This study examines the role of noise barriers as traffic pollution shields for the areas adjacent to busy roads by means of computer modelling using the LES (Large Eddy Simulation) approach. There have been few pre- vious studies in which the transport and dispersion of air pollution have been assessed using LES modelling, particularly ,  or . However, these studies implemented LES modelling of air-pollution dispersion re- leased from stationary point sources. Application of the LES approach to pollutant dispersion from vehicles is described in  but this study focused on the near-wake region close to the tip of exhaust pipes on light vehicles. Numerical simulation of turbulent dispersion from two-way roads using an LES approach is used in  and the problem of wind fields and dispersion of air pollution from vehicles in residential areas is addressed with an LES-based model in . The wind field and pollutant dispersion in the downtown area of Macao is investigated using an LES-based model in . The effect of trees on pollutant dispersion within a street canyon is modeled using an LES approach and validated with a wind tunnel experiment in . All these previous studies address air pollution along roads or street canyons, but none has examined the impact of the noise barriers that can shel- ter surrounding areas from traffic emissions. This issue is addressed in the present study. Computational Fluid Dynamic (CFD) approaches have been used in previous studies, and results have been compared with measured data (e.g., ,  or ). However, such studies used less sophisticated parameterization of turbulence than that used in this study,
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ABSTRACT: The current study assesses critical condition of oil dispassion, considering the unsaturated soil condition dispersity behavior for oil dispersion. The numerical model is used as a finite element method to model the oil spill pollution with two different saturated and unsaturated soil conditions chosen and their pollution dispersion results compared. Extracted results from numerical model show that considering the form of unsaturated soil, by changing the matric suction its soil conductivity ratio will differ. Regarding the current study analysis, it has been observed that the pattern of oil dispersion in case of unsaturated soil can be changed, in comparison to saturated soil condition. The vertical penetration of oil pollution in both cases of saturated and unsaturated soil condition will be more than horizontal dispersion pollution speed. As for oil pollution control in soil domain, the condition of unsaturated soil may be controllable, compared to the saturated one. Extracted results show that oil dispersion velocity, considering saturated soil, is more than 10 times greater than unsaturated one.
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The relevancy of using the 3D spatial city model (CityGML) for air quality monitoring is its scale. As discussed in Section 2, air quality modeling in urban ar- eas requires a scale model that less than 2 km resolution. But to acquire data for micro-scale urban areas is chal- lenging. Detailed geometries for buildings and street ob- jects are necessary before executing the calculations. However in CityGML they have different scales for im- plementations called the Levels of Detail (LOD). Each five LODs are based on precisely in what way specific model required in different applications (Figure 9). Based on these LODs, LOD1 and LOD2 appear related to the scale model by less than 2 km resolution in urban air pollution dispersion model. LOD1 is the well-known blocks model comprising prismatic buildings with flat roofs. Meanwhile, a building in LOD2 has differentiated roof structures and thematically differentiated surfaces. The generalizations of spatial objects for each LOD are described in Table 3.
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The impacts of air pollution, in particular the suspended particulate maters are considerably severe in and around a coal washery complex. The dust is generated significantly due to different operational units such as screening, crushing, loading & unloading, exposed piles and stock yards, thermal dryers and the dropping points of conveyer belts etc. The particulate maters generated during its operations are being transported by wind in downwind direction and disperse both horizontally and vertically. Further the pollutants have an adverse impact on the buildings, plants and other valuable receptors . As a result, the whole eco-system is disturbed and the fertility status of the soil around the coal washery complex is significantly changes with unpleasant impacts . Therefore it is very much warranted to estimate the emission of air quality from different sources of coal washery complexes using suitable statistical approach. Further the air quality in and around coal washery complexes has to be predicted using an appropriate air quality dispersion model, developed for multi-sources like elevated point source, area source, ground level point source and line source taking the terrain elevation factor and the effect of temperature variance into account.
