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Journal of Material Cycles and Waste Management

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16.01.2024 | REGIONAL CASE STUDY

Characterization of municipal solid waste generation and seasonal classification for various socio-demographic groups in Guwahati city

verfasst von: Tinka Singh, Abhipsa Naik, Ramagopal V. S. Uppaluri

Erschienen in: Journal of Material Cycles and Waste Management | Ausgabe 2/2024

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Abstract

Municipal solid waste management (MSWM) is a pressing environmental issue in rapidly urbanizing cities, including Guwahati, India. Finding sustainable solutions to handle the increasing waste generation while minimizing environmental impact is challenging. This article focuses on Guwahati as a model city and presents a survey-based quantification of municipal solid waste, considering seasonal variations and socio-demographic groups. The study utilizes statistical analysis to identify dominant waste constituents and their correlation with population, household characteristics, and income levels. The results depict that across all socioeconomic categories, an average of 0.201 kg of waste is generated per person daily. In addition, it is observed that higher income levels are associated with increased solid waste generation. For sub-areas A1 (middle income), A2 (high income), and A3 (low income), the respective per capita waste generation rates are 0.18 kg/capita/day, 0.23 kg/capita/day, and 0.17 kg/capita/day. These findings provide crucial insights for developing a sustainable solid waste management plan in Guwahati, aiding policymakers and waste management authorities in designing tailored strategies for waste collection, treatment, reuse, and disposal. By implementing targeted measures such as waste reduction campaigns and promoting recycling, the city can work towards effective waste management and sustainable development.

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Chang N-B, Davila E (2008) Municipal solid waste characterizations and management strategies for the Lower Rio Grande Valley, Texas. Waste Manage 28:776–794. https://doi.org/10.1016/j.wasman.2007.04.002CrossRef

Abdel-Shafy HI, Mansour MSM (2018) Solid waste issue: Sources, composition, disposal, recycling, and valorization. Egypt J Pet 27:1275–1290. https://doi.org/10.1016/j.ejpe.2018.07.003CrossRef

Hoornweg D, Bhada-Tata P, Kennedy C (2013) Environment: waste production must peak this century. Nature 502:615–617. https://doi.org/10.1038/502615aCrossRefPubMed

Qu X et al (2009) Combined monitoring of changes in Î´13CH4 and archaeal community structure during mesophilic methanization of municipal solid waste. FEMS Microbiol Ecol 68:236–245. https://doi.org/10.1111/j.1574-6941.2009.00661.xCrossRefPubMed

Phuntsho S, Dulal I, Yangden D et al (2009) Studying municipal solid waste generation and composition in the urban areas of Bhutan. Waste Manage Res J Sustain Circul Econ 28:545–551. https://doi.org/10.1177/0734242x09343118CrossRef

Ojeda-Benítez S, Vega CA, Marquez-Montenegro MY (2008) Household solid waste characterization by family socioeconomic profile as unit of analysis. Resour Conserv Recycl 52:992–999. https://doi.org/10.1016/j.resconrec.2008.03.004CrossRef

Sujauddin M, Huda SMS, Hoque ATMR (2008) Household solid waste characteristics and management in Chittagong, Bangladesh. Waste Manage 28:1688–1695. https://doi.org/10.1016/j.wasman.2007.06.013CrossRef

Thanh NP, Matsui Y, Fujiwara T (2010) Household solid waste generation and characteristic in a Mekong Delta city. Vietnam J Environ Manage 91:2307–2321. https://doi.org/10.1016/j.jenvman.2010.06.016CrossRefPubMed

Ogwueleka TC (2013) Survey of household waste composition and quantities in Abuja, Nigeria. Resour Conserv Recycl 77:52–60. https://doi.org/10.1016/j.resconrec.2013.05.011CrossRef

10.

Alqader AA, Hamad J (2012) Municipal solid waste composition determination supporting the integrated solid waste management inGaza strip. Int J Environ Sci Develop. https://doi.org/10.7763/ijesd.2012.v3.210CrossRef

11.

Kamran A, Chaudhry MN, Batool SA (2015) Effects of socio-economic status and seasonal variation on municipal solid waste composition: a baseline study for future planning and development. Environm Sci Europe. https://doi.org/10.1186/s12302-015-0050-9CrossRef

12.

Nguyen KLP, Chuang YH, Chen HW, Chang CC (2020) Impacts of socioeconomic changes on municipal solid waste characteristics in Taiwan. Resour Conserv Recycl 161:104931. https://doi.org/10.1016/j.resconrec.2020.104931CrossRef

13.

Zhu J-J, Park D, Chang DT et al (2021) Unsupervised aided investigation on the associations between municipal solid waste characteristics and socio-economic conditions. Environ Res 194:110633. https://doi.org/10.1016/j.envres.2020.110633CrossRefPubMed

14.

