output energy divided by the input energy, considering that the output is composed by the ethanol produced and the others co-products evaluated by their Lower Heating Value (LHV).

However, the FDP impacts of the ethanol production are related of the diesel consumption for the sugarcane transport, the agricultural practices and the ethanol distribution. Another favorable

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result in relation to the FDP impact category was found for the BEV, which have a FDP of 1.13E+00 MJ–eq./km, due to the fact that the Brazilian electric matrix has a low consumption of fossil fuels sources. Scenarios 2 and 4 have a great FDP because of the consumption of the Gasoline A in FFV (Scenario 2) and PHEV (Scenario 4), respectively.

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Specifically, lower impacts for BEV are only evident in this category when the energy grid mix is comprised to a large extent of hydropower plants, and battery does not represent a substantial

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proportion of the overall primary energy use. Battery production is responsible of 7% of the FDP impact for Scenario 4 and 28% of the FDP impact for Scenario 5. It is likely that most of the impacts across this category would be lower for PHEV and BEV if the average electricity grid were less dependent on fossil fuels, and relied more on renewable sources of energy. Electricity production contributes with 2% and 55% of the energy consumption (MJ–eq./km) of the Scenario 4 and Scenario 5, respectively.

Fig. 7. Fossil Fuel Abiotic Depletion Potential (FDP) for vehicles under Brazilian conditions.

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Global Warming Potential (GWP)

Fig. 8 shows the potential impacts of vehicle technologies on climate change in terms of kg CO2–eq./km driven and the breakdown of total emissions into contributions from different life cycle stages. The Scenario 3 presented the best environmental result for the GWP impact category (9.72E-

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02 kg CO2–eq./km), followed by the Scenario 5 (1.51E-01 kg CO2–eq./km), Scenario 4 (2.42E-01 kg CO2–eq./km) and Scenario 2 (2.65E-01 kg CO2–eq./km). In relation to GWP the worst case is represented by the Scenario 1 (2.91E-01 kg CO2–eq./km). It should be noted that the sequence order of the environmental performance regarding to GWP is the same as previous environmental impact

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category (FDP), because the GHG emissions are directly proportional to fossil fuels consumption. It should be noted that considering the FU of 1.0 km driven for comparison of different

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vehicle technologies the automobile manufacturing becomes relevant in terms of GHG emissions and accounting for GWP environmental impact category. On average, the vehicle production contributes with 21% of GWP impact category for Scenario 1, 24% for Scenario 2, 65% for Scenario 3, 26% for Scenario 4 and 42% for Scenario 5. The scenario that uses gasoline will emit the highest amounts of CO2–eq./km, due to the large quantity of CO2 thrown to the atmosphere by the combustion of the gasoline. The exhaust gas from gasoline is responsible for 65% of GHG

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emissions for Scenario 1, 60% for Scenario 2 and 55% for Scenario 4. The scenario with the lowest GWP is the ICEVe, even considering the whole CO2 emissions of the sugarcane chain (emissions of agricultural phase, sugarcane transport step and industrial stage of ethanol production) because during the growth of sugarcane CO2 sequestration is carried out. In

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addition, there was an increase of productivity in the sugarcane production during the recent years (on average of 50 ton/ha in 1975 to 80 ton/ha in 2013, as described by Matsuoka et al. (2009), as

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well as, the drastic decrease of the burning of the sugarcane crop for harvesting and in this way diminishing even more the CO2 emission. Exhaust gas from ethanol and exhaust gas from transport have no relevance concerning to GHG emissions, whereas the maximum achieved value is 4% (exhaust gas from ethanol for Scenario 3). In the life cycle of automobile and Li–ion batteries production, the greatest contributions to the CO2 emissions are in the stages of raw materials processing and manufacturing. The battery production contributes with 6% of the GHG emissions for Scenario 4 and 15% for Scenario 5. The BEV has the second position in terms of the emissions of CO2–eq./km, just behind the vehicle powered by ethanol. The results of this analysis suggest that the emissions of BEVs are in general lower than that of existing ICEVs, even for countries with a large amount of coal based electricity 28

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production such as U.S., China and India. This suggests that the emissions caused by a BEV largely depend on the energy grid mix used for electricity production. The electricity production contributes with 3% of the GHG emissions for Scenario 4 and 48% for Scenario 5. Therefore, it is necessary to state that such values are relatively low due to the characteristic of the Brazilian electric matrix, based mainly on renewable sources. The Scenarios 2 and 4 have huge emissions of CO2–eq./km due

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to the consumption of non-renewable fuel (gasoline) and its associated GHG emissions.

Fig. 8. Global Warming Potential (GWP) for vehicles under Brazilian conditions.

Human Toxicity Potential (HTP)

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Human toxicity represents potential impacts on human health due to toxic emissions to the

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atmosphere of benzene, ethene, butadiene, phenols, dioxins, furans, Polycyclic Aromatic Hydrocarbons (PAHs), Non-Methane Volatile Organic Compounds (NMVOCs) heavy metals and dust. Fig. 9 shows the potential impacts of vehicle technologies on HTP in terms of kg 1,4 dichlorobenzene equivalents per kilometer (kg 1,4 DB–eq./km) driven. The Scenario 3 presented the best environmental result for the HTP impact category (1.19E-02 kg 1,4 DB–eq./km), followed by the Scenario 2 (1.40E-02 kg 1,4 DB–eq./km), Scenario 1 (1.43E-02 kg 1,4 DB–eq./km) and

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Scenario 4 (1.88E-02 kg 1,4 DB–eq./km). In relation to HTP the worst case is represented by the Scenario 5 (3.55E-02 kg 1,4 DB–eq./km). It was estimated that HTP increases for EVs relative to ICEVs both in the production and the use phase, and this trend was similar to results obtained by Sharma and Strezov (2017).

