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

• Asian Journal of Atmospheric Environment
• /
• v.7 no.4
• /
• pp.177-190
• /
• 2013

Air pollution trends in Japan between 1970 and 2012 were analyzed, and the impact of air pollution countermeasures was evaluated. Concentrations of CO decreased from 1970 to 2012, and in 2012, the Japanese environmental quality standard (EQS) for CO was satisfied. Concentrations of $SO_2$ dropped markedly in the 1970s, owing to use of desulfurization technologies and low-sulfur heavy oil. Major reductions in the sulfur content of diesel fuel in the 1990s resulted in further decreases of $SO_2$ levels. In 2012, the EQS for $SO_2$ was satisfied at most air quality monitoring stations. Concentrations of $NO_2$ decreased from 1970 to 1985, but increased from 1985 to 1995. After 1995, $NO_2$ concentrations decreased, especially after 2006. In 2012, the EQS for $NO_2$ was satisfied at most air quality monitoring stations, except those alongside roads. The annual mean for the daily maximum concentrations of photochemical oxidants (OX) increased from 1980 to 2010, but after 2006, the $98^{th}$ percentile values of the OX concentrations decreased. In 2012, the EQS for OX was not satisfied at most air quality monitoring stations. Non-methane hydrocarbon (NMHC) concentrations generally decreased from 1976 to 2012. In 2011, NMHC concentrations near roads and in the general environment were nearly the same. The concentration of suspended particulate matter (SPM) generally decreased. In 2011, the EQS for SPM was satisfied at 69.2% of ambient air monitoring stations, and 72.9% of roadside air-monitoring stations. Impacts from mineral dust from continental Asia were especially pronounced in the western part of Japan in spring, and year-round variation was large. The concentration of $PM_{2.5}$ generally decreased, but the EQS for $PM_{2.5}$ is still not satisfied. The air pollution trends were closely synchronized with promulgation of regulations designed to limit pollutant emissions. Trans-boundary OX and $PM_{2.5}$ has become a big issue which contains global warming chemical species such as ozone and black carbon (so called SLCP: Short Lived Climate Pollutants). Cobeneficial reduction approach for these pollutants will be important to improve both in regional and global atmospheric environmental conditions.

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

• Korean Journal of Remote Sensing
• /
• v.29 no.6
• /
• pp.663-670
• /
• 2013

Total Vertical Column Density (VCD) of $NO_2$, a key component in air quality and tropospheric chemistry was measured using a ground-based instrument, Pandora, in Seoul from March 2012 to October 2013. The $NO_2$ measurements using Pandora were compared with those obtained by satellite remote sensing from Ozone Monitoring Instrument (OMI) where the intercomparison characteristics were analyzed as a function of measurement geometry, cloud amount and aerosol loading. The negative biases of the OMI $NO_2$ VCD were larger when cloud amount and Aerosol Optical Depth (AOD) were higher. The correlation coefficient between $NO_2$ VCDs from Pandora and OMI was 0.53 for the entire measurement period, whereas the correlation coefficient between the two was 0.74 when the cloud amount and AOD were low (cloud amount<3, AOD<0.4). The low bias of OMI data was associated with the shielding effect of the cloud and the aerosols.

• Journal of Korean Society for Atmospheric Environment
• /
• v.9 no.3
• /
• pp.207-215
• /
• 1993

In order to statistically predict $O_3$ levels in Seoul, the study used the TMS (telemeted air monitoring system) data from the Department of Environment, which have monitored at 20 sites in 1989 and 1990. Each data in each site was characterized by 6 major criteria pollutants ($SO_2, TSP, CO, NO_2, THC, and O_3$) and 2 meteorological parameters, such as wind speed and wind direction. To select proper variables and to determine each pollutant's behavior, univariate statistical analyses were extensively studied in the beginning, and then various applied statistical techniques like cluster analysis, regression analysis, and expert system have been intensively examined. For the initial study of high level $O_3$ prediction, the raw data set in each site was separated into 2 group based on 60 ppb $O_3$ level. A hierarchical cluster analysis was applied to classify the group based on 60 ppb $O_3$ into small calsses. Each class in each site has its own pattern. Next, multiple regression for each class was repeatedly applied to determine an $O_3$ prediction submodel and to determine outliers in each class based on a certain level of standardized redisual. Thus, a prediction submodel for each homogeneous class could be obtained. The study was extended to model $O_3$ prediction for both on-time basis and 1-hr after basis. Finally, an expect system was used to build a unified classification rule based on examples of the homogenous classes for all of sites. Thus, a concept of high level $O_3$ prediction model was developed for one of $O_3$ alert systems.

