Prediction of dynamics change in biowaste quantity collected in functionally different regions. A case study of Poland

• Autorzy: Tałałaj Izabela Anna , Hajduk Sławomira , Wiszniewska Anna

Identyfikatory

DOI

10.34659/eis.2025.93.2.920

Warianty tytułu

PL

Prognoza dynamiki zmian odpadów biodegradowalnych w funkcjonalnie zróżnicowanych regionach. Studium przypadku Polski

• Języki publikacji: EN

Abstrakty

EN

The aim of the paper is to determine the dynamics of change in biowaste quantity as well as to forecast the amount of biowaste generated in 4 functionally different regions of Poland. The analysis was made for a period of 16 years (2007-2022), and a prognosis was made for the next 4 years (2023-2026). Based on the obtained data, the following calculations were made: share of biowaste from households in the quantity of total municipal biowaste, accumulation rate of biowaste from households, medium-term change rate in the amount of biowaste from households, and prediction of changes in the biowaste accumulation index until 2026. In all the analysed regions, an increasing trend in the collected biowaste mass index has been observed. The agricultural and recreational regions were characterised by the highest dynamics of changes in collected biowaste quantity (T=0.21 and 0.25, respectively) and by the lowest values of their accumulation indicator (48.9 and 44.7 kg/ca per year, respectively). The highest quantity of biowaste is predicted to be generated in urbanised and industrialised regions (62.1 and 53.2 kg/ca per year, respectively).

PL

Celem artykułu jest określenie dynamiki zmian ilości bioodpadów oraz prognoza ilości generowanych bioodpadów w czterech funkcjonalnie różnych regionach Polski. Analizy zostały przeprowadzone dla okresu 16 lat (2007–2022), a prognozy obejmują kolejne 4 lata (2023–2026). Na podstawie uzyskanych danych obliczono: udział bioodpadów pochodzących z gospodarstw domowych w całkowitej ilości odpadów komunalnych, wskaźnik akumulacji bioodpadów z gospodarstw domowych, średniookresową dynamikę zmian ilości bioodpadów zebranych z gospodarstw domowych oraz prognozę zmian wskaźnika akumulacji bioodpadów do 2026 roku. We wszystkich analizowanych regionach zaobserwowano rosnący trend wskaźnika nagromadzenia zebranych bioodpadów. Obszary rolnicze i rekreacyjne charakteryzowały się najwyższą dynamiką zmian ilości bioodpadów (T = 0,21 i 0,25, odpowiednio) oraz najniższymi wartościami wskaźnika ich nagromadzenia (odpowiednio 48,9 i 44,7 kg/os. rocznie). Największe ilości zbieranych bioodpadów prognozuje się dla regionów zurbanizowanych i uprzemysłowionych (odpowiednio 62,1 i 53,2 kg/os. rocznie).

Słowa kluczowe

EN

biodegradable; change dynamics; prediction; biowaste

PL

odpady biodegradowalne; dynamika zmian; prognoza; bioodpady

• Wydawca: Polskie Stowarzyszenie Ekonomistów Środowiska i Zasobów Naturalnych
• Czasopismo: Economics and Environment
• Rocznik: 2025
• Tom: No. 2
• Strony: art. no. 920
• Opis fizyczny: Bibliogr. 38 poz., tab., wykr.

Twórcy

autor

Tałałaj Izabela Anna

• Faculty of Civil Engineering and Environmental Science, Bialystok University of Technology, Wiejska Street 45E, 15‑351 Bialystok, Poland

