Spatial Pattern of Land Use Carbon Emissions and Carbon Balance Zoning in Jiangxi Province
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摘要: 二氧化碳浓度升高，导致全球气候变暖，生态环境问题逐渐凸显. 为此，绿色、低碳和循环发展成为我国当前工作重点. 江西省作为长江经济带生态文明建设的重要节点，大规模的城镇化建设导致碳排放量增加. 鉴于此，基于土地利用和能源消费数据构建碳排放量计算模型，探究江西省2000—2018年的碳排放空间格局特征，通过基尼系数、经济贡献系数和生态承载系数等多种分析方法探讨区域内的碳排放空间差异以及碳收支情况，同时从经济和生态的角度进行碳平衡分区并提出针对性的策略. 结果表明：①江西省2000—2018年土地利用碳排放总量逐年上升，从1 215.687×104 t增至4 907.425×104 t，总体表现为净碳源，碳减排压力较大. ②江西省碳排放空间格局呈现北高南低、西高东低的特征，北部和西部地区的碳排放总量明显大于南部和东部地区，其碳排放总量与各区域内的土地利用结构以及能源消费结构密切相关. ③江西省历年的碳补偿率均低于34%且逐年递减，碳补偿率、经济贡献系数和生态承载系数三者均空间差异明显，其中北部地区的碳补偿率低于南部地区，南部地区、东北地区的经济贡献率和生态承载系数高于西部地区. ④基于碳平衡分析，根据净碳排放量、生态承载系数等指标将江西省各地级市划分为4个碳排放发展功能区域，即碳汇功能区、低碳经济区、碳强度控制区、高碳优化区. 研究期内碳汇功能区数量变化较大，逐渐转为低碳经济区；碳强度控制区和高碳优化区数量基本无变化. 研究显示，江西省土地利用碳排放空间差异显著，协同减排的困难较大，为此根据碳平衡分区调整土地利用结构，有利于促进区域协同减排，推动全省低碳经济的发展，缓解因碳排放引起的全球气候变化问题.Abstract: The rising concentration of carbon dioxide has led to global warming and the gradual accentuation of ecological and environmental problems. As an important node in the construction of ecological civilization in the Yangtze River Economic Belt, Jiangxi Province has seen an increase in carbon emissions due to large-scale urbanization. Therefore, a carbon emission calculation model was constructed based on land use and energy consumption data to explore the characteristics of the spatial pattern of carbon emissions in Jiangxi Province from 2000 to 2018, analyze the spatial differences of carbon emissions and carbon income and expenditure in the region through various analysis methods such as Gini coefficient, economic contribution coefficient and ecological carrying coefficient, so as to improve the accuracy of the research results, as well as to conduct carbon balance zoning and propose targeted strategies from the economic and ecological perspectives. The results show that: (1) During the study period, the total land use carbon emissions in Jiangxi Province increased year by year, from 1215.687×104 t to 4907.425×104 t. Construction land dominated the total carbon emissions, forestland played a major role in the carbon sink, and the study area was generally a net carbon source with high carbon emission reduction pressure. (2) The spatial pattern of carbon emissions in the region was high in the north and low in the south, and high in the west and low in the east. The total carbon emissions in the northern and western regions were significantly greater than in the southern and eastern regions. Total carbon emissions were closely related to the land use structure and the energy consumption structure within each region. (3) The carbon offset rate in Jiangxi Province was lower than 34% and decreased year by year, and the carbon offset rate, economic contribution coefficient and ecological carrying coefficient were all spatially different. The carbon offset rate in the northern region was lower than that in the southern region, and the economic contribution rate and ecological carrying coefficient in the southern and northeastern regions were higher than those in the western region. (4) Based on carbon balance analysis, each prefecture-level city in Jiangxi Province was divided into four carbon emission development functional areas based on net carbon emissions, ecological carrying coefficient and other indicators, namely, carbon sink functional area, low-carbon economic area, carbon intensity control area, and high-carbon optimization area. Among them, the carbon sink functional area changed the most, and gradually transformed into a low-carbon economic area during the study period; the number of carbon intensity control areas and high carbon optimization areas basically remained unchanged. This method can provide a reference for future targeted carbon reduction advice and future development directions for each region. The study shows that the spatial differences in carbon emissions from land use in Jiangxi Province are significant, the difficulties of collaborative emission reduction are great. Therefore, adjusting the land use structure according to the carbon balance zoning is conducive to promoting regional coordinated emission reduction, promoting the development of low-carbon economy in the province, and mitigating the global climate change caused by carbon emissions.
