Shoot growth dynamics and photosynthetic response to increased nitrogen availability in the alpine willow salix-glauca

Plants subjected to increases in the supply of resource(s) limiting growth may allocate more of those resources to existing leaves, increasing photosynthetic capacity, and/or to production of more leaves, increasing whole-plant photosynthesis. The responses of three populations of the alpine willow, Salix glauca, growing along an alpine topographic sequence representing a gradient in soil moisture and organic matter, and thus potential N supply, to N amendments, were measured over two growing seasons, to elucidate patterns of leaf versus shoot photosynthetic responses. Leaf-(foliar N, photosynthesis rates, photosynthetic N-use efficiency) and shoot-(leaf area per shoot, number of leaves per shoot, stem weight, N resorption efficiency) level measurements were made to examine the spatial and temporal variation in these potential responses to increased N availability. The predominant response of the willows to N fertilization was at the shoot-level, by production of greater leaf area per shoot. Greater leaf area occurred due to production of larger leaves in both years of the experiment and to production of more leaves during the second year of fertilization treatment. Significant leaf-level photosynthetic response occurred only during the first year of treatment, and only in the dry meadow population. Variation in photosynthesis rates was related more to variation in stomatal conductance than to foliar N concentration. Stomatal conductance in turn was significantly related to N fertilization. Differences among the populations in photosynthesis, foliar N, leaf production, and responses to N fertilization indicate N availability may be lowest in the dry meadow population, and highest in the ridge population. This result is contrary to the hypothesis that a gradient of plant available N corresponds with a snowpack/topographic gradient.

An alginate-based hybrid system for growth factor delivery in the functional repair of large bone defects

The treatment of challenging fractures and large osseous defects presents a formidable problem for orthopaedic surgeons. Tissue engineering/regenerative medicine approaches seek to solve this problem by delivering osteogenic signals within scaffolding biomaterials. In this study, we introduce a hybrid growth factor delivery system that consists of an electrospun nanofiber mesh tube for guiding bone regeneration combined with peptide-modified alginate hydrogel injected inside the tube for sustained growth factor release. We tested the ability of this system to deliver recombinant bone morphogenetic protein-2 (rhBMP-2) for the repair of critically-sized segmental bone defects in a rat model. Longitudinal [mu]-CT analysis and torsional testing provided quantitative assessment of bone regeneration. Our results indicate that the hybrid delivery system resulted in consistent bony bridging of the challenging bone defects. However, in the absence of rhBMP-2, the use of nanofiber mesh tube and alginate did not result in substantial bone formation. Perforations in the nanofiber mesh accelerated the rhBMP-2 mediated bone repair, and resulted in functional restoration of the regenerated bone. [mu]-CT based angiography indicated that perforations did not significantly affect the revascularization of defects, suggesting that some other interaction with the tissue surrounding the defect such as improved infiltration of osteoprogenitor cells contributed to the observed differences in repair. Overall, our results indicate that the hybrid alginate/nanofiber mesh system is a promising growth factor delivery strategy for the repair of challenging bone injuries.

Urban growth monitoring techniques for sustainable development

This paper discusses the role of advance techniques for monitoring urban growth and change for sustainable development of urban environment. It also presents results of a case study involving satellite data for land use/land cover classification of Lucknow city using IRS-1C multi-spectral features. Two classification algorithms have been used in the study. Experiments were conducted to see the level of improvement in digital classification of urban environment using Artificial Neural Network (ANN) technique.

Integrated sustainable urban infrastructure management: the Brisbane urban growth model

Sustainable urban development and the liveability of a city are increasingly important issues in the context of land use planning and infrastructure management. In recent years, the promotion of sustainable urban development in Australia and overseas is facing various physical, socio-economic and environmental challenges. These challenges and problems arise from the lack of capability of local governments to accommodate the needs of the population and economy in a relatively short timeframe. The planning of economic growth and development is often dealt with separately and not included in the conventional land use planning process. There is also a sharp rise in the responsibilities and roles of local government for infrastructure planning and management. This increase in responsibilities means that local elected officials and urban planners have less time to prepare background information and make decisions. The Brisbane Urban Growth Model has proven initially successful in providing a dynamic platform to ensure timely and coordinated delivery of urban infrastructure. Most importantly, this model is the first step for local governments in moving toward a systematic approach to pursuing sustainable and effective urban infrastructure management.

