Analysis on carbon emission reduction intensity of fuel cell vehicles from a life-cycle perspective

Abstract

The hydrogen fuel cell vehicle is rapidly developing in China for carbon reduction and neutrality. This paper evaluated the life-cycle cost and carbon emission of hydrogen energy via lots of field surveys, including hydrogen production and packing in chlor-alkali plants, transport by tube trailers, storage and refueling in hydrogen refueling stations (HRSs), and application for use in two different cities. It also conducted a comparative study for battery electric vehicles (BEVs) and internal combustion engine vehicles (ICEVs). The result indicates that hydrogen fuel cell vehicle (FCV) has the best environmental performance but the highest energy cost. However, a sufficient hydrogen supply can significantly reduce the carbon intensity and FCV energy cost of the current system. The carbon emission for FCV application has the potential to decrease by 73.1% in City A and 43.8% in City B. It only takes 11.0%–20.1% of the BEV emission and 8.2%–9.8% of the ICEV emission. The cost of FCV driving can be reduced by 39.1% in City A. Further improvement can be obtained with an economical and “greener” hydrogen production pathway.

Graphical abstract

Keywords

hydrogen energy / life-cycle assessment (LCA) / fuel cell vehicle / carbon emission / energy cost

1 Introduction

Today, the transportation sector plays a significant role in global carbon emissions [1]. According to the data of International Energy Agency (IEA), approximately 20% of carbon emissions come from transportation every year [2]. Vehicle electrification is considered to effectively reduce carbon emission to achieve sustainable transportation [3,4]. As a country that accounts for one-third of global carbon emissions, China contributes 12 billion tons of CO₂ emissions in 2021 [5,6]. Therefore, the Chinese government is paying substantial attention to new energy vehicles (NEVs), mainly battery electric, plug-in hybrid, and fuel cell vehicles, for energy security, carbon emission reduction, and industrial upgrading [7–9]. In 2009, China implemented a Ten Cities and Thousands of Units program to stimulate the NEV market, which planned a 1000-NEVs demonstration in ten cities, respectively. This program started an over-ten-year fiscal subsidy for NEVs in China [10]. By the end of 2022, China’s NEV ownership reached 13.1 million units, accounting for 4.1% of the total vehicles, net of scrap notes sales increased by 5.26 million units or 67.1% compared to 2021, of which, 10.45 million are battery electric vehicles (BEVs), accounting for 79.8% of the total NEVs [11]. Since 2020, China has implemented a new encouragement policy for NEVs, which is described as another Ten Cities and Thousands of Units program for fuel cell vehicles (FCVs) [12]. It introduces a new policy to replace the direct financial subsidy, named “substitute subsidies with rewards.”

China is exploring new ways to replace direct financial subsidies, such as carbon trading. In 2016, the government canvassed opinions on carbon quota regulation for NEVs [13]. However, this regulation has not been fully implemented, which might be restricted by the difficulty of vehicle emissions. China constructed the National Emissions Trading System (ETS) in 2017 [14]. On July 16, 2021, China officially launched its national carbon trading [15]. The transport sector is believed to be brought into the national carbon market in the future, especially after setting the 30/60 Targets (China is committed to hit peak emissions by 2030 and carbon neutrality by 2060) of China. For this purpose, the life-cycle economic and environmental assessment of NEVs become key performance indexes of great concern to policy-makers, greatly influencing whether to and how to promote NEV technologies [16].

In recent years, there has been an amount of comparative life-cycle analysis for BEVs, FCVs, and internal combustion engine vehicles (ICEVs) [17]. Many of these analyses were conducted using the mature model/software/database, such as GaBi (Germany), GREET (USA), SimaPro (Netherlands), Umberto (Germany), and eBalance (China) [18,19], focusing on the factors such as technology, economy, environment, and driven patterns. Hwang [20] used the GREET model from Argonne National Laboratory (ANL) to analyze the life-cycle energy consumption and greenhouse gas (GHG) emission of FCVs and ICEVs. Wei et al. [21] also used the GREET tool to investigate the fuel economy of an FCV at different driving patterns. Liu [18] used the GaBi software and database for life-cycle assessment (LCA) of FCVs.

