Oxygen extended sooting index of FAME blends with aviation kerosene

The use of biofuels in the aviation sector has economic and environmental benefits. Among the options for the production of renewable jet fuels, hydroprocessed esters and fatty acids (HEFA) have received predominant attention in comparison with fatty acid methyl esters (FAME), which are not approved as additives for jet fuels. However, the presence of oxygen in methyl esters tends to reduce soot emissions and therefore particulate matter emissions. This sooting tendency is quantified in this work with an oxygen-extended sooting index, based on smoke point measurements. Results have shown considerable reduction in the sooting tendency for all biokerosenes (produced by transesterification and eventually distillation) with respect to fossil kerosenes. Among the tested biokerosenes, that made from palm kernel oil was the most effective one, and nondistilled methyl esters (from camelina and linseed oils) showed lower effectiveness than distilled biokerosenes to reduce the sooting tendency. These results may constitute an additional argument for the use of FAME’s as blend components of jet fuels. Other arguments were pointed out in previous publications, but some controversy has aroused over the use of these components. Some of the criticism was based on the fact that the methods used in our previous work are not approved for jet fuels in the standard methods and concluded that the use of FAME in any amount is, thus, inappropriate. However, some of the standard methods are not updated for considering oxygenated components (like the method for obtaining the lower heating value), and others are not precise enough (like the methods for measuring the freezing point), whereas some alternative methods may provide better reproducibility for oxygenated fuels.

Discriminating Crop, Weeds and Soil Surface with a Terrestrial LIDAR Sensor

In this study, the evaluation of the accuracy and performance of a light detection and ranging (LIDAR) sensor for vegetation using distance and reflection measurements aiming to detect and discriminate maize plants and weeds from soil surface was done. The study continues a previous work carried out in a maize field in Spain with a LIDAR sensor using exclusively one index, the height profile. The current system uses a combination of the two mentioned indexes. The experiment was carried out in a maize field at growth stage 12–14, at 16 different locations selected to represent the widest possible density of three weeds: Echinochloa crus-galli (L.) P.Beauv., Lamium purpureum L., Galium aparine L.and Veronica persica Poir.. A terrestrial LIDAR sensor was mounted on a tripod pointing to the inter-row area, with its horizontal axis and the field of view pointing vertically downwards to the ground, scanning a vertical plane with the potential presence of vegetation. Immediately after the LIDAR data acquisition (distances and reflection measurements), actual heights of plants were estimated using an appropriate methodology. For that purpose, digital images were taken of each sampled area. Data showed a high correlation between LIDAR measured height and actual plant heights (R 2 = 0.75). Binary logistic regression between weed presence/absence and the sensor readings (LIDAR height and reflection values) was used to validate the accuracy of the sensor. This permitted the discrimination of vegetation from the ground with an accuracy of up to 95%. In addition, a Canonical Discrimination Analysis (CDA) was able to discriminate mostly between soil and vegetation and, to a far lesser extent, between crop and weeds. The studied methodology arises as a good system for weed detection, which in combination with other principles, such as vision-based technologies, could improve the efficiency and accuracy of herbicide spraying.

Evaluation of reactivity monitoring techniques at the Yalina – Booster subcritical facility

