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Competitiveness of the China-Europe Railway Express and liner shipping under the enforced sulfur emission control convention
Transportation Research Part E 135 (2020) 101861
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Competitiveness of the China-Europe Railway Express and liner shipping under the enforced sulfur emission control convention Feng Lian, Yunzhu He, Zhongzhen Yang
T
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Faculty of Maritime and Transportation, Ningbo University, Ningbo, China
ARTICLE INFO
ABSTRACT
Keywords: Sulfur emission cap China-Europe Railway Express Mode choice Total transport time Pass-through ratio
The sensitivity of the pass-through ratio of the added costs due to the enforced sulfur emission cap of liner shipping as extra fare for shippers and rail operation frequency on the competitiveness of China-Europe railway express (CER-express) and liner shipping for cargo transportation between China and Europe is analyzed. The objective is to lay a theoretical basis for liner companies to optimize the pass-through ratio for maximizing shipping profit, for CER-express to determine an expected operation frequency and for IMO to understand the effects of the enforced sulfur emission cap when CER-express is available.
1. Introduction At its 70th conference, the IMO’s Marine Environment Protection Committee (MEPC) approved a regulation coming into force on 1 January 2020 on limiting bunker fuel with sulfur content to less than 0.5% m/m globally. At the 71st conference, it was again confirmed that the new global limitation for sulfur content would be initiated on 1 January 2020, while the sulfur content of 0.1% m/ m would remain in the emission control areas (ECAs) of the Baltic Sea, the North Sea, North America and the Caribbean Sea. There is no doubt that the enforced sulfur cap will enter into force as planned, and all maritime shipping companies will have to face its implications in 2020. The enforced sulfur cap (hereafter IMO 2020) is likely to make low-sulfur fuel cost more initially than the heavy oil currently used by a majority of ships. According to Maersk, the new sulfur limit will cost Maersk Line an additional 2 billion US dollars every year. In 2018, the total revenue of Maersk Line was 39.019 billion US dollars, while its profit was only 0.22 billion US dollars (Maersk 2018 Financial Report). Compared to Maersk’s profit in 2018, the additional cost for complying with IMO 2020 is far beyond its profit. Therefore, it is impossible for shipping companies to bear all the added fuel cost alone. On 17 September 2018, Maersk Line announced that a new fuel surcharge will take effect on 1 January 2019. On 24 September 2019, following Maersk Line, two other giant lines, CMA and MSC, also announced their fuel surcharge plan. The CER Express is a new type of intercontinental trade transport mode between China and Europe. The development of the CER Express has been greatly boosted since the Belt and Road Initiative (BRI) was adopted by the Chinese government. In particular, in recent years, the number of routes and cargo volumes of the CER Express have been increasing exponentially. The data from the Ministry of Commerce of the People’s Republic of China show that train journeys increased from 7 in 2011 to 6300 in 2018. The “China Railway Express Construction and Development Plan (2016–2020)” shows that 5000 CER Express train journeys will be operated in 2020. However, this projected number was actually fulfilled in 2018. By the end of 2018, there were 61 CER Express routes linking 56 Chinese cities with 49 cities in 15 European countries. The one-way trip time of the CER Express train has been
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Corresponding author. E-mail address: [email protected] (Z. Yang).
https://doi.org/10.1016/j.tre.2020.101861 Received 15 August 2019; Received in revised form 19 December 2019; Accepted 27 January 2020 Available online 29 February 2020 1366-5545/ © 2020 Elsevier Ltd. All rights reserved.
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shortened by 30% to 12–14 days, while in the initial stage, it was approximately 20 days. The freight rate of a whole journey has dropped by approximately 40% (data from the Ministry of Commerce of the People’s Republic of China). It can rationally be said that at present and in the future, the CER Express is a competitor of liner shipping between China and Europe. In the transport market between China and Europe, the transport time and fare of different transport modes differ greatly. When the CER Express was unavailable, maritime shipping and air transport rarely competed with each other. As a result, few studies on the competition among China-Europe trade transport modes can be found. The CER-Express is a stronger competitor to liner shipping in terms of transport time (Li et al., 2019) and freight rate because the utility difference between the two modes is not big enough. Moreover, after IMO 2020, the competitiveness of the CER Express may be further consolidated because emission control will increase the bunker fuel cost of liner companies past the cost ceiling that liner companies are able to afford; thus, they will inevitably pass some or all of this additional cost onto shippers. In contrast, with the advancement of the BRI, the transport time of the CER Express continues to decrease, and the service frequency continues to increase, which reduces both waiting times and fares for the shippers. As a result, liner shipping will become less competitive, and shippers may be more likely to choose the CER Express. The mode choice of shippers depends on the utility of the modes, while the mode utility is jointly determined by cargo attributes and the generalized transport cost, which is an integration of transport time and fare. In the near future, all the relative influencing factors of the two modes may change, such as the IMO 2020, the fast growth of the CER Express, and the diversification of ChinaEurope trade commodities. Therefore, it is necessary to study how the pass-through ratio of the added fuel cost to shippers and the change in train frequency affect the modal split in transporting the trade commodities, liner companies’ profits and sulfur and CO2 emissions. In this context, this study makes a threefold contribution to the literature. First, we study ECAs’ impact on the business strategies of liner shipping companies in the case of a fungible mode is available. Existing studies have mainly studied shipping route design or bunker fuel adoption due to the ECA under the assumption that only ocean shipping is available, which means the intercontinental shipping market is a closed market. Shipping companies could adopt measures with the objective of minimizing total cost. However, due to the availability of the CER-Express, the freight transport market between China and Europe is not closed for liner shipping and existing studying results are not correct anymore. Therefore, instead of cost minimization, this paper studies the strategies of liner shipping companies for dealing with ECA with the aim of profit maximization. Second, this paper considers the roles of the value of time for different commodities in shippers’ mode choices, which complexes the model but makes it more useful and realistic Based on the value of time, in our study the commodities are divided into 9 categories. In this way, by model analysis we can illustrate the different business strategies being adopted by shipping companies for different market segments, which may result in different emission control effects. Third, our method can reveal the relationship between shipping profits and the combination of rail operating frequencies and shipping companies’ pass-through ratios in term of different kinds of commodity categories. It is helpful for shipping companies or the CER-Express in designing their service specifications and marking strategies. The remainder of this paper is organized as follows. Section 2 provides a literature review to show the research gap and lay background for our paper. Section 3 gives the methods to calculate the transport cost of liner shipping and the CER-Express between China and Europe, the modal splits and the emission from the transportation. Section 4 presents the calculation results and the extensive analysis of sensitivities of pass-through ratio of the added cost and the rail operation frequency. A summary and directions for future research are presented in Section 5. 2. Literature review There have been many papers on the topic of sulfur emission control in the maritime sector; these papers have studied the issue mainly from three points of view: (1) the impacts of emission control areas (ECAs) on vessel speed and routing; (2) the impacts of ECAs on modal splits; and (3) the measures shipping companies take to meet the sulfur control regulation. Vessels are required to use low-sulfur bunker fuels or operate sulfur scrubbers in ECAs, which will increase the operation cost for shipping companies. Because sailing speed is the key variable determining the bunker fuel cost, shipping companies usually make vessels sail with different speeds inside and outside ECAs. To meet the expected sailing time, liner shipping companies need to optimize the speed combination. Fagerholt and Psaraftis (2015) analyzed different vessel speeds inside and outside ECAs to reduce fuel cost with a constant total on-route time. A similar problem was also discussed by Doudnikoff and Lacoste (2014), who thought that deceleration in ECAs and acceleration outside ECAs could reduce the total cost without changing the total on-route time but at the expense of increasing CO2 emissions. Qin et al. (2017) estimated ECAs’ effectiveness on the reduction of SO2 and CO2 emissions in the Shanghai port area with the assumption of an ECA being a reduced speed zone. It is shown that in the port area of Shanghai for the year 2020, a reduction in SO2 emissions by at least 103,998 tons may be achieved with the 12-nmi ECA, CO2 emissions may be reduced by 827,733 tons with a 12-knot speed limit in the 12-nmi ECA, and an additional SO2 reduction of 522.23 tons can be achieved by slow steaming. Cariou et al. (2018) established a mixed-integer linear programming model to maximize shipping company profit with a series of decision variables, such as port-of-call selection and sequence, cargo flow between ports, number of ships and sailing speed on each segment. Their model solved the problem of how to balance the cost and the sulfur emission. Aiming at minimizing the total cost composed of liner fleet cost and carbon emission cost, Cheng and Zhang (2017) employed a mixed-integer linear programming model to compare the total costs in two scenarios of using identical/different sailing speeds inside and outside ECAs. They found that using different sailing speeds could reduce the total operating cost. They also studied the impacts of ECA length and carbon tax rate on a liner’s total cost. To minimize liner operating cost and CO2 cost, Lv and Mao (2017) used ship size, number of ships and sailing speed 2
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as decision variables to establish a nonlinear programming model to optimize the speed combination and fleet deployment. Zhen et al. (2018) optimized the speeds, the sailing patterns and the port-of-call sequence for a cruiser voyage with the aim of reducing fuel costs. The numerical test based on real-world data of cruise lines is done to explore the effects of ECA regulations on cruise shipping. With regard to the impacts of ECAs on maritime routing, Fagerholt et al. (2015) stated that ECAs would change route choices, especially for long-distance voyages, on which ships would take detours to avoid the ECAs. In certain situations, the establishment of ECAs will, in contrast, increase sulfur emissions because of those detours. The authors noted that the impact of ECAs on maritime routing had a positive correlation with the price gap between marine gas oil (MGO) and heavy fuel oil (HFO). The opinion that ECAs will change ship routing is also supported by Chen et al. (2017). They analyzed the route-choosing behaviors of liner shipping through the ECA in the Mediterranean by targeting the Asia-Europe route. It was revealed that a large number of ships will re-route around the ECA, and regional emissions will be excessive under certain conditions, while small ships are more likely to re-route than are large ships. Dulebenets (2017) investigated the problem of ship scheduling under the constraint of ECA emission and on-route time requirement. They found that ships were inclined to decelerate on some segments to reduce the total fuel cost but eventually had to pay extra penalties because of the induced delay. The first type of study assumes that shipping freight demands are unchanged (which means that the shipping income of liner companies are fixed), and then optimizes the route or path of a single ship to minimize its total operation costs, and estimates the emissions of CO2 and SO2. In the context of no substitute service for liner shipping, the studying results are correct and can be adopted by shipping company. In the case that the CER-Express is available, any changes (path or freight rate) of liner shipping may induce changes in shipping freight demand and further shipping income of the liner companies. Therefore, instead of cost minimization, it is necessary to study the business strategies of liner companies for dealing with ECA with the aim of profit maximization. Concerning the impacts on modal splits, Algaba (2014) studied the impact of the sulfur emission control convention on short-sea transport in the North Sea and found that lowering vessel speed would push cargos to shift from maritime shipping to other transport alternatives. Kontovas et al. (2016) studied the impacts of the sulfur emission control convention on the modal splits between intermodal transport and highway transport. They found that the sulfur emission control convention would decrease the mode share of intermodal transport but increase that of highway transport. Holmgren et al. (2014) analyzed the impacts of the sulfur emission control convention on the path choice of high-value cargos from eastern Lithuania to western United Kingdom, and the results indicated that the modal shift from sea shipping to highway transport would be unlikely even if the ECAs were set. To recognize the competition of the Suez Canal with other routes, Shibasaki et al. (2016) focus on the share of its transit in the container shipping market on a global scale to estimate the shares’ difference in the years 2010 and 2013 using an aggregated logit model. The second type of literature has indeed analyzed ECA impacts on modal splits and proved that the sulfur emission control convention will decrease shipping’s modal split. The existing studies have taken the added costs due to the sulfur emission control convention as the decrement of shipping utility directly. Because shipping companies may not pass all the added cost onto shippers, the estimated mode share of shipping transport would be smaller than the actual one. Therefore, it is necessary for us to analyze the modal splits in the cases of shipping companies not passing all the added costs because they want to maximize the profit. In the literature on emission control measures, Lindstad et al. (2015) claimed that ship engine size, annual fuel consumption in ECAs and future fuel price are the main influencing factors of abatement for sulfur emission. In terms of costs and benefits, Jiang et al. (2014) compared two measures for sulfur emission control, namely, using sulfur scrubbers or maritime gas oil, and found that the price gap was the determining factor in the selection of the two measures. Yang et al. (2012) assessed several emission control measures with the analytic hierarchy process and concluded that changing bunker fuel was the desirable solution to comply with the sulfur emission control convention, but sulfur scrubbers could be the best solution in the future if sulfur emission control became more stringent. Brynolf et al. (2014) proposed three fuel alternatives complying with the ECA emission regulation. They used lifecycle assessment to comparatively analyze the three alternatives and found that none of them could significantly reduce CO2 emissions compared to heavy fuel oil (HFO), but they could decrease the emissions of particulate matter, photochemical ozone formation, acidification and terrestrial eutrophication potential. Schinas and Stefanakos (2014) presented a multicriterion approach based on the analytic network process (ANP), which could reveal the preferences and relationships among criteria, to help shipping companies choose the necessary technology alternatives. Abadie et al. (2017) evaluated the economic gap between the two main techniques (namely, changing bunker fuel or using sulfur scrubbers) currently used by the shipping industry by accounting for the factors of fuel spot and future prices, the cost for installing scrubbers, vessel on-route time in ECA and the remaining lifetime of vessels. Based on the ECA regulation for Baltic Sea shipping, Antturi et al. (2016) first compared the costs of the measures of using low sulfur fuel and installing sulfur scrubbers for shipping companies. Then, they evaluated the benefits of the selected abatement measure through a high-resolution impact pathway analysis, taking into account the formation and dispersion of emissions, and considered the positive health impacts resulting from lowered ambient PM2.5 concentrations. The results showed that for the Baltic Sea, the new sulfur emission regulation was not cost effective because the cost paid by shipping companies was far more than the benefit to the environment. In the last type of study, which has the largest volume, the technical issues of bunker fuel adoption and sulfur scrubber installation have been studied, while factors beyond ship operation are excluded. They are essential; however, because shippers, competitors, network and transport routes are excluded, the results could only be used for vessel management rather than business strategies or emission analysis of the ECA. It is necessary to study the effects of the enforced sulfur emission cap on business strategy of liner shipping companies and emission reduction in micro level by taking account the relationships between shippers and carriers as well as the competition between the two kinds of carriers into account.