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Generating energy produces large amounts of NMVOCs, dust and heavy metals, therefore the by far largest human toxicity potential is caused by the BEV due to the high burdens from the

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Brazilian electric matrix, which accounts of 9% of toxic emissions concerning of HTP for Scenario 4 and 54% of toxic emissions for Scenario 5. The metal mining activities and metal production by means of metallurgic techniques placed by lithium, nickel, cooper, platinum, iron and aluminum production are also the main sources of toxic substances released in the environment, which can represents potential impacts on human health. The vehicle production was found to contribute more than other processes to HTP due to toxic substances emissions (74% for Scenario 1, 75% for Scenario 2, 89% for Scenario 3, 56% for Scenario 4 and 30% for Scenario 5). The Li–ion battery production has the more significant participation for this category of impact, because of the high presence of toxic substances released, which accounts of 26% for Scenario 4 and 21% for Scenario 5, as well as, the power transmission and distribution grid. In the 29

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future, with the changes in the Brazilian electricity matrix, it is expected that HTP environmental impacts caused by BEV and PHEV will be lower if compared to fossil fueled vehicles. In general, the gasoline production has intermediate impacts of human health (32% for Scenario 1, 28% for Scenario 2 and 17% for Scenario 4). The HTP stands out as a potentially significant category for displacement or transfer of problems between different environmental pressures over time associated with a shift from ICEVs to EVs.

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The HTP impact of the EV scenario is 3 times higher if compared to the ICEVe scenario. The ethanol production makes a reasonable contribution to this category of impact for Scenario 3 (23%), due to the use of herbicides, pesticides and fertilizers in the agricultural activities for ethanol production. For all other scenarios this contribution will not be significant (3% for Scenario 1, 6%

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for Scenario 2 and 2% for Scenario 4). As pointed out by Rocha et al. (2014) agrochemicals generally are biologically active substances with a compound-specific inherent toxicity and contain

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heavy metals, with high impact over the aquatic and terrestrial ecotoxicity and human toxicity. The exhaust gases emissions to air (emissions from gasoline, ethanol and emissions from transport) have low contribution to this category of impact, with a maximum around of 1%. The large amount of energy and materials saved by vehicle recycling and battery recycling will therefore significantly decrease emissions of substances that are harmful to human health, contributing to

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reduce 10% in average of the total environmental impacts.

Fig. 9. Human Toxicity Potential (HTP) for vehicles under Brazilian conditions.

Photochemical Oxidant Formation Potential (POP)

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Photochemical ozone creation, representing the summer smog, is as result of emissions of

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NOx, unburned hydrocarbons, Volatile Organic Compounds (VOCs), NMVOCs, CO and sunlight, which is harmful for both human health and ecosystem. Fig. 10 shows the potential impacts of vehicle technologies on POP in terms of kg ethylene equivalents per kilometer (kg C2H4–eq./km) driven and the impacts of the subsystems. The Scenario 5 presented the best environmental result for the POP impact category (1.75E-05 kg C2H4–eq./km), followed by the Scenario 4 (4.23E-05 kg C2H4–eq./km), Scenario 1 (5.21E-05 kg C2H4–eq./km) and Scenario 2 (7.50E-05 kg C2H4–eq./km). In relation to POP the worst case is represented by the Scenario 3 (1.63E-04 kg C2H4–eq./km). The results show similar trend with the results obtained by Girardi et al. (2015).

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In general, BEVs are very promising technology to reduce urban air pollution contributing to decrease the ground level ozone precursors in populated areas. The contribution of vehicle manufacturing for this impact category is relatively small for Scenario 1 to Scenario 3 (21% for Scenario 1, 14% for Scenario 2 and 6% for Scenario 3), but is higher to Scenario 4 and Scenario 5 (27% for Scenario 4 and 64% for Scenario 5). Exhaust gas from transportation has no significant influence in this impact category, with contributions below 0.5% for all analyzed scenarios.

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The vehicle and battery EOL has on overall positive effect on this impact category, because of the recycling credits, particularly for energy saved and metals and plastics recovery, which affect the POP around 6% for Scenario 1 to Scenario 4 and 17% for Scenario 5%. POP is the impact category in which exhaust gas emissions from gasoline and ethanol of ICEVg, ICEVf and ICEVe

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generate intermediate contributions. The contribution of exhaust gas emissions from gasoline for POP is 30% for Scenario 1, 18% for Scenario 2 and 26% for Scenario 4. The contribution of

Scenario 3 and 8% for Scenario 4.

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exhaust gas emissions from ethanol for POP is 10% for Scenario 1, 13% for Scenario 2, 18% for

According to Fig. 10 the highest values of POP correspond to the vehicles that use ethanol as fuel. The main reason of the ICEVe to have the worst environmental performance in relation to the POP impact category is the emissions of VOCs, CO and NOx in the sugarcane bagasse combustion for cogeneration purposes and the ethanol combustion in an ICE itself. In general, the

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environmental impacts of the Li–ion batteries are a consequence of the metal mining activity and with the production of electronic parts. Also, the gasoline production stage has a participation in that category because of the stage of crude oil prospection and natural gas production.

Acidification Potential (ACP)

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4.7

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Fig. 10. Photochemical Oxidant Formation Potential (POP) for vehicles under Brazilian conditions.

This impact category derives from acidifying pollutants such as NH3, NO2 NOx and SOx reaching the atmosphere and reacting with water vapor to form acids. Fig. 11 shows the potential impacts of vehicle technologies on ACP in terms of kg sulfur dioxide equivalents per kilometer (kg SO2–eq./km) driven and the impacts of the subsystems. The Scenario 5 presented the best environmental result for the ACP impact category (1.90E-04 kg SO2– eq./km), followed by the Scenario 1 (2.11E-04 kg SO2–eq./km), Scenario 4 (2.19E-04 kg SO2– eq./km) and Scenario 2 (2.74E-04 kg SO2–eq./km). The results concerning about the ACP confirm

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that the worst case is represented by the Scenario 3 (4.81E-04 kg SO2–eq./km). The obtained results are in agreement with Tagliaferri et al. (2016). It should be noted that the values found in this study for ACP impact category are close for all the analyzed scenarios, with exception of the Scenario 3, whose result is higher than other scenarios. The life cycle of the vehicle production was responsible for a major portion of the ACP impact category, because of the large consumption of metals, plastics and rubber contained in the

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vehicle body shell. The vehicle production contributes with 68% of acidifying emissions for Scenario 1, 53% for Scenario 2, 30% for Scenario 3, 66% for Scenario 4 and 77% for Scenario 5. According to the results, the BEV scenario is 61% more environmentally benign in terms of ACP impact category than the ICEVe scenario. This behavior is due to the use of fertilizers,

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agrochemicals and phosphate chemical products in the agricultural stage of the sugarcane production and also due to the acidifying substances emissions in the sugarcane bagasse combustion

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for cogeneration purposes and the combustion of ethanol in ICE. The ethanol production contributes with 25% of acidifying emissions for Scenario 1, 38% for Scenario 2, 63% for Scenario 3 and 17% for Scenario 4.

