Abstract
Understanding the effect of freight structure (FS) on carbon dioxide (CO2) emissions is significant for policymakers in the transport sector. However, few studies have investigated fully how the freight structure influences transport CO2 emissions. In the paper, a comprehensive freight structure index is proposed to assess the freight structure in 16 provinces of China during 2005–2019. Then, the heterogeneous effect of the freight structure and other factors on CO2 emissions are quantified by the quantile regression model developed. The mediating effect between freight structure and CO2 emissions is further examined. And the panel causality test is used to explore the directions of causality among variables. The main results indicate that (1) the level of freight structure shows a distribution of increase from western and central regions to eastern regions in 16 provinces. (2) Freight structure has a positive effect on transport CO2 emissions, and its effect is significantly heterogeneous in all quantiles. (3) Freight structure has an indirect impact on CO2 emissions through the scale effect. (4) The bidirectional causality is confirmed between economic growth, industrial structure, and information and communication technology with carbon emissions. A unidirectional causality from CO2 emissions to freight structure is also found. Finally, some policy recommendations are proposed for sustainable transport development in China. The results facilitate the formulation of the regionally tailored carbon emission reduction strategy in the transport sector.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
Data availability
The datasets in this study are available from the corresponding author upon reasonable request.
Abbreviations
- CO2:
-
Carbon dioxide
- GHG:
-
Greenhouse gas
- EU:
-
European Union
- IPCC:
-
Intergovernmental Panel on Climate Change
- CKC:
-
Carbon Kuznets curve
- LMDI:
-
Logarithmic mean divisia index
- STIRPAT:
-
Stochastic Impact by Regression on Population, Affluence, and Technology
- OLS:
-
Ordinary least squares
- VIF:
-
Variance inflation factor
- IPS:
-
I'm, Pesaran Shin
- CIPS:
-
Cross-sectionally augmented I'm, Pesaran, Shin
- Q-Q :
-
Quantile-quantile
- SIC:
-
Schwarz information criterion
- GDP:
-
Gross domestic product
- R&D:
-
Research and development
- FTC:
-
Freight transport capacity
- RTI:
-
Regional transport infrastructure
- FTT:
-
Freight transport technology
- FS:
-
Freight structure
- PGDP:
-
Per capita GDP
- IS:
-
Industrial structure
- TO:
-
Trade openness
- ICT:
-
Information and communication technology
- AVT:
-
Added value to the transport sector
References
Adams S, Boateng E, Acheampong AO (2020) Transport energy consumption and environmental quality: does urbanization matter? Sci Total Environ 744:140617. https://doi.org/10.1016/j.scitotenv.2020.140617
Alataş S (2021) The role of information and communication technologies for environmental sustainability: evidence from a large panel data analysis. J Environ Manage 293:112889. https://doi.org/10.1016/j.jenvman.2021.112889
Andrés L, Padilla E (2018) Driving factors of GHG emissions in the EU transport activity. Transp Policy 61:60–74. https://doi.org/10.1016/j.tranpol.2017.10.008
Anwar A, Ahmad N, Madni GR (2020) Industrialization, freight transport and environmental quality: evidence from belt and road initiative economies. Environ Sci Pollut Res 27:7053–7070. https://doi.org/10.1007/s11356-019-07255-8
Ariken M, Zhang F, Weng Chan N, Kung H (2021) Coupling coordination analysis and spatio-temporal heterogeneity between urbanization and eco-environment along the Silk Road Economic Belt in China. Ecol Indic 121:107014. https://doi.org/10.1016/j.ecolind.2020.107014
Bekun FV, Alola AA, Sarkodie SA (2019) Toward a sustainable environment: nexus between CO2 emissions, resource rent, renewable and nonrenewable energy in 16-EU countries. Sci Total Environ 657:1023–1029. https://doi.org/10.1016/j.scitotenv.2018.12.104
