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首页> 外文期刊>Applied Energy >Modeling spatiotemporal CO2 (carbon dioxide) emission dynamics in China from DMSP-OLS nighttime stable light data using panel data analysis
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Modeling spatiotemporal CO2 (carbon dioxide) emission dynamics in China from DMSP-OLS nighttime stable light data using panel data analysis

机译:使用面板数据分析从DMSP-OLS夜间稳定光数据模拟中国的时空CO2(二氧化碳)排放动态

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摘要

China's rapid industrialization and urbanization have resulted in a great deal of CO2 (carbon dioxide) emissions, which is closely related to its sustainable development and the long term stability of global climate. This study proposes panel data analysis to model spatiotemporal CO2 emission dynamics at a higher resolution in China by integrating the Defense Meteorological Satellite Program's Operational Linescan System (DMSP-OLS) nighttime stable light (NSL) data with statistic data of CO2 emissions. Spatiotemporal CO2 emission dynamics were assessed from national scale down to regional and urban agglomeration scales. The evaluation showed that there was a true positive correlation between NSL data and statistic CO2 emissions in China at the provincial level from 1997 to 2012, which could be suitable for estimating CO2 emissions at 1 km resolution. The spatiotemporal CO2 emission dynamics between different regions varied greatly. The high-growth type and high-grade of CO2 emissions were mainly distributed in the Eastern region, Shandong Peninsula and Middle south of Liaoning, with clearly lower concentrations in the Western region, Central region and Sichuan-Chongqing. The results of this study will enhance the understanding of spatiotemporal variations of CO2 emissions in China. They will provide a scientific basis for policy-making on viable CO2 emission mitigation policies. (C) 2015 Elsevier Ltd. All rights reserved.
机译:中国快速的工业化和城市化进程导致大量的CO2(二氧化碳)排放,这与中国的可持续发展和全球气候的长期稳定性密切相关。这项研究提出了面板数据分析方法,通过将美国国防气象卫星计划的作战线扫描系统(DMSP-OLS)夜间稳定光(NSL)数据与CO2排放统计数据相结合,以更高分辨率模拟中国的时空CO2排放动态。从国家规模到区域和城市集聚规模,对时空CO2排放动态进行了评估。评估显示,从1997年到2012年,中国省级NSL数据与统计的CO2排放之间存在真正的正相关性,这可能适合于以1 km的分辨率估算CO2排放。不同地区之间的CO2排放时空变化很大。高增长类型和高等级的二氧化碳排放主要分布在东部地区,山东半岛和辽宁中南部,而西部地区,中部地区和川渝地区的二氧化碳浓度明显较低。这项研究的结果将增进对中国CO2排放时空变化的认识。它们将为制定可行的二氧化碳减排政策提供科学依据。 (C)2015 Elsevier Ltd.保留所有权利。

著录项

  • 来源
    《Applied Energy》 |2016年第15期|523-533|共11页
  • 作者单位

    E China Normal Univ, Minist Educ, Key Lab Geog Informat Sci, Shanghai 200241, Peoples R China|CSIRO Land & Water, Canberra, ACT 2601, Australia;

    CSIRO Land & Water, Canberra, ACT 2601, Australia;

    E China Normal Univ, Minist Educ, Key Lab Geog Informat Sci, Shanghai 200241, Peoples R China;

    Australian Natl Univ, Fenner Sch Environm & Soc, Linnaeus Way, Canberra, ACT 2601, Australia;

    E China Normal Univ, Minist Educ, Key Lab Geog Informat Sci, Shanghai 200241, Peoples R China;

    E China Normal Univ, Minist Educ, Key Lab Geog Informat Sci, Shanghai 200241, Peoples R China|CSIRO Land & Water, Canberra, ACT 2601, Australia;

    Wuhan Univ, Sch Remote Sensing & Informat Engn, Wuhan 430079, Peoples R China;

    E China Normal Univ, Minist Educ, Key Lab Geog Informat Sci, Shanghai 200241, Peoples R China;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    CO2 emissions; Spatiotemporal dynamics; DMSP-OLS; Panel data analysis; China;

    机译:二氧化碳排放时空动态DMSP-OLS面板数据分析中国;

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