• Asian Journal of Atmospheric Environment
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• v.12 no.2
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• pp.139-152
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• 2018

The urban model inter-comparison study (UMICS) was conducted in order to improve the performance of air quality models (AQMs) for simulating fine particulate matter ($PM_{2.5}$) in the Greater Tokyo Area of Japan. UMICS consists of three phases: the first phase focusing on elemental carbon (UMICS1), the second phase focusing on sulfate, nitrate and ammonium (UMICS2), and the third phase focusing on organic aerosol (OA) (UMICS 3). In UMICS2/3, all the participating AQMs were the Community Multiscale Air Quality modeling system (CMAQ) with different configurations, and they similarly overestimated $PM_{2.5}$ nitrate concentration and underestimated $PM_{2.5}$ OA concentration. Various sensitivity analyses on CMAQ configurations, emissions and boundary concentrations, and meteorological fields were conducted in order to seek pathways for improvement of $PM_{2.5}$ simulation. The sensitivity analyses revealed that $PM_{2.5}$ nitrate concentration was highly sensitive to emissions of ammonia ($NH_3$) and dry deposition of nitric acid ($HNO_3$) and $NH_3$, and $PM_{2.5}$ OA concentration was highly sensitive to emissions of condensable organic compounds (COC). It was found that $PM_{2.5}$ simulation was substantially improved by using modified monthly profile of $NH_3$ emissions, larger dry deposition velocities of $HNO_3$ and $NH_3$, and additionally estimated COC emissions. Moreover, variability in $PM_{2.5}$ simulation was estimated from the results of all the sensitivity analyses. The variabilities on CMAQ configurations, chemical inputs (emissions and boundary concentrations), and meteorological fields were 6.1-6.5, 9.7-10.9, and 10.3-12.3%, respectively.

• Asian Journal of Atmospheric Environment
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• v.4 no.3
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• pp.150-156
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• 2010

Inter-comparison of chemical transport models (CTMs) was conducted among four modeling research groups. Model performance of the ensemble approach to $O_3$ and $PM_{2.5}$ simulation was evaluated by using observational data with a time resolution of 1 or 6 hours at four sites in the Kanto area, Japan, in summer 2007. All groups applied the Community Multiscale Air Quality model. The ensemble average of the four CTMs reproduced well the temporal variation of $O_3$ (r=0.65-0.85) and the daily maximum $O_3$ concentration within a factor of 1.3. By contrast, it underestimated $PM_{2.5}$ concentrations by a factor of 1.4-2, and did not reproduce the $PM_{2.5}$ temporal variation at two suburban sites (r=~0.2). The ensemble average improved the simulation of ${SO_4}^{2-}$, ${NO_3}^-$, and ${NH_4}^+$, whose production pathways are well known. In particular, the ensemble approach effectively simulated ${NO_3}^-$, despite the large variability among CTMs (up to a factor of 10). However, the ensemble average did not improve the simulation of organic aerosols (OAs), underestimating their concentrations by a factor of 5. The contribution of OAs to $PM_{2.5}$ (36-39%) was large, so improvement of the OA simulation model is essential to improve the $PM_{2.5}$ simulation.

• Journal of Korean Society of Environmental Engineers
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• v.30 no.11
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• pp.1123-1131
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• 2008

In this study, measurement uncertainty of instrumental neutron activation analysis was evaluated for ambient As concentration in PM2.5. Expanded uncertainties of the measurements were calculated by applying both ISO-GUM approximation and Monte Carlo Simulation(MCS). The estimate of As concentration on a specific day by the Monte Carlo Simulation differed from that of ISO-GUM approximation by less than 4%. Relative expanded uncertainties of As concentrations from a total number of 60 PM2.5 samples were also estimated to be more or less than 10% with 95% confidence level using the Monte Carlo Simulation. Sensitivity test of the measurement uncertainties showed that $\gamma$-ray counting error(62.3%), efficiency(18.5%), air volume(12.3%), neutron flux(2.3%), and absolute gamma-intensity(1.8%) are major factors of uncertainty variations.