Corona ions from overhead transmission voltage powerlines : effect on DC e-field and ambient particle concentration levels

Along with their essential role in electricity transmission and distribution, some powerlines also generate large concentrations of corona ions. This study aimed at comprehensive investigation of corona ions, vertical dc e-field, ambient aerosol particle charge and particle number concentration levels in the proximity of some high/sub-transmission voltage powerlines. The influence of meteorology on the instantaneous value of these parameters, and the possible existence of links or associations between the parameters measured were also statistically investigated. The presence of positive and negative polarities of corona ions was associated with variation in the mean vertical dc e-field, ambient ion and particle charge concentration level. Though these variations increased with wind speed, their values also decreased with distance from the powerlines. Predominately positive polarities of ions were recorded up to a distance of 150 m (with the maximum values recorded 50 m downwind of the powerlines). At 200 m from the source, negative ions predominated. Particle number concentration levels however remained relatively constant (103 particle cm-3) irrespective of the sampling site and distance from the powerlines. Meteorological factors of temperature, humidity and wind direction showed no influence on the electrical parameters measured. The study also discovered that e-field measurements were not necessarily a true representation of the ground-level ambient ion/particle charge concentrations.

The organic fraction of bubble-generated, accumulation mode Sea Spray Aerosol (SSA)

Recent studies have detected a dominant accumulation mode (~100 nm) in the Sea Spray Aerosol (SSA) number distribution. There is evidence to suggest that particles in this mode are composed primarily of organics. To investigate this hypothesis we conducted experiments on NaCl, artificial SSA and natural SSA particles with a Volatility-Hygroscopicity-Tandem-Differential-Mobility-Analyser (VH-TDMA). NaCl particles were atomiser generated and a bubble generator was constructed to produce artificial and natural SSA particles. Natural seawater samples for use in the bubble generator were collected from biologically active, terrestrially-affected coastal water in Moreton Bay, Australia. Differences in the VH-TDMA-measured volatility curves of artificial and natural SSA particles were used to investigate and quantify the organic fraction of natural SSA particles. Hygroscopic Growth Factor (HGF) data, also obtained by the VH-TDMA, were used to confirm the conclusions drawn from the volatility data. Both datasets indicated that the organic fraction of our natural SSA particles evaporated in the VH-TDMA over the temperature range 170–200°C. The organic volume fraction for 71–77 nm natural SSA particles was 8±6%. Organic volume fraction did not vary significantly with varying water residence time (40 secs to 24 hrs) in the bubble generator or SSA particle diameter in the range 38–173 nm. At room temperature we measured shape- and Kelvin-corrected HGF at 90% RH of 2.46±0.02 for NaCl, 2.35±0.02 for artifical SSA and 2.26±0.02 for natural SSA particles. Overall, these results suggest that the natural accumulation mode SSA particles produced in these experiments contained only a minor organic fraction, which had little effect on hygroscopic growth. Our measurement of 8±6% is an order of magnitude below two previous measurements of the organic fraction in SSA particles of comparable sizes. We stress that our results were obtained using coastal seawater and they can’t necessarily be applied on a regional or global ocean scale. Nevertheless, considering the order of magnitude discrepancy between this and previous studies, further research with independent measurement techniques and a variety of different seawaters is required to better quantify how much organic material is present in accumulation mode SSA.

