Skip to main content
SpringerLink
Log in

Co-composting of Biowaste: Simultaneous Optimization of the Process and Final Product Quality Using Simulation and Optimisation Tools

  • Original Paper
  • Published:
Waste and Biomass Valorization Aims and scope Submit manuscript

Abstract

To improve the financial sustainability and business management of composting facilities, mostly small-scale and manually operated facilities, the simultaneous optimization of the process and quality of the final product must be prioritized. This study used artificial neural networks (ANNs) and particle swarm optimization (PSO) as tools to evaluate the composting of biowaste (BW) with different cosubstrates (i. star grass (SG) and ii. a SG and sugarcane filter cake (SFC) mixture). The simulation aimed to maximize product quality in the shortest processing time by varying the mixing ratio and turning frequency. The simulation showed optimal conditions with a turning frequency of twice per week with the following mixtures: (i) BW:SG (72.9:27.1), 76 days of processing; and (ii) BW:SFC:SG (60:16:24), 88 days of processing. The results showed the effect of the type of carbon source in the cosubstrates on the retention time, which may imply the need for a larger area in composting facilities. On the other hand, the findings show that a minimum time is required to achieve a product that meets quality standards, although a longer processing time reduces the agricultural value of the compost. This model can be used to define design criteria and operating conditions and select a cosubstrate that can contribute to improving the agricultural quality of the final product.

Graphic Abstract

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7

Similar content being viewed by others

Abbreviations

ANN:

Artificial neural networks

BW:

Biowaste

MLP:

Multilayered perceptron

MR:

Mixing Ratio

R2 :

Coefficient of determination

RMSE:

Root mean square error

PSO:

Particle Swarm optimization

SFC:

Filter cake

SOM:

Self-organizing map

TOC:

Total organic carbon

TN:

Total nitrogen

TP:

Total phosphorus

TK:

Total potassium

TF:

Turning Frequency

SG:

Star Grass

References

  1. Abdelhafez, A.A., Abbas, M.H., Attia, T.M., El Bably, W., Mahrous, S.E.: Mineralization of organic carbon and nitrogen in semi-arid soils under organic and inorganic fertilization. Environl Technol Innov 9, 243–253 (2018)

    Article  Google Scholar 

  2. Lasaridi, K., Protopapa, I., Kotsou, M., Pilidis, G., Manios, T., Kyriacou, A.: Quality assessment of composts in the Greek market: the need for standards and quality assurance. J Environ Manage 80(1), 58–65 (2006). https://doi.org/10.1016/j.jenvman.2005.08.011

    Article  Google Scholar 

  3. Zhou, H., Zhao, Y., Yang, H., Zhu, L., Cai, B., Luo, S., Cao, J., Wei, Z.: Transformation of organic nitrogen fractions with different molecular weights during different organic wastes composting. Biores Technol 262, 221–228 (2018). https://doi.org/10.1016/j.biortech.2018.04.088

    Article  Google Scholar 

  4. Cesaro, A., Belgiorno, V., Guida, M.: Compost from organic solid waste: quality assessment and European regulations for its sustainable use. Resour Conserv Recycl 94, 72–79 (2015). https://doi.org/10.1016/j.resconrec.2014.11.003

    Article  Google Scholar 

  5. Thi, N., Kumar, G., Lin, C.-Y.: An overview of food waste management in developing countries: current status and future perspective. J Environ Manage 157, 220–229 (2015). https://doi.org/10.1016/j.jenvman.2015.04.022

    Article  Google Scholar 

  6. Campuzano, R., González-Martínez, S.: Characteristics of the organic fraction of municipal solid waste and methane production: a review. Waste Manage 54, 3–12 (2016). https://doi.org/10.1016/j.wasman.2016.05.016

    Article  Google Scholar 

  7. Oviedo, R., Marmolejo, L., Torres, P.: Advances in research on biowaste composting in small municipalities of developing countries. Lessons from Colombia. Revista Ingenieria Investigacion y Tecnologia 18(01) (2017).

