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Waste activated sludge (WAS) was disintegrated by composite ferrate solution (CFS) in this work, and the effect of CFS disintegrated sludge supernatant (CDSS), as a supplementary carbon source, on enhancement of nitrogen and phosphorus removal and sludge reduction in an AAO-CFSSDR (Anaerobic/Anoxic/Oxic combined with CFS-Sludge disintegration reactor) process was evaluated. The results showed that CDSS was easily utilizable by the denitrification bacteria due to the high content of readily biodegradable substrates. When compared with the AAO process, the operation results of AAO-CFSSDR suggested that the removal efficiencies of TN, NH4+-N and TP increased from 71.15, 79.23 and 85.52% to 85.05, 87.70 and 90.06%, respectively; and the sludge was reduced by 34.79%. The 16SrRNA high-throughput sequencing results showed that the introduction of CDSS weakened the microbial diversity but enhanced the microbial richness; and the abundance of bacteria related to the removal of nitrogen and phosphorus, increased in the AAO-CFSSDR process.

This article focuses on new method to estimate biological activity of peat humic acids (HAs) using artificial neural network (ANN) to process spectroscopic measurements in infrared and visible ranges. Conventional approaches generally rely on biological models and direct detection of chemical substances related to bioactivity. These methods proved to be accurate and reliable, but at the expense of speed and simplicity.

Recently, a conception of quantitative structure-activity relationship (QSAR) has been introduced and successfully implemented to predict effects of HAs on toxicity of polycyclic aromatic hydrocarbons. Our research stems from this conception, but employs multilayer perceptron (MLP) model to improve overall performance. The developed MLP model allowed us to estimate biological activity of the complete vertical peat cores collected from oligotrophic peat bog, located in southern taiga zone of West Siberia (north-eastern spurs of the Great Vasyugan Mire, 56°58' N 82о36' E). In total, 42 samples taken from the cores were collected. The protocol included spectroscopy (in infrared and visible ranges) and biological model with peritoneal activated macrophages as a reference method to directly measure biological activity of HAs.

and discussion. Numerical experiments confirmed consistency of the measured and estimated bioactivity, coefficient of determination R2=0.97. These experiments also showed that the MLP model significantly outperforms conventional linear multiple regression models, mainly due to essential nonlinearity of structure-activity relationships.

Our research demonstrates that biological activity of HAs extracted from peat samples can be estimated using an artificial neural network model trained on infrared and visible spectra.

Our research demonstrates that biological activity of HAs extracted from peat samples can be estimated using an artificial neural network model trained on infrared and visible spectra.Australia is a highly developed country with low population density. Capital cities are situated mainly around the coastline and are subjected to different meteorological conditions. This complex set of drivers is expected to result in varying trends in particulate matter (PM) mass concentrations in urban ambient air across the country. Thus, the aim of this study was to determine the long-term trends in PM10 and PM2.5 concentrations in capital cities, and to analyse the factors that influenced such trends. The spatial variability of PM concentrations within the capital cities was first established to identify representative stations. Entinostat cost Then trends were determined using the Mann-Kendall trend test, Sen's slope, and the generalised additive model. The results show that, in general, the PM concentrations in Australian cities are relatively low (12.1-21.7 μg m-3 mean daily PM10 and 4.6-8.7 μg m-3 mean daily PM2.5) and within the WHO daily limit 95% of the time. Over the past two decades, very small declines of 8.0trations in Australian cities is unlikely, considering the expanding urbanisation and the changing climate.Iron (hydr)oxide-natural organic matter (NOM) colloids, the dominant components of soil, usually occur in varied circumstances and may affect Hg transport and fate in soil. This study aims to reveal the Hg binding to preformed composites rather than only focusing on Hg retention by iron (hydr)oxides in the presence of NOM. Ferrihydrite-humic acid (FH-HA) is chosen as a representative composite, and the effect of the complexation method and FH morphology on Hg binding to various composites is evaluated. Three types of composites are developed a dense coprecipitated composite (p-d-f), a gel-like adsorbed composite (a-g-f) and a dense adsorbed (a-d-f) composite. Batch sorption and stirred-flow kinetic tests together with surface property analysis and modern spectral analyses are carried out to explore the binding behavior of Hg to the three composites and clarify the interactions in the ternary systems of FH-HA-Hg. The results show that the Hg sorption isotherms all fit well with the Langmuir model, and the maximum sorption capacities follow the order a-g-f> a-d-f > p-d-f, implying that the adsorbed composite is more favorable than the coprecipitated composite for Hg binding and a gel morphology is more beneficial than a dense morphology. The stirred-flow experiments show that the adsorbed composite has a small advantage in Hg sorption compared to the coprecipitated composite and that the gel-like composite can adsorb more Hg at a faster rate than the dense composite. Both FH and HA participate in Hg sorption, and FH-HA-Hg complexes are speculated to form. These findings are helpful to better understand the mobility and fate of Hg in soils, as well as the associated dynamic model for predicting Hg behavior in the environment where the iron (hydr) oxide-NOM composites are pre-existed.The main objective of the study is to assess the groundwater quality based on water quality index and health threats associated with fluoride contamination in the Tiruppur region of southern India. Totally 40 groundwater samples were collected and analyzed for various physicochemical parameters such as pH, EC, TDS, Ca2+, Mg2+, Na+, K+, Cl-, HCO3-, SO42-, NO3- and F-. The dominance of major cations and anions conforms to the following order Ca2+> Na+> K+> Mg2+ and Cl- > HCO3- > SO42-> NO3- > F-, respectively. About 48% of the groundwater samples indicated Ca-Mg-Cl water type in the Piper trilinear diagram. The Gibbs plot indicated that all the water samples fell under rock dominance. Water quality index (WQI) results showed that 22.5, 75 and 2.5% of the samples represented good, poor and very poor quality water types, respectively. The fluoride ions in groundwater of this region ranged from 0.1 to 2.70 mg/L with a mean of 1.33 mg/L. About 50% of the groundwater samples experienced fluoride concentration exceeding the permissible limit of 1.