首页|基于OCO-2卫星的中国人为碳排放时空变化与社会经济影响分析

基于OCO-2卫星的中国人为碳排放时空变化与社会经济影响分析

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利用OCO-2碳卫星二氧化碳柱浓度(XCO2)数据,结合时空克里格和XCO2异常计算方法,研究2015~2021年中国地区XCO2异常的时空变化趋势,并基于随机森林算法定量分析社会经济影响因素对XCO2异常的影响。结果表明,2015~2021年中国地区XCO2异常在时间上呈现显著的周期性变化趋势,尤其在冬季会出现显著的波峰,在空间上呈现东高西低、南高北低的梯度分布。基于OCO-2卫星的XCO2异常空间分布与人为排放清单基本一致,特别在大空间尺度和高排放地区,XCO2异常值更能有效地展示人为碳排放的空间分布特征。在省级尺度下,GDP、地方财政支出、人口、汽车保有量等因素影响因子对XCO2异常呈现显著的正相关关系,其中GDP的相关性和贡献度占比最高,分别是0。56和0。46,与此同时,能源强度、产业结构和能源消费结构等也对XCO2异常有一定的影响和贡献。研究结果表明卫星遥感在检测中国地区人为碳排放时空变化趋势和影响因子分析的研究上具有可行性,可为生态环境保护和碳减排决策提供支持。
Spatiotemporal trends and socio-economic impacts of anthropogenic carbon emissions in China based on OCO-2GHG satellite data
The spatiotemporal dynamics of column-averaged CO2 dry air mole fractions,as captured by OCO-2 satellite XCO2 data,were meticulously examined across China from 2015 to 2021.This investigation harnessed the synergistic capabilities of spatiotemporal kriging methodologies and advanced XCO2 anomaly computation techniques.Additionally,the quantitative influence of socioeconomic determinants on XCO2 anomalies was elucidated through the application of the random forest algorithm.The findings revealed a discernible cyclical temporal pattern in XCO2 anomalies over the study period,with pronounced seasonal maxima during the winter months.Geographically,the anomalies exhibited a gradient distribution,with elevated concentrations in the eastern and southern regions,juxtaposed against lower levels in the western and northern territories.The spatial configuration of XCO2 anomalies derived from OCO-2 satellite observations was found to be largely congruent with anthropogenic emission inventories.Notably,at broader spatial scales and in regions characterized by higher emission intensities,XCO2 anomalies more effectively encapsulated the spatial distribution attributes of anthropogenic carbon emissions.At the provincial level,variables including GDP,local fiscal expenditure,population density,and vehicle ownership exhibited a significant positive correlation with XCO2 anomalies.Among these,GDP demonstrated the most pronounced association,with correlation and contribution ratios of 0.56 and 0.46,respectively.Furthermore,energy intensity,industrial composition,and energy consumption profiles were identified as consequential determinants contributing to XCO2 anomalies.These research outcomes substantiate the viability of leveraging satellite remote sensing to monitor spatiotemporal fluctuations in anthropogenic carbon emissions and to dissect their underlying drivers across China.This approach is anticipated to furnish critical insights for ecological conservation,environmental stewardship,and the formulation of informed strategies for carbon mitigation initiatives.

OCO-2 carbon satelliteanthropogenic carbon emissionsspatiotemporal trendsXCO2 anomaly

高顺、欧金沛、黄晓蕾、黄英剑、谢纪腾

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中山大学地理科学与规划学院,广东省城市化与地理环境空间模拟重点实验室,广东 广州 510006

OCO-2碳卫星 人为碳排放 时空变化趋势 XCO2异常

2024

中国环境科学
中国环境科学学会

中国环境科学

CSTPCDCHSSCD北大核心
影响因子:2.174
ISSN:1000-6923
年,卷(期):2024.44(12)