  8. González, D., Colón, J., Gabriel, D., Sánchez, A.: The effect of the composting time on the gaseous emissions and the compost stability in a full-scale sewage sludge composting plant. Sci Total Environ 654, 311–323 (2019)

    Article  Google Scholar 

  9. Iqbal, M., Nadeem, A., Sherazi, F., Khan, R.: Optimization of process parameters for kitchen waste composting by response surface methodology. Int J Environ Sci Technol 12(5), 1759–1768 (2015)

    Article  Google Scholar 

  10. Bian, B., Hu, X., Zhang, S., Lv, C., Yang, Z., Yang, W., Zhang, L.: Pilot-scale composting of typical multiple agricultural wastes: parameter optimization and mechanisms. Biores Technol 287, 121482 (2019). https://doi.org/10.1016/j.biortech.2019.121482

    Article  Google Scholar 

  11. Onwosi, C.O., Igbokwe, V.C., Odimba, J.N., Eke, I.E., Nwankwoala, M.O., Iroh, I.N., Ezeogu, L.I.: Composting technology in waste stabilization: on the methods, challenges and future prospects. J Environ Manage 190, 140–157 (2017)

    Article  Google Scholar 

  12. Muscolo, A., Papalia, T., Settineri, G., Mallamaci, C., Jeske-Kaczanowska, A.: Are raw materials or composting conditions and time that most influence the maturity and/or quality of composts? comparison of obtained composts on soil properties. J Clean Prod 195, 93–101 (2018). https://doi.org/10.1016/j.jclepro.2018.05.204

    Article  Google Scholar 

  13. Fernández, C., Mateu, C., Moral, R., Sole-Mauri, F.: A predictor model for the composting process on an industrial scale based on Markov processes. Environ Model Softw 79, 156–166 (2016)

    Article  Google Scholar 

  14. Boem, F., Ferrari, R.M., Keliris, C., Parisini, T., Polycarpou, M.M.: A distributed networked approach for fault detection of large-scale systems. IEEE Trans Autom Control 62(1), 18–33 (2017)

    Article  MathSciNet  Google Scholar 

  15. Fernando, H., Surgenor, B.: An unsupervised artificial neural network versus a rule-based approach for fault detection and identification in an automated assembly machine. Robot Comput Integr Manuf 43, 79–88 (2017)

    Article  Google Scholar 

  16. Díaz, M., Eugenio, M., López, F., García, J., Yañez, R.: Neural models for optimizing lignocellulosic residues composting process. Waste Biomass Valorization 3(3), 319–331 (2012)

    Article  Google Scholar 

  17. Boniecki, P., Dach, J., Mueller, W., Koszela, K., Przybyl, J., Pilarski, K., Olszewski, T.: Neural prediction of heat loss in the pig manure composting process. Appl Therm Eng 58(1–2), 650–655 (2013)

    Article  Google Scholar 

  18. Kujawa, S., Nowakowski, K., Tomczak, R.J., Dach, J., Boniecki, P., Weres, J., Mueller, W., Raba, B., Piechota, T., Carmona, P.C.R.: Neural image analysis for maturity classification of sewage sludge composted with maize straw. Comput Electron Agric 109, 302–310 (2014)

    Article  Google Scholar 

  19. Soto-Paz, J., Alfonso-Morales, W., Caicedo-Bravo, E., Oviedo-Ocaña, E.R., Torres-Lozada, P., Manyoma, P.C., Sanchez, A., Komilis, D.: A New Approach for the Optimization of Biowaste Composting Using Artificial Neural Networks and Particle Swarm Optimization. Waste Biomass Valorization, 1–15 (2019).

  20. Soto-Paz, J., Oviedo-Ocaña, E.R., Manyoma, P.C., Gaviría-Cuevas, J.F., Marmolejo-Rebellón, L.F., Torres-Lozada, P., Sánchez, A., Komilis, D.: A Multi-criteria decision analysis of co-substrate selection to improve biowaste composting: a mathematical model applied to Colombia. Environ Process 6(3), 673–694 (2019)

    Article  Google Scholar 

  21. Soto-Paz, J., Oviedo-Ocaña, E.R., Manyoma-Velásquez, P.C., Torres-Lozada, P., Gea, T.: Evaluation of mixing ratio and frequency of turning in the co-composting of biowaste with sugarcane filter cake and star grass. Waste Manage 96, 86–95 (2019). https://doi.org/10.1016/j.wasman.2019.07.015

    Article  Google Scholar 

  22. Montejo, C., Costa, C., Márquez, M.C.: Influence of input material and operational performance on the physical and chemical properties of MSW compost. J Environ Manage 162, 240–249 (2015). https://doi.org/10.1016/j.jenvman.2015.07.059

    Article  Google Scholar 

  23. Zhang, L., Sun, X.: Influence of bulking agents on physical, chemical, and microbiological properties during the two-stage composting of green waste. Waste Manage 48, 115–126 (2016)

