• 한국대기환경학회지
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• 제27권1호
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• pp.30-40
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• 2011

Numerical simulations were carried out to investigate the impact of SST spatial distribution on the result of air quality modeling. Eulerian photochemical dispersion model CAMx (Comprehensive Air quality Model with eXtensions, version 4.50) was applied in this study and meteorological fields were prepared by RAMS (Regional Atmospheric Modeling System). Three different meteorological fields, due to different SST spatial distributions were used for air quality modeling to assess the sensitivity of CAMx modeling to the different meteorological input data. The horizontal distributions of surface ozone concentrations were analyzed and compared. In each case, the simulated ozone concentrations were different due to the discrepancies of horizontal SST distributions. The discrepancies of land-sea breeze velocity caused the difference of daytime and nighttime ozone concentrations. The result of statistic analysis also showed differences for each case. Case NG, which used meteorological fields with high resolution SST data was most successfully estimated correlation coefficient, root mean squared error and index of agreement value for ground level ozone concentration. The prediction accuracy was also improved clearly for case NG. In conclusion, the results suggest that SST spatial distribution plays an important role in the results of air quality modeling on high ozone episode at coastal region.

• 한국환경과학회지
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• 제13권4호
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• pp.377-387
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• 2004

This study has been performed to clarify the characteristics of temporal and spatial distribution of surface ozone concentration over Jeju Island, one of the cleanest areas in Korea with low emissions of air pollutants. Ozone data are monitored at four sites in Jeju Island. These monitoring sites are located at two urban area(referred to Ido and Donghong), coastal area(Gosan site) and forest site(Chuna site). Ozone data has been routinely collected at these sites for the late four years. The patterns of seasonal cycle of ozone concentrations at all stations show the bimodal with the peaks on spring and autumn and a significant summer minimum. However, the patterns of diurnal variations at rural station, i.e., Gosan and Chuna sites are considerably different to those at urban stations such as Ido and Donghong sites. The patterns of $\DeltaO_3$ variations are very similar with those of monthly mean ozone concentrations and $\DeltaO_3$ values are exceeded 30 ppb, at urban stations. This may be that urban stations are more influenced by local photochemical reactions rather than rural stations. In order to assess the potential roles of meteorological parameters on ozone formation, the meteorological parameters, such as radiation, temperature, and wind are monitored together with ozone concentrations at all stations. The relationships of meteorological parameters to the corresponding ozone concentration are found to be insignificant in Jeju Island. However, at Gosan and Donghong stations, when the sea breeze blew toward the station, the ozone concentration is considerably increased.

• 한국입자에어로졸학회지
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• 제7권1호
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• pp.21-30
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• 2011

The spatial distributions of air pollutants, in particular, ultrafine particles near traffic congestion roads at urban areas need to reduce human exposure levels for protecting public health. In this study, the number concentrations of ultrafine particles larger than 5 nm were measured every second during driving on the major roads of Nowon-gu, Seoul for 1.6 h using a mobile emission laboratory on October 5, 2010. The ultrafine particle number concentrations ranged from 7,009 to $265,600particles/cm^3$ with an average of $55,570particles/cm^3$, and these levels were comparable to concentrations of ultrafine particles larger than 3 or 7 nm on the arterial roads at urban areas in Los Angeles, USA and Zurich, Switzerland. It was frequently observed that the ultrafine particle number increased rapidly when vehicle speed was accelerated and it decreased sharply when vehicle speed was decelerated. The high peak events of ultrafine particle concentration larger than $200,000particles/cm^3$ were observed seven times during the measurement period. From the three repeated measurements during the short period of 50 min, it was concluded that the ultrafine particle number concentration on the road was significantly time-dependent. This on-road measurement approach can be utilized to manage vehicle-related air pollution in urban.

• Communications for Statistical Applications and Methods
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• 제27권5호
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• pp.547-568
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• 2020

Modeling the statistical autocorrelations in spatial data is often achieved through the estimation of the variograms, where the selection of the appropriate valid variogram model, especially for small samples, is crucial for achieving precise spatial prediction results from kriging interpolations. To estimate such a variogram, we traditionally start by computing the empirical variogram (traditional Matheron or robust Cressie-Hawkins or kernel-based nonparametric approaches). In this article, we conduct numerical studies comparing the performance of these empirical variograms. In most situations, the nonparametric empirical variable nearest-neighbor (VNN) showed better performance than its competitors (Matheron, Cressie-Hawkins, and Nadaraya-Watson). The analysis of the spatial groundwater dataset used in this article suggests that the wave variogram model, with hole effect structure, fitted to the empirical VNN variogram is the most appropriate choice. This selected variogram is used with the ordinary kriging model to produce the predicted pollution map of the nitrate concentrations in groundwater dataset.

