• Journal of Environmental Health Sciences
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• v.47 no.3
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• pp.267-278
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• 2021

Objectives: Using atmospheric dispersion representative models (AERMOD and CALPUFF), the emissions characteristics of each model were compared and analyzed in ready-mixed concrete manufacturing facilities that generate a large amount of particulate matter (PM-10, PM-2.5). Methods: The target facilities were the ready-mixed concrete manufacturing facilities (Siheung RMC, Goyang RMC, Ganggin RMC) and modeling for each facility was performed by dividing it into construction and operation times. The predicted points for each target facility were selected as 8-12ea (Siheung RMC 10, Goyang RMC 8, and Gangjin RMC 12ea) based on an area within a two-kilometer radius of each project district. The terrain input data was SRTM-3 (January-December 2019). The meteorological input data was divided into surface weather and upper layer weather data, and weather data near the same facility as the target facility was used. The predicted results were presented as a 24-hour average concentration and an annual average concentration. Results: First, overall, CALPUFF showed a tendency to predict higher concentrations than AERMOD. Second, there was almost no difference in the concentration between the two models in non-complex terrain such as in mountainous areas, but in complex terrain, CALPUFF predicted higher concentrations than AERMOD. This is believed to be because CALPUFF better reflected topographic characteristics. Third, both CALPUFF and AERMOD predicted lower concentrations during operation (85.2-99.7%) than during construction, and annual average concentrations (76.4-99.9%) lower than those at 24 hours. Fourth, in the ready-mixed concrete manufacturing facility, PM-10 concentration (about 40 ㎍/m³) was predicted to be higher than PM-2.5 (about 24 ㎍/m³). Conclusions: In complex terrain such as mountainous areas, CALPUFF predicted higher concentrations than AERMOD, which is thought to be because CALPUFF better reflected topographic characteristics. In the future, it is recommended that CALPUFF be used in complex terrain and AERMOD be used in other areas to save modeling time. In a ready-mixed concrete facility, PM-10, which has a relatively large particle size, is generated more than PM-2.5 due to the raw materials used and manufacturing characteristics.

• Journal of Korean Society for Atmospheric Environment
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• v.26 no.1
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• pp.94-102
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• 2010

Water content of $PM_{2.5}$ (particles in the atmosphere with a diameter of less than or equal to a nominal $2.5{\mu}m$) was estimated by using a gas/aerosol equilibrium model, SCAPE2, for the particles collected at Seoul and Gosan, Korea. From measured and analyzed characteristics of the particles, the largest difference between Seoul and Gosan is the proportions of total ammonia (t-$NH_3$=gas phase $NH_3$+particle phase ${NH_4}^+$), total nitric acid (t-$HNO_3$=gas phase $HNO_3$+particle phase ${NO_3}^-$) and sulfuric acid ($H_2SO_4$). Even though both sites have sufficient t-$NH_3$ to neutralize acidic species such as $H_2SO_4$, t-$HNO_3$, and t-HCl (total chloric acid=gas phase HCl+particle phase $Cl^-$), equivalent fraction of t-$NH_3$ and t-$HNO_3$ are higher at Seoul and $H_2SO_4$ is higher at Gosan. Based on the modeling result, it is identified that the $PM_{2.5}$ at Seoul is more hygroscopic than Gosan if the meteorological conditions are the same. To reduce water content of $PM_{2.5}$, and thus, mass concentration, control measures for ammonia and nitrate reduction are needed for Seoul, and inter-governmental cooperation is required for Gosan.

• Journal of Environmental Impact Assessment
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• v.31 no.2
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• pp.83-94
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• 2022

In this study, DNN-based models were learned using air quality determination data for 2017, 2019, and 2020 provided by the National Measurement Network (Air Korea), and this models evaluated using data from 2016 and 2018. Based on Pearson correlation coefficient 0.2, four items (SO₂, CO, NO₂, PM₁₀) were initially modeled as independent variables. In order to improve the accuracy of prediction, monthly independent modeling was carried out. The error was calculated by RMSE (Root Mean Square Error) method, and the initial model of RMSE was 5.78, which was about 46% betterthan the national moving average modelresult (10.77). In addition, the performance improvement of the independent monthly model was observed in months other than November compared to the initial model. Therefore, this study confirms that DNN modeling was effective in predicting PM_2.5 concentrations based on air pollutants concentrations, and that the learning performance of the model could be improved by selecting additional independent variables.

