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Exploring social determinants of municipal solid waste management: survey processing with fuzzy logic and self-organized maps

  • Advances & Prospects in the field of Waste Management
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Abstract

In the present study, the establishment of decision-making criteria and a novel and robust interdisciplinary approach for systematically characterizing effects of uncertainties in social determinants of municipal solid waste management using an important fuzzy logic methodology is demonstrated. The primary goal is to highlight the social benefits of this waste management option such as job creation, hygiene and health protection, and working safety as well as to indicate certain side effects occurring during waste processing (odor and leachate production, social trust). The current research is based on a social survey in an agro-industrial region, Thessaly, Greece, and indicates a set of diversified key factors that are related to public acceptance of municipal waste management schemes. These features are input to Kohonen Self-Organized Maps (a special type of Artificial Neural Networks) for clustering residents according to their social perception and attitudes in terms of solid waste collecting and recycling. Both analyses highlight the environmental concern, social perception, hygiene and health, economic status, and lifestyle as the primary social determinants in affecting the public attitudes towards recycling. In both cases, these soft computing techniques seem to outperform the classical statistical and logical regression methodologies and become very promising in accurately predicting waste management practice and possibly other environmental behaviors.

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Abbreviations

Notation:

Definition

FL:

fuzzy logic

MSW:

municipal solid waste

SOM:

self-organized maps

ANN:

artificial neural network

ECGB:

environmental concern and general behavior

SPHH:

social perception hygiene and health

ESLF:

economic status and lifestyle

GB:

general behavior

SP:

social perception attitudes and beliefs

HH:

hygiene and health protection

BD:

behavior determinants towards waste production

LF:

lifestyle

Amean :

mean answer of all available data

GBmean/Amean :

ratio of mean-GB over Amean

SPmean/Amean :

ratio of mean-SP over Amean

HHmean/Amean :

ratio of mean-HH over Amean

BDmean/Amean :

ratio of mean-BD over Amean

LFmean/Amean :

ratio of mean-LF over Amean

References

  • Afroz R, Rahman A, Masud MM, Akhtar R (2017) The knowledge, awareness, attitude and motivational analysis of plastic waste and household perspective in Malaysia. Environ Sci Pollut Res 24(3):2304–2315

    Article  Google Scholar 

  • Akintola OA, Sangodoyin AY, Agunbiade FO (2018) Anthropogenic activities impact on atmospheric environmental quality in a gas-flaring community: application of fuzzy logic modelling concept. Environ Sci Pollut Res 25(22):21915–21926

    Article  CAS  Google Scholar 

  • Borror CM (2009) Statistical decision making. In: Borror CM (ed) The certified quality engineer handbook, 3rd edn. ASQ Quality Press, Milwaukee, pp 418–472

    Google Scholar 

  • Braun C, Merk C, Pönitzsch G, Rehdanz K, Schmidt U (2018) Public perception of climate engineering and carbon capture and storage in Germany: survey evidence. Clim Pol 18(4):471–484

    Article  Google Scholar 

  • Çolak M, Kaya İ (2017) Prioritization of renewable energy alternatives by using an integrated fuzzy MCDM model: a real case application for Turkey. Renew Sust Energ Rev 80:840–853

    Article  Google Scholar 

  • De Fao G (2014) Sociological survey in a municipality with a high level separate collection programme in an area of historic unpopularity. Waste Manag J 34:1369–1380

    Article  Google Scholar 

  • Duţu LC, Mauris G, Bolon P (2018) A fast and accurate rule-base generation method for Mamdani fuzzy systems. IEEE Trans Fuzzy Syst 26(2):715–733

    Article  Google Scholar 

  • Fay MP, Proschan MA (2010) Wilcoxon-Mann-Whitney or t-test? On assumptions for hypothesis tests and multiple interpretations of decision rules. Stat Surv 4:1–39

    Article  Google Scholar 

  • Gosset WS (1908) The probable error of a mean. Biometrika 6:1–25

    Article  Google Scholar 

  • Hong Y-ST, Rosen MR, Bhamidimarri R (2003) Analysis of a municipal wastewater treatment plant using a neural network-based pattern analysis. Water Res 37(7):1608–1618

    Article  CAS  Google Scholar 

  • Karayannis V, Charalampides G, Lakioti E (2014) Socio-economic aspects of CCS. Proced Econ Financ 14:295–302

    Article  Google Scholar 

  • Kaya M, Conley S, Varol A (2016) Visualization of the social bot’s fingerprints. 4th International Symposium on Digital Forensics and Security (ISDFS’16), Little Rocl, AR., USA

  • Kohonen T (1998) The self-organizing map. Neurocomputing 21(1):1–6

    Article  Google Scholar 

  • Kohonen T (2001) Self-organizing maps. Springer Series in Information Sciences, vol. 30

    Book  Google Scholar 

  • Kohonen T (2013) Essentials of the self-organizing map. J Neural Netw 37:52–65

    Article  Google Scholar 

  • Kohonen T (2014) MATLAB implementations and applications of the self-organizing map. Unigrafia Oy, Helsinki

  • Kokkinos K, Lakioti E, Papageorgiou E, Moustakas K, Karayannis V (2018) Fuzzy cognitive map-based modeling of social acceptance to overcome uncertainties in establishing waste biorefinery facilities. Front Energy Res 6(112):1–17

