This study focused on CO 2 inventory analysis as a preliminary step for future life cycle impact assessment (LCIA) study. Therefore, in this paper, the life cycle CO 2 emissions of gasoline and diesel ICV (GE, DE), and BEV were calculated. The US, European Union (EU), Japan, China, and Australia were selected as the regions of vehicle usage, and the fuel efficiency, the electric efficiency, the CO 2 emission factor of electric power generation and the CO 2 emission for battery production in each region were applied. Also, the effects of variations in driving distance and the CO 2 emission from battery production on the total life cycle CO 2 emissions was evaluated.

Previous LCA studies for conventional internal combustion engine vehicles (ICV) [ 2 6 ] and advanced powertrain namely; battery electric vehicles (BEV) [ 2 6 ], hybrid electric vehicles (HEV) [ 3 6 ] and plug-in hybrid electric vehicles (plug-in HEV) [ 3 6 ] already exist. In these studies, the COemissions were calculated assuming that the region, the lifetime driving distance, and the COemission from the battery production were fixed at certain conditions which are summarized in Table 1 . However, it is commonly understood that the power generation mix for BEV and plug-in HEV, and a vehicle’s lifetime driving distance, vary by region. Also, LCA could be affected by the difference of fuel and electricity consumption of vehicles by region due to the difference of the driving conditions, such as vehicle speed ranges, loading weights, etc. It is noteworthy that Delogu et al. [ 7 ] conducted LCA of a diesel car considering some kinds of fuel consumption test cycle. The fact that the COemission from the battery production differs depending on the reference source cannot be overlooked [ 8 11 ]. Therefore, it is necessary to analyze the effects of those variations holistically.

A prospective unbiased measure to evaluate GHG emissions during a vehicle’s life can be a life-cycle assessment (LCA). This considers the CO 2 emissions of vehicles during its operational phase as well as the emissions generated from the fuel extraction, refining, power generation, and its end-of-life phases. LCA studies have gained more attention in recent years as a more holistic view of powertrain solutions for passenger transport with the goal of reducing CO 2 emissions.

In response to the awareness of human induced climate change in the past decades, the international policy agenda has been driven toward greenhouse gas (GHG) reduction. The transport sector, especially land based passenger transport constitutes the fastest growing source of all GHG emissions. It is recognized as a primary sector [ 1 ]. Despite the growing importance of COregulation in the passenger transport sector, the focal point of current regulations is limited only to a vehicle’s operational phase, i.e., tank-to-wheel tailpipe emissions. There is currently no regulatory consideration for the other phases of a vehicle’s life cycle.

The scope of this study excluded disposal and recycling of waste materials in the vehicle production phase, recycling of parts removed from the vehicle in the maintenance phase and recycling of the disassembled powertrain parts from the vehicles in the EOL phase. The scope of this assessment is shown as Figure 1

The entire life cycle of vehicles was considered as the scope of this study. The amounts of CO 2 emissions were calculated from phases 1 to 5.

In this study the lifetime driving distance was defined as a variable from 0 km to 200,000 km in the five regions referring to the above literature.

The LCA study for automobiles requires the lifetime driving distance of the vehicles as the functional unit. The lifetime driving distances were cited in the LCA literature for ICVs and/or BEVs such as 150,000 km [ 22 ], 160,000 km [ 23 ], 180,000 km [ 2 ] and 200,000 km [ 4 24 ] for the EU, 193,120 km [ 10 ] and 320,000 km [ 2 ] for the US, and 100,000 km [ 25 ] and 110,000 km [ 26 ] for Japan.

In order to analyze the effect of regional vehicle’s lifetime and the COemissions from battery production, the vehicle type for this study was unified to the compact class (also known as “C-segment” in Europe [ 19 ]) for both ICV (GE, DE) and BEV, which had the highest production volumes in the world. Specifications of the vehicles listed in Table 2 were referenced by the publicized information on existing vehicles sold in each region as of April 2018; whereby, fuel efficiency and electric efficiency data were officially provided by the automotive manufacturers. The difference in the fuel efficiency of the same vehicle by region could be caused by different driving conditions, as represented by vehicle speed ranges, loading weights, etc. In order to calculate the COemissions of BEV in five regions, the electric efficiency of the BEV in the EU was substituted for China and Australia because the selected model in this paper was not actually sold in these regions and their test cycles for energy efficiency were similar to those of the EU [ 20 ]. On the other hand, the COemissions of the selected DE were calculated only for the EU and Japan where they were sold. In Table 2 , the fuel and electricity efficiency value in Europe and Japan are based on the NEDC and the JC08 test cycle respectively. Currently, these test cycles are both switched to the WLTC (Worldwide Light-duty vehicle Test Cycle) which reflects real driving conditions more precisely [ 21 ], but the data of NEDC and JC08 were used in this study due to limited availability of WLTC data in the market.

