碳中和背景下统筹土地利用碳收支的广东省横向碳补偿

杜梦晴; 杨欣

doi:10.13870/j.cnki.stbcxb.2024.01.026

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碳中和背景下统筹土地利用碳收支的广东省横向碳补偿

更新时间：2025-03-12

- 碳中和背景下统筹土地利用碳收支的广东省横向碳补偿
- Horizontal Carbon Compensation in Guangdong Province Based on Coordinating Land Use Carbon Budget Under the Background of Carbon Neutrality
- 水土保持学报 2024年38卷第1期页码：197-206
- 作者机构：
  
  华中农业大学公共管理学院,武汉,430070
- 作者简介：
  
  [ "杜梦晴(2000—),女,硕士研究生,主要从事土地利用与生态环境研究。E-mail:dmq@webmail.hzau.edu.cn" ]
- 基金信息：
  
  国家自然科学基金项目(71704061);教育部人文社科基金规划项目(21YJA790072);武汉市曙光计划项目(2023020201020349);中央高校基本科研业务费专项(2662023YJ001,2662023PY015)
- DOI：10.13870/j.cnki.stbcxb.2024.01.026
  中图分类号： X196
- 纸质出版：2024
- 稿件说明：
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杜梦晴, 杨欣. 碳中和背景下统筹土地利用碳收支的广东省横向碳补偿[J]. 水土保持学报, 2024,38(1):197-206.

DU Mengqing, YANG Xin. Horizontal Carbon Compensation in Guangdong Province Based on Coordinating Land Use Carbon Budget Under the Background of Carbon Neutrality[J]. 2024, 38(1): 197-206.
杜梦晴, 杨欣. 碳中和背景下统筹土地利用碳收支的广东省横向碳补偿[J]. 水土保持学报, 2024,38(1):197-206. DOI： 10.13870/j.cnki.stbcxb.2024.01.026.

DU Mengqing, YANG Xin. Horizontal Carbon Compensation in Guangdong Province Based on Coordinating Land Use Carbon Budget Under the Background of Carbon Neutrality[J]. 2024, 38(1): 197-206. DOI： 10.13870/j.cnki.stbcxb.2024.01.026.

摘要

[目的] 碳补偿机制是实现双碳目标和社会环境公平的重要途经。[方法] 在测算2010—2020年碳收支基础上

建立碳补偿模型核算碳补偿空间转移额度。[结果] (1)研究期间全省碳排放总量年平均递增率为2.51%

除佛山、东莞、清远外其余城市的碳排放均不同程度增加

空间上呈现以广州为中心的"核心-外围"的格局。广东省2010—2020年碳吸收总量呈现缓慢下降趋势

空间格局趋于稳定

总体呈现北高南低的特点。(2)研究期间碳补偿支付区范围变大

面积占比由55.22%扩大至60.49 %

支付区主要分布净碳排放较多的惠州及净碳排放少但碳排放效率低的云浮、阳江等

受偿区主要分为2类

一类是净碳排放量少的河源、汕尾等地;另一类是碳排放多但碳排放效率高的深圳、广州、东莞等。(3)惠州需支付碳补偿额度居于首位

深圳获得碳补偿额度最多

各市跨区域碳补偿额度占区域GDP的比例在0.017%~0.095%波动

跨区域碳补偿具有可操作性。[结论] 为实现广东省区域间的低碳协同发展

未来应建立以政府为主导的区域横向碳补偿制度

并实施以低碳为导向的差异化的低碳优化策略

这对区域协调和低碳发展具有重要的现实意义。

Abstract

[Objective] The carbon compensation mechanism is an important way to promote the achievement of carbon peaking and carbon neutrality goals and social environment equity. [Methods] This study established the carbon compensation model to calculate the amount of spatial transfer carbon compensation based on the calculation of the carbon budget from 2010 to 2020. [Results] (1) During the study period

the average annual incremental rate of total carbon emissions was 2.51%

with the remaining cities except Foshan

Dongguan and Qingyuan increasing to varying degrees

presenting a spatial pattern of "core-periphery" centered around Guangzhou. From 2010 to 2020

the total carbon absorption showed a slow downward trend

and the spatial pattern tended to be stable with a general characteristic of high in the northern and low in the southern. (2) The carbon compensation payment area became larger during the study period

the proportion of area increased from 55.22% to 60.49%. The payment regions were mainly distributed in Huizhou

which had higher net carbon emissions

and Yunfu and Yangjiang

which had lower net carbon emissions but lower carbon emission efficiency. The compensated areas were mainly divided into two types

one type exhibited low net carbon emissions

e.g.

