Frontiers in Business, Economics and Management ISSN: 2766-824X | Vol. 10, No. 2, 2023 223 Evolution of Global Plastic Scrap Trade and Analysis of China's Plastic Scrap Trade Network under the "Dual Carbon" Goal Yubo Lan School of Management, Xiโ€™an Polytechnic University, China Abstract: Plastics and their products are favored by the public for their advantages such as good corrosion resistance, high convenience, good transparency, cheap price, and wide range of uses, which have triggered a further increase in the demand for plastics and their products. However, plastics and their products directly or indirectly affect the global climate due to their inability to be decomposed naturally, easy to burn and produce toxic gases, and difficult to be recycled. Based on the UN Comtrade database, this paper obtains the global scrap plastics trade data from 2012 to 2021, including 233 countries around the world, constructs 20 overall trade networks of import and export of global scrap plastics trade, and synthesizes 10 years of data to explore the characteristics of the global plastics trade pattern as well as the evolution process, and conducts an analysis of China's plastics trade network in terms of the structure of the trade network and the roles and partners. Analyze the trade network from the perspective of trade network structure and roles and partners. The results show that: the participation of developing countries in import gradually increases, while developed countries take the primary position in export; China exits from the top in both import and export rankings in the evolution of the trade pattern of plastics scrap; the global greenhouse effect and the aggravation of environmental pollution make the participation in the import trade of every country in the world decline, but still dominated by developed countries. Keywords: Trade Patterns, Scrap Plastics, Carbon Neutrality, Carbon Peaking, Social Network Analysis. 1. Introduction and Literature Review Climate change is an important common issue, and in October 2022, the 26th United Nations Climate Change Conference emphasized the impacts of climate change on food security, refugees, and ecosystems, among other socio- economic issues.2023 In July 2023, the World Meteorological Organization (WMO) released its "State of the Climate in Asia 2022", which indicated that temperatures in Asia will continue to rise in 2022. The National Development and Reform Commission (NDRC) and the Ministry of Ecology and Environment (MOE) issued and implemented the Opinions on Further Strengthening the Treatment of Plastic Pollution in January 2020, and the NDRC responded to the "14th Five-Year Plan of Action for the Treatment of Plastic Pollution" in September 2021, and the Central Committee of the Communist Party of China (CPC) and the State Council issued the "Opinions on the Complete and Accurate Comprehensive In October 2021, the CPC Central Committee and the State Council "Opinions on Implementing the New Development Concept and Doing a Good Job in Carbon Peak and Carbon Neutrality" pointed out that realizing carbon peak and carbon neutrality is an inevitable choice to focus on solving the outstanding problems of resource and environmental constraints, and emphasized that it is important to incorporate carbon peak and carbon neutrality into the overall situation of economic and social development, to reduce the level of carbon dioxide emissions, and to enhance the ecosystem's ability to be a carbon sink. The State Council issued the notice of National Climate Change Adaptation Strategy 2035 in June 2022, emphasizing that all provinces and regions should effectively prevent the adverse impacts and risks brought by climate change. The current high temperatures and low rainfall in the middle and lower reaches of China's Yangtze River Basin have caused incalculable impacts on local shipping/crops and drinking water supply, as well as economic losses. global sea level is expected to rise by an average of 4.62 millimeters per year from 2013 to 2022. The twenty-sixth Conference of the Parties to the United Nations Framework Convention on Climate Change emphasized the need to act now in solidarity to protect the environment and save humanity. This paper is based on the development of social network analysis method. since 1973, when Granvit published his article about weak relationships, social networks began to appear frequently in the journals of Chinese and foreign scholars. in 1969, Milgram proposed small-world studies, and in 2020, Byron & Landis suggested that social network analysis might gain new development. At present, social network analysis has been developed and matured in the most basic network structure characteristics. Therefore, it is feasible and extremely necessary to make an in-depth analysis of the structure as well as the evolution characteristics of the global trade pattern of plastic scrap with the help of social network analysis. Theoretically, it is possible to visualize the degree of participation of each country and the dynamic evolution of the trade pattern through the analysis of the plastic scrap trade network. Empirically, there is a lot of literature on the use of social