Investigation of Zinc removal capacities of different sorbent materials to be used in constructed wetlands

ABSTRACTIt has been found over the past couple of years that health hazards associated with heavy metals havebeen on the rise, particularly the chronic diseases. Lack of tertiary treatment of wastewater may havecontributed to this emergent problem, mainly due to the high costs involved in the removal of heavymetals. Constructed wetlands have therefore received great attention as a tertiary treatment method ora polishing technique of wastewater due to its low construction and operation costs. However, findinga low-cost sorbent material to be used as the wetland filter material, which can be used as analternative to activated carbon, has been a problem for decades. Therefore, the present study focuseson applicability of low-cost sorbent materials: viz., clay tile, brick, saw dust and rice husks, as filtermediums. Laboratory-scale experiments were performed with a synthetic Zinc solution. Resultsrevealed that clay tile material has the highest adsorption capacity (47.6 mg/g) and removal efficiency,(98%), while brick (37.0 mg/g, 86%), sawdust (20.4 mg/g, 80%) and rice husks (15.8 mg/g, 64%)have relatively low adsorption capacities and removal efficiencies, respectively. The separation factorof equilibrium (RL) indicates favourable isotherms (0< RL<1) for all tested sorbent materials. Amongthe studied materials clay tile, brick and rice husks are good adsorbents for Zinc (n>2) while sawdustis a moderately difficult material for adsorption of Zinc (n <2).Keywords: adsorption isotherms, constructed wetlands, sorbent material, Zin

Zinc adsorption by lowcost sorbent materials: clay tile, Brick, sawdust and rice husk

It has been found over the past couple of years rapid growth of population, industrialization and urbanization has first and foremost contributed to the severe water pollution in both surface and ground water. The health hazards associated with heavy metals have been on the rise, particularly the chronic diseases. Lack of tertiary treatment of wastewater may have contributed to this emergent problem, adsorption process is considered as the best available water treatment method and activated carbon has proven to be the best sorbent material which can be used in removing wide variety of pollutants. However, usage of this activated carbon becomes restrict due to its high cost and regeneration cost. Therefore, the present study focuses on low-cost sorbent materials: viz., clay tile, brick, sawdust and rice husks. Laboratory-scale experiments were performed with a synthetic Zinc solution. Results revealed that clay tile material has the highest adsorption capacity (47.6 mg/g) and removal efficiency, (98%), while brick (37.0 mg/g, 86%), sawdust (20.4 mg/g, 80%) and rice husks (15.8 mg/g, 64%) have relatively low adsorption capacities and removal efficiencies, respectively. The separation factor of equilibrium (RL) indicates favourable isotherms (0< RL<1) for all tested sorbent materials. Among the studied materials clay tile, brick and rice husks are good adsorbent for Zinc (n>2) while sawdust is a moderately difficult material for adsorption of Zinc (n <2)

Are Green Jobs Sustainable for Sri Lankan Economy?

It is imperative that Sri Lanka grasps the concepts of green jobs to meet the most vital but intricatechallenge of the 21st Century, which is the transformation to a sustainable and a low-carbon economy.Such a transformation or a paradigm shift, which can be gradual or rapid depending on the circumstances,will undoubtedly have a considerable positive effect on the way we produce and/or consume goods andservices. The speed at which this transformation would occur is likely to accelerate in the near future asthere is a trend of global transition from a traditional to a low-carbon economy, in order to attainsustainable economies. Such trends will help create an array of different forms of green jobs across manysectors, and most probably can become a catalyst for further development. The International LabourOrganization (ILO) has defined green jobs as “Jobs created when they help in reducing the negativeenvironmental impacts ultimately leading to environmentally, economically and socially sustainableenterprises and economies”. Green jobs, in general, stand on two pillars: decent work and environmentalsustainability. Thus, green jobs can be defined as decent work that contributes to environmentalsustainability. In a broader sense decent work needs to address the core of international labour standardssuch as freedom of association and effective recognition of the right to collective bargaining, eliminationof all forms of forced or compulsory labour, effective abolition of child labour, elimination ofdiscrimination in respect of employment and occupation, occupational health and safety, etc. whilstaligning to laws applicable to Sri Lanka. Environmental sustainability addresses issues such as effectivelycombating climate change, pollution prevention and control, conservation of eco-systems and biodiversityetc. (ILO, 2007)