• Asian Journal of Atmospheric Environment
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• v.8 no.2
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• pp.108-114
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• 2014

In the companion paper (Lee et al., 2012), it was showed that CMAQ simulation using a lateral boundary conditions (LBCs) derived from RAQMS-CMAQ linkage, compared to the CMAQ results with the default CMAQ LBCs, improved ozone simulations in the conterminous US domain. In the present paper, the study is extended to investigate the influence of LBCs on PM2.5 simulation. MM5-SMOKE-CMAQ modeling system was used for meteorological field generation, emissions preparation and air quality simulations, respectively. Realtime Air Quality Modeling System (RAQMS) model assimilated with satellite observations were used to generate the CMAQ-ready LBCs. CMAQ PM2.5 simulations with RAQMS LBCs and predefined LBCs were compared with U.S. EPA Air Quality System (AQS) measurements. Mean PM2.5 lateral boundary conditions taken from RAQMS outputs showed strong variations both in the horizontal grid and vertical layers in the northern and western boundaries and affected the results of CMAQ PM2.5 predictions. CMAQ with RAQMS LBCs could improve CMAQ PM2.5 predictions resulting in the improvement of index of agreement from 0.38 to 0.63.

• Journal of Environmental Health Sciences
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• v.49 no.5
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• pp.275-288
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• 2023

Background: When basic local governments want to improve their air quality management policies, they need fundamental evidence, such as the effectiveness of current policies or scenario results. Objectives: The purpose of this study is to lay the groundwork for a process to calculate air pollutant reduction from basic local government air quality policies and provide numerical estimates of PM_2.5 concentrations following improved policies. Methods: We calculated the amount of air pollutant reduction that can be expected in the research region based on the Gyeonggi-do Air Environment Management Implementation Plan issued in 2021 and guidelines from the Korean Ministry of Environment. The PM_2.5 concentration variations were numerically simulated using the CMAQ (photochemical air quality model). Results: The research regions selected were Suwon, Ansan, Yongin, Pyeongtaek, and Hwaseong in consideration of population, air pollutant emissions, and geographical requirements. The expected reduction ratios in 2024 compared to 2018 are CO (3.0%), NO_x (7.9%), VOCs (0.7%), SO_x (0.1%), PM₁₀ (2.4%), PM_2.5 (6.1%), NH₃ (0.05%). The reduced PM_2.5 concentration ratio was highest in July and lowest in April. The expected concentration reduction of yearly mean PM_2.5 in the research region is 0.12 ㎍/m³ (0.6%). Conclusions: Gyeonggi-do is now able to quickly provide air pollutant emission reduction calculations by respective policy scenario and PM_2.5 simulation results, including for secondary aerosol particles. In order to provide more generalized results to basic local governments, it is necessary to conduct additional research by expanding the analysis tools and periods.

• The Journal of Korean Society for Radiation Therapy
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• v.21 no.1
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• pp.33-39
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• 2009

Purpose: The aim of this study is to compare patient's body posture and its position at the time of simulation with one at the treatment room using On-board Imaging (OBI) and CT (CBCT). The detected offsets are compared with position errors of Rando Phantom that are practically applied. After that, Rando Phantom's position is selected by moving couch based on detected deviations. In addition, the errors between real measured values of Rando Phantom position and theoretical ones is compared. And we will evaluate target position's accuracy of KV X-ray imaging's 2D and CBCT's 3D one. Materials and Methods: Using the Rando Phantom (Alderson Research Laboratories Inc. Stanford. CT, USA) which simulated human body's internal structure, we will set up Rando Phantom on the treatment couch after implementing simulation and RTP according to the same ways as the real radioactive treatment. We tested Rando Phantom that are assumed to have accurate position with different 3 methods. We measured setup errors on the axis of X, Y and Z, and got mean standard deviation errors by repeating tests 10 times on each tests. Results: The difference between mean detection error and standard deviation are as follows; lateral 0.4+/-0.3 mm, longitudinal 0.6+/-0.5 mm, vertical 0.4+/-0.2 mm which all within 0~10 mm. The couch shift variable after positioning that are comparable to residual errors are 0.3+/-0.1, 0.5+/-0.1, and 0.3+/-0.1 mm. The mean detection errors by longitudinal shift between 20~40 mm are 0.4+/-0.3 in lateral, 0.6+/-0.5 in longitudinal, 0.5+/-0.3 in vertical direction. The detection errors are all within range of 0.3~0.5 mm. Residual errors are within 0.2~0.5 mm. Each values are mean values based on 3 tests. Conclusion: Phantom is based on treatment couch shift and error within the average 5mm can be gained by the diminution detected by image registration based on OBI and CBCT. Therefore, the selection of target position which depends on OBI and CBCT could be considered as useful.

