An enhanced engineering perspective of global climate systems and statistical formulation of terrestrial CO2 exchanges

This paper designs a comprehensive approach based on the engineering machine/system concept, to model, analyze, and assess the level of carbon dioxide (CO₂) exchange between the atmosphere and terrestrial ecosystems, which is an important factor in understanding changes in global climate. The focus of this article is on spatial patterns and on the correlation between levels of CO₂ fluxes and a variety of influencing factors in eco-environments. The engineering/machine concept used is a system protocol that includes the sequential activities of design, test, observe, and model. This concept is applied to explicitly include various influencing factors and interactions associated with CO₂ fluxes. To formulate effective models of a large and complex climate system, this article introduces a modeling technique that will be referred to as stochastic filtering analysis of variance (SF-ANOVA). The CO₂ flux data observed from some sites of AmeriFlux are used to illustrate and validate the analysis, prediction, and globalization capabilities of the proposed engineering approach and the SF-ANOVA technique. The SF-ANOVA modeling approach was compared to stepwise regression, ridge regression, and neural networks. The comparison indicated that the proposed approach is a valid and effective tool with similar accuracy and less complexity than the other procedures.     

Imaging the Yellow Sea Bottom Cold Water from multichannel seismic data

The Yellow Sea Bottom Cold Water (YSBCW) is a large cold water mass lying in the deep part of the Yellow Sea during the warm season. We acquired multichannel seismic (MCS) data using an air gun source to image the structure of the YSBCW. The MCS data recorded reflections from sea water. The recognition of these reflections was confirmed by finite-difference seismic modeling in the frequency-domain. The seismic section from MCS data enabled discrimination of water masses distinctly separated by reflecting horizons. The structure of the water masses is fairly consistent with temperature-depth variations obtained using expandable bathythermograph (XBT) casts. The YSBCW is imaged as the lowermost water mass, maximally 40 m thick, that extends as a lens-like form along the sea bottom under the warm mixed layer. The correlation of XBT measurements and the seismic section indicates a rapid decrease in temperature from around 11 to 8 °C in the uppermost part of the YSBCW. A transition zone between the mixed layer and the underlying YSBCW is also defined. This transition zone has fairly uniform thickness of 14–18 m and marks an interval of rapid temperature drop, indicating vigorous thermal mixing. Our study demonstrates that MCS profiling is a useful and reliable tool for imaging fine structures in the shallow Yellow Sea.     

Ecological effects of soil antimony on the crop plant growth and earthworm activity

High levels of antimony have been frequently detected in some industrial sites. This study evaluated the adverse effects of antimony (Sb) on the surface-casting activity of earthworm and the early growths of some important crop plants. Asian earthworm (Perionyx excavates) and four crop plant species (Chinese cabbage, Brassica campestris; wheat, Triticum aestivum; cucumber, Cucumis sativus; and mung bean, Phaseolus radiatus) were exposed to soil antimony in laboratory. Survival, abnormality and the surface-casting activity of earthworm were monitored. Negative effects of the survival and the morphological abnormalities were observed in the P. excavates exposed to Sb. The earthworm activity, expressed as surface cast production, was significantly inhibited with elevated Sb levels. In terms of plant assay, the growth of all test plants was adversely affected in Sb-contaminated soils, and the content of Sb in plant tissues increased with increasing Sb concentration in soil. The results demonstrate that elevated Sb concentrations in soil would inhibit the early growth of crop plants, and the earthworm casting activity that is a key function of earthworm to increase soil fertility. This is the first report on the negative effect of Sb on the casting activity of earthworm as well as the growth of test plant species selected.     

Effects of BPA and DES on longchin goby (Chasmichthys dolichognathus) in vitro during the oocyte maturation

This study was performed in order to assess whether bisphenol (BPA) and diethylstilbestrol (DES) had agonistic or antagonistic effects on oocyte maturation using marine fish. We tested the effects of these chemicals on in vitro maturation, germinal vesicle breakdown (GVBD), assay using oocytes from the longchin goby, Chasmichthys dolichognathus. During the maturation process, low concentrations of BPA and DES triggered GVBD depending on the stage of oocyte development; BPA at 0.044 nM and DES at 0.037, 0.37, and 3.73 nM induced GVBD in 0.82-0.88 mm diameter oocytes (germinal vesicle located near the center of oocytes). In 0.76-0.80 mm diameter oocytes (fully vitellogenic oocytes), BPA induced GVBD at relatively higher concentrations (4.38, 43.8, and 438 nM). In 0.86-0.90 mm diameter oocytes, BPA and DES had no observable effect on GVBD at the concentrations tested. Oocytes with diameters between 0.82 and 0.88 mm appeared to be more sensitive to these chemicals. Moreover, our results showed that BPA and DES did not inhibit GVBD.     