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In fact, under IMO 2020, liner shipping companies will inevitably encounter higher fuel costs or additional costs for installing sulfur scrubbers. Passing a part but not all of the added cost onto shippers may be a key decision of the liner companies. Therefore, we can rationally say that because the CER-Express is available, the impacts of the sulfur emission control convention on the competitiveness of liner shipping between China and Europe needs to be studied in the context of liner companies wanting to maximize their operation profit. In this context, we attempt to study the competitive relationship between liner shipping and the CER Express in the China-Europe cargo transport market by analyzing the impacts of the IMO 202 and CER Express development on shippers’ mode choices. Furthermore, we explore the impacts of the control convention on the sulfur and carbon emissions of China-Europe trade transport. 3. Model building 3.1. Problem description Per IMO 2020, maritime fuels are required to meet the sulfur content limitation of 0.5% m/m in the whole ocean area and a more stringent limitation of 0.1% m/m in specific ECAs, which is believed to cost shipping companies more for bunker fuel alternatives. The added cost may be too much for shipping companies to bear by themselves; thus, they will have to pass a part of these costs onto shippers by levying a bunker surcharge. In other words, shippers’ maritime shipping cost will increase. In contrast, due to the BRI the railway transport cost between China and Europe is decreasing because the CER-Express has gradually gained financial and political support from Chinese government as an important mode between China and Europe (Wu et al., 2019), and has been developing faster and faster (Hong and Zhu, 2019). When comparing the two aforementioned transport modes in the China-Europe freight market, shippers will observe decreased utility of liner shipping and increased utility of the CER Express. Consequently, some shippers may be likely to shift from liner shipping to CER Express transport. To analyze the impacts of IMO 2020 and CER Express development on the modal shift, the profits of liner companies and the sulfur and carbon emissions in the China-Europe freight transport market, first, the general transport cost must be decomposed into two parts, namely, total transport time (including on-route time and waiting time) and total transport fare. Second, the modal split model must be calibrated. Finally, the modal split of the CER Express, the profits of liner companies, and the sulfur and carbon emissions with regard to the passthrough ratio of the added cost onto shippers and the increment of the train frequency of the CER Express in the China-Europe freight market must be calculated. 3.2. Methodology Based on the following facts about the China-Europe trade transport system, a shipper’s mode choice behaviors will be analyzed. A1: A2: A3: A4: A5:
The capacity of a liner ship is 18,000 TEUs. Train capacity of the CER Express is 84 TEUs. Sailing speed of a liner ship is 20 knots. All the freight demands of China-Europe trade should be served. The CER Express train uses HXD3 electric locomotives.
The probability of choosing an alternative will increase with its utility increment (Psaraftis and Kontovas, 2010); therefore, the probability of choosing a given mode can be calculated by Eq. (1) (Kontovas et al., 2016).
Pi, k = Exp ( i Vi, k )/
k = 1,2
Exp ( i Vi, k )
(1)
Here, Pi, k is the probability that mode k is selected for commodity i; Vi, k is the utility of mode k for transporting commodity i; i is a parameter to be calibrated; and k is a binary variable (0 denotes liner shipping, and 1 denotes CER Express). The utility can be calculated as follows:
Vi, k = - Ci, k
(2)
Ci, k = Fk + ui Tk
(3)
ui = Mi r/(24 × 365)
(4)
where Ci, k is the generalized transport cost of mode k for transporting commodity i; Fk is the roundtrip freight rate of mode k; Tk is the total transport time of mode k for a round trip; ui is a positive constant directly proportional to the value of commodity i, which has been estimated in our former studies (Zhao et al., 2018); Mi is the money value of commodity I (USD/TEU); and r is the opportunity cost of the shipper’s capital. In practice, r is regarded as the annual return rate on risk-free investment and is usually denoted by the interest rate of long-term government bonds. (5)
Tk = Ttk + Wtk
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(6)
Wtk = 168/ fk /2
Here, Ttk is the on-route time of mode k, Wtk is the waiting time of mode k, and fk (shift/week) is the train frequency of the CER Express. As a week totals 168 h, Wtk is equal to 168/ fk /2 (Zhao et al., 2018). (7)
Tt1 = T1, ECA + T1, OUT
T1, ECA =
T1, OUT =
d1, ECA v
d1
(8)
d1, ECA v
(9)
Eq. (7) is used to calculate the liner ship on-route time, which consists of the time (T1, ECA ) in ECAs and the time (T1, OUT ) outside the ECAs. In Eqs. (8) and (9), d1, ECA is the sailing distance in the ECA; d1 is the total sailing distance of the whole voyage; and v is liner shipping sailing speed.
M1, ECA = FH (v/ vd )3
T1, ECA 24
(10)
M1, OUT = FH (v / vd )3
T1, OUT 24
(11)
Eqs. (10) and (11) present fuel consumption inside and outside the ECAs, respectively (Doudnikoff and Lacoste, 2014). FH is the daily fuel consumption when operating under designated speed vd .
FH = (Sfoc × El × WS )
24 106
(12)
Here, Sfoc is the fuel consumption rate of the main engine of the liner ship, and El and Ws are the load and power of the main engine, respectively. (13)
C1, fuel = P1, OUT M1, OUT + P1, ECA M1, ECA
Here, C1, fuel is the total fuel cost, and P1, ECA , P1, OUT are the prices of bunker fuels used inside and outside the ECAs, respectively.
F1 = µ
(C1, fuel
C1, )
18000
+ F1,
(14)
Eq. (14) is used to calculate the liner shipping unit freight rate after IMO 2020 takes effect; the value equals the sum of the previous unit freight rate F1, and the added cost for the expensive bunker fuel. The added cost for liner shipping equals the prorated fuel cost increment per TEU multiplied by the passthrough ratioµ . C1, is the previous fuel cost.
DiPik
Dk =
(15)
i
n=
f1 T1
(16)
24 × 7
Here, Dk is the transport volume of mode k, and used to determine the number of liner ships needed.
Di
REV = D1 F1
f1 C1, fuel
is the freight demand of commodity i between China and Europe. Eq. (16) is (17)
n (Cfc + Copex )
Here, REV is the weekly profit from transporting commodity i by liner ship. Cfc and Copex are the weekly capital cost and operating cost of the liner ship, respectively.
EMIS =
EMIS0 =
EMISk k
(18)
PW × Tt 0 × Ratio × ratecoal D × PPMcoal × o 106 × (1 rateloss ) 84
(19) (20)
EMIS1 = PPM1, OUT M1, OUT + PPM1, ECA M1, ECA
Here, EMIS is the total sulfur emission from CER Express trains and liner ships. Eq. (19) is used to calculate the sulfur emission from the CER Express train. PW is the power of the CER Express train. Ratio is the percentage of thermal power generation of the total domestic electricity production. ratecoal is the net coal consumption rate in thermal power generation. rateloss is the electricity loss rate during transmission. PPMcoal is the sulfur content of coal. Eq. (20) is used to calculate the sulfur emission of the liner ship. PPM1, ECA and PPM1, OUT are the sulfur content of the bunker fuels used in and out of the ECA.
EMIC =
EMICk
(21)
k
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Table 1 Commodity categories used for the case study. Category
Commodity
China Customs Code
Value (USD/TEU)
1 2 3 4 5 6 7 8 9
Food processing & tobacco Textiles Apparel, Shoes & Hats, Leather & Down Feathers Wood Processing, Paper Making & Paper Products Chemical Raw Materials & Chemical Products Nonmetal Mineral Products Metal Smelting and Processing & Metal Products Equipment Manufacturing Products Other Manufacturing Products
1–26 50–60,63 41–43,61,62,64,65 44–49 27–40 68–70 71–83 84–91,93 66,67,92,94–97
41,562 20,211 86,957 21,355 522,977 41,667 769,231 1,111,111 149,254
Data Source: General Administration of Customs, P.R. China
EMIC0 =
D PW × TT0 × Ratio × ratecoal × CCcoal × o 106 × (1 rateloss ) 84
(22) (23)
EMIC1 = (M1, OUT + M1, ECA ) × CCfuel
Here, EMIC is the total CO2 emission from liner ships and CER Express trains, and EMICk is the CO2 emission from mode k. Eqs. (22) and (23) are used to estimate the CO2 emissions of CER Express trains and liner ships, respectively. CCcoal and CCfuel are the conversion coefficients of coal and bunker fuel, respectively. 4. Numerical study 4.1. Data sources Based on the commodity clustering method proposed by Lee, Wu & Lee (2011), we group 97 kinds of import and export commodities in the statistical data of Chinese Customs into 9 categories, which are listed in Table 1 and are used for the empirical study. In fact, the grouping has taken the commodity and value proximities into account, which are the factors affecting their transportation utilities. Table 2 presents the freight demands of the 9 categories of commodities between China and Europe in 2011–2020, in which the 2011–2018 data are from the Ministry of Commerce of the People’s Republic of China, and the 2019–2020 data are forecasted by using the stochastic frontier gravity model (Li, et al., 2018) as follows.
