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Lightweight materials equal lightweight greenhouse gas emissions?: A historical analysis of greenhouse gases of vehicle material substitution
Journal Pre-proof Lightweight materials equal lightweight greenhouse gas emissions?: A historical analysis of greenhouse gases of vehicle material substitution Kotaro Kawajiri, Michio Kobayashi, Kaito Sakamoto PII:
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DOI:
https://doi.org/10.1016/j.jclepro.2019.119805
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JCLP 119805
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Journal of Cleaner Production
Received Date: 3 July 2019 Revised Date:
17 December 2019
Accepted Date: 18 December 2019
Please cite this article as: Kawajiri K, Kobayashi M, Sakamoto K, Lightweight materials equal lightweight greenhouse gas emissions?: A historical analysis of greenhouse gases of vehicle material substitution, Journal of Cleaner Production (2020), doi: https://doi.org/10.1016/j.jclepro.2019.119805. This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. 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. © 2019 Published by Elsevier Ltd.
Lightweight materials equal lightweight greenhouse gas emissions?: A historical analysis of greenhouse gases of vehicle material substitution
Kotaro Kawajiri (Corresponding) National Institute of Advanced Industrial Science and Technology 1-1-1 Higashi, Tsukuba, Ibaraki, 305-8505, Japan Email: [email protected] Tel: (81)-29-861-8089
Michio Kobayashi National Institute of Advanced Industrial Science and Technology 1-1-1 Higashi, Tsukuba, Ibaraki, 305-8505, Japan
Kaito Sakamoto National Institute of Advanced Industrial Science and Technology 1-1-1 Higashi, Tsukuba, Ibaraki, 305-8505, Japan
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Highlight:
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Greenhouse gas impacts by material substitution of an automobile are investigated.
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Weight of automobile has increased even with light materials by rebound of design.
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Embodied GHGs of automobiles have increased with increasing low-density materials.
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Substitution from steel to high tensile steel is a promising option to reduce GHGs.
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Competition over steel will become severer for lightweight but GHG intensive materials.
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Abstract 8
The impacts of greenhouse gases (GHG) to vehicles through improvements in fuel
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efficiency via material substitutions and their historical trends were analyzed to assess if
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lightweighting actually provides its expected benefits. Data for the weight and fuel efficiency of
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American and Japanese cars over the past 30 years was used for trend analysis. Also, the
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impacts of GHG in substituting steel for high strength steel, aluminum, carbon fiber reinforced
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polymer, and magnesium were analyzed. This study shows that while the amount of low-density
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materials in a vehicle has increased, the weight itself has increased because of the “rebound of
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design” reflecting the consumer demands. In lightweighting strategy, the material substitution of
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steel for high strength steel is the most promising option to reduce GHG emissions. Based on
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recent historical trends, this analysis shows that the GHG payback miles have increased and will
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continue to increase unless the reduction in GHG emissions occur at higher rates than that of
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fuel efficiency improvement from steel-based vehicles. This suggests that the competition over
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steel will become severer in the future for other materials with low densities. To reverse the
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result, it is necessary to reduce GHG intensities of materials at higher rates than that of
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improvement of fuel efficiency.
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Key words: automobile, GHG impact, material substitution, historical analysis, lifecycle
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analysis 2
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1. Introduction:
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Reducing greenhouse gas (GHG) emissions in the transportation industry is an
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increasing priority. According to the International Organization of Motor Vehicle Manufacturers
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(OICA), road transport is responsible for approximately 16% of total global carbon dioxide
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(CO2) emissions (OICA, 2015). The automotive industry has a positive impact on daily life but
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concerns over the negative environmental impact of CO2 emissions have intensified due to the
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growing number of vehicle (Orsato and Wells, 2007).
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market is expected to produce over 100 million new vehicles per year (Pervaiz, 2015). To
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reduce vehicle GHG emissions, Automotive OEMs (Original Equipment Manufacturers) are
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now required to comply with governmental goals to improve fuel efficiency. In the U.S.A.,
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Corporate Average Fuel Economy (CAFE) requirements will rise to 54.5 miles per gallon (mpg)
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by 2025 from 37.8 mpg in 2016 (U.S. EPA, 2010). The European Union (EU) has imposed strict
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CO2 limits, 95 g CO2/km(REGULATION (EC), 2009), which have a direct relation with fuel
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efficiency.
By the year 2020, the automotive
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There are number of approaches that manufacturers can use to achieve fuel efficiency
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and comply with CO2 targets, such as reducing aerodynamic drag, driveline, transmission loss,
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tire rolling resistance, electrical plastics, and weight (Simply and Haywood, 2016). Among
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those options, lightweight automotive designs that reduce vehicle weight is currently considered
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one of the most important solutions to improve fuel economy and reduce harmful emissions
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(Cui et al., 2011). In recent years, this concept, known as lightweighting, has become a major
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research theme in the transport industry; the main motivations are the anticipated fuel savings
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and the ability to comply with stricter environmental legislation in various jurisdictions, such as
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Europe, North America, and Asia (Pervaiz et al., 2016). As previous studies have discussed,
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material substitution appears a promising option for lightweighting (Simply and Haywood,
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2016).
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2. Past studies on lightweighting and improvements in fuel efficiency
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A number of studies have discussed the relationship between weight reduction and fuel
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efficiency improvements (Tharumarajah and Koltum, 2007). Here, some examples of these
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studies are discussed. Pervaiz et al. (2016) suggested that compliance with the CO2 emission
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targets set for Europe in 2020, i.e., 95 g CO2/km, requires a 200–300 kg reduction in vehicle
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weight. A 2002 National Academy of Sciences (NAS) study estimated that each 10% reduction
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in mass (up to a 20% maximum) results in a 5.1% reduction in fuel consumption, which does
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not include engine downsizing or other powertrain changes that maintain constant performance
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levels (Isenstadt et al., 2016). Modeling work, sponsored by the Department of Energy at the
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National Renewable Energy Laboratory (NREL), also used a detailed model to understand
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vehicle efficiency and predicted a 6.9% improvement in fuel efficiency for a 10% reduction in
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weight with engine size adjustments. A model that combines curb weight and fuel consumption
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data with a technique to normalize vehicle performance indicates that a 10% reduction in
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vehicle weight yields a 5.6% reduction in fuel consumption for passenger cars (Cheah, 2016). In
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these analyses, the main conclusion is that weight reduction will improve fuel efficiency.
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However, an argument exists stating that weight reduction alone does not improve fuel
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efficiency (Cheah, 2016). Therefore, attempts to understand if there is historical truth to the
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concept of lightweighting become necessary.
