基于DMSP/OLS数据的中国碳排放时空模拟与分异格局

精准模拟和精细尺度获取碳排放的时空动态信息,对于合理制定差别化的区域碳减排政策具有重要意义.利用DMSP/OLS夜间灯光数据在完成年内和跨年数据的校正、像元去饱和、异常值剔除的基础上,提取了城市建成区范围,并以中国大陆为研究对象,根据夜间灯光数据和碳排放统计数据之间的定量关联,构建面板数据模型模拟了2000~2013年中国的碳排放量;采用Theil-Sen Median趋势分析方法与Mann-Kendall检验,探讨了14年间中国碳排放量的时空变化趋势及空间分布特征.结果表明：系统校正后的DMSP/OLS夜间灯光影像构建面板模型模拟的碳排放量拟合精度较高,2002,2007和2012年多尺度回归检验的决定系数R²值分别为0.893,0.955和0.951.2000~2013年中国碳排放时空演化差异显著,稳慢增长型和迅猛增长型分别占碳排放区域总面积的77.6%和19.4%,稳慢增长型面域宽广,迅猛增长型主要位于都市区及都市连绵区.受城市规模及城市化发育程度的影响,迅猛增长型空间结构呈"空心型"与"中心型"空间指向性分异.研究提出,促进经济增长方式和发展模式的实质性转变、因地制宜差别化的减排措施与省区联动策略的实施是"精准减排"目标实现的重要途径.

Spatio-temporal simulation and differentiation pattern of carbon emissions in China based on DMSP/OLS nighttime light data

A precise simulation and measurement of the time-resolved and spatial distribution characteristics of carbon dioxide (CO₂) can help critical references to the formulation of reasonable and differential carbon emission reduction policies. Taking the DMSP/OLS nighttime light data as basic data, this paper extracted the urban built-up area in Chinese mainland on the basis of data rectification, pixel desaturation and outliers elimination. To simulate China's carbon emissions in the period of 2000 to 2013, the carbon emission panel data model was constructed according to the quantitative correlations between DMSP/OLS nighttime light image data and carbon emission statistics. Then the spatio-temporal evolving trend and spatial distribution characteristics of carbon emissions in the research period of 14 years were discussed using Theil-Sen Median trend analysis and Mann-Kendall test method. The results showed that: 1) by correcting the DMSP/OLS nighttime light image data systematically, the simulation here of long-time serial carbon emissions showed high accuracy. The determination coefficient value, R², from the multiscale regression test for the year of 2002, 2007, 2012 were 0.893, 0.955 and 0.951, respectively. 2) It indicated that the overall carbon emissions from 2000 to 2013 in China have a significant characteristic of spatial-temporal evolution. The stable-slow rise type and rapid rise type carbon emission aeras accounted for 77.6% and 19.4% respectively of the total carbon emissions areas. It also showed that most regions in China were dominated by a stable-slow rise type, while the urban centers and its extended regions show a rapid rise type. 3) By the influence of city size and urbanization level, cities of the rapid rise type showed a clear directional difference with ‘hollow structure’ or ‘centered structure’. This study proposes that, the essential transformation of economic growth pattern and the development mode, as well as the implementation of different carbon emission reduction measures adapted to local conditions and provinces-regions linked strategy are the vital approach to achieve the “targeted emission alleviation”.