ARTICLES

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

Expand
  • Institute Of Remote Sensing and Digital Earth, CAS, Beijing 100101, China

Received date: 2013-05-23

  Revised date: 2013-10-20

  Online published: 2014-03-10

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.

Cite this article

ZHAO Jing, CUI Weihong . Spatial and Temporal Distribution Characteristics of CO2 Column Concentration in China from 2009 to 2010[J]. Journal of Geo-information Science, 2014 , 16(2) : 207 -213 . DOI: 10.3724/SP.J.1047.2014.00207

References

[1] 白文广,张兴赢,张鹏.卫星遥感监测中国地区对流层二氧化碳时空变化特征分析[J].科学通报,2010,55(30):2953-2960.

[2] 戴丽君,崔伟宏.2003-2010年中国对流层CO2时空分布研究[J].生态环境学报,2012,21(7):1266-1270.

[3] 李红林,张春华,王伟华.新一代温室气体观测卫星(GOSAT、OCO)传感器设置[J].气象科技,2011,39(5):603-607.

[4] 张兴赢,张鹏,方宗义,等.应用卫星遥感技术监测大气痕量气体的研究进展[J].气象,2007,33(7):3-14.

[5] Fan S, Gloor M, Mahlman J, et al. A large terrestrial carbon sink in north america implied by atmospheric and oceanic carbon dioxide data and models[J]. Science, 1998,282(5388):442-446.

[6] Aumann H H, Chahine M T, Gautier C, et al. AIRS/AMSU/HSB on the aqua mission: Design, science objectives, data products, and processing systems[J]. IEEE Transactions on Geoscience and Remote Sensing, 2003,41(2):253-264.

[7] Buchwitz M, de Beek R, Noël S, et al. Atmospheric carbon gases retrieved from SCIAMACHY by WFM-DOAS: Version 0.5 CO and CH4 and impact of calibration improvements on CO2 retrieval[J]. Atmospheric Chemistry and Physics, 2006,6(9):2727-2751.

[8] Crevoisier C, Chédin A, H Matsueda, et al. First year of upper tropospheric integrated content of CO2 from IASI hyperspectral infrared observations[J]. Atmospheric Chemistry and Physics, 2009,9(14):4797-4810.

[9] Yokota T, Yoshida Y, Eguchi N, et al. Global concentrations of CO2 and CH4 retrieved from GOSAT: First preliminary results[J]. Scientific Online Letters on the Atmosphere, 2009(5):160-163.

[10] 刘毅,吕达仁,陈洪滨,等.卫星遥感大气CO2的技术与方法进展综述[J].遥感技术与应用,2011,26(2):247-254.

[11] Crisp D, Atlas R M, Breon F M, et al. The orbiting carbon observatory (OCO) mission[J]. Advances in Space Research, 2004,34(4):700-709.

[12] 崔伟宏,S.弗雷德·辛格,万森·库尔提欧,等.自然是气候变化的主要驱动因素[M].北京:中国科学技术出版社,2012,154-178.

[13] 朱小花,王荣辉.基于GIS的开发区土地集约利用潜力微观评价及空间分异规律研究[C].第十三届华东六省一市测绘学会学术交流会,中国江苏南京, 2011,179-182.

[14] NIES. GOSAT level 4 data product format description[J]. National Institute for Environmental Studies GOSAT Project Office, 2012.

[15] NIES. GOSAT level 4 data product(Version 02.01)release note[J]. National Institute for Environmental Studies GOSAT Project Office, 2012.

[16] Gerbig C, Lin J C, Wofsy S C, et al. Toward constraining regional-scale fluxes of CO2 with atmospheric observations over a continent: 2. Analysis of cobra data using a receptor-oriented framework[J]. Journal of Geophysical Research, 2003, 108: 4757. doi:10.1029/2003JD003770.

[17] Tiwari Y K, Gloor M, Engelen R J, et al. Comparing CO2 retrieved from Atmospheric Infrared Sounder with model predictions: Implications for constraining surface fluxes and lower-to-upper troposphere transport[J]. Journal of Geophysical Research: Atmospheres (1984-2012), 2006, 111: D17106, dio: 10.1029/2005JD006681.

Outlines

/