Acidifying emissions are also related to combustion of fossil fuels hence the exhaust emissions from gasoline are responsible for 11% of acidifying emissions for Scenario 1, 7% for Scenario 2 and 8% for Scenario 4. The transportation stage is responsible for 0.5% of the ACP

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impacts for Scenario 1, 4% for Scenario 2 and 3% for Scenarios 3, 4 and 5. The calculation of the ACP has revealed that the PHEV is contributing more than the ICEVg. This is due to the production of the metals contained in the battery production, which is responsible for 24% of the ACP impacts for Scenario 4 and 42% for Scenario 5. The metals production are responsible for a higher emission

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of NOx and SOx which are the main pollutants leading the ACP impacts. The vehicle and battery recycling contributes to a reduction of approximately 8–12% of the SO2–eq./km emissions.

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Negative values presented in Fig. 11 results in beneficial environmental impacts, regarding to the fact that the vehicle recycling makes a contribution in terms of avoided products.

Fig. 11. Acidification Potential (ACP) for vehicles under Brazilian conditions.

4.8

Eutrophication Potential (ETP)

Eutrophication covers all potential impacts of excessively high environmental levels of macronutrients, the most important of which are N–P2O5. Nutrient enrichment may cause an increase in the aquatic plant growth and the shift in species composition in both aquatic and 32

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terrestrial ecosystems. The major contributors to the ETP are the emissions of NH3, HNO3, NO, ା NO2, NOି ଷ , NHସ to air and Chemical Oxygen Demand (COD), Total–P, Total–N, phosphorus, ି H3PO4, NOି ଷ , NOଶ , NO, NOx to water.

Fig. 12 shows the potential impacts of vehicle technologies on ETP in terms of kg phosphate equivalents per kilometer (kg POିଷ ସ –eq./km) driven and the impacts of the subsystems. The Scenario 5 presented the best environmental result for the ETP impact category (2.95E-05 kg

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ିଷ POିଷ ସ –eq./km), followed by the Scenario 1 (3.79E-05 kg POସ –eq./km), Scenario 4 (4.09E-05 kg ିଷ POିଷ ସ –eq./km) and Scenario 2 (5.51E-05 kg POସ –eq./km). The results concerning about the ETP

confirm that the worst case is represented by the Scenario 3 (1.11E-04 kg POିଷ ସ –eq./km).

ETP impact demonstrates similar patterns to previous impact category. In fact, the ETP

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impact category is dominated by the same processes as the ACP (vehicle production, ethanol production and exhaust gas from gasoline). It should be noted that there are environmental impacts

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categories, such as, ACP, ETP and POP, where ICEVs fueled by ethanol presented worse environmental performance than ICEV fueled by gasoline, as well, the advanced vehicle technologies (PHEV and BEV).

These categories are, in general, intrinsic to agricultural products and they are expected to be higher than products derived from fossil resources such as gasoline. Similar trend was obtained by Bauer et al. (2015). The ethanol production was responsible for a major portion of the ETP impact

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category, because of the large consumption of agrochemicals in sugarcane culture, since the agricultural stage makes use of substances that contribute for this environmental impact category, such as stillage and fertilization with nitrogen and phosphate. The ethanol production contributes with 40% of eutrophicating substances emissions for Scenario 1, 54% for Scenario 2, 80% for

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Scenario 3 and 26% for Scenario 4.

The second major contributor for ETP impact was the vehicle production with 25% for

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Scenario 1, 17% for Scenario 2, 9% for Scenario 3, 23% for Scenario 4 and 32% for Scenario 5. The third main contributor for ETP impact was the exhaust gas from gasoline with 35% for Scenario 1, 20% for Scenario 2 and 23% for Scenario 4. The electricity production has a low rate of eutrophicating emissions with 1% for Scenario 4 and 12% for Scenario 5. The Li–ion battery production has a medium rate of emission of POିଷ ସ –eq./km with 38% for Scenario 4 and 79% for Scenario 5. The stage of more emission contribution is the production of the cathodes because of the residues responsible for the ETP impacts. The recycling stage (vehicle and battery) contributes to a reduction of approximately 6–10% of POିଷ ସ –eq./km emissions.

Fig. 12. Eutrophication Potential (ETP) for vehicles under Brazilian conditions. 33

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Sensitivity analysis

The sensitivity analysis has as objective to evaluate the uncertainties associated with the model by determining how an input parameter variation reflects on the indicators. The sensitivity analysis was carried out to find out the effect of the fuels and electricity consumption on the following environmental impact categories: ODP, ADP, FDP, GWP, HTP, POP, ACP and ETP. For

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the sensitivity analysis, the following variations were established: reduction of energy supply use by -10%, -30% and -50% and increase of energy supply use by +10%, +30% and +50%. The variation of the energy supply use (fuels and electricity) was chosen because is an important parameter, which influences all of the analyzed impact categories and it is common for each impact category

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under study.

According to the analysis, scenarios using gasoline have the highest GWP and ADP

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variations, while scenarios using ethanol have the largest variations for POP, ACP and ETP. HTP and ODP impact categories are more influenced by other non-energy raw materials, which produce more environmental impacts than those resulting from the variation in the energy supply use (fuel and electricity), so their variations are relative for each scenario. Table 5 provides a sensitivity analysis of the analyzed scenario. It should be noted that the negative sign denotes a decrease from

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the base case and the positive sign denotes an increase from the base case.

Table 5

Sensitivity analysis results for all evaluated scenarios and for each impact category analyzed.

