Search

Since China's reform and opening up, the social economy has achieved rapid development, followed by a sharp increase in carbon dioxide (CO2) emissions. Therefore, at the 75th United Nations General Assembly, China proposed to achieve carbon peaking by 2030 and carbon neutrality by 2060. The research work on advance forecasting of CO2 emissions is essential to achieve the above-mentioned carbon peaking and carbon neutrality goals in China. In order to achieve accurate prediction of CO2 emissions, this study establishes a hybrid intelligent algorithm model suitable for CO2 emissions prediction based on China's CO2 emissions and related socioeconomic indicator data from 1971 to 2017. The hyperparameters of Least Squares Support Vector Regression (LSSVR) are optimized by the Adaptive Artificial Bee Colony (AABC) algorithm to build a high-performance hybrid intelligence model. The research results show that the hybrid intelligent algorithm model designed in this paper has stronger robustness and accuracy with relative error almost within ±5% in the advance prediction of CO2 emissions. The modeling scheme proposed in this study can not only provide strong support for the Chinese government and industry departments to formulate policies related to the carbon peaking and carbon neutrality goals, but also can be extended to the research of other socioeconomic-related issues. [ABSTRACT FROM AUTHOR]

Based on data from the China Industry Business Performance Database from 1998 to 2007 and the time of establishment of the administrative examination and approval center in each administrative division in China, this study attempts to empirically determine the effects of the reform of the administrative examination and approval system on the efficiency of resource allocation from the perspectives of the degree of enterprise-level productivity dispersion. The empirical results showed that the reform of the administrative examination and approval system significantly reduced the degree of productivity dispersion among enterprises in an industry, in addition to enhancing the efficiency of resource allocation in the industry. A further analysis of heterogeneity revealed that the reform of the administrative examination and approval system yielded greater enhancements of the efficiency of resource allocation in industries with lower entry and exit rates. [ABSTRACT FROM AUTHOR]

Establishing a high-precision numerical geological time scale for the Paleozoic Era remains a considerable challenge. In this study, we conducted detailed cyclostratigraphic analysis on the Middle Ordovician of the Huangnitang section and the core Changjin 3 (CJ-3), Zhejiang Province, South China. Magnetic susceptibility (MS) series were obtained from a total of 3909 discrete samples and are used as a paleoclimate proxy indicative of variations in detrital input of magnetic minerals. Power spectral analyses show that both the section and core have recorded an excellent hierarchy of Milankovitch cycles of 405 kyr, 101–135 kyr, 31–34 kyr, and 15.8–21.3 kyr. An integrated floating astronomical time scale (ATS) for the section and core was established according to the extracted stable 405-kyr eccentricity cycles. This new floating ATS suggests that the durations of the Darriwilian and Dapingian stages were 8.38 ± 0.4 Myr and 1.97 ± 0.7 Myr, and the durations of complete graptolite zones of the Middle Ordovician were precisely estimated. The ratios of band (obliquity or short eccentricity) power to total power reveal periodicities of ~1.2 Myr for the s 4 – s 3 term and ~1.9 Myr for the g 4 – g 3 term, and ~1.2-Myr obliquity cycles may have controlled global third-order eustatic sequences during the late Darriwilian. [ABSTRACT FROM AUTHOR]

A high-precision time framework is critical for improving our understanding of three major events: the Late Ordovician mass extinction, the Hirnantian glaciation, and the Hirnantian isotopic carbon excursion (HICE). In the present study, we conducted detailed cyclostratigraphic analysis of a high-resolution (1–2-cm intervals) anhysteretic remanent magnetization series obtained from the Wanhe section in South China, covering the lower Katian through Hirnantian. Power spectra and derived average spectral misfit results show that the section records the ensemble of Milankovitch cycles with 405-kyr (long-eccentricity), 93–125-kyr (short-eccentricity), 33.8-kyr (main obliquity), and 17–22-kyr (precession) periods. The obliquity period of 33.8 ± 0.46 kyr indicates a precession constant k of 57.19 ± 0.53 arcsec/yr, a length of day of 22.37 ± 0.12 h, and an Earth–Moon distance of 375,330 ± 722 km (vs. 384,000 km today) during the Late Ordovician (445 Ma). The ratios of obliquity band power to total power reveal periodicities of 1.32 Myr for the s 4 – s 3 term and 173.4 kyr for the s 3 – s 6 term. Aided by the highly fluctuating magnetic susceptibility (MS), we recognized a series of 1.32-Myr obliquity-forced glacio-eustatic cycles with three intervals of sea-level rise and climate warming trend characterized by high MS values and two episodes of sea-level fall and climate cooling trend before the Hirnantian. The 405-kyr and subsequent 33.8-kyr calibrations produce an ~7.36-Myr floating astronomical time scale (FATS) for the studied succession, indicating that the estimated durations for the Hirnantian Stage, the worldwide Hirnantian glaciation, and the first and second phases of the Late Ordovician mass extinction were ~1225 kyr, ~830 kyr, ~440 kyr, and ~540 kyr, respectively. This work provides a reliable high-resolution time framework for further investigation of the major geological events occurred in the Late Ordovician, and improves our knowledge of Solar System behaviour and Earth–Moon history during that period. • An ~7.36 Myr ATS was constructed for the early Katian through Hirnantian. • The durations of Hirnantian Stage, glaciation and mass extinction were estimated. • Earth–Moon evolution was constrained for the Late Ordovician. • Obliquity forcing controlled the Late Ordovician glacio-eustasy. [ABSTRACT FROM AUTHOR]

Since China's reform and opening up, the social economy has achieved rapid development, followed by a sharp increase in carbon dioxide (CO 2 ) emissions. Therefore, at the 75th United Nations General Assembly, China proposed to achieve carbon peaking by 2030 and carbon neutrality by 2060. The research work on advance forecasting of CO 2 emissions is essential to achieve the above-mentioned carbon peaking and carbon neutrality goals in China. In order to achieve accurate prediction of CO 2 emissions, this study establishes a hybrid intelligent algorithm model suitable for CO 2 emissions prediction based on China's CO 2 emissions and related socioeconomic indicator data from 1971 to 2017. The hyperparameters of Least Squares Support Vector Regression (LSSVR) are optimized by the Adaptive Artificial Bee Colony (AABC) algorithm to build a high-performance hybrid intelligence model. The research results show that the hybrid intelligent algorithm model designed in this paper has stronger robustness and accuracy with relative error almost within ±5% in the advance prediction of CO 2 emissions. The modeling scheme proposed in this study can not only provide strong support for the Chinese government and industry departments to formulate policies related to the carbon peaking and carbon neutrality goals, but also can be extended to the research of other socioeconomic-related issues., Competing Interests: The authors declare that there are no conflicts of interest regarding the publication of this paper., (Copyright © 2022 Pan Wang et al.)