966 resultados para Dynamic air atmosphere


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Water uptake refers to the ability of atmospheric particles to take up water vapour from the surrounding atmosphere. This is an important property that affects particle size and phase and therefore influences many characteristics of aerosols relevant to air quality and climate. However, the water uptake properties of many important atmospheric aerosol systems, including those related to the oceans, are still not fully understood. Therefore, the primary aim of this PhD research program was to investigate the water uptake properties of marine aerosols. In particular, the effect of organics on marine aerosol water uptake was investigated. Field campaigns were conducted at remote coastal sites on the east coast of Australia (Agnes Water; March-April 2007) and west coast of Ireland (Mace Head; June 2007), and laboratory measurements were performed on bubble-generated sea spray aerosols. A combined Volatility-Hygroscopicity-Tandem Differential Mobility Analyser (VH-TDMA) was employed in all experiments. This system probes the changes in the hygroscopic properties of nanoparticles as volatile organic components are progressively evaporated. It also allows particle composition to be inferred from combined volatility-hygroscopicity measurements. Frequent new particle formation and growth events were observed during the Agnes Water campaign. The VH-TDMA was used to investigate freshly nucleated particles (17-22.5 nm) and it was found that the condensation of sulphate and/or organic vapours was responsible for driving particle growth during the events. Aitken mode particles (~40 nm) were also measured with the VH-TDMA. In 3 out of 18 VH-TDMA scans evaporation of a volatile, organic component caused a very large increase in hygroscopicity that could only be explained by an increase in the absolute water uptake of the particle residuals, and not merely an increase in their relative hygroscopicity. This indicated the presence of organic components that were suppressing the hygroscopic growth of mixed particles on the timescale of humidification in the VH-TDMA (6.5 secs). It was suggested that the suppression of water uptake was caused by either a reduced rate of hygroscopic growth due to the presence of organic films, or organic-inorganic interactions in solution droplets that had a negative effect on hygroscopicity. Mixed organic-inorganic particles were rarely observed by the VH-TDMA during the summer campaign conducted at Mace Head. The majority of particles below 100 nm in clean, marine air appeared to be sulphates neutralised to varying degrees by ammonia. On one unique day, 26 June 2007, particularly large concentrations of sulphate aerosol were observed and identified as volcanic emissions from Iceland. The degree of neutralisation of the sulphate aerosol by ammonia was calculated by the VH-TDMA and found to compare well with the same quantity measured by an aerosol mass spectrometer. This was an important verification of the VH-TMDA‘s ability to identify ammoniated sulphate aerosols based on the simultaneous measurement of aerosol volatility and hygroscopicity. A series of measurements were also conducted on sea spray aerosols generated from Moreton Bay seawater samples in a laboratory-based bubble chamber. Accumulation mode sea spray particles (38-173 nm) were found to contain only a minor organic fraction (< 10%) that had little effect on particle hygroscopicity. These results are important because previous studies have observed that accumulation mode sea spray particles are predominantly organic (~80% organic mass fraction). The work presented here suggests that this is not always the case, and that there may be currently unknown factors that are controlling the transfer of organics to the aerosol phase during the bubble bursting process. Taken together, the results of this research program have significantly improved our understanding of organic-containing marine aerosols and the way they interact with water vapour in the atmosphere.

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Atmospheric concentration of total suspended particulate matter (TSP) and associated heavy metals are a great concern due to their adverse health impacts and contribution to stormwater pollution. This paper discusses the outcomes of a study which investigated the variation of atmospheric TSP and heavy metal concentrations with traffic and land use characteristics during weekdays and weekends. Data for this study was gathered from fifteen sites at the Gold Coast, Australia using a high volume air sampler. The study detected consistently high TSP concentrations during weekdays compared to weekends. This confirms the significant influence of traffic related sources on TSP loads during weekdays. Both traffic and land use related sources equally contribute to TSP during weekends. Almost all the measured heavy metals showed high concentration on weekdays compared to weekends indicating significant contributions from traffic related emissions. Among the heavy metals, Zn concentration was the highest followed by Pb. It is postulated that re-suspension of previously deposited reserves was the main Pb source. Soil related sources were the main contributors of Mn.

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With the growing significance of services in most developed economies, there is an increased interest in the role of service innovation in service firm competitive strategy. Despite growing literature on service innovation, it remains fragmented reflecting the need for a model that captures key antecedents driving the service innovation-based competitive advantage process. Building on extant literature and using thirteen in-depth interviews with CEOs of project-oriented service firms, this paper presents a model of innovation-based competitive advantage. The emergent model suggests that entrepreneurial service firms pursuing innovation carefully select and use dynamic capabilities that enable them to achieve greater innovation and sustained competitive advantage. Our findings indicate that firms purposefully use create, extend and modify processes to build and nurture key dynamic capabilities. The paper presents a set of theoretical propositions to guide future research. Implications for theory and practice are discussed. Finally, directions for future research are outlined.

