Dissolved inorganic carbon and CO2 fluxes across Jiaozhou Bay air-water interface

On the basis of data collected in the Jiaozhou Bay in June and July 2003, the DIC distribution in seawater is studied, and an average air-sea flux of CO2 is estimated. The results show that the content of DIC inside the bay is markedly higher than outside the bay in June, but the content of DIC outside the bay is markedly higher than inside the bay in July. The trend of DIC distribution inside the bay is similar, viz. the content is the maximum in the northeast, then decreases gradually toward the west, and the content is the minimum in the west. The total trend of vertical distribution is to increase gradually from surface to bottom. This characteristic of DIC distribution is determined by Jiaozhou Bay hydrology and there is a close relation between DIC and particulate N,P. Average CO2 flux across the air-sea interface is 0.55 mol/(m(2.)a) in June and 0.72 mol/(m(2.)a) in July. Jiaozhou Bay is considered as a net annual source for atmospheric CO2 in June and July, and the total CO2 flux from seawater into atmosphere is about 740 t in June and 969 t in July.

Dissolved oxygen and O-2 flux across the water-air interface of the Changjiang Estuary in May 2003

The field observation of this study was carried out in the Changjiang Estuary from May 19 to 26,2003, just a few days before the Three Gorges Dam began to store water. A total of 29 stations, including 2 anchor stations, were distributed through almost the whole salinity gradient Based on the data gained from these stations, the biogeochemical characteristics of dissolved oxygen (DO) were examined. Spatial distribution of DO concentrations showed the pattern that it increased in a downriver direction. DO concentration generally varied within a narrow range of 733-8.10 mg l(-1) in the freshwater region and the west part of the mixed water region, and after that it increased rapidly. In vertical direction, the differences in DO concentrations between surface and 2 m above the bottom were big at the stations with water depths exceeding 20 m; DO concentration up to 14.88 mg l(-1) was recorded at the sea surface, while at 2 m above the bottom its concentration was only about 4 mg l(-1). The fluctuation in DO concentrations was small during a period of 48 h in the mixed water region and 2 m above the bottom of the seawater region; while it was large during the same period in the seawater region for surface and 5 m below the surface layer, and a maximum variation from 8.77 to 12.66 mg l(-1) in 4 h was recorded. Oxygen fluxes also showed a marked spatio-temporal variation. As a whole, the freshwater region and mixed water region were an oxygen sink while the seawater region was a source. Relationships between dissolved oxygen and some biogeochemical parameters which could markedly influence its spatio-temporal distribution were discussed in this paper. (C) 2008 Elsevier B.V. All rights reserved.

pCO(2) and carbon fluxes across sea-air interface in the Changjiang Estuary and Hangzhou Bay

Partial pressure of CO2 (pCO(2)) was investigated in the Changjiang (Yangtze River) Estuary, Hangzhou Bay and their adjacent areas during a cruise in August 2004, China. The data show that pCO(2) in surface waters of the studied area was higher than that in the atmosphere with only exception of a patch east of Zhoushan Archipelago. The pCO(2) varied from 168 to 2 264 mu atm, which fell in the low range compared with those of other estuaries in the world. The calculated sea-air CO2 fluxes decreased offshore and varied from -10.0 to 88.1 mmol m(-2) d(-1) in average of 24.4 +/- 16.5 mmol m(-2) d(-1). Although the area studied was estimated only 2 x 10(4) km(2), it emitted (5.9 +/- 4.0) x 10(3) tons of carbon to the atmosphere every day. The estuaries and their plumes must be further studied for better understanding the role of coastal seas playing in the global oceanic carbon cycle.

Assessment of metal contamination in surface sediments of Jiaozhou Bay, Qingdao, China

