RUNOFF FROM COAL PILES: EFFECTS ON THE ENVIRONMENT AND THE PUBLIC'S HEALTH

The use of coal for fuel in place of oil and natural gas has been increasing in the United States. Typically, users store their reserves of coal outdoors in large piles and rainfall on the coal creates runoffs which may contain materials hazardous to the environment and the public's health. To study this hazard, rainfall on model coal piles was simulated, using deionized water and four coals of varying sulfur content. The simulated surface runoffs were collected during 9 rainfall simulations spaced 15 days apart. The runoffs were analyzed for 13 standard water quality parameters, extracted with organic solvents and then analyzed with capillary column GC/MS, and the extracts were tested for mutagenicity with the Ames Salmonella microsomal assay and for clastogenicity with Chinese hamster ovary cells.^ The runoffs from the high-sulfur coals and the lignite exhibited extremes of pH (acidity), specific conductance, chemical oxygen demand, and total suspended solids; the low-sulfur coal runoffs did not exhibit these extremes. Without treatment, effluents from these high-sulfur coals and lignite would not comply with federal water quality guidelines.^ Most extracts of the simulated surface runoffs contained at least 10 organic compounds including polycyclic aromatic hydrocarbons, their methyl and ethyl homologs, olefins, paraffins, and some terpenes. The concentrations of these compounds were generally less than 50 (mu)g/l in most extracts.^ Some of the extracts were weakly mutagenic and affected both a DNA-repair proficient and deficient Salmonella strain. The addition of S9 decreased the effect significantly. Extracts of runoffs from the low-sulfur coal were not mutagenic.^ All extracts were clastogenic. Extracts of runoffs from the high-sulfur coals were both clastogenic and cytotoxic; those from the low-sulfur coal and the lignite were less clastogenic and not cytotoxic. Clastogenicity occurred with and without S9 activation. Chromosomal lesions included gaps, breaks and exchanges. These data suggest a relationship between the sulfur content of a coal, its mutagenicity and also its clastogenicity.^ The runoffs from actual coal piles should be investigated for possible genotoxic effects in view of the data presented in this study.^

THE NATURAL AND ORTHOGONAL INTERACTION (NOIA) MODELS FOR QUANTITATIVE TRAITS (QTs) AND COMPLEX DISEASES

My dissertation focuses on developing methods for gene-gene/environment interactions and imprinting effect detections for human complex diseases and quantitative traits. It includes three sections: (1) generalizing the Natural and Orthogonal interaction (NOIA) model for the coding technique originally developed for gene-gene (GxG) interaction and also to reduced models; (2) developing a novel statistical approach that allows for modeling gene-environment (GxE) interactions influencing disease risk, and (3) developing a statistical approach for modeling genetic variants displaying parent-of-origin effects (POEs), such as imprinting. In the past decade, genetic researchers have identified a large number of causal variants for human genetic diseases and traits by single-locus analysis, and interaction has now become a hot topic in the effort to search for the complex network between multiple genes or environmental exposures contributing to the outcome. Epistasis, also known as gene-gene interaction is the departure from additive genetic effects from several genes to a trait, which means that the same alleles of one gene could display different genetic effects under different genetic backgrounds. In this study, we propose to implement the NOIA model for association studies along with interaction for human complex traits and diseases. We compare the performance of the new statistical models we developed and the usual functional model by both simulation study and real data analysis. Both simulation and real data analysis revealed higher power of the NOIA GxG interaction model for detecting both main genetic effects and interaction effects. Through application on a melanoma dataset, we confirmed the previously identified significant regions for melanoma risk at 15q13.1, 16q24.3 and 9p21.3. We also identified potential interactions with these significant regions that contribute to melanoma risk. Based on the NOIA model, we developed a novel statistical approach that allows us to model effects from a genetic factor and binary environmental exposure that are jointly influencing disease risk. Both simulation and real data analyses revealed higher power of the NOIA model for detecting both main genetic effects and interaction effects for both quantitative and binary traits. We also found that estimates of the parameters from logistic regression for binary traits are no longer statistically uncorrelated under the alternative model when there is an association. Applying our novel approach to a lung cancer dataset, we confirmed four SNPs in 5p15 and 15q25 region to be significantly associated with lung cancer risk in Caucasians population: rs2736100, rs402710, rs16969968 and rs8034191. We also validated that rs16969968 and rs8034191 in 15q25 region are significantly interacting with smoking in Caucasian population. Our approach identified the potential interactions of SNP rs2256543 in 6p21 with smoking on contributing to lung cancer risk. Genetic imprinting is the most well-known cause for parent-of-origin effect (POE) whereby a gene is differentially expressed depending on the parental origin of the same alleles. Genetic imprinting affects several human disorders, including diabetes, breast cancer, alcoholism, and obesity. This phenomenon has been shown to be important for normal embryonic development in mammals. Traditional association approaches ignore this important genetic phenomenon. In this study, we propose a NOIA framework for a single locus association study that estimates both main allelic effects and POEs. We develop statistical (Stat-POE) and functional (Func-POE) models, and demonstrate conditions for orthogonality of the Stat-POE model. We conducted simulations for both quantitative and qualitative traits to evaluate the performance of the statistical and functional models with different levels of POEs. Our results showed that the newly proposed Stat-POE model, which ensures orthogonality of variance components if Hardy-Weinberg Equilibrium (HWE) or equal minor and major allele frequencies is satisfied, had greater power for detecting the main allelic additive effect than a Func-POE model, which codes according to allelic substitutions, for both quantitative and qualitative traits. The power for detecting the POE was the same for the Stat-POE and Func-POE models under HWE for quantitative traits.

