globalchange  > 气候变化事实与影响
CSCD记录号: CSCD:6492371
论文题名:
市域尺度货物运输碳排放时空变化及因素分析
其他题名: Spatiotemporal variations and potential variables of greenhouse gas emissions based on city scale
作者: 郑梦柳1; 杨红磊1; 彭军还1; 魏佳珩1; 赵斌滨2
刊名: 测绘科学
ISSN: 1009-2307
出版年: 2019
卷: 44, 期:5, 页码:799-806
语种: 中文
中文关键词: 空间分析 ; 地理加权回归 ; 空间自相关 ; 碳排放
英文关键词: spatial analysis ; geographically weighted regression ; spatial autocorrelation ; greenhouse gas emission
WOS学科分类: GEOSCIENCES MULTIDISCIPLINARY
WOS研究方向: Geology
中文摘要: 针对货物运输导致碳排放成为温室气体主要来源之一的问题,该文综合货物运输车辆的微观温室气体排放及时空变化,从市域尺度分析货物运输碳排放的时空变化规律。利用微观排放模型计算了2000年、2005年、2010年和2015年全国286个城市货物运输碳排放的空间分布及其变化,并应用地理加权回归模型探究城市化不同层面因素对碳排放时空分布变化的影响。结果表明:货物运输碳排放具有显著的空间集聚特征,且高排放地区的集聚规律更加显著;地理加权回归模型精度明显高于普通线性回归模型,经济变量、人口变量、货运强度变量与货物运输碳排放存在显著正相关关系。该研究可为中国各市级区域制订节能减排政策提供量化的科学依据。
英文摘要: A large amount of greenhouse gas(GHG)emissions are generated by the freight transport sector,which have significant influence on the global climate change.In this paper,the spatiotemporal variation of GHG emissions in cities was analyzed with the integration of microscopic emission investigation and spatially local assessment.This paper calculated the spatial distribution and changes of GHG emissions of freight transportation in 286cities of China in 2000,2005,2010and 2015with microscopic emission model,and explored the influence of potential variables on distribution of GHG emissions by geographically weighted regression(GWR)model.Results showed that the GHG emissions had significant spatial agglomeration characteristics,especially in hot-spot regions;compared with the linear regression, GWR had significantly improved the estimation accuracy,the economy,population and freight strength variables had positively associations with GHG emissions.This study will provide a quantitative scientific basis for formulating energy conservation and emission reduction policies in various cities in China.
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/155525
Appears in Collections:气候变化事实与影响

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作者单位: 1.中国地质大学(北京), 北京 100083, 中国
2.中国电力科学研究院有限公司, 北京 100192, 中国

Recommended Citation:
郑梦柳,杨红磊,彭军还,等. 市域尺度货物运输碳排放时空变化及因素分析[J]. 测绘科学,2019-01-01,44(5):799-806
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