Effect of cabin ventilation rate on ultrafine particle exposure inside automobiles

We alternately measured on-road and in-vehicle ultrafine (<100 nm) particle (UFP) concentration for 5 passenger vehicles that comprised an age range of 18 years. A range of cabin ventilation settings were assessed during 301 trips through a 4 km road tunnel in Sydney, Australia. Outdoor airflow(ventilation) rates under these settings were quantified on open roads using tracer gas techniques. Significant variability in tunnel trip average median in-cabin/on-road (I/O) UFP ratios was observed (0.08 to ∼1.0). Based on data spanning all test automobiles and ventilation settings, a positive linear relationship was found between outdoor air flow rate and I/O ratio, with the former accounting for a substantial proportion of variation in the latter (R2 ) 0.81). UFP concentrations recorded in cabin during tunnel travel were significantly higher than those reported by comparable studies performed on open roadways. A simple mathematical model afforded the ability to predict tunnel trip average in-cabin UFP concentrations with good accuracy. Our data indicate that under certain conditions, in-cabin UFP exposures incurred during tunnel travel may contribute significantly to daily exposure. The UFP exposure of automobile occupants appears strongly related to their choice of ventilation setting and vehicle.

Critical analysis of high particle number emissions from accelerating compressed natural gas buses

Compressed natural gas (CNG) engines are thought to be less harmful to the environment than conventional diesel engines, especially in terms of particle emissions. Although, this is true with respect to particulate matter (PM) emissions, results of particle number (PN) emission comparisons have been inconclusive. In this study, results of on-road and dynamometer studies of buses were used to derive several important conclusions. We show that, although PN emissions from CNG buses are significantly lower than from diesel buses at low engine power, they become comparable at high power. For diesel buses, PN emissions are not significantly different between acceleration and operation at steady maximum power. However, the corresponding PN emissions from CNG buses when accelerating are an order of magnitude greater than when operating at steady maximum power. During acceleration under heavy load, PN emissions from CNG buses are an order of magnitude higher than from diesel buses. The particles emitted from CNG buses are too small to contribute to PM10 emissions or contribute to a reduction of visibility, and may consist of semivolatile nanoparticles.

Observation of the suppression of water uptake by marine particles

A 4 week intensive measurement campaign was conducted in March–April 2007 at Agnes Water, a remote coastal site on the east coast of Australia. A Volatility-Hygroscopicity-Tandem Differential Mobility Analyser (VH-TDMA) was used to investigate changes in the hygroscopic properties of ambient particles as volatile components were progressively evaporated. Nine out of 18 VH-TDMA volatility scans detected internally mixed multi-component particles in the nucleation and Aitken modes in clean marine air. Evaporation of a volatile, organic-like component in the VH-TDMA caused significant increases in particle hygroscopicity. In 3 scans the increase in hygroscopicity was so large it was explained by an increase in the absolute volume of water uptake by the particle residuals, and not merely an increase in their relative hygroscopicity. This indicates 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). This observation was supported by ZSR calculations for one scan, which showed that the measured growth factors of mixed particles were up to 18% below those predicted assuming independent water uptake of the individual particle components. The observed suppression of water uptake could be due to a reduced rate of hygroscopic growth caused by the presence of organic films or organic-inorganic interactions in solution droplets that had a negative effect on hygroscopicity.

Derivation of motor vehicle tailpipe particle emission factors suitable for modelling urban fleet emissions and air quality assessments

