830 resultados para emission control


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A catalyst comprising a catalytic material supported on a support, characterized in that the support comprises particles predominantly having a max. particle size of less than 1000 nm and an aspect ratio of greater than, and the. catalytic material is mainly present in the form of discrete islands of catalytic material supported on the support, with a substantial proportion of the islands of catalytic material being sep. and isolated from other islands of catalytic material. The islands of catalytic material are sep. and isolated from other islands of catalytic material such that diffusion and growth of the islands of catalytic material at elevated temp. is minimized or avoided. The disclosure and examples pertain to emission control catalysts. [on SciFinder(R)]

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A method for forming a material comprising a metal oxide supported on a support particle comprising the steps of: (a) providing a precursor mixt. comprising a soln. contg. one or more metal cations and (i) a surfactant; or (ii) a hydrophilic polymer; said precursor mixt. further including support particles; and (b) treating the precursor mixt. from (a) above by heating to remove the surfactant or hydrophilic polymer and form metal oxide having nanosized grains, wherein at least some of the metal oxide formed in step (b) is deposited on or supported by the support particles and the metal oxide has an oxide matrix that includes metal atoms derived solely from sources other than the support particles. The disclosure and examples pertain to emission control catalysts. [on SciFinder(R)]

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This paper tested the effects of the 2005 vehicle emission-control law issued in Japan on the market linkages between the U.S. and Japanese palladium futures markets, To determine these effects, we applied a cointegration test both with and without break points in the time series and found that the market linkages between the two countries changed after the break in October 2005. Our results show that the 2005 long-term regulation of vehicle emissions enacted in Japan influenced the international palladium futures market.

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Though increased particulate air pollution has been consistently associated with elevated mortality, evidence regarding whether diminished particulate air pollution would lead to mortality reduction is limited. Citywide air pollution mitigation program during the 2010 Asian Games in Guangzhou, China, provided such an opportunity. Daily mortality from non-accidental, cardiovascular and respiratory diseases was compared for 51 intervention days (November 1–December 21) in 2010 with the same calendar date of baseline years (2006–2009 and 2011). Relative risk (RR) and 95% confidence interval (95% CI) were estimated using a time series Poisson model, adjusting for day of week, public holidays, daily mean temperature and relative humidity. Daily PM10 (particle with aerodynamic diameter less than 10 μm) decreased from 88.64 μg/m3 during the baseline period to 80.61 μg/m3 during the Asian Games period. Other measured air pollutants and weather variables did not differ substantially. Daily mortality from non-accidental, cardiovascular and respiratory diseases decreased from 32, 11 and 6 during the baseline period to 25, 8 and 5 during the Games period, the corresponding RR for the Games period compared with the baseline period was 0.79 (95% CI: 0.73–0.86), 0.77 (95% CI: 0.66–0.89) and 0.68 (95% CI: 0.57–0.80), respectively. No significant decreases were observed in other months of 2010 in Guangzhou and intervention period in two control cities. This finding supports the efforts to reduce air pollution and improve public health through transportation restriction and industrial emission control.

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The Mobile Emissions Assessment System for Urban and Regional Evaluation (MEASURE) model provides an external validation capability for hot stabilized option; the model is one of several new modal emissions models designed to predict hot stabilized emission rates for various motor vehicle groups as a function of the conditions under which the vehicles are operating. The validation of aggregate measurements, such as speed and acceleration profile, is performed on an independent data set using three statistical criteria. The MEASURE algorithms have proved to provide significant improvements in both average emission estimates and explanatory power over some earlier models for pollutants across almost every operating cycle tested.

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Despite of a significant contribution of transport sector in the global economy and society, it is one of the largest sources of global energy consumption, green house gas emissions and environmental pollutions. A complete look onto the whole life cycle environmental inventory of this sector will be helpful to generate a holistic understanding of contributory factors causing emissions. Previous studies were mainly based on segmental views which mostly compare environmental impacts of different modes of transport, but very few consider impacts other than the operational phase. Ignoring the impacts of non-operational phases, e.g., manufacture, construction, maintenance, may not accurately reflect total contributions on emissions. Moreover an integrated study for all motorized modes of road transport is also needed to achieve a holistic estimation. The objective of this study is to develop a component based life cycle inventory model which considers impacts of both operational and non-operational phases of the whole life as well as different transport modes. In particular, the whole life cycle of road transport has been segmented into vehicle, infrastructure, fuel and operational components and inventories have been conducted on each component. The inventory model has been demonstrated using the road transport of Singapore. Results show that total life cycle green house gas emissions from the road transport sector of Singapore is 7.8 million tons per year, among which operational phase and non-operational phases contribute about 55% and about 45%, respectively. Total amount of criteria air pollutants are 46, 8.5, 33.6, 13.6 and 2.6 thousand tons per year for CO, SO2, NOx, VOC and PM10, respectively. From the findings, it can be deduced that stringent government policies on emission control measures have a significant impact on reducing environmental pollutions. In combating global warming and environmental pollutions the promotion of public transport over private modes is an effective sustainable policy.

