• Journal of the Korean Data and Information Science Society
• /
• v.25 no.6
• /
• pp.1293-1300
• /
• 2014

The temperature data influences on various policies of the country. In this article, the autoregressive error (ARE) model has been considered for analyzing the monthly and seasonal temperature data at the northern part of the Chungcheong Namdo, Seosan monitoring site in Korea. In the ARE model, five meteorological variables, four greenhouse gas variables and five pollution variables are used as the explanatory variables for the temperature data set. The five meteorological variables are wind speed, rainfall, radiation, amount of cloud, and relative humidity. The four greenhouse gas variables are carbon dioxide ($CO_2$), methane ($CH_4$), nitrous oxide ($N_2O$), and chlorofluorocarbon ($CFC_{11}$). And the five air pollution explanatory variables are particulate matter ($PM_{10}$), sulfur dioxide ($SO_2$), nitrogen dioxide ($NO_2$), ozone ($O_3$), and carbon monoxide (CO). The result showed that the monthly ARE model explained about 39-63% for describing the temperature. However, the ARE model will be expected better when we add the more explanatory variables in the model.

• Journal of the Korean Data and Information Science Society
• /
• v.26 no.6
• /
• pp.1409-1416
• /
• 2015

The change of temperature influences on the various aspect, especially human health, plant and animal's growth, economics, industry, and culture of the country. In this article, the autoregressive error (ARE) model has been considered for analyzing the monthly temperature data at the Suwon monitoring site in Korea. In the ARE model, five meteorological variables, four greenhouse gas variables and five pollution variables are used as the explanatory variables for the temperature data set. The five meteorological variables are wind speed, rainfall, radiation, amount of cloud, and relative humidity. The four greenhouse gas variables are carbon dioxide ($CO_2$), methane ($CH_4$), nitrous oxide ($N_2O$), and chlorofluorocarbon ($CFC_{11}$). And the five air pollution explanatory variables are particulate matter ($PM_{10}$), sulfur dioxide ($SO_2$), nitrogen dioxide ($NO_2$), ozone ($O_3$), and carbon monoxide (CO). Among five meteorological variables, radiation, amount of cloud, and wind speed are more influence on the temperature. The radiation influences during spring, summer and fall, whereas wind speed influences for the winter time. Also, among four greenhouse gas variables and five pollution variables, chlorofluorocarbon, methane, and ozone are more influence on the temperature. The monthly ARE model explained about 43-69% for describing the temperature.

• Korean Chemical Engineering Research
• /
• v.47 no.3
• /
• pp.355-361
• /
• 2009

Effects of operating variables on solid separation rate in two-interconnected fluidized beds system for selective solid circulation have been investigated. Coarse(212~300 or $425{\sim}600{\mu}m$) and fine($63{\sim}106{\mu}m$) particles were separated using the solid separator and the solid separation rate was ranged from 66 to 987 g/min. The solid separation rate increased as the gas velocity through the solid injection nozzle, solid height, diameter of solid injection nozzle, particle size of coarse particles, aperture of the solid separator, and weight fraction of fines in the solid mixture increased. However, the effect of the fluidization velocity was negligible.

• Economic and Environmental Geology
• /
• v.55 no.6
• /
• pp.617-632
• /
• 2022

In recent years, environmental pollution and determining the main factors causing this pollution have become an important issue. This study investigates the relationship between the agricultural sector and environmental pollution in Azerbaijan for 1992-2018. The dependent variable in the study is the agricultural greenhouse gas emissions (CO₂ equivalent). Eight variables were selected as explanatory variables: four agricultural inputs and four agricultural macro indicators. Unit root tests, ARDL boundary test, FMOLS, DOLS and CCR long-term estimators, Granger causality analysis, and variance decomposition analyses were used to investigate the effect of these variables on agricultural emissions. The results show that chemical fertilizer consumption, livestock number, and pesticide use positively and statistically significantly affect agricultural emissions from agricultural input variables. In contrast, agricultural energy consumption has a negative and significant effect. From agricultural macro indicator variables, it was found that the crop and animal production index had a positive and significant effect on agricultural emissions. According to the Granger causality test results, it was concluded that there are a causality relationship from chemical fertilizer consumption, livestock number, crop and livestock production index variables towards agricultural emissions. Considering all the results obtained, it is seen that the variables that have the most effect on the increase in agricultural emissions in Azerbaijan are the number of livestock, the consumption of chemical fertilizers, and the use of pesticides, respectively. The results from the research will contribute to the information on agricultural greenhouse gas emissions and will play an enlightening role for policymakers and the general public.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.13 no.1
• /
• pp.431-438
• /
• 2012

The $CO_2$ capture technology using an aqueous amine solution is studied widely now. The entire process consists of an absorber to remove carbon dioxide selectively and a regenerator to regenerate absorbent and acquire pure carbon dioxide. Because there are the complicated design variables that affect performance of the process, it needs optimization and analysis through modeling to make a commercially reliable process. In this study, the decomposition method was proposed to consider convergence problem and sensitivity analysis was executed for the carbon dioxide capture process variables. Non-equilibrium model was used in the simulation to get more realistic results and we designed optimized process with more than 95% purity and 90% recovery.

