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Article

Spatial–Temporal Patterns of Methane Emissions from Livestock in Xinjiang During 2000–2020

1
Key Laboratory of Geographic Information Science, Ministry of Education, East China Normal University, Shanghai 200241, China
2
School of Geographic Sciences, East China Normal University, Shanghai 200241, China
3
School of Plant and Environmental Sciences, Virginia Tech, Blacksburg, VA 24061, USA
4
Key Laboratory of Ecological Safety and Sustainable Development in Arid Lands, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830000, China
5
College of Life Sciences, Shihezi University, Shihezi 823003, China
*
Author to whom correspondence should be addressed.
Sustainability 2025, 17(20), 9021; https://doi.org/10.3390/su17209021 (registering DOI)
Submission received: 3 September 2025 / Revised: 30 September 2025 / Accepted: 8 October 2025 / Published: 11 October 2025
(This article belongs to the Special Issue Geographical Information System for Sustainable Ecology)

Abstract

Livestock represent a significant source of methane (CH4) emissions, particularly in pastoral regions. However, in Xinjiang—a pivotal pastoral region of China—the spatiotemporal patterns of livestock CH4 emissions remain poorly characterized, constraining regional mitigation actions. Here, a detailed CH4 emissions inventory for livestock in Xinjiang spanning the period 2000–2020 is compiled. Eight livestock categories were covered, gridded livestock maps were developed, and the dynamic emission factors were built by using the IPCC 2019 Tier 2 approaches. Results indicate that the CH4 emissions increased from ~0.7 Tg in 2000 to ~0.9 Tg in 2020, a 28.5% increase over the past twenty years. Beef cattle contributed the most to the emission increase (59.6% of total increase), followed by dairy cattle (35.7%), sheep (13.9%), and pigs (4.3%). High-emission hotspots were consistently located in the Ili River Valley, Bortala, and the northwestern margins of the Tarim Basin. Temporal trend analysis revealed increasing emission intensities in these regions, reflecting the influence of policy shifts, rangeland dynamics, and evolving livestock production systems. The high-resolution map of CH4 emissions from livestock and their temporal trends provides key insights into CH4 mitigation, with enteric fermentation showing greater potential for emission reduction. This study offers the first long-term, high-resolution CH4 emission inventory for Xinjiang, providing essential spatial insights to inform targeted mitigation strategies and enhance sustainable livestock management in arid and semi-arid ecosystems.
Keywords: CH4 emissions; livestock distribution; random forest; climate change; IPCC Tier 2 CH4 emissions; livestock distribution; random forest; climate change; IPCC Tier 2

Share and Cite

MDPI and ACS Style

Xu, Q.; Li, Y.; You, Y.; Zhang, L.; Zhang, H.; Zhang, Z.; Yao, Y.; Huang, Y. Spatial–Temporal Patterns of Methane Emissions from Livestock in Xinjiang During 2000–2020. Sustainability 2025, 17, 9021. https://doi.org/10.3390/su17209021

AMA Style

Xu Q, Li Y, You Y, Zhang L, Zhang H, Zhang Z, Yao Y, Huang Y. Spatial–Temporal Patterns of Methane Emissions from Livestock in Xinjiang During 2000–2020. Sustainability. 2025; 17(20):9021. https://doi.org/10.3390/su17209021

Chicago/Turabian Style

Xu, Qixiao, Yumeng Li, Yongfa You, Lei Zhang, Haoyu Zhang, Zeyu Zhang, Yuanzhi Yao, and Ye Huang. 2025. "Spatial–Temporal Patterns of Methane Emissions from Livestock in Xinjiang During 2000–2020" Sustainability 17, no. 20: 9021. https://doi.org/10.3390/su17209021

APA Style

Xu, Q., Li, Y., You, Y., Zhang, L., Zhang, H., Zhang, Z., Yao, Y., & Huang, Y. (2025). Spatial–Temporal Patterns of Methane Emissions from Livestock in Xinjiang During 2000–2020. Sustainability, 17(20), 9021. https://doi.org/10.3390/su17209021

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