The US, EU (the average of member countries), Japan, China, and Australia were selected as the regions for this study considering variations in energy situations (e.g., electricity generation mix, petroleum refinery efficiency) and vehicle driving conditions.

The amount of COemissions in the phase of a vehicle’s end-of-life (EOL) for GE were estimated; referenced from [ 34 ] whereby, the EOL treatment consisted of four processes; “Disassembly”, “Shredding and sorting vehicles”, “Transportation (trucking) of the shredder residue” and “Landfilling of shredder residue”. The target parts were body parts, interior parts and exterior parts for the GE. The same boundary used in this literature was applied to DE and BEV in this study. As a result, the amount of COemissions in the EOL phase was the same for GE, DE and BEV which is shown in Table 6

In order to maintain vehicles, some parts need to be replaced at certain intervals. In this study, COemissions from production of parts for maintenance were assessed considering maintenance intervals as shown in Table 5 . The interval for a lithium-ion battery was cited from the warranty distances for a lithium-ion battery of BEVs in the US [ 31 33 ] in which similar distances were shown in the EU and Japan. Maintenance intervals for other parts and the amount of COemissions for their production were cited from the JLCA [ 27 ].

The amount of COemissions in the phase of electric power generation for BEV was obtained with the following equation:where;

Based on the above results, the amount of COemissions in the phase of fuel production and combustion for ICV (GE and DE) was obtained by the equation below:where;

The COemission factors of the electric power generation in each region were cited from ”GaBi” [ 29 ] ; data was referenced from 2013. The system boundary for the electric power generation is from energy resource extraction to transformation of electric energy to low voltage as the grid mix.

The COemission factors of gasoline and diesel fuel combustion were cited [ 30 ] which were 2.28 kg-CO/L for gasoline and 2.62 kg-CO/L for diesel respectively and they were used in all five regions covered by the study. For both gasoline and diesel fuels, the COemission factors of fuel combustion [ 30 ] are 5 to 8 times greater than those of fuel production [ 29 ] which varies from region to region.

The COemission factors of the fuel production in each region were cited from the LCA database ”GaBi” [ 29 ] ; data was referenced from 2013. Each system boundary for gasoline and diesel fuel is from resource extraction up to service stations. The emission factors of the fuels in “GaBi” [ 29 ] are specified with the amount of COemissions by 1 kg fuel [kg-CO/kg], therefore, the density values of fuel (gasoline: 0.727 kg/L, diesel: 0.828 kg/L) [ 30 ] were used to convert [kg-CO/L] into [kg-CO/kg].

In this study, the CO 2 emissions of gasoline and diesel fuel production, combustion of these fuels and electric power generation which were required to drive GE, DE and BEV, were calculated as follows.

As they were already mentioned above, the chassis parts production and the engine parts production were calculated as COinventory but the motor, inverter and lithium-ion batteries were calculated as greenhouse gas inventory (CO-eq). In terms of the production of the motor, inverter and lithium-ion batteries, the electricity generation for manufacturing is the main source of the greenhouse gas emissions. According to the LCA database “GaBi” [ 29 ], from the electricity generation, the greenhouse gases other than CO(e.g., CH, NO) are contained only around 5 %. So CO-eq values were regarded as COvalues in this study.

(4) The COemission factor represents the amount of COemissions per unit battery capacity, which was estimated based on various works in the literature [ 8 11 ]. The criteria for selecting the literature included the following three items: (1) The boundary encompassed raw material extraction through to production of a battery system (or battery pack, which was ready to be assembled to vehicles); (2) Each detailed process of battery production was considered (e.g., cathode production, cell assembly, pack assembly); (3) The lithium-ion battery included either mainstream cathode described as lithium nickel-manganese-cobalt oxide (NMC) cathode or lithium iron phosphate (LFP) cathode types. The results of the COemission factor of battery production are shown in Table 3 . The average of the values in the literature was 177 kg-CO-eq/kWh with the lowest value (121 kg-CO-eq /kWh) and the highest value (250 kg-CO-eq /kWh). The summary of the COemissions of the vehicle production phase is shown in Table 4 . These values were regarded as COvalues in this study.