Buchinsky M (1995) Estimating the asymptotic covariance matrix for quantile regression models a Monte Carlo study. J Econom 68:303–338. https://doi.org/10.1016/0304-4076(94)01652-G
Bueno G (2012) Analysis of scenarios for the reduction of energy consumption and GHG emissions in transport in the Basque Country. Renew Sust Energ Rev 16:1988–1998. https://doi.org/10.1016/j.rser.2012.01.004
Chatti W (2021) Moving towards environmental sustainability: information and communication technology (ICT), freight transport, and CO2 emissions. Heliyon 7:e08190. https://doi.org/10.1016/j.heliyon.2021.e08190
Chen J, **an Q, Zhou J, Li D (2020) Impact of income inequality on CO2 emissions in G20 countries. J Environ Manage 271:110987. https://doi.org/10.1016/j.jenvman.2020.110987
Chen R, Wang X, Zhang Y, Luo Q (2022) The nonlinear effect of land freight structure on carbon emission intensity: new evidence from road and rail freight in China. Environ Sci Pollut Res 29:78666–78682. https://doi.org/10.1007/s11356-022-21352-1
Chen Y, Long X, Salman M (2021) Did the 2014 Nan**g Youth Olympic Games enhance environmental efficiency? New evidence from a quasi-natural experiment. Energy Policy 159:112581. https://doi.org/10.1016/j.enpol.2021.112581
Cheng Z, Li L, Liu J (2018) Industrial structure, technical progress and carbon intensity in China’s provinces. Renew Sust Energ Rev 81:2935–2946. https://doi.org/10.1016/j.rser.2017.06.103
Churchill SA, Inekwe J, Ivanovski K, Smyth R (2021) Transport infrastructure and CO2 emissions in the OECD over the long run. Transport Res Part D Transport Environ 95:102857. https://doi.org/10.1016/j.trd.2021.102857
Danish (2019) Effects of information and communication technology and real income on CO2 emissions: The experience of countries along Belt and Road. Telemat Inform 45:101300. https://doi.org/10.1016/j.tele.2019.101300
Danish ZJ, Hassan ST, Iqbal K (2020) Toward achieving environmental sustainability target in organization for economic cooperation and development countries: the role of real income, research and development, and transport infrastructure. Sustain Dev 28:83–90. https://doi.org/10.1002/sd.1973
Dehghan Shabani Z, Shahnazi R (2019) Energy consumption, carbon dioxide emissions, information and communications technology, and gross domestic product in Iranian economic sectors: a panel causality analysis. Energy 169:1064–1078. https://doi.org/10.1016/j.energy.2018.11.062
Du Q, Li J, Li Y et al (2020) Carbon inequality in the transportation industry: empirical evidence from China. Environ Sci Pollut Res 27:6300–6311. https://doi.org/10.1007/s11356-019-07291-4
Dumitrescu E-I, Hurlin C (2012) Testing for Granger non-causality in heterogeneous panels. Econ Model 29:1450–1460. https://doi.org/10.1016/j.econmod.2012.02.014
Godil DI, Yu Z, Sharif A et al (2021) Investigate the role of technology innovation and renewable energy in reducing transport sector CO2 emission in China: a path toward sustainable development. Sustain Dev 29:694–707. https://doi.org/10.1002/sd.2167
Goh T, Zhong S, Ang BW et al (2021) Driving factors of changes in international maritime energy consumption: microdata evidence 2014–2017. Energy Policy 154:112288. https://doi.org/10.1016/j.enpol.2021.112288
Gupta D, Garg A (2020) Sustainable development and carbon neutrality: integrated assessment of transport transitions in India. Transport Res Part D Transport Environ 85:102474. https://doi.org/10.1016/j.trd.2020.102474
Hao Y, Li Y, Guo Y et al (2022) Digitalization and electricity consumption: does internet development contribute to the reduction in electricity intensity in China? Energy Policy 164:112912. https://doi.org/10.1016/j.enpol.2022.112912
Hassan SA, Nosheen M, Rafaz N, Haq I (2021) Exploring the existence of aviation Kuznets curve in the context of environmental pollution for OECD nations. Environ Dev Sustain 23:15266–15289. https://doi.org/10.1007/s10668-021-01297-0