La gestión de los residuos radiactivos de vida larga producidos en los reactores nucleares constituye uno de los principales desafíos de la tecnología nuclear en la actualidad. Una posible opción para su gestión es la transmutación de los nucleidos de vida larga en otros de vida más corta. Los sistemas subcríticos guiados por acelerador (ADS por sus siglas en inglés) son una de las tecnologías en desarrollo para logar este objetivo. Un ADS consiste en un reactor nuclear subcrítico mantenido en un estado estacionario mediante una fuente externa de neutrones guiada por un acelerador de partículas. El interés de estos sistemas radica en su capacidad para ser cargados con combustibles que tengan contenidos de actínidos minoritarios mayores que los reactores críticos convencionales, y de esta manera, incrementar las tasas de trasmutación de estos elementos, que son los principales responsables de la radiotoxicidad a largo plazo de los residuos nucleares. Uno de los puntos clave que han sido identificados para la operación de un ADS a escala industrial es la necesidad de monitorizar continuamente la reactividad del sistema subcrítico durante la operación. Por esta razón, desde los años 1990 se han realizado varios experimentos en conjuntos subcríticos de potencia cero (MUSE, RACE, KUCA, Yalina, GUINEVERE/FREYA) con el fin de validar experimentalmente estas técnicas. En este contexto, la presente tesis se ocupa de la validación de técnicas de monitorización de la reactividad en el conjunto subcrítico Yalina-Booster. Este conjunto pertenece al Joint Institute for Power and Nuclear Research (JIPNR-Sosny) de la Academia Nacional de Ciencias de Bielorrusia. Dentro del proyecto EUROTRANS del 6º Programa Marco de la UE, en el año 2008 se ha realizado una serie de experimentos en esta instalación concernientes a la monitorización de la reactividad bajo la dirección del CIEMAT. Se han realizado dos tipos de experimentos: experimentos con una fuente de neutrones pulsada (PNS) y experimentos con una fuente continua con interrupciones cortas (beam trips). En el caso de los primeros, experimentos con fuente pulsada, existen dos técnicas fundamentales para medir la reactividad, conocidas como la técnica del ratio bajo las áreas de los neutrones inmediatos y retardados (o técnica de Sjöstrand) y la técnica de la constante de decaimiento de los neutrones inmediatos. Sin embargo, varios experimentos han mostrado la necesidad de aplicar técnicas de corrección para tener en cuenta los efectos espaciales y energéticos presentes en un sistema real y obtener valores precisos de la reactividad. En esta tesis, se han investigado estas correcciones mediante simulaciones del sistema con el código de Montecarlo MCNPX. Esta investigación ha servido también para proponer una versión generalizada de estas técnicas donde se buscan relaciones entre la reactividad el sistema y las cantidades medidas a través de simulaciones de Monte Carlo. El segundo tipo de experimentos, experimentos con una fuente continua e interrupciones del haz, es más probable que sea empleado en un ADS industrial. La versión generalizada de las técnicas desarrolladas para los experimentos con fuente pulsada también ha sido aplicada a los resultados de estos experimentos. Además, el trabajo presentado en esta tesis es la primera vez, en mi conocimiento, en que la reactividad de un sistema subcrítico se monitoriza durante la operación con tres técnicas simultáneas: la técnica de la relación entre la corriente y el flujo (current-to-flux), la técnica de desconexión rápida de la fuente (source-jerk) y la técnica del decaimiento de los neutrones inmediatos. Los casos analizados incluyen la variación rápida de la reactividad del sistema (inserción y extracción de las barras de control) y la variación rápida de la fuente de neutrones (interrupción larga del haz y posterior recuperación). ABSTRACT The management of long-lived radioactive wastes produced by nuclear reactors constitutes one of the main challenges of nuclear technology nowadays. A possible option for its management consists in the transmutation of long lived nuclides into shorter lived ones. Accelerator Driven Subcritical Systems (ADS) are one of the technologies in development to achieve this goal. An ADS consists in a subcritical nuclear reactor maintained in a steady state by an external neutron source driven by a particle accelerator. The interest of these systems lays on its capacity to be loaded with fuels having larger contents of minor actinides than conventional critical reactors, and in this way, increasing the transmutation rates of these elements, that are the main responsible of the long-term radiotoxicity of nuclear waste. One of the key points that have been identified for the operation of an industrial-scale ADS is the need of continuously monitoring the reactivity of the subcritical system during operation. For this reason, since the 1990s a number of experiments have been conducted in zero-power subcritical assemblies (MUSE, RACE, KUCA, Yalina, GUINEVERE/FREYA) in order to experimentally validate these techniques. In this context, the present thesis is concerned with the validation of reactivity monitoring techniques at the Yalina-Booster subcritical assembly. This assembly belongs to the Joint Institute for Power and Nuclear Research (JIPNR-Sosny) of the National Academy of Sciences of Belarus. Experiments concerning reactivity monitoring have been performed in this facility under the EUROTRANS project of the 6th EU Framework Program in year 2008 under the direction of CIEMAT. Two types of experiments have been carried out: experiments with a pulsed neutron source (PNS) and experiments with a continuous source with short interruptions (beam trips). For the case of the first ones, PNS experiments, two fundamental techniques exist to measure the reactivity, known as the prompt-to-delayed neutron area-ratio technique (or Sjöstrand technique) and the prompt neutron decay constant technique. However, previous experiments have shown the need to apply correction techniques to take into account the spatial and energy effects present in a real system and thus obtain accurate values for the reactivity. In this thesis, these corrections have been investigated through simulations of the system with the Monte Carlo code MCNPX. This research has also served to propose a generalized version of these techniques where relationships between the reactivity of the system and the measured quantities are obtained through Monte Carlo simulations. The second type of experiments, with a continuous source with beam trips, is more likely to be employed in an industrial ADS. The generalized version of the techniques developed for the PNS experiments has also been applied to the result of these experiments. Furthermore, the work presented in this thesis is the first time, to my knowledge, that the reactivity of a subcritical system has been monitored during operation simultaneously with three different techniques: the current-to-flux, the source-jerk and the prompt neutron decay techniques. The cases analyzed include the fast variation of the system reactivity (insertion and extraction of a control rod) and the fast variation of the neutron source (long beam interruption and subsequent recovery).

