Showing papers by "Michel Ramonet published in 2010"

CO2 surface fluxes at grid point scale estimated from a global 21 year reanalysis of atmospheric measurements

Abstract: This paper documents a global Bayesian variational inversion of CO2 surface fluxes during the period 1988-2008. Weekly fluxes are estimated on a 3.75 degrees x 2.5 degrees (longitude-latitude) grid throughout the 21 years. The assimilated observations include 128 station records from three large data sets of surface CO2 mixing ratio measurements. A Monte Carlo approach rigorously quantifies the theoretical uncertainty of the inverted fluxes at various space and time scales, which is particularly important for proper interpretation of the inverted fluxes. Fluxes are evaluated indirectly against two independent CO2 vertical profile data sets constructed from aircraft measurements in the boundary layer and in the free troposphere. The skill of the inversion is evaluated by the improvement brought over a simple benchmark flux estimation based on the observed atmospheric growth rate. Our error analysis indicates that the carbon budget from the inversion should be more accurate than the a priori carbon budget by 20% to 60% for terrestrial fluxes aggregated at the scale of subcontinental regions in the Northern Hemisphere and over a year, but the inversion cannot clearly distinguish between the regional carbon budgets within a continent. On the basis of the independent observations, the inversion is seen to improve the fluxes compared to the benchmark: the atmospheric simulation of CO2 with the Bayesian inversion method is better by about 1 ppm than the benchmark in the free troposphere, despite possible systematic transport errors. The inversion achieves this improvement by changing the regional fluxes over land at the seasonal and at the interannual time scales. (Less)

Inverse modeling of European CH4 emissions 2001-2006

Abstract: European CH4 emissions are estimated for the period 2001-2006 using a four-dimensional variational (4DVAR) inverse modeling system, based on the atmospheric zoom model TM5. Continuous observations are used from various European monitoring stations, complemented by European and global flask samples from the NOAA/ESRL network. The available observations mainly provide information on the emissions from northwest Europe (NWE), including the UK, Ireland, the BENELUX countries, France and Germany. The inverse modeling estimates for the total anthropogenic emissions from NWE are 21% higher compared to the EDGARv4.0 emission inventory and 40% higher than values reported to U.N. Framework Convention on Climate Change. Assuming overall uncertainties on the order of 30% for both bottom-up and top-down estimates, all three estimates can be still considered to be consistent with each other. However, the uncertainties in the uncertainty estimates prevent us from verifying (or falsifying) the bottom-up inventories in a strict sense. Sensitivity studies show some dependence of the derived spatial emission patterns on the set of atmospheric monitoring stations used, but the total emissions for the NWE countries appear to be relatively robust. While the standard inversions include a priori information on the spatial and temporal emission patterns from bottom-up inventories, a further sensitivity inversion without this a priori information results in very similar NWE country totals, demonstrating that the available observations provide significant constraints on the emissions from the NWE countries independent from bottom-up inventories.

Recent acceleration of the sea surface fCO2 growth rate in the North Atlantic subpolar gyre (1993–2008) revealed by winter observations