Background, aim, and scope Urban motor vehicle fleets are a major source of particulate matter pollution, especially of ultrafine particles (diameters < 0.1 µm), and exposure to particulate matter has known serious health effects. A considerable body of literature is available on vehicle particle emission factors derived using a wide range of different measurement methods for different particle sizes, conducted in different parts of the world. Therefore the choice as to which are the most suitable particle emission factors to use in transport modelling and health impact assessments presented as a very difficult task. The aim of this study was to derive a comprehensive set of tailpipe particle emission factors for different vehicle and road type combinations, covering the full size range of particles emitted, which are suitable for modelling urban fleet emissions. Materials and methods A large body of data available in the international literature on particle emission factors for motor vehicles derived from measurement studies was compiled and subjected to advanced statistical analysis, to determine the most suitable emission factors to use in modelling urban fleet emissions. Results This analysis resulted in the development of five statistical models which explained 86%, 93%, 87%, 65% and 47% of the variation in published emission factors for particle number, particle volume, PM1, PM2.5 and PM10 respectively. A sixth model for total particle mass was proposed but no significant explanatory variables were identified in the analysis. From the outputs of these statistical models, the most suitable particle emission factors were selected. This selection was based on examination of the statistical robustness of the statistical model outputs, including consideration of conservative average particle emission factors with the lowest standard errors, narrowest 95% confidence intervals and largest sample sizes, and the explanatory model variables, which were Vehicle Type (all particle metrics), Instrumentation (particle number and PM2.5), Road Type (PM10) and Size Range Measured and Speed Limit on the Road (particle volume). Discussion A multiplicity of factors need to be considered in determining emission factors that are suitable for modelling motor vehicle emissions, and this study derived a set of average emission factors suitable for quantifying motor vehicle tailpipe particle emissions in developed countries. Conclusions The comprehensive set of tailpipe particle emission factors presented in this study for different vehicle and road type combinations enable the full size range of particles generated by fleets to be quantified, including ultrafine particles (measured in terms of particle number). These emission factors have particular application for regions which may have a lack of funding to undertake measurements, or insufficient measurement data upon which to derive emission factors for their region. Recommendations and perspectives In urban areas motor vehicles continue to be a major source of particulate matter pollution and of ultrafine particles. It is critical that in order to manage this major pollution source methods are available to quantify the full size range of particles emitted for traffic modelling and health impact assessments.

Characterization of particle number concentrations and PM2.5 in a school : influence of outdoor air pollution on indoor air

Background, Aim and Scope The impact of air pollution on school children’s health is currently one of the key foci of international and national agencies. Of particular concern are ultrafine particles which are emitted in large quantities, contain large concentrations of toxins and are deposited deeply in the respiratory tract. Materials and methods In this study, an intensive sampling campaign of indoor and outdoor airborne particulate matter was carried out in a primary school in February 2006 to investigate indoor and outdoor particle number (PN) and mass concentrations (PM2.5), and particle size distribution, and to evaluate the influence of outdoor air pollution on the indoor air. Results For outdoor PN and PM2.5, early morning and late afternoon peaks were observed on weekdays, which are consistent with traffic rush hours, indicating the predominant effect of vehicular emissions. However, the temporal variations of outdoor PM2.5 and PN concentrations occasionally showed extremely high peaks, mainly due to human activities such as cigarette smoking and the operation of mower near the sampling site. The indoor PM2.5 level was mainly affected by the outdoor PM2.5 (r = 0.68, p<0.01), whereas the indoor PN concentration had some association with outdoor PN values (r = 0.66, p<0.01) even though the indoor PN concentration was occasionally influenced by indoor sources, such as cooking, cleaning and floor polishing activities. Correlation analysis indicated that the outdoor PM2.5 was inversely correlated with the indoor to outdoor PM2.5 ratio (I/O ratio) (r = -0.49, p<0.01), while the indoor PN had a weak correlation with the I/O ratio for PN (r = 0.34, p<0.01). Discussion and Conclusions The results showed that occupancy did not cause any major changes to the modal structure of particle number and size distribution, even though the I/O ratio was different for different size classes. The I/O curves had a maximum value for particles with diameters of 100 – 400 nm under both occupied and unoccupied scenarios, whereas no significant difference in I/O ratio for PM2.5 was observed between occupied and unoccupied conditions. Inspection of the size-resolved I/O ratios in the preschool centre and the classroom suggested that the I/O ratio in the preschool centre was the highest for accumulation mode particles at 600 nm after school hours, whereas the average I/O ratios of both nucleation mode and accumulation mode particles in the classroom were much lower than those of Aitken mode particles. Recommendations and Perspectives The findings obtained in this study are useful for epidemiological studies to estimate the total personal exposure of children, and to develop appropriate control strategies for minimizing the adverse health effects on school children.