Intradeit = dit =
i0
+
i1 Ingdp1t
+
i2 Ingdp2t
+
i3 Ind1t
+
i 4 Inpop1t
+
i5 Inpop2t
(24)
+ vit
Intradeit Mi
(25)
In Eq. (24), tradeit is the trade volume of category i between China and Europe in year t (USD); gdp1t and gdp2t are the GDP of China and Europe, respectively, in year t (USD); d1t is the transport distance between China and Europe (km); pop1t and pop2t are the population in China and Europe in year t (100 million persons), respectively; and vit is a random error term. im (m = 0, 1, 2, 3, 4, 5) is the parameter to be calibrated. In Eq. (25), dit is the freight demand of category i between China and Europe in year t, and Mi is the cargo value of category i (USD/TEU). Table 2 Freight demands between China and Europe in 2011–2020 (TEU/Week). Year Category
2011
2012
2013
2014
2015
2016
2017
2018
2019
2020
1 2 3 4 5 6 7 8 9
2034 8770 7510 7035 1350 461 770 4088 4304
2177 7505 7369 6573 1325 434 669 3808 4073
2657 28,732 7975 8589 1677 583 898 6445 4365
4433 2272 28,126 7473 1595 456 908 3458 3561
5542 4944 36,963 7416 1481 424 884 3829 3492
4638 4399 34,170 7123 1494 422 677 3972 3485
5615 10,483 33,927 7521 1753 472 802 3999 3880
3633 1660 35,545 7291 1786 601 1053 6471 5573
6359 2700 37,688 7500 1813 510 928 4909 4238
7222 2263 39,157 7532 1877 518 953 5034 4282
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Table 3 Specifications of liner shipping and\CER Express transportation. Year
2011 2012 2013 2014 2015 2016 2017 2018 2019 2020
Freight rate1 (USD/TEU)
Total transport time2 (h)
Opportunity cost of Capital3 (r)
CER Express
Liner
CER Express
Liner
8333 7857 7381 6905 6429 5952 5476 5000 4743 4411
1920 1920 1920 1920 1920 1920 1920 1920 1920 1920
1044 1017 989 962 934 907 879 852 830 806
1524 1524 1524 1524 1524 1524 1524 1524 1524 1524
3.86% 3.49% 3.85% 4.13% 3.36% 2.89% 3.62% 3.62% 3.33% 3.28%
Data sources: 1. Clarksons Shipping; 2. China Railway; 3. Ministry of Finance of the P. R. China.
Table 3 lists the specifications of liner shipping and CER Express transport, where the data of 2019 and 2020 are predicted. For the forecast, the following ARMA model is built.
Here, Nti (i = 1,2,3) represents the forecasted values of freight rate, total transport time of the CER Express, and capital opportunity cost, respectively. When i = 1, Eq. (26.1a) is obtained (MA (m) model), which reflects the relationship between the current and previous freight rates of the CER Express. Eq. (26.1b) is the MA (q) model illustrating the relationship between current freight rate and the error terms ( t ) of the CER Express; and Eq. (26.1c) is the ARMA (m, q) model, which reflects the relationship not only between the current and previous freight rate but also between the freight rate and the error term. 4.2. Calibration of modal split models Based on the historical freight demands of the 9 commodity categories, the modal split of the CER Express during 2011–2018 is estimated, and the results are shown in Table 4. The 3 commodity categories with the highest modal splits of the CER Express are Category 5 (Chemical Raw Materials & Chemical Products), Category 7 (Metal Smelting and Processing & Metal Products), and Category 8 (Equipment Manufacturing Products). Category 3 (Apparel, Shoes & Hats, Leather & Down Feathers), Category 4 (Wood Processing, Paper Making & Paper Products), and Category 9 (Other Manufacturing Products) are mainly transported by liner ships. Based on the transport data of liner shipping and CER Express trains during 2011–2018, the modal split model is calibrated to obtain Table 5, where R2 is the coefficient of determination, which is the regression sum of squares (SSR) to the total sum of squares (SST). The closer this value is to 1, the better the regression accuracy is. An R2 value greater than 0.9 (all greater than 0.9) shows that calibrations of the modal split model of the 9 commodity categories all have satisfactory goodness-of-fit. 4.3. Forecasting modal split of the CER Express The CER Express on-route time is assumed to be 722 h (Total transport time of CER Express - the waiting time) and the total liner Table 4 Modal splits of SER-Express during 2011–2018. Year Category
2011
2012
2013
2014
2015
2016
2017
2018
1 2 3 4 5 6 7 8 9
0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.67% 0.00%
0.00% 0.13% 0.00% 0.00% 0.72% 0.00% 0.00% 2.46% 0.00%
0.43% 0.06% 0.00% 0.04% 3.07% 0.00% 0.00% 7.34% 0.04%
2.25% 1.97% 0.01% 0.21% 10.75% 2.95% 20.06% 15.59% 0.24%
2.55% 2.84% 0.06% 0.45% 15.67% 5.60% 24.39% 23.96% 0.60%
2.98% 4.50% 0.23% 0.81% 21.45% 7.73% 26.90% 29.18% 0.94%
5.89% 10.15% 3.50% 2.24% 30.58% 12.69% 32.34% 37.64% 2.57%
10.34% 21.23% 8.18% 4.55% 36.19% 18.19% 36.67% 42.28% 5.35%
Data Sources: Ministry of Commerce of the P. R. China; 2. China Railway; 3. General Administration of Customs, P. R. China 7
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Table 5 Calibrated results of the modal split models. Category
Parameter
1 2 3 4 5
0.000812 0.000406 0.000558 0.000914 0.000198
i
(R2) (t-value)
(0.9871) (0.9731) (0.9809) (0.9800) (0.9147)
(13.1023) (10.8092) (12.1342) (11.7389) (9.2870)
Category
Parameter
6 7 8 9
0.000536 0.000466 0.000447 0.000954
i
(R2) (t-value)
(0.9920) (0.9791) (0.9293) (0.9839)
(13.6456) (12.3457) (11.9369) (12.2576)
transport time is assumed constant. The total transport time of a liner and the CER Express can be calculated according to Eq. (5) and Eq. (6), respectively. The choice of liner bunker fuel is changed globally, and the sulfur content of liner bunker fuel decreases from 3.5% to 0.5% globally while the fuel price increases from 372 USD/ton to 526 USD/ton. In ECAs, the sulfur content cap of liner bunker fuel remains 0.1%, that is, equal to previously, and the price of the 0.1% sulfur-content bunker fuel is 619 USD/ton (http:// www.cn-eship.com/SteelPrice/gjgkryjg.jsp). The CER Express freight rate is 4411 USD/TEU, while the liner shipping freight rate is determined using Eqs. (10)-(14). The utilities of the CER Express and liner shipping can then be calculated using Eqs. (2) and (4). Finally, the modal splits of the two modes can be computed using Eq. (1). Fig. 1 illustrates how the modal split of the CER-Express changes with the increment of the train frequency and the pass-through ratio of the added cost of liner shipping in the China-Europe commodity transport market. The modal splits of the CER-Express for the 9 commodity categories show different trends. When the train frequency increases from 1 shift/week to 7 shifts/week, the modal splits in transporting Category 5 (chemical raw materials & chemical products), Category 7 (metal smelting and processing & metal products) and Category 8 (equipment manufacturing products) increase substantially. When the shipping company does not pass any of the added fuel costs onto shippers, the modal splits of the CER-Express for the 3 categories increase by 39%, namely, from 52.02% to 72.14%. When the shipping company passes all of the added fuel cost onto shippers, the modal splits of the CER-Express for the 3 categories increase from 55.26% to 76.91%. The above 3 categories are all high-value commodities that are more sensitive to transport time. When transporting these commodities, higher service frequency and lower time cost make the CER-Express more competitive than liner shipping. As a result, the utility gap between the CER-Express train and liner shipping narrows, and the modal split of the CER-Express increases significantly. A small change can be observed in the modal splits of the CER-Express in transporting Category 1 (food processing & tobacco), Category 2 (textiles), Category 3 (apparel, shoes & hats, leather & down feathers), Category 4 (wood processing, paper making & paper products), Category 6 (nonmetal mineral products) and Category 9 (other manufacturing products) as the train frequency of the CER-Express increases. When the passthrough ratio of the added fuel cost is 0% as the frequency increases from 1 shift/week to 7 shifts/week, the modal splits of the CER-Express for transporting Categories 1, 2, 3 4, 6 and 9 (low-value commodities) will only increase from 14.02% to 14.43%, 26.60% to 28.90%, 17.04% to 17.65%, 7.23% to 7.89%, 30.77% to 35.27%, and 9.89% to 11.32%, respectively. All of the increases are less than 10%. When the passthrough ratio of the added fuel cost is 100%, as the train frequency increases from 1 shift/week to 7 shifts/week, the increment of the modal splits of the CER-Express for transporting these 6 commodity categories is still less than 15%. In other words, the shippers of low-value commodities are not sensitive to total transport time, and the enhancement of time effectiveness only has limited effects on the increment of the modal split of the CER-Express, while lowering the freight rate is an effective means of raising the modal split. On the other hand, when the passthrough ratio of the added fuel cost increases from 0% to 100%, the modal splits of the CERExpress in transporting Category 1 (food processing & tobacco), Category 2 (textiles), Category 3 (apparel, shoes & hats, leather & down feathers); Category 4 (wood processing, paper making & paper products), Category 6 (nonmetal mineral products) and Category 9 (other manufacturing products) increase dramatically. The largest increase occurs in Category 4. When the train frequency of the CER-Express is 1 shift/week, as the passthrough ratio increases from 0% to 100%, the modal split of the CER-Express increases by 2.43 times, from 7.23% to 26.50%. When the frequency is 7 shifts/week, as the passthrough ratio increases from 0% to 100%, the modal split of the CER-Express increases by 2.46 times, from 7.89% to 27.28%. The modal splits of the CER-Express in transporting Category 5 (chemical raw materials & chemical products), Category 7 (metal smelting and processing & metal products) and Category 8 (equipment manufacturing products) remain roughly stable with the changes in the passthrough ratio, which indicates that these 3 commodity categories are not sensitive to the freight rate and will hardly be affected by the IMO 2020. 4.4. Analysis of liner company profits Fig. 2 presents the profits of the liner shipping company in the circumstances of different frequencies of the CER-Express and different passthrough ratios. The profit of the liner shipping company is the highest when the frequency of the CER-Express is 1 shift/ week and the passthrough ratio is 40%. When the frequency increases to 2–6 shifts/week, if the shipping company wants to maximize its profits, the passthrough ratio should be 30%. Therefore, with the frequency increment of the CER-Express, shipping companies should reduce the passthrough ratio to pursue maximum profits. Table 6 lists the profits of shipping companies in the cases with and without IMO 2020. It can be found that the enforcement of sulfur emission control will reduce shipping company profits by approximately 15%. The profit decline is mainly because of the 8
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increased bunker fuel cost and the decreased revenue due to the modal split to the CER-Express. Moreover, to calculate the passthrough ratios of the added fuel cost, the shipping company evenly allocates the total added fuel cost to all the slots in a ship. However, ships are usually not fully loaded; thus, shipping companies still bear the part of the added fuel cost allocated to the unloaded slots, which will further hurt their profits.
