Application of the sustainable system-of-systems approach and econometric analysis to address China’s decarbonisation problem

Figures & data

Table 1. Main measures in China’s National Working Guidance for carbon dioxide peaking and carbon neutrality.

Objectives/Targets	By 2025	By 2030	Before 2060
Objectives	To achieve a green and low-carbon circular economy, the energy efficiency of key industries shall be significantly improved for the pursuit of CO2 peaking and carbon neutrality.	To achieve significant green transformation in socio-economic development, the energy efficiency of key industries shall reach the international advanced level.	To achieve the harmonious coexistence of human nature and a green circular economy, the carbon neutrality target and energy utilisation efficiency shall reach the international advanced level.
Targets: Energy consumption per unit of gross domestic production (GDP)	Reduced by 13.5% compared with 2020	Reduced significantly.	n.a.
Targets: Carbon dioxide emissions per unit of GDP	Reduced by 18% compared with 2020	Reduced by more than 65% compared with 2005	n.a.
Targets: Forest coverage rate	Reach 24.1%	Reach about 25%	n.a.
Targets: Forest stock volume	Reach 18 billion cubic metres	Reach 19 billion cubic metres	n.a.
Targets: Total installed capacity of wind and solar power	n.a.	Reach more than 1.2 billion kilowatts	n.a.
Targets: Proportion of non-fossil fuel energy consumption	Reach about 20%	Reach about 25%	Reach more than 80%

Source: National Development and Reform Commission of China (NDRC) 2021.

Figure 1. SSoS framework to address China’s decarbonisation problem.

(Note: The equations for the econometric analysis for each level are presented in the Section 3.3).

The figure shows four oval shapes with the smaller ones nested within the bigger ones. The smallest one is the micro level system, followed by the meso level system, macro level system and lastly the trajectory of climate change. Each level contains an objective, a key stakeholder (i.e. residential communities, industrial communities and government) and Equation/s (4) to (8). Across the nested oval shapes are the three capitals, i.e. social, economic and natural capitals. The model is to address the complex problem of determining the fossil fuel sources to reduce.

Table 2. Provinces/cities in the Eastern Region, Central Region, and Western Region of China.

	Eastern Region	Central Region	Western Region
	Liaoning	Jiangxi	Gansu
	Guangdong	Heilongjiang	Guangxi
	Hebei	Hubei	Guizhou
	Fujian	Chongqing	Inner Mongolia
	Shanghai	Shanxi	Ningxia
	Shandong	Jilin	Qinghai
	Beijing	Anhui	Shaanxi
	Hainan	Henan	Sichuan
	Tianjin	Hunan	Xinjiang
	Jiangsu		Yunnan
	Zhejiang
Number of provinces/cities	11	9	10
Sample size, 2009–2019	121	99	110

Table 3. Descriptive statistics of the variables for 30 provinces in China, 2009–2019.

Variable	Mean	Std. Dev.	Min	Max
$E_{RC}/L$	0.0074485	0.0059891	0.0001767	0.0378603
$E_{CO}/L$	0.0012334	0.0007113	0.0003084	0.0043256
$E_{NG}/L$	0.0004335	0.000454	1.66E-06	0.002346
$F_{RC}/L$	0.1617055	0.1005584	0.005783	0.6572683
$F_{CO}/L$	0.0494559	0.0332592	0.0107269	0.1895289
$F_{NG}/L$	0.0017831	0.0017856	0.0000282	0.0108958
$K/L$	84.8118	51.88833	14.99754	313.3446
$\mathit{GDP}/L$	0.0608608	0.0327856	0.0115828	0.2126791
$H/L$	2242.939	1030.952	668.6	6220.8
Total sample size	330
Total cross-sections	30

Table 4. Econometric analysis results.