Huang Y, Zhu H, Zhang Z (2020) The heterogeneous effect of driving factors on carbon emission intensity in the Chinese transport sector: evidence from dynamic panel quantile regression. Sci Total Environ 727:138578. https://doi.org/10.1016/j.scitotenv.2020.138578
Im KS, Pesaran MH, Shin Y (2003) Testing for unit roots in heterogeneous panels. J Econom 115:53–74. https://doi.org/10.1016/S0304-4076(03)00092-7
Isik M, Sarica K, Ari I (2020) Driving forces of Turkey’s transportation sector CO2 emissions: an LMDI approach. Transp Policy 97:210–219. https://doi.org/10.1016/j.tranpol.2020.07.006
Koenker R, Bassett G (1978) Regression quantiles. Econometrica 46:33–50. https://doi.org/10.2307/1913643
Li L (2019) Structure and influencing factors of CO2 emissions from transport sector in three major metropolitan regions of China: estimation and decomposition. Transportation 46:1245–1269. https://doi.org/10.1007/s11116-017-9827-6
Li Y, Du Q, Lu X et al (2019) Relationship between the development and CO2 emissions of transport sector in China. Transport Res Part D Transport Environ 74:1–14. https://doi.org/10.1016/j.trd.2019.07.011
Lin B, Xu B (2018) Factors affecting CO2 emissions in China’s agriculture sector: a quantile regression. Renew Sust Energ Rev 94:15–27. https://doi.org/10.1016/j.rser.2018.05.065
Liu J, Li S, Ji Q (2021) Regional differences and driving factors analysis of carbon emission intensity from transport sector in China. Energy 224:120178. https://doi.org/10.1016/j.energy.2021.120178
Liu S, Zhu X, Jia S (2009) A review of urban traffic structure optimization. J Transp Syst Eng Inf Technol 9:29–38
Long X, Chen Y, Du J et al (2017) Environmental innovation and its impact on economic and environmental performance: evidence from Korean-owned firms in China. Energy Policy 107:131–137. https://doi.org/10.1016/j.enpol.2017.04.044
Long X, Wu C, Zhang J, Zhang J (2018) Environmental efficiency for 192 thermal power plants in the Yangtze River Delta considering heterogeneity: a metafrontier directional slacks-based measure approach. Renew Sust Energ Rev 82:3962–3971. https://doi.org/10.1016/j.rser.2017.10.077
Lu S, Jiang H, Liu Y, Huang S (2017) Regional disparities and influencing factors of average CO2 emissions from transportation industry in Yangtze River Economic Belt. Transport Res Part D Transport Environ 57:112–123. https://doi.org/10.1016/j.trd.2017.09.005
Luo X, Dong L, Dou Y et al (2016) Regional disparity analysis of Chinese freight transport CO2 emissions from 1990 to 2007: driving forces and policy challenges. J Transp Geogr 56:1–14. https://doi.org/10.1016/j.jtrangeo.2016.08.010
Luo Y, Lu Z, Long X (2020) Heterogeneous effects of endogenous and foreign innovation on CO2 emissions stochastic convergence across China. Energy Econ 91:104893. https://doi.org/10.1016/j.eneco.2020.104893
Luo Y, Wang Q, Long X, et al (2022) Green innovation and SO 2 emissions: dynamic threshold effect of human capital. Bus Strateg Environ bse.3157. https://doi.org/10.1002/bse.3157
Mao B hua, Sun Q xin, Chen S kuan (2009) Structural analysis on 2008 intercity transport system of China. J Transp Syst Eng Inf Technol 9:11–18
Maparu TS, Mazumder TN (2021) Investigating causality between transport infrastructure and urbanization: a state-level study of India (1991–2011). Transp Policy 113:46–55. https://doi.org/10.1016/j.tranpol.2020.03.008
Mensah CN, Long X, Dauda L et al (2019) Technological innovation and green growth in the organization for economic cooperation and development economies. J Clean Prod 240:118204. https://doi.org/10.1016/j.jclepro.2019.118204
Meyer T (2020) Decarbonizing road freight transportation – a bibliometric and network analysis. Transport Res Part D Transport Environ 89:102619. https://doi.org/10.1016/j.trd.2020.102619