Fig. 1. Modal splits of the CER-Express with different frequencies and passthrough ratios. 9
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Fig. 1. (continued)
4.5. Analysis of sulfur and carbon emissions The power of the HXD3 electric locomotive used for the CER-Express is 720 kw. According to the National Energy Administration of P. R. China, in 2018, 75.88% of the gross domestic electricity is generated by thermal power; the net coal consumption rate is 298.4 g/kwh; the electricity loss rate along the transmission line is 3.9%; and the sulfur content of the used coal is 1% m/m. As required by the IMO 2020, the sulfur content of bunker fuels used inside and outside the ECA are 0.1% m/m and 0.5% m/m, while the figures before IMO 2020 are 0.1% m/m and 3.5% m/m. By inserting these data into Eqs. (18) and (19), the total sulfur emission of liner ships and CER-Express trains can be calculated. Fig. 3 shows sulfur emissions under different train frequencies of the CER-Express and ratios of shipping companies passing the added fuel cost onto the shippers. Obviously, the sulfur emission decreases with the passthrough ratio decrement. The reason is that CER-Express trains will release more sulfur than liner ships when transporting the same volume of cargo. As the passthrough ratio increases, the modal split of liner shipping will decrease, while that of CER-Express trains will increase, which means that more freight demands will shift from liner shipping to the CER-Express to induce more sulfur emission. Therefore, it can be concluded that sulfur emission positively correlates with the passthrough ratio of the added fuel cost. Table 7 lists the total sulfur emissions under IMO 2020. It can be found that the new sulfur emission cap has positive effects on the reduction of sulfur emission for commodity transport between China and Europe. If the new sulfur emission cap is adopted, the total sulfur emission will decrease by over 40%. The decrease can be explained based on two aspects. First, the sulfur content of the bunker fuel decreases from 3.5% to 0.5%, which leads to a dramatic reduction of sulfur emission in maritime transportation. Second, although part of the liner shipping demand will shift to the CER-Express to generate more sulfur emission, the increment of sulfur emission due to CER-Express transport is still less than the total decrement of sulfur emission in liner shipping transport. In Eqs. (21)-(23), which are used to calculate the total CO2 emissions from liner ships and CER-Express trains, the conversion 10
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Fig. 2. Profits of shipping companies for different train frequencies and passthrough ratios.
Table 6 Shipping company’s profit comparison (million USD). CER-Express Frequency
Without IMO 2020
With IMO 2020
Growth Rate
CER-Express Frequency
Without IMO 2020
With IMO 2020
Growth Rate
1 2 3 4
126.23 123.30 122.40 121.96
105.56 103.96 103.14 102.74
−16.38% −15.68% −15.73% −15.76%
5 6 7
121.70 121.53 121.41
102.50 102.34 102.23
−15.78% −15.79% −15.80%
Fig. 3. Sulfur emissions for different train frequencies and passthrough ratios.
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Table 7 Sulfur emissions in the two cases. Train Frequency
Without
With
Growth Rate
Train Frequency
Without IMO 2020
With IMO 2020
Growth Rate
1 2 3 4
6,186 6,285 6,321 6,339
3,489 3,453 3,498 3,516
−44% −45% −45% −45%
5 6 7
6,348 6,357 6,366
3,534 3,534 3,543
−44% −44% −44%
Table 8 CO2 emissions before and after IMO 2020 in the two cases. Train Frequency
Without
With
Growth Rate
Train Frequency
Without IMO 2020
With IMO 2020
Growth Rate
1 2 3 4
943,389 967,809 976,689 981,129
1,054,409 1,045,529 1,056,629 1,061,069
12% 8% 8% 8%
5 6 7
983,349 985,569 987,789
1,065,509 1,065,509 1,067,729
8% 8% 8%
coefficients of bunker fuel and coal are set to 3.17 and 2.46 (Lee et al., 2011), respectively. Table 8 shows the calculated results in the cases with and without IMO 2020. According to Table 8, total CO2 emissions will increase by approximately 10% between China and Europe under IMO 2020. The new sulfur emissions cap is likely to have negative effects on carbon emission control because the CO2 emission of CER-Express trains is much more than that of liner ships to transport the same volume of cargo. If part of the liner shipping demand shifts to “the CER-Express, the total CO2 emission will undoubtedly increase”. 5. Conclusions Based on the modal split model and the generalized transport cost composed of freight rate, cargo on-route time, shipper waiting time and cargo value, this paper proposes an approach for calculating the modal splits of the CER-Express and liner shipping between China and Europe in the case of IMO 2020, the profits of liner shipping companies and total sulfur and CO2 emissions for commodity transportation. The parameters of the logit-based modal split model are calibrated with data on actual trade between China and Europe. Using the calibrated model, this paper analyzes the impacts of two variables, i.e., the train frequency of the CER-Express and the ratio of liner shipping companies passing added bunker fuel cost onto shippers, on the modal splits for transporting the 9 categories of commodities, the profits of the liner shipping company and the total sulfur and CO2 emissions associated with trade transport between China and Europe. To improve competitiveness, the CER-Express can be enhanced in several aspects. First, the time effectiveness of the train can be raised by reducing the on-route time and increasing the service frequency, especially when competing for highly time-sensitive cargos, such as chemical raw materials & chemical products (Category 5); metal smelting and processing & metal products (Category 7); and equipment manufacturing products (Category 8). For these time-sensitive cargos, it is more necessary to market time precision to encourage shippers to shift from liner shipping to the CER-Express. Furthermore, due to the cost increment of liner shipping, the CER-Express will be more attractive to shippers that are sensitive to freight rate increments, such as the shippers of the commodities food processing & tobacco (Category 1); textiles (Category 2); apparel, shoes & hats, leather & down feathers (Category 3); wood processing (Category 4); chemical raw materials & chemical products (Category 6); and other manufacturing products (Category 9). The modal split of the CER-Express can be further improved in transporting freight rate-sensitive commodities if the Chinese government increases the subsidies to the CER-Express. For liner shipping, passing all the added fuel cost onto shippers is not helpful for maximizing operational profits in the case of IMO 2020. According to the analysis results, liner shipping companies may obtain maximum profits when the passthrough ratio is 30%40%. However, the IMO 2020 will reduce the profits of liner shipping companies by 15%, which will be a new challenge for shipping companies. Another finding is that IMO 2020 may reduce the total sulfur emission for transporting commodities between China and Europe, but it may increase total CO2 emissions. In summary, the development of the CER-Express and the upcoming IMO 2020 will increase the competitiveness and raise the role and status of the CER-Express in the transport market between China and Europe. Faced with potentially shrinking profits, liner shipping companies should take mitigation actions to meet the challenges from the CER-Express and the new sulfur emission cap. In addition, there is no doubt that IMO 2020 will have a positive effect on sulfur emission reduction, but we should also remain vigilant against the possible increment in CO2 emissions due to the modal shift from liner shipping to CER-Express transportation. For the case study, the freight rate of the CER-Express is the actually executed price, which includes a discount by the Chinese government. Although most people expect that such a discount cannot last forever, when the subsidy will disappear cannot easily be forecast. Because the government would like to support the CER-Express until it can survive in the market via economies of scale, using the discount price will not damage the quality of the numerical analysis. On the other hand, using a fixed freight rate for liner shipping is also a minor defect of this study because the freight rate of liner shipping fluctuates significantly. However, the problem of the market shares of two transport corridors or the modal splits of two 12
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kinds of traffic modes in this study belongs to a microplanning issue rather than a daily operation one. Assigning an aggregate average value to the freight rate of liner shipping has its rationality. Actually, we do not analyze the path or mode choice of a specific shipper at a specific time but rather study the path or mode choices of a representative shipper over the long term. In this case, the freight rate of either the CER-Express or shipping should be an averaged one. Moreover, due to the ECA, shipping companies may adjust sailing routes, adopt low sulfur fuel or install scrubbers, however, due to the short of detailed data for calculating the cost increment this paper only considers the case of adaptation of low sulfur fuel. It is better for us to calculate the cost increments for all the feasible methods for dealing with the ECA and then give a weighted average value. We hope we can elaborate this issue in our future study. Acknowledgement This work was supported by the key project of Natural Science Foundation of China (Grant No. 71431001), Natural Science Foundation of Zhejiang Province of China (LY19G030012) and K.C. Wong Magna Fund in Ningbo University. Appendix A. Supplementary material Supplementary data to this article can be found online at https://doi.org/10.1016/j.tre.2020.101861. References Abadie, L.M., Goicoechea, N., Galarraga, I., 2017. Adapting the shipping sector to stricter emissions regulations: fuel switching or installing a scrubber? Transp. Res. Part D 57, 237–250. Algaba, O.B., 2014. Impact study of the new sulphur regulations on a North Sea short-sea route (Master’s thesis). DTU, Department of Transport, Kongens Lyngby, Denmark. Antturi, J., Hänninen, O., Jalkanen, J.P., Johansson, L., Prank, M., Sofiev, M., Ollikainen, M., 2016. Costs and benefits of low-Sulphur fuel standard for Baltic Sea shipping. J. Environ. Manage. 184 (Pt 2), 431–440. Brynolf, S., Magnusson, M., Fridell, E., Andersson, K., 2014. Compliance possibilities for the future ECA regulations through the use of abatement technologies or change of fuels. Transport. Res. Part D T 28 (5), 6–18. Cariou, P., Cheaitou, A., Larbi, R., Hamdan, S., 2018. Liner shipping network design with emission control areas: a genetic algorithm-based approach. Transp. Res. Part D 63, 604–621. Chen, L., Yip, T.L., Mou, J., 2017. Provision of emission control area and the impact on shipping route choice and ship emissions. Transp. Res. Part D 58, 280–291. Cheng, W., Zhang, C., 2017. Sulfur emissions control area and carbon emission reduction under the liner route optimization research. J. Central China Normal Univ. (Nat. Sci.) 51 (5), 663–670. Doudnikoff, M., Lacoste, R., 2014. Effect of a speed reduction of containerships in response to higher energy costs in Sulphur Emission Control Areas. Transp. Res. Part D 28 (5), 51–61. Dulebenets, M.A., 2017. The green vessel scheduling problem with transit time requirements in a liner shipping route with Emission Control Areas. Alexandr. Eng. J. 57 (1), 331–342. Fagerholt, K., Gausel, N.T., Rakke, J.G., Psaraftis, H., 2015. Maritime routing and speed optimization with emission control areas. Transp. Res. Part C 52, 57–73. Fagerholt, K., Psaraftis, H.N., 2015. On two speed optimization problems for ships that sail in and out of emission control areas. Transp. Res. Part D 39 (1), 56–64. Holmgren, J., Nikopoulou, Z., Ramstedt, L., Woxenius, J., 2014. Modelling modal choice effects of regulation on low-Sulphur marine fuels in Northern Europe. Transp. Res. Part D 28, 62–73. Hong, C., Zhu, X., 2019. Organizational optimization study on western outbound transportation for China Railway Express. J. Phys. Conf. Ser. 1176, 1–5. Jiang, L., Kronbak, J., Christensen, L.P., 2014. The costs and benefits of Sulphur reduction measures: sulphur scrubbers versus marine gas oil. Transp. Res. Part D 28 (2), 19–27. Kontovas, C.A., Panagakos, G, Psaraftis, H.N., Stamatopoulou, E., 2016. Being green on Sulphur: Targets, measures and side-effects. Green Transportation Logistics. Springer International Publishing, pp. 351–386. Lee, T.C., Wu, C.H., Lee, P.T.W., 2011. Impacts of the ECFA on seaborne trade volume and policy development for shipping and port industry in Taiwan. Maritime Policy Manage. 38 (2), 169–189. Li, C.P., Bo, L., Zhao, N., 2018. Measurement of Trade Potential Between China and Southeast Asian Countries and Its Determinants Based on Stochastic Frontier Gravity Model. The Theory and Practice of Finance and Economics, 39(05):124-129+149. Lindstad, H., Sandaas, I., Strømman, A.H., 2015. Assessment of cost as a function of abatement options in maritime emission control areas. Transp. Res. Part D 38, 41–48. Li, S., Lang, M., Yu, X., Zhang, M., Jiang, M., Tsai, S., Wang, C., Bian, F., 2019. A sustainable transport competitiveness analysis of the China Railway Express in the Context of the Belt and Road Initiative. Sustainability 11 (10), 1–30. Lv, J., Mao, H., 2017. Fleet deployment for liner shipping under the restriction of SOx emission control areas and CO2 emission. (Chin. Ed.). J. Dalian Marit. Univ. 43 (1), 101–105. Psaraftis, H., Kontovas, C., 2010. Balancing the economic and environmental performance of maritime transportation. Transp. Res. Part D 15, 458–462. Qin, Z., Yin, J., Cao, Z., 2017. Evaluation of effects of ship emissions control areas. Transp. Res. Rec. 2611 (1), 50–55. Schinas, O., Stefanakos, C.N., 2014. Selecting technologies towards compliance with MARPOL Annex VI: the perspective of operators. Transp. Res. Part D 28 (28), 28–40. Shibasaki, R., Azuma, T., Yoshida, T., 2016. Route choice of containership on a global scale and model development: focusing on the Suez Canal. Int. J. Transp. Econ. 43 (3), 265–290. Wu, Y., Lin, C., Huang, J., 2019. Network planning location model for China Railway Express. Transport. Res. Rec.: J. Trans. Res. Board 2673 (2), 263–274. Yang, Z.L., Zhang, D., Caglayan, O., Jenkinson, I.D., Bonsall, S., Wang, J., Huang, M., Pan, X.P., 2012. Selection of techniques for reducing shipping NOx and SOx emissions. Transp. Res. Part D 17 (6), 478–486. Zhao, Y.R., Yang, Z., Notteboom, T., 2018. Roles of China Railway Express in Sino-Euro trade transportation system. J. Dalian Maritime Univ. 44 (03), 33–40. Zhen, L., Li, M., Hu, Z., Lv, W.Y., Zhao, X., 2018. The effects of emission control area regulations on cruise shipping. Transp. Res. Part D 62, 47–63.
