Production of high concentrations of H2O2 in a bioelectrochemical reactor fed with real municipal wastewater

Bioelectrochemical systems can be used to energy-efficiently produce hydrogen peroxide (H2O2) from wastewater. Organic compounds in the wastewater are oxidized by microorganisms using the anode as electron acceptor. H2O2 is produced by reduction of oxygen on the cathode. In this study, we demonstrate for the first time production of high concentrations of H2O2 production from real municipal wastewater. A concentration of 2.26g/L H2O2 was produced in 9h at 8.3kWh/kgH(2)O(2). This concentration could poTENTially be useful for membrane cleaning at membrane bioreactor wastewater treatment plants. With an acetate-containing nutrient medium as anode feed, a H2O2 concentration of 9.67g/L was produced in 21h at an energy cost of 3.0kWh/kgH(2)O(2). The bioelectrochemical reactor used in this study suffered from a high internal resistance, most likely caused by calcium carbonate deposits on the cathode-facing side of the cation exchange membrane separating the anode and cathode compartments

Quality of Source Water and Drinking Water in Urban Areas of Myanmar

Myanmar is one of the least developed countries in the world, and very little information is available regarding the nation's water quality. This report gives an overview of the current situation in the country, presenting the results of various water-quality assessments in urban areas of Myanmar. River, dam, lake, and well water sources were examined and found to be of generally good quality. Both As and F − were present in relatively high concentrations and must be removed before deep wells are used. Heterotrophic plate counts in drinking water were highest in public pots, followed by nonpiped tap water, piped tap water, and bottled water. Measures need to be taken to improve low-quality water in pots and nonpiped tap waters

Absorbed dose rate in air in metropolitan Tokyo before the Fukushima Daiichi Nuclear Power Plant Accident

The monitoring of absorbed dose rate in air has been carried out continually at various locations in metropolitan Tokyo after the accident of the Fukushima Daiichi Nuclear Power Plant. While the data obtained before the accident are needed to more accurately assess the effects of radionuclide contamination from the accident, detailed data for metropolitan Tokyo obtained before the accident have not been reported. A car-borne survey of the absorbed dose rate in air in metropolitan Tokyo was carried out during August to September 2003. The average absorbed dose rate in air in metropolitan Tokyo was 49±6 nGy h⁻¹. The absorbed dose rate in air in western Tokyo was higher compared with that in central Tokyo. Here, if the absorbed dose rate indoors in Tokyo is equivalent to that outdoors, the annual effective dose would be calculated as 0.32 mSv y⁻¹

FEASIBILITY STUDY ON THE FUSION OF PHITS SIMULATIONS AND THE DLNN ALGORITHM

We have recently have developed an in-situ multiple-channel depth distribution spectrometer (DDS) that can easily acquire on-site measurements of the depth distribution of specific radioactivities of Cs-134 and Cs-137 underground. Despite considerable improvements in the hardware developed for this device, the quantitative method for determining of radioactivities with this DDS device cannot yet achieve satisfactory performance for practical use. For example, this method cannot discriminate each γ-ray spectra of Cs-134 and Cs-137 acquired by the 20 thallium-doped caesium iodine CsI(Tl) scintillation crystal detectors of the DDS device from corresponding depth levels of underground soil. Therefore, we have applied deep learning neural network (DLNN) as a novel radiation measurement technique to discriminate the spectra and to determine the specific radioactivities of Cs-134 and Cs-137. We have developed model soil layers on a virtual space in Monte-Carlo based PHITS simulations and transported γ-ray radiation generated from a particular single soil layer or multiple layers as radiation sources; next, we performed PHITS calculations of those specific radioactivity measurements for each soil layer using DDS device based on machine learning via the DLNN algorithm. In this study, we obtained informative results regarding the feasibility of the proposal innovative radiation measurement method for further practical use in on-site applications

The interface between the stellar wind and interstellar medium around R Cassiopeiae revealed by far-infrared imaging

The circumstellar dust shells of intermediate initial-mass (about 1 to 8 solar masses) evolved stars are generated by copious mass loss during the asymptotic giant branch phase. The density structure of their circumstellar shell is the direct evidence of mass loss processes, from which we can investigate the nature of mass loss. We used the AKARI Infrared Astronomy Satellite and the Spitzer Space Telescope to obtain the surface brightness maps of an evolved star R Cas at far-infrared wavelengths, since the temperature of dust decreases as the distance from the star increases and one needs to probe dust at lower temperatures, i.e., at longer wavelengths. The observed shell structure and the star's known proper motion suggest that the structure represents the interface regions between the dusty wind and the interstellar medium. The deconvolved structures are fitted with the analytic bow shock structure to determine the inclination angle of the bow shock cone. Our data show that (1) the bow shock cone of 1 - 5 x 10^-5 solar masses (dust mass) is inclined at 68 degrees with respect to the plane of the sky, and (2) the dust temperature in the bow shock cone is raised to more than 20 K by collisional shock interaction in addition to the ambient interstellar radiation field. By comparison between the apex vector of the bow shock and space motion vector of the star we infer that there is a flow of interstellar medium local to R Cas whose flow velocity is at least 55.6 km/s, consistent with an environment conducive to dust heating by shock interactions.Comment: 7 pages, 2 figures, accepted for publication in Astronomy and Astrophysic

Variation of radiocesium concentrations in cedar pollen in the Okutama area since the Fukushima Daiichi Nuclear Power Plant Accident

Due to releases of radionuclides in the Fukushima Daiichi Nuclear Power Plant Accident, radiocesium (¹³⁴Cs and ¹³⁷Cs) has been incorporated into large varieties of plant species and soil types. There is a possibility that radiocesium taken into plants is being diffused by pollen. Radiocesium concentrations in cedar pollen have been measured in Ome City, located in the Okutama area of metropolitan Tokyo, for the past 3 years. In this research, the variation of radiocesium concentrations was analysed by comparing data from 2011 to 2014. Air dose rates at 1 m above the ground surface in Ome City from 2011 to 2014 showed no significant difference. Concentration of ¹³⁷Cs contained in the cedar pollen in 2012 was about half that in 2011. Between 2012 and 2014, the concentration decreased by approximately one fifth, which was similar to the result of a press release distributed by the Japanese Ministry of Agriculture, Forestry and Fisheries

Identifying land use and land cover (LULC) change from 2000 to 2025 driven by tourism growth: A study case in Bali

Bali has been open to tourism since the beginning of the 20 th century and is known as the first tourist destination in Indonesia. The Denpasar, Badung, Gianyar, and Tabanan (Sarbagita) areas experience the most rapid growth of tourism activity in Bali. This rapid tourism growth has caused land use and land cover (LULC) to change drastically. This study mapped the land-use change in Bali from 2000 to 2025. The land change modeller (LCM) tool in ArcGIS was employed to conduct this analysis. The images were classified into agricultural land, open area, mangrove, vegetation/forest, and built-up area. Some Landsat images in 2000 and 2015 were exploited in predicting the land use and land cover (LULC) change in 2019 and 2025. To measure the accuracy of prediction, Landsat 8 OLI images for 2019 were classified and tested to verify the LULC model for 2019. The Multi-Layer Perceptron (MLP) neural network was trained with two influencing factors: elevation and road network. The result showed that the built-up growth direction expanded from the Denpasar area to the neighbouring areas, and land was converted from agriculture, open area and vegetation/forest to built-up for all observation years. The built-up was predicted growing up to 43 % from 2015 to 2025. This model could support decision-makers in issuing a policy for monitoring LULC since the Kappa coefficients were more than 80% for all models