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Windows are one of the most significant elements in the design of buildings. Whether there are small punched openings in the facade or a completely glazed curtain wall, windows are usually a dominant feature of the building's exterior appearance. From the energy use perspective, windows may also be regarded as thermal holes for a building. Therefore, window design and selection must take both aesthetics and serviceability into consideration. In this paper, using building computer simulation techniques, the effects of glass types on the thermal and energy performance of a sample air-conditioned office building in Australia are studied. It is found that a glass type with lower shading coefficient will have a lower building cooling load and total energy use. Through the comparison of results between current and future weather scenarios, it is identified that the pattern found from the current weather scenario would also exist in the future weather scenario, although the scale of change would become smaller. The possible implication of glazing selection in face of global warming is also examined. It is found that compared with its influence on building thermal performance, its influence on the building energy use is relatively small or insignificant.

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The availability of bridges is crucial to people’s daily life and national economy. Bridge health prediction plays an important role in bridge management because maintenance optimization is implemented based on prediction results of bridge deterioration. Conventional bridge deterioration models can be categorised into two groups, namely condition states models and structural reliability models. Optimal maintenance strategy should be carried out based on both condition states and structural reliability of a bridge. However, none of existing deterioration models considers both condition states and structural reliability. This study thus proposes a Dynamic Objective Oriented Bayesian Network (DOOBN) based method to overcome the limitations of the existing methods. This methodology has the ability to act upon as a flexible unifying tool, which can integrate a variety of approaches and information for better bridge deterioration prediction. Two demonstrative case studies are conducted to preliminarily justify the feasibility of the methodology

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Twitter is now well established as the world’s second most important social media platform, after Facebook. Its 140-character updates are designed for brief messaging, and its network structures are kept relatively flat and simple: messages from users are either public and visible to all (even to unregistered visitors using the Twitter website), or private and visible only to approved ‘followers’ of the sender; there are no more complex definitions of degrees of connection (family, friends, friends of friends) as they are available in other social networks. Over time, Twitter users have developed simple, but effective mechanisms for working around these limitations: ‘#hashtags’, which enable the manual or automatic collation of all tweets containing the same #hashtag, as well allowing users to subscribe to content feeds that contain only those tweets which feature specific #hashtags; and ‘@replies’, which allow senders to direct public messages even to users whom they do not already follow. This paper documents a methodology for extracting public Twitter activity data around specific #hashtags, and for processing these data in order to analyse and visualize the @reply networks existing between participating users – both overall, as a static network, and over time, to highlight the dynamic structure of @reply conversations. Such visualizations enable us to highlight the shifting roles played by individual participants, as well as the response of the overall #hashtag community to new stimuli – such as the entry of new participants or the availability of new information. Over longer timeframes, it is also possible to identify different phases in the overall discussion, or the formation of distinct clusters of preferentially interacting participants.

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For many people, a relatively large proportion of daily exposure to a multitude of pollutants may occur inside an automobile. A key determinant of exposure is the amount of outdoor air entering the cabin (i.e. air change or flow rate). We have quantified this parameter in six passenger vehicles ranging in age from 18 years to <1 year, at three vehicle speeds and under four different ventilation settings. Average infiltration into the cabin with all operable air entry pathways closed was between 1 and 33.1 air changes per hour (ACH) at a vehicle speed of 60 km/h, and between 2.6 and 47.3 ACH at 110 km/h, with these results representing the most (2005 Volkswagen Golf) and least air-tight (1989 Mazda 121) vehicles, respectively. Average infiltration into stationary vehicles parked outdoors varied between ~0 and 1.4 ACH and was moderately related to wind speed. Measurements were also performed under an air recirculation setting with low fan speed, while airflow rate measurements were conducted under two non-recirculate ventilation settings with low and high fan speeds. The windows were closed in all cases, and over 200 measurements were performed. The results can be applied to estimate pollutant exposure inside vehicles.

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For the shop scheduling problems such as flow-shop, job-shop, open-shop, mixed-shop, and group-shop, most research focuses on optimizing the makespan under static conditions and does not take into consideration dynamic disturbances such as machine breakdown and new job arrivals. We regard the shop scheduling problem under static conditions as the static shop scheduling problem, while the shop scheduling problem with dynamic disturbances as the dynamic shop scheduling problem. In this paper, we analyze the characteristics of the dynamic shop scheduling problem when machine breakdown and new job arrivals occur, and present a framework to model the dynamic shop scheduling problem as a static group-shop-type scheduling problem. Using the proposed framework, we apply a metaheuristic proposed for solving the static shop scheduling problem to a number of dynamic shop scheduling benchmark problems. The results show that the metaheuristic methodology which has been successfully applied to the static shop scheduling problems can also be applied to solve the dynamic shop scheduling problem efficiently.

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It has been suggested that the accumulation of valuable resources and capabilities, such as Internet application, is not enough to support a firm’s sustainable competitive advantage, especially for high technology-mediated firms; which often operate in fast changing dynamic environments. While the idea of ‘Internet-enabled resources and capabilities’ has been recognised by RBV theorists, the notion has largely been ignored in conceptual and empirical studies. Given this finding, a conceptual framework is constructed and research issues are then developed in order to focus attention on the relationship between, the Internet and a firm’s resource base, dynamic capabilities and international market performance. We postulate that successful Internet-enabled market performance arises from those international entrepreneurial-oriented firms which encompass: international vision, international business experience, Internet-international marketing capabilities and international networking capabilities. Recommendations for future theory development are presented, along with the implications for international entrepreneurial managers in Australian small and medium sized firms

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In this work a biomechanical model is used for simulation of muscle forces necessary to maintain the posture in a car seat under different support conditions.