Abstract
Landfill leachate, due to its quantity and inherent risk, is generally collected and transported by piping system for advanced treatment. During the piping, the pipe materials may react with leachate, resulting in corrosion and scaling. In order to reduce possible failures and mitigate the associated consequences, this study provides an indicator system for material selection to aid the pipe system design. The material functional, economic, and environmental attributes are incorporated into the indicator system, to perform a precise selection of commercial drainage pipe materials, thus improving empirically oriented selection. Four common drainage pipe materials including high-density polyethylene (HDPE), polyvinyl chloride (PVC), galvanized steel, and seamless steel are taken as the material alternatives for the selection. Based upon their experimental data, a grey target decision-making framework is employed to perform the priority ranking of the materials. The results indicate that HDPE has the best performance, followed by PVC, galvanized steel, and seamless steel. This study discusses the validity of the selection results and the applicability of the proposed method, to provide insight into leachate piping system design.
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References
Abastante F, Corrente S, Greco S, Ishizaka A, Lami IM (2019) A new parsimonious AHP methodology: assigning priorities to many objects by comparing pairwise few reference objects. Expert Syst Appl 127:109–120
Akhtar S, Reza B, Hewage K, Shahriar A, Zargar A, Sadiq R (2015) Life cycle sustainability assessment (LCSA) for selection of sewer pipe materials. Clean Tech Environ Policy 17:973–992
Akram M, Ilyas F, Garg H (2020) Multi-criteria group decision making based on ELECTRE I method in pythagorean fuzzy information. Soft Comput 24:3425–3453
Anojkumar L, Ilangkumaran M, Sasirekha V (2014) Comparative analysis of MCDM methods for pipe material selection in sugar industry. Expert Syst Appl 41:2964–2980
Ashby MF (2009) Materials and the environment: eco-informed material choice. Elsevier, Oxford
Bao J, Zhang J, Shi S, Johansson J (2018) Cleaner production assessment of group company based on improved AHP and grey relational analysis. J Intell Fuzzy Syst 35(1):439–444
Barton NA, Farewell TS, Hallett SH, Acland TF (2019) Improving pipe failure predictions: factors affecting pipe failure in drinking water networks. Water Res 164:114926
Chee R, Lansey K, Chee E (2018) Estimation of water pipe installation construction costs. J Pipeline Syst Eng Pract 9:04018008
Chen Q, Wang C, Wen P, Sun X, Guo T (2019) Performance evaluation of tourmaline modified asphalt mixture based on grey target decision method. Constr Build Mater 205:137–147
de Almeida Filho AT, Clemente TRN, Morais DC, de Almeida AT (2018) Preference modeling experiments with surrogate weighting procedures for the PROMETHEE method. Eur J Opera Res 264:453–461
Deng J (2010) Grey entropy and grey target decision making. J Grey Syst 22:1–4
Dev S, Aherwar A, Patnaik A (2020) Material selection for automotive piston component using entropy-VIKOR method. Silicon 12:155–169
Du F, Woods GJ, Kang D, Lansey KE, Arnold RG (2013) Life cycle analysis for water and wastewater pipe materials. J Environ Eng 139(5):703–711
Du JL, Liu Y, Forrest JYL (2019) An interactive group decision model for selecting treatment schemes for mitigating air pollution. Environ Sci Pollut Res 26(18):18687–18707
Gupta M, Kumar S (2013) Multi-objective optimization of cutting parameters in turning using grey relational analysis. Int J Ind Eng Comput 4:547–558
Hafezalkotob A, Hafezalkotob A (2016) Fuzzy entropy-weighted MULTIMOORA method for materials selection. J Intell Fuzzy Syst 31:1211–1226