Abstract: [1] Recent studies based on ocean and atmospheric carbon dioxide (CO2) observations, suggesting that the ocean carbon uptake has been reduced, may help explain the increase in the fraction of anthropogenic CO2 emissions that remain in the atmosphere. Is it a response to climate change or a signal of ocean natural variability or both? Regional process analyses are needed to follow the ocean carbon uptake and to enable better attributions of the observed changes. Here, we describe the evolution of the surface ocean CO2 fugacity (fCO2oc) over the period 1993–2008 in the North Atlantic subpolar gyre (NASPG). This analysis is based primarily on observations of dissolved inorganic carbon (DIC) and total alkalinity (TA) conducted at different seasons in the NASPG between Iceland and Canada. The fCO2oc trends based on DIC and TA data are also compared with direct fCO2 measurements obtained between 2003 and 2007 in the same region. During winters 1993–2003, the fCO2oc growth rate was 3.7 (±0.6) μatm yr−1, higher than in the atmosphere, 1.8 (±0.1) μatm yr−1. This translates to a reduction of the ocean carbon uptake primarily explained by sea surface warming, up to 0.24 (±0.04) °C yr−1. This warming is a consequence of advection of warm water northward from the North Atlantic into the Irminger basin, which occurred as the North Atlantic Oscillation (NAO) index moved into a negative phase in winter 1995/1996. In winter 2001–2008, the fCO2oc rise was particularly fast, between 5.8 (±1.1) and 7.2 (±1.3) μatm yr−1 depending on the region, more than twice the atmospheric growth rate of 2.1 (±0.2) μatm yr−1, and in the winter of 2007–2008 the area was supersaturated with CO2. As opposed to the 1990s, this appears to be almost entirely due to changes in seawater carbonate chemistry, the combination of increasing DIC and decreasing of TA. The rapid fCO2oc increase was not only driven by regional uptake of anthropogenic CO2 but was also likely controlled by a recent increase in convective processes-vertical mixing in the NASPG and cannot be directly associated with NAO variability. The fCO2oc increase observed in 2001–2008 leads to a significant drop in pH of −0.069 (±0.007) decade−1.

Relations source-récepteur transcontinentales identifiées avec un modèle Lagrangien de dispersion et une analyse en clusters Transcontinental source-receptor relationships identified with a Lagrangian dispersion model and cluster analysis

Abstract: Long range transport of pollutants has the ability to degrade air quality far from emissions sources. We describe a recently developed technique for the analysis of pollutantʼs measurements that allows the identification of systematic source-receptor relationship across an observational dataset. This technique uses a Lagrangian particles dispersion model (LPDM). LPDMs calculate retroplumes that represent potential emission sensitivity (PES) for individual measurements. The PESs can be grouped according to their similarities by using a clustering algorithm. Grouping PES can inform about the impact of various patterns of long range transport on the measurements, and has the ability to deconvolve atmospheric mixing from the impact of surface emissions. We apply our method to measurements above Siberia, and found that ~20 ppb excess carbon monoxide (CO) over background is related to long range transport of biomass burning emissions in Kazakhstan, and ~10 ppb excess CO are associated to European emissions. We highlight the advantage of our method over traditional methods for the establishment of source-receptor relationships in long range transport studies.

Relations source-récepteur transcontinentales identifiées avec un modèle Lagrangien de dispersion et une analyse en clusters

Abstract: Le transport des polluants a longue distance peut provoquer une degradation de la qualite de lʼair loin des sources dʼemissions. Nous decrivons ici une technique recemment developpee pour lʼanalyse des mesures de polluants, qui permet lʼidentification systematique de relations source-recepteur a travers un jeu dʼobservations. Cette technique utilise un modele lagrangien de dispersion de particules (MLDP). Les MLDP calculent des retropanaches qui representent la sensibilite aux emissions potentielles (SEP) pour des mesures individuelles. Les SEP peuvent etre regroupees selon leurs ressemblances en utilisant un algorithme de clustering. La classification des SEP peut informer sur lʼimpact de differents modes de transport a longue distance sur les mesures, et permet de deconvoluer le melange atmospherique de lʼimpact des emissions de surface. Nous appliquons notre methode a des mesures au-dessus de la Siberie, et constatons quʼun exces de ~ 20 ppb de monoxyde de carbone (CO) par rapport aux concentrations de fond est explique par le transport a longue distance dʼemissions provenant de la combustion de biomasse au Kazakhstan, et que ~10 ppb dʼexces de CO sont associes a des emissions europeennes. Nous mettons en avant lʼavantage de notre methode par rapport aux methodes traditionnelles pour lʼetablissement de relations source-recepteur dans les etudes du transport a longue distance.