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Competitiveness of the China-Europe Railway Express and liner shipping under the enforced sulfur emission control convention Feng Lian, Yunzhu He, Zhongzhen Yang
T
⁎
Faculty of Maritime and Transportation, Ningbo University, Ningbo, China
ARTICLE INFO
ABSTRACT
Keywords: Sulfur emission cap China-Europe Railway Express Mode choice Total transport time Pass-through ratio
The sensitivity of the pass-through ratio of the added costs due to the enforced sulfur emission cap of liner shipping as extra fare for shippers and rail operation frequency on the competitiveness of China-Europe railway express (CER-express) and liner shipping for cargo transportation between China and Europe is analyzed. The objective is to lay a theoretical basis for liner companies to optimize the pass-through ratio for maximizing shipping profit, for CER-express to determine an expected operation frequency and for IMO to understand the effects of the enforced sulfur emission cap when CER-express is available.
1. Introduction At its 70th conference, the IMO’s Marine Environment Protection Committee (MEPC) approved a regulation coming into force on 1 January 2020 on limiting bunker fuel with sulfur content to less than 0.5% m/m globally. At the 71st conference, it was again confirmed that the new global limitation for sulfur content would be initiated on 1 January 2020, while the sulfur content of 0.1% m/ m would remain in the emission control areas (ECAs) of the Baltic Sea, the North Sea, North America and the Caribbean Sea. There is no doubt that the enforced sulfur cap will enter into force as planned, and all maritime shipping companies will have to face its implications in 2020. The enforced sulfur cap (hereafter IMO 2020) is likely to make low-sulfur fuel cost more initially than the heavy oil currently used by a majority of ships. According to Maersk, the new sulfur limit will cost Maersk Line an additional 2 billion US dollars every year. In 2018, the total revenue of Maersk Line was 39.019 billion US dollars, while its profit was only 0.22 billion US dollars (Maersk 2018 Financial Report). Compared to Maersk’s profit in 2018, the additional cost for complying with IMO 2020 is far beyond its profit. Therefore, it is impossible for shipping companies to bear all the added fuel cost alone. On 17 September 2018, Maersk Line announced that a new fuel surcharge will take effect on 1 January 2019. On 24 September 2019, following Maersk Line, two other giant lines, CMA and MSC, also announced their fuel surcharge plan. The CER Express is a new type of intercontinental trade transport mode between China and Europe. The development of the CER Express has been greatly boosted since the Belt and Road Initiative (BRI) was adopted by the Chinese government. In particular, in recent years, the number of routes and cargo volumes of the CER Express have been increasing exponentially. The data from the Ministry of Commerce of the People’s Republic of China show that train journeys increased from 7 in 2011 to 6300 in 2018. The “China Railway Express Construction and Development Plan (2016–2020)” shows that 5000 CER Express train journeys will be operated in 2020. However, this projected number was actually fulfilled in 2018. By the end of 2018, there were 61 CER Express routes linking 56 Chinese cities with 49 cities in 15 European countries. The one-way trip time of the CER Express train has been
⁎
Corresponding author. E-mail address: [email protected] (Z. Yang).
https://doi.org/10.1016/j.tre.2020.101861 Received 15 August 2019; Received in revised form 19 December 2019; Accepted 27 January 2020 Available online 29 February 2020 1366-5545/ © 2020 Elsevier Ltd. All rights reserved.
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shortened by 30% to 12–14 days, while in the initial stage, it was approximately 20 days. The freight rate of a whole journey has dropped by approximately 40% (data from the Ministry of Commerce of the People’s Republic of China). It can rationally be said that at present and in the future, the CER Express is a competitor of liner shipping between China and Europe. In the transport market between China and Europe, the transport time and fare of different transport modes differ greatly. When the CER Express was unavailable, maritime shipping and air transport rarely competed with each other. As a result, few studies on the competition among China-Europe trade transport modes can be found. The CER-Express is a stronger competitor to liner shipping in terms of transport time (Li et al., 2019) and freight rate because the utility difference between the two modes is not big enough. Moreover, after IMO 2020, the competitiveness of the CER Express may be further consolidated because emission control will increase the bunker fuel cost of liner companies past the cost ceiling that liner companies are able to afford; thus, they will inevitably pass some or all of this additional cost onto shippers. In contrast, with the advancement of the BRI, the transport time of the CER Express continues to decrease, and the service frequency continues to increase, which reduces both waiting times and fares for the shippers. As a result, liner shipping will become less competitive, and shippers may be more likely to choose the CER Express. The mode choice of shippers depends on the utility of the modes, while the mode utility is jointly determined by cargo attributes and the generalized transport cost, which is an integration of transport time and fare. In the near future, all the relative influencing factors of the two modes may change, such as the IMO 2020, the fast growth of the CER Express, and the diversification of ChinaEurope trade commodities. Therefore, it is necessary to study how the pass-through ratio of the added fuel cost to shippers and the change in train frequency affect the modal split in transporting the trade commodities, liner companies’ profits and sulfur and CO2 emissions. In this context, this study makes a threefold contribution to the literature. First, we study ECAs’ impact on the business strategies of liner shipping companies in the case of a fungible mode is available. Existing studies have mainly studied shipping route design or bunker fuel adoption due to the ECA under the assumption that only ocean shipping is available, which means the intercontinental shipping market is a closed market. Shipping companies could adopt measures with the objective of minimizing total cost. However, due to the availability of the CER-Express, the freight transport market between China and Europe is not closed for liner shipping and existing studying results are not correct anymore. Therefore, instead of cost minimization, this paper studies the strategies of liner shipping companies for dealing with ECA with the aim of profit maximization. Second, this paper considers the roles of the value of time for different commodities in shippers’ mode choices, which complexes the model but makes it more useful and realistic Based on the value of time, in our study the commodities are divided into 9 categories. In this way, by model analysis we can illustrate the different business strategies being adopted by shipping companies for different market segments, which may result in different emission control effects. Third, our method can reveal the relationship between shipping profits and the combination of rail operating frequencies and shipping companies’ pass-through ratios in term of different kinds of commodity categories. It is helpful for shipping companies or the CER-Express in designing their service specifications and marking strategies. The remainder of this paper is organized as follows. Section 2 provides a literature review to show the research gap and lay background for our paper. Section 3 gives the methods to calculate the transport cost of liner shipping and the CER-Express between China and Europe, the modal splits and the emission from the transportation. Section 4 presents the calculation results and the extensive analysis of sensitivities of pass-through ratio of the added cost and the rail operation frequency. A summary and directions for future research are presented in Section 5. 2. Literature review There have been many papers on the topic of sulfur emission control in the maritime sector; these papers have studied the issue mainly from three points of view: (1) the impacts of emission control areas (ECAs) on vessel speed and routing; (2) the impacts of ECAs on modal splits; and (3) the measures shipping companies take to meet the sulfur control regulation. Vessels are required to use low-sulfur bunker fuels or operate sulfur scrubbers in ECAs, which will increase the operation cost for shipping companies. Because sailing speed is the key variable determining the bunker fuel cost, shipping companies usually make vessels sail with different speeds inside and outside ECAs. To meet the expected sailing time, liner shipping companies need to optimize the speed combination. Fagerholt and Psaraftis (2015) analyzed different vessel speeds inside and outside ECAs to reduce fuel cost with a constant total on-route time. A similar problem was also discussed by Doudnikoff and Lacoste (2014), who thought that deceleration in ECAs and acceleration outside ECAs could reduce the total cost without changing the total on-route time but at the expense of increasing CO2 emissions. Qin et al. (2017) estimated ECAs’ effectiveness on the reduction of SO2 and CO2 emissions in the Shanghai port area with the assumption of an ECA being a reduced speed zone. It is shown that in the port area of Shanghai for the year 2020, a reduction in SO2 emissions by at least 103,998 tons may be achieved with the 12-nmi ECA, CO2 emissions may be reduced by 827,733 tons with a 12-knot speed limit in the 12-nmi ECA, and an additional SO2 reduction of 522.23 tons can be achieved by slow steaming. Cariou et al. (2018) established a mixed-integer linear programming model to maximize shipping company profit with a series of decision variables, such as port-of-call selection and sequence, cargo flow between ports, number of ships and sailing speed on each segment. Their model solved the problem of how to balance the cost and the sulfur emission. Aiming at minimizing the total cost composed of liner fleet cost and carbon emission cost, Cheng and Zhang (2017) employed a mixed-integer linear programming model to compare the total costs in two scenarios of using identical/different sailing speeds inside and outside ECAs. They found that using different sailing speeds could reduce the total operating cost. They also studied the impacts of ECA length and carbon tax rate on a liner’s total cost. To minimize liner operating cost and CO2 cost, Lv and Mao (2017) used ship size, number of ships and sailing speed 2
