• International Journal of High-Rise Buildings
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• v.1 no.2
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• pp.81-85
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• 2012

Vertical meteorological conditions encountered by super tall buildings, such as wind speed, temperature and humidity, vary due to their height. Therefore, it is necessary to consider these environmental changes to properly estimate the heating and cooling loads, and to minimize the energy demands for HVAC in super tall buildings. This paper aims to analyze how vertical meteorological changes affect heating and cooling loads of super tall buildings by using numerical simulation. A radiosonde, which observes atmospheric parameters of upper air such as wind speed, wind direction, temperature, relative humidity and pressure, was used to provide weather data for the building load simulation. A hypothetical super tall building was used for the simulation to provide quantified characteristics of the heating and cooling loads, comparing the lower, middle and upper parts of the building. The effect of weather data on the heating and cooling loads in super tall building was also discussed.

• Proceedings of the Korea Water Resources Association Conference
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• 2005.05b
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• pp.766-770
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• 2005

Cascade-Correlation Neural Networks Model(CCNNM) is used to estimate daily evaporation using limited climatical variables such as atmospheric temperature, dewpoint temperature, relative humidity, wind speed, sunshine duration and radiation. DeBruln equation is applied to estimate daily free-surface evaporation. It is converted into pan evaporation using pan coefficient. The results of CCNNM shows better than those of Debruin equation. This research represents that the strong nonlinear relationship such as evaporation modeling can be generalized by the CCNNM ; a special type of Backpropagation algorithm Neural Networks Model.

• Journal of Korean Society for Atmospheric Environment
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• v.24 no.5
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• pp.604-612
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• 2008

The ozone concentration is one of the important environmental issue for measurement of the atmospheric condition of the country. This study focuses on applying the Autoregressive Error (ARE) model for analyzing the ozone data at middle part of the Gyeonggi-Do, Anyang monitoring site in Korea. In the ARE model, eight meteorological variables and four pollution variables are used as the explanatory variables. The eight meteorological variables are daily maximum temperature, wind speed, amount of cloud, global radiation, relative humidity, rainfall, dew point temperature, and water vapor pressure. The four air pollution variables are sulfur dioxide $(SO_2)$, nitrogen dioxide $(NO_2)$, carbon monoxide (CO), and particulate matter 10 (PM10). The result shows that ARE models both overall and monthly data are suited for describing the oBone concentration. In the ARE model for overall ozone data, ozone concentration can be explained about 71% to by the PM10, global radiation and wind speed. Also the four types of ARE models for high level of ozone data (over 80 ppb) have been analyzed. In the best ARE model for high level of ozone data, ozone can be explained about 96% by the PM10, daliy maximum temperature, and cloud amount.

• Atmosphere
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• v.17 no.1
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• pp.109-114
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• 2007

The mist on the inside of an automobile windshield is not only uncomfortable but also very dangerous because it obstructs the driver's vision. However, the removal process of the mist has never been studied in detail. This study performed experiments analyzing the mechanism causes the mist in a car and investigated the appropriate removal process. The experiments were performed on two rainy days, 10 April 2006 and 26 May 2006, with temperature and relative humidity sensors of testo-175-H2 and DICKSON-TK500. We found a passenger increased water vapor by 0.2 g $min^{-1}$ through respiration and thereby relative humidity (RH) from 55% to 67% in 8 minutes. Even though RH was not saturated, misting occurred because the humid air contacted the colder surface of the window. To remove the mist, it is necessary to increase the temperature or inflow drier air in the car. Therefore, we expected that the heater would be more effective than air conditioner for this matter. However, the outcome was the other way around due to the structure of the heating and cooling system in the car. When the air-conditioner was on, colder and drier air was generated and flowed through the so-called evaporator. Droplets were produced in the evaporator due to cooling procedure. When the heater was on, the warm air evaporated the droplets and increased the water content in the air resulting in an increase of relative humidity. Consequently, the air conditioner is more effective than the heater to remove the mist.

• Corrosion Science and Technology
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• v.19 no.4
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• pp.174-188
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• 2020

Atmospheric corrosion is a natural surface degradation process of metal due to changes in environmental parameters in the surrounding atmosphere. It is very sensitive to environmental parameters such as temperature, relative humidity, sulphur dioxide, and chloride, making it a major global economic challenge. Existing forecasting empirical corrosion models including the ISO standard are based on statistical analysis of experimental studies without considering the behavior of atmospheric parameters. The present study proposes a reliable global empirical model for estimating short and long-term atmospheric corrosion rates based on environmental parameters and corrosion mechanisms obtained from a parametric study. Repercussion of atmospheric corrosion rate due to individual and combined influences of environmental parameters specifies their importance in the estimation. New global empirical coefficients obtained for environmental parameters are statistically established (R² =0.998) with 95% confidence limit. They are validated using experimental datasets of existing studies observed at 88 different continental locations. The current proposed model can predict atmospheric corrosion by means of corrosion formation mechanisms influenced by combined effects of environmental parameters, further abating applicability limitations of location and time.