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Although the use of new types of lightweight materials with improved fuel efficiency
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can reduce fuel consumption and tailpipe emissions during the driving stage, those lightweight
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materials may also consume more energy and produce more environmental emissions during
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other life phases compared with traditional steel materials (Liu et al., 2012). A lightweight
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design could lead to higher environmental impacts over the lifespan of a vehicle compared with
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traditional designs with respect to the lifecycle (Dubreuil et al., 2010). Current fuel economy
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and tailpipe emission standards and regulations ignore the environmental performance of other
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vehicle life phases such as the production and processing of lightweight materials (Liu and
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Müller, 2012) and do not ensure overall GHG emissions in the lifecycle of a vehicle (Danilecki
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et al., 2017). Therefore, understanding the net benefits of lightweighting is required since the
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production of lightweight materials (e.g., aluminum, magnesium, and carbon composites) is
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generally more energy intensive than conventional materials, such as steel and steel alloys (Kim
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and Wallington, 2013). However, conclusions based on lifecycle assessments (LCAs) of the
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benefits of vehicle lightweighting are often inconsistent due to the use of incongruous modeling
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methods and parameters (Raugei et al., 2015). LCA practitioners face the challenge of
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estimating fuel consumption during lightweight vehicle operation, i.e., the most energy
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consuming stage of a vehicle’s lifecycle (Kim and Wallington, 2013). Therefore, understanding
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how the amount of weight reduction correlates with the magnitude of improvement in fuel
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efficiency are crucial steps.
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3. Goals and scope of this study In this analysis, two important questions in applying the lightweighting concept are addressed.
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The first is whether past material substitution actually yields lightweight vehicles.
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Whitefoot et al. (2012) mentioned that lightweighting is possible by producing smaller vehicles.
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However automotive manufacturers could instead reduce weight through material substitution
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coupled with vehicle component redesign all while maintaining current vehicle size. Cheah
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(2010) pointed out that increases in vehicle weight continue to occur in spite of the vast effort
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placed on material improvement in the industrial and academic sectors. In order to understand
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what had happened in the past, the historical trend of vehicle weight, material compositions and
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GHG emissions of American and Japanese cars for the past thirty years are analyzed. With this
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fact base analysis,
the first question is answered.
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The second question relates to the benefits of material substitution. Material
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substitution involves the use of aluminum, high strength steel, magnesium, plastic, or polymer
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composites as alternatives to cast iron and steel (Bandivadekar et al., 2008). However, from a
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lifecycle perspective, choosing the most appropriate lightweight concepts and materials is
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crucial to avoid shifts in environmental burdens (Warsen and Krinke, 2012). And, a range of
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lightweighting strategies are currently being considered and tested by a number of car
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manufacturers in Europe and elsewhere such as Audi (Audi, 2017), BMW (BMW, 2016), Ford
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(Ford, 2014), and JLR (JLR, 2018). For the second question, life-cycle analysis on GHG
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emissions when 1kg of steel is substituted by other materials is performed. Then,
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increase by material substitution and GHG savings by fuel efficiency improvement achieved by
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lightweighting during the use phase are compared. There are several articles performing the
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analysis of net GHG increase/decrease by comparing GHG emissions increase and savings by
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GHG
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material substitution. Some examples are to compare the net GHG emissions in several
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generation of vehicle models (Danilecki et at., 2017), to compare them in producing a particular
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part of a vehicle (Tharumarajah and Koltum, 2007), and to compare them by changing the
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percent ratio of the substitution (Suzuki et al., 2005). The approach in this study is unique in a
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sense that
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compared to accurately assess GHG impact change by material itself. No other factors are
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introduced. According to Kim and Wallington (2013), the use phase accounts for 63-92% of the
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life cycle energy consumption, material production 8-12%, manufacturing and assembly 1-4%,
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and the rest <4%. Therefore, the comparison between GHG increase by material substitution,
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which corresponds to material production and GHG saving in the use phase can provide pretty
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accurate predictions regarding GHG impacts for lightweighting as those two phases occupy the
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majority of the entire life cycle of vehicles. Furthermore, GHG payback miles, which are the
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distance to compensate GHG increase by material substitution by GHG savings during the use
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phase, are estimated as the result of lightweighting strategy from the past trend in fuel
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efficiencies and vehicle weights.
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GHG emissions in 1kg of steel and equivalent amounts of substituted materials are
The objective of this study is to answer these two questions discussed above based on a historical analysis and to discuss future pathways for material substitution.
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4. A historical analysis of vehicle weight, fuel efficiency, and GHG emissions
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4.1. Trends in weight and fuel efficiency
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Figure 1 shows the trends in vehicle weight and fuel efficiency improvement in
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American light-duty vehicles (Dai et al., 2013) as well as Japanese vehicles (AIRIA, 2015) for
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the past thirty years. There are two noticeable phenomena.
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One is the weight reduction in American cars from 1970 to 1980. The weight of
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American cars decreased and the fuel efficiency improved rapidly. During this period, the
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gasoline price was very high due to “Oil Shock” and the fuel efficiency were improved by the
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higher fuel efficiency standards set by Congress. Those resulted in an increasing share of
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smaller cars(lighter cars) in the US market. Therefore, the improved fuel efficiency during this
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time period was a mixture of the higher fuel efficiency standards, higher gasoline prices, and
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low weight cars. From 1980, with the stability of gasoline price, the car weight started
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increasing (eia, 2012).
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The other is the fuel efficiency improvements of Japanese cars from 2010 (Car Watch,
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2015). The reason for this is that Japanese government subsidized some amount of money in
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buying clean energy vehicles such as hybrid, clean diesel engine, and electric cars from 2009.
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With this policy, those clean energy vehicles started increasing the share and reached 36% in
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2017 (Nev, 2018). Looking at longer terms, despite a vast effort to improve materials and
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increase fuel efficiency over the past thirty years, average vehicle weight has not decreased in
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the US (Dai et al., 2013) and has increased in Japan (AIRIA, 2015) (Fig. 1). Efforts to reduce
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total vehicle weight frequently result in no net gain to total vehicle mass and often only reduce
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the amount of mass increase that would have otherwise occurred. In fact, the production of
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vehicles that satisfy consumer wants and needs, regulatory requirements, and environmental and
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societal needs, without causing inflationary growth in vehicle mass, is continually regarded as
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one of the toughest challenges facing the automotive industry (Glennan, 2007).
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Despite these increasing customer demands and other requirements, fuel efficiency has
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increased (see Fig. 1). Considering the fact that weight has not decreased, the increase in fuel
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efficiency is due to other reasons, such as improvements in powertrain and not by
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lightweighting.
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Figure 1
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Figure 2 shows the weight trends of specific vehicles of Honda CRV and Ford F150
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(NADA GUIDE, 2018) and Toyota Corolla (Industrial Marketing Consultants, 2008), and Table
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S1 shows their specifications (See Supporting Information (S1)). There are a number of reasons
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for the weight increases shown in Fig. 2. Several are performance-related features, infotainment
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and driver support system improvements, and advancements in safety and emission reduction.
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Manufacturers have added this weight due to consumer demand for comfort and convenience
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(Baron, 2017).
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Figure 2
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4.2. Trends in material composition and GHG emissions
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The weight and GHG emissions trends in American cars for the past thirty years with
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respect to the materials used are shown in Figs. 3 (Dai et al., 2016) and GHG emissions
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associated with the materials used are shown in Figs. 4 (IDEA_v2.1.3, 2017). The weight of
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American cars has slightly increased over the past thirty years. By material, the use of high and
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medium strength steel and aluminum has increased while regular steel and iron casting has
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decreased . On the other hand, GHG emissions have increased, i.e., GHG emissions associated
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with regular steel and iron casting show decreasing trends while aluminum with higher GHG
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coefficient than regular steel and iron casting (Aluminum with 10.26 kg-CO2 eq/kg vs. Steel
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with 1.77 kg-CO2 eq/kg) (IDEA_v2.1.3, 2017) has increased.