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as decision variables to establish a nonlinear programming model to optimize the speed combination and fleet deployment. Zhen et al. (2018) optimized the speeds, the sailing patterns and the port-of-call sequence for a cruiser voyage with the aim of reducing fuel costs. The numerical test based on real-world data of cruise lines is done to explore the effects of ECA regulations on cruise shipping. With regard to the impacts of ECAs on maritime routing, Fagerholt et al. (2015) stated that ECAs would change route choices, especially for long-distance voyages, on which ships would take detours to avoid the ECAs. In certain situations, the establishment of ECAs will, in contrast, increase sulfur emissions because of those detours. The authors noted that the impact of ECAs on maritime routing had a positive correlation with the price gap between marine gas oil (MGO) and heavy fuel oil (HFO). The opinion that ECAs will change ship routing is also supported by Chen et al. (2017). They analyzed the route-choosing behaviors of liner shipping through the ECA in the Mediterranean by targeting the Asia-Europe route. It was revealed that a large number of ships will re-route around the ECA, and regional emissions will be excessive under certain conditions, while small ships are more likely to re-route than are large ships. Dulebenets (2017) investigated the problem of ship scheduling under the constraint of ECA emission and on-route time requirement. They found that ships were inclined to decelerate on some segments to reduce the total fuel cost but eventually had to pay extra penalties because of the induced delay. The first type of study assumes that shipping freight demands are unchanged (which means that the shipping income of liner companies are fixed), and then optimizes the route or path of a single ship to minimize its total operation costs, and estimates the emissions of CO2 and SO2. In the context of no substitute service for liner shipping, the studying results are correct and can be adopted by shipping company. In the case that the CER-Express is available, any changes (path or freight rate) of liner shipping may induce changes in shipping freight demand and further shipping income of the liner companies. Therefore, instead of cost minimization, it is necessary to study the business strategies of liner companies for dealing with ECA with the aim of profit maximization. Concerning the impacts on modal splits, Algaba (2014) studied the impact of the sulfur emission control convention on short-sea transport in the North Sea and found that lowering vessel speed would push cargos to shift from maritime shipping to other transport alternatives. Kontovas et al. (2016) studied the impacts of the sulfur emission control convention on the modal splits between intermodal transport and highway transport. They found that the sulfur emission control convention would decrease the mode share of intermodal transport but increase that of highway transport. Holmgren et al. (2014) analyzed the impacts of the sulfur emission control convention on the path choice of high-value cargos from eastern Lithuania to western United Kingdom, and the results indicated that the modal shift from sea shipping to highway transport would be unlikely even if the ECAs were set. To recognize the competition of the Suez Canal with other routes, Shibasaki et al. (2016) focus on the share of its transit in the container shipping market on a global scale to estimate the shares’ difference in the years 2010 and 2013 using an aggregated logit model. The second type of literature has indeed analyzed ECA impacts on modal splits and proved that the sulfur emission control convention will decrease shipping’s modal split. The existing studies have taken the added costs due to the sulfur emission control convention as the decrement of shipping utility directly. Because shipping companies may not pass all the added cost onto shippers, the estimated mode share of shipping transport would be smaller than the actual one. Therefore, it is necessary for us to analyze the modal splits in the cases of shipping companies not passing all the added costs because they want to maximize the profit. In the literature on emission control measures, Lindstad et al. (2015) claimed that ship engine size, annual fuel consumption in ECAs and future fuel price are the main influencing factors of abatement for sulfur emission. In terms of costs and benefits, Jiang et al. (2014) compared two measures for sulfur emission control, namely, using sulfur scrubbers or maritime gas oil, and found that the price gap was the determining factor in the selection of the two measures. Yang et al. (2012) assessed several emission control measures with the analytic hierarchy process and concluded that changing bunker fuel was the desirable solution to comply with the sulfur emission control convention, but sulfur scrubbers could be the best solution in the future if sulfur emission control became more stringent. Brynolf et al. (2014) proposed three fuel alternatives complying with the ECA emission regulation. They used lifecycle assessment to comparatively analyze the three alternatives and found that none of them could significantly reduce CO2 emissions compared to heavy fuel oil (HFO), but they could decrease the emissions of particulate matter, photochemical ozone formation, acidification and terrestrial eutrophication potential. Schinas and Stefanakos (2014) presented a multicriterion approach based on the analytic network process (ANP), which could reveal the preferences and relationships among criteria, to help shipping companies choose the necessary technology alternatives. Abadie et al. (2017) evaluated the economic gap between the two main techniques (namely, changing bunker fuel or using sulfur scrubbers) currently used by the shipping industry by accounting for the factors of fuel spot and future prices, the cost for installing scrubbers, vessel on-route time in ECA and the remaining lifetime of vessels. Based on the ECA regulation for Baltic Sea shipping, Antturi et al. (2016) first compared the costs of the measures of using low sulfur fuel and installing sulfur scrubbers for shipping companies. Then, they evaluated the benefits of the selected abatement measure through a high-resolution impact pathway analysis, taking into account the formation and dispersion of emissions, and considered the positive health impacts resulting from lowered ambient PM2.5 concentrations. The results showed that for the Baltic Sea, the new sulfur emission regulation was not cost effective because the cost paid by shipping companies was far more than the benefit to the environment. In the last type of study, which has the largest volume, the technical issues of bunker fuel adoption and sulfur scrubber installation have been studied, while factors beyond ship operation are excluded. They are essential; however, because shippers, competitors, network and transport routes are excluded, the results could only be used for vessel management rather than business strategies or emission analysis of the ECA. It is necessary to study the effects of the enforced sulfur emission cap on business strategy of liner shipping companies and emission reduction in micro level by taking account the relationships between shippers and carriers as well as the competition between the two kinds of carriers into account.
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In fact, under IMO 2020, liner shipping companies will inevitably encounter higher fuel costs or additional costs for installing sulfur scrubbers. Passing a part but not all of the added cost onto shippers may be a key decision of the liner companies. Therefore, we can rationally say that because the CER-Express is available, the impacts of the sulfur emission control convention on the competitiveness of liner shipping between China and Europe needs to be studied in the context of liner companies wanting to maximize their operation profit. In this context, we attempt to study the competitive relationship between liner shipping and the CER Express in the China-Europe cargo transport market by analyzing the impacts of the IMO 202 and CER Express development on shippers’ mode choices. Furthermore, we explore the impacts of the control convention on the sulfur and carbon emissions of China-Europe trade transport. 3. Model building 3.1. Problem description Per IMO 2020, maritime fuels are required to meet the sulfur content limitation of 0.5% m/m in the whole ocean area and a more stringent limitation of 0.1% m/m in specific ECAs, which is believed to cost shipping companies more for bunker fuel alternatives. The added cost may be too much for shipping companies to bear by themselves; thus, they will have to pass a part of these costs onto shippers by levying a bunker surcharge. In other words, shippers’ maritime shipping cost will increase. In contrast, due to the BRI the railway transport cost between China and Europe is decreasing because the CER-Express has gradually gained financial and political support from Chinese government as an important mode between China and Europe (Wu et al., 2019), and has been developing faster and faster (Hong and Zhu, 2019). When comparing the two aforementioned transport modes in the China-Europe freight market, shippers will observe decreased utility of liner shipping and increased utility of the CER Express. Consequently, some shippers may be likely to shift from liner shipping to CER Express transport. To analyze the impacts of IMO 2020 and CER Express development on the modal shift, the profits of liner companies and the sulfur and carbon emissions in the China-Europe freight transport market, first, the general transport cost must be decomposed into two parts, namely, total transport time (including on-route time and waiting time) and total transport fare. Second, the modal split model must be calibrated. Finally, the modal split of the CER Express, the profits of liner companies, and the sulfur and carbon emissions with regard to the passthrough ratio of the added cost onto shippers and the increment of the train frequency of the CER Express in the China-Europe freight market must be calculated. 3.2. Methodology Based on the following facts about the China-Europe trade transport system, a shipper’s mode choice behaviors will be analyzed. A1: A2: A3: A4: A5:
The capacity of a liner ship is 18,000 TEUs. Train capacity of the CER Express is 84 TEUs. Sailing speed of a liner ship is 20 knots. All the freight demands of China-Europe trade should be served. The CER Express train uses HXD3 electric locomotives.
The probability of choosing an alternative will increase with its utility increment (Psaraftis and Kontovas, 2010); therefore, the probability of choosing a given mode can be calculated by Eq. (1) (Kontovas et al., 2016).
Pi, k = Exp ( i Vi, k )/
k = 1,2
Exp ( i Vi, k )
(1)
Here, Pi, k is the probability that mode k is selected for commodity i; Vi, k is the utility of mode k for transporting commodity i; i is a parameter to be calibrated; and k is a binary variable (0 denotes liner shipping, and 1 denotes CER Express). The utility can be calculated as follows:
Vi, k = - Ci, k
(2)
Ci, k = Fk + ui Tk
(3)
ui = Mi r/(24 × 365)
(4)
where Ci, k is the generalized transport cost of mode k for transporting commodity i; Fk is the roundtrip freight rate of mode k; Tk is the total transport time of mode k for a round trip; ui is a positive constant directly proportional to the value of commodity i, which has been estimated in our former studies (Zhao et al., 2018); Mi is the money value of commodity I (USD/TEU); and r is the opportunity cost of the shipper’s capital. In practice, r is regarded as the annual return rate on risk-free investment and is usually denoted by the interest rate of long-term government bonds. (5)
Tk = Ttk + Wtk
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(6)
Wtk = 168/ fk /2
Here, Ttk is the on-route time of mode k, Wtk is the waiting time of mode k, and fk (shift/week) is the train frequency of the CER Express. As a week totals 168 h, Wtk is equal to 168/ fk /2 (Zhao et al., 2018). (7)
Tt1 = T1, ECA + T1, OUT
T1, ECA =
T1, OUT =
d1, ECA v
d1
(8)
d1, ECA v
(9)
Eq. (7) is used to calculate the liner ship on-route time, which consists of the time (T1, ECA ) in ECAs and the time (T1, OUT ) outside the ECAs. In Eqs. (8) and (9), d1, ECA is the sailing distance in the ECA; d1 is the total sailing distance of the whole voyage; and v is liner shipping sailing speed.
M1, ECA = FH (v/ vd )3
T1, ECA 24
(10)
M1, OUT = FH (v / vd )3
T1, OUT 24
(11)
Eqs. (10) and (11) present fuel consumption inside and outside the ECAs, respectively (Doudnikoff and Lacoste, 2014). FH is the daily fuel consumption when operating under designated speed vd .
FH = (Sfoc × El × WS )
24 106
(12)
Here, Sfoc is the fuel consumption rate of the main engine of the liner ship, and El and Ws are the load and power of the main engine, respectively. (13)
C1, fuel = P1, OUT M1, OUT + P1, ECA M1, ECA
Here, C1, fuel is the total fuel cost, and P1, ECA , P1, OUT are the prices of bunker fuels used inside and outside the ECAs, respectively.