Near-shore wave power characterized with a remotely controlled surface vehicle in Admiralty Inlet, Puget Sound, WA

Senior thesis written for Oceanography 445

Non-invasive respiratory monitoring using long-period fiber grating sensors

In non-invasive ventilation, continuous monitoring of respiratory volumes is essential. Here, we present a method for the measurement of respiratory volumes by a single fiber-grating sensor of bending and provide the proof-of-principle by applying a calibration-test measurement procedure on a set of 18 healthy volunteers. Results establish a linear correlation between a change in lung volume and the corresponding change in a local thorax curvature. They also show good sensor accuracy in measurements of tidal and minute respiratory volumes for different types of breathing. The proposed technique does not rely on the air flow through an oronasal mask or the observation of chest movement by a clinician, which distinguishes it from the current clinical practice. © 2014 Optical Society of America.

Interferometric and fibre Bragg grating sensor interrogation using an arrayed waveguide grating

We investigate the use of an arrayed waveguide grating (AWG) to interrogate both fibre Bragg grating (FBG) and interferometric sensors. A broadband light source is used to illuminate both the FBG and interferometric sensors. Reflected spectral information is directed to an AWG with integral photodetectors providing 40 electrical outputs. To interrogate interferometric sensors we investigated the dual wavelength technique to measure the distance of a Fabry-Perot cavity, which produced a maximum unambiguous range of 1440μm with an active sensor. Three methods are described to interrogate FBG sensors. The first technique makes use of the reflected light intensity in an AWG channel passband from a narrow bandwidth grating, giving a usable range of 500με and a dynamic strain resolution of 96nε/√Hz at 30Hz. The second approach utilises wide gratings larger than the channel spacing of the AWG; by monitoring the intensity present in corresponding AWG channels an improved range of 1890με was achieved. The third method improves the dynamic range by utilising a heterodyne approach based on interferometric wavelength shift detection providing a dynamic strain resolution of 17nε/√Hz at 30Hz.

The effects of self-monitoring on homework completion and accuracy rates of students with disabilities in an inclusive general education classroom

This study investigated the effects of self-monitoring on the homework completion and accuracy rates of four, fourth-grade students with disabilities in an inclusive general education classroom. A multiple baseline across subjects design was utilized to examine four dependent variables: completion of spelling homework, accuracy of spelling homework, completion of math homework, accuracy of math homework. Data were collected and analyzed during baseline, three phases of intervention, and maintenance. ^ Throughout baseline and all phases, participants followed typical classroom procedures, brought their homework to school each day and gave it to the general education teacher. During Phase I of the intervention, participants self-monitored with a daily sheet at home and on the computer at school in the morning using KidTools (Fitzgerald & Koury, 2003); a student friendly, self-monitoring program. They also participated in brief daily conferences to review their self-monitoring sheets with the investigator, their special education teacher. Phase II followed the same steps except conferencing was reduced to two days a week, which were randomly selected by the researcher and Phase III conferencing was one random day a week. Maintenance data were taken over a two-to-three week period subsequent to the end of the intervention. ^ Results of this study demonstrated self-monitoring substantially improved spelling and math homework completion and accuracy rates of students with disabilities in an inclusive, general education classroom. On average, completion and accuracy rates were highest over baseline in Phase III. Self-monitoring led to higher percentages of completion and accuracy during each phase of the intervention compared to baseline, group percentages also rose slightly during maintenance. Therefore, results suggest self-monitoring leads to short-term maintenance in spelling and math homework completion and accuracy. ^ This study adds to the existing literature by investigating the effects of self-monitoring of homework for students with disabilities included in general education classrooms. Future research should consider selecting participants with other demographic characteristics, using peers for conferencing instead of the teacher, and the use of self-monitoring with other academic subjects (e.g., science, history). Additionally, future research could investigate the effects of each of the two self-monitoring components used alone, with or without the conferencing.^

