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Transport Carbon Emission Measurement Models and Spatial Patterns Under the Perspective of Land–Sea Integration–Take Tianjin as an Example

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  • Lina Ke

    (School of Geographical Science, Liaoning Normal University, Dalian 116029, China
    Center for Studies of Marine Economy and Sustainable Development, Liaoning Normal University, Dalian 116029, China)

  • Zhiyu Ren

    (School of Geographical Science, Liaoning Normal University, Dalian 116029, China)

  • Quanming Wang

    (National Sea Environmental Monitoring Center, Dalian 116023, China)

  • Lei Wang

    (School of Geographical Science, Liaoning Normal University, Dalian 116029, China)

  • Qingli Jiang

    (School of Geographical Science, Liaoning Normal University, Dalian 116029, China)

  • Yao Lu

    (School of Geographical Science, Liaoning Normal University, Dalian 116029, China)

  • Yu Zhao

    (School of Geographical Science, Liaoning Normal University, Dalian 116029, China)

  • Qin Tan

    (School of Geographical Science, Liaoning Normal University, Dalian 116029, China)

Abstract

The goal of “double carbon” puts forward higher requirements for the control of transport carbon emissions, and the exploration of transport carbon emission modelling driven by big data is an important attempt to reduce carbon accurately. Based on the land Vehicle Miles Traveled data (VMT) and the sea Automatic Identification System (AIS) data, this study establishes a refined, high-resolution carbon emission measurement model that incorporates the use of motor vehicles and ships from a bottom-up approach and analyzes the spatial distribution characteristics of land and sea transport carbon emissions in Tianjin using geospatial analysis. The results of the study show that (1) the transportation carbon emissions in Tianjin mainly come from land road traffic, with small passenger cars contributing the most to the emissions; (2) high carbon emission zones are concentrated in economically developed, densely populated, and high road network density areas, such as the urban center Binhai New Area, and the marine functional zone of Tianjin; (3) carbon emission values are generally higher in the segments where ports, airports, and interchanges are connected. The transportation carbon emission measurement model developed in this study provides practical, replicable, and scalable insights for other coastal cities.

Suggested Citation

  • Lina Ke & Zhiyu Ren & Quanming Wang & Lei Wang & Qingli Jiang & Yao Lu & Yu Zhao & Qin Tan, 2025. "Transport Carbon Emission Measurement Models and Spatial Patterns Under the Perspective of Land–Sea Integration–Take Tianjin as an Example," Sustainability, MDPI, vol. 17(7), pages 1-19, March.
    • Handle: RePEc:gam:jsusta:v:17:y:2025:i:7:p:3095-:d:1625059
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    References listed on IDEAS

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    1. Kazimierz Lejda & Artur Jaworski & Maksymilian Mądziel & Krzysztof Balawender & Adam Ustrzycki & Danylo Savostin-Kosiak, 2021. "Assessment of Petrol and Natural Gas Vehicle Carbon Oxides Emissions in the Laboratory and On-Road Tests," Energies, MDPI, vol. 14(6), pages 1-19, March.
    2. Liu, Jiaguo & Li, Sujuan & Ji, Qiang, 2021. "Regional differences and driving factors analysis of carbon emission intensity from transport sector in China," Energy, Elsevier, vol. 224(C).
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    1. Seyed Behbood Issa-Zadeh & Claudia Lizette Garay-Rondero, 2025. "Decarbonizing Seaport Maritime Traffic: Finding Hope," World, MDPI, vol. 6(2), pages 1-19, April.

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