• 대한원격탐사학회지
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• 제26권6호
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• pp.617-627
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• 2010

Although many researches for heat island study have been developed, there is little attempt to link the findings to actual and hypothetical scenarios of urban developments which would help to mitigate the Urban Heat Island (UHI) in cities. The aim of this paper is to analyze the UHI at urban area with different geometries, land use, and environmental factors, and emphasis on the influence of different geometric and environmental parameters on ambient air temperature. In order to evaluate these effects, the parameters of (i) Air pollution (i.e. Aerosol Optical Thickness (AOT)), (ii) Green space Normalized Difference Vegetation Index (NDVI), (iii) Anthropogenic heat (AH) (iv) Building density (BD), (v) Building height (BH), and (vi) Air temperature (Ta) were mapped. The optimum operational scales between Heat Island Intensity (HII) and above parameters were evaluated by testing the strength of the correlations for every resolution. The best compromised scale for all parameters is 275m resolution. Thus, the measurements of these parameters contributing to heat island formation over the study areas of Hong Kong were established from mathematical relationships between them and in combination at 275m resolution. The mathematical models were then tabulated to show the impact of different percentages of parameters on HII. These tables are useful to predict the probable climatic implications of future planning decisions.

• Journal of Microbiology and Biotechnology
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• 제11권4호
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• pp.607-613
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• 2001

The biodegradation rates of diesel oil by a selected diesel-degrading bacterium, Pseudomonas stutzeri strain Y2G1, and microbial consortia composed of combinations of 5 selected diesel-degrading bacterial were determined in liquid and soil systems. The diesel degradation rate by strain Y2G1 linearly increased $(R^2=0.98)$ as the diesel concentration increased up to 12%, and a degradation rate as high as 5.64 g/l/day was obtained. The diesel degradation by strain Y2G1 was significantly affected by several environmental factors, and the optimal conditions for pH, temperature, and moisture content were at pH8, $25^{\circ}C$, and 10%, respectively. In the batch soil microcosm tests, inoculation, especially in the form of a consortium, and the addition of nutrients both significantly enhanced the diesel degradation by a factor of 1.5 and 4, respectively. Aeration of the soil columns effectively accelerated the diesel degradation, and the initial degradation rate was obviously stimulated with the addition of inorganic nutrients. Based on these results, it was concluded that the major rate-limiting factors in the tested diesel-contaminated soil were the presence of inorganic nutrients, oxygen, and diesel-degrading microorganisms. To resolve these limiting parameters, bioremediation strategies were specifically designed for the tested soil, and the successful mitigation of the limiting parameters resulted in an enhancement of the bioremediation efficiency by a factor of 11.

• Advances in environmental research
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• 제7권2호
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• pp.109-120
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• 2018

In the present study research air quality analyses for $PM_{10}$, were conducted in Shiraz, a city in the south of Iran. The measurements were taken from 2011 through 2012 in two different locations to prepare average data in the city. The averages concentrations were calculated for every 24 hours, each month and each season. Results showed that the highest concentration of $PM_{10}$ occurs generally in the night while the least concentration was found at the afternoon. Monthly concentrations of $PM_{10}$ showed highest value in August, while least value was found in January. The seasonal concentrations showed the least amounts in autumn while the highest amounts in summer. Relations between the air pollutant and some meteorological parameters were calculated statistically using the daily average data. The wind data (velocity, direction), relative humidity, temperature, sunshine periods, evaporation, dew point and rainfall were considered as independent variables. The relationships between concentration of pollutant and meteorological parameters were expressed by multiple linear regression equations for both annual and seasonal conditions SPSS software. RMSE test showed that among different prediction models, stepwise model is the best option.

