• Journal of Korean Society for Atmospheric Environment
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• v.34 no.2
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• pp.356-365
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• 2018

While social networks have become very popular and powerful way of connecting people and sharing new information, they also effectively spread wrong or biased information to the public. We examine the so-called "Shandong peninsular rumor" that claims Chinese government is responsible for the increased air pollution in South Korea and Japan, by moving pollution-causing industries near Beijing to the Shandong peninsular which is close to South Korea. We demonstrate that the amounts of $NO_x$ and $SO_2$ emissions inferred by space-borne monitoring and regional air quality models show clear declining trends in past several years. We do not have any evidences to support the relation of Shandong peninsular emissions change to South Korean air quality.

• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.378-380
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• 2005

Remote sensing of atmospheric aerosol using MODIS satellite data has been proven to be very useful in global/regional scale aerosol monitoring. Due to their large spatial resolution of $10km^2$ MODIS aerosol optical thickness (AOT) data have limitations for local/urban scale aerosol monitoring applications. Modified Bremen Aerosol Retrieval (BAER) algorithm developed by von Hoyningen-Huene et al. (2003) and Lee et al. (2005) has been applied in this study to retrieve AOT in fe resolutions of $500m^2$ over Korea. Look up tables (LUTs) were constructed from the aerosol properties based on sun-photometer observation and radiation transfer model calculations. It was found that relative error between the satellite products and the ground observations was within about $15\%$. Resulting AOT products were correlated with surface PMIO concentration data. There was good correlation between MODIS AOT and surface PM concentration under certain atmospheric conditions, which supports the feasibility of using the high-resolution MODIS AOT for local and urban scale air quality monitoring

• Journal of Environmental Science International
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• v.3 no.4
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• pp.357-365
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• 1994

Air pollution characteristics and the influence of sea breeze on air pollution concentration were studied using the data measured at 7 air quality continuous monitoring stations in Pusan, 1993. Maximum air pollution concentration in Pusan was Gamjeondong for $SO_2$, Sinpyeongdong for TSP, Daeyeondong for $O_3, Kwangbokdong for $NO_2$, Beomcheondong for CO and all substances were under annual ambient air quality standards. Increased rate of concentration for sea breeze was 24.4% for 502, 31.5% for TSP, 8.0% fort $O_3, 26.7% for $NO_2$, 15.7% for CO. Frequencies distribution of $SO_2$, TSP, $O_3$, $NO_2$, and CO concentration for sea breeze moved toward high concentration class.

• Korean Journal of Remote Sensing
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• v.36 no.2_1
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• pp.121-137
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• 2020

Data from the Ozone Monitoring Instrument (OMI) satellite and national emission inventories were used in this study to analyze air quality in East Asia and estimate the impact of domestic and foreign emissions on South Korea's air quality, based on which future emissions were predicted. The concentration trends of nitrogen dioxide (NO₂) and sulfur dioxide (SO₂) in East Asia from 2005 to 2015 showed that both substances were highest in North East China (NEC), followed by South East China (SEC) and Seoul Metropolitan Area (SMA). The average SO₂ concentration was 1.63 times higher in NEC than in SMA. Analysis on the ratios of NO₂/SO₂ and NO_x/SO_x provides an indirect picture of the effect of transboundary air pollutants on atmospheric composition in Korea. The concentration ratio of NO₂/SO₂ in all study areas peaked in 2013 and SMA's emission ratio of NO_x/SO_x increased in 2015 by over 22% from 2013. Despite the reduction in domestic emissions, the concentration-to-emission ratios (NO₂/NO_x, SO₂/SO_x) rose gradually, which implies that other factors besides domestic emissions (e.g., foreign sources, lifetime, etc.) influence air quality in SMA. We estimated future emissions of NO_x and SO_x in SMA to be 296.2 and 39.0 ktons in 2025 and 284.4 and 33.8 ktons in 2035, respectively. Application of the inter-comparison techniques of this study to the data from the Geostationary Environment Monitoring Instrument (GEMS) is expected to provide concrete information which can be used to improve national emission inventories and figure out factors and sources that affect domestic air quality.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.8A
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• pp.846-851
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• 2008

