Exploration of Dual-Carbon Target Pathways Based on Machine Learning Stacking Model and Policy Simulation—A Case Study in Northeast China DOI Creative Commons
Xuezhi Ren,

Jianya Zhao,

Shu Wang

et al.

Land, Journal Year: 2025, Volume and Issue: 14(4), P. 844 - 844

Published: April 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.

Language: Английский

Increasing pesticide diversity impairs soil microbial functions DOI Creative Commons

Bang Ni,

Lu Xiao, Da Lin

et al.

Proceedings of the National Academy of Sciences, Journal Year: 2025, Volume and Issue: 122(2)

Published: Jan. 9, 2025

Pesticide application is essential for stabilizing agricultural production. However, the effects of increasing pesticide diversity on soil microbial functions remain unclear, particularly under varying nitrogen (N) fertilizer management practices. In this study, we investigated stochasticity microbes and multitrophic networks through amplicon sequencing, assessed community related to carbon (C), N, phosphorus (P), sulfur (S) cycling, characterized dominant bacterial life history strategies via metagenomics along a gradient two N addition levels. Our findings show that higher enriches abundance specialists opportunists capable degrading or resisting pesticides, reducing proportion generalists in absence addition. These shifts can complicate networks. Under increased diversity, selective pressure may drive bacteria streamline their average genome size conserve energy while enhancing C, P, S metabolic capacities, thus accelerating nutrient loss. comparison, was found reduce niche differentiation at mitigating impacts network complexity functional traits associated with ultimately alleviating results reveal contrasting different input scenarios emphasize strategic mitigate ecological use systems.

Language: Английский

Citations

5
Exploring Crop Production Strategies to Mitigate Greenhouse Gas Emissions Based on Scenario Analysis DOI Creative Commons
Zhuoyuan Gu, Jing Xue,

Hongfang Han

et al.

Land, Journal Year: 2025, Volume and Issue: 14(2), P. 256 - 256

Published: Jan. 26, 2025

In the context of global climate change and carbon neutrality goals, agriculture has emerged as a major source greenhouse gas (GHG) emissions, faces critical challenge reducing emissions while ensuring food security. However, existing research rarely focused on dynamic simulation scenario-based analysis optimised agricultural layouts their impact GHG emissions. Taking three northeastern provinces (Heilongjiang, Jilin, Liaoning) China study area, this quantifies from grain crops employs time-series machine learning methods to conduct scenario analysis, including scenarios (Business Usual, Sustainable Optimisation, Ecological Priority). Specific policy implications are proposed for optimising mitigating The results indicate that in Northeast primarily stem methane rice cultivation nitrous oxide fertiliser use. A reveals “Sustainable Optimisation” reduces by 22.0% through planting maintaining stable crop production. “Ecological Priority” further enhances emission reductions 25.2% increasing share low-emission crops, such corn, high-emission rice. provides practical reference promoting low carbonisation agriculture, demonstrates production structures can simultaneously achieve security mitigation.

Language: Английский

Citations

0
Synergies and trade-offs of crop diversification system for productive, energy budget, economic, and environmental indicators in Northeast China DOI
Tao Sun, Haotian Chen, Yao Li

et al.

Field Crops Research, Journal Year: 2025, Volume and Issue: 325, P. 109816 - 109816

Published: Feb. 28, 2025

Language: Английский

Citations

0
Exploration of Dual-Carbon Target Pathways Based on Machine Learning Stacking Model and Policy Simulation—A Case Study in Northeast China DOI Creative Commons
Xuezhi Ren,

Jianya Zhao,

Shu Wang

et al.

Land, Journal Year: 2025, Volume and Issue: 14(4), P. 844 - 844

Published: April 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.

Language: Английский

Citations

0