    Google Scholar 

  • Krzywinski M, Altman N (2013) Points of significance: significance, P values and t-tests. Nat Methods 10:1041–1042

    Article  CAS  Google Scholar 

  • Lakioti E, Moustakas K, Komilis D, Domopoulou A, Karayannis V (2017) Sustainable solid waste management: socio-economic considerations. Chem Eng Trans 56:661–666

    Google Scholar 

  • Lee HM (1996) Applying fuzzy set theory to evaluate the rate of aggregative risk in software development. Fuzzy Sets Syst 79:323–336

    Article  Google Scholar 

  • Lee Y-J, Tung C-M, Lin S-C (2018) Attitudes to climate change, perceptions of disaster risk, and mitigation and adaptation behavior in Yunlin County, Taiwan. Environ Sci Pollut Res. Article in Press:1–11

  • Lin GF, Chen LH (2005) Identification of homogenous regions for regional frequency analysis using the self-organizing map. J Hydrol 324:1–9

    Article  Google Scholar 

  • Liu X, Wu Y, Hu Y, Liu D, Zhang J, Chen C, Yuan Z, Lu Y (2016) Government employees’ perception of urban air pollution and willingness to pay for improved quality: a cross-sectional survey study in Nanchang, China. Environ Sci Pollut Res 23(21):22183–22189

    Article  Google Scholar 

  • Liu J, Gong E, Wang D, Lai X, Zhu J (2018) Attitudes and behaviour towards construction waste minimisation: a comparative analysis between China and the USA. Environmental science and pollution research, Article in Press

  • Mamdani E, Assilian S (1975) An experiment in linguistic synthesis with a fuzzy logic controller. Int J Man Mach Stud 7:1–13

    Article  Google Scholar 

  • Milutinovic B, Stefanovic G, Milutinovic S, Cojbasic Z (2016) Application of fuzzy logic for evaluation of the level of social acceptance of waste treatment. Clean Techn Environ Policy 18:863–1875

    Article  Google Scholar 

  • Moustakas K, Loizidou M (2018) Sustainable waste management. Environ Sci Pollut Res 25(36):35761–35763

    Article  Google Scholar 

  • Munda G (2004) Social multi-criteria evaluation: methodological foundations and operational consequences. Eur J Oper Res 158:662–677

    Article  Google Scholar 

  • Munda G (2008) Social multi criteria evaluation for a sustainable economy. Springer, Berlin

    Book  Google Scholar 

  • Nadiri AA, Naderi K, Khatibi R, Gharekhani M (2019) Modelling groundwater level variations by learning from multiple models using fuzzy logic. Hydrological Sciences Journal, Article in Press

  • Ostadi B, Mokhtarian Daloie R, Sepehri MM (2019) A combined modelling of fuzzy logic and time-driven activity-based costing (TDABC) for hospital services costing under uncertainty. J Biomed Inform 89:11–28

    Article  Google Scholar 

  • Singh J, Singh N, Sharma JK (2006) Fuzzy modeling and control of HVAC systems – a review. Int J Sci Indust Res 65:470–476

    Google Scholar 

  • SOM in Matlab (2014) (last accessed Jan. 17th, 2019) http://www.mathworks.com/help/nnet/gs/cluster-data-with-a-self-organizing-map.html

  • Song Q, Wang Z, Li J (2016) Exploring residents’ attitudes and willingness to pay for solid waste management in Macau. Environ Sci Pollut Res 23(16):16456–16462

    Article  Google Scholar 

  • Stezar IC, Ozunu A, Barry DL (2014) The role of stakeholder attitudes in managing contaminated sites: survey of Romanian stakeholder awareness. Environ Sci Pollut Res 21(1):787–800

    Article  CAS  Google Scholar 

  • Turcott Cervantes DE, López Martínez A, Cuartas Hernández M, Lobo García de Cortázar A (2018) Using indicators as a tool to evaluate municipal solid waste management: A critical review. Waste Manag 80:51–63

    Article  Google Scholar 

  • Yen J, Langeri R (1999) Fuzzy logic: intelligence, control, and information. Prentice Hall, Englewood Cliffs, New Jersey

    Google Scholar 

  • Zadeh LA (1965) Fuzzy sets. Inf Control J 8(3):338–353

    Article  Google Scholar 

  • Zadeh LA (2008) Is there a need for fuzzy logic? Inf Sci J 178:2751–2779

    Article  Google Scholar 

  • Zorpas AA, Dimitriou M, Voukkali I (2018) Disposal of household pharmaceuticals in insular communities: social attitude, behaviour evaluation and prevention activities. Environ Sci Pollut Res 25(27):26725–26735

    Article  Google Scholar 

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Correspondence to Konstantinos Moustakas.

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Appendix

Appendix

Table 5 Pair correlations between the SURVEY statistics and the FIS model statistics
Table 6 Pairwise sample Statistics

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Kokkinos, K., Karayannis, V., Lakioti, E. et al. Exploring social determinants of municipal solid waste management: survey processing with fuzzy logic and self-organized maps. Environ Sci Pollut Res 26, 35288–35304 (2019). https://doi.org/10.1007/s11356-019-05506-2

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  • DOI: https://doi.org/10.1007/s11356-019-05506-2

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