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Spatial correlation network characteristics and drivers of carbon reduction-construction waste control-green expansion-economic growth synergy effect in construction industry
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Zhen-shuang WANG1, Yu-fei WANG1, Tao WANG2, *, Ning ZHAO3
China Environmental Science | 2025, 45(7) : 4064 - 4079
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China Environmental Science | 2025, 45(7): 4064-4079
• Carbon Emission Control •
Spatial correlation network characteristics and drivers of carbon reduction-construction waste control-green expansion-economic growth synergy effect in construction industry
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Zhen-shuang WANG1, Yu-fei WANG1, Tao WANG2, *, Ning ZHAO3
Affiliations
  • 1.School of Investment and Construction Management, Dongbei University of Finance and Economics, Dalian 116025, China
  • 2.School of Public Policy and Administration, Chongqing University, Chongqing 400044, China
  • 3.School of Finance, Dongbei University of Finance and Economics, Dalian 116025, China
Published: 2025-07-20
Outline
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The research explored the evolution trend, spatial correlation network characteristics and driving mechanism of the synergistic effects on carbon reduction, construction waste control, green expansion, and economic growth among different provinces in construction industry from 2010 to 2020 by entropy method, coupling coordination degree model, social network analysis method, and exponential random graph model. The results showed that: The synergistic effect of carbon reduction, construction waste control, green expansion, and economic growth in the construction industry increased from 0.51 to 0.60, gradually transitioning from a barely imbalanced state to a primary coordinated state, with significant spatial heterogeneity. The synergistic effect spatial correlation network presented a "Core-edge" distribution characteristic, and the network density showed an increasing trend, reaching 0.2287 in 2020. The network's dependence on the core region was weak, but the network state had not yet reached optimal state, and there was still significant for improvement, such as Henan, Hunan, Shaanxi, and Xinjiang were in a dominant position in the internet and had apparent "Matthew effect". Hebei, Anhui, Jiangxi, and Henan provinces had shown significant "Siphon effect". Heilongjiang, Jilin, Liaoning and other provinces played the role of peripheral actors in the network. Most of the spatial correlations of the synergistic effects of carbon reduction, construction waste control, green expansion, and economic growth in the construction industry were concentrated within blocks rather than between blocks. The developed eastern region was mainly the "Net profit" block, while the central and western regions were the "Two-way spillover" blocks. Hunan, Shaanxi, Hubei and other provinces occupied the network structure holes position and had obvious advantages in the construction of synergistic effects. The significant driving force of endogenous network structure was the formation process of the synergistic effect network. The factor of the proportion of construction industry output value/GDP strengthened the spatial correlation between the synergistic effects. The proximity of geographical locations helped to promote the formation of a basin collaborative governance network. Thus, targeted policies for carbon reduction, construction waste control, green expansion, and economic growth in the construction industry should be formulated based on the characteristics of different regions to promote high-quality development of the regional construction industry.

construction industry  /  synergy effect  /  coupling coordination degree model  /  entropy method  /  social network  /  exponential random graph model
汪振双, 王宇飞, 汪涛, 赵宁. 建筑业降碳-减污-扩绿-增长协同效应空间关联网络特征及驱动机制. 中国环境科学, 2025 , 45 (7) : 4064 -4079 .
Zhen-shuang WANG, Yu-fei WANG, Tao WANG, Ning ZHAO. Spatial correlation network characteristics and drivers of carbon reduction-construction waste control-green expansion-economic growth synergy effect in construction industry[J]. China Environmental Science, 2025 , 45 (7) : 4064 -4079 .
Year 2025 volume 45 Issue 7
81
16
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Article Info
  • Receive Date:2024-12-12
  • Online Date:2026-10-08
  • Published:2025-07-20
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  • Received:2024-12-12
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Affiliations
    1.School of Investment and Construction Management, Dongbei University of Finance and Economics, Dalian 116025, China
    2.School of Public Policy and Administration, Chongqing University, Chongqing 400044, China
    3.School of Finance, Dongbei University of Finance and Economics, Dalian 116025, China
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表12种不同金属材料的力学参数
科
Family
属数
Number of
genus
种数
Number of
species
占总种数比例
Percentage of
total species (%)
属
Genus
种数
Number of
species
占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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