F1 = µ
(C1, fuel
C1, )
18000
+ F1,
(14)
Eq. (14) is used to calculate the liner shipping unit freight rate after IMO 2020 takes effect; the value equals the sum of the previous unit freight rate F1, and the added cost for the expensive bunker fuel. The added cost for liner shipping equals the prorated fuel cost increment per TEU multiplied by the passthrough ratioµ . C1, is the previous fuel cost.
DiPik
Dk =
(15)
i
n=
f1 T1
(16)
24 × 7
Here, Dk is the transport volume of mode k, and used to determine the number of liner ships needed.
Di
REV = D1 F1
f1 C1, fuel
is the freight demand of commodity i between China and Europe. Eq. (16) is (17)
n (Cfc + Copex )
Here, REV is the weekly profit from transporting commodity i by liner ship. Cfc and Copex are the weekly capital cost and operating cost of the liner ship, respectively.
EMIS =
EMIS0 =
EMISk k
(18)
PW × Tt 0 × Ratio × ratecoal D × PPMcoal × o 106 × (1 rateloss ) 84
(19) (20)
EMIS1 = PPM1, OUT M1, OUT + PPM1, ECA M1, ECA
Here, EMIS is the total sulfur emission from CER Express trains and liner ships. Eq. (19) is used to calculate the sulfur emission from the CER Express train. PW is the power of the CER Express train. Ratio is the percentage of thermal power generation of the total domestic electricity production. ratecoal is the net coal consumption rate in thermal power generation. rateloss is the electricity loss rate during transmission. PPMcoal is the sulfur content of coal. Eq. (20) is used to calculate the sulfur emission of the liner ship. PPM1, ECA and PPM1, OUT are the sulfur content of the bunker fuels used in and out of the ECA.
EMIC =
EMICk
(21)
k
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Table 1 Commodity categories used for the case study. Category
Commodity
China Customs Code
Value (USD/TEU)
1 2 3 4 5 6 7 8 9
Food processing & tobacco Textiles Apparel, Shoes & Hats, Leather & Down Feathers Wood Processing, Paper Making & Paper Products Chemical Raw Materials & Chemical Products Nonmetal Mineral Products Metal Smelting and Processing & Metal Products Equipment Manufacturing Products Other Manufacturing Products
1–26 50–60,63 41–43,61,62,64,65 44–49 27–40 68–70 71–83 84–91,93 66,67,92,94–97
41,562 20,211 86,957 21,355 522,977 41,667 769,231 1,111,111 149,254
Data Source: General Administration of Customs, P.R. China
EMIC0 =
D PW × TT0 × Ratio × ratecoal × CCcoal × o 106 × (1 rateloss ) 84
(22) (23)
EMIC1 = (M1, OUT + M1, ECA ) × CCfuel
Here, EMIC is the total CO2 emission from liner ships and CER Express trains, and EMICk is the CO2 emission from mode k. Eqs. (22) and (23) are used to estimate the CO2 emissions of CER Express trains and liner ships, respectively. CCcoal and CCfuel are the conversion coefficients of coal and bunker fuel, respectively. 4. Numerical study 4.1. Data sources Based on the commodity clustering method proposed by Lee, Wu & Lee (2011), we group 97 kinds of import and export commodities in the statistical data of Chinese Customs into 9 categories, which are listed in Table 1 and are used for the empirical study. In fact, the grouping has taken the commodity and value proximities into account, which are the factors affecting their transportation utilities. Table 2 presents the freight demands of the 9 categories of commodities between China and Europe in 2011–2020, in which the 2011–2018 data are from the Ministry of Commerce of the People’s Republic of China, and the 2019–2020 data are forecasted by using the stochastic frontier gravity model (Li, et al., 2018) as follows.
Intradeit = dit =
i0
+
i1 Ingdp1t
+
i2 Ingdp2t
+
i3 Ind1t
+
i 4 Inpop1t
+
i5 Inpop2t
(24)
+ vit
Intradeit Mi
(25)
In Eq. (24), tradeit is the trade volume of category i between China and Europe in year t (USD); gdp1t and gdp2t are the GDP of China and Europe, respectively, in year t (USD); d1t is the transport distance between China and Europe (km); pop1t and pop2t are the population in China and Europe in year t (100 million persons), respectively; and vit is a random error term. im (m = 0, 1, 2, 3, 4, 5) is the parameter to be calibrated. In Eq. (25), dit is the freight demand of category i between China and Europe in year t, and Mi is the cargo value of category i (USD/TEU). Table 2 Freight demands between China and Europe in 2011–2020 (TEU/Week). Year Category
2011
2012
2013
2014
2015
2016
2017
2018
2019
2020
1 2 3 4 5 6 7 8 9
2034 8770 7510 7035 1350 461 770 4088 4304
2177 7505 7369 6573 1325 434 669 3808 4073
2657 28,732 7975 8589 1677 583 898 6445 4365
4433 2272 28,126 7473 1595 456 908 3458 3561
5542 4944 36,963 7416 1481 424 884 3829 3492
4638 4399 34,170 7123 1494 422 677 3972 3485
5615 10,483 33,927 7521 1753 472 802 3999 3880
3633 1660 35,545 7291 1786 601 1053 6471 5573
6359 2700 37,688 7500 1813 510 928 4909 4238
7222 2263 39,157 7532 1877 518 953 5034 4282
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Table 3 Specifications of liner shipping and\CER Express transportation. Year
2011 2012 2013 2014 2015 2016 2017 2018 2019 2020
Freight rate1 (USD/TEU)
Total transport time2 (h)
Opportunity cost of Capital3 (r)
CER Express
Liner
CER Express
Liner
8333 7857 7381 6905 6429 5952 5476 5000 4743 4411
1920 1920 1920 1920 1920 1920 1920 1920 1920 1920
1044 1017 989 962 934 907 879 852 830 806
1524 1524 1524 1524 1524 1524 1524 1524 1524 1524
3.86% 3.49% 3.85% 4.13% 3.36% 2.89% 3.62% 3.62% 3.33% 3.28%
Data sources: 1. Clarksons Shipping; 2. China Railway; 3. Ministry of Finance of the P. R. China.
Table 3 lists the specifications of liner shipping and CER Express transport, where the data of 2019 and 2020 are predicted. For the forecast, the following ARMA model is built.
Here, Nti (i = 1,2,3) represents the forecasted values of freight rate, total transport time of the CER Express, and capital opportunity cost, respectively. When i = 1, Eq. (26.1a) is obtained (MA (m) model), which reflects the relationship between the current and previous freight rates of the CER Express. Eq. (26.1b) is the MA (q) model illustrating the relationship between current freight rate and the error terms ( t ) of the CER Express; and Eq. (26.1c) is the ARMA (m, q) model, which reflects the relationship not only between the current and previous freight rate but also between the freight rate and the error term. 4.2. Calibration of modal split models Based on the historical freight demands of the 9 commodity categories, the modal split of the CER Express during 2011–2018 is estimated, and the results are shown in Table 4. The 3 commodity categories with the highest modal splits of the CER Express are Category 5 (Chemical Raw Materials & Chemical Products), Category 7 (Metal Smelting and Processing & Metal Products), and Category 8 (Equipment Manufacturing Products). Category 3 (Apparel, Shoes & Hats, Leather & Down Feathers), Category 4 (Wood Processing, Paper Making & Paper Products), and Category 9 (Other Manufacturing Products) are mainly transported by liner ships. Based on the transport data of liner shipping and CER Express trains during 2011–2018, the modal split model is calibrated to obtain Table 5, where R2 is the coefficient of determination, which is the regression sum of squares (SSR) to the total sum of squares (SST). The closer this value is to 1, the better the regression accuracy is. An R2 value greater than 0.9 (all greater than 0.9) shows that calibrations of the modal split model of the 9 commodity categories all have satisfactory goodness-of-fit. 4.3. Forecasting modal split of the CER Express The CER Express on-route time is assumed to be 722 h (Total transport time of CER Express - the waiting time) and the total liner Table 4 Modal splits of SER-Express during 2011–2018. Year Category
2011
2012
2013
2014
2015
2016
2017
2018
1 2 3 4 5 6 7 8 9
0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.67% 0.00%
0.00% 0.13% 0.00% 0.00% 0.72% 0.00% 0.00% 2.46% 0.00%
0.43% 0.06% 0.00% 0.04% 3.07% 0.00% 0.00% 7.34% 0.04%
2.25% 1.97% 0.01% 0.21% 10.75% 2.95% 20.06% 15.59% 0.24%
2.55% 2.84% 0.06% 0.45% 15.67% 5.60% 24.39% 23.96% 0.60%
2.98% 4.50% 0.23% 0.81% 21.45% 7.73% 26.90% 29.18% 0.94%
5.89% 10.15% 3.50% 2.24% 30.58% 12.69% 32.34% 37.64% 2.57%
10.34% 21.23% 8.18% 4.55% 36.19% 18.19% 36.67% 42.28% 5.35%
Data Sources: Ministry of Commerce of the P. R. China; 2. China Railway; 3. General Administration of Customs, P. R. China 7
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Table 5 Calibrated results of the modal split models. Category
Parameter
1 2 3 4 5
0.000812 0.000406 0.000558 0.000914 0.000198
i
(R2) (t-value)
(0.9871) (0.9731) (0.9809) (0.9800) (0.9147)
(13.1023) (10.8092) (12.1342) (11.7389) (9.2870)
Category
Parameter
6 7 8 9
0.000536 0.000466 0.000447 0.000954
i
(R2) (t-value)
(0.9920) (0.9791) (0.9293) (0.9839)
(13.6456) (12.3457) (11.9369) (12.2576)
transport time is assumed constant. The total transport time of a liner and the CER Express can be calculated according to Eq. (5) and Eq. (6), respectively. The choice of liner bunker fuel is changed globally, and the sulfur content of liner bunker fuel decreases from 3.5% to 0.5% globally while the fuel price increases from 372 USD/ton to 526 USD/ton. In ECAs, the sulfur content cap of liner bunker fuel remains 0.1%, that is, equal to previously, and the price of the 0.1% sulfur-content bunker fuel is 619 USD/ton (http:// www.cn-eship.com/SteelPrice/gjgkryjg.jsp). The CER Express freight rate is 4411 USD/TEU, while the liner shipping freight rate is determined using Eqs. (10)-(14). The utilities of the CER Express and liner shipping can then be calculated using Eqs. (2) and (4). Finally, the modal splits of the two modes can be computed using Eq. (1). Fig. 1 illustrates how the modal split of the CER-Express changes with the increment of the train frequency and the pass-through ratio of the added cost of liner shipping in the China-Europe commodity transport market. The modal splits of the CER-Express for the 9 commodity categories show different trends. When the train frequency increases from 1 shift/week to 7 shifts/week, the modal splits in transporting Category 5 (chemical raw materials & chemical products), Category 7 (metal smelting and processing & metal products) and Category 8 (equipment manufacturing products) increase substantially. When the shipping company does not pass any of the added fuel costs onto shippers, the modal splits of the CER-Express for the 3 categories increase by 39%, namely, from 52.02% to 72.14%. When the shipping company passes all of the added fuel cost onto shippers, the modal splits of the CER-Express for the 3 categories increase from 55.26% to 76.91%. The above 3 categories are all high-value commodities that are more sensitive to transport time. When transporting these commodities, higher service frequency and lower time cost make the CER-Express more competitive than liner shipping. As a result, the utility gap between the CER-Express train and liner shipping narrows, and the modal split of the CER-Express increases significantly. A small change can be observed in the modal splits of the CER-Express in transporting Category 1 (food processing & tobacco), Category 2 (textiles), Category 3 (apparel, shoes & hats, leather & down feathers), Category 4 (wood processing, paper making & paper products), Category 6 (nonmetal mineral products) and Category 9 (other manufacturing products) as the train frequency of the CER-Express increases. When the passthrough ratio of the added fuel cost is 0% as the frequency increases from 1 shift/week to 7 shifts/week, the modal splits of the CER-Express for transporting Categories 1, 2, 3 4, 6 and 9 (low-value commodities) will only increase from 14.02% to 14.43%, 26.60% to 28.90%, 17.04% to 17.65%, 7.23% to 7.89%, 30.77% to 35.27%, and 9.89% to 11.32%, respectively. All of the increases are less than 10%. When the passthrough ratio of the added fuel cost is 100%, as the train frequency increases from 1 shift/week to 7 shifts/week, the increment of the modal splits of the CER-Express for transporting these 6 commodity categories is still less than 15%. In other words, the shippers of low-value commodities are not sensitive to total transport time, and the enhancement of time effectiveness only has limited effects on the increment of the modal split of the CER-Express, while lowering the freight rate is an effective means of raising the modal split. On the other hand, when the passthrough ratio of the added fuel cost increases from 0% to 100%, the modal splits of the CERExpress in transporting Category 1 (food processing & tobacco), Category 2 (textiles), Category 3 (apparel, shoes & hats, leather & down feathers); Category 4 (wood processing, paper making & paper products), Category 6 (nonmetal mineral products) and Category 9 (other manufacturing products) increase dramatically. The largest increase occurs in Category 4. When the train frequency of the CER-Express is 1 shift/week, as the passthrough ratio increases from 0% to 100%, the modal split of the CER-Express increases by 2.43 times, from 7.23% to 26.50%. When the frequency is 7 shifts/week, as the passthrough ratio increases from 0% to 100%, the modal split of the CER-Express increases by 2.46 times, from 7.89% to 27.28%. The modal splits of the CER-Express in transporting Category 5 (chemical raw materials & chemical products), Category 7 (metal smelting and processing & metal products) and Category 8 (equipment manufacturing products) remain roughly stable with the changes in the passthrough ratio, which indicates that these 3 commodity categories are not sensitive to the freight rate and will hardly be affected by the IMO 2020. 4.4. Analysis of liner company profits Fig. 2 presents the profits of the liner shipping company in the circumstances of different frequencies of the CER-Express and different passthrough ratios. The profit of the liner shipping company is the highest when the frequency of the CER-Express is 1 shift/ week and the passthrough ratio is 40%. When the frequency increases to 2–6 shifts/week, if the shipping company wants to maximize its profits, the passthrough ratio should be 30%. Therefore, with the frequency increment of the CER-Express, shipping companies should reduce the passthrough ratio to pursue maximum profits. Table 6 lists the profits of shipping companies in the cases with and without IMO 2020. It can be found that the enforcement of sulfur emission control will reduce shipping company profits by approximately 15%. The profit decline is mainly because of the 8
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increased bunker fuel cost and the decreased revenue due to the modal split to the CER-Express. Moreover, to calculate the passthrough ratios of the added fuel cost, the shipping company evenly allocates the total added fuel cost to all the slots in a ship. However, ships are usually not fully loaded; thus, shipping companies still bear the part of the added fuel cost allocated to the unloaded slots, which will further hurt their profits.