networks to study trade, but little literature on plastic trade. In terms of research objects, there are studies on the impact of product trade, the impact of industrial trade, and the change in the status of a certain country or region in the trade network and the relationship between countries. In terms of product trade, Zhan Miaohua (2018) analyzes and studies the agricultural export trade based on the agricultural trade data in the UN Comtrade database and argues that the complementarity of agricultural exports between countries is 224 greater than the competition[1]; Zhong Zuchang et al. (2022) find that there is an interactive effect between the import and export trade of high-tech products through the high-tech products' export trade network[2]; in terms of industrial trade, Xu Xin (2020) argues that there is interconnection of productive service trade between countries, and analyzes the influencing factors through the QAP way, and finds that geographic distance has a greater impact on productive service trade[3]. In terms of country status and inter-country relations, Dai Ling et al. (2022) focus on analyzing the relationship between China and Europe in terms of value- added trade, and find that the scale of value-added trade is growing, and that there is a closer connection between countries[4]; Ge Chunbao et al. (2022), based on UNCTAD- Eora value-added trade data combined with the spatial Durbin model, show that the direct facilitation effect of trade facilitation in countries with low network status is more obvious[5]. The study shows that the direct facilitation effect of trade facilitation is more obvious in countries with low network status. From the perspective of research, there are analyses of trade patterns and structural characteristics of trade networks. In terms of trade pattern analysis, Xu Bin (2015) used social network analysis to find that China did not have a significant impact on international trade[6]; Jiang Xuemei et al. (2021) used the OECD inter-regional input- output table to identify the key nodes of the trade network based on the PageRank algorithm to find that the status of developed economies declined, while the status of developing economies in global trade has increased[7]. In terms of the structural characteristics of the trade network, Li Guangqin et al. (2022) obtain ICT trade data, construct an ICT export trade network, and use QAP to explain the structure of the trade network, and find that China occupies the core nodes in the field of manufacturing equipment[8]. In view of this, this paper takes the global plastic scrap trade network as the research object, selects the data of UN Comtrade database from 2012 to 2021, applies the social network analysis method, explores the characteristics of the evolution of the global plastic scrap trade pattern as well as the trend, and selects China as the center of the self-network, and analyzes the value of the import and export trade as well as the volume of trade in China's plastics trade network. The main marginal contributions of this paper are: to study the trade of waste plastics that have an impact on the environment from the perspective of the dual-carbon goal; to explore the evolution of the trade pattern using the social network analysis method with the global trade network of waste plastics as the research object. 2. Research Design 2.1. Research methodology 2.1.1. Network Structure Measurement Metrics and Descriptions (1) Network node centrality Network node centrality is an indicator of network individual characteristics, which is a broad and wide concept. Specifically, it includes: in-degree centrality, out-degree centrality, proximity centrality, intermediate centrality, and eigenvector centrality. network node centrality in this paper refers to Average centrality (AC), which is manifested in each node. The average centrality of node i is the total number of direct connections between i and other n-1 nodes, which can be expressed as Eq: ๐ด๐ถ ๐‘ฅ ๐‘– ๐‘— where๐ด๐ถ denotes the average centrality of node i, and๐‘ฅ denotes the relationship between node i and node j. When node i is related to node j๐‘ฅ 1 , otherwise๐‘ฅ = 0. ๐‘– ๐‘— That is, excluding the connection between i and itself, in simple terms, the formula is to add up the cell values of node i in the corresponding row or column of the network matrix. (2) Strength of network node links Network node linkage strength is a network individual characteristic indicator, refers to the trade volume of all nodes directly connected to node i with the node, using network node linkage strength to portray the value of trade transactions occurring directly between a certain country and other countries, which in this paper refers to the value volume of direct plastics trade, which is manifested as the edges connecting each node. The network connection strength of node i is measured by the sum of plastic trade value (Trade Value, TV) between node i and other n-1 nodes, which can be expressed by the formula: ๐‘‡๐‘‰ ๐‘ก๐‘ฃ ๐‘ฅ ๐‘– ๐‘— where๐‘‡๐‘‰ denotes the total trade value between node i and each of the other nodes, and๐‘ก๐‘ฃ denotes the value of plastic trade that occurs between country i and country j both. The network node centrality as well as the network node linkage strength can be synthesized and represented by a matrix: ๐‘‹ ๐‘ฅ โ‹ฏ ๐‘ฅ โ‹ฎ โ‹ฑ โ‹ฎ ๐‘ฅ โ‹ฏ ๐‘ฅ ๐‘ฅ 1, ๐‘ฅ 0, There is plastic trade between node ij๐‘ฅ 1 and vice versa is 0. Eq.