    Article  Google Scholar 

  24. Chang, J., Chen, Y.: Effects of bulking agents on food waste composting. Biores Technol 101(15), 5917–5924 (2010)

    Article  Google Scholar 

  25. de Guardia, A., Mallard, P., Teglia, C., Marin, A., Le Pape, C., Launay, M., Benoist, J.C., Petiot, C.: Comparison of five organic wastes regarding their behaviour during composting: part 1, biodegradability, stabilization kinetics and temperature rise. Waste Manage 30(3), 402–414 (2010)

    Article  Google Scholar 

  26. Li, Z., Lu, H., Ren, L., He, L.: Experimental and modeling approaches for food waste composting: a review. Chemosphere 93(7), 1247–1257 (2013). https://doi.org/10.1016/j.chemosphere.2013.06.064

    Article  Google Scholar 

  27. Zaborowicz, M., Wojcieszak, D., Górna, K., Kujawa, S., Kozłowski, R., Przybył, K., Mioduszewska, N., Idziaszek, P., Boniecki, P.: Determination of dry matter content in composted material based on digital images of compost taken under mixed visible and UV-A light. In: Eighth International Conference on Digital Image Processing (ICDIP 2016) 2016, p. 100332G. International Society for Optics and Photonics

  28. Kohonen, T.: Self-organized formation of topologically correct feature maps. Biol Cybern 43(1), 59–69 (1982)

    Article  MathSciNet  Google Scholar 

  29. Beltramo, T., Ranzan, C., Hinrichs, J., Hitzmann, B.: Artificial neural network prediction of the biogas flow rate optimised with an ant colony algorithm. Biosys Eng 143, 68–78 (2016). https://doi.org/10.1016/j.biosystemseng.2016.01.006

    Article  Google Scholar 

  30. Barrena, R., Lima, F.V., Bolasell, M.A.G., Gea, T., Ferrer, A.S.: Respirometric assays at fixed and process temperatures to monitor composting process. Biores Technol 96(10), 1153–1159 (2005)

    Article  Google Scholar 

  31. Bueno, P., Yanez, R., Rivera, A., Diaz, M.: Modelling of parameters for optimization of maturity in composting trimming residues. Biores Technol 100(23), 5859–5864 (2009)

    Article  Google Scholar 

  32. Sharma, D., Yadav, K.D., Kumar, S.: Biotransformation of flower waste composting: optimization of waste combinations using response surface methodology. Biores Technol 270, 198–207 (2018). https://doi.org/10.1016/j.biortech.2018.09.036

    Article  Google Scholar 

  33. Soobhany, N.: Assessing the physicochemical properties and quality parameters during composting of different organic constituents of Municipal Solid Waste. J Environ Chem Eng 6(2), 1979–1988 (2018). https://doi.org/10.1016/j.jece.2018.02.049

    Article  Google Scholar 

  34. Ponsá, S., Pagans, E., Sánchez, A.: Composting of dewatered wastewater sludge with various ratios of pruning waste used as a bulking agent and monitored by respirometer. Biosys Eng 102(4), 433–443 (2009). https://doi.org/10.1016/j.biosystemseng.2009.01.002

    Article  Google Scholar 

  35. Hemidat, S., Jaar, M., Nassour, A., Nelles, M.: Monitoring of Composting Process Parameters: a Case Study in Jordan. Waste and Biomass Valorization, 1–18 (2018).

  36. Waqas, M., Nizami, A.S., Aburiazaiza, A.S., Barakat, M.A., Rashid, M.I., Ismail, I.M.I.: Optimizing the process of food waste compost and valorizing its applications: a case study of Saudi Arabia. J Clean Prod 176, 426–438 (2018). https://doi.org/10.1016/j.jclepro.2017.12.165

    Article  Google Scholar 

  37. Kalemelawa, F., Nishihara, E., Endo, T., Ahmad, Z., Yeasmin, R., Tenywa, M.M., Yamamoto, S.: An evaluation of aerobic and anaerobic composting of banana peels treated with different inoculums for soil nutrient replenishment. Biores Technol 126, 375–382 (2012). https://doi.org/10.1016/j.biortech.2012.04.030

    Article  Google Scholar 

  38. Puyuelo, B., Ponsá, S., Gea, T., Sánchez, A.: Determining C/N ratios for typical organic wastes using biodegradable fractions. Chemosphere 85(4), 653–659 (2011). https://doi.org/10.1016/j.chemosphere.2011.07.014

    Article  Google Scholar 

  39. Cáceres, R., Malińska, K., Marfà, O.: Nitrification within composting: a review. Waste Manage 72, 119–137 (2018). https://doi.org/10.1016/j.wasman.2017.10.049

