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氯菊酯在 PET 容器中的迁移及其通过人工神经网络的排放估算。

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

机构信息

Department of Organic Chemical Technology, Faculty of Technology and Metallurgy, University of Belgrade, Karnegijeva 4, Belgrade, 11120, Serbia.

Innovation Center of the Faculty of Technology and Metallurgy, University of Belgrade, Karnegijeva 4, Belgrade, 11120, Serbia.

出版信息

Environ Sci Pollut Res Int. 2019 Oct;26(28):28933-28939. doi: 10.1007/s11356-019-06108-8. Epub 2019 Aug 6.

DOI:10.1007/s11356-019-06108-8
PMID:31388955
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 R = 0.94 and the mean absolute percentage error (MAPE) of only 6.2% on testing.

摘要

如今,在农作物生产中广泛使用农药,这对在安全生产、储存和使用后处理过程中尽量减少其副作用提出了重大挑战。本文报告了与通过 PET 容器排放某些农药制剂以及在储存过程中减轻这些制剂对 PET 容器影响相关的结果。研究了储存时间对氯菊酯通过 PET 迁移到 PET 容器中和通过 PET 容器迁移的影响,该研究采用了短期合作国际农药分析理事会测试,持续时间长达 30 天。PET 容器中填充了纯二甲苯和农药制剂,其中活性物质氯菊酯(CY)的含量从 5 到 20wt%不等,而乳化剂的含量保持不变。结果表明,农药制剂以平均增加其初始质量 1.5%的速度向 PET 容器扩散。储存的头 24 个月内扩散最剧烈,之后其速度显著下降。值得注意的是,研究中扩散的农药制剂也非常依赖于 CY 浓度。除了向 PET 容器迁移外,还发现农药制剂在储存的头 17 到 24 个月内通过 PET 容器排放,具体取决于 CY 浓度。排放速率也依赖于 CY 浓度,范围在 15.3 到 38.0mg/月·容器。使用人工神经网络成功地预测了通过 PET 容器的排放,其在测试中的 R 值为 0.94,平均绝对百分比误差(MAPE)仅为 6.2%。

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本文引用的文献

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