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Figure 3
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Figure 4
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The weight and GHG emissions trends of Japanese cars are shown in Figs. 5 and 6.
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For Japanese cars, weight has increased over time. By material, cold rolled steel sheets comprise
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the largest share of weight and are decreasing while high tensile strength steel and primary
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aluminum are on the rise (Kusakawa, 2004). Similar to American cars trend, GHG emissions
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have increased with an increasing usage of aluminum with a higher GHG coefficient.
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These analyses show that while weight reduction due to material substitution has been
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used, the weight itself has not decreased. As previously mentioned, this is due to the fact that
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manufacturers have added more features for comfort, safety, and regulatory requirements to new
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vehicles. Furthermore, GHG emissions have increased over time as lighter materials, such as
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aluminum, are more GHG intensive. This is called “rebound of design”.
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Figure 5
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Figure 6
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5. Methods to assess impacts of GHG emissions in material substitution
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5.1. Analysis for GHG emission increased vs saved by material substitutions
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Material selection is an important discipline in engineering design (Mayyas et al,
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2013). Some methods emphasize selecting a single portion of a product’s life cycle (e.g. end of
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life material recovery) (Duval and MacLean, 2007) while others consider the entire life cycle of
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the product (Du et al, 2010). Works on the environmental optimization of car manufacturing
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process often analyze the input of energy and material used in the construction of the car
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(Ribeiro et al, 2008). And, since the use phase has a decisive influence on the total GHG
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emissions in the entire life cycle of the car, the assessment of the environmental impact of the
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car’s weight should consider the duration of this phase (Spielmann and Althaus, 2007).
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Here, GHG emissions increased by substituting 1kg of steel with another material and
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GHG emissions saved by material substitutions through reduction in fuel consumption by
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lightweighting are compared. IDEA_v2.1.3 database (2017) is used for GHG coefficients for the
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materials as it includes GHG emissions covering from mining to finished materials. Steel is
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used as the reference for GHG emissions estimates. High strength steel, aluminum, carbon fiber
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reinforced polymer, and magnesium are used as substitution materials. In this study, the analysis
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was confined to the assessment to global warming categories, which are particularly important
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for the automotive sector (Modaresi et al., 2014) since CO2 is one of the greatest risks
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associated with transport (White Paper, 2011).
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5.2. Calculation of GHG increased and saved by material substitutions The analysis was conducted between GHG emission increased and saved by material
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substitutions. The abbreviations used in this study are as follows: “S” “HS” “Al” “CF” and “Mg”
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represent steel, high strength steel, aluminum, carbon fiber reinforced polymer, and magnesium,
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respectively. The notation “S→Al” indicates that aluminum substitutes for steel. The weight
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substitution ratios are taken from the Steel Market Development Institute (Hall, 2012). The
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weight substitution ratio considers volume increases required to maintain the same strength as
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the substituted material. For example, the specific weight of aluminum is 2.55 g/cm3 and steel is
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7.87 g/cm3. Thus, the ratio of weight between aluminum and steel is 0.33. However, achieving
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the identical material strength as steel requires more aluminum. Therefore, its weight
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substitution ratio now becomes 0.67 (Cortes, 2012). The material properties are shown in Table
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1.
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Table 1
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The net GHG impact by substituting 1kg of steel at the production stage is given by the
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following equation: where IGHGnp, IGHGa, IGHGs, and rs represents net GHG impact [kg-CO2 eq/kg]
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by substituting 1kg of steel by another new material in at the production stage, GHG intensity of
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alternative material [kg-CO2 eq/kg], GHG intensity of steel [kg-CO2 eq/kg], and weight
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substitution ratio [-], respectively;
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IGHGnp = IGHGa × rs – IGHGs
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(1)
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5.3. Calculation of GHG payback miles
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Here, the GHG payback miles (PBMGHG) is defined as the distance in km required to
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compensate the GHG increase by material substitutions, by GHG reduction with fuel efficiency
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improvements. The longer the payback mile, the fewer improvements in fuel efficiency due to
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lightweighting.
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The fuel efficiency at the specific weight of automobile using the following six
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models (see Table 2) is calculated. Suzuki et al. (2005) estimate fuel efficiency by regression
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analysis on the catalogue data. Thus, this model reflects all the possible effects in addition to car
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weight reduction. Helms et al. (2006) considers an adjustment in powertrain. Simply et al.
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(2016) focuses on the weight reduction assuming that 75 % of fuel consumption directly relates
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to vehicle weight and the other 25% relates to other factors (BCC, 2011) and came up with the
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formula of 25% weight reduction would improve 10% fuel efficiency. Cazuc model uses weigh
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reduction alone assuming 110kg weight reduction can reduce CO2 emissions by 10g/km while
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10% improvement in rolling resistance reduces only 2g/kg. Isenstadt model focus on mass
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reduction assuming same vehicle size, safety, and performance without maintaining constant
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performance.
Brooker model used FASTsim, which includes drag coefficient, frontal area,
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mass, rolling resistance, base line acceleration. Also, it includes engine resizing.
Therefore,
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Suzuki, Helms, and Brooker models include the effects of power train reduction, rolling
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resistance, and other effects while Simply, Cazuc, and Isenstadt models use mass reduction
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effect alone. In
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mentioned.
this analysis, Brooker model was used because it included several effects
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Here, the GHG payback miles (PBMGHG) [km] are estimated by the following
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equation: where IGHGnu is net GHG reduction per kg of substituting steel and per km of distance
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in the use phase [kg-CO2 eq/kg/km];
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PBMGHG = IGHGnp /IGHGnu
(2)
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The IGHGnu is estimated by the following equation: where ef, ∆ef , and fC are the fuel
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efficiency [km/ℓ], the improvement of ef by 1kg of weight reduction [km/ℓ/kg], and conversion
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factor of GHG by burning gasoline (2.873 [kg-CO2/ ℓ]), respectively;
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=
×
−
∆
×
(3)
When PBMGHG is smaller than the lifetime distance, the material substitution makes sense to reduce lifecycle GHG emissions.
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Table 2
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6. Results
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6.1 Payback miles via the substitution of 1 kg of steel with other materials
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The GHG payback miles in six models for material substitutions are shown in Figure 7.
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While the GHG payback miles highly depend on their models, the average GHG payback miles
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of “S→HS”, “S→Al”, “S→CF”, and “S→Mg” are around 4,500 km, 172,000 km, 177,000 km,
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and 545,000 km, respectively. Usually, foregoing studies employ from 100,000 km to 200,000
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km of life-long drive distance. Therefore, the feasibility of materials to reduce GHG emissions
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changes by the model and the life-long distance. However, HS is the most promising option
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among the four materials and it would be certain that substitution of HS reduces GHG emissions
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regardless of model and assumption of life-long distance.
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On the other hand, the feasibilities of Al and CF to reduce GHG emissions depend on
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the models and life-long distance. The feasibility of Mg seems doubtful under our present
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assumptions because of the large GHG coefficient of magnesium. However, these results highly
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depend on the assumptions. Therefore, there are some possibility to change the results by
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changing the assumptions. For example, GHG intensity of materials changes by the location of
314
production because GHG intensity of electricity is drastically different among the countries and
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the regions. Or, if a large amount of renewable energy is deployed in the future, it favors the
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materials produced by consuming large amount of electricity. GHG intensity of materials can
317
decrease with employing more efficient processes. Finally, recycling of materials becomes
318
useful option in the future if they can recycle materials without degrading the materials’
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properties.
