Detailed municipal solid waste composition analysis for Nur-Sultan City, Kazakhstan with implications for sustainable waste management in Central Asia

Abylkhani, Bexultan; Güney, Mert; Aiymbetov, Berik; Yagofarova, Almira; Sarbassov, Yerbol; Zorpas, Antonis A.; Venetis, Christos; Inglezakis, Vassilis J.

doi:10.1007/s11356-020-08431-x

Cited by 28 publications

(14 citation statements)

References 27 publications

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“…According to Zorpas et al, (2014a), Kiessling et al, (2017) and Agapiou et al, (2020) household and tourist activities will continue to be the main polluter worldwide taking into account the production of municipal waste. Hence, Vardopoulos et al, (2020) mentioned that economic and social development will continue to put pressure on the environment. (b) Pressure (P) : There is much evidence provided by many researchers (Abylkhani et al, 2020; Agapiou et al, 2020; Economist, 2018; Eurostat, 2019; Food and Agriculture Organization of the United Nations, 2011; Loizia et al, 2018; Loizia et al, 2019; WRAP, 2008; World Bank, 2018; Loizia et al, 2021) that the production and the generation of the waste will continue to increase. As a result of this the waste generation in coastal area will also continue to increase.…”

Section: Methodsmentioning

confidence: 99%

“…(b) Pressure (P) : There is much evidence provided by many researchers (Abylkhani et al, 2020; Agapiou et al, 2020; Economist, 2018; Eurostat, 2019; Food and Agriculture Organization of the United Nations, 2011; Loizia et al, 2018; Loizia et al, 2019; WRAP, 2008; World Bank, 2018; Loizia et al, 2021) that the production and the generation of the waste will continue to increase. As a result of this the waste generation in coastal area will also continue to increase.…”

Section: Methodsmentioning

confidence: 99%

“…There are several KPIs to assess the level of an area or to quantify something that is not really there (directly recognizable and identifiable either from the citizens or the stakeholders). Such KPIs related to evaluation and or validation of the existing waste management strategy, as well as the level of sustainability, may include TAEs, TI, TD, life cycle analysis, waste compositional analysis (C-MSW), clean coast index (CCI), accumulation rate (AR), waste accumulation index (WAI), waste generation index or rate (WGR), driving force–pressure–state–impact–response (DPSIR), waste recycling index (R-MSW), waste recovery index or rate (WRR), existing waste infrastructure per citizen (WI), prevention activities and or awareness activities as well as other qualitative approaches such as political, economic, socio-cultural and technological and strengths, weaknesses, opportunities and threats (SWOT) analyses (Abylkhani et al, 2020; Fernandez-Aracil et al, 2018; Inglezakis and Zorpas, 2014; Lasaridi et al, 2015; Loizia et al, 2018, 2021; Mori and Christodoudou, 2012; Priyadarshini and Abhilash, 2020; Tofalli et al, 2018; Tsangas et al, 2020, Urban Wins, 2019; Vardopoulos et al, 2020; Wang et al, 2018a, 2018b; Zorpas, 2020).…”

Section: Introductionmentioning

confidence: 99%

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Urban strategies evaluation for waste management in coastal areas in the framework of area metabolism

et al. 2021

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Europe is considered one of the most attractive and safe prevalent tourist destinations in the entire world. Approximately half (47.4%) of European tourist visits occurred in coastal regions, defined “on the basis of and consist of local administrative units or municipalities that border the sea, or have at least half of their total surface area within a distance of 10 km from the sea.” Destinations such as Malta, Greece, Cyprus, Spain and Croatia presented with an increased level of tourist accommodation establishments, as well as, the overall flow of tourism in the European Union is mostly concentrated on Mediterranean coastal regions (as nine out 10 tourists, in 2015, spent their holidays at coastal areas). This paper, is dealing with the assessment of a tourist area and how the concept of urban metabolism has been affected by touristic activities. Moreover, this research using several key performance indicators such as waste compositional analysis, the clean coast index, the accumulation rate, and accumulation index, etc., tries to measure the level of environmental performance, and furthermore, to assess the existing infrastructures and the waste management plan, that are being implemented. The results are very useful, for any policy-maker, as well as competent authorities and/or tourist organizations which are dealing with tourist activities and aim to propose or re-schedule any waste strategy targeting the goals of United Nations Sustainable Development Goals, European Green Deal, and the new circular economy strategy.

