IDEAS home Printed from https://ideas.repec.org/a/eee/renene/v163y2021icp105-122.html
   My bibliography  Save this article

Valorization of lignite wastes into humic acids: Process optimization, energy efficiency and structural features analysis

Author

Listed:
  • Sarlaki, Ehsan
  • Sharif Paghaleh, Ali
  • Kianmehr, Mohammad Hossein
  • Asefpour Vakilian, Keyvan

Abstract

The present work investigates the optimization of humic acids (HAs) production from lignite processing wastes using a developed mechanical agitated (MA) tank reactor based on the results of response surface methodology (RSM). The structures of the obtained HAs were characterized using elemental analysis, spectroscopy, scanning electron microscopy (SEM), particle size distribution (PSD), acidic functional groups, and ash content. The highest extraction efficiency of HA was 54.2%, which was obtained from the MA tank reactor under optimal conditions of using 0.5 M NaOH, the reaction time of 4 h, stirring speed of 850 rpm, and temperature of 70 °C. The developed MA tank reactor was capable of improving the HA extraction and energy efficiency of the process up to 26.9% and 24.8%, respectively, compared to the conventional magnetic stirred (MS) glass reactor. The extracted HA from the MA tank reactor exerted better quality indices, including higher oxygen content (37.02%), higher C/N and O/C ratios (61.26 and 0.47, respectively), higher total acidity and phenolic-OH contents (8.87 and 5.6 meq.g−1, respectively), higher E4/E6 ratio (3.765), more homogeneously porous structure, higher specific surface area, lower H/C ratio (0.64), and lower ash content (2.2%), than the MS method, which indicate its suitability in agricultural applications.

Suggested Citation

  • Sarlaki, Ehsan & Sharif Paghaleh, Ali & Kianmehr, Mohammad Hossein & Asefpour Vakilian, Keyvan, 2021. "Valorization of lignite wastes into humic acids: Process optimization, energy efficiency and structural features analysis," Renewable Energy, Elsevier, vol. 163(C), pages 105-122.
    • Handle: RePEc:eee:renene:v:163:y:2021:i:c:p:105-122
    DOI: 10.1016/j.renene.2020.08.096
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0960148120313410
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.renene.2020.08.096?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Jack P. C. Kleijnen, 2015. "Response Surface Methodology," International Series in Operations Research & Management Science, in: Michael C Fu (ed.), Handbook of Simulation Optimization, edition 127, chapter 0, pages 81-104, Springer.
    2. Betiku, Eriola & Okunsolawo, Samuel S. & Ajala, Sheriff O. & Odedele, Olatunde S., 2015. "Performance evaluation of artificial neural network coupled with generic algorithm and response surface methodology in modeling and optimization of biodiesel production process parameters from shea tr," Renewable Energy, Elsevier, vol. 76(C), pages 408-417.
    3. Banerjee, Avik & Guria, Chandan & Maiti, Subodh K., 2016. "Fertilizer assisted optimal cultivation of microalgae using response surface method and genetic algorithm for biofuel feedstock," Energy, Elsevier, vol. 115(P1), pages 1272-1290.
    4. Singh, Rishikesh Kumar & Chakraborty, Jyoti Prasad & Sarkar, Arnab, 2020. "Optimizing the torrefaction of pigeon pea stalk (cajanus cajan) using response surface methodology (RSM) and characterization of solid, liquid and gaseous products," Renewable Energy, Elsevier, vol. 155(C), pages 677-690.
    5. Betiku, Eriola & Omilakin, Oluwasesan Ropo & Ajala, Sheriff Olalekan & Okeleye, Adebisi Aminat & Taiwo, Abiola Ezekiel & Solomon, Bamidele Ogbe, 2014. "Mathematical modeling and process parameters optimization studies by artificial neural network and response surface methodology: A case of non-edible neem (Azadirachta indica) seed oil biodiesel synth," Energy, Elsevier, vol. 72(C), pages 266-273.
    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. Chen, Qi & Qu, Zhaoming & Ma, Guohua & Wang, Wenjing & Dai, Jiaying & Zhang, Min & Wei, Zhanbo & Liu, Zhiguang, 2022. "Humic acid modulates growth, photosynthesis, hormone and osmolytes system of maize under drought conditions," Agricultural Water Management, Elsevier, vol. 263(C).
    2. Nassef, Ahmed M. & Sayed, Enas T. & Rezk, Hegazy & Inayat, Abrar & Yousef, Bashria A.A. & Abdelkareem, Mohammad A. & Olabi, A.G., 2020. "Developing a fuzzy-model with particle swarm optimization-based for improving the conversion and gasification rate of palm kernel shell," Renewable Energy, Elsevier, vol. 166(C), pages 125-135.
    3. Esmaili, Maryam & Aliniaeifard, Sasan & Mashal, Mahmoud & Vakilian, Keyvan Asefpour & Ghorbanzadeh, Parisa & Azadegan, Behzad & Seif, Mehdi & Didaran, Fardad, 2021. "Assessment of adaptive neuro-fuzzy inference system (ANFIS) to predict production and water productivity of lettuce in response to different light intensities and CO2 concentrations," Agricultural Water Management, Elsevier, vol. 258(C).