(3) The amount of COemissions of the motor and inverter production for the BEV was estimated to be 1070 kg-COand 641 kg-COcited from Hawkins et al. [ 28 ] where the material compositions and the COemission factor were quoted from the literature and the COemissions of production of these parts were calculated considering each production process. Although their results were calculated with COequivalent values (kgCO-eq), these values were regarded as COvalues in this study.

(2) The amount of COemissions from the gasoline engine and transmission production was also calculated based on JLCA [ 27 ] and assumed to be 1274 kg-CO(= 5494 kg-CO–4219 kg-CO). As the amount of COemissions from the diesel engine and transmission production was not described in JLCA [ 27 ], it was estimated based on the weight difference of 50 kg (= 1360 kg–1310 kg) between GE and DE shown in Table 2 and the weight of the gasoline engine and transmission of 241 kg cited from JLCA [ 27 ]. As a result, the amount of COemissions from the diesel engine and transmission production was estimated to be 1,539kg-CO(= 1274 kg-CO× (241 kg + 50 kg)/241 kg).

(1) Chassis parts (body, tires, interiors, etc.) of the GE, DE and BEV were assumed to be identical. The amounts of COemissions of the chassis parts production in this study were calculated based on database of the Life-Cycle Assessment Society of Japan (JLCA) [ 27 ]. According to the database, COinventory from material extraction to manufacturing of small passenger gasoline engine vehicle, whose vehicle size is similar to that in this study, was 5494 kg-COand chassis parts account for 76.8% of total vehicle weight. To supplement this, material extraction to vehicle manufacturing was also modeled and the COinventory was calculated based on database JLCA [ 27 ]. For the purposes of this study, COemissions for production of chassis parts is assumed to be proportionate to their weight as a fraction of the total vehicle weight. Therefore, COemissions for the production of chassis parts is assumed to be 4219 kg-CO(= 5494 kg-CO× 0.768) in this study.

The amounts of CO 2 emissions for the production phase were calculated by splitting them into four items such as (1) chassis, (2) engine and transmission for GE and DE, (3) inverter and motor for BEV, (4) battery for BEV as follows. In this study, the CO 2 emission for the production phase was regarded as the same for all regions.

The DIP variation in each region was caused by the differences in the set of assumptions that were used in the calculation assumptions. The details will be discussed in Section 5

The results shown in Figure 2 indicate that DIP varied by region. For example, for DIPs between GE and BEV, the U.S was the shortest followed by the EU, Japan, and China. Australia had no DIP. In the case of DE and BEV, the DIP in EU was by around 5,000 km less than that of Japan.

These results summarized that the longer the vehicle was driven during the vehicle’s lifetime distance, the more the BEVs benefited from COreduction compared to ICV (Australia is only one exception to this point). It was also worth mentioning that the amount of the COemissions of battery replacement of BEV could alter the amount COemissions of ICV to become lower than those of BEV. About the end-of-life emissions, it is hard to identify them in Figure 2 because they were very small relative to the emissions of the other phases.

Also, in this study, the battery of a BEV was assumed to be replaced once at 160,000 km. For example, in Figure 2 a for EU, the amount of COemission of DE was lower than BEV when the driving distance was less than 109,415 km (DIP) and more than 160,000 km (battery replacement mileage). One exception was seen in Figure 2 e for Australia, where ICV (GE) consistently indicated lower COemissions than BEV at any driving distance up to 200,000 km.

The first observation from the results is that vehicles which exhibit lower COemissions, i.e., ICVs or BEVs, were dependent on the driving distance. For example, as shown in Figure 2 c for the US, GE indicated lower COemissions than BEV when the driving distance was less than 60,779 km due to the high COemissions associated with battery production for BEVs, while BEV indicated lower COemissions when the driving distance was over 60,779 km.

The calculation results of total life cycle COemissions for five regions are shown in Figure 2 , e.g., (a) EU, (b) Japan, (c) US, (d) China and (e) Australia. The amounts of COemissions of GE, DE and BEV were calculated in the EU and Japan, while those for GE and BEV were calculated in the US, China, and Australia. For these assessments, the averaged value of the COemission factor of the battery production of BEV (177 kg-CO/kWh) was used as shown in Table 3 . In each figure, the point at which lines of GE or DE and BEV intersect each other indicates the driving distance which was defined as “Distance of Intersection Point (DIP)” in this study.

Ellingsen et al. cited in this study calculated the COemissions from the battery production based on the electric power consumption for the battery production, etc. provided by a battery supplier [ 11 ]. It is desirable that more reliable COemission data of battery production will become available in the future.

