• Journal of Environmental Health Sciences
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• v.22 no.4
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• pp.43-48
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• 1996

Indoor air quality(IAQ) in museum is very important for protection of cultural properties. In our study, we measured air pollutants($NO_x, NH_3, SO_2, O_3$, CO, $CO_2$, TSP), temperature and humidity to evaluate IAQ of national central museum. Indoor carbon dioxide and TSP concentrations were higher than outdoor concentrations. Temperature, huinidity and TSP had large deviation depending on air conditioning operates or not. Indoor gas phase pollutants except $CO_2$ were lower than outdoor concentrations, but $SO_2$ concentration was high in storage. $CO_2$ and TSP were influenced by the number of spectators.

• Journal of Environmental Science International
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• v.7 no.5
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• pp.573-580
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• 1998

This study examined the carbon dioxide ($CO_2$) pollution inside vehicles under low ventilation condition and evaluated the Air Quality System (AQS) for in-vehicle air quality using two techniques. The low ventilation condition is not recommended in order to keep oxygen-rich condition inside vehicles. Under the low ventilation condition, the in-vehicle $CO_2$ concentrations exceeded 1,000 ppm, the air qualify guidelines in the United States, Western Europe, and Japan, indicating more oxygen deficiency inside vehicles. On the contrary, with the AQS-on condition, the in-vehicle $CO_2$ concentrations were less than 1,000 ppm fer most of the driving time, indicating that the AQS could solve the problem of $CO_2$ accumulation inside vehicles under the low ventilation condition. The AQS test conducted by comparing carbon monoxide (CO) and volatile organic compound (VOC) concentrations inside two vehicles indicated that the AQS effectively decreased the in-vehicle concentrations by 21 to 36%, as compared to medium ventilation condition with the windows closed, the vent opened, and air conditioning on. In addition, The AQS test conducted by comparing the interior and exterior concentrations indicated that the AQS effectively decreased the in-vehicle concentrations by 18 to 31%, as compared to medium ventilation condition.

• Asian Journal of Atmospheric Environment
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• v.11 no.4
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• pp.235-253
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• 2017

This study was conducted for analyzing the contribution factors on ozone concentrations and its long term trends in each major city and province in Korea through several statistical methods such as simple linear regression, generalized linear model, KZ-filer, correlation matrix, Kringing method, and cluster analysis. The overall ozone levels in South Korea have been consistently increasing over the past 10 years. The ozone concentrations in Seoul, the biggest city in Korea, are the lowest in all areas with the highest increasing ratio for $95^{th}%$ ozone. It is thought that the active photochemical reaction could affect the higher ozone concentration increase. On the other hand, the ozone concentrations in Jeju are the highest in Korea with the highest increasing ratio for $5^{th}%$, $33^{th}%$, and $50^{th}%$ ozone. It is also thought that the weak $NO_x$ titration could be the reason of higher ozone concentrations in Jeju. In case of Jeju, transport related factors is the major factor affecting the ozone trend. Thus, it is assumed that the variation of ozone trend of Asian region affecting the ozone trend in Jeju, where domestic ozone photochemical reaction is less active than urban area. It is thought that the photochemical reaction plays the role of increasing of ozone concentrations in the urban area, even though the LRT affected on the increase of ozone concentrations in non-urban area.

• Journal of Korean Society for Atmospheric Environment
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• v.30 no.5
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• pp.434-448
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• 2014

The aerosol characteristics between haze episode and Asian dust event were identified in January and March, 2013 in Gwang-ju of Korea to investigate the metal elements, ionic concentrations and carbonaceous particles of $PM_{2.5}$ and $PM_{10}$. In the haze episode, the concentrations were increased 1~3.2 times of ionic species and 1.6~2.7 of metal elements. Especially, the concentration of $NO{_3}{^-}$, $SO{_4}{^2-}$ and $NH{_4}{^+}$ consists of 50 percent in ionic species during haze episode that was higher than Asian dust event. This suggests that secondary aerosols from anthropogenic air pollution were mainly contributed by haze episode. During the Asian dust event, increase of metal concentrations was higher than haze episode because of remarkable increase of Ti, K and Fe originated from soil. The concentrations of carbonaceous particles were increased 2.5 times during haze episode, and 2.4 times of OC and 2.1 times of EC during Asian dust event in $PM_{2.5}$. However, these aerosol mass concentration does not affect the OC/EC ratio. The average equivalence ratios of cations/anions in $PM_{2.5}$ were 0.99 in haze episodes and 0.94 during non-event day. The neutralization factor of $NH_3$ was higher than that of $CaCO_3$. Futhermore, $NH{_4}{^+}$ aerosol was aged due to atmospheric stagnation that might be affected by the haze episode.