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Al Mirfa is a coastal town on the Arabian Gulf located in the western part of Abu Dhabi. The population of Al Mirfa and the neighbouring areas is estimated at 15,000. The region is predominantly composed of one and two story buildings, and is surrounded by open desert with no critical obstacles affecting plume transport and diffusion which need to be incorporated into the modelling analy- sis. The plant is located about 4 km upwind of town, and is equipped with four gas turbines that each has a capac- ity of 48 MW. The facility also has a distillation plant with a maximum capacity of 37.7 million gallons per day (MGD). The distillation plant runs continuously on natu- ral gas and occasionally on diesel. In 2008, the plant burned 18,090 MSCf of gas and 14,238 gallons of diesel . The major air pollution emission sources in the Al Mirfa region are the stationary sources of the power plant stacks. The plant consists of 12 stacks with an average height of 60 m from the ground level .The area under investigation was defined prior to the modelling process. Four receptors locations considered to require specific references in the air dispersion modelling study were identified as presented in Figure 1, include the accom- modation camp and local facilities (1), private palace (2), residential villas (3) and Al Mirfa Hotel (4).
Abstract: The air pollution dispersion modelling via spatial analyses (Land Use Regression – LUR) is an alternative approach to the air quality assessment to the standard air pollution dispersion modelling techniques. Its advantages are mainly much simpler mathematical apparatus, quicker and simpler calculations and a possibility to incorporate other factors affecting pollutant’s concentration. The goal of the study was to model the PM10 particles dispersion modelling via spatial analyses v in Czech-Polish border area of Upper Silesian industrial agglomeration and compare results with results of the standard Gaussian dispersion model SYMOS’97. Results show that standard Gaussian model with the same data as the LUR model gives better results (determination coefficient 71% for Gaussian model to 48% for LUR model). When factors of the land cover and were included into the LUR model, the LUR model results were significantly improved (65% determination coefficient) to the level comparable with Gaussian model. The hybrid approach combining the Gaussian model with the LUR gives superior quality of results (65% determination coefficient).
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considered the time dependence of household emissions, by applying a 24 h-pattern, and we applied a function for outdoor temperature dependence to account for seasonal fluctuations. These functions were derived from energy use statistics. In this way, hourly household emissions were estimated from annual household emissions. Emissions from industrial sources do not contribute significantly to small-scale variations in air pollution con- centrations. Emissions from shipping are quite stable over time and also display relatively small temporal fluc- tuations. Therefore, these emissions were not adjusted for fixed temporal patterns. Nevertheless, even if some small-scale variations had occurred as a result of these emissions, the difference would have been corrected for in the next step (adjustment for hourly background concentrations).
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Noise pollution, both in large and small urban areas is regarded as a growing problem of communities. There are various factors that contribute to increase of noise levels. One of main factors is increasing urban population, which contributes to higher traffic volume and intensity. In most urban areas, the corridors are developed in a close proximity to residential areas, due to limited space thus increase the number of high rise buildings. Numerous countries have implemented new technologies to control noise pollution in urban areas.
The choice of the turbulent parameterization in the air pollution models has an important contribution in the calculation of the contaminant concentration in the PBL. Furthermore, the turbulent parameterization describe the diffusion and transport processes observed in the low atmosphere. The performance of each model depends on the way with that the turbulent parameters are related with the evolution of the turbulent patterns of the PBL. Two turbulent parameterizations in a three-dimensional Eulerian model were tested in this work. The model is based in the solution of the advection-diffusion equation. The solution is obtained applying the integral transform technique. The model was tested with integral and algebraic eddy diffusivities. The wind profile was represented by wind power and similarity law.
For the implementation of BRT there is a need for road widening. Road widening has not only been considered under the ambit of City Development Plan (CDP) for BRT but also for reducing traffic congestion on roads. The total budget for the implementation of road widening was around Rs. 1,340 Crores. Although the translation of such projects in terms of emissions inventory is relatively possible, the concentration estimates from those inventories is a great task. Experience of such dispersion models while evaluating use of AERMOD and sensitivity analysis has provided ample scope for the use of engineering estimates of such translation of emissions to ambient air concentration in Pune and was used here as a cumulative 15% rollback. The incidence and health valuation estimates are provided in Table 6.
