中国家庭消费间接碳排放空间关联结构演变——基于社会网络分析法

doi:10.12118/j.issn.1000-6060.2024.035

摘要/Abstract

摘要： 把握家庭消费间接碳排放的空间聚类及结构特征对于中国在新发展格局下实现“双碳”目标具有重要意义。在测算出中国家庭消费间接碳排放量的基础上，运用社会网络分析法探究2013—2022年中国家庭消费间接碳排放空间关联网络结构特征。结果表明：（1）家庭消费间接碳排放量整体呈上升趋势，10 a间增长了1.2倍；其中“食品”“居住”“交通通信”和“教育文化娱乐”为主构成部分，占总量的75%。（2）整体网络特征：以江苏、北京、浙江、上海等省市为中心，呈“核心-边缘”分布趋势。其中，网络密度和关联数有所下降，等级梯度和关联密度有所上升。（3）块模型特征：按照节点溢出和接收效应划分为四大板块，即“净溢出”“净受益”“经纪人”和“双向溢出”，各板块在空间关联领域中扮演不同角色。（4）个体网络特征：上海、江苏、浙江等省市中心度最高位于关联网络的核心区域，空间关联性影响显著，具有向外辐射的特点，而青海、黑龙江等省份处于关联网络边缘区域，关联效应较弱。

关键词: 家庭消费间接碳排放, 空间关联网络, 社会网络分析, 引力模型

Abstract:

Understanding the spatial clustering and structural characteristics of indirect carbon emissions from household consumption is crucial for China to achieve the “carbon peaking and carbon neutrality” goal under its new development framework. This study calculates indirect carbon emissions from household consumption in China and examines the structural characteristics of the spatial correlation network for these emissions from 2013 to 2022 using social network analysis. The findings reveal the following: (1) Indirect carbon emissions from household consumption exhibit an overall upward trend, increasing 1.2-fold over ten years. Emissions from “food”, “housing”, “transport and communication”, and “education, culture, and entertainment” constitute 75% of the total. (2) Overall network characteristics: The overall network structure, centered on provinces and cities such as Jiangsu Province, Beijing City, Zhejiang Province, and Shanghai City, demonstrates a “core-edge” distribution pattern. Network density and the number of associations have declined, while grade gradient and association intensity have increased. (3) Characteristics of the block model: Regional network characteristics, based on node spillover and reception effects, are categorized into four segments: “net spillover”, “net benefit”, “broker”, and “two-way spillover”, and each segment plays different roles in the field of spatial correlation. (4) Individual network characteristics: Regarding individual network characteristics, provinces such as Shanghai City, Jiangsu Province, and Zhejiang Province, with the highest degree of centrality, occupy the core areas of the correlation network and exhibit significant spatial correlation and outward radiation effects. In contrast, provinces such as Qinghai Province and Heilongjiang Province, located on the periphery, exhibit weaker correlation effects.

Key words: indirect carbon emissions from household consumption, spatially associative networks, social network analysis, gravitational model

付伟, 巩海秀, 陈建成. 中国家庭消费间接碳排放空间关联结构演变——基于社会网络分析法[J]. 干旱区地理, 2025, 48(1): 119-129.

FU Wei, GONG Haixiu, CHEN Jiancheng. Evolution of spatial correlation structure of indirect carbon emissions from household consumption in China: Based on social network analysis[J]. Arid Land Geography, 2025, 48(1): 119-129.

图/表 11

表1

图1

表2

网络整体结构与个体结构特征指标"

整体网络结构	公式	个体网络结构	公式
网络密度（T）	$T = R / N N - 1$	点度中心度（C_RD）	$C R D = N / N - 1$
网络等级度（H）	$H = 1 - K / K m a x$	中介中心度（C_RB）	$C R B = 2 ∑ j = 1 N ∑ k = 1 N b j k i / N 2 - 3 N + 2$
网络效率（T）	$T = 1 - M / M m a x$	接近中心度（C_AP）	$C A P = ∑ j = 1 n d i j / N - 1$

表2

表3

块模型中的经济增长板块分类"

位置内部的关系比例	位置接受到的关系比例
位置内部的关系比例	$≈ 0$	$0$
$≥ (s k - 1 / (s - 1$	双向溢出板块	净受益板块
$(s k - 1 / (s - 1$	净溢出板块	经纪人板块

表3

图2

图3

图4

图5

表4

图6

表5

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消费性支出项目	涉及内容	间接碳排放系数/kg CO₂·元^-1
食品	农林牧渔产品及服务；食品和烟草	0.049
衣着	纺织品；纺织服装鞋帽皮革羽绒及其制品	0.076
居住	非金属矿物制品；金属制品；电力、热力、燃气和水生产和供应；建筑	0.210
生活用品及服务	木材加工品和家具；电气机械和器材	0.068
交通通信	通信设备、计算机和其他电子设备；交通运输、仓储和邮政	0.198
教育文化娱乐	造纸印刷和文教体育用品	0.144
医疗保健	医药制品	0.117
其他用品及服务	批发和零售；住宿和餐饮	0.234

板块	接收关系		发出关系		期望内部关系比例/%	实际内部关系比例/%	板块属性
板块	板块内	板块外	板块内	板块外	期望内部关系比例/%	实际内部关系比例/%	板块属性
第一板块	6	98	6	16	10.00	27.27	净受益
第二板块	16	20	16	115	60.00	12.21	净溢出
第三板块	5	11	5	15	13.33	25.00	经纪人
第四板块	2	37	2	20	6.67	9.09	双向溢出

省市	点出度	点入度	点度中心度	中介中心度	接近中心度
江苏	27	27	90.00	63.30	90.91
上海	27	27	90.00	58.24	90.91
北京	25	25	83.33	74.74	85.71
浙江	25	25	83.33	44.90	85.71
广东	18	18	60.00	14.47	71.43
福建	17	17	56.67	16.32	68.18
甘肃	12	12	40.00	3.85	62.50
湖北	12	12	40.00	3.45	62.50
重庆	10	10	33.33	1.59	60.00
河南	10	10	33.33	2.39	60.00
山东	10	10	33.33	8.04	60.00
湖南	10	10	33.33	1.02	60.00
四川	9	9	30.00	0.91	58.82
广西	9	9	30.00	0.91	58.82
贵州	9	9	30.00	0.91	58.82
陕西	8	8	26.67	2.47	57.69
河北	7	7	23.33	3.59	56.60
云南	7	7	23.33	0.56	56.60
青海	7	7	23.33	0.56	56.60
宁夏	6	6	20.00	0.37	55.56
黑龙江	6	6	20.00	0.27	55.56
新疆	6	6	20.00	0.37	55.56
海南	6	6	20.00	0.37	55.56
西藏	6	6	20.00	0.37	55.56
山西	5	5	16.67	0.58	54.55
吉林	5	5	16.67	0.13	54.55
安徽	5	5	16.67	0.37	54.55
内蒙古	5	5	16.67	0.29	53.57
辽宁	4	4	13.33	0.13	53.57
江西	4	4	13.33	0.12	53.57
天津	3	3	10.00	0.00	50.85
均值	10	10	34.41	9.86	61.77