• 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.

• Journal of Korean Society for Atmospheric Environment
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• v.31 no.4
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• pp.330-344
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• 2015

Semi-continuous measurements of $PM_{2.5}$ mass, organic and elemental carbon were made for the period of January to October 2014, at six national air monitoring stations in Korea. OC and EC concentrations showed a clear seasonal variation with the highest in winter (January) and the lowest in summer (August). In winter, the high carbonaceous concentrations were likely influenced by increased fuel combustion from residential heating. OC and EC concentrations varied by monitoring stations with 5.9 and $1.7{\mu}g/m^3$ in Joongbu area, 4.2 and $1.2{\mu}g/m^3$ in Honam area, 4.0 and $1.3{\mu}g/m^3$ in Yeongnam area, 3.7 and $1.6{\mu}g/m^3$ in Seoul Metropolitan area, 3.0 and $0.8{\mu}g/m^3$ in Jeju Island, 2.9 and $0.7{\mu}g/m^3$ in Baengnyeong Island respectively. The concentrations of OC and EC comprised 9.6~ 15.5% and 2.4~ 4.7% of $PM_{2.5}$. Urban Joongbu area located adjacent to the intersection of several main roads showed the highest carbon concentration among six national air monitoring station. On the other hand, background Baengnyeong Island showed the lowest carbon concentration and the highest OC/EC ratio (4.5). During the haze episode, OC and EC were enhanced with increase in $PM_{2.5}$ about 1.3~ 3 and 1.3~ 4.0 times respectively. The concentrations of OC, EC in the Asian dust case are about 1~ 2.4 times greater than in the nondust case. The origins of air mass pathways arriving at Seoul, using the backward trajectory analysis, can be mostly classified into 6 groups (Sector I Northern Korea including the sea of Okhotsk, Sector II Northern China including Mongolia, Sector III Southern China, Sector IV South Pacific area, Sector V Japan, Sector VI Southern Korea area). When an air mass originating from northern China and Mongolia, the OC concentrations were the most elevated, with a higher OC/EC ratio (2.4~ 3.3), and accounting for 17% of $PM_{2.5}$ mass on average.

• Journal of Korean Society for Atmospheric Environment
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• v.31 no.2
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• pp.157-163
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• 2015

To establish National Reference Method (NRM) for $PM_{2.5}$, operational performance of 5 different commercial gravimetric-based $PM_{2.5}$ measuring instruments was assessed at Bulkwang monitoring station from January 23, 2014 to February 28, 2014. First, physical properties, design, and functional performance of the instruments were assessed. Evaluation was carried out to determine whether operating method for the instruments and levels of QA/QC activities meet the data quality objectives (DQOs). To verify whether DQOs were satisfied, reproducibility of QA/QC procedures, accuracy, relative sensitivity, limit of detection, margin of error, and coefficient of determination of the instruments were also evaluated. Results of flow rate measurement of 15 candidate instruments indicated that all the instruments met performance criteria with accuracy deviation of 4.0% and reproducibility of 0.6%. Comparison of final $PM_{2.5}$ mass concentrations showed that the coefficient of determination ($R^2$) values were greater than or equal to 0.9995, and concentration gradient ranged from 0.97 to 1.03. All the instruments satisfied criteria for NRM with the estimated precision of 1.47~2.60%, accuracy of -1.90~3.00%, and absolute accuracy of 1.02~3.12%. This study found that one particular type of measuring instrument was proved to be excellent, with overall evaluation criteria satisfied.