BAYESIAN STATISTICAL METHODS IN GENE-ENVIRONMENT AND GENE-GENE INTERACTION STUDIES

Complex diseases such as cancer result from multiple genetic changes and environmental exposures. Due to the rapid development of genotyping and sequencing technologies, we are now able to more accurately assess causal effects of many genetic and environmental factors. Genome-wide association studies have been able to localize many causal genetic variants predisposing to certain diseases. However, these studies only explain a small portion of variations in the heritability of diseases. More advanced statistical models are urgently needed to identify and characterize some additional genetic and environmental factors and their interactions, which will enable us to better understand the causes of complex diseases. In the past decade, thanks to the increasing computational capabilities and novel statistical developments, Bayesian methods have been widely applied in the genetics/genomics researches and demonstrating superiority over some regular approaches in certain research areas. Gene-environment and gene-gene interaction studies are among the areas where Bayesian methods may fully exert its functionalities and advantages. This dissertation focuses on developing new Bayesian statistical methods for data analysis with complex gene-environment and gene-gene interactions, as well as extending some existing methods for gene-environment interactions to other related areas. It includes three sections: (1) Deriving the Bayesian variable selection framework for the hierarchical gene-environment and gene-gene interactions; (2) Developing the Bayesian Natural and Orthogonal Interaction (NOIA) models for gene-environment interactions; and (3) extending the applications of two Bayesian statistical methods which were developed for gene-environment interaction studies, to other related types of studies such as adaptive borrowing historical data. We propose a Bayesian hierarchical mixture model framework that allows us to investigate the genetic and environmental effects, gene by gene interactions (epistasis) and gene by environment interactions in the same model. It is well known that, in many practical situations, there exists a natural hierarchical structure between the main effects and interactions in the linear model. Here we propose a model that incorporates this hierarchical structure into the Bayesian mixture model, such that the irrelevant interaction effects can be removed more efficiently, resulting in more robust, parsimonious and powerful models. We evaluate both of the 'strong hierarchical' and 'weak hierarchical' models, which specify that both or one of the main effects between interacting factors must be present for the interactions to be included in the model. The extensive simulation results show that the proposed strong and weak hierarchical mixture models control the proportion of false positive discoveries and yield a powerful approach to identify the predisposing main effects and interactions in the studies with complex gene-environment and gene-gene interactions. We also compare these two models with the 'independent' model that does not impose this hierarchical constraint and observe their superior performances in most of the considered situations. The proposed models are implemented in the real data analysis of gene and environment interactions in the cases of lung cancer and cutaneous melanoma case-control studies. The Bayesian statistical models enjoy the properties of being allowed to incorporate useful prior information in the modeling process. Moreover, the Bayesian mixture model outperforms the multivariate logistic model in terms of the performances on the parameter estimation and variable selection in most cases. Our proposed models hold the hierarchical constraints, that further improve the Bayesian mixture model by reducing the proportion of false positive findings among the identified interactions and successfully identifying the reported associations. This is practically appealing for the study of investigating the causal factors from a moderate number of candidate genetic and environmental factors along with a relatively large number of interactions. The natural and orthogonal interaction (NOIA) models of genetic effects have previously been developed to provide an analysis framework, by which the estimates of effects for a quantitative trait are statistically orthogonal regardless of the existence of Hardy-Weinberg Equilibrium (HWE) within loci. Ma et al. (2012) recently developed a NOIA model for the gene-environment interaction studies and have shown the advantages of using the model for detecting the true main effects and interactions, compared with the usual functional model. In this project, we propose a novel Bayesian statistical model that combines the Bayesian hierarchical mixture model with the NOIA statistical model and the usual functional model. The proposed Bayesian NOIA model demonstrates more power at detecting the non-null effects with higher marginal posterior probabilities. Also, we review two Bayesian statistical models (Bayesian empirical shrinkage-type estimator and Bayesian model averaging), which were developed for the gene-environment interaction studies. Inspired by these Bayesian models, we develop two novel statistical methods that are able to handle the related problems such as borrowing data from historical studies. The proposed methods are analogous to the methods for the gene-environment interactions on behalf of the success on balancing the statistical efficiency and bias in a unified model. By extensive simulation studies, we compare the operating characteristics of the proposed models with the existing models including the hierarchical meta-analysis model. The results show that the proposed approaches adaptively borrow the historical data in a data-driven way. These novel models may have a broad range of statistical applications in both of genetic/genomic and clinical studies.