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Particulate matter is common in our environment and has been linked to human health problems particularly in the ultrafine size range. A range of chemical species have been associated with particulate matter and of special concern are the hazardous chemicals that can accentuate health problems. If the sources of such particles can be identified then strategies can be developed for the reduction of air pollution and consequently, the improvement of the quality of life. In this investigation, particle number size distribution data and the concentrations of chemical species were obtained at two sites in Brisbane, Australia. Source apportionment was used to determine the sources (or factors) responsible for the particle size distribution data. The apportionment was performed by Positive Matrix Factorisation (PMF) and Principal Component Analysis/Absolute Principal Component Scores (PCA/APCS), and the results were compared with information from the gaseous chemical composition analysis. Although PCA/APCS resolved more sources, the results of the PMF analysis appear to be more reliable. Six common sources identified by both methods include: traffic 1, traffic 2, local traffic, biomass burning, and two unassigned factors. Thus motor vehicle related activities had the most impact on the data with the average contribution from nearly all sources to the measured concentrations higher during peak traffic hours and weekdays. Further analyses incorporated the meteorological measurements into the PMF results to determine the direction of the sources relative to the measurement sites, and this indicated that traffic on the nearby road and intersection was responsible for most of the factors. The described methodology which utilised a combination of three types of data related to particulate matter to determine the sources could assist future development of particle emission control and reduction strategies.

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A novel electrochemical route is used to form highly {111}-oriented and size-controlled Au nanoprisms directly onto the electrodes of quartz crystal microbalances (QCMs) which are subsequently used as mercury vapor sensors. The Au nanoprism loaded QCM sensors exhibited excellent response–concentration linearity with a response enhancement of up to ~ 800% over a non-modified sensor at an operating temperature of 28 °C. The increased surface area and atomic-scale features (step/defect sites) introduced during the growth of nanoprisms are thought to play a significant role in enhancing the sensing properties of the Au nanoprisms toward Hg vapor. The sensors are shown to have excellent Hg sensing capabilities in the concentration range of 0.123–1.27 ppmv (1.02–10.55 mg m − 3), with a detection limit of 2.4 ppbv (0.02 mg m − 3) toward Hg vapor when operating at 28 °C, and 17 ppbv (0.15 mg m − 3) at 89 °C, making them potentially useful for air monitoring applications or for monitoring the efficiency of Hg emission control systems in industries such as mining and waste incineration. The developed sensors exhibited excellent reversible behavior (sensor recovery) within 1 h periods, and crucially were also observed to have high selectivity toward Hg vapor in the presence of ethanol, ammonia and humidity, and excellent long-term stability over a 33 day operating period.

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A catalyst comprising a catalytic material supported on a support, characterized in that the support comprises particles predominantly having a max. particle size of less than 1000 nm and an aspect ratio of greater than, and the. catalytic material is mainly present in the form of discrete islands of catalytic material supported on the support, with a substantial proportion of the islands of catalytic material being sep. and isolated from other islands of catalytic material. The islands of catalytic material are sep. and isolated from other islands of catalytic material such that diffusion and growth of the islands of catalytic material at elevated temp. is minimized or avoided. The disclosure and examples pertain to emission control catalysts. [on SciFinder(R)]

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Over recent decades, efforts have been made to reduce human exposure to atmospheric pollutants including polycyclic aromatic hydrocarbons (PAHs) and polychlorinated biphenyls (PCBs) through emission control and abatement. Along with the potential changes in their concentrations resulting from these efforts, profiles of emission sources may have also changed over such extended timeframes. However relevant data are quite limited in the Southern Hemisphere. We revisited two sampling sites in an Australian city, where the concentration data in 1994/5 for atmospheric PAHs and PCBs were available. Monthly air samples from July 2013 to June 2014 at the two sites were collected and analysed for these compounds, using similar protocols to the original study. A prominent seasonal pattern was observed for PAHs with elevated concentrations in cooler months whereas PCB levels showed little seasonal variation. Compared to two decades ago, atmospheric concentrations of ∑13 PAHs (gaseous + particle-associated) in this city have decreased by approximately one order of magnitude and the apparent halving time ( t 1 / 2 ) was estimated as 6.2 ± 0.56 years. ∑6 iPCBs concentrations (median value; gaseous + particle-associated) have decreased by 80% with an estimated t 1 / 2 of 11 ± 2.9 years. These trends and values are similar to those reported for comparable sites in the Northern Hemisphere. To characterise emission source profiles, samples were also collected from a bushfire event and within a vehicular tunnel. Emissions from bushfires are suggested to be an important contributor to the current atmospheric concentrations of PAHs in this city. This contribution is more important in cooler months, i.e. June, July and August, and its importance may have increased over the last two decades.

