Removal of disinfection by-product precursors by activated carbon and MIEX(R)

Title from PDF of title page (University of Missouri--Columbia, viewed on May 23, 2012).The entire thesis text is included in the research.pdf file; the official abstract appears in the short.pdf file; a non-technical public abstract appears in the public.pdf file.Thesis advisor: Dr. Thomas ClevengerIncludes bibliographical references."July 2011"The objective of this research was to investigate NOM removal with activated carbon and MIEX(R). Hydrophilic (HPI), hydrophobic (HPO), and transphilic (TPI) NOM was fractionated and subsequent DBP formation from these fractions was studied. Several new adsorptive materials (greensand, carbon nanotubes, iron impregnated activated carbon) were tested for DBP reduction potential. Reductions by the materials were poor and therefore the materials were not investigated further. Activated carbons, although similar in structure, perform differently from each other. Aqua Nuchar[copyright] and Hawkins Sabre Series[copyright] had greater than 30% difference in TTHM FP reduction under the same test conditions. None of the activated carbons investigated were found to have potential for brominated DBP precursor removal. When MIEX(R) (magnetic ion exchange) was compared to activated carbon with respect to NOM fraction removal, it was found that MIEX(R) removed more of the HPI and TPI fractions. This was represented well in DBP FP reductions specifically derived from reactions with NOM in these fractions. In particular, MIEX(R) decreased NOM in the HPI fraction only 10% more than activated carbon but decreased TTHM FP 34% greater than activated carbon. This suggests that MIEX(R) preferentially removes DBP precursors to a greater extent than activated carbon. MIEX(R) was also found to decrease formation of brominated DBPs. SUVA, UV254, DOC, and chlorine demand were all investigated as surrogate parameters for DBPs. UV254 was found to correlate best with DBP formation with 0.56<R2<0.80. UV254 absorbed by HPO NOM was found to correlate best with TTHM FP (R2=0.88) with HPI being poorly correlated (R2=0.20). THMs resulting from reactions with HPI NOM accounted for between 40% and 55% of THMs from all fractions

Developing and interpreting aqueous functional assays for comparative property-activity relationships of different nanoparticles

It is difficult to relate intrinsic nanomaterial properties to their functional behavior in the environment. Unlike frameworks for dissolved organic chemicals, there are few frameworks comparing multiple and inter-related properties of engineered nanomaterials (ENMs) to their fate, exposure, and hazard in environmental systems. We developed and evaluated reproducibility and inter-correlation of 12 physical, chemical, and biological functional assays in water for eight different engineered nanomaterials (ENMs) and interpreted results using activity-profiling radar plots. The functional assays were highly reproducible when run in triplicate (average coefficient of variation [CV] = 6.6%). Radar plots showed that each nanomaterial exhibited unique activity profiles. Reactivity assays showed dissolution or aggregation potential for some ENMs. Surprisingly, multi-walled carbon nanotubes (MWCNTs) exhibited movement in a magnetic field. We found high inter-correlations between cloud point extraction (CPE) and distribution to sewage sludge (R-2 = 0.99), dissolution at pH 8 and pH 4.9 (R-2 = 0.98), and dissolution at pH 8 and zebrafish mortality at 24 hpf (R-2 = 0.94). Additionally, most ENMs tend to distribute out of water and into other phases (i.e., soil surfaces, surfactant micelles, and sewage sludge). The activity-profiling radar plots provide a framework and estimations of likely ENM disposition in the environment. (C) 2018 Elsevier B.V. All rights reserved

Trade-offs in ecosystem impacts from nanomaterial versus organic chemical ultraviolet filters in sunscreens

Both nanoparticulate (nZnO and nTiO(2)) and organic chemical ultraviolet (UV) filters are active ingredients in sunscreen and protect against skin cancer, but limited research exists on the environmental effects of sunscreen release into aquatic systems. To examine the trade-offs of incorporating nano particles (NPs) into sunscreens over the past two decades, we targeted endpoints sensitive to the potential risks of different UV filters: solar reactive oxygen production in water and disruption of zebrafish embryo development. First, we developed methodology to extract nanoparticles from sunscreens with organic solvents. Zebrafish embryos exposed to parts-per-million NPs used in sunscreens displayed limited toxicological effects; nZnO particles appeared to be slightly more toxic than nTiO(2) at the highest concentrations. In contrast, seven organic UV filters did not affect zebrafish embryogenesis at or near aqueous solubility. Second, to simulate potent photo-initiated reactions upon release into water, we examined methylene blue (MB) degradation under UV light. nTiO(2) from sunscreen caused 10 times faster MB loss than nZnO and approached the photocatalytic degradation rate of a commercial nTiO(2) photo catalysts (P25). Organic UV filters did not cause measurable MB degradation. Finally, we estimated that between 1 and 10 ppm of sunscreen NPs in surface waters could produce similar steady state hydroxyl radical concentrations as naturally occurring fluvic acids under sunlight irradiation. Incorporation of NPs into sunscreen may increase environmental concentrations of reactive oxygen, albeit to a limited extent, which can influence transformation of dissolved substances and potentially affect ecosystem processes. (C) 2018 Elsevier Ltd. All rights reserved