    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. Aghbashlo, Mortaza & Hosseinpour, Soleiman & Tabatabaei, Meisam & Dadak, Ali, 2017. "Fuzzy modeling and optimization of the synthesis of biodiesel from waste cooking oil (WCO) by a low power, high frequency piezo-ultrasonic reactor," Energy, Elsevier, vol. 132(C), pages 65-78.
    2. Muhammad, Gul & Potchamyou Ngatcha, Ange Douglas & Lv, Yongkun & Xiong, Wenlong & El-Badry, Yaser A. & Asmatulu, Eylem & Xu, Jingliang & Alam, Md Asraful, 2022. "Enhanced biodiesel production from wet microalgae biomass optimized via response surface methodology and artificial neural network," Renewable Energy, Elsevier, vol. 184(C), pages 753-764.
    3. Najafi, Gholamhassan & Ghobadian, Barat & Yusaf, Talal & Safieddin Ardebili, Seyed Mohammad & Mamat, Rizalman, 2015. "Optimization of performance and exhaust emission parameters of a SI (spark ignition) engine with gasoline–ethanol blended fuels using response surface methodology," Energy, Elsevier, vol. 90(P2), pages 1815-1829.
    4. Iftikhar Ahmad & Adil Sana & Manabu Kano & Izzat Iqbal Cheema & Brenno C. Menezes & Junaid Shahzad & Zahid Ullah & Muzammil Khan & Asad Habib, 2021. "Machine Learning Applications in Biofuels’ Life Cycle: Soil, Feedstock, Production, Consumption, and Emissions," Energies, MDPI, vol. 14(16), pages 1-27, August.
    5. Pirmoradi, Neda & Ghaneian, Mohammad Taghi & Ehrampoush, Mohammad Hassan & Salmani, Mohammad Hossein & Hatami, Behnam, 2021. "The conversion of poultry slaughterhouse wastewater sludge into biodiesel: Process modeling and optimization," Renewable Energy, Elsevier, vol. 178(C), pages 1236-1249.
    6. Soltanali, Hamzeh & Nikkhah, Amin & Rohani, Abbas, 2017. "Energy audit of Iranian kiwifruit production using intelligent systems," Energy, Elsevier, vol. 139(C), pages 646-654.
    7. Anietie O. Etim & Eriola Betiku & Sheriff O. Ajala & Peter J. Olaniyi & Tunde V. Ojumu, 2018. "Potential of Ripe Plantain Fruit Peels as an Ecofriendly Catalyst for Biodiesel Synthesis: Optimization by Artificial Neural Network Integrated with Genetic Algorithm," Sustainability, MDPI, vol. 10(3), pages 1-15, March.
    8. Sukiran, Mohamad Azri & Wan Daud, Wan Mohd Ashri & Abnisa, Faisal & Nasrin, Abu Bakar & Abdul Aziz, Astimar & Loh, Soh Kheang, 2021. "A comprehensive study on torrefaction of empty fruit bunches: Characterization of solid, liquid and gas products," Energy, Elsevier, vol. 230(C).
    9. Ong, Hwai Chyuan & Yu, Kai Ling & Chen, Wei-Hsin & Pillejera, Ma Katreena & Bi, Xiaotao & Tran, Khanh-Quang & Pétrissans, Anelie & Pétrissans, Mathieu, 2021. "Variation of lignocellulosic biomass structure from torrefaction: A critical review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 152(C).
    10. He, Yuan & Meng, Zhiyi & Xu, Hong & Zou, Yue, 2020. "A dynamic model of evaluating differential automatic method for solving plane problems based on BP neural network algorithm," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 556(C).