• Journal of the Korean Data Analysis Society
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• v.20 no.6
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• pp.2941-2951
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• 2018

The purpose of this paper is to analyse the effect of ocean weather factors on shipments of swimming crab. We use the data of data portal and ocean weather factors (mean wind velocity, mean atmospheric pressure, mean relative humidity, mean air temperature, mean water temperature, mean maximum wave height, mean significant wave height, maximum significant wave height, maximum wave height, mean wave period, maximum wave period). We did statistical analysis using Poisson regression analysis and negative binomial regression analysis. As the result of study, important factors influential in the shipments of swimming crab turn out to be mean wind velocity, mean atmospheric pressure, mean relative humidity, mean water temperature, maximum wave height, mean wave period and maximum wave period. the shipments of swimming crab increases as mean wind velocity, mean atmospheric pressure, mean relative humidity, mean water temperature increases or mean wave period increase. However, as maximum wave height, maximum wave period decreases, the shipment of swimming crab increases.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 1993.10a
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• pp.413-422
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• 1993

Air shipment affords the quickest possible delivery of horticultural products. The price of air shipped horticultural products are relatively high as most of these products are perishable. Usually the temperature in the cargo compartment is not controlled during flight. Thus, special attention should be paid to procooling prior to shipment. The environmental condition during transportation of horticultural products is an essential parameter for maintaining the quality of perishable products. Commonly horticultural products were loaded by ULD(Unit Load Devices) as a container or pallet in the aircraft (except for small aircraft) . Therefore, inside temperature of the container and cargo compartment came into question. Scarce literature on the relationship between environmental condition and quality changes of horticultural products during air shipment can be found. By the stand point of keeping fresh quality, investigations on the actual condition of air shipments were carried out to improve the technique during the distribution process of fresh horticultural products. Temperature, humidity, atmospheric pressure, carbon dioxide, ethylene, impacts, and changes in quality during the air shipment of snapbeans, okras and chrysanthemums were measured. Temperature was measured by recording thermometers, relative humidity by recording hygrometers, atmospheric pressure by a strain -guage type pressure sensor, carbon dioxide by testing tubes, ethylene by sampling bags and a gaschromatograph, impacts and vibrations by impact recorders and a 3D accelerometer. Relationships between environmental conditions and quality changes during air shipments were clarified. It was expected from investigations into actual shipments that the ventilation and insulation properties of air freight containers were related to the quality of agricultural products. Aircraft can no directly load and unload trucks into them. The transshipment is inclined to cause shocks and vibrations, and to invite damages within a short time.

• Journal of Korean Society for Atmospheric Environment
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• v.23 no.E2
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• pp.47-56
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• 2007

Among all the nitrogen species present in the atmosphere, ammonia forms a considerable portion along with the nitrogen oxides. The major sources of atmospheric ammonia are animal feedlot operations including emission from excreta of domestic animals and agricultural activities, followed by emission from synthetic fertilizers, biomass burning and to some lesser extent, fossil fuel combustion. Ammonia emission factor, expressed as the weight of ammonia per unit weight, volume, or duration of the activity emitting it, is generally used in developing emission estimates for emission inventories. The factors determining ammonia loss from soil or from manures are the temperature, pH, humidity, precipitation and the velocity of wind above it.

• Journal of Environmental Science International
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• v.22 no.9
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• pp.1171-1180
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• 2013

Recent climate change has led to fluctuations in agricultural production, and as a result national food supply has become an important strategic factor in economic policy. As such, in this study, panel data was collected to analyze the effects of seven meteorological elements and using the Lagrange multipliers method, the fixed-effects model for the production of five types of food crop and the seven meteorological elements were analyzed. Results showed that the key factors effecting increases in production of rice grains were average temperature, average relative humidity and average ground surface temperature, while wheat and barley were found to have positive correlations with average temperature and average humidity. The implications of this study are as follow. First, it was confirmed that the meteorological elements have profound effects on the production of food crops. Second, when compared to existing studies, the study was not limited to one food crop but encompassed all five types, and went beyond other studies that were limited to temperature and rainfall to include various meterological elements.

• Atmosphere
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• v.33 no.1
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• pp.1-20
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• 2023

Holding the longest observation data from April 1904, Busan is one of the essential points to understand the climate variability of the Korean Peninsula without missing data since implementing the modern weather observation of the South Korea. Busan is featured by coastal areas and affected by various climate factors and fluctuations. This study aims to investigate climate variability and changes in climatic variables, extremes, and several weather indexes. The statistically significant change points in daily mean rainfall intensity and temperature were found in 1964 and 1965. Based on the change point detection, 117 years were divided into two periods for daily mean rainfall intensity and temperature, respectively. In the long-term temperature analysis of Busan, the increasing trend of the daily maximum temperature during the period of 1965~2021 was larger than the daily mean temperature and the daily minimum temperature. Applying Ensemble Empirical Mode Decomposition, daily maximum temperature is largely affected by the decadal variability compared to the daily mean and minimum temperature. In addition, the trend of daily precipitation intensity from 1964~2021 shows a value of about 0.50 mm day^-1, suggesting that the rainfall intensity has increased compared to the preceding period. The results in extremes analysis demonstrate that return values of both extreme temperatures and precipitation show higher values in the latter than in the former period, indicating that the intensity of the current extreme phenomenon increases. For Wet-Bulb Globe Temperature (effective humidity), increasing (decreasing) trend is significant in Busan with the second (third)-largest change among four stations.