986 resultados para 050206 Environmental Monitoring


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The aim of this work was to review the existing instrumental methods to monitor airborne nanoparticle in different types of indoor and outdoor environments in order to detect their presence and to characterise their properties. Firstly the terminology and definitions used in this field are discussed, which is followed by a review of the methods to measure particle physical characteristics including number concentration, size distribution and surface area. An extensive discussion is provided on the direct methods for particle elemental composition measurements, as well as on indirect methods providing information on particle volatility and solubility, and thus in turn on volatile and semivolatile compounds of which the particle is composed. A brief summary of broader considerations related to nanoparticle monitoring in different environments concludes the paper.

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Human-specific Bacteroides HF183 (HS-HF183), human-specific Enterococci faecium esp (HS-esp), human-specific adenoviruses (HS-AVs) and human-specific polyomaviruses (HS-PVs) assays were evaluated in freshwater, seawater and distilled water to detect fresh sewage. The sewage spiked water samples were also tested for the concentrations of traditional fecal indicators (i.e., Escherichia coli, enterococci and Clostridium perfringens) and enteric viruses such as enteroviruses (EVs), sapoviruses (SVs), and torquetenoviruses (TVs). The overall host-specificity of the HS-HF183 marker to differentiate between humans and other animals was 98%. However, the HS-esp, HS-AVs and HS-PVs showed 100% hostspecificity. All the human-specific markers showed >97% sensitivity to detect human fecal pollution. E. coli, enterococci and, C. perfringens were detected up to dilutions of sewage 10_5, 10_4 and 10_3 respectively.HS-esp, HS-AVs, HS-PVs, SVs and TVs were detected up to dilution of sewage 10_4 whilst EVs were detected up to dilution 10_5. The ability of the HS-HF183 marker to detect freshsewagewas3–4 orders ofmagnitude higher than that of the HS-esp and viral markers. The ability to detect fresh sewage in freshwater, seawater and distilled water matrices was similar for human-specific bacterial and viral marker. Based on our data, it appears that human-specific molecular markers are sensitive measures of fresh sewage pollution, and the HS-HF183 marker appears to be the most sensitive among these markers in terms of detecting fresh sewage. However, the presence of the HS-HF183 marker in environmental waters may not necessarily indicate the presence of enteric viruses due to their high abundance in sewage compared to enteric viruses. More research is required on the persistency of these markers in environmental water samples in relation to traditional fecal indicators and enteric pathogens.

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A vast amount of research into autonomous underwater navigation has, and is, being conducted around the world. However, typical research and commercial platforms have limited autonomy and are generally unable to navigate efficiently within coral reef environments without tethers and significant external infrastructure. This paper outlines the development and presents experimental results into the performance evaluation of a new robotic vehicle for underwater monitoring and surveying in highly unstructured environments. The hybrid AUV design developed by the CSIRO robotic reef monitoring team realises a compromise between endurance, manoeuvrability and functionality. The vehicle represents a new era in AUV design specifically focused at providing a truly lowcost research capability that will progress environmental monitoring through unaided navigation, cooperative robotics, sensor network distribution and data harvesting.

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Mobile sensor platforms such as Autonomous Underwater Vehicles (AUVs) and robotic surface vessels, combined with static moored sensors compose a diverse sensor network that is able to provide macroscopic environmental analysis tool for ocean researchers. Working as a cohesive networked unit, the static buoys are always online, and provide insight as to the time and locations where a federated, mobile robot team should be deployed to effectively perform large scale spatiotemporal sampling on demand. Such a system can provide pertinent in situ measurements to marine biologists whom can then advise policy makers on critical environmental issues. This poster presents recent field deployment activity of AUVs demonstrating the effectiveness of our embedded communication network infrastructure throughout southern California coastal waters. We also report on progress towards real-time, web-streaming data from the multiple sampling locations and mobile sensor platforms. Static monitoring sites included in this presentation detail the network nodes positioned at Redondo Beach and Marina Del Ray. One of the deployed mobile sensors highlighted here are autonomous Slocum gliders. These nodes operate in the open ocean for periods as long as one month. The gliders are connected to the network via a Freewave radio modem network composed of multiple coastal base-stations. This increases the efficiency of deployment missions by reducing operational expenses via reduced reliability on satellite phones for communication, as well as increasing the rate and amount of data that can be transferred. Another mobile sensor platform presented in this study are the autonomous robotic boats. These platforms are utilized for harbor and littoral zone studies, and are capable of performing multi-robot coordination while observing known communication constraints. All of these pieces fit together to present an overview of ongoing collaborative work to develop an autonomous, region-wide, coastal environmental observation and monitoring sensor network.

