Particle number emissions from a large fleet of diesel and CNG buses

Exhaust emissions were monitored in real-time at the kerb of a busy busway used by a mix of diesel and CNG-powered transport buses. Particle number concentration in the size range 3 nm to 3 µm was measured with a TSI condensation particle counter (CPC 3025). Particle mass (PM2.5) was measured with a TSI Dustrak 8520. The CO2 emissions were measured with a fast response CO2 analyser (Sable CA-10A). All emission concentrations were recorded in real time at 1 sec resolution, together with the precise passage times of buses. The instantaneous ratio of particle number (or mass) to CO2 concentration, denoted Z, was used as a measure of the particle number (or mass) emission factor of each passing bus.

Defining the spatiotemporal surveillance space for alien species’ invasions using approximate Bayesian computation

The spatiotemporal dynamics of an alien species invasion across a real landscape are typically complex. While surveillance is an essential part of a management response, planning surveillance in space and time present a difficult challenge due to this complexity. We show here a method for determining the highest probability sites for occupancy across a landscape at an arbitrary point in the future, based on occupancy data from a single slice in time. We apply to the method to the invasion of Giant Hogweed, a serious weed in the Czech republic and throughout Europe.

Using informative priors in the estimation of mixtures over time with application to aerosol particle size distributions

The issue of using informative priors for estimation of mixtures at multiple time points is examined. Several different informative priors and an independent prior are compared using samples of actual and simulated aerosol particle size distribution (PSD) data. Measurements of aerosol PSDs refer to the concentration of aerosol particles in terms of their size, which is typically multimodal in nature and collected at frequent time intervals. The use of informative priors is found to better identify component parameters at each time point and more clearly establish patterns in the parameters over time. Some caveats to this finding are discussed.

Nano and ultrafine particle number concentrations in different environments : application towards air quality regulations

Particle number concentrations vary significantly with environment and, in this study, we attempt to assess the significance of these differences. Towards this aim, we reviewed 85 papers that have reported particle number concentrations levels at 126 sites covering different environments. We grouped the results into eight categories according to measurement location including: road tunnel, on-road, road-side, street canyon, urban, urban background, rural, and clean background. From these reports, the overall median number concentration for each of the eight site categories was calculated. The eight location categories may be classified into four distinct groups. The mean median particle number locations for these four types were found to be statistically different from each other. Rural and clean background sites had the lowest concentrations of about 3x103 cm-3. Urban and urban background sites showed concentrations that were three times higher (9x103 cm-3). The mean concentration for the street canyon, roadside and on-road measurement sites was 4.6x104 cm-3, while the highest concentrations were observed in the road tunnels (8.6x104 cm-3). This variation is important when assessing human exposure-response for which there is very little data available, making it difficult to develop health guidelines, a basis for national regulations. Our analyses shows that the current levels in environments affected by vehicle emissions are 3 to 28 times higher than in the natural environments. At present, there is no threshold level in response to exposure to ultrafine particles. Therefore, future control and management strategies should target a decrease of these particles in urban environments by more than one order of magnitude to bring them down to the natural background. At present there is a long way to go to achieve this.

Comparison of particle number concentrations between different environments

Particle number concentrations vary significantly with environment and, in this study, we attempt to assess the significance of these differences. Towards this aim, we reviewed 85 papers that have reported particle number concentrations levels at 126 sites covering different environments. We grouped the results into eight categories according to measurement location including: road tunnel, on-road, road-side, street canyon, urban, urban background, rural, and clean background. Median values were calculated for each category. This review was restricted to papers that presented concentrations numerically. The majority of the reports were based on either CPC or SMPS measurements, with a limited number of papers reporting results from both instruments at the same site. Hence there were several overlaps between the number of CPC and SMPS measuring sites. Most of the studies reported multiple measurements at a given study site, while some studies included results from more than one site. From these reports, the overall median value for each location category was calculated...

Vertical graphene nanosheets coated with gold nanoparticle arrays: Effect of inter-particle spacing on optical response

Vertical graphene nanosheets have advantages over their horizontal counterparts, primarily due to the larger surface area available in the vertical systems. Vertical sheets can accommodate more functional particles, and due to the conduction and optical properties of thin graphene, these structures can find niche applications in the development of sensing and energy storage devices. This work is a combined experimental and theoretical study that reports on the synthesis and optical responses of vertical sheets decorated with gold nanoparticles. The findings help in interpreting optical responses of these hybrid graphene structures and are relevant to the development of future sensing platforms.

