Study on carbon emission driving factors and carbon peak forecasting in power sector of Shanxi province DOI Creative Commons
Wei Hu, Tingting Zheng, Yi Zhang

et al.

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

Towards Carbon Neutrality & Baku/Azerbaijan - Belem/Brazil: Exploring the Impacts of Economic, Environmental, Social, and Governance (ECON-ESG) Factors on Climate Policy Uncertainty (CPU) for Sustainable Development DOI Creative Commons
Cem Işık, Serdar Ongan, Jiale Yan

et al.

Heliyon, Journal Year: 2025, Volume and Issue: unknown, P. e41944 - e41944

Published: Jan. 1, 2025

Climate policy is crucial in shaping global responses to environmental challenges and steering societies towards sustainable resilient futures. Thus, research study, we examine the impacts of Economic (ECONF), Environmental (ENVF), Social (SOCF), Governance (GOVNF) factors, as well combined (ECON-ESG) on Policy Uncertainty (CPU) at level. The new ECON-ESG form sustainability, defined this refers holistic approach sustainability by including economic factors (ECON) traditional ESG factors. Empirical findings reveal that while (E) social (S) worsen CPU, improve it long run. (G) have no impact CPU. While a 1 % increase E S increases CPU 22 27 %, same percentage ECON decreases 40 %. These results clearly show analyses conducted only through conventional may be insufficient inaccurate analyzing effects Our study's result should not considered limited only, will helpful use proposed form, ECON-ESG, more comprehensive concept studies since also incorporates This enable policymakers look climate policies lens with ECON-ESG. adopt includes when policies.

Language: Английский

Citations

4
Green credit policy’s influence on construction firm ESG performance: a difference in differences estimation DOI Creative Commons
Yongjie Wu, Lei Hou, Yuan Yue

et al.

Journal of Asian Architecture and Building Engineering, Journal Year: 2025, Volume and Issue: unknown, P. 1 - 13

Published: March 19, 2025

Language: Английский

Citations

2
Low carbon finance drives corporate carbon emissions reduction: A perspective from issuing carbon neutral bonds DOI
Juan Lu, He Li, Ran Yang

et al.

Technological Forecasting and Social Change, Journal Year: 2024, Volume and Issue: 203, P. 123404 - 123404

Published: April 17, 2024

Language: Английский

Citations

11
Examining the relationship between technological innovation, environmental social governance and corporate sustainability: the moderating role of green operational innovation DOI Creative Commons
Oluwole Nurudeen Omonijo, Yunsheng Zhang

Humanities and Social Sciences Communications, Journal Year: 2025, Volume and Issue: 12(1)

Published: Jan. 30, 2025

Language: Английский

Citations

1
Unleashing green technology innovation in agribusiness: traditional environmental regulations, carbon trading, or synergies? DOI Creative Commons
Wei Wang,

Yanan She,

Yue Peng

et al.

Humanities and Social Sciences Communications, Journal Year: 2025, Volume and Issue: 12(1)

Published: Jan. 31, 2025

Stimulating green technology innovation in agricultural enterprises through appropriate environmental policies is of great significance for achieving development. Based on the data listed agribusinesses from 2007 to 2020, this paper analyzes incentive effects traditional regulatory tools, carbon trading, and policy synergies using SDM-SDID model. It was found that: (1) Although both tools trading provide effects, former tends exhibit more pronounced direct making it suitable adoption by local governments, while latter demonstrates stronger spatial spillover application a national market context. (2) Command-and-control instruments are complementary mixes, other mixes be used as context actual situation. (3) The significant eastern regions, non-heavily polluting, state-owned agribusinesses, but not basic sector. above research, reveals differentiated different types combinations agribusinesses. This contributes deepening research selection provides theoretical support practical references precise implementation collaborative governance.

Language: Английский

Citations

1
ESG introduction mechanism of construction firms based on Bayesian network coupled with machine learning: Evidence from Zhengzhou DOI Creative Commons

Jinzhao Tian,

Yi‐Sheng Liu, Lincoln C. Wood

et al.

Journal of Environmental Management, Journal Year: 2025, Volume and Issue: 375, P. 124185 - 124185

Published: Jan. 25, 2025

Chinese construction enterprises are at a pivotal point in their transition to sustainable development, with Environmental, Social, and Governance (ESG) emerging as key driver. However, limited understanding of ESG mechanisms hampers effective management strategies. To address this challenge, study constructs an introduction mechanism framework based on Bayesian networks machine learning algorithms. Using Zhengzhou, major city China, case study, the research employs quantitative methods identify factors influencing introduction. The findings reveal that attitudes towards ESG-related products, establishment corporate brand image, readiness three primary driving among enterprises. Further scenario simulation analyses indicate positive attitude significantly enhances likelihood successful Additionally, fostering expanding local consulting service agencies strengthening regulatory measures markedly improve success rate This provides enterprise managers practical tool analyze offers critical decision-making support for policymakers designing policies promote

Language: Английский

Citations

0
Study on the key factors of public participation in low carbon city construction and willingness to pay DOI Creative Commons
Yang Tan, Xiaoyu Ying, Jian Ge

et al.

Scientific Reports, Journal Year: 2025, Volume and Issue: 15(1)

Published: Feb. 25, 2025

The popularity of urban distributed photovoltaics is crucial for building low-carbon cities. Retrofitting roofs with photovoltaic tiles a new option. However, whether the public supports this initiative needs to be understood. Assessing willingness pay critical way measure acceptance. Therefore, paper assesses Chinese households' support retrofit promote construction To obtain factors that better explain pay, variables such as personal interest perception, moral perception and policy are added initial theory planned behavior psychological interpretation framework extended explanatory constructed. It encouraging note expanded has increased power where dominant variable in explaining pay. We believe we should attention impact on increase publicity importance retrofitting city through Internet means individual which may help participation

Language: Английский

Citations

0
Digital platforms enabling carbon neutral technology innovation: based on market incentives and government constraints DOI Creative Commons

Dongri Han,

Miaomiao Li, Ke Lu

et al.

Humanities and Social Sciences Communications, Journal Year: 2025, Volume and Issue: 12(1)

Published: March 10, 2025

Language: Английский

Citations

0
Mechanism conflicts: carbon reduction pathways and optimization in China’s Big Data Policy DOI Creative Commons

Bihua Zhou,

Yun Huang, Hang Su

et al.

Humanities and Social Sciences Communications, Journal Year: 2025, Volume and Issue: 12(1)

Published: April 21, 2025

Language: Английский

Citations

0
Exploring Emerging NLP and Machine Learning Methods in Climate Change Discourse Analysis on Social Media: A Systematic Literature Review DOI Creative Commons

Hana Ghiloufi,

Nicolás Merveille, Sehl Mellouli

et al.

Published: Jan. 1, 2025

Abstract This study systematically examines emerging methods, particularly NLP and ML, for analyzing climate change discourse on social media platforms. Within this framework, sub-objectives encompass presenting methodological approaches identifying prevalent themes, data sources. As communication has evolved rapidly in the digital age, with becoming a pivotal arena public discourse, opinion dissemination, information exchange. The intersection of ML techniques offers unprecedented opportunities to transform vast amounts unstructured into valuable information, ready be consumed by policymakers different stakeholders. Drawing upon comprehensive review 56 articles, identifies synthesizes six methods that are further divided sub-approaches techniques, addressing themes platforms used. research contributes literature most used effective potential areas needing more investigation future. It also provides insight trending overlooked ones, offering best practices future directions.

Language: Английский

Citations

0