Comments and conclusions on the I International Seminary “Interdiscipline in Territorial Management "

El objetivo principal del I Seminario Internacional “ La Interdisciplina en el Ordenamiento Territorial, fue debatir sobre el aporte de las diversas disciplinas que confluyen en el Ordenamiento Territorial. Las ponencias presentadas fueron de un alto nivel científico y a partir de los casos analizados se demuestra que en la realidad coexisten espacios fragmentados social y económicamente, ya que se verifica la existencia de espacios globalizados con fuertes inversiones frente a otros que quedan marginados. Esta situación se manifiesta a través de la presencia de nuevos procesos de expansión y suburbanización, espacios rurales que se desvalorizan y se abandonan, ecosistemas naturales que deben ser protegidos para evitar un mayor deterioro medioambiental. Entre las conclusiones de los trabajos presentados se destacan: • La necesidad del mejoramiento de la capacidad de gestión a través de propuestas de nuevas metodológicas de trabajo, • la búsqueda de soluciones a las grandes disparidades socioeconómicas y al progresivo deterioro ambiental a partir del consenso de los agentes que intervienen, • la formulación de nuevas normativas acordes a las exigencias que impone la economía de mercado, entre otros.

Flow separation and roughness lengths over large bedforms in a tidal environment

This study characterises the shape of the flow separation zone (FSZ) and wake region over large asymmetric bedforms under tidal flow conditions. High resolution bathymetry, flow velocity and turbulence data were measured along two parallel transects in a tidal channel covered with bedforms. The field data are used to verify the applicability of a numerical model for a systematic study using the Delft3D modelling system and test the model sensitivity to roughness length. Three experiments are then conducted to investigate how the FSZ size and wake extent vary depending on tidally-varying flow conditions, water levels and bathymetry. During the ebb, a large FSZ occurs over the steep lee side of each bedform. During the flood, no flow separation develops over the bedforms having a flat crest; however, a small FSZ is observed over the steepest part of the crest of some bedforms, where the slope is locally up to 15°. Over a given bedform morphology and constant water levels, no FSZ occurs for velocity magnitudes smaller than 0.1 m s**-1; as the flow accelerates, the FSZ reaches a stable size for velocity magnitudes greater than 0.4 m s**-1. The shape of the FSZ is not influenced by changes in water levels. On the other hand, variations in bed morphology, as recorded from the high-resolution bathymetry collected during the tidal cycle, influence the size and position of the FSZ: a FSZ develops only when the maximum lee side slope over a horizontal distance of 5 m is greater than 10°. The height and length of the wake region are related to the length of the FSZ. The total roughness along the transect lines is an order of magnitude larger during the ebb than during the flood due to flow direction in relation to bedform asymmetry: during the ebb, roughness is created by the large bedforms because a FSZ and wake develops over the steep lee side. The results add to the understanding of hydrodynamics of natural bedforms in a tidal environment and may be used to better parameterise small-scale processes in large-scale studies.

