Ecology And Seasonal Variation Of Microalgal Community In An Oil Refinery Effluent Holding Pond: Monitoring And Assessment

The microalgal community as primary producers has to play a significant role in the biotic and abitoic interactions of any aquatic ecosystem. Whenever a community is exposed to a pollutant, responses can occur because individuals acclimate to pollutant caused changes and selection can occur favouring resistant genotypes within a population and selection among species can result in changes in community structure. The microalgal community of industrial effluent treatment systems are continuously exposed to pollutants and there is little data available on the structure and seasonal variation of microalgal community of industrial effluent holding ponds, especially of a complex effluent like that of refinery. The aim of the present study was to investigate the annual variation in the ecology, biomass, productivity and community structure of the algal community of a refinery effluent holding pond. The results of the study showed the pond to be a eutrophic system with a resistant microalgal community with distinct seasonal variation in species composition

Assessment of Energy Conservation in Indian Cement Industry and Forecasting of Co2 Emissions

Cement industry ranks 2nd in energy consumption among the industries in India. It is one of the major emitter of CO2, due to combustion of fossil fuel and calcination process. As the huge amount of CO2 emissions cause severe environment problems, the efficient and effective utilization of energy is a major concern in Indian cement industry. The main objective of the research work is to assess the energy cosumption and energy conservation of the Indian cement industry and to predict future trends in cement production and reduction of CO2 emissions. In order to achieve this objective, a detailed energy and exergy analysis of a typical cement plant in Kerala was carried out. The data on fuel usage, electricity consumption, amount of clinker and cement production were also collected from a few selected cement industries in India for the period 2001 - 2010 and the CO2 emissions were estimated. A complete decomposition method was used for the analysis of change in CO2 emissions during the period 2001 - 2010 by categorising the cement industries according to the specific thermal energy consumption. A basic forecasting model for the cement production trend was developed by using the system dynamic approach and the model was validated with the data collected from the selected cement industries. The cement production and CO2 emissions from the industries were also predicted with the base year as 2010. The sensitivity analysis of the forecasting model was conducted and found satisfactory. The model was then modified for the total cement production in India to predict the cement production and CO2 emissions for the next 21 years under three different scenarios. The parmeters that influence CO2 emissions like population and GDP growth rate, demand of cement and its production, clinker consumption and energy utilization are incorporated in these scenarios. The existing growth rate of the population and cement production in the year 2010 were used in the baseline scenario. In the scenario-1 (S1) the growth rate of population was assumed to be gradually decreasing and finally reach zero by the year 2030, while in scenario-2 (S2) a faster decline in the growth rate was assumed such that zero growth rate is achieved in the year 2020. The mitigation strategiesfor the reduction of CO2 emissions from the cement production were identified and analyzed in the energy management scenarioThe energy and exergy analysis of the raw mill of the cement plant revealed that the exergy utilization was worse than energy utilization. The energy analysis of the kiln system showed that around 38% of heat energy is wasted through exhaust gases of the preheater and cooler of the kiln sysetm. This could be recovered by the waste heat recovery system. A secondary insulation shell was also recommended for the kiln in the plant in order to prevent heat loss and enhance the efficiency of the plant. The decomposition analysis of the change in CO2 emissions during 2001- 2010 showed that the activity effect was the main factor for CO2 emissions for the cement industries since it is directly dependent on economic growth of the country. The forecasting model showed that 15.22% and 29.44% of CO2 emissions reduction can be achieved by the year 2030 in scenario- (S1) and scenario-2 (S2) respectively. In analysing the energy management scenario, it was assumed that 25% of electrical energy supply to the cement plants is replaced by renewable energy. The analysis revealed that the recovery of waste heat and the use of renewable energy could lead to decline in CO2 emissions 7.1% for baseline scenario, 10.9 % in scenario-1 (S1) and 11.16% in scenario-2 (S2) in 2030. The combined scenario considering population stabilization by the year 2020, 25% of contribution from renewable energy sources of the cement industry and 38% thermal energy from the waste heat streams shows that CO2 emissions from Indian cement industry could be reduced by nearly 37% in the year 2030. This would reduce a substantial level of greenhouse gas load to the environment. The cement industry will remain one of the critical sectors for India to meet its CO2 emissions reduction target. India’s cement production will continue to grow in the near future due to its GDP growth. The control of population, improvement in plant efficiency and use of renewable energy are the important options for the mitigation of CO2 emissions from Indian cement industries

Yield gap analysis and assessment of climate-induced yield trends of irrigated rice in selected provinces of the Philippines