Most of the studies conducted in China have used LCA models developed abroad, which makes parameters and data in the model not accurately reflect the local situation in China. Furthermore, as China accounts for 94% of the global quantity of FCBs, previous research has overlooked the significance of focusing on FCBs. Therefore, this paper evaluated the life-cycle economic and environmental performance of FCVs in China using locally sourced hydrogen FCBs data. For these purposes, case studies were conducted and accurate first-hand operating data were collected from many enterprises along the industrial chain of hydrogen energy and FCVs, including hydrogen production, transport, refueling, and bus manufacturing and operating. Relevant vehicle (bus) parameters analyzed in this case are shown in Tables S1 and S2 in Electronic Supplementary Material, collected from the National Big Data Alliance of New Energy Vehicles (NDANEV) and confirmed by the Original Design Manufactures (OEMs) (Mar. 2021).

2 LCA of vehicles

The LCA of vehicles evaluates the average GHG emissions generated during the production, transportation, use, and recycling of a product. It always includes vehicle and fuel cycle assessments (or material and energy cycles) [22–24]. Generally, the LCA method can analyze the energy consumption, cost, and carbon emission of a vehicle, as shown in Fig.1. The data used in this paper are obtained mainly from open-source information publicly released by ministries, research institutions, and consulting agencies. The working conditions and operation data of vehicles are basically obtained from the government regulation platform and the transportation management platform of vehicle enterprises. The production energy consumption data are obtained from enterprise factory research in Jinan, Weifang, Zhengzhou, and Foshan cities, China (In the subsequent empirical study, these city names will be replaced by code names.), which is always obtained from tests for individual samples or limited customer feedback.

This paper used carbon dioxide as the standard GHG to account for the carbon dioxide equivalent of emissions. The energy cost and CO₂ emission are usually calculated based on the energy consumption by Eqs. (1) and (2) [25].

(1){\mathrm{C}}_{E,i}= E_i\cdot P_{E,i},

(2){\mathrm{C}\mathrm{O}}_{2,i}=E_i\cdot F_{E,i},

where E_i is the energy consumption, P_{E,i} is the energy price, and F_{E,i} is the CO₂ emission factor of the energy.

3 LCA of hydrogen energy

The LCA of hydrogen energy is very similar to the “well-to-wheel” (WTW) process of fossil energy for conventional automobiles, which includes production, storage, transport, and application stages [1,20,26,27]. Environmental cost is sometimes involved, such as CO₂ tax [27]. In this case, the life-cycle steps of hydrogen energy were detailed based on the investigation, as shown in Fig.2, where E is the specific energy used; P and F are the corresponding energy price and CO₂ emission factor, respectively; and S is the H₂ delivery distance. This case investigated the expense for daily operation and energy consumption. The fixed cost, such as equipment purchase and land lease, is not focused in this paper. The life-cycle cost and emissions are the sum of hydrogen production, packing, transport, storage in hydrogen refueling stations (HRSs), and refueling to FCVs, which are expressed as

(3){\mathrm{C}}_{{\mathrm{H}}_2,\mathrm{L}\mathrm{C}}={\mathrm{C}}_{{\mathrm{H}}_2,\mathrm{p}\mathrm{r}\mathrm{o}\mathrm{d}}+{\mathrm{C}}_{{\mathrm{H}}_2,\mathrm{p}\mathrm{a}\mathrm{c}\mathrm{k}}+{\mathrm{C}}_{{\mathrm{H}}_2,\mathrm{t}\mathrm{r}\mathrm{a}\mathrm{n}}+{\mathrm{C}}_{{\mathrm{H}}_2,\mathrm{s}\mathrm{t}\mathrm{o}\mathrm{r}}+{\mathrm{C}}_{{\mathrm{H}}_2,\mathrm{r}\mathrm{e}\mathrm{f}\mathrm{u}},

(4){\mathrm{C}\mathrm{O}}_{2,\mathrm{L}\mathrm{C}} ={\mathrm{C}\mathrm{O}}_{2,\mathrm{p}\mathrm{r}\mathrm{o}\mathrm{d}}+ {\mathrm{C}\mathrm{O}}_{2,\mathrm{p}\mathrm{a}\mathrm{c}\mathrm{k}} +{\mathrm{C}\mathrm{O}}_{2,\mathrm{t}\mathrm{r}\mathrm{a}\mathrm{n}}+ {\mathrm{C}\mathrm{O}}_{2,\mathrm{s}\mathrm{t}\mathrm{o}\mathrm{r}} +{\mathrm{C}\mathrm{O}}_{2,\mathrm{r}\mathrm{e}\mathrm{f}\mathrm{u}}.

