In a groundbreaking development poised to reshape the future of the coal industry, researchers have constructed a comprehensive knowledge map of carbon emission governance technologies for coal mining and utilization. This innovative work, led by Ying Wang from the School of Management at China University of Mining and Technology-Beijing, promises to support mining enterprises in their quest to reduce carbon emissions and transition towards greener, more sustainable practices.
The study, published in *Meitan kexue jishu* (translated to *Coal Science and Technology*), focuses on the critical role of coal in China’s energy consumption and the significant carbon emissions generated during its exploitation and utilization. “Coal accounts for about 60%−70% of the total national carbon emissions,” explains Wang. “This makes it the key to accomplishing China’s carbon reduction tasks.”
The research team embarked on an ambitious project to systematically organize and analyze the knowledge related to carbon emission management technologies in coal mining and utilization. They employed a hybrid construction method, combining bottom-up and top-down approaches, to build a conceptual knowledge model. This model was further refined using advanced techniques such as the BERT+CRF (Bidirectional Encoder Representations from Transformer Representations & Conditional Random Fields) method for entity recognition and the BiLSTM–Attention model for relationship extraction.
The resulting knowledge map is a comprehensive framework that covers four major categories: emission characteristics, mining methods, utilization methods, and carbon reduction technologies. These categories are further subdivided into 12 subclasses and 30 subclasses, forming a complete conceptual classification system. The map defines ten types of named entities and six kinds of relationships, providing a detailed and nuanced understanding of the complex associations between different technologies and their emission characteristics.
One of the most significant aspects of this research is its practical application. The knowledge map can support mining enterprises in selecting the most appropriate carbon reduction technology paths, thereby optimizing their operations and reducing their environmental impact. “With the expansion of low-carbon development scenarios in the coal industry, the accumulation of data, and the development of artificial intelligence and big models, this study will optimize the construction method of the atlas on the basis of multimodal data fusion,” Wang notes. “This will expand the application scope of the atlas and improve the accuracy of the recommendation of technology paths.”
The implications of this research are far-reaching. As the energy sector grapples with the challenges of reducing carbon emissions and transitioning to more sustainable practices, tools like the knowledge map developed by Wang and her team can provide invaluable support. By offering a clear and structured understanding of the available technologies and their relationships, the map can help enterprises make informed decisions, ultimately contributing to a greener and more sustainable future.
In the rapidly evolving landscape of the energy sector, this research represents a significant step forward. It highlights the potential of advanced technologies and data-driven approaches to address some of the most pressing challenges facing the industry. As the coal industry continues to evolve, the insights and tools provided by this research will be crucial in shaping its future trajectory.
With the publication of this study in *Meitan kexue jishu*, the stage is set for a new era of innovation and sustainability in the coal industry. The knowledge map developed by Ying Wang and her team is not just a tool; it is a beacon of hope for a greener, more sustainable future.