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Evolution and Driving Mechanisms of Industrial Solid Waste in China: A Data-Driven Analysis

Received Date:2026-01-23 Revised Date:2026-02-05 Accepted Date:2026-02-07

DOI:10.20078/j.eep.20260301

Abstract:Against the backdrop of continued industrialization and China′s "dual-carbon" targets, industrial solid waste (ISW) gene... Open+
Abstract:Against the backdrop of continued industrialization and China′s "dual-carbon" targets, industrial solid waste (ISW) generation has exhibited persistent growth amidst structural adjustments and governance transitions. Understanding whether this growth follows a stable trajectory or undergoes stage-specific shifts is essential for interpreting governance outcomes and designing differentiated waste management strategies. This study applies a data-driven analytical framework to a city-level panel dataset to identify the long-term stage structure of urban ISW generation in China from 2003 to 2019 and to examine how its driving mechanisms evolve across different stages and spatial scales. First, unsupervised time-series structural learning is employed to detect endogenous stage boundaries in national ISW generation without predefined breakpoints. Second, inter-stage changes are decomposed using the Logarithmic Mean Divisia Index (LMDI) method into population scale, economic affluence, industrial structure, and composite intensity effects. Third, city-level dynamics are analyzed using two-way fixed effects models and a random forest-based feature selection procedure to identify governance-relevant signals that remain stable at the annual municipal scale. We identify three stable stages, namely, 2003–2007, 2008–2012, and 2013–2019. Total ISW continued to increase in all stages; however, the growth rate declined over time. Scale effects remained persistently positive, strengthened across stages, and explained 33.4% of cumulative growth. The post-2013 slowdown primarily reflects structural transition. The industrial structure effect shifted from a positive contribution (+113 Mt) to a substantial negative contribution (−290 Mt). In contrast, the intensity effect was negative across all stages, with minimal variation in magnitude, indicating a stable offset rather than a trigger of stage change. Regionally, all major regions share a common temporal stage structure but rely on different pathways to mitigate scale-driven growth. In the later stage (2013–2019), Eastern and Central regions primarily depended on intensity-related mitigation, whereas Western regions exhibited stronger structural offsets. Northeast China, however, demonstrated a notable deviation in driving mechanisms in the later stage, in which the intensity effect turned positive and became the dominant contributor to regional ISW changes. City-level evidence suggests this pattern is consistent in direction across cities but highly concentrated in magnitude, with a small number of cities accounting for most of the positive intensity contribution. At the city scale, ISW generation is more responsive to short-term interannual changes in industrial activity intensity than to variations in economic scale or industrial structure, once time-invariant city characteristics and common shocks are controlled for (coefficient = 0.078 7, p = 0.032). Under multi-indicator competition, performance- and process-oriented indicators, such as comprehensive ISW utilization, demonstrate greater stability and explanatory power in annual variations, standing out as especially informative for municipal operations. Overall, the findings suggest that the recent slowdown in China′s ISW growth primarily reflects a structural transition rather than a weakening of scale pressures. Effective governance, therefore, requires aligning policy instruments with stage-specific driving mechanisms, emphasizing structural adjustment at the macro level while strengthening process-oriented management at the urban scale. Close-

Authors:

  • YUAN Jiayi1
  • CHEN Chuke1,*
  • WU Yuehan1
  • CHEN Sichen1
  • CHANG Huimin2
  • YANG Hang1
  • XU Ming3

Units

  • 1.  School of Environment, Tsinghua University
  • 2.  TianGong Think Tank, Research Institute for Environmental Innovation Suzhou
  • 3.  State Key Laboratory of Iron and Steel Industry Environmental Protection, School of Environment, Tsinghua University

Keywords

  • Industrial  solid  waste  ISW
  • Stage  Identification
  • Structural  transition
  • Urban heterogeneity
  • Random Forest

Citation

YUAN Jiayi, CHEN Chuke, WU Yuehan, CHEN Sichen, CHANG Huimin, YANG Hang, XU Ming. Evolution and Driving Mechanisms of Industrial Solid Waste in China: A Data-Driven Analysis[J/OL]. Energy Environmental Protection: 1-12[2026-03-04]. https://doi.org/10.20078/j.eep.20260301.

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