Heyuan and Shanwei

and the other type was of high carbon emissions but high carbon emission efficiency

such as Shenzhen

Guangzhou and Dongguan. (3) Huizhou ranked the first of the compensation amounts to be paid

while Shenzhen received the largest amount of carbon compensation. The proportion of cross regional carbon compensation amounts to the regional GDP of each city varied from 0.017% to 0.095%

indicating that cross regional carbon compensation was feasible. [Conclusion] In order to achieve the low-carbon collaborative development of Guangdong province

it is needed to establish carbon compensation system guided by the government in the future and implement the low-carbon-oriented regional differentiation low-carbon optimization strategy. The above has important practical significance for regional coordination and low-carbon development.

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Keywords

references

方精云,黄耀,朱江玲,等.森林生态系统碳收支及其影响机制[J].中国基础科学,2015,17(3):20-25. FANG J Y, HUANG Y, ZHU J L, et al. Carbon budget of forest ecosystems and its driving forces[J].China Basic Science,2015,17(3):20-25.

丁仲礼.中国碳中和框架路线图研究[J].中国工业和信息化,2021,37(8):54-61. DING Z L. Research on China's carbon neutral framework roadmap[J].China Industry and Information Technology,2021,37(8):54-61.

李若玮,叶冲冲,王毅,等.基于InVEST模型的青藏高原碳储量估算及其驱动力分析[J].草地学报,2021,29(增刊1):43-51. LI R W, YE C C, WANG Y, et al. Carbon storage estimation and its drivering force analysis based on InVEST model in the Tibetan Plateau[J].Acta Agrestia Sinica,2021,29(S1):43-51.

陈耀亮,罗格平,叶辉,等.1975—2005年中亚土地利用/覆被变化对森林生态系统碳储量的影响[J].自然资源学报,2015,30(3):397-408. CHEN Y L, LUO G P, YE H, et al. Sources and sinks of carbon caused by forest land use change from 1975 to 2005 in Central Asia[J].Journal of Natural Resources,2015,30(3):397-408.

曲福田,卢娜,冯淑怡.土地利用变化对碳排放的影响[J].中国人口·资源与环境,2011,21(10):76-83. QU F T, LU N, FENG S Y. Effects of land use change on carbon emissions[J].China Population, Resources and Environment,2011,21(10):76-83.

王超越,郭先华,郭莉,等.基于FLUS-InVEST的西北地区土地利用变化及其对碳储量的影响:以呼包鄂榆城市群为例[J].生态环境学报,2022,31(8):1667-1679. WANG C Y, GUO X H, GUO L, et al. Land use change and its impact on carbon storage in northwest China based on FLUS-Invest: A case study of Hu-Bao-Er-Yu urban agglomeration[J].Ecology and Environmental Sciences,2022,31(8):1667-1679.

孙方虎,方凤满,洪炜林,等.基于PLUS和InVEST模型的安徽省委储量演化分析与预测[J].水土保持学报,2023,37(1):151-158. SUN F H, FANG F M, HONG W L, et al. Evolution analysis and prediction of carbon storage in Anhui Province based on PLUS and InVEST models[J].Journal of Soil and Water Conservation,2023,37(1):151-158.

张平平,李艳红,殷浩然,等.中国南北过渡带生态系统碳储量时空变化及动态模拟[J].自然资源学报,2022,37(5):1183-1197. ZHANG P P, LI Y H, YIN H R, et al. Spatio-temporal variation and dynamic simulation of ecosystem carbon storage in the North-south Transitional Zone of China[J].Journal of Natural Resources,2022,37(5):1183-1197.

巩晟萱,张玉虎,李宇航.基于PLUS-InVEST模型的京津冀碳储量变化及预测[J].干旱区资源与环境,2023,37(6):20-28. GONG S X, ZHANG Y H, LI Y H. Spatio-temporal variation and prediction of carbon storage in Beijing-Tianjin-Hebei Region:A PLUS-InVEST model approach[J].Journal of Arid Land Resources and Environment,2023,37(6):20-28.

朱志强,马晓双,胡洪.基于耦合FLUS-InVEST模型的广州市生态系统碳储量时空演变与预测[J].水土保持通报,2021,41(2):222-229. ZHU Z Q, MA X S, HU H. Spatio-temporal evolution and prediction of ecosystem carbon stocks in Guangzhou City by coupling FLUS-InVEST models[J].Bulletin of Soil and Water Conservation,2021,41(2):222-229.