This study describes a combined empirical/modeling approach to assess the possible impact of climate variability on rice production in the Philippines. We collated climate data of the last two decades (1985-2002) as well as yield statistics of six provinces of the Philippines, selected along a North-South gradient. Data from the climate information system of NASA were used as input parameters of the model ORYZA2000 to determine potential yields and, in the next steps, the yield gaps defined as the difference between potential and actual yields. Both simulated and actual yields of irrigated rice varied strongly between years. However, no climate-driven trends were apparent and the variability in actual yields showed no correlation with climatic parameters. The observed variation in simulated yields was attributable to seasonal variations in climate (dry/wet season) and to climatic differences between provinces and agro-ecological zones. The actual yield variation between provinces was not related to differences in the climatic yield potential but rather to soil and management factors. The resulting yield gap was largest in remote and infrastructurally disfavored provinces (low external input use) with a high production potential (high solar radiation and day-night temperature differences). In turn, the yield gap was lowest in central provinces with good market access but with a relatively low climatic yield potential. We conclude that neither long-term trends nor the variability of the climate can explain current rice yield trends and that agroecological, seasonal, and management effects are over-riding any possible climatic variations. On the other hand the lack of a climate-driven trend in the present situation may be superseded by ongoing climate change in the future.

Preparing an Annotated Bibliography and overview of the Data Protection Act

Slides used in lecture, explaining coursework and providing an introduction to the Data Protection Act. Students should use these resources as guidance for the forthcoming coursework (annotated bibliography). Like all materials you can expect slides to address issues which come up future assessment activities

Reliability of the Brief Neuropsychological Assessment Instrument Neupsilin

This study aimed to evaluate the reliability of Neupsilin Brief Neuropsychological Assessment Instrument, a brief battery developed in Brazil. Hundred two Brazilian man and women participated, from 18 to 40 years of age. It was evaluated the test-retest reliability of the Neupsilin tasks and the reliability of the correction of the constructional praxis task by different evaluators. The data were analyzed by Spearman’s correlation, intraclass correlation and Cronbach’s alpha. Language, memory, praxis and executive functions presented the highest correlations in the test-retest analyses. The agreement in the correction of the constructional praxis task was moderate to high. The results indicate temporal reliability of Neupsilin tasks and inter-rater agreement in the correction of the constructional praxis task. Suggestions to improve the tasks, the validity and reliability of Neupsilin were presented.

Brief neuropsychological assessment of adults post-stroke in the left hemisphere

The neuropsychological assessment investigates cognitive deficits to improve the diagnosis, the prognosis and the rehabilitation of patients. In Brazil, stroke is a major cause of hospitalization and the leading cause of mortality and disability. The stroke in the left hemisphere (LH) is associated with different degrees of loss of language and other cognitive impairments, for example, in the memory. We compared the performance in brief neuropsychological tasks of the left hemisphere poststroke patients, without moderate or severe aphasia, with healthy controls. A list of 135 patients was selected based on inclusion criteria. The study included 15 patients with left stroke, paired by sex, age and education to 30 neurologically healthy adults. The data resulting from application of the Neupsilin Brief Neuropsychological Assessment Instrument were analyzed with the nonparametric Mann-Whitney U. Adults with LH stroke showed a significant reduction in performance when compared to healthy controls on language, working memory and ideomotor praxis, results also found in other studies of patients with left hemisphere stroke

Brain injury: Assessment of hemineglect occurence and of attentional deficit through cancellation tasks

Hemineglect (HN) is a widely studied syndrome after unilateral lesions due to stroke. However, although there are some studies with HN rehabilitation of posttraumatic brain injury (TBI), there seems to be no published data about the prevalence of HN in TBI through cancellation tasks. Thus, the objective of this study was to characterize the occurrence of this syndrome and of attentional deficits in patients with TBI by means of the Bells Test and of a line cancellation task. The sample was comprised of 21 patients with TBI and 21 healthy controls matched by education, age and frequency of written language habits. There was a poorer performance of patients with TBI with a greater number of omissions on the left side and lower speed processing. In addition, suggestive signs of HN were found in 38 % of the sample of TBI patients. More research is needed to characterize clinical syndromes regarding the occurrence of HN after a TBI through the traditionally known cancellation paradigm.

