In this study, surface particulate matter (PM2.5) concentrations were calculated based on empirical equations using measurements of ceilometer backscatter intensities and meteorological variables taken over 19 months. To quantify the importance of meteorological conditions on the calculations of surface PM2.5 concentrations, eight different meteorological conditions were considered. For each meteorological condition, the optimal upper limit height for an integration of ceilometer backscatter intensity and coefficients for the empirical equations were determined using cross-validation processes with and without considering meteorological variables. The results showed that the optimal upper limit heights and coefficients depended heavily on the meteorological conditions, which, in turn, exhibited extensive impacts on the estimated surface PM2.5 concentrations. A comparison with the measurements of surface PM2.5 concentrations showed that the calculated surface PM2.5 concentrations exhibited better results (i.e., higher correlation coefficient and lower root mean square error) when considering meteorological variables for all eight meteorological conditions. Furthermore, applying optimal upper limit heights for different weather conditions revealed better results compared with a constant upper limit height (e.g., 150 m) that was used in previous studies. The impacts of vertical distributions of ceilometer backscatter intensities on the calculations of surface PM2.5 concentrations were also examined.
Since low-floor apartments ate vertically closer to patting lots and roadways, it is hypothesized that residents in low-floor apartments may be exposed to elevated ambient levels of motet vehicle emissions compared to residents in high-floor apartments. The present study examined this hypothesis by measuring two motor vehicle source-related pollutants(CO and PM10) in ambient air of high-rise apartment buildings within the boundary of industrial complexes according to atmospheric stability The ambient air concentrations of CO and PM10 were higher for low-floor apartments than for high-floor apartments, regardless of atmospheric stability, The median concentration ratio of the low-floor air to high-floor alt ranged from 1.3 to 2.0, depending upon atmospheric stabilities, seasons and compounds. Moreover, the CO and PM10 concentrations were significantly higher in the winter and in the summer, regardless of the Hoot height. Atmospheric stability also was suggested to be important for the residents' exposure of high-rise apartment buildings to both CO and PM10. The median ratios of surface inversion air to non-surface inversion air ranged from 1.2 to 1.7 and from 1.0 to 1.6 lot PM10 and CO, respectively, depending upon seasons. Conclusively, these parameters(apartment floor height, season, and atmospheric stability) should be considered when evaluating the exposure of residents, living in high-rise apartment buildings, to CO and PM10. Meanwhile, the median PMl0 outdoor concentrations were close to or higher than the Korean annual standards for PM10, and the maximum PM10 concentrations substantially exceeded the Korean PM10 standard, thus suggesting the need for a management strategy for ambient PM 10. Neither the median nor the maximum outdoor CO concentrations, however, were higher than the Korean CO standard.
Numerous researchers have proposed that surface area is a more appropriate indicator than mass for evaluating pulmonary inflammatory responses caused by exposure to fine and ultrafine particles. In this study, measurements of surface area concentrations of aerosols were conducted in Yokohama, Japan, using the diffusion charging method. $PM_{2.5}$ mass concentration and black carbon concentration in $PM_{2.5}$ were also measured. The 24-hour continuous measurement campaigns were conducted 39 times from March to November, 2014. The surface area concentration was more closely correlated with the black carbon concentration than with the $PM_{2.5}$ mass concentration. It is considered that the abundance of black carbon particles significantly affects the surface area concentration of $PM_{2.5}$. The strength of the correlation between the surface area and black carbon concentrations varied considerably among the measurement campaigns. A relatively weaker afternoon correlation was observed compared with the other time zones (morning, evening, and night). We consider that these phenomena are due to the transportation/formation of the particles other than black carbon that affects surface area concentration and/or the variation of the surface condition of the black carbon particles.
Journal of Korean Society for Atmospheric Environment
/
v.22
no.4
/
pp.440-450
/
2006
PM10, NOx, and $O_3$ were measured at six locations, of which each three is horizontally and vertically distributed respectively, in an apartment complex around the heavily traffic road. Those were measured seven times a day with two hours interval starting from 8 o'clock in the morning for 15 days during May 2005 $\sim$ September 2005. PM10 and NOx showed high concentrations in rush hours while low concentrations in midday due to the direct emissions from automobiles in operation. Temporal variations of 01 showed very much similar trend appeared in normal urban atmospheres. The spatial distributions of PM10, NOx and $O_3$ showed that almost all of concentrations were higher in a row of Roadside > Surface at 130 m apart from the road > Surface at 230 m apart from the road > 3rd floor of apartment building > 15th floor of apartment building > 27th floor of apartment building. Model equations, which can project spatial concentration distributions, were constructed by combining the horizontal and the vertical linear regression equations derived from six mean values corresponding to six measuring locations. According to inter-comparison of PM10, NOx, and $O_3$ with the constructed model equations, concentration gradients were higher in a row of Vertical direction of NOx > Vertical direction of PM10 > Horizontal direction of NOx > Horizontal direction of PMIO > Vertical direction of $O_3$ > Horizontal direction of $O_3$. Why concentration gradient of particulate PM10 is lower than that of gaseous NOx is in question, and should be studied.
