42 resultados para NOx SCR


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The US Clean Air Act Amendments introduce an emissions trading system to regulate SO2 emissions. This study finds that changes in SO2 emissions prices are related to innovations induced by these amendments. We find that electricity-generating plants are able to increase electricity output and reduce emissions of SO2 and NOx from 1995 to 2007 due to the introduction of the allowance trading system. However, compared to the approximate 8% per year of exogenous technological progress, the induced effect is relatively small, and the contribution of the induced effect to overall technological progress is about 1-2%.

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This research measured particle and gaseous emissions from ships and trains operating within the Port of Brisbane, and explored their influence on ambient air composition at a downwind suburban measurement site. The ship and train emission factor investigations resulted in the development of novel measurement techniques which permit the quantification of particle and gaseous emission factors using samples collected from post-emission exhaust plumes. The urban influence investigation phase of the project produced a new approach to identifying influences from ship emissions.

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In this study, the biodiesel properties and effects of blends of oil methyl ester petroleum diesel on a CI direct injection diesel engine is investigated. Blends were obtained from the marine dinoflagellate Crypthecodinium cohnii and waste cooking oil. The experiment was conducted using a four-cylinder, turbo-charged common rail direct injection diesel engine at four loads (25%, 50%, 75% and 100%). Three blends (10%, 20% and 50%) of microalgae oil methyl ester and a 20% blend of waste cooking oil methyl ester were compared to petroleum diesel. To establish suitability of the fuels for a CI engine, the effects of the three microalgae fuel blends at different engine loads were assessed by measuring engine performance, i.e. mean effective pressure (IMEP), brake mean effective pressure (BMEP), in cylinder pressure, maximum pressure rise rate, brake-specific fuel consumption (BSFC), brake thermal efficiency (BTE), heat release rate and gaseous emissions (NO, NOx,and unburned hydrocarbons (UHC)). Results were then compared to engine performance characteristics for operation with a 20% waste cooking oil/petroleum diesel blend and petroleum diesel. In addition, physical and chemical properties of the fuels were measured. Use of microalgae methyl ester reduced the instantaneous cylinder pressure and engine output torque, when compared to that of petroleum diesel, by a maximum of 4.5% at 50% blend at full throttle. The lower calorific value of the microalgae oil methyl ester blends increased the BSFC, which ultimately reduced the BTE by up to 4% at higher loads. Minor reductions of IMEP and BMEP were recorded for both the microalgae and the waste cooking oil methyl ester blends at low loads, with a maximum of 7% reduction at 75% load compared to petroleum diesel. Furthermore, compared to petroleum diesel, gaseous emissions of NO and NOx, increased for operations with biodiesel blends. At full load, NO and NOx emissions increased by 22% when 50% microalgae blends were used. Petroleum diesel and a 20% blend of waste cooking oil methyl ester had emissions of UHC that were similar, but those of microalgae oil methyl ester/petroleum diesel blends were reduced by at least 50% for all blends and engine conditions. The tested microalgae methyl esters contain some long-chain, polyunsaturated fatty acid methyl esters (FAMEs) (C22:5 and C22:6) not commonly found in terrestrial-crop-derived biodiesels yet all fuel properties were satisfied or were very close to the ASTM 6751-12 and EN14214 standards. Therefore, Crypthecodinium cohnii- derived microalgae biodiesel/petroleum blends of up to 50% are projected to meet all fuel property standards and, engine performance and emission results from this study clearly show its suitability for regular use in diesel engines.

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Non-thermal plasma (NTP) is a promising candidate for controlling engine exhaust emissions. Plasma is known as the fourth state of matter, where both electrons and positive ions co-exist. Both gaseous and particle emissions of diesel exhaust undergo chemical changes when they are exposed to plasma. In this project diesel particulate matter (DPM) mitigation from the actual diesel exhaust by using NTP technology has been studied. The effect of plasma, not only on PM mass but also on PM size distribution, physico-chemical structure of PM and PM removal mechanisms, has been investigated. It was found that NTP technology can significantly reduce both PM mass and number. However, under some circumstances particles can be formed by nucleation. Energy required to create the plasma with the current technology is higher than the benchmark set by the commonly used by the automotive industry. Further research will enable the mechanism of particle creation and energy consumption to be optimised.

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Measurements of aerosol particle number size distributions (15-700 nm), CO and NOx were performed in a bus tunnel, Australia. Daily mean particle size distributions of mixed diesel/CNG (Compressed Natural Gas) buses traffic flow were determined in 4 consecutive measurement days. EFs (Emission Factors) of Particle size distribution of diesel buses and CNG buses were obtained by MLR (Multiple Linear Regression) methods, particle distributions of diesel buses and CNG buses were observed as single accumulation mode and nuclei-mode separately. Particle size distributions of mixed traffic flow were decomposed by two log-normal fitting curves for each 30 minutes interval mean scans, all the mix fleet PSD emission can be well fitted by the summation of two log-normal distribution curves, and these were composed of nuclei mode curve and accumulation curve, which were affirmed as the CNG buses and diesel buses PN emission curves respectively. Finally, particle size distributions of diesel buses and CNG buses were quantified by statistical whisker-box charts. For log-normal particle size distribution of diesel buses, accumulation mode diameters were 74.5~87.5nm, geometric standard deviations were 1.89~1.98. As to log-normal particle size distribution of CNG buses, nuclei-mode diameters were 21~24 nm, geometric standard deviations were 1.27~1.31.

