首页|基于夜间灯光数据的长江流域碳排放时空格局及异质性研究

基于夜间灯光数据的长江流域碳排放时空格局及异质性研究

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  • NETL
  • NSTL
  • 万方数据
长江流域作为国家发展的重要战略区和示范区，科学监测和分析长江流域碳排放变化及影响因素，对长江流域高质量发展具有重要意义。构建长时间序列的DMSP/OLS和NPP/VIIRS夜间灯光数据集，估算长江流域碳排放，采用空间自相关分析和GTWR模型探究长江流域碳强度的时空格局和空间异质性。结果显示:(1)两种夜光数据融合模型在P＜0。001的显著性水平下，拟合优度为0。93满足精度要求;分省构建的碳排放估算模型，在P＜0。001的显著性水平下，拟合精度均大于0。85，平均相对误差为14。54％，满足估算精度要求。(2)全局自相关分析发现2000～2021年长江流域市级尺度碳强度的全局Moran's I均大于0，且均在1％水平上显著，长江流域市级尺度碳强度具有显著的空间正相关性。(3)局部自相关分析中发现市级尺度显著性聚集从2000年的51。82％下降到2021年的43。52％，碳强度在空间上存在一定聚集性。(4)GTWR模型的回归结果表明，土地利用对碳强度的影响最大，且主要表现为正向，产业结构的影响次之，人口密度存在双向影响，经济发展水平的影响最小且以负向影响为主。研究结果表明，从合理规划土地利用、促进产业的低碳转型和产业结构升级等领域出发，充分发挥长江流域的人口和经济优势，对改善长江流域生态环境、加快实现"双碳"目标具有重要意义。
Spatio-temporal Pattern and Heterogeneity of Carbon Emissions Based on Multi-source Nighttime Light Data in The Yangtze Basin
As an important strategic and demonstration area for national development,scientific monitoring and analysis of carbon emission changes and associate influencing factors is of great significance to the high-quality development of the Yangtze River Basin.In this paper,the long time series DMSP/OLS and NPP/VIIRS nighttime light datasets were constructed to estimate carbon emissions in the Yangtze River Basin.The spatial autocorrelation analysis and GTWR model were used to explore the spatio-temporal pattern and spatial heterogeneity of carbon intensity.The results showed that:(1)The goodness of fit of the two types of night-light data fusion models was 0.93,at the significance level of P＜0.001,which met the accuracy requirements;The carbon emission estimation models for provinces had a fitting accuracy of 0.85 and an average relative error of 14.54％,at the significance level of P＜0.001,which met the requirements of estimation accuracy.(2)The global autocorrelation analysis found that the global Moran's I of the municipal-scale carbon emissions from 2000 to 2021 were all greater than 0,at significance level of 1％.The municipal-scale carbon intensity had a significant spatial positive correlation.(3)In the local autocorrelation analysis,a significant aggregation at the municipal scale was found to decrease from 51.82％in 2000 to 43.52％in 2021,with certain spatial aggregation of carbon intensity.(4)The regression results of the GTWR model showed that the influence of land use on carbon intensity was the largest and had positive effects.The influence of industrial structure was the second largest,the population density had a bidirectional influence,and the level of economic development had the lowest and negative effects.The results of the study showed that it was of great significance to give full play to the demographic and economic advantages of the Yangtze River Basin in terms of rational planning of land use,promotion of low-carbon transformation of industries and upgrading of the industrial structure,in order to encompass the ecological environment and to accelerate the realization of the goal of"dual-carbon".

carbon emissionsnight lightYangtze River Basinspatial and temporal patternGTWR

姜渭宗、徐建辉、赵田

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安徽大学资源与环境工程学院,合肥安徽 230601

滁州学院地理信息与旅游学院,滁州安徽 239012

碳排放 夜间灯光 长江流域 时空格局 GTWR

安徽省高校自然重点项目安徽省高校自然重点项目安徽省高校自然重点项目安徽省高校自然重点项目安徽省高校人文社会科学重点研究项目安徽省高校人文社会科学重点研究项目滁州市科学技术局科技计划项目

KJ2021A1078KJ2021A1079KJ2020A0724zrjz2021021SK2021A06872022AH0510632021ZD007

2024

10.11870/cjlyzyyhj202409014

长江流域资源与环境
中国科学院资源环境科学与技术局 中国科学院武汉文献情报中心

长江流域资源与环境

CSTPCDCSSCICHSSCD北大核心
影响因子：1.35
ISSN：1004-8227
年,卷(期)：2024.33(9)