Lee, Hae Young;Kim, Wan;Kim, Yong-Hwan;Maeng, Seongjin;Lee, Sang Hoon
Journal of Radiation Protection and Research
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v.41
no.3
/
pp.268-273
/
2016
Background: This study was a long-term evaluation of $^{137}Cs$ and $^{90}Sr$ activity concentrations in seawater samples from the East Sea, Korea, in order to establish current activity levels. Results and long-term monitoring trends will be useful in the future monitoring of environmental radioactivity. Materials and Methods: Surface seawater samples were collected quarterly from Guryongpo and Jangho in the East Coast between 1998 and 2010 and the quarterly deep seawater samples were collected from three sites in the sea adjacent to Ulleung-do between 2012 and 2015. The activity concentrations of $^{137}Cs$ were measured using a gamma-spectrometer. The activity concentrations of $^{90}Sr$ and $^{90}Y$ in a radioactive equilibrium state were measured using a gas flow proportional counter. Results and Discussion: We found the annual average activity concentrations of $^{137}Cs$ in the surface seawater was $1.66-2.89mBq{\cdot}kg^{-1}$ in Guryongpo and $1.68-2.43mBq{\cdot}kg^{-1}$ in Jangho. The annual average activity concentrations of $^{90}Sr$ in the surface seawater was $0.83-1.98mBq{\cdot}kg^{-1}$ in Guryongpo and $0.82-1.57mBq{\cdot}kg^{-1}$ in Jangho. The annual average activity concentrations of $^{137}Cs$ in the deep seawater sites were $1.51-1.73mBq{\cdot}kg^{-1}$, $1.19-1.60mBq{\cdot}kg^{-1}$ and $0.87-1.15mBq{\cdot}kg^{-1}$ in TH, JD, and HP. The annual average activity concentrations of $^{90}Sr$ in the same deep seawater sites were $1.00-1.94mBq{\cdot}kg^{-1}$, $0.82-1.26mBq{\cdot}kg^{-1}$, and $0.79-1.32mBq{\cdot}kg^{-1}$. The effective half-life was calculated by analyzing change over time in the activity concentration in the surface seawater. The effective half-life of $^{137}Cs$ was $15.3{\pm}0.1years$ in Guryongpo and $102{\pm}3years$ in Jangho. The effective half-life of $^{90}Sr$ was $28.3{\pm}4.3years$ in Guryongpo and $16.6{\pm}0.1years$ in Jangho. The ratio of the average activity concentration ($^{137}Cs/^{90}Sr$) was 1.72 in the surface seawater, which is similar to the reported ratio of the global radioactive fallout. The ratio in the deep seawater was 1.24, which is somewhat low compared to the global ratio (1.6, 1.8). Conclusion: Activity concentrations of $^{137}Cs$ and $^{90}Sr$ in the seawaters of the East Sea were similar to the previously reported activity levels in the East Sea and northwestern Pacific as a result of global radioactive fallout following atmospheric nuclear weapon tests.
Park, Il-Soo;Park, Moon-Soo;Lee, Joonsuk;Jang, Yu Woon
Journal of Environmental Science International
/
v.29
no.12
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pp.1223-1237
/
2020
This study focused on comparing the meteorological conditions in the Atmospheric Boundary Layer (ABL) on high-event days and non-event days in the Seoul Metropolitan Area (SMA). We utilized observed PM10 and meteorological variables at the surface as well as at the upper heights. The results showed that high-event days were consistently associated with lower wind speed, whereas wind direction showed no particular difference between high-event and non-event days with frequent westerlies and northwesterlies for both cases. During high-event days, the temperature was much warmer than the monthly normal values with a sharp increasing trend, and Relative Humidity (RH) was higher than the monthly normal, especially on high-event days in February. During high-event days in spring, a double inversion layer was present at surface and upper heights. This indicates that stability in the multi-layer is an important indicator of higher PM10 concentrations. Net radiation in spring and winter is also closely associated with higher PM10 concentrations. Strong net radiation resulted in large sensible heat, which in turn facilitated a deeper mixing height with diluted PM10 concentrations; in contrast, PM10 concentrations were higher when sensible heat in spring and winter was very low. We also confirmed that convective and friction velocity was higher on non-event days than on high-event days, and this was especially obvious in spring and winter. This indicated that thermal turbulence was dominant in spring, whereas in winter, mechanical turbulence was dominant over the SMA.