• Fire Science and Engineering
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• v.33 no.4
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• pp.140-151
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• 2019

It is to assess the indoor air quality of the chemical hazardous materials exposed to the fire after firefighters returned to the fire scene. The research subject randomly selected four fire stations located in Seoul, Korea. Two fire stations were set up as control groups after the return of the firefighting activities at the actual fire scene, and two other fire stations were set up as control groups to measure the air quality of the room at normal levels regardless of the action. We conducted 24-hour monitoring for all fire accidents that occurred in Seoul Metropolitan using fire safety map computer system. Also, indoor air quality was measured immediately after homecoming if the experiment group was to be dispatched due to an accident of intermediate or larger scale. 11 hazardous substance items such as fine dust, formaldehyde, volatile organic compounds, PAH, VCM, acidity, asbestos, CO₂, NO₂, O₃ were measured according to the process test method. Three of 11 types of harmful substances exceeded domestic and foreign standards, and one of them was found to be close to foreign standards. In particular, total volatile organic compounds, carbon dioxide and sulfuric acids were 2.5 times, 2.2 times and 1.1 times higher than the standard. Also, for formaldehyde and sulfuric acid, it was measured higher in the control group than in the case group. This findings could be used in policies to improve indoor air quality in the fire station of the Seoul Metropolitan Government.

• Journal of Environmental Health Sciences
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• v.40 no.3
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• pp.204-214
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• 2014

Objectives: Vehicular emissions are one of the main sources of air pollution in urban areas. Correlation analysis was conducted between air pollutants and traffic volume in order to identify causes of air pollution in Gwangju. Methods: Using traffic volumes and air quality monitoring data from 2002 to 2012 from nine stations (seven urban areas, two roadside areas), especially at three sites where traffic volumes were high, the correlation coefficients were obtained between air pollutants as PM-10 (particulate matter), $NO_2$, $SO_2$, CO and $O_3$ at the stations and traffic volumes near the air monitoring stations. Results: Due to traffic volume and distance between the station and the traffic road, concentrations of pollutants at roadside areas were higher than at urban areas, with the exception of $O_3$. The concentration of $O_3$ showed statistically significance with those of other gas materials as $NO_2$, $SO_2$, and CO in winter (p<0.001) and spring (p<0.05). During the period of October 7 to 20, 2012, excluding periods of yellow dust, smog and rainy season, the ratio of $NO/(NO+NO_2)$ showed the highest value 0.57 and 0.40 at Unam and Chipyeong of two roadside stations, followed by 0.35 at Nongseong with vehicular effects. The correlation coefficient between traffic volume and $O_3$, CO, $NO_2$ became higher when the data on mist and haze days were excluded, than when all hourly data were used in that period, at the three sites of Unam, Chipyeong, and Nongseong. Conclusions: Air quality showed a considerable effect from vehicles at roadside areas compared to in urban areas. Air pollutant diminishment strategies need to be aggressively adopted in order to protect atmospheric environment.

• Journal of Environmental Health Sciences
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• v.45 no.6
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• pp.577-582
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• 2019

Objectives: The purpose of this survey was to assess the concentrations of heavy metals in the atmosphere of Pocheon City by measuring heavy metals in the industrial complex area and at the city air measuring station, and also to assess the degree of impact that the industrial area has on urban air quality. Methods: Sampling was carried out between February 2018 and November 2018 at two sites in the industrial complex and in the city air monitoring stations. Results: At the industrial complex in Pocheon City, air pollutant emitting businesses were emitting concentrations of fine dust (PM₁₀) between 45 and 60 ㎍/㎥ higher than in the city air. The daily maximum concentrations of lead (Pb), manganese (Mn), and cadmium (Cd) in the industrial complex are below the WHO recommendation standard (annual average), and the impact on the urban atmosphere is judged to be insignificant. Three to five percent of fine dust (PM₁₀) consists of metallic materials, and as the fine dust increased, metals were detected proportionally. Although cadmium (Cd) and beryllium (Be) were not detected in the city air in Pocheon and chromium (Cr), copper (Cu), and arsenic (As) were found to be 50 percent or less, it is deemed that copper (Cu) was detected at unusually high levels due to unknown air pollutants, which requires regular heavy metal measurement and cause verification. Conclusions: An analysis of the heavy metals in the industrial zone and the urban atmosphere in Pocheon City in this study showed that the linear relationship of heavy metals in the industrial zone, or the direct impact relationship, on the heavy metals in the urban atmosphere could not be estimated. The sampling device for equivalent assessment of particulate matter installed at air pollution monitoring stations is highly likely to be used for analysis of fine dust and heavy metals.

