935 resultados para Pollutant Removal
Resumo:
The application of layered double hydroxides (LDHs) and thermally activated LDHs for the removal of various fluorine (F-, BF-4), chlorine (Cl-,ClO-4), bromine (Br-, BrO-3) and iodine (I-, IO-3) species from aqueous solutions has been reviewed in this article. LDHs and thermally activated LDHs were able to significantly reduce the concentration of selected anions in laboratory scale experiments. The M2+:M3+ cation ratio of the LDH adsorbent was an important factor which influenced anion uptake. Though LDHs were able to remove some target anion species through anion exchange and surface adsorption thermal activation and reformation generally produced better results. The presence of competing anions including carbonate, phosphate and sulphate had a significant impact on uptake of the target anion as LDHs typically exhibit lower affinity towards monovalent anions compared to anions with multiple charges. The removal of fluoride and perchlorate from aqueous solution by a continuous flow system utilising fixed bed columns packed with LDH adsorbents has also been investigated. The adsorption capacity of the columns at breakpoint was heavily dependent on the flow rate and lower than result reported for the corresponding batch methods. There is still considerable scope for future research on numerous topics summarised in this article.
Resumo:
Due to knowledge gaps in relation to urban stormwater quality processes, an in-depth understanding of model uncertainty can enhance decision making. Uncertainty in stormwater quality models can originate from a range of sources such as the complexity of urban rainfall-runoff-stormwater pollutant processes and the paucity of observed data. Unfortunately, studies relating to epistemic uncertainty, which arises from the simplification of reality are limited and often deemed mostly unquantifiable. This paper presents a statistical modelling framework for ascertaining epistemic uncertainty associated with pollutant wash-off under a regression modelling paradigm using Ordinary Least Squares Regression (OLSR) and Weighted Least Squares Regression (WLSR) methods with a Bayesian/Gibbs sampling statistical approach. The study results confirmed that WLSR assuming probability distributed data provides more realistic uncertainty estimates of the observed and predicted wash-off values compared to OLSR modelling. It was also noted that the Bayesian/Gibbs sampling approach is superior compared to the most commonly adopted classical statistical and deterministic approaches commonly used in water quality modelling. The study outcomes confirmed that the predication error associated with wash-off replication is relatively higher due to limited data availability. The uncertainty analysis also highlighted the variability of the wash-off modelling coefficient k as a function of complex physical processes, which is primarily influenced by surface characteristics and rainfall intensity.
Resumo:
The approach adopted for investigating the relationship between rainfall characteristics and pollutant wash-off process is commonly based on the use of parameters which represent the entire rainfall event. This does not permit the investigation of the influence of rainfall characteristics on different sectors of the wash-off process such as first flush where there is a high pollutant wash-off load at the initial stage of the runoff event. This research study analysed the influence of rainfall characteristics on the pollutant wash-off process using two sets of innovative parameters by partitioning wash-off and rainfall characteristics. It was found that the initial 10% of the wash-off process is closely linked to runoff volume related rainfall parameters including rainfall depth and rainfall duration while the remaining part of the wash-off process is primarily influenced by kinetic energy related rainfall parameters, namely, rainfall intensity. These outcomes prove that different sectors of the wash-off process are influenced by different segments of a rainfall event.
Resumo:
The validity of using rainfall characteristics as lumped parameters for investigating the pollutant wash-off process such as first flush occurrence is questionable. This research study introduces an innovative concept of using sector parameters to investigate the relationship between the pollutant wash-off process and different sectors of the runoff hydrograph and rainfall hyetograph. The research outcomes indicated that rainfall depth and rainfall intensity are two key rainfall characteristics which influence the wash-off process compared to the antecedent dry period. Additionally, the rainfall pattern also plays a critical role in the wash-off process and is independent of the catchment characteristics. The knowledge created through this research study provides the ability to select appropriate rainfall events for stormwater quality treatment design based on the required treatment outcomes such as the need to target different sectors of the runoff hydrograph or pollutant species. The study outcomes can also contribute to enhancing stormwater quality modelling and prediction in view of the fact that conventional approaches to stormwater quality estimation is primarily based on rainfall intensity rather than considering other rainfall parameters or solely based on stochastic approaches irrespective of the characteristics of the rainfall event.
