Research on the policy inconsistency, network motifs and low carbon effects for municipal solid waste management
In the past 30 years, China introduced 259 municipal solid waste management (MSWM) policies. However, the impacts of green network motif fluctuations on policy consistency and implementation effectiveness remain unclear. This study combines the policy consistency formula, a four-node network motif e...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2025-12-01
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| Series: | Sustainable Futures |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S266618882500629X |
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| Summary: | In the past 30 years, China introduced 259 municipal solid waste management (MSWM) policies. However, the impacts of green network motif fluctuations on policy consistency and implementation effectiveness remain unclear. This study combines the policy consistency formula, a four-node network motif evolution algorithm, and the Exponential Random Graph Model (ERGM), analyzing MSWM green network motifs with carbon emission data. Results show MSWM network motifs have evolved from sanitation - focused to resource - utilization - oriented, with methods shifting from landfill/incineration to classification/recycling. This reflects China's unique policy development towards environmental protection. Policy consistency significantly influences motif formation, with 10 motif clusters emerging from 1995 to 2024. The classification degree (ρ) and local clustering coefficient (ccl) drive green motif evolution, supported by network density, structural holes, and closeness centrality. Notably, the low - carbon effect of MSWM lacks validation, calling for stronger low - carbon policies. By integrating network science and explainable AI, the study reveals that while policy consistency weakly correlates with carbon reduction (r = 0.125, p = 0.5508), network structural features significantly affect policy outcomes. It offers strategies for enhancing carbon reduction through network optimization and phased policy design, aiding low - carbon MSWM policy improvement. |
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| ISSN: | 2666-1888 |