{
  "abstract": "Accurate prediction of NOx emissions is critical for optimizing selective non-catalytic reduction systems in circulating fluidized bed boilers co-firing sewage sludge and coal. This study develops a data-driven framework by using operational records. A multidimensional feature engineering scheme incorporating auto-regressive, combustion-related, denitration-related features is constructed. Six models-linear regression, random forest, XGBoost, backpropagation neural network, tuned XGBoost, and a stacking ensemble-are systematically compared. SHAP analysis reveals that the model correctly learns the key physicochemical mechanisms, including the temperature window effect and the reducing role of ammonia. The results provide a reliable predictive basis for precise ammonia injection control under fluctuating sludge incineration conditions.",
  "abstract_shown": true,
  "affiliations": [
    "College of Materials Science and Engineering, Zhejiang University of Technology, Hangzhou 310014, China.",
    "Shaoxing Research Institute, Zhejiang University of Technology, Shaoxing 312000, China.",
    "Zhejiang Zheneng Binhai Environmental Protection Energy Co., Ltd., Shaoxing 312000, China.",
    "Zhejiang Carbon Neutral Innovation Institute, Zhejiang University of Technology, Hangzhou 310014, China.",
    "International Science and Technology Cooperation Base in Carbon Emission Reduction and Monitoring Authorized by Zhejiang Provincial Department of Science and Technology, Hangzhou 310014, China."
  ],
  "article_type": "research article",
  "arxiv": null,
  "author_total": 13,
  "authors": [
    {
      "affs": [
        0,
        1
      ],
      "name": "Suwan Wei"
    },
    {
      "affs": [
        2
      ],
      "name": "Guanghua Wu"
    },
    {
      "affs": [
        2
      ],
      "name": "Jinli Zhou"
    },
    {
      "affs": [
        2
      ],
      "name": "Zhigang Jiang"
    },
    {
      "affs": [
        2
      ],
      "name": "Hong Li"
    },
    {
      "affs": [
        2
      ],
      "name": "Zhenyi Qian"
    },
    {
      "affs": [
        2
      ],
      "name": "Ping Lv"
    },
    {
      "affs": [
        2
      ],
      "name": "Xiaoqian Wang"
    },
    {
      "affs": [
        2
      ],
      "name": "Efeng Ma"
    },
    {
      "affs": [
        0,
        1
      ],
      "name": "Jun Chu"
    },
    {
      "affs": [
        1
      ],
      "name": "Junliang Wang",
      "orcid": "0000-0002-7222-9061"
    },
    {
      "affs": [
        2
      ],
      "name": "Lian Fan"
    },
    {
      "affs": [
        0,
        1,
        3,
        4
      ],
      "name": "Min Wu"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/1jg5tc87y0s44.bib",
  "cited_by": 0,
  "doi": "10.3390/toxics14100877",
  "fulltext_url": "https://europepmc.org/articles/PMC13709758",
  "id": "1jg5tc87y0s44",
  "issns": [
    "2305-6304"
  ],
  "landing_url": "https://europepmc.org/article/MED/42931664",
  "language": "eng",
  "licence": "CC-BY",
  "licence_label": "CC BY",
  "licence_source": "article",
  "licence_url": "https://creativecommons.org/licenses/by/4.0/",
  "metadata_licence": null,
  "native_subjects": [
    [
      "openalex",
      "2210|Industrial Gas Emission Control"
    ]
  ],
  "openalex": "W7214944051",
  "pdf_url": "https://europepmc.org/articles/PMC13709758?pdf=render",
  "pmcid": "PMC13709758",
  "pmid": "42931664",
  "published": "2026-09-30",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/1jg5tc87y0s44.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:22:01Z",
      "native_id": "MED:42931664",
      "source": "europepmc",
      "url": "https://europepmc.org/article/MED/42931664"
    }
  ],
  "subjects": [
    {
      "field": "medicine",
      "origin": "journal-openalex:2307|Environmental Toxicology and Ecotoxicology",
      "subfield": "pharmacology-toxicology"
    }
  ],
  "title": "Machine Learning Prediction of NOx Emissions from Sewage Sludge Incineration.",
  "title_text": "Machine Learning Prediction of NOx Emissions from Sewage Sludge Incineration.",
  "type": "peer-reviewed",
  "updated_at": "2026-10-30T12:22:01Z",
  "url": "https://research.draconitic.com/paper/1jg5tc87y0s44",
  "venue": "Toxics",
  "versions": []
}