Warming and acidification experiment on early life-stage F. vesiculosus under natural fluctuation and seasonal variations (spring 2013 - 2014)

Genetic diversity of baltic F. vesiculosus is low compared to other populations which might jeopardize their potential for adaptation to climate change. Especially the early life-stage F. vesiculosus may be threaten by ocean warming and acidification. To test this, we exposed F. vesiculosus germlings to warming and acidification in the near-natural scenario in the "Kiel Outdoor Benthocosms" maintaining the natural variation of the Kiel Fjord, Germany (54°27 'N, 10°11 'W) in all seasons (spring 2013 - 2014). Warming was simulated by using a delta treatment adding 5 °C and by increasing pCO2 at 1000 µatm. Warming positively affected germlings' growth in spring and in summer but decreased non-photochemical quenching in spring and survival in summer. Acidified conditions showed much weaker effects than warming. The high genotypic variation in stress sensitivity as well as the enhanced survival at high diversity levels indicate higher potential for adaptation for genetically diverse populations. We conclude that the combination of stressors and season determines the sensitivity to environmental stress and that genetic variation is crucial for the adaptation to climate change stress.

Interview forms for integrating education for conservation in marine protected areas management in Colombia

Environmental Education (EE) is a key component in any marine protected area management. However, its visibility and action plans are still poorly developed and structured as a clear element in management procedures. The objective of this study is to contribute with a methodological route that integrates EE to the existing model of management planning and strategies, taking the Colombian National Natural Parks System as a case study. The creation of the route is proposed as a participatory research with different stakeholders in order to respond to the specific conservation needs and goals for the National Parks System. The EE national diagnosis has shown that its integration within the parks management structure is a first priority need, being a converging result on the two case studies on National Parks from the Pacific Coast of Colombia. The diagnosis also demonstrates that communication, participation, training and evaluation have to be reinforced, linking the community and stakeholders involved in the park management to the whole EE process. The proposed methodology route has been agreed upon by the National Parks staff and incorporates advice and recommendations from different stakeholders, in order to better include the park users. This step will help us to advance toward sustainable management in marine and coastal protected areas elsewhere, taking into account not only the biological but also the social-cultural prism. The main challenges in the management and conservation of coastal and marine ecosystems today are discussed.

Sensitivity to ocean acidification parallels natural pCO2 gradients experienced by Arctic copepods under winter sea ice

The Arctic Ocean is a bellwether for ocean acidification, yet few direct Arctic studies have been carried out and limited observations exist, especially in winter. We present unique under-ice physicochemical data showing the persistence of a mid water column area of high CO2 and low pH through late winter, Zooplankton data demonstrating that the dominant copepod species are distributed across these different physicochemical conditions, and empirical data demonstrating that these copepods show sensitivity to pCO2 that parallels the range of natural pCO2 they experience through their daily vertical migration behavior. Our data, collected as part of the Catlin Arctic Survey, provide unique insight into the link between environmental variability, behavior, and an organism's physiological tolerance to CO2 in key Arctic biota.

Molecular fingerprinting and amplicon sequencing of the bacterial biofilm on settlement tiles deployed along natural pH gradients in Papua New Guinea

Bacterial biofilms provide cues for the settlement of marine invertebrates such as coral larvae, and are therefore important for the resilience and recovery of coral reefs. This study aimed to better understand how ocean acidification may affect the community composition and diversity of bacterial biofilms on surfaces under naturally reduced pH conditions. Settlement tiles were deployed at coral reefs in Papua New Guinea along pH gradients created by two CO2 seeps, and upper and lower tiles surfaces were sampled 5 and 13 months after deployment. Automated Ribosomal Intergenic Spacer Analysis were used to characterize more than 200 separate bacterial communities, complemented by amplicon sequencing of the bacterial 16S rRNA gene of 16 samples. The bacterial biofilm consisted predominantly of Alpha-, Gamma- and Deltaproteobacteria, as well as Cyanobacteria, Flavobacteriia and Cytophaga, whereas putative settlement-inducing taxa only accounted for a small fraction of the community. Bacterial biofilm composition was heterogeneous with approximately 25% shared operational taxonomic units between samples. Among the observed environmental parameters, pH only had a weak effect on community composition (R² ~ 1%) and did not affect community richness and evenness. In contrast, there were strong differences between upper and lower surfaces (contrasting in light exposure and grazing intensity). There also appeared to be a strong interaction between bacterial biofilm composition and the macroscopic components of the tile community. Our results suggest that on mature settlement surfaces in situ, pH does not have a strong impact on the composition of bacterial biofilms. Other abiotic and biotic factors such as light exposure and interactions with other organisms may be more important in shaping bacterial biofilms than changes in seawater pH.

