Ruminal methane emission by dairy cattle in Southeast Brazil

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Influence of different supplements and sugarcane (Saccharum officinarum L.) cultivars on intake, digestible variables and methane production of dairy heifers under tropical conditions

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Laboratory evaluation of Amazon forest biomass burning emissions

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

Straightforward systematic approach for fuel efficiency and emissions assessment in automotive systems

At this time, each major automotive market bares its own standards and test procedures to regulate the vehicle green house gases emissions and, thus, fuel consumption. Hence, much are the ways to evaluate the overall efficiency of motor vehicles. The majority of such standards rely on dynamometer cycle tests that appraise only the vehicle as a whole, but fail to assess emissions for each component or sub-system. Once the amount of work generated by the power source of an ICE vehicle to overcome the driving resistance forces is proportional to the energy contained in the required amount of fuel, the power path of the vehicle can be straightforwardly modeled as a set of mechanical systems, and each sub-system evaluated for its share on the total fuel consumption and green house gases emission. This procedure enables the estimation of efficiency gains on the system due to improvement of particular elements on the vehicle's driveline. In this work a simple systematic mechanical model of an arbitrary smallsized hatch back was assembled and total required energy calculated for different regulatory cycles. All the modeling details of the energy balance throughout the system are presented. Afterward, each subsystem was investigated for its role on the fuel consumption and the generated emission quantified. Furthermore, the application of the modeling technique for different sets of sub-systems was introduced. Copyright © 2011 SAE International.

Quantification of uncertainties associated with space-time estimates of short-term soil CO2 emissions in a sugar cane area

The characterization of soil CO2 emissions (FCO2) is important for the study of the global carbon cycle. This phenomenon presents great variability in space and time, a characteristic that makes attempts at modeling and forecasting FCO2 challenging. Although spatial estimates have been performed in several studies, the association of these estimates with the uncertainties inherent in the estimation procedures is not considered. This study aimed to evaluate the local, spatial, local-temporal and spatial-temporal uncertainties of short-term FCO2 after harvest period in a sugar cane area. The FCO2 was featured in a sampling grid of 60m×60m containing 127 points with minimum separation distances from 0.5 to 10m between points. The FCO2 was evaluated 7 times within a total period of 10 days. The variability of FCO2 was described by descriptive statistics and variogram modeling. To calculate the uncertainties, 300 realizations made by sequential Gaussian simulation were considered. Local uncertainties were evaluated using the probability values exceeding certain critical thresholds, while the spatial uncertainties considering the probability of regions with high probability values together exceed the adopted limits. Using the daily uncertainties, the local-spatial and spatial-temporal uncertainty (Ftemp) was obtained. The daily and mean emissions showed a variability structure that was described by spherical and Gaussian models. The differences between the daily maps were related to variations in the magnitude of FCO2, covering mean values ranging from 1.28±0.11μmolm-2s-1 (F197) to 1.82±0.07μmolm-2s-1 (F195). The Ftemp showed low spatial uncertainty coupled with high local uncertainty estimates. The average emission showed great spatial uncertainty of the simulated values. The evaluation of uncertainties associated with the knowledge of temporal and spatial variability is an important tool for understanding many phenomena over time, such as the quantification of greenhouse gases or the identification of areas with high crop productivity. © 2013 Elsevier B.V.

Thermochemical equilibrium modeling of a biomass downdraft gasifier: Constrained and unconstrained non-stoichiometric models

The objective of this work is to develop a non-stoichiometric equilibrium model to study parameter effects in the gasification process of a feedstock in downdraft gasifiers. The non-stoichiometric equilibrium model is also known as the Gibbs free energy minimization method. Four models were developed and tested. First a pure non-stoichiometric equilibrium model called M1 was developed; then the methane content was constrained by correlating experimental data and generating the model M2. A kinetic constraint that determines the apparent gasification rate was considered for model M3 and finally the two aforementioned constraints were implemented together in model M4. Models M2 and M4 showed to be the more accurate among the four developed models with mean RMS (root mean square error) values of 1.25 each.Also the gasification of Brazilian Pinus elliottii in a downdraft gasifier with air as gasification agent was studied. The input parameters considered were: (a) equivalence ratio (0.28-035); (b) moisture content (5-20%); (c) gasification time (30-120 min) and carbon conversion efficiency (80-100%). (C) 2014 Elsevier Ltd. All rights reserved.

Measurements and modeling of reactive nitrogen deposition in southeast Brazil

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Engine LES with fuel-spray modeling

Pós-graduação em Engenharia Mecânica - FEG

Soil greenhouse gas emissions and their relations to soil attributes in a sugarcane area

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