An assessment of metal contamination in surface sediments of the Jiaozhou Bay, Qingdao, one of the rapidly developing coastal economic zones in China, is provided. Sediments were collected from 10 stations and a total of 15 heavy metals were analyzed. Concentrations of metals show significant variability and range from 210 to 620 ppm for Ti, 2.7 to 23 ppm for Ni, 4.2 to 28 ppm for Cu, 5.2 to 18 ppm for Pb, 12 to 58 ppm for Zn, 0.03 to 0.11 ppm for Cd, 5 to 51 ppm for Cr, 1.5 to 9.9 ppm for Co, 5.3 to 19 ppm for As, 12 to 32 ppm for Se, and 19 to 97 ppm for Sr. Based on concentration relationships and enrichment factor (EF) analyses, the results indicate that sediment grain size and organic matter played important roles in controlling the distribution of the heavy metals in surface sediments of the Jiaozhou Bay. The study shows that the sediment of the Jiaozhou Bay has been contaminated by heavy metals to various degrees, with prominent arsenic contributing the most to the contamination. The analysis suggests that the major sources of metal contamination in the Jiaozhou Bay are land-based anthropogenic ones, such as discharge of industrial waste water and municipal sewage and run-off. Notably, the elevated heavy metal concentrations of the Jiaozhou Bay sediments could have a significant impact on the bay's ecosystem. With the rapid economic development and urbanization around the Jiaozhou Bay, coastal management and pollution control should focus on these contaminant sources, as well as provide ongoing monitoring studies of heavy metal contamination within the bay.

A Neural Model of Surface Perception: Lightness, Anchoring, and Filling-in

This article develops a neural model of how the visual system processes natural images under variable illumination conditions to generate surface lightness percepts. Previous models have clarified how the brain can compute the relative contrast of images from variably illuminate scenes. How the brain determines an absolute lightness scale that "anchors" percepts of surface lightness to us the full dynamic range of neurons remains an unsolved problem. Lightness anchoring properties include articulation, insulation, configuration, and are effects. The model quantatively simulates these and other lightness data such as discounting the illuminant, the double brilliant illusion, lightness constancy and contrast, Mondrian contrast constancy, and the Craik-O'Brien-Cornsweet illusion. The model also clarifies the functional significance for lightness perception of anatomical and neurophysiological data, including gain control at retinal photoreceptors, and spatioal contrast adaptation at the negative feedback circuit between the inner segment of photoreceptors and interacting horizontal cells. The model retina can hereby adjust its sensitivity to input intensities ranging from dim moonlight to dazzling sunlight. A later model cortical processing stages, boundary representations gate the filling-in of surface lightness via long-range horizontal connections. Variants of this filling-in mechanism run 100-1000 times faster than diffusion mechanisms of previous biological filling-in models, and shows how filling-in can occur at realistic speeds. A new anchoring mechanism called the Blurred-Highest-Luminance-As-White (BHLAW) rule helps simulate how surface lightness becomes sensitive to the spatial scale of objects in a scene. The model is also able to process natural images under variable lighting conditions.

Laminar Cortical Dynamics of 3D Surface Perception: Stratification, transparency, and Neon Color Spreading

How does the laminar organization of cortical circuitry in areas VI and V2 give rise to 3D percepts of stratification, transparency, and neon color spreading in response to 2D pictures and 3D scenes? Psychophysical experiments have shown that such 3D percepts are sensitive to whether contiguous image regions have the same relative contrast polarity (dark-light or lightdark), yet long-range perceptual grouping is known to pool over opposite contrast polarities. The ocularity of contiguous regions is also critical for neon color spreading: Having different ocularity despite the contrast relationship that favors neon spreading blocks the spread. In addition, half visible points in a stereogram can induce near-depth transparency if the contrast relationship favors transparency in the half visible areas. It thus seems critical to have the whole contrast relationship in a monocular configuration, since splitting it between two stereogram images cancels the effect. What adaptive functions of perceptual grouping enable it to both preserve sensitivity to monocular contrast and also to pool over opposite contrasts? Aspects of cortical development, grouping, attention, perceptual learning, stereopsis and 3D planar surface perception have previously been analyzed using a 3D LAMINART model of cortical areas VI, V2, and V4. The present work consistently extends this model to show how like-polarity competition between VI simple cells in layer 4 may be combined with other LAMINART grouping mechanisms, such as cooperative pooling of opposite polarities at layer 2/3 complex cells. The model also explains how the Metelli Rules can lead to transparent percepts, how bistable transparency percepts can arise in which either surface can be perceived as transparent, and how such a transparency reversal can be facilitated by an attention shift. The like-polarity inhibition prediction is consistent with lateral masking experiments in which two f1anking Gabor patches with the same contrast polarity as the target increase the target detection threshold when they approach the target. It is also consistent with LAMINART simulations of cortical development. Other model explanations and testable predictions will also be presented.

