• Asian Journal of Atmospheric Environment
• /
• v.9 no.1
• /
• pp.22-30
• /
• 2015

This study evaluated road shape and roadside barrier impact on near-road air pollution dispersion using FLUENT computational fluid dynamics (CFD) model. Simulated road shapes are three types, namely at-grade, depressed, and filled road. The realizable k-${\varepsilon}$ model in FLUENT CFD code was used to simulate the flow and dispersion around road. The selected concentration profile results were compared with the wind tunnel experiments. The overall concentration profile results show good agreement with the wind tunnel results. The results showed that noise barriers, which positioned around the at-grade road, decrease the horizontal impact distance (In this study, the impact distance was defined as the distance from road surface origin coordinate to the position whose mass fraction is 0.1.) lower 0.33~0.65 times and change the vertical air pollution impact distance larger 2.0~2.27 times than those of no barrier case. In case of filled road, noise barriers decrease the horizontal impact distance lower 0.24~0.65 times and change the vertical air pollution impact distance larger 3.33~3.55 times than those of no barrier case. The depressed road increase 1.53~1.68 times the vertical air pollution impact distance. It contributes the decrease of horizontal air pollution impact distance 0.32~0.60 times compare with no barrier case.

• Journal of Environmental Science International
• /
• v.27 no.4
• /
• pp.241-250
• /
• 2018

The objective of this study was to estimate air quality trends in the study area by surveying monthly and seasonal concentration trends. To do this, the mass concentration of $PM_{10}$ samples and the metals, ions, and total carbon in the $PM_{10}$ were analyzed. The mean concentration of $PM_{10}$ was $33.9{\mu}g/m^3$. The composition of $PM_{10}$ was 39.2% ionic species, 5.1% metallic species, and 26.6% carbonic species (EC and OC). Ionic species, especially sulfate, ammonium, and nitrate, were the most abundant in the $PM_{10}$ and had a high correlation coefficient with $PM_{10}$. Seasonal variation of $PM_{10}$ showed a similar pattern to those of ionic and metallic species. with high concentration during the winter and spring seasons. $PM_{10}$ showed high correlation with the ionic species $NO_3{^-}$ and $NH_4{^+}$. In addition, $NH_4{^+}$ was highly correlated with $SO{_4}^{2-}$ and $NO_3{^-}$. We obtained four factors through factor analysis and determined the pollution sources using the United States Environmental Protection Agency(U.S. EPA) pollution profile. The first factor accounted for 51.1% of $PM_{10}$ from complex sources, that is, soil, motor vehicles, and secondary particles: the second factor indicated marine sources; the third factor, industry-related sources; and the last factor, heating-related sources. However, the pollution profile used in this study may be somewhat different from the actual situation in Korea because it was from US EPA. Therefore, to more accurately estimate the pollutants present, it is necessary to create a pollution profile for Korea.

• Journal of Environmental Science International
• /
• v.28 no.4
• /
• pp.413-422
• /
• 2019

The objective of this study was to estimate the trends of air quality in the study area by analyzing monthly and seasonal concentration trends obtained from sampled data. To this aim, the mass concentrations of $PM_{2.5}$ in the air were analyzed, as well as those of metals, ions, and total carbon within the $PM_{2.5}$. The mean concentration of $PM_{2.5}$ was $22.7{\mu}g/m^3$. The mass composition of $PM_{2.5}$ was as follows: 31.1% of ionic species, 2.2% of metallic species, and 26.7% of carbonic species (EC and OC). Ionic species, especially sulfate, ammonium, and nitrate, were the most abundant in the $PM_{2.5}$ and exhibited a high correlation coefficient with the mass concentration of $PM_{2.5}$. Seasonal variations of $PM_{2.5}$ showed a similar pattern to those of ionic and metallic species, with high concentrations during winter and spring. $PM_{2.5}$ also had a high correlation with the ionic species $NO_3{^-}$ and $NH_4{^+}$. In addition, $NH_4{^+}$ was highly correlated with $NO_3{^-}$. Through factor analysis, we identified four controlling factors, and determined the pollution sources using the United States Environmental Protection Agency(U.S. EPA) pollution profile. The first factor, accounting for 19.1% of $PM_{2.5}$ was attributed to motor vehicles and heating-related sources: the second factor indicated industry-related sources and secondary particles, and the other factors indicated soil, industry-related and marine sources. However, the pollution profile used in this study may be somewhat different from the actual situation in Korea, since it was obtained from US EPA. Therefore, to more accurately estimate the pollutants present in the air, a pollution profile for Korea should be produced.

• Proceedings of the Korea Air Pollution Research Association Conference
• /
• 2009.10a
• /
• pp.489-490
• /
• 2009

• Magazine of the Korean Society of Agricultural Engineers
• /
• v.34 no.E
• /
• pp.1-11
• /
• 1992

Increasing national concern on nonpoint source pollution of surface and ground water Systems has led researchers and policy makers to develop certain agricultural Best Management Practices. As an initial step of broad study program above mentioned, this study reflected the effects of different tillage practice on bulk density and degree of saturation on two regional soils, namely Tama silt loam and Catlin silt loam. Results may help to clarify some of the conflicting findings on the impact of tillage systems on these parameters and it may also explain some of the reasons for specific role that different tillage systems play regarding nonpoint source pollution from agricultural fields.

