Thermochemical equilibrium modeling of biomass downdraft gasifier: Stoichiometric models

The aim of this work is to develop stoichiometric equilibrium models that permit the study of parameters effect in the gasification process of a particular feedstock. In total four models were tested in order to determine the syngas composition. One of these four models, called M2, was based on the theoretical equilibrium constants modified by two correction factors determined using published experimental data. The other two models, M3 and M4 were based in correlations, while model M4 was based in correlations to determine the equilibrium constants, model M3 was based in correlations that relate the H-2, CO and CO2 content on the synthesis gas. Model M2 proved to be the more accurate and versatile among these four models, and also showed better results than some previously published models. Also a case study for the gasification of a blend of hardwood chips and glycerol at 80% and 20% respectively, was performed considering equivalence ratios form 0.3 to 0.5, moisture contents from 0%-20% and oxygen percentages in the gasification agent of 100%, 60% and 21%. (C) 2013 Elsevier Ltd. All rights reserved.

Amazon forest biomass density maps: tackling the uncertainty in carbon emission estimates

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Prediction of the combustion process in fluidized bed based on physical-chemical properties of biomass particles and their hydrodynamic behaviors

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Assessment of fungi in soils of sugarcane crops and their potential for production of biomass-degrading enzymes

Soil management practices are konwn to affect the biomass and enzyme activities of microbial soil communities. To assess whether burning of sugarcane prior to harvesting affects the community of soilborne fungi, we collected soil simples in two sites: burned sugarcane culture prior harvesting (BS) and non-burned sugarcane culture (NBS). A total of 75 filamentous fungal isolates were recovered from soils in both sites. Trichoderma was the most prevalent genus in both sites, followed by Fusarium, Cunninghamella and Aspergillus. The Sorensen's index (0.60) suggested a slight difference in fungi associated with both areas, with high number of fungal isolates found on BB soil. The abundance of Trichoderma isolates in NBS soil was higher than BS soil; however, the abundance of Fusarium, Aspergillus and Cunninghamella was higher in the latter type of soil. In addition, fungi isolated from BS soil showed the highest production of xylanase and laccase in comparision with fungi isolated form NBS soil. Our results indicate that the different types of sugarcane harvesting apparently did not interfere with the diversity of fungal communnities as revealed by culture-dependent methods. In addition, our data indicates the potencial of fungi from soils of sugarcane crops to produce relevant enzymes related to biomass conversion.

Allometric equations for estimating tree biomass in restored mixed-species Atlantic Forest stands

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Biomass burning fuel consumption rates: a field measurement database

Landscape fires show large variability in the amount of biomass or fuel consumed per unit area burned. Fuel consumption (FC) depends on the biomass available to burn and the fraction of the biomass that is actually combusted, and can be combined with estimates of area burned to assess emissions. While burned area can be detected from space and estimates are becoming more reliable due to improved algorithms and sensors, FC is usually modeled or taken selectively from the literature. We compiled the peerreviewed literature on FC for various biomes and fuel categories to understand FC and its variability better, and to provide a database that can be used to constrain biogeochemical models with fire modules. We compiled in total 77 studies covering 11 biomes including savanna (15 studies, average FC of 4.6 t DM (dry matter) ha 1 with a standard deviation of 2.2), tropical forest (n = 19, FC = 126 +/- 77), temperate forest (n = 12, FC = 58 +/- 72), boreal forest (n = 16, FC = 35 +/- 24), pasture (n = 4, FC = 28 +/- 9.3), shifting cultivation (n = 2, FC = 23, with a range of 4.0-43), crop residue (n = 4, FC = 6.5 +/- 9.0), chaparral (n = 3, FC = 27 +/- 19), tropical peatland (n = 4, FC = 314 +/- 196), boreal peatland (n = 2, FC = 42 [42-43]), and tundra (n = 1, FC = 40). Within biomes the regional variability in the number of measurements was sometimes large, with e. g. only three measurement locations in boreal Russia and 35 sites in North America. Substantial regional differences in FC were found within the defined biomes: for example, FC of temperate pine forests in the USA was 37% lower than Australian forests dominated by eucalypt trees. Besides showing the differences between biomes, FC estimates were also grouped into different fuel classes. Our results highlight the large variability in FC, not only between biomes but also within biomes and fuel classes. This implies that substantial uncertainties are associated with using biome-averaged values to represent FC for whole biomes. Comparing the compiled FC values with co-located Global Fire Emissions Database version 3 (GFED3) FC indicates that modeling studies that aim to represent variability in FC also within biomes, still require improvements as they have difficulty in representing the dynamics governing FC.