• Journal of Korean Society for Atmospheric Environment
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• v.17 no.5
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• pp.395-405
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• 2001

To make an assessment of the compatibility between DOAS and conventional point monitoring system (MCSAM-2: MS2), we investigated the concentrations of three criteria pollutants which include S $O_2$, N $O_2$, and $O_3$from a national monitoring station in Seoul during the periods of June 1999~August 2000. The average concentration values for the whole study period derived from hourly concentration data sets of those three species indicated that the mean differences between the two methods can be approximated as 18%. When the bias structure of two systems was evaluated through the computation of percent difference(PD) between the two such as ( $C_{DOAS}$- $C_{conventional}$ $C_{DOAS}$*100, differences between the two systems appeared to be quite systematic among different compounds. While the mode of bias peaked at 0~20% or 20~40% in terms of PD values, the cause of such positive bias mainly arised from generally enhanced concentration values of DOAS system. The structure of bias among different species was further assessed through linear regression analysis. Results of the analysis indicated that the dominant portions of differences observed from two monitoring systems can be accounted for by the systematic differences in their spanning and zeroing systems. S $O_2$(MS2)=0.6385 S $O_2$(DOAS)+2.0985($r^2$=0.7894) N $O_2$(MS2)=0.6548 N $O_2$(DOAS)+7.437($r^2$=0.7687) $O_3$(MS2)=1.0359 $O_3$(DOAS)-7.7885($r^2$=0.7944) The findings of slope values at around 0.64~0.65 from two species suggest that DOAS should respond more sensitively in upper bound concentration range. The offset values apart from zero indicate that more deliberate comparison needs to be made between these monitoring systems. However, based on the existence of strong correlations from at least 8,000 data points for each species of comparison, we were able to conclude that the compatibility of two monitoring systems is highly significant. With the improvement of calibration techniques for the DOAS system. its applicability for routine monitoring of airborne pollutant species is expected to be quite extendable.

• Korean Journal of Soil Science and Fertilizer
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• v.44 no.6
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• pp.991-997
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• 2011

Soil erosion and sediment has been known as one of pollutants causing water quality degradation in water bodies. With global warming issues worldwide, various soil erosion studies have been performed. Although on-site monitoring of sediment loss would be an ideal method to evaluate soil erosion condition, modeling approaches have been utilized to estimate soil erosion and to evaluate various best management practices on soil erosion reduction. Although the USLE has been used in soil erosion estimation for the last 40 years, the USLE model has limitations in estimating event-based soil erosion reflecting rainfall intensity and rainfall duration for long-term period. Thus, the calibrated model, capable of simulating soil erosion using hourly rainfall data, was utilized in this study to evaluate the effects of rainfall amount and rainfall intensity on soil erosion. It was found that USLE soil erosion value is $3.06ton\;ha^{-1}\;yr^{-1}$, while soil erosion values from 2006~2010 were $2.469ton\;ha^{-1}\;yr^{-1}$, $0.882ton\;ha^{-1}\;yr^{-1}$, $1.489ton\;ha^{-1}\;yr^{-1}$, $2.158ton\;ha^{-1}\;yr^{-1}$, $1.602ton\;ha^{-1}\;yr^{-1}$, respectively. Especially, soil erosion from single storm event for 2008-2010 would be responsible for 30% or more of annual soil loss. As shown in this study, hourly soil erosion estimation system would provide more detailed output from the study area. In addition, the effects of rainfall intensity on soil erosion could be evaluated with this system.

• Atmosphere
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• v.34 no.3
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• pp.283-304
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• 2024

This study analyzed the variability and correlation between ground-level air pollutant concentrations and the atmospheric mixing layer height using data from four types of air pollutants (PM_2.5, PM₁₀, NO₂, and O₃) collected at AirKorea monitoring stations nationwide over a five-year period (2018~2022), and aerosol backscatter data observed by the Vaisala CL31 to derive atmospheric mixing layer heights. The five-year trends and variability of ground-level air pollutant concentrations under seasonal and hourly conditions were examined, as well as the seasonal distribution and diurnal variation of the atmospheric mixing layer height. Five correlation coefficient methodologies were applied to analyze the correlations between ground-level air pollutants and atmospheric mixing layer height under various seasonal and hourly conditions, confirming the dilution effect of the atmospheric mixing layer height. The results showed that PM_2.5, PM₁₀, and NO₂ generally had negative correlations with the atmospheric mixing layer height, while O₃ showed a strong positive correlation up to an altitude of 1,200~1,500 meters, and a negative correlation beyond that altitude. It was also shown that a single high concentration event (e.g., PM₁₀) can alter the overall correlation. The correlation can also vary depending on the characteristics of the correlation coefficient methodology, highlighting the importance of applying the appropriate methodology for each case during the analysis process.

