An experimental investigation of air flow and convective heat transfer in enclosures having large ventilative flow rates

The prediction of convective heat transfer in enclosures under high ventilative flow rates is primarily of interest for building design and simulation purposes. Current models are based on experiments performed forty years ago with flat plates under natural convection conditions.

Associação de sistema biológico do tipo lodo ativado com reatores air lift e fotocatálise heterogênea com TiO2 para a remediação de efluente oriundo da produção industrial de TNT

Trinitrotoluene in the purification step (TNT) produced in industries, are carried out two washes at the end of the process. The first wash is done with vaporized water, which originates from the first effluent called yellow water, then the second washing with the use of sodium sulfite is performed (Na2SO3), generating a second effluent red water. This study aimed to study the individual effects, as well as the association of heterogeneous photocatalysis using TiO2 and biological treatment in air lift reactor using activated sludge (bacterial biomass) for the remediation of wastewater contaminated with nitroaromatic compounds in order to reduce toxicity and adjust the legal parameters according to regulatory agencies for disposal in waterways. The photocatalytic treatment was conducted by factorial design obtaining the best reaction conditions (pH 6.5 and concentration of TiO2 0.1 gL-1), with best results obtained at 360 minutes of reaction, reducing the absorbance 97.00%, 94.20% of the chemical oxygen demand (COD), 67.70% of total phenols, as well as a total reduction of observed peaks and assigned to nitroaromatic compounds by high-performance liquid chromatography. In the biological treatment, there was a 53.40% reduction in absorbance at 275 nm 10.00% 36.00% COD and total phenols in a short time (3 days), while for extended periods (48 days) there was an antagonistic influence on the results so that was the elevation of these parameters (COD and total phenols) instead of reducing. Chromatographic analysis confirmed the effectiveness of the biological degradation by reducing the peaks corresponding to compounds DNT and TNT. The Association of photocatalytic and biological treatments decreased results in the order of 91.10% absorbance, 70.26% of total phenols and 88.87% of COD. While the combination of biological and photocatalytic treatments generated relatively lower efficiencies, with 77.30% of absorbance reduction, 62.10% reduction of total phenols and a decrease of 87.00% of COD. In general, when comparing the chemical and biological processes in isolation, the photocatalytic treatment showed the best results. However, comparing the results of isolation and established associations, the association biological x photocatalysis showed more promising results in the treatment of red water effluent.

Evaluation Of An Extended Duct Air Delivery System For Spaces Conditioned By Rooftop Units

Traditional air delivery to high-bay buildings involves ceiling level supply and return ducts that create an almost-uniform temperature in the space. Problems with this system include potential recirculation of supply air and higher-than-necessary return air temperatures. A new air delivery strategy was investigated that involves changing the height of conventional supply and return ducts to have control over thermal stratification in the space. A full-scale experiment using ten vertical temperature profiles was conducted in a manufacturing facility over one year. The experimental data was utilized to validated CFD and EnergyPlus models. CFD simulation results show that supplying air directly to the occupied zone increases stratification while holding thermal comfort constant during the cooling operation. The building energy simulation identified how return air temperature offset, set point offset, and stratification influence the building’s energy consumption. A utility bill analysis for cooling shows 28.8% HVAC energy savings while the building energy simulation shows 19.3 – 37.4% HVAC energy savings.