A Neuromorphic Model for Achromatic and Chromatic Surface Representation of Natural Images

This study develops a neuromorphic model of human lightness perception that is inspired by how the mammalian visual system is designed for this function. It is known that biological visual representations can adapt to a billion-fold change in luminance. How such a system determines absolute lightness under varying illumination conditions to generate a consistent interpretation of surface lightness remains an unsolved problem. Such a process, called "anchoring" of lightness, has properties including articulation, insulation, configuration, and area effects. The model quantitatively simulates such psychophysical lightness data, as well as other data such as discounting the illuminant, the double brilliant illusion, and lightness constancy and contrast effects. The model retina embodies gain control at retinal photoreceptors, and spatial contrast adaptation at the negative feedback circuit between mechanisms that model the inner segment of photoreceptors and interacting horizontal cells. The model can thereby adjust its sensitivity to input intensities ranging from dim moonlight to dazzling sunlight. A new anchoring mechanism, called the Blurred-Highest-Luminance-As-White (BHLAW) rule, helps simulate how surface lightness becomes sensitive to the spatial scale of objects in a scene. The model is also able to process natural color images under variable lighting conditions, and is compared with the popular RETINEX model.

View-Invariant Object Category Learning, Recognition, and Search: How Spatial and Object Attention Are Coordinated Using Surface-Based Attentional Shrouds

Air Force Office of Scientific Research (F49620-01-1-0397); National Science Foundation (SBE-0354378); Office of Naval Research (N00014-01-1-0624)

A Neural Theory of Attentive Visual Search: Interactions of Boundary, Surface, Spatial, and Object Representations

Visual search data are given a unified quantitative explanation by a model of how spatial maps in the parietal cortex and object recognition categories in the inferotemporal cortex deploy attentional resources as they reciprocally interact with visual representations in the prestriate cortex. The model visual representations arc organized into multiple boundary and surface representations. Visual search in the model is initiated by organizing multiple items that lie within a given boundary or surface representation into a candidate search grouping. These items arc compared with object recognition categories to test for matches or mismatches. Mismatches can trigger deeper searches and recursive selection of new groupings until a target object io identified. This search model is algorithmically specified to quantitatively simulate search data using a single set of parameters, as well as to qualitatively explain a still larger data base, including data of Aks and Enns (1992), Bravo and Blake (1990), Chellazzi, Miller, Duncan, and Desimone (1993), Egeth, Viri, and Garbart (1984), Cohen and Ivry (1991), Enno and Rensink (1990), He and Nakayarna (1992), Humphreys, Quinlan, and Riddoch (1989), Mordkoff, Yantis, and Egeth (1990), Nakayama and Silverman (1986), Treisman and Gelade (1980), Treisman and Sato (1990), Wolfe, Cave, and Franzel (1989), and Wolfe and Friedman-Hill (1992). The model hereby provides an alternative to recent variations on the Feature Integration and Guided Search models, and grounds the analysis of visual search in neural models of preattentive vision, attentive object learning and categorization, and attentive spatial localization and orientation.

A Neural Model of 3D Shape-From-Texture: Multiple-Scale Filtering, Boundary Grouping, and Surface Filling-In

A neural model is presented of how cortical areas V1, V2, and V4 interact to convert a textured 2D image into a representation of curved 3D shape. Two basic problems are solved to achieve this: (1) Patterns of spatially discrete 2D texture elements are transformed into a spatially smooth surface representation of 3D shape. (2) Changes in the statistical properties of texture elements across space induce the perceived 3D shape of this surface representation. This is achieved in the model through multiple-scale filtering of a 2D image, followed by a cooperative-competitive grouping network that coherently binds texture elements into boundary webs at the appropriate depths using a scale-to-depth map and a subsequent depth competition stage. These boundary webs then gate filling-in of surface lightness signals in order to form a smooth 3D surface percept. The model quantitatively simulates challenging psychophysical data about perception of prolate ellipsoids (Todd and Akerstrom, 1987, J. Exp. Psych., 13, 242). In particular, the model represents a high degree of 3D curvature for a certain class of images, all of whose texture elements have the same degree of optical compression, in accordance with percepts of human observers. Simulations of 3D percepts of an elliptical cylinder, a slanted plane, and a photo of a golf ball are also presented.