M’raihi R, Mraihi T, Harizi R, Taoufik Bouzidi M (2015) Carbon emissions growth and road freight: analysis of the influencing factors in Tunisia. Transp Policy 42:121–129. https://doi.org/10.1016/j.tranpol.2015.05.018
Muhammad S, Long X, Salman M, Dauda L (2020) Effect of urbanization and international trade on CO2 emissions across 65 belt and road initiative countries. Energy 196:117102. https://doi.org/10.1016/j.energy.2020.117102
Nasreen S, Saidi S, Ozturk I (2018) Assessing links between energy consumption, freight transport, and economic growth: evidence from dynamic simultaneous equation models. Environ Sci Pollut Res 25:16825–16841. https://doi.org/10.1007/s11356-018-1760-5
Pesaran MH (2004) General diagnostic tests for cross section dependence in panels. https://doi.org/10.17863/CAM.5113
Pesaran MH (2007) A simple panel unit root test in the presence of cross-section dependence. J Appl Econom 22:265–312. https://doi.org/10.1002/jae.951
Powell D (2016) Quantile treatment effects in the presence of covariates. Rev Econ Stat 102:994–1005. https://doi.org/10.1162/rest_a_00858
Pradhan RP, Arvin MB, Nair M (2021) Urbanization, transportation infrastructure, ICT, and economic growth: a temporal causal analysis. Cities 115:103213. https://doi.org/10.1016/j.cities.2021.103213
Rahman MM (2020) Environmental degradation: the role of electricity consumption, economic growth and globalisation. J Environ Manage 253:109742. https://doi.org/10.1016/j.jenvman.2019.109742
Saidi S, Hammami S (2017) Modeling the causal linkages between transport, economic growth and environmental degradation for 75 countries. Transport Res Part D Transport Environ 53:415–427. https://doi.org/10.1016/j.trd.2017.04.031
Saidi S, Mani V, Mefteh H et al (2020) Dynamic linkages between transport, logistics, foreign direct investment, and economic growth: empirical evidence from develo** countries. Transp Res Part A Policy Pract 141:277–293. https://doi.org/10.1016/j.tra.2020.09.020
Salman M, Long X, Dauda L et al (2019) Different impacts of export and import on carbon emissions across 7 ASEAN countries: a panel quantile regression approach. Sci Total Environ 686:1019–1029. https://doi.org/10.1016/j.scitotenv.2019.06.019
Sikder M, Wang C, Yao X et al (2022) The integrated impact of GDP growth, industrialization, energy use, and urbanization on CO2 emissions in develo** countries: evidence from the panel ARDL approach. Sci Total Environ 837:155795. https://doi.org/10.1016/j.scitotenv.2022.155795
Solaymani S (2019) CO2 emissions patterns in 7 top carbon emitter economies: the case of transport sector. Energy 168:989–1001. https://doi.org/10.1016/j.energy.2018.11.145
Song M, Zhang G, Zeng W et al (2016) Railway transportation and environmental efficiency in China. Transport Res Part D Transport Environ 48:488–498. https://doi.org/10.1016/j.trd.2015.07.003
Su B, Goh T, Ang BW, Ng TS (2022) Energy consumption and energy efficiency trends in Singapore: the case of a meticulously planned city. Energy Policy 161:112732. https://doi.org/10.1016/j.enpol.2021.112732
Tian G, Shi J, Sun L et al (2017) Dynamic changes in the energy–carbon performance of Chinese transportation sector: a meta-frontier non-radial directional distance function approach. Nat Hazards 89:585–607. https://doi.org/10.1007/s11069-017-2981-5
Tong T, Yu TE (2018) Transportation and economic growth in China: a heterogeneous panel cointegration and causality analysis. J Transp Geogr 73:120–130. https://doi.org/10.1016/j.jtrangeo.2018.10.016
Vanek F (2019) Mode and commodity perspectives on U.S. freight energy consumption and CO2 emissions: insights and directions for improvement. Int J Sustain Transp 13:741–760. https://doi.org/10.1080/15568318.2018.1512690
Wang Y, Shen N (2016) Environmental regulation and environmental productivity: the case of China. Renew Sust Energ Rev 62:758–766. https://doi.org/10.1016/j.rser.2016.05.048
