IDEAS home Printed from https://ideas.repec.org/a/eee/chsofr/v82y2016icp125-130.html

Dynamic characterization of an anaerobic digester during the start-up phase by pH time-series analysis

Author

Listed:
  • Garcia-Solano, Magnolia
  • Méndez-Acosta, Hugo O.
  • Puebla, Hector
  • Hernandez-Martinez, Eliseo

Abstract

In this paper, an alternative methodology for the online monitoring of key variables during the start-up phase of continuous anaerobic digestion processes is presented. The proposal is based on the application of fractal analysis to pH time-series obtained from a lab-scale fixed-bed reactor (FBR) used in the tequila vinasses treatment. Results showed that fractal parameters exhibit a dynamic behavior closely related to that of key process variables such that, chemical oxygen demand (COD), volatile fatty acids (VFA) and biogas production, whose on-line monitoring is difficult and expensive in practice. Thus, the industrial implementation of the here proposed ideas is quite encouraging, since it is shown that fractal analysis of conventional pH signals can be used as an inexpensive and easy to implement tool for anaerobic digesters diagnosis, which could drastically reduce the time and problems currently associated to the start-up phase.

Suggested Citation

  • Garcia-Solano, Magnolia & Méndez-Acosta, Hugo O. & Puebla, Hector & Hernandez-Martinez, Eliseo, 2016. "Dynamic characterization of an anaerobic digester during the start-up phase by pH time-series analysis," Chaos, Solitons & Fractals, Elsevier, vol. 82(C), pages 125-130.
    • Handle: RePEc:eee:chsofr:v:82:y:2016:i:c:p:125-130
    DOI: 10.1016/j.chaos.2015.11.015
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S096007791500380X
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.chaos.2015.11.015?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

    for a different version of it.

    References listed on IDEAS

    as
    1. John Geweke & Susan Porter‐Hudak, 1983. "The Estimation And Application Of Long Memory Time Series Models," Journal of Time Series Analysis, Wiley Blackwell, vol. 4(4), pages 221-238, July.
    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. Romero-Bustamante, Jorge A. & Velazquez-Camilo, Oscar & Garcia‐Hernandez, Ángeles & Rivera, Victor M. & Hernandez-Martinez, Eliseo, 2022. "Monitoring of cane sugar crystallization process by multiscale time-series analysis," Chaos, Solitons & Fractals, Elsevier, vol. 156(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. Mohamed CHIKHI & Claude DIEBOLT, 2022. "Testing the weak form efficiency of the French ETF market with the LSTAR-ANLSTGARCH approach using a semiparametric estimation," Eastern Journal of European Studies, Centre for European Studies, Alexandru Ioan Cuza University, vol. 13, pages 228-253, June.
    2. Jinquan Liu & Tingguo Zheng & Jianli Sui, 2008. "Dual long memory of inflation and test of the relationship between inflation and inflation uncertainty," Psychometrika, Springer;The Psychometric Society, vol. 3(2), pages 240-254, June.
    3. Erhard Reschenhofer & Manveer K. Mangat, 2021. "Fast computation and practical use of amplitudes at non-Fourier frequencies," Computational Statistics, Springer, vol. 36(3), pages 1755-1773, September.
    4. Pierre Perron & Zhongjun Qu, 2007. "An Analytical Evaluation of the Log-periodogram Estimate in the Presence of Level Shifts," Boston University - Department of Economics - Working Papers Series wp2007-044, Boston University - Department of Economics.
    5. Gil-Alana, L.A., 2006. "Fractional integration in daily stock market indexes," Review of Financial Economics, Elsevier, vol. 15(1), pages 28-48.
    6. Richard T. Baillie & Fabio Calonaci & Dooyeon Cho & Seunghwa Rho, 2019. "Long Memory, Realized Volatility and HAR Models," Working Papers 881, Queen Mary University of London, School of Economics and Finance.
    7. Magazzino, Cosimo & Drago, Carlo & Schneider, Nicolas, 2023. "Evidence of supply security and sustainability challenges in Nigeria’s power sector," Utilities Policy, Elsevier, vol. 82(C).
    8. Guglielmo Maria Caporale & Luis A. Gil-Alana, 2020. "Modelling Loans to Non-Financial Corporations within the Eurozone: A Long-Memory Approach," CESifo Working Paper Series 8674, CESifo.
    9. Kai Wenger & Christian Leschinski & Philipp Sibbertsen, 2019. "Change-in-mean tests in long-memory time series: a review of recent developments," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 103(2), pages 237-256, June.
    10. Marie Busch & Philipp Sibbertsen, 2018. "An Overview of Modified Semiparametric Memory Estimation Methods," Econometrics, MDPI, vol. 6(1), pages 1-21, March.
    11. Bhandari, Avishek, 2020. "Long Memory and Correlation Structures of Select Stock Returns Using Novel Wavelet and Fractal Connectivity Networks," MPRA Paper 101946, University Library of Munich, Germany.
    12. Alan M. M. Leal & Stefan D'Amato & Igor V. M. Viveiros, 2021. "Short and long-run relations between capital netflows and the differential of american and brazilian interest rates," Textos para Discussão Cedeplar-UFMG 629, Cedeplar, Universidade Federal de Minas Gerais.
    13. Julien Chevallier & Benoît Sévi, 2011. "On the realized volatility of the ECX CO 2 emissions 2008 futures contract: distribution, dynamics and forecasting," Annals of Finance, Springer, vol. 7(1), pages 1-29, February.
    14. Adekoya, Oluwasegun B. & Oliyide, Johnson A., 2022. "Commodity and financial markets’ fear before and during COVID-19 pandemic: Persistence and causality analyses," Resources Policy, Elsevier, vol. 76(C).
    15. Yaya, OlaOluwa S. & Lukman, Adewale F. & Vo, Xuan Vinh, 2022. "Persistence and volatility spillovers of bitcoin price to gold and silver prices," Resources Policy, Elsevier, vol. 79(C).
    16. Papa Ousmane Cissé & Dominique Guégan & Abdou Kâ Diongue, 2018. "On parameters estimation of the Seasonal FISSAR Model," Documents de travail du Centre d'Economie de la Sorbonne 18018, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
    17. Alia Afzal & Philipp Sibbertsen, 2021. "Modeling fractional cointegration between high and low stock prices in Asian countries," Empirical Economics, Springer, vol. 60(2), pages 661-682, February.
    18. Mtiraoui, Amine & Boubaker, Heni & BelKacem, Lotfi, 2023. "A hybrid approach for forecasting bitcoin series," Research in International Business and Finance, Elsevier, vol. 66(C).
    19. Manveer Kaur Mangat & Erhard Reschenhofer, 2020. "Frequency-Domain Evidence for Climate Change," Econometrics, MDPI, vol. 8(3), pages 1-15, July.
    20. Federico Carlini & Paolo Santucci de Magistris, 2019. "Resuscitating the co-fractional model of Granger (1986)," CREATES Research Papers 2019-02, Department of Economics and Business Economics, Aarhus University.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    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:chsofr:v:82:y:2016:i:c:p:125-130. 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: Thayer, Thomas R. (email available below). General contact details of provider: https://www.journals.elsevier.com/chaos-solitons-and-fractals .

    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.