Suthar S, Singh P (2015) Household solid waste generation and composition in different family size and socio-economic groups: a case study. Sustain Cities Soc 14:56–63. https://doi.org/10.1016/j.scs.2014.07.004CrossRef

15.

Monavari SM, Omrani GA, Karbassi A, Raof FF (2011) The effects of socioeconomic parameters on household solid-waste generation and composition in developing countries (a case study: Ahvaz, Iran). Environ Monit Assess 184:1841–1846. https://doi.org/10.1007/s10661-011-2082-yCrossRefPubMed

16.

Xu F, Liu Y, Wang J et al (2014) Characterization of heavy metals and brominated flame retardants in the indoor and outdoor dust of e-waste workshops: implication for on-site human exposure. Environ Sci Pollut Res 22:5469–5480. https://doi.org/10.1007/s11356-014-3773-zCrossRef

17.

Singh T, Uppaluri RVS (2023) Application of ANN and traditional ML algorithms in modelling compost production under different climatic conditions. Neural Comput Appl. https://doi.org/10.1007/s00521-023-08404-4CrossRefPubMedPubMedCentral

18.

Senzige JP (2014) Factors influencing solid waste generation and composition in Urban Areas of Tanzania: The case of Dar-es-Salaam. Am J Environ Protect 3:172. https://doi.org/10.11648/j.ajep.20140304.11

19.

Bandara NJGJ (2011) Municipal solid waste management - The Sri Lankan Case. Proceedings of International Forestry and Environment Symposium https://doi.org/10.31357/fesympo.v0i0.21

20.

Namlis K-G, Komilis D (2019) Influence of four socioeconomic indices and the impact of economic crisis on solid waste generation in Europe. Waste Manage 89:190–200. https://doi.org/10.1016/j.wasman.2019.04.012CrossRef

21.

Grazhdani D (2016) Assessing the variables affecting on the rate of solid waste generation and recycling: an empirical analysis in Prespa Park. Waste Manage 48:3–13. https://doi.org/10.1016/j.wasman.2015.09.028CrossRef

22.

Kontokosta CE, Hong B, Johnson NE, Starobin D (2018) Using machine learning and small area estimation to predict building-level municipal solid waste generation in cities. Comput Environ Urban Syst 70:151–162. https://doi.org/10.1016/j.compenvurbsys.2018.03.004CrossRef

23.

Kolekar (2017) Prediction of municipal solid waste generation for developing countries in temporal scale: a fuzzy inference system approach. Glob NEST J 19(3):511–520.https://doi.org/10.30955/gnj.002323

24.

Singh T, Uppaluri RVS (2022) Machine learning tool-based prediction and forecasting of municipal solid waste generation rate: a case study in Guwahati, Assam, India. Int J Environ Sci Technol. https://doi.org/10.1007/s13762-022-04644-4CrossRef

25.

Kannangara M, Dua R, Ahmadi L, Bensebaa F (2018) Modeling and prediction of regional municipal solid waste generation and diversion in Canada using machine learning approaches. Waste Manage 74:3–15. https://doi.org/10.1016/j.wasman.2017.11.057CrossRef

26.

Al-Khatib IA, Monou M, Abu Zahra ASF et al (2010) Solid waste characterization, quantification and management practices in developing countries. A case study: Nablus district – Palestine. J Environ Manage 91:1131–1138. https://doi.org/10.1016/j.jenvman.2010.01.003CrossRefPubMed

27.

Ozcan H, Guvenc S, Guvenc L, Demir G (2016) Municipal solid waste characterization according to different income levels: a case study. Sustainability 8:1044. https://doi.org/10.3390/su8101044CrossRef

28.

www.mospi.gov.in/sites/default/files/main_menu/annual_report_2011_2012/Annual_Report_Ministry/Printed_Annual_Report_2021_22_%28Eng.%29.pdf

29.

des.assam.gov.in/sites/default/files/swf_utility_folder/departments/ecostat_medhassu_in_oid_3/menu/document/economic_survey%202015–16_0.pdf

30.

Tchobanoglous G, Kreith F (2002) Handbook of solid waste management. Mcgraw-Hill, New York

31.

des.assam.gov.in/sites/default/files/swf_utility_folder/departments/ecostat_medhassu_in_oid_3/menu/document/economic_survey%202018–19_0.pdf

32.

Singhal A, Gupta AK, Dubey B, Ghangrekar MM (2021) Seasonal characterization of municipal solid waste for selecting feasible waste treatment technology for Guwahati city, India. J Air Waste Manage Assotechc 72:147–160. https://doi.org/10.1080/10962247.2021.1980450CrossRef

33.

Dunteman GH (2008) Principal components analysis. Sage, Newbury Park

34.

Vicente P, Reis E (2008) Factors influencing households’ participation in recycling. Waste Manage Res 26:140–146. https://doi.org/10.1177/0734242x07077371CrossRef

35.

Chen Liu WuX (2010) Factors influencing municipal solid waste generation in China: a multiple statistical analysis study. Waste Manage Res 29:371–378. https://doi.org/10.1177/0734242x10380114CrossRef

36.

