• Proceedings of the Korea Air Pollution Research Association Conference
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• 2008.04a
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• pp.221-223
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• 2008

• Proceedings of the KSR Conference
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• 2007.11a
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• pp.989-993
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• 2007

It was intended in this study to seek for the measures to utilize the USN technique, which has high usability due to low price and low power consumption, in air quality monitoring. As a method, the sensors of temperature, humidity, particulate matters (PM10), and carbon dioxide ($CO_2$) were installed in the self-manufactured sensor nodes; the nodes were installed in the waiting rooms and platforms of a subway station and the measurements were collected at real time with use of a computer which micro gateway was built in. Collected data was to be processed by the statistics program installed in the computer; the collected data is to be used in managing the air quality of stations after transmission to the ventilation system of ventilation chambers.

• Proceedings of the SAREK Conference
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• 2008.06a
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• pp.90-95
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• 2008

This article presents practical advice regarding the implementation and management of an impeccable Building Management System. The BMS was introduced to the series of computerized systems including manufacturing, storage, distribution, and quality control. Recently revised GMP regulation is requesting an improvement in drug product quality regulatory system by computer system validation. Quality is critical to guarantee the efficacy and the safety of drugs and is approved in the evaluation process after the audit trail application. HVAC parameter monitoring system will record the identity of operators entering or confirming critical data. Authority to amend entered data should be restricted to nominated persons. Any alteration to an entry of critical data should be authorized in advance and recorded with the reason for the change.

• Korean Journal of Remote Sensing
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• v.37 no.3
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• pp.657-664
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• 2021

In this study, we investigated the relationships between the air quality (PM_2.5, PM₁₀, O₃) concentrations and local geographical characteristics (terrain heights, building area ratios, population density in 9 km × 9 km gridded subareas) in the Seoul metropolitan area. To analyze the terrain heights and building area ratios, we used the geographic information system data provided by the NGII (National Geographic Information Institute). Also, we used the administrative districts and population provided by KOSIS (Korean Statistical Information Service) to estimate population densities. We analyzed the PM_2.5, PM₁₀, and O₃ concentrations measured at the 146 AQMSs (air quality monitoring system) within the Seoul metropolitan area. The analysis period is from January 2010 to December 2020, and the monthly concentrations were calculated by averaging the hourly concentrations. The terrain is high in the northern and eastern parts of Gyeonggi-do and low near the west coastline. The distributions of building area ratios and population densities were similar to each other. During the analysis period, the monthly PM_2.5 and PM₁₀ concentrations at 146 AQMSs were high from January to March. The O₃ concentrations were high from April to June. The population densities were negatively correlated with PM_2.5, PM₁₀, and O₃ concentrations (weakly with PM_2.5 and PM₁₀ but strongly with O₃). On the other hand, the AQMS heights showed no significant correlation with the pollutant concentrations, implying that further studies on the relationship between terrain heights and pollutant concentrations should be accompanied.

• Asian Journal of Atmospheric Environment
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• v.12 no.3
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• pp.232-243
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• 2018

The construction, development and maintenance of an economically, environmentally and socially sustainable campus involves the integration of measuring tools and technical information that invites and encourages the community to know the actual state to generate positive actions for reducing the negative impacts over the local environment. At the Universidad Nacional de Colombia - Campus $Bogot{\acute{a}}$, a public area with daily traffic of more than 25000 people, the Environmental Management Bureau has committed with the monitoring of the noise pollution and air quality, as support to the campaigns aiming to reduce the pollutant emissions associated to the student's activities and campus operation. The target of this study is based in the implementation of mobile air quality and sonometry monitoring equipment, the mapping of the actual air quality and noise pollution inside the university campus as a novel methodology for a sub-area inside a megacity. This results and mapping are proposed as planning tool for the institution administrative sections. A mobile Kunak$^{(R)}$ Air & OPC air monitoring station with the capability to measure particulate matter $PM_{10}$, $PM_{2.5}$, Ozone ($O_3$), Sulfur Oxide ($SO_2$), Carbon Monoxide (CO) and Nitrogen Oxide ($NO_2$) as well as Temperature, Relative Humidity and Latitude and Longitude coordinates for the data georeferenciation; and a sonometer Cirrus$^{(R)}$ 162B Class 2 were used to perform the measurements. The measurements took place in conditions of academic activity and without it, with the aim of identify the impacts generated by the campus operation. Using the free code geographical information software QGIS$^{(R)}$ 2.18, the maps of each variable measured were developed, and the impacts generated by the operation of the campus were identified qualitative and quantitively. For the measured variables, an increase of around 21% for the $L_{Aeq}$ noise level and around 80% to 90% for air pollution were detected during the operation period.

• Proceedings of the Korean Environmental Sciences Society Conference
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• 2003.11a
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• pp.73-78
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• 2003

In this research, we implement Realtime Air Diffusion Prediction System which is a parallel Fortran model running on distributed-memory parallel computers. The system is designed for air diffusion simulations with four-dimensional data assimilation. For regional air quality forecasting a series of dynamic downscaling technique is adopted using the NCAR/Penn. State MM5 model which is an atmospheric model. The realtime initial data have been provided daily from the KMA (Korean Meteorological Administration) global spectral model output. It takes huge resources of computation to get 24 hour air quality forecast with this four step dynamic downscaling (27km, 9km, 3km, and lkm). Parallel implementation of the realtime system is imperative to achieve increased throughput since the realtime system have to be performed which correct timing behavior and the sequential code requires a large amount of CPU time for typical simulations. The parallel system uses MPI (Message Passing Interface), a standard library to support high-level routines for message passing. We validate the parallel model by comparing it with the sequential model. For realtime running, we implement a cluster computer which is a distributed-memory parallel computer that links high-performance PCs with high-speed interconnection networks. We use 32 2-CPU nodes and a Myrinet network for the cluster. Since cluster computers more cost effective than conventional distributed parallel computers, we can build a dedicated realtime computer. The system also includes web based Gill (Graphic User Interface) for convenient system management and performance monitoring so that end-users can restart the system easily when the system faults. Performance of the parallel model is analyzed by comparing its execution time with the sequential model, and by calculating communication overhead and load imbalance, which are common problems in parallel processing. Performance analysis is carried out on our cluster which has 32 2-CPU nodes.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.42 no.4
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• pp.203-210
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• 2019