• Journal of Environmental Science International
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• v.27 no.10
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• pp.925-931
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• 2018

The characteristics of $PM_{10}$, $PM_{2.5}$ and Ratio($PM_{2.5}/PM_{10}$) of 11 urban air monitoring stations in Gyeongnam were analyzed for the last 3 years('15~'17). The average of the all stations was $PM_{10}\;45{\mu}g/m^3$, $PM_{2.5}\;24{\mu}g/m^3$ and Ratio 0.54, and annual reduction rates were $PM_{10}-2.9%$, $PM_{2.5}-2.7%$ and Ratio -1.2%, respectively. The seasonal characteristics of $PM_{10}$ were spring $54{\mu}g/m^3$ > winter $48{\mu}g/m^3$ > summer/autumn $40{\mu}g/m^3$, $PM_{2.5}$ were spring/winter $26{\mu}g/m^3$ > summer 23 > autumn $22{\mu}g/m^3$ and Ratio were summer 0.56 > winter 0.55 > autumn 0.54 > spring 0.51, respectively. The hourly characteristics of $PM_{10}$ were $11{\mu}g/m^3$ higher than 09:00~12:00 at 03:00~06:00, $PM_{2.5}$ were $6{\mu}g/m^3$ higher than 09:00~12:00 at 17:00~18:00 and Ratio were 0.07 higher than 04:00~06:00 at 19:00. By site, the highest concentration of $PM_{10}$ was YJ site $53{\mu}g/m^3$ and $PM_{2.5}$ was HW site $28{\mu}g/m^3$. And Ratio at HD site showed the largest reduction from '15 0.62 to '17 0.52.

• Journal of Korean Society on Water Environment
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• v.28 no.3
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• pp.375-383
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• 2012

Soil erosion has been emphasized as serious environmental problem affecting water quality in the receiving waterbodies. Recently, Best Management Practices (BMPs) have been applied at a field to reduce soil erosion and its effectiveness in soil erosion reduction has been monitored with various methods. Although monitoring at fields/watershed outlets would be accurate way for these ends, it is not possible at some fields/watersheds due to various limitations in direct monitoring. Thus modeling has been suggested as an alternative way to evaluate effects of the BMPs. Most models, which have been used in evaluating hydrology and water quality at a watershed, could not reflect rainfall intensity in runoff generation and soil erosion processes. In addition, source codes of these models are not always public for modification/enhancement. Thus, runoff-sediment evaluation system using hourly rainfall data and vegetated filter strip (VFS) evaluation module at field level were developed using open source MapWindow GIS component in this study. This evaluation system was applied to Bangdongri, Chuncheonsi to evaluate its prediction ability and VFS module in this study. The NSE and $R^2$ values for runoff estimation were 0.86 and 0.91, respectively, and measured and simulated sediment yield were 15.2 kg and 16.5 kg indicating this system, developed in this study, can be used to simulate runoff and sediment yield with acceptable accuracies. Nine VFS scenarios were evaluated for effectiveness of soil erosion reduction. Reduction efficiency of the VFS was high when sediment inflow was small. As shown in this study, this evaluation system can be used for evaluation BMPs with local rainfall intensity and variations considered with ease-of-use GIS interface.

• Journal of Environmental Impact Assessment
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• v.30 no.4
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• pp.237-246
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• 2021

The similarity of hourly PM₁₀ and PM_2.5 concentration profiles of the atmospheric monitoring stations in Gyeonggi-do was evaluated through the multilateral analysis between stations. The existing category for most stations in the regions shows relatively low Pearson correlation values of 0.68 and 0.7 for PM₁₀ and PM_2.5 on average respectively, and some monitoring stations revealed high relationships over 0.8 to other regions. Since the current regions are mainly categorized by cluster analysis based on the number of occurrence of high concentration events and geological factors, it is necessary to reclassify them by concentration characteristics for precise fine dust management. In accordance, multi-dimensional scaling being able to visualize could categorize the regions based on regional emission contribution rate and hourly fine dust concentration. As a result of the current analysis, PM₁₀ and PM_2.5 could be reclassified into five regions and fourregions, respectively.