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4.10 Policy implications

adoption

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There are two principal conceptual frameworks of policy instruments, which promote the of

advanced

transportation

technologies,

including

alternatives

vehicles

and

fuels/electricity: policy of technology push and policy of demand pull. The technology push is based on technology or fuel regulation and the demand pull is based on outcome regulation. In terms of alternative fuels, Brazil has already played a pioneering role in promoting the use of bioethanol derived from sugarcane. Therefore, on a nationwide scale, a pioneering system of blending gasoline and ethanol for FFVs was developed in Brazil. All these technological developments in Brazil have resulted in a reduction of the ethanol prices over the years (learning curve). Learning curves are empirical, with several benchmarks throughout the world. The Brazilian Alcohol Program (Proalcool) was established in 1975 with the purpose of reducing oil imports by 34

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producing ethanol from sugarcane. The program had positive environmental, economic, environmental and social aspects, and has become the most important biomass energy program in the world. The Proalcool program was based on a policy of technology push due to mainly the development of vehicle powered exclusively by ethanol. However, if Brazil was the pioneer in the development of ethanol fuel, the same could not be said about the electric cars. The EVs are not spreading in the Brazilian market, mainly due to the

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lack of infrastructure, economic and political issues and especially the high cost. The increase of the fleet of EVs in Brazil will require an increasing amount of energy supply in the coming years, which will make the use of electricity in the transportation sector an interesting alternative in relation to the conventional fuels currently used from a strategic and environmental point of views.

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On the strategic side, there would be greater diversification of energy sources for the transport sector. Electricity in Brazil is generated locally and distributed by a highly reliable interconnected

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system, with a relatively low cost, when compared to other liquid fuels. In addition, the use of EVs coupled with smart grids allows electric vehicles to function as buffers in the distribution network. In this case, the EVs charge its batteries in off-peak hours and discharging them at peak times. On the environmental side, the introduction of EVs reinforce the use of electricity, which in Brazil is generated almost entirely from renewable energy sources and reduces the use of the ICEs that are an important contributor of the GHG emissions. Moreover, this change can contributes to increase the

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energy efficiency, since the efficiency of the electric motor is 90% and the efficiency of ICE is 40%. Therefore, the government needs to implement acts of incentive programs (subsidies), tax exemptions, invest in the development of the EVs recharge stations infrastructure and mainly invest

diffusion of EVs.

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in Research & Development programs to create partnerships with industries to encourage the

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5. Conclusions

In this study, the environmental performances of five types of vehicles in Brazilian conditions were compared by means of LCA: ICEVg, ICEVe, ICEVf, PHEV and BEV. The environmental impacts assessment categories in this work include: ODP, ADP, FDP, GWP, HTP, POP, ACP and ETP. Life cycle impact assessment method applied in this work was the CML 2 Baseline 2000 method that is an update from the CML 1992 method. The software SimaPro 7.0.1 was used to make the calculations, analyses and comparisons of the environmental impacts in the analyzed scenarios.

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Main particularities of the Brazilian scenarios are the electricity grid mix including a significant percentage of renewable energy sources and the widespread utilization of ethanol as fuel used in FFVs and mixture with the commercialized gasoline in a percentage above 25%. There is not a single technology with a good performance in all the environmental impact categories. However, the BEV is the vehicle with the lower environmental charges, followed by the ICEVe that has also lower environmental charges, while the ICEVg and ICEVf are the vehicles with the highest

impact categories isolated, having in mind its objective.

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global environmental loads. This means that for a specific study, it is mandatory to analyze the

The ICEVg, ICEVf, ICEVe and PHEV have similar trend lines for the environmental impact categories that are more sensible to the ethanol production (POP, ACP and ETP), since they use

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ethanol as a component of the fuel. However, the ICEVe has the greatest impacts in POP, ACP and ETP, as a result of the exclusive use of ethanol as fuel, manly due of the contribution of the

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agricultural practices for sugarcane production due to the agrochemicals, application of fertilizers (N-P-K), filter cake and stillage. The ethanol fuel is beneficial with respect to the saving of fossil fuel energy and in relation to climate change; nevertheless, it is detrimental regarding to ACP, ETP and POP.

For the environmental impact categories that are more sensible to the use of gasoline (ADP, FDP and GWP) ICEVg, ICEVf and PHEV have similar trend lines, where ICEVg has the higher

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impacts because of the predominant use of gasoline. In view of the concerns about the increase in emissions of GHG by vehicular emissions, it is concluded that these particularities of the Brazilian energy system heavily influence the results, and could reduce the amount of these gases in the atmosphere. The replacement of 50% of the fleet of ICEVg by ICEVe and would decrease annually

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the carbon emissions around 4.58E+10 kg CO2–eq. (33% of the total emissions) and the replacement of 50% of the fleet of ICEVg by BEV would reduce the carbon emissions by 3.32E+10

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kg CO2–eq. (24% of the total emissions) by the total fleet of vehicles. For the HTP category the higher results are for the BEV and PHEV because of the influence of the impacts of the Li–ion batteries production. The vehicles using batteries have the major HTP potential, with this result as a consequence of the products used in the manufacture of the batteries. The ICEVf presents significant improvements referred to the GWP and FDP in relation to the ICEVg, because of the hydrous ethanol consumption of this one, as part of its fuel. The PHEV presents similar characteristics with the ICEVg because both use gasoline as fuel, but the electricity utilization as fuel result in a GWP significantly lower in comparison with the ICEVg. The PHEV also shows similar characteristics with the BEV, mainly to the fact the use of Li– ion batteries, which promotes higher values for the HTP and the ADP categories, but a lower weight of the batteries in relation to the BEV, the PHEV shows slightly better results for these categories. 36

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The charging electricity has very low emissions of fossil carbon; therefore EVs can reach their full potential in mitigating global warming. Thus, the technology referred to BEV has the better results of the environmental impacts in relation to the categories of POP, ACP and ETP due to the electric matrix of Brazil.

Acknowledgements

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The authors are very grateful to the financial support provided by the Brazilian National Research and Development Council (CNPq). The Research Support Foundation of the Minas Gerais State (FAPEMIG) and the Coordinating Body for the Improvement of Postgraduate Studies in Higher Education (CAPES) for the funding of Research and Development (R&D) projects. The support of

Appendix A. Supplementary data

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projects whose results are included in this paper.

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graduate students and the production grants that allowed the accomplishment of the research

Supplementary data related to this article can be found, in the online version, at: https://doi.org/10.1016/j.jclepro.2018.XX.XXX.

