IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v14y2021i21p6877-d660755.html
   My bibliography  Save this article

Quality and Delivery Costs of Wood Chips by Railway vs. Road Transport

Author

Listed:
  • Mariusz Jerzy Stolarski

    (Department of Genetics, Plant Breeding and Bioresource Engineering, Faculty of Agriculture and Forestry, Centre for Bioeconomy and Renewable Energies, University of Warmia and Mazury in Olsztyn, Plac Łódzki 3, 10-724 Olsztyn, Poland)

  • Paweł Stachowicz

    (Department of Genetics, Plant Breeding and Bioresource Engineering, Faculty of Agriculture and Forestry, Centre for Bioeconomy and Renewable Energies, University of Warmia and Mazury in Olsztyn, Plac Łódzki 3, 10-724 Olsztyn, Poland
    Quercus sp. z o.o. (Limited Liability Company), ul. Jana Pawła II 21, 12-130 Pasym, Poland)

  • Waldemar Sieniawski

    (Quercus sp. z o.o. (Limited Liability Company), ul. Jana Pawła II 21, 12-130 Pasym, Poland)

  • Michał Krzyżaniak

    (Department of Genetics, Plant Breeding and Bioresource Engineering, Faculty of Agriculture and Forestry, Centre for Bioeconomy and Renewable Energies, University of Warmia and Mazury in Olsztyn, Plac Łódzki 3, 10-724 Olsztyn, Poland)

  • Ewelina Olba-Zięty

    (Department of Genetics, Plant Breeding and Bioresource Engineering, Faculty of Agriculture and Forestry, Centre for Bioeconomy and Renewable Energies, University of Warmia and Mazury in Olsztyn, Plac Łódzki 3, 10-724 Olsztyn, Poland)

Abstract

Forests are the main sources of wood chips delivered to the end customers by road or railway. This research analysed the impact of the quarter of the year: Q1 (January–March), Q2 (April–June), Q3 (July–September), Q4 (October–December) when wood chips were obtained over two consecutive years (2019–2020) and the type of transport used (railway and road) on the thermophysical properties of wood chips and the cost of their delivery. The mean moisture content in the wood chips was 38.28% and it was the highest (45.55%) in Q1, while in Q2 and Q3, this parameter was 8 and 17 percentage points (p.p.) lower. The mean lower heating value (LHV) of the chips was 10.46 GJ Mg −1 . The chips delivered by road transport had a 4% higher LHV compared to those shipped by railway transport. The wood chips contained 3.42% d.m. of ash. The road transport at a distance of 200 km was found to be approximately 10% cheaper compared to the transport by rail for most of the study period, both with respect to 1 Mg of fresh or dry mass and 1 GJ of energy in the chips. The railway transport was cheaper in the winter (Q1).