Kaiser HF (1974) An index of factorial simplicity. Psychometrika 39:31–36. https://doi.org/10.1007/bf02291575CrossRef

37.

Ngai EWT, Poon JKL, Chan YHC (2007) Empirical examination of the adoption of WebCT using TAM. Comput Educ 48:250–267. https://doi.org/10.1016/j.compedu.2004.11.007CrossRef

38.

Rao CR (1964) The use and interpretation of principal component analysis in applied research. Sankhyā Indian J Statist Series A (1961–2002) 6:329–358MathSciNet

39.

van den Wollenberg AL (1977) Redundancy analysis an alternative for canonical correlation analysis. Psychometrika 42:207–219. https://doi.org/10.1007/bf02294050CrossRef

40.

Huang W-J, Lin Y-H, Chen W-Y et al (2015) Causal relationships among biological toxicity, geochemical conditions and derived DBPs in groundwater. J Hazard Mater 283:24–34. https://doi.org/10.1016/j.jhazmat.2014.08.031CrossRefPubMed

41.

Chen Q-L, Li H, Zhou X-Y et al (2017) An underappreciated hotspot of antibiotic resistance: The groundwater near the municipal solid waste landfill. Sci Total Environ 609:966–973. https://doi.org/10.1016/j.scitotenv.2017.07.164ADSCrossRefPubMed

42.

You X, Wu D, Wei H et al (2018) Fluoroquinolones and β-lactam antibiotics and antibiotic resistance genes in autumn leachates of seven major municipal solid waste landfills in China. Environ Int 113:162–169. https://doi.org/10.1016/j.envint.2018.02.002CrossRefPubMed

43.

Hira M, Yadav S, Morthekai P et al (2018) Mobile Phones—An asset or a liability: A study based on characterization and assessment of metals in waste mobile phone components using leaching tests. J Hazard Mater 342:29–40. https://doi.org/10.1016/j.jhazmat.2017.08.008CrossRefPubMed

44.

Chuang Y-H, Huang W-J, Nguyen KLP et al (2019) Redundancy analysis for characterizing the groundwater quality in coastal industrial areas. Environm Forens 20:77–91. https://doi.org/10.1080/15275922.2019.1566292CrossRef

45.

Legendre P, Legendre L (2012) Numerical ecology. Elsevier

46.

Noori R, Abdoli MA, Ghasrodashti AA, Jalili Ghazizade M (2009) Prediction of municipal solid waste generation with combination of support vector machine and principal component analysis: a case study of Mashhad. Environ Prog Sustain Energy 28:249–258. https://doi.org/10.1002/ep.10317CrossRef

47.

Mckenzie SK, Carter KN, Blakely T, Ivory V (2011) Effects of childhood socioeconomic position on subjective health and health behaviours in adulthood: how much is mediated by adult socioeconomic position? BMC Public Health. https://doi.org/10.1186/1471-2458-11-269CrossRefPubMedPubMedCentral

48.

Filmer D, Pritchett LH (2001) Estimating Wealth effects without expenditure data-or tears: an application to educational enrollments in States of India. Demography 38:115. https://doi.org/10.2307/3088292CrossRefPubMed

49.

Abu Qdais HA, Hamoda MF, Newham J (1997) Analysis of residential solid waste at generation sites. Waste Manage Res 15:395–405. https://doi.org/10.1177/0734242x9701500407CrossRef

50.

Buenrostro O, Bocco G, Bernache G (2001) Urban solid waste generation and disposal in Mexico: a case study. Waste Manage Res 19:169–176. https://doi.org/10.1177/0734242x0101900208CrossRef

51.

Cao LJ, Keerthi SS, Ong C-J et al (2006) Parallel sequential minimal optimization for the training of support vector machines. IEEE Trans Neural Networks 17:1039–1049. https://doi.org/10.1109/tnn.2006.875989CrossRefPubMed

52.

Hristovski K, Olson L, Hild N et al (2007) The municipal solid waste system and solid waste characterization at the municipality of Veles, Macedonia. Waste Manage 27:1680–1689. https://doi.org/10.1016/j.wasman.2006.09.003CrossRef

53.

Mmereki D, Baldwin A, Li B, Liu M (2017) Healthcare waste management in Botswana: storage, collection, treatment and disposal system. J Mater Cycles Waste Manag 19:351–365CrossRef

Titel: Characterization of municipal solid waste generation and seasonal classification for various socio-demographic groups in Guwahati city
verfasst von: Tinka Singh
Abhipsa Naik
Ramagopal V. S. Uppaluri
Publikationsdatum: 16.01.2024
Verlag: Springer Japan
Erschienen in: Journal of Material Cycles and Waste Management / Ausgabe 2/2024
Print ISSN: 1438-4957
Elektronische ISSN: 1611-8227
DOI: https://doi.org/10.1007/s10163-023-01870-x

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