QIAO Lan, DENG Naifu, MA Shiji, LI Qingwen, SONG Linbo, ZHANG Qinglong. Intelligent carbon emission assessment method for metal mine shaft construction projects[J]. Chinese Journal of Engineering, 2024, 46(6): 1024-1040. DOI: 10.13374/j.issn2095-9389.2023.09.11.002
Citation: QIAO Lan, DENG Naifu, MA Shiji, LI Qingwen, SONG Linbo, ZHANG Qinglong. Intelligent carbon emission assessment method for metal mine shaft construction projects[J]. Chinese Journal of Engineering, 2024, 46(6): 1024-1040. DOI: 10.13374/j.issn2095-9389.2023.09.11.002

Intelligent carbon emission assessment method for metal mine shaft construction projects

  • The metal mining industry is the second-largest carbon emitter in China, followed by the power industry. The metal mining industry is closely intertwined with six major industries that prioritize emission reduction, including steel, nonferrous metals, and building materials. The construction of mine shafts and drifts plays a pivotal role in the initial development and construction of the metallurgical mining industry, and its carbon emissions are integral to the advancement of the industry under the “dual carbon” strategy. This study delves into the distinctive characteristics of budget quota preparation for metal mine shaft and drift construction projects during the construction period. This study proposes a carbon emission assessment framework and model based on the dual assessment path of direct and auxiliary systems. Carbon emissions from ten key projects and seven auxiliary projects are calculated at each level within each carbon assessment path. Furthermore, a comprehensive analysis of the list of substances in the smallest unit processes at various levels is conducted through multilevel dissection. This analysis culminates in the development of a carbon emission factor database specific to the mine shaft and drift construction projects, which is achieved by searching and analyzing global lists of carbon emission substances across different industries. Based on the carbon emission assessment framework presented in this study, the fundamental data for the top ten carbon emissions in metal mine shaft and drift construction projects are established using the MySQL database, with each database labeled by a unique identifier. Subsequently, an efficient indexing and scheduling mechanism is implemented for the top ten basic data tables using the MATLAB App Designer. This mechanism facilitates the application of a comprehensive dual-path carbon emission measurement model for detailed carbon emission calculation and analysis of metal mine shaft and drift construction projects. Case analysis reveals that, in main shaft construction, the primary carbon emitters are associated with the use of cement, macadam, and electrically driven equipment, accounting for approximately 70%–80% of carbon emissions. From an emission source perspective, major carbon emitters result from material usage, generating approximately two to three times the carbon emissions of machinery energy consumption. From an emission pathway perspective, major carbon emitters are predominantly concentrated in the shaft body construction phase, constituting approximately 92% of carbon emissions within this segment of the main shaft project. Further analysis indicates that electricity consumption is the primary source of carbon emissions from machinery and equipment, representing approximately one-fourth to one-third of the total carbon emissions. By contrast, cement consumption serves as the principal source of carbon emissions from material use, accounting for approximately one-fifth to one-fourth of the total carbon emissions. Accordingly, energy-saving and emission-reduction techniques should prioritize the optimization of the material preparation process, such as cement, and the utilization of electrically driven equipment. The outcomes of this study can provide methodological foundation and data support for detailed carbon assessment and concrete implementation of low carbon emission-reduction policies for mine shaft and drift construction projects in China.
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