A graph-factor-based random forest model for assessing and predicting carbon emission patterns - Pearl River Delta urban agglomeration

Journal of Cleaner Production, Год журнала: 2024, Номер 469, С. 143220 - 143220

Опубликована: Июль 20, 2024

Язык: Английский

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Elucidating Kinetic Mechanisms of Lignin and Biomass Pyrolysis by Distributed Activation Energy Model with Genetic Algorithm

Energy, Год журнала: 2024, Номер 312, С. 133548 - 133548

Опубликована: Окт. 20, 2024

Язык: Английский

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Exploration of Dual-Carbon Target Pathways Based on Machine Learning Stacking Model and Policy Simulation—A Case Study in Northeast China

Land, Год журнала: 2025, Номер 14(4), С. 844 - 844

Опубликована: Апрель 12, 2025

Northeast China, a traditional heavy industrial base, faces significant carbon emissions challenges. This study analyzes the drivers of in 35 cities from 2000–2022, utilizing machine-learning approach based on stacking model. A model, integrating random forest and eXtreme Gradient Boosting (XGBoost) as base learners support vector machine (SVM) meta-model, outperformed individual algorithms, achieving coefficient determination (R2) 0.82. Compared to methods, model significantly improves prediction accuracy stability by combining strengths multiple algorithms. The Shapley additive explanations (SHAP) analysis identified key drivers: total energy consumption, urbanization rate, electricity population positively influenced emissions, while sulfur dioxide (SO2) smoke dust average temperature, humidity showed negative correlations. Notably, green coverage exhibited complex, slightly positive relationship with emissions. Monte Carlo simulations three scenarios (Baseline Scenario (BS), Aggressive De-coal (ADS), Climate Resilience (CRS)) projected peak 2030 under ADS, lowest fluctuation (standard deviation 5) largest reduction (17.5–24.6%). Baseline indicated around 2039–2040. These findings suggest important role de-coalization. Targeted policy recommendations emphasize accelerating transition, promoting low-carbon transformation, fostering urbanization, enhancing sequestration China’s sustainable development achievement dual-carbon goals.

Язык: Английский

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Displacement Effect of CO₂/N₂-ECBM Process with Different Water Saturations Based on THMC Coupling

Energy & Fuels, Год журнала: 2025, Номер unknown

Опубликована: Апрель 16, 2025

Язык: Английский

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Gas displacement characteristics during the water wetting process of gas-bearing coal and microscopic influence mechanism

The Science of The Total Environment, Год журнала: 2024, Номер 949, С. 175034 - 175034

Опубликована: Июль 25, 2024

Язык: Английский

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Dynamic Multi-Factor Correlation Analysis for Prediction of Provincial Carbon Emissions in China’s Bohai Rim Region

Processes, Год журнала: 2024, Номер 12(10), С. 2207 - 2207

Опубликована: Окт. 10, 2024

This study presents a dynamic multi-factor correlation analysis method designed to predict provincial carbon dioxide emissions (CDE) within China’s Bohai Rim region, including Tianjin, Hebei, Shandong, and Liaoning. By employing the sliding window technique, curves are computed between various influencing factors CDE at different time intervals, thereby facilitating identification of key feature attributes. A novel metric, Consistency Index Influencing Factors (CIIF), is introduced evaluate consistency these across regions. Furthermore, Accurate Predictive Capability Indicator (APCI) defined measure impact categories on prediction accuracy. The findings reveal that models relying single factor exhibit limited accuracy, whereas combining multiple with diverse features significantly improves introduces refined analytical framework comprehensive indicator system for prediction. It enhances understanding complex influence provides scientific rationale implementing effective emission reduction strategies.

Язык: Английский

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Green bonds and carbon prices: a dynamic relationship revealed

Environment Development and Sustainability, Год журнала: 2024, Номер unknown

Опубликована: Ноя. 10, 2024

Язык: Английский

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Synergistic Management of Water, energy, and carbon: A case Study from Shandong Province, China

Applied Energy, Год журнала: 2024, Номер 381, С. 125192 - 125192

Опубликована: Дек. 23, 2024

Язык: Английский

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Techno-economic and environmental assessment of hydrogen utilization system based on different demand scenarios: An oil and gas field case

International Journal of Hydrogen Energy, Год журнала: 2024, Номер 101, С. 334 - 347

Опубликована: Дек. 31, 2024

Язык: Английский

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