Multi-source data assessment and multi-factor analysis of urban carbon emissions: A case study of the Pearl River Basin, China

Zhang, Bin; Yin, Jian; Jiang, Hongtao; Chen, Shihui; Ding, Yi; Xia, Ruici; Wei, Danqi; Luo, Xinyuan

doi:10.1016/j.uclim.2023.101653

Cited by 16 publications

(4 citation statements)

References 85 publications

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“…In 2020, the PRB had the highest urbanization level, with a permanent population of 15,767.9 million and a GDP of CNY 122,639.4 billion, accounting for 12.10% of the national total. Its economic development level ranked second among the seven major river basins [42]. The YRB is the largest river in Asia and the third longest globally.…”

Section: Study Site and Data Sourcementioning

confidence: 99%

Spatial Correlation between the Changes in Supply and Demand for Water-Related Ecosystem Services

Jiang,

Ouyang,

Yan

2024

IJGI

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Clarifying the spatiotemporal changes in the supply and demand of water-related ecosystem services (WESs) can provide comprehensive support information for ecological governance decisions. However, the spatial mismatch between the supply and demand of WESs is often overlooked, resulting in a lack of targeted decision-making. At the grid scale, while preserving both natural and social attributes, this study quantitatively analyzed the spatiotemporal changes in the supply and demand of WESs in the Southern River Basin from 2000 to 2020. Ecological zoning was performed based on the temporal changes in WESs supply and demand. The OPGD model was used to investigate the impacts of socio-economic and natural factors on different WESs supply factors and further explore the spatial correlation of WESs supply and demand changes in different zones. The results show that there is significant spatial heterogeneity in the changes in WESs supply and demand. Economic belts and megacities have experienced remarkable changes, with WESs supply decreasing and WESs demand increasing. WESs demand changes significantly affect WESs supply changes. The supply of WESs in all zones is influenced by WESs demand. In the high supply–low demand zone, WY has the highest explanatory power for WESs demand changes. From the high supply–middle demand zone to the low supply–middle demand zone and then to the high supply–high demand zone, the explanatory power of PE for WESs demand changes gradually increases. As WESs demand starts from the middle level, HAI gradually dominates WESs demand changes. The increase in land use changes may promote the impact of WESs demand changes on WESs supply changes. This study contributes to incorporating the supply and demand changes of WESs and their correlations into the ecological protection and restoration system, providing a new perspective and method for regional sustainable management.

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Section: Study Site and Data Sourcementioning

confidence: 99%

Spatial Correlation between the Changes in Supply and Demand for Water-Related Ecosystem Services

Jiang,

Ouyang,

Yan

2024

IJGI

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“…However, a universal empirical coefficient may not be applicable to all study regions. Additionally, this method is challenging to apply to micro-scale studies at the city level and below due to constraints in data availability [23]. For example, with regard to carbon emissions from construction land, the regional energy balance tables available in the "China Energy Statistical Yearbook" only provide provincial energy consumption data.…”

Section: Introductionmentioning

confidence: 99%

Spatiotemporal Pattern and Spatial Convergence of Land Use Carbon Emission Efficiency in the Pan-Pearl River Delta: Based on the Difference in Land Use Carbon Budget

