IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v12y2020i8p3165-d345462.html
   My bibliography  Save this article

Analysis of Rock Raw Materials Transport and its Implications for Regional Development and Planning. Case Study of Lower Silesia (Poland)

Author

Listed:
  • Jan Blachowski

    (Faculty of Geoengineering, Mining and Geology, Wrocław University of Science and Technology, Wybrzeże Wyspiańskiego 27, 50-370 Wroclaw, Poland)

  • Anna Buczyńska

    (Faculty of Geoengineering, Mining and Geology, Wrocław University of Science and Technology, Wybrzeże Wyspiańskiego 27, 50-370 Wroclaw, Poland)

Abstract

The movement of rock raw materials from source to demand areas is carried out predominately with road and railway transport. The latter is less damaging to infrastructure, the environment and society and is cheaper for longer distances, but it is also less flexible and not widely used. The Lower Silesia region in southwestern Poland is an important producer of rock raw materials and the principal provider of igneous and metamorphic dimension stones and crushed rocks in the country. A multicriteria scoring scheme has been developed and applied to identify mines presently using road transport, that are predisposed to switch to or include a railway form of transport. Four criteria have been proposed, C1—distance to railway loading point, C2—annual production of rock raw material, C3—economic reserves, and C4—type of rock raw material. The scoring scheme (classification) was developed based on the results of descriptive statistics for mines presently using railway or combined road and railway forms of transport. Two scenarios were analyzed, one with equal weights (0.25) and the other with higher significance of C1 = 0.40 and C2 = 0.30, and lower significance of C3 = 0.20 and C4 = 0.10. In the result, 24 mines were identified and ranked in terms of their potential to introduce railway transport. The proposed methodology can be used universally for other regions and countries, and the results will be included in drawing up regional spatial development policies.

