TRENDS OF MUNICIPAL WASTE FLOWS, COMPOSITION, TREATMENT IN LITHUANIA AND ITS REGIONS

Purpose – to propose conceptual model for forecasting of waste trends and empirically implement the model based on the case of Lithuania and its regions. Research methodology – 1) scientific literature analysis on circular economy, zero waste and waste management, 2) gathering of statistical data on waste flows, composition and treatment 3) creation of conceptual model of forecasting with Exponential Smoothing for prediction of waste-related trends based on literature review. Findings – proposed conceptual model for prediction of waste-related trends is adequate for prognosis of waste flows, composition and treatment ways. The main forecasting results are that the total waste flows will increase in Lithuania, on a regional level, Alytus, Kaunas, Klaipėda, Telšiai, have a tendency of the increase in municipal waste flows. The results imply that in order to contribute to the reduction of waste, the active involvement on a regional level is necessary. Research limitations – the research can be extended with statistical data on waste of other countries to check adequacy of the conceptual model for waste-related trends prognosis. Practical implications – the findings of the research can be applied in planning and decision-making process of government bodies on national or local level. The results are also useful for the general public in educational purposes. Originality/Value – the study provides original conceptual model for the forecasting of waste-related trends which provides robust results of predictions and can be replicated by different countries.


Introduction
The dominance of linear economy over the past decades has stipulated the growth of municipal waste around the world. Also, changing economic conditions in different parts of the world have stipulated the movement of inhabitants moving from rural areas to cities, which also has an effect on the waste formation flows (Allam, 2018;Zaman, 2012;Zaman & Lehmann, 2013).
The emerging importance of the waste problems are now the major concern of citizens, companies, governments and policy makers. The number of studies has been carried out by academics to tackle waste problems and propose solutions such as shift to circular economy and adoption of zero waste principles. In turn, European Commission, United Nations, local governments have issued measures aimed to control the waste generation and, subsequently, to decrease the waste flows in the future.
However, projections of future waste generation doesn't indicate any improvement or reduction of waste flows (Allam, 2018;Zaman & Swapan, 2016). World Bank Group (Kaza et al., 2018) estimated that the world will produce 2.59 billion tonnes of municipal solid waste annually and this number is going to increase up to 3.4 billion tonnes by 2050, compared to 2.01 billion tonnes in 2016. This research also indicates that that high-income countries are subject to incremental increase of municipal solid waste, whereas low-income and lower-middle-income countries have a tendency of greatest increase in waste flows due to economic progression and raise of the population.