• Environmental Engineering Research
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• 제25권3호
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• pp.374-383
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• 2020

Landfill gas (LFG) emissions from a given amount of landfill waste depend on the carbon flows in the waste. The objective of this study was to more accurately estimate the first-order decay parameters through methane (CH₄) and carbon flow balances based on the analysis of a full-scale landfill with long-term data and detailed field records on LFG and leachate. The carbon storage factor for the case-study landfill was 0.055 g-degradable organic carbon (DOC) stored per g-wet waste and the amounts of DOC lost with the leachate were less than 1.3%. The appropriate CH₄ generation rate constant (k) for bulk waste was 0.24 y-1. The the CH₄ generation potential (L0) values ranged 33.7-46.7 m3-CH₄ Mg-1, based on the fraction of DOC that can decompose (DOCf) value of 0.40. Results show that CH4 and carbon flow balance methods can be used to estimate model parameters appropriately and to predict long-term carbon emissions from landfills.

• Structural Engineering and Mechanics
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• 제83권5호
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• pp.671-680
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• 2022

The shear capacity of beams is an essential parameter in designing beams carrying shear loads. Precise estimation of the ultimate shear capacity typically requires comprehensive calculation methods. For steel fiber reinforced concrete (SFRC) beams, traditional design methods may not accurately predict the interaction between different parameters affecting ultimate shear capacity. In this study, artificial neural network (ANN) modeling was utilized to predict the ultimate shear capacity of SFRC beams using ten input parameters. The results demonstrated that the ANN with 30 neurons had the best performance based on the values of root mean square error (RMSE) and coefficient of determination (R²) compared to other ANN models with different neurons. Analysis of the ANN model has shown that the clear shear span to depth ratio significantly affects the predicted ultimate shear capacity, followed by the reinforcement steel tensile strength and steel fiber tensile strength. Moreover, a Genetic Algorithm (GA) was used to optimize the ANN model's input parameters, resulting in the least cost for the SFRC beams. Results have shown that SFRC beams' cost increased with the clear span to depth ratio. Increasing the clear span to depth ratio has increased the depth, height, steel, and fiber ratio needed to support the SFRC beams against shear failures. This study approach is considered among the earliest in the field of SFRC.

• 한국환경보건학회:학술대회논문집
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• 한국환경보건학회 2004년도 International Conference Global Environmental Problems and their Health Consequences
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• pp.178-181
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• 2004

Di-n-butyl phthalate (DBP) is used extensively in the plastic industry and has been known as an environmental hormone (endocrine disruptor). Present study was undertaken to examine whether DBP can induce oxidative stress in mice. In this study, oxidative stress was measured in terms of the modification of lipid peroxidation and gamma-glutamyltranspeptidase (${\gamma}-GT$) activity. The activity of ${\gamma}-GT$, the level of lipid peroxidation and serum toxicity index were measured in male ICR mice after treatment with DBP (5 g/kg, po). Administration of DBP was found to significantly increase the level of lipid peroxidation approximately 2 fold in liver. The activity of ${\gamma}-GT$ in the liver of DBP-exposed animals was also increased approximately 2.5 fold. However, DBP did not alter the parameters for hepatotoxicity and nephrotoxicity such as alanine aminotransferase (ALT), aspartate aminotransferase (AST) and creatinine. These results indicate that DBP can induce oxidative stress in mice. The ${\gamma}-GT$ activity is considered to be increased as one of the adaptive defense mechanisms to oxidative stress induced by DBP.

• Nuclear Engineering and Technology
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• 제54권2호
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• pp.770-780
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• 2022

In 1993 the University of Extremadura initiated the design, construction and management of the Radiological Alert Network of Extremadura (RAREx). The goal was to acquire reliable near-real-time information on the environmental radiological status in the surroundings of the Almaraz Nuclear Power Plant by measuring, mainly, the ambient dose equivalent. However, the phased development of this network has been carried out from two points of view. Firstly, there has been an increase in the number of stations comprising the network. Secondly, there has been an increase in the number of monitored parameters. As a consequence of the growth of RAREx network, large data volumes are daily generated. To face this big data paradigm, software applications have been developed and implemented in order to maintain the indispensable real-time and efficient performance of the alert network. In this paper, the description of the current status of RAREx network after 30 years of design and performance is showed. Also, the performance of the graphing software for daily assessment of the registered parameters and the automatic on real time warning notification system, which aid with the decision making process and analysis of values of possible radiological and non-radiological alterations, is briefly described in this paper.

