962 resultados para AMBIENT OZONE


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BACKGROUND The number of older adults in the global population is increasing. This demographic shift leads to an increasing prevalence of age-associated disorders, such as Alzheimer's disease and other types of dementia. With the progression of the disease, the risk for institutional care increases, which contrasts with the desire of most patients to stay in their home environment. Despite doctors' and caregivers' awareness of the patient's cognitive status, they are often uncertain about its consequences on activities of daily living (ADL). To provide effective care, they need to know how patients cope with ADL, in particular, the estimation of risks associated with the cognitive decline. The occurrence, performance, and duration of different ADL are important indicators of functional ability. The patient's ability to cope with these activities is traditionally assessed with questionnaires, which has disadvantages (eg, lack of reliability and sensitivity). Several groups have proposed sensor-based systems to recognize and quantify these activities in the patient's home. Combined with Web technology, these systems can inform caregivers about their patients in real-time (e.g., via smartphone). OBJECTIVE We hypothesize that a non-intrusive system, which does not use body-mounted sensors, video-based imaging, and microphone recordings would be better suited for use in dementia patients. Since it does not require patient's attention and compliance, such a system might be well accepted by patients. We present a passive, Web-based, non-intrusive, assistive technology system that recognizes and classifies ADL. METHODS The components of this novel assistive technology system were wireless sensors distributed in every room of the participant's home and a central computer unit (CCU). The environmental data were acquired for 20 days (per participant) and then stored and processed on the CCU. In consultation with medical experts, eight ADL were classified. RESULTS In this study, 10 healthy participants (6 women, 4 men; mean age 48.8 years; SD 20.0 years; age range 28-79 years) were included. For explorative purposes, one female Alzheimer patient (Montreal Cognitive Assessment score=23, Timed Up and Go=19.8 seconds, Trail Making Test A=84.3 seconds, Trail Making Test B=146 seconds) was measured in parallel with the healthy subjects. In total, 1317 ADL were performed by the participants, 1211 ADL were classified correctly, and 106 ADL were missed. This led to an overall sensitivity of 91.27% and a specificity of 92.52%. Each subject performed an average of 134.8 ADL (SD 75). CONCLUSIONS The non-intrusive wireless sensor system can acquire environmental data essential for the classification of activities of daily living. By analyzing retrieved data, it is possible to distinguish and assign data patterns to subjects' specific activities and to identify eight different activities in daily living. The Web-based technology allows the system to improve care and provides valuable information about the patient in real-time.

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The ground-based radiometer GROMOS, stationed in Bern (47.95° N, 7.44° E), Switzerland, has a unique dataset: it obtains ozone profiles from November 1994 to present with a time resolution of 30 min and equal quality during night- and daytime. Here, we derive a monthly climatology of the daily ozone cycle from 17 yr of GROMOS observation. We present the diurnal ozone variation of the stratosphere and mesosphere. Characterizing the diurnal cycle of stratospheric ozone is important for correct trend estimates of the ozone layer derived from satellite observations. The diurnal ozone cycle from GROMOS is compared to two models: The Whole Atmosphere Community Climate Model (WACCM) and the Hamburg Model of Neutral and Ionized Atmosphere (HAMMONIA). Aura Microwave Limb Sounder (Aura/MLS) ozone data, from night- and daytime overpasses over Bern, have also been included in the comparison. Generally, observation and models show good qualitative agreement: in the lower mesosphere, daytime ozone is for both GROMOS and models around 25% less than nighttime ozone (reference is 22:30–01:30). In the stratosphere, ozone reaches its maximum in the afternoon showing values several percent larger than the midnight value. It is important that diurnal ozone variations of this order are taken into account when merging different data sets for the derivation of long-term ozone trends in the stratosphere. Further, GROMOS and models indicate a seasonal behavior of daily ozone variations in the stratosphere with a larger afternoon maximum during daytime in summer than in winter. At 0.35 hPa, observations from GROMOS and Aura/MLS show a seasonal pattern in diurnal ozone variations with larger relative amplitudes during daytime in winter (−25 ± 5%) than in summer (−18 ± 4%) (compared to mean values around midnight). For the first time, a time series of the diurnal variations in ozone is presented: 17 yr of GROMOS data show strong interannual variations in the diurnal ozone cycle for both the stratosphere and the mesosphere. There are some indications that strong temperature tides can suppress the diurnal variation of stratospheric ozone via the anticorrelation of temperature and ozone. That means the spatio-temporal variability of solar thermal tides seems to affect the diurnal cycle of stratospheric ozone.