Evaluation of the Community Land Model 3.5 with carbon and nitrogen cycles (CLM3.5CN) at a Tibetan grassland site

The Tibetan plateau plays an important role in energy and carbon cycles by providing an elevated heat source and by storing a large amount of soil carbon due to low temperature. The main vegetation of the plateau is alpine grassland. This study evaluates performance of Community Land Model 3.5 with carbon and nitrogen cycles (CLM3.5CN) over a alpine grassland in the Tibetan plateau in terms of energy and carbon fluxes in conditions of reasonable phenology and initial carbon pool comparable to observations. Comparison between model and observation shows following features. The model captures the magnitude of maximum leaf area index (LAI) but underestimats leaf mass. Net ecosystem exchange (NEE) is significantly underestimated during the growing season and soil temperature is also underestimated throughout a year with higher negative bias in winter than in other seasons. In order to examine the cause of the model deficiencies, we design four sensitivity tests: seasonal mulch; shallow rooting depth; reduction of critical soil moisture to limit the decomposition rate; smaller specific leaf area (SLA). Considering seasonal mulch improves the negative bias of soil temperature during dormant season has little effect on the NEE during the growing seasson. Underestimation of NEE during the growing season is partly due to underestimated decomposition rate which results from underestimated soil temperature and deep root placement in the soil column. Underestimation of latent heat flux during summer is partly due to use of large SLA in the model. Other deficiencies are also discussed.     

Concentrations and sources of PAHs at three stations in Istanbul,Turkey

The chemical mass balance model was applied to atmospheric Polycyclic Aromatic Hydrocarbons (PAHs) in Istanbul, Turkey. A total of 326 airborne samples were collected and analyzed for 16 PAHs and Total Suspended Particles (TSP) in the September 2006–December 2007 period at three monitoring stations: Yildiz, DMO (urban sites) and Kilyos (rural site). The total average PAH concentrations were 100.66 ± 61.26, 84.63 ± 46.66 and 25.12 ± 13.34 ng m^?3 and the TSP concentrations were 101.16 ± 53.22, 152.31 ± 99.12, 49.84 ± 18.58 μg m^?3 for Yildiz, DMO and Kilyos stations respectively. At all the sites, the lighter compounds were the most abundant, notably Nap, AcPy and PA. The average correlation values between TSP and total heavier PAH were greater than 0.5 for Yildiz and DMO stations. The patterns of PAH and TSP concentrations showed spatial and temporal variations. PAH concentrations were evaluated for the PAH contribution from four sources (diesel engines, gasoline engines, natural gas combustion, and coal + wood burning). Vehicle emissions appear to be the major source with contributions of 61.2%, 63.3% and 54.1% for Yildiz, DMO and Kilyos stations respectively. Seasonal and yearly variations had different trends for all sites.     

Routing procedures for observed dispersion coefficients in two-dimensional river mixing

Routing procedures have been used for determining the observed values of the dispersion coefficient in river mixing studies. In order to overcome the shortcomings of the existing routing procedures, we developed a new routing procedure capable of being applied under a transient concentration situation while accounting for river irregularities. The proposed routing procedure is based on the exact solution of the depth-averaged, two-dimensional, mass transport equation combined with the stream-tube concept and was verified through the tracer data acquired from field tests conducted in natural rivers located in Korea. The observed dispersion coefficients evaluated by the routing procedure exhibited a stream-wise variation along the rivers, in that a minimum value was seen in the straight region and a maximum value downstream of the apex of the bend. This variation was attributed to the flow dynamics of secondary currents induced by the meandering of the rivers. The dispersion coefficients obtained by the new method over the reach were in the same range of those calculated by other methods.     

Overview of geostationary ocean color imager (GOCI) and GOCI data processing system (GDPS)

GOCI, the world??s first geostationary ocean color satellite, provides images with a spatial resolution of 500 m at hourly intervals up to 8 times a day, allowing observations of short-term changes in the Northeast Asian region. The GOCI Data Processing System (GDPS), a specialized data processing software for GOCI, was developed for real-time generation of various products. This paper describes GOCI characteristics and GDPS workflow/products, so as to enable the efficient utilization of GOCI. To provide quality images and data, atmospheric correction and data analysis algorithms must be improved through continuous Cal/Val. GOCI-II will be developed by 2018 to facilitate in-depth studies on geostationary ocean color satellites.