Exposure to particle number, surface area and PM concentrations in pizzerias

The aim of this work was to quantify exposure to particles emitted by wood-fired ovens in pizzerias. Overall, 15 microenvironments were chosen and analyzed in a 14-month experimental campaign. Particle number concentration and distribution were measured simultaneously using a Condensation Particle Counter (CPC), a Scanning Mobility Particle Sizer (SMPS), an Aerodynamic Particle Sizer (APS). The surface area and mass distributions and concentrations, as well as the estimation of lung deposition surface area and PM1 were evaluated using the SMPS-APS system with dosimetric models, by taking into account the presence of aggregates on the basis of the Idealized Aggregate (IA) theory. The fraction of inhaled particles deposited in the respiratory system and different fractions of particulate matter were also measured by means of a Nanoparticle Surface Area Monitor (NSAM) and a photometer (DustTrak DRX), respectively. In this way, supplementary data were obtained during the monitoring of trends inside the pizzerias. We found that surface area and PM1 particle concentrations in pizzerias can be very high, especially when compared to other critical microenvironments, such as the transport hubs. During pizza cooking under normal ventilation conditions, concentrations were found up to 74, 70 and 23 times higher than background levels for number, surface area and PM1, respectively. A key parameter is the oven shape factor, defined as the ratio between the size of the face opening in respect

Development of a composite line source emission model for traffic interrupted microenvironments and its application in particle number emissions at a bus station

A composite line source emission (CLSE) model was developed to specifically quantify exposure levels and describe the spatial variability of vehicle emissions in traffic interrupted microenvironments. This model took into account the complexity of vehicle movements in the queue, as well as different emission rates relevant to various driving conditions (cruise, decelerate, idle and accelerate), and it utilised multi-representative segments to capture the accurate emission distribution for real vehicle flow. Hence, this model was able to quickly quantify the time spent in each segment within the considered zone, as well as the composition and position of the requisite segments based on the vehicle fleet information, which not only helped to quantify the enhanced emissions at critical locations, but it also helped to define the emission source distribution of the disrupted steady flow for further dispersion modelling. The model then was applied to estimate particle number emissions at a bi-directional bus station used by diesel and compressed natural gas fuelled buses. It was found that the acceleration distance was of critical importance when estimating particle number emission, since the highest emissions occurred in sections where most of the buses were accelerating and no significant increases were observed at locations where they idled. It was also shown that emissions at the front end of the platform were 43 times greater than at the rear of the platform. Although the CLSE model is intended to be applied in traffic management and transport analysis systems for the evaluation of exposure, as well as the simulation of vehicle emissions in traffic interrupted microenvironments, the bus station model can also be used for the input of initial source definitions in future dispersion models.

Freeway traffic estimation in Beijing based on particle filter

Short-term traffic flow data is characterized by rapid and dramatic fluctuations. It reflects the nature of the frequent congestion in the lane, which shows a strong nonlinear feature. Traffic state estimation based on the data gained by electronic sensors is critical for much intelligent traffic management and the traffic control. In this paper, a solution to freeway traffic estimation in Beijing is proposed using a particle filter, based on macroscopic traffic flow model, which estimates both traffic density and speed.Particle filter is a nonlinear prediction method, which has obvious advantages for traffic flows prediction. However, with the increase of sampling period, the volatility of the traffic state curve will be much dramatic. Therefore, the prediction accuracy will be affected and difficulty of forecasting is raised. In this paper, particle filter model is applied to estimate the short-term traffic flow. Numerical study is conducted based on the Beijing freeway data with the sampling period of 2 min. The relatively high accuracy of the results indicates the superiority of the proposed model.

Ubiquitous and smart system approaches to infrastructure planning : learnings from Korea, Japan and Hong Kong

The robust economic growth across South East Asia and the significant advances in nano-technologies in the past two decades have resulted in the creation of intelligent urban infrastructures. Cities like Seoul, Tokyo and Hong Kong have been competing against each other to develop the first ‘ubiquitous city’, a strategic global node of science and technology that provides all municipal services for residents and visitors via ubiquitous infrastructures. This chapter scrutinises the development of ubiquitous and smart infrastructure in Korea, Japan and Hong Kong. These cases provide invaluable learnings for policy-makers and urban and infrastructure planners when considering adopting these systems approaches in their cities.