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Objective Self-report measures are typically used to assess the effectiveness of road safety advertisements. However, psychophysiological measures of persuasive processing (i.e., skin conductance response [SCR]) and objective driving measures of persuasive outcomes (i.e., in-vehicle GPS devices) may provide further insights into the effectiveness of these advertisements. This study aimed to explore the persuasive processing and outcomes of two anti-speeding advertisements by incorporating both self-report and objective measures of speeding behaviour. In addition, this study aimed to compare the findings derived from these different measurement approaches. Methods Young drivers (N = 20, Mage = 21.01 years) viewed either a positive or negative emotion-based anti-speeding television advertisement. Whilst viewing the advertisement, SCR activity was measured to assess ad-evoked arousal responses. The RoadScout® GPS device was then installed into participants’ vehicles for one week to measure on-road speed-related driving behaviour. Self-report measures assessed persuasive processing (emotional and arousal responses) and actual driving behaviour. Results There was general correspondence between the self-report measures of arousal and the SCR and between the self-report measure of actual driving behaviour and the objective driving data (as assessed via the GPS devices). Conclusions This study provides insights into how psychophysiological and GPS devices could be used as objective measures in conjunction with self-report measures to further understand the persuasive processes and outcomes of emotion-based anti-speeding advertisements.

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Atmospheric pressure gas plasma (AGP) generates reactive oxygen species (ROS) that induce apoptosis in cultured cancer cells. The majority of cancer cells develop a ROS-scavenging anti-oxidant system regulated by Nrf2, which confers resistance to ROS-mediated cancer cell death. Generation of ROS is involved in the AGP-induced cancer cell death of several colorectal cancer cells (Caco2, HCT116 and SW480) by activation of ASK1-mediated apoptosis signaling pathway without affecting control cells (human colonic sub-epithelial myofibroblasts; CO18, human fetal lung fibroblast; MRC5 and fetal human colon; FHC). However, the identity of an oxidase participating in AGP-induced cancer cell death is unknown. Here, we report that AGP up-regulates the expression of Nox2 (NADPH oxidase) to produce ROS. RNA interference designed to target Nox2 effectively inhibits the AGP-induced ROS production and cancer cell death. In some cases both colorectal cancer HT29 and control cells showed resistance to AGP treatment. Compared to AGP-sensitive Caco2 cells, HT29 cells show a higher basal level of the anti-oxidant system transcriptional regulator Nrf2 and its target protein sulfiredoxin (Srx) which are involved in cellular redox homeostasis. Silencing of both Nrf2 and Srx sensitized HT29 cells, leads to ROS overproduction and decreased cell viability. This indicates that in HT29 cells, Nrf2/Srx axis is a protective factor against AGP-induced oxidative stress. The inhibition of Nrf2/Srx signaling should be considered as a central target in drug-resistant colorectal cancer treatments.

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There are numerous load estimation methods available, some of which are captured in various online tools. However, most estimators are subject to large biases statistically, and their associated uncertainties are often not reported. This makes interpretation difficult and the estimation of trends or determination of optimal sampling regimes impossible to assess. In this paper, we first propose two indices for measuring the extent of sampling bias, and then provide steps for obtaining reliable load estimates by minimizing the biases and making use of possible predictive variables. The load estimation procedure can be summarized by the following four steps: - (i) output the flow rates at regular time intervals (e.g. 10 minutes) using a time series model that captures all the peak flows; - (ii) output the predicted flow rates as in (i) at the concentration sampling times, if the corresponding flow rates are not collected; - (iii) establish a predictive model for the concentration data, which incorporates all possible predictor variables and output the predicted concentrations at the regular time intervals as in (i), and; - (iv) obtain the sum of all the products of the predicted flow and the predicted concentration over the regular time intervals to represent an estimate of the load. The key step to this approach is in the development of an appropriate predictive model for concentration. This is achieved using a generalized regression (rating-curve) approach with additional predictors that capture unique features in the flow data, namely the concept of the first flush, the location of the event on the hydrograph (e.g. rise or fall) and cumulative discounted flow. The latter may be thought of as a measure of constituent exhaustion occurring during flood events. The model also has the capacity to accommodate autocorrelation in model errors which are the result of intensive sampling during floods. Incorporating this additional information can significantly improve the predictability of concentration, and ultimately the precision with which the pollutant load is estimated. We also provide a measure of the standard error of the load estimate which incorporates model, spatial and/or temporal errors. This method also has the capacity to incorporate measurement error incurred through the sampling of flow. We illustrate this approach using the concentrations of total suspended sediment (TSS) and nitrogen oxide (NOx) and gauged flow data from the Burdekin River, a catchment delivering to the Great Barrier Reef. The sampling biases for NOx concentrations range from 2 to 10 times indicating severe biases. As we expect, the traditional average and extrapolation methods produce much higher estimates than those when bias in sampling is taken into account.

