Waste and Biomass Valorization

, Volume 6, Issue 3, pp 327–333 | Cite as

Determination of the Higher Heating Value of Pig Manure

  • R. Wnetrzak
  • D. J. M. Hayes
  • L. S. Jensen
  • J. J. Leahy
  • W. Kwapinski
Original Paper


The ability of using novel method of near-infrared (NIR) spectra to predict the composition and higher heating value (HHV) of dry pig manure was examined. Number of pig manure solid fractions variously pre-treated samples were collected in Denmark, from different pig slurry treatment plants (using mechanical or chemical–mechanical separation) and then analysed for their energy values. These values were determined by conventional method using bomb calorimetry and also calculated based on ultimate analysis. NIR spectra method was successfully applied and reasonable R2 values were obtained for the independent prediction set for nitrogen, ash, and the HHV. NIR also showed ability for predicting which type of treatment plants the samples came from. In addition, new empirical equations, based on ultimate analyses of pig manure solids used for prediction of the HHV was established.


Higher heating value Pig manure Near-infrared Slurry Energy 



This research was partially supported by The Danish Council for Strategic Research, Danish Ministry of Science, Technology and Innovation, the program for sustainable energy and environment the project CLEANWASTE (Project No. J. nr. 2104-09-0056).


  1. 1.
    Gerber, P.J., Steinfeld, H., Henderson, B., Mottet, A., Opio, C., Dijkman, J., Falcucci, A., Tempio, G.: Tackling climate change through livestock: a global assessment of emissions and mitigation opportunities. Food and Agriculture Organization of the United Nations (FAO), Rome (2013)Google Scholar
  2. 2.
    Irish Statute Book Statutory Instrument No 610/2010—European Communities (Good Agricultural Practice for Protection of Waters) Regulations http://www.irishstatutebookie/2010/en/si/0610html (2010). Accessed 18 July 2010
  3. 3.
    Thipkhunthod, P., Meeyoo, V., Rangsunvigit, P., Kitiyanan, B., Siemanond, K., Rirksomboon, T.: Predicting the heating value of sewage sludges in Thailand from proximate and ultimate analyses. Fuel 84, 849–857 (2005)CrossRefGoogle Scholar
  4. 4.
    Jenkins, B.M.: Physical properties of biomass. In: Kitani, O., Hall, C.W. (eds.) Biomass Handbook Chap Gordon and Breach New York NY (1989)Google Scholar
  5. 5.
    Jørgensen, K., Jensen, L.S.: Chemical and biochemical variation in animal manure solids separated using different commercial separation technologies. Bioresour. Technol 100, 3088–3096 (2009)CrossRefGoogle Scholar
  6. 6.
    Huang, C., Han, L., Yang, Z., Liu, X.: Prediction of heating value of straw by proximate data, and near infrared spectroscopy. Energy Convers. Manag 49, 3433–3438 (2008)CrossRefGoogle Scholar
  7. 7.
    Sørensen, L.K., Sørensen, P., Birkmose, T.S.: Application of reflectance near infrared spectroscopy for animal slurry analysis. Soil Sci. Soc. Am. J 71, 1398–1405 (2007)CrossRefGoogle Scholar
  8. 8.
    Huang, G., Han, L., Yang, Z., Wang, X.: Evaluation of the nutrient metal content in Chinese animal manure compost using near infrared spectroscopy (NIRS). Bioresour. Technol 99, 8164–8169 (2008)CrossRefGoogle Scholar
  9. 9.
    Saeys, W., Mouazen, A.M., Ramon, H.: Potential for onsite and online analysis of pig manure using visible and near infrared reflectance spectroscopy. Biosyst. Eng 91, 393–402 (2005)CrossRefGoogle Scholar
  10. 10.
    Hayes, D.J.M.: Development of near infrared spectroscopy models for the quantitative prediction of the lignocellulosic components of wet Miscanthus samples. Bioresour. Technol. 119, 393–405 (2012)CrossRefGoogle Scholar
