Energy consumption and CO2 emissions in hinterland container transport

https://doi.org/10.1016/j.jclepro.2020.123394Get rights and content

Highlights

  • The ASIF approach is revised to assess energy use and CO2 of hinterland transport.

  • Yiwu-Ningbo container traffic used 82.675 ktce and emitted 249.414 kt CO2 in 2017.

  • Energy consumption is underestimated by 0.04–45.50% if certain factors are omitted.

  • All-road transport dominates the energy use and CO2 emissions.

  • Reducing road energy intensity and modal shift effectively decrease energy and CO2.

Abstract

To correctly estimate both energy consumption and CO2 emissions of hinterland transport, the currently accepted Activity – modal Structure – energy Intensity – emission Factor (ASIF) method needs to be revised. Therefore, this study introduces the concept of both “yard-door-port” transport chain and semi-life cycle assessment, and establishes a generalized analytical framework. This framework considers all energy consumption and well-to-wheel (WTW) emissions of main-haulage, loading/unloading, pre-/post-haulage, and transshipment of both loaded container movement and empty container repositioning. An empirical study of the Yiwu-Ningbo corridor shows that the energy consumption and CO2 emissions were 82.675 ktce and 249.414 kt in 2017, respectively. Depending on the factors that are not considered, total energy consumption and CO2 emissions will be underestimated by 0.04–45.50% and 0.08–45.37%, respectively. All-road transport consumes 99.17% of the total energy and emits 98.84% of the overall WTW CO2 emissions. The intensities of energy consumption and CO2 emissions for the road-rail combined transport are 81.34% and 74.24% lower than those of all-road transport, respectively. Accordingly, decreasing the energy intensity of semi-trailers and shifting container traffic from all-road transport to road-rail combined transport are effective measures to save energy and reduce CO2. This revised ASIF method enabled the reasonable estimation and structural analysis of energy consumption and CO2 emissions under different scenarios.

Introduction

In 2018, China’s container port traffic reached 251 million twenty-foot equivalent units (TEUs), placing China first among container port traffic of the world for the sixteenth time since 2003 (MOT, 2019; Li, 2019). However, the market share of hinterland transport modes (all-road: 83.7%, road plus water: 15%, and road plus rail: 1.3%) for Chinese container ports is extremely unbalanced (Zhao, 2018). This unbalanced state is detrimental for the construction of regional low-carbon transport systems. In this context, not only national but also local governments of China have released a series of policies (i.e., The Three-year Plan to Push forward Restructuring Transportation in China, The Action Plan to Strengthen Emission Controls of Diesel Trucks in China, and The Three-Year Action Plan for Winning the Blue-Sky Defense War in Zhejiang Province). These policies aim to both save energy and reduce CO2 emissions by shifting intercity freight traffic from all-road transport to combined transport, especially along port-hinterland corridors. However, how to reasonably and accurately evaluate the effects (or pre-evaluate the potential effects) of such policy measures on energy saving and CO2 emissions reduction remains unknown.

One of the main challenges is the absence of a reasonable and practical approach to assess the energy consumption and/or CO2 emissions from freight transport at the corridor level. In more general terms, without an appropriate assessment approach, neither developed economies nor developing countries can objectively assess the effectiveness of an issued regional low-carbon transport policy in the freight sector. Moreover, pre-evaluating the potential energy saving and CO2 emissions reduction of a proposed regional freight transport policy is also only possible with an appropriate assessment approach. Therefore, it is essential to establish a generalized practical approach for the assessment of both energy consumption and CO2 emissions from freight transport at the corridor level.