• 한국대기환경학회지
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• 제33권3호
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• pp.277-288
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• 2017

Previous studies of health effects of $PM_{2.5}$ performed spatial monitoring campaigns to assess spatial variability of $PM_{2.5}$ across people's residences. Highly reliable portable and cost-effective samplers will be useful for such campaigns. This study aimed to investigate applicability of the Deployable Particulate Impact Sampler(DPIS), one of the compact impact samplers, to spatial monitoring campaigns of $PM_{2.5}$ in Seoul, Korea. The investigation focused on the consistency of $PM_{2.5}$ concentrations measured by DPISs compared to those by the Low-volume Cyclone sampler (LCS). LCS has operated at a fixed site in the Seoul National University Yeongeon campus, Seoul, Korea since 2003 and provided qualified $PM_{2.5}$ data. $PM_{2.5}$ sampling of DPISs was carried out at the same site from November 17, 2015 through February 3, 2016. $PM_{2.5}$ concentrations were quantified by the gravimetric method. Using a duplicated DPIS, we confirmed the reliability of DPIS by computing relative precision and mean square error-based R squared value ($R^2$). Relative precision was one minus the difference of measurements between two samplers relative to the sum. For accuracy, we compared $PM_{2.5}$ concentrations from four DPISs (DPIS_Tg, DPIS_To, DPIS_Qg, and DPIS_Qo) to those of LCS. Four samplers included two types of collection filters(Teflon, T; quartz, Q) and impaction discs(glass fiber filter, g; pre-oiled porous plastic disc, o). We assessed accuracy using accuracy value which is one minus the difference between DPIS and LCS $PM_{2.5}$ relative to LCS $PM_{2.5}$ in addition to $R^2$. DPIS showed high reliability (average precision=97.28%, $R^2=0.98$). Accuracy was generally high for all DPISs (average accuracy=83.78~88.88%, $R^2=0.89{\sim}0.93$) except for DPIS_Qg (77.35~78.35%, 0.82~0.84). Our results of high accuracy of DPIS compared to LCS suggested that DPIS will help the assessment of people's individual exposure to $PM_{2.5}$ in extensive spatial monitoring campaigns.

• 한국환경과학회지
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• 제26권1호
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• pp.55-65
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• 2017

Average concentration of PM in Seoul metropolitan area satisfied the Korean air quality standard in 2010. Furthermore, concentration of PM in all boroughs across Seoul met the air environment standard in 2012. $PM_{10}$ concentration was relatively higher in center of Seoul in comparison to the rest, while $PM_{2.5}$ concentration showed exactly the contrary result. We analyzed the effect that PM emissions from vehicles would have on PM concentrations across Seoul. The results showed that average annual PM concentration recently decreased in Seoul although the number of vehicles registered annually continued its upward trend. By contrast, average fine dust concentrations in Seoul showed a decline which suggested that correlation between annual average PM concentrations and number of registered vehicles remained low. However, year-on-year vehicle registration rate recently showed a declining tendency in the same way as the trend of changes in average PM concentrations. Particularly, the upward trend in annual average PM concentrations in 2002 and 2007 was consistent with the increase in vehicle registration rate, suggesting that vehicle registration rate was closely associated with changes in PM concentrations.

• 대한원격탐사학회지
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• 제23권3호
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• pp.161-169
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• 2007

A study was conducted in the Hong Kong with the aim of deriving an algorithm for the retrieval of suspended sediment (SS) and sea surface salinity (SSS) concentrations from Aqua/MODIS level 1B reflectance data with 250m and 500m spatial resolutions. 'In-situ' measurements of SS and SSS were also compared with coincident MODIS spectral reflectance measurements over the ocean surface. This is the first study of SSS modeling in Southeast Asia using earth observation satellite images. Three analysis techniques such as multiple regression, linear regression, and principal component analysis (PCA) were performed on the MODIS data and the 'in-situ' measurement datasets of the SS and SSS. Correlation coefficients by each analysis method shows that the best correlation results are multiple regression from the 500m spatial resolution MODIS images, $R^2$= 0.82 for SS and $R^2$ = 0.81 for SSS. The Root Mean Square Error (RMSE) between satellite and 'in-situ' data are 0.92mg/L for SS and 1.63psu for SSS, respectively. These suggest that 500m spatial resolution MODIS data are suitable for water quality modeling in the study area. Furthermore, the application of these models to MODIS images of the Hong Kong and Pearl River Delta (PRO) Region are able to accurately reproduce the spatial distribution map of the high turbidity with realistic SS concentrations.