Suggested Citation

  • Mariusz Jerzy Stolarski & Paweł Stachowicz & Waldemar Sieniawski & Michał Krzyżaniak & Ewelina Olba-Zięty, 2021. "Quality and Delivery Costs of Wood Chips by Railway vs. Road Transport," Energies, MDPI, vol. 14(21), pages 1-17, October.
  • Handle: RePEc:gam:jeners:v:14:y:2021:i:21:p:6877-:d:660755
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/14/21/6877/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1996-1073/14/21/6877/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Gadd, Henrik & Werner, Sven, 2013. "Daily heat load variations in Swedish district heating systems," Applied Energy, Elsevier, vol. 106(C), pages 47-55.
    2. Windisch, Johannes & Väätäinen, Kari & Anttila, Perttu & Nivala, Mikko & Laitila, Juha & Asikainen, Antti & Sikanen, Lauri, 2015. "Discrete-event simulation of an information-based raw material allocation process for increasing the efficiency of an energy wood supply chain," Applied Energy, Elsevier, vol. 149(C), pages 315-325.
    3. Eriksson, Anders & Eliasson, Lars & Sikanen, Lauri & Hansson, Per-Anders & Jirjis, Raida, 2017. "Evaluation of delivery strategies for forest fuels applying a model for Weather-driven Analysis of Forest Fuel Systems (WAFFS)," Applied Energy, Elsevier, vol. 188(C), pages 420-430.
    4. Nodirjon Nurmatov & Daniel Armando Leon Gomez & Frank Hensgen & Lutz Bühle & Michael Wachendorf, 2016. "High-Quality Solid Fuel Production from Leaf Litter of Urban Street Trees," Sustainability, MDPI, vol. 8(12), pages 1-13, November.
    5. P Flisberg & M Frisk & M Rönnqvist, 2012. "FuelOpt: a decision support system for forest fuel logistics," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 63(11), pages 1600-1612, November.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Lukáš Rečka & Milan Ščasný & Dali Tsintskiladze Laxton, 2023. "The Role of Biomass in Decarbonisation Efforts: Spatially Enriched Energy System Optimisation Modelling," Energies, MDPI, vol. 16(21), pages 1-18, October.
    2. Mariusz Jerzy Stolarski & Michał Krzyżaniak & Ewelina Olba-Zięty & Jakub Stolarski, 2023. "Changes in Commercial Dendromass Properties Depending on Type and Acquisition Time," Energies, MDPI, vol. 16(24), pages 1-20, December.
    3. Stolarski, Mariusz J. & Stachowicz, Paweł & Dudziec, Paweł, 2022. "Wood pellet quality depending on dendromass species," Renewable Energy, Elsevier, vol. 199(C), pages 498-508.
    4. Mariusz Jerzy Stolarski & Natalia Wojciechowska & Mateusz Seliwiak & Tomasz Krzysztof Dobrzański, 2024. "Properties of Forest Tree Branches as an Energy Feedstock in North-Eastern Poland," Energies, MDPI, vol. 17(8), pages 1-18, April.
    5. Dudziec, Paweł & Stachowicz, Paweł & Stolarski, Mariusz J., 2023. "Diversity of properties of sawmill residues used as feedstock for energy generation," Renewable Energy, Elsevier, vol. 202(C), pages 822-833.
    6. Jakub Stolarski & Sławomir Wierzbicki & Szymon Nitkiewicz & Mariusz Jerzy Stolarski, 2023. "Wood Chip Production Efficiency Depending on Chipper Type," Energies, MDPI, vol. 16(13), pages 1-15, June.