3.1 H₂ production

Hydrogen can be produced by mature technologies like natural gas (NG) reforming, coal gasification, and water electrolysis [26,28]. The carbon intensities of these producing approaches were collected from IEA, as shown in Fig.3. The carbon capture utilization and storage (CCUS) technology is not included in this case. The carbon intensity of the by-product H₂ was calculated based on a case study. The insert of Fig.3 shows that NG reforming and coal gasification are the main ways for H₂ production in China in 2020, which accounts for 81% of the total [29,30]. The carbon intensity of industrial by-product H₂ is assumed to be 0. This assumption will be discussed in the following section. Therefore, the average carbon intensity of H₂ production in China is estimated to be 14.715 kg CO₂ emission per kg H₂.

3.2 H₂ packing

HRSs can produce hydrogen on-site or supplied from hydrogen production plants. When choosing a hydrogen supply method, the cost, safety, and delivery distance must be considered. The HRSs in Jinan, Weifang, Zhengzhou, and Foshan, China were surveyed and it was found that most of the HRSs are supplied with by-product H₂ from the chemical plants, especially chlor-alkali plants, within a 200 km distance. The status is mainly based on the qualification of hydrogen production, the price of hydrogen, and the delivery distance. Several typical chlor-alkali plants in China were investigated to study the energy consumption, cost, and carbon emission of by-product H₂ manufacturing, all of which have a million-ton-scale caustic soda production capacity. In this case, most of the relevant data were referred from a typical chlor-alkali plant in northeast China, which was named as the alpha plant (AP) for reason of commercial security.

In 2018, the AP produced 10900 t of by-product H₂. It sold 6.5% of the H₂ to HRSs and vented 68.6% into the air (Fig.4(a)). It refined and packed the gaseous H₂ with the process and cost shown in Fig.4(b) and Fig.4(c), respectively, before delivering. The packing size is 300 kg gaseous H₂ at 20 MPa per tube trailer. The facilities and parameters of the process are shown in Tables S3 and S4. The sale price of the packed hydrogen is (2.87 ± 0.02) \mathrm{\$}(USD)/kg, which is in good agreement with the feedback from different HRSs. Additionally, this is a tax and delivery-free price. The average cost for hydrogen refining and packing is (1.85 ± 0.72) $/kg, an annual average recorded by the AP.

According to the AP, the primary energy consumption during H₂ refining and packing is gas compressing, which is considered as the total energy consumption of H₂ packing in this case. Therefore, the packing energy consumption is approximate to the energy consumption of the compressors, expressed as

(5)E_{\mathrm{c}\mathrm{o}\mathrm{m}\mathrm{p}}=\frac{P_{\mathrm{e},\mathrm{c}\mathrm{o}\mathrm{m}\mathrm{p}}}{Q_{\mathrm{c}\mathrm{o}\mathrm{m}\mathrm{p}}\cdot {\rho }_{{\mathrm{H}}_2}},

where Q_{\mathrm{c}\mathrm{o}\mathrm{m}\mathrm{p}} is the flow rate of the hydrogen compressor, which is 5887 m³/h; P_{\mathrm{e},\mathrm{c}\mathrm{o}\mathrm{m}\mathrm{p}} is the power of the hydrogen compressor, which is 200 kW; and {\rho }_{{\mathrm{H}}_2} is the density of gaseous hydrogen, which is 0.089 g/L. The compressor parameters were collected from the AP, as shown in Table S4. Thus, the E_{\mathrm{c}\mathrm{o}\mathrm{m}\mathrm{p}} is 0.382 kWh per kg of H₂ packing Then, the carbon intensity of H₂ packing is 0.242 kg CO₂ emission per kg of H₂ calculated by Eq. (2), in which the CO₂ emission factor of grid electricity (F_{\mathrm{e}\mathrm{l}\mathrm{e}\mathrm{c}}) value is 0.635 kg CO₂ emission per kWh [31]. The energy cost of the compressor is 0.034 $/kg H₂, calculated by using Eq. (1), where the local grid electricity price is 0.09 $/kWh. The primary data for hydrogen packing is shown in Table S4. The parameters of the hydrogen packing are listed in Tab.1.

