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See detailIntercomparison of in-situ NDIR and column FTIR measurements of CO2 at Jungfraujoch
Schibig, M. F.; Mahieu, Emmanuel ULg; Henne, S. et al

in Atmospheric Chemistry & Physics Discussions (2016), 2016

We compare two CO2 time series measured at the High Alpine Research Station Jungfraujoch (3580 m a.s.l., Switzerland) in the period from 2005 to 2013 with an in-situ surface measurement system using a ... [more ▼]

We compare two CO2 time series measured at the High Alpine Research Station Jungfraujoch (3580 m a.s.l., Switzerland) in the period from 2005 to 2013 with an in-situ surface measurement system using a nondispersive infrared analyzer (NDIR) and a ground-based remote sensing system using solar absorption Fourier Transform Infrared spectrometry (FTIR). Although the two data sets show an absolute shift of about 13 ppm, the slopes of the annual CO2 increase are in good agreement within their uncertainties. They are 2.04 ± 0.07 ppm yr-1 and 1.97 ± 0.05 ppm yr-1 for the FTIR and the NDIR system, respectively. The seasonality of the FTIR and the NDIR system is 4.46 ± 1.11 ppm and 10.10 ± 0.73 ppm, respectively. The difference is caused by a dampening of the CO2 signal with increasing altitude due to mixing processes. While the minima of both data series occur in the middle of August, the maxima of the two datasets differ by about ten weeks, the maximum of the FTIR measurements is in middle of January, whereas the maximum of the NDIR measurements is found at the end of March. Sensitivity analyses revealed that the air masses measured by the NDIR system at the surface of Jungfraujoch are mainly influenced by central Europe, whereas the air masses measured by the FTIR system in the column above Jungfraujoch are influenced by regions as far west as the Caribbean and the United States. [less ▲]

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See detailHCOOH distributions from IASI for 2008-2014: comparison with ground-based FTIR measurements and a global chemistry-transport model
Pommier, M.; Clerbaux, C.; Coheur, P.-F. et al

in Atmospheric Chemistry & Physics Discussions (2016), 2016

Formic acid (HCOOH) is one of the most abundant volatile organic compounds in the atmosphere. It is a major contributor to rain acidity in remote areas. There are however large uncertainties on its ... [more ▼]

Formic acid (HCOOH) is one of the most abundant volatile organic compounds in the atmosphere. It is a major contributor to rain acidity in remote areas. There are however large uncertainties on its sources and sinks, and HCOOH is misrepresented by global chemistry-transport models. This work presents global distributions from 2008 to 2014 as derived from the measurements of the Infrared Atmospheric Sounding Interferometer (IASI), based on conversion factors between brightness temperature differences and representative retrieved total columns over seven regions: Africa N, Africa S, Amazonia, Atlantic, Australia, Pacific and Russia. The dependence of the thermal contrast is taking account in the conversion method. This conversion presents errors lower than 20 % for total columns ranging between 0.5 and 1 × 1016 molec/cm2 but reaches higher values, up to 78 %, for columns lower than 0.3 × 1016 molec/cm2. Signatures from biomass burning events are highlighted, such as in the Southern Hemisphere and in Russia, as well as biogenic emission sources, e.g. over Eastern US. A comparison between 2008 and 2014 with ground-based FTIR measurements obtained at 4 locations (Maido and Saint-Denis at La Réunion, Jungfraujoch and Wollongong) is shown. Although IASI columns are found to correlate well with FTIR data, a large bias (> 100 %) is found over the two sites at La Réunion. A better agreement is found at Wollongong with a negligible bias. The comparison also highlights the difficulty for IASI to retrieve the total columns over mountainous regions such as Jungfraujoch. A comparison of the retrieved columns with the global chemistry-transport model IMAGESv2 is also presented, showing the good representation of the seasonal and inter-annual cycles over America, Australia, Asia and Siberia. A global model underestimation of the distribution and a misrepresentation of the seasonal cycle over India are also noted. A small positive trend in the IASI columns is also observed over Australia, Amazonia and India over 2008–2014 (from 0.7 to 1.5 %/year), while a decrease of ~ 0.8 %/year is measured over Siberia. [less ▲]

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See detailSeasonal variability of surface and column carbon monoxide over megacity Paris, high altitude Jungfraujoch and Southern Hemispheric Wollongong stations
Té, Y; Jeseck, P; Franco, Bruno ULg et al

in Atmospheric Chemistry & Physics Discussions (2016)

Carbon monoxide (CO) is an atmospheric key species due to its toxicity and its impact on the atmospheric oxidizing capacity, both factors affecting air quality. The paper studies the altitude dependent ... [more ▼]

Carbon monoxide (CO) is an atmospheric key species due to its toxicity and its impact on the atmospheric oxidizing capacity, both factors affecting air quality. The paper studies the altitude dependent seasonal variability of CO at the three different sites Paris, Jungfraujoch and Wollongong, with an emphasis on establishing a link between the CO vertical distribution and the nature of CO emission sources. The CO seasonal variability obtained from the total columns and from the free tropospheric partial columns shows a maximum around March-April and a minimum around September-October in the Northern Hemisphere (Paris and Jungfraujoch). In the Southern Hemisphere (Wollongong) this seasonal variability is shifted by about 6 months. Satellite observations by IASI-MetOp and MOPITT instruments confirm this seasonality. Ground-based FTIR is demonstrated to provide useful complementary information due to good sensitivity in the boundary layer. In situ surface measurements of CO volume mixing ratios in Paris and at Jungfraujoch reveal a time-lag of the near surface seasonal variability of about 2 months with respect to the total column variability at the same sites. The chemical transport model GEOS-Chem is employed to interpret our observations. GEOS-Chem sensitivity runs allow identifying the emission sources influencing the seasonal cycle of CO. In Paris and on top of Jungfraujoch, the surface seasonality is mainly driven by anthropogenic emissions, while the total column seasonality is also controlled by air masses transported from distant sources. In the case of Wollongong, where the CO seasonality is mainly affected by biomass burning, no time shift is observed between surface and above the boundary layer. [less ▲]

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See detailAnalysis of the global atmospheric methane budget using ECHAM-MOZ simulations for present-day, pre-industrial time and the Last Glacial Maximum
Basu, A.; Schultz, M. G.; Schröder, S. et al

in Atmospheric Chemistry & Physics Discussions (2014), 14

Atmospheric methane concentrations increased considerably from pre-industrial (PI) to present times largely due to anthropogenic emissions. However, firn and ice core records also document a notable rise ... [more ▼]

Atmospheric methane concentrations increased considerably from pre-industrial (PI) to present times largely due to anthropogenic emissions. However, firn and ice core records also document a notable rise of methane levels between the Last Glacial Maximum (LGM) and the pre-industrial era, the exact cause of which is not entirely clear. This study investigates these changes by analyzing the methane sources and sinks at each of these climatic periods. Wetlands are the largest natural source of methane and play a key role in determining methane budget changes in particular in the absence of anthropogenic sources. Here, a simple wetland parameterization suitable for coarse-scale climate simulations over long periods is introduced, which is derived from a high- resolution map of surface slopes together with various soil hydrology parameters from the CARAIB vegetation model. This parameterization was implemented in the chem- istry general circulation model ECHAM5-MOZ and multi-year time slices were run for LGM, PI and present-day (PD) climate conditions. Global wetland emissions from our parameterization are 72 Tg yr [less ▲]

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