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Biochar for Vertical Greenery Systems

Author

Listed:
  • Michal Kraus

    (Department of Civil Engineering, Institute of Technology and Business in České Budějovice, Okružní 517/10, 370 01 České Budějovice, Czech Republic)

  • Kateřina Žáková

    (Department of Statistics and Operation Analysis, Faculty of Business and Economics, Mendel University in Brno, Zemědělská 1, 613 00 Brno, Czech Republic)

  • Jaroslav Žák

    (Department of Civil Engineering, Institute of Technology and Business in České Budějovice, Okružní 517/10, 370 01 České Budějovice, Czech Republic)

Abstract

Vertical greenery systems (VGS) are effective at solving urban heat. They can absorb noise pollution and dust, and, aesthetically, they are positively perceived. Systems using hydroponic irrigation and nutrition, in combination with mineral wool as a base, are light and effective (they are able to hold water, with a high percentage of air, and a good mechanical structure to hold the plant stable). However, the functionality of a system can be compromised if the water supply is depleted or the irrigation system fails. This deficiency can be partially remedied if a certain amount of biochar or a suitable organic fertilizer is also a part of the system. The research task consisted of verifying this assumption and determining the effective amount of the biochar. Samples with different amounts of biochar were examined under the same temperature and humidity conditions; extended drying times, additional costs, and safety tank size savings were found. Subsequently, the effective amount of the biochar was determined by the Data Envelopment Analysis (DEA) method. It has been experimentally verified that biochar has a positive effect and prolongs the drying time; the additional costs are almost offset by the benefits. It should be noted that the results are valid for central Europe, and may be modified for different climate and economic zones.

Suggested Citation

  • Michal Kraus & Kateřina Žáková & Jaroslav Žák, 2020. "Biochar for Vertical Greenery Systems," Energies, MDPI, vol. 13(23), pages 1-13, November.
  • Handle: RePEc:gam:jeners:v:13:y:2020:i:23:p:6320-:d:453855
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    References listed on IDEAS

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    1. Karishma Asarpota & Vincent Nadin, 2020. "Energy Strategies, the Urban Dimension, and Spatial Planning," Energies, MDPI, vol. 13(14), pages 1-25, July.
    2. Vojtěch Máca & Jan Melichar, 2016. "The Health Costs of Revised Coal Mining Limits in Northern Bohemia," Energies, MDPI, vol. 9(2), pages 1-20, January.
    3. Charnes, A. & Cooper, W. W. & Rhodes, E., 1978. "Measuring the efficiency of decision making units," European Journal of Operational Research, Elsevier, vol. 2(6), pages 429-444, November.
    4. Manso, Maria & Castro-Gomes, João, 2015. "Green wall systems: A review of their characteristics," Renewable and Sustainable Energy Reviews, Elsevier, vol. 41(C), pages 863-871.
    5. Jiayu Li & Bohong Zheng & Wenquan Shen & Yanfen Xiang & Xiao Chen & Zhiyong Qi, 2019. "Cooling and Energy-Saving Performance of Different Green Wall Design: A Simulation Study of a Block," Energies, MDPI, vol. 12(15), pages 1-17, July.
    6. Sri Yuliani & Gagoek Hardiman & Erni Setyowati, 2020. "Green-Roof: The Role of Community in the Substitution of Green-Space toward Sustainable Development," Sustainability, MDPI, vol. 12(4), pages 1-14, February.
    7. Łukasz Pardela & Tomasz Kowalczyk & Adam Bogacz & Dorota Kasowska, 2020. "Sustainable Green Roof Ecosystems: 100 Years of Functioning on Fortifications—A Case Study," Sustainability, MDPI, vol. 12(11), pages 1-21, June.
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