System-on-a-Chip (SOC) based environmental monitoring platform for the detection of hazardous materials

The purpose of this research is design considerations for environmental monitoring platforms for the detection of hazardous materials using System-on-a-Chip (SoC) design. Design considerations focus on improving key areas such as: (1) sampling methodology; (2) context awareness; and (3) sensor placement. These design considerations for environmental monitoring platforms using wireless sensor networks (WSN) is applied to the detection of methylmercury (MeHg) and environmental parameters affecting its formation (methylation) and deformation (demethylation). ^ The sampling methodology investigates a proof-of-concept for the monitoring of MeHg using three primary components: (1) chemical derivatization; (2) preconcentration using the purge-and-trap (P&T) method; and (3) sensing using Quartz Crystal Microbalance (QCM) sensors. This study focuses on the measurement of inorganic mercury (Hg) (e.g., Hg2+) and applies lessons learned to organic Hg (e.g., MeHg) detection. ^ Context awareness of a WSN and sampling strategies is enhanced by using spatial analysis techniques, namely geostatistical analysis (i.e., classical variography and ordinary point kriging), to help predict the phenomena of interest in unmonitored locations (i.e., locations without sensors). This aids in making more informed decisions on control of the WSN (e.g., communications strategy, power management, resource allocation, sampling rate and strategy, etc.). This methodology improves the precision of controllability by adding potentially significant information of unmonitored locations.^ There are two types of sensors that are investigated in this study for near-optimal placement in a WSN: (1) environmental (e.g., humidity, moisture, temperature, etc.) and (2) visual (e.g., camera) sensors. The near-optimal placement of environmental sensors is found utilizing a strategy which minimizes the variance of spatial analysis based on randomly chosen points representing the sensor locations. Spatial analysis is employed using geostatistical analysis and optimization occurs with Monte Carlo analysis. Visual sensor placement is accomplished for omnidirectional cameras operating in a WSN using an optimal placement metric (OPM) which is calculated for each grid point based on line-of-site (LOS) in a defined number of directions where known obstacles are taken into consideration. Optimal areas of camera placement are determined based on areas generating the largest OPMs. Statistical analysis is examined by using Monte Carlo analysis with varying number of obstacles and cameras in a defined space. ^

Energy-efficient self -organization of wireless acoustic sensor networks for ground target tracking

With the developments in computing and communication technologies, wireless sensor networks have become popular in wide range of application areas such as health, military, environment and habitant monitoring. Moreover, wireless acoustic sensor networks have been widely used for target tracking applications due to their passive nature, reliability and low cost. Traditionally, acoustic sensor arrays built in linear, circular or other regular shapes are used for tracking acoustic sources. The maintaining of relative geometry of the acoustic sensors in the array is vital for accurate target tracking, which greatly reduces the flexibility of the sensor network. To overcome this limitation, we propose using only a single acoustic sensor at each sensor node. This design greatly improves the flexibility of the sensor network and makes it possible to deploy the sensor network in remote or hostile regions through air-drop or other stealth approaches. Acoustic arrays are capable of performing the target localization or generating the bearing estimations on their own. However, with only a single acoustic sensor, the sensor nodes will not be able to generate such measurements. Thus, self-organization of sensor nodes into virtual arrays to perform the target localization is essential. We developed an energy-efficient and distributed self-organization algorithm for target tracking using wireless acoustic sensor networks. The major error sources of the localization process were studied, and an energy-aware node selection criterion was developed to minimize the target localization errors. Using this node selection criterion, the self-organization algorithm selects a near-optimal localization sensor group to minimize the target tracking errors. In addition, a message passing protocol was developed to implement the self-organization algorithm in a distributed manner. In order to achieve extended sensor network lifetime, energy conservation was incorporated into the self-organization algorithm by incorporating a sleep-wakeup management mechanism with a novel cross layer adaptive wakeup probability adjustment scheme. The simulation results confirm that the developed self-organization algorithm provides satisfactory target tracking performance. Moreover, the energy saving analysis confirms the effectiveness of the cross layer power management scheme in achieving extended sensor network lifetime without degrading the target tracking performance.