• Journal of Korean Society for Atmospheric Environment
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• v.24 no.4
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• pp.423-438
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• 2008

BEIS2 (Biogenic Emissions Inventory System version 2) and BEIS3.12 (BEIS version 3.12) were used to estimate hourly biogenic emissions over South Korea using a set of vegetation and meteorological data simulated with the MM5 (Mesoscale Model version 5). Two biogenic emission models utilized different emission factors and showed different responses to solar radiations, resulting in about $10{\sim}20%$ difference in the nationwide isoprene emission estimates. Among the 11-vegetation classes, it was found that mixed forest and deciduous forest are the most important vegetation classes producing isoprene emissions over South Korea comprising ${\sim}90%$ of the total. The simulated isoprene concentrations over Seoul metropolitan area show that diurnal and daily variations match relatively well with the PAMS (Photochemical Air Monitoring Station) measurements during the period of June 3${\sim}$June 10, 2004. Compared to BEIS2, BEIS3.12 yielded ${\sim}35%$ higher isoprene concentrations during daytime and presented better matches to the high peaks observed over the Seoul area. This study showed that the importance of vegetation data and emission factors to estimate biogenic emissions. Thus, it is expected to improve domestic vegetation categories and emission factors in order to better represent biogenic emissions over South Korea.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.6
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• pp.294-301
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• 2013

The particle matter concentrations in the subway stations should be monitored and controlled for the health of commuters on the subway system. Seoul Metro and Seoul Metropolitan Rapid Transit Corporation are measuring several air pollutants regularly. In this paper, the reliability of the cheap instruments using light scattering method is improved with the help of a linear regression analysis technique to measure the $PM_{10}$ concentrations continuously in the subway stations. In addition, a monitoring system is implemented to display and record the data of $PM_{10}$, $CO_2$, humidity, and temperature. To transmit and receive these measured sensor data, CDMA M2M wireless communication method is applied.

• International Journal of Computer Science & Network Security
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• v.24 no.3
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• pp.196-200
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• 2024

Weather forecasting is considered to be of utmost important among various important sectors such as flood management and hydro-electricity generation. Although there are various numerical methods for weather forecasting but majority of them are reported to be Mechanistic computationally demanding due to their complexities. Therefore, it is necessary to develop and build models for accurately predicting the weather conditions which are faster as well as efficient in comparison to the prevalent meteorological models. The study has been undertaken to forecast various atmospheric parameters in the city of Bangalore using Naïve Bayes algorithms. The individual parameters analyzed in the study consisted of wind speed (WS), wind direction (WD), relative humidity (RH), solar radiation (SR), black carbon (BC), radiative forcing (RF), air temperature (AT), bar pressure (BP), PM₁₀ and PM_2.5 of the Bangalore city collected from Air Quality Monitoring Station for a period of 5 years from January 2015 to May 2019. The study concluded that Naive Bayes is an easy and efficient classifier that is centered on Bayes theorem, is quite efficient in forecasting the various air pollution parameters of the city of Bangalore.

• Journal of environmental and Sanitary engineering
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• v.24 no.4
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• pp.60-68
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• 2009

The most principal approach to improve indoor air quality(IAQ) of subway was to examine the fine particulate(PM-10) from the emission sources. Therefore, this study was carried on the investigation the fine particulate for comparison with the removal efficiency of PM-10 in divided the PSD(Platform Screen Door) and Non-PSD subway station from July, 2007 to May 2008. In the monitoring results, the range of PM-10 concentration of Non-PSD station was $44.6{\sim}116.5{\mu}g/m^3$ and the range of PM-10 concentration of PSD station was $23.9{\sim}81.1{\mu}g/m^3$. And then the range of PM-2.5 concentration of Non-PSD station was $17.4-56.6{\mu}g/m^3$, and then the range of PM-2.5 concentration of PSD station was $17.9{\sim}34.4{\mu}g/m^3$. In comparison with the results of the PSD and Non-PSD subway station, we found that the PM-10 removal efficiency of PSD was 30-40%. In conclusion, the PSD will be applied the effective facilities of decreasing PM-10 in subway station in Korea.