• Journal of Korean Society for Atmospheric Environment
• /
• v.23 no.3
• /
• pp.344-352
• /
• 2007

Quantifying the methane emission from landfills is important to evaluate measures for reduction of greenhouse gas emissions. To estimate methane emission for the entire landfills from 1990 through 2004 in Korea, Tier 1 and 2 methodologies were used. In addition, five different scenarios were adopted to identify the effect of important variables on methane emission. The trends of methane emission using Tier 1 were similar to the disposed waste amount. Methane emission using Tier 2 increased as the degradation of waste was gradually proceeded. This result indicates that disposed waste amount and methane generation rate are the important variables for the estimation of methane emission by Tier 1 and 2, respectively. As for the different scenarios, methane emission was highest with scenario I that the entire landfills in Korea were regarded as one landfill. Methane emissions by scenario III and IV considering different $DOC_F$ values with the waste type and different MCF values with the height of waste layer, respectively, were underestimated compared to scenario II. This result indicates that the method of scenario I employed to most previous studies may lead to the overestimation of methane emission. Therefore, more careful consideration of the variables should be needed to develop the methodologies of greenhouse gas emission in landfills along with the characteristics of disposed waste in Korea.

• Clean Technology
• /
• v.20 no.3
• /
• pp.321-329
• /
• 2014

In this study, Indonesia low rank coal, which has moisture content of around 26%, is dried less than 5% by using a laboratory-scale (batch type) steam fluidized-bed dryer in order to produce the low-moisture, high rank coal. Normally, CCS (carbon capture and storage) process discharges $CO_2$ and steam mixture gas around $100-150^{\circ}C$ of temperature after regeneration reactor. The final purpose of this research is to dry low rank coal by using the outlet gas of CCS process. At this stage, steam is used as heat source for drying through the heat exchanger and $CO_2$ is used as fluidizing gas to the dryer. The experimental variables were the steam flow rate ranging from 0.3 to 1.1 kg/hr, steam temperature ranging from 100 to $130^{\circ}C$, and bed height ranging from 9 to 25 cm. The characteristics of the coal, before and after drying, were analyzed by a proximate analysis, the heating value analysis and particle size analysis. In summary, the drying rate of low rank coal was increased as steam flow rate and steam temperature increased and increased as bed height decreased.

• Korean Journal of Organic Agriculture
• /
• v.26 no.4
• /
• pp.619-628
• /
• 2018

This study analyze the economic effect of chemical fertilizer. We used the input and output data, and the analysis variables include production output nitrogen, phosphoric acid, potassium, seeds, and labor. The main results are as follows. First, for spring potatoes, potassium increases to a certain level of output, but over a certain stage, the output decreases as the input increases. Optimal use of potassium in the calculation of spring potatoes can achieve the effect of reducing input costs and increasing output simultaneously. Second, radish In autumn, nitrogen increases to a certain level, but over a certain stage it represents a reverse U-shaped relationship in which output decreases as input increases. This means that reducing the amount of fertilizer input increases the output. This means that soil-related agricultural big data can contribute to the management of nutrients and greenhouse gas reduction in agricultural land.

• Korean Chemical Engineering Research
• /
• v.50 no.6
• /
• pp.994-1001
• /
• 2012

The Effects of operating variables on reactivity of two $CO_2$ absorbents (PKM1-SU and P4-600) for SEWGS process were investigated in a pressurized fluidized bed reactor. For both $CO_2$ absorbents, $CO_2$ sorption capacity decreased as the number of absorption-regeneration cycles increased. PKM1-SU absorbent represented higher $CO_2$ sorption capacity than that of P4-600 absorbent. However, P4-600 absorbent represented better performance than PKM1-SU absorbent from the view points of regeneration temperature and regeneration rate. For PKM1-SU absorbent, $CO_2$ sorption capacity increased as the steam concentration increased. However, $CO_2$ sorption capacity increased initially as the steam concentration increased from 5% to 10%, but maintained thereafter for P4-600 absorbent. For both $CO_2$ absorbents, $CO_2$ sorption capacity increased as the final regeneration temperature increased. For PKM1-SU absorbent, $CO_2$ sorption capacity increased as the pressure increased and the increment tendency was drastic at higher pressure than 15 bar.

• Ecology and Resilient Infrastructure
• /
• v.2 no.2
• /
• pp.185-190
• /
• 2015

Greenhouse gas (GHG) emission from agricultural lands is recognized as one of important factors of global warming. The objective of this short communication was to evaluate the applicability of different soil GHG emission prediction models on agricultural systems in Korea. Four models, namely, DNDC, DAYCENT, EXPERT-N and COUP, were selected and the basic structure (e.g., components and sub-model), input variables, and output variables were compared. In particular, the availability and compilation of essential input variables were assessed. Major input variables needed for operating these predictive models were found to be available through database systems established by national organizations such as the Korea Meteorological Administration, the Korean Soil Information System, and the Rural Development Administration. However, in order to apply these models in Korea, it was necessary to calibrate and validate each of the models for the domestic landscape settings and climate conditions. In addition, field data of long-term monitoring of GHG emission from agricultural lands are limited and therefore should be measured.