| 1. |
|
|
| 2. |
|
|
| 3. |
- Kehoe, Laura, et al.
(författare)
-
Make EU trade with Brazil sustainable
- 2019
-
Ingår i: Science. - : American Association for the Advancement of Science (AAAS). - 0036-8075 .- 1095-9203. ; 364:6438, s. 341-
-
Tidskriftsartikel (övrigt vetenskapligt/konstnärligt)
|
|
| 4. |
- dos Santos, Victor Hugo J. M., et al.
(författare)
-
Discriminant analysis of biodiesel fuel blends based on combined data from Fourier Transform Infrared Spectroscopy and stable carbon isotope analysis
- 2017
-
Ingår i: Chemometrics and Intelligent Laboratory Systems. - : Elsevier. - 0169-7439 .- 1873-3239. ; 161, s. 70-78
-
Tidskriftsartikel (refereegranskat)abstract
- A multivariate approach was used for classification of fuel blends using the combined information from Fourier Transform Infrared Spectroscopy (FTIR) and stable carbon isotopes analysis by Isotope Ratio Mass Spectrometry (IRMS). Linear Discriminant Analysis (LDA) and Partial Least Squares Discriminant Analysis (PLS-DA) were applied to the classification of biodiesel/diesel fuel blends containing 0-100% (v/v) of biodiesel. The LDA and PLS-DA methods were able to discriminate samples ranging from 10% to 100% biodiesel (v/v) using the combined information from FTIR and IRMS. Since the global trend is toward a gradual increase in the percentage of biodiesel in fuel blends, the technique presented in this paper could be an important development in improving the traceability and identification of different raw materials used in biodiesel production.
|
|
| 5. |
- Melo, Clarissa L., et al.
(författare)
-
Integration results of soil CO2 flux and subsurface gases in the Ressacada Pilot site, Southern Brazil
- 2017
-
Ingår i: 13th International Conference on Greenhouse Gas Control Technologies, GHGT-13. - : Elsevier. ; , s. 3793-3804
-
Konferensbidrag (refereegranskat)abstract
- The first CO2 monitoring field lab at the Ressacada Farm, in the Southern region of Brazil, started in 2011 and until 2015 offered an excellent opportunity to run controlled CO2 releases experiments in soil and shallow subsurface through vertical injection wells. This paper focus on the presentation and comparison of the results obtained at the last campaign realized at this site in August 2015. The results integrate a time-lapse monitoring experiment of CO2 migration in both saturated and unsaturated sand-rich sediments and soil, using soil CO2 flux measurements and subsurface gas analyses through CO2 concentrations (ppm) and carbon isotope ratios (delta C-13 of CO2). The CO2 flux results in the studied area showed an increase in the flux values according to the increasing of injection rate and along the campaign are directed to the southwest portion of the area. However, even by injecting large amounts of CO2, fluxes are greatly reduced when it rains. The gas analysis also showed an increase in CO2 concentrations according to the increasing of the injection rate mainly in the superficial levels of the monitoring wells (0.5m and 2m depth). The delta C-13 of CO2 found on the 3rd injection day showed the presence of CO2 injected and demonstrate that the sampling methodology with vacutainer vial was effective, since there is no atmospheric contamination. The correlation of isotopic analysis were consistent with the results of concentrations and CO2 fluxes and thus, it is clear that the CO2 breakthrough occurred from the 3rd day of injection, while were obtained the largest CO2 fluxes, the higher gas concentrations in the subsurface, as well as the industrial origin of delta C-13 of CO2.
|
|
| 6. |
- dos Santos, Victor Hugo J. M., et al.
(författare)
-
Classification of Fuel Blends Using Exploratory Analysis with Combined Data from Infrared Spectroscopy and Stable Isotope Analysis
- 2017
-
Ingår i: Energy & Fuels. - : American Chemical Society (ACS). - 0887-0624 .- 1520-5029. ; 31:1, s. 523-532
-
Tidskriftsartikel (refereegranskat)abstract
- Chemometric tools were applied for exploratory analysis and classification of fuel blends using the combined information on Fourier transform infrared spectroscopy and stable isotope analysis through isotope ratio mass spectrometry. Principal component analysisand hierarchical clustering analysis were applied for exploratory analysis, while support vector machine (SVM) was used to classify the biodiesel/diesel blends. All of the chemometric models used present better results from the combination of spectral information with isotopic data for biodiesel contents of over 10% in the mixture, with the best results being Obtained from the SVM classification. Therefore, the development presented in this paper could become an important technique to improve the discrimination of the feedstock used in biodiesel production and a resource for quality control in industry.
|
|