๐‘‹ denotes the plastic trade network with node j in year T with node i as the self-centering point,obviously there is a direction, thus๐‘‹ is a directed network, to indicate the country's direct trade value of the edge with the value of trade๐‘ก๐‘ฃ To reflect, we can construct the plastic trade network in year t with trade direction and trade value.๐‘‡๐‘‰ Its matrix form is as follows: ๐‘‡๐‘‰ ๐‘ก๐‘ฃ โ‹ฏ ๐‘ก๐‘ฃ โ‹ฎ โ‹ฑ โ‹ฎ ๐‘ก๐‘ฃ โ‹ฏ ๐‘ก๐‘ฃ (3) Network density Network density (ND) is a kind of network overall characteristic index, used to measure the close degree of connection of the nodes in the network, the value range is [0,1], the smaller the network density, that is, the smaller the degree of connection of the nodes in the network. In addition to this, the overall network characteristics indicators are network diameter, average path length and average clustering coefficient. Network density refers to the actual existence of plastic trade transactions accounted for (ideally) the proportion of the network assuming that the nodes have trade, can be expressed as: ๐‘๐ท ๐น ๐‘› ๐‘› 1 2 Eq:๐น refers to the total sum of the number of plastic trade transactions that actually exist, which can be expressed as: ๐น ๐‘ฅ ๐‘– ๐‘— 225 (4) Average clustering coefficient Clustering refers to the fact that countries with๐‘– There may also be links between other countries that are linked to form a cluster. Clustering coefficient refers to the closeness of the links between the countries within the cluster, and takes values in the range of [0,1]. Average clustering coefficient (ACC) is the average of the clustering coefficients of all nodes in the network and can be expressed as: ๐ด๐ถ๐ถ 1 ๐‘› ๐‘ƒ ๐ด๐ถ ๐ด๐ถ 1 Eq:๐ด๐ถ denotes the network node centrality, i.e., the number of nodes๐‘– the number of trades that exist with other nodes in the network.๐ด๐ถ ๐ด๐ถ 1 denotes the ideal case where countries that are๐‘– trade exists with all other countries linked to it (obviously, this assumption is directed)๐‘ƒ indicates that trade exists with the country๐‘– indicates the number of other countries linked to the country with which trade exists. (5) Degree Distribution and Cumulative Degree Distribution The nodal degree distribution mainly refers to the distribution pattern of plastic trade with other countries connected to a particular country, and the cumulative degree distribution refers to the percentage of countries connected to a certain overall network with the number of countries not less than x. The distribution function of nodal degree is expressed by the formula: ๐‘ ๐‘ฅ ๐‘› ๐‘› where: n is the number of nodes, i.e., the total number of countries in the plastics trade network, and๐‘› is the number of nodes whose node centrality is๐‘ฅ of the number of nodes. The cumulative degree distribution is expressed by Eq: ๐‘ ๐‘ฅ ๐‘ฅ ๐‘ ๐‘ฅ Eq:๐‘ฅ refers to the node with the greatest node centrality corresponding to the๐ด๐ถ that๐‘ ๐‘ฅ which is the degree distribution described above. 2.1.2. Block model analysis for network associations By profiling the structural characteristics of the network, countries with ๐‘– connected to other countries consisting of clusters with high clustering coefficients are considered as a block model, which is then analyzed as a model. This method of chunking structurally similar countries facilitates the analysis of the roles and partners of individual countries in the plastics trade network. If the number of countries included in a block model B is๐‘ , then the total number of trade links in that block of the model in the ideal state is๐‘ ๐‘ 1 , and at the same time, the number of countries included in that model B๐‘ countries have a total number of trade links with all the countries in that network in an ideal state is๐‘ ๐‘ 1 , then the proportion of model B in the whole is ๐‘ 1 ๐‘ 1โ„ Therefore, the global plastic scrap trade network can be categorized according to the range of ratios, as shown in the following table Table 1. Global Plastic Scrap Trade Network by Block tectonic plate Countries with high TV for import and export of waste plastics Eastern European Czech Republic (CZE), Poland (POL), Slovakia (SVK) Western European Austria (AUT), Belgium (BEL), France (FRA), Germany (DEU), Netherlands (NLD) southern Europe Italy (ITA), Spain (ESP) Scandinavia Denmark (DNK), Sweden (SWE), United Kingdom of Great Britain (GBR) any property China (CHN), Hong Kong, China (HKG) southern Asia India (IND) Southeast Asia Indonesia (IDN), Malaysia (MYS), Philippines (PHL), Thailand (THA), Viet Nam (VNM) North America United States (USA) 2.2. Data sources Data from the United Nations Conference on Trade and Development database UNCTAD stat involving Global plastics trade, ANNUAL 233 countries from 2012-2021 total plastics trade value as well as trade volume. In addition, using the United Nations Commodity Trade Statistics Database UN Comtrade, the value of export trade in plastics scrap (HS code 3915) and