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Figure 7
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6.2. Historical trends in GHG payback miles for American and Japanese cars
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Historical trends for GHG payback miles in American and Japanese cars are shown in
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Figures 8. Based on historical car weight and fuel efficiency data, the historical GHG payback
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miles is calculated. Here, the model proposed by Brooker et al. (2013)is used because it
329
considers several effects in addition to weight reduction as previously mentioned and the result
330
by this model in Figure 7 is close to the mean of other results.
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The result shows that the GHG payback miles in all substitution cases have increased
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for both American and Japanese cars over the period of approximately 20 years. This is due to
20
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the improvement of fuel efficiencies, i.e., higher km/ℓ in both American and Japanese cars. As
334
fuel efficiency improves, the amount of GHG reduction by lightweight becomes small and
335
hence, the GHG payback miles increase. While improvements in fuel efficiency continue, the
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GHG payback miles will increase in the future. Those observations imply that unless reductions
337
in GHG emissions at a higher rate than the rate of improvement in fuel efficiency using steel are
338
achieved, competition over steel resources compared with other materials will rise significantly
339
in the future. However, it shall be noted that this analysis aims to analyze trends in GHG
340
impacts due to improvements in fuel efficiency and, therefore, GHG coefficients were fixed
341
throughout the analysis period.
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Figure 8
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7. Conclusions
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The conclusions of this paper can be summarized as the following three points.
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Firstly, while manufacturers have increasingly used lightweight materials, vehicle
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weight has increased due to “rebound of design” to add features as vehicle generations advance.
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Moreover, GHG emissions of lightweight materials are much more environmentally intensive.
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Thus, substitutions using lightweight materials have not decreased vehicle weight and their
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GHG emissions.
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Secondly, the most effective material substitution is from steel to high strength steel
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under the present conditions. The feasibility of material substitution to reduce GHG emissions
357
highly depends on the life-long drive distance. When it is extended to 200,000km, most of
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models support aluminum and CFRP as the effective substitutions. This case can be true in the
359
countries with long life-long distance such as the US.
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Thirdly, the GHG payback miles have increased and will continue to increase because
361
of the improvement of fuel efficiency. It means that the competition over steel resources
362
compared with other materials will increase in the future. To reverse the result, it is necessary to
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reduce GHG intensities of materials at higher rates than that of improvement of fuel efficiency.
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Acknowledgement: We express gratitude to Tsukuba-city, which partially supported this research.
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29
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500
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510
511 512
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513
Figure captions:
514
Figure 1. Weight and fuel efficiency of American and Japanese vehicles over the past 30 years.
515
Figure 2. Historical increases in the weight of specific vehicles.
516
Figure 3. Trends in the material composition of American cars.
517
Figure 4. Trends in GHG emissions based on materials in American cars.
518
Figure 5. Trends in material compositions of Japanese cars.
519
Figure 6. Trends in GHG emissions based on materials used in Japanese cars.
520
Figure 7. GHG payback miles based on the 6 models listed in Table 2.
521
Figure 8. GHG payback miles in American and Japanese cars based on material substitutions.
522
31
Table 1. Material properties.
523
Physical property Material
Model Density Number (g/cm3)
Tensile Yield Strength Strength (Mpa) (Mpa)
Steel
SM400
7.87
400
235
High Strength Steel
HT690
7.87
690
590
Aluminium
A1050
2.70
130
125
Magnesium
AM60
1.80
240
130
CFRP
ZC-100
1.60
1100
900
524
GHG intensity Reference The Japan Iron and Steel Federation The Japan Iron and Steel Federation TOYO SUCCESS Japan Steel Works, LTD Tip COMPOSITE
Value [kg-CO2eq/kg]
Material Substitution ratio
Reference
1.77
Reference
1
2.50 10.26
Value [-]
0.75 IDEA_v2.1.3 (2017)
Cortes (2012) 0.67
52.39
0.5
23.33
0.45
525
Table 2. The six models used in this study.
526
1 2
100 kg of weight reduction yields 0.35 ℓ /100km improvement
3
based on testing and simulation 25% of weight reduction yields 10% fuel efficiency improvement
4
110 kg of weight reduction yields 10 g CO2/km improvement
5 6
527
Model FE=1/(0.00006 x Weight+0.0174) km/ℓ based on empirical data
10% of weight reduction yields 5.1% reduction in fuel consumption bases on studies and simulation 10% of weight reduction yields 6.3% reduction in fuel consumption based on simulation
32
Reference Suzuki et al., (2005) Helms et al., (2006) Simply et al., (2016) Cazuc, (2016) Isenstadt et al., (2016) Brooker et al., (2015)
Table 1. Table 1. Material properties.
Physical property Material
Model
Density 3
Number
(g/cm )
Tensile
Yield
Strength Strength (Mpa)
GHG intensity
Reference
(Mpa)
Value [kg-CO2eq/kg]
Reference
Material Substitution ratio Value [-]
Reference
The Japan Steel
SM400
7.87
400
235
Iron and Steel
1.77
1
2.50
0.75
Federation High Strength Steel
The Japan HT690
7.87
690
590
Aluminium
A1050
2.70
130
125
Magnesium
AM60
1.80
240
130
CFRP
ZC-100
1.60
1100
900
Iron and Steel Federation
IDEA_v2.1.3
TOYO
(2017)
SUCCESS Japan Steel Works, LTD Tip COMPOSITE
10.26
Cortes (2012) 0.67
52.39
0.5
23.33
0.45
Table 2. The six models used in this study. Model
Reference
1
FE=1/(0.00006 x Weight+0.0174) km/ℓ based on empirical data
Suzuki et al., (2005)
2
100 kg of weight reduction yields 0.35 ℓ/100km improvement
Helms et al., (2006)
based on testing and simulation 3
25% of weight reduction yields 10% fuel efficiency improvement
Simply et al., (2016)
4
110 kg of weight reduction yields 10 g CO2/km improvement
Cazuc, (2016)
5
10% of weight reduction yields 5.1% reduction in fuel consumption bases on
Isenstadt et al., (2016)
studies and simulation 6
10% of weight reduction yields 6.3% reduction in fuel consumption based on simulation
Brooker et al., (2013)
Declaration of interests ☒ The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. ☐The authors declare the following financial interests/personal relationships which may be considered as potential competing interests:
S0959-6526(19)34675-X
DOI:
https://doi.org/10.1016/j.jclepro.2019.119805
Reference:
JCLP 119805
To appear in:
Journal of Cleaner Production
Received Date: 3 July 2019 Revised Date:
17 December 2019
Accepted Date: 18 December 2019
Please cite this article as: Kawajiri K, Kobayashi M, Sakamoto K, Lightweight materials equal lightweight greenhouse gas emissions?: A historical analysis of greenhouse gases of vehicle material substitution, Journal of Cleaner Production (2020), doi: https://doi.org/10.1016/j.jclepro.2019.119805. This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. 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. © 2019 Published by Elsevier Ltd.