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The overall aim of our research was to characterize airborne particles from selected nanotechnology processes and to utilize the data to develop and test quantitative particle concentration-based criteria that can be used to trigger an assessment of particle emission controls. We investigated particle number concentration (PNC), particle mass (PM) concentration, count median diameter (CMD), alveolar deposited surface area, elemental composition, and morphology from sampling of aerosols arising from six nanotechnology processes. These included fibrous and non-fibrous particles, including carbon nanotubes (CNTs). We adopted standard occupational hygiene principles in relation to controlling peak emission and exposures, as outlined by both Safe Work Australia, (1) and the American Conference of Governmental Industrial Hygienists (ACGIH®). (2) The results from the study were used to analyses peak and 30-minute averaged particle number and mass concentration values measured during the operation of the nanotechnology processes. Analysis of peak (highest value recorded) and 30-minute averaged particle number and mass concentration values revealed: Peak PNC20–1000 nm emitted from the nanotechnology processes were up to three orders of magnitude greater than the local background particle concentration (LBPC). Peak PNC300–3000 nm was up to an order of magnitude greater, and PM2.5 concentrations up to four orders of magnitude greater. For three of these nanotechnology processes, the 30-minute average particle number and mass concentrations were also significantly different from the LBPC (p-value < 0.001). We propose emission or exposure controls may need to be implemented or modified, or further assessment of the controls be undertaken, if concentrations exceed three times the LBPC, which is also used as the local particle reference value, for more than a total of 30 minutes during a workday, and/or if a single short-term measurement exceeds five times the local particle reference value. The use of these quantitative criteria, which we are terming the universal excursion guidance criteria, will account for the typical variation in LBPC and inaccuracy of instruments, while precautionary enough to highlight peaks in particle concentration likely to be associated with particle emission from the nanotechnology process. Recommendations on when to utilize local excursion guidance criteria are also provided.

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Structural health monitoring (SHM) is the term applied to the procedure of monitoring a structure’s performance, assessing its condition and carrying out appropriate retrofitting so that it performs reliably, safely and efficiently. Bridges form an important part of a nation’s infrastructure. They deteriorate due to age and changing load patterns and hence early detection of damage helps in prolonging the lives and preventing catastrophic failures. Monitoring of bridges has been traditionally done by means of visual inspection. With recent developments in sensor technology and availability of advanced computing resources, newer techniques have emerged for SHM. Acoustic emission (AE) is one such technology that is attracting attention of engineers and researchers all around the world. This paper discusses the use of AE technology in health monitoring of bridge structures, with a special focus on analysis of recorded data. AE waves are stress waves generated by mechanical deformation of material and can be recorded by means of sensors attached to the surface of the structure. Analysis of the AE signals provides vital information regarding the nature of the source of emission. Signal processing of the AE waveform data can be carried out in several ways and is predominantly based on time and frequency domains. Short time Fourier transform and wavelet analysis have proved to be superior alternatives to traditional frequency based analysis in extracting information from recorded waveform. Some of the preliminary results of the application of these analysis tools in signal processing of recorded AE data will be presented in this paper.

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Acoustic emission (AE) technique is a popular tool used for structural health monitoring of civil, mechanical and aerospace structures. It is a non-destructive method based on rapid release of energy within a material by crack initiation or growth in the form of stress waves. Recording of these waves by means of sensors and subsequent analysis of the recorded signals convey information about the nature of the source. Ability to locate the source of stress waves is an important advantage of AE technique; but as AE waves travel in various modes and may undergo mode conversions, understanding of the modes (‘modal analysis’) is often necessary in order to determine source location accurately. This paper presents results of experiments aimed at finding locations of artificial AE sources on a thin plate and identifying wave modes in the recorded signal waveforms. Different source locating techniques will be investigated and importance of wave mode identification will be explored.

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Acoustic emission (AE) technique is one of the popular diagnostic techniques used for structural health monitoring of mechanical, aerospace and civil structures. But several challenges still exist in successful application of AE technique. This paper explores various tools for analysis of recorded AE data to address two primary challenges: discriminating spurious signals from genuine signals and devising ways to quantify damage levels.

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The mineral nesquehonite Mg(OH)(HCO3)•2H2O has been analysed by a combination of infrared (IR) and infrared emission spectroscopy (IES). Both techniques show OH vibrations, both stretching and deformation modes. IES proves the OH units are stable up to 450°C. The strong IR band at 934 cm-1 is evidence for MgOH deformation modes supporting the concept of HCO3- units in the molecular structure. Infrared bands at 1027, 1052 and 1098 cm-1 are attributed to the symmetric stretching modes of HCO3- and CO32- units. Infrared bands at 1419, 1439, 1511, and 1528 cm-1 are assigned to the antisymmetric stretching modes of CO32- and HCO3- units. IES supported by thermoanalytical results defines the thermal stability of nesquehonite IES defines the changes in the molecular structure of nesquehonite with temperature. The results of IR and IES supports the concept that the formula of nesquehonite is better defined as Mg(OH)(HCO3)•2H2O.