Spatiotemporal differentiation and trend prediction of carbon emissions in China’s swine industry DOI Creative Commons
Qingsong Zhang, Liang Chen,

Hassan Saif Khan

et al.

Ecological Indicators, Journal Year: 2024, Volume and Issue: 166, P. 112391 - 112391

Published: July 27, 2024

Assessing carbon emissions in China's swine industry and understanding its spatial–temporal characteristics under peak neutrality goals are vital for promoting low-carbon farming. This study measures the industry's across 30 provinces China from 2006 to 2022 using life cycle assessment IPCC coefficient methods. Spatial temporal patterns were analyzed with exploratory spatial data analysis, an XGBoost model was used predict 2023 2032. The results show a "W"-shaped oscillating trend total emissions, phases of rapid decline, fluctuating rise, resurgence. Emissions highest Central region, followed by West, East, Northeast. Manure management Feed crop cultivation primary emission sources, accounting 59.7% 29.9% respectively. pattern high low regions remained stable, dynamic changes moderate regions. High concentrated major grain-producing livestock-raising South coastal farming projects that green development will have significant future impact. intensity shows initial decline stabilization, whereas projected remain gradually increase, primarily due continuous growth production capacity. conclusions this provide reference basis transformation optimization regional layout livestock industry.

Language: Английский

Spatiotemporal evolution and driving factors of the synergistic effects of pollution control and carbon reduction in China DOI Creative Commons
Qinggang Meng, Xiaolan Chen, Hui Wang

et al.

Ecological Indicators, Journal Year: 2025, Volume and Issue: 170, P. 113103 - 113103

Published: Jan. 1, 2025

Language: Английский

Citations

1
Sustainable livestock management under anthropogenic pressure: Bridging traditional herding and contemporary conservation in Eurasia's oldest protected area DOI
Maria Vittoria Mazzamuto, Enkhbat Enkhmaa,

Jeff Dolphin

et al.

Journal of Environmental Management, Journal Year: 2025, Volume and Issue: 379, P. 124901 - 124901

Published: March 9, 2025

Language: Английский

Citations

0
Dynamic prediction and quantitative assessment of carbon emissions from animal husbandry: A case study of inner mongolia autonomous region, China DOI Open Access
Jikang Luo, Zhao Zhen, Jing Pang

et al.

Journal of Environmental Quality, Journal Year: 2025, Volume and Issue: unknown

Published: March 12, 2025

Abstract Climate change, driven by greenhouse gas emissions, has emerged as a pressing global ecological and environmental challenge. Our study is dedicated to exploring the various factors influencing emissions from animal husbandry predicting their future trends. To this end, we have analyzed data China's Inner Mongolia Autonomous Region spanning 1978 2022, aiming estimate carbon associated with in region. Furthermore, constructed an SA‐STIRPAT model grounded scenario analysis forecast timing of peak. findings reveal several notable From 2001 region followed pattern “rapid growth, smooth fluctuations, then gradual recovery.” Notably, 2019, reached peak contribution accounting for 8.34% national total. Ruminants, including cattle, sheep, camels, were identified primary emitters, responsible 91.6% total emissions. Additionally, our indicates that such production efficiency, industrial structure, economic level, population structure positively impact while size negatively affects husbandry's footprint. predicts under both low‐carbon benchmark scenarios, are expected decline after 2030. However, high‐carbon scenario, anticipated 2040. In conclusion, achieve Mongolia's “dual carbon” goals, it imperative implement effective control measures, enhance elevate level urbanization, optimize structure.

Language: Английский

Citations

0
Spatiotemporal differentiation and trend prediction of carbon emissions in China’s swine industry DOI Creative Commons
Qingsong Zhang, Liang Chen,

Hassan Saif Khan

et al.

Ecological Indicators, Journal Year: 2024, Volume and Issue: 166, P. 112391 - 112391

Published: July 27, 2024

Assessing carbon emissions in China's swine industry and understanding its spatial–temporal characteristics under peak neutrality goals are vital for promoting low-carbon farming. This study measures the industry's across 30 provinces China from 2006 to 2022 using life cycle assessment IPCC coefficient methods. Spatial temporal patterns were analyzed with exploratory spatial data analysis, an XGBoost model was used predict 2023 2032. The results show a "W"-shaped oscillating trend total emissions, phases of rapid decline, fluctuating rise, resurgence. Emissions highest Central region, followed by West, East, Northeast. Manure management Feed crop cultivation primary emission sources, accounting 59.7% 29.9% respectively. pattern high low regions remained stable, dynamic changes moderate regions. High concentrated major grain-producing livestock-raising South coastal farming projects that green development will have significant future impact. intensity shows initial decline stabilization, whereas projected remain gradually increase, primarily due continuous growth production capacity. conclusions this provide reference basis transformation optimization regional layout livestock industry.

Language: Английский

Citations

0