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Analysis on the variations of atmospheric CO_2 concentrations along the urban-rural gradients of Chinese cities based on the OCO-2 XCO_2 data

机译:基于OCO-2 XCO_2数据的中国城市大气CO_2浓度沿城乡梯度的变化分析

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摘要

Anthropogenic CO2 emissions contribute the most to the growth of atmospheric CO2 concentrations. These emissions are largely concentrated in urban areas where human activities are intense. Studies have been conducted to explore the urban and rural difference in CO2 concentrations based on ground-based measurements. The launch of NASA's Orbiting Carbon Observatory-2 (OCO-2) satellite provides a new opportunity to monitor CO2 concentrations and their spatial and temporal variations at city scale. The objective of this study is to analyse the spatial and temporal distributions of CO2 concentrations along the urban-rural gradients of Chinese cities, using the column averaged CO2 dry air mole fraction (XCO2) data derived from OCO-2. We used both conceptual and physical urban-rural gradients to analyse variations in CO2 concentrations over space. The results show that the urban and rural difference in CO2 concentrations of these cities can be monitored. And, the seasonal variations of CO2 concentrations in these cities can also be detected using the XCO2 data. Moreover, the variations in CO2 concentrations along the urban-rural gradients have four main types with significant enhancements of CO2 concentrations were observed in urban areas, urban-rural transitional areas, rural areas, and without regular patterns, respectively. The results are generally different from the common assumption that CO2 concentrations peak in central urban areas and decline in rural areas. In conclusion, the XCO2 data can be used to analyse the spatial-temporal variations of CO2 concentrations along the urban-rural gradients of Chinese cities, and the results have important policy implications for mitigating CO2 emissions.
机译:人为排放的二氧化碳对大气中二氧化碳浓度的增长贡献最大。这些排放物主要集中在人类活动密集的城市地区。已经进行了研究,以基于地面测量来探索城市和农村地区的二氧化碳浓度差异。 NASA的轨道碳观测站2(OCO-2)卫星的发射提供了一个新的机会,可以监测城市范围内的CO2浓度及其时空变化。这项研究的目的是使用源自OCO-2的列平均CO2干空气摩尔分数(XCO2)数据,分析中国城市沿城乡梯度分布的CO2浓度的时空分布。我们使用概念性的和城乡的物理梯度来分析空间中二氧化碳浓度的变化。结果表明,可以监测这些城市的城乡二氧化碳浓度差异。而且,还可以使用XCO2数据检测这些城市的CO2浓度的季节性变化。此外,CO2浓度沿城乡梯度的变化有四种主要类型,分别在城市地区,城乡过渡地区,农村地区和没有规律的格局中观察到了CO2浓度的显着提高。结果通常不同于通常的假设,即二氧化碳浓度在中心城市地区达到峰值而在农村地区则下降。总之,XCO2数据可用于分析中国城市沿城乡梯度变化的CO2浓度时空变化,其结果对减少CO2排放具有重要的政策意义。

著录项

  • 来源
    《International journal of remote sensing》 |2018年第12期|4194-4213|共20页
  • 作者单位

    Peking Univ Shenzhen Grad Sch Key Lab Human & Environm Sci & Technol Sch Urban Planning & Design Shenzhen Peoples R China;

    China Meteorol Adm Natl Climate Ctr Beijing 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

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