Fig. 1. Modal splits of the CER-Express with different frequencies and passthrough ratios. 9
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Fig. 1. (continued)
4.5. Analysis of sulfur and carbon emissions The power of the HXD3 electric locomotive used for the CER-Express is 720 kw. According to the National Energy Administration of P. R. China, in 2018, 75.88% of the gross domestic electricity is generated by thermal power; the net coal consumption rate is 298.4 g/kwh; the electricity loss rate along the transmission line is 3.9%; and the sulfur content of the used coal is 1% m/m. As required by the IMO 2020, the sulfur content of bunker fuels used inside and outside the ECA are 0.1% m/m and 0.5% m/m, while the figures before IMO 2020 are 0.1% m/m and 3.5% m/m. By inserting these data into Eqs. (18) and (19), the total sulfur emission of liner ships and CER-Express trains can be calculated. Fig. 3 shows sulfur emissions under different train frequencies of the CER-Express and ratios of shipping companies passing the added fuel cost onto the shippers. Obviously, the sulfur emission decreases with the passthrough ratio decrement. The reason is that CER-Express trains will release more sulfur than liner ships when transporting the same volume of cargo. As the passthrough ratio increases, the modal split of liner shipping will decrease, while that of CER-Express trains will increase, which means that more freight demands will shift from liner shipping to the CER-Express to induce more sulfur emission. Therefore, it can be concluded that sulfur emission positively correlates with the passthrough ratio of the added fuel cost. Table 7 lists the total sulfur emissions under IMO 2020. It can be found that the new sulfur emission cap has positive effects on the reduction of sulfur emission for commodity transport between China and Europe. If the new sulfur emission cap is adopted, the total sulfur emission will decrease by over 40%. The decrease can be explained based on two aspects. First, the sulfur content of the bunker fuel decreases from 3.5% to 0.5%, which leads to a dramatic reduction of sulfur emission in maritime transportation. Second, although part of the liner shipping demand will shift to the CER-Express to generate more sulfur emission, the increment of sulfur emission due to CER-Express transport is still less than the total decrement of sulfur emission in liner shipping transport. In Eqs. (21)-(23), which are used to calculate the total CO2 emissions from liner ships and CER-Express trains, the conversion 10
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Fig. 2. Profits of shipping companies for different train frequencies and passthrough ratios.
Table 6 Shipping company’s profit comparison (million USD). CER-Express Frequency
Without IMO 2020
With IMO 2020
Growth Rate
CER-Express Frequency
Without IMO 2020
With IMO 2020
Growth Rate
1 2 3 4
126.23 123.30 122.40 121.96
105.56 103.96 103.14 102.74
−16.38% −15.68% −15.73% −15.76%
5 6 7
121.70 121.53 121.41
102.50 102.34 102.23
−15.78% −15.79% −15.80%
Fig. 3. Sulfur emissions for different train frequencies and passthrough ratios.
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Table 7 Sulfur emissions in the two cases. Train Frequency
Without
With
Growth Rate
Train Frequency
Without IMO 2020
With IMO 2020
Growth Rate
1 2 3 4
6,186 6,285 6,321 6,339
3,489 3,453 3,498 3,516
−44% −45% −45% −45%
5 6 7
6,348 6,357 6,366
3,534 3,534 3,543
−44% −44% −44%
Table 8 CO2 emissions before and after IMO 2020 in the two cases. Train Frequency
Without
With
Growth Rate
Train Frequency
Without IMO 2020
With IMO 2020
Growth Rate
1 2 3 4
943,389 967,809 976,689 981,129
1,054,409 1,045,529 1,056,629 1,061,069
12% 8% 8% 8%
5 6 7
983,349 985,569 987,789
1,065,509 1,065,509 1,067,729
8% 8% 8%
coefficients of bunker fuel and coal are set to 3.17 and 2.46 (Lee et al., 2011), respectively. Table 8 shows the calculated results in the cases with and without IMO 2020. According to Table 8, total CO2 emissions will increase by approximately 10% between China and Europe under IMO 2020. The new sulfur emissions cap is likely to have negative effects on carbon emission control because the CO2 emission of CER-Express trains is much more than that of liner ships to transport the same volume of cargo. If part of the liner shipping demand shifts to “the CER-Express, the total CO2 emission will undoubtedly increase”. 5. Conclusions Based on the modal split model and the generalized transport cost composed of freight rate, cargo on-route time, shipper waiting time and cargo value, this paper proposes an approach for calculating the modal splits of the CER-Express and liner shipping between China and Europe in the case of IMO 2020, the profits of liner shipping companies and total sulfur and CO2 emissions for commodity transportation. The parameters of the logit-based modal split model are calibrated with data on actual trade between China and Europe. Using the calibrated model, this paper analyzes the impacts of two variables, i.e., the train frequency of the CER-Express and the ratio of liner shipping companies passing added bunker fuel cost onto shippers, on the modal splits for transporting the 9 categories of commodities, the profits of the liner shipping company and the total sulfur and CO2 emissions associated with trade transport between China and Europe. To improve competitiveness, the CER-Express can be enhanced in several aspects. First, the time effectiveness of the train can be raised by reducing the on-route time and increasing the service frequency, especially when competing for highly time-sensitive cargos, such as chemical raw materials & chemical products (Category 5); metal smelting and processing & metal products (Category 7); and equipment manufacturing products (Category 8). For these time-sensitive cargos, it is more necessary to market time precision to encourage shippers to shift from liner shipping to the CER-Express. Furthermore, due to the cost increment of liner shipping, the CER-Express will be more attractive to shippers that are sensitive to freight rate increments, such as the shippers of the commodities food processing & tobacco (Category 1); textiles (Category 2); apparel, shoes & hats, leather & down feathers (Category 3); wood processing (Category 4); chemical raw materials & chemical products (Category 6); and other manufacturing products (Category 9). The modal split of the CER-Express can be further improved in transporting freight rate-sensitive commodities if the Chinese government increases the subsidies to the CER-Express. For liner shipping, passing all the added fuel cost onto shippers is not helpful for maximizing operational profits in the case of IMO 2020. According to the analysis results, liner shipping companies may obtain maximum profits when the passthrough ratio is 30%40%. However, the IMO 2020 will reduce the profits of liner shipping companies by 15%, which will be a new challenge for shipping companies. Another finding is that IMO 2020 may reduce the total sulfur emission for transporting commodities between China and Europe, but it may increase total CO2 emissions. In summary, the development of the CER-Express and the upcoming IMO 2020 will increase the competitiveness and raise the role and status of the CER-Express in the transport market between China and Europe. Faced with potentially shrinking profits, liner shipping companies should take mitigation actions to meet the challenges from the CER-Express and the new sulfur emission cap. In addition, there is no doubt that IMO 2020 will have a positive effect on sulfur emission reduction, but we should also remain vigilant against the possible increment in CO2 emissions due to the modal shift from liner shipping to CER-Express transportation. For the case study, the freight rate of the CER-Express is the actually executed price, which includes a discount by the Chinese government. Although most people expect that such a discount cannot last forever, when the subsidy will disappear cannot easily be forecast. Because the government would like to support the CER-Express until it can survive in the market via economies of scale, using the discount price will not damage the quality of the numerical analysis. On the other hand, using a fixed freight rate for liner shipping is also a minor defect of this study because the freight rate of liner shipping fluctuates significantly. However, the problem of the market shares of two transport corridors or the modal splits of two 12
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kinds of traffic modes in this study belongs to a microplanning issue rather than a daily operation one. Assigning an aggregate average value to the freight rate of liner shipping has its rationality. Actually, we do not analyze the path or mode choice of a specific shipper at a specific time but rather study the path or mode choices of a representative shipper over the long term. In this case, the freight rate of either the CER-Express or shipping should be an averaged one. Moreover, due to the ECA, shipping companies may adjust sailing routes, adopt low sulfur fuel or install scrubbers, however, due to the short of detailed data for calculating the cost increment this paper only considers the case of adaptation of low sulfur fuel. It is better for us to calculate the cost increments for all the feasible methods for dealing with the ECA and then give a weighted average value. We hope we can elaborate this issue in our future study. 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