Coherence of circular economy, zero waste city concept and municipal waste management
The importance of circular economy is growing nowadays and receives increased interest from citizens, companies, governments and policy makers (Corona et al., 2019;Cudečka-Puriņa et al., 2019;Haupt et al., 2019;Kirchherr et al., 2017;Lahti et al., 2018;Schroeder et al., 2019). Circular economy aims to foster responsible and circular use of resources (Moraga et al., 2019;Wilson, 2015), its principles can be compared to the processes happening in our nature, where the end of one process lays the groundwork for a new process (Allam, 2018;Hannon & Zaman, 2018). Circular economy model is substantially different from linear economy as it oriented towards improvement of linear economy drawbacks (Doussoulin, 2020). Circular economy model is a long-term objective supported with a synergy of economic growth, zero waste and sustainability (Greyson, 2007). The successful long-term orientation towards circular economy can be achieved through the cooperation and interrelationship between society, businesses and governments (Sánchez-Ortiz et al., 2020). As a result of application of circular economy model, society, companies and governments can exercise increased employment opportunities, reduction of costs, increased productivity and innovation capabilities and effective use of resources (Schroeder et al., 2019).
One of supporting disciplines of circular economy is orientation towards zero waste. The main focus of a zero-waste concept is to tackle waste issues (Zaman, 2014(Zaman, , 2015Zaman & Lehmann, 2013) with avoidance and prevention of waste instead of application of waste treatment methods (Hamid et al., 2020). Zero waste programs are beneficial from financial, economic, social and environmental standpoints (Pietzsch et al., 2017;Roetman & Daniels, 2011). At social level, zero waste programs contribute to reduction of health dangers and have a positive impact on societal lifestyle. Environment can benefit from reduced waste flows and increased environmental control. At financial and economic levels, zero waste programs contribute to symbiosis of cost reduction and amplification of profits supported by enhanced productivity, ameliorated product or service design and boosted competitiveness.
However, successful implementation of zero waste programmes include potential execution challenges arising from the micro and macroenvironment (Pietzsch et al., 2017). Typical microenvironmental challenges include increased need of political support on waste management policies, bear societal behavioural change and education requirements, stipulate the need of tax reforms and raised R&D budgets to contribute to the development of waste management technologies. Microenvironmental difficulties are usually related to the questions arising at a company-level, where businesses face ambiguities in understanding technical solutions of reaching zero waste goals at reasonable costs, along with implementation of waste management solutions into practice and improvement of products or services.
Increasing amounts of waste globally and the relatively low rates of recycled and composed waste is receiving increased interest from the policy makers world-wide. Waste Framework Directive 2008/98/EC (European Union Law, 2008;Scarlat et al., 2019) issued by the European Commission lays the groundwork for basic waste management principles such as waste management practices which exclude harm to environment or human beings, includes "polluter pays" and "increased producer responsibility" principles. The Directive also provides common waste management hierarchy, where prevention of waste is considered to be non-waste, while preparation of waste for re-use, recycling, recovery and disposal are attributed to waste. On the other hand, academics (Chen et al., 2020) evaluated the trends in world's municipal waste flows and suggested that European Commission's circular economy targets may be effortful to reach by 2030 if more channelled policies will not be introduced.
Scientists, policy makers, governments stress the importance of the education of citizens towards zero waste practices -increase in knowledge will have a positive effect on waste generation patters. Circular economy and zero waste models also include education of society on waste management problems and ways of involvement into waste reduction as one of the elements of successful municipal waste reduction. Academics (Minelgaitė & Liobikienė, 2019) analysed the difference between the intention of citizens of the European Union to reuse, recycle and recover and the actual behaviour based on Eurobarometer survey "Attitudes of Europeans towards waste management and resource efficiency" and concluded that countries seeking to minimise the generation of waste, should put an emphasis on the promotion of sustainable consumption and production practices. Furthermore, the academics found that waste-reducing behaviour can be stimulated by the increase in knowledge of global waste problems and how citizens individually can make a change in terms of waste reduction. The study suggests that to enhance waste-reusing behaviour, improvement of the quality and life span of products practices should take place, whereas, to promote recycling behaviour, improved in recycling facilities should be implemented with an emphasis that the waste from these facilities is recycled in an effective manner.

Research methods
Waste flows and waste formation trends receive increased interest from the academic communities, governments, policy makers and the public. As a result of need to forecast waste to carry out adequate policies and directives along with understanding of future trends, academics suggest diverse ways of forecasting waste flows.
Among the variety of methods, academics also use Exponential Smoothing (Buhl et al., 2020;Denafas et al., 2014;Wąsik & Chmielowski, 2016) and observe that the method is suitable for forecasting waste. However, other researchers (Akgül et al., 2020;Mwenda et al., 2014) argue that other methods like ARIMA provide more robust forecasting results.
The aim of this paper is to propose the conceptual model for the forecasting of municipal waste flows based on the application of Exponential Smoothing and validate the accuracy of the proposed model based on the Lithuania's data. The methodology for the prediction of the municipal waste formation flow in Lithuania's regions is depicted in Figure 1. The actual data on municipal waste formation flows is collected at the Environmental Protection Agency's web page. The data is grouped to summarise country-level variables and the amounts dedicated for 10 regions of Lithuania -Alytus, Kaunas, Klaipėda, Marijampolė, Panevėžys, Šiauliai, Tauragė, Telšiai, Utena, Vilnius. Thus, calculation of Exponential Smoothing in MS Office Excel is carried out with corresponding statistical measures of forecast accuracy.
Exponential Smoothing techniques have gained popularity among scientists and the business due to strong forecasting capabilities, reliable results and relatively straightforward application (Ariyanti et al., 2018;Cadenas et al., 2010;Corberán-Vallet et al., 2011;de Faria et al., 2009;Gardner, 2006;Snyder et al., 2004;J. Taylor, 2004;J. W. Taylor, 2003;Yager, 2013). The calculation of Exponential Smoothing is established on linear statistical models (Snyder et al., 2002), where the most recent actual values are assigned with more weights while former actual values receive decreasing weights (Ariyanti et al., 2018;de Oliveira & Cyrino Oliveira, 2018;Ferbar Tratar et al., 2016;Shim, 2009;J. Taylor, 2004). Therefore, Exponential Smoothing depends on the tree types of data: the latest actual data, the latest forecast, and a smoothing constant Alpha (Hoshmand, 2010;Ravinder, 2013), which varies from 0 to 1. When smoothing constant is close to 0, then the impact of smoothing is greater, and vice versa, when smoothing constant is close to 1, smoothing effect is weaker (Ariyanti et al., 2018 (Dakhil et al., 2018), rainfall and ground water production of Deir El-Balah City in the Gaza Strip (Abuamra et al., 2020), salinity rates and levels of groundwater in Deir El-Balah (Abuamra et al., 2021), the number of COVID-19 cases in Chennai City , analyse COVID-19 situation in Bengaluru .