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In this study we compare the diurnal variation in stratospheric ozone derived from free-running simulations of the Whole Atmosphere Community Climate Model (WACCM) and from reanalysis data of the atmospheric service MACC (Monitoring Atmospheric Composition and Climate) which both use a similar stratospheric chemistry module. We find good agreement between WACCM and the MACC reanalysis for the diurnal ozone variation in the high-latitude summer stratosphere based on photochemistry. In addition, we consult the ozone data product of the ERA-Interim reanalysis. The ERA-Interim reanalysis ozone system with its long-term ozone parametrization can not capture these diurnal variations in the upper stratosphere that are due to photochemistry. The good dynamics representations, however, reflects well dynamically induced ozone variations in the lower stratosphere. For the high-latitude winter stratosphere we describe a novel feature of diurnal variation in ozone where changes of up to 46.6% (3.3 ppmv) occur in monthly mean data. For this effect good agreement between the ERA-Interim reanalysis and the MACC reanalysis suggest quite similar diurnal advection processes of ozone. The free-running WACCM model seriously underestimates the role of diurnal advection processes at the polar vortex at the two tested resolutions. The intercomparison of the MACC reanalysis and the ERA-Interim reanalysis demonstrates how global reanalyses can benefit from a chemical representation held by a chemical transport model. The MACC reanalysis provides an unprecedented description of the dynamics and photochemistry of the diurnal variation of stratospheric ozone which is of high interest for ozone trend analysis and research on atmospheric tides. We confirm the diurnal variation in ozone at 5 hPa by observations of the Superconducting Submillimeter-Wave Limb-Emission Sounder (SMILES) experiment and selected sites of the Network for Detection of Atmospheric Composition Change (NDACC). The latter give valuable insight even to diurnal variation of ozone in the polar winter stratosphere.

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We present a new approach to the issues of spacetime singularities and cosmic censorship in general relativity. This is based on the idea that standard 4-dimensional spacetime is the conformal infinity of an ambient metric for the 5-dimensional Einstein equations with fluid sources. We then find that the existence of spacetime singularities in four dimensions is constrained by asymptotic properties of the ambient 5-metric, while the non-degeneracy of the latter crucially depends on cosmic censorship holding on the boundary.

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Smart homes for the aging population have recently started attracting the attention of the research community. The "health state" of smart homes is comprised of many different levels; starting with the physical health of citizens, it also includes longer-term health norms and outcomes, as well as the arena of positive behavior changes. One of the problems of interest is to monitor the activities of daily living (ADL) of the elderly, aiming at their protection and well-being. For this purpose, we installed passive infrared (PIR) sensors to detect motion in a specific area inside a smart apartment and used them to collect a set of ADL. In a novel approach, we describe a technology that allows the ground truth collected in one smart home to train activity recognition systems for other smart homes. We asked the users to label all instances of all ADL only once and subsequently applied data mining techniques to cluster in-home sensor firings. Each cluster would therefore represent the instances of the same activity. Once the clusters were associated to their corresponding activities, our system was able to recognize future activities. To improve the activity recognition accuracy, our system preprocessed raw sensor data by identifying overlapping activities. To evaluate the recognition performance from a 200-day dataset, we implemented three different active learning classification algorithms and compared their performance: naive Bayesian (NB), support vector machine (SVM) and random forest (RF). Based on our results, the RF classifier recognized activities with an average specificity of 96.53%, a sensitivity of 68.49%, a precision of 74.41% and an F-measure of 71.33%, outperforming both the NB and SVM classifiers. Further clustering markedly improved the results of the RF classifier. An activity recognition system based on PIR sensors in conjunction with a clustering classification approach was able to detect ADL from datasets collected from different homes. Thus, our PIR-based smart home technology could improve care and provide valuable information to better understand the functioning of our societies, as well as to inform both individual and collective action in a smart city scenario.

