Impact of system factors on the water saving efficiency of household grey water recycling

Copyright © 2010 Taylor & Francis. This is an Author's Accepted Manuscript of an article published in Desalination and Water Treatment Volume 24, Issue 1-3 (2010), available online at: http://www.tandfonline.com/10.5004/dwt.2010.1542A general concern when considering the implementation of domestic grey water recycling is to understand the impacts of system factors on water saving efficiency. Key factors include household occupancy, storage volumes, treatment capacity and operating mode. Earlier investigations of the impacts of these key factors were based on a one-tank system only. This paper presents the results of an investigation into the effect of these factors on the performance of a more realistic ‘two tank’ system with treatment using an object based household water cycle model. A Monte-Carlo simulation technique was adopted to generate domestic water appliance usage data which allows long-term prediction of the system's performance to be made. Model results reveal the constraints of treatment capacity, storage tank sizes and operating mode on percentage of potable water saved. A treatment capacity threshold has been discovered at which water saving efficiency is maximised for a given pair of grey and treated grey water tank. Results from the analysis suggest that the previous one-tank model significantly underestimates the tank volumes required for a given target water saving efficiency

The 2015 edition of the GEISA spectroscopic database

The GEISA database (Gestion et Etude des Informations Spectroscopiques Atmosphériques: Management and Study of Atmospheric Spectroscopic Information) has been developed and maintained by the ARA/ABC(t) group at LMD since 1974. GEISA is constantly evolving, taking into account the best available spectroscopic data. This paper presents the 2015 release of GEISA (GEISA-2015), which updates the last edition of 2011 and celebrates the 40th anniversary of the database. Significant updates and additions have been implemented in the three following independent databases of GEISA. The “line parameters database” contains 52 molecular species (118 isotopologues) and transitions in the spectral range from 10−6 to 35,877.031 cm−1, representing 5,067,351 entries, against 3,794,297 in GEISA-2011. Among the previously existing molecules, 20 molecular species have been updated. A new molecule (SO3) has been added. HDO, isotopologue of H2O, is now identified as an independent molecular species. Seven new isotopologues have been added to the GEISA-2015 database. The “cross section sub-database” has been enriched by the addition of 43 new molecular species in its infrared part, 4 molecules (ethane, propane, acetone, acetonitrile) are also updated; they represent 3% of the update. A new section is added, in the near-infrared spectral region, involving 7 molecular species: CH3CN, CH3I, CH3O2, H2CO, HO2, HONO, NH3. The “microphysical and optical properties of atmospheric aerosols sub-database” has been updated for the first time since 2003. It contains more than 40 species originating from NCAR and 20 from the ARIA archive of Oxford University. As for the previous versions, this new release of GEISA and associated management software facilities are implemented and freely accessible on the AERIS/ESPRI atmospheric chemistry data center website

Stress granules, RNA-binding proteins and polyglutamine diseases: too much aggregation?

Stress granules (SGs) are membraneless cell compartments formed in response to different stress stimuli, wherein translation factors, mRNAs, RNA-binding proteins (RBPs) and other proteins coalesce together. SGs assembly is crucial for cell survival, since SGs are implicated in the regulation of translation, mRNA storage and stabilization and cell signalling, during stress. One defining feature of SGs is their dynamism, as they are quickly assembled upon stress and then rapidly dispersed after the stress source is no longer present. Recently, SGs dynamics, their components and their functions have begun to be studied in the context of human diseases. Interestingly, the regulated protein self-assembly that mediates SG formation contrasts with the pathological protein aggregation that is a feature of several neurodegenerative diseases. In particular, aberrant protein coalescence is a key feature of polyglutamine (PolyQ) diseases, a group of nine disorders that are caused by an abnormal expansion of PolyQ tract-bearing proteins, which increases the propensity of those proteins to aggregate. Available data concerning the abnormal properties of the mutant PolyQ disease-causing proteins and their involvement in stress response dysregulation strongly suggests an important role for SGs in the pathogenesis of PolyQ disorders. This review aims at discussing the evidence supporting the existence of a link between SGs functionality and PolyQ disorders, by focusing on the biology of SGs and on the way it can be altered in a PolyQ disease context.ALG-01-0145-FEDER-29480, SFRH/BD/133192/2017, SFRH/BD/133192/2017, SFRH/BD/148533/2019info:eu-repo/semantics/publishedVersio

Analysis of trace elements in airborne particulate matters collected in Ankara, Turkey by TXRF

The main focus point of the presented study was the assessment of atmospheric burden of particulate matter and toxic trace metals in the atmosphere of Ankara, Turkey. For this purpose, outdoor samplings were accomplished in the capital city, Ankara. The types of filters, sample collection and sample preparation methods were investigated and optimized. Analyses were provided by the total reflection X-ray fluorescence (TXRF) spectroscopic technique in Germany. Spatial and temporal variations of air particulate matter (APM) levels in the city were examined. In some stations, APM sampled in according to their size distribution such as PM10 and PM2.5. Elemental characterization of size distributed PM were achieved and evaluated. It was detected that the elements mainly originated from soil in Beytepe station, from soil and solid fuel usage in Kayas station and from traffic and a variety of human activities in Sıhhiye station in air samplings. While the elements of natural origin observed in PM10 fraction, the elements from traffic and human activities were in PM2.5. Eventually, enrichment calculations were performed in order to identify the pollution sources