Page 61 - Read Online

Han et al. Carbon Footprints 2025, 4, 25 https://dx.doi.org/10.20517/cf.2025.18 Page 3 of 20

between emissions and economic growth in the European transport sector. Since then, Tapio's framework
has been widely applied to examine the decoupling of CO emissions and economic development in OECD
2
[49]
countries , BRICS countries , and B&R countries [50-52] . Building on this, the logarithmic mean Divisia
[48]
index (LMDI) method is often used to identify the key drivers and barriers of emission trends [53,54] , which
has been broadly applied in energy and environmental research .
[55]
Although extensive studies have investigated the carbon footprints, environmental emissions, and water
scarcity of the B&R region, the issue of CH emissions remains underexplored. To address this gap, this
4
study makes the following contributions: (i) it examines the evolution of production-based emissions
(PBEs) and consumption-based emissions (CBEs) in the B&R countries using MRIO modeling; (ii) it
compares inequality in CH emissions across income groups and regions using the Lorenz curve and Gini
4
coefficient; and (iii) it investigates the evolution and drivers of decoupling between CH emissions and
4
economic growth, offering practical insights for reducing CH inequality and developing mitigation
4
strategies in the B&R region.

METHODS AND DATA SOURCES
The methodology employed in this study is comprehensively illustrated in Figure 1, with a specific focus on
the B&R countries. First, the global multi-regional input-output model is used to assess the total CH 4
emission flows generated by each B&R country. This model enables a detailed examination of CH 4
emissions from both production and consumption perspectives, providing a comprehensive understanding
of emission sources and transfers within the B&R context. Next, the Lorenz curve and Gini coefficient are
applied to measure spatial inequality in CH emissions across the B&R countries. These tools provide both
4
visual and quantitative insights into disparities in emission levels, highlighting regions with
disproportionately high or low emissions within this international cooperation framework. Finally, a
decoupling decomposition analysis is conducted to delve into the driving forces behind CH emissions in
4
the B&R countries.

Multi-regional input-output modeling
[56]
Input-output analysis, originally proposed by Leontief , provides a framework for describing commodity
supply chains from both production and consumption perspectives. The balance of the MRIO model can be
expressed in matrix form as:

X = AX + F (1)

where X denotes the total output, matrix A represents the technical coefficients that describe the
interdependencies among economic sectors, and matrix F denotes final demand.

According to the MRIO framework, Eq. (2) can be expressed as:

X = (I - A) F = LF (2)
-1

-1
where L = (I - A) represents the Leontief inverse matrix, which reflects the total economic inputs to satisfy
one unit of final demand in monetary terms.

The Leontief inverse matrix can also be used to link direct GHG emissions with final demand categories, as
expressed in Eq. (3):