Analysis of air pollution in two major Korean cities: trends, seasonal variations, daily 1-hour maximum versus other hour-based concentrations, and standard exceedances

This study considers the characteristics of carbon monoxide (CO), nitrogen dioxide (NO(2)), ozone (O(3)) and sulfur dioxide (SO(2)) in two major South Korean cities, including the capital city of Seoul, over a time period of 7-8 years. Changes in the annual mean and percentiles of the daily 1-h maximum and other hour-based concentrations varied according to the compound and city type. Seasonal variations varied according to the compound, yet not with the city type. Both Seoul and Taegu exhibited lower O(3) concentrations in July compared to other summer months. There was a high degree of correlation between the daily 1- and 8-h maximum or daily mean concentrations of all compounds in both cities, with an R(2) of 0.66-0.90 at p<0.0001. It was indicated that for CO and O(3), the 8-h standard was more stringent than the 1-h standard, while for NO(2) and SO(2), the 1-h standard was more stringent than the 24-h standard. The correlation coefficients between the daily 1-h maximum and daily mean concentrations decreased as the maximum concentration values of NO(2), O(3 ), and SO(2) increased in the two cities. For all the target compounds, Seoul recorded a substantially higher frequency of days with concentrations above the relevant 1-, 8-, and 24-h standards compared to Taegu.     

Modeling of SO<Subscript>2</Subscript> distribution in Istanbul using artificial neural networks

Urban air pollution is a growing problem in developing countries. Some compounds especially sulphur dioxide (SO₂) is considered as typical indicators of the urban air quality. Air pollution modeling and prediction have great importance in preventing the occurrence of air pollution episodes and provide sufficient time to take the necessary precautions. Recently, various stochastic image-processing algorithms such as Artificial Neural Network (ANN) are applied to environmental engineering. ANN structure employs input, hidden and output layers. Due to the complexity of the problem, as the number of input–output parameters differs, ANN model settings such as the number of neurons of these layers changes. The ability of ANN models to learn, particularly capability of handling large amounts (or sets) of data simultaneously as well as their fast response time, are invariably the characteristics desired for predictive and forecasting purposes. In this paper, ANN models have been used to predict air pollutant parameter in meteorological considerations. We have especially focused on modeling of SO₂ distribution and predicting its future concentration in Istanbul, Turkey. We have obtained data sets including meteorological variables and SO₂ concentrations from Istanbul-Florya meteorological station and Istanbul-Yenibosna air pollution station. We have preferred three-layer perceptron type of ANN which consists of 10, 22 and 1 neurons for input, hidden and output layers, respectively. All considered parameters are measured as daily mean. The input parameters are: SO₂ concentration, pressure, temperature, humidity, wind direction, wind speed, strength of sunshine, sunshine, cloudy, rainfall and output parameter is the future prediction of SO₂. To evaluate the performance of ANN model, our results are compared to classical nonlinear regression methods. The over all system finds an optimum correlation between input–output variables. Here, the correlation parameter, r is 0.999 and 0.528 for training and test data. Thus in our model, the trend of SO₂ is well estimated and seasonal effects are well represented. As a result, we conclude that ANN is one of the compromising methods in estimation of environmental complex air pollution problems.     

A hierarchical end-of-life decision model for determining the economic levels of remanufacturing and disassembly under environmental regulations

Remanufacturing, in contrast to material recycling and disposal, can reduce environmental impacts by retaining the geometrical form of the product, thereby regarded as a more eco-efficient approach. In this paper, an end-of-life (EOL) decision model for remanufacturing options is presented to facilitate remanufacturing. The proposed model, in order to maximize the economic value of remanufacturing options while meeting environmental regulations, takes an integrative approach to EOL-option decision-making. Also presented in this paper is a hierarchical approach that represents both the overall hierarchical structure of a product and the interconnections among components. Illustrative examples are provided to demonstrate the effectiveness of the model.     