Energy-Efficient Self-Organization of Wireless Acoustic Sensor Networks for Ground Target Tracking

With the developments in computing and communication technologies, wireless sensor networks have become popular in wide range of application areas such as health, military, environment and habitant monitoring. Moreover, wireless acoustic sensor networks have been widely used for target tracking applications due to their passive nature, reliability and low cost. Traditionally, acoustic sensor arrays built in linear, circular or other regular shapes are used for tracking acoustic sources. The maintaining of relative geometry of the acoustic sensors in the array is vital for accurate target tracking, which greatly reduces the flexibility of the sensor network. To overcome this limitation, we propose using only a single acoustic sensor at each sensor node. This design greatly improves the flexibility of the sensor network and makes it possible to deploy the sensor network in remote or hostile regions through air-drop or other stealth approaches. Acoustic arrays are capable of performing the target localization or generating the bearing estimations on their own. However, with only a single acoustic sensor, the sensor nodes will not be able to generate such measurements. Thus, self-organization of sensor nodes into virtual arrays to perform the target localization is essential. We developed an energy-efficient and distributed self-organization algorithm for target tracking using wireless acoustic sensor networks. The major error sources of the localization process were studied, and an energy-aware node selection criterion was developed to minimize the target localization errors. Using this node selection criterion, the self-organization algorithm selects a near-optimal localization sensor group to minimize the target tracking errors. In addition, a message passing protocol was developed to implement the self-organization algorithm in a distributed manner. In order to achieve extended sensor network lifetime, energy conservation was incorporated into the self-organization algorithm by incorporating a sleep-wakeup management mechanism with a novel cross layer adaptive wakeup probability adjustment scheme. The simulation results confirm that the developed self-organization algorithm provides satisfactory target tracking performance. Moreover, the energy saving analysis confirms the effectiveness of the cross layer power management scheme in achieving extended sensor network lifetime without degrading the target tracking performance.

Development and reliability of a direct access sensor using flip chip on flex technology with anisotropic conductive adhesive

Technological developments in biomedical microsystems are opening up new opportunities to improve healthcare procedures. Swallowable diagnostic sensing capsules are an example of these. In none of the diagnostic sensing capsules, is the sensor’s first level packaging achieved via Flip Chip Over Hole (FCOH) method using Anisotropic Conductive Adhesive (ACA). In a capsule application with direct access sensor (DAS), ACA not only provides the electrical interconnection but simultaneously seals the interconnect area and the underlying electronics. The development showed that the ACA FCOH was a viable option for the DAS interconnection. Adequate adhesive formed a strong joint that withstood a shear stress of 120N/mm2 and a compressive stress of 6N required to secure the final sensor assembly in place before encapsulation. Electrical characterization of the ACA joint in a fluid environment showed that the ACA was saturated with moisture and that the ions in the solution actively contributed to the leakage current, characterized by the varying rate of change of conductance. Long term hygrothermal aging of the ACA joint showed that a thermal strain of 0.004 and a hygroscopic strain of 0.0052 were present and resulted in a fatigue like process. In-vitro tests showed that high temperature and acidity had a deleterious effect of the ACA and its joint. It also showed that the ACA contact joints positioned at around or over 1mm would survive the gastrointestinal (GI) fluids and would be able to provide a reliable contact during the entire 72hr of the GI transit time. A final capsule demonstrator was achieved by successfully integrating the DAS, the battery and the final foldable circuitry into a glycerine capsule. Final capsule soak tests suggested that the silicone encapsulated system could survive the 72hr gut transition.

Oxygen targeting in preterm infants using the Masimo SET Radical pulse oximeter

BACKGROUND: A pretrial clinical improvement project for the BOOST-II UK trial of oxygen saturation targeting revealed an artefact affecting saturation profiles obtained from the Masimo Set Radical pulse oximeter.

METHODS: Saturation was recorded every 10 s for up to 2 weeks in 176 oxygen dependent preterm infants in 35 UK and Irish neonatal units between August 2006 and April 2009 using Masimo SET Radical pulse oximeters. Frequency distributions of % time at each saturation were plotted. An artefact affecting the saturation distribution was found to be attributable to the oximeter's internal calibration algorithm. Revised software was installed and saturation distributions obtained were compared with four other current oximeters in paired studies.