Lightweight materials equal lightweight greenhouse gas emissions?: A historical analysis of greenhouse gases of vehicle material substitution
Kotaro Kawajiri (Corresponding) National Institute of Advanced Industrial Science and Technology 1-1-1 Higashi, Tsukuba, Ibaraki, 305-8505, Japan Email: [email protected] Tel: (81)-29-861-8089
Michio Kobayashi National Institute of Advanced Industrial Science and Technology 1-1-1 Higashi, Tsukuba, Ibaraki, 305-8505, Japan
Kaito Sakamoto National Institute of Advanced Industrial Science and Technology 1-1-1 Higashi, Tsukuba, Ibaraki, 305-8505, Japan
1
Highlight:
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Greenhouse gas impacts by material substitution of an automobile are investigated.
3
Weight of automobile has increased even with light materials by rebound of design.
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Embodied GHGs of automobiles have increased with increasing low-density materials.
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Substitution from steel to high tensile steel is a promising option to reduce GHGs.
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Competition over steel will become severer for lightweight but GHG intensive materials.
7
1
Abstract 8
The impacts of greenhouse gases (GHG) to vehicles through improvements in fuel
9
efficiency via material substitutions and their historical trends were analyzed to assess if
10
lightweighting actually provides its expected benefits. Data for the weight and fuel efficiency of
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American and Japanese cars over the past 30 years was used for trend analysis. Also, the
12
impacts of GHG in substituting steel for high strength steel, aluminum, carbon fiber reinforced
13
polymer, and magnesium were analyzed. This study shows that while the amount of low-density
14
materials in a vehicle has increased, the weight itself has increased because of the “rebound of
15
design” reflecting the consumer demands. In lightweighting strategy, the material substitution of
16
steel for high strength steel is the most promising option to reduce GHG emissions. Based on
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recent historical trends, this analysis shows that the GHG payback miles have increased and will
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continue to increase unless the reduction in GHG emissions occur at higher rates than that of
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fuel efficiency improvement from steel-based vehicles. This suggests that the competition over
20
steel will become severer in the future for other materials with low densities. To reverse the
21
result, it is necessary to reduce GHG intensities of materials at higher rates than that of
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improvement of fuel efficiency.
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Key words: automobile, GHG impact, material substitution, historical analysis, lifecycle
25
analysis 2
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3
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1. Introduction:
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Reducing greenhouse gas (GHG) emissions in the transportation industry is an
29
increasing priority. According to the International Organization of Motor Vehicle Manufacturers
30
(OICA), road transport is responsible for approximately 16% of total global carbon dioxide
31
(CO2) emissions (OICA, 2015). The automotive industry has a positive impact on daily life but
32
concerns over the negative environmental impact of CO2 emissions have intensified due to the
33
growing number of vehicle (Orsato and Wells, 2007).
34
market is expected to produce over 100 million new vehicles per year (Pervaiz, 2015). To
35
reduce vehicle GHG emissions, Automotive OEMs (Original Equipment Manufacturers) are
36
now required to comply with governmental goals to improve fuel efficiency. In the U.S.A.,
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Corporate Average Fuel Economy (CAFE) requirements will rise to 54.5 miles per gallon (mpg)
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by 2025 from 37.8 mpg in 2016 (U.S. EPA, 2010). The European Union (EU) has imposed strict
39
CO2 limits, 95 g CO2/km(REGULATION (EC), 2009), which have a direct relation with fuel
40
efficiency.
By the year 2020, the automotive
41
There are number of approaches that manufacturers can use to achieve fuel efficiency
42
and comply with CO2 targets, such as reducing aerodynamic drag, driveline, transmission loss,
43
tire rolling resistance, electrical plastics, and weight (Simply and Haywood, 2016). Among
44
those options, lightweight automotive designs that reduce vehicle weight is currently considered
4
45
one of the most important solutions to improve fuel economy and reduce harmful emissions
46
(Cui et al., 2011). In recent years, this concept, known as lightweighting, has become a major
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research theme in the transport industry; the main motivations are the anticipated fuel savings
48
and the ability to comply with stricter environmental legislation in various jurisdictions, such as
49
Europe, North America, and Asia (Pervaiz et al., 2016). As previous studies have discussed,
50
material substitution appears a promising option for lightweighting (Simply and Haywood,
51
2016).
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53
54
55
2. Past studies on lightweighting and improvements in fuel efficiency
56
A number of studies have discussed the relationship between weight reduction and fuel
57
efficiency improvements (Tharumarajah and Koltum, 2007). Here, some examples of these
58
studies are discussed. Pervaiz et al. (2016) suggested that compliance with the CO2 emission
59
targets set for Europe in 2020, i.e., 95 g CO2/km, requires a 200–300 kg reduction in vehicle
60
weight. A 2002 National Academy of Sciences (NAS) study estimated that each 10% reduction
61
in mass (up to a 20% maximum) results in a 5.1% reduction in fuel consumption, which does
62
not include engine downsizing or other powertrain changes that maintain constant performance
5
63
levels (Isenstadt et al., 2016). Modeling work, sponsored by the Department of Energy at the
64
National Renewable Energy Laboratory (NREL), also used a detailed model to understand
65
vehicle efficiency and predicted a 6.9% improvement in fuel efficiency for a 10% reduction in
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weight with engine size adjustments. A model that combines curb weight and fuel consumption
67
data with a technique to normalize vehicle performance indicates that a 10% reduction in
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vehicle weight yields a 5.6% reduction in fuel consumption for passenger cars (Cheah, 2016). In
69
these analyses, the main conclusion is that weight reduction will improve fuel efficiency.
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However, an argument exists stating that weight reduction alone does not improve fuel
71
efficiency (Cheah, 2016). Therefore, attempts to understand if there is historical truth to the
72
concept of lightweighting become necessary.
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Although the use of new types of lightweight materials with improved fuel efficiency
74
can reduce fuel consumption and tailpipe emissions during the driving stage, those lightweight
75
materials may also consume more energy and produce more environmental emissions during
76
other life phases compared with traditional steel materials (Liu et al., 2012). A lightweight
77
design could lead to higher environmental impacts over the lifespan of a vehicle compared with
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traditional designs with respect to the lifecycle (Dubreuil et al., 2010). Current fuel economy
79
and tailpipe emission standards and regulations ignore the environmental performance of other
80
vehicle life phases such as the production and processing of lightweight materials (Liu and
6
81
Müller, 2012) and do not ensure overall GHG emissions in the lifecycle of a vehicle (Danilecki
82
et al., 2017). Therefore, understanding the net benefits of lightweighting is required since the
83
production of lightweight materials (e.g., aluminum, magnesium, and carbon composites) is
84
generally more energy intensive than conventional materials, such as steel and steel alloys (Kim
85
and Wallington, 2013). However, conclusions based on lifecycle assessments (LCAs) of the
86
benefits of vehicle lightweighting are often inconsistent due to the use of incongruous modeling
87
methods and parameters (Raugei et al., 2015). LCA practitioners face the challenge of
88
estimating fuel consumption during lightweight vehicle operation, i.e., the most energy
89
consuming stage of a vehicle’s lifecycle (Kim and Wallington, 2013). Therefore, understanding
90
how the amount of weight reduction correlates with the magnitude of improvement in fuel
91
efficiency are crucial steps.
