Evidence map›Paper›PMID 42034868›Full record

ArticleCarbon balance and management2026

Revealing the network structure characteristics and driving factors of carbon-emission spillovers in the greater bay area of China: a coupled multi-scenario analytical framework.

Zhigang Li, Jiapei Tan

Abstract read
In one paragraph

Article in Carbon balance and management, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

2 authors.

Zhigang LiSchool of Geography and Planning, Chengdu University of Technology, Sichuan, 610059, Chengdu, China.
Jiapei TanSchool of Geography and Planning, Chengdu University of Technology, Sichuan, 610059, Chengdu, China. 19924813040@163.com.

Funding

Philosophy and Social Sciences in Chengdu YJZX-2024-ZZZD-01
6 · The paper itself

Abstract

The Guangdong–Hong Kong–Macao Greater Bay Area (GBA) is a critical region for coordinated low-carbon development in China, yet the structure and drivers of intercity carbon-emission spillovers remain poorly understood, especially under alternative development pathways. In addition, the carbon consequences of land-use change have received little attention. To fill these gaps, this study develops a coupled multi-scenario analytical framework to examine the spillover structure and drivers of land-use carbon emissions (LUCE), using observational data from 2000, 2010, and 2020, together with 2030 simulations under natural development (NDS), economic development (EDS), and ecological protection (EPS) scenarios. The results show that the northeastern and southwestern GBA function as relatively stable carbon sinks, whereas the central corridor exhibits persistent emission growth. Intercity LUCE disparities are largest under EDS and shrink markedly under EPS. The LUCE network is highly connected, multilevel, and transmission-efficient, indicating a robust yet centralized spillover system. Shenzhen remains the dominant hub, and the increasing number of intermediary cities further strengthens intercity carbon flows. Driver analysis reveals that historical network linkages are significantly associated with differences in per capita GDP and geographic proximity. Under the 2030 scenarios, however, industrial structure upgrading becomes increasingly influential, highlighting a scenario-dependent shift in the key drivers of intercity spillovers. Overall, this study offers a transferable multi-scenario framework for analyzing regional LUCE spillovers and provides management-relevant evidence for coordinated mitigation, cross-jurisdictional carbon governance, and policy design in the GBA.

Indexed as

Guangdong-Hong Kong-Macao Greater Bay Area (GBA)Land-use carbon emissions (LUCE)Scenario networkSpillover structure

Identifiers

PMID42034868
PMCPMC13173777

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.