the value of import trade in plastics scrap in 233 countries from 2012-2021 and 2012-2021, we constructed 20 "whole nets" to analyze the trade pattern of plastics in a separate and comprehensive manner. In 2013, China implemented the "Green Fence Initiative", and in 2017, it enacted the "Upgraded Plastic Ban", and 2021 is the opening year of the 14th Five-Year Plan, as well as the first year of the implementation of the Carbon Peak and Carbon Neutral Strategies, which is the first year of the implementation of the Carbon Neutral Strategy, which is the first year of the implementation of the Carbon Peak Strategy. Based on the principle of equidistant sampling of time nodes, the four years of 2013, 2016, 2019 and 2021 are selected as special analysis samples for personalized analysis. 3. Evolution of the Global Trade Pattern of Waste Plastics 3.1. Centrality analysis of core nodes of the global plastics scrap trade network 3.1.1. Core import node centrality Tables 1 and 2 below show the top 15 countries after sorting the import TV in the global scrap plastics trade in accordance with the selected time points, and extracting the top ranked countries.Countries with more imported plastics trade TV are in a more advanced relative position, i.e., the higher the country's participation in the scrap plastics trade network.From 2012-2017, China, Hong Kong, China, and the U.S. steadily ranked in the top three of the import trade volume of scrap plastics, and the Netherlands , Germany, India, Belgium, Italy, Malaysia, Canada, Ireland, the United Kingdom, Austria, France, these countries also ranked in the top of the plastic import trade volume. 2018-2021, the trade pattern has changed a lot, China fell out of the top fifteen, China's scrap plastics import trade value in 2019 is only 226 0.0104 billion U.S. dollars, located in the global ranking of 91st. In 2018-2020, the United States replaces China at the top of the list.In 2021, the United States exits the rankings, the Netherlands tops the list in terms of the value of trade in scrap plastics imports, and developing countries gradually emerge, with top-ranked developing countries including Turkey, Poland, Mexico, India, and Pakistan. China's plastic restriction enacted in 2017 has greatly changed the global trade pattern of waste plastics and reshaped the global cross-border transfer of waste plastics. The developing countries of Hong Kong, China, the Netherlands, Germany, Belgium, Italy, and Canada are at the forefront of the trade value of scrap plastics imports from 2012-2021, indicating that the above countries continue to have a high degree of participation in the global plastics trade, and realize frequent trade transactions with other countries around the globe in the trade of scrap plastics with a large trading volume, and have a core node centrality. In the 21st century, when the level of climate pollution is getting more and more serious, these countries should be more responsible and should formulate relevant policies to control the import and use of waste plastics and plastic products. Table 2. Top 15 countries in terms of import TV for trade in plastics scrap, 2012-2017 (in billions of dollars) 2012 2013 2014 2015 2016 2017 nations TV nations TV nations TV nations TV nations TV nations TV CHN 128.084 CHN 120.979 CHN 120.693 CHN 83.677 CHN 73.894 CHN 65.267 HKG 25.701 HKG 21.153 HKG 25.431 HKG 20.932 HKG 18.374 HKG 13.248 USA 4.473 USA 5.245 USA 5.747 USA 4.695 USA 4.676 USA 4.885 NLD 4.160 NLD 4.976 NLD 5.402 NLD 4.350 NLD 3.895 NLD 4.178 DEU 4.053 DEU 3.837 DEU 4.699 DEU 3.914 DEU 3.751 DEU 3.382 BEL 2.457 IND 3.177 IND 3.255 BEL 2.198 ITA 2.078 MYS 2.286 IND 2.312 BEL 2.603 BEL 2.374 IND 1.885 BEL 1.953 ITA 2.276 ITA 2.092 MYS 1.997 ITA 2.267 ITA 1.857 IND 1.595 BEL 2.035 CAN 1.921 ITA 1.972 CAN 1.937 CAN 1.752 CAN 1.516 TUR 1.465 IRL 1.805 IRL 1.798 IRL 1.802 AUT 1.389 GBR 1.355 IND 1.438 AUT 1.429 IDN 1.630 AUT 1.793 IRL 1.312 MYS 1.322 VNM 1.416 IDN 1.334 CAN 1.537 GBR 1.713 MYS 1.242 IRL 1.197 CAN 1.401 MYS 1.310 GBR 1.461 FRA 1.280 GBR 1.083 AUT 1.113 IRL 1.343 FRA 1.236 AUT 1.375 IDN 1.050 VNM 1.030 POL 0.992 GBR 1.203 GBR 1.164 FRA 1.304 VNM 1.044 FRA 0.970 FRA 0.974 POL 1.194 Table 3. Top 15 countries in terms of import TV for trade in plastics scrap, 2018-2021 (in billions of dollars) 2018 2019 2020 2021 nations TV ($) nations TV ($) nations TV ($) nations TV ($) USA 5.379 USA 4.981 USA 4.660 NLD 6.083 HKG 4.873 HKG 3.982 NLD 3.502 TUR 3.902 NLD 3.883 NLD 3.775 MYS 3.355 DEU 3.852 DEU 3.131 DEU 3.355 DEU 2.852 ITA 2.199 ITA 2.189 VNM 3.003 VNM 2.831 CAN 2.140 VNM 2.162 TUR 2.262 TUR 2.796 BEL 2.026 BEL 2.149 MYS 2.199 HKG 1.936 ESP 1.807 IDN 2.047 ITA 1.741 BEL 1.537 POL 1.508 POL 1.579 BEL 1.704 CAN 1.396 MEX 1.047 IRL 1.501 IDN 1.664 ITA 1.396 HKG 0.684 CAN 1.471 FRA 1.543 FRA 1.349 IND 0.574 FRA 1.462 GBR 1.496 IDN 1.261 PAK 0.549 THA 1.458 CAN 1.451 POL 1.095 CZE 0.502 IND 1.378 ESP 1.415 AUT 1.094 SWE 0.470 GBR 1.368 POL 1.374 GBR 1.049 LTU 0.432 3.1.2. Core exit node centrality Similarly we take 2017 as the dividing line, the top ranked countries in 2012-2017 in terms of export TV of plastic scrap trade are the United States, Hong Kong, China, Japan, Germany, the United Kingdom, Mexico, France, the Netherlands, Thailand, Belgium, Spain, Vietnam, Canada, India and so on. Among them, Mexico, Thailand, Vietnam, and India belong to developing countries, and the rest are developed countries.The 2018-2021 Scrap Plastics trade pattern is very different from 2012-2017, and the top developing countries in 2018 are Mexico, Thailand, Vietnam, and Poland.The developing country Philippines' Scrap Plastics trade export volume is gradually rising in 2019, with a trade transaction value of 189.3 million USD and ranked 10th.China reappears in 2019-2020 at the top of the trade export list, and the Czech Republic, Sweden, Slovakia, and Denmark make their first appearance in 2021 in trade exports of plastics scrap. 