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93
94
95
3. Goals and scope of this study In this analysis, two important questions in applying the lightweighting concept are addressed.
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The first is whether past material substitution actually yields lightweight vehicles.
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Whitefoot et al. (2012) mentioned that lightweighting is possible by producing smaller vehicles.
98
However automotive manufacturers could instead reduce weight through material substitution
7
99
coupled with vehicle component redesign all while maintaining current vehicle size. Cheah
100
(2010) pointed out that increases in vehicle weight continue to occur in spite of the vast effort
101
placed on material improvement in the industrial and academic sectors. In order to understand
102
what had happened in the past, the historical trend of vehicle weight, material compositions and
103
GHG emissions of American and Japanese cars for the past thirty years are analyzed. With this
104
fact base analysis,
the first question is answered.
105
The second question relates to the benefits of material substitution. Material
106
substitution involves the use of aluminum, high strength steel, magnesium, plastic, or polymer
107
composites as alternatives to cast iron and steel (Bandivadekar et al., 2008). However, from a
108
lifecycle perspective, choosing the most appropriate lightweight concepts and materials is
109
crucial to avoid shifts in environmental burdens (Warsen and Krinke, 2012). And, a range of
110
lightweighting strategies are currently being considered and tested by a number of car
111
manufacturers in Europe and elsewhere such as Audi (Audi, 2017), BMW (BMW, 2016), Ford
112
(Ford, 2014), and JLR (JLR, 2018). For the second question, life-cycle analysis on GHG
113
emissions when 1kg of steel is substituted by other materials is performed. Then,
114
increase by material substitution and GHG savings by fuel efficiency improvement achieved by
115
lightweighting during the use phase are compared. There are several articles performing the
116
analysis of net GHG increase/decrease by comparing GHG emissions increase and savings by
8
GHG
117
material substitution. Some examples are to compare the net GHG emissions in several
118
generation of vehicle models (Danilecki et at., 2017), to compare them in producing a particular
119
part of a vehicle (Tharumarajah and Koltum, 2007), and to compare them by changing the
120
percent ratio of the substitution (Suzuki et al., 2005). The approach in this study is unique in a
121
sense that
122
compared to accurately assess GHG impact change by material itself. No other factors are
123
introduced. According to Kim and Wallington (2013), the use phase accounts for 63-92% of the
124
life cycle energy consumption, material production 8-12%, manufacturing and assembly 1-4%,
125
and the rest <4%. Therefore, the comparison between GHG increase by material substitution,
126
which corresponds to material production and GHG saving in the use phase can provide pretty
127
accurate predictions regarding GHG impacts for lightweighting as those two phases occupy the
128
majority of the entire life cycle of vehicles. Furthermore, GHG payback miles, which are the
129
distance to compensate GHG increase by material substitution by GHG savings during the use
130
phase, are estimated as the result of lightweighting strategy from the past trend in fuel
131
efficiencies and vehicle weights.
132
133
GHG emissions in 1kg of steel and equivalent amounts of substituted materials are
The objective of this study is to answer these two questions discussed above based on a historical analysis and to discuss future pathways for material substitution.
134
9
135
4. A historical analysis of vehicle weight, fuel efficiency, and GHG emissions
136
4.1. Trends in weight and fuel efficiency
137
Figure 1 shows the trends in vehicle weight and fuel efficiency improvement in
138
American light-duty vehicles (Dai et al., 2013) as well as Japanese vehicles (AIRIA, 2015) for
139
the past thirty years. There are two noticeable phenomena.
140
One is the weight reduction in American cars from 1970 to 1980. The weight of
141
American cars decreased and the fuel efficiency improved rapidly. During this period, the
142
gasoline price was very high due to “Oil Shock” and the fuel efficiency were improved by the
143
higher fuel efficiency standards set by Congress. Those resulted in an increasing share of
144
smaller cars(lighter cars) in the US market. Therefore, the improved fuel efficiency during this
145
time period was a mixture of the higher fuel efficiency standards, higher gasoline prices, and
146
low weight cars. From 1980, with the stability of gasoline price, the car weight started
147
increasing (eia, 2012).
148
The other is the fuel efficiency improvements of Japanese cars from 2010 (Car Watch,
149
2015). The reason for this is that Japanese government subsidized some amount of money in
150
buying clean energy vehicles such as hybrid, clean diesel engine, and electric cars from 2009.
151
With this policy, those clean energy vehicles started increasing the share and reached 36% in
152
2017 (Nev, 2018). Looking at longer terms, despite a vast effort to improve materials and
10
153
increase fuel efficiency over the past thirty years, average vehicle weight has not decreased in
154
the US (Dai et al., 2013) and has increased in Japan (AIRIA, 2015) (Fig. 1). Efforts to reduce
155
total vehicle weight frequently result in no net gain to total vehicle mass and often only reduce
156
the amount of mass increase that would have otherwise occurred. In fact, the production of
157
vehicles that satisfy consumer wants and needs, regulatory requirements, and environmental and
158
societal needs, without causing inflationary growth in vehicle mass, is continually regarded as
159
one of the toughest challenges facing the automotive industry (Glennan, 2007).
160
Despite these increasing customer demands and other requirements, fuel efficiency has
161
increased (see Fig. 1). Considering the fact that weight has not decreased, the increase in fuel
162
efficiency is due to other reasons, such as improvements in powertrain and not by
163
lightweighting.
164
165
----------------------------------------------------------
166
Figure 1
167
----------------------------------------------------------
168
169
Figure 2 shows the weight trends of specific vehicles of Honda CRV and Ford F150
170
(NADA GUIDE, 2018) and Toyota Corolla (Industrial Marketing Consultants, 2008), and Table
11
171
S1 shows their specifications (See Supporting Information (S1)). There are a number of reasons
172
for the weight increases shown in Fig. 2. Several are performance-related features, infotainment
173
and driver support system improvements, and advancements in safety and emission reduction.
174
Manufacturers have added this weight due to consumer demand for comfort and convenience
175
(Baron, 2017).
176
177
178
----------------------------------------------------------
179
Figure 2
180
----------------------------------------------------------
181
182
4.2. Trends in material composition and GHG emissions
183
The weight and GHG emissions trends in American cars for the past thirty years with
184
respect to the materials used are shown in Figs. 3 (Dai et al., 2016) and GHG emissions
185
associated with the materials used are shown in Figs. 4 (IDEA_v2.1.3, 2017). The weight of
186
American cars has slightly increased over the past thirty years. By material, the use of high and
187
medium strength steel and aluminum has increased while regular steel and iron casting has
188
decreased . On the other hand, GHG emissions have increased, i.e., GHG emissions associated
12
189
with regular steel and iron casting show decreasing trends while aluminum with higher GHG
190
coefficient than regular steel and iron casting (Aluminum with 10.26 kg-CO2 eq/kg vs. Steel
191
with 1.77 kg-CO2 eq/kg) (IDEA_v2.1.3, 2017) has increased.
192
193
----------------------------------------------------------
194
Figure 3
195
----------------------------------------------------------
196
----------------------------------------------------------
197
Figure 4
198
----------------------------------------------------------
199
200
The weight and GHG emissions trends of Japanese cars are shown in Figs. 5 and 6.
