• Energy Research
• Closed Access close
• Open Source close
• engineering and technology close
• English close

The importance of emission control has increased sharply due to increased need of energy from combustion. However, biomass utilization in energy production is not free from problems because of physical and chemical characteristics which are substantially different from conventional energy sources. In this situation, the quantity and quality of emissions as well as used renewable source as wood or corn grain are often unknown. To assess this problem the paper addresses the objectives to quantify the amount of greenhouse gases during the combustion of corn as compared to the emissions in fossil combustion (natural gas, LPG and diesel boiler). The test was carried out in Friuli Venezia Giulia in 2006-2008 to determine the air pollution (CO, NO, NO2, NOx, SO2 and CO2) from fuel combustion in the family boilers with power between 20-30 kWt. The flue gas emission was measured with a professional semi-continuous multi-gas analyzer, (Vario plus industrial, MRU air Neckarsulm-Obereisesheim). Data showed a lower emission of fossil fuel compared to corn in family boilers in reference to pollutants in the flue gas (NOx, SO2 and CO). In particular way the biomass combustion make a higher concentration of carbon monoxide (for a incomplete combustion because there aren’t a good mixing between fuel and air) and nitrogen oxides (in relation at higher content of nitrogen in herbaceous biomass in comparison of another fuel). Proceedings of the 19th European Biomass Conference and Exhibition, 6-10 June 2011, Berlin, Germany, pp. 1296-1304

The project between tthe Deutsche Biomasseforschungszentrum (DBFZ) and the Karlsruhe Institute of Technology (KIT) focuses on the pr rovision of alternative fuels by thermochemical conversion. Biogenic residues and wastes which are not used yet or which could be utilised more efficiently are studied. The selection of possible feedstock was supported by a techhnical potential analysis including the competition to th he food industry. The technical suitability of raw materials for the fast pyrolysis (FP) process was of special in nterest. As a possible feedstock following types of biomass were studied: corn stover, corn cobs, biogenic floating re efuse (river Rhine and Baltic Sea), scrap wood, bark, rape s straw, sunflower straw, draff, diverse residues of flour production and hay. A process development unit (PDU) with a biomass feeding rate of 10 kg/h and a twin screw m mixer reactor was used for all experiments. It was found that different types of biomass form different char, condensate e and gas yields due to varying ash levels and lignocellulosic composition. Elemental formulas for feedstock, char, organic condensate and gas were estimated independent on t the feedstock due to similar elemental compositions. Pyrolysis gas analysis during the experiments gave information on the mass yields. A CO/CO2-ratio of 1 (i.e. wood) corresponds to organic condensate yields of about 50 wt.-%%, whereas a ratio of 0.3-0.7 (straw) corresponds to 18-32 wt. .-% respectively. Proceedings of the 20th European Biomass Conference and Exhibition, 18-22 June 2012, Milan, Italy, pp. 973-977

The devolatilization of solid fuels is of crucial importance for all thermo­chemical processes and is the basic step in gasification and combustion models. Here a structural model is developed to provide an Advanced tool for Biomass and Coal Devolatilization (ABCD model), even in blend. The main features are founded on the original approach of the CPD (Chemical Percolation Devolatilization) model by Fletcher [1]. The ABCD model extends the approach also to biomass fuels. Further improvements of the ABCD model are: (i) a population balance between n­mers in liquid metaplast; (ii) elemental balance closure with the speciation of light gases, hetero­species and tar composition; (iii) introduction of secondary reactions of tar­cracking and crosslinking. The ABCD model results agree with a selection of experimental data (from homemade and literature works) on different biomasses. The results reported in this paper encouraged IFRF in continuing the experimental campaign for the validation of the model by extending the Solid Fuel DataBase SFDB. The inclusion of ABCD in comprehensive codes (e.g., Reactor Network Analysis, RNA [2]) and process models is valuable because it gives detailed distribution of pyrolysis products in a wide range of conditions with a low computational cost. Proceedings of the 18th European Biomass Conference and Exhibition, 3-7 May 2010, Lyon, France, pp. 923-930

The agonist activity of the title compounds on GABA(c) receptor as well as GABA uptake inhibition activity is reported. B3LYP/6-311++G(d,p) calculations have been performed to obtain the quantum chemical descriptors such as global hardness, electrophilicity, the electronic chemical potential of the title compounds. Polarized continuum model has been used to explore the solvent effect on activity of the title compounds in four solvent media, viz., chloroform, ethanol, DMSO, and water. The results obtained from the quantum chemical calculations show that the calculated energy gap and the global hardness, as well as molecular electrostatic potential values, are in good agreement with the experimental data. The financial support of the scientific research projects of Cumhuriyet University (F-222), Sivas, Turkey is acknowledged. All calculations have been conducted at TUBITAK (the scientific and technological Research Council), ULAKBIM (Turkish academic Network and information center), High Performance and Grid Computing Center (TR-Grid e-Infrastructure), Turkey. Cumhuriyet University, Sivas, Turkey [F-222] WOS: 000415784500004

In Finland, as there is no feed-in tariff, the wind power producers have to make contracts on how the electricity is sold and also make contracts for balance settlement. For this paper, wind power production is estimated 1–38 hours ahead for wind turbines located in 4 small clusters about 380 km apart on the West coast of Finland. Wind speed forecasts from the very-high-resolution ETA meteorological forecast model run by Foreca Ltd are used together with two production forecast models, which employ neural networks developed by Cybersoft and time series modeling by VTT. To show the effect of even more spread wind power production in Finland, prediction errors are determined for both one site, one producer and for the whole West Coast of Finland. Balancing costs resulting from day-ahead forecasts are estimated with year 2004 price data. Some example weeks are taken to examine the possibilities of improving the meteorological prediction for wind speeds.