Air Pollution Emission Inventory Survey for Israel

High ozone levels are regularly measured during summer months over the inland and mountainous regions of Israel. Studies analyzing the back trajectories of air masses responsible for the high ozone levels showed that the precursors originated from the densely populated Israeli coastline. In order to better understand the contribution of those emission sources to ozone production, it is essential to have an accurate emission inventory that can be inputted into a photochemical model. The present paper describes the methods used in preparing an emission inventory for Israel based on information available and published until 1998. The source and accuracy of the data available are described. The calculations performed and the assumptions taken in order to obtain data not directly available are clarified. The sources reported in the inventory were the major polluters (power plants, oil refineries, and cement industries); industry; transportation; and biogenic sources. The pollutants studied were SO₂, NO_x, CO, saturated and unsaturated hydrocarbons, ethylene, isoprene, toluene, xylene, formaldehyde, and aldehydes. The inventory showed that transportation is responsible for almost the entire CO and 30% of the volatile organic compounds emitted, although transportation itself accounts for only a fifth of total fuel consumption. About 75% of the NO_x emitted can be attributed to industrial sources and the remaining 25% to transportation. Model simulations using the emission inventory were performed and compared to data available from a monitoring station situated 30 km east of Tel Aviv. The results showed good agreement, validating the accuracy of the emission inventory. The present emission inventory provides an important database as input to photochemical models used in forecasting ozone levels over Israel.     

Development and numerical validation of a new model for walls with phase change materials implemented in TRNSYS

This paper presents a model of a wall with variable properties dedicated to modelling phase change materials (PCMs) in building envelopes. The model is implemented in the TRNSYS simulation tool and referred to as Type 3258. The 1-D conduction heat transfer equation is solved using an explicit finite-difference method coupled with an enthalpy method to consider the variable PCM thermal capacity. This model includes temperature-dependent thermal conductivity and PCM-specific effects like hysteresis and supercooling. The stability conditions are discussed and the algorithm implemented in TRNSYS is described. A numerical validation performed on wall test cases proposed by the International Energy Agency is presented, showing that the developed model is in agreement with reference models. The paper also discusses the impact of temporal and spatial discretization on the model performance. Modelling problems encountered when using an effective heat capacity method (compared to an enthalpy method) and when representing supercooling are also discussed.     

High-damping carbon nanotube hinged micromirrors

New developments in digital mirror devices (DMDs) require suspension hinges with a good damping and high temperature stability. Carbon nanotubes (CNTs) offer these unique properties. Herein it is shown how CNT hinges can be integrated in micromirrors. The image illustrates a micromirror with a CNT suspension, and a typical overdamped stepresponse (Q-factor < 0.5).     

Modal dynamics in multimode fibers

The dynamics of modes and their states of polarizations in multimode fibers as a function of time, space, and wavelength are experimentally and theoretically investigated. The results reveal that the states of polarizations are displaced in Poincaré sphere representation when varying the angular orientations of the polarization at the incident light. Such displacements, which complicate the interpretation of the results, are overcome by resorting to modified Poincaré sphere representation. With such modification it should be possible to predict the output modes and their state of polarization when the input mode and state of polarization are known.     

Preparation and characterization of magnetic carbon nanomaterials bearing APTS–silica on their surface

The formation of metal-encapsulated carbon nanomaterials by using metallic catalysts (iron, cobalt, and nickel) has been studied. Moreover, these materials were coated with silica surface modified by (3-Aminopropyl)-trimethoxysilane (APTS). Each intermediate structure was confirmed by X-ray diffraction (XRD) and transmission electron microscopy (TEM). The surface morphology of silica-coated carbon nanomaterials was analyzed by scanning electron microscopy (SEM). The modified, APTS–silica surface was additionally characterized by Fourier transform infrared spectroscopy (FT-IR), elemental (EA), and thermogravimetric analysis (TGA).     

In vivo optic nerve head biomechanics: performance testing of a three-dimensional tracking algorithm

Measurement of optic nerve head (ONH) deformations could be useful in the clinical management of glaucoma. Here, we propose a novel three-dimensional tissue-tracking algorithm designed to be used in vivo. We carry out preliminary verification of the algorithm by testing its accuracy and its robustness. An algorithm based on digital volume correlation was developed to extract ONH tissue displacements from two optical coherence tomography (OCT) volumes of the ONH (undeformed and deformed). The algorithm was tested by applying artificial deformations to a baseline OCT scan while manipulating speckle noise, illumination and contrast enhancement. Tissue deformations determined by our algorithm were compared with the known (imposed) values. Errors in displacement magnitude, orientation and strain decreased with signal averaging and were 0.15 µm, 0.15° and 0.0019, respectively (for optimized algorithm parameters). Previous computational work suggests that these errors are acceptable to provide in vivo characterization of ONH biomechanics. Our algorithm is robust to OCT speckle noise as well as to changes in illumination conditions, and increasing signal averaging can produce better results. This algorithm has potential be used to quantify ONH three-dimensional strains in vivo, of benefit in the diagnosis and identification of risk factors in glaucoma.     

Modeling microbial populations with the original and modified versions of the continuous and discrete logistic equations

The life histories of microbial populations, under favorable and adverse conditions, exhibit a variety of growth, decay, and fluctuation patterns. They have been described by numerous mathematical models that varies considerably in structure and number of constants. The continuous logistic equation alone and combined with itself or with its mirror image, the Fermi function, can produce many of the observed growth patterns. They include those that are traditionally described by the Gompertz equation and peaked curves, with the peak being symmetric or asymmetric narrow or wide. The shape of survival and dose response curves appears to be determined by the distribution of the resistance's to the lethal agent among the individual organisms. Thus, exponential decay and Fermian or Gompertz‐type curves can be considered manifestations of skewed to the right, symmetric, and skewed to the left distributions, respectively.

Because of the mathematical constraints and determinism, the original discrete logistic equation can rarely be an adequate model of real microbial populations. However, by making its proportionality constant a normal‐random variate it can simulate realistic histories of fluctuating microbial populations, including scenarios of aperiodic population explosions of varying intensities of the kind found in food‐poisoning episodes.