A cost-efficiency and health benefit approach to improve urban air quality

When ambient air quality standards established in the EU Directive 2008/50/EC are exceeded, Member States are obliged to develop and implement Air Quality Plans (AQP) to improve air quality and health. Notwithstanding the achievements in emission reductions and air quality improvement, additional efforts need to be undertaken to improve air quality in a sustainable way - i.e. through a cost-efficiency approach. This work was developed in the scope of the recently concluded MAPLIA project "Moving from Air Pollution to Local Integrated Assessment", and focuses on the definition and assessment of emission abatement measures and their associated costs, air quality and health impacts and benefits by means of air quality modelling tools, health impact functions and cost-efficiency analysis. The MAPLIA system was applied to the Grande Porto urban area (Portugal), addressing PM10 and NOx as the most important pollutants in the region. Four different measures to reduce PM10 and NOx emissions were defined and characterized in terms of emissions and implementation costs, and combined into 15 emission scenarios, simulated by the TAPM air quality modelling tool. Air pollutant concentration fields were then used to estimate health benefits in terms of avoided costs (external costs), using dose-response health impact functions. Results revealed that, among the 15 scenarios analysed, the scenario including all 4 measures lead to a total net benefit of 0.3M€·y(-1). The largest net benefit is obtained for the scenario considering the conversion of 50% of open fire places into heat recovery wood stoves. Although the implementation costs of this measure are high, the benefits outweigh the costs. Research outcomes confirm that the MAPLIA system is useful for policy decision support on air quality improvement strategies, and could be applied to other urban areas where AQP need to be implemented and monitored.

Air-coupled ultrasonic tomographic imaging of concrete elements

Ultrasonic tomography is a powerful tool for identifying defects within an object or structure. This method can be applied on structures where x-ray tomography is impractical due to size, low contrast, or safety concerns. By taking many ultrasonic pulse velocity (UPV) readings through the object, an image of the internal velocity variations can be constructed. Air-coupled UPV can allow for more automated and rapid collection of data for tomography of concrete. This research aims to integrate recent developments in air-coupled ultrasonic measurements with advanced tomography technology and apply them to concrete structures. First, non-contact and semi-contact sensor systems are developed for making rapid and accurate UPV measurements through PVC and concrete test samples. A customized tomographic reconstruction program is developed to provide full control over the imaging process including full and reduced spectrum tomographs with percent error and ray density calculations. Finite element models are also used to determine optimal measurement configurations and analysis procedures for efficient data collection and processing. Non-contact UPV is then implemented to image various inclusions within 6 inch (152 mm) PVC and concrete cylinders. Although there is some difficulty in identifying high velocity inclusions, reconstruction error values were in the range of 1.1-1.7% for PVC and 3.6% for concrete. Based upon the success of those tests, further data are collected using non-contact, semi-contact, and full contact measurements to image 12 inch (305 mm) square concrete cross-sections with 1 inch (25 mm) reinforcing bars and 2 inch (51 mm) square embedded damage regions. Due to higher noise levels in collected signals, tomographs of these larger specimens show reconstruction error values in the range of 10-18%. Finally, issues related to the application of these techniques to full-scale concrete structures are discussed.

Rapid continuous chemical analysis of meat chicken shed emissions by SIFT–MS

Assessing and addressing odour impacts from poultry production is extremely difficult and subjective because the odorants involved and their dynamics over time and space are poorly understood. This knowledge gap is due, in part, to the lack of suitable analytical tools for measuring and monitoring odorants in the field. The emergence of Selected Ion Flow Tube – Mass Spectrometry (SIFT–MS) and similar instruments is changing that. These tools can rapidly quantify targeted odorants in ambient air in real time, even at very low concentrations. Such data is essential for developing better odour abatement strategies, assessment methods and odour dispersion models. This project trialled a SIFT–MS to determine its suitability for assessing the odorants in meat chicken shed emissions over time and space. This report details evaluations in New Zealand and Australia to determine the potential of SIFT–MS as a tool for the chicken meat industry, including odour measurement (as a proxy for dynamic olfactometry). The report is specifically targeted at those funding and conducting poultry odour research. It will be of interest to those involved with environmental odour monitoring and assessment in general. The high upfront cost of SIFT–MS will lead to potential users wanting compelling evidence that SIFT–MS will meet their needs before they invest in one.

