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Spatio-temporal statistical assessment of anthropogenic CO2 emissions from satellite data

Author

Listed:
  • Patrick Vetter

    (Faculty of Business Administration and Economics, European University Viadrina, Frankfurt (Oder))

  • Wolfgang Schmid

    (Faculty of Business Administration and Economics, European University Viadrina, Frankfurt (Oder))

  • Reimund Schwarze

    (Europa University Viadrina and Helmholtz Centre for Environmental Research (UFZ))

Abstract

The analysis of sources and sinks of CO2 is a dominant topic in diverse research fields and in political debates these days. The threat of climate change fosters the research efforts in the natural sciences in order to quantify the carbon sequestration potential of the terrestrial ecosystem and CO2 mitigation negotiations strengthens the need for a transparent, consistent and verifiable Moni- toring, Verification and Reporting infrastructure. This paper provides a spatio-temporal statistical modeling framework, which allows for a quantification of the Net Ecosystem Production and of anthropogenic sources, based on satellite data for surface CO2 concentrations and source and sink connected covariates. Using spatial and temporal latent random effects, that act as space-time varying coefficients, the complex dependence structure can be modeled adequately. Finally, spatio-temporal smoothed estimates for the sources and sinks can be used to provide dynamic maps on 0.5 × 0.5 grid for the Eurasien area in intervals of 16 days between September 2009 and August 2012. Finally, the self-reported CO2 emissions within the UNFCCC can be compared with the model results.

Suggested Citation

  • Patrick Vetter & Wolfgang Schmid & Reimund Schwarze, 2016. "Spatio-temporal statistical assessment of anthropogenic CO2 emissions from satellite data," Discussion Paper Series RECAP15 24, RECAP15, European University Viadrina, Frankfurt (Oder).
  • Handle: RePEc:euv:dpaper:24
    as

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    File URL: https://www.europa-uni.de/de/forschung/institut/recap15/downloads/recap15_DP024.pdf
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    References listed on IDEAS

    as
    1. Wenceslao González‐Manteiga & Rosa M. Crujeiras & Matthias Katzfuss & Noel Cressie, 2012. "Bayesian hierarchical spatio‐temporal smoothing for very large datasets," Environmetrics, John Wiley & Sons, Ltd., vol. 23(1), pages 94-107, February.
    2. Patrick Vetter & Wolfgang Schmid & Reimund Schwarze, 2016. "Spatio-temporal statistical analysis of the carbon budget of the terrestrial ecosystem," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 25(1), pages 143-161, March.
    3. Kanti Mardia & Colin Goodall & Edwin Redfern & Francisco Alonso, 1998. "The Kriged Kalman filter," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 7(2), pages 217-282, December.
    4. Patrick Vetter & Wolfgang Schmid & Reimund Schwarze, 2013. "Efficient Approximation of the Spatial Covariance Function for Large Datasets - Analysis of Atmospheric CO2 Concentrations," Discussion Paper Series RECAP15 009, RECAP15, European University Viadrina, Frankfurt (Oder).
    5. Matthias Katzfuss & Noel Cressie, 2011. "Spatio‐temporal smoothing and EM estimation for massive remote‐sensing data sets," Journal of Time Series Analysis, Wiley Blackwell, vol. 32, pages 430-446, July.
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    More about this item

    Keywords

    Anthropogenic CO2 emissions; Net Ecosystem Production; Linear mixed effects; Spatio- temporal model;
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