986 resultados para Atmospheric parameters


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The microwave radiometer TROWARA measures integrated water vapour (IWV) and integrated cloud liquid water (ILW) at Bern since 1994 with a time resolution of 7 s. In this study, we compare TROWARA measurements with a simulation of summer 2012 in Switzerland performed with the Weather Research and Forecasting (WRF) model. It is found that the WRF model agrees very well with TROWARA’s IWV variations with a mean bias of only 0.7 mm. The ILW distribution of the WRF model, although similar in shape to TROWARA’s distribution, overestimates the fraction of clear sky periods (83% compared to 60%).

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Grass pollen is an important risk factor for allergic rhinitis and asthma in Australia and is the most prevalent pollen component of the aerospora of Brisbane, accounting for 71.6% of the annual airborne pollen load. A 5-year (June 1994-May 1999) monitoring program shows the grass pollen season to occur during the summer and autumn months (December-April), however the timing of onset and intensity of the season vary from year to year. During the pollen season, Poaceae counts exceeding 30 grains m(-3) were recorded on 244 days and coincided with maximum temperatures of 28.1 +/- 2.0degreesC. In this study, statistical associations between atmospheric grass pollen loads and several weather parameters, including maximum temperature, minimum temperature and precipitation, were investigated. Spearman's correlation analysis demonstrated that daily grass pollen counts were positively associated (P < 0.0001) with maximum and minimum temperature during each sampling year. Precipitation, although considered a less important daily factor (P < 0.05), was observed to remove pollen grains from the atmosphere during significant periods of rainfall. This study provides the first insight into the influence of meteorological variables, in particular temperature, on atmospheric Poaceae pollen counts in Brisbane. An awareness of these associations is critical for the prevention and management of allergy and asthma for atopic individuals within this region.

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Traffic emissions are an important contributor to ambient air pollution, especially in large cities featuring extensive and high density traffic networks. Bus fleets represent a significant part of inner city traffic causing an increase in exposure to general public, passengers and drivers along bus routes and at bus stations. Limited information is available on quantification of the levels, and governing parameters affecting the air pollution exposure at bus stations. The presented study investigated the bus emissions-dominated ambient air in a large, inner city bus station, with a specific focus on submicrometer particles. The study’s objectives were (i) quantification of the concentration levels; (ii) characterisation of the spatio-temporal variation; (iii) identification of the parameters governing the emissions levels at the bus station and (iv) assessment of the relationship between particle concentrations measured at the street level (background) and within the bus station. The results show that up to 90% of the emissions at the station are ultrafine particles (smaller than 100 nm), with the concentration levels up to 10 times the value of urban ambient air background (annual) and up to 4 times the local ambient air background. The governing parameters affecting particle concentration at the station were bus flow rate and meteorological conditions (wind velocity). Particle concentration followed a diurnal trend, with an increase in the morning and evening, associated with traffic rush hours. Passengers’ exposure could be significant compared to the average outdoor and indoor exposure levels.

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Atmospheric deposition is one of the most important pollutant pathways for urban stormwater pollution. Atmospheric deposition can be in the form of dry and wet depositions which have distinct characteristics in terms of pollutant types, pollutant sources and influential parameters. This paper discusses the outcomes of a comprehensive study undertaken to identify the characteristics of wet and dry deposition of pollutants. Sample collection was undertaken at eight study sites with distinct characteristics. Four sites were close to road sites with varying traffic characteristics, whilst the other four sites had different land use characteristics. Dry deposition samples were collected for different antecedent dry days and wet deposition samples were collected immediately after rainfall events. The dry deposition was found to increase with the antecedent dry days and consisted of relatively coarser particles (greater than 1 µm) when compared to wet deposition. The wet deposition showed a strong affinity to rainfall depth, but was not related to the antecedent dry period. It was also found that smaller size particles (less than 1 µm) travel much longer distances from the source and deposit mainly with the wet deposition

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Atmospheric deposition is one of the most important pathways of urban stormwater pollution. Atmospheric deposition which can be in the form of either wet or dry deposition have distinct characteristics in terms of associated particulate sizes, pollutant types and influential parameters. This paper discusses the outcomes of a comprehensive research study undertaken to identify important traffic characteristics and climate factors such as antecedent dry period and rainfall characteristics which influences the characteristics of wet and dry deposition of solids and heavy metals. The outcomes confirmed that Zinc (Zn) is correlated with traffic volume whereas Lead (Pb), Cadmium (Cd), Nickel (Ni), and Copper (Cu) are correlated with traffic congestion. Consequently, reducing traffic congestion will be more effective than reducing traffic volume for improving air quality particularly in relation to Pb, Cd, Ni, and Cu. Zn was found to have the highest atmospheric deposition rate compared to other heavy metals. Zn in dry deposition is associated with relatively larger particle size fractions (>10 µm), whereas Pb, Cd, Ni and Cu are associated with relatively smaller particle size fractions (<10 µm). The analysis further revealed that bulk (wet plus dry) deposition which is correlated with rainfall depth and contains a relatively higher percentage of smaller particles compared to dry deposition which is correlated with the antecedent dry period. As particles subjected to wet deposition are smaller, they disperse over a larger area from the source of origin compared to particles subjected to dry deposition as buoyancy forces become dominant for smaller particles compared to the influence of gravity. Furthermore, exhaust emission particles were found to be primarily associated with bulk deposition compared to dry deposition particles which mainly originate from vehicle component wear.