• Journal of Environmental Health Sciences
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• v.47 no.6
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• pp.521-529
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• 2021

Background: The coronavirus disease (COVID-19) has caused changes in human activity, and these changes may possibly increase or decrease exposure to fine dust (PM_2.5). Therefore, it is necessary to evaluate the exposure to PM_2.5 in relation to the outbreak of COVID-19. Objectives: The purpose of this study was to compare and evaluate the exposure to PM_2.5 concentrations by the variation of dynamic populations before and after the outbreak of COVID-19. Methods: This study evaluated exposure to PM_2.5 concentrations by changes in the dynamic population distribution in Guro-gu, Seoul, before and after the outbreak of COVID-19 between Jan and Feb, 2020. Gurogu was divided into 2,204 scale standard grids of 100 m×100 m. Hourly PM_2.5 concentrations were modeled by the inverse distance weight method using 24 sensor-based air monitoring instruments. Hourly dynamic population distribution was evaluated according to gender and age using mobile phone network data and time-activity patterns. Results: Compared to before, the population exposure to PM_2.5 decreased after the outbreak of COVID-19. The concentration of PM_2.5 after the outbreak of COVID-19 decreased by about 41% on average. The variation of dynamic population before and after the outbreak of COVID-19 decreased by about 18% on average. Conclusions: Comparing before and after the outbreak of COVID-19, the population exposures to PM_2.5 decreased by about 40%. This can be explained to suggest that changes in people's activity patterns due to the outbreak of COVID-19 resulted in a decrease in exposure to PM_2.5.

• Journal of Korean Society for Atmospheric Environment
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• v.32 no.1
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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.

• Journal of Ecology and Environment
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• v.34 no.2
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• pp.149-156
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• 2011

Phenological variables derived from remote sensing are useful in determining the seasonal cycles of ecosystems in a changing climate. Satellite remote sensing imagery is useful for the spatial continuous monitoring of vegetation phenology across broad regions; however, its applications are substantially constrained by atmospheric disturbances such as clouds, dusts, and aerosols. By way of contrast, a tower-based ground remote sensing approach at the canopy level can provide continuous information on canopy phenology at finer spatial and temporal scales, regardless of atmospheric conditions. In this study, a tower-based ground remote sensing system, called the "Phenological Eyes Network (PEN)", which was installed at the Gwangneung Deciduous KoFlux (GDK) flux tower site in Korea was introduced, and daily phenological progressions at the canopy level were assessed using ratios of red, green, and blue (RGB) spectral reflectances obtained by the PEN system. The PEN system at the GDK site consists of an automatic-capturing digital fisheye camera and a hemi-spherical spectroradiometer, and monitors stand canopy phenology on an hourly basis. RGB data analyses conducted between late March and early December in 2009 revealed that the 2G_RB (i.e., 2G - R - B) index was lower than the G/R (i.e., G divided by R) index during the off-growing season, owing to the effects of surface reflectance, including soil and snow effects. The results of comparisons between the daily PEN-obtained RGB ratios and daily moderate-resolution imaging spectroradiometer (MODIS)-driven vegetation indices demonstrate that ground remote sensing data, including the PEN data, can help to improve cloud-contaminated satellite remote sensing imagery.

• Proceedings of the Korean Environmental Sciences Society Conference
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• 1997.10a
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• pp.1.1-32
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• 1997

Atmospheric monitoring capabilities were established in 1988 by the University of Florida at Duke forest, near Durham. NC: Cary forest, near Gainesville, FL: and Austin forest, near Nacogdoches, TX. Continuous (hourly averaged) measurements of air quality (ozone, nitrogen oxides and sulfur dioxide) and meteorological variables were made at these three low elevation (< 200 meters), rural locations in the southeastern U.S. for more than three years. During the same period at these sites wet and dry acid deposition samples were collected and analyzed on an event and weekly basis, respectively The monitoring locations were selected to determine actual atmospheric exposure indices for southern pine species in support of on-site surrogate exposure chamber studies conducted by Southern Commercial Forest Research Cooperative (SCFRC) investigators. Daily and quarterly averaged ozone maxima were higher (55 ppb) at the northernmost site in the network (Duke forest) in the second and third quarters (spring and summer seasons) and lower (35 ppb) in the first and fourth quarters (winter and fall seasons), when compared to ozone levels at the two southernmost sites (Cary and Austin forests). Seasonal ozone levels at the latter two sites were similar Nitrogen oxieds and sulfur dioxide levels were insignificant (< 5 ppb) most of the time at all sites, although soil emissions of NO at two sites were found to influence nighttime ozone concentrations. Typical maximum quarterly and annual aggregate ozone exposure indices were significantly higher at Duke forest (92.5/259 ppm-hr) than those values observed at the two southern sites (65.6/210 ppm-hr). Acid deposition (wet and dry) components concentrations and deposition fluxes observed at the Duke forest, NC piedmont site, were generally greater, dependent on site and season, than corresponding variables measured at either of the two southern coastal plain sites (Cary and Austin forests). Acid deposition variables observed at the latter two sites were remarkably similar, both qualitatively and quantitatively, although the sites were located 1300 km apart. A comparison of deposition fluxes of elemental nitrogen (NO3, NH4') and sulfur (5042-, SO3) components in wet and dry forms indicated that wet deposition accounts for approximately 70% of the total nitrogen and 73% of the total sulfur input on an annual equivalent basis at all sites.