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We discuss the topological nature of the boundary spacetime, the conformal infinity of the ambient cosmological metric. Due to the existence of a homothetic group, the bounding spacetime must be equipped not with the usual Euclidean metric topology but with the Zeeman fine topology. This then places severe constraints to the convergence of a sequence of causal curves and the extraction of a limit curve, and also to our ability to formulate conditions for singularity formation.

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Ozone-depleting substances emitted through human activitiescause large-scale damage to the stratospheric ozone layer, and influence global climate. Consequently, the production of many of these substances has been phased out; prominent examples are the chlorofluorocarbons (CFCs), and their intermediate replacements, the hydrochlorofluorocarbons (HCFCs). So far, seven types of CFC and six types of HCFC have been shown to contribute to stratospheric ozone destruction 1,2. Here, we report the detection and quantification of a further three CFCs and one HCFC. We analysed the composition of unpolluted air samples collected in Tasmania between 1978 and 2012, and extracted from deep firn snow in Greenland in 2008, using gas chromatography with mass spectrometric detection. Using the firn data, we show that all four compounds started to emerge in the atmosphere in the 1960s. Two of the compounds continue to accumulate in the atmosphere. We estimate that, before 2012, emissions of all four compounds combined amounted to more than 74,000 tonnes. This is small compared with peak emissions of other CFCs in the 1980s of more than one million tonnes each year 2. However, the reported emissions are clearly contrary to the intentions behind the Montreal Protocol, and raise questions about the sources of these gases.

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After major volcanic eruptions the enhanced aerosol causes ozone changes due to greater heterogeneous chemistry on the particle surfaces (HET-AER) and from dynamical effects related to the radiative heating of the lower stratosphere (RAD-DYN). We carry out a series of experiments with an atmosphere–ocean–chemistry–climate model to assess how these two processes change stratospheric ozone and Northern Hemispheric (NH) polar vortex dynamics. Ensemble simulations are performed under present day and preindustrial conditions, and with aerosol forcings representative of different eruption strength, to investigate changes in the response behaviour. We show that the halogen component of the HET-AER effect dominates under present-day conditions with a global reduction of ozone (−21 DU for the strongest eruption) particularly at high latitudes, whereas the HET-AER effect increases stratospheric ozone due to N2O5 hydrolysis in a preindustrial atmosphere (maximum anomalies +4 DU). The halogen-induced ozone changes in the present-day atmosphere offset part of the strengthening of the NH polar vortex during mid-winter (reduction of up to −16 m s-1 in January) and slightly amplify the dynamical changes in the polar stratosphere in late winter (+11 m s-1 in March). The RAD-DYN mechanism leads to positive column ozone anomalies which are reduced in a present-day atmosphere by amplified polar ozone depletion (maximum anomalies +12 and +18 DU for present day and preindustrial, respectively). For preindustrial conditions, the ozone response is consequently dominated by RAD-DYN processes, while under present-day conditions, HET-AER effects dominate. The dynamical response of the stratosphere is dominated by the RAD-DYN mechanism showing an intensification of the NH polar vortex in winter (up to +10 m s-1 in January). Ozone changes due to the RAD-DYN mechanism slightly reduce the response of the polar vortex after the eruption under present-day conditions.