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The effects of ethanol fumigation on the inter-cycle variability of key in-cylinder pressure parameters in a modern common rail diesel engine have been investigated. Specifically, maximum rate of pressure rise, peak pressure, peak pressure timing and ignition delay were investigated. A new methodology for investigating the start of combustion was also proposed and demonstrated—which is particularly useful with noisy in-cylinder pressure data as it can have a significant effect on the calculation of an accurate net rate of heat release indicator diagram. Inter-cycle variability has been traditionally investigated using the coefficient of variation. However, deeper insight into engine operation is given by presenting the results as kernel density estimates; hence, allowing investigation of otherwise unnoticed phenomena, including: multi-modal and skewed behaviour. This study has found that operation of a common rail diesel engine with high ethanol substitutions (>20% at full load, >30% at three quarter load) results in a significant reduction in ignition delay. Further, this study also concluded that if the engine is operated with absolute air to fuel ratios (mole basis) less than 80, the inter-cycle variability is substantially increased compared to normal operation.

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In this paper, we report on the fabrication of Mo-oxide nanostructures and nanoarchitectures using an atmospheric-microplasma (AMP) system. This AMP system shows a high degree of flexibility and is capable of producing several different nanostructures and nanoarchitectures by varying the process parameters. The low-cost and simplicity of the process are important characteristics for nanomanufacturing, and AMPs offer such advantages. In addition, AMPs have shown the ability of promoting self-organization of nanostructures. © 2009 IEEE.

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Atmospheric-pressure microplasma-assisted electrochemistry was used to synthesize Ag nanoparticles (NPs) for plasmonic applications. It is shown that the size and dispersion of the nanoparticles can be controlled by variation of the microplasma-assisted electrochemical process parameters such as electrolyte concentration and temperature. Moreover, Ag NP synthesis is also achieved in the absence of a stabilizer, with additional control over the dispersion and NP formation possible. As the microplasma directly reduces Ag ions in solution, the incorporation of toxic reducing agents into the electrolytic solution is unnecessary, making this an environmentally friendly fabrication technique with strong potential for the design and growth of plasmonic nanostructures for a variety of applications. These experiments therefore link microplasma-assisted electrochemical synthesis parameters with plasmonic characteristics.

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Long-term measurements of particle number size distribution (PNSD) produce a very large number of observations and their analysis requires an efficient approach in order to produce results in the least possible time and with maximum accuracy. Clustering techniques are a family of sophisticated methods which have been recently employed to analyse PNSD data, however, very little information is available comparing the performance of different clustering techniques on PNSD data. This study aims to apply several clustering techniques (i.e. K-means, PAM, CLARA and SOM) to PNSD data, in order to identify and apply the optimum technique to PNSD data measured at 25 sites across Brisbane, Australia. A new method, based on the Generalised Additive Model (GAM) with a basis of penalised B-splines, was proposed to parameterise the PNSD data and the temporal weight of each cluster was also estimated using the GAM. In addition, each cluster was associated with its possible source based on the results of this parameterisation, together with the characteristics of each cluster. The performances of four clustering techniques were compared using the Dunn index and Silhouette width validation values and the K-means technique was found to have the highest performance, with five clusters being the optimum. Therefore, five clusters were found within the data using the K-means technique. The diurnal occurrence of each cluster was used together with other air quality parameters, temporal trends and the physical properties of each cluster, in order to attribute each cluster to its source and origin. The five clusters were attributed to three major sources and origins, including regional background particles, photochemically induced nucleated particles and vehicle generated particles. Overall, clustering was found to be an effective technique for attributing each particle size spectra to its source and the GAM was suitable to parameterise the PNSD data. These two techniques can help researchers immensely in analysing PNSD data for characterisation and source apportionment purposes.

