Spatial differentiation and functional zoning of carbon budget: evidence from Jiangxi Province

Regional carbon budget and compensation are one of the current research hotspots, which is of great practical significance for dealing with climate change and promoting the coordinated development of low carbon. Based on energy consumption and land use data, a carbon budget and carbon compensation measurement model was established to analyze the change characteristics and spatial differentiation of the carbon budget of 11 prefecture-level cities in Jiangxi Province from 2010 to 2020 and carry out functional zoning, and further calculate the carbon compensation value of each prefecture-level city. The results showed that (1) during the study period, the carbon emissions in Jiangxi Province showed an increasing trend, with an average annual growth rate of 6.00 million tons, showing a spatial distribution pattern of “high in the west and low in the east.” The province was mainly represented by net carbon sources. (2) During the study period, the forest land in Jiangxi Province was the main carbon sink. The carbon sink absorption capacity declined from 60.56 million tons in 2010 to 59.69 million tons in 2020. (3) The regional difference in the economic contribution coefficient of prefecture-level cities in Jiangxi Province is relatively tiny. The ecological support coefficient has apparent spatial heterogeneity, showing a spatial distribution feature of “high in the south and low in the north.” (4) The 11 prefecture-level cities in Jiangxi Province could be divided into four regions: the carbon sink functional area, low-carbon optimization area, total carbon control area, and carbon intensity control area. By calculating the carbon compensation value and according to the difference in the carbon compensation value, the 11 prefecture-level cities in Jiangxi province are divided into four high-compensation areas, three low-compensation areas, and four compensated areas. The larger the carbon budget is, the higher the carbon compensation amount; conversely, the smaller the budget, the more carbon compensation amount can be obtained. According to the above conclusions, 11 prefecture-level cities should improve emission reduction mechanisms and strengthen the management of forest land utilization. Meanwhile, Jiangxi Province should formulate differentiated development, and compensation strategies should be developed to promote low-carbon, coordinated, and sustainable development among regions.

Authors

Institutions

Publication Details

Journal
Frontiers in Environmental Science
Published
2024-11-20
DOI
https://doi.org/10.3389/fenvs.2024.1404760
Primary Topic
Land Use and Ecosystem Services
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Spatial differentiation and functional zoning of carbon budget: evidence from Jiangxi Province

Wenmei Liao, Liwen Jiang, Zhipeng Wang, Zou Jiamin et al.
Frontiers in Environmental Science
Land Use and Ecosystem Services
article

Spatial differentiation and functional zoning of carbon budget: evidence from Jiangxi Province

Wenmei Liao, Liwen Jiang, Zhipeng Wang, Zou Jiamin, Qiu Hailan, Sun Shuie
article en

Abstract

Regional carbon budget and compensation are one of the current research hotspots, which is of great practical significance for dealing with climate change and promoting the coordinated development of low carbon. Based on energy consumption and land use data, a carbon budget and carbon compensation measurement model was established to analyze the change characteristics and spatial differentiation of the carbon budget of 11 prefecture-level cities in Jiangxi Province from 2010 to 2020 and carry out functional zoning, and further calculate the carbon compensation value of each prefecture-level city. The results showed that (1) during the study period, the carbon emissions in Jiangxi Province showed an increasing trend, with an average annual growth rate of 6.00 million tons, showing a spatial distribution pattern of “high in the west and low in the east.” The province was mainly represented by net carbon sources. (2) During the study period, the forest land in Jiangxi Province was the main carbon sink. The carbon sink absorption capacity declined from 60.56 million tons in 2010 to 59.69 million tons in 2020. (3) The regional difference in the economic contribution coefficient of prefecture-level cities in Jiangxi Province is relatively tiny. The ecological support coefficient has apparent spatial heterogeneity, showing a spatial distribution feature of “high in the south and low in the north.” (4) The 11 prefecture-level cities in Jiangxi Province could be divided into four regions: the carbon sink functional area, low-carbon optimization area, total carbon control area, and carbon intensity control area. By calculating the carbon compensation value and according to the difference in the carbon compensation value, the 11 prefecture-level cities in Jiangxi province are divided into four high-compensation areas, three low-compensation areas, and four compensated areas. The larger the carbon budget is, the higher the carbon compensation amount; conversely, the smaller the budget, the more carbon compensation amount can be obtained. According to the above conclusions, 11 prefecture-level cities should improve emission reduction mechanisms and strengthen the management of forest land utilization. Meanwhile, Jiangxi Province should formulate differentiated development, and compensation strategies should be developed to promote low-carbon, coordinated, and sustainable development among regions.

Frontiers in Environmental ScienceVol. 12
Guangzhou Vocational College of Science and Technology (CN), Jiangxi Agricultural University (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 82%
Land Use and Ecosystem Services
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.