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43

Table 1

ACCEPTED An overview of recent LCA studies (2012–2018) of MANUSCRIPT conventional internal combustion engines vehicles, fuel cell vehicles, hybrid electric and pure electric vehicles. Abbreviations are explained right below the Table. Functional

Goal and scope

Powertrains

Unit (km)

Analysed environmental impact

configurations/fuels

GHG emissions, energy consumption

different sport utility vehicles for life cycle

and water withdrawal. BEV had the

phases ranging from manufacturing to End-of-

lowest GHG emissions (77,200 kg

Life (EOL) recycling, which differ only in terms

CO2–eq.) and the lowest energy

of type of fuel used (gasoline, diesel or

consumption

(1046.8

electricity). It was carried out a hybrid economic

considering

the

input-output life cycle assessment (EIO-LCA)

impacts

method to estimate the environmental impacts of

manufacturing.

vehicles. In manufacturing stage, the life cycle inventories of car fabrication, battery/fuel cell

miles)

production and infrastructure manufacturing

ICEVg, ICEVd, PHEVg, FCEV, BEV

LCA

was

complemented with a sensitivity analysis, using

It was performed a cradle-to-grave comparative for

comprehensive

GJ) and water withdrawal (5186 m³

comparison

and

environmental impact assessment of ICE-based vehicles fueled by different types of fuels (fossil

similar

between 100,000 and 110,000 kg CO2–eq., but the FCEV fueled by H2

had a large water withdrawal (8530

HTP, GWP, ACP, ETP, ADP, ODP, TEP

from

assessment Health,

CML

2001

impact

method

and

Human

Ecosystem

quality

and

TE D

Resources from Eco-indicator 99. ICEVH2 is more favorable in all of the

50% gasoline). All the processes for life cycle

environmental

were

analyzed

from

vehicles

operation/maintenance

and

ICEVg, ICEVd, ICEVmg, BEV,

impact

categories

analyzed. ICEVa has lowest GWP after the BEVs and yield lower ODP

Bicer and

PHEV, ICEVa, ICEVH2,

values than BEVs because NH3 is a

Dincer

to calculate the energy consumption and GHG

ICEVLPG, ICEVcng

sustainable and clean fuel. Although

(2018)

EP

vehicles disposal. GREET 2015 model was used

emissions of selected vehicles from the well-to-

BEVs is the best option in relation to

wheels. The LCA database Ecoinvent, v2.2 was

GHG emissions, the production and

used as source of background life cycle

disposal of batteries have significant

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200,000

demonstrated

in hybrid electric vehicles (50% electricity and

manufacturing,

al. (2018)

of GHG emissions, which ranged

fuels and renewable fuels), pure battery and plug-

phases

Karaaslan et

m³).

Monte Carlo simulation.

LCA

between energy consumption (1172.9

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The

battery

PHEVg

environmental performances in terms

In the EOL stage, the benefits of recycling were

phase.

the

The

demonstrates a good performance

vehicles

and emissions were calculated for each vehicle.

manufacturing

even

of water). All of the fuel powered

impacts of fuel production, electricity generation

taken into account and then subtracted from the

for

SC

were estimated separately. In operation step, the

GJ)

environmental

RI PT

321,869

1.0

categories and main results

Cradle-to-grave comparative LCA for five

(200,000

Reference

inventories data. Life cycle impact assessment of

impacts in relation to ACP, ETP and

the selected vehicle types was carried out using

HTP. ICEVmg is the worst option in

the LCA software SimaPro. A Monte Carlo

relation to GHG emissions because

analysis

methanol

was

performed

to

assess

the

production

is

mainly

uncertainties.

dependent of natural gas.

Compare the environmental performances of four

GWP, ODP, ACP, FEUP, MEUP;

types of vehicles using a LCA perspective. They

HTP,

compared the impacts of different powertrains

METP, IRP, ALO, ULO, NLT,

and a repowering of the same initial vehicle,

WDP, MDP, FDP from ReCiPe

which is a midsize car and a motor power of 75

impact assessment method. In the

kW was chosen for the electric vehicles in order to ensure the original drivability. It was assessed

ICEVg, BEV, PHEVg, FCHEV

POP,

PMF,

TEP,

FETP,

case of the climate change, fuel

Lombardi et

depletion and cumulative energy

al. (2017)

the impacts of powertrain production, vehicle use

demand indexes, the lowest value

phase and powertrain EOL.

corresponds to the PHEVg, followed by the FCHEV, BEV and lastly ICEVg. Substituting a conventional ICEVg with the corresponding pure

BEV offers the reduction of the values of climate change (-15%),

ACCEPTED MANUSCRIPT cumulative

energy demand (-12%)

and the fuel depletion (-28%). LCA of a passenger car, which is comprised by

ADP, FDP, ACP, ETP, GWP, HTP,

the manufacturing, use phase and disposal phase

ODP, POP, FETP, METP, TEP from

of advanced vehicles and compare it to the life

CML 2001 baseline. The results

cycle of conventional vehicle, in such way that

appointed the ICEVd as the greatest

all the components of the vehicle, including the

contribution of GWP, mainly in the

battery system, the glider, and the powertrain are

use phase. The manufacturing phase

analysed in hot spot analysis.

of the BEV is almost double that of

HEVd (60%), PHEV

ICEVd

for

GWP

due

to

the

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ICEVd, BEV, HEVd (30%),

1.0

production

and

use

of

metals,

Tagliaferri et al. (2016)

chemicals and energy required in the systems. The BEV manufacturing phase

determined

the

highest

environmental burdens, mainly in the

SC

ETP, HTP and TEP categories, as a result of the use of metals in the battery manufacturing. GWP, HTP, ACP, POP, PMF from

Cradle-to-grave LCA of passenger vehicles and

electric

devices.

It

was

investigated

the

environmental performance of current and future mid-size passenger vehicles. A comparative LCA was performed to assess the conventional internal 240,000

combustion engine vehicles (fuelled by gasoline, diesel and natural gas), plug-in electric vehicles, fuel cell vehicles and pure electric vehicles. The electricity and H2 production chains from fossil,

ReCiPe impact assessment method.