Development of a cloud-based platform for reproducible science: a case study of an IUCN red list of ecosystems assessment

One of the challenges of computational-centric research is to make the research undertaken reproducible in a form that others can repeat and re-use with minimal effort. In addition to the data and tools necessary to re-run analyses, execution environments play crucial roles because of the dependencies of the operating system and software version used. However, some of the challenges of reproducible science can be addressed using appropriate computational tools and cloud computing to provide an execution environment. Here, we demonstrate the use of a Kepler scientific workflow for reproducible science that is sharable, reusable, and re-executable. These workflows reduce barriers to sharing and will save researchers time when undertaking similar research in the future. To provide infrastructure that enables reproducible science, we have developed cloud-based Collaborative Environment for Ecosystem Science Research and Analysis (CoESRA) infrastructure to build, execute and share sophisticated computation-centric research. The CoESRA provides users with a storage and computational platform that is accessible from a web-browser in the form of a virtual desktop. Any registered user can access the virtual desktop to build, execute and share the Kepler workflows. This approach will enable computational scientists to share complete workflows in a pre-configured environment so that others can reproduce the computational research with minimal effort. As a case study, we developed and shared a complete IUCN Red List of Ecosystems Assessment workflow that reproduces the assessments undertaken by Burns et al. (2015) on Mountain Ash forests in the Central Highlands of Victoria, Australia. This workflow provides an opportunity for other researchers and stakeholders to run this assessment with minimal supervision. The workflow also enables researchers to re-evaluate the assessment when additional data becomes available. The assessment can be run in a CoESRA virtual desktop by opening a workflow in a Kepler user interface and pressing a “start” button. The workflow is pre-configured with all the open access datasets and writes results to a pre-configured folder

Riječ uredništva

BACKGROUND: Methods for estimating air pollutant exposures for epidemiological studies are becoming more complex in an effort to minimise exposure error and its associated bias. While land use regression (LUR) modelling is now an established method, there has been little comparison between LUR and other recent, more complex estimation methods. Our aim was to develop a LUR model to estimate intra-city exposures to nitrogen dioxide (NO2) for a Sydney cohort, and to compare those with estimates from a national satellite-based LUR model (Sat-LUR) and a regional Bayesian Maximum Entropy (BME) model. METHODS: Satellite-based LUR and BME estimates were obtained using existing models. We used methods consistent with the European Study of Cohorts for Air Pollution Effects (ESCAPE) methodology to develop LUR models for NO2 and NOx. We deployed 46 Ogawa passive samplers across western Sydney during 2013/2014 and acquired data on land use, population density, and traffic volumes for the study area. Annual average NO2 concentrations for 2013 were estimated for 947 addresses in the study area using the three models: standard LUR, Sat-LUR and a BME model. Agreement between the estimates from the three models was assessed using interclass correlation coefficient (ICC), Bland-Altman methods and correlation analysis (CC). RESULTS: The NO2 LUR model predicted 84% of spatial variability in annual mean NO2 (RMSE: 1.2 ppb; cross-validated R2: 0.82) with predictors of major roads, population and dwelling density, heavy traffic and commercial land use. A separate model was developed that captured 92% of variability in NOx (RMSE 2.3 ppb; cross-validated R2: 0.90). The annual average NO2 concentrations were 7.31 ppb (SD: 1.91), 7.01 ppb (SD: 1.92) and 7.90 ppb (SD: 1.85), for the LUR, Sat-LUR and BME models respectively. Comparing the standard LUR with Sat-LUR NO2 cohort estimates, the mean estimates from the LUR were 4% higher than the Sat-LUR estimates, and the ICC was 0.73. The Pearson's correlation coefficients (CC) for the LUR vs Sat-LUR values were r = 0.73 (log-transformed data) and r = 0.69 (untransformed data). Comparison of the NO2 cohort estimates from the LUR model with the BME blended model indicated that the LUR mean estimates were 8% lower than the BME estimates. The ICC for the LUR vs BME estimates was 0.73. The CC for the logged LUR vs BME estimates was r = 0.73 and for the unlogged estimates was r = 0.69. CONCLUSIONS: Our LUR models explained a high degree of spatial variability in annual mean NO2 and NOx in western Sydney. The results indicate very good agreement between the intra-city LUR, national-scale sat-LUR, and regional BME models for estimating NO2 for a cohort of children residing in Sydney, despite the different data inputs and differences in spatial scales of the models, providing confidence in their use in epidemiological studies

Making ecological monitoring successful: Insights and lessons from the Long Term Ecological Research Network