227 Table 4. Top 15 countries in terms of TV export of plastics scrap trade, 2012-2017 (in billions of dollars) Table 5. Top 15 Countries in Plastic Scrap Trade Exports, 2018-2021 (in billions of dollars) 2018 2019 2020 2021 nations TV ($) nations TV ($) nations TV ($) nations TV ($) USA 8.929 DEU 7.645 DEU 5.972 DEU 6.399 DEU 8.294 JPN 7.057 JPN 5.763 JPN 5.818 JPN 7.872 USA 5.571 USA 4.505 NLD 5.148 FRA 3.444 FRA 3.162 NLD 3.002 MEX 3.017 NLD 3.244 NLD 3.148 CHN 2.703 BEL 2.603 GBR 3.060 GBR 2.670 GBR 2.412 ITA 1.839 MEX 2.991 MEX 2.412 FRA 2.216 CAN 1.836 BEL 2.806 BEL 2.351 BEL 2.075 PHL 1.691 THA 2.434 THA 2.146 MEX 1.993 POL 1.685 HKG 1.903 PHL 1.893 AUT 1.356 ESP 1.158 AUT 1.845 CHN 1.705 THA 1.199 AUS 1.003 VNM 1.564 AUT 1.644 POL 1.194 CZE 0.786 ITA 1.519 POL 1.441 ITA 1.121 SWE 0.696 CAN 1.432 ITA 1.370 CAN 1.116 SVK 0.462 POL 1.431 HKG 1.306 PHL 0.975 DNK 0.450 3.2. Characterization of global trade networks for plastics scrap With the help of Gephi data visualization tool, this paper constructs a total of 20 trade networks for the import and export of plastics scrap trade from 2012 to 2021, and takes 2017 as the demarcation point to analyze the evolution of the plastics scrap trade pattern before 2017 and after 2017. In view of the space limitation, only a total of 8 trade networks of scrap plastics trade import and export in 2013, 2016, 2019 and 2021 are shown and their network characteristics are analyzed. To ensure the clarity of the picture, the trade networks in each year are automatically filtered by K-core, and only the number of countries in the global scrap plastics trade network is kept to about 60. Since the network characteristic indicators are concentrated in the core part of the trade network rather than the sparse part of the edge, the reduction of the number of countries in the network will not affect the analysis results, so this operation is feasible. 3.2.1. Network Density of Global Plastic Scrap Export Trade Networks Figure 1,2. Plastic scrap export trade network, 2013, 2016 2012 2013 2014 2015 2016 2017 nations TV nations TV nations TV nations TV nations TV nations TV HKG 21.005 USA 17.388 USA 19.055 HKG 17.967 HKG 17.624 USA 12.737 USA 18.950 JPN 16.214 HKG 18.597 USA 16.328 USA 14.677 HKG 11.308 JPN 18.498 HKG 15.274 JPN 15.249 JPN 12.564 JPN 10.977 JPN 10.648 DEU 14.066 DEU 13.821 DEU 14.498 DEU 10.834 DEU 9.829 DEU 8.674 GBR 5.963 MEX 5.715 MEX 5.937 GBR 5.604 GBR 4.410 GBR 3.700 MEX 5.929 FRA 5.438 GBR 5.486 FRA 4.256 NLD 3.834 FRA 3.445 FRA 5.776 NLD 5.432 FRA 5.408 NLD 4.233 MEX 3.586 NLD 3.443 NLD 4.762 THA 5.216 NLD 4.944 MEX 4.185 FRA 3.556 THA 3.383 THA 4.254 GBR 4.470 THA 4.915 THA 3.208 THA 3.280 MEX 3.158 IDA 3.108 BEL 3.488 BEL 3.145 BEL 2.508 BEL 2.392 BEL 2.632 BEL 3.053 IDN 3.467 ESP 2.793 ESP 2.464 ESP 2.275 VNM 2.235 MYS 2.609 MYS 2.947 IDN 2.732 CAN 2.129 VNM 2.043 ESP 2.167 CAN 2.365 VNM 2.523 VNM 2.432 MYS 1.843 CAN 1.909 CAN 1.857 ESP 2.082 CAN 2.085 CAN 2.209 IDN 1.659 IDN 1.866 IDN 1.846 VNM 1.887 ESP 1.996 ITA 1.566 POL 1.599 MYS 1.615 MYS 1.712 228 Figure 3,4. Plastic scrap export trade network in 2019,2021 Prior to 2017, the network density of the global plastic scrap export trade network was clearly high. Through the scrap plastics export trade network in 2013 (Figure 1), it can be clearly seen that the lines between individual countries are intertwined and kneaded into one. That is, the trade and export links between countries are extremely close. Among them, China, the United States, Hong Kong, China, India, the United Kingdom, Germany, Italy, Belgium, Spain, the Netherlands, the participation in the trade network is relatively high, occupying a more important position. It is not difficult to find, in addition to China, India, other countries or regions (Hong Kong, China) are developed countries or developed economies (Hong Kong, China). In addition, Germany, the United Kingdom, Belgium, the Netherlands belongs to the Western European countries; Italy, Spain belongs to the Southern European countries; the United States belongs to the North American countries; China, Hong Kong, China belongs to the Asian countries and regions; India belongs to the South Asian countries. That is, these countries with high network density are centrally distributed in Europe, North America and Asia. 2016 scrap plastics export trade network is also the same, the trade links between countries are relatively close, the network density of countries with high network