• Journal of Korean Society for Atmospheric Environment
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• v.33 no.5
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• pp.458-472
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• 2017

The optical properties and direct aerosol radiative forcing (DARF) of different aerosol components in $PM_{2.5}$ (water-soluble, insoluble, black carbon (BC), and sea-salt) were estimated using the hourly resolution data measured at Aewol intensive air monitoring site on Jeju Island during 2013, based on a modeling approach. In general, the water-soluble component was predominant over all other components with respect to its impact on the optical properties(except for absorbing BC) and DARF. The annual mean aerosol optical depth (AOD) at 500 nm for the water-soluble component was $0.14{\pm}0.14$ ($0.04{\pm}0.01$ for BC). The total DARF at the surface ($DARF_{SFC}$) and top of the atmosphere ($DARF_{TOA}$), and in the atmosphere ($DARF_{ATM}$) for most aerosol components(except for sea-salt) during the daytime were highest in spring and lowest in fall and/or summer. The maximum $DARF_{SFC}$ of most aerosol components occurred around noon (12:00~14:00 LST) during all seasons, while the maximum $DARF_{TOA}$ occurred in the afternoon (13:00~16:00 LST) during most seasons (except for spring). In addition, the estimated $DARF_{SFC}$ and $DARF_{ATM}$ of the water-soluble component were -20 to $-59W/m^2$ and +3.5 to $+14W/m^2$, respectively, while those of BC were -18 to $-29W/m^2$ and +23 to $+37W/m^2$, respectively.

• Journal of Korean Society for Atmospheric Environment
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• v.24 no.1
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• pp.30-42
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• 2008

In this study, the chemical compositions of $PM_{2.5}$ samples collected at the Redwood National Park IMPROVE site in California from March 1988 to May 2004 were analyzed to provide source identification and apportionment. A total of 1,640 samples were collected and 33 chemical species were analyzed by particle induced X-ray emission, proton elastic scattering analysis, photon induced X-ray fluorescence, ion chromatography, and thermal optical reflectance methods. Positive matrix factorization (PMF) was used to develop source profiles and to estimate their mass contributions. The PMF modeling identified five sources and the average mass was apportioned to motor vehicle (35.8%, $1.58\;{\mu}g/m^3$), aged sea salt (23.2%, $1.02\;{\mu}g/m^3$), fresh sea salt (21.4%, $0.94\;{\mu}g/m^3$), wood/field burning (16.1%, $0.71\;{\mu}g/m^3$), and airborne soil (3.5%, $0.15\;{\mu}g/m^3$), respectively. To analyze local source impacts from various wind directions, the CPF and NPR analyses were performed using source contribution results with the wind direction values measured at the site. These results suggested that sources of $PM_{2.5}$ are also sources of visibility degradation and then source apportionment studies derived for $PM_{2.5}$ are also used for understanding visibility problem.

• Asian Journal of Atmospheric Environment
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• v.5 no.2
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• pp.86-96
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• 2011

The positive matrix factorization (PMF2) and multilinear engine (ME2) models have been shown to be powerful environmental analysis techniques and have been successfully applied to the assessment of ambient particulate matter (PM) source contributions. Because these models are difficult to apply practically, the US EPA developed a more user-friendly version of the PMF. The initial version of the EPA PMF model does not provide any rotational capabilities; for this reason, the model was upgraded to include rotational functions in the EPA PMF ver. 2.0. In this study, PMF and EPA PMF modeling identified ten particulate matter sources including secondary sulfate I, vehicle gasoline, secondary sulfate II, secondary nitrate, secondary sulfate III, incinerators, aged sea salt, airborne soil particles, oil combustion, and diesel emissions. All of the source profiles determined by the two models showed excellent agreement. The calculated average concentrations of $PM_{2.5}$ were consistent between the PMF2 and EPA PMF ($17.94{\pm}0.30{\mu}g/m^3$ and $17.94{\pm}0.30\;{\mu}g/m^3$, respectively). Also, each set of estimated source contributions of the PMF2 and EPA PMF showed good agreement. The results from the new EPA PMF version applying rotational functions were consistent with those of PMF2. Therefore, the updated version of EPA PMF with rotational capabilities will provide more reasonable solutions compared with those of PMF2 and can be more widely applied to air quality management.