So far, notable efforts by numerous researchers have been directed to address this issue, mainly using a traditional activity-based method (also known as bottom-up method). For North America, Winebrake et al. (2008) proposed an intermodal network analysis model for the selection of optimal routes, and obtained both energy consumption and CO2 emissions of container transport for three corridors along the U.S. eastern seaboard. Similarly, Comer et al. (2010) depicted both CO2 intensity and total CO2 emissions for different hinterland transport modes from Montreal, Canada, to Cleveland, Ohio, USA, utilizing the model developed by Winebrake et al. (2008). In Europe, Michalk and Meimbresse (2012) presented a method to design new container train services, and computed the CO2 emissions of both road and intermodal transport along the Ulm-Wustermark corridor. Kim and Van Wee (2014) established a model that integrates the semi-life cycle assessment concept (considering the well-to-wheel (WTW) energy emissions, including both well-to-tank (WTT) and tank-to-wheel (TTW) energy emissions. The authors used this model to examine whether combined transport emits less CO2 than road transport in a European corridor between Rotterdam and Gdansk. Kirschstein and Meisel (2015) constructed a series of mesoscopic emission models to evaluate the CO2 emissions of road and rail transportation, and conducted a case study for the container transport from the port of Hamburg to Bratislava. In Asia, Liao et al. (2011) calculated the fuel consumption and CO2 emissions of hinterland transport in Taiwan, and analyzed the effects of four managerial strategies for the reduction of CO2 emissions. Regmi and Hanaoka (2015) analyzed the CO2 emission reductions resulting from a modal shift along the Laem Chabang Port-Thanaleng corridor. Tao et al. (2017) developed a comprehensive analytical framework for the evaluation of the mitigation potential of CO2 emissions from modal shift, induced by subsidy for hinterland container transport, which was tested, using the container transport along the Yiwu-Ningbo corridor.

Except for research at the freight corridor level, few studies reported the CO2 emissions at the freight node level, e.g., port or consolidation center. Na et al. (2017) evaluated the environmental efficiency of China’s eight coastal container ports using CO2 emissions, including those from ships, loading/unloading equipment, and yard trucks. Nocera and Cavallaro (2017) concluded that WTW (well-to-wheel) analysis is the most appropriate approach to assess the real freight CO2 emissions, and assessed the impacts of four scenarios on CO2 emissions via WTW analysis.

In general, the above-mentioned studies provided insights into the assessment of both energy consumption and CO2 emissions in port-hinterland container transport. However, they still suffer from a number of shortcomings. Firstly, only Winebrake et al. (2008) and Liao et al. (2011) calculated both energy consumption and CO2 emissions, while the remaining studies only considered CO2 emissions. Secondly, almost none of the selected studies included the CO2 emissions that emerge from the loading and unloading of loaded containers (except for Na et al., 2017; Tao et al., 2017) and the activities of empty container repositioning. Thirdly, the WTT CO2 emissions were either neglected (Comer et al., 2010; Michalk and Meimbresse, 2012; Regmi and Hanaoka, 2015) or the WTW CO2 emissions of pre-/post-haulage and transshipment were not included (Kirschstein and Meisel, 2015). Therefore, both the energy consumption and CO2 emissions were underestimated to varying degrees for container transport along a specific freight corridor (Tao et al., 2018b). Additionally, previous research did not analyze the structure of both total energy consumption and total CO2 emissions in container transport. Hence, it is almost impossible to either identify the key influencing factors of, or to select efficient managerial strategies for, the reduction of energy consumption and CO2 emissions in hinterland transport.

To fill these gaps within the literature (see Table 1), this study proposes a generalized framework that not only enables reasonable estimates but also enables a structural analysis of both energy consumption and CO2 emissions for hinterland container transport. To this end, the concept of both “yard-door-port” transport chain (from the loading of an empty container at the empty container yard, the loading cargoes at the door of factory or warehouse, to the unloading of full-loaded container at the port terminal or vice versa) and semi-life cycle assessment (namely WTW analysis including both WTT and TTW energy emissions) are introduced in an attempt to revise the traditional activity-based method.

