Synergistic Effect of Combating Air Pollutants and Carbon Emissions in the Yangtze River Delta of China: Spatial and Temporal Divergence Analysis and Key Influencing Factors DOI Creative Commons

Fang Liu,

Anqi Li, Muhammad Bilal

et al.

Research Square (Research Square), Journal Year: 2023, Volume and Issue: unknown

Published: Sept. 22, 2023

Abstract Synergizing the reduction of air pollutants and carbon emissions (APCE) has become a critical tactic alternative to address issue climate change. Taking Yangtze River Delta (YRD) region China as case study, this paper explores spatial temporal distribution pattern coupling coordination degree (CCD) combating APCE from 2011 2022, analyzes dynamic change in CCD using convergence test, investigates key factors affecting via Tobit regression model. The results show that: (1) (AP) CO2 emission (CE) YRD decrease at annual rate 10.32% 0.85%, respectively; (2) reducing presents W-shaped fluctuation before 2016 then steps into steady increase status after 2016; (3) order four provincial-level units by 2022 is Shanghai>Zhejiang>Jiangsu>Anhui. proportion cities where enters high-coordination period reached 87.8%; (4) affirm that economic growth, industrial structure, green technological innovation exacerbate APCE, while opening-up level mitigates it. Therefore, it recommended prioritize facilitating technology development competitive advantage amid international trade.

Language: Английский

Cultivating a sustainable future in the artificial intelligence era: A comprehensive assessment of greenhouse gas emissions and removals in agriculture DOI
Morteza SaberiKamarposhti,

Kok-Why Ng,

Mehdi Yadollahi

et al.

Environmental Research, Journal Year: 2024, Volume and Issue: 250, P. 118528 - 118528

Published: Feb. 23, 2024

Language: Английский

Citations

22
Tree-structured parzen estimator optimized-automated machine learning assisted by meta–analysis for predicting biochar–driven N2O mitigation effect in constructed wetlands DOI

Bi–Ni Jiang,

Yingying Zhang, Zhiyong Zhang

et al.

Journal of Environmental Management, Journal Year: 2024, Volume and Issue: 354, P. 120335 - 120335

Published: Feb. 17, 2024

Language: Английский

Citations

13
Paddy rice methane emissions, controlling factors, and mitigation potentials across Monsoon Asia DOI
Hong Zhou, Fulu Tao, Yi Chen

et al.

The Science of The Total Environment, Journal Year: 2024, Volume and Issue: 935, P. 173441 - 173441

Published: May 21, 2024

Language: Английский

Citations

5
Machine learning-driven analysis of greenhouse gas emissions from rice production in major Chinese provinces: Identifying key factors and developing reduction strategies DOI

Songhua Huan,

Xiuli Liu

European Journal of Agronomy, Journal Year: 2025, Volume and Issue: 164, P. 127536 - 127536

Published: Feb. 6, 2025

Language: Английский

Citations

0
Enhancing energy materials with data-driven methods: A roadmap to long-term hydrogen energy sustainability using machine learning DOI
Cheng Li, Jianjun Ma, D. R. Gibson

et al.

International Journal of Hydrogen Energy, Journal Year: 2025, Volume and Issue: 119, P. 108 - 125

Published: March 21, 2025

Language: Английский

Citations

0
Synergistic effect of combating air pollutants and carbon emissions in the Yangtze River Delta of China: spatial and temporal divergence analysis and key influencing factors DOI

Fang Liu,

Anqi Li, Muhammad Bilal

et al.

Environmental Science and Pollution Research, Journal Year: 2024, Volume and Issue: unknown

Published: Feb. 1, 2024

Language: Английский

Citations

3
Low-power flux gradient measurements for quantifying the impact of agricultural management on nitrous oxide emissions DOI Creative Commons
Shannon E. Brown, Claudia Wagner‐Riddle,

Ben Conrad

et al.

