Driving Factors and Decoupling Effects of Non-CO2 Greenhouse Gas Emissions from Agriculture in Southwest China DOI Creative Commons
Ruiyi Tang,

Yuanyue Chu,

Xiaoqian Liu

et al.

Atmosphere, Journal Year: 2024, Volume and Issue: 15(9), P. 1084 - 1084

Published: Sept. 6, 2024

In light of the growing demand for green and low-carbon development, advancement agriculture in alignment with China’s specific national circumstances is imminent. Given this urgency, accounting non-CO2 greenhouse gas (GHG) emissions agricultural system still process continuous research improvement. Therefore, paper, we present an account GHG Southwest China from 1995 to 2021, based on carbon emission coefficient method. Furthermore, explore extent influence drivers relationship economic utilizing Stochastic Impact Regression Population, Affluence, Technology (STIRPAT) model Tapio model. We observe a general trend increasing then decreasing region, pattern higher center lower east west. Economic, demographic, structural, technological levels show different degrees impact provinces, favoring development targeted planning policies each region. For majority study period, there was weak or strong decoupling between growth emissions. Finally, recommendations are made promote China, providing database policy support clarify contribution system.

Language: Английский

Progress and Hotspots of Research on Land-Use Carbon Emissions: A Global Perspective DOI Open Access
Min Liu, Chen Yin-rong, Kun Chen

et al.

Sustainability, Journal Year: 2023, Volume and Issue: 15(9), P. 7245 - 7245

Published: April 27, 2023

Carbon emissions from land use change are the leading causes of greenhouse effect. Exploration progress and hotspots research on land-use carbon (LUCE) is crucial for mitigating global climate warming. However, a comprehensive systematic review LUCE perspective still lacking. We used WoS Core Collection Database to analyze current status with aid bibliometrix tool, aiming reveal future development trends. found that (1) process has gone through nascent exploration stage (1992–2001), problem-focused (2002–2011), prosperous (2012–2022) under different policy orientations. European North American countries prioritize more than others. (2) Overseas mainly focus effects change, impact deforestation fire stocks, soil organic stocks biodiversity, agricultural emissions. Research in China study influencing factors emissions, path achieving dual goal, transition low economy. (3) frontiers show researches low-carbon intensification context “dual carbon” strategy; emission reduction based energy transition; multi-dimensional, dynamic, accurate tracking monitoring systems using remote sensing satellite data. Other have shifted measuring historical deforestation, degradation biomass combustion warming mitigation research. This enhances depth breadth research, which can provide theoretical foundation scientific reference subsequent LUCE.

Language: Английский

Citations

20
Design strategies of passive solar greenhouses: A bibliometric and systematic review DOI Creative Commons
Ding Ding

Ain Shams Engineering Journal, Journal Year: 2024, Volume and Issue: 15(5), P. 102680 - 102680

Published: Feb. 13, 2024

During passive solar design of greenhouses, engineers usually encounter issues such as building form parameter selection. Suitable parameters can help to reduce energy losses related interior temperature control and relatively intensive crop production. However, by using bibliometric analyses, no existing review works provide concise selection lists. To fill in this gap, paper compares evaluates various technologies for greenhouse five areas: (1) orientation, (2) structures, (3) envelope materials, (4) heat storage options, (5) numerical modeling. First, the orientation a significantly influences its performance. Second, greenhouses exhibit architectural shapes, including single- multispan, with transparent opaque envelopes. Third, include envelopes constructed from movable insulation materials. Fourth, most daily systems equipped media, water, soil, rock, brick, phase change material (PCM). Finally, reviews modeling performance evaluations greenhouses.

Language: Английский

Citations

7
The Spatiotemporal Characteristics and Driving Factors of Agricultural Carbon Emissions in the Yellow River Basin DOI
Lei Nie,

Bao Xueli,

Sun Quan

et al.

Journal of Resources and Ecology, Journal Year: 2025, Volume and Issue: 16(2)

Published: April 4, 2025

Language: Английский

Citations

0
Prediction model and demonstration of regional agricultural carbon emissions based on Isomap–ACO–ET: a case study of Guangdong Province, China DOI Creative Commons
Yanwei Qi, Huailiang Liu, Jianbo Zhao

et al.

Scientific Reports, Journal Year: 2023, Volume and Issue: 13(1)

Published: Aug. 4, 2023

Abstract Scientific analysis of regional agricultural carbon emission prediction models and empirical studies are great practical significance to the realization low-carbon agriculture, which can help revitalize build up ecological beautiful countryside in China. This paper takes agriculture Guangdong Province, China, as research object, uses extended STIPAT model construct an indicator system for factors influencing emissions Guangdong. Based on this system, a combined Isomap–ACO–ET combing isometric mapping algorithm (Isomap), ant colony (ACO) extreme random tree (ET) was used predict Province under five scenarios. Effective predictions be made expected fluctuate between 11,142,200 tons 11,386,000 2030. And compared with other machine learning neural network models, has better performance MSE 0.00018 accuracy 98.7%. To develop we should improve farming methods, reduce intensity agrochemical application, strengthen development promotion energy-saving reduction technologies energy sources, from consumption, optimize planting structure, green products agro-ecological tourism according local conditions. will promote sustainable direction.

