中国低碳试点城市碳排放效率时空演变与影响因素

doi:10.31497/zrzyxb.20220511

Abstract

Abstract:

China puts forward the strategic goal of achieving carbon peaks by 2030 and carbon neutrality by 2060. Improving carbon emission efficiency and promoting green and low-carbon development are important ways to achieve the "dual carbon" goal. The study uses the Super-SBM model that includes undesired output to measure the carbon emission efficiency of 68 low carbon cities in China from 2003 to 2018 and analyzes their spatio-temporal evolution characteristics. The panel regression model is used to analyze the influencing factors of urban carbon emission efficiency. The following conclusions are drawn: (1) The carbon emission efficiency of low carbon city has shown an overall upward trend over time, from 0.169 to 0.423, with an average annual growth rate of 6.31%, and there is still room for improvement. (2) Regional differences in the carbon emission efficiency of low carbon cities show a trend of shrinking first and then gradually expanding, and a declining distribution pattern of "from eastern to central and western region" in space; the carbon emission efficiency of pilot city at various levels is characterized as "megacity > supercity > large city > medium-sized city > small city". (3) Economic development level, industrial structure, urbanization level, green technology innovation and carbon emission efficiency of a pilot city are significantly positively correlated, and the intensity of foreign investment has restrictions on urban carbon emission efficiency. There are some differences in the degree of influence of each factor on the three regions and cities of different sizes. The paper puts forward countermeasures and suggestions from the aspects of innovation input, industrial structure and regional differentiation, which has certain reference significance for promoting urban green and low-carbon development and the construction of ecological civilization.

Key words: low carbon city, carbon emission efficiency, Super-SBM model, China

XU Ying-qi, CHENG Yu, WANG Jing-jing, LIU Na. Spatio-temporal evolution and influencing factors of carbon emission efficiency in low carbon city of China[J].JOURNAL OF NATURAL RESOURCES, 2022, 37(5): 1261-1276.

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指标	一级指标	二级指标	单位
投入指标	资本要素	固定资本存量	10⁸元
	劳动要素	从业人员	10⁴人
	能源要素	全年用电总量	10⁴ kW·h
产出指标	期望产出	GDP	10⁸元
产出指标	非期望产出	CO₂排放	10⁴ t

指标属性	指标名称	指标解释
被解释变量	碳排放效率（CE）	碳排放效率值
解释变量	经济发展水平（ED）	人均GDP
	产业结构（IS）	第二产业增加值/GDP
	城市化水平（UR）	非农业人口/总人口
	绿色技术创新（GTI）	绿色发明专利+实用新型专利授权数
	外资强度（FDI）	当年实际使用外资金额/GDP
	土地集约利用（LU）	第二、三产业增加值/市域面积

年份	变异系数	基尼系数	泰尔指数
2003	0.354	0.195	0.027
2008	0.298	0.159	0.019
2010	0.273	0.143	0.016
2013	0.281	0.151	0.017
2018	0.425	0.210	0.030

变量名	单位	最小值	最大值	均值	标准差
CE	—	0.0579	1.0018	0.3284	0.1392
ED	元	3127	467749	48293	36854
IS	%	13.13	84.39	48.352	9.763
UR	%	13.9185	100	54.7415	20.1995
GTI	件	0	13337	510.5083	1243.912
FDI	万美元/万元	3×10^-5	0.0454	0.0054	0.0047
LU	亿元/km²	0.0763	745.3947	31.6499	67.3002

变量值	LLC统计量	P值	ADF统计量	结论
CE	-2.7012	0.0035	5.9088	平稳
ED	-1.6851	0.0460	4.8104	平稳
IS	-10.6202	0.0000	15.3946	平稳
UR	-8.5694	0.0000	8.5348	平稳
GTI	-5.0725	0.0000	13.6172	平稳
FDI	-5.8731	0.0000	14.9819	平稳
LU	-9.4544	0.0000	11.5299	平稳

Spatio-temporal evolution and influencing factors of carbon emission efficiency in low carbon city of China