    11. Abiola Ezekiel Taiwo & Tafirenyika Nyamayaro Madzimbamuto & Tunde Victor Ojumu, 2018. "Optimization of Corn Steep Liquor Dosage and Other Fermentation Parameters for Ethanol Production by Saccharomyces cerevisiae Type 1 and Anchor Instant Yeast," Energies, MDPI, vol. 11(7), pages 1-20, July.
    12. Takeno, Mitsuo L. & Mendonça, Iasmin M. & Barros, Silma de S. & de Sousa Maia, Paulo J. & Pessoa Jr., Wanison A.G. & Souza, Mayane P. & Soares, Elzalina R. & Bindá, Rosane dos S. & Calderaro, Fábio L., 2021. "A novel CaO-based catalyst obtained from silver croaker (Plagioscion squamosissimus) stone for biodiesel synthesis: Waste valorization and process optimization," Renewable Energy, Elsevier, vol. 172(C), pages 1035-1045.
    13. Atmanli, Alpaslan & Ileri, Erol & Yilmaz, Nadir, 2016. "Optimization of diesel–butanol–vegetable oil blend ratios based on engine operating parameters," Energy, Elsevier, vol. 96(C), pages 569-580.
    14. Kusumo, F. & Silitonga, A.S. & Masjuki, H.H. & Ong, Hwai Chyuan & Siswantoro, J. & Mahlia, T.M.I., 2017. "Optimization of transesterification process for Ceiba pentandra oil: A comparative study between kernel-based extreme learning machine and artificial neural networks," Energy, Elsevier, vol. 134(C), pages 24-34.
    15. Sajjadi, Baharak & Raman, Abdul Aziz Abdul & Arandiyan, Hamidreza, 2016. "A comprehensive review on properties of edible and non-edible vegetable oil-based biodiesel: Composition, specifications and prediction models," Renewable and Sustainable Energy Reviews, Elsevier, vol. 63(C), pages 62-92.
    16. Shen-Tsu Wang, 2016. "Integrating grey sequencing with the genetic algorithm--immune algorithm to optimise touch panel cover glass polishing process parameter design," International Journal of Production Research, Taylor & Francis Journals, vol. 54(16), pages 4882-4893, August.
    17. Yek, Peter Nai Yuh & Cheng, Yoke Wang & Liew, Rock Keey & Wan Mahari, Wan Adibah & Ong, Hwai Chyuan & Chen, Wei-Hsin & Peng, Wanxi & Park, Young-Kwon & Sonne, Christian & Kong, Sieng Huat & Tabatabaei, 2021. "Progress in the torrefaction technology for upgrading oil palm wastes to energy-dense biochar: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 151(C).
    18. Qin, Caiyan & Kim, Joong Bae & Lee, Bong Jae, 2019. "Performance analysis of a direct-absorption parabolic-trough solar collector using plasmonic nanofluids," Renewable Energy, Elsevier, vol. 143(C), pages 24-33.
    19. Kaushik, Lav Kumar & Muthukumar, P., 2020. "Thermal and economic performance assessments of waste cooking oil /kerosene blend operated pressure cook-stove with porous radiant burner," Energy, Elsevier, vol. 206(C).
    20. Yaman, Hayri & Yesilyurt, Murat Kadir & Uslu, Samet, 2022. "Simultaneous optimization of multiple engine parameters of a 1-heptanol / gasoline fuel blends operated a port-fuel injection spark-ignition engine using response surface methodology approach," Energy, Elsevier, vol. 238(PC).

    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:eee:renene:v:163:y:2021:i:c:p:105-122. 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: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/renewable-energy .

    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.