School of Business, Dr. Vishwanath Karad MIT World Peace University, Pune, India.
Lakshmibai College, University of Delhi, 110052, New Delhi, India.
Environ Sci Pollut Res Int. 2023 Dec;30(59):123039-123054. doi: 10.1007/s11356-023-30799-9. Epub 2023 Nov 18.
Plastic pollution has become a prominent and pressing environmental concern within the realm of pollution. In recent times, microplastics have entered our ecosystem, especially in freshwater. In the contemporary global landscape, there exists a mounting apprehension surrounding the manifold environmental and public health issues that have emerged as a result of the substantial accumulation of microplastics. The objective of the current study is to employ an enhanced grey prediction model in order to forecast global plastic production and microplastic emissions. This study compared the accuracy level of the four grey prediction models, namely, EGM (1,1, α, θ), DGM (1,1), EGM (1,1), and DGM (1,1, α) models, to evaluate the accuracy levels. As per the estimation of the study, DGM (1,1, α) was found to be more suitable with higher accuracy levels to predict microplastic emission. The EGM (1,1, α, θ) model has slightly better accuracy than the DGM (1,1, α) model in predicting global plastic production. Various accuracy measurement tools (MAPE and RMSE) were used to determine the model's efficiency. There has been a gradual growth in both plastic production and microplastic emission. The current study using the DGM (1,1, α) model predicted that microplastic emission would be 1,084,018 by 2030. The present study aims to provide valuable insights for policymakers in formulating effective strategies to address the complex issues arising from the release of microplastics into the environment and the continuous production of plastic materials.
塑料污染已成为污染领域中一个突出且紧迫的环境问题。近年来，微塑料已经进入我们的生态系统，尤其是在淡水中。在当代全球背景下，人们越来越担心大量微塑料的积累所带来的各种环境和公共卫生问题。本研究旨在采用改进的灰色预测模型来预测全球塑料产量和微塑料排放量。本研究比较了四种灰色预测模型，即 EGM(1,1,α,θ)、DGM(1,1)、EGM(1,1)和 DGM(1,1,α)模型的准确性水平，以评估其准确性。研究结果表明，DGM(1,1,α)模型更适合预测微塑料排放，具有更高的准确性。EGM(1,1,α,θ)模型在预测全球塑料产量方面的准确性略高于 DGM(1,1,α)模型。研究采用了多种精度测量工具（MAPE 和 RMSE）来确定模型的效率。塑料产量和微塑料排放量都呈逐渐增长的趋势。本研究采用 DGM(1,1,α)模型预测，到 2030 年微塑料排放量将达到 1,084,018 吨。本研究旨在为政策制定者提供有价值的见解，以制定有效的策略来应对微塑料释放到环境中以及塑料材料不断生产所带来的复杂问题。