邵壮,陈然,赵晶,等.基于FLUS与InVEST模型的北京市生态系统碳储量时空演变与预测[J].生态学报,2022,42(23):9456-9469. SHAO Z, CHEN R, ZHAO J, et al. Spatio-temporal variation and prediction of carbon storage in Beijing's ecosystem based on FLUS and InVEST models[J].Acta Ecologica Sinica,2022,42(23):9456-9469.

孙欣欣,薛建辉,董丽娜.基于PLUS模型和InVEST模型的南京市生态系统碳储量时空变化与预测[J].生态与农村环境学报,2023,39(1):41-51. SUN X X, XUE J H, DONG L N. Spatio-temporal change and prediction of carbon storage in Nanjing based on PLUS model and InVEST model[J].Journal of Ecology and Rural Evironment,2023,39(1):41-51.

侯建坤,陈建军,张凯琪,等.基于InVEST和GeoSoS-FLUS模型的黄河源区碳储量时空变化特征及其对未来不同情景模式的响应[J].环境科学,2022,43(11):5253-5262. HOU J K, CHEN J J, ZHANG K Q, et al. Temporal and spatial variation characteristics of carbon storage in the source region of the Yellow River based on InVEST and GeoSoS-FLUS models and its response to different future scenarios[J].Environmental Science,2022,43(11): 5253-5262.

陈科屹,王建军,何友均,等.黑龙江大兴安岭重点国有林区森林碳储量及固碳潜力评估[J].生态环境学报,2022,31(9):1725-1734. CHEN K Y, WANG J J, HE J Y, et al. Estimations of forest carbon storage and carbon sequestration potential of key state-owned forest region in Daxing'anling, Heilongjiang Province[J].Ecology and Environmental Sciences,2022,31(9):1725-1734.

邓喆,丁文广,蒲晓婷,等.基于InVEST模型的祁连山国家公园碳储量时空分布研究[J].水土保持通报,2022,42(3):324-334. DENG Z, DING W G, PU X T, et al. Spatio-temporal change and prediction of carbon storage in Qilian Mountain National Park based on InVEST model[J]. Bulletin of Soil and Water Conservation, 2022,42(3):324-334.

TANG X, ZHAO X, BAI Y, et al. Carbon pools in China's terrestrial ecosystems: New estimates based on an intensive field survey[J]Proceedings of the National Academy of Sciences of the United States of America,2018,115(16):4021-4026.

李涛.阿坝牧区不同利用方式与程度草地土壤与植被碳储量研究[D].成都:四川农业大学,2013. LI T. Research on soil and vegetation carbon storage of grassland under different land use and degree in Aba pastoral areas[D].Chengdu:Sichuan Agricultural University,2013.

吴胜义,王飞,徐干君,等.川西北高山峡谷区森林碳储量及空间分布研究:以四川洛须自然保护区为例[J].生态环境学报,2022,31(9):1735-1744. WU S Y, WANG F, XU G J, et al. Study on forest carbon storage and spatial distribution in the alpine gorge region of northwest Sichuan: Take Sichuan Luoxu Nature Reserve as an example[J].Ecology and Environmental Sciences,2022,31(9):1735-1744.

陈良帅,黄新亚,薛丹,等.川西高原泥炭沼泽土壤有机碳分布特征及其影响因素[J].应用与环境生物学报,2022,28(2):267-275. CHEN L S, HUANG X Y, XUE D, et al.Distribution characteristics and influencing factors of soil organic carbon in peat swamp of Western Sichuan Plateau[J].Chinese Journal of Applied and Environmental Biology,2022,28(2):267-275.

巫明焱,董光,王艺积,等.川西米亚罗自然保护区森林地上碳储量遥感估算[J].生态学报,2020,40(2):621-628. WU M Y, DONG G, WANG Y J, et al. Estimation of forest aboveground carbon storage in Sichuan Miyaluo Nature Reserve based on remote sensing[J].Acta Ecologica Sinica,2020,40(2):621-628.

XIANG M S, WANG C J, TAN Y X, et al. Spatio-temporal evolution and driving factors of carbon storage in the Western Sichuan Plateau[J].Scientific Reports,2022,12(1):e8114.