Journal of Korean Society of Occupational and Environmental Hygiene
/
v.24
no.1
/
pp.65-73
/
2014
Objectives: The purposes of this study are to investigate workers' exposures to respirable particles generated in taconite mines and to compare two metric methods for mass concentrations using direct-reading instruments. Methods: Air monitorings were conducted at six mines where subjects have been exposed primarily to particulate matters in crushing, concentrating, and pelletizing processes. Air samples were collected during 4 hours of the entire work shift for similarly exposure groups(SEGs) of nine jobs(N=37). Following instruments were employed to evaluate the workplace: a nanoparticle aerosol monitor(particle size range; 10-1000 nm, unit: ${\mu}m^2/cc$, Model 9000, TSI Inc.); DustTrak air monitors($PM_{10}$, $PM_{2.5}$, unit: $mg/m^3$, Model 8520, TSI Inc.); a condensation particle counter(size range; 20-1000 nm, unit: #/cc, P-Trak 8525, TSI Inc.); and an optical particle counter(particle number by size range $0.3-25{\mu}m$, unit: #/cc, Aerotrak 9306, TSI Inc.). Results: The highest airborne concentration among SEGs was for furnace operator followed by pelletizing maintenance workers in number of particle and surface area, but not in mass concentrations. The geometric means of $PM_{2.5}$ by the DustTrak and the Ptrak/Aerotrak were $0.04{\mu}m$(GSD 2.52) and $0.07{\mu}m$(GSD 2.60), respectively. Also, the geometric means of RPM by the DustTrak and the Ptrak/Aerotrak were $0.16{\mu}m$(GSD 2.24) and $0.32{\mu}m$(GSD 3.24), respectively. The Pearson correlation coefficient for DustTrak $PM_{2.5}$ and Ptrak/Aerotrak $PM_{2.5}$ was 0.56, and that of DustTrak RPM and Ptrak/Aerotrak RPM was 0.65, indicating a moderate positive association between the two sampling methods. Surface area and number concentration were highly correlated($R^2$ = 0.80), while $PM_{2.5}$ and RPM were also statistically correlated each other($R^2$ = 0.79). Conclusions: The results suggest that it is possible to measure airborne particulates by mass concentrations or particle number concentrations using real-time instruments instead of using the DustTrak Aerosol monitor that monitor mass concentrations only.
During the 1st Korea-Russia Arctic Expedition from 3 to 26 August, 2000 phytoplankton biomass and nutrient concentration were measured in the Barents and Kara Seas. Total of 57 surface samples were collected f3r the phytoplankton related measurements. Chlorophyll a (chi a) concentraitons were measured to investigate the relations between physico-chemical factors and phytoplankton biomass distribution. Chl a values ranged from 0.14 to $2.34mg\;m^{-3}$ (mean of $0.65{\pm}0.42mg\;m^{-3}$) over the surface stations. The elevated values of the chi a concentrations $(1.49{\sim}2.34mg\;m^{-3})$ were found in the southeastern Barents Sea near the Pechora River. Nanoplanktonic $(<20{\mu}m)$ phytoflagellates were the important contributors for the increase of the chi a. The nano-sized phytoflagellates accounted for more than 80% of the total chi a biomass in the study area. Mean chi a concentration in the Barents Sea $(0.72{\pm}0.57 mg\;m^{-3})$ was higher than in the Kan Sea $(0.52{\pm}0.45mg\;m^{-3})$, but there was no big difference between two areas. Surface temperatures and salinities ranged from 4.1 to $11.7^{\circ}C$ (mean of $8.8{\pm}1.9^{\circ}C$) and from 23.8 to 32.5psu (mean of $30.3{\pm}1.9^{\circ}C$ psu), respectively. The physical factors were not highly correