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

Qixiao Xu, Yumeng Li, Yongfa You, Lei Zhang (), Haoyu Zhang, Zeyu Zhang, Yuanzhi Yao and Ye Huang
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Qixiao Xu: Key Laboratory of Geographic Information Science, Ministry of Education, East China Normal University, Shanghai 200241, China
Yumeng Li: Key Laboratory of Geographic Information Science, Ministry of Education, East China Normal University, Shanghai 200241, China
Yongfa You: School of Plant and Environmental Sciences, Virginia Tech, Blacksburg, VA 24061, USA
Lei Zhang: Key Laboratory of Ecological Safety and Sustainable Development in Arid Lands, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830000, China
Haoyu Zhang: Key Laboratory of Geographic Information Science, Ministry of Education, East China Normal University, Shanghai 200241, China
Zeyu Zhang: Key Laboratory of Ecological Safety and Sustainable Development in Arid Lands, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830000, China
Yuanzhi Yao: Key Laboratory of Geographic Information Science, Ministry of Education, East China Normal University, Shanghai 200241, China
Ye Huang: Key Laboratory of Geographic Information Science, Ministry of Education, East China Normal University, Shanghai 200241, China

Sustainability, 2025, vol. 17, issue 20, 1-18

Abstract: Livestock represent a significant source of methane (CH 4 ) emissions, particularly in pastoral regions. However, in Xinjiang—a pivotal pastoral region of China—the spatiotemporal patterns of livestock CH 4 emissions remain poorly characterized, constraining regional mitigation actions. Here, a detailed CH 4 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 CH 4 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 CH 4 emissions from livestock and their temporal trends provides key insights into CH 4 mitigation, with enteric fermentation showing greater potential for emission reduction. This study offers the first long-term, high-resolution CH 4 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: CH 4 emissions; livestock distribution; random forest; climate change; IPCC Tier 2 (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2025
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