Abstract
Carbon prediction on the township level is usually difficult due to a lack of necessary information. To fulfil the research gap, the study focused on a town located in a nearshore island (Lingshan) in China. A questionnaire survey was performed to collect essential information about the future development of the town, followed by validating interviews with the island management committee. The carbon prediction of the town was established by the Low Emissions Analysis Platform (LEAP) model. The baseline scenario reflecting the existing method of carbon management was compared with an alternative low-carbon scenario. The prediction from 2020 to 2060 covers the periods of the planned carbon emissions peak in 2030 and carbon neutrality in 2060. It is found that energy-related activities and electricity consumption are the primary contributors to carbon emissions on the island. The carbon emission of Lingshan Island increases from −1333 tCO2e in 2020 to 2744 tCO2e in 2060, and the carbon peak target cannot be achieved in the baseline scenario. However, the carbon emission of the low-carbon scenario is predicted to have a peak of −850 tCO2e in 2029. The prediction model developed in this study, along with the proposed policy recommendations, can be applied to other towns or regions where data availability is limited to promote carbon reduction.
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Abbreviations
- DCGs:
-
Dual-carbon goals
- GHGs:
-
Greenhouse gases
- LCA:
-
Life cycle assessment
- LMDI:
-
Logarithmic Mean Divisia Index
- LEAP:
-
Low Emissions Analysis Platform
- LPG:
-
Liquefied petroleum gas
- tCO2e:
-
Tons of carbon dioxide equivalent
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Funding
This study is funded by the Natural Science Foundation of Shandong Province, China (No. ZR2021MG035), the Science and Technology Development Fund of Macao SAR (No. 0146/2022/A; No. 007/2023/R1B1), and Macau University of Science and Technology (No. FRG-22–091-FIE).
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YZ wrote the manuscript, conducted the models, collected data, and prepared the figures. YD conceived and designed the analysis, wrote and revised the manuscript. PL reviewed and revised the manuscript.
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Zhao, Y., Dong, Y. & Liu, P. Predicting low carbon pathways on the township level in China: a case study of an island. Environ Monit Assess 196, 150 (2024). https://doi.org/10.1007/s10661-023-12278-3
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DOI: https://doi.org/10.1007/s10661-023-12278-3