Ramadan school holidays as a natural experiment : impacts of seasonality on school dropout in Bangladesh

In 2000, Ramadan school vacation coincided with the original annual exam period of December in Bangladesh. This forced schools to pre-pone their final exam schedules in November, which was the month before the harvest begins. 'Ramadan 2000' is a natural experiment that reduced the labor demand for children during the exam period. Using household level panel data of 2000 and 2003, and after controlling for various unobservable variations including individual fixed effects, aggregate year effects, and subdistrict-level year effects, this paper finds evidence of statistically significant impact of seasonal labor demand on school dropout in Bangladesh among the children from agricultural households.

Trade, economic growth and environment

The literature on trade openness, economic development, and the environment is largely inconclusive about the environmental consequences of trade. This study review previous studies focusing on treating trade and income as endogenous and estimating the overall impact of trade openness on environmental quality using the instrumental variables technique. The results show that whether or not trade has a beneficial effect on the environment varies depending on the pollutant and the country. Trade is found to benefit the environment in OECD countries. It has detrimental effects, however, on sulfur dioxide (SO2) and carbon dioxide (CO2) emissions in non-OECD countries, although it does lower biochemical oxygen demand (BOD) emissions in these countries. The results also find the impact is large in the long term, after the dynamic adjustment process, although it is small in the short term.

Geochemistry and risk assessment of street dust in Luanda, Angola, a tropical urban environment

A total of 92 samples of street dust were collected in Luanda, Angola, were sieved below 100 μm, and analysed by ICP-MS for 35 elements after an aqua-regia digestion. The concentration and spatial heterogeneity of trace elements in the street dust of Luanda are generally lower than in most industrialized cities in the Northern hemisphere. These observations reveal a predominantly “natural” origin for the street dust in Luanda, which is also manifested in that some geochemical processes that occur in natural soils are preserved in street dust: the separation of uranium from thorium, and the retention of the former by carbonate materials, or the high correlation between arsenic and vanadium due to their common mode of adsorption on solid particles in the form of oxyanions. The only distinct anthropogenic fingerprint in the composition of Luanda's street dust is the association Pb–Cd–Sb–Cu (and to a lesser extent, Ba–Cr–Zn). The use of risk assessment strategies has proved helpful in identifying the routes of exposure to street dust and the trace elements therein of most concern in terms of potential adverse health effects. In Luanda the highest levels of risk seem to be associated (a) with the presence of As and Pb in the street dust and (b) with the route of ingestion of dust particles, for all the elements included in the study except Hg, for which inhalation of vapours presents a slightly higher risk than ingestion. However, given the large uncertainties associated with the estimates of toxicity values and exposure factors, and the absence of site-specific biometric factors, these results should be regarded as preliminary and further research should be undertaken before any definite conclusions regarding potential health effects are drawn.

On the onset of turbulence in natural convection on inclined plates

The problem of determination of the turbulence onset in natural convection on heated inclined plates in an air environment has been experimentally revisited. The transition has been detected by using hot wire velocity measurements. The onset of turbulence has been considered to take place where velocity fluctuations (measured through turbulence intensity) start to grow. Experiments have shown that the onset depends not only on the Grashof number defined in terms of the temperature difference between the heated plate and the surrounding air. A correlation between dimensionless Grashof and Reynolds numbers has been obtained, fitting quite well the experimental data.

Dispersal of aphids, whiteflies and their natural enemies under photoselective nets

Integrated Pest Management of insects includes several control tactics, such as the use of photoselective nets, which may reduce the flight activity of insects. Limiting the dispersal of pests such as aphids and whiteflies is important because of their major role as vectors of plant viruses, while a minor impact on natural enemies is desired. In this study, we examined for the first time the dispersal ability of three vector species, Bemisia tabaci (Gennadius) (Hemiptera: Aleyrodidae), Macrosiphum euphorbiae (Thomas) (Hemiptera: Aphididae) and Myzus persicae (Sulzer) (Hemiptera: Aphididae), in cages covered with photoselective nets. Contrary to the results obtained with aphids, the ability of the whitefly B. tabaci, to reach the target plant was reduced by photoselective nets. In a second set of experiments, the impact of UV-absorbing nets on the visual cues of two important predator species, Orius laevigatus (Fieber) (Hemiptera: Anthocoridae) and Amblyseius swirskii Athias-Henriot (Acari: Phytoseiidae), was evaluated. The anthocorid was caught in higher numbers in traps placed under regular nets, whereas the mites preferably chose environments in which the UV radiation was attenuated. We have observed a wide range of effects that impedes generalization, although photoselective nets have a positive effect on pest management of whiteflies and aphids under protected environments.