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Improving Spatial Estimates of Greenhouse Gas Emissions at a Fine Resolution: A Review of Approaches

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Part of the book series: Studies in Computational Intelligence ((SCI,volume 634))

Abstract

The paper presents a review of the methods which can be useful in quantification of greenhouse gas (GHG) emissions at a fine spatial resolution. The discussed approaches include: spatial disaggregation of GHG emissions based on proxy data and/or statistical modeling of spatial correlation, an estimation of fossil fuel emission changes from measuring rates (mixing ratios) of tracer (like \(^{14}\)CO\(_{2}\)) concentrations in the atmosphere, the atmospheric inversion methods, and flux tower observations.

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Acknowledgments

This study was partly conducted within the 7th FP Marie Curie Actions project Geoinformation technologies, spatio-temporal approaches, and full carbon account for improving accuracy of GHG inventories, Grant Agreement No. PIRSES-GA-2009-247645. Joanna Horabik-Pyzel was supported by the Foundation for Polish Science under International PhD Projects in Intelligent Computing; project financed from The European Union within the Innovative Economy Operational Programme 2007–2013 and European Regional Development Fund.

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Horabik-Pyzel, J., Nahorski, Z. (2016). Improving Spatial Estimates of Greenhouse Gas Emissions at a Fine Resolution: A Review of Approaches. In: Trė, G., Grzegorzewski, P., Kacprzyk, J., Owsiński, J., Penczek, W., Zadrożny, S. (eds) Challenging Problems and Solutions in Intelligent Systems. Studies in Computational Intelligence, vol 634. Springer, Cham. https://doi.org/10.1007/978-3-319-30165-5_12

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