地球信息科学学报 ›› 2014, Vol. 16 ›› Issue (2): 207-213.doi: 10.3724/SP.J.1047.2014.00207

• 地理空间分析综合应用 • 上一篇    下一篇

中国区域近地面CO2时空分布特征研究

赵静, 崔伟宏   

  1. 中国科学院遥感与数字地球研究所, 北京 100101
  • 收稿日期:2013-05-23 修回日期:2013-10-20 出版日期:2014-03-10 发布日期:2014-03-10
  • 作者简介:赵 静(1988- ),女,江苏镇江人,硕士生,研究方向为遥感三维重建理论与方法。E-mail:zhaojingzjtoxz@163.com
  • 基金资助:

    国家科技支撑计划项目“我国绿色低碳发展的关键支撑政策与技术研究——跟踪全球气候变化不确定性研究及各国气候变化政策调整”研究课题(2012BAC20B00)。

Spatial and Temporal Distribution Characteristics of CO2 Column Concentration in China from 2009 to 2010

ZHAO Jing, CUI Weihong   

  1. Institute Of Remote Sensing and Digital Earth, CAS, Beijing 100101, China
  • Received:2013-05-23 Revised:2013-10-20 Online:2014-03-10 Published:2014-03-10
  • Contact: 10.3724/SP.J.1047.2014.00207

摘要:

本文利用2009年6月至2010年5月日本宇宙航空研究开发机构(JAXA)、日本环境署(MOE)与日本环境研究(NIES)所等联合开发的全球首颗专用温室气体观测卫星“呼吸号”(GOSAT)上的被动红外探测器(TANSO)官方反演的近地面975hPa左右的CO2浓度L4B数据产品,采用ArcGIS地统计分析方法,对比瓦里关全球大气本底站地面观测数据进行真实性检验,分析中国区域近地面CO2浓度分布的时空变化特征。结果表明:中国区域近地面CO2浓度空间分布集中,东高西低,差异显著;CO2浓度具有明显的季节变化特征,月平均浓度4月份(春季)升至最高,7月份(夏季)降至最低。结合“中国统计年鉴2012”中的2009年人口密度、能源消费总量(煤)和GDP等辅助数据对比发现:导致中国近地面CO2浓度空间分布规律的原因多种多样,不可轻易定论是人为或自然使然,需进一步深入研究。

关键词: 近地面, 时空分布, GOSAT, CO2

Abstract:

Data adopted was the official near the ground surface (975hPa) CO2 concentration L4B retrieval data products of GOSAT-the world's first Greenhouse Gases Observing Satellite "Breathing No." - with a passive infrared detector (TANSO) from June 2009 to May 2010, which was jointly developed by Japan Aerospace Exploration Agency (JAXA), Japanese Environment Agency (MOE) and the Japan Institute for Environmental Studies (NIES). Based on the ArcGIS Geostatistical Analytical Method, authenticity inspection was processed by comparing the data mentioned above with the ground observation data of the Global Atmospheric Background Station (Waliguan), in order to analyze Chinese CO2 concentration spatial and temporal variations near the ground surface. The results show that: (i) Chinese CO2 concentration near the ground surface is concentrated and has a high value in the East, a low value in the West; (ii) Chinese CO2 concentration has an obviously seasonal variation characteristic that monthly average concentration has a largest amount in April (spring) and a smallest in July (summer); (iii) Combining with 2009 Chinese population density, total energy consumption (coal), GDP and other auxiliary data from the China Statistical Yearbook 2012, we find that the reasons of Chinese CO2 spatial and temporal distribution near the ground surface are various, and cannot be attributed easily to human or nature.

Key words: CO2, near the ground surface, GOSAT, spatial and temporal distribution