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It is well-known that new particle formation (NPF) in the atmosphere is inhibited by pre-existing particles in the air that act as condensation sinks to decrease the concentration and, thus, the supersaturation of precursor gases. In this study, we investigate the effects of two parameters - atmospheric visibility, expressed as the particle back-scatter coefficient (BSP), and PM10 particulate mass concentration, on the occurrences of NPF events in an urban environment where the majority of precursor gases originate from motor vehicle and industrial sources. This is the first attempt to derive direct relationships between each of these two parameters and the occurrence of NPF. NPF events were identified from data obtained with a neutral cluster and air ion spectrometer over 245 days within a calendar year. Bayesian logistic regression was used to determine the probability of observing NPF as functions of BSP and PM10. We show that the BSP at 08 h on a given day is a reliable indicator of an NPF event later that day. The posterior median probability of observing an NPF event was greater than 0.5 (95%) when the BSP at 08 h was less than 6.8 Mm-1.

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Gas discharge plasmas formed at atmospheric pressure and near room temperature have recently been shown as a promising tool for cancer treatment. The mechanism of the plasma action is attributed to generation of reactive oxygen and nitrogen species, electric fields, charges, and photons. The relative importance of different modes of action of atmospheric-pressure plasmas depends on the process parameters and specific treatment objects. Hence, an in-depth understanding of biological mechanisms that underpin plasma-induced death in cancer cells is required to optimise plasma processing conditions. Here, the intracellular factors involved in the observed anti-cancer activity in melanoma Mel007 cells are studied, focusing on the effect of the plasma treatment dose on the expression of tumour suppressor protein TP73. Over-expression of TP73 causes cell growth arrest and/or apoptosis, and hence can potentially be targeted to enhance killing efficacy and selectivity of the plasma treatment. It is shown that the plasma treatment induces dose-dependent up-regulation of TP73 gene expression, resulting in significantly elevated levels of TP73 RNA and protein in plasma-treated melanoma cells. Silencing of TP73 expression by means of RNA interference inhibited the anticancer effects of the plasma, similar to the effect of caspase inhibitor z-VAD or ROS scavenger N-acetyl cysteine. These results confirm the role of TP73 protein in dose-dependent regulation of anticancer activity of atmospheric-pressure plasmas.

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Simultaneous and collocated measurements of total and hemispherical backscattering coefficients (σ and β, respectively) at three wavelengths, mass size distributions, and columnar spectral aerosol optical depth (AOD) were made onboard an extensive cruise experiment covering, for the first time, the entire Bay of Bengal (BoB) and northern Indian Ocean. The results are synthesized to understand the optical properties of aerosols in the marine atmospheric boundary layer and their dependence on the size distribution. The observations revealed distinct spatial and spectral variations of all the aerosol parameters over the BoB and the presence of strong latitudinal gradients. The size distributions varied spatially, with the majority of accumulation modes decreasing from north to south. The scattering coefficient decreased from very high values (resembling those reported for continental/urban locations) in the northern BoB to very low values seen over near-pristine environments in the southeastern BoB. The average mass scattering efficiency of BoB aerosols was found to be 2.66 ± 0.1 m2 g−1 at 550 nm. The spectral dependence of columnar AOD deviated significantly from that of the scattering coefficients in the northern BoB, implying vertical heterogeneity in the aerosol type in that region. However, a more homogeneous scenario was observed in the southern BoB. Simultaneous lidar and in situ measurements onboard an aircraft over the ocean revealed the presence of elevated aerosol layers of enhanced extinction at altitudes of 1 to 3 km with an offshore extent of a few hundred kilometers. Back-trajectory analyses showed these layers to be associated with advection from west Asia and western India. The large spatial variations and vertical heterogeneity in aerosol properties, revealed by the present study, need to be included in the regional radiative forcing over the Bay of Bengal.

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Delineation of homogeneous precipitation regions (regionalization) is necessary for investigating frequency and spatial distribution of meteorological droughts. The conventional methods of regionalization use statistics of precipitation as attributes to establish homogeneous regions. Therefore they cannot be used to form regions in ungauged areas, and they may not be useful to form meaningful regions in areas having sparse rain gauge density. Further, validation of the regions for homogeneity in precipitation is not possible, since the use of the precipitation statistics to form regions and subsequently to test the regional homogeneity is not appropriate. To alleviate this problem, an approach based on fuzzy cluster analysis is presented. It allows delineation of homogeneous precipitation regions in data sparse areas using large scale atmospheric variables (LSAV), which influence precipitation in the study area, as attributes. The LSAV, location parameters (latitude, longitude and altitude) and seasonality of precipitation are suggested as features for regionalization. The approach allows independent validation of the identified regions for homogeneity using statistics computed from the observed precipitation. Further it has the ability to form regions even in ungauged areas, owing to the use of attributes that can be reliably estimated even when no at-site precipitation data are available. The approach was applied to delineate homogeneous annual rainfall regions in India, and its effectiveness is illustrated by comparing the results with those obtained using rainfall statistics, regionalization based on hard cluster analysis, and meteorological sub-divisions in India. (C) 2011 Elsevier B.V. All rights reserved.