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变量	随机效应模型	个体固定效应模型	时刻固定效应模型	双向固定效应模型
ED	0.0182^***	0.0181^***	0.0133^***	0.0126^***
ED	(16.48)	(16.90)	(9.59)	(8.67)
IS	0.0427^***	0.0515^***	0.0108^***	0.0117^***
IS	(11.54)	(13.60)	(3.68)	(3.89)
UR	0.0722^***	0.0839^***	-0.0661^***	-0.0717^***
UR	(9.50)	(11.29)	(-7.97)	(-7.81)
GTI	0.0022^***	0.0022^***	0.0015^***	0.0015^***
GTI	(7.90)	(8.09)	(5.04)	(4.75)
FDI	-0.1938^***	-0.1944^***	-0.0587^***	-0.1245^***
FDI	(-7.09)	(-7.00)	(-2.62)	(-5.13)
LU	0.0365^***	0.0527^***	0.0307^***	0.0274^***
LU	(5.25)	(7.35)	(5.42)	(4.81)
Cons	-0.3699^***	-0.4102^***	0.0187	-0.0866
Cons	(-5.52)	(-6.01)	(0.36)	(-1.52)
城市固定	—	是	否	是
年份固定	—	否	是	是
R²	0.7286	0.7309	0.3350	0.6418
F统计量	—	32.83	24.99	2.13

变量	东部试点城市			中部试点城市			西部试点城市
变量	Re	Fe	Fe-tw	Re	Fe	Fe-tw	Re	Fe	Fe-tw
ED	0.0107^***	0.0101^***	0.0108^***	0.0513^***	0.0492^***	0.0556^***	0.0285^***	0.0278^***	0.0030
ED	(8.17)	(7.72)	(6.26)	(14.44)	(13.41)	(10.96)	(8.65)	(9.18)	(0.47)
IS	0.0253^***	0.0389^***	0.0148^***	0.0397^***	0.0415^***	0.0002	0.0506^***	0.0609^***	0.0105^*
IS	(4.19)	(5.48)	(2.94)	(6.28)	(6.49)	(0.02)	(9.10)	(11.83)	(1.80)
UR	0.0443^***	0.0608^***	-0.0439^***	-0.0090	-0.0057	-0.0818^***	0.0655^***	0.0890^***	-0.0976^***
UR	(3.53)	(4.67)	(-3.11)	(-0.74)	(-0.46)	(-3.22)	(4.51)	(6.77)	(-4.65)
GTI	0.0020^***	0.0022^***	0.0015^***	0.0009	0.0009	0.0051^**	0.0041^**	0.0021	0.0096^***
GTI	(6.88)	(7.48)	(4.57)	(0.87)	(0.93)	(2.43)	(2.47)	(1.40)	(3.92)
FDI	-0.3434^***	-0.3446^***	-0.2040^***	-0.2019^***	-0.2308^***	0.0286	-0.0635	-0.0252	-0.2124^***
FDI	(-8.04)	(-7.08)	(-5.40)	(-3.52)	(-3.92)	(0.40)	(-1.56)	(-0.70)	(-3.48)
LU	0.0424^***	0.0598^***	0.0215^***	-0.2242^***	-0.1852^***	-0.4678^***	-0.0114	0.1533	-0.1908
LU	(6.13)	(7.83)	(3.65)	(-3.35)	(-2.61)	(-7.91)	(-0.09)	(1.24)	(-1.48)
Cons	-0.6180^***	-0.6832^***	-0.2850^***	-0.4571^***	-0.5218^***	0.1510	-0.1848^*	-0.1374	-0.2604^*
Cons	(-5.82)	(-5.49)	(-3.18)	(-3.67)	(-4.13)	(0.86)	(-1.85)	(-1.56)	(-1.79)
城市固定	—	是	是	—	是	是	—	是	是
年份固定	—	否	是	—	否	是	—	否	是
R²	0.7259	0.7303	0.6955	0.8699	0.8702	0.7310	0.7575	0.7650	0.5723
F统计量	—	15.73	1.15	—	40.33	1.49	—	51.93	1.19