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Stratospheric ozone is of major interest as it absorbs most harmful UV radiation from the sun, allowing life on Earth. Ground-based microwave remote sensing is the only method that allows for the measurement of ozone profiles up to the mesopause, over 24 hours and under different weather conditions with high time resolution. In this paper a novel ground-based microwave radiometer is presented. It is called GROMOS-C (GRound based Ozone MOnitoring System for Campaigns), and it has been designed to measure the vertical profile of ozone distribution in the middle atmosphere by observing ozone emission spectra at a frequency of 110.836 GHz. The instrument is designed in a compact way which makes it transportable and suitable for outdoor use in campaigns, an advantageous feature that is lacking in present day ozone radiometers. It is operated through remote control. GROMOS-C is a total power radiometer which uses a pre-amplified heterodyne receiver, and a digital fast Fourier transform spectrometer for the spectral analysis. Among its main new features, the incorporation of different calibration loads stands out; this includes a noise diode and a new type of blackbody target specifically designed for this instrument, based on Peltier elements. The calibration scheme does not depend on the use of liquid nitrogen; therefore GROMOS-C can be operated at remote places with no maintenance requirements. In addition, the instrument can be switched in frequency to observe the CO line at 115 GHz. A description of the main characteristics of GROMOS-C is included in this paper, as well as the results of a first campaign at the High Altitude Research Station at Jungfraujoch (HFSJ), Switzerland. The validation is performed by comparison of the retrieved profiles against equivalent profiles from MLS (Microwave Limb Sounding) satellite data, ECMWF (European Centre for Medium-Range Weather Forecast) model data, as well as our nearby NDACC (Network for the Detection of Atmospheric Composition Change) ozone radiometer measuring at Bern.

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In situ and simultaneous measurement of the three most abundant isotopologues of methane using mid-infrared laser absorption spectroscopy is demonstrated. A field-deployable, autonomous platform is realized by coupling a compact quantum cascade laser absorption spectrometer (QCLAS) to a preconcentration unit, called trace gas extractor (TREX). This unit enhances CH4 mole fractions by a factor of up to 500 above ambient levels and quantitatively separates interfering trace gases such as N2O and CO2. The analytical precision of the QCLAS isotope measurement on the preconcentrated (750 ppm, parts-per-million, µmole mole−1) methane is 0.1 and 0.5 ‰ for δ13C- and δD-CH4 at 10 min averaging time. Based on repeated measurements of compressed air during a 2-week intercomparison campaign, the repeatability of the TREX–QCLAS was determined to be 0.19 and 1.9 ‰ for δ13C and δD-CH4, respectively. In this intercomparison campaign the new in situ technique is compared to isotope-ratio mass spectrometry (IRMS) based on glass flask and bag sampling and real time CH4 isotope analysis by two commercially available laser spectrometers. Both laser-based analyzers were limited to methane mole fraction and δ13C-CH4 analysis, and only one of them, a cavity ring down spectrometer, was capable to deliver meaningful data for the isotopic composition. After correcting for scale offsets, the average difference between TREX–QCLAS data and bag/flask sampling–IRMS values are within the extended WMO compatibility goals of 0.2 and 5 ‰ for δ13C- and δD-CH4, respectively. This also displays the potential to improve the interlaboratory compatibility based on the analysis of a reference air sample with accurately determined isotopic composition.

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Under the Clean Air Act, Congress granted discretionary decision making authority to the Administrator of the Environmental Protection Agency (EPA). This discretionary authority involves setting standards to protect the public's health with an "adequate margin of safety" based on current scientific knowledge. The Administrator of the EPA is usually not a scientist, and for the National Ambient Air Quality Standard (NAAQS) for particulate matter (PM), the Administrator faced the task of revising a standard when several scientific factors were ambiguous. These factors included: (1) no identifiable threshold below which health effects are not manifested, (2) no biological basis to explain the reported associations between particulate matter and adverse health effects, and (3) no consensus among the members of the Clean Air Scientific Advisory Committee (CASAC) as to what an appropriate PM indicator, averaging period, or value would be for the revised standard. ^ This project recommends and demonstrates a tool, integrated assessment (IA), to aid the Administrator in making a public health policy decision in the face of ambiguous scientific factors. IA is an interdisciplinary approach to decision making that has been used to deal with complex issues involving many uncertainties, particularly climate change analyses. Two IA approaches are presented; a rough set analysis by which the expertise of CASAC members can be better utilized, and a flag model for incorporating the views of stakeholders into the standard setting process. ^ The rough set analysis can describe minimal and maximal conditions about the current science pertaining to PM and health effects. Similarly, a flag model can evaluate agreement or lack of agreement by various stakeholder groups to the proposed standard in the PM review process. ^ The use of these IA tools will enable the Administrator to (1) complete the NAAQS review in a manner that is in closer compliance with the Clean Air Act, (2) expand the input from CASAC, (3) take into consideration the views of the stakeholders, and (4) retain discretionary decision making authority. ^