Hajibabaei M, Nazif S, Sereshgi FT (2018) Life cycle assessment of pipes and piping process in drinking water distribution networks to reduce environmental impact. Sust. Cities Soc. 43:538–549
Hatami-Marbini A, Toloo M (2017) An extended multiple criteria data envelopment analysis model. Expert Syst Appl 7:201–219
Hogg RV, McKean JW, Craig AT (2012) Introduction to mathematical statistics. Pearson, New York
Jahan A, Edwards KL (2015) A state-of-the-art survey on the influence of normalization techniques in ranking: improving the materials selection process in engineering design. Mater Des 65:335–342
Jin Y (2016) Integration of stochastic approaches in the life cycle cost analysis of sewer pipe applications. Int J Prod Econ 179:35–43
Kamaruddin MA, Yusoff MS, Rui LM, Isa AM, Zawawi MH, Alrozi R (2017) An overview of municipal solid waste management and landfill leachate treatment: Malaysia and Asian perspectives. Environ Sci Pollut Res 24:26988–27020
Khoshand A, Rahimi K, Ehteshami M, Gharaei S (2019) Fuzzy AHP approach for prioritizing electronic waste management options: a case study of Tehran, Iran. Environ Sci Pollut Res 26:9649–9660
Kuo JY (2017) The study on the evaluation of the pollution control situation of the sewage systems in the counties and cities of Taiwan by applying the VIKOR method. Environ Sci Pollut Res 24(35):26958–26966
Lee HC, Chang CT (2018) Comparative analysis of MCDM methods for ranking renewable energy sources in Taiwan. Renew Sust Energ Rev 92:883–896
Li Y (2014) Study on scaling and corrosion of HDPE pipeline material in leachate transportation. Southwest Jiaotong University 16-46. (In Chinese with English Abstract)
Liu S, Lin Y (2006) Grey information: theory and practical applications. Springer, London
Liu S, Chan FTS, Ran W (2016) Decision making for the selection of cloud vendor: an improved approach under group decision-making with integrated weights and objective/subjective attributes. Expert Syst Appl 55:37–47
Liu S, Yang Y, Forrest J (2017) Grey Data Analysis. Springer, Singapore
Madić M, Antucheviciene J, Radovanović M, Petković D (2017) Determination of laser cutting process conditions using the preference selection index method. Opt Laser Technol 89:214–220
Mahjouri M, Ishak MB, Torabian A, Manaf LA, Halimoon N, Ghoddusi J (2017) Optimal selection of Iron and steel wastewater treatment technology using integrated multi-criteria decision-making techniques and fuzzy logic. Process Saf Environ Protec 107:54–68
Maity SR, Chakraborty S (2015) Tool steel material selection using PROMETHEE II method. Int J Adv Manuf Technol 78:1537–1547
Manivannan R, Kumar MP (2017) Multi-attribute decision-making of cryogenically cooled micro-EDM drilling process parameters using TOPSIS method. Mater Manuf Process 32:209–215
Mao Y (2013) Based on multiple attribute decision optimization method of leachate transport pipeline material selection research. Southwest Jiaotong University 6-35. (In Chinese with English Abstract)
Mardani A, Zavadskas EK, Govindan K, Senin AA, Jusoh A (2016) VIKOR technique: a systematic review of the state-of-the-art literature on methodologies and applications. Sustainability 8:37
MOC (Ministry of Construction of the People’s Republic of China) (2009) Technical code for municipal solid waste sanitary landfill (CJJ 17–2004). Beijing. (In Chinese)
Mohsin M, Zhang J, Saidur R, Sun H, Sait SM (2019) Economic assessment and ranking of wind power potential using fuzzy-TOPSIS approach. Environ Sci Pollut Res 26(22):22494–22511
Mota JM, Pereira A, Afonso MD (2018) Selection of materials for biofouling detection in cooling water systems. Water Sci Technol: Water Supply 18:1162–1172
Mousavi-Nasab SH, Sotoudeh-Anvari A (2017) A comprehensive MCDM-based approach using TOPSIS, COPRAS and DEA as an auxiliary tool for material selection problems. Mater Des 121:237–253
