ALBERT

Description: Methane (CH4) impacts climate as the second strongest anthropogenic greenhouse gas and air quality by influencing tropospheric ozone levels. Space-based observations have identified the Four Corners region in the Southwest United States as an area of large CH4 enhancements. We conducted an airborne campaign in Four Corners during April 2015...

Description: A novel light-weight, elevation scanning and absolutely calibrated UV/vis spectrometer and its application to balloon-borne limb radiance and trace gas profile measurements is described. Its performance and the novel method of balloon-borne UV/vis limb trace gas measurements has been tested against simultaneous observations of the same atmospheric parameters available from either (a) in-situ instrumentation (cf., by an electrochemical cell (ECC) ozone sonde also deployed aboard the gondola) or (b) trace gas profiles inferred from UV/vis/near IR solar occultation measurements performed on the same payload. The novel technique is also cross validated with radiative transfer modeling. Reasonable agreement is found (a) between measured and simulated limb radiances and (b) inferred limb O3, NO2, and BrO and correlative profile measurements when properly accounting for all relevant atmospheric parameters (temperature, pressure, aerosol extinction, and major absorbers).

Description: Carbon dioxide (CO2) and Methane (CH4) are the two most important anthropogenic greenhouse gases. CH4 is furthermore one of the most potent present and future contributors to global warming because of its large global warming potential (GWP). Our knowledge of CH4 sources and sinks is based primarily on sparse in-situ local point measurements from micro sites and surface networks and more recently on low spatial resolution satellite observations. There is a need for measurements of the dry columns of CO2 and CH4 having high spatial resolution and spatial coverage. In order to fill this gap a new passive airborne 2-channel grating spectrometer instrument for remote sensing of small scale and mesoscale column-averaged CH4 and CO2 observations has been developed. This Methane Airborne MAPper (MAMAP) instrument measures reflected and scattered solar radiation in the short wave infrared (SWIR) and near-infrared (NIR) parts of the electro-magnetic spectrum at moderate spectral resolution. The SWIR channel yields measurements of atmospheric absorption bands of CH4 and CO2 in the spectral range between 1.59 and 1.69 μm at a spectral resolution of 0.82 nm. The NIR channel around 0.76 μm measures the atmospheric O2-A-band absorption with a resolution of 0.46 nm. MAMAP has been designed for flexible operation aboard a variety of airborne platforms. The instrument design and performance, together with some results from on-ground and in-flight engineering tests are presented. The instrument performance has been analyzed using a retrieval algorithm applied to the SWIR channel nadir measured spectra. The signal-to-noise ratio (SNR) of the SWIR channel is approximately 1000 for integration times (tint) in the range of 0.6–0.8 s for scenes with surface spectral reflectances of around 0.18. At these integration times the ground scene size is about 23×33 m2 for an aircraft altitude of 1 km and a ground speed of 200 km/h. For these scenes the CH4 and CO2 column retrieval precisions are typically about 1% (1 σ). Elevated levels of CH4 have been retrieved above a CH4 emitting landfill. Similarly the plume of CO2 from coal-fired power plants can be well detected and tracked. The measurements by the MAMAP sensor enable estimates of anthropogenic, biogenic and geological emissions of localized intense CH4 and CO2 sources such as anthropogenic fugitive emissions from gas industry and waste, emissions from coal-fired power plants or geologic emissions from seepage and volcanoes. Appropriate analysis of the measurements of MAMAP potentially also yields CH4 emissions from less intense but extensive sources such as wetlands.

Description: Within the framework of the ENVISAT/-SCIAMACHY satellite validation, solar irradiance spectra are absolutely measured at moderate resolution in the UV/visible spectral range (in the UV from 316.7-418 nm and the visible from 400-652 nm at a full width half maximum resolution of 0.55 nm and 1.48 nm, respectively) from aboard the azimuth-controlled LPMA/DOAS balloon gondola at around 32 km balloon float altitude. After accounting for the atmospheric extinction due to Rayleigh scattering and gaseous absorption (O3 and NO2), the measured solar spectra are compared with previous observations. Our solar irradiance spectrum perfectly agrees within +0.03% with the re-calibrated Kurucz et al. (1984) solar spectrum (Fontenla et al., 1999, called MODTRAN 3.7) in the visible spectral range (415-650 nm), but it is +2.1% larger in the (370-415 nm) wavelength interval, and -4% smaller in the UV-A spectral range (316.7-370 nm), when the Kurucz spectrum is convolved to the spectral resolution of our instrument. Similar comparisons of the SOLSPEC (Thuillier et al., 1997, 1998a, b) and SORCE/SIM (Harder et al., 2000) solar spectra with MODTRAN 3.7 confirms our findings with the values being -0.5%, +2%, and -1.4% for SOLSPEC -0.33%, -0.47%, and -6.2% for SORCE/SIM, respectively. Comparison of the SCIAMACHY solar spectrum from channels 1 to 4 (- re-calibrated by the University of Bremen -) with MODTRAN 3.7 indicates an agreement within -0.4% in the visible spectral range (415-585 nm), -1.6% within the 370-415 nm, and -5.7% within 325-370 nm wavelength interval, in agreement with the results of the other sensors. In agreement with findings of Skupin et al. (2002) our study emphasizes that the present ESA SCIAMACHY level 1 calibration is systematically +15% larger in the considered wavelength intervals when compared to all available other solar irradiance measurements.

