• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Polish Journal of Environmental Studies >Using a Geographically Weighted Regression Model to Explore the Influencing Factors of CO2 Emissions from Energy Consumption in the Industrial Sector
【24h】

Using a Geographically Weighted Regression Model to Explore the Influencing Factors of CO2 Emissions from Energy Consumption in the Industrial Sector

机译：使用地理加权回归模型探讨工业部门能源消耗产生的二氧化碳排放量的影响因素

获取原文
获取原文并翻译 | 示例
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

This study presents the methodology as well as a quantitative analysis of the influence of social and economic factors, namely GDP, population, economic growth rate, urbanization rate, and industrial structure on CO2 emissions as a result of energy consumption in the 101 counties of Inner Mongolia's industrial sector based on a geographically weighted regression model (GWR) and geographical information systems (GIS) from the perspectives of energy and environmental science. The results show significant differences in the measured CO2 emission levels among different counties. Utilizing the GWR method (which was tested on the smallest scale that has been published thus far), the relationship between CO2 emissions and these five explanatory variables produced an overall model fit of 99%. The GWR results showed that the parameters of variables in the GWR varied spatially, suggesting that the influencing factors had different effects on the CO2 emissions among the various counties. Overall, population, GDP, and urbanization rates positively affect CO2 emissions, industrial structure, and economic growth rate, and affect CO2 emissions both positively and negatively. We also characterize the fact that varying industrial structures and economic growth rates result in different effects on the CO2 emission of various regions.
机译：这项研究提出了方法论并定量分析了社会和经济因素，即内蒙古101个县的能源消耗对GDP，人口，经济增长率，城市化率和产业结构对二氧化碳排放的影响。从能源和环境科学的角度出发，蒙古的工业部门基于地理加权回归模型（GWR）和地理信息系统（GIS）。结果表明，不同县之间测得的CO2排放水平存在显着差异。利用GWR方法（迄今为止已在最小规模上进行了测试），CO2排放量与这五个解释变量之间的关系产生了99％的总体模型拟合。 GWR结果表明，GWR中变量的参数在空间上变化，这表明影响因素对各县之间的CO2排放有不同的影响。总体而言，人口，GDP和城市化率对CO2排放，产业结构和经济增长率产生积极影响，对CO2排放产生积极和消极影响。我们还描述了一个事实，即不同的产业结构和经济增长率对各个地区的CO2排放产生不同的影响。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号