Resumo:
Within the cardiac high dependency unit it is currently a member of the surgical team who makes the decision for a patient's chest drain to be removed after cardiac surgery. This has often resulted in delays in discharging one patient and therefore in admitting the next. A pilot study was carried out using a working standard that had been developed, incorporating an algorithmic model. The results have enabled nursing staff in a cardiac high dependency unit to undertake this responsibility independently.
Resumo:
Zero valent iron (ZVI) was prepared by reducing natural goethite (NG-ZVI) and synthetic goethite (SG-ZVI) in hydrogen at 550 °C. XRD, TEM, FESEM/EDS and specific surface area (SSA) and pore analyser were used to characterize goethites and reduced goethites. Both NG-ZVI and SG-ZVI with a size of nanoscale to several hundreds of nanometers were obtained by reducing goethites at 550 °C. The reductive capacity of the ZVIs was assessed by removal of Cr(VI) at ambient temperature in comparison with that of commercial iron powder (CIP). The effect of contact time, initial concentration and reaction temperature on Cr(VI) removal was investigated. Furthermore, the uptake mechanism was discussed according to isotherms, thermodynamic analysis and the results of XPS. The results showed that SG-ZVI had the best reductive capacity to Cr(VI) and reduced Cr(VI) to Cr(III). The results suggest that hydrogen reduction is a good approach to prepare ZVI and this type of ZVI is potentially useful in remediating heavy metals as a material of permeable reaction barrier.
Resumo:
Rolling Element Bearings (REBs) are vital components in rotating machineries for providing rotating motion. In slow speed rotating machines, bearings are normally subjected to heavy static loads and a catastrophic failure can cause enormous disruption to production and human safety. Due to its low operating speed the impact energy generated by the rotating elements on the defective components is not sufficient to produce a detectable vibration response. This is further aggravated by the inability of general measuring instruments to detect and process the weak signals at the initiation of the defect accurately. Furthermore, the weak signals are often corrupted by background noise. This is a serious problem faced by maintenance engineers today and the inability to detect an incipient failure of the machine can significantly increases the risk of functional failure and costly downtime. This paper presents the application of noise removal techniques for enhancing the detection capability for slow speed REB condition monitoring. Blind deconvolution (BD) and adaptive line enhancer (ALE) are compared to evaluate their performance in enhancing the source signal with consequential removal of background noise. In the experimental study, incipient defects were seeded on a number of roller bearings and the signals were acquired using acoustic emission (AE) sensor. Kurtosis and modified peak ratio (mPR) were used to determine the detectability of signal corrupted by noise.
Resumo:
This thesis advances the understanding of the impact of stigma on property values. A case study in Wellington, New Zealand, enabled hedonic modelling and an empirical analysis to determine the impact of the stigma from the high voltage transmission line structure and how long the stigma remained after removal. The results reveal a substantial difference between the discount applied to individual properties while the structure is in place, as compared to the overall increase in neighbourhood value once the structure, which created the stigma, is removed.
Resumo:
Methyl orange (MO) is a kind of anionic dye and widely used in industry. In this study, tricalcium aluminate hydrates (Ca-Al-LDHs) are used as an adsorbent to remove methyl orange (MO) from aqueous solutions. The resulting products were studied by X-ray diffraction (XRD), infrared spectroscopy (MIR), thermal analysis (TG-DTA) and scanning electron microscope (SEM). The XRD results indicated that the MO molecules were successfully intercalated into the tricalcium aluminate hydrates, with the basal spacing of Ca-Al-LDH expanding to 2.48 nm. The MIR spectrum for CaAl-MO-LDH shows obvious bands assigned to the N@N, N@H stretching vibrations and S@O, SO_ 3 group respectively, which are considered as marks to assess MO_ ion intercalation into the interlayers of LDH. The overall morphology of CaAl-MOLDH displayed a ‘‘honey-comb’’ like structure, with the adjacent layers expanded.
Resumo:
This article analyses in detail the approaches which have been taken when the court has been called upon to order removal of a caveat, particularly in circumstances where the caveat in question is valid as to form and protects a recognisable caveatable interest in land. It examines the question in all jurisdictions, with a primary focus on Western Australia.
