中国人类福祉变化的驱动效应及时空分异

doi:10.18306/dlkxjz.2016.05.010

摘要/Abstract

摘要：

为建立碳排放敏感性人类福祉指数(HWI),运用LMDI方法对全国、区域及省区层面人类福祉变化的驱动效应及其时空分异进行分析,并得出以下结论：①改革开放30多年来,中国人类福祉水平不断提高,正向世界高人类福祉水平推进,但2005年以后人类福祉提升所付出的生态环境代价越来越大;②在1980-2010年期间的中国人类福祉提升中,2000年以前由经济效应和技术进步效应共同驱动,2000年以后则以经济效应驱动为主;③经济增长、技术进步和生态效率等因素共同影响中国区域人类福祉演变趋势。其中,经济增长和技术进步是主要驱动力,而生态效率效应则是主要的抑制力;从四大区域来看,提高技术进步和经济效率是东部地区提升人类福祉最主要的驱动因素,经济增长是中部、西部、东北地区提升人类福祉的核心驱动力;④中国人类福祉变化驱动效应可归纳为4种区域模式。其中,上海是技术效应为主的驱动模式,江西、湖南、四川、甘肃是经济效应为主的驱动模式,北京是“生态效率效应+技术效应”组合驱动模式,其他省区主要是“经济效应+技术效应”组合驱动模式;⑤中国应实施兼顾降低碳排放和提高人类福祉的低碳人文发展战略,着力扭转生态效率因素的减量效应;逐步改变经济效应为主推动人类福祉提升的驱动模式,构建人类福祉可持续提升的多元驱动模式。

关键词: 人类福祉, 碳排放, 区域差异, 驱动效应, 时空分异

Abstract:

By incorporating per capita carbon emission factor into human development index (HDI), this study proposed a carbon emission sensitive human well-being index (HWI) framework. By using this framework, we performed quantitative evaluations of change and regional patterns of human well-being in China from 1980 to 2010. The driving factors and spatiotemporal differentiation and change of human well-being were analyzed by logarithmic mean divisia index (LMDI) method. The results show that: (1) With over 30 years of reform and opening up, human well-being in China has been enormous increased and now is heading towards a high level compared to the global average. At the same time, however, carbon emission sensitive human well-being index of China presented an inverted U-shaped trend, which suggests that the environmental costs were also rising. (2) At the national level, the improvement of human well-being from 1980 to 2010 was mainly dependent on economic growth and limited by ecological efficiency. Before 2000, the change of human well-being was driven by economic growth together with technological advancement, but after 2000 the improvement was mainly dominated by the effect of economic growth. (3) Economic growth, technological advancement, and ecological efficiency were the main factors that jointly affected the change of human well-being at the regional level. Among these factors, economic growth and technological advancement were key driving forces but ecological efficiency was a main constraining force. Human well-being improvement in eastern China was mainly driven by technological advancement and economic efficiency, and in central, western, and northeastern China it was driven by the economic growth factor. (4) At the provincial level, driving factors of human well-being change can be divided into four types: in Shanghai, the change was mainly driven by technological advancement effect and in Jiangxi, Hunan, Sichuan, and Gansu it was economic growth that drove the change. In Beijing, ecological efficiency effect plus technological advancement effect led to the improvement in human well-being, and in other provinces the driving factors were economic growth and technological advancement. (5) We suggest that low-carbon human development strategy should be implemented to reverse the negative impact of low ecological efficiency. Economic development-driven human well-being improvement should be changed and more attention should be paid to advance technology development and reduce the negative effect of low ecological efficiency in China.

Key words: human well-being, carbon emission, regional disparity, driving factor, spatiotemporal differentiation

王圣云. 中国人类福祉变化的驱动效应及时空分异[J]. 地理科学进展, 2016, 35(5): 632-643.

Shengyun WANG. Driving factors and spatiotemporal differentiation of human well-being change in China[J]. PROGRESS IN GEOGRAPHY, 2016, 35(5): 632-643.