Wang B, Sun Y, Chen Q, Wang Z (2018) Determinants analysis of carbon dioxide emissions in passenger and freight transportation sectors in China. Struct Change and Econ Dyn 47:127–132. https://doi.org/10.1016/j.strueco.2018.08.003
Wang J, Wang S, Li S, Feng K (2019) Coupling analysis of urbanization and energy-environment efficiency: evidence from Guangdong province. Appl Energy 254:113650. https://doi.org/10.1016/j.apenergy.2019.113650
Wang C, Lim MK, Zhang X et al (2020a) Railway and road infrastructure in the Belt and Road Initiative countries: estimating the impact of transport infrastructure on economic growth. Transp Res Part A Policy Pract 134:288–307. https://doi.org/10.1016/j.tra.2020.02.009
Wang C, Wood J, Wang Y et al (2020) CO2 emission in transportation sector across 51 countries along the belt and road from 2000 to 2014. J Clean Prod 266:122000. https://doi.org/10.1016/j.jclepro.2020b.122000
Wang C, Kim Y-S, Kim CY (2021) Causality between logistics infrastructure and economic development in China. Transp Policy 100:49–58. https://doi.org/10.1016/j.tranpol.2020.10.005
Wang B, Zhao J, Dong K, Jiang Q (2022a) High-quality energy development in China: comprehensive assessment and its impact on CO2 emissions. Energy Econ 110:106027. https://doi.org/10.1016/j.eneco.2022a.106027
Wang C, Yao X, Sinha PN et al (2022b) Why do government policy and environmental awareness matter in predicting NEVs purchase intention? Moderating role of education level. Cities 131:103904. https://doi.org/10.1016/j.cities.2022.103904
Wang C, Zhao Y, Wang Y et al (2020c) Transportation CO2 emission decoupling: an assessment of the Eurasian logistics corridor. Transport Res Part D Transport Environ 86:102486. https://doi.org/10.1016/j.trd.2020.102486
Wei F, Zhang X, Chu J et al (2021) Energy and environmental efficiency of China’s transportation sectors considering CO2 emission uncertainty. Transport Res Part D Transport Environ 97:102955. https://doi.org/10.1016/j.trd.2021.102955
Wen L, Song Q (2022) Simulation study on carbon emission of China’s freight system under the target of carbon peaking. Sci Total Environ 812:152600. https://doi.org/10.1016/j.scitotenv.2021.152600
**e R, Fang J, Liu C (2017) The effects of transportation infrastructure on urban carbon emissions. Appl Energy 196:199–207. https://doi.org/10.1016/j.apenergy.2017.01.020
Xu B, Lin B (2016) Differences in regional emissions in China’s transport sector: determinants and reduction strategies. Energy 95:459–470. https://doi.org/10.1016/j.energy.2015.12.016
Xu B, Lin B (2018) Investigating the differences in CO2 emissions in the transport sector across Chinese provinces: evidence from a quantile regression model. J Clean Prod 175:109–122. https://doi.org/10.1016/j.jclepro.2017.12.022
Xu X, Chase N, Peng T (2021) Economic structural change and freight transport demand in China. Energy Policy 158:112567. https://doi.org/10.1016/j.enpol.2021.112567
Yuan D, Li S, Li R, Zhang F (2022) Economic policy uncertainty, oil and stock markets in BRIC: evidence from quantiles analysis. Energy Econ 110:105972. https://doi.org/10.1016/j.eneco.2022.105972
Zhang C, Nian J (2013) Panel estimation for transport sector CO2 emissions and its affecting factors: a regional analysis in China. Energy Policy 63:918–926. https://doi.org/10.1016/j.enpol.2013.07.142
Zhang K, Liu X, Yao J (2019) Identifying the driving forces of CO2 emissions of China’s transport sector from temporal and spatial decomposition perspectives. Environ Sci Pollut Res 26:17383–17406. https://doi.org/10.1007/s11356-019-05076-3
Zhang L, Chen D, Peng S et al (2020a) Carbon emissions in the transportation sector of Yangtze River Economic Belt: decoupling drivers and inequality. Environ Sci Pollut Res 27:21098–21108. https://doi.org/10.1007/s11356-020-08479-9
