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A remote sensing technique for global monitoring of power plant CO2 emissions from space and related applications

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Author(s): H. Bovensmann | M. Buchwitz | J. P. Burrows | M. Reuter | T. Krings | K. Gerilowski | O. Schneising | J. Heymann | A. Tretner | J. Erzinger

Journal: Atmospheric Measurement Techniques Discussions
ISSN 1867-8610

Volume: 3;
Issue: 1;
Start page: 55;
Date: 2010;
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ABSTRACT
Carbon dioxide (CO2) is the most important anthropogenic greenhouse gas causing global warming. The atmospheric CO2 concentration increased by more than 30% since pre-industrial times – primarily due to burning of fossil fuels – and still continues to increase. Reporting of CO2 emissions is required by the Kyoto protocol. Independent verification of reported emissions, which are typially not directly measured, by methods such as inverse modeling of measured atmospheric CO2 concentrations is currently not possible globally due to lack of appropriate observations. Existing greenhouse gas observing satellites such as SCIAMACHY and GOSAT focus on advancing our understanding of natural CO2 sources and sinks. The obvious next step for future generation satellites is to also measure anthropogenic CO2 emissions. Here we present a promising satellite remote sensing technology based on spectroscopic measurements of reflected solar radiation in the short-wave infrared (SWIR) and near-infrared (NIR) spectral regions and show, using power plants as an example, that strong localized CO2 point sources can be detected and their emissions quantified. This requires mapping the CO2 column distribution at a spatial resolution of 2×2 km2 or better with a precision of about 0.5% (2 ppm) or better of the background column. We indicate that this can be achieved with existing technology. For a single satellite in sun-synchronous orbit with an across-track swath width of 500 km each power plant is overflown every 6 days or faster. Based on clear sky statistics we conservatively estimate that about one useful measurement per 1–2 months for a given power plant can typically be achieved. We found that the uncertainty of the retrieved power plant CO2 emission during a single satellite overpass is in the range 0.5–5 MtCO2/year – depending on observation conditions – which is about 2–20% of the CO2 emission of large power plants (25 Mt CO2/year). The investigated instrument aims at fulfilling all requirements for global regional-scale CO2 and CH4 surface flux inverse modeling. Using a significantly less demanding instrument concept based on a single SWIR channel we indicate that this also enables the monitoring of power plant CO2 emissions in addition to high-quality methane retrievals. The latter has already been demonstrated by SCIAMACHY. The discussed technology has the potential to significantly contribute to an independent verification of reported anthropogenic CO2 emissions and therefore could be an important component of a future global anthropogenic CO2 emission monitoring system. This is of relevance in the context of Kyoto protocol follow-on agreements but also allows to detect and monitor strong natural CO2 and CH4 emitters such as (mud) volcanoes.
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