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Migration of cypermethrin to and through the PET containers and artificial neural network–based estimation of its emission

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Abstract

Nowadays, the extensive use of pesticides in crops production puts a significant challenge to minimize its side effects along with safe production, storage, and after-use treatment. This paper reports results related to the emission of certain pesticide formulations through the PET containers, as well as, their mitigation to the PET containers during their storage. The influence of storage time on cypermethrin migration to and through the PET was studied in short-term Collaborative International Pesticides Analytical Council test lasting up to 30 days. The PET containers were filled with pure xylene and pesticide formulations, where the amount of active substance, cypermethrin (CY), varied from 5 to 20 wt%, while the amount of emulsifier was kept constant. The results indicate that pesticide formulations diffuse to PET containers with an average increase of its initial mass up to 1.5%. The most intensive diffusion is in the first 24 months of storage, after its rate significantly decreases. It should be noted that the diffusion studied pesticide formulations are also very dependent on CY concentration. Besides the migration to the PET containers, it was also found that pesticide formulation was emitted through the PET containers in the first 17 to 24 months of storage depending on CY concentration. Emission rates were also dependent on CY concentration and were in the range of 15.3 to 38.0 mg/month·container. The emission through the PET containers was successfully predicted using artificial neural networks with R2 = 0.94 and the mean absolute percentage error (MAPE) of only 6.2% on testing.

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References

  • Abujazar MSS, Fatihah S, Ibrahim IA, Kabeel AE, Sharil S (2018) Productivity modelling of a developed inclined stepped solar still system based on actual performance and using a cascaded forward neural network model. J Clean Prod 170:147–159

    Article  Google Scholar 

  • Antanasijević DZ, Ristić MĐ, Perić-Grujić AA, Pocajt VV (2013b) Forecasting human exposure to PM10 at the national level using an artificial neural network approach. J Chemom 27:170–177

    Article  Google Scholar 

  • Antanasijevic D, Pocajt V, Peric-Grujic A, Ristic M (2014) Modelling of dissolved oxygen in the Danube River using artificial neural networks and Monte Carlo simulation uncertainty analysis. J Hydrol 519:1895–1907

    Article  CAS  Google Scholar 

  • Antanasijević DZ, Pocajt VV, Povrenović DS, Ristić MĐ, Perić-Grujić AA (2013a) PM 10 emission forecasting using artificial neural networks and genetic algorithm input variable optimization. Sci Total Environ 443:511–519

    Article  Google Scholar 

  • Antanasijević D, Pocajt V, Perić-Grujić A, Ristić M (2018) Multiple-input–multiple-output general regression neural networks model for the simultaneous estimation of traffic-related air pollutant emissions. Atmos Pollut Res 9:388–397

    Article  Google Scholar 

  • Chidambaram D, Venkatraj R, Manisankar P (2002) Solvent-induced modifications in poly(ethylene terephthalate) structure, properties and dyeability. Indian J Fibre Text 27:199–210 http://hdl.handle.net/123456789/22770

    CAS  Google Scholar 

  • Eras J, Vilaró JC, Pelacho AM, Canela-Garayoa R, Martin-Closas L (2017) Prevalence of pesticides in postconsumer agrochemical polymeric packaging. Sci Total Environ 580:1530–1538

    Article  CAS  Google Scholar 

  • Gullett BK, Tabor D, Touati A, Kasaic J, Fitz N (2012) Emissions from open burning of used agricultural pesticide containers. J Hazard Mater 221–222:236–241

    Article  Google Scholar 

  • Feng J, Shi Y, Yu Q, Sun C, Yang G (2016) Effect of emulsifying process on stability of pesticide nanoemulsions. Environ Sci Pollut R 497:286–292

    CAS  Google Scholar 

  • Feng J, Yang G, Zhang S, Liu Q, Jafari SM, McClements DJ (2018) Fabrication and characterization of β-cypermethrin-loaded PLA microcapsules prepared by emulsion-solvent evaporation: loading and release properties. Environ Sci Pollut Res 25:13525–13535

    Article  CAS  Google Scholar 

  • Hansen J-P, McDonald IR (2006) Theory of simple liquids (Third Edition), Elsevier.

