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Zhang et al. Carbon Footprints 2025, 4, 36 https://dx.doi.org/10.20517/cf.2025.29 Page 15 of 17

Figure 8. Relationship between greenhouse gas emissions and urine and manure management.

intensities, we identified a critical threshold: ungrazed meadows act as significant carbon sinks, whereas the
introduction of yaks converts these ecosystems into net GHG sources. This source strength escalates with
increasing stocking rates, a trend mirrored by a corresponding rise in GHG intensity per unit of live weight
gain. Within the grazed systems, enteric fermentation and manure management emerge as the second and
third most significant contributors to the total GHG emissions, respectively. Consequently, effective
mitigation strategies for yak grazing systems must prioritize the reduction of emissions from these two key
processes. Given the unique geographical and biophysical context of the QTP, substituting dry manure
consumption with renewable energy sources such as solar and wind presents a viable pathway to curb
emissions from manure management. Furthermore, the implementation of adaptive management practices,
such as appropriately fenced grazing, can enhance the soil’s carbon sequestration capacity. This not only
promotes the removal of atmospheric CO but also offers a crucial mechanism for mitigating the overall
2
GHG footprint of the QTP’s alpine grazing ecosystems.

DECLARATIONS
Authors’ contributions
Methodology, investigation, formal analysis, writing - original draft: Zhang, J.
Methodology, investigation, writing - review & editing, Conceptualization: Cheng, P.; Liu, Y.
Conceptualization, writing - review & editing, project administration, supervision, funding acquisition:
Hou, F.; Chang, S.
Data collection and manuscript revision: Yan, C.; Sun, Y.; Zhang, Y.; Wang, Z. F.

Availability of data and materials
The data are available from the corresponding authors upon reasonable request.

Financial support and sponsorship
This study was funded by the National Key Research and Development Program of China, Grant/Award
Number: 2021YFD1300504; the National Natural Science Foundation of China, Grant/Award Number:
U21A20242; Gansu Province Science and Technology Plan Project, Grant/Award Number: 23JDKA0009;
the Innovative Research Team in University, Grant/Award Number: IRT_17R50; ‘Lanzhou City’s Scientific