• Particle and aerosol research
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• v.20 no.2
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• pp.25-33
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• 2024

Suspension of particulate matter (PM) in indoor spaces, which increases risk of negative impact on occupants' health from exposure to PM, is influenced by humidity level in the indoor environment. The goal of this study is to investigate the property of size-resolved PM suspension in accordance with the relative humidity through simulation chamber experiments which reflect the indoor environmental characteristics. The relative humidity of simulation chamber is adjusted to 35%, 55% and 75% by placing it inside a real-size environmental chamber which allows artificial control of climatic conditions (e.g., temperature, humidity). At the respective humidity conditions, PM suspension concentration caused by occupant walking is analyzed by particle size (0.5-0.8, 0.8-1.0, 1.0-2.5, 2.5-3.5, 3.5-4.5, 4.5-5.5, 5.5-8.0, and 8.0-10 ㎛). Irrespective of the particle size, the suspension concentration reveals a decreasing tendency as the relative humidity increases. Furthermore, a one-way analysis of variance (one-way ANOVA) test statistically verifies that the suspension concentration has a significant difference depending on the indoor relative humidity level. In addition, as the relative humidity increases, a proportion of the suspended particles with 0.5-2.5 ㎛ diameter decreases, while that with 2.5-3.5 ㎛ diameter increases. The reason is considered that the humidity has an effect on adhesion and coagulation forces of the particles.

• Land and Housing Review
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• v.10 no.2
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• pp.53-58
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• 2019

Particulate matter (PM) is designated as a group 1 carcinogen by the International Agency for Research on Cancer (IARC) of the World Health Organization (WHO). In South Korea, the health threat caused by PM is the most serious level internationally. Therefore, in order to solve the urban PM problem, it is important to develop the technology that can control PM efficiently. In this study, CFD(Computational Fluid Dynamics) simulation was performed for PM pre-filter (type 1-3 with different PM collecting room) to develop a high-efficiency PM collecting device. The complex flow field and the local flow phenomenon inside the PM collecting device were understood with CFD simulation by changing the shape and size of the pre-filter. The PM removal performance can be described with flow rate through the device and PM removal efficiency. The type-1 pre-filter with 5x5 size collecting room was confirmed to have the highest efficiency. Based on the analysis results, the optimal type of pre-filter could be developed and it would be applied as an element technology included in the PM collecting device.

• Journal of the Korean Society of Radiology
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• v.5 no.6
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• pp.383-389
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• 2011

This study offered a new method to calculate absorbed dose of actual patients through Monte Carlo Simulation by using the linkage of Geant4 and DICOM, and, the experimental value of absorbed dose at the center and Geant 4 simulation result according to the depth of PMMA mock phantom were compared by using MOSEF in order to verify Geant4 calculation code. In the area where there was no air space between the irregular gap due to incomplete compression of PMMA slab, the differences were $0.46{\pm}4.69$ percent and $-0.75{\pm}5.19$percent in $15{\times}15cm^2$ and $20{\times}20cm^2$ respectively. Excluding the error due to incomplete compression of PMMA mock phantom, the calculation values of the Monte Carlo simulation by linkage of Geant4 and DICOM was the same.

• Journal of Korean Society for Atmospheric Environment
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• v.34 no.4
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• pp.517-533
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• 2018

We utilize the CAMx (Comprehensive Air Quality Model with eXtensions) system and the PSAT (Particulate Source Apportionment Technology) diagnostic tool to determine the $PM_{2.5}$ concentration and to perform its source apportionment in the southeastern region of South Korea. For a year-long simulation, eight local authorities in the region such as Pohang, Daegu, Gyeongju, Ulsan, Busan-Gimhae, Gosung-Changwon, Hadong, and all remaining areas in Gyeongsangnam-do, are selected as source areas based on the emission rates of $NO_x$, $SO_x$, VOC, and primary PM in CAPSS (Clean Air Policy Support System) 2013 emissions inventory. The CAMx-PSAT simulation shows that Pohang has the highest $PM_{2.5}$ self-contribution rate (25%), followed by Hadong (15%) and Busan-Gimhae (14%). With the exception of Pohang, which has intense fugitive dust emissions, other authorities are strongly affected by emissions from their neighboring areas. This may be measured as much as 1 to 2 times higher than that of the self-contribution rate. Based on these estimations, we conclude that the efficiency of emission reduction measures to mitigate $PM_{2.5}$ concentrations in the southeastern region of South Korea can be maximized when the efforts of local or regional emission controls are combined with those from neighboring regions. A comprehensive control policy planning based on the collaboration between neighboring jurisdictional boundaries is required.