Comparison of the First Order and Modified First-Order Model for Biogas Production from Chicken Manure in Maiduguri, Borno State of Nigeria

Authors

  • Abdulhalim Musa Abubakar Department of Chemical Engineering, Faculty of Engineering, Modibbo Adama University, Nigeria
  • Abdulghaffaar Assayyidi Yusuf Department of Chemical Engineering, Faculty of Engineering, University of Maiduguri, Nigeria
  • Suleiman A. Wali Department of Chemical Engineering, Faculty of Engineering, Modibbo Adama University, Nigeria
  • Aliyu Buba Ngulde Department of Chemical Engineering, Faculty of Engineering, University of Maiduguri, Nigeria

DOI:

https://doi.org/10.55927/ijsmr.v1i2.3320

Keywords:

First-Order, Biogas Potential, Biogas Kinetics, Chicken Manure, NLREG, Maiduguri

Abstract

Maiduguri in North-Eastern Nigeria can boost of considerable amount of biogas generated from chicken manure (CM) if the organic waste is exploited for such purposes. The objective of this work is to determine the most accurate model for predicting biogas kinetic parameters by analyzing the CM empirical data obtained in Maiduguri. Biogas potential (BP) estimates using NLREG 6.6 software from the First Order and the Modified First-Order models gives BP = 10252217.1g and 83861.2925g respectively. The First Order model is the most correct kinetic model based on a careful assessment of statistical results gotten from both the ORIGIN and NLREG softwares. However, constant parameters estimated from the models, which would have helped significantly in optimizing future biogas production from CM are ambiguous and might be ascribed to errors in the biogas yield measurements or the inability of the selected models to effectively predict the constant parameters

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Published

2023-03-09

How to Cite

Abdulhalim Musa Abubakar, Abdulghaffaar Assayyidi Yusuf, Suleiman A. Wali, & Aliyu Buba Ngulde. (2023). Comparison of the First Order and Modified First-Order Model for Biogas Production from Chicken Manure in Maiduguri, Borno State of Nigeria. International Journal of Scientific Multidisciplinary Research, 1(2), 73–84. https://doi.org/10.55927/ijsmr.v1i2.3320

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