ArticleScientific data2025
An inventory of industrial solid waste in 337 cities of China: Applying machine learning for data completion.
Article in Scientific data, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
2 citing papers in PubMed.
- Comparative Strength Development and Microstructural Characteristics of Individual Industrial Solid Waste Systems Treated with Sodium Silicate.Materials (Basel, Switzerland) · 2026Article
- An inventory of industrial solid waste in 337 cities of China: Applying machine learning for data completion.Scientific data · 2025Article
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Authors and funding
8 authors.
Funding
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Abstract
Rapid industrialization of China generated a massive quantity of waste, among them industrial solid waste contributed the biggest flow to some 60 gigatonnes (Gt) in the past two decades. A complete tempo-spatial dataset of industrial waste, however, is absent in many areas in China, due to numerous waste producers and insufficient statistical coverage. To fill up the gap, we collected current available data from thousands of sources. We further developed six machine learning models to complete the dataset across all the 337 cities in China for the period 1990-2022. Bayesian optimization was employed to obtain the best estimation model for each city and to enhance its performance and resilience. In addition to the aggregate waste amount, generation of six major subcategories of industrial waste, i.e., metallurgical slags, fly ash, furnace slags, coal gangue, tailings, and desulfurization gypsum, are presented for more than half of the cities in 2022. This dataset can help researchers and policymakers recognize and address challenges brought by industrial waste.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.