Temporal and spatial distribution of tropospheric CO2 over China based on satellite observations

Bai, Wenguang; Zhang, Xingying; Zhang, Peng

doi:10.1007/s11434-010-4182-4

Cited by 30 publications

(19 citation statements)

References 15 publications

(17 reference statements)

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“…Surprisingly, we find that potential source regions of CO 2 are extensively distributed west of the site (Zhang et al, 2011), which was unexpected since the area is typically regarded as relatively remote and clean. High CO 2 concentrations in the area have also been retrieved based on the satellite data (Bai et al, 2010), which further indicates strong CO 2 sources. This change may be the result of emerging economies in western China during the past two decades thus leading to significant increases in CO 2 emissions.…”

Section: Resultsmentioning

confidence: 67%

Implications for CO2 emissions and sinks changes in western China during 1995–2008 from atmospheric CO2 at Waliguan

Zhang

Li-hua

2013

Tellus B: Chemical and Physical Meteorology

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A B S T R A C T Carbon dioxide (CO 2 ) emissions and sinks in western China are estimated and implied from atmospheric CO 2 measured at Waliguan during the period of 1995Á2008. The observed CO 2 data are first classified as background, elevated, and sequestration, using a modified background identification method. Comparing it with two other methods tests the applicability of the method. By using this method, approximately 17.2%91.2% and 10.1%90.8% of all observed data are identified as elevated and sequestered CO 2 , respectively, the percentages (occurrence rates) for both of which increased during 1995Á2008. CO 2 emissions in western China have enhanced significantly in all seasons during the past 14 yr. Annual mean growth rates of CO 2 emissions in the region increased by Â8.4 Tg C yr(1 (3.9% yr (1 ) during 1995Á2008 but accelerated after 2000 to Â12.6 TgC yr (1 (6.2% yr (1 ). The growth rates of CO 2 emission in western China are lower than the rest of the country. The annual mean emissions in the country during 1995Á1999 and 2000Á2006 are thought to be approximately 5.5 and 6.5 times higher than in western China, respectively. However, the growth rates of CO 2 emissions in western China are higher than global increase rates as reported by other studies. CO 2 sinks in western China varied from 86.0 Tg C yr

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Section: Resultsmentioning

confidence: 67%

Implications for CO2 emissions and sinks changes in western China during 1995–2008 from atmospheric CO2 at Waliguan

Zhang

Li-hua

2013

Tellus B: Chemical and Physical Meteorology

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“…As one of the long-lived greenhouse gases, carbon dioxide (CO 2 ) contributes greatly to global warming [1,2]. With global coverage and high measurement density, satellite observations of CO 2 provide new ways to understand the functioning of the carbon cycle [3]. Although observing at high density, these satellite observations have gaps and are irregularly positioned because of certain limitations, such as cloud and the observational mode of the satellite [4].…”

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confidence: 99%

Incorporating temporal variability to improve geostatistical analysis of satellite-observed CO2 in China

et al. 2013

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Observations of atmospheric carbon dioxide (CO 2 ) from satellites offer new data sources to understand global carbon cycling. The correlation structure of satellite-observed CO 2 can be analyzed and modeled by geostatistical methods, and CO 2 values at unsampled locations can be predicted with a correlation model. Conventional geostatistical analysis only investigates the spatial correlation of CO 2 , and does not consider temporal variation in the satellite-observed CO 2 data. In this paper, a spatiotemporal geostatistical method that incorporates temporal variability is implemented and assessed for analyzing the spatiotemporal correlation structure and prediction of monthly CO 2 in China. The spatiotemporal correlation is estimated and modeled by a product-sum variogram model with a global nugget component. The variogram result indicates a significant degree of temporal correlation within satellite-observed CO 2 data sets in China. Prediction of monthly CO 2 using the spatiotemporal variogram model and spacetime kriging procedure is implemented. The prediction is compared with a spatial-only geostatistical prediction approach using a cross-validation technique. The spatiotemporal approach gives better results, with higher correlation coefficient (r 2 ), and less mean absolute prediction error and root mean square error. Moreover, the monthly mapping result generated from the spatiotemporal approach has less prediction uncertainty and more detailed spatial variation of CO 2 than those from the spatial-only approach.CO 2 , Greenhouse Gases Observing Satellite (GOSAT), geostatistical analysis, space-time kriging, product-sum model Citation:Zeng Z C, Lei L P, Guo L J, et al. Incorporating temporal variability to improve geostatistical analysis of satellite-observed

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“…The tropospheric CO 2 products are derived by binning the Level 2 standard retrievals in a grid that is 2 deg in latitude by 2.5 deg in longitude over daily, 8-day, and monthly time spans. observation stations throughout the world 18,19 to obtain information about variations in CO 2 . Data from ground-based and aerial CO 2 measurements are available at the WMO World Data Centre for Greenhouse Gases (WMO WDCGG) web site (http://gaw.kishou.go.jp/ wdcgg/wdcgg.html).…”

Section: Ground-based Validation Of the Airs Co 2 Productmentioning

confidence: 99%

Sensitivity studies for atmospheric carbon dioxide retrieval from atmospheric infrared sounder observations

Zhou

Shu

Song

et al. 2014

J. Appl. Remote Sens

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Abstract. The atmospheric infrared sounder (AIRS) exhibits great potential for providing atmospheric observation data for long-term regional and global carbon-cycle studies, which are essential for understanding the uncertainty of climate change. The sensitivity of global atmospheric CO 2 retrieval from the AIRS observations by quantifying errors related to CO 2 measurements in the infrared spectrum is investigated. A line-by-line radiative transfer model is used to evaluate the effects of atmospheric temperature profile, water vapor profile, and ozone (O 3 ) data on the accuracy of CO 2 measurements under five standard atmospheric models. The analytical results indicate that temperature, water vapor, and O 3 are important factors, which have great influences on the sensitivity of atmospheric CO 2 retrieval from the AIRS observations. The water vapor is the most important factor in the tropics, whereas the temperature represents major interference for multitude and subarctic regions. The results imply that precise measurements of temperature, water vapor, and O 3 can improve the quality of atmospheric CO 2 data retrieved from the AIRS observations. © The Authors. Published by SPIE under a Creative Commons Attribution 3.0 Unported License. Distribution or reproduction of this work in whole or in part requires full attribution of the original publication, including its DOI.

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Temporal and spatial distribution of tropospheric CO2 over China based on satellite observations

Cited by 30 publications

References 15 publications

Implications for CO<sub>2</sub> emissions and sinks changes in western China during 1995–2008 from atmospheric CO<sub>2</sub> at Waliguan

Implications for CO<sub>2</sub> emissions and sinks changes in western China during 1995–2008 from atmospheric CO<sub>2</sub> at Waliguan

Incorporating temporal variability to improve geostatistical analysis of satellite-observed CO2 in China

Sensitivity studies for atmospheric carbon dioxide retrieval from atmospheric infrared sounder observations

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