Environmental Science and Ecotechnology 30 (2026) 100682
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Environmental Science and Ecotechnology
journal homepage: www.journals.elsevier.com/environmental-science-and- ecotechnology/
Original Research Plant-level carbon accounting of China's pulp and paper industry via multimodal fusion Song Hu a , Huaqing Qi a , Zifei Wang a , Xiaoyu Wu b , Yulin Han a , , Yi Man a , a State Key Laboratory of Advanced Papermaking and Paper-Based Materials, South China University of Technology, Guangzhou, 510640, China b School of Chemistry and Chemical Engineering, South China University of Technology, Guangzhou, 510640, China
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Article history: Received 8 August 2025 Received in revised form 2 March 2026 Accepted 3 March 2026 Keywords: Multimodal Pulp and paper industry Plant-scale Carbon accounting Carbon reduction potential
Plant-scale industrial carbon accounting is critical for developing targeted emission-reduction policies. However, most assessments of carbon-intensive sectors rely on aggregate statistics, which obscure significant heterogeneity among individual plants. China's pulp and paper industry (PPI), the largest globally, encompasses diverse production processes, raw material inputs, and emission sources. Existing accounting frameworks rely on statistical data and average emission factors within poorly defined system boundaries, which prevents differentiation at the individual plant level. Here, we propose a multimodal data fusion framework that integrates high-resolution remote-sensing imagery with plant textual data to capture structural and operational characteristics undetectable by any single data mo- dality. Applied to 720 pulping and papermaking plants across China, the framework achieves R 2 values of up to 0.96 across five plant types and estimates total sectoral carbon emissions at 163.6 million tonnes of CO 2 in 2022, with pronounced regional disparities concentrated in eastern coastal provinces. Analysis of functional-zone contributions further reveals that wastewater treatment areas are a consistent cross-category emission driver, and that just 5% of high-emission plants account for approximately 43% of sectoral emissions — a skewed structure that demands differentiated regulatory intervention. Incorporating regional solar radiation data, rooftop photovoltaic deployment is projected to reduce annual PPI emissions by up to 10.3%, with primary-fiber pulp plants offering the greatest mitigation leverage. Beyond China's PPI, this scalable, data-driven approach provides a transferable blueprint for granular, plant-level carbon accounting in other heterogeneous heavy industries. © 2026 The Authors. Published by Elsevier B.V. on behalf of Chinese Society for Environmental Sciences, Harbin Institute of Technology, Chinese Research Academy of Environmental Sciences. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
Previous researchers have assessed PPI carbon emissions at global [3], national [4], and regional [5] scales, thereby informing the development of macro-level policies to mitigate emissions. As fundamental units within the PPI that generate carbon emissions, pulping and papermaking plants (PPPs) represent the most gran- ular scale at which CER policies can be effectively implemented [6]. Achieving sector-wide carbon neutrality in the PPI depends on the decarbonization performance of individual plants [7]. There- fore, there is a need to establish a high-resolution, operationally feasible carbon accounting framework at the plant scale. Such a framework would facilitate the precise identification of emission source distributions and provide a robust scientific basis for the design of differentiated and targeted mitigation strategies. Carbon emissions from PPPs are commonly estimated by combining energy consumption data with corresponding emission factors. Existing emissions inventories span scales ranging from individual plants [8] to industrial clusters of up to 23 plants [9].
1. Introduction
As the world’s largest producer of paper products, China has included the pulp and paper industry (PPI) among the eight key emission-intensive sectors of the national carbon market. The PPI's energy conservation and emissions-reduction process is vital to supporting China’s transition toward sustainable development [1], and carbon accounting for the PPI is the foundation for achieving carbon emissions reduction (CER) [2]. Accurate quantification of carbon emissions and source contributions is thus fundamental for formulating mitigation strategies and policy frameworks.
This article is part of a special issue entitled: Green AI and Sustainable Computing published in Environmental Science and Ecotechnology. Corresponding author. Corresponding author. E-mail addresses: linyv@scut.edu.cn (Y. Han), manyi@scut.edu.cn (Y. Man).
https://doi.org/10.1016/j.ese.2026.100682 2666-4984/ © 2026 The Authors. Published by Elsevier B.V. on behalf of Chinese Society for Environmental Sciences, Harbin Institute of Technology, Chinese Research Academy of Environmental Sciences. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
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