available. We therefore used five categories of proxy air pol- lution metrics in this study, namely: 1) measurements from ambient monitoring stations, 2) predictions from a disper- sion model, 3) predictions from land use regression (LUR) models, 4) traffic density, and 5) distance to roadways. Monitor-based measurements provide the greatest tem- poral variability and reflect mostly regional emission sources (and to a lesser extent, local sources especially when monitors are surrounded by a high density of these, e.g. in Los Angeles County). The dispersion model predictions reflect local traffic emissions at a high spatial resolution but with a limited temporal variability. LUR predictions capture local traffic emissions but also local land use characteristics as well as regional traffic emissions. Traffic density and distance to roadways are crude proxies for primary emissions of traffic-related pollutants, but are easy to obtain and have been used in many epidemiological studies. These air pollution metrics have already been used in a previous epidemiological study of preeclampsia and preterm birth conducted in the same setting , although the present study further presents results according to distances to roadways.
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The two dispersion compensators, i.e. DCF and FBG are used for an 8 channel optical network and it is analyzed for 120 km distance. DCF employs three compensation methods which are pre, post and symmetrical and the FBG technique employs two compensation methods which re pre and post. Non Return to Zero modulation format is used and after simulation it is shown that the post FBG compensation method has better performance with maximum Q-factor and minimum BER value .
stabilizing the process and improving its efficiency through decreasing its variability. Clearly, SPC can be used for any process in different fields . In particular, ceramic tiles produced by manufacturing plants by new or traditional machines do not meet quality control standards because of improper quality control system by the managements. Seven SPC tools include: registration sheets, histogram, Pareto chart, cause and effect chart, dispersion chart, defects concentration chart, and control chart. These tools stabilize production processes and improve products quality . The data collected over the period of three months from a commercial tile manufacturing plant in city of Yazd in central desert part of Iran. The collected data included measurements of dimensions for different tile sizes over the selected period. This study attempts to implement SPC methodology in order to improve product quality in a ceramic tile manufacturing plant in city of Yazd. This factory has been manufacturing ceramic tiles in different sizes since 1974. There are 225 employees who are working in three shifts. The factory has four different lines for automatic press process. There are also two tunnel kilns for firing the ceramic tile products. This paper presents research work involved in determining the unwanted defects in different tiles produced in the manufacturing plant. The next section offers a discussion of materials and methods. Section 3 presents experimental results. The discussion is presented in Sections 4. Finally concluding remarks are presented in Section 5.
Abstract — Fibre Optics is one of the best transmission technologies in the recent years; however, dispersion limits its transmission distances. This paper presents effects of dispersion in optical links and demonstrates how dispersion compensation fibre (DCF) is used to compensate for the effect of dispersion in a single mode fibre transmission link. Two scenarios were demonstrated using Optisystem simulation tool; a transmission network without a DCF and another with DCF. Results showed that network without DCF was greatly affected by dispersion. The bit error ratio (BER) analysers showed high bit error ratio and very low quality factor (Q factor). This depicts that the pulses were spreading out in time as it propagates down the fibre due to dispersion. In the second scenario, DCFs were introduced in the network based on designed specifications and results showed that BER at each receiver was very low and some to the tone of e-25. Q factor obtained was high enough. The results reveal that with DCF, the effect of dispersion in single mode fibre is compensated for.
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In this paper proposed evaluated the chromatic dispersion compensation for a long-haul WDM transmission. A 4 channel optical network was modeled, simulated and analyzed at a 600 km distance using two chromatic dispersion compensators i.e. fiber Bragg grating (FBG) and dispersion compensated fiber (DCF). Subsequently the modulation scheme and also the traffic load are varied to determine the robustness of the compensators to sustain the changes imposed on the light wave optical system. This analysis concludes that the grating device seems to be the better compensating solution for the long haul narrowband transmission. In addition, the FBG is also able to sustain the changes in traffic load and modulation scheme much better than the DCF. It was interestingly noted that when the traffic load for the system was made to increase from 2.5Gb/s to 40Gb/s, the performance for the DCF compensated system deteriorated more in comparison to the FBG compensated system. Though both systems deteriorated, the FBG compensated system deteriorated much slower when the traffic load was increased.