Quantification of air quality in space and time and its effects on health

The long-term adverse effects on health associated with air pollution exposure can be estimated using either cohort or spatio-temporal ecological designs. In a cohort study, the health status of a cohort of people are assessed periodically over a number of years, and then related to estimated ambient pollution concentrations in the cities in which they live. However, such cohort studies are expensive and time consuming to implement, due to the long-term follow up required for the cohort. Therefore, spatio-temporal ecological studies are also being used to estimate the long-term health effects of air pollution as they are easy to implement due to the routine availability of the required data. Spatio-temporal ecological studies estimate the health impact of air pollution by utilising geographical and temporal contrasts in air pollution and disease risk across $n$ contiguous small-areas, such as census tracts or electoral wards, for multiple time periods. The disease data are counts of the numbers of disease cases occurring in each areal unit and time period, and thus Poisson log-linear models are typically used for the analysis. The linear predictor includes pollutant concentrations and known confounders such as socio-economic deprivation. However, as the disease data typically contain residual spatial or spatio-temporal autocorrelation after the covariate effects have been accounted for, these known covariates are augmented by a set of random effects. One key problem in these studies is estimating spatially representative pollution concentrations in each areal which are typically estimated by applying Kriging to data from a sparse monitoring network, or by computing averages over modelled concentrations (grid level) from an atmospheric dispersion model. The aim of this thesis is to investigate the health effects of long-term exposure to Nitrogen Dioxide (NO2) and Particular matter (PM10) in mainland Scotland, UK. In order to have an initial impression about the air pollution health effects in mainland Scotland, chapter 3 presents a standard epidemiological study using a benchmark method. The remaining main chapters (4, 5, 6) cover the main methodological focus in this thesis which has been threefold: (i) how to better estimate pollution by developing a multivariate spatio-temporal fusion model that relates monitored and modelled pollution data over space, time and pollutant; (ii) how to simultaneously estimate the joint effects of multiple pollutants; and (iii) how to allow for the uncertainty in the estimated pollution concentrations when estimating their health effects. Specifically, chapters 4 and 5 are developed to achieve (i), while chapter 6 focuses on (ii) and (iii). In chapter 4, I propose an integrated model for estimating the long-term health effects of NO2, that fuses modelled and measured pollution data to provide improved predictions of areal level pollution concentrations and hence health effects. The air pollution fusion model proposed is a Bayesian space-time linear regression model for relating the measured concentrations to the modelled concentrations for a single pollutant, whilst allowing for additional covariate information such as site type (e.g. roadside, rural, etc) and temperature. However, it is known that some pollutants might be correlated because they may be generated by common processes or be driven by similar factors such as meteorology. The correlation between pollutants can help to predict one pollutant by borrowing strength from the others. Therefore, in chapter 5, I propose a multi-pollutant model which is a multivariate spatio-temporal fusion model that extends the single pollutant model in chapter 4, which relates monitored and modelled pollution data over space, time and pollutant to predict pollution across mainland Scotland. Considering that we are exposed to multiple pollutants simultaneously because the air we breathe contains a complex mixture of particle and gas phase pollutants, the health effects of exposure to multiple pollutants have been investigated in chapter 6. Therefore, this is a natural extension to the single pollutant health effects in chapter 4. Given NO2 and PM10 are highly correlated (multicollinearity issue) in my data, I first propose a temporally-varying linear model to regress one pollutant (e.g. NO2) against another (e.g. PM10) and then use the residuals in the disease model as well as PM10, thus investigating the health effects of exposure to both pollutants simultaneously. Another issue considered in chapter 6 is to allow for the uncertainty in the estimated pollution concentrations when estimating their health effects. There are in total four approaches being developed to adjust the exposure uncertainty. Finally, chapter 7 summarises the work contained within this thesis and discusses the implications for future research.

Thermal and exergy analysis for evaluation and optimization of performance of cooling towers for fresh water and seawater

In this study, thermal, exergetic analysis and performance evaluation of seawater and fresh wet cooling tower and the effect of parameters on its performance is investigated. With using of energy and mass balance equations, experimental results, a mathematical model and EES code developed. Due to lack of fresh water, seawater cooling is interesting choice for future of cooling, so the effect of seawater in the range of 1gr/kg to 60gr/kg for salinity on the performance characteristics like air efficiency, water efficiency, output water temperature of cooling tower, flow of the exergy, and the exergy efficiency with comparison with fresh water examined. Decreasing of air efficiency about 3%, increasing of water efficiency about 1.5% are some of these effects. Moreover with formation of fouling the performance of cooling tower decreased about 15% which this phenomena and its effects like increase in output water temperature and tower excess volume has been showed and also accommodate with others work. Also optimization for minimizing cost, maximizing air efficiency, and minimizing exergy destruction has been done, results showed that optimization on minimizing the exergy destruction has been satisfy both minimization of the cost and the maximization of the air efficiency, although it will not necessarily permanent for all inputs and optimizations. Validation of this work is done by comparing computational results and experimental data which showed that the model have a good accuracy.