density did not change much compared with 2013, France in Western Europe, Canada in North America gradually emerged. After 2017, the network density of the global trade network for plastics scrap exports decreases, trade exports between countries decrease, and trade relations become sparse.The trade network for plastics scrap in 2019 becomes significantly sparse compared to the network in 2013 as well as in 2016, with a significant decrease in the number of edges.The trade network in 2021 becomes even more sparse, with a decrease in the export of plastics scrap between countries. Among these countries are Germany, Italy, Spain, the Netherlands, Belgium, Poland, Turkey, India, Canada, and Australia, which are at the core of the trade network, i.e., they are more involved in the export of plastics from scrap. Australia belongs to Oceania, Turkey belongs to Asia, these countries are concentrated in Europe, Asia, North America and Oceania. With the exception of Poland, India, and Turkey, the rest of the countries are developed countries. 3.2.2. Network Density of Global Scrap Plastics Import Trade Networks Figure 5,6. Plastic scrap import trade network in 2013,2016 Figure 7,8. Plastic scrap import trade network in 2019,2021 229 By observing the degree of intertwining of lines in the network in 2013 and 2016, it can be known that the network density of the global import trade network of plastics scrap is high, and the import of plastics scrap trade between countries is extremely close, and China is at the core of the network until 2017, and China has the highest participation in the network, i.e., China imports plastics scrap from many countries or China is the primary export of plastics scrap from many countries object of choice. In the network, China mainly imports waste plastics from developed countries such as the United States, France, Japan and Germany. In 2013, in addition to China, there are the United States, Germany, Hong Kong, China, Italy, the United Kingdom, Belgium, the Netherlands, Malaysia, India, France, Spain, Turkey, Austria in the import of waste plastics in the higher participation. Among them, except for Malaysia, India and Turkey, the rest of the countries are developed countries. In 2016, China, the United States, Hong Kong, China, Germany, Italy, Turkey, the Netherlands, Belgium, the United Kingdom, and Spain occupy important positions in the trade network. Compared to 2013, the relative positions have not changed much. After 2017, the global trade pattern of waste plastics was clearly affected by China's enactment of the plastic ban, with the United States replacing China at the center of the network. Combined with the comparison in Figure 3, the United States occupies an important position in both import and export trade of waste plastics, with the highest degree of participation.In the trade network in 2019 (Figure 7), the United States, Germany, Spain, Italy, the Netherlands, Hong Kong, China, Turkey, Belgium, the United Kingdom, China, France, Poland, and Malaysia, which are all developing countries, have a high degree of participation. Among them, Poland, Malaysia, Turkey and China are all developing countries. In addition to this, it can also be seen that China has been the primary choice of the United States and other developed countries to export waste plastics until 2017, while in 2019, the United States and other developed countries mainly exported waste plastics to Malaysia, India, Vietnam, Thailand, Indonesia and these developing countries. Among them, except for India, all other countries are Southeast Asian countries.2021 The trade network (Figure 8), which is more sparse than that of 2019, has a significantly lower network density. Unlike in the past the participation of the United States in the scrap plastics import network has significantly decreased, probably due to the growing epidemic of New Crown Pneumonia in the U.S. Many developing countries have abandoned the U.S. in favor of importing scrap plastics from other developed countries or even from developing countries. Developing country Turkey is at the core of the network, besides Germany, Netherlands, Spain, Italy, Belgium, Canada, Hong Kong (China) and Poland have a high participation in the network of plastic scrap trade. It is also clear that China's ban on plastics is not a "total" ban, and the presence of China in the import trade network in 2019 and 2021 may be related to the global C.N.C.P. epidemic, where on the one hand people tend to choose disposable products in order to minimize the risk of infection, and on the other hand the C.N.C.P. epidemic is related to medical devices, nucleic acid tests, and other products that have been used for the past few years. On the one hand, people tend to choose disposable products in order to minimize infections; on the other hand, medical devices related to the CIP epidemic, such as nucleic acid testing "swabs" and syringes, are all related to plastics, and in this context, China's demand for plastics and their products has risen sharply, which has led to imports of some waste plastics. Overall, affected by China's plastic ban in 2017, the export object of the United States and other developed countries has been expanded from the original East Asian country China to a number of developing countries in Southeast Asia, and China's initiative has had a profound impact on the global trade pattern of waste plastics, which has led to the evolution of the global trade pattern of waste plastics. 