	Eastern	Eastern	Eastern	Eastern	Eastern	Central	Central	Central	Central	Central	Western	Western	Western	Western	Western
Equation	(4)	(5)	(6)	(7)	(8)	(4)	(5)	(6)	(7)	(8)	(4)	(5)	(6)	(7)	(8)
Level	Micro	Meso	Meso	Meso	Macro	Micro	Meso	Meso	Meso	Macro	Micro	Meso	Meso	Meso	Macro
	$Ln\left(\frac{H}{L}\right)$	$Ln(\frac{E_{RC}}{L})$	$Ln(\frac{E_{CO}}{L})$	$Ln(\frac{E_{NG}}{L})$	$Ln(\frac{\mathit{GDP}}{L})$	$Ln(\frac{H}{L})$	$Ln(\frac{E_{RC}}{L})$	$Ln(\frac{E_{CO}}{L})$	$Ln(\frac{E_{NG}}{L})$	$Ln(\frac{\mathit{GDP}}{L})$	$Ln(\frac{H}{L})$	$Ln(\frac{E_{RC}}{L})$	$Ln(\frac{E_{CO}}{L})$	$Ln(\frac{E_{NG}}{L})$	$Ln(\frac{\mathit{GDP}}{L})$
$Ln(E_{RC}/L)$	0.09**				0.09*	0.31***				–0.59***	–0.14***				0.13
	(0.04)				(0.05)	(0.09)				(0.11)	(0.03)				(0.21)
$Ln(E_{CO}/L)$	–0.11*				0.21	0.14**				–0.05	–0.48***				0.62
	(0.07)				(0.27)	(0.07)				(0.19)	(0.12)				(0.39)
$Ln(E_{NG}/L)$	0.17***				–0.16*	0.03				0.07	0.03				–0.01
	(0.04)				(0.09)	(0.03)				(0.18)	(0.02)				(0.10)
$Ln(F_{RC}/L)$		0.91***			–0.17***		0.49***			0.24***		1.35***			–1.14*
		(0.04)			(0.06)		(0.06)			(0.07)		(0.04)			(0.64)
$Ln(F_{CO}/L)$			0.87***		–0.24			0.92***		0.18			0.85***		0.23
			(0.02)		(0.23)			(0.04)		(0.19)			(0.04)		(0.40)
$Ln(F_{NG}/L)$				0.63***	0.27***				0.91***	–0.07				1.07***	–0.32**
				(0.04)	(0.07)				(0.02)	(0.15)				(0.03)	(0.13)
$Ln(\mathit{GDP}/L)$	0.78***	–0.01	–0.03	0.77***		0.79***	0.35***	–0.008	0.02		1.46***	0.04	–0.02	0.20
	(0.07)	(0.07)	(0.03)	(0.11)		(0.08)	(0.07)	(0.05)	(0.06)		(0.11)	(0.06)	(0.04)	(0.13)
$Ln(H/L)$					–0.21***					0.22***					–1.45**
					(0.07)					(0.05)					(0.64)
$Ln(K/L)$					0.92***					0.68***					2.40***
					(0.07)					(0.05)					(0.78)
Constant	10.89***	–3.19***	–4.13***	–1.67***	–3.82**	13.01***	–3.21***	–3.90***	–2.04***	–9.75***	8.45***	–2.44***	–4.22***	–0.47	–0.62
	(0.59)	(0.16)	(0.07)	(0.25)	(1.51)	(0.58)	(0.22)	(0.09)	(0.18)	(0.81)	(0.66)	(0.17)	(0.13)	(0.46)	(2.17)
Observations	121	121	121	121	121	99	99	99	99	99	110	110	110	110	110

***, **, * denote significance at 1%, 5%, and 10% level, respectively, Robust standard errors are in parentheses.

National Development and Reform Commission of China (NDRC). 2021. “Working Guidance for Carbon Dioxide Peaking and Carbon Neutrality in Full and Faithful Implementation of the New Development Philosophy.” Retrieved from https://en.ndrc.gov.cn/policies/202110/t20211024_1300725.html

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