Zhang Y, Chen X, Wu Y et al (2020b) Peaks of transportation CO2 emissions of 119 countries for sustainable development: results from carbon Kuznets curve. Sustain Dev 28:550–571. https://doi.org/10.1002/sd.2008
Zhang J, Zhang S, Wang Y et al (2021a) Air quality improvement via modal shift: assessment of rail-water-port integrated system planning in Shenzhen China. Sci Total Environ 791:148158. https://doi.org/10.1016/j.scitotenv.2021a.148158
Zhang M, Liu X, Ding Y (2021b) Assessing the influence of urban transportation infrastructure construction on haze pollution in China: a case study of Bei**g-Tian**-Hebei region. Environ Impact Assess Rev 87:106547. https://doi.org/10.1016/j.eiar.2020.106547
Zhao J, Guo D, Wang J et al (2018) Examining the Association of economic development with intercity multimodal transport demand in China: a focus on spatial autoregressive analysis. ISPRS Int J Geo-Inf 7:56–73. https://doi.org/10.3390/ijgi7020056
Zhao J, Jiang Q, Dong X, Dong K (2021a) Assessing energy poverty and its effect on CO2 emissions: the case of China. Energy Econ 97:105191. https://doi.org/10.1016/j.eneco.2021a.105191
Zhao Y, Ding H, Lin X et al (2021b) Carbon emissions peak in the road and marine transportation sectors in view of cost-benefit analysis: a case of Guangdong Province in China. Front Environ Sci 9:754192. https://doi.org/10.3389/fenvs.2021b.754192
Zhao C, Wang K, Dong X, Dong K (2022a) Is smart transportation associated with reduced carbon emissions? The case of China. Energy Econ 105:105715. https://doi.org/10.1016/j.eneco.2021.105715
Zhao J, Jiang Q, Dong X et al (2022b) How does industrial structure adjustment reduce CO2 emissions? Spatial and mediation effects analysis for China. Energy Econ 105:105704. https://doi.org/10.1016/j.eneco.2021.105704
Zhao S, Cao Y, Feng C et al (2022c) How do heterogeneous R&D investments affect China’s green productivity: revisiting the Porter hypothesis. Sci Total Environ 825:154090. https://doi.org/10.1016/j.scitotenv.2022c.154090
Zheng H, Gao X, Sun Q et al (2020) The impact of regional industrial structure differences on carbon emission differences in China: an evolutionary perspective. J Clean Prod 257:120506. https://doi.org/10.1016/j.jclepro.2020.120506
Zhou X, Zhang J, Li J (2013) Industrial structural transformation and carbon dioxide emissions in China. Energy Policy 57:43–51. https://doi.org/10.1016/j.enpol.2012.07.017
Zhou D, Huang F, Wang Q, Liu X (2021) The role of structure change in driving CO2 emissions from China’s waterway transport sector. Resour Conserv Recycl 171:105627. https://doi.org/10.1016/j.resconrec.2021.105627
Zhu X (2022) Have carbon emissions been reduced due to the upgrading of industrial structure? Analysis of the mediating effect based on technological innovation. Environ Sci Pollut Res 29:54890–54901. https://doi.org/10.1007/s11356-022-19722-w
Funding
The work is supported by the Joint Research Fund Key Project of the National Natural Science Foundation of China and the Civil Aviation Administration of China (Grant U2133211).
Author information
Authors and Affiliations
Contributions
Rujia Chen: data curation, formal analysis, methodology, and writing-original draft.
Ya** Zhang: supervision, validation, and funding acquisition.
All authors read and approved the final manuscript.
Corresponding author
Ethics declarations
Ethical approval
Not applicable.
Consent to participate
Not applicable.
Consent to publish
Not applicable.
Competing interests
The authors declare no competing interests.
Additional information
Responsible Editor: V.V.S.S. Sarma
Publisher's note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
About this article
Cite this article
Chen, R., Zhang, Y. Assessing freight structure and its effect on transport CO2 emissions: heterogeneous and mediating effect analysis. Environ Sci Pollut Res 30, 42034–42055 (2023). https://doi.org/10.1007/s11356-023-25250-y
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11356-023-25250-y