Research results
The proposed conceptual model of forecasting waste provides predictions, denoted as F, of waste generation flows, waste treatment ways and waste composition (Table 1 and Table 2)  Results imply that the total waste generated in the country will be reduced by 1.36% at 2025 compared to 2019 (see Table 1). Waste treatment in landfill and waste burned without energy recovery will not take place. Forecast also shows increase in waste to energy, composed waste, processed waste and untreated waste amounts. MASE and SMAPE statistics indicate variations in accuracy of the forecast of waste generation flows is treatment ways, however, MAE and RMSE statistics indicate less robustness of the prediction.
According to the forecast (see Table 2), the considerable reduction in a composition of waste in Lithuania can be observed in green and wood waste, PET packaging, plastics, metals, glass, ceramics, concrete and stones. The increase in waste can be adhered to paper and paperboard, biodegradable food, textiles, other municipal biodegradable waste, combined packaging and other waste. MASE, SMAPE, MAE, RMSE indicate high prediction of the forecast.
Statistics vary in the same manner on regional data. Prediction of waste generation flows on regional level shows variations in MASE and SMAPE indicating on reliability of the forecast, while MAE and RMSE statistics indicate less robustness of the prediction.
The results of the prognosis of waste composition and corresponding statistics of the 10 regions of Lithuania are depicted in Appendix. The research proposes that the highest reduction of paper and paperboard can be observed at Marijampolė region and increase in Klaipėda region. Green waste is going to be reduced in Tauragė region, while forecast of other regions shows increase in this type of waste. The highest decrease in wood waste is depicted in Panevėžys region, while the highest increase in Kaunas region. Other noticeable results -amounts of biodegradable foods will increase in seven regions, with slight reduction in Alytus, Vilnius and Utena. Also, metal waste reduces considerably except for Alytus and Klaipėda regions. Lastly, forecast proposes that Utena region will have reduced the amounts of green, wood, biodegradable waste, PET and combined packaging and ceramics, concrete and stones to a minimum. MASE, SMAPE, MAE, RMSE indicate high prediction of the forecast.

Conclusions
Forecasting future waste trends play an important role in formation of waste management policies and planning of waste treatment ways. Among a variety of forecasting methods and techniques, it is important to distinguish methods applicable for waste prediction. The conceptual model of waste forecasting using Exponential Smoothing proposed in this research is empirically implemented on the country-level and regional data. Accuracy of the proposed conceptual model's results is evaluated and provides rationale that conceptual model is adequate for the prediction of waste trends.
The findings of the research show that total waste generated in the country will be reduced by 1.36% at 2025 compared to 2019. In 2025, the increase in waste in Lithuania can be attributed to paper and paperboard, biodegradable food, textiles, other municipal biodegradable waste, combined packaging and other waste. On a regional level, the amount of waste will increase in four regions by 2025 -Alytus, Kaunas, Klaipėda, Telšiai, wherease in other six regions, namely Marijampolė, Panevėžys, Šiauliai, Tauragė, Utena, Vilnius, amounts of waste are subject to decrease in 2025.
Supplementary analysis can be carried out to investigate the relationships between the trends of municipal waste flows and factors which have an effect on increase of decrease in waste. Results of such study would complement the policy and decision makers in selection process of waste control measures.
The further research can be extended by the application of statistical data on waste of other countries and cities to check adequacy of the conceptual model for waste-related trends prognosis. The conceptual model can be validated on the cities and corresponding countries depicted by Zero Waste Europe (Zero Waste Europe, 2020) as showing best zero waste practices implemented: Munich and Germany, Bruges and Belgium, Prelog and Croatia, etc. Also, conceptual model can be extended with application of other forecasting methods in order to increase the robustness of the forecast in combination with exponential Smoothing. Lastly, the conceptual model can be validated via application of other waste types, such as e-waste, in order to address the fastest-growing element of the world's domestic waste stream, according to the Global E-Waste Monitor Report (Forti et al., 2020).

Disclosure statement
The authors do not have any competing financial, professional, or personal interests from other parties. End of Table A2