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| Titel |
Refined estimate of China's CO2 emissions in spatiotemporal distributions |
| VerfasserIn |
M. Liu, H. Wang, H. Wang, T. Oda, Y. Zhao, X. Yang, R. Zang, B. Zang, J. Bi, J. Chen |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
1680-7316
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| Digitales Dokument |
URL |
| Erschienen |
In: Atmospheric Chemistry and Physics ; 13, no. 21 ; Nr. 13, no. 21 (2013-11-07), S.10873-10882 |
| Datensatznummer |
250085800
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| Publikation (Nr.) |
 copernicus.org/acp-13-10873-2013.pdf |
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| Zusammenfassung |
| Being the largest contributor to the global source of
fossil-fuel CO2 emissions, China's emissions need to be accurately
quantified and well understood. Previous studies have usually focused on the
amount of national emissions and rarely discussed their spatiotemporal
distributions, which are also crucial for both carbon flux and carbon
management. In this study, we calculated China's CO2 emissions from
fossil fuel use and industrial processes using provincial statistics and then
mapped those emissions at 0.25° resolution on a monthly basis. Several
key steps have been implemented to gain a better understanding of the
spatiotemporal distributions, including (1) development and application of
China's CO2 emission inventories using provincial statistics; (2)
separate calculations of emissions from large point sources and accurate
identification of their geographical locations; (3) development of
1 km × 1 km gridded population and GDP (gross domestic product) data for China from 2000 to
2009 and application of them as dynamic spatial proxies to allocate
emissions; and (4) monthly variation curves of CO2 emissions from
various sectors that were developed for each province and applied to our
inventory. China's total CO2 emission from fossil fuels and industrial
processes has increased from 3.6 billion tons in 2000 to 8.6 billion tons in
2009, which may be off by 14–18% and is enough to skew global totals.
The resulting spatiotemporal distributions of our inventories also differed
greatly in several ways from those derived using a national statistics and
population-based approach for the various economic development levels,
industrial and energy structures, and even large point emission sources
within China and each province. |
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