Exploratory Study on Occupational Health Exposure to Chemical Agents, in a Public Hospital in Valencia, Venezuela. Preliminar Assessment

Descriptive study that identified chemical agents (AQ) use and training on risk management and waste disposal techniques in a public Hospital in Valencia. A questionnaire was answered by 48 workers. Information obtained was: personal data, occupational history, AQ used; knowledge of risk management and waste disposal. There were 16 occupations from 12 “High Risk” areas. “Adult emergency” was the one with more workers (11 individuals), followed by “sterilization” and “clinical laboratory” (7 each) and oncology (5). The remained areas had less than 8.3% workers. The most used anesthetic agents were: Halothane, Enfluorane and Isofluorane 4.17% each and main antineoplastics used were: Doxorubicin 16.67% and Paclitaxel, 5-Fluoracil and Etoposide, 8.33% each. The most mentioned substances were: alcohol (70.8%) and Chlorine (64.6%). None of the answers regarding knowledge of AQ’ risk management and waste disposal was satisfactory. Statistical associations between training and several variables such as age, time in their job and being or not a professional, resulted non-significant. The correlation between training and the knowledge of AQ’s management was significant (p < 0.001). Participants showed that their knowledge about chemical occupational risk factors they are exposed to is still insufficient. Therefore, this theme should be included in graduate course curricula. These results provide important data and will serve as a pilot research for the follow up Phase II study that will include clinical aspects and environmental and biological monitoring.

Population Assessment of an Endangered Shorebird: the Piping Plover (Charadrius melodus melodus) in Eastern Canada

Small, at-risk populations are those for which accurate demographic information is most crucial to conservation and recovery, but also where data collection is constrained by logistical challenges and small sample sizes. Migratory animals in particular may experience a wide range of threats to survival and reproduction throughout each annual cycle, and identification of life stages most critical to persistence may be especially difficult for these populations. The endangered eastern Canadian breeding population of Piping Plover (Charadrius melodus melodus) was estimated at only 444 adults in 2005, and extensive effort has been invested in conservation activities, reproductive monitoring, and marking of individual birds, providing a comprehensive data set on population dynamics since 1998. We used these data to build a matrix projection model for two Piping Plover population segments that nest in eastern Canada in order to estimate both deterministic and stochastic rates of population growth (λd and λs, respectively). Annual population censuses suggested moderate growth in abundance between 1998–2003, but vital rate estimates indicated that this temporary growth may be replaced by declines in the long term, both in southern Nova Scotia (λd = 1.0043, λs = 0.9263) and in the Gulf of St. Lawrence (λd = 0.9651, λs = 0.8214). Nonetheless, confidence intervals on λ estimates were relatively wide, highlighting remaining uncertainty in future population trajectories. Differences in projected growth between regions appear to be driven by low estimated juvenile post-fledging survival in the Gulf, but threats to juveniles of both population segments following departure from nesting beaches remain unidentified. Similarly, λ in both population segments was particularly sensitive to changes in adult survival as expected for most migratory birds, but very little is understood about the threats to Piping Plover survival during migration and overwintering. Consequently, we suggest that future recovery efforts for these and other vulnerable migrants should quantify and manage the largely unknown sources of both adult and juvenile mortality during non-breeding seasons while maintaining current levels of nesting habitat protection.

Artificial Cavities and Nest Site Selection by Puerto Rican Parrots: a Multiscale Assessment

We examined nest site selection by Puerto Rican Parrots, a secondary cavity nester, at several spatial scales using the nest entrance as the central focal point relative to 20 habitat and spatial variables. The Puerto Rican Parrot is unique in that, since 2001, all known nesting in the wild has occurred in artificial cavities, which also provided us with an opportunity to evaluate nest site selection without confounding effects of the actual nest cavity characteristics. Because of the data limitations imposed by the small population size of this critically endangered endemic species, we employed a distribution-free statistical simulation approach to assess site selection relative to characteristics of used and unused nesting sites. Nest sites selected by Puerto Rican Parrots were characterized by greater horizontal and vertical visibility from the nest entrance, greater density of mature sierra palms, and a more westerly and leeward orientation of nest entrances than unused sites. Our results suggest that nest site selection in this species is an adaptive response to predation pressure, to which the parrots respond by selecting nest sites offering advantages in predator detection and avoidance at all stages of the nesting cycle. We conclude that identifying and replicating the “nest gestalt” of successful nesting sites may facilitate conservation efforts for this and other endangered avian species.

The effectiveness of assessment learning objects produced using pair programming

Pair Programming is a technique from the software development method eXtreme Programming (XP) whereby two programmers work closely together to develop a piece of software. A similar approach has been used to develop a set of Assessment Learning Objects (ALO). Three members of academic staff have developed a set of ALOs for a total of three different modules (two with overlapping content). In each case a pair programming approach was taken to the development of the ALO. In addition to demonstrating the efficiency of this approach in terms of staff time spent developing the ALOs, a statistical analysis of the outcomes for students who made use of the ALOs is used to demonstrate the effectiveness of the ALOs produced via this method.

