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基于夜间灯光数据的晋陕蒙能源消费碳排放时空格局
引用本文:武娜,沈镭,钟帅.基于夜间灯光数据的晋陕蒙能源消费碳排放时空格局[J].地球信息科学,2019,21(7):1040-1050.
作者姓名:武娜  沈镭  钟帅
作者单位:1. 中国科学院地理科学与资源研究所,北京 1001012. 中国科学院大学,北京 1000493. 自然资源部资源环境承载力评价重点实验室,北京 100083
基金项目:中国科学院战略性先导科技专项(A类)(XDA19040102);科技部国家重点研发计划项目(2016YFA0602802);国家自然科学基金面上项目(41771566)
摘    要:晋陕蒙三省区既是能源生产基地又是碳排放主要地区。对晋陕蒙市县的碳排放估算难度较大,如何准确快捷地获取其碳排放时空动态信息,对于合理制定区域碳减排规划具有重要的应用价值。本文选取中国晋陕蒙三省作为研究对象,基于夜间灯光数据,模拟晋陕蒙地区碳排放空间分布,进而系统地刻画其碳排放空间分布特征和规律。研究结果表明:① 1997-2016年,晋陕蒙三省区夜间灯光像元总值与能源消耗碳排放量之间的相关系数较高,均通过了1%的显著性检验;② 1997-2016 年,晋陕蒙地区的CO2排放总量呈逐年增长趋势,鄂尔多斯市属于“高碳”地区;铜川市、安康市、商洛市、汉中市、阿拉善盟和阳泉市属于“低碳”地区;③ 陕西省碳排放清晰地呈现出“陕北>关中>陕南”的格局。晋陕蒙地区碳排放空间分布规律分析为该区域制定切实可行的碳减排政策提供了重要的理论依据。

关 键 词:夜间灯光数据  能源消费  碳排放  时空格局  晋陕蒙  
收稿时间:2019-01-07

Spatio-temporal Pattern of Carbon Emissions based on Nightlight Data of the Shanxi-Shaanxi-Inner Mongolia Region of China
Na WU,Lei SHEN,Shuai ZHONG.Spatio-temporal Pattern of Carbon Emissions based on Nightlight Data of the Shanxi-Shaanxi-Inner Mongolia Region of China[J].Geo-information Science,2019,21(7):1040-1050.
Authors:Na WU  Lei SHEN  Shuai ZHONG
Institution:1. Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences,Beijing 100101, China2. University of Chinese Academy of Sciences,Beijing 100049, China3. Key Laboratory of Carrying Capacity Assessment for Resource and Environment, Ministry of Natural Resources, Beijing 100083, China
Abstract:The Shanxi-Shaanxi-Inner Mongolia region is China's energy production base and also a major carbon emission area. It is very difficult to estimate the carbon emissions of in Shanxi, Shaanxi, Inner Mongolia. How to obtain the spatiotemporal dynamic information of carbon emissions accurately and quickly has important application value for making more informed regional carbon emission reduction plans. In this paper, the Shanxi-Shaanxi-Inner Mongolia region was selected as the study area. Based on nighttime light imagery, the spatial distribution of carbon emissions in Shanxi、Shaanxi and Inner Mongolia were simulated, and then the spatial distribution characteristics and rules of carbon emissions were systematically described. The results showed that the correlation coefficient between the total value of night light pixels and energy consumption carbon emissions was relatively high in the three provinces of Shanxi, Shaanxi and Mongolia during 1997-2016, which all passed the significance test of 1%. From 1997 to 2016, the carbon emissions increased year by year in Shanxi、Shaanxi and Inner Mongolia. Ordos is a "high carbon" area; Tongchuan, Ankang, Shangluo, Hanzhong, Alashan, and Yangquan are "low carbon" areas. The distribution of the carbon emissions presented a distinct pattern ? smaller in southern Shaanxi than in the central areas. The analysis of spatial distribution patterns of carbon emissions in energy rich areas can better inform the formulation of feasible carbon emission reduction policies.
Keywords:nightlight data  CO2emission  energy consumption  spatio-temporal pattern  Shanxi-Shaanxi-Inner Mongolia  
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