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Non-thermal plasma (NTP) has been introduced over the last few years as a promising after- treatment system for nitrogen oxides and particulate matter removal from diesel exhaust. NTP technology has not been commercialised as yet, due to its high rate of energy consumption. Therefore, it is important to seek out new methods to improve NTP performance. Residence time is a crucial parameter in engine exhaust emissions treatment. In this paper, different electrode shapes are analysed and the corresponding residence time and NOx removal efficiency are studied. An axisymmetric laminar model is used for obtaining residence time distribution numerically using FLUENT software. If the mean residence time in a NTP plasma reactor increases, there will be a corresponding increase in the reaction time and consequently the pollutant removal efficiency increases. Three different screw thread electrodes and a rod electrode are examined. The results show the advantage of screw thread electrodes in comparison with the rod electrode. Furthermore, between the screw thread electrodes, the electrode with the thread width of 1 mm has the highest NOx removal due to higher residence time and a greater number of micro-discharges. The results show that the residence time of the screw thread electrode with a thread width of 1 mm is 21% more than for the rod electrode.

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Physical and chemical properties of biofuels vary among various feedstocks and their subsequent conversions to fuels. The biofuels contain various amounts of oxygen, and this has a significant influence on exhaust emission. This oxygen content has been considered in order to investigate its effect on diesel engine exhaust emissions. The experiments have been conducted with a heavy duty diesel engine and various oxygenated fuels. It is found that the amount of oxygen in the fuel has a high level of influence on its exhaust emissions, and this provides agreement with diesel emissions results such as PN reduction. By increasing the amount of oxygen in the blend (by adding more biofuel), the particulate number (PN) is reduced and NOx increases gradually. However, the variation of PN and NOx are not similar for waste cooking biodiesel (WCBD) and butanol blend, even though their oxygen content are the same in the blends. This is due to the source of the biofuel and their internal chemistry.

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Ambient ultrafine particle number concentrations (PNC) have inhomogeneous spatio-temporal distributions and depend on a number of different urban factors, including background conditions and distant sources. This paper quantitatively compares exposure to ambient ultrafine particles at urban schools in two cities in developed countries, with high insolation climatic conditions, namely Brisbane (Australia) and Barcelona (Spain). The analysis used comprehensive indoor and outdoor air quality measurements at 25 schools in Brisbane and 39 schools in Barcelona. PNC modes were analysed with respect to ambient temperature, land use and urban characteristics, combined with the measured elemental carbon concentrations, NOx (Brisbane) and NO2 (Barcelona). The trends and modes of the quantified weekday average daily cycles of ambient PNC exhibited significant differences between the two cities. PNC increases were observed during traffic rush hours in both cases. However, the mid-day peak was dominant in Brisbane schools and had the highest contribution to total PNC for both indoors and outdoors. In Barcelona, the contribution from traffic was highest for ambient PNC, while the mid-day peak had a slightly higher contribution for indoor concentrations. Analysis of the relationships between PNC and land use characteristics in Barcelona schools showed a moderate correlation with the percentage of road network area and an anti-correlation with the percentage of green area. No statistically significant correlations were found for Brisbane. Overall, despite many similarities between the two cities, school-based exposure patterns were different. The main source of ambient PNC at schools was shown to be traffic in Barcelona and mid-day new particle formation in Brisbane. The mid-day PNC peak in Brisbane could have been driven by the combined effect of background and meteorological conditions, as well as other local/distant sources. The results have implications for urban development, especially in terms of air quality mitigation and management at schools.

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Multipotent neural stem cells (NSCs) provide a model to investigate neurogenesis and develop mechanisms of cell transplantation. In order to define improved markers of stemness and lineage specificity, we examined self-renewal and multi-lineage markers during long-term expansion and under neuronal and astrocyte differentiating conditions in human ESC-derived NSCs (hNSC H9 cells). In addition, with proteoglycans ubiquitous to the neural niche, we also examined heparan sulfate proteoglycans (HSPGs) and their regulatory enzymes. Our results demonstrate that hNSC H9 cells maintain self-renewal and multipotent capacity during extended culture and express HS biosynthesis enzymes and several HSPG core protein syndecans (SDCs) and glypicans (GPCs) at a high level. In addition, hNSC H9 cells exhibit high neuronal and a restricted glial differentiative potential with lineage differentiation significantly increasing expression of many HS biosynthesis enzymes. Furthermore, neuronal differentiation of the cells upregulated SDC4, GPC1, GPC2, GPC3 and GPC6 expression with increased GPC4 expression observed under astrocyte culture conditions. Finally, downregulation of selected HSPG core proteins altered hNSC H9 cell lineage potential. These findings demonstrate an involvement for HSPGs in mediating hNSC maintenance and lineage commitment and their potential use as novel markers of hNSC and neural cell lineage specification.