Accelerated photodegradation (minute range) of the commercial azo-dye Orange II mediated by Co3O4/Raschig rings in the presence of oxone

The accelerated discoloration of Orange II by an innovative Co3O4/Raschig ring photocatalyst (from now on Co3O4/RR) is feasible and proceeds to completion using oxone as an oxidant within the surprisingly short time of ∼5 min. The preparation of Co3O4 small clusters (2–10 nm in size) on RR is reported. The discoloration/mineralization of the azo-dye Orange II was carried out in a concentric coaxial photo-reactor and was a function of the Orange II and oxone concentrations, the solution pH and the recirculation rate. At bio-compatible pH-values, the concentration of Co-ions in solution after photocatalysis (15 min) was found to be between 0.5 and 2 ppm, within the limits allowed for treated waters. The generation of peroxide was observed as long as Orange II was still available in solution. By elemental analysis (EA), the amount of Co of the Raschig rings was determined to be ∼65% (w/w) before and after the photocatalysis. This confirms the stability observed during long-term operation of the Co3O4/RR catalyst. The sizes of the Co3O4 clusters on the RR surface were determined by transmission electron spectroscopy (TEM). A non-uniform distribution of Co3O4 particles on RR with sizes between 2 and 10 nm was found. The presence of Co-clusters on the RR-surface was confirmed by electron dispersive spectroscopy (EDS) showing 12.6% surface Co-enrichment before the photocatalysis and 18.8% surface enrichment after the photocatalysis. By confocal microscopy the irregularly thick shaped Co3O4 on the Raschig rings was analyzed. The most striking observation is very large shift of Co2p3/2 line from 779.6 eV at time zero to 782.2 eV within 10 min after due to the photocatalysis taking place. This indicates a strong reduction of electron density on the cobalt atoms of Co3O4/RR and providing the evidence for the strong oxidation properties of this catalyst

Potrzeba nowych rozwiązań dla zakupów energii z OZE

The paper presents one of the key problems in renewable energy trading. The support system for RES is operating on financial levels leaving to the RES producers decisions on the energy trade. However, the flawed legal regulations impose the obligations on Default Electricity Supplier (SzU1) to buy all RES production from the installations located in the areas of the SzU operation. Such legal provisions result in the additional burden on the SzU, which main duty is to provide electric energy to customers who do not want to enter competitive electricity markets. Additionally, over interpretation of the Energy Law provisions by the Energy Regulatory Authority (URE2), allowing the RES producers to trade a part of their production on electricity markets leaving the obligation on SzUs, has led to the speculative trade of renewable energy. Some RES producers sell the electricity produced in competitive markets during peak demand hours – usually working days from 7 a.m. to 8 p.m. – when the Power Exchange prices are significantly higher than the obligatory purchase price. When during off peak demand hours electricity prices in the Power Exchange are lower than the obligatory level, RES producers sell the electric energy to SzUs at the obligatory price, determined by the URE. Such an abuse of fair trade results in the additional income for the RES producers being burden on SzUs, which have to transfer such costs to energy endusers. The simulations, carried out for Poland indicate that the additional costs can count for about 200 mln zł per year.Produkcja energii ze źródeł odnawialnych wiąże się z dodatkowymi kosztami, które są pokrywane ze środków uzyskanych przez wszystkie firmy handlujące energią elektryczną ze sprzedaży tzw. zielonych certyfikatów. Niejasne zapisy w ustawie Prawo energetyczne oraz ich interpretacja przez prezesa URE powodują, że tzw. sprzedawcy z urzędu ponoszą dodatkowe koszty wynikające nie tylko z nabywania energii z OZE po cenach ustalonych przez prezesa URE, ale także na skutek rynkowych spekulacji producentów energii elektrycznej. Sprzedawcy z urzędu, których głównym celem jest sprzedaż energii małym odbiorcom niekorzystającym z rynku energii elektrycznej, zostali obarczeni dodatkowym kosztem zakupu energii z OZE produkowanej na obszarze ich działania. Takie rozwiązanie powoduje, że niektóre firmy, jak ENERGA-OBRÓT SA, które pełnią funkcję sprzedawcy z urzędu na terenie, gdzie ulokowana jest znaczna liczba instalacji OZE, ponoszą dodatkowe koszty, co pogarsza ich pozycję konkurencyjną. Rynkowe spekulacje producentów OZE polegają na sprzedaży energii elektrycznej na rynku konkurencyjnym po wysokich cenach w okresach dużego zapotrzebowania i sprzedaży energii do zobowiązanych sprzedawców z urzędu w okresach, kiedy ceny rynkowe są niższe od ceny obligatoryjnego zakupu ustalonej przez prezesa URE. Poprzez takie rynkowe spekulacje producenci OZE mogą osiągać dodatkowe przychody na poziomie 40 zł/MWh – 25% ceny rynkowej. Jednak te dodatkowe przychody producentów OZE obciążają odbiorców energii i kwota tych obciążeń może sięgać 200–300 mln złotych rocznie

