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Explaining the dynamics and identifying potential risks of hazardous materials truck movements

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  • Li, Zhaoxiang
  • Ma, Xu
  • Pan, Ruixu
  • Yang, Chao
  • Yuan, Quan

Abstract

The growth of global economy and deep specialization of industries have jointly led to a steady increase in demand for hazardous materials (HazMat) such as liquid hydrogen and nitrogen, resulting in high frequency of HazMat truck movements. Identifying the activities and understanding the characteristics of such movements are critical to reducing their negative environmental impacts. In this study, we propose a data-driven approach for extracting trips from GPS data and analyze the travel characteristics of HazMat trucks. Three dwell time thresholds are determined for distinguishing HazMat truck stop activities corresponding to 1 min, 20 min, and 288 min, respectively. Results show the spatial network of HazMat movement is subject to locations of both suppliers such as chemical industries and customers like medical offices. The spatial distribution of the trips uncovers the mobility patterns of HazMat trucks. While long-distance trips that handles the intercity shipment of HazMat generate environmental risks at the regional level, trips of less than 20 km impose potential hazards on local streets even in central areas. The risk maps for different types of HazMat transportation further reveal the unique spatial risk hotspot distributions of each category, providing valuable insights for precise risk management and policy development. The approach proposed can help characterize the mobility patterns and assess potential risks of HazMat movements, thereby promoting sustainable urban freight transportation.