• Journal of Environmental Science International
• /
• v.21 no.2
• /
• pp.165-179
• /
• 2012

Indirect $CO_2$ effect due to non-methane volatile organic compound (NMVOC) emissions from solvent and product use and fugitive NMVOC emissions from fuels in the Republic of Korea and 13 Annex I countries under United Nations Framework on Climate Change were estimated and the proportions of them to total greenhouse gas (GHG) emissions ranged from 0.092% to 0.45% in 2006. Indirect greenhouse effect ($CO_2$, $CH_4$, and $O_3$) were estimated at 13 photochemical assessment monitoring sites in the Republic of Korea using concentrations of 8 NMVOCs of which indirect global warming potential (GWP) were available. The contribution of toluene to mixing ratio was highest at 11 sites and however, the contribution of toluene to indirect greenhouse effect was highest at nine sites. In contrast to toluene, the contributions of ethane, butane, and ethylene were enhanced. The indirect greenhouse effects of ethane and propane, of which ozone formation potentials are the lowest and the third lowest respectively among targeted 10 NMVOCs, ranked first and fourth highest respectively. Acetaldehyde has relatively higher maximum incremental reactivity and is classified as probable human carcinogen however, its indirect GWP ranked second lowest.

• Proceedings of the Korean Environmental Sciences Society Conference
• /
• 2003.11a
• /
• pp.5-10
• /
• 2003

This paper explores not only emerging scientific problems but also the difficulties communicating air quality issues into an increasingly sensitive the public and policy arena. The public understanding and trust in air pollution information and indices may be very different to the notions of validity or accuracy that are important for a scientist. We operate in a world where openness requires us to reveal both the difficulties and disagreements in our understanding of the polluted atmosphere. Yet this can be confusing and increase complexity in situations where clear political and social decisions are required. I am going to examine these issues, starting with questions of what substances we regard as pollutants and the difficulties of getting the correct balance of concern given the broadening the base of chemicals emitted to the environment. There are also questions of exposure particularly in terms of vulnerable populations, who may spend large amounts of time indoors, where air is rarely monitored. In contemporary society there are pollution problems that extend far beyond urban areas and we have to consider regional issues such as windblown dusts, smoke from forest fires along with issues of the emission of green house gases and ozone depleting substances. Finally I will discuss the issues of communicating with a concerned public and sceptical politicians and the troubling interface between technological and sociological control. Such complexity is often missed in a maze of seemingly stronger political and social needs.

• Journal of Korean Society for Atmospheric Environment
• /
• v.22 no.4
• /
• pp.518-528
• /
• 2006

The air quality index (AQI) is an index for reporting daily or hourly air quality to the general public. The AQI focuses on health effects that can happen within a few hours or days after breathing polluted air. Many countries have their own AQI reporting systems, and the HAEI (hourly air environment index) method is now being used in Korea. In this study, in order to compare the AQI results from different methods, we applied three methods. i.e. US AQI, Canadian AQI, and Korean HAEI, to the same air quality data-base. The data-base was constructed from 10 monitoring sites in Gyeong-buk province for the last four years since 2000. Based on the results, a critical evaluation of the Korean HAEI method was made, and a number of suggestions and recommendations were presented to improve the AQI reporting system in Korea.

• Journal of the Korean Data and Information Science Society
• /
• v.21 no.6
• /
• pp.1117-1124
• /
• 2010

The PM10 (Promethium 10) data is one of the important environmental data for measurement of the atmospheric condition of the country. In this article, the Autoregressive Error (ARE) model has been considered for analyzing the monthly PM10 data at the southern part of the Gyeonggi-Do, Suwon monitoring site in Korea. In the ARE model, six meteorological variables and four pollution variables are used as the explanatory variables for the PM10 data set. The six meteorological variables are daily maximum temperature, wind speed, relative humidity, rainfall, radiation, and amount of cloud. The four air pollution explanatory variables are sulfur dioxide ($SO_2$), nitrogen dioxide ($NO_2$), carbon monoxide (CO), and ozone ($O_3$). The result showed that the monthly ARE models explained about 13-49% for describing the PM10 concentration.

• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.34 no.3
• /
• pp.24-34
• /
• 2011

An Unmanned Aerial Vehicle (UAV) is a powered pilotless aircraft, which is controlled remotely or autonomously. UAVs are an attractive alternative for many scientific and military organizations. UAVs can perform operations that are considered to be risky or uninhabitable for human. UA V s are currently employed in many military missions such as reconnaissance, surveillance, enemy radar jamming, decoying, suppression of enemy air defense (SEAD), fixed and moving target attack, and air-to-air combat. UAVs also are employed in a number of civilian applications such as monitoring ozone depletion, inclement weather, traffic congestion, and taking images of dangerous territory. For accomplishing the UAV's missions, guarantee of survivability should be preceded. The main objective of this study is to suggest a mathematical programming model and a $A^*PS$-PGA (A-star with Post Smoothing-Parallel Genetic Algorithm) for an UAV's path planning to maximize survivability. A mathematical programming model is composed by using MRPP (Most Reliable Path Problem) and TSP (Traveling Salesman Problem). A path planning algorithm for UAV is applied by transforming MRPP into SPP (Shortest Path Problem).