基于城镇化的中国县级城市碳排放空间分布特征及影响因素

doi:10.18306/dlkxjz.2021.12.002

Abstract

Abstract:

This study selected 1897 county-level cities in China as the research unit to examine the spatial distribution pattern of carbon emissions and the effects of population, economy, and multi-dimensional urbanization levels on carbon emissions. The data sources are CHRED-online carbon emission public database and social and economic statistics of counties and county-level cities. Spatial autocorrelation and geographic detector methods were used in the empirical research. The results show that: 1) County-level cities of China are relatively highly different in carbon emissions, and the number of areas with high carbon emissions is relatively small, but the emission value is relatively large. The carbon emissions per unit of GDP are higher than the national average. 2) The spatial distribution of total carbon emissions mainly presents a pattern of high in the east and low in the west. The high-value areas of total carbon emissions are mainly concentrated in the east, the periphery of large cities in central China, and the central and northern regions of Inner Mongolia, showing a clustered distribution structure. Per capita carbon emissions and carbon intensity show a pattern of high in the north and low in the south, mainly concentrated in the central and northern parts of Inner Mongolia and the border areas of Xinjiang and Qinghai. 3) The spatial heterogeneity of the level of economic and land urbanization has a strong explanatory power for the difference in the total carbon emissions of county-level cities, and the impact of population urbanization on the total carbon emissions is not obvious. The interaction between economic urbanization and land urbanization has the most dramatic impact on carbon emissions, and shows a nonlinear enhancement effect. 4) With regard to regional differences, the level of urbanization has the most dramatic effect on the underdeveloped areas in the west. The eastern, central, and western regions also show different spatial characteristics in terms of the explanatory power of the same indicators and the key influencing factors.

Key words: urbanization, carbon emissions, county-level cities, spatial pattern, influencing factors

WANG Rui, ZHANG He, QIANG Wenli, LI Fan, PENG Jingyi. Spatial characteristics and influencing factors of carbon emissions in county-level cities of China based on urbanization[J].PROGRESS IN GEOGRAPHY, 2021, 40(12): 1999-2010.

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References 35

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系统	变量指标	释义(单位)	均值	标准差	最小值	最大值
人口城镇化	人口规模(UP)	城镇人口数量(万人)	9.74	8.64	7.50E-3	81.92
	城镇化率(UR)	城镇人口占总人口比例(%)	20.63	14.09	0.28	99.60
	人口集中度(UPP)	县城区人口占总人口比例(%)	24.80	12.12	2.14	98.89
	人口密度(PI)	单位建设用地面积常住人口数量(万人/km²)	1.48	1.91	0.01	14.60
经济城镇化	经济总量(GDP)	县域国内生产总值数量(亿元)	159.42	161.17	2.16	3080.02
	经济结构(RSF)	二产增加值与一产增加值比值	3.98	6.15	0.07	99.69
	经济密度(PCGDP)	人均国内生产总值(万元/人)	3.63	3.68	0.55	46.16
土地城镇化	土地规模(BUA)	建设用地总规模(km²)	75.38	78.46	2.00	563.00
土地城镇化	土地集中度(PULBL)	城区建设用地占总建设用地比例(%)	15.08	19.59	2.20E-4	99.18
区域发展	经济分区(EGD)	东部地区、中部地区和西部地区	—	—	—	—
区域发展	所在市经济发展程度(REL)	县级城市所在市人均国内生产总值(万元/人)	4.14	2.41	1.01	20.56

两两交互	交互值	交互结果	两两交互	交互值	交互结果
GDP∩RSF	0.42	非线性增强	GDP∩EGD	0.28	非线性增强
PCGDP∩PULBL	0.41	非线性增强	UR∩GDP	0.27	非线性增强
GDP∩PCGDP	0.37	非线性增强	GDP∩REL	0.26	非线性增强
GDP∩PULBL	0.37	非线性增强	GDP∩BUA	0.25	非线性增强
RSF∩PCGDP	0.36	非线性增强	UP∩GDP	0.24	非线性增强
PCGDP∩REL	0.35	非线性增强	UPP∩GDP	0.24	非线性增强
UP∩PCGDP	0.34	非线性增强	UP∩UR	0.23	非线性增强
UR∩PCGDP	0.33	非线性增强	RSF∩BUA	0.21	非线性增强
PCGDP∩BUA	0.30	非线性增强	PI∩GDP	0.20	非线性增强
RSF∩REL	0.29	非线性增强	BUA∩REL	0.20	非线性增强
UPP∩PCGDP	0.28	非线性增强	PULBL∩REL	0.20	非线性增强

地区	因子探测	UP	UR	UPP	PI	GDP	RSF	PCGDP	BUA	PULBL
东部	q值	0.038	0.016	0.074	0.037	0.151	0.106	0.142	0.109	0.036
东部	P值	0.006	0.630	0.026	0.067	<0.001	<0.001	<0.001	<0.001	0.120
中部	q值	0.023	0.014	0.025	0.007	0.102	0.074	0.069	0.050	0.117
中部	P值	0.060	0.575	0.658	0.491	<0.001	<0.001	<0.001	0.005	<0.001
西部	q值	0.021	0.041	0.038	0.060	0.376	0.031	0.185	0.135	0.049
西部	P值	0.082	0.004	0.005	<0.001	<0.001	0.019	<0.001	<0.001	0.005

Spatial characteristics and influencing factors of carbon emissions in county-level cities of China based on urbanization

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