3.3 H₂ transport

Hydrogen can be stored in high-pressure gas, cryogenic liquid, metal hydride, or organic liquid, and transported in corresponding ways [26,32]. Currently, gaseous hydrogen tube trailers are China’s primary transport method for HRS hydrogen supply. All HRSs investigated are supplied by pressured gaseous H₂ via tube trailers within a 200 km delivery.

According to the data from hydrogen suppliers and customers (HRSs), the unit energy consumption and carbon emission for H₂ transport can be calculated by the hydrogen transport parameters via tube trailers listed in Tab.2, which means the carbon intensity of H₂ transportation in kg CO₂ emission per kg of H₂ equals the product of (unit carbon emission × delivery distance). The unit cost of H₂ transportation is about 3 $/kg, which is the feedback from different HRSs. The cost described here is the total expense of hydrogen delivery, including fuel, labor, and truck leasing.

3.4 H₂ storage and refueling

This paper investigated the HRSs in Jinan, Weifang, Zhengzhou, and Foshan, China. Most of the HRSs use a high-pressure buffer storage system called cascade storage to store hydrogen for daily demand [35]. Fig.5 shows a typical hydrogen storage and refueling system in the HRSs, which makes a cost-efficient use of hydrogen and electric power. After delivering to HRSs by tube trailers, the 20 MPa gaseous H₂ is boosted and stored in 35 or 45 MPa hydrogen storage tanks. Then, the pressured hydrogen is dispensed to vehicles from the tube trailer and storage tanks in multi-level pressures.

According to those HRSs, hydrogen boosters consume most of the electricity of the station, but account for about 1/3 of the total cost of the station operation. The daily cost of the HRSs is the sum of labor, utilities, and electricity consumption of hydrogen boosters. Thus, the unit cost of hydrogen energy in an HRS can be calculated as

(6){\mathrm{C}}_{\mathrm{u},\mathrm{H}\mathrm{R}\mathrm{S}}=\frac{\sum ({\mathrm{C}}_{\mathrm{H}\mathrm{R}\mathrm{S},\mathrm{o}\mathrm{p}\mathrm{e}\mathrm{r}}+E_{\mathrm{b}\mathrm{o}\mathrm{o}\mathrm{s}}\cdot P_{\mathrm{e}\mathrm{l}\mathrm{e}\mathrm{c}})}{M_{\mathrm{s}\mathrm{a}\mathrm{l}\mathrm{e}}},

where {\mathrm{C}}_{\mathrm{H}\mathrm{R}\mathrm{S},\mathrm{o}\mathrm{p}\mathrm{e}\mathrm{r}} is the operating cost of HRS, including labor and utilities, E_{\mathrm{b}\mathrm{o}\mathrm{o}\mathrm{s}} is the electricity consumption of boosters, P_{\mathrm{e}\mathrm{l}\mathrm{e}\mathrm{c}} is the local electricity price, and is the kilogram of hydrogen refueled/sold.

The unit carbon emission of an HRS approximates to the carbon emission of boosters, which is calculated by

(7){\mathrm{C}\mathrm{O}}_{2,\mathrm{u},\mathrm{H}\mathrm{R}\mathrm{S}}=\frac{\sum E_{\mathrm{b}\mathrm{o}\mathrm{o}\mathrm{s}}\cdot F_{\mathrm{e}\mathrm{l}\mathrm{e}\mathrm{c}}}{M_{\mathrm{s}\mathrm{a}\mathrm{l}\mathrm{e}}}.

The investigation demonstrates that the value \sum E_{\mathrm{b}\mathrm{o}\mathrm{o}\mathrm{s}} is almost fixed for an HRS with a specific capacity, and the refueling H₂ mass for each bus (M_{\mathrm{u}}) is also improved. Thus, the M_{\mathrm{s}\mathrm{a}\mathrm{l}\mathrm{e}} can be presented based on the number of refueled buses as

(8)M_{\mathrm{s}\mathrm{a}\mathrm{l}\mathrm{e}}=M_{\mathrm{u}}\cdot N_{\mathrm{r}\mathrm{e}\mathrm{f}\mathrm{u}}.

