Abstract
The study was carried out to evaluate the amount and composition of SMW and to determine the potential for waste treatment. The simulation model that underlies the information subsystem of management support for solid municipal waste management has been developed. The system dynamics model was used to estimate the average annual amount of SMW. Simulation was performed using the AnyLogic 7 environment. To analyze the sensitivity of the model, it is necessary to consider the main factors of influence: population, waste components.
For developing a simulation model, regression equations were used: the dynamics of population change, the dynamics of changes in the generated waste, the dynamics of changes in the volume of housing stock, the dynamics of changes indicators of retail trade and public catering, the dynamics of changes industrial production, the dynamics of changes household income.
The used amount depends on the produced and recycled wastes, while the com-pacted density is constant. This means that if the amount of collected wastes increases as a result of population decline, the volume of use will increase. The model allows to carry out the forecast of volumes of the generated waste for decision-making in system of regional management.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Laznenko, D.: Vyznachennya parametriv utvorennya komunalʹnykh vidkhodiv u naselenykh punktakh Ukrayiny dlya tsiley rehionalʹnoho planuvannya. Kyyiv (2019)
Morozova, T., Lukianova, V., Anpilova, Y.: Conceptualization of latent ecosystem services. Ecol. Saf. Nat. Resour. 1(29), 54–64 (2019)
Adamović, V.M., Antanasijević, D.Z., Ristić, M.Đ., Perić-Grujić, A.A., Pocajt, V.V.: Prediction of municipal solid waste generation using artificial neural network approach enhanced by structural break analysis. Environ. Sci. Pollut. Res. 24(1), 299–311 (2016). https://doi.org/10.1007/s11356-016-7767-x
Ghinea, C., Niculina, D.E., Comăniţă, E., Gavrilescu, M., Câmpean, T.: Hybrid model for the prediction of municipal solid waste generation in Hangzhou. China Waste Manag. Res. 37(8), 781–792 (2019). https://doi.org/10.1177/0734242X19855434
Anfilatov, V.S., Emelyanov, A.A., Kukushkin, A.L.: System analysis in management of Moscow “Finance and Statistics”, p. 368 (2002)
Khrutba, V.O.: Fundamentals of project management and waste management in the road complex. Monograph, Kiev, p. 192 (2013)
Odrin, V.M., Kartavov, S.S.: Morphological analysis of systems. Building a morphological matrix, Kiev, p. 183 (1977)
Main Department of Statistics in Zhytomyr Oblast. http://www.zt.ukrstat.gov.ua/
Curteanu, S., Gavrilescu, M.: Forecasting municipal solid waste generation using prognostic tools and regression analysis. J. Environ. Manag. 1(182), 80–93 (2016). https://doi.org/10.1016/j.jenvman.2016.07.026
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2021 The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG
About this paper
Cite this paper
Khrutba, V., Morozova, T., Kotsiuba, I., Shamrai, V. (2021). Simulation Modeling for Predicting the Formation of Municipal Waste. In: Shkarlet, S., Morozov, A., Palagin, A. (eds) Mathematical Modeling and Simulation of Systems (MODS'2020). MODS 2020. Advances in Intelligent Systems and Computing, vol 1265. Springer, Cham. https://doi.org/10.1007/978-3-030-58124-4_3
Download citation
DOI: https://doi.org/10.1007/978-3-030-58124-4_3
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-58123-7
Online ISBN: 978-3-030-58124-4
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)