• Journal of Korean Society for Atmospheric Environment
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• v.34 no.1
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• pp.16-37
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• 2018

In this study, difference in chemical composition of $PM_{2.5}$ observed between the year 2013 and 2015 at six air quality intensive monitoring stations (Bangryenogdo (BR), Seoul (SL), Daejeon (DJ), Gwangju (GJ), Ulsan (US), and Jeju (JJ)) was investigated and the possible factors causing their difference were also discussed. $PM_{2.5}$, organic and elemental carbon (OC and EC), and water-soluble ionic species concentrations were observed on a hourly basis in the six stations. The difference in chemical composition by regions was examined based on emissions of gaseous criteria pollutants (CO, $SO_2$, and $NO_2$), meteorological parameters (wind speed, temperature, and relative humidity), and origins and transport pathways of air masses. For the years 2013 and 2014, annual average $PM_{2.5}$ was in the order of SL ($${\sim_=}DJ$$)>GJ>BR>US>JJ, but the highest concentration in 2015 was found at DJ, following by GJ ($${\sim_=}SJ$$)>BR>US>JJ. Similar patterns were found in $SO{_4}^{2-}$, $NO_3{^-}$, and $NH_4{^+}$. Lower $PM_{2.5}$ at SL than at DJ and GJ was resulted from low concentrations of secondary ionic species. Annual average concentrations of OC and EC by regions had no big difference among the years, but their patterns were distinct from the $PM_{2.5}$, $SO{_4}^{2-}$, $NO_3{^-}$, and $NH_4{^+}$ concentrations by regions. 4-day air mass backward trajectory calculations indicated that in the event of daily average $PM_{2.5}$ exceeding the monthly average values, >70% of the air masses reaching the all stations were coming from northeastern Chinese polluted regions, indicating the long-range transportation (LTP) was an important contributor to $PM_{2.5}$ and its chemical composition at the stations. Lower concentrations of secondary ionic species and $PM_{2.5}$ at SL in 2015 than those at DJ and GJ sites were due to the decrease in impact by LTP from polluted Chinese regions, rather than the difference in local emissions of criteria gas pollutants ($SO_2$, $NO_2$, and $NH_3$) among the SL, DJ, and GJ sites. The difference in annual average $SO{_4}^{2-}$ by regions was resulted from combination of the difference in local $SO_2$ emissions and chemical conversion of $SO_2$ to $SO{_4}^{2-}$, and LTP from China. However, the $SO{_4}^{2-}$ at the sites were more influenced by LTP than the formation by chemical transformation of locally emitted $SO_2$. The $NO_3{^-}$ increase was closely associated with the increase in local emissions of nitrogen oxides at four urban sites except for the BR and JJ, as well as the LTP with a small contribution. Among the meterological parameters (wind speed, temperature, and relative humidity), the ambient temperature was most important factor to control the variation of $PM_{2.5}$ and its major chemical components concentrations. In other words, as the average temperature increases, the $PM_{2.5}$, OC, EC, and $NO_3{^-}$ concentrations showed a decreasing tendency, especially with a prominent feature in $NO_3{^-}$. Results from a case study that examined the $PM_{2.5}$ and its major chemical data observed between February 19 and March 2, 2014 at the all stations suggest that ambient $SO{_4}^{2-}$ and $NO_3{^-}$ concentrations are not necessarily proportional to the concentrations of their precursor emissions because the rates at which they form and their gas/particle partitioning may be controlled by factors (e.g., long range transportation) other than the concentration of the precursor gases.

• Journal of Korean Society for Atmospheric Environment
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• v.31 no.5
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• pp.430-436
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• 2015

Numerical air quality forecasting suffers from the large uncertainties of input data including emissions, boundary conditions, earth surface properties. Data assimilation has been widely used in the field of weather forecasting as a way to reduce the forecasting errors stemming from the uncertainties of input data. The present study aims at evaluating the effect of input data on the air quality forecasting results in Korea when data assimilation was invoked to generate the initial concentrations. The forecasting time was set to 36 hour and the emissions and initial conditions were chosen as tested input parameters. The air quality forecast model for Korea consisting of WRF and CMAQ was implemented for the test and the chosen test period ranged from November $2^{nd}$ to December $1^{st}$ of 2014. Halving the emission in China reduces the forecasted peak value of $PM_{10}$ and $SO_2$ in Seoul as much as 30% and 35% respectively due to the transport from China for the no-data assimilation case. As data assimilation was applied, halving the emissions in China has a negligible effect on air pollutant concentrations including $PM_{10}$ and $SO_2$ in Seoul. The emissions in Korea still maintain an effect on the forecasted air pollutant concentrations even after the data assimilation is applied. These emission sensitivity tests along with the initial condition sensitivity tests demonstrated that initial concentrations generated by data assimilation using field observation may minimize propagation of errors due to emission uncertainties in China. And the initial concentrations in China is more important than those in Korea for long-range transported air pollutants such as $PM_{10}$ and $SO_2$. And accurate estimation of the emissions in Korea are still necessary for further improvement of air quality forecasting in Korea even after the data assimilation is applied.

