Carbon monoxide and related trace gases and aerosols over the Amazon Basin during the wet and dry seasons

We present the results of airborne measurements of carbon monoxide (CO) and aerosol particle number concentration (CN) made during the Balan double dagger o Atmosf,rico Regional de Carbono na Amazonia (BARCA) program. The primary goal of BARCA is to address the question of basin-scale sources and sinks of CO2 and other atmospheric carbon species, a central issue of the Large-scale Biosphere-Atmosphere (LBA) program. The experiment consisted of two aircraft campaigns during November-December 2008 (BARCA-A) and May-June 2009 (BARCA-B), which covered the altitude range from the surface up to about 4500 m, and spanned most of the Amazon Basin. Based on meteorological analysis and measurements of the tracer, SF6, we found that airmasses over the Amazon Basin during the late dry season (BARCA-A, November 2008) originated predominantly from the Southern Hemisphere, while during the late wet season (BARCA-B, May 2009) low-level airmasses were dominated by northern-hemispheric inflow and mid-tropospheric airmasses were of mixed origin. In BARCA-A we found strong influence of biomass burning emissions on the composition of the atmosphere over much of the Amazon Basin, with CO enhancements up to 300 ppb and CN concentrations approaching 10 000 cm(-3); the highest values were in the southern part of the Basin at altitudes of 1-3 km. The Delta CN/Delta CO ratios were diagnostic for biomass burning emissions, and were lower in aged than in fresh smoke. Fresh emissions indicated CO/CO2 and CN/CO emission ratios in good agreement with previous work, but our results also highlight the need to consider the residual smoldering combustion that takes place after the active flaming phase of deforestation fires. During the late wet season, in contrast, there was little evidence for a significant presence of biomass smoke. Low CN concentrations (300-500 cm(-3)) prevailed basinwide, and CO mixing ratios were enhanced by only similar to 10 ppb above the mixing line between Northern and Southern Hemisphere air. There was no detectable trend in CO with distance from the coast, but there was a small enhancement of CO in the boundary layer suggesting diffuse biogenic sources from photochemical degradation of biogenic volatile organic compounds or direct biological emission. Simulations of CO distributions during BARCA-A using a range of models yielded general agreement in spatial distribution and confirm the important contribution from biomass burning emissions, but the models evidence some systematic quantitative differences compared to observed CO concentrations. These mismatches appear to be related to problems with the accuracy of the global background fields, the role of vertical transport and biomass smoke injection height, the choice of model resolution, and reliability and temporal resolution of the emissions data base.

Aerosol profiling with lidar in the Amazon Basin during the wet and dry season

For the first time, multiwavelength polarization Raman lidar observations of optical and microphysical particle properties over the Amazon Basin are presented. The fully automated advanced Raman lidar was deployed 60 km north of Manaus, Brazil (2.5 degrees S, 60 degrees W) in the Amazon rain forest from January to November 2008. The measurements thus cover both the wet season (Dec-June) and the dry or burning season (July-Nov). Two cases studies of young and aged smoke plumes are discussed in terms of spectrally resolved optical properties (355, 532, and 1064 nm) and further lidar products such as particle effective radius and single-scattering albedo. These measurement examples confirm that biomass burning aerosols show a broad spectrum of optical, microphysical, and chemical properties. The statistical analysis of the entire measurement period revealed strong differences between the pristine wet and the polluted dry season. African smoke and dust advection frequently interrupt the pristine phases during the wet season. Compared to pristine wet season conditions, the particle scattering coefficients in the lowermost 2 km of the atmosphere were found to be enhanced, on average, by a factor of 4 during periods of African aerosol intrusion and by a factor of 6 during the dry (burning) season. Under pristine conditions, the particle extinction coefficients and optical depth for 532 nm wavelength were frequently as low as 10-30 Mm(-1) and <0.05, respectively. During the dry season, biomass burning smoke plumes reached to 3-5 km height and caused a mean optical depth at 532 nm of 0.26. On average during that season, particle extinction coefficients (532 nm) were of the order of 100 Mm(-1) in the main pollution layer (up to 2 km height). Angstrom exponents were mainly between 1.0 and 1.5, and the majority of the observed lidar ratios were between 50-80 sr.

Semantic integration of gene expression analysis tools and data sources using software connectors

Abstract Background The study and analysis of gene expression measurements is the primary focus of functional genomics. Once expression data is available, biologists are faced with the task of extracting (new) knowledge associated to the underlying biological phenomenon. Most often, in order to perform this task, biologists execute a number of analysis activities on the available gene expression dataset rather than a single analysis activity. The integration of heteregeneous tools and data sources to create an integrated analysis environment represents a challenging and error-prone task. Semantic integration enables the assignment of unambiguous meanings to data shared among different applications in an integrated environment, allowing the exchange of data in a semantically consistent and meaningful way. This work aims at developing an ontology-based methodology for the semantic integration of gene expression analysis tools and data sources. The proposed methodology relies on software connectors to support not only the access to heterogeneous data sources but also the definition of transformation rules on exchanged data. Results We have studied the different challenges involved in the integration of computer systems and the role software connectors play in this task. We have also studied a number of gene expression technologies, analysis tools and related ontologies in order to devise basic integration scenarios and propose a reference ontology for the gene expression domain. Then, we have defined a number of activities and associated guidelines to prescribe how the development of connectors should be carried out. Finally, we have applied the proposed methodology in the construction of three different integration scenarios involving the use of different tools for the analysis of different types of gene expression data. Conclusions The proposed methodology facilitates the development of connectors capable of semantically integrating different gene expression analysis tools and data sources. The methodology can be used in the development of connectors supporting both simple and nontrivial processing requirements, thus assuring accurate data exchange and information interpretation from exchanged data.