PCR-Internal Transcribed Spacer (ITS) genes sequencing and phylogenetic analysis of clinical and environmental Aspergillus species associated with HIV-TB co infected patients in a hospital in Abeokuta, southwestern Nigeria.

Background: Aspergillosis has been identified as one of the hospital acquired infections but the contribution of water and inhouse air as possible sources of Aspergillus infection in immunocompromised individuals like HIV-TB patients have not been studied in any hospital setting in Nigeria. Objective: To identify and investigate genetic relationship between clinical and environmental Aspergillus species associated with HIV-TB co infected patients. Methods: DNA extraction, purification, amplification and sequencing of Internal Transcribed Spacer (ITS) genes were performed using standard protocols. Similarity search using BLAST on NCBI was used for species identification and MEGA 5.0 was used for phylogenetic analysis. Results: Analyses of sequenced ITS genes of selected fourteen (14) Aspergillus isolates identified in the GenBank database revealed Aspergillus niger (28.57%), Aspergillus tubingensis (7.14%), Aspergillus flavus (7.14%) and Aspergillus fumigatus (57.14%). Aspergillus in sputum of HIV patients were Aspergillus niger, A. fumigatus, A. tubingensis and A. flavus. Also, A. niger and A. fumigatus were identified from water and open-air. Phylogenetic analysis of sequences yielded genetic relatedness between clinical and environmental isolates. Conclusion: Water and air in health care settings in Nigeria are important sources of Aspergillus sp. for HIV-TB patients.

Statistical Analysis of Sea Surface Temperature and Chlorophyll-a Concentration Patterns in the Gulf of Tadjourah (Djibouti)

The sea surface temperature (SST) and chlorophyll-a concentration (CHL-a) were analysed in the Gulf of Tadjourah from two set of 8-day composite satellite data, respectively from 2008 to 2012 and from 2005 to 2011. A singular spectrum analysis (SSA) shows that the annual cycle of SST is strong (74.3% of variance) and consists of warming (April-October) and cooling (November-March) of about 2.5C than the long-term average. The semi-annual cycle captures only 14.6% of temperature variance and emphasises the drop of SST during July-August. Similarly, the annual cycle of CHL-a (29.7% of variance) depicts high CHL-a from June to October and low concentration from November to May. In addition, the first spatial empirical orthogonal function (EOF) of SST (93% of variance) shows that the seasonal warming/cooling is in phase across the whole study area but the southeastern part always remaining warmer or cooler. In contrast to the SST, the first EOF of CHL-a (54.1% of variance) indicates the continental shelf in phase opposition with the offshore area in winter during which the CHL-a remains sequestrated in the coastal area particularly in the south-east and in the Ghoubet Al-Kharab Bay. Inversely during summer, higher CHL-a quantities appear in the offshore waters. In order to investigate processes generating these patterns, a multichannel spectrum analysis was applied to a set of oceanic (SST, CHL-a) and atmospheric parameters (wind speed, air temperature and air specific humidity). This analysis shows that the SST is well correlated to the atmospheric parameters at an annual scale. The windowed cross correlation indicates that this correlation is significant only from October to May. During this period, the warming was related to the solar heating of the surface water when the wind is low (April-May and October) while the cooling (November-March) was linked to the strong and cold North-East winds and to convective mixing. The summer drop in SST followed by a peak of CHL-a, seems strongly correlated to the upwelling. The second EOF modes of SST and CHL-a explain respectively 1.3% and 5% of the variance and show an east-west gradient during winter that is reversed during summer. This work showed that the seasonal signals have a wide spatial influence and dominate the variability of the SST and CHL-a while the east-west gradient are specific for the Gulf of Tadjourah and seem induced by the local wind modulated by the topography.

