Affiliation:
1. School of Electric Power, South China University of Technology, Guangzhou 510640, China
2. Guangdong Institute of Special Equipment Inspection and Research Shunde Branch, Foshan 528300, China
Abstract
During the process of determining carbon emissions from coal using the emission factor method, third-party organizations in China are responsible for verifying the accuracy of the carbon emission data. However, these verifiers face challenges in efficiently handling large quantities of data. Therefore, this study proposed a fast screening method that utilizes multiple linear regression (MLR), in combination with the stepwise backward regression method, to identify problematic carbon emission data for the lower calorific value (LCV) and carbon content (C) of coal. The results demonstrated the effectiveness of the proposed method. The regression models for LCV and C exhibited high R-squared (R2) values of 0.9784 and 0.9762, respectively, and the root mean square error (RMSE) values of the validation set were 0.32 MJ/kg and 0.80% for LCV and C, respectively, indicating strong predictive capabilities. By analyzing the obtained results, the study established the optional error threshold interval for the LCV and C of coal as 2RMSE–3RMSE. This interval can be utilized as a reliable criterion for judging the quality and reliability of carbon emission data during the verification process. Overall, the proposed screening method can serve as a valuable tool for verifiers in assessing the quality and reliability of carbon emission data in various regions.
Funder
the National Key R&D Program of the Intergovernmental International Science and Technology Innovation Cooperation Project
the Natural Science Foundation of Guangdong Province‘s Outstanding Youth Project
the National Natural Science Foundation of China
Subject
Energy (miscellaneous),Energy Engineering and Power Technology,Renewable Energy, Sustainability and the Environment,Electrical and Electronic Engineering,Control and Optimization,Engineering (miscellaneous),Building and Construction
Reference37 articles.
1. Coal measure energy production and the reservoir space utilization in China under carbon neutral target;Chen;Front. Earth Sci.,2023
2. Trend model and key technologies of coal mine methane emission reduction reduction arming for the carbon neutrality;Liu;J. China Coal Soc.,2022
3. Study on the Decomposition of Factors Affecting Energy-Related Carbon Emissions in Guangdong Province, China;Wang;Energies,2011
4. Analysis and suggestion on carbon accounting of thermal power enterprises under the background of carbon peak and carbon neutrality;Lu;Clean Coal Technol.,2023
5. Liu, Y., Wang, D., and Ren, X. (2022). Rapid Quantitation of Coal Proximate Analysis by Using Laser-Induced Breakdown Spectroscopy. Energies, 15.
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