  11. 11.
    Wold, S., Sjostrom, M., Eriksson, L.: PLS-regression: a basic tool of chemometrics. Chemom. Intell. Lab. 58, 109–130 (2001)CrossRefGoogle Scholar
  12. 12.
    Savitzky, A., Golay, M.J.E.: Smoothing and differentiation of data by simplified least squares procedures. Anal. Chem 36, 1627–1639 (1964)CrossRefGoogle Scholar
  13. 13.
    Workman, J.J.: NIR spectroscopy calibration basics. In: Burns, D.A., Ciurczak. E.W., Dekker. M. (eds.) Handbook of Near Infrared Analysis, 2nd ed. New York (2001)Google Scholar
  14. 14.
    Friedl, A., Padouvas, E., Rotter, H., Varmuza, K.: Prediction of heating values of biomass fuel from elemental composition. Anal. Chim. Acta 544, 191–198 (2005)CrossRefGoogle Scholar
  15. 15.
    Demirbas, A., Güllü, D., Caglar, A., Akdeniz, F.: Determination of calorific values of fuel from lignocellulosics. Energ. Source 19, 765–770 (1997)CrossRefGoogle Scholar
  16. 16.
    Moller, H.B., Sommer, S.G., Ahring, B.K.: Separation efficiency and particle size distribution in relation to manure type and storage conditions. Bioresour. Technol 85, 189–196 (2002)CrossRefGoogle Scholar
  17. 17.
    van Kessel, J.S., Reeves, J.B., Meisinger, J.J.: Storage and handling can alter the mineralization characteristics of manure. J. Environ. Qual 28, 1984–1990 (1999)CrossRefGoogle Scholar
  18. 18.
    Hansen, M.N., Henriksen, K., Sommer, S.G.: Observations of production and emission of greenhouse gases and ammonia during storage of solids separated from pig slurry: effects of covering. Atmos. Environ 40, 4172–4181 (2006)CrossRefGoogle Scholar
  19. 19.
    Petersen, J., Sørensen, P.: Loss of nitrogen and carbon during storage of the fibrous fraction of separated pig slurry and influence on nitrogen availability. J. Agric. Sci 146, 403–413 (2008)CrossRefGoogle Scholar
  20. 20.
    Elemental Analysis Fakultät für Chemie Mikroanalytisches Laboratorium Universitat Wien available URL http://www.univieacat/Mikrolabor/chn_enghtm#Interferenzen (2014). Accessed 18 July 2014
  21. 21.
    Naramabuye, F.X., Haynes, R.J.: The liming effect of five organic manures when incubated with an acid soil. J. Plant Nutr. Soil Sci 170, 615–622 (2007)CrossRefGoogle Scholar
  22. 22.
    Sommer, S.G., Husted, S.: The chemical buffer system in raw and digested animal slurry. J. Agri. Sci 124, 45–53 (1995)CrossRefGoogle Scholar
  23. 23.
    Demirbas, A.: Calculation of higher heating values of biomass fuels. Fuel 76, 431–434 (1997)CrossRefGoogle Scholar
  24. 24.
    Yin, C.-Y.: Prediction of higher heating values of biomass from proximate and ultimate analyses. Fuel 90, 1128–1132 (2011)CrossRefGoogle Scholar
  25. 25.
    Channiwala, S., Parikh, P.: A unified correlation for estimating HHV of solid liquid and gaseous fuels. Fuel 81, 1051–1063 (2002)CrossRefGoogle Scholar
  26. 26.
    Jablonský, M., Ház, A., Orságová, A., Botková, M., Šmatko, L., Kočiš, J.: Relationships between elemental carbon contentsand heating values of lignins. In: Proceedings of the 4th International Conference Renewable Energy Sources (2013)Google Scholar

Copyright information

© Springer Science+Business Media Dordrecht 2015

Authors and Affiliations

  • R. Wnetrzak
    • 1
  • D. J. M. Hayes
    • 1
    • 2
  • L. S. Jensen
    • 3
  • J. J. Leahy
    • 1
  • W. Kwapinski
    • 1
  1. 1.Carbolea Research Group, Department of Chemical and Environmental ScienceUniversity of LimerickLimerickIreland
  2. 2.Celignis Limited, Nexus Innovation CentreUniversity of LimerickLimerickIreland
  3. 3.Department of Agriculture and Ecology, Faculty of ScienceUniversity of CopenhagenFrederiksbergDenmark

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