Wind turbine indirect ice detection and operational analysis

Wind energy is one of the most promising and fast growing sector of energy production. Wind is ecologically friendly and relatively cheap energy resource available for development in practically all corners of the world (where only the wind blows). Today wind power gained broad development in the Scandinavian countries. Three important challenges concerning sustainable development, i.e. energy security, climate change and energy access make a compelling case for large-scale utilization of wind energy. In Finland, according to the climate and energy strategy, accepted in 2008, the total consumption of electricity generated by means of wind farms by 2020, should reach 6 - 7% of total consumption in the country [1]. The main challenges associated with wind energy production are harsh operational conditions that often accompany the turbine operation in the climatic conditions of the north and poor accessibility for maintenance and service. One of the major problems that require a solution is the icing of turbine structures. Icing reduces the performance of wind turbines, which in the conditions of a long cold period, can significantly affect the reliability of power supply. In order to predict and control power performance, the process of ice accretion has to be carefully tracked. There are two ways to detect icing – directly or indirectly. The first way applies to the special ice detection instruments. The second one is using indirect characteristics of turbine performance. One of such indirect methods for ice detection and power loss estimation has been proposed and used in this paper. The results were compared to the results directly gained from the ice sensors. The data used was measured in Muukko wind farm, southeast Finland during a project 'Wind power in cold climate and complex terrain'. The project was carried out in 9/2013 - 8/2015 with the partners Lappeenranta university of technology, Alstom renovables España S.L., TuuliMuukko, and TuuliSaimaa.

Measurement of the depth of maximum of extensive air showers above 10(18) eV

We describe the measurement of the depth of maximum, X-max, of the longitudinal development of air showers induced by cosmic rays. Almost 4000 events above 10(18) eV observed by the fluorescence detector of the Pierre Auger Observatory in coincidence with at least one surface detector station are selected for the analysis. The average shower maximum was found to evolve with energy at a rate of (106 +/- 35-21) g/cm(2)/decade below 10(18.24) +/- (0.05) eV, and d24 +/- 3 g/cm(2)/ecade above this energy. The measured shower-to-shower fluctuations decrease from about 55 to 26 g/cm(2). The interpretation of these results in terms of the cosmic ray mass composition is briefly discussed.

GC-MS Analysis, Antimicrobial and Antioxidant Activities of Extracts of the Aerial Parts of Conyza sumatrensis

Phytochemical analyses as well as antimicrobial and antioxidant activities of the extracts of C. sumatrensis aerial parts were investigated in this study. METHODS: The aerial parts of C. sumatrensis were air dried, weighed and exhaustively extracted with hexane, ethyl acetate and methanol successively. The crude extracts were screened for metabolites. These extracts of the plant were evaluated for antimicrobial and antioxidant activities using agar diffusion and DPPH method respectively. The extracts were also analysed using Gas chromatography – Mass spectrometry, and the chromatogram coupled with mass spectra of the compounds were matched with a standard library. RESULTS: Preliminary phytochemical investigation of crude n-hexane, ethyl acetate and methanol extracts of the aerial parts of Conyza sumatrensis revealed the presence of anthraquinones, flavonoids, terpenoids, phenolics, tannin, glycosides and carbohydrate. All the crude extracts gave a clear zone of inhibition against the growth of the test bacteria ( Staphylococcus aureus , Escherichia coli , Bacillus subtilis , Pseudomona aeruginosa, Salmonella typhi , Klebsiellae pneumonae ) at moderate to high concentrations, as well as test fungi ( Candida albicans , Aspergillus niger , penicillium notatum and Rhizopus stolonifer ) at high concentration. Methanolic extract exhibited significant radical scavenging property with IC50 of 17.08 μg/mL while n-hexane and ethyl acetate extracts showed no significant antioxidant activity. GC-MS of N-hexane extract showed a total number of eleven chemical constituents with α-Farnesene and spathulenol being the most abundance compounds constituting 20.27 and 22.28% of the extract respectively. Ethyl acetate extract revealed thirteen compounds with two most abundant compounds, cis-β-farnesene (16.64 %) and cis-pinane (21.09 %). While methanolic extract affords seventeen compounds with Ephytol being the most abundant compound (19.36 %).