Jianxu Xing, F. Lu, Liang Cen, Xiaoming Yin, Kang Pan, Hai-Fen Liu, Xiaofei Chen, Chao Li
{"title":"一种新的基于能源碳排放码的企业碳效率评价方法","authors":"Jianxu Xing, F. Lu, Liang Cen, Xiaoming Yin, Kang Pan, Hai-Fen Liu, Xiaofei Chen, Chao Li","doi":"10.1109/ICIST55546.2022.9926851","DOIUrl":null,"url":null,"abstract":"This article studies the energy carbon emission (ECE) evaluation problem for enterprises, and designs ECE-codes to conduct multi-factor grading evaluation of the ECE. The ECE evaluation results of enterprises need to be displayed to non-professionals such as consumers. Therefore, in addition to being able to characterize the ECE level, the ECE evaluation results of enterprise should be intuitive and easy to understand. For this purpose, the ECE-codes are designed, including the horizontal identification code (HIC), the efficiency identification code (EIC), and the neutralization identification code (NIC). Define carbon emission intensity (CEI) as the ECEs required to produce an unit of profit. The HIC is formed by dividing the CEI of enterprises into three levels, and is used to grade an enterprise's carbon emission level in the entire industrial sector. The EIC is formed through five-level evaluation of CEI in sector (CEIS), which is used to measure the CEI level of an enterprise in its sector. The CEIS is the ratio of CEI to the average value of the sector CEI. NIC is used to display an enterprise's carbon neutrality process, which is the ratio of carbon neutrality to total carbon emissions. To achieve effective grading of CEI and CEIS, a Gaussian mixture model (GMM) is established to describe the distribution of the CEI and CEIS, and the model parameters are identified by the expectation maximization (EM) algorithm. Then, the grading thresholds can be obtained according to the GMM probability density function with given percentage parameters. The effectiveness of the ECE-codes based grading evaluation method is verified by applying this method to the carbon emission evaluation of the registered enterprises in Huzhou, china.","PeriodicalId":211213,"journal":{"name":"2022 12th International Conference on Information Science and Technology (ICIST)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2022-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A novel energy carbon emission codes based carbon efficiency evaluation method for enterprises\",\"authors\":\"Jianxu Xing, F. Lu, Liang Cen, Xiaoming Yin, Kang Pan, Hai-Fen Liu, Xiaofei Chen, Chao Li\",\"doi\":\"10.1109/ICIST55546.2022.9926851\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This article studies the energy carbon emission (ECE) evaluation problem for enterprises, and designs ECE-codes to conduct multi-factor grading evaluation of the ECE. The ECE evaluation results of enterprises need to be displayed to non-professionals such as consumers. Therefore, in addition to being able to characterize the ECE level, the ECE evaluation results of enterprise should be intuitive and easy to understand. For this purpose, the ECE-codes are designed, including the horizontal identification code (HIC), the efficiency identification code (EIC), and the neutralization identification code (NIC). Define carbon emission intensity (CEI) as the ECEs required to produce an unit of profit. The HIC is formed by dividing the CEI of enterprises into three levels, and is used to grade an enterprise's carbon emission level in the entire industrial sector. The EIC is formed through five-level evaluation of CEI in sector (CEIS), which is used to measure the CEI level of an enterprise in its sector. The CEIS is the ratio of CEI to the average value of the sector CEI. NIC is used to display an enterprise's carbon neutrality process, which is the ratio of carbon neutrality to total carbon emissions. To achieve effective grading of CEI and CEIS, a Gaussian mixture model (GMM) is established to describe the distribution of the CEI and CEIS, and the model parameters are identified by the expectation maximization (EM) algorithm. Then, the grading thresholds can be obtained according to the GMM probability density function with given percentage parameters. The effectiveness of the ECE-codes based grading evaluation method is verified by applying this method to the carbon emission evaluation of the registered enterprises in Huzhou, china.\",\"PeriodicalId\":211213,\"journal\":{\"name\":\"2022 12th International Conference on Information Science and Technology (ICIST)\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-10-14\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 12th International Conference on Information Science and Technology (ICIST)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICIST55546.2022.9926851\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 12th International Conference on Information Science and Technology (ICIST)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICIST55546.2022.9926851","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A novel energy carbon emission codes based carbon efficiency evaluation method for enterprises
This article studies the energy carbon emission (ECE) evaluation problem for enterprises, and designs ECE-codes to conduct multi-factor grading evaluation of the ECE. The ECE evaluation results of enterprises need to be displayed to non-professionals such as consumers. Therefore, in addition to being able to characterize the ECE level, the ECE evaluation results of enterprise should be intuitive and easy to understand. For this purpose, the ECE-codes are designed, including the horizontal identification code (HIC), the efficiency identification code (EIC), and the neutralization identification code (NIC). Define carbon emission intensity (CEI) as the ECEs required to produce an unit of profit. The HIC is formed by dividing the CEI of enterprises into three levels, and is used to grade an enterprise's carbon emission level in the entire industrial sector. The EIC is formed through five-level evaluation of CEI in sector (CEIS), which is used to measure the CEI level of an enterprise in its sector. The CEIS is the ratio of CEI to the average value of the sector CEI. NIC is used to display an enterprise's carbon neutrality process, which is the ratio of carbon neutrality to total carbon emissions. To achieve effective grading of CEI and CEIS, a Gaussian mixture model (GMM) is established to describe the distribution of the CEI and CEIS, and the model parameters are identified by the expectation maximization (EM) algorithm. Then, the grading thresholds can be obtained according to the GMM probability density function with given percentage parameters. The effectiveness of the ECE-codes based grading evaluation method is verified by applying this method to the carbon emission evaluation of the registered enterprises in Huzhou, china.