• https://orcid.org/0000-0003-4820-6182

autor

Hajduk Sławomira

• Faculty of Engineering Management, Bialystok University of Technology

• https://orcid.org/0000-0003-0314-1661

autor

Wiszniewska Anna

• Marshal's Office of the Podlaskie Voivodeship, Poland

• https://orcid.org/0009-0002-9790-3486

Bibliografia

• Act from 14 December 2012. Waste Act. Journal of Laws 2013, item 21, as amended. https://isap.sejm.gov.pl/isap.nsf/DocDetails.xsp?id=wdu20130000021 (in Polish).
• Ahrens, T., Drescher-Hartung, S., & Anne, O. (2017). Sustainability of the Biowaste Utilization to Energy Production. In J.S. Tumuluru (Ed.), Biomass Volume Estimation and Valorization for Energy (pp. 165-185). nTech. https://doi.org/10.5772/62678
• Ahuja, N. J., & Bahukhandi, K. D. (2012). Expert systems for Solid Waste Management: A Review. International Review on Computers and Software (IRECOS), 7(4), 1608-1613. https://www.researchgate.net/publication/288578597_Expert_systems_for_solid_waste_management_A_review
• Araiza-Aguilar, J. A., Rojas-Valencia, M. N., & Aguilar-Vera, R. A. (2020). Forecast generation model of municipal solid waste using multiple linear regression. Global Journal of Environmental Science and Management, 6(1), 1-14. https://doi.org/10.22034/gjesm.2020.01.01
• Ayeleru, O. O., Fajimi, L. I., Oboirien, B. O., & Olubambi, P. A. (2021). Forecasting municipal solid waste quantity using artificial neural network and supported vector machine techniques: A case study of Johannesburg, South Africa. Journal of Cleaner Production, 289, 125671. https://doi.org/10.1016/j.jclepro.2020.125671
• Azadi, S., & Karimi-Jashni, A. (2016). Verifying the performance of artificial neural network and multiple linear regression in predicting the mean seasonal municipal solid waste generation rate: A case study of Fars province, Iran. Waste Management, 48, 14-23. https://doi.org/10.1016/j.wasman.2015.09.034
• Azarmi, S. L., Oladipo, A. A., Roozbeh, V., & Alipour, H. (2018). Comparative Modelling and Artificial Neural Network Inspired Prediction of Waste Generation Rates of Hospitality Industry: The Case of North Cyprus. Sustainability, 10(9), 2965. https://doi.org/10.3390/su10092965
• Babalola, M. A. (2020). A Benefit–Cost Analysis of Food and Biodegradable Waste Treatment Alternatives: The Case of Oita City, Japan. Sustainability, 12, 1916. https://doi.org/10.3390/su12051916
• Baquero, M., Cifrian, E., Pérez-Gandarillas, L., & Andres, A. (2022). Methodology Proposed for Estimating Biowaste Generation Using Municipal Rurality Indexes. Waste Biomass Valor, 13, 941-954. https://doi.org/10.1007/s12649-021-01571-2
• Batinic, B., Vukmirovic, S., Vujic, G., Stanisavljevic, N., Ubavin, D., & Vukmirovic, G. (2011). Using ANN model to determine future waste characteristics in order to achieve specific waste management targets - case study of Serbia. Journal of Scientific & Industrial Research, 70(7), 513-518. https://www.researchgate.net/publication/266243404_Using_ANN_model_to_determine_future_waste_characteristics_in_order_to_achieve_specific_waste_management_targets_-case_study_of_Serbia
• Boschin, G., Scigliuolo, G. M., Resta, D., & Arnoldi, A. (2014). ACE-inhibitory activity of enzymatic protein hydrolysates from lupin and other legumes. Food Chemistry, 145, 34-40. https://doi.org/10.1016/j.foodchem.2013.07.076
• Ceylan, Z. (2020). Estimation of municipal waste generation of Turkey using socio-economic indicators by Bayesian optimization tuned Gaussian process regression. Waste Management and Research, 38(8), 840-850. https://doi.org/10.1177/0734242X20906877
• Chioatto, E., Khan, M. A., & Sospiro, P. (2023). Sustainable solid waste management in the European Union: Four countries regional analysis. Sustainable Chemistry and Pharmacy, 33, 101037. https://doi.org/10.1016/j.scp.2023.101037
• Directive 2008/98/EC of the European Parliament and of the Council of 19 November 2008 on waste and repealing certain Directives, Pub. L. No. 32008L0098, 312 OJ L (2008). https://eur-lex.europa.eu/eli/dir/2008/98/oj/eng
• Generowicz, A. (2020). Evaluation of the Ecological Effect of Biodegradable Waste Processing in a Comprehensive Municipal Waste Management System. Architecture, Civil Engineering, Environment, 13(1), 121-128. https://doi.org/10.21307/acee-2020-010
• Ghinea, C., Drăgoi, E. N., Comăniţă, E. D., Gavrilescu, M., Câmpean, T., Curteanu, S., & Gavrilescu, M. (2016). Forecasting municipal solid waste generation using prognostic tools and regression analysis. Journal of Environmental Management, 182(1), 80-93. https://doi.org/10.1016/j.jenvman.2016.07.026
• GUS. (2023). Statistical Yearbook of the Republic of Poland. https://stat.gov.pl/en/topics/statistical-yearbooks/statistical-yearbooks/statistical-yearbook-of-the-republic-of-poland-2023,2,25.html (in Polish).
• Jalili, G. Z. M., & Noori, R. (2008). Prediction of municipal solid waste generation by use of artificial neural network: A case study of Mashhad. International Journal of Environmental Research and Public Health, 2(1), 13-22. https://www.researchgate.net/publication/27794359_Prediction_of_Municipal_Solid_Waste_Generation_by_Use_of_Artificial_Neural_Network_A_Case_Study_of_Mashhad
