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Page 8 of 17 Zhang et al. Carbon Footprints 2025, 4, 36 https://dx.doi.org/10.20517/cf.2025.29

The indirect CO emissions from electricity consumption were calculated using
2

E = C ·EF CO2-P
p
p
where E is the total CO emission from electricity consumption each year, C is the electricity consumption
p
p
2
each year, and EF CO2-P is the CO emission factor from the power sector that was cited in the “2014 Baseline
2
Emission Factors for Regional Power Grids in China” (NDRC, China).
Functional unit selection and data compilation
The assessment of GHG emissions was standardized using a functional unit, which acts as the common
reference point for all system outputs. The primary analysis employed an area-based functional unit to
determine the net GHG balance. Subsequently, to evaluate the production efficiency, a performance-based
metric was introduced: the GHG intensity. This metric was calculated by dividing the area-based net GHG
balance by the corresponding LWG per unit area. As a result, the final GHG outcomes were dual-
dimensional: the annual net GHG flux was reported both on an areal basis [in kg CO -equivalents
2
-1
(CO -eq) ha ] and in relation to animal production (in kg CO -eq kg LWG). For the calculation itself,
-1
2
2
individual emissions of CO , CH , and N O were first converted to CO -eq by applying their 100-year global
2
2
4
2
warming potentials (GWP) of 1, 25, and 298, respectively . The net GHG balance was then obtained by the
[28]
summation of these converted values.
Statistics analysis
The statistical analysis focused on differences in carbon sequestration, CH and N O fluxes from each
2
4
source, and the net GHG balance among four grazing management types: HSR, MSR, LSR, and a fenced
control. For this analysis, a One-Way Analysis of Variance was implemented using Statistical Product and
Service Solutions (version 20.0). Following a significant ANOVA result, Tukey’s post-hoc test was utilized
to conduct pairwise comparisons of the treatment means, with differences considered statistically significant
at P < 0.05.
RESULTS
Net GHG fluxes of alpine meadow
From 2012 to 2013, LSR did not reduce SOC compared with other treatments. Topsoil organic carbon
stocks increased in the enclosed (no grazing) site. The topsoil organic carbon stock at the LSR, MSR, and
HSR sites demonstrated a trend of being either largely stable or marginally depleted [Figure 2]. Therefore,
the topsoil organic carbon stocks were depleted in moderate and heavy grazed alpine meadows. In contrast,
grazing exclusion significantly increased the topsoil organic carbon stocks. A decline in the topsoil organic
carbon stocks at the MSR and HSR sites indicates that these areas function as net sources of CO .
2
Conversely, an increase in carbon stock in ungrazed grasslands demonstrates their role as effective CO
2
sinks [Figure 2B]. While the alpine meadow served as a significant CH sink, this crucial ecosystem function
4
was substantially constrained by grazing activities. NO gas emissions in the alpine meadow showed a hump
2
distribution, and the maximum emissions reached 60.87 NO eq/year (Nitrogen dioxide equivalent/year)
2
when the stocking rate was 1.19 yak/ha, and the CO gas level gradually increased as the stocking rate
2
increased. The GHG flow of the alpine meadow is mainly methane absorption and nitrous oxide emission.
With the increase of stocking rate, the absorption capacity of methane decreases and the emission capacity
of nitrous oxide increases [Figure 2C].

Enteric fermentation and manure management
The enteric CH emissions were not measured directly, but we adopted the emission factor from Ding et al.
4
-1
-1
(2010) , who reported a value of 81.4 g CH day yak at an estimated daily grass DM intake of 3.78 kg for
[26]
4