变量	东部试点城市	中部试点城市	西部试点城市
ED	0.0122^***	0.0562^***	0.0188^***
ED	(3.09)	(11.68)	(4.50)
IS	0.0103^*	0.0158^*	0.0061
IS	(1.95)	(1.92)	(1.23)
UR	0.0055	-0.0509^**	-0.0792^***
UR	(0.26)	(-2.50)	(-3.91)
GTI	0.0011^**	0.0004	0.0177^***
GTI	(2.25)	(0.25)	(5.29)
FDI	-0.3138^***	-0.0088	-0.2673^***
FDI	(-8.03)	(-0.11)	(-4.60)
LU	0.0229^**	-0.3059^***	-0.4229^***
LU	(2.22)	(-7.23)	(-3.11)

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[2]	WANG Zi-yu, WANG De-gen, ZHU Mei. Spatial differentiation and formation mechanism of China's 20th-century architectural heritages [J]. JOURNAL OF NATURAL RESOURCES, 2022, 37(3): 784-802.
[3]	WANG Ting, LI Shuang-shuang, YAN Jun-ping, HE Jin-ping. Spatio-temporal variation of summer precipitation in China based on ENSO development process [J]. JOURNAL OF NATURAL RESOURCES, 2022, 37(3): 803-815.
[4]	SUN Cai-zhi, WEI Ya-qiong, ZHAO liang-shi. Co-evolution of water-energy-food nexus in arid areas: Take Northwest China as an example [J]. JOURNAL OF NATURAL RESOURCES, 2022, 37(2): 320-333.
[5]	ZHANG Yu, WANG Jie-yong, LIU Yan-sui. The potentiality and model of China's hollowing village reclamation based on Meta-analysis [J]. JOURNAL OF NATURAL RESOURCES, 2022, 37(1): 110-120.
[6]	WU Ying-di, MENG Ji-jun. Quantifying the spatial pattern for the importance of natural resource ecosystem services in China [J]. JOURNAL OF NATURAL RESOURCES, 2022, 37(1): 17-33.
[7]	CHEN Xiao-lin, TAN Xiao-yue, LI Lu-ning, CHEN Jin, LI Qiang. The association between high-yield and stable-yield characteristics of winter wheat and its influencing factors in the main producing areas in Northern China [J]. JOURNAL OF NATURAL RESOURCES, 2022, 37(1): 263-276.
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变量	超大、特大城市		大城市		中小城市
变量	Re	Fe-tw	Re	Fe-tw	Re	Fe-tw
ED	0.0061^***	0.0044	0.0346^***	0.0399^***	0.0270^***	0.0088^**
ED	(3.42)	(1.35)	(6.90)	(6.50)	(11.45)	(2.41)
IS	0.0359^**	-0.0415^**	0.0455^***	0.0003	0.0462^***	0.0097^**
IS	(2.29)	(-2.62)	(3.17)	(0.02)	(11.27)	(2.36)
UR	0.0846^**	0.1014^**	0.0593^***	-0.0212	0.0483^***	-0.0605^***
UR	(2.48)	(2.35)	(2.68)	(-0.80)	(5.19)	(-3.76)
GTI	0.0028^***	0.0000	0.0020^*	-0.0034	0.0039	0.0184^***
GTI	(7.14)	(0.00)	(1.91)	(-1.21)	(1.38)	(4.25)
FDI	-0.5164^***	0.3635^*	-0.2769^***	-0.1162	-0.0996^**	-0.1303^***
FDI	(-4.54)	(1.84)	(-3.23)	(-1.21)	(-2.95)	(-3.88)
LU	0.0500^***	0.0442^***	-0.1126	-0.2887^***	-0.0056	-0.0947^**
LU	(6.23)	(4.77)	(-1.29)	(-2.77)	(-0.13)	(-2.25)
Cons	-1.0921^***	1.4816^***	-0.5999^***	0.0392	-0.1870^**	-0.0842
Cons	(-3.66)	(2.87)	(-2.86)	(0.14)	(-2.36)	(-1.14)
城市固定	—	是	—	是	—	是
年份固定	—	是	—	是	—	是
R²	0.8276	0.8665	0.8408	0.8706	0.7248	0.4968
F统计量	—	1.31	—	2.09	—	1.28