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Automatic species recognition plays an important role in assisting ecologists to monitor the environment. One critical issue in this research area is that software developers need prior knowledge of specific targets people are interested in to build templates for these targets. This paper proposes a novel approach for automatic species recognition based on generic knowledge about acoustic events to detect species. Acoustic component detection is the most critical and fundamental part of this proposed approach. This paper gives clear definitions of acoustic components and presents three clustering algorithms for detecting four acoustic components in sound recordings; whistles, clicks, slurs, and blocks. The experiment result demonstrates that these acoustic component recognisers have achieved high precision and recall rate.

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The world is facing problems due to the effects of increased atmospheric pollution, climate change and global warming. Innovative technologies to identify, quantify and assess fluxes exchange of the pollutant gases between the Earth’s surface and atmosphere are required. This paper proposes the development of a gas sensor system for a small UAV to monitor pollutant gases, collect data and geo-locate where the sample was taken. The prototype has two principal systems: a light portable gas sensor and an optional electric–solar powered UAV. The prototype will be suitable to: operate in the lower troposphere (100-500m); collect samples; stamp time and geo-locate each sample. One of the limitations of a small UAV is the limited power available therefore a small and low power consumption payload is designed and built for this research. The specific gases targeted in this research are NO2, mostly produce by traffic, and NH3 from farming, with concentrations above 0.05 ppm and 35 ppm respectively which are harmful to human health. The developed prototype will be a useful tool for scientists to analyse the behaviour and tendencies of pollutant gases producing more realistic models of them.

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While there are sources of ions both outdoors and indoors, ventilation systems can introduce as well as remove ions from the air. As a result, indoor ion concentrations are not directly related to air exchange rates in buildings. In this study, we attempt to relate these quantities with the view of understanding how charged particles may be introduced into indoor spaces.

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Well-designed indoor environments can support people’s health and welfare. In this literature review, we identify the environmental features that affect human health and wellbeing. Environmental characteristics found to influence health outcomes and/or wellbeing included: environmental safety; indoor air quality (e.g. odour and temperature); sound and noise; premises and interior design (e.g. construction materials, viewing nature and experiencing nature, windows versus no windows, light, colours, unit layout and placement of the furniture, the type of room, possibilities to control environmental elements, environmental complexity and sensory simulations, cleanliness, ergonomics and accessibility, ‛‛wayfinding’’); art, and music, among others. Indoor environments that incorporate healing elements can, for instance, reduce anxiety, lower blood pressure, lessen pain and shorten hospital stays.

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Airborne particles have been shown to be associated with a wide range of adverse health effects, which has led to a recent increase in medical research to gain better insight into their health effects. However, accurate evaluation of the exposure-dose-response relationship is highly dependent on the ability to track actual exposure levels of people to airborne particles. This is quite a complex task, particularly in relation to submicrometer and ultrafine particles, which can vary quite significantly in terms of particle surface area and number concentrations. Therefore, suitable monitors that can be worn for measuring personal exposure to these particles are needed. This paper presents an evaluation of the metrological performance of six diffusion charger sensors, NanoTracer (Philips Aerasense) monitors, when measuring particle number and surface area concentrations, as well as particle number distribution mean when compared to reference instruments. Tests in the laboratory (by generating monodisperse and polydisperse aerosols) and in the field (using natural ambient particles) were designed to evaluate the response of these devices under both steady-state and dynamics conditions. Results showed that the NanoTracers performed well when measuring steady state aerosols, however they strongly underestimated actual concentrations during dynamic response testing. The field experiments also showed that, when the majority of the particles were smaller than 20 nm, which occurs during particle formation events in the atmosphere, the NanoTracer underestimated number concentration quite significantly. Even though the NanoTracer can be used for personal monitoring of exposure to ultrafine particles, it also has limitations which need to be considered in order to provide meaningful results.