• 한국환경보건학회지
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• 제40권1호
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• pp.27-37
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• 2014

Objectives: On September 27, 2012, leakage of anhydrous hydrofluoric acid occurred in a chemical plant in the Gumi National Industrial Complex. Following the accident, local factory workers and residents complained of abnormal health conditions. In addition, visual discolorations were widely observed in crops and trees in surrounding areas. The main objectives of the present study were to identify the area that was affected by the spill using data obtained from plants, soil, and water samples after the accident. Methods: Fluoride concentrations were analyzed in pine tree needles, soil, nearby streams, ponds and reservoirs collected from an area within a radius of three kilometers from the plant where the leak occurred. Fluoride concentrations in the air at the time of leakage were then estimated from fluoride concentrations that were measured in the pine tree needles. A Kriged map was developed to describe the spatial distribution of hydrofluoric acid at the time of the leakage and was compared with the area designated as a Special Disaster Zone by the government. Results: The Special Disaster Zone did not include all the affected area that was estimated by the Kriged map. Analytical results of the environmental samples also supported this discrepancy. Conclusion: Using plants, atmospheric concentrations of fluoride at the time of the leakage could be estimated. For the area that was identified as affected, further public health risk assessment and environmental risk assessment should be considered. Also, in the absence of air monitoring at the time of leakage, studies employing plants may be conducted in order to better understand the spatial extent and severity of the contamination.

• Asian-Australasian Journal of Animal Sciences
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• 제32권5호
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• pp.637-647
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• 2019

Objective: The study aimed at quantifying seasonal and spatial variations in availability and nutritive value of herbaceous vegetation on native pastures and supplement feedstuffs for domestic ruminants in Western Kenya. Methods: Samples of herbaceous pasture vegetation (n = 75) and local supplement feedstuffs (n = 46) for cattle, sheep, and goats were collected in 20 villages of three geographic zones (Highlands, Mid-slopes, Lowlands) in Lower Nyando, Western Kenya, over four seasons of one year. Concentrations of dry matter (DM), crude ash (CA), ether extract (EE), crude protein (CP), neutral detergent fibre (NDF), gross energy (GE), and minerals were determined. Apparent total tract organic matter digestibility (dOM) was estimated from in vitro gas production and proximate nutrient concentrations or chemical composition alone using published prediction equations. Results: Nutrient, energy, and mineral concentrations were 52 to 168 g CA, 367 to 741 g NDF, 32 to 140 g CP, 6 to 45 g EE, 14.5 to 18.8 MJ GE, 7.0 to 54.2 g potassium, 0.01 to 0.47 g sodium, 136 to 1825 mg iron, and 0.07 to 0.52 mg selenium/kg DM. The dOM was 416 to 650 g/kg organic matter but differed depending on the estimation method. Nutritive value of pasture herbage was superior to most supplement feedstuffs, but its value strongly declined in the driest season. Biomass yields and concentrations of CP and potassium in pasture herbage were highest in the Highlands amongst the three zones. Conclusion: Availability and nutritive value of pasture herbage and supplement feedstuffs greatly vary between seasons and geographical zones, suggesting need for season- and region-specific feeding strategies. Local supplement feedstuffs partly compensate for nutritional deficiencies. However, equations to accurately predict dOM and improved knowledge on nutritional characteristics of tropical ruminant feedstuffs are needed to enhance livestock production in this and similar environments.

• 한국대기환경학회지
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• 제32권1호
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• pp.114-126
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• 2016

Many cohort studies have reported associations of individual-level long-term exposures to $PM_{10}$ and health outcomes. Individual exposures were often estimated by using exposure prediction models relying on $PM_{10}$ data measured at national regulatory monitoring sites. This study explored spatial and temporal characteristics of regulatory $PM_{10}$ measurement data in South Korea and suggested $PM_{10}$ concentration metrics as long-term exposures for assessing health effects in cohort studies. We obtained hourly $PM_{10}$ data from the National Institute of Environmental Research for 2001~2012 in South Korea. We investigated spatial distribution of monitoring sites using the density and proximity in each of the 16 metropolitan cities and provinces. The temporal characteristics of $PM_{10}$ measurement data were examined by annual/seasonal/diurnal patterns across urban background monitoring sites after excluding Asian dust days. For spatial characteristics of $PM_{10}$ measurement data, we computed coefficient of variation (CV) and coefficient of divergence (COD). Based on temporal and spatial investigation, we suggested preferred long-term metrics for cohort studies. In 2010, 294 urban background monitoring sites were located in South Korea with a site over an area of $415.0km^2$ and distant from another site by 31.0 km on average. Annual average $PM_{10}$ concentrations decreased by 19.8% from 2001 to 2012, and seasonal $PM_{10}$ patterns were consistent over study years with higher concentrations in spring and winter. Spatial variability was relatively small with 6~19% of CV and 21~46% of COD across 16 metropolitan cities and provinces in 2010. To maximize spatial coverage and reflect temporal and spatial distributions, our suggestion for $PM_{10}$ metrics representing long-term exposures was the average for one or multiple years after 2009. This study provides the knowledge of all available $PM_{10}$ data measured at national regulatory monitoring sites in South Korea and the insight of the plausible longterm exposure metric for cohort studies.