3.2.3. Clustering coefficients and community discovery The clustering coefficient is the degree to which a country๐‘– The clustering coefficient is the degree to which there is some connection between other countries linked to a certain country. Given that the import and export trade of waste plastics is concentrated in Europe, Asia, and North America, this paper selects each state import and export๐‘‡๐‘‰ countries and use them as the core countries in the calculation of the clustering coefficient ๐‘– . Again, 2017 is used as the dividing line to observe the evolution of the global import and export trade pattern of scrap plastics. Core countries of scrap plastics trade in each segment ๐‘– Based on the import and export ๐‘‡๐‘‰ principle, specifically: Poland for Eastern Europe, Germany for Western Europe, Italy for Southern Europe, the UK for Northern Europe, China for East Asia, India for South Asia, Indonesia for Southeast Asia, and the United States for North America. After considering the latitude and longitude, the network diagram of global import and export of plastic scrap trade in 2013 and 2021 is as follows: Figure 9. Export network for trade in plastics scrap in 2013 (latitude and longitude) 230 Figure 10. Export network for trade in plastics scrap in 2021 (latitude and longitude) Figure 11. Import network for trade in plastics scrap in 2013 (latitude and longitude) Figure 12. Import network for trade in plastics scrap in 2021 (latitude and longitude) From the network diagram of global scrap plastics trade import and export in 2013 and 2021, it can be seen that the pattern of import and export trade has changed drastically.In 2013, the clustering coefficient is higher in Eastern Europe, Southeast Asia, North America and other major segments. In 2021, the clustering coefficient is higher in Western Europe, North America, Eastern Europe, Southern Europe, South Asia and other major segments. 4. Analysis of China's Plastics Trade Network 4.1. Analysis of the structure of China's plastics trade network (1) Through the import centrality statistics of the global scrap plastics trade network, it is found that China's scrap plastics import trade volume steadily ranked first among 233 countries in the world from 2012 to 2017. Due to the enactment of China's plastic restriction in 2017 greatly changed the global waste plastic trade pattern. 2018-2020 the United States of America's waste plastic trade imports jumped to the top, while the Netherlands replaced the United Kingdom in 2021, and China's waste plastic trade imports dropped sharply since 2018. (2) On the contrary, through the collation of global statistics, it was found that China's excessive demand for plastic products due to its large population base from 2012-2017 has kept China in a passive import of waste plastics trade with little or no export behavior of waste plastics trade.The enactment of the plastic restriction order in 2017 has resulted 231 in China being in an active exporter of waste plastic trade in the period of 2018-2021.In Carbon Neutral, Carbon Peak and fulfill its commitments. 4.2. China's role and partners in the global plastics trade network Due to space constraints, this paper selects the special years of 2013, 2016, 2019, and 2021 as personalized analysis samples to analyze China's role and partnership in the global plastics trade network. In 2013, China's participation in the global scrap plastics trade and export network is high in the core node position, as a major scrap plastics trade exporter main trading partners are the United States, Hong Kong, China, the United Kingdom, Germany, etc. In 2016, China and the United States as the two major scrap plastics trade exporters, China's main trading partners compared with 2013 increased Belgium, Italy, Turkey, Japan and so on. several countries, and the export trade gradually expanded. However, from 2019, China's participation in the export trade of plastics scrap declined, and the main trading partners gradually changed from developed countries to developing countries, and showed a decreasing trend.In 2021, China gradually faded out of the export trade network of plastics scrap, and its trading partners are mainly Poland. From the global import network of scrap plastics trade, it can be seen that in 2013 China, as a major importing trading country, was disconnected from other trading countries, mainly importing scrap plastics from the United States, Hong Kong, China, Germany, Italy, Belgium, the United Kingdom, and other countries.The situation eased in 2016, the participation of the United States, Germany, and Italy gradually increased, and although China, as a major exporter of scrap plastics trade, the degree of involvement has decreased, and the main trading partners have not changed much compared to 2013.In 2019, China's participation has decreased sharply, and the main trading partners have changed from developed countries to some developing countries, such as Pakistan and Ukraine.In 2021, China has almost no more import activities in the scrap plastics trade network, and not only China, but also the global greenhouse effect and the increase of environmental pollution, which makes the The global greenhouse effect and increasing environmental pollution have led to a decline in import trade participation in every country in the world. Among them, China has only a very small amount of plastic scrap imports with a very small number of developing countries. 