    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. Anerud, Erik & Jirjis, Raida & Larsson, Gunnar & Eliasson, Lars, 2018. "Fuel quality of stored wood chips – Influence of semi-permeable covering material," Applied Energy, Elsevier, vol. 231(C), pages 628-634.
    2. Eriksson, Anders & Eliasson, Lars & Sikanen, Lauri & Hansson, Per-Anders & Jirjis, Raida, 2017. "Evaluation of delivery strategies for forest fuels applying a model for Weather-driven Analysis of Forest Fuel Systems (WAFFS)," Applied Energy, Elsevier, vol. 188(C), pages 420-430.
    3. Eliasson, Lars & Eriksson, Anders & Mohtashami, Sima, 2017. "Analysis of factors affecting productivity and costs for a high-performance chip supply system," Applied Energy, Elsevier, vol. 185(P1), pages 497-505.
    4. Prinz, Robert & Väätäinen, Kari & Laitila, Juha & Sikanen, Lauri & Asikainen, Antti, 2019. "Analysis of energy efficiency of forest chip supply systems using discrete-event simulation," Applied Energy, Elsevier, vol. 235(C), pages 1369-1380.
    5. Mobtaker, A. & Ouhimmou, M. & Audy, J.-F. & Rönnqvist, M., 2021. "A review on decision support systems for tactical logistics planning in the context of forest bioeconomy," Renewable and Sustainable Energy Reviews, Elsevier, vol. 148(C).
    6. Guelpa, Elisa, 2021. "Impact of thermal masses on the peak load in district heating systems," Energy, Elsevier, vol. 214(C).
    7. Andrea Menapace & Simone Santopietro & Rudy Gargano & Maurizio Righetti, 2021. "Stochastic Generation of District Heat Load," Energies, MDPI, vol. 14(17), pages 1-17, August.
    8. Gao, Datong & Zhao, Bin & Kwan, Trevor Hocksun & Hao, Yong & Pei, Gang, 2022. "The spatial and temporal mismatch phenomenon in solar space heating applications: status and solutions," Applied Energy, Elsevier, vol. 321(C).
    9. Frank Hensgen & Michael Wachendorf, 2018. "Aqueous Leaching Prior to Dewatering Improves the Quality of Solid Fuels from Grasslands," Energies, MDPI, vol. 11(4), pages 1-13, April.
    10. Xue, Puning & Zhou, Zhigang & Fang, Xiumu & Chen, Xin & Liu, Lin & Liu, Yaowen & Liu, Jing, 2017. "Fault detection and operation optimization in district heating substations based on data mining techniques," Applied Energy, Elsevier, vol. 205(C), pages 926-940.
    11. Francesco Neirotti & Michel Noussan & Stefano Riverso & Giorgio Manganini, 2019. "Analysis of Different Strategies for Lowering the Operation Temperature in Existing District Heating Networks," Energies, MDPI, vol. 12(2), pages 1-17, January.
    12. Zhang, Fan & Bales, Chris & Fleyeh, Hasan, 2021. "Night setback identification of district heat substations using bidirectional long short term memory with attention mechanism," Energy, Elsevier, vol. 224(C).
    13. Kensby, Johan & Trüschel, Anders & Dalenbäck, Jan-Olof, 2015. "Potential of residential buildings as thermal energy storage in district heating systems – Results from a pilot test," Applied Energy, Elsevier, vol. 137(C), pages 773-781.
    14. Leanda C. Garvie & David J. Lee & Biljana Kulišić, 2024. "Towards a Bioeconomy: Supplying Forest Residues for the Australian Market," Energies, MDPI, vol. 17(2), pages 1-19, January.
    15. Talebi, Behrang & Haghighat, Fariborz & Tuohy, Paul & Mirzaei, Parham A., 2018. "Validation of a community district energy system model using field measured data," Energy, Elsevier, vol. 144(C), pages 694-706.
    16. Hirvijoki, Eero & Hirvonen, Janne, 2022. "The potential of intermediate-to-deep geothermal boreholes for seasonal storage of district heat," Renewable Energy, Elsevier, vol. 198(C), pages 825-832.
    17. Mosayeb Dashtpeyma & Reza Ghodsi, 2021. "Forest Biomass and Bioenergy Supply Chain Resilience: A Systematic Literature Review on the Barriers and Enablers," Sustainability, MDPI, vol. 13(12), pages 1-21, June.
    18. Ferla, G. & Caputo, P., 2022. "Biomass district heating system in Italy: A comprehensive model-based method for the assessment of energy, economic and environmental performance," Energy, Elsevier, vol. 244(PB).
    19. Danica Djurić Ilić, 2020. "Classification of Measures for Dealing with District Heating Load Variations—A Systematic Review," Energies, MDPI, vol. 14(1), pages 1-27, December.
    20. Shamshirband, Shahaboddin & Petković, Dalibor & Enayatifar, Rasul & Hanan Abdullah, Abdul & Marković, Dušan & Lee, Malrey & Ahmad, Rodina, 2015. "Heat load prediction in district heating systems with adaptive neuro-fuzzy method," Renewable and Sustainable Energy Reviews, Elsevier, vol. 48(C), pages 760-767.

    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:jeners:v:14:y:2021:i:21:p:6877-:d:660755. 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.