As shown in Fig.5, the bus is refueled when the pressure of the on-board hydrogen tank is lower than 8 MPa, but not empty. Therefore, the value of M_{\mathrm{u}} is not precisely the capacity of the tank, but the result is calculated as

(9)\frac{p_{35\mathrm{M}\mathrm{P}\mathrm{a}}}{M_{\mathrm{t}\mathrm{a}\mathrm{n}\mathrm{k}}}=\frac{p_{35\mathrm{M}\mathrm{P}\mathrm{a}}-p_{8\mathrm{M}\mathrm{P}\mathrm{a}}}{M_{\mathrm{u}}},

where M_{\mathrm{t}\mathrm{a}\mathrm{n}\mathrm{k}} is the on-board hydrogen capacity of a bus, which was collected from the bus OEMs (original equipment manufacturer). As shown in Tables S5 and S6, the M_{\mathrm{t}\mathrm{a}\mathrm{n}\mathrm{k}} of the 8.6 and 12 m FCBs are 13.8 and 26.4 kg H₂, respectively. Thus, their values are 10.6 and 20.4 kg H₂, respectively.

Then, a representative city in both southern and northern China were selected to further study HRSs, which is referred to as Cities A and B. They were named HRS-A (Yutong Hydrogen Station, City A) and HRS-B (Grandblue Songgang Hydrogen Station, City B) for short. Tab.3 shows the parameters for HRSs. The data of H₂ sales is an average value of a whole year. For example, the HRS-B typically sold 750 kg H₂ per day in winter, but 450 kg H₂ per day in the other seasons. The unit cost and emission were calculated based on Eqs. (6) and (7). All parameters are derived from field research, through actual data generation and self-measurement.

4 Results

4.1 Life-cycle CO₂ emission and cost of H₂ energy and different vehicles

The cost and carbon emission values for hydrogen packing, transport, and HRS are shown in Tab.1, Tab.2, and Tab.3, respectively. The life-cycle cost and carbon emission of hydrogen energy was calculated by Eqs. (3) and (4). Fig.6 exhibits the life-cycle CO₂ emission and cost of H₂ energy in Cities A and B, with related parameters and results summarized in Table S5. As shown in Fig.6(a), the carbon emission of H₂ energy consists of hydrogen packing, transport, and HRS (storage and refueling), where the emission of the by-product H₂ from the AP is considered zero. The cost of H₂ energy mainly includes the H₂ price from the production plant, the cost of H₂ delivery (transport), and the expense for HRS operation (which consists of labor, utility, and electricity for boosters). Fig.6(b) is an additional reference for hydrogen life-cycle carbon emission, where the emission of hydrogen production is considered as the average carbon intensity of H₂ production in China.

Similarly, Fig.7 shows the comparison of CO₂ emission and respective energy cost for different types of vehicles investigated, with more detailed parameters shown in Tab.4. Energy consumption of FCVs were measured and provided by their OEMs. Energy consumption of BEVs equals accumulated electricity consumption divided by accumulated operating mileage, which is based on the data from the NDANEV. Carbon emission factor of hydrogen energy shares the unit carbon emission value of the hydrogen fuel life cycle as calculated. Energy cost and carbon emission are calculated by Eqs. (1) and (2), respectively.

4.2 Energy cost and CO₂ emission of HRSs

As shown in Fig.6(a), the main difference in hydrogen life-cycle carbon emission between Cities A and B comes from the hydrogen storage and refueling processes in HRSs. This difference is caused by the unsaturated load at the capacity of the HRS, which is further ascribed to the short supply of hydrogen in City A. A model was built as depicted in Fig.8(a) and Fig.8(b) to show the relationship between the unit carbon emission and unit cost for hydrogen in the HRS, the vehicle number of refueling (N_{\mathrm{r}\mathrm{e}\mathrm{f}\mathrm{u}}), and the capacity of the on-board hydrogen tank (M_{\mathrm{t}\mathrm{a}\mathrm{n}\mathrm{k}}). The different colored curves in Fig.8 represent different M_{\mathrm{t}\mathrm{a}\mathrm{n}\mathrm{k}}. The electricity consumption of the HRS is fixed, which is mainly based on the power, flow rate, and operating time of the boosters (Eqs. (5) and (7)). Thus, the unit carbon emission and unit cost of the HRS can be shown as functions of N_{\mathrm{r}\mathrm{e}\mathrm{f}\mathrm{u}}:

(10){{\mathrm{C}\mathrm{O}}_{2,\mathrm{u},\mathrm{H}\mathrm{R}\mathrm{S}}\left(N_{\mathrm{r}\mathrm{e}\mathrm{f}\mathrm{u}}\right)=\frac{\sum E_{\mathrm{b}\mathrm{o}\mathrm{o}\mathrm{s}}\cdot F_{\mathrm{e}\mathrm{l}\mathrm{e}\mathrm{c}}}{M_{\mathrm{u}}\cdot N_{\mathrm{r}\mathrm{e}\mathrm{f}\mathrm{u}}}|}_{M_{\mathrm{u}}\cdot N_{\mathrm{r}\mathrm{e}\mathrm{f}\mathrm{u}}⩽M_{\mathrm{H}\mathrm{R}\mathrm{S}}},

(11){{\mathrm{C}}_{\mathrm{u},\mathrm{H}\mathrm{R}\mathrm{S}}\left(N_{\mathrm{r}\mathrm{e}\mathrm{f}\mathrm{u}}\right)=\frac{\sum ({\mathrm{C}}_{\mathrm{H}\mathrm{R}\mathrm{S},\mathrm{o}\mathrm{p}\mathrm{e}\mathrm{r}}+E_{\mathrm{b}\mathrm{o}\mathrm{o}\mathrm{s}}\cdot P_{\mathrm{e}\mathrm{l}\mathrm{e}\mathrm{c}})}{M_{\mathrm{u}}\cdot N_{\mathrm{r}\mathrm{e}\mathrm{f}\mathrm{u}}}|}_{M_{\mathrm{u}}\cdot N_{\mathrm{r}\mathrm{e}\mathrm{f}\mathrm{u}}⩽M_{\mathrm{H}\mathrm{R}\mathrm{S}}},

where M_{\mathrm{u}} can be calculated by Eq. (9) based on the value of M_{\mathrm{t}\mathrm{a}\mathrm{n}\mathrm{k}}, and M_{\mathrm{H}\mathrm{R}\mathrm{S}} is the refueling capacity of the HRS.

5 Discussion

5.1 CO₂ emission

As shown in Fig.7(a), the carbon emission of FCVs is significantly lower than other types of vehicles, including BEVs. In contrast, the carbon emission of FCVs in City B is 59.6% lower than in City A. This is because the life cycle carbon emission of hydrogen energy in City B is 55.7% lower than that in City A (Fig.6(a)), primarily contributed by the CO₂ emission from the HRSs. As shown in Fig.8(a), the carbon emission decreases significantly when the refueling vehicle increases, especially at the starting stage. The on-board hydrogen tank capacity of the vehicle will also influence carbon emission, with larger capacities resulting in lower CO₂ emissions for the same number of FCVs. In City B, the FCV number of refueling is only 9 more than that in City A, and the capacity of on-board hydrogen tank is 91.3% larger than that in City A. The combined effect of both factors results in a 60.4% reduction in CO₂ emission from the HRSs compared to City A.

However, the same optimal value shows (0.770 ± 0.004) kg CO₂ emission per 100 km for all situations when the HRS works at total capacity with the existing hydrogen supply system. Therefore, although the CO₂ emission of the FCVs in City A is 28.950 kg CO₂ emission per 100 km, it can potentially be reduced to 7.792 kg CO₂ emission per 100 km in the current hydrogen supply system.

In addition, the surplus by-product hydrogen in this paper supplied the hydrogen energy, and its carbon emission during production was considered to be 0. It is also believed that the by-product hydrogen cannot satisfy the whole hydrogen energy market in the future. The carbon emission will significantly increase if the hydrogen is produced in any specific way, as shown in Fig.6(b). The average carbon intensity of hydrogen production in China is 14.715 kg CO₂ emission per kg of H₂, calculated based on the data from IEA as demonstrated in Fig.3. Therefore, the production process is still the vital stage to make hydrogen energy “greener” for FCV application.