Recently, a number of researchers have produced research and reports in order to forecast more exactly air quality such as particulate matter and odor. However, such research mainly focuses on the atmospheric diffusion models that have been used for the air quality prediction in environmental engineering area. Even though it has various merits, it has some limitation in that it uses very limited spatial attributes such as geographical attributes. Thus, we propose the new approach to forecast an air quality using a deep learning based ensemble model combining temporal and spatial predictor. The temporal predictor employs the RNN LSTM and the spatial predictor is based on the geographically weighted regression model. The ensemble model also uses the RNN LSTM that combines two models with stacking structure. The ensemble model is capable of inferring the air quality of the areas without air quality monitoring station, and even forecasting future air quality. We installed the IoT sensors measuring PM2.5, PM10, H2S, NH3, VOC at the 8 stations in Jeonju in order to gather air quality data. The numerical results showed that our new model has very exact prediction capability with comparison to the real measured data. It implies that the spatial attributes should be considered to more exact air quality prediction.

• Korean Journal of Remote Sensing
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• v.36 no.2_1
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• pp.139-153
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• 2020

Using a computationalfluid dynamics(CFD) model, thisstudy evaluated the representativeness of an air quality monitoring system (AQMS) in an urban area and presented a methodology to determine the suitable AQMS locations for specific purposes. For this, we selected a 1.6 km × 1.6 km area around the Eunpyeong-gu AQMS (AQMS 111181) as a target area. We conducted simulationsfor two emission scenarios (scenario one: air pollutants transported from inflow boundaries, scenario two: air pollutants emitted from roads). Urban airflows were markedly influenced by mountainous terrain located in the northeast and southeast of the target area, and complicated airflow patterns occurred around the buildings. The distributions of air pollutants were dependent on the terrain (mountain) in scenario one, but the road location and building height in scenario 2. We evaluated whether the AQMS could represent the air quality in the target area based on the simulations for two scenarios. The concentrations simulated at the AQMS were similar in magnitude to the layer mean concentrations, which indicated good representativeness for the air quality in the target area. We also suggested which locations were suitable for different measurement purposes (hot spots, clean zones, average zones, shelter zones, equi-background zones).

• The Journal of the Korea institute of electronic communication sciences
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• v.15 no.6
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• pp.1217-1222
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• 2020

Currently, studies on environmental pollution are being conducted in worldwide including Korea. Among them, various efforts are being made to prevent the health and environmental pollution of the people nationwide by keeping and managing the indoor air of various facilities used by many users. In particular, it is suggested that many people who visit medical institutions have diseases or illnesses and may have a significant impact on chronic diseases such as headache, depression, neuroticism, heart disease, and cancer related to indoor air pollution. Considering this situation, this paper is expected to provide comfortable and clean indoor environment to the inmate by providing central monitoring of air pollution and automatic call function of the person in charge through indoor air monitoring IoT system to be applied to medical institutions.

• Journal of Korean Society for Atmospheric Environment
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• v.22 no.5
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• pp.574-589
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• 2006

Although concentrations of hazardous air pollutants(HAPs) are very low in the atmosphere, a growing attention has been paid on such compounds due to their high toxicity and bioaccumulation potentials into human body. In order to control and manage the amount of these materials in ambient air, it is necessary to construct monitoring system of them and to know the current concentration level of HAPs above all. In this work, a wide range of HAPs has been measured in metropolitan area to recognize the present state of HAPs in this area. The measured concentration of VOCs was higher in order of Jeonnongdong, Jeongdong, and Yangsuri. The regional difference of VOCs concentration was also highest in spring. Its total VOCs was ranged from $15.17{\sim}41.45$ ppb. Benzene $0.43{\sim}2.32$ ppb showed similar concentration level with the result of previous researches in Seoul. This value is a little higher than the average concentration 0.92 ppb for national ambient air quality standards in Japan. The concentration of aldehydes in this study was lower than those of other researches. Previous works in Seoul metropolitan area showed that the concentration of formaldehyde and acetaldehyde were higher than 5 ppb. The concentration of gaseous and particulate PAHs was high in order of winter, spring, and summer More than 90% of PAHs with low molecular weight such as 2-rings and 3-rings PAHs existed in gas phase. On the other hands, PAHs with high molecular weight more than 5-rings PAHs almost existed in particulate. In spring, the concentration of gaseous PAHs was 24.38 $ng/m^3$ in Jeongdong. Among the particulate PAHs, the concentrations of Naphthalene, Benzo(b)fluoranthene, and Benzo(g, h, i)perylene were higher than others. Especially, the concentration of Benzo(a)pyrene, a important carcinogenic pollutant, was highest in winter 0.5 $ng/m^3$ and ranged from 0.03 to 0.3 $ng/m^3$ in spring and summer, which is lower than the monitoring result in 90's. These components were mainly originated from the vehicle exhaust or heating equipment use.