• Janmaimool, P., & Denpaiboon, C. (2016). Influence of urbanisation on metropolitan solid waste generation and residents' hierarchy waste management behaviors. Proccedings of the 14th Pacific Regional Science Conference Organization Summer Institute, Bangkok, Thailand, 1-7. https://www.researchgate.net/publication/318708136_INFLUENCE_OF_URBANIZATION_ON_METROPOLITAN_SOLID_WASTE_GENERATION_AND_RESIDENTS'_HIERARCHY_WASTE_MANAGEMENT_BEHAVIORS
• Kamran, A., Chaudhry, M. N., & Batool, S. A. (2015). Effects of socio-economic status and seasonal variation on municipal solid waste composition: a baseline study for future planning and development. Environmental Science Europe, 27, 16. https://doi.org/10.1186/s12302-015-0050-9
• Karnasuta, S., & Laoanantana, P. (2022). Forecasting Models of Community Biodegradable Waste Management. Journal of Arts Management, 6(1), 47-64. https://so02.tci-thaijo.org/index.php/jam/article/download/251606/171176
• Kaza, S., Yao, L., Bhada-Tata, P., & Van Woerden, F. (2018). What a Waste 2.0 – A Global Snapshot of Solid Waste Management to 2050. The World Bank Group. https://openknowledge.worldbank.org/handle/10986/30317
• Kulisz, M., & Kujawska, J. (2020). Prediction of Municipal Waste Generation in Poland Using Neural Network Modeling. Sustainability, 12(23), 10088. https://doi.org/10.3390/su122310088
• Kumar, A., & Samadder, S. R. (2017). An empirical model for prediction of household solid waste generation rate – A case study of Dhanbad, India. Waste Management, 68, 3-15. https://doi.org/10.1016/j.wasman.2017.07.034
• Kurtulus, H. O., Ucan, O. N., Sahin, U., Borat, M., & Bayat, C. (2006). Artificial neural network modelling of methane emissions at Istanbul Kemerburgaz-Odayeri landfill site. Journal of Scientific & Industrial Research, 65(2), 128-134. https://www.researchgate.net/publication/289129436_Artificial_Neural_Network_Modeling_of_Methane_Emissions_at_Istanbul_Kemerburgaz-Odayeri_Landfill_Site
• Namlis, K. G., & Komilis, D. (2019). Influence of four socioeconomic indices and the impact of economic crisis on solid waste generation in Europe. Waste Management, 89, 190-200. https://doi.org/10.1016/j.wasman.2019.04.012
• Nassereldeen, A., Kabbashi, S., Mohammed, A., Munif, J., & Nur, A. (2011). Integrated schedule waste management system in Kuala Lumpur using expert system. African Journal of Biotechnology, 10(81), 1871-1878. https://www.ajol.info/index.php/ajb/article/view/98670
• Nguyen, K. L. P., Chuang, Y. H., Chen, H. W., & Chang, C. C. (2020). Impacts of socioeconomic changes on municipal solid waste characteristics in Taiwan. Resources, Conservation and Recycling, 161, 104931. https://doi.org/10.1016/j.resconrec.2020.104931
• Saravanan, A., Karishma, S., Senthil Kumar, P., & Rangasamy, G. (2023). A review on regeneration of biowaste into bio-products and bioenergy: Life cycle assessment and circular economy. Fuel, 338, 127221. https://doi.org/10.1016/j.fuel.2022.127221
• Seruga, P. (2021). The Municipal Solid Waste Management System with Anaerobic Digestion. Energies, 14(8), 2067. https://doi.org/10.3390/en14082067
• Statistics Poland. (2023, November 15). Local Data Bank. https://bdl.stat.gov.pl/bdl/start (in Polish).
• Szyba, M., & Muweis, J. (2022). The Importance of Biodegradable Waste in Transforming the Economy into a Circular Model in Poland. Polish Journal of Environmental Studies, 31(3), 2245-2253. https://doi.org/10.15244/pjoes/143491
• Tatarczak, A. (2021). Statystyka. Podręcznik. Studia przypadków. Lublin: Innovatio Press. (in Polish).
• Tesfamariam, E. H., Cogger, C., & Zvimba, J. N. (2022). Impact of Treatment of Biodegradable Waste on Nutrient Recovery. In M. Kacprzak, E. Attard, K.-A. Lyng, H. Raclavska, B. Singh, E. Tesfamariam & F. Vandenbulcke (Eds.), Biodegradable Waste Management in the Circular Economy (pp. 419-431). John Wiley & Sons, Ltd. https://doi.org/10.1002/9781119679523.ch15
• Tot, B., Vujić, G., Srđević, Z., Ubavin, D., & Russo, M. A. T. (2017). Group assessment of key indicators of sustainable waste management in developing countries. Waste Management and Research, 35(9), 913-922. https://doi.org/10.1177/0734242X17709911
• Trang, P. T. T., Dong, H. Q., Toan, D. Q., Hanh, N. T. X., & Thu, N. T. (2017). The Effects of Socio-economic Factors on Household Solid Waste Generation and Composition: A Case Study in Thu Dau Mot, Vietnam. Energy Procedia, 107, 253-258. https://doi.org/10.1016/j.egypro.2016.12.144
• Tun, M. M., Juchelková, D., Raclavská, H., & Sassmanová, V. (2018). Utilization of Biodegradable Wastes as a Clean Energy Source in the Developing Countries: A Case Study in Myanmar. Energies, 11(11), 3183. https://doi.org/10.3390/en11113183
• Voukkali, I., Papamichael, I., Loizia, P., & Zorpas, A. A. (2023). Urbanisation and solid waste production: prospects and challenges. Environmental Science and Pollution Research, 31, 17678-17689. https://doi.org/10.1007/s11356-023-27670-2