• International Journal of Advanced Culture Technology
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• 제10권3호
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• pp.164-173
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• 2022

This study aimed to explore the themes and parameters of environmental health behaviors based on Rogers' protection motivation theory through a systematic mapping review. Using a systematic approach, a literature review was conducted of articles that adopted Rogers' protection motivation theory. A total of 11 articles on protection motivation theory using participants and environmental health as outcomes were identified in a search of CINAHL, Cochrane Library, EMBASE, Eric, PsycARTICLES, PubMed, and RISS between September 1 and September 8, 2021. Themes related to the environment and personal behaviors between 2002 and 2021 were extracted. The parameters based on protection motivation theory were identified through systematic mapping as fear appraisal, rewards of maladaptive response, severity, vulnerability, costs of adaptive response, response efficacy, self-efficacy, and intention. Self-efficacy and response efficacy considerably affected environmental health behaviors. Emotional fear appeal related to environmental hazards motivates an internal process that alters the threat appraisal and their coping appraisal. Environmental behavior perception and intention influenced on environmental health behaviors with small effect sizes. Therefore, a deeper understanding of the severity of environmental health issues could lead to the development of helpful, effective, and intensive interventions to promote healthcare among the vulnerable population.

• Geomechanics and Engineering
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• 제8권4호
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• pp.559-594
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• 2015

A nonlinear creep function incorporated into the elastic visco-plastic model may describe the long-term soil deformation more accurately. However, by applying the conventional procedure, there are challenges to determine the model parameters due to limitation of suitable data points. This paper presents a numerical solution to obtain several parameters simultaneously for a nonlinear elastic visco-plastic (EVP) model using the available consolidation data. The finite difference scheme using the Crank-Nicolson procedure is applied to solve a set of coupled partial differential equations of the time dependent strain and pore water pressure dissipation. The model parameters are determined by applying the algorithm of trust-region reflective optimisation in conjunction with the finite difference solution. The proposed method utilises all available consolidation data during dissipation of the excess pore water pressure to determine the required model parameters. Moreover, the reference time in the elastic visco-plastic model can readily be adopted as a unit of time; denoting creep is included in the numerical predictions explicitly from the very first time steps. In this paper, the settlement predictions of thick soft clay layers are presented and discussed to evaluate and compare the accuracy and reliability of the proposed method against the graphical procedure to obtain the model parameters. In addition, comparison of the available experimental results to the numerical predictions confirms the accuracy of the numerical procedure.

• Journal of Ecology and Environment
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• 제38권2호
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• pp.145-156
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• 2015

This study was based on water quality data of the Lake Doam watershed, monitored from 2010 to 2013 at eight different sites with multiple physiochemical parameters. The dataset was divided into two sub-datasets, namely, non-rainy and rainy. Principal component analysis (PCA) and factor analysis (FA) techniques were applied to evaluate seasonal correlations of water quality parameters and extract the most significant parameters influencing stream water quality. The first five principal components identified by PCA techniques explained greater than 80% of the total variance for both datasets. PCA and FA results indicated that total nitrogen, nitrate nitrogen, total phosphorus, and dissolved inorganic phosphorus were the most significant parameters under the non-rainy condition. This indicates that organic and inorganic pollutants loads in the streams can be related to discharges from point sources (domestic discharges) and non-point sources (agriculture, forest) of pollution. During the rainy period, turbidity, suspended solids, nitrate nitrogen, and dissolved inorganic phosphorus were identified as the most significant parameters. Physical parameters, suspended solids, and turbidity, are related to soil erosion and runoff from the basin. Organic and inorganic pollutants during the rainy period can be linked to decayed matters, manure, and inorganic fertilizers used in farming. Thus, the results of this study suggest that principal component analysis techniques are useful for analysis and interpretation of data and identification of pollution factors, which are valuable for understanding seasonal variations in water quality for effective management.