From Stereograms to Surface: How the Brain Sees the World in Depth

When we look at a scene, how do we consciously see surfaces infused with lightness and color at the correct depths? Random Dot Stereograms (RDS) probe how binocular disparity between the two eyes can generate such conscious surface percepts. Dense RDS do so despite the fact that they include multiple false binocular matches. Sparse stereograms do so even across large contrast-free regions with no binocular matches. Stereograms that define occluding and occluded surfaces lead to surface percepts wherein partially occluded textured surfaces are completed behind occluding textured surfaces at a spatial scale much larger than that of the texture elements themselves. Earlier models suggest how the brain detects binocular disparity, but not how RDS generate conscious percepts of 3D surfaces. A neural model predicts how the layered circuits of visual cortex generate these 3D surface percepts using interactions between visual boundary and surface representations that obey complementary computational rules.

Ambient aerosol size distributions and number concentrations measured during the Pittsburgh Air Quality Study (PAQS)

Twelve months of aerosol size distributions from 3 to 560nm, measured using scanning mobility particle sizers are presented with an emphasis on average number, surface, and volume distributions, and seasonal and diurnal variation. The measurements were made at the main sampling site of the Pittsburgh Air Quality Study from July 2001 to June 2002. These are supplemented with 5 months of size distribution data from 0.5 to 2.5μm measured with a TSI aerosol particle sizer and 2 months of size distributions measured at an upwind rural sampling site. Measurements at the main site were made continuously under both low and ambient relative humidity. The average Pittsburgh number concentration (3-500nm) is 22,000cm-3 with an average mode size of 40nm. Strong diurnal patterns in number concentrations are evident as a direct effect of the sources of particles (atmospheric nucleation, traffic, and other combustion sources). New particle formation from homogeneous nucleation is significant on 30-50% of study days and over a wide area (at least a hundred kilometers). Rural number concentrations are a factor of 2-3 lower (on average) than the urban values. Average measured distributions are different from model literature urban and rural size distributions. © 2004 Elsevier Ltd. All rights reserved.

Pittsburgh air quality study overview

Ambient sampling for the Pittsburgh Air Quality Study (PAQS) was conducted from July 2001 to September 2002. The study was designed (1) to characterize particulate matter (PM) by examination of size, surface area, and volume distribution, chemical composition as a function of size and on a single particle basis, morphology, and temporal and spatial variability in the Pittsburgh region; (2) to quantify the impact of the various sources (transportation, power plants, biogenic sources, etc.) on the aerosol concentrations in the area; and (3) to develop and evaluate the next generation of atmospheric aerosol monitoring and modeling techniques. The PAQS objectives, study design, site descriptions and routine and intensive measurements are presented. Special study days are highlighted, including those associated with elevated concentrations of daily average PM2.5 mass. Monthly average and diurnal patterns in aerosol number concentration, and aerosol nitrate, sulfate, elemental carbon, and organic carbon concentrations, light scattering as well as gas-phase ozone, nitrogen oxides, and carbon monoxide are discussed with emphasis on the processes affecting them. Preliminary findings reveal day-to-day variability in aerosol mass and composition, but consistencies in seasonal average diurnal profiles and concentrations. For example, the seasonal average variations in the diurnal PM2.5 mass were predominately driven by the sulfate component. © 2004 Elsevier Ltd. All rights reserved.

Three-dimensional free surface modelling in an unstructured mesh environment for metal processing applications

In the casting of metals, tundish flow, welding, converters, and other metal processing applications, the behaviour of the fluid surface is important. In aluminium alloys, for example, oxides formed on the surface may be drawn into the body of the melt where they act as faults in the solidified product affecting cast quality. For this reason, accurate description of wave behaviour, air entrapment, and other effects need to be modelled, in the presence of heat transfer and possibly phase change. The authors have developed a single-phase algorithm for modelling this problem. The Scalar Equation Algorithm (SEA) (see Refs. 1 and 2), enables the transport of the property discontinuity representing the free surface through a fixed grid. An extension of this method to unstructured mesh codes is presented here, together with validation. The new method employs a TVD flux limiter in conjunction with a ray-tracing algorithm, to ensure a sharp bound interface. Applications of the method are in the filling and emptying of mould cavities, with heat transfer and phase change.