Peters et al. investigated some literature pertaining to battery production, including batteries for stationary systems in the same manner as this study, and calculated the averaged values. The results were, 160 kg-CO/kWh for lithium nickel-manganese-cobalt oxide (NCM)-type batteries and 161 kg-CO/kWh for lithium iron phosphate (LFP)-type batteries [ 13 ]. The difference in averaged values between Peters et al. [ 13 ] and this study was approximately 10 %. It was concluded that they analyzed differentials in the factors and concluded that the assessment assumptions were the main causes of the differences.

Variations in this CO 2 factor in past studies result from a variety of different assumptions used in the calculation of CO 2 emissions. These include battery manufacturing processes, types of battery materials (cathode, anode, electrolyte, battery pack structure, etc.), system boundaries (how many direct/indirect processes relating to manufacturing are included), and public database used for the calculation.

In Section 4.3 ., it was made clear that the COemission factor of battery production for BEVs significantly affects the results of the total life-cycle COemissions. As described in Section 3 , the COemission factor of battery production for BEVs was estimated from previous studies.

As explained above, the comparison results of CO 2 emissions between ICV and BEV differ in each region. When more electricity is generated by renewables leading to a smaller CO 2 emission factor of electricity, the amounts of the CO 2 emissions of BEV are lower than those of ICV and the DIP comes at a shorter distance. Besides CO 2 emission factor of electric power generation, the fuel efficiency of ICV and the electric efficiency of BEV also contribute to the variability between regional differences.

On the other hand, although the CO 2 emission factor of electric power generation in the US was larger than that in the EU, the DIP of the US was shorter than that of the EU. Such causes are attributed by the reason that the fuel efficiency of ICV (GE, DE) and the electric efficiency of BEV in the US were substantially worse than those in other regions.

As noted in Section 4.1 , driving distance significantly affects the results of the lifecycle COof ICV compared to BEV to the degree in which the conclusion may be reversed. Therefore, it is essential to use driving distances referenced from the averaged values of statistical data published, for instance, through governments and research institutes in order to properly assess which vehicle powertrain technology demonstrates lower COemissions in the region, ICV or BEV.

6. Conclusions

In this study, the CO 2 emissions of conventional ICV (GE, DE), and BEV were evaluated using the methodology of LCA.

From the regional vehicle’s lifetime perspective, the calculation of CO 2 emissions revealed that as the vehicle was driven longer, the lifecycle CO 2 emission of BEV became lower than that of ICV, except in Australia where ICV emission was lower than BEV until the end of life. Another observation was that regional sources of power generation (coal, contribution from renewable sources, etc.) had a great effect on the CO 2 emissions of BEV. The more the generated electricity came from renewables, the lower the CO 2 emissions of BEV were than those of ICV and the DIP comes at a shorter distance. From the viewpoint of battery production, the CO 2 emission of BEV had a wide variety which results in the lowest emission factor of battery production, which in turn lowered the CO 2 emissions of BEV compared to those of ICV while the highest factor resulted in the opposite conclusion.

This study revealed that the CO 2 emissions of ICV (GE, DE), and BEV are dependent on the regions as well as the CO 2 emissions of battery production. This study suggested that BEV is not only solution for reducing CO 2 emissions globally, but it is important for car manufacturers to introduce ICV as well as BEV to each region in consideration of electricity mixes and so on. In the meanwhile, this study included the limitations listed below.

This study focused on the regional differences of the CO 2 emission on the fuel production, electric power generation, and fuel combustion phase (i.e., vehicle use stage) but the CO 2 emission on the vehicle and parts production phase is assumed to be the same for all regions.

2 emissions because it can avoid productions of new materials or parts, but it was out of scope of this study because there are not sufficient data of recycling in each region. As the Joint Research Centre in the EU mentioned [ 35 ], the reuse and recycling of lithium-ion batteries is important to mitigate the COemissions because it can avoid productions of new materials or parts, but it was out of scope of this study because there are not sufficient data of recycling in each region.

2 emissions [ This study focused on ICV and BEV. A fuel cell electric vehicle fueled by hydrogen is also important to mitigate the COemissions [ 36 37 ] but it was out of scope of this study.

The CO 2 emissions in the use phase were calculated based on the fuel/electricity efficiency values of type approval test in each region. These values can be different from the values by real driving conditions.

The uncertainty of cited data from references were taken care of in this study, but this study did not holistically perform a sensitivity check to examine which data could change the results widely other than battery production.