Suggested Citation

  • Jan Blachowski & Anna Buczyńska, 2020. "Analysis of Rock Raw Materials Transport and its Implications for Regional Development and Planning. Case Study of Lower Silesia (Poland)," Sustainability, MDPI, vol. 12(8), pages 1-14, April.
    • Handle: RePEc:gam:jsusta:v:12:y:2020:i:8:p:3165-:d:345462
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/12/8/3165/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/12/8/3165/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Kendall, Alissa & Kesler, Stephen E. & Keoleian, Gregory A., 2010. "Megaquarry versus decentralized mineral production: network analysis of cement production in the Great Lakes region, USA," Journal of Transport Geography, Elsevier, vol. 18(2), pages 322-330.
    2. Beuthe, Michel & Jourquin, Bart & Geerts, Jean-François & Koul à Ndjang' Ha, Christian, 2001. "Freight transportation demand elasticities: a geographic multimodal transportation network analysis," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 37(4), pages 253-266, August.
    3. Andrés, Lidia & Padilla, Emilio, 2015. "Energy intensity in road freight transport of heavy goods vehicles in Spain," Energy Policy, Elsevier, vol. 85(C), pages 309-321.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Casavant, Ken & Jessup, Eric, 2005. "What Makes them Viable? Determining the Attributes that Offer Potential Viability to Inter-Modal Truck-Rail Facilities in Washington State," 46th Annual Transportation Research Forum, Washington, D.C., March 6-8, 2005 208221, Transportation Research Forum.
    2. Peterson, Steven, 2005. "Factors Influencing Inter-Modal Facility Location Decisions: Comparison of Different Empirical Estimation Procedures," 46th Annual Transportation Research Forum, Washington, D.C., March 6-8, 2005 208177, Transportation Research Forum.
    3. Román-Collado, Rocío & Colinet, María José, 2018. "Are labour productivity and residential living standards drivers of the energy consumption changes?," Energy Economics, Elsevier, vol. 74(C), pages 746-756.
    4. Li, Zheng & Hensher, David A. & Rose, John M., 2011. "Identifying sources of systematic variation in direct price elasticities from revealed preference studies of inter-city freight demand," Transport Policy, Elsevier, vol. 18(5), pages 727-734, September.
    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. Zhao, Yiran & Yang, Zhongzhen & Haralambides, Hercules, 2019. "Optimizing the transport of export containers along China's coronary artery: The Yangtze River," Journal of Transport Geography, Elsevier, vol. 77(C), pages 11-25.
    7. Álvarez-SanJaime, Óscar & Cantos-Sánchez, Pedro & Moner-Colonques, Rafael & Sempere-Monerris, José J., 2013. "Competition and horizontal integration in maritime freight transport," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 51(C), pages 67-81.
    8. Morales-Fusco, Pau & Saurí, Sergi & Lago, Alejandro, 2012. "Potential freight distribution improvements using motorways of the sea," Journal of Transport Geography, Elsevier, vol. 24(C), pages 1-11.
    9. Ron Yang, 2022. "(Don’t) Take Me Home: Home Preference and the Effect of Self-Driving Trucks on Interstate Trade," NBER Chapters, in: Economics of Artificial Intelligence, National Bureau of Economic Research, Inc.
    10. Ferrari, Paolo, 2016. "Instability and dynamic cost elasticities in freight transport systems," Transport Policy, Elsevier, vol. 49(C), pages 226-233.
    11. Wang, Juan & Hu, Mingming & Rodrigues, João F.D., 2018. "The evolution and driving forces of industrial aggregate energy intensity in China: An extended decomposition analysis," Applied Energy, Elsevier, vol. 228(C), pages 2195-2206.
    12. 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.
    13. Hensher, David A. & Collins, Andrew T. & Rose, John M. & Smith, Nariida C., 2013. "Direct and cross elasticities for freight distribution access charges: Empirical evidence by vehicle class, vehicle kilometres and tonne vehicle kilometres," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 56(C), pages 1-21.
    14. Pedinotti-Castelle, Marianne & Pineau, Pierre-Olivier & Vaillancourt, Kathleen & Amor, Ben, 2022. "Freight transport modal shifts in a TIMES energy model: Impacts of endogenous and exogenous modeling choice," Applied Energy, Elsevier, vol. 324(C).
    15. Edyta Sidorczuk-Pietraszko, 2020. "Spatial Differences in Carbon Intensity in Polish Households," Energies, MDPI, vol. 13(12), pages 1-21, June.
    16. Rich, J. & Kveiborg, O. & Hansen, C.O., 2011. "On structural inelasticity of modal substitution in freight transport," Journal of Transport Geography, Elsevier, vol. 19(1), pages 134-146.
    17. Kurtuluş, Ercan & Çetin, İsmail Bilge, 2020. "Analysis of modal shift potential towards intermodal transportation in short-distance inland container transport," Transport Policy, Elsevier, vol. 89(C), pages 24-37.
    18. Russian Presidential Academy of National Economy and Public Administration authors collective, 2012. "The Consequences of Weak Competition: Quantitative Evaluation and Policy Implications (Think Tank Report)," Ekonomicheskaya Politika / Economic Policy, Russian Presidential Academy of National Economy and Public Administration, vol. 6, pages 1-49.
    19. Iannone, Fedele, 2012. "The private and social cost efficiency of port hinterland container distribution through a regional logistics system," Transportation Research Part A: Policy and Practice, Elsevier, vol. 46(9), pages 1424-1448.
    20. Igor Taran & Asem Karsybayeva & Vitalii Naumov & Kenzhegul Murzabekova & Marzhan Chazhabayeva, 2023. "Fuzzy-Logic Approach to Estimating the Fleet Efficiency of a Road Transport Company: A Case Study of Agricultural Products Deliveries in Kazakhstan," Sustainability, MDPI, vol. 15(5), pages 1-14, February.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:12:y:2020:i:8:p:3165-:d:345462. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.