• 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 Environmental Impact Assessment
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• v.27 no.2
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• pp.215-231
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• 2018

It was analyzed to identify the cause of $PM_{2.5}$ concentration changes for the fall in 2016 and 2017 in South Korea using ground measurement data such as meterological variables and $PM_{2.5}$, AOD from GOCI satellite, and WRF-CMAQ modeling system. The result of ground measurement data showed that the $PM_{2.5}$ concentrations for the fall in 2017 decreased by 12.3% ($3.0{\mu}g/m^3$) compared to that of 2016. The difference of $PM_{2.5}$ concentrations between 2016 and 2017 mainly occurred for 11 Oct. - 20 Oct. (CASE1) and 15 Nov. - 19 Nov. (CASE2) when weather conditions were difficult to long-range transport from foreign regions and favored atmospheric ventilation in 2017 compared to 2016. Simulated $PM_{2.5}$ concentrations in 2017 decreased by 64.0% ($23.1{\mu}g/m^3$) and 35.7% ($12.2{\mu}g/m^3$) during CASE1 and CASE2, respectively. These results corresponded to the changes in observed $PM_{2.5}$ concentrations such as 53.6% for CASE1 and 47.8% for CASE2. It is implied that the changes in weather conditions affected significantly the $PM_{2.5}$ concentrations for the fall between 2016 and 2017. The contributions to decreases in $PM_{2.5}$ concentrations was assessed as 52.8% by long-range transport from foreign regions and 47.2% by atmospheric ventilation effects in domestic regions during CASE1, whereas their decreases during CASE2 were affected by 66.4% from foreign regions and 33.6% in domestic regions.

• Journal of Environmental Impact Assessment
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• v.16 no.6
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• pp.381-391
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• 2007

The air quality modeling was carried out to assess the impact of air quality for large scale urban development. The site for the assessment is Multi-fuctional Administrative City which locates in Yeongi-gun, Chungcheongnam-do and estimated population in 2030 is 500,000. Two automatic weather monitoring stations were installed to monitor the meteorological variables for a year and upper air meteorological parameters were measured using radiosonde for 5 days with 4 hours interval in every season. The air quality of standard air pollutants were also measured for 5 days continuously in every season. The results of wind field analysis based on the site measurements and CALMET modeling showed that the valley and mountain winds were prevailed when the sypnotic wind was weak. It also showed that wind speed and directions were highly space-variable within the site basin. The variable wind characteristics implies that the Gaussian dispersion model such ISC3 and AERMOD are not appropriate and the unsteady-sate Lagrangian model such as CALPUFF is preferable. CALPUFF model was applied to assess air quality impact of new sources. The new sources were those for individual and group heating facilities as well as the traffic increases. The results showed that the estimated concentrations of CO and $SO_2$ pollutants by summing the impact concentration of new sources by the dispersion model and the ambient air concentrations by the site measurements were acceptable but those of PM-10 and $NO_2$ would violate ambient air quality standards at several locations due to high ambient air concentrations. It is recommended that the emission reductions near the site should be enforced to improve the ambient air quality.

• Journal of Environmental Health Sciences
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• v.39 no.1
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• pp.99-103
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• 2013

Objectives: This paper was prepared in memory of Jerry Sherwood, who provided a significant contribution to the Korean environmental and occupational health fields. Methods: Rare air quality data in Seoul were gathered by Jerry Sherwood when he visited Korea in the early 1980s. $SO_2$ and TPM concentrations were measured. These air quality measurements were based on ambient stationary monitoring and indoor air quality monitoring in various locations. Measurement during transportation was also applied. Results: Ambient $SO_2$ and TPM concentrations in Seoul were very high in the early 1980s. Ambient $SO_2$ concentrations were higher at nighttime. While ambient $SO_2$ concentrations varied by location, the Guro industrial area showed high levels. When indoor sources were presented, indoor $SO_2$ concentration was higher than outdoor level. Coal briquettes were closely associated with high indoor $SO_2$ concentration. Conclusion: This paper provided valuable historical information of air quality in Seoul.