RESULTS: There was a reduction in saturation values of 87-90%. Values above 87% were elevated by up to 2%, giving a relative excess of higher values. The software revision eliminated this, improving the distribution of saturation values. In paired comparisons with four current commercially available oximeters, Masimo oximeters with the revised software returned similar saturation distributions.

CONCLUSIONS: A characteristic of the software algorithm reduces the frequency of saturations of 87-90% and increases the frequency of higher values returned by the Masimo SET Radical pulse oximeter. This effect, which remains within the recommended standards for accuracy, is removed by installing revised software (board firmware V4.8 or higher). Because this observation is likely to influence oxygen targeting, it should be considered in the analysis of the oxygen trial results to maximise their generalisability.

A review of Parkinson’s disease cardinal and dyskinetic motor symptoms assessment methods using sensor systems

This paper is reviewing objective assessments of Parkinson’s disease(PD) motor symptoms, cardinal, and dyskinesia, using sensor systems. It surveys the manifestation of PD symptoms, sensors that were used for their detection, types of signals (measures) as well as their signal processing (data analysis) methods. A summary of this review’s finding is represented in a table including devices (sensors), measures and methods that were used in each reviewed motor symptom assessment study. In the gathered studies among sensors, accelerometers and touch screen devices are the most widely used to detect PD symptoms and among symptoms, bradykinesia and tremor were found to be mostly evaluated. In general, machine learning methods are potentially promising for this. PD is a complex disease that requires continuous monitoring and multidimensional symptom analysis. Combining existing technologies to develop new sensor platforms may assist in assessing the overall symptom profile more accurately to develop useful tools towards supporting better treatment process.

User Behavioral Modeling of Web-based Systems for Continuous User Authentication

Authentication plays an important role in how we interact with computers, mobile devices, the web, etc. The idea of authentication is to uniquely identify a user before granting access to system privileges. For example, in recent years more corporate information and applications have been accessible via the Internet and Intranet. Many employees are working from remote locations and need access to secure corporate files. During this time, it is possible for malicious or unauthorized users to gain access to the system. For this reason, it is logical to have some mechanism in place to detect whether the logged-in user is the same user in control of the user's session. Therefore, highly secure authentication methods must be used. We posit that each of us is unique in our use of computer systems. It is this uniqueness that is leveraged to "continuously authenticate users" while they use web software. To monitor user behavior, n-gram models are used to capture user interactions with web-based software. This statistical language model essentially captures sequences and sub-sequences of user actions, their orderings, and temporal relationships that make them unique by providing a model of how each user typically behaves. Users are then continuously monitored during software operations. Large deviations from "normal behavior" can possibly indicate malicious or unintended behavior. This approach is implemented in a system called Intruder Detector (ID) that models user actions as embodied in web logs generated in response to a user's actions. User identification through web logs is cost-effective and non-intrusive. We perform experiments on a large fielded system with web logs of approximately 4000 users. For these experiments, we use two classification techniques; binary and multi-class classification. We evaluate model-specific differences of user behavior based on coarse-grain (i.e., role) and fine-grain (i.e., individual) analysis. A specific set of metrics are used to provide valuable insight into how each model performs. Intruder Detector achieves accurate results when identifying legitimate users and user types. This tool is also able to detect outliers in role-based user behavior with optimal performance. In addition to web applications, this continuous monitoring technique can be used with other user-based systems such as mobile devices and the analysis of network traffic.

Monitoring pollutants in occupied spaces.

There is increasing evidence of a causal link between airborne particles and ill health and this study monitored the exposure to both airborne particles and the gas phase contaminants of environmental tobacco smoke (ETS) in a nightclub. The present study followed a number of pilot studies in which the human exposure to airborne particles in a nightclub was assessed and the spatio-temporal distribution of gas phase pollutants was evaluated in restaurants and pubs. The work reported here re-examined the nightclub environment and utilized concurrent and continuous monitoring using optical scattering samplers to measure particulates (PM10) together with multi-gas analysers. The analysis illustrated the highly episodic nature of both gaseous and particulate concentrations in both the dance floor and in the bar area but levels were well below the maximum recommended exposure levels. Short-term exposure to high concentrations may however be relevant when considering the possible toxic effects on biological systems. The results give an indication of the problems associated with achieving acceptable indoor air quality (IAQ) in a complex space and identified some of the problems inherent in the design and operation of ventilation systems for such spaces.