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Robotic systems are increasingly being utilised as fundamental data-gathering tools by scientists, allowing new perspectives and a greater understanding of the planet and its environmental processes. Today's robots are already exploring our deep oceans, tracking harmful algal blooms and pollution spread, monitoring climate variables, and even studying remote volcanoes. This article collates and discusses the significant advancements and applications of marine, terrestrial, and airborne robotic systems developed for environmental monitoring during the last two decades. Emerging research trends for achieving large-scale environmental monitoring are also reviewed, including cooperative robotic teams, robot and wireless sensor network (WSN) interaction, adaptive sampling and model-aided path planning. These trends offer efficient and precise measurement of environmental processes at unprecedented scales that will push the frontiers of robotic and natural sciences.

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The Lake Wivenhoe Integrated Wireless Sensor Network is conceptually similar to traditional SCADA monitoring and control approaches. However, it is applied in an open system using wireless devices to monitor processes that affect water quality at both a high spatial and temporal frequency. This monitoring assists scientists to better understand drivers of key processes that influence water quality and provide the operators with an early warning system if below standard water enters the reservoir. Both of these aspects improve the safety and efficient delivery of drinking water to the end users.

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Biomonitoring has become the ‘gold standard’ in assessing chemical exposures, and plays an important role in risk assessment. The pooling of biological specimens – combining multiple individual specimens into a single sample – can be used in biomonitoring studies to monitor levels of exposure and identify exposure trends, or to identify susceptible populations in a cost-effective manner. Pooled samples provide an estimate of central tendency, and may also reveal information about variation within the population. The development of a pooling strategy requires careful consideration of the type and number of samples collected, the number of pools required, and the number of specimens to combine per pool in order to maximize the type and robustness of the data. Creative pooling strategies can be used to explore exposure-outcome associations, and extrapolation from other larger studies can be useful in identifying elevated exposures in specific individuals. The use of pooled specimens is advantageous as it saves significantly on analytical costs, may reduce the time and resources required for recruitment, and in certain circumstances, allows quantification of samples approaching the limit of detection. In addition, use of pooled samples can provide population estimates while avoiding ethical difficulties that may be associated with reporting individual results.

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Persistent monitoring of the ocean is not optimally accomplished by repeatedly executing a fixed path in a fixed location. The ocean is dynamic, and so should the executed paths to monitor and observe it. An open question merging autonomy and optimal sampling is how and when to alter a path/decision, yet achieve desired science objectives. Additionally, many marine robotic deployments can last multiple weeks to months; making it very difficult for individuals to continuously monitor and retask them as needed. This problem becomes increasingly more complex when multiple platforms are operating simultaneously. There is a need for monitoring and adaptation of the robotic fleet via teams of scientists working in shifts; crowds are ideal for this task. In this paper, we present a novel application of crowd-sourcing to extend the autonomy of persistent-monitoring vehicles to enable nonrepetitious sampling over long periods of time. We present a framework that enables the control of a marine robot by anybody with an internet-enabled device. Voters are provided current vehicle location, gathered science data and predicted ocean features through the associated decision support system. Results are included from a simulated implementation of our system on a Wave Glider operating in Monterey Bay with the science objective to maximize the sum of observed nitrate values collected.

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Environmental monitoring is becoming critical as human activity and climate change place greater pressures on biodiversity, leading to an increasing need for data to make informed decisions. Acoustic sensors can help collect data across large areas for extended periods making them attractive in environmental monitoring. However, managing and analysing large volumes of environmental acoustic data is a great challenge and is consequently hindering the effective utilization of the big dataset collected. This paper presents an overview of our current techniques for collecting, storing and analysing large volumes of acoustic data efficiently, accurately, and cost-effectively.

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Wastewater containing human sewage is often discharged with little or no treatment into the Antarctic marine environment. Faecal sterols (primarily coprostanol) in sediments have been used for assessment of human sewage contamination in this environment, but in situ production and indigenous faunal inputs can confound such determinations. Using gas chromatography with mass spectral detection profiles of both C27 and C29 sterols, potential sources of faecal sterols were examined in nearshore marine sediments, encompassing sites proximal and distal to the wastewater outfall at Davis Station. Faeces from indigenous seals and penguins were also examined. Faeces from several indigenous species contained significant quantities of coprostanol but not 24-ethylcoprostanol, which is present in human faeces. In situ coprostanol and 24-ethylcoprostanol production was identified by co-production of their respective epi isomers at sites remote from the wastewat er source and in high total organic matter sediments. A C 29 sterols-based polyphasic likelihood assessment matrix for human sewage contamination is presented, which distinguishes human from local fauna faecal inputs and in situ production in the Antarctic environment. Sewage contamination was detected up to 1.5 km from Davis Station.