Based on empirical research, the following main findings were obtained: (1) Yiwu-Ningbo container traffic used 82.675 ktce and emitted 249.414 kt CO2 in 2017. (2) The results will be underestimated by 0.04–45.50% if relevant factors are omitted. (3) All-road transport dominants both the energy use and CO2 emissions. (4) Reducing road energy intensity and prompting modal shift can effectively reduce energy and CO2.

To the best of our knowledge, this study contributes to the literature in the following aspects: (1) Considering all activities included in the “yard-door-port” transport chain (including main-haulage, loading and unloading, pre- and post-haulage, and transshipment, which in turn includes both loaded container movement and empty container repositioning), potential underestimation of energy consumption in hinterland container transport could be avoided. (2) Introduction of the concepts of both “yard-door-port” transport chain and semi-life cycle assessment results in a fair and reasonable assessment of CO2 emissions in hinterland container transport. (3) The generalized framework proposed in this study enables the structural analysis of both energy consumption and CO2 emissions in either developed economies or other developing countries. Moreover, several efficient strategies for energy saving and CO2 reduction are suggested.

The rest of this paper is organized as follows: Section 2 analyzes both the elements and functions of a typical hinterland container transport system in China. Section 3 presents a generalized framework with which to objectively estimate the energy consumption and CO2 emissions of hinterland container transport. Section 4 provides background information and data collection for the case study. Section 5 presents the results including structure analysis, uncertainty analysis, comparative analysis, and scenario analysis. Section 6 summarizes the main findings and proposes relevant policy implications.

Section snippets

The typical hinterland transport system of China

Hinterland container transport refers to the container movement between port and hinterland, which is a fundamental leg of the entire international container transport chain. A seamless, efficient, and sustainable hinterland container transport system is beneficial for economic growth, social development, and environmental protection of the entire port-hinterland corridor. A typical hinterland container transport system in China is composed of transport networks, vehicles, handling equipment,

Methodology

Two main approaches can be used to calculate CO2 emissions resulting from freight transportation. The first approach is an energy-based method (Macharis et al., 2012), in which the CO2 emissions can be calculated by summing the multiplied energy consumptions by energy type and the energy-specific CO2 emission factors. The second approach is an activity-based method (Macharis et al., 2012), in which the CO2 emissions can be computed by summing the multiplied freight turnover per energy type, the

Case study

This section presents an empirical analysis using the case of the export container transport along the Yiwu-Ningbo corridor. This case was chosen for two reasons: First, this corridor is one of the busiest hinterland container transport corridors in China. Second, a good research foundation already exists (Tao et al., 2017; Tao et al., 2018a, 2018b) and data sources are available for this case.

Results

Estimations can be obtained by inputting the parameter values into Eq. (2). The energy consumption of the hinterland container transport along the Yiwu-Ningbo Corridor in 2017 was 82.675 ktce (kilotons coal equivalent). Accordingly, the TTW and WTW CO2 emissions were 178.169 kt and 249.414 kt. Therefore, the total CO2 emissions will be underestimated by 28.56% if WTT CO2 emissions are omitted. To improve both accuracy and comparability, the WTW CO2 emissions are included in the following

Conclusions

The hinterland container transport is one of the most important sectors for the development of international trade and for the construction of a low-carbon transport system. It is therefore necessary to establish a reasonable and practical generalized framework with which to accurately estimate both the energy consumption and CO2 emissions of the hinterland container transport. This paper revises the traditional ASIF methodology and introduces the concepts of both “yard-door-port” transport

CRediT authorship contribution statement

Xuezong Tao: Conceptualization, Methodology, Visualization, Writing - original draft, Supervision, Project administration, Funding acquisition. Qin Wu: Resources, Investigation, Software, Data curation, Writing - review & editing.

Declaration of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Acknowledgments

This work was supported by the National Natural Science Foundation of China [Grant no. 71603162]; and sponsored by the Natural Science Foundation of Shanghai [Grant no. 15ZR1420400]. The authors would like to thank the editors and three dedicated reviewers for their contribution to improve the manuscript.

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