201
For Japanese cars, weight has increased over time. By material, cold rolled steel sheets comprise
202
the largest share of weight and are decreasing while high tensile strength steel and primary
203
aluminum are on the rise (Kusakawa, 2004). Similar to American cars trend, GHG emissions
204
have increased with an increasing usage of aluminum with a higher GHG coefficient.
205
These analyses show that while weight reduction due to material substitution has been
206
used, the weight itself has not decreased. As previously mentioned, this is due to the fact that
13
207
manufacturers have added more features for comfort, safety, and regulatory requirements to new
208
vehicles. Furthermore, GHG emissions have increased over time as lighter materials, such as
209
aluminum, are more GHG intensive. This is called “rebound of design”.
210
211
----------------------------------------------------------
212
Figure 5
213
----------------------------------------------------------
214
----------------------------------------------------------
215
Figure 6
216
----------------------------------------------------------
217
218
5. Methods to assess impacts of GHG emissions in material substitution
219
5.1. Analysis for GHG emission increased vs saved by material substitutions
220
Material selection is an important discipline in engineering design (Mayyas et al,
221
2013). Some methods emphasize selecting a single portion of a product’s life cycle (e.g. end of
222
life material recovery) (Duval and MacLean, 2007) while others consider the entire life cycle of
223
the product (Du et al, 2010). Works on the environmental optimization of car manufacturing
224
process often analyze the input of energy and material used in the construction of the car
14
225
(Ribeiro et al, 2008). And, since the use phase has a decisive influence on the total GHG
226
emissions in the entire life cycle of the car, the assessment of the environmental impact of the
227
car’s weight should consider the duration of this phase (Spielmann and Althaus, 2007).
228
Here, GHG emissions increased by substituting 1kg of steel with another material and
229
GHG emissions saved by material substitutions through reduction in fuel consumption by
230
lightweighting are compared. IDEA_v2.1.3 database (2017) is used for GHG coefficients for the
231
materials as it includes GHG emissions covering from mining to finished materials. Steel is
232
used as the reference for GHG emissions estimates. High strength steel, aluminum, carbon fiber
233
reinforced polymer, and magnesium are used as substitution materials. In this study, the analysis
234
was confined to the assessment to global warming categories, which are particularly important
235
for the automotive sector (Modaresi et al., 2014) since CO2 is one of the greatest risks
236
associated with transport (White Paper, 2011).
237
238
239
5.2. Calculation of GHG increased and saved by material substitutions The analysis was conducted between GHG emission increased and saved by material
240
substitutions. The abbreviations used in this study are as follows: “S” “HS” “Al” “CF” and “Mg”
241
represent steel, high strength steel, aluminum, carbon fiber reinforced polymer, and magnesium,
242
respectively. The notation “S→Al” indicates that aluminum substitutes for steel. The weight
15
243
substitution ratios are taken from the Steel Market Development Institute (Hall, 2012). The
244
weight substitution ratio considers volume increases required to maintain the same strength as
245
the substituted material. For example, the specific weight of aluminum is 2.55 g/cm3 and steel is
246
7.87 g/cm3. Thus, the ratio of weight between aluminum and steel is 0.33. However, achieving
247
the identical material strength as steel requires more aluminum. Therefore, its weight
248
substitution ratio now becomes 0.67 (Cortes, 2012). The material properties are shown in Table
249
1.
250
251
----------------------------------------------------------
252
Table 1
253
----------------------------------------------------------
254
255
The net GHG impact by substituting 1kg of steel at the production stage is given by the
256
following equation: where IGHGnp, IGHGa, IGHGs, and rs represents net GHG impact [kg-CO2 eq/kg]
257
by substituting 1kg of steel by another new material in at the production stage, GHG intensity of
258
alternative material [kg-CO2 eq/kg], GHG intensity of steel [kg-CO2 eq/kg], and weight
259
substitution ratio [-], respectively;
260
16
IGHGnp = IGHGa × rs – IGHGs
261
(1)
262
263
5.3. Calculation of GHG payback miles
264
Here, the GHG payback miles (PBMGHG) is defined as the distance in km required to
265
compensate the GHG increase by material substitutions, by GHG reduction with fuel efficiency
266
improvements. The longer the payback mile, the fewer improvements in fuel efficiency due to
267
lightweighting.
268
The fuel efficiency at the specific weight of automobile using the following six
269
models (see Table 2) is calculated. Suzuki et al. (2005) estimate fuel efficiency by regression
270
analysis on the catalogue data. Thus, this model reflects all the possible effects in addition to car
271
weight reduction. Helms et al. (2006) considers an adjustment in powertrain. Simply et al.
272
(2016) focuses on the weight reduction assuming that 75 % of fuel consumption directly relates
273
to vehicle weight and the other 25% relates to other factors (BCC, 2011) and came up with the
274
formula of 25% weight reduction would improve 10% fuel efficiency. Cazuc model uses weigh
275
reduction alone assuming 110kg weight reduction can reduce CO2 emissions by 10g/km while
276
10% improvement in rolling resistance reduces only 2g/kg. Isenstadt model focus on mass
277
reduction assuming same vehicle size, safety, and performance without maintaining constant
278
performance.
Brooker model used FASTsim, which includes drag coefficient, frontal area,
17
279
mass, rolling resistance, base line acceleration. Also, it includes engine resizing.
Therefore,
280
Suzuki, Helms, and Brooker models include the effects of power train reduction, rolling
281
resistance, and other effects while Simply, Cazuc, and Isenstadt models use mass reduction
282
effect alone. In
283
mentioned.
this analysis, Brooker model was used because it included several effects
284
Here, the GHG payback miles (PBMGHG) [km] are estimated by the following
285
equation: where IGHGnu is net GHG reduction per kg of substituting steel and per km of distance
286
in the use phase [kg-CO2 eq/kg/km];
287
PBMGHG = IGHGnp /IGHGnu
(2)
288
The IGHGnu is estimated by the following equation: where ef, ∆ef , and fC are the fuel
289
efficiency [km/ℓ], the improvement of ef by 1kg of weight reduction [km/ℓ/kg], and conversion
290
factor of GHG by burning gasoline (2.873 [kg-CO2/ ℓ]), respectively;
291
292
293
=
×
−
∆
×
(3)
When PBMGHG is smaller than the lifetime distance, the material substitution makes sense to reduce lifecycle GHG emissions.
294
295
----------------------------------------------------------
296
Table 2
18
----------------------------------------------------------
297
298
299
6. Results
300
6.1 Payback miles via the substitution of 1 kg of steel with other materials
301
The GHG payback miles in six models for material substitutions are shown in Figure 7.
302
While the GHG payback miles highly depend on their models, the average GHG payback miles
303
of “S→HS”, “S→Al”, “S→CF”, and “S→Mg” are around 4,500 km, 172,000 km, 177,000 km,
304
and 545,000 km, respectively. Usually, foregoing studies employ from 100,000 km to 200,000
305
km of life-long drive distance. Therefore, the feasibility of materials to reduce GHG emissions
306
changes by the model and the life-long distance. However, HS is the most promising option
307
among the four materials and it would be certain that substitution of HS reduces GHG emissions
308
regardless of model and assumption of life-long distance.