Language: Английский

Citations

7
Research on Niche Improvement Path of Photovoltaic Agriculture in China DOI Open Access
Lingjun Wang, Yuanyuan Li

International Journal of Environmental Research and Public Health, Journal Year: 2022, Volume and Issue: 19(20), P. 13087 - 13087

Published: Oct. 12, 2022

To explore the niche improvement path of photovoltaic agriculture in China, a influencing factor system was constructed first. Then, this study innovatively combined DEMATEL and analytic network process (DANP) method NK model, which can correct defects traditional model. Based on above method, influence coefficients index weight each were calculated, fitness landscape constructed. Finally, according to map combination state, optimal configuration state factors explored. We found that interaction between six determines agriculture, changes are coordinated. It proposed China is “technological innovation → policy formulation resource allocation economic social recognition environmental protection”, research conclusions further explained discussed.

Language: Английский

Citations

9
Study on the Spatiotemporal Evolution and Influencing Factors of Agricultural Carbon Emissions in the Counties of Zhejiang Province DOI Open Access

Changcun Wen,

Jiaru Zheng,

Bao Hu

et al.

International Journal of Environmental Research and Public Health, Journal Year: 2022, Volume and Issue: 20(1), P. 189 - 189

Published: Dec. 23, 2022

The accurate measurement of agricultural carbon emissions and the analysis key influential factors spatial effects are premise rational formulation emission reduction policies promotion regional coordinated governance reductions in emissions. In this paper, a autocorrelation model Dubin used to explore spatiotemporal characteristics, (ACEs). results show that (1) From 2014 2019, overall Zhejiang Province showed downward trend, while density an upward trend. ACEs mainly caused by rice planting land management, accounting for 59.08% 26.17% total emissions, respectively. (2) have obvious autocorrelation. clustering characteristics enhanced, “H-H” cluster is concentrated northeast Zhejiang, “L-L” southwest. (3) across whole sample area exhibit significant spillover effect. disposable income per capita rural areas county significantly promotes increase neighboring counties, adjustment industrial structure has positive effect on counties. (4) grouping there heterogeneity between 26 counties mountainous non-mountainous areas. urbanization rate, population, mechanization level negative economic development residents These research can provide theoretical basis low-carbon agriculture according region category.

Language: Английский

Citations

9
Trends and driving forces of agricultural carbon emissions: A case study of Anhui, China DOI Creative Commons
Yanwei Qi, Huailiang Liu, Jianbo Zhao

et al.

PLoS ONE, Journal Year: 2024, Volume and Issue: 19(2), P. e0292523 - e0292523

Published: Feb. 12, 2024

To facilitate accurate prediction and empirical research on regional agricultural carbon emissions, this paper uses the LLE-PSO-XGBoost emission model, which combines Local Linear Embedding (LLE), Particle Swarm Algorithm (PSO) Extreme Gradient Boosting (XGBoost), to forecast emissions in Anhui Province under different scenarios. The results show that generally an upward then downward trend during 2000–2021, 2030 are expected fluctuate between 11,342,100 tones 14,445,700 five set projections of can play important role supporting development local agriculture, helping guide input policy guidance rural low-carbon agriculture promoting areas towards a resource-saving environment-friendly society.

Language: Английский

Citations

1
How does planting structure change affect the agricultural net carbon sink? Evidence from the Jiangsu coastal economic Belt DOI Creative Commons
Xiaomei Shen, Rong Yan,

Mingdong Jiang

et al.

Ecological Indicators, Journal Year: 2024, Volume and Issue: 170, P. 112949 - 112949

Published: Dec. 12, 2024

Language: Английский

Citations

1
Time, Spatial and Component Characteristics of Agricultural Carbon Emissions of China DOI Creative Commons
Shulong Li, Zhizhang Wang

Agriculture, Journal Year: 2023, Volume and Issue: 13(1), P. 214 - 214

Published: Jan. 14, 2023

In this study, the time trend, regional distribution and component characteristics of agricultural carbon emissions (ACEs) China are analyzed. The estimation methods each ACE introduced. According to annually provincial panel data set with 31 provinces from 1996 2019, empirically discussed. Meanwhile, since it is also worthwhile explore effect on economic growth, econometric models such as pooled ordinary least squares (OLS) fixed (FE) employed examine inverted “U”-shape both GDP under control other variables. results show that (1) emission started fall after 2015; (2) majority source caused by chemical fertilizer, which approximately half total; (3) current levels (0.287 ×1010 kg in 2019) significantly smaller than estimated optimal level for well (respectively, 1.003×1010 1.256×1010 kg). light this, environmental protection development currently conflicted. Therefore, we suggest government should accept a trade-off between growth quality environment.

Language: Английский

Citations

2
New evidence on the impact of No-tillage management on agricultural carbon emissions DOI
Yuan Tian, Chenxi Pu, Guanghao Wu

et al.

Environmental Science and Pollution Research, Journal Year: 2023, Volume and Issue: 30(48), P. 105856 - 105872

Published: Sept. 18, 2023

Language: Английский

Citations

2