A Tropospheric Assessment of the ERA-40, NCEP, and JRA-25 Global Reanalyses in the Polar Regions

The reliability of the global reanalyses in the polar regions is investigated. The overview stems from an April 2006 Scientific Committee on Antarctic Research (SCAR) workshop on the performance of global reanalyses in high latitudes held at the British Antarctic Survey. Overall, the skill is much higher in the Arctic than the Antarctic, where the reanalyses are only reliable in the summer months prior to the modern satellite era. In the Antarctic, large circulation differences between the reanalyses are found primarily before 1979, when vast quantities of satellite sounding data started to be assimilated. Specifically for ERA-40, this data discontinuity creates a marked jump in Antarctic snow accumulation, especially at high elevations. In the Arctic, the largest differences are related to the reanalyses depiction of clouds and their associated radiation impacts; ERA-40 captures the cloud variability much better than NCEP1 and JRA-25, but the ERA-40 and JRA-25 clouds are too optically thin for shortwave radiation. To further contrast the reanalyses skill, cyclone tracking results are presented. In the Southern Hemisphere, cyclonic activity is markedly different between the reanalyses, where there are few matched cyclones prior to 1979. In comparison, only some of the weaker cyclones are not matched in the Northern Hemisphere from 1958-2001, again indicating the superior skill in this hemisphere. Although this manuscript focuses on deficiencies in the reanalyses, it is important to note that they are a powerful tool for climate studies in both polar regions when used with a recognition of their limitations.

Stochastic modelling of rainfall from satellite data

Satellite-based rainfall monitoring is widely used for climatological studies because of its full global coverage but it is also of great importance for operational purposes especially in areas such as Africa where there is a lack of ground-based rainfall data. Satellite rainfall estimates have enormous potential benefits as input to hydrological and agricultural models because of their real time availability, low cost and full spatial coverage. One issue that needs to be addressed is the uncertainty on these estimates. This is particularly important in assessing the likely errors on the output from non-linear models (rainfall-runoff or crop yield) which make use of the rainfall estimates, aggregated over an area, as input. Correct assessment of the uncertainty on the rainfall is non-trivial as it must take account of • the difference in spatial support of the satellite information and independent data used for calibration • uncertainties on the independent calibration data • the non-Gaussian distribution of rainfall amount • the spatial intermittency of rainfall • the spatial correlation of the rainfall field This paper describes a method for estimating the uncertainty on satellite-based rainfall values taking account of these factors. The method involves firstly a stochastic calibration which completely describes the probability of rainfall occurrence and the pdf of rainfall amount for a given satellite value, and secondly the generation of ensemble of rainfall fields based on the stochastic calibration but with the correct spatial correlation structure within each ensemble member. This is achieved by the use of geostatistical sequential simulation. The ensemble generated in this way may be used to estimate uncertainty at larger spatial scales. A case study of daily rainfall monitoring in the Gambia, west Africa for the purpose of crop yield forecasting is presented to illustrate the method.

Use of airborne remote sensing to detect riverside Brassica rapa to aid in risk assessment of transgenic crops

High resolution descriptions of plant distribution have utility for many ecological applications but are especially useful for predictive modelling of gene flow from transgenic crops. Difficulty lies in the extrapolation errors that occur when limited ground survey data are scaled up to the landscape or national level. This problem is epitomized by the wide confidence limits generated in a previous attempt to describe the national abundance of riverside Brassica rapa (a wild relative of cultivated rapeseed) across the United Kingdom. Here, we assess the value of airborne remote sensing to locate B. rapa over large areas and so reduce the need for extrapolation. We describe results from flights over the river Nene in England acquired using Airborne Thematic Mapper (ATM) and Compact Airborne Spectrographic Imager (CASI) imagery, together with ground truth data. It proved possible to detect 97% of flowering B. rapa on the basis of spectral profiles. This included all stands of plants that occupied >2m square (>5 plants), which were detected using single-pixel classification. It also included very small populations (<5 flowering plants, 1-2m square) that generated mixed pixels, which were detected using spectral unmixing. The high detection accuracy for flowering B. rapa was coupled with a rather large false positive rate (43%). The latter could be reduced by using the image detections to target fieldwork to confirm species identity, or by acquiring additional remote sensing data such as laser altimetry or multitemporal imagery.