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Key words:
- land use /
- carbon emissions /
- spatial patterns /
- carbon balance
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图 2 2000—2018年江西省净碳排放量和增长率趋势
Figure 2. Net carbon emissions and growth rate trends in Jiangxi Province from 2000 to 2018
图 3 2000—2018年江西省各地级市净碳排放量的空间分布
Figure 3. Spatial distribution of net carbon emissions by municipalities in Jiangxi Province from 2000 to 2018
图 4 2000—2018年江西省各地级市的净碳排放增量
Figure 4. Net carbon emission increment by municipalities in Jiangxi Province from 2000 to 2018
图 5 江西省土地利用碳补偿率和基尼系数的变化
Figure 5. Changes of carbon offset rate and Gini coefficient of land use in Jiangxi Province
图 6 2000年和2018年江西省经济贡献系数、生态承载系数的空间分布
Figure 6. Spatial distribution of economic contribution coefficient and ecological carrying coefficient of Jiangxi Province in 2000 and 2018
图 7 2000—2018年江西省碳平衡分区
Figure 7. Carbon balance zoning in Jiangxi Province from 2000 to 2018
表 1 碳排放转换系数
Table 1. Table of carbon emission conversion factors
碳源 折算标准煤系数1)/(t/t) 碳排放系数2) 原煤消费量 0.714 3 0.755 9 焦炭 0.971 4 0.855 0 汽油 1.471 4 0.553 8 柴油 1.457 1 0.592 1 燃料油 1.428 6 0.618 5 煤油 1.471 4 0.571 4 液化石油气 1.714 3 0.504 2 洗精煤 0.900 0 0.755 9 注：1)来自《中国能源统计年鉴》；2)来自《IPCC国家温室气体清单指南》. 
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表 2 2000—2018年江西省不同土地利用类型的碳排放
Table 2. Carbon emissions of different land use types in Jiangxi Province from 2000 to 2018
年份 碳源/(104 t) 碳汇/(104 t) 净碳排放量 建设用地 耕地 碳排放总量 林地 草地 水域 未利用地 碳吸收总量 2000 1 610.112 224.987 1 835.099 −600.789 −1.504 −17.073 −0.046 −619.412 1 215.687 2005 2 913.439 224.182 3 137.621 −600.603 −1.47 −17.528 −0.032 −619.633 2 517.988 2010 4 498.651 223.391 4 722.042 −601.544 −1.43 −17.394 −0.035 −620.403 4 101.639 2015 5 116.077 221.32 5 337.397 −596.978 −1.504 −17.54 −0.034 −616.056 4 721.341 2018 5 301.726 218.586 5 520.312 −593.242 −1.506 −18.112 −0.027 −612.887 4 907.425
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表 3 2000—2018年江西省各地级市净碳排放量
Table 3. Net carbon emissions of municipalities in Jiangxi Province from 2000 to 2018
城市 净碳排放量/(104 t) 2000年 2005年 2010年 2015年 2018年 南昌市 189.098 327.624 392.863 396.097 429.925 景德镇市 132.487 210.28 202.082 484.79 371.685 萍乡市 179.801 432.096 807.754 654.816 437.744 九江市 395.082 574.217 761.128 1 011.035 1 368.008 新余市 251.888 456.292 814.407 810.744 716.392 鹰潭市 84.689 120.833 105.300 192.53 221.192 赣州市 −98.298 −90.862 38.742 42.178 90.891 吉安市 −31.342 72.357 183.702 177.278 178.772 宜春市 157.852 391.437 623.175 731.51 632.418 抚州市 −32.529 −24.295 −26.949 −23.214 220.343 上饶市 −13.041 48.009 199.435 243.577 240.055
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表 4 碳平衡分区特征
Table 4. Characteristics of carbon balance zoning
碳平衡分区 划分依据 区域特征 碳汇功能区 ECC>1、ESC>1、CA>Ci 碳排放经济贡献效率和生态贡献系数都比较高，总体上碳吸收量大于碳排放量，呈现出碳汇功能，固碳能力强 低碳经济区 ECC>1、ESC>1、CA<Ci 碳排放经济贡献效率和生态贡献系数较高，但碳吸收量小于碳排放量，净碳排放总量略低 碳强度控制区 ECC>1、ESC<1、CA<Ci 碳排放经济贡献较高，但生态承载水平偏低，碳吸收量小于碳排放量，净碳排放量偏高 高碳优化区 ECC<1、ESC<1、CA<Ci 净碳排放总量极高，且碳排放经济贡献和生态承载系数水平均较低 注：CA为碳吸收量，Ci为i市的碳排放量.
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