Fan,

Xia,

et al. 2024

Land

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Research on land use carbon emission efficiency (LUCEE) in the Pan-Pearl River Delta (PPRD) can aid in formulating regional differentiated carbon reduction strategies. In this work, the inversion of carbon emissions using night-time light (NTL) data and the modified Carnegie Ames Stanford Approach (CASA) model were used to measure the net carbon emissions from land use (NCELU). On this basis, the SBM-undesirable model was used to assess the LUCEE. Additionally, the exploratory spatial data analysis (ESDA), Dagum Gini coefficient, and spatial convergence model were further introduced to analyze the spatial correlation, regional differences, and convergence trend of the LUCEE. Findings indicate that: (1) The NCELU showed an increasing fluctuation. During the period of 2006–2020, the NCELU increased from −168.58 million tons to −724.65 million tons. (2) The LUCEE exhibited a three-phase fluctuating downward trend of “decrease–rise–decrease”. The LUCEE first decreased from 0.612 in 2006 to 0.544 in 2008, then gradually increased to 0.632 in 2016, and finally decreased to 0.488 in 2020. Spatially, the LUCEE manifested a distribution characteristic of “high in the north and south, low in the middle”, with distinct spatial clustering features. (3) The overall Gini coefficient in the study period increased from 0.1819 to 0.2461. The primary contributor to the overall difference over the entire sample period was hypervariable density. (4) The PPRD and its various subregions displayed significant features of absolute and conditional β convergence. The speed of regional convergence from fastest to slowest was central > west > east, with the absolute convergence speeds of 0.0505, 0.0360, and 0.0212, respectively. Finally, policy recommendations are proposed to achieve regional carbon neutrality for the PPRD.

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“…Multi-source data refer to the combination of two or more distinct data sources, aimed at integrating the advantages of different data sources. Previous research has recognized the importance of utilizing multi-source data, especially big data, in monitoring and understanding various societal trends and issues [24,[28][29][30]. In the context of the SDGs, multi-source data can provide valuable insights into the awareness and priorities of both public and government stakeholders, thereby enabling policymakers to pinpoint areas in need of heightened attention and public engagement [4].…”

Section: Introductionmentioning

confidence: 99%

Bridging Gaps towards the 2030 Agenda: A Data-Driven Comparative Analysis of Government and Public Engagement in China towards Achieving Sustainable Development Goals

Fu,

Dávid

et al. 2024

Land

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The United Nations’ 17 Sustainable Development Goals (SDGs) provide a pivotal framework to guide government policies and mobilize public engagement for sustainability, although further exploration is still needed to analyze the attention given to the SDGs by these stakeholders using multi-source data. To comparatively analyze government and public engagement in the SDGs, based on a case study in China, this study employed a multi-source data and content analysis to assess the perceived importance and performance of the two stakeholders. Then, this study performed an importance–performance analysis (IPA) to assess the SDGs’ priority for further improvement. The results highlight the government’s emphasis on SDG 7, SDG 2, and SDG 9, contrasting with public attention predominantly on SDG 8, SDG 9, and SDG 4. Regarding the performance of the SDGs in China, the greatest achievements have been exhibited for SDG 4 and SDG 1, while SDG 10, SDG 15, and SDG 17 have shown the least progress. Concerning the individual indicators, 12 out of 98 have attained 100% completion, while 19 out of 98 remain below the 50% threshold. According to the IPA results, China should concentrate on SDG 10 and SDG 15 and improve SDGs 6, 7, 14, 16, and 17 as a relatively low priority. The stakeholder analysis indicated that these SDGs are neglected zones by both the public and government. This research innovatively assessed the priorities of SDGs and could strengthen the cooperation between the government and the public to drive the implementation of the Sustainable Development Goals more effectively. This study could contribute to guiding policy directions, inform strategies for public engagement, and enhance the comprehension of sustainable development in China. The framework could serve as a valuable reference for stakeholder engagement in the SDGs in other countries.

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Multi-source data assessment and multi-factor analysis of urban carbon emissions: A case study of the Pearl River Basin, China

Cited by 16 publications

References 85 publications

Spatial Correlation between the Changes in Supply and Demand for Water-Related Ecosystem Services

Spatial Correlation between the Changes in Supply and Demand for Water-Related Ecosystem Services

Spatiotemporal Pattern and Spatial Convergence of Land Use Carbon Emission Efficiency in the Pan-Pearl River Delta: Based on the Difference in Land Use Carbon Budget

Bridging Gaps towards the 2030 Agenda: A Data-Driven Comparative Analysis of Government and Public Engagement in China towards Achieving Sustainable Development Goals

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