5.2 H₂ energy consumption and cost

The energy consumption and driving costs of a vehicle are major indexes for consumers [36]. As shown in Fig.7(b), the driving cost of FCVs in City A is about 0.60 $/km, higher than either BEVs or conventional vehicles. The driving cost of FCVs in City B is comparable to the traditional vehicles. The unit hydrogen consumption of FCVs in Cities A and B are (5.7 ± 0.1) and (5.2 ± 0.5) kg H₂ per 100 km, respectively (Tab.4), which are almost identical. The difference in driving cost is mainly attributed to their different hydrogen refueling price, as shown in Tab.3, which is 10.45 $/kg for City A and 5.97 $/kg for City B. As seen, a 5.97 $/kg price makes the energy cost of FCV comparable to the conventional vehicle. In contrast, according to ANL, the hydrogen price at dispensers is (13–15) $/kg in California [1,37]. China seems to have a price advantage on hydrogen refueling. However, this advantage may be attributed to the surplus by-product of hydrogen. For a long-term plan, the cost of hydrogen production deserves more attention.

Moreover, the current hydrogen supply system has ample space for cost reduction. The cost of hydrogen refueling in City A can be reduced to 0.36 $/kg from 0.60 $/kg if the HRS operates at its total capacity, representing a 39.1% decrease in price. This price cut is attributed to the full use of the HRS in the current hydrogen supply system of City A, which can make the unit cost for hydrogen storage and refueling drop by 82.8% (from 3.02 to 0.52 $/kg as shown in Fig.8(c)). The cost of hydrogen energy shown in Fig.6(a) is based on the price of the hydrogen transaction, which may also contain profits. As shown in Tab.1, the unit cost for by-product hydrogen refining and packing is (1.85 ± 0.72) $/kg, while the sale price is (2.87±0.02) $/kg, while the sale price is (2.87 ± 0.02) $/kg. Hence, if the hydrogen supply system can be further developed and optimized, it will probably be effective in reducing the cost of hydrogen refueling.

The case study of Cities A and B suggests that the FCV has a similar driving efficiency to the BEV, which is fully competent as an urban vehicle, especially passenger vehicles. Nonetheless, the operating rate of the FCV is much lower than that of the BEV due to the lack of hydrogen energy, which also increases the price of hydrogen refueling. This presents a significant regional difference between Cities A and B. This gap can be closed with an adequate hydrogen supply. The reduction in energy cost and CO₂ emission of HRSs is foreseeable with the increase in the number of FCV for refueling, as shown in Fig.8(c). Finally, with enough hydrogen in the current system, the carbon emissions for FCV application can decrease by 73.1% in City A and 43.8% in City B. It only takes about 11.0%–20.1% of the BEV emissions and 8.2%–9.8% of traditional vehicle emissions. The cost of FCV driving can be reduced by 39.1% in City A.

6 Conclusions

6.1 Carbon emission reduction

Compared with conventional diesel or electric vehicles, hydrogen FCVs have a particular advantage in carbon emission reduction. Even if the carbon emissions are similar for each type of vehicle at the manufacturing stage, due to its low carbon emissions in the use phase, FCVs demonstrate lower carbon emission targets throughout the entire life cycle. The carbon emission reduction potential of FCVs will become increasingly pronounced with the maturity of renewable energy technologies, such as zero-emission water electrolysis for hydrogen production.

The development of FCVs will be conducive to China’s high-quality achievement of carbon peaking. Compared with high-energy-consuming and high-emission industries such as electricity, steel, and chemicals, the total carbon emissions of the automotive industry are relatively small. However, considering the objective problems, such as China’s “30/60” commitment, the space compression of high-emission industry carbon reduction is complicated, and economic growth makes carbon neutrality more difficult. The FCV industry, which has a great potential for emission reduction, must take action and prepare for technology, industry, path planning, and action guidelines as soon as possible. In this way, the time convergence of the national carbon emission reduction actions can be completed and the carbon neutrality target achieved as scheduled.

6.2 Carbon market construction of NEVs

Carbon market construction has a particularly positive effect on the healthy development of the FCV industry. The construction of the NEV carbon market should be accelerated by strengthening the development of the NEVs industry, especially the FCV industry, on all fronts. At the same time, market-oriented measures promote the continuous expansion of the FCV market to alleviate the constraints on industrial development by policy instruments such as subsidy withdrawal.

Multiple measures are an effective way to build and develop the carbon market for FCVs. As the scale of the FCV industry expands, policy instruments will gradually give way to more flexible market instruments. The development trend of carbon trading market construction will be consistent, evolving from government pricing to mixed pricing and market pricing. By integrating multiple elements such as technology, innovation, and culture, NEVs, including FCVs, will eventually form a positive market economic form and development trend under macro-regulation.

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