Use of the biolistic particle delivery system to transform fungal genomes

Biolistic delivery of transforming DNA into fungal genomes, especially when performed on uninucleate haploid conidia, has proven successful in bypassing the time-consuming repetitive purification of protoplasts used for the widely applied polyethylene glycol-mediated method. Biolistic transformation is also relatively quick compared to other available methods and provides a high percentage of stable transformants.

Interpreting scratch assays using pair density dynamics and approximate Bayesian computation

Quantifying the impact of biochemical compounds on collective cell spreading is an essential element of drug design, with various applications including developing treatments for chronic wounds and cancer. Scratch assays are a technically simple and inexpensive method used to study collective cell spreading; however, most previous interpretations of scratch assays are qualitative and do not provide estimates of the cell diffusivity, D, or the cell proliferation rate,l. Estimating D and l is important for investigating the efficacy of a potential treatment and provides insight into the mechanism through which the potential treatment acts. While a few methods for estimating D and l have been proposed, these previous methods lead to point estimates of D and l, and provide no insight into the uncertainty in these estimates. Here, we compare various types of information that can be extracted from images of a scratch assay, and quantify D and l using discrete computational simulations and approximate Bayesian computation. We show that it is possible to robustly recover estimates of D and l from synthetic data, as well as a new set of experimental data. For the first time, our approach also provides a method to estimate the uncertainty in our estimates of D and l. We anticipate that our approach can be generalized to deal with more realistic experimental scenarios in which we are interested in estimating D and l, as well as additional relevant parameters such as the strength of cell-to-cell adhesion or the strength of cell-to-substrate adhesion.

Particle size distribution effects on preferential deposition areas in metal foam wrapped tube bundle

This paper presents a numerical model for understanding particle transport and deposition in metal foam heat exchangers. Two-dimensional steady and unsteady numerical simulations of a standard single row metal foam-wrapped tube bundle are performed for different particle size distributions, i.e. uniform and normal distributions. Effects of different particle sizes and fluid inlet velocities on the overall particle transport inside and outside the foam layer are also investigated. It was noted that the simplification made in the previously-published numerical works in the literature, e.g. uniform particle deposition in the foam, is not necessarily accurate at least for the cases considered here. The results highlight the preferential particle deposition areas both along the tube walls and inside the foam using a developed particle deposition likelihood matrix. This likelihood matrix is developed based on three criteria being particle local velocity, time spent in the foam, and volume fraction. It was noted that the particles tend to deposit near both front and rear stagnation points. The former is explained by the higher momentum and direct exposure of the particles to the foam while the latter only accommodate small particles which can be entrained in the recirculation region formed behind the foam-wrapped tubes.

Approximate Bayesian Computation for astronomical model analysis : a case study in galaxy demographics and morphological transformation at high redshift

Approximate Bayesian Computation’ (ABC) represents a powerful methodology for the analysis of complex stochastic systems for which the likelihood of the observed data under an arbitrary set of input parameters may be entirely intractable – the latter condition rendering useless the standard machinery of tractable likelihood-based, Bayesian statistical inference [e.g. conventional Markov chain Monte Carlo (MCMC) simulation]. In this paper, we demonstrate the potential of ABC for astronomical model analysis by application to a case study in the morphological transformation of high-redshift galaxies. To this end, we develop, first, a stochastic model for the competing processes of merging and secular evolution in the early Universe, and secondly, through an ABC-based comparison against the observed demographics of massive (Mgal > 1011 M⊙) galaxies (at 1.5 < z < 3) in the Cosmic Assembly Near-IR Deep Extragalatic Legacy Survey (CANDELS)/Extended Groth Strip (EGS) data set we derive posterior probability densities for the key parameters of this model. The ‘Sequential Monte Carlo’ implementation of ABC exhibited herein, featuring both a self-generating target sequence and self-refining MCMC kernel, is amongst the most efficient of contemporary approaches to this important statistical algorithm. We highlight as well through our chosen case study the value of careful summary statistic selection, and demonstrate two modern strategies for assessment and optimization in this regard. Ultimately, our ABC analysis of the high-redshift morphological mix returns tight constraints on the evolving merger rate in the early Universe and favours major merging (with disc survival or rapid reformation) over secular evolution as the mechanism most responsible for building up the first generation of bulges in early-type discs.