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| Titel |
Towards space based verification of CO2 emissions from strong localized sources: fossil fuel power plant emissions as seen by a CarbonSat constellation |
| VerfasserIn |
V. A. Velazco, M. Buchwitz, H. Bovensmann, M. Reuter, O. Schneising, J. Heymann, T. Krings, K. Gerilowski, J. P. Burrows |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
1867-1381
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| Digitales Dokument |
URL |
| Erschienen |
In: Atmospheric Measurement Techniques ; 4, no. 12 ; Nr. 4, no. 12 (2011-12-21), S.2809-2822 |
| Datensatznummer |
250002155
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| Publikation (Nr.) |
 copernicus.org/amt-4-2809-2011.pdf |
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| Zusammenfassung |
| Carbon dioxide (CO2) is the most important man-made greenhouse
gas (GHG) that cause global warming. With electricity generation through
fossil-fuel power plants now being the economic sector with the largest
source of CO2, power plant emissions monitoring has become
more important than ever in the fight against global warming. In a
previous study done by Bovensmann et al. (2010), random and systematic
errors of power plant CO2 emissions have been quantified
using a single overpass from a proposed CarbonSat instrument. In this
study, we quantify errors of power plant annual emission estimates
from a hypothetical CarbonSat and constellations of several CarbonSats
while taking into account that power plant CO2 emissions
are time-dependent. Our focus is on estimating systematic errors arising
from the sparse temporal sampling as well as random errors that are
primarily dependent on wind speeds. We used hourly emissions data
from the US Environmental Protection Agency (EPA) combined with
assimilated and re-analyzed meteorological fields from the National
Centers of Environmental Prediction (NCEP). CarbonSat orbits were
simulated as a sun-synchronous low-earth orbiting satellite (LEO)
with an 828-km orbit height, local time ascending node (LTAN) of 13:30
(01:30 p.m. LT) and achieves global coverage after 5 days. We show, that
despite the variability of the power plant emissions and the limited
satellite overpasses, one CarbonSat has the potential to verify reported
US annual CO2 emissions from large power plants (≥5 Mt CO2 yr−1)
with a systematic error of less than ~4.9%
and a random error of less than ~6.7% for 50% of
all the power plants. For 90% of all the power plants, the systematic
error was less than ~12.4% and the random error was
less than ~13%. We additionally investigated two
different satellite configurations using a combination of 5 CarbonSats.
One achieves global coverage everyday but only samples the targets
at fixed local times. The other configuration samples the targets
five times at two-hour intervals approximately every 6th
day but only achieves global coverage after 5 days. From the statistical
analyses, we found, as expected, that the random errors improve by
approximately a factor of two if 5 satellites are used. On the other
hand, more satellites do not result in a large reduction of the systematic
error. The systematic error is somewhat smaller for the CarbonSat
constellation configuration achieving global coverage everyday. Therefore,
we recommend the CarbonSat constellation configuration that achieves
daily global coverage. |
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