• Magazine of the Korean Society of Agricultural Engineers
• /
• v.44 no.4
• /
• pp.51-61
• /
• 2002

The objective of this study is to develop GLEANS-PADDY model to predict nutrients loading from paddy-field areas. This model is developed by modifying the GLEANS model which is used for uplands, and composed of hydrology and nutrient submodels. The optimal field size for CLEANS-PADDY model application is about up to 50 ha with mild slope, relatively homogeneous Soils and spatially rainfall, and a single crop farming. The CLEAMS model is modified to handle ponded soil surface condition and saturated soil profile in paddy field. In the hydrology submodel of the CLEAMS-PADDY model. the ponded depth routing method is used to handle the ponded water condition of paddy field. To compute potential evapotranspiration the FAO-24 Corrected Blaney-Criddle method is used for paddy field instead of Penman-Monteith method in the CLEAMS model. In the nutrients submodel of the CLEAMS-PADDY model, the soil was assumed saturated and soil profile in the root zone was divided into oxidized and reduced zones.

• Journal of Korean Society for Atmospheric Environment
• /
• v.19 no.6
• /
• pp.789-803
• /
• 2003

The purpose of this study is to compare the usefulness between Gaussian dispersion model and receptor model with the experimental result of the dispersion tracing of the particulate pollutants from Taean coal-fired power plants. For this purpose, the component analysis of the collected PM 10 samples was performed. In order to trace the pollution sources, factor analysis was done with the result of the component analysis. As a result of the correlativity analysis of the fifteen power plants' profiles offered by US EPA, the correlativity of No.11202 source profile showed highest rate up to 84.5%. Thus it was adopted as proper one and the contribution rate by each pollution source was calculated by Chemical Mass Balance (CMB)-8 model. The contribution rate, which was the effect rate of the power plants on each measuring point, were calculated with a range of 24∼52％ and the standard error was below 0.9 $\mu\textrm{g}$/㎥. This indicates the selection of the source profile was appropriate. Also, the concentrations of each point were calculated by the ISCST3 which is suggested by US EPA as one of the regulatory Gaussian dispersion model. The calculation result showed that the predicted concentration was 50∼58 $\mu\textrm{g}$/㎥, comparing with the measured result of 9∼65 $\mu\textrm{g}$/㎥. It was found that the concentration calculated by ISCST3 was underpredicted. It was thought that the receptor model was more favorable than the Gaussian dispersion model in estimating the effect of the particulate matter on a certain receptive point.

• Journal of Microbiology and Biotechnology
• /
• v.20 no.5
• /
• pp.925-934
• /
• 2010

Three typical biological solid wastes, namely, animal manure, garbage, and sewage sludge, were compared with regard to the composting process and the changes in microbial community structure. The effects of different bulking agents such as rice straw, vermiculite, sawdust, and waste paper were compared in manure compost. The differences in the microbial community were characterized by the quinone profile method. The highest mass reduction was found in garbage composting (56.8%), compared with manure and sludge (25% and 20.2%, respectively). A quinone content of $305.2\;{\mu}mol/kg$ was observed in the late stage of garbage composting, although the diversity index of the quinone profile was 9.7, lower than that in manure composting. The predominant quinone species was found to be MK-7, which corresponds to Gram-positive bacteria with a low G+C content, such as Bacillus. The predominance of MK-7 was especially found in the garbage and sludge composting process, and the increase in quinones with partially saturated long side-chains was shown in the late composting process of manure, which corresponded to the proliferation of Actinobacteria. The effects of different bulking agents on the composting process was much smaller than the effects of different raw materials. High organic matter content in the raw materials resulted in a higher microbial biomass and activity, which was connected to the high mass reduction rate.

• Agricultural and Biosystems Engineering
• /
• v.6 no.2
• /
• pp.39-46
• /
• 2005

Because soil compaction is a concern in crop production and environmental pollution, quantification and management of spatial and vertical variability in soil compaction for soil strength) would be a useful aspect of site -specific field management. In this paper, a soil strength profile sensor (SSPS) that could take measurements continuously while traveling across the field was developed and the performance was evaluated through laboratory and field tests. The SSPS obtained data simultaneously at 5 evenly spaced depths up to 50 em using an array of load cells, each of which was interfaced with a soil-cutting tip. Means of soil strength measurements collected in adjacent, parallel transects were not significantly different, confirming the repeatability of soil strength sensing with the SSPS. Maps created with sensor data showed spatial and vertical variability in soil strength. Depth to the restrictive layer was different for different field locations, and only 5 to 16% of the tested field areas were highly compacted.

• Transactions on Electrical and Electronic Materials
• /
• v.18 no.5
• /
• pp.246-249
• /
• 2017

Pollution flashover of outdoor insulators is a common risk, which affects the safe operation of overhead transmission networks. Early electrical power systems, which feature insulators made from ceramic materials have been used all over the world with good performance. At present, non-ceramic insulators are in common use, as a result of their good electrical as well as mechanical properties. The aim of this paper is to discuss and compare the flashover performance of insulators typically used in power lines, such as, porcelain, ethylene-propylene-diene-monomer (EPDM) rubber, room temperature vulcanized (RTV) and high temperature vulcanized (HTV) coated silicone rubber. The effect of various parameters, including the severity of pollution, ice accumulation, and shade profile, are considered.. From the studies reviewed it was concluded that there is a distinct difference in the flashover voltages of different types of insulators, and the silicone provides the best flashover performance of all insulating materials.