It was observed that taking spatial dispersion into consideration may lead to qualitatively new phenomena not seen in conventional materials obeying classical optics (spatial dispersion is ignored). In particular, spatial dispersion can allow electromagnetic wave propagation with negative group velocity to occur, even when both the permittivity and permeability are positive [1, 2]. Such interesting behavior was originally anticipated in connection with natural materials in crystal form, where spatial dispersion is manifest, for example, in the phenomena of exciton. Recently, the same original conclusions in  were reinstated [3, 4]. It is still possible, however, to put the problem in a wider context by referring not only to natural crystals, but also to any type of artiﬁcial materials. To demonstrate the philosophy of the engineering approach, consider Fig. 1 where we take the medium function to be ( ω, k). The physics approach is illustrated in Fig. 1(a) where the starting stage is assuming certain models for the natural material under consideration (usually crystal). Then, Taylor
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DOI: 10.4236/opj.2017.710016 165 Optics and Photonics Journal Obviously, the Gauss distribution has been distorted. They are no longer symmetrical distributions and both have phase shifts consistent with  and as its authors have expected that, “if the dispersion effect was taken into account, the asymmetric modulation side-bands occur.” The reasons are that, item
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An examination of prominent OSS development platforms finds a high prevalence of defunct, dirty data (Howison and Crowston 2004). Moreover, OSS (like all software) may contain bugs (Gyimothy et al. 2005; Stamelos et al. 2002) and is vulnerable to misuse by actors that deliberately insert malicious code (Ransbotham 2010). Similarly, Wikis may contain incomplete, biased, manipulated, and erroneous information ( Holman Rector 2008; Kupferberg and Protus 2011; Lavasa et al. 2011). Given that virtually everyone, from students (Haigh 2011; Lim 2009) to professionals (Brokowski and Sheehan 2009; Miller and Murray 2010; Peoples 2009), turn to Wikis for information, frequent and persisting low-quality information is likely to spillover and impact society as whole. 16 In addition, frequent and persisting low-quality information is likely to reduce the trust we put in OC systems. Hence, the question of how these systems address pollution quickly before it spills over and causes mistrust is crucial to the lasting viability of the novel and innovative OC mode. Although extant research provides important empirical findings on some factors associated with OC system quality (Arazy et al. 2011; Arazy and Nov 2010; Kittur and Kraut 2008), it provides little theoretical insight on which OC governance practices best achieve timely resolution of quality issues as they arise.
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Coastal and estuarine ecosystems have been, and still are, heavily influenced by the human species through pollution and habitat loss throughout the world. This coastal pollution and its impacts have resulted in a number of environmental issues including the enrichment of enclosed waters with organic matter leading to eutrophication, pollution by chemicals such as oil, and sedimentation due to land-based activities. Over Eighty per cent of all marine pollution originates from land-based sources which are primarily industrial, agricultural and urban. Pollution accompanies most kinds of human activities, including offshore oil and gas production and marine oil transportation. Most marine animals, particularly marine mammals and fish, are very sensitive to pollution. Decreased species diversity in whales and dolphins was related to an increase in heavy pollution. Many marine species have been shown to be impacted by various pollution to some degree. So, oceanic pollution must be managed both nationally and internationally in a precautionary way before irreversible damage to biodiversity and the marine ecosystem occurs.
Pollution of air in Bangladesh is the most significant environmental pollution. Air pollution from coal-fired power plants is huge and contributes to a negative envi- ronmental and health effects. When coal is burned to generate electricity, the combustion releases a combina- tion of toxic chemicals into the environment. Its combus- tion releases nitrogen oxides, sulfur dioxide, particulate matter (PM), mercury, and dozens of other substances known to be hazardous to environment. Carbon dioxide is a big component of air pollution. It is responsible for Global warming. The dangers of global warming include disruption of Bangladesh weather patterns and ecosys- tems, flooding, severe storms, and droughts. A warming climate will also extend the range of infectious diseases. That is why people living besides power stations are af- fected mostly.