Ecological monitoring allows us to track changes in the environment and helps us see how our actions affect the environment. Long-term monitoring is particularly important, yielding valuable insights that are not possible from shorter-term investigations. We consider successful ecological monitoring to be monitoring that generates knowledge that is useful to others, and can be valuable in adaptive and effective environmental management. Any effective monitoring program requires a number of fundamental considerations, and additional factors should be considered in the design of a long-term monitoring program. This booklet describes what we consider to be the key characteristics of successful ecological monitoring, including long-term monitoring.All these characteristics work together. For example, good project design cannot meet its objectives without long-term funding; data management must be matched by good communication; and good partnerships must be maintained through succession and project planning. In discussing these characteristics and our recommendations for how they may be achieved, we present a series of stories and quotes. These insights are based on the collective experience of research leaders of the 12 plot networks within the Long Term Ecological Research Network, along with other professionals associated with the network. These stories highlight just how difficult it is to do long-term ecological research in Australia. They also illustrate the unique value of this kind of research for helping to understand and manage the Australian environment. We hope that this booklet will support the development of more effective and influential long-term ecological projects in Australia.LTERN is a facility within the Terrestrial Ecosystem Research Network (TERN). TERN is supported by the Australian Government through the National Collaborative Research Infrastructure Strategy

Carcinogenic Effects in a Phenylketonuria Mouse Model

Phenylketonuria (PKU) is a metabolic disorder caused by impaired phenylalanine hydroxylase (PAH). This condition results in hyperphenylalaninemia and elevated levels of abnormal phenylalanine metabolites, among which is phenylacetic acid/phenylacetate (PA). In recent years, PA and its analogs were found to have anticancer activity against a variety of malignancies suggesting the possibility that PKU may offer protection against cancer through chronically elevated levels of PA. We tested this hypothesis in a genetic mouse model of PKU (PAHenu2) which has a biochemical profile that closely resembles that of human PKU. Plasma levels of phenylalanine in homozygous (HMZ) PAHenu2 mice were >12-fold those of heterozygous (HTZ) littermates while tyrosine levels were reduced. Phenylketones, including PA, were also markedly elevated to the range seen in the human disease. Mice were subjected to 7,12 dimethylbenz[a]anthracene (DMBA) carcinogenesis, a model which is sensitive to the anticancer effects of the PA derivative 4-chlorophenylacetate (4-CPA). Tumor induction by DMBA was not significantly different between the HTZ and HMZ mice, either in total tumor development or in the type of cancers that arose. HMZ mice were then treated with 4-CPA as positive controls for the anticancer effects of PA and to evaluate its possible effects on phenylalanine metabolism in PKU mice. 4-CPA had no effect on the plasma concentrations of phenylalanine, phenylketones, or tyrosine. Surprisingly, the HMZ mice treated with 4-CPA developed an unexplained neuromuscular syndrome which precluded its use in these animals as an anticancer agent. Together, these studies support the use of PAHenu2 mice as a model for studying human PKU. Chronically elevated levels of PA in the PAHenu2 mice were not protective against cancer

Inherited determinants of Crohn's disease and ulcerative colitis phenotypes: a genetic association study

Crohn's disease and ulcerative colitis are the two major forms of inflammatory bowel disease; treatment strategies have historically been determined by this binary categorisation. Genetic studies have identified 163 susceptibility loci for inflammatory bowel disease, mostly shared between Crohn's disease and ulcerative colitis. We undertook the largest genotype association study, to date, in widely used clinical subphenotypes of inflammatory bowel disease with the goal of further understanding the biological relations between diseases

Pollen Loads and Allergic Rhinitis in Darwin, Australia: A Potential Health Outcome of the Grass-Fire Cycle

Although the prevalence of asthma and allergic rhinitis has been increasing in tropical regions, little is known about the allergenicity of pollens from tropical plant families or the importance of ongoing environmental changes. We investigated associations between daily average pollen counts of several tropical plant families and sales of medications for the treatment of allergic rhinitis in Darwin, Australia-a tropical setting in which grass abundance has increased due to increased fire frequencies and the introduction of African pasture grasses. Daily pollen counts with detailed identification of plant species were undertaken in conjunction with a weekly survey of flowering plant species from April 2004 to November 2005. Five pharmacies provided daily sales data of selected medications commonly used to treat allergic rhinitis. We used generalized linear modeling to examine outcomes. All analyses accounted for the potential confounding effects of time trends, holidays, respiratory viral illnesses, meteorological conditions, and air pollution. The peak total pollen count was 94 grains/m3. Despite the low levels of Poaceae (grass) pollen (maximum daily count, 24 grains/m3), there was a clear association with daily sales of anti-allergic medications greatest at a lag of 1 day. Sales increased by 5% with an interquartile range rise (3 grain/m 3) in Poaceae pollen (5.07%, 95%CI 1.04%, 9.25%). No associations were observed with pollen from other plant families. Although further testing is required, we suggest that an overlooked aspect of the "grass-fire cycle" that is degrading many tropical landscapes, could be an increase in the prevalence of allergic rhinitis