Resources Conservation and Recycling, Journal Year: 2025, Volume and Issue: 215, P. 108118 - 108118
Published: Jan. 5, 2025
Language: Английский
Resources Conservation and Recycling, Journal Year: 2025, Volume and Issue: 215, P. 108118 - 108118
Published: Jan. 5, 2025
Language: Английский
Buildings, Journal Year: 2023, Volume and Issue: 13(7), P. 1617 - 1617
Published: June 26, 2023
As an industry that consumes a quarter of social energy and emits third greenhouse gases, the construction has important responsibility to achieve carbon peaking neutrality. Based on Web Science, Science-Direct, CNKI, accounting prediction models emissions from buildings are reviewed. The emission factor method, mass balance actual measurement method analyzed. top-down bottom-up their subdivision introduced Individual building assessments generally adopt physical model, while urban economic input-output model. Most current studies follow path “exploring influencing factors then putting forward based factors”. driving mainly use Stochastic Impacts by Regression Population, Affluence, Technology (STIRPAT) Logarithmic Mean Divisia Index (LMDI) grey correlation degree other models. model is realized regression system dynamics mathematical models, as well Artificial Neural Network (ANN) Support Vector Machine (SVM) machine learning At present, research individual focuses operational consumption, for stages should become focus in future research.
Language: Английский
Citations
53Applied Energy, Journal Year: 2025, Volume and Issue: 384, P. 125450 - 125450
Published: Feb. 6, 2025
Language: Английский
Citations
3Energy, Journal Year: 2025, Volume and Issue: unknown, P. 135091 - 135091
Published: Feb. 1, 2025
Language: Английский
Citations
2Journal of Cleaner Production, Journal Year: 2023, Volume and Issue: 428, P. 139347 - 139347
Published: Oct. 21, 2023
Language: Английский
Citations
35Sustainability, Journal Year: 2023, Volume and Issue: 15(10), P. 8279 - 8279
Published: May 19, 2023
The carbon emission trading system profoundly impacts enterprises’ sustainable development as an important market incentive environmental regulation tool. Through data collected from Chinese A-share listed enterprises in Shanghai and Shenzhen 2011 to 2019 Bloomberg ESG score data, this paper empirically analyses the impact of policy on enterprise performance its channel mechanism using difference-in-difference (DID) method. Results study indicate that improves significantly, robustness tests confirm these findings. Carbon can encourage enhance their R&D investments promote internal controls, ultimately enhancing performance. Additionally, positively low-carbon enterprises, where CEO is separated company, with a high degree digital transformation, receiving government subsidies. This extends our research into economic implications policy, enriching literature market-based policies’ With respect governments’ use regulate environmentally, provides theoretical guidance. It has significant practical for improving sustainability.
Language: Английский
Citations
26Construction and Building Materials, Journal Year: 2024, Volume and Issue: 421, P. 135759 - 135759
Published: March 1, 2024
Language: Английский
Citations
12Sustainable Futures, Journal Year: 2025, Volume and Issue: unknown, P. 100535 - 100535
Published: March 1, 2025
Language: Английский
Citations
1Journal of Environmental Management, Journal Year: 2022, Volume and Issue: 330, P. 117139 - 117139
Published: Dec. 28, 2022
Language: Английский
Citations
37Journal of Environmental Management, Journal Year: 2023, Volume and Issue: 351, P. 119720 - 119720
Published: Dec. 14, 2023
Language: Английский
Citations
22Journal of Environmental Management, Journal Year: 2023, Volume and Issue: 348, P. 119206 - 119206
Published: Oct. 26, 2023
Language: Английский
Citations
20