中国省域制造业碳排放时空交互特征及影响因素研究

doi:10.3969/j.issn.1004-9479.2025.08.20230785

摘要/Abstract

摘要：

制造业作为现代产业体系的核心，已成为拉动国民经济增长的重要动力。基于2005—2019年中国30个省（市）面板数据，运用探索性时空数据分析、空间杜宾模型等方法，探究中国省域制造业碳排放的时空演化特征及影响因素，结果表明：①2005—2019年，中国制造业碳排放量呈现先上升后下降的趋势，制造业碳排放量空间集聚与分异特征明显，呈现由东南向西北逐渐递减的分布格局。②在制造业碳排放的空间结构与依赖方向上，东北地区制造业碳排放空间结构的动态性较强，但空间依赖方向并不稳定；西部地区制造业碳排放的空间结构和空间依赖方向都比较稳定。制造业碳排放时空跃迁具有一定的空间依赖性和转移惰性，其时空网络格局以正向关联为主，大部分省份间存在合作共赢关系。③能源结构、城镇化率、制造业总产值、经济规模对制造业碳排放量产生显著的正向影响，而外商直接投资占GDP的比重对制造业碳排放量产生显著负向影响。各影响因素对不同跃迁类型的省份、不同行业的制造业碳排放量存在一定异质性，相较于低碳行业和III型省份，高碳行业和I、II型省份的制造业碳排放量影响更为显著。研究从发挥区域优势，加强协同合作等方面为制造业转型升级和碳减排提供对策建议。

关键词: 制造业碳排放, 时空交互特征, 探索性时空数据分析, 影响因素

Abstract:

As the core of modern industrial system, manufacturing industry is an important driving force for national economic growth. Based on the panel data of 30 provinces (municipalities) in China from 2005 to 2019, this study uses exploratory spatio-temporal data Analysis, spatial Durbin model and other methods to explore the spatio-temporal evolution characteristics and influencing factors of carbon emissions in China's provincial manufacturing industry. The results show that ① From 2005 to 2019， manufacturing carbon emissions showed a trend of first increasing and then decreasing， and the spatial agglomeration and differentiation of manufacturing carbon emissions were obvious， showing a gradually decreasing distribution pattern from southeast to northwest.② In terms of the spatial structure and dependence direction of manufacturing carbon emissions， the spatial structure of manufacturing carbon emissions in northeast China is more dynamic， but the spatial dependence direction is not stable， while the spatial structure and dependence direction of manufacturing carbon emissions in western China are relatively stable. The spatio-temporal transition of carbon emissions in manufacturing industry has certain spatial dependence and transfer inertia， and its spatio-temporal network pattern is mainly positive correlation， and most provinces have win-win cooperation.③The proportion of coal consumption in total energy， urbanization rate， total output value of manufacturing industry and per capita GDP have significant positive effects on manufacturing carbon emissions， while the proportion of foreign direct investment in GDP has significant negative effects on manufacturing carbon emissions. Various influencing factors have a certain heterogeneity in manufacturing carbon emissions in different provinces and industries with different transition types. Compared with low-carbon industries and type III provinces, high-carbon industries and manufacturing industries in type I and II provinces have a more significant impact on carbon emissions.The study provides countermeasures and suggestions for the transformation and upgrading of manufacturing industry and carbon emission reduction from the aspects of giving full play to regional advantages and strengthening collaborative cooperation.

Key words: manufacturing carbon emissions, spatio-temporal interaction feature, exploratory spatio-temporal data analysis, influence factor

王丹, 程钰, 赵鸿潇. 中国省域制造业碳排放时空交互特征及影响因素研究[J]. 世界地理研究, 2025, 34(8): 139-156.

Dan WANG, Yu CHENG, Hongxiao ZHAO. Spatial and temporal interaction characteristics and influencing factors of carbon emissions from manufacturing industries in China[J]. World Regional Studies, 2025, 34(8): 139-156.

图/表 14

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类型	状态
类型Ⅰ	本省和相邻省均无跃迁（HH→HH LH→LH LL→LL HL→HL）
类型Ⅱ	仅本省发生跃迁（LH→HH HH→LH HL→LL LL→HL）
类型Ⅲ	仅相邻省发生跃迁（HL→HH LL→LH LH→LL HH→HL）
类型Ⅳ	本省和相邻省都有跃迁（LL→HH HL→LH HH→LL LH→HL）

类型	状态
类型Ⅰ	本省和相邻省均无跃迁（HH→HH LH→LH LL→LL HL→HL）
类型Ⅱ	仅本省发生跃迁（LH→HH HH→LH HL→LL LL→HL）
类型Ⅲ	仅相邻省发生跃迁（HL→HH LL→LH LH→LL HH→HL）
类型Ⅳ	本省和相邻省都有跃迁（LL→HH HL→LH HH→LL LH→HL）

变量	样本量	平均值	标准差	最小值	最大值
CE	450	93.124	75.163	3.708	478.672
EST	450	0.680	0.294	0.018	1.758
MS	450	2 500 000	3 170 000	1 371.480	18 119 615
UR	450	0.544	0.141	0.269	0.938
FDI	450	0.024	0.021	0	0.121
MP	450	23 892.898	29 452.832	239.840	165 000
ES	450	40 423.892	26 187.983	5 218	161 776

变量	样本量	平均值	标准差	最小值	最大值
CE	450	93.124	75.163	3.708	478.672
EST	450	0.680	0.294	0.018	1.758
MS	450	2 500 000	3 170 000	1 371.480	18 119 615
UR	450	0.544	0.141	0.269	0.938
FDI	450	0.024	0.021	0	0.121
MP	450	23 892.898	29 452.832	239.840	165 000
ES	450	40 423.892	26 187.983	5 218	161 776

时段	t/t+1	HH	LH	LL	HL	SF	SC
2005—2012年	HH	I(鲁晋苏冀豫辽)	II(浙)	IV	III	0.166 7	0.833 3
	LH	II	I(沪蒙吉皖赣琼陕)	III(闽)	IV
	LL	IV	III(云贵渝)	I(京津宁桂新甘青黑)	II
	HL	III	IV	II	I(川粤鄂湘)
2012—2019年	HH	I(鲁晋苏冀豫辽)	II	IV	III	0.233 3	0.766 7
	LH	II(蒙)	I(沪吉皖浙琼贵)	III(云赣渝陕)	IV
	LL	IV	III	I(京津宁新甘闽青黑)	II(桂)
	HL	III	IV	II(湘)	I(鄂川粤)
2005—2019年	HH	I(鲁晋苏冀豫辽)	II(浙)	IV	III	0.266 7	0.733 3
	LH	II(蒙)	I(沪吉皖琼)	III(赣闽陕)	IV
	LL	IV	III(贵)	I(云京津宁新甘渝青黑)	II(桂)
	HL	III	IV	II(湘)	I(川粤鄂)