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their energy supply chains with a focus on

A great mitigation of climate change was obtained for BEVs, while nonfossil energy resources were used for

ICEVg, ICEVd, ICEVcng,

production of electricity and H2.

HEVg, HEVd, HEVcng, BEV,

However, BEVs and FCEVs were

FCEV

worse than modern fossil fueled

PMF, as a consequence of emissions

European (EU-27) countries for 2012 and 2030

chains.

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along vehicle and fuel production

GWP, ACP, ETP, ADP, HTP from

vehicles and combustion engine vehicles was

CML 2001 and POP, FDP and PMF

compared through LCA. It was taken particular

from ReCiPe. The BEVs have better

EP

The environmental performance of electric

attention on the electricity grid mix of Italy that

performance

will charge the electric vehicles using appropriate

approximately

power mix of the Italian electricity market for

impact categories, with except for

two different scenarios (2013 and 2030). In both

ETP and HTP, mainly due to battery

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150,000

2013 and 2030 scenarios, the power mix that

(2015)

ICEVs in terms of ACP, HTP and

nuclear and renewable energy resources from

were taken into account.

Bauer et al.

ICEVg, BEV

than all

ICEVg the

in

analyzed

manufacturing. The environmental

supplies energy to electric vehicles is dominated

impacts of ICEVg are mainly due to

by fossil fuel power plants, which is comprised

use phase and fuel production. In

by more than 60% of gas turbine combined cycle

addition, the BEVs and batteries

power plants.

manufacturing have greater loads for

Girardi et al. (2015)

all environmental impact categories than in relation to conventional ICEVg manufacturing.

18,186 (11,300 miles)

Life cycle emissions for different types of

Total air pollutants emissions and

vehicles associating the emissions with travel at

greenhouse effects (GHG emissions). Life cycle studies of transportation

different urban speeds. Also, this paper describes

Mitropoulos

a life cycle costing to include indirect costs, such

ICEVg, HEV, FCEV, BEV,

sector needs to have data from fuel

and

as health damage due to air pollution and loss of

PHEV, GPT, GSUV

types and costs, insurance, fees and

Prevedouros

productivity due to wasting time for users. They

taxes, vehicle weight, fuel efficiency,

(2015)

analysed different vehicle life cycle pollutants,

vehicle mileage, battery capacity, etc.

and the resultant societal and consumer life cycle

The best environmental option was

costs associated. The comparisons are enabled by

BEV, followed by PHEV and FCEV

internalizing externalities including emissions

but the electricity costs are a limiting

ACCEPTED MANUSCRIPT factor.

and time losses.

LCA study comparing different vehicle options

Greenhouse effects (GHG emissions)

across 50 states of the U.S., including their

and

representative average and marginal electricity

widespread adoption of BEVs was

generation mixes and regional driving patterns,

not a favorable strategy because of

also it includes the battery manufacturing and

electricity generation mix of the U.S.,

vehicle maintenance.

which is based on natural gas (31%),

energy

consumption.

The

coal (30%) and petroleum (1.5%). The adoption of BEVs could result in

Onat et al.

(18%), HEV, ICEVg

reductions of up to 73% of GHG

(2015)

RI PT

1.0

BEV, PHEV (62%), PHEV

emissions

and

55%

of

energy

consumption. Variations of GHG emission factors of electric power generation showed that any GHG emission factor below 600 g CO2–

SC

eq./kWh could make BEVs the least carbon intensive option.

Comparative LCA to assess the environmental

GWP, ACP, MDP and respiratory inorganic

impacts of all vehicles registered in Europe in

production, manufacturing of vehicles, use phase operation, maintenance and EOL of all the cars. It was taken into account the data of fuel consumption, direct emissions, weight and acceptable limits for exhaust of vehicles from European databases. An attributional LCA was

variation of the vehicle weight, the energy

batteries

impacts regarding to the ACP and MDP, but these types of vehicles have positive environmental benefits

BEV, FCEV, ICEVcng, HEV,

with respect GWP. Conventional

ICEVLPG, ICEVg, ICEVbio,

ICEVs using fossil fuels have the

ICEVe, ICEVd.

largest impact on GWP. On average

Messagie et

ICEVd have lower impacts on GWP

al. (2014)

compared to ICEVg, as they tend to

a Monte Carlo simulation.

consume less fuel. BEVs have the

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consumption and the emissions were assessed by

lowest impact on GWP, with the exception of the ICEVe fueled with ethanol from sugarcane (Brazil). When producing electricity solely from oil or coal the impact on GWP can be as high as in the case of conventional ICEVs.

It was carried out a LCA to analysis the whole

ADP, ACP, ETP, GWP, ODP, HTP,

life cycle, from the fuel production, storage,

POP, FETP, METP, TEP. The use of

transportation and its use as fuel in the

renewable

operational phase of the vehicle. The fuel

production or electricity generation)

(hydrogen) production was based on Italian

has better performance on most of the

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200

The

contribute to high environmental

EP

1.0

performed and the results of the simultaneous

effects.

present in BEVs, FCEV and HEV

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2011. It was investigated the raw material

energy

source

(H2

energy mix that was analysed as benchmarking

FCEV-WE, FCEV-BE, ICEVH2,

considered impact categories than the

element. The results are compared with electric

FCEV-IT, BEV-W, BEV-B,

use of electricity from Italy public

Bartolozzi

BEV-IT

grid. BEV scenarios have in general

et al. (2013)

vehicles based on Italian electricity mix.

better environmental performances compared

to

the

H2 scenarios.

