全球二氧化碳浓度非均匀分布条件下碳排放与升温关系的统计分析

为定量评估全球二氧化碳浓度非均匀分布条件下碳排放与升温的关系,采用空间自相关分析与空间联立方程组模型,基于1度、2度与3度空间分辨率的全球二氧化碳浓度,碳排放与近地面气温等格点数据,揭示了2003—2015年全球二氧化碳浓度的空间分布聚集特征并估计了碳排放对升温的影响系数。结果发现：二氧化碳浓度在空间上表现为北半球高浓度值聚集与南半球低浓度值聚集的分布型。利用二氧化碳浓度非均匀分布的参数条件对碳排放与升温影响的估计结果表明,代入二氧化碳浓度非均匀分布这一参数会小幅拉低碳排放对升温影响的估计结果。研究表明,全球二氧化碳浓度非均匀分布是当前评估碳排放升温影响亟待引入的参数;同时由于估计结果的空间尺度效应的存在,相关参数的空间范围与分辨率的选择也需要关注。

Statistical analysis of the relationship between carbon emissions and temperature rise with the spatially heterogenous distribution of carbon dioxide concentration

In order to quantify the relationship between carbon emissions and temperature rise with the spatially heterogenous distribution of carbon dioxide concentration, this paper used the spatial autocorrelation analysis and the spatial simultaneous equations model to reveal the spatial distribution and aggregation characteristics of global carbon dioxide concentration during 2003-2015 and estimated the impact of carbon emissions on temperature rise based on the grid data of global carbon dioxide concentration, carbon emissions and temperature. The results indicate that carbon dioxide concentration has high value in the northern hemisphere and low value in the southern hemisphere. Spatially heterogenous distribution of carbon dioxide concentration will slightly decrease the estimation results of the impact of carbon emissions on temperature rise. The results show that the spatially heterogenous distribution is an important parameter that should be introduced into the assessment of global warming. At the same time, due to the existence of the spatial scale effect, the selection of spatial range and resolution deserves more attention.