Group-level organizational citizenship behavior: Effects of demographic faultlines and conflict in small work groups

Organizational scholars have recently shifted their attention to examining organizational citizenship behavior (OCB) as a group-level phenomenon. Adopting the input-mediator-outcome model of group performance, we examined antecedents and intermediate processes that predict group-level OCB (GOCB) in small work groups. The results, based on data from 62 work groups representing a variety of industries, revealed that demographic faultlines based on relation-oriented attributes (gender, age, and race) and a task-related attribute (tenure) had differentiated relationships with task and relationship conflict, which mediated the relationships between faultlines and group outcomes (GOCB and group performance). Both task and relationship conflict were negative predictors of group performance. However, task conflict increased GOCB, whereas relationship conflict decreased it. The present study offers evidence of the relationship between demographic faultlines and various group processes and outcome variables in natural work groups. Copyright © 2009 John Wiley & Sons, Ltd.     

Effect of reactive media composition and co-contaminants on sulfur-based autotrophic denitrification

As a part of a study developing a biological reactive barrier system to treat nitrate-contaminated groundwater, the effects of reactive media composition and co-contaminants on sulfur-oxidizing autotrophic denitrification were investigated. The size of sulfur granules affected the denitrification rates; kinetic constants of 2.883, 2.949, and 0.677 mg-N(1/2)/L(1/2)/day were obtained when the granule sizes were below 2 mm, between 2 and 5 mm, and over 5 mm, respectively. When the volume ratios of sulfur to limestone were 1:1, 2:1, 3:1, and 4:1, kinetic constants of 5.490, 3.903, 4.072, and 2.984 mg-N(1/2)/L(1/2)/day were obtained, respectively. The presence of TCE up to 20 mg/L didn't significantly affect nitrate removal efficiency. At the TCE concentration of 80 mg/L, however, nitrate removal was markedly inhibited. Also, Zn and Cu inhibited the denitrification activity at more than 0.5 mg/L of concentration whereas Cr (VI) did not significantly affect the nitrate removal efficiency at all levels tested.     

Adsorption characteristics of siloxanes in landfill gas by the adsorption equilibrium test

Due to the increase in energy cost by constantly high oil prices and the obligation to reduce greenhouse effect gases, landfill gas is frequently used as an alternative energy source for producing heat and electricity. Most of landfill gas utility facilities, however, are experiencing problems controlling siloxanes from landfill gas as their catalytic oxidizers are becoming fouled by silicon dioxide dust. To evaluate adsorption characteristics of siloxanes, an adsorption equilibrium test was conducted and parameters in the Freundlich and Langmuir isotherms were analyzed. Coconut activated carbon (CA1), coal activated carbon (CA2), impregnated activated carbon (CA3), silicagel (NCA1), and activated alumina (NCA2) were used for the adsorption of the mixed siloxane which contained hexamethyldisiloxane (L2), octamethylcyclotetrasiloxane (D4), and decamethylcyclopentasiloxane (D5). L2 had higher removal efficiency in noncarbon adsorbents compared to carbon adsorbents. The application of Langmuir and Freundlich adsorption isotherm demonstrated that coconut based CA1 and CA3 provided higher adsorption capacity on L2. And CA2 and NCA1 provided higher adsorption capacity on D4 and D5. Based on the experimental results, L2, D4, and D5 were converted by adsorption and desorption in noncarbon adsorbents. Adsorption affinity of siloxane is considered to be affect by the pore size distribution of the adsorbents and by the molecular size of each siloxane.     

The effects of self‐emotion,counterpart emotion,and counterpart behavior on negotiator behavior: a comparison of individual‐level and dyad‐level dynamics

This study expands the negotiation literature by examining how negotiator behavior is predicted by various emotions felt by the negotiators and their counterparts and by counterpart negotiation behavior. Using hierarchical linear modeling, we also compare individual‐ and dyad‐level processes that lead to negotiator behavior and outcomes. The results from a dyadic negotiation simulation showed that both the valence and agency of negotiator and counterpart emotions need to be considered to understand the roles of emotion in negotiator behavior. Negotiators tend to reciprocate counterparts' integrating, compromising, and dominating behaviors, but they also offer complementary (or matching) responses to the counterparts' dominating and yielding behaviors. Integrating behavior was more dependent on dyad‐level interpersonal dynamics than were the other behaviors. The comparison of negotiator‐level and dyad‐level results suggests that negotiation needs to be understood in the context of collective exchanges as well as individual‐level cognitive processes. Copyright © 2005 John Wiley & Sons, Ltd.