王庆莉,王茹琳,张利平,等.基于MaxEnt模型的川西高原松茸气候生态适宜性与潜在分布[J].应用生态学报,2021,32(7):2525-2533. WANG Q L, WANG R L, ZHANG L P, et al. Climatic ecological suitability and potential distribution of

Tricholoma

matsutake in western Sichuan Plateau, China based on MaxEnt model[J].Chinese Journal of Applied Ecology,2021,32(7):2525-2533.

YANG J, HUANG X. The 30 m annual land cover dataset and its dynamics in China from 1990 to 2019[J].Earth System Science Data,2021,13(8):3907-3925.

ALAM S A, STARR M, CLARK B J F. Tree biomass and soil organic carbon densities across the Sudanese woodland savannah: A regional carbon sequestration study[J].Journal of Arid Environments,2013,89:67-76.

RAICH J W, NADELHOFFER K J. Belowground carbon allocation in forest ecosystems: Global trends[J].Ekologia Bratislava,1989,70(5):1346-1354.

GIAEDINA C P, RYAN M G. Evidence that decomposition rates of organic carbon in mineral soil do not vary with temperature[J].Nature,2000,404(6780):858-861.

黄玫,季劲钧,曹明奎,等.中国区域植被地上与地下生物量模拟[J].生态学报,2006,26(12):4156-4163. HUANG M, JI J J, CAO M K, et al. Modeling study of vegetation shoot and root biomass in China[J].Acta Ecologica Sinica,2006,26(12):4156-4163.

YANG Y, WANG G X, SHEN H H, et al. Dynamics of carbon and nitrogen accumulation and C∶N stoichiometry in a deciduous broadleaf forest of deglaciated terrain in the eastern Tibetan Plateau[J].Forest Ecology and Management,2014,312:10-18.

陈利军,刘高焕,励惠国.中国植被净第一性生产力遥感动态监测[J].遥感学报,2002,6(2):129-135. CHEN L J, LIU G H, LI H G. Estimating net primary productivity of terrestrial vegetation in China using remote sensing[J].Journal of Remote Sensing,2002,6(2):129-135.

吕铭志,盛连喜,张立.中国典型湿地生态系统碳汇功能比较[J].湿地科学,2013,11(1):114-120. LÜ M Z, SHENG L X, ZHANG L. A review on carbon fluxes for typical wetlands in different climates of China[J].Wetland Science,2013,11(1):114-120.

ZHANG Y B, DUAN B L, LI C Y, et al. Links between plant diversity, carbon stocks and environmental factors along a successional gradient in a subalpine coniferous forest in Southwest China[J].Forest Ecology and Management,2011,262(3):361-369.

薛晶月,王丽华,谢雨,等.西南地区草地群落灌木植物盖度对生态系统碳库的影响[J].植物生态学报,2019,43(4):365-373. XUE J Y, WANG L H, XIE Y, et al. Effect of shrub coverage on grassland ecosystem carbon pool in southwestern China[J].Journal of Plant Ecology,2019,43(4):365-373.

姜广争.岷江上游干旱河谷区不同土地利用方式土壤有机碳差异性特征研究[D].成都:四川农业大学,2012. JIANG G Z. Study on differences characteristic of soil organic carbon of different land-use type in dry valley of the upper reaches of Minjiang River[D].Chengdu: Sichuan Agricultural University,2012.

YANG Y Y, FANG J Y, MA W H, et al. Soil carbon stock and its changes in northern China's grasslands from 1980s to 2000s[J].Global Change Biology,2010,16(11):3036-3047.

高俊琴,雷光春,李丽,等.若尔盖高原3种湿地土壤有机碳分布特征[J].湿地科学,2010,8(4):327-330. GAO J G, LEI G C, LI L, et al. The distribution characteristics of soil organic carbon in three kinds of wetland soils in Zoigê Plateau[J].Wetland Science,2010,8(4):327-330.

刘晓娟,黎夏,梁迅,等.基于FLUS-InVEST模型的中国未来土地利用变化及其对碳储量影响的模拟[J].热带地理,2019,39(3):397-409. LIU X J, LI X, LIANG X, et al. Simulating the change of terrestrial carbon storage in China based on the FLUS-InVEST model[J].Tropical Geography,2019,39(3):397-409.

SANG L L, ZHANG C, YANG J Y, et al. Simulation of land use spatial pattern of towns and villages based on CA-Markov model[J].Mathematical and Computer Modelling,2011,54(3/4):938-943.

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