Noryani M, Sapuan SM, Mastura MT (2018) Multi-criteria decision-making tools for material selection of natural fibre composites: a review. J Mech Eng Sci 12:3330–3353
Pedgley O, Rognoli V, Karana E (2016) Materials experience as a foundation for materials and design education. Int J Technol Des Ed 26:613–630
Rajesh R, Ravi V (2015) Supplier selection in resilient supply chains: a grey relational analysis approach. J Clean Prod 86:343–359
Salwa HN, Sapuan SM, Mastura MT, Zuhri MYM (2019) Analytic hierarchy process (AHP)-based materials selection system for natural fiber as reinforcement in biopolymer composites for food packaging. BioResources 14:10014–10046
Samaras GF, Haidemenopoulos GN (2015) Carburization of high-temperature steels: a simulation-based ranking of carburization resistance. Eng Fail Anal 51:29–36
Sanjuan-Delmás D, Petit-Boix A, Gasol CM, Villalba G, Suárez-Ojeda ME, Gabarrel X, Josa A, Rieradevall J (2014) Environmental assessment of different pipelines for drinking water transport and distribution network in small to medium cities: a case from Betanzos, Spain. J Clean Prod 66:588–598
Shaha BN, Meeroff DE, Kohn K, Townsend TG, Schert JD, Mayer N, Schultz R, Telson J (2019) Effect of electronic water treatment system on calcium carbonate scale formation in landfill leachate collection piping. J Environ Eng 145:04019052
Stibinger J (2017) Approximation of clogging in a leachate collection system in municipal solid waste landfill in Osecna (northern Bohemia, Czech Republic). Waste Manag 63:131–142
Toloo M, Salahi M (2018) A powerful discriminative approach for selecting the most efficient unit in DEA. Comput Ind Eng 115:269–277
Vahidi E, Jin E, Das M, Singh M, Zhao F (2016) Environmental life cycle analysis of pipe materials for sewer systems. Sust Cities Soc 27:167–174
Yazdani M, Payam AF (2015) A comparative study on material selection of microelectromechanical systems electrostatic actuators using Ashby, VIKOR and TOPSIS. Mater Des 65:328–334
Yurdakul M, İç YT (2019) Comparison of fuzzy and crisp versions of an AHP and TOPSIS model for nontraditional manufacturing process ranking decision. Int J Adv Manuf Technol 18:167–192
Zhang K, Zhan J, Yao Y (2019) TOPSIS method based on a fuzzy covering approximation space: an application to biological nano-materials selection. Inform Sciences 502:297–329
Zhao R, Neighbour G, Deutz P, McGuire M (2012) Materials selection for cleaner production: an environmental evaluation approach. Mater Des 37:429–434
Zhao R, Su H, Chen X, Yu Y (2016) Commercially available materials selection in sustainable design: an integrated multi-attribute decision making approach. Sustainability 8:1–15
Zhao R, Liu S, Liu Y, Zhang L, Li Y (2018) A safety vulnerability assessment for chemical enterprises: a hybrid of a data envelopment analysis and fuzzy decision-making. J Loss Prev Process Ind 56:95–103
Zhao R, Wang X, Chen X, Liu Y (2019a) Impacts of different aged landfill leachate on PVC corrosion. Environ Sci Pollut Res 26:18256–18266
Zhao R, Huang Y, Yu Y, Guo S (2019b) An IVTIFN–TOPSIS based computational approach for pipe materials selection. Appl Sci 9:5457
Funding
This study is sponsored by the National Key Plan for Research and Development of China (No. 2019YFC1905600), National Natural Science Foundation of China (Nos. 41571520 and 51608499), Sichuan Young Talent Scientific Funding (No. 2019JDJQ0020), Sichuan Provincial Key Technology Support (Nos. 2019JDTD0024 and 2019ZHCG0048), and Sichuan Province Circular Economy Research Centre Fund (No. XHJJ-1802).
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Zhao, R., Li, M., Ma, S. et al. Material selection for landfill leachate piping by using a grey target decision-making approach. Environ Sci Pollut Res 28, 494–502 (2021). https://doi.org/10.1007/s11356-020-10385-z
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DOI: https://doi.org/10.1007/s11356-020-10385-z