A fuzzy-based approach to analyse system demand in the Australian Electricity Market

In the Australian National Electricity Market (NEM), pool prices are fully determined by the balance between electricity supply and demand. Market participants provide price and power bids in half-hour periods. Dispatch prices are determined by the market operator in five-minute periods. The bidding behaviour is based on the prediction of electricity market in particular system demand which determines prices in most trading intervals. The more accurate prediction of demand patterns can lead to optimisation of bidding strategies. This paper presents the application of fuzzy sets to analyse system demand in the Australian Electricity Market as the basic input information for optimisation of bidding strategies. Linguistic variables are effective tools to analyse trends of system demand and predict its future values

Analysis of bids and re-bids of generators in the Australian National Electricity Market

In Australia's National Electricity Market (NEM), generators provide their bids and re-bids in 0.5 hour trading intervals. Spot prices are determined in 5-minute periods by the intersection of the bids and power demand. Generator bids and re-bids are composed of power price determined in 10 pricing bands and power offered in 0.5 hour intervals. Generator's behaviour depends on several elements such as daily demand forecasted, maximum system capacity, the generation reserve predicted, transfer between the regions. The paper presents generator bids and re-bids based on two main aspects: distribution of prices and power offered in price bands. The functional relations for various days of a week, months and seasons for three main categories of power stations: thermal, gas and hydro are subject to the analysis carried out for two main regions of the National Electricity Market (NEM) in Australia. Statistical distribution functions of typical bidding behaviour are derived allowing the prediction of future pool prices

Bidding strategies in electricity markets

In electricity markets organized as pools, electrical power producers provide offers (called sometimes bids) of power generation in defined price bands for every trading interval. Usually, the price offered reflects the variable cost of generation. Bidding behavior of market participants is determined by several factors. They include vesting and bilateral contracts, predicted demand, generation reserve, experience from the past and gaming attitudes. This paper analyses a typical bidding behavior of power generators in the Victorian and Australian national markets. Australia has a significant experience in designing of electricity market structures and construction of market simulators

Inactivation Of E. Coli Mediated By High Surface Area Cuo Accelerated By Light Irradiation >360 Nm