    Article  Google Scholar 

  40. Hargreaves, J., Adl, M., Warman, P.: A review of the use of composted municipal solid waste in agriculture. Agric Ecosyst Environ 123(1), 1–14 (2008)

    Article  Google Scholar 

  41. Lakhdar, A., Rabhi, M., Ghnaya, T., Montemurro, F., Jedidi, N., Abdelly, C.: Effectiveness of compost use in salt-affected soil. J Hazard Mater 171(1–3), 29–37 (2009)

    Article  Google Scholar 

  42. Hurst, C., Longhurst, P., Pollard, S., Smith, R., Jefferson, B., Gronow, J.: Assessment of municipal waste compost as a daily cover material for odour control at landfill sites. Environ Pollut 135(1), 171–177 (2005)

    Article  Google Scholar 

  43. Bryndum, S., Muschler, R., Nigussie, A., Magid, J., de Neergaard, A.: Reduced turning frequency and delayed poultry manure addition reduces N loss from sugarcane compost. Waste Manage 65, 169–177 (2017). https://doi.org/10.1016/j.wasman.2017.04.001

    Article  Google Scholar 

  44. Jara-Samaniego, J., Pérez-Murcia, M.D., Bustamante, M.A., Pérez-Espinosa, A., Paredes, C., López, M., López-Lluch, D.B., Gavilanes-Terán, I., Moral, R.: Composting as sustainable strategy for municipal solid waste management in the Chimborazo Region, Ecuador: suitability of the obtained composts for seedling production. J Clean Prod (2016). https://doi.org/10.1016/j.jclepro.2016.09.178

    Article  Google Scholar 

  45. Proietti, P., Calisti, R., Gigliotti, G., Nasini, L., Regni, L., Marchini, A.: Composting optimization: integrating cost analysis with the physical-chemical properties of materials to be composted. J Clean Prod 137, 1086–1099 (2016). https://doi.org/10.1016/j.jclepro.2016.07.158

    Article  Google Scholar 

Download references

Acknowledgements

The authors thank the Universidad del Valle for the financing of the investigation project CI 2985. Jonathan Soto-Paz thanks Colciencias for financing the National Doctorate-Convocatoria Doctorados Nacionales [National Doctorate Call] 727 - 2015. R. Oviedo-Ocaña thanks Universidad Industrial de Santander (UIS) for the support received during the development of this research.

Author information

Authors and Affiliations

  1. Facultad de Ingeniería, Grupo de Investigación Estudio y Control de La Contaminación Ambiental – ECCA, Universidad del Valle, Calle 13 No. 100-00, Cali, Colombia

    Jonathan Soto-Paz & Patricia Torres-Lozada

  2. GICOM Research Group, Department of Chemical, Biological and Environmental Engineering, School of Engineering, Universitat Autònoma de Barcelona, 08193, Bellaterra, Barcelona, Spain

    Teresa Gea

  3. Facultad de Ingeniería, Perception and Intelligent Systems – PSI Research Group, Universidad del Valle, Calle 13 No. 100-00, Cali, Colombia

    Wilfredo Alfonso-Morales & Eduardo Caicedo-Bravo

  4. Facultad de Ingenierías Fisicomecánicas, Grupo de Investigación en Recurso Hídrico y Saneamiento Ambiental - GPH, Universidad Industrial de Santander, Carrera 27 Calle 9 Ciudad Universitaria Bucaramanga, Bucaramanga, Colombia

    Edgar Ricardo Oviedo-Ocaña

  5. Facultad de Ingeniería, Grupo de Investigación Logística y Producción, Universidad del Valle, Calle 13 No. 100-00, Cali, Colombia

    Pablo César Manyoma-Velásquez

Authors
  1. Jonathan Soto-Paz
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Teresa Gea
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Wilfredo Alfonso-Morales
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Eduardo Caicedo-Bravo
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Edgar Ricardo Oviedo-Ocaña
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Pablo César Manyoma-Velásquez
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Patricia Torres-Lozada
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Teresa Gea.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary Information

Below is the link to the electronic supplementary material.

Supplementary file1 (DOCX 2828 KB)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Soto-Paz, J., Gea, T., Alfonso-Morales, W. et al. Co-composting of Biowaste: Simultaneous Optimization of the Process and Final Product Quality Using Simulation and Optimisation Tools. Waste Biomass Valor 12, 4489–4502 (2021). https://doi.org/10.1007/s12649-020-01321-w

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12649-020-01321-w

Keywords

Search

Navigation