A novel fractional-order grey prediction model: a case study of Chinese carbon emissions

Environmental Science and Pollution Research, Journal Year: 2023, Volume and Issue: 30(51), P. 110377 - 110394

Published: Oct. 3, 2023

Language: Английский

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Network Effects in Global Carbon Transfer: New Evidence from a Carbon-Connectedness Network Centered on China

Sustainability, Journal Year: 2024, Volume and Issue: 16(10), P. 4116 - 4116

Published: May 14, 2024

There is plenty of evidence to suggest that global carbon emission transfer has evolved into a mutually related system, where realistic and complex network formed. To profile the structures features in network, carbon-connectedness model adapted combined with multiregional input–output analysis framework, on basis massive multi-layer flow data. This study formulates topological features, spatio-temporal dynamic core–periphery from brand-new perspective China. Meanwhile, this identifies effects including spillover, spillin spillback effects. In general, an increase China’s would lead significant spillover most economies worldwide, especially developing those weaker tertiary industry or situated at upstream value chain. Simultaneously, China itself also face substantial Spillovers spillbacks underscore broader negative impact exceeds its initial magnitude. Focused connectedness centered China, complementary traditional insights, helping comprehend connections relationships emissions among economies. understanding substantive significance for formulation multi-national mitigation strategies fostering climate governance cooperation.

Language: Английский

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The Impact of ESG Responsibility Fulfillment on Enterprise Value in China: A Regulated Intermediary Model Approach

Published: March 14, 2024

ESG (Environmental, Social, and Governance) responsibility fulfillment increasingly affects enterprise valuation. Although researchers debate about the precise effects, prevailing view suggests a linear relationship between performance value. This study introduces novel metric through Regulated Intermediary Model to delve into this within Chinese context. Our findings reveal an inverted U-shaped value, with financing constraints having significant moderating effect. These remain robust after employing instrumental variables mitigate potential endogeneity. Heterogeneity analysis demonstrates that is particularly pronounced in non-polluting non-state-owned enterprises. Moreover, comparison equity debt mechanisms underscores improved associated lower cost of financing, thereby enhancing Financial institutions are encouraged leverage innovative financial instruments diversify channels alleviate enterprises fulfill their responsibilities.

Language: Английский

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Can Resource Dependency and Corporate Social Responsibility Drive Green Innovation Performance?

Sustainability, Journal Year: 2024, Volume and Issue: 16(11), P. 4848 - 4848

Published: June 6, 2024

As the producers of environmental pollution, it is urgent for enterprises to make up their lack responsibility and realize green transformation development. At same time, resource dependence promoted from single level economic growth field development, which a research development on broadens perspective related in academic world. In this paper, we select panel data 30 regions China 2009 2022 validate impact corporate social innovation performance. The conclusions are as follows: (1) From 2022, average industrial performance provinces was 0.553, with efficiency values eastern, central, western showing gradual decreasing trend. (2) We found consistently negative correlation between dependency performance, confirming existence “resource curse” linking two. Meanwhile, regression coefficient CSR positive, driving effect former latter. (3) does not manifest conditionally or have threshold effect. Instead, that has long-term persistent characteristics. shows “reverse N-shaped” double-threshold effect, where can improve only when reaches certain value. This paper provides insights support Chinese enhancing lays theoretical foundation fulfill responsibility.

Language: Английский

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Study on carbon emission driving factors and carbon peak forecasting in power sector of Shanxi province

PLoS ONE, Journal Year: 2024, Volume and Issue: 19(7), P. e0305665 - e0305665

Published: July 12, 2024

The realisation of the low-carbon transition energy system in resource-intensive regions, as embodied by Shanxi Province, depends on a thorough understanding factors impacting power sector’s carbon emissions and an accurate prediction peak trend. Because this, industry’s province are measured this article from 1995 to 2020 using data Intergovernmental Panel Climate Change (IPCC). To obtain deeper sector, factor decomposition is performed Logarithmic Mean Divisia Index (LMDI). Second, order precisely mine relationship between variables emissions, Sparrow Search Algorithm (SSA) aids optimisation Long Short-Term Memory (LSTM). In implement SSA-LSTM-based industry, four development scenarios finally built up. findings indicate that: (1) There has been fluctuating upward trend Province’s total industry 2020, with cumulative growth 372.10 percent. (2) intensity consumption main restricting rise contributing -65.19%, while per capita secondary contribution factor, 158.79%, driver emissions. (3) While baseline scenario rapid fail 2030, low green at 243,991,100 tonnes 258,828,800 tonnes, respectively, 2025 2028. (4) Based performance results, cities like Shanxi’s should concentrate upgrading strengthening industrial structure, getting rid obsolete production capacity, encouraging faster each help sector reach performance.

Language: Английский

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