Description: Aerosol remote sensing is very much dependent on the accurate knowledge of the top-of-atmosphere (TOA) reflectance measured by a particular instrument. The status of the calibration of such an instrument is reflected in the quality of the aerosol retrieval. Current data of the SCIAMACHY (SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY) instrument (operated with the data processor version 5 and earlier) give too small values of the TOA reflectance, compared e.g. to data from MERIS (Medium Resolution Imaging Spectrometer), both operating on ENVISAT (ENVIronmental SATellite). This effect causes retrievals of wrong aerosol optical thickness and disables the processing of aerosol parameters. From an inter-comparison of MERIS and SCIAMACHY TOA reflectance, for collocated scenes correction factors are derived to improve the insufficient SCIAMACHY L1 data calibration for data obtained with the processor 5 for the purpose of aerosol remote sensing. The corrected reflectance has been used for tests of remote sensing of the aerosol optical thickness by the BAER (Bremen AErosol Retrieval) approach using SCIAMACHY data.

Description: The SemiAnalytical CloUd Retrieval Algorithm (SACURA) is applied to the SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY (SCIAMACHY) data. In particular, we derive simultaneously cloud optical thickness (COT) and cloud top height (CTH), using SCIAMACHY measurements in the visible (442 nm, COT) and in the oxygen A-band (755–775 nm, CTH). Some of the results obtained are compared with those derived from the Medium Resolution Imaging Spectrometer (MERIS), which has better spatial resolution and observes almost the same scene as SCIAMACHY. The same cloud algorithm is applied to both MERIS and SCIAMACHY data. In addition, we perform the vicarious calibration of SCIAMACHY at the wavelength 442 nm, using MERIS measurements at the same wavelength. Differences in the retrieved COT for the same cloud field obtained using MERIS and SCIAMACHY measurements are discussed.

Description: MAMAP is an airborne passive remote sensing instrument designed for measuring columns of methane (CH4) and carbon dioxide (CO2). The MAMAP instrument consists of two optical grating spectrometers: One in the short wave infrared band (SWIR) at 1590–1690 nm to measure CO2 and CH4 absorptions and another one in the near infrared (NIR) at 757–768 nm to measure O2 absorptions for reference purposes. MAMAP can be operated in both nadir and zenith geometry during the flight. Mounted on an airplane MAMAP can effectively survey areas on regional to local scales with a ground pixel resolution of about 29 m × 33 m for a typical aircraft altitude of 1250 m and a velocity of 200 km h−1. The retrieval precision of the measured column relative to background is typically ≲ 1% (1σ). MAMAP can be used to close the gap between satellite data exhibiting global coverage but with a rather coarse resolution on the one hand and highly accurate in situ measurements with sparse coverage on the other hand. In July 2007 test flights were performed over two coal-fired powerplants operated by Vattenfall Europe Generation AG: Jänschwalde (27.4 Mt CO2 yr−1) and Schwarze Pumpe (11.9 Mt CO2 yr−1), about 100 km southeast of Berlin, Germany. By using two different inversion approaches, one based on an optimal estimation scheme to fit Gaussian plume models from multiple sources to the data, and another using a simple Gaussian integral method, the emission rates can be determined and compared with emissions as stated by Vattenfall Europe. An extensive error analysis for the retrieval's dry column results (XCO2 and XCH4) and for the two inversion methods has been performed. Both methods – the Gaussian plume model fit and the Gaussian integral method – are capable of delivering reliable estimates for strong point source emission rates, given appropriate flight patterns and detailed knowledge of wind conditions.

Description: The quantification of emissions of the greenhouse gas methane is essential for attributing the roles of anthropogenic activity and natural phenomena in global climate change. Our current measurement systems and networks whilst having improved during the last decades, are deficient in many respects. For example, the emissions from localised and point sources such as landfills or fossil fuel exploration sites are not readily assessed. A tool developed to better understand point sources of the greenhouse gases carbon dioxide and methane is the optical remote sensing instrument MAMAP, operated from aircraft. After a recent instrument modification, retrievals of the column averaged dry air mole fractions for methane XCH4 (or for carbon dioxide XCO2) derived from MAMAP data, have a precision of about 0.4% or better and thus can be used to infer emission rate estimates using an optimal estimation inverse Gaussian plume model or a simple integral approach. CH4 emissions from two coal mine ventilation shafts in Western Germany surveyed during the AIRMETH 2011 measurement campaign are used as examples to demonstrate and assess the value of MAMAP data for quantifying CH4 from point sources. While the knowledge of the wind is an important input parameter in the retrieval of emissions from point sources and is generally extracted from models, additional information from a turbulence probe operated on-board the same aircraft was utilised to enhance the quality of the emission estimates. Although flight patterns were optimised for remote sensing measurements, data from an in-situ analyser for CH4 were found to be in good agreement with retrieved dry columns of CH4 from MAMAP and could be used to investigate and refine underlying assumptions for the inversion procedures. With respect to the total emissions of the mine at the time of the overflight, the inferred emission rate of 50.4 kt CH4 yr−1 has a difference of less than 1% compared to officially reported values by the mine operators, while the uncertainty, which reflects variability of the sources and conditions as well as random and systematic errors, is about ±13.5%.

Description: 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 as 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.) 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 can verify reported US annual CO2 emissions from large power plants (≥5 Mt CO2 yr−1) with a systematic error of less than ~4.9 % for 50 % of all the power plants. For 90 % of all the power plants, the systematic error was less than ~12.4 %. 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. Finally, we recommend the CarbonSat constellation configuration that achieves daily global coverage.

Description: 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.