309
On the other hand, the feasibilities of Al and CF to reduce GHG emissions depend on
310
the models and life-long distance. The feasibility of Mg seems doubtful under our present
311
assumptions because of the large GHG coefficient of magnesium. However, these results highly
312
depend on the assumptions. Therefore, there are some possibility to change the results by
313
changing the assumptions. For example, GHG intensity of materials changes by the location of
314
production because GHG intensity of electricity is drastically different among the countries and
19
315
the regions. Or, if a large amount of renewable energy is deployed in the future, it favors the
316
materials produced by consuming large amount of electricity. GHG intensity of materials can
317
decrease with employing more efficient processes. Finally, recycling of materials becomes
318
useful option in the future if they can recycle materials without degrading the materials’
319
properties.
320
321
----------------------------------------------------------
322
Figure 7
323
----------------------------------------------------------
324
325
6.2. Historical trends in GHG payback miles for American and Japanese cars
326
Historical trends for GHG payback miles in American and Japanese cars are shown in
327
Figures 8. Based on historical car weight and fuel efficiency data, the historical GHG payback
328
miles is calculated. Here, the model proposed by Brooker et al. (2013)is used because it
329
considers several effects in addition to weight reduction as previously mentioned and the result
330
by this model in Figure 7 is close to the mean of other results.
331
The result shows that the GHG payback miles in all substitution cases have increased
332
for both American and Japanese cars over the period of approximately 20 years. This is due to
20
333
the improvement of fuel efficiencies, i.e., higher km/ℓ in both American and Japanese cars. As
334
fuel efficiency improves, the amount of GHG reduction by lightweight becomes small and
335
hence, the GHG payback miles increase. While improvements in fuel efficiency continue, the
336
GHG payback miles will increase in the future. Those observations imply that unless reductions
337
in GHG emissions at a higher rate than the rate of improvement in fuel efficiency using steel are
338
achieved, competition over steel resources compared with other materials will rise significantly
339
in the future. However, it shall be noted that this analysis aims to analyze trends in GHG
340
impacts due to improvements in fuel efficiency and, therefore, GHG coefficients were fixed
341
throughout the analysis period.
342
343
344
----------------------------------------------------------
345
Figure 8
346
----------------------------------------------------------
347
348
7. Conclusions
349
The conclusions of this paper can be summarized as the following three points.
350
Firstly, while manufacturers have increasingly used lightweight materials, vehicle
21
351
weight has increased due to “rebound of design” to add features as vehicle generations advance.
352
Moreover, GHG emissions of lightweight materials are much more environmentally intensive.
353
Thus, substitutions using lightweight materials have not decreased vehicle weight and their
354
GHG emissions.
355
Secondly, the most effective material substitution is from steel to high strength steel
356
under the present conditions. The feasibility of material substitution to reduce GHG emissions
357
highly depends on the life-long drive distance. When it is extended to 200,000km, most of
358
models support aluminum and CFRP as the effective substitutions. This case can be true in the
359
countries with long life-long distance such as the US.
360
Thirdly, the GHG payback miles have increased and will continue to increase because
361
of the improvement of fuel efficiency. It means that the competition over steel resources
362
compared with other materials will increase in the future. To reverse the result, it is necessary to
363
reduce GHG intensities of materials at higher rates than that of improvement of fuel efficiency.
364
365
366
Acknowledgement: We express gratitude to Tsukuba-city, which partially supported this research.
367 368
22
369
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510
511 512
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513
Figure captions:
514
Figure 1. Weight and fuel efficiency of American and Japanese vehicles over the past 30 years.
515
Figure 2. Historical increases in the weight of specific vehicles.
516
Figure 3. Trends in the material composition of American cars.
517
Figure 4. Trends in GHG emissions based on materials in American cars.
518
Figure 5. Trends in material compositions of Japanese cars.
519
Figure 6. Trends in GHG emissions based on materials used in Japanese cars.
520
Figure 7. GHG payback miles based on the 6 models listed in Table 2.
521
Figure 8. GHG payback miles in American and Japanese cars based on material substitutions.
522
31
Table 1. Material properties.
523
Physical property Material
Model Density Number (g/cm3)
Tensile Yield Strength Strength (Mpa) (Mpa)
Steel
SM400
7.87
400
235
High Strength Steel
HT690
7.87
690
590
Aluminium
A1050
2.70
130
125
Magnesium
AM60
1.80
240
130
CFRP
ZC-100
1.60
1100
900
524
GHG intensity Reference The Japan Iron and Steel Federation The Japan Iron and Steel Federation TOYO SUCCESS Japan Steel Works, LTD Tip COMPOSITE
Value [kg-CO2eq/kg]
Material Substitution ratio
Reference
1.77
Reference
1
2.50 10.26
Value [-]
0.75 IDEA_v2.1.3 (2017)
Cortes (2012) 0.67
52.39
0.5
23.33
0.45
525
Table 2. The six models used in this study.
526
1 2
100 kg of weight reduction yields 0.35 ℓ /100km improvement
3
based on testing and simulation 25% of weight reduction yields 10% fuel efficiency improvement
4
110 kg of weight reduction yields 10 g CO2/km improvement
5 6
527
Model FE=1/(0.00006 x Weight+0.0174) km/ℓ based on empirical data
10% of weight reduction yields 5.1% reduction in fuel consumption bases on studies and simulation 10% of weight reduction yields 6.3% reduction in fuel consumption based on simulation
32
Reference Suzuki et al., (2005) Helms et al., (2006) Simply et al., (2016) Cazuc, (2016) Isenstadt et al., (2016) Brooker et al., (2015)
Table 1. Table 1. Material properties.
Physical property Material
Model
Density 3
Number
(g/cm )
Tensile
Yield
Strength Strength (Mpa)
GHG intensity
Reference
(Mpa)
Value [kg-CO2eq/kg]
Reference
Material Substitution ratio Value [-]
Reference
The Japan Steel
SM400
7.87
400
235
Iron and Steel
1.77
1
2.50
0.75
Federation High Strength Steel
The Japan HT690
7.87
690
590
Aluminium
A1050
2.70
130
125
Magnesium
AM60
1.80
240
130
CFRP
ZC-100
1.60
1100
900
Iron and Steel Federation
IDEA_v2.1.3
TOYO
(2017)
SUCCESS Japan Steel Works, LTD Tip COMPOSITE
10.26
Cortes (2012) 0.67
52.39
0.5
23.33
0.45
Table 2. The six models used in this study. Model
Reference
1
FE=1/(0.00006 x Weight+0.0174) km/ℓ based on empirical data
Suzuki et al., (2005)
2
100 kg of weight reduction yields 0.35 ℓ/100km improvement
Helms et al., (2006)
based on testing and simulation 3
25% of weight reduction yields 10% fuel efficiency improvement
Simply et al., (2016)
4
110 kg of weight reduction yields 10 g CO2/km improvement
Cazuc, (2016)
5
10% of weight reduction yields 5.1% reduction in fuel consumption bases on
Isenstadt et al., (2016)
studies and simulation 6
10% of weight reduction yields 6.3% reduction in fuel consumption based on simulation
Brooker et al., (2013)
Declaration of interests ☒ The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. ☐The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: