Inventory of Spatio-Temporal Methane Emissions from Livestock and Poultry Farming in Beijing

Yixuan Guo, Yidong Wang, Shufeng Chen, Shunan Zheng, Changcheng Guo, Dongmei Xue, Yakov Kuzyakov and Zhong-Liang Wang
Additional contact information
Yixuan Guo: Tianjin Key Laboratory of Water Resources and Environment, Tianjin Normal University, Tianjin 300387, China
Yidong Wang: Tianjin Key Laboratory of Water Resources and Environment, Tianjin Normal University, Tianjin 300387, China
Shufeng Chen: Beijing Municipal Research Institute of Environmental Protection, Beijing 100037, China
Shunan Zheng: Rural Energy and Environment Agency, Ministry of Agriculture and Rural Affairs, Beijing 100125, China
Changcheng Guo: Tianjin Key Laboratory of Water Resources and Environment, Tianjin Normal University, Tianjin 300387, China
Dongmei Xue: Tianjin Key Laboratory of Water Resources and Environment, Tianjin Normal University, Tianjin 300387, China
Yakov Kuzyakov: Tianjin Key Laboratory of Water Resources and Environment, Tianjin Normal University, Tianjin 300387, China
Zhong-Liang Wang: Tianjin Key Laboratory of Water Resources and Environment, Tianjin Normal University, Tianjin 300387, China

Sustainability, 2019, vol. 11, issue 14, 1-11

Abstract: Livestock and poultry farming sectors are among the largest anthropogenic methane (CH 4 ) emission sources, mainly from enteric fermentation and manure management. Previous inventories of CH 4 emission were generally based on constant emission factor (EF) per head, which had some weaknesses mainly due to the succession of breeding and feeding systems over decades. Here, more reliable long-term changes of CH 4 emissions from livestock and poultry farming in Beijing are estimated using the dynamic EFs based on the Intergovernmental Panel on Climate Change (IPCC) Tier 2 method, and high-resolution spatial patterns of CH 4 emissions are also estimated with intensive field survey. The results showed that the estimated CH 4 emissions derived by dynamic EFs were approximately 13–19% lower than those based on the constant EF before 2010. After 2011, however, the dynamic EFs-derived CH 4 emissions were a little higher (3%) than the constant EF method. Temporal CH 4 emissions in Beijing had experienced four developing stages (1978–1988: stable; 1989–1998: slow growth; 1999–2004: rapid growth and reached hot moments; 2005–2014: decline) during 1978–2014. Over the first two decades, the contributions of pigs (45%) and cattle (46%) to annual CH 4 emission were similar; subsequently, the cattle emitted more CH 4 compared to the pigs. At a spatial scale, Shunyi, Daxing, and Tongzhou districts with more cattle and pigs are the hotspots of CH 4 emission. In conclusion, the dynamic EFs method obviously improved the spatio-temporal estimates of CH 4 emissions compared to the constant EF approach, and the improvements depended on the period and aquaculture structure. Therefore, the dynamic EFs method should be recommended for estimating CH 4 emissions from livestock and poultry farming in the future.

Keywords: enteric emissions; greenhouse gases; livestock and poultry; CH 4 emission; China (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/2071-1050/11/14/3858/pdf (application/pdf)
https://www.mdpi.com/2071-1050/11/14/3858/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jsusta:v:11:y:2019:i:14:p:3858-:d:248700

Access Statistics for this article

Sustainability is currently edited by Ms. Alexandra Wu

More articles in Sustainability from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().