Resumo:
Using a case study approach, this paper presents a robust methodology for assessing the compatibility of stormwater treatment performance data between two geographical regions in relation to a treatment system. The desktop analysis compared data derived from a field study undertaken in Florida, USA, with South East Queensland (SEQ) rainfall and pollutant characteristics. The analysis was based on the hypothesis that when transposing treatment performance information from one geographical region to another, detailed assessment of specific rainfall and stormwater quality parameters is required. Accordingly, characteristics of measured rainfall events and stormwater quality in the Florida study were compared with typical characteristics for SEQ. Rainfall events monitored in the Florida study were found to be similar to events that occur in SEQ in terms of their primary characteristics of depth, duration and intensity. Similarities in total suspended solids (TSS) and total nitrogen (TN) concentration ranges for Florida and SEQ suggest that TSS and TN removal performances would not be very different if the treatment system is installed in SEQ. However, further investigations are needed to evaluate the treatment performance of total phosphorus (TP). The methodology presented also allows comparison of other water quality parameters.
Resumo:
Stormwater bioretention basins are subjected to spontaneous intermittent wetting and drying, unlike water treatment filter systems that are subjected to continuous feed. Drinking water filters when constructed new or after back-wash, are subjected to a phase of stabilization. Experiments show that bioretention basins are similarly impacted by intermittent wetting and drying. The common parameter monitored in the stabilisation of filters is the concentration of total solids in the outflow. Filter media in bioretention basins however, consists of a mix of particulate organic matter and fine sand. Organic carbon and solids are therefore needed to be monitored. Four Perspex bioretention filter columns of 94 mm (ID) were packed with a filter layer (800 mm), transition layer and a gravel layer and operated with synthetic stormwater in the laboratory. The filter layer contained 8% organic material by weight. A free board of 350 mm provided detention storage and head to facilitate infiltration. Synthetic stormwater was prepared by adding NH4NO3 (ammonium nitrate) and C2H5NO2 (glycine) and a mixture of kaolinite and montmorillonite clay, to tapwater. The columns were fed with synthetic stormwater with different Antecedent Dry Days (ADD) (0 – 25 day) and constant inflow concentration (2 ppm: nitrate-nitrogen, 1.5 ppm: ammonium-nitrogen, 2.5 ppm: organic-nitrogen 100 ppm: total suspended solids and 7 ppm: organic carbon) at a feed rate of 100mL.min (85.7cm/h). Samples were collected from the outflow at different time intervals between 2 – 150 min from the start of outflow and were tested for Total Suspended Solids (TSS) and Total Organic Carbon (TOC). Both TSS and TOC concentrations in the outflow were observed to be much higher than the concentration of both the parameters in the inflow during the stabilisation period indicating a phase of wash-off (first flush) which lasted for approximately 30 min for both parameters at the beginning of each storm event. The wash-off of TSS and TOC were found to be highly variable depending on the age of the filter and the number of antecedent dry days. The duration of stabilisation phase in the experiments is significant compared with many of the stormwater events. A computational analysis on total mass of each pollutant further affirmed the significance of the first flush of an event on removal of these pollutants. Therefore, the kinetics of the first flush in the stabilisation phase needs to be considered in the performance analysis of the systems.
Resumo:
Stormwater pollution is linked to stream ecosystem degradation. In predicting stormwater pollution, various types of modelling techniques are adopted. The accuracy of predictions provided by these models depends on the data quality, appropriate estimation of model parameters, and the validation undertaken. It is well understood that available water quality datasets in urban areas span only relatively short time scales unlike water quantity data, which limits the applicability of the developed models in engineering and ecological assessment of urban waterways. This paper presents the application of leave-one-out (LOO) and Monte Carlo cross validation (MCCV) procedures in a Monte Carlo framework for the validation and estimation of uncertainty associated with pollutant wash-off when models are developed using a limited dataset. It was found that the application of MCCV is likely to result in a more realistic measure of model coefficients than LOO. Most importantly, MCCV and LOO were found to be effective in model validation when dealing with a small sample size which hinders detailed model validation and can undermine the effectiveness of stormwater quality management strategies.