图/表 11

图1

表1

表2

图2

表3

表4

图3

表5

表6

1990-2010年中国四大区域人类福祉驱动效应动态演变"

区域	时段	$经济效应 G eff$			$技术效应 C eff$			$生态效率效应 E eff$		ΔHWI
区域	时段	效应值		贡献率/%		效应值		贡献率/%	效应值	贡献率/%
东部地区	1990-1995年	0.277	367.8		-0.119	-157.3		-0.083	-110.5	0.075
	1995-1999年	-0.085	-1688.2		0.109	2155.0		-0.019	-366.8	0.005
	1999-2005年	0.142	503.8		0.200	709.0		-0.313	-1112.7	0.028
	2005-2010年	-0.012	-24.5		0.214	422.0		-0.151	-297.5	0.051
	1990-2010年	0.334	209.8		0.378	237.6		-0.553	-347.4	0.159
东北地区	1990-1995年	0.151	378.5		-0.118	-296.0		0.007	17.6	0.040
	1995-1999年	0.057	135.2		-0.078			-185.4	0.063		150.3	0.042
	1999-2005年	0.144	552.7		0.163			626.9	-0.280		-1079.7	0.026
	2005-2010年	0.010	20.8		0.250			533.5	-0.213		-454.3	0.047
	1990-2010年	0.369	238.8	0.185		119.7	-0.399		-258.5	0.155
中部地区	1990-1995年	0.173	333.5	0.085	163.8	-0.206	-397.3	0.052
	1995-1999年	0.299	389.0	-0.374		-486.3	0.152		197.3	0.077
	1999-2005年	0.167	481.0	0.279		803.0	-0.411		-1184.0	0.035
	2005-2010年	0.022	30.4	0.169		237.0	-0.119		-167.4	0.071
	1990-2010年	0.683	291.0	0.127		54.2	-0.576		-245.2	0.235
西部地区	1990-1995年	0.085	240.2	0.043	120.9	-0.092	-261.1	0.035
	1995-1999年	0.350	356.7	-0.328		-334.1	0.076		77.3	0.098
	1999-2005年	0.176	563.2	0.293		934.0	-0.438		-1397.2	0.031
	2005-2010年	0.277	367.8	-0.119		-157.3	-0.083		-110.5	0.065
	1990-2010年	0.656	285.1	0.287	124.5	-0.713	-309.6	0.230

表6

图4

图5

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燃料品类	低位发热量/(kJ/kg)	含碳量/%	氧化率	碳排放系数
原煤	20908	25.8	1	0.5394
焦炭	28435	29.2	1	0.8303
原油	41816	20.0	1	0.8363
汽油	43070	18.9	1	0.8140
柴油	42652	20.2	1	0.8616
燃料油	41816	21.1	1	0.8823
天然气	38931^*	15.3	1	0.4478
煤油	43070	19.5	1	0.8399

国家	1980年	1990年	2000年	2005年	2010年	2013年	1980-2013年平均增长/%
挪威	0.793	0.841	0.910	0.935	0.939	0.944	19.0
美国	0.825	0.858	0.883	0.897	0.908	0.914	10.7
巴西	0.545	0.612	0.682	0.705	0.739	0.744	36.4
印度	0.369	0.431	0.483	0.527	0.570	0.586	58.9
中国	0.423	0.502	0.591	0.645	0.701	0.719	70.0

分指数	1980年	1990年	2000年	2005年	2010年	2013年	1980-2013平均增长率/%
收入指数	0.292	0.408	0.540	0.606	0.683	0.716	145.2
教育指数	0.358	0.406	0.478	0.531	0.599	0.610	70.2
健康指数	0.724	0.761	0.802	0.832	0.844	0.851	17.5

区域	1990年	1995年	1999年	2005年	2010年
东部地区	0.708	0.783	0.788	0.816	0.867
东北地区	0.686	0.726	0.768	0.794	0.840
中部地区	0.602	0.654	0.731	0.766	0.837
西部地区	0.572	0.607	0.705	0.737	0.802

	1980-1990年			1990-2000年		2000-2010年			1980-2010年
	效应值		贡献率/%		效应值	贡献率/%	效应值	贡献率/%	效应值	贡献率/%
经济效应	0.154	36.475		0.153	30.469	0.151	25.616		0.468	293.651
技术效应	0.021	4.932		0.363	72.352	-0.726	-122.817		-0.229	-143.586
生态效率效应	-0.098	-23.152		-0.022	-4.371	-0.426	-72.035		-0.503	-315.569