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Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Urban strategies evaluation for waste management in coastal areas in the framework of area metabolism

et al. 2021

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“…To determine the seasonal change in waste, composition studies were applied separately in summer and winter. Once collected, the samples were sorted according to the method described by Abylkhani et al (2020). After conducting two screenings, the remaining waste material had a particle size <12.7 mm for the composition analysis.…”

Section: Methodsmentioning

confidence: 99%

Application of life cycle assessment for municipal solid waste management options in Hohhot, People’s Republic of China

et al. 2020

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With increasing population and urbanization levels in the People’s Republic of China, environmental problems related to the management of municipal solid waste (MSW) are inevitable. This study aimed to determine the environmental impact of the current MSW management system in Hohhot City and to establish an optimum future strategy for it by applying life cycle assessment (LCA) methodology. Four scenarios were compared using the CML-IA impact characterization method, which took into account their potential contribution to global warming, ozone depletion, human toxicity, photochemical ozone creation, acidification, and eutrophication potentials. The system boundaries included the collection and recycling, transfer and transportation of MSW, and its disposal by incineration, landfilling, and carbon dioxide (CO2) capture methods. The results showed that the scenario involving landfill and incineration in a ratio of 1:5 was the optimal waste management option; however, increasing the proportion of waste incinerated led to a significant increase in global warming potential. Additional technologies are thus required to overcome this problem, and it was found that the use of CO2 capture technology resulted in a 30% reduction in the total environmental impact potential. This study’s results indicate that LCA is a valuable and practical tool to support decision-making that can be used to suggest problematic areas in current waste management strategies and to determine an optimal alternative to the solid waste management option.

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“…A meta‐analysis was applied for collecting the food waste composition data from 1995 to 2015 in the United States, by using a large amount of sampling data for statistical analysis and curve‐fitting (Thyberg et al., 2015). It is time‐consuming for obtaining representative PCMSW datasets, owing to the mass‐heterogeneity of mixed MSW samples (Abylkhani et al., 2020; Li et al., 2009; Villalba et al., 2020).…”

Section: Introductionmentioning

confidence: 99%

A comparison study of bottom‐up and top‐down methods for analyzing the physical composition of municipal solid waste

Zhou

Xiao³

et al. 2021

J of Industrial Ecology

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Municipal solid waste (MSW) management is a crucial issue in socioeconomic metabolism and requires multicategory and high‐resolution data, and data on the physical composition of municipal solid waste (PCMSW) are fundamental in MSW research. Extensive financial resources have been invested in the research on field investigations of PCMSW; however, it is time‐consuming and sometimes not truly representative of the studied case. In this work, two bottom‐up and two top‐down approaches were applied for analyzing the PCMSW, namely, field investigation (FI), BP neural network (BPNN), material flow analysis (MFA), and inversion algorithm based on electricity generation of waste incinerator (IAEI). Wuhan City, China, was chosen as the studied case for analyzing and comparing the PCMSW results. The PCMSW values obtained by applying those four methods showed acceptable differences, and the standard deviations of organic fraction, ash and stone, paper, plastic and rubber, textile, wood, metal, glass, and others were 3.94%, 2.77%, 6.57%, 2.22%, 2.49%, 1.36%, 0.53%, 1.19%, and 0.28%, respectively. Use of the MFA, BPNN, and IAEI methods could reduce time and labor spent on manual sampling, sorting, and weighing of MSW, compared to the FI method. BPNN algorithm advances in providing PCMSW data in history and by trajectory throughout the year, whereas IAEI contributes PCMSW data with much higher temporal resolution. Data quality and applicability of different methods were discussed, considering the availability of time, labor, and reference data.

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Detailed municipal solid waste composition analysis for Nur-Sultan City, Kazakhstan with implications for sustainable waste management in Central Asia

Cited by 28 publications

References 27 publications

Urban strategies evaluation for waste management in coastal areas in the framework of area metabolism

Urban strategies evaluation for waste management in coastal areas in the framework of area metabolism

Application of life cycle assessment for municipal solid waste management options in Hohhot, People’s Republic of China

A comparison study of bottom‐up and top‐down methods for analyzing the physical composition of municipal solid waste

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