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GB/T 46019.2-2025 PDF English

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GB/T 46019.2-2025: Plastics - Identification of recycled plastics - Part 2: Polypropylene(PP) materials
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Basic data

Standard ID GB/T 46019.2-2025 (GB/T46019.2-2025)
Description (Translated English) Plastics - Identification of recycled plastics - Part 2: Polypropylene(PP) materials
Sector / Industry National Standard (Recommended)
Classification of Chinese Standard G31
Classification of International Standard 83.080.01, 13.030.50
Word Count Estimation 26,276
Date of Issue 2025-08-01
Date of Implementation 2026-02-01
Issuing agency(ies) State Administration for Market Regulation, Standardization Administration of China

GB/T 46019.2-2025: Plastics - Identification of recycled plastics - Part 2: Polypropylene(PP) materials




---This is an excerpt. Full copy of true-PDF in English version (including equations, symbols, images, flow-chart, tables, and figures etc.), auto-downloaded/delivered in 9 seconds, can be purchased online: https://www.ChineseStandard.net/PDF.aspx/GBT46019.2-2025
ICS 83.080.01;13.030.50 CCSG31 National Standard of the People's Republic of China Identification of recycled plastic components Part 2.Polypropylene (PP) materials Released on August 1, 2025 Implementation on February 1, 2026 State Administration for Market Regulation The National Standardization Administration issued

Table of Contents

Preface III Introduction IV 1 Scope 1 2 Normative references 1 3 Terms and Definitions 1 4 Principle 2 5 Model construction and evaluation 2 6 Identification of test samples 6 Appendix A (Informative) Identification Process of Virgin PP and Recycled PP 8 Appendix B (Informative) Typical Total Ion Chromatograms of Virgin PP and Recycled PP 11 Appendix C (Informative) Typical characteristic volatile components for identification of virgin PP and recycled PP 14 Appendix D (Informative) Random Forest Model Hyperparameter Combination Setting Examples 15 Appendix E (Informative) Examples of Identification of Virgin PP and Recycled PP 16 Reference 19 Preface This document is in accordance with the provisions of GB/T 1.1-2020 "Guidelines for standardization work Part 1.Structure and drafting rules for standardization documents" Drafting. This document is Part 2 of GB/T 46019 “Plastics – Identification of Recycled Plastics Content”. GB/T 46019 has been published in the following parts. --- Part 1.Polyethylene terephthalate (PET) material; --- Part 2.Polypropylene (PP) material. Please note that some of the contents of this document may involve patents. The issuing organization of this document does not assume the responsibility for identifying patents. This document was proposed by the China Petroleum and Chemical Industry Federation. This document is under the jurisdiction of the National Technical Committee on Plastics Standardization (SAC/TC15). This document was drafted by. Guangzhou Customs Technology Center, Circular New Materials (Handan) Co., Ltd., Beijing Academy of Science and Technology Analysis and Testing Institute (Beijing Physical and Chemical Analysis and Testing Center), Toshiba Home Appliance Manufacturing (Nanhai) Co., Ltd., Fujian Huasheng Mingtu Environmental Protection Technology Co., Ltd. Company, Zhili Technology (Guangdong) Co., Ltd., Guangzhou Shitian Material Technology Co., Ltd., Beijing Huasu Chenguang Technology Co., Ltd., Jiangsu Saiwei Er New Material Technology Co., Ltd., Sinopec (Beijing) Chemical Research Institute Co., Ltd., Zhonglan Chenguang Chengdu Testing Technology Co., Ltd., Ningbo Hai Guan Technology Center, Shandong Dawn Polymer Materials Co., Ltd., Guangzhou Quality Supervision and Inspection Institute, Tonggui Technology Chengdu Co., Ltd., Zhejiang Boluite Environmental Protection Technology Engineering Co., Ltd., Tianjin University, Guizhou University, Zhuhai Gree New Materials Co., Ltd., Jinan University, Guangdong C Xin New Materials Co., Ltd., Kingfa Science & Technology Co., Ltd., Shanghai Research Institute of Chemical Industry Co., Ltd., Guangdong Sunway Saite Engineering Plastics Development Co., Ltd. Co., Ltd., Fujian Fiber Inspection Center, Wanrong Rili New Materials (Hunan) Co., Ltd., Yantai Zhenghai Hetai Technology Co., Ltd., Qingdao Customs Technology Center, Zhejiang Jincai New Materials Co., Ltd., Hunan Zhongke New Materials Co., Ltd., Shenzhen Rigao Adhesive Tape New Materials Co., Ltd., Hubei Botao Synthetic Fiber Co., Ltd., Shenzhen Haixinglong Plastic Hardware Products Co., Ltd., Shanghai Qianshi Technology Co., Ltd., China Quality Standard Research Institute (Beijing) Standardization Service Center, Shanghai Ruiju Environmental Protection Technology Co., Ltd. The main drafters of this document are. Su Qizhi, Zhong Huaining, Li Zhuoying, Gao Xia, Huo Yaonan, Wei Yunan, Yang Qinghua, Wen Jianghe, Zheng Huiqin, Li Dan, Zhang Shuo, Xue Yanbo, Xie Peng, Luo Chuan, Wang Zefang, Ye Yuanjian, Chen Hongyuan, Ou Xiwen, Li Zhonglei, Zhang Zhenming, Yang Weiye, Lin Qinbao, Zhang Mei, Zhou Jingnan, Zheng Wen, Shen Xianting, Gu Jiajun, Yang Huahao, Chen Minjian, Zhu Feng, Song Zhen, Wei Ming, Liu Jie, Wang Lun, Sun Xia, Sun Liming, Li Yan, Zhao Lei, Zhang Shibo, Ding Haibo, Wu Weijun, Lu Ning, Zhang Changan, Xiong Wei, Mo Hongren, Li Zhou, Luo Xiaoxia, and Shi Yingjie.