With rapid development of communication industry, the kinds of communication service vary. According to the increasing use of radio waves, the intelligent and effective radio monitoring system needs to be developed, which is replaced for previous radio monitoring system. Next-generation intelligent radio monitoring system based on ITU-R, Rule of wireless facilities, and Radio Waves Act is used, and which can accurately and effectively function as effective radio monitoring system through spectrum analysis of channel power, frequency deviation, offset, and an occupied frequency bandwidth(99% or x-dB), about the analog and digital signal in On-Air of V/UHF bandwidth. Main function of the system has an radio quality measurement, unwanted electromagnetic signals (spurious, harmonic) measurement, high-speed spectrum measurement, frequency usage efficiency investigation, illegal radio exploration, working monitoring, In this paper, we proposes radio quality measurement, high-speed spectrum measurement of next-generation intelligent radio monitoring system.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2018.05a
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• pp.55-56
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• 2018

In order to construct an efficient monitoring system for major port cities in Korea, the first step to build and manage related laws and institutional infrastructure with strengthen the cooperation of the relevant agencies, regional port authorities, and port corporations. Second, for the management of air pollutants emitted by ports, a management system should be established through systematic inventory source inventory and real-time monitoring system. Third, active countermeasures should be established to reduce the emission of air pollutants by sources such as ships, harbor equipment, and trucks. This will improve the air quality of major port cities and move them to clean port cities.

• Journal of Korean Society for Atmospheric Environment
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• v.32 no.6
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• pp.559-574
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• 2016

Based on air quality monitoring data ('10~'14) of Suwon City provided by the Korean Department of Environment, a fundamental statistic for 5 criteria pollutants such as $SO_2$, CO, $NO_2$, $O_3$, and $PM_{10}$ was initially investigated. The purpose of this paper was to review the ambient air quality standards(AAQS) of Korea, the U.S.A. and the EU and further to assess the degree of standard strength by the achievability of the AAQS comparing each national standard. Since the level and the way of standards for each air pollutant are various among countries, it is difficult to determine the degree of relative attainment using the same set of data above. Further when all the areas having bad air quality for a specific pollutant are classified as non-attainment case, it is more difficult to assess the degree of standard strength. Thus we introduced a new concept called the average concentration distance (ACD) to quantitatively estimate the strength. As results, the Korean 1-hr $NO_2$ AAQS is slightly stronger than the US standard and weaker than the EU standard. The Korean $O_3$ standard is strongest; however, the Korean $PM_{10}$ standard is weakest. Furthermore the equivalent levels of 8-hr $O_3$ standards in the U.S.A. and the EU were respectively estimated as 97.5 and 95.7 percentiles of the Korean standard with maintaining the existing standard of 60 ppb.

• Journal of Environmental Science International
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• v.14 no.11
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• pp.1049-1056
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• 2005

[ $NO_2$ ] concentration characteristics of Busan metropolitan city was analysed by statistical method using hourly $NO_2$ concentration data$(1998\~2000)$ collected from air quality monitoring sites of the metropolitan city. 4 representative regions were selected among air quality monitoring sites of Ministry of environment. Concentration data of $NO_2$, 5 air pollutants, and data collected at AWS was used. Both Stepwise Multiple Regression model and ARIMA model for prediction of $NO_2$ concentrations were adopted, and then their results were compared with observed concentration. While ARIMA model was useful for the prediction of daily variation of the concentration, it was not satisfactory for the prediction of both rapid variation and seasonal variation of the concentration. Multiple Regression model was better estimated than ARIMA model for prediction of $NO_2$ concentration.

• 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.

• International Journal of Internet, Broadcasting and Communication
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• v.12 no.1
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• pp.130-136
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• 2020

There are many problems that occur currently in agriculture industries. The problems such as unexpected of changing weather condition, lack of labor, dry soil were some of the reasons that may cause the growth of the plants. Condition of the weather in local area is inconsistent due to the global warming effect thus affecting the production of the crops. Furthermore, the loss of farm labor to urban manufacturing jobs is also the problem in this industry. Besides, the condition for the plant like air humidity, air temperature, air quality index, and soil moisture are not being recorded automatically which is more reason for the need of implementation system to monitor the data for future research and development of agriculture industry. As of this, we aim to provide a solution by developing IoT-based platform along with the irrigation for increasing crop quality and productivity in agriculture field. We aim to develop a smart garden system environment which the system is able to auto-monitoring the humidity and temperature of surroundings, air quality and soil moisture. The system also has the capability of automating the irrigation process by analyzing the moisture of soil and the climate condition (like raining). Besides, we aim to develop user-friendly system interface to monitor the data collected from the respective sensor. We adopt an open source hardware to implementation and evaluate this research.