  • Hirogaki K, Tabata I, Hisada K, Hori T (2005) An investigation of the interaction of supercritical carbon dioxide with poly(ethylene terephthalate) and the effects of some additive modifiers on the interaction. J Supercrit Fluids 36:166–172

    Article  CAS  Google Scholar 

  • ICSC (2018) ILO International Chemical Safety Cards; http://www.ilo.org/dyn/icsc/showcard.display?p_version=2&p_card_id=0246)

  • Leng Z, Padhan RK, Sreeram A (2018) Production of a sustainable paving material through chemical recycling of waste PET into crumb rubber modified asphalt. J Clean Prod 180:682–688

    Article  CAS  Google Scholar 

  • Lin K-P, Pai P-F (2016) Solar power output forecasting using evolutionary seasonal decomposition least-square support vector regression. J Clean Prod 134:456–462

    Article  Google Scholar 

  • Machado SC, Martins I (2018) Risk assessment of occupational pesticide exposure: use of endpoints and surrogates. Regul Toxicol Pharmacol 98:388–397

    Article  Google Scholar 

  • Marnasidis S, Stamatelatou K, Verikouki E, Kazantzis K (2018) Assessment of the generation of empty pesticide containers in agricultural Areas. J Environ Manag 224:37–48

    Article  Google Scholar 

  • OECD Guidance on Pesticide Compliance and Enforcement Best Practices, OECD Environment, Health and Safety Publications, Series on Pesticides No. 71, Paris 2012.

  • Pao H-T, Fu H-C, Tseng C-L (2012) Forecasting of CO2 emissions, energy consumption and economic growth in China using an improved grey model. Energy 40:400–409

    Article  Google Scholar 

  • Patel S, Bajpai J, Saini R, Bajpai AK, Acharya S (2018) Sustained release of pesticide (cypermethrin) from nanocarriers: an effective technique for environmental and crop protection. Process Saf Environ 117:315–325

    Article  CAS  Google Scholar 

  • Paydar MM, Olfati M (2018) Designing and solving a reverse logistics network for polyethylene terephthalate bottles. J Clean Prod 195:605–617

    Article  Google Scholar 

  • Specht DF (1991) A general regression neural network. IEEE Trans Neural Netw 2:568–576

    Article  CAS  Google Scholar 

  • Taghavifar H, Mardani A (2015) Prognostication of energy consumption and greenhouse gas (GHG) emissions analysis of apple production in West Azarbayjan of Iran using artificial neural network. J Clean Prod 87:159–167

    Article  Google Scholar 

  • Thwin MMT, Quah T-S (2005) Application of neural networks for software quality prediction using object-oriented metrics. J Syst Softw 76:47–156

    Article  Google Scholar 

  • Weast RC (1974) Handbook of chemistry and physics. 55th ed., Cleveland, Ohio

  • Whitford F., Martin AG (2006) Pesticides and Container Management’, Purdue Pesticide Programs, Joseph D. Becovitz, Office of the Indiana State Chemist Edited by Arlene Blessing, Purdue Pesticide Programs Frank Koontz, Russ Merzdorf, Agricultural Communication Service

  • Yang Y-S, Chou J-H, Huang W, Fu T-C, Li G-W (2013) An artificial neural network for predicting the friction coefficient of deposited Cr1−xAlxC films. Appl Soft Comput 13:109–115

    Article  Google Scholar 

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Acknowledgments

The authors gratefully acknowledge Dr. Aleksandra Perić-Grujić (University of Belgrade, Faculty of Technology and Metallurgy, Serbia) for her contribution to this work.

Funding

This received funding from the Ministry of Education, Science and Technological Development of the Republic of Serbia, Projects Nos. OI 172062 and OI 172007.

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Correspondence to Davor Antanasijević.

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Jevremović, N., Krušić, M.K., Antanasijević, D. et al. Migration of cypermethrin to and through the PET containers and artificial neural network–based estimation of its emission. Environ Sci Pollut Res 26, 28933–28939 (2019). https://doi.org/10.1007/s11356-019-06108-8

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