DETECTION OF CLOUDS IN MEDIUM-RESOLUTION SATELLITE IMAGERY USING DEEP CONVOLUTIONAL NEURAL NETS

Cloud detection is an inextricable pre-processing step in remote sensing image analysis workflows. Most of the traditional rule-based and machine-learning-based algorithms utilize low-level features of the clouds and classify individual cloud pixels based on their spectral signatures. Cloud detection using such approaches can be challenging due to a multitude of factors including harsh lighting conditions, the presence of thin clouds, the context of surrounding pixels, and complex spatial patterns. In recent studies, deep convolutional neural networks (CNNs) have shown outstanding results in the computer vision domain. These methods are practiced for better capturing the texture, shape as well as context of images. In this study, we propose a deep learning CNN approach to detect cloud pixels from medium-resolution satellite imagery. The proposed CNN accounts for both the low-level features, such as color and texture information as well as high-level features extracted from successive convolutions of the input image. We prepared a cloud-pixel dataset of approximately 7273 randomly sampled 320 by 320 pixels image patches taken from a total of 121 Landsat-8 (30m) and Sentinel-2 (20m) image scenes. These satellite images come with cloud masks. From the available data channels, only blue, green, red, and NIR bands are fed into the model. The CNN model was trained on 5300 image patches and validated on 1973 independent image patches. As the final output from our model, we extract a binary mask of cloud pixels and non-cloud pixels. The results are benchmarked against established cloud detection methods using standard accuracy metrics

Aggregation and settling in aqueous polydisperse alumina nanoparticle suspensions

Nanoparticle suspensions (also called nanofluids) are often polydisperse and tend to settle with time. Settling kinetics in these systems are known to be complex and hence challenging to understand. In this work, polydisperse spherical alumina (Al2O3) nanoparticles in the size range of ~10-100nm were dispersed in water and examined for aggregation and settling behaviour near its isoelectric point (IEP). A series of settling experiments were conducted and the results were analysed by photography and by Small Angle X-ray Scattering (SAXS). The settling curve obtained from standard bed height measurement experiments indicated two different types of behaviour, both of which were also seen in the SAXS data. But the SAXS data were remarkably able to pick out the rapid settling regime as a result of the high temporal resolution (10s) used. By monitoring the SAXS intensity, it was further possible to record the particle aggregation process for the first time. Optical microscopy images were produced on drying and dried droplets extracted from the suspension at various times. Dried deposits showed the rapid decrease in the number of very large particles with time which qualitatively validates the SAXS prediction, and therefore its suitability as a tool to study unstable polydisperse colloids. Keywords: Nanoparticles, nanofluids, polydisperse, aggregation, settling, alumina, microscopy, SAX

High-affinity RNA binding by a hyperthermophilic single-stranded DNA-binding protein

Single-stranded DNA-binding proteins (SSBs), including replication protein A (RPA) in eukaryotes, play a central role in DNA replication, recombination, and repair. SSBs utilise an oligonucleotide/oligosaccharide-binding (OB) fold domain to bind DNA, and typically oligomerise in solution to bring multiple OB fold domains together in the functional SSB. SSBs from hyperthermophilic crenarchaea, such as Sulfolobus solfataricus, have an unusual structure with a single OB fold coupled to a flexible C-terminal tail. The OB fold resembles those in RPA, whilst the tail is reminiscent of bacterial SSBs and mediates interaction with other proteins. One paradigm in the field is that SSBs bind specifically to ssDNA and much less strongly to RNA, ensuring that their functions are restricted to DNA metabolism. Here, we use a combination of biochemical and biophysical approaches to demonstrate that the binding properties of S. solfataricus SSB are essentially identical for ssDNA and ssRNA. These features may represent an adaptation to a hyperthermophilic lifestyle, where DNA and RNA damage is a more frequent event.Publisher PDFPeer reviewe

A review on boiling heat transfer enhancement with nanofluids

There has been increasing interest of late in nanofluid boiling and its use in heat transfer enhancement. This article covers recent advances in the last decade by researchers in both pool boiling and convective boiling applications, with nanofluids as the working fluid. The available data in the literature is reviewed in terms of enhancements, and degradations in the nucleate boiling heat transfer and critical heat flux. Conflicting data have been presented in the literature on the effect that nanofluids have on the boiling heat-transfer coefficient; however, almost all researchers have noted an enhancement in the critical heat flux during nanofluid boiling. Several researchers have observed nanoparticle deposition at the heater surface, which they have related back to the critical heat flux enhancement