However, these scenarios do not include the energy storage and distribution phase, which gives a great contribution to the H2 scenarios. LCA of the vehicles and WtW for energy carriers 1.0

using cradle-to-grave perspective in such way that a comparative LCA allows a detailed

Greenhouse ICEVg, ICEVd, BEV, HEV

effects

(GHG

emissions), energy consumption. The BEVs are more efficient and cleaner

Faria et al. (2013)

comparison between vehicles technologies and

than ICEVs. The BEVs significantly

the

of

reduce the country’s dependence on

technological development and improvement in

fuels. The most significant

the life-cycle phase of vehicles. This work

contributor to the GHG emissions

focused on mainly on the emissions of the

over the life cycle of vehicles is the

vehicle operation phase. A detailed analysis was

operation phase, contributing with

made on the electricity grid mix, based on the

85–90% for a conventional ICEVg.

contribution of each type of primary energy

However, for a BEV this is highly

source and their variation along a year for the

dependent on the electricity mix,

electric vehicles assessment.

whereas if the grid mix is highly

identification

of

opportunities

ACCEPTED MANUSCRIPT fossil

comprised

by

fossil

fuels

the

RI PT

operation phase of a BEV will represent 75% of vehicle life cycle emissions. On the other hand, if the electricity mix is comprised by renewable

energy,

the

BEV

manufacturing and battery production will represent 50% of the whole

SC

emissions.

LCA of vehicles production and utilization stages

Air

taking into account the phases that are involved

energy in a motor. Economic and environmental impacts were evaluated, based on extensive real data. Thus, the goal of the work was to obtain results 250,000

to

support

the

implementation

of

advanced technologies of powertrain in Greece.

and

HEV and BEV have advantages over

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the final transformation of fuel into mechanical

emissions

greenhouse effects (GHG emissions).

in a vehicle’s energy life cycle, from the extraction of natural resources to produce fuels to

pollutants

conventional

ICEVs.

While

electricity consumption does not emit CO2 at the point of use, the GHG emitted by electricity mix used to charge HEVs and BEVs is essential to calculate the whole life cycle GHG

ICEVg, HEV, BEV

emissions.

Therefore,

electric

EP

TE D

vehicles cause significantly lower

renewable sources, the environmental impacts should be clearly addressed at all phases of the fuel production and energy generation to prove the benefits of electric vehicles due to the CO2 savings potential. Energy consumption and greenhouse effects

AC C

cycles

maintenance,

dismantling

and

(manufacture, recycle)

(2013)

the electricity grid is comprised by

account

vehicles

Koroneos

emissions than the ICEVg. If most of

LCA focused on well-to-wheels not taking into the

Nanaki and

(GHG

emissions).

The

of

authors conclude that all these

advanced vehicles throughout their lifetimes. It

advanced vehicles require more

was investigated the lifetime GHG emissions

energy for production than ICEVs,

30.0, 60.0

and energy use for different types of fuel

ICEV, HEV, PHEV, EREV,

and 90.0

efficient vehicles, showing that all of them

BEV, FCEV

mainly due to the additional power electronics

and

battery

packs.

improve, in both dimensions, the values

Nevertheless, the energy savings in

associated with ICEVs.

the fuel cycle for these advanced

Gao and Winfield (2012)

vehicles compensates the marginal energy required during the vehicle cycle (production stage). Comparative LCA of typical small European

GWP, ACP, POP, HTP, ETP, ADP,

vehicles, including vehicle production, use phase 1.0

and EOL together with supply chains

FDP, PMF, FETP, TEP. For a vehicle EV Li-NCM, EV Li-FePO4, ICEVg, ICEVd

lifetime

of

150,000

km

BEVs

powered by the European electricity mix offer a 10–24% decrease in GWP relative to ICEVs (ICEVg and

Hawkins et al. (2012)

ICEVd). However, BEVs exhibit the potential for significant increases in

ACCEPTED MANUSCRIPT ETP, FETP, HTP and MDP impacts. The results are sensitive in relation to electricity mix, use phase energy consumption, vehicle lifetime and timetable of the replacement of battery. If the lifetime of vehicle is set at 200,000 km the benefits of BEVs

regarding

to

GWP

are

overdone in relation to ICEVg (27– and

ICEVd

(17–20%).

RI PT

29%)

However, if the lifetime of vehicle is set at 100,000 km the benefits of EVs are decreased in relation to ICEVg (9–15%) and would be equivalents from those of ICEVd.

SC

Legend: ACP: Acidification Potential; ADP: Abiotic Depletion Potential; ALO: Agricultural Land Occupation; BEV: Battery Electric Vehicle; BEV-B: Battery Electric Vehicle fuelled with electricity from biomass gasification; BEV-IT: Battery Electric Vehicle fuelled with electricity from Italian electricity mix; BEV-W: Battery Electric Vehicle fuelled with wind electricity; EOL: End-of-Life; EREV: Extended-Range Electric Vehicle; ETP: Eutrophication Potential; EV Li-FePO4 Euro: Electric Vehicle with battery of Lithium Iron Phosphate; EV Li-NCM Euro: Electric Vehicle with battery of Lithium Nickel Cobalt Manganese; FCEV: Fuel Cell

M AN U

Electric Vehicle; FCEV-BE: Fuel Cell Electric Vehicle fuelled with hydrogen produced by electrolysis supplied with biomass gasification electricity; FCEV-IT: Fuel Cell Electric Vehicle fuelled with hydrogen produced from Italian electricity mix; FCEV-WE: Fuel Cell Electric Vehicle fueled with hydrogen produced by electrolysis supplied with wind electricity; FCHEV: Fuel Cell Hybrid Electric Vehicle; FDP: Fossil Fuel Depletion Potential; FETP: Freshwater Ecotoxicity Potential; FEUP: Freshwater Eutrophication Potential; GHG: Greenhouse Gases; GPT: Gasoline Pickup Truck; GSUV: Gasoline Sports Utility Vehicle; GWP: Global Warming Potential; HEV: Hybrid Electric Vehicle; HEVcng: Hybrid Electric Vehicle compressed natural gas fuelled; HEVd: Hybrid Electric Vehicle diesel fuelled; HEVg: Hybrid Electric Vehicle gasoline fuelled; HTP: Human Toxicity Potential; ICEVa: Internal Combustion Engine Vehicle fuelled by ammonia; ICEVbio: Internal Combustion Engine Vehicle fuelled by biodiesel; ICEVcng: Internal Combustion Engine compressed natural gas fuelled; ICEVd: Internal Combustion Engine diesel fuelled; ICEVe: Internal Combustion Engine ethanol fuelled; ICEVg: Internal Combustion Engine gasoline fuelled; ICEVH2: Internal Combustion Engine Vehicle fuelled with hydrogen produced by direct separation in biomass gasification; ICEVLPG: Internal Combustion Engine Liquefied Petroleum Gas fuelled; ICEVmg:

TE D

Internal Combustion Engine Vehicle fuelled by methanol (90%) and gasoline (10%); IRP: Ionizing Radiation Potential; LCA: Life Cycle Assessment; MDP: Mineral Resources Depletion Potential; METP: Marine Ecotoxicity Potential; MEUP: Marine Eutrophication Potential; NLT: Natural Land Transformation; ODP: Ozone Layer Depletion Potential; PHEV: Plug-in Hybrid Electric Vehicle; PHEVg: Plug-in Hybrid Electric Vehicle gasoline fuelled; PMF: Particulate Matter Formation; POP:

AC C

EP

Photochemical Ozone Formation Potential; TEP: Terrestrial Ecotoxicity Potential; ULO: Urban Land Occupation; WDP: Water Depletion Potential.