• Journal of People, Plants, and Environment
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• v.24 no.3
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• pp.267-275
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• 2021

Background and objective: Particulate matter (PM) has a fatal effect on health. There have been many studies on the use of plants such as trees and shrubs as eco-friendly and sustainable biofilter for the removal of PM. In forming more green space, ground cover plants play an important role in multi-layered planting. This study was conducted to investigate the ability of plants to reduce PM, targeting Korean native ground cover plants with high availability in urban green spaces. Methods: For 4 species of Asteraceae, 4 species of Liliaceae, and 3 species of Rosaceae, one species of plants at a time were placed in an acrylic chamber (800 × 800 × 1000 mm, L × W × H) modeling an indoor space. After the injection of PM, the amount of PM remaining in the chamber over time was investigated. Results: For all three types of PM (PM10, PM2.5, PM1), significant difference occurred in the amount of PM remaining between plant species after 1 hour in the Liliaceae chamber, 3 hours in the Asteraceae chamber, and 5 hours in the Rosaceae chamber. With Liliaceae, the leaf area and the amount of PM remaining in the chamber showed a negative (-) correlation. With the Asteraceae and Rosaceae, there was a weak negative correlation between the leaf area and the amount of PM remaining in the chamber. Conclusion: When using ground cover plants as a biofilter to remove PM, it is considered effective to select a species with a large total leaf area, especially for Liliaceae.

• Journal of Korean Society for Atmospheric Environment
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• v.34 no.3
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• pp.469-485
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• 2018

On September 26, 2017, South Korean government has established the Particulate Matter Comprehensive Plan to improve Korean air quality by 2022, which aims to reduce annual mean surface $PM_{2.5}$ concentration to $18{\mu}g/m^3$. This study demonstrates quantitative assessment of predicted $PM_{2.5}$ concentrations over 17 South Korean regions with the enforcement of the comprehensive plan. We utilize the Community Multi-scale Air Quality (CMAQ) modeling system with CAPSS 2013 and CREATE 2015 emissions inventories. Simulations are conducted for 2015 with the base emissions and the planned emissions, and impacts from model biases are minimized using the RRF (Relative Response Factor). With effective emission reduction scenario suggested by the comprehensive plan, the model demonstrates that the surface $PM_{2.5}$ concentration may decrease by $6{\mu}g/m^3$ ($23{\mu}g/m^3{\rightarrow}17{\mu}g/m^3$) and $7{\mu}g/m^3$ ($25{\mu}g/m^3{\rightarrow}18{\mu}g/m^3$) for Seoul and South Korea, respectively. The number of high $PM_{2.5}$ days(daily mean>$25{\mu}g/m^3$) also decreases from 21 days to 4 days.

• Journal of Korean Society for Atmospheric Environment
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• v.33 no.1
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• pp.11-18
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• 2017

The performance of a modeling system consisting of WRF model v3.3 and CMAQ model v4.7.1 for forecasting $PM_{2.5}$ concentrations were evaluated during the period May 2012 through December 2014. Twenty-four hour averages of $PM_{2.5}$ and its major components obtained through filter sampling at the Bulgwang intensive measurement station were used for comparison. The mean predicted $PM_{2.5}$ concentration over the entire period was 68% of the mean measured value. Predicted concentrations for major components were underestimated except for $NO_3{^-}$. The model performance for $PM_{2.5}$ generally tended to degrade with increasing the concentration level. However, the mean fractional bias (MFB) for high concentration above the $80^{th}$ percentile fell within the criteria, the level of accuracy acceptable for standard model applications. Among three bias correction methods, the ratio adjustment was generally most effective in improving the performance. Albeit for limited test conditions, this analysis demonstrated that the effects of bias correction were larger when using the data with a larger bias of predicted values from measurement values.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.4
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• pp.877-879
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• 2011

Bowel sounds (BS) are produced by the movement of the intestinal contents in the lumen of the gastro-intestinal tract during peristalsis and thus, it can be used clinically as useful indicators of bowel motility. We devised an estimation algorithm of bowel motility based on the regression modeling of the jitter and shimmer of BS signals measured by auscultation. Ten healthy males ($23.5\pm2.1$ years) were examined. Consequently, the correlation coefficient, coefficient of determination and standard error between the colon transit times (CTT) measured by a conventional radiograph and the values estimated by our algorithm were 0.98, 0.96 and 2.86, respectively. Also, through k-fold cross validation, the average value of the absolute differences between them was $5.0\pm2.5$ hours. This method could be used as a complementary tool for the non-invasive measurement of bowel motility.