Population growth, economic development, and industrialization have resulted in a notable surge in the hazardous waste (HW) generation, consequently leading to adverse effects on human health and environmental safety. In this work, a Waste Extended Input-Output-based Transformer-Long Short-Term Memory (WEIO-TL) method was developed to simulate the HW generation patterns of various economic industries in the supply chain and generate the desired strategies for reducing HW generation. The WEIO-TL method was applied to Shanghai to identify its HW reduction path and potential by 2035. Multiple scenarios were designed to investigate the impacts of different degrees of economic and technological development on HW generation. The primary results indicated that the economic proportion of each key industry and the technological innovation capability were the main factors influencing the HW generation in Shanghai. The six key industries identified by the WEIO were the chemical industry (CI), other services (OS), transportation equipment (MTE), computers, communication, and other electronic equipment (MCCOEE), wholesale and retail trades (WRT), and construction (C). HW generation would peak at 1570.9 kt in 2025 and subsequently decrease to 949.0 kt by 2035 under the optimal scenario based on the optimal TL model (R and RMSE values of 0.976 and 5.968), associated with industry structure optimization (i.e., part of high-polluting industries would be shifted to service) and technological innovation capability improvement. The results of the study will serve as a theoretical foundation to guide other cities toward achieving "zero waste."

中文翻译：

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基于废物扩展输入输出的 Transformer-LSTM 方法分析危险废物减量模式：以上海为例

人口增长、经济发展和工业化导致危险废物（HW）产生量显着增加，对人类健康和环境安全造成不利影响。在这项工作中，开发了一种基于废物扩展输入输出的变压器-长短期记忆（WEIO-TL）方法来模拟供应链中各个经济行业的硬件生成模式，并生成减少硬件生成的所需策略。将WEIO-TL方法应用于上海，以确定其到2035年的硬件发电减少路径和潜力。设计了多个情景来研究不同程度的经济和技术发展对硬件发电的影响。初步结果表明，各重点产业经济比重和技术创新能力是影响上海家电发电的主要因素。 WEIO确定的六大重点行业是化学工业（CI）、其他服务（OS）、运输设备（MTE）、计算机、通信和其他电子设备（MCCOEE）、批发和零售贸易（WRT）以及建筑业（C）。在基于最佳 TL 模型（R 和 RMSE 值分别为 0.976 和 5.968）的最佳情景下，与产业结构优化（即高容量发电的一部分）相关的最佳情景下，HW 发电量将在 2025 年达到峰值 1570.9 kt，随后到 2035 年下降至 949.0 kt。污染产业向服务业转移）和技术创新能力提升。研究结果将为指导其他城市实现“零废弃”提供理论基础。