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| Titel |
Detection from space of a reduction in anthropogenic emissions of nitrogen oxides during the Chinese economic downturn |
| VerfasserIn |
J.-T. Lin, M. B. McElroy |
| 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 ; 11, no. 15 ; Nr. 11, no. 15 (2011-08-10), S.8171-8188 |
| Datensatznummer |
250009997
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| Publikation (Nr.) |
 copernicus.org/acp-11-8171-2011.pdf |
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| Zusammenfassung |
| Rapid economic and industrial development in China and relatively weak
emission controls have resulted in significant increases in emissions of
nitrogen oxides (NOx) in recent years, with the exception of late 2008 to
mid 2009 when the economic downturn led to emission reductions detectable
from space. Here vertical column densities (VCDs) of tropospheric NO2
retrieved from satellite observations by SCIAMACHY, GOME-2 and OMI (both by
KNMI and by NASA) are used to evaluate changes in emissions of NOx from
October 2004 to February 2010 identifying impacts of the economic downturn.
Data over polluted regions of Northern East China suggest an increase of
27–33 % in 12-month mean VCD of NO2 prior to the downturn, consistent
with an increase of 49 % in thermal power generation (TPG) reflecting the
economic growth. More detailed analysis is used to quantify changes in
emissions of NOx in January over the period 2005–2010 when the effect of
the downturn was most evident. The GEOS-Chem model is employed to evaluate
the effect of changes in chemistry and meteorology on VCD of NO2. This
analysis indicates that emissions decreased by 20 % from January 2008 to
January 2009, close to the reduction of 18 % in TPG that occurred over the
same interval. A combination of three independent approaches indicates that
the economic downturn was responsible for a reduction in emissions by
9–11 % in January 2009 with an additional decrease of 10 % attributed to
the slow-down in industrial activity associated with the coincident
celebration of the Chinese New Year; errors in the estimate are most likely
less than 3.4 %. |
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