CuO powders with different specific surface areas are reported hereby to inactivate E. coli in aqueous solution in the dark under visible light irradiation λ > 360 nm. The inactivation of E. coli mediated by the CuO suspensions was investigated as a function of the solution parameters: specific surface area of the Cu-oxides (40-77 m 2/g), amount of CuO, light intensity and fate of the Cu 1+-ion within the inactivation process. The specific surface area of the CuO was observed to play an important role during the E. coli inactivation kinetics. The light induced inactivation of E. coli in CuO suspensions (1 g/L) was complete within 4 h. The cytotoxicity of E. coli when using CuO (77 m 2/g) was found for CuO concentrations as low as 0.2 g/L. A reaction mechanism is suggested for the Fenton-like reactions due to the Cu-ions/CuO action and the reactive oxygen species (ROS) generated in solution. These highly oxidative radicals decompose Orange II and methylene blue (MB) dyes in aqueous solution of CuO. The CuO in contact with the bacterial suspension shows a change in its surface oxidation state from Cu 2+ to Cu 1+. The outermost layer of the catalyst (5-7 nm) becomes mainly Cu 2O (80%) and CuO (20%) as observed by X-ray photoelectron spectroscopy (XPS). A shift of the Cu 2p 3/2 peak from the initial position at 933.6-932.6 eV upon contact of the E. coli with CuO was observed concomitant with the disappearance of the Cu 2+ shake-up satellite lines at 942.3 and 962.2 eV. The XPS surface composition of copper catalyst is reported at different stages of E. coli inactivation and it was observed that the reduced copper oxide remains stable during the 4 h needed to inactivate the E. coli suspension. © 2008 Elsevier B.V. All rights reserved.1991105111D.K. Karlin, Y. Gulneth, In Progress in Inorganic Chemistry, vol. 35, Lippard, Ed., 1987, pp. 220-237Tolman, B.W., (1997) Acc. Chem. Res., 30, pp. 227-240Bandara, J., Guasaquillo, I., Bowen, P., Soare, L., Jardim, F.W., Kiwi, J., (2005) Langmuir, 21, pp. 8554-8559Bandara, J., Kiwi, J., Pulgarin, C., Peringer, P., Pajonk, G.-M., Elalui, A., Albers, P., (1996) Environ. Sci. Technol., 30, pp. 1261-1267Li, D., Yuranova, T., Kiwi, J., (2004) Water Res., 38, pp. 3541-3550Oppenlaender, Th., (2003) Photochemical Purification of Water and Air, , Wiley-VCH, Weinheim, GermanyGak, Y., Nadtochenko, V., Kiwi, J., (1998) J. Photochem. Photobiol. A., 116, pp. 57-62Carnes, L.C., Stipp, J., Klabunde, J., Bonevich, J., (2002) Langmuir, 18, pp. 1352-1358Wang, W., Zhan, X., Wang, Y., Liu, Y., Zheng, G., Wang, G., (2002) Mater. Res. Bull., 37, pp. 1092-1100Sadana, A., Katzer, J., (1974) J. Catal., 35, pp. 140-152Hai-Yan, D., Yu-Ling, C., Jing-Kui, L., Si-Shen, X.J., (1993) Mater. Sci., 28, pp. 5176-5178Walsh, D., Arcelli, T., Ikoma, J., Tanaka, J., Mann, S., (2003) Nat. Maters, 2, pp. 386-388Yokota, T., Kubota, Y., Takahata, Y., Katsuyama, T., Matsuda, Y., (2004) J. Chem. Eng. Jpn, 37, pp. 238-244(2002) Drug Ther. Bull., 40, pp. 67-69Bader, H., Sturzenegger, V., Hoigné, (1988) J. Wat. Res., 22, pp. 1109-1115Hulanicki, A., Krawczyk, T.K.V., Lewenstam, A., (1984) Anal. Chim. Acta, 158, pp. 343-355Murray, P.R., Baron, E.J., Pfaller, M.A., Tenover, F.C., Yolken, R.H., (1995) Manual of Clinical Microbiology. sixth edition, , American Society of Microbiology, Washington, D.CCooney, T.E., (1995) Infect. Control. Hosp. Epidemiol., 16, pp. 444-450Bacsa, R., Kiwi, J., Ohno, T., Albers, P., Nadtochenko, V., (2005) J. Phys. Chem. B., 109, pp. 5994-6003. , (and references therein)Sunada, K., Watanabe, T., Hashimoto, K., (2003) Environ. Sci. Technol., 37, pp. 4785-4789Hardee, K., Bard, A., (1977) J. Electrochem. Soc., 124, p. 215Hardee, K., Bard, A., (1977) J. Electrochem. Soc., 124, pp. 215-224Goldstein, S., Czapski, G., Meyerstein, D., (1990) J. Am. Chem. Soc., 112, pp. 6489-6493Bielski, J.B., Cabelli, D., Arudi, R., Ross, A., (1985) J. Phys. Chem. Ref. Data, 14, pp. 1041-1061Petasne, R.G., Zika, R.G., (1997) Mar. Chem., 56, pp. 215-225Kieber, R.J., George, R.H., (1995) Estuarine, Coastal Shelf Sci., 40, pp. 495-503Cooper, W.J., Lean, D.R.S., (1989) Environ. Sci. Technol., 23, pp. 1425-1428Jardim, W.F., Soldá, M.I., Gimenez, S.M., (1986) Sci. Total Environ., 58, pp. 47-54Weiss, J., (1935) Naturwissenchaften, 23, pp. 64-67Letelier, M.E., Lepe, A., Faundez, M., Salazar, J., Marin, R., Aracena, P., Speisky, H., (2005) Chem.-Biol. Interact., 151, pp. 71-82Takeshi, N., Insook, M., Noriyuki, S., Takakiro, I., (1997) J. Biol. Chem., 272, pp. 23037-2304