5. Conclusions and Revelations 5.1. Conclusion (1) Through the global 233 countries or regions scrap plastics import and export trade volume statistics found that in 2012 the scrap plastics imports more countries (or regions) are China, Hong Kong, China, the United States, the Netherlands, Germany, Belgium, imports ranked in the top fifteen countries or regions only four developing countries, developed countries or regions accounted for about 73%; the largest exports of countries (or regions) for the Hong Kong, China, the United States, Japan, Germany, the United Kingdom, Mexico, exports ranked in the top fifteen countries or regions only five belonging to developing countries, developed countries or regions accounted for 2/3. 2021 the largest volume of imports of waste plastics is the Netherlands, imports ranked in the top fifteen of Turkey, Poland, Mexico, India, Pakistan, these developing countries participation is gradually revealed, China's imports Sharp decline, there is no longer China in the top fifteen. The largest export volume of countries for Germany, the Czech Republic, Sweden, Slovakia, Denmark in the waste plastic trade exports for the first time, only Mexico, the Philippines for developing countries, developed countries accounted for about 87%. From 2012-2021, it is clearly visualized that the participation of developing countries in exports is gradually increasing, while developed countries occupy the primary position in exports. (2) In 2013, when China implemented "Operation Green Fence", China temporarily ranked first in the global trade pattern of waste plastics in terms of imports, and after China enacted the "upgraded version of the ban on plastics" in 2017, and as the opening year of the 14th Five-Year Plan in 2021, both import and export rankings of trade in waste plastics have dropped out of the top rankings. In 2017, after China enacted the "upgraded plastic ban", in 2021, the opening year of the 14th Five-Year Plan, the ranking of import and export of waste plastics will be withdrawn from the top. (3) In 2013, China's plastic scrap export trade partners are mainly the United States, Hong Kong, China, the United Kingdom, Germany, etc.; import trade partners are the United States, Hong Kong, China, Germany, Italy, Belgium, the United Kingdom, etc. In 2021, China is gradually fading out of the plastic scrap export trade network, and the trade partners are mainly Poland; China is almost no longer imported in the plastic scrap trade network, and it's not only China, but also the whole world. Greenhouse effect as well as the intensification of environmental pollution, so that all countries around the world import trade participation has declined. 5.2. Revelations (1) The countries or regions with the highest trade volume of plastic scrap imports in 2021 are the Netherlands, Turkey, Germany, Italy, Canada, Belgium, Spain, Poland, Mexico, Hong Kong (China), India, Pakistan, the Czech Republic, Switzerland and Lithuania. The import of waste plastics can lead to higher management costs for developing countries, while at the same time causing incalculable environmental impacts due to the difficulty of degradation. In this regard, developing countries need to raise awareness of the potential environmental risks associated with the disposal of foreign waste plastics and develop timely and restrictive policies to improve global environmental sustainability. (2) The countries or regions with the largest export trade volume of waste plastics in 2021 include Germany, Japan, the Netherlands, Mexico, Belgium, Italy, Canada, the Philippines, Poland, Spain, Austria, the Czech Republic, Switzerland, Slovakia, Denmark and so on. The countries with higher export volume are still mainly developed countries, which can strengthen the territorialized management of waste plastics and enhance the recycling rate through policy incentives and financial support. (3) China has developed many policies in favor of environmental protection in the import and export trade of waste plastics. In order to further reach the goal of carbon neutrality and carbon peaking, China should further reduce greenhouse gas emissions by lowering the threshold as well as the cost of sustainable consumption, quantifying the carbon reduction contribution of consumers, and then increasing 232 public participation and enforcement. It should also improve the whole chain management system of plastic pollution, further refine the reduction of plastic use at the source, and reduce the amount of plastic waste going to landfills and environmental leakage. References [1] Zhan Miaohua. 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