Suggested Citation

  • Li, Zhaoxiang & Ma, Xu & Pan, Ruixu & Yang, Chao & Yuan, Quan, 2025. "Explaining the dynamics and identifying potential risks of hazardous materials truck movements," Journal of Transport Geography, Elsevier, vol. 123(C).
    • Handle: RePEc:eee:jotrge:v:123:y:2025:i:c:s096669232500016x
    DOI: 10.1016/j.jtrangeo.2025.104125
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    as
    1. Sanchez-Diaz, Ivan, 2020. "Assessing the magnitude of freight traffic generated by office deliveries," Transportation Research Part A: Policy and Practice, Elsevier, vol. 142(C), pages 279-289.
    2. Ciro Caliendo & Maria Luisa De Guglielmo, 2017. "Quantitative Risk Analysis on the Transport of Dangerous Goods Through a Bi‐Directional Road Tunnel," Risk Analysis, John Wiley & Sons, vol. 37(1), pages 116-129, January.
    3. Ditta, A. & Figueroa, O. & Galindo, G. & Yie-Pinedo, R., 2019. "A review on research in transportation of hazardous materials," Socio-Economic Planning Sciences, Elsevier, vol. 68(C).
    4. Ming Sun & Ronggui Zhou, 2023. "Investigation on Hazardous Material Truck Involved Fatal Crashes Using Cluster Correspondence Analysis," Sustainability, MDPI, vol. 15(12), pages 1-21, June.
    5. Joubert, J.W. & Axhausen, K.W., 2011. "Inferring commercial vehicle activities in Gauteng, South Africa," Journal of Transport Geography, Elsevier, vol. 19(1), pages 115-124.
    6. Yingying Xing & Shengdi Chen & Shengxue Zhu & Yi Zhang & Jian Lu, 2020. "Exploring Risk Factors Contributing to the Severity of Hazardous Material Transportation Accidents in China," IJERPH, MDPI, vol. 17(4), pages 1-19, February.
    7. Dadkar, Yashoda & Nozick, Linda & Jones, Dean, 2010. "Optimizing facility use restrictions for the movement of hazardous materials," Transportation Research Part B: Methodological, Elsevier, vol. 44(2), pages 267-281, February.
    8. Erhan Erkut & Vedat Verter, 1998. "Modeling of Transport Risk for Hazardous Materials," Operations Research, INFORMS, vol. 46(5), pages 625-642, October.
    9. Sheng Dong & Jibiao Zhou & Changxi Ma, 2020. "Design of a Network Optimization Platform for the Multivehicle Transportation of Hazardous Materials," IJERPH, MDPI, vol. 17(3), pages 1-14, February.
    10. Tang, Jinjun & Liu, Fang & Wang, Yinhai & Wang, Hua, 2015. "Uncovering urban human mobility from large scale taxi GPS data," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 438(C), pages 140-153.
    11. Pani, Agnivesh & Sahu, Prasanta K., 2022. "Modelling non-response in establishment-based freight surveys: A sampling tool for statewide freight data collection in middle-income countries," Transport Policy, Elsevier, vol. 124(C), pages 128-138.
    12. Laranjeiro, Patrícia F. & Merchán, Daniel & Godoy, Leonardo A. & Giannotti, Mariana & Yoshizaki, Hugo T.Y. & Winkenbach, Matthias & Cunha, Claudio B., 2019. "Using GPS data to explore speed patterns and temporal fluctuations in urban logistics: The case of São Paulo, Brazil," Journal of Transport Geography, Elsevier, vol. 76(C), pages 114-129.
    13. Vidhi Patel & Mina Maleki & Mehdi Kargar & Jessica Chen & Hanna Maoh, 2022. "A cluster-driven classification approach to truck stop location identification using passive GPS data," Journal of Geographical Systems, Springer, vol. 24(4), pages 657-677, October.
    14. Yang, Yitao & Jia, Bin & Yan, Xiao-Yong & Li, Jiangtao & Yang, Zhenzhen & Gao, Ziyou, 2022. "Identifying intercity freight trip ends of heavy trucks from GPS data," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 157(C).
    15. Xifei Huang & Xinhao Wang & Jingjing Pei & Ming Xu & Xiaowu Huang & Yun Luo, 2018. "Risk assessment of the areas along the highway due to hazardous material transportation accidents," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 93(3), pages 1181-1202, September.
    16. Florence Toilier & Marc Serouge & Jean-Louis Routhier & Danièle Patier & Mathieu Gardrat, 2016. "How can Urban Goods Movements be Surveyed in a Megacity? The Case of the Paris Region," Post-Print halshs-01474235, HAL.
    17. Julian Allen & Michael Browne & Tom Cherrett, 2012. "Survey Techniques in Urban Freight Transport Studies," Transport Reviews, Taylor & Francis Journals, vol. 32(3), pages 287-311, February.
    18. Siripirote, Treerapot & Sumalee, Agachai & Ho, H.W., 2020. "Statistical estimation of freight activity analytics from Global Positioning System data of trucks," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 140(C).
    19. Oka, Hideki & Hagino, Yasukatsu & Kenmochi, Takeshi & Tani, Ryota & Nishi, Ryuta & Endo, Kotaro & Fukuda, Daisuke, 2019. "Predicting travel pattern changes of freight trucks in the Tokyo Metropolitan area based on the latest large-scale urban freight survey and route choice modeling," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 129(C), pages 305-324.
    20. Tao Wu & Huiqing Shen & Jianxin Qin & Longgang Xiang, 2021. "Extracting Stops from Spatio-Temporal Trajectories within Dynamic Contextual Features," Sustainability, MDPI, vol. 13(2), pages 1-25, January.
    21. Ling Zhang & Jingjing Hao & Xiaofeng Ji & Lan Liu, 2019. "Research on the Complex Characteristics of Freight Transportation from a Multiscale Perspective Using Freight Vehicle Trip Data," Sustainability, MDPI, vol. 11(7), pages 1-20, March.
    22. Yee Leung & Rongrong Li & Nannan Ji, 2017. "Application of extended Dempster–Shafer theory of evidence in accident probability estimation for dangerous goods transportation," Journal of Geographical Systems, Springer, vol. 19(3), pages 249-271, July.
    23. Yang, Lin & Zhang, Fayong & Kwan, Mei-Po & Wang, Ke & Zuo, Zejun & Xia, Shaotian & Zhang, Zhiyong & Zhao, Xinpei, 2020. "Space-time demand cube for spatial-temporal coverage optimization model of shared bicycle system: A study using big bike GPS data," Journal of Transport Geography, Elsevier, vol. 88(C).
    24. Yang, Zhiwei & Chen, Xiaohong & Deng, Jihao & Li, Tianhao & Yuan, Quan, 2023. "Footprints of goods movements: Spatial heterogeneity of heavy-duty truck activities and its influencing factors in the urban context," Journal of Transport Geography, Elsevier, vol. 113(C).
    25. He, Zhangyuan & Zhao, Pengjun & Xiao, Zuopeng & Huang, Xin & Li, Zhaoxiang & Kang, Tingting, 2024. "Exploring the distance decay in port hinterlands under port regionalization using truck GPS data," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 181(C).
    26. Mulholland, Eamonn & Teter, Jacob & Cazzola, Pierpaolo & McDonald, Zane & Ó Gallachóir, Brian P., 2018. "The long haul towards decarbonising road freight – A global assessment to 2050," Applied Energy, Elsevier, vol. 216(C), pages 678-693.
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