ACCEPTED MANUSCRIPT

Table 2

Summary of the different proportions of gasoline, ethanol and electricity used in the five different scenarios analysed in this work. Scenarios

For entire life cycle of vehicle (160,000 km)

For Functional Unit (1 km)

Ethanol (l)

Electricity (kwh)

Gasoline (l)

Ethanol (l)

Electricity (kwh)

Scenario 1

9836.10

3278.70

–

0.061

0.020

–

Scenario 2

8108.10

6306.30

–

0.051

0.039

–

Scenario 3

–

18823,50

–

–

0.118

–

Scenario 4

7137.90

2379.30

3751.80

0.045

0.015

0.023

Scenario 5

–

–

27200.00

–

–

0.170

AC C

EP

TE D

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RI PT

Gasoline (l)

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Table 3

Total quantity of fuels used in the Scenario 1, Scenario 2 and Scenario 3. Unit

Scenario 1 (ICEVg)

Scenario 2 (ICEVf)

Scenario 3 (ICEVe)

Specific consumption

km/l

12.2

11.1

8.5

Total gasoline A consumption

l

9836.10

8108.11

0

Total ethanol consumption

l

3278.70

6306.31

18823.50

AC C

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TE D

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Parameter

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Table 4

Calculated energy consumption of Scenario 4 and Scenario 5. Unit

Scenario 4 (PHEV)

Scenario 5 (BEV)

Travelled distance in electric mode

km

224,000

160,000

Travelled distance in gasoline mode

km

137,600

0

kWh

3808.0

27200.0

Total consumption of type A gasoline

l

7120.8

0

Total ethanol consumption

l

2373.6

0

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EP

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Total electrical consumption

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Parameter

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Table 5

Sensitivity analysis results for all evaluated Scenarios and for each impact category analyzed. Range of variation

Scenarios

Percentage change from Base Case ADP (%)

FDP (%)

GWP (%)

ODP (%)

HTP (%)

POP (%)

ACP (%)

ETP (%)

Scenario 1

0.00

-46.87

-39.90

-9.55

-19.94

-43.77

-27.73

-44.62

-50%

Scenario 2

0.00

-46.34

-37.50

-9.26

-20.92

-45.58

-31.09

-43.42

-50%

Scenario 3

0.00

-4.00

-12.54

-6.20

-22.42

-47.98

-39.72

-45.84

-50%

Scenario 4

0.00

-43.17

-33.35

-8.32

-16.99

-38.62

-19.77

-31.94

-50%

Scenario 5

0.00

-27.44

-23.84

-11.30

-27.51

-14.92

-4.15

-7.18

-30%

Scenario 1

0.00

-28.12

-23.94

-5.73

-11.97

-26.26

-16.64

-26.77

-30%

Scenario 2

0.00

-27.80

-22.50

-5.56

-12.55

-27.35

-18.65

-26.05

-30%

Scenario 3

0.00

-2.40

-7.53

-3.72

-13.45

-28.79

-23.83

-27.50

-30%

Scenario 4

0.00

-25.90

-20.01

-4.99

-10.19

-23.17

-11.86

-19.16

-30%

Scenario 5

0.00

-16.47

-14.30

-6.78

-16.51

-8.95

-2.49

-4.31

-10%

Scenario 1

0.00

-9.37

-7.98

-1.91

-3.99

-8.75

-5.55

-8.92

-10%

Scenario 2

0.00

-9.27

-7.50

-1.85

-4.18

-9.12

-6.22

-8.68

-10%

Scenario 3

0.00

-0.80

-2.51

-1.24

-4.48

-9.60

-7.94

-9.17

-10%

Scenario 4

0.00

-8.63

-6.67

-1.66

-3.40

-7.72

-3.95

-6.39

-10%

Scenario 5

0.00

-5.49

-4.77

-2.26

-5.50

-2.98

-0.83

-1.44

10%

Scenario 1

0.00

9.37

7.98

1.91

3.99

8.75

5.55

8.92

10%

Scenario 2

0.00

9.27

7.50

1.85

4.18

9.12

6.22

8.68

10%

Scenario 3

0.00

0.80

2.51

1.24

4.48

9.60

7.94

9.17

10%

Scenario 4

0.00

8.63

6.67

1.66

3.40

7.72

3.95

6.39

10%

Scenario 5

0.00

5.49

4.77

2.26

5.50

2.98

0.83

1.44

30%

Scenario 1

0.00

28.12

23.94

5.73

11.97

26.26

16.64

26.77

30%

Scenario 2

0.00

27.80

22.50

5.56

12.55

27.35

18.65

26.05

30%

Scenario 3

0.00

2.40

7.53

3.72

13.45

28.79

23.83

27.50

30%

Scenario 4

0.00

25.90

20.01

4.99

10.19

23.17

11.86

19.16

30%

Scenario 5

0.00

16.47

14.30

6.78

16.51

8.95

2.49

4.31

50%

Scenario 1

0.00

46.87

39.90

9.55

19.94

43.77

27.73

44.62

Scenario 2

0.00

46.34

37.50

9.26

20.92

45.58

31.09

43.42

Scenario 3

0.00

4.00

12.54

6.20

22.42

47.98

39.72

45.84

Scenario 4

0.00

43.17

33.35

8.32

16.99

38.62

19.77

31.94

Scenario 5

0.00

27.44

23.84

11.30

27.51

14.92

4.15

7.18

50% 50% 50%

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