introduction

Building a waste recycling system is a key step in my country's implementation of a comprehensive conservation strategy, ensuring national resource security, and actively and steadily promoting carbon peak and carbon neutrality. The recycling and reuse of post-consumer plastics is an important part of waste recycling. Part, not only can reduce resource waste and environmental pollution, but also effectively reduce carbon emissions, is an important part of promoting the green and efficient development of the plastics industry Polypropylene (PP) is a thermoplastic widely used in packaging, automobiles, home appliances and other fields. Its efficient recycling of post-consumer waste Recycling and reuse are of great significance for promoting resource circulation and promoting the green and efficient development of the plastics industry. Plastic materials may introduce various impurities during use, disposal and recycling. However, unlike chemical recycling, mechanical recycling is difficult to Completely remove impurities from post-consumer plastics. Therefore, mechanically recycled PP (also known as PP (REC)) is similar to the original PP in terms of volatile component characteristics. By analyzing the volatile components in PP materials, typical characteristic volatile components can be screened out. The results provide a basis for the identification of virgin and recycled PP. This document is based on the analysis of volatile components in virgin PP and recycled PP samples using headspace gas chromatography-mass spectrometry (HS-GC-MS) technology. The typical volatile components were screened out by analysis and the random forest classification model was combined to give the predicted value of the regeneration PP probability, so as to achieve the prediction of whether the sample is No, it is identification of post-consumer mechanically recycled PP. To ensure the scientificity and reliability of the detection method, this document combines the current relevant standards to clarify the sample preparation method, instrument reference conditions, The standardized process of software and data processing, as well as the specific steps of model construction and evaluation, aims to provide a systematic, repeatable and Traceable technical guidance helps to efficiently recycle plastic waste. GB/T 46019 "Plastics - Identification of Recycled Plastics Components" is intended to consist of three parts. --- Part 1.Polyethylene terephthalate (PET) materials. The purpose is to establish a method for identifying recycled PET materials. --- Part 2.Polypropylene (PP) materials. The purpose is to establish a method for identifying recycled PP materials. --- Part 3.Polyethylene (PE) materials. The purpose is to establish a method for identifying recycled PE materials. Identification of recycled plastic components Part 2.Polypropylene (PP) materials

1 Scope

This document describes the determination of volatile components of polypropylene (PP) materials using headspace gas chromatography-mass spectrometry, using a random forest algorithm. A method to construct a predictive model to distinguish post-consumer mechanically recycled PP plastic materials from virgin PP plastic materials. This document applies to pellets made from post-consumer PP through processes such as crushing, screening, classification, cleaning, and melt extrusion granulation. Identification of PP recycled plastic materials. This document is not applicable to the identification of recycled PP plastic materials obtained through chemical recycling.

2 Normative references

The contents of the following documents constitute the essential clauses of this document through normative references in this document. For referenced documents without a date, only the version corresponding to that date applies to this document; for referenced documents without a date, the latest version (including all amendments) applies to This document. GB/T 2035 Plastics Terminology GB/T 30102 Guidelines for the recycling and reuse of plastic waste GB/T 40006.1 Plastics Recycled Plastics Part 1.General GB/T 41867 Information Technology - Artificial Intelligence Terminology GB/T 45090 Plastics - Marking and identification of recycled plastics

3 Terms and Definitions

The following terms and definitions are defined in GB/T 2035, GB/T 30102, GB/T 40006.1, GB/T 45090 and GB/T 41867. The definitions apply to this document. 3.1 post-consumer plastic Plastics generated by end users that have fulfilled their intended use or are no longer usable (including plastics returned from circulation). [Source. GB/T 30102-2024, 3.3, modified] 3.2 Random Forest Model randomforestmodel A machine learning method that performs classification or regression by building multiple decision trees and aggregating their predictions. 3.3 Gini impurity An indicator to measure the purity of a dataset, that is, the probability that two samples randomly selected from the dataset belong to different categories. Note. The smaller the Gini impurity, the higher the purity of the dataset. 3.4 Grid Search Train the models one by one within the preset hyperparameter combination range and evaluate the performance to determine the optimal hyperparameter combination.
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