Agricultural and Forest Meteorology, Journal Year: 2024, Volume and Issue: 353, P. 110027 - 110027

Published: May 17, 2024

Nitrous oxide (N2O) emissions from agricultural soils occur as pulses presenting a challenge for assessing mitigation practices. Since the timing and magnitude of is dependent on soil climatic conditions, side-by-side comparisons are needed. The flux gradient (FG) eddy covariance (EC) methods both capture spatially temporally variable N2O emissions, but FG requirements more flexible operation using low power and/or in multi-plot configuration with one gas analyzer. Instrumentation measurement requires strong pumps (> 500 W), limiting deployment. Here we developed new instrumentation method minimal (∼30 W). Field measurements were conducted 2017 2018 an field Ontario, Canada to test equipment's quality, consumption, ease-of-use. A low-power system (FGLP) was co-located EC tower (N2O-EC) existing (FGMP) operated ∼50 m away. FGLP fluxes correlated well N2O-EC (r2 = 0.97, slope 1.05), ran uninterrupted maintenance only 30 W. non-co-located FGMP still showed relatively good correlation 0.65) through growing season although there mismatch footprints, well-known hot spots. Better agreement observed measured CO2 (slope r2 0.93), giving additional confidence FGMP. systems captured important during rainy, foggy dewy periods when data discarded. Results confirmed functionality verified against fluxes. option provides possibilities expand locations restrictions essential evaluating effects practices emissions.

Language: Английский

Citations

3
Recoupled crop-livestock system can potentially reduce agricultural greenhouse gas emissions by over 40 % in China DOI
Ying Cai, Fan Zhang, Xiangzheng Deng

et al.

Environmental Impact Assessment Review, Journal Year: 2024, Volume and Issue: 112, P. 107756 - 107756

Published: Dec. 12, 2024

Language: Английский

Citations

1
Prediction of Water Carbon Fluxes and Emission Causes in Rice Paddies Using Two Tree-Based Ensemble Algorithms DOI Open Access

Xinqin Gu,

Li Yao, Lifeng Wu

et al.

Sustainability, Journal Year: 2023, Volume and Issue: 15(16), P. 12333 - 12333

Published: Aug. 13, 2023

Quantification of water carbon fluxes in rice paddies and analysis their causes are essential for agricultural management budgets. In this regard, two tree-based machine learning models, which extreme gradient boosting (XGBoost) random forest (RF), were constructed to predict evapotranspiration (ET), net ecosystem exchange (NEE), methane flux (FCH4) seven paddy sites. During the training process, k-fold cross-validation algorithm by splitting available data into multiple subsets or folds avoid overfitting, XGBoost model was used assess importance input factors. When predicting ET, outperformed RF at all Solar radiation most important ET predictions. Except KR-CRK site, prediction NEE that models also performed better other six sites, root mean square error decreased 0.90–11.21% compared models. Among sites (except absence (NETRAD) JP-Mse site), NETRAD normalized difference vegetation index (NDVI) well NEE. Air temperature, soil content (SWC), longwave particularly individual Similarly, more capable FCH4 than model, except IT-Cas site. sensitivity factors varied from site SWC, respiration, NDVI, temperature prediction. It is proposed use paddies.

Language: Английский

Citations

3
Synergistic Effect of Combating Air Pollutants and Carbon Emissions in the Yangtze River Delta of China: Spatial and Temporal Divergence Analysis and Key Influencing Factors DOI Creative Commons

Fang Liu,

Anqi Li, Muhammad Bilal

et al.

Research Square (Research Square), Journal Year: 2023, Volume and Issue: unknown

Published: Sept. 22, 2023

Abstract Synergizing the reduction of air pollutants and carbon emissions (APCE) has become a critical tactic alternative to address issue climate change. Taking Yangtze River Delta (YRD) region China as case study, this paper explores spatial temporal distribution pattern coupling coordination degree (CCD) combating APCE from 2011 2022, analyzes dynamic change in CCD using convergence test, investigates key factors affecting via Tobit regression model. The results show that: (1) (AP) CO2 emission (CE) YRD decrease at annual rate 10.32% 0.85%, respectively; (2) reducing presents W-shaped fluctuation before 2016 then steps into steady increase status after 2016; (3) order four provincial-level units by 2022 is Shanghai>Zhejiang>Jiangsu>Anhui. proportion cities where enters high-coordination period reached 87.8%; (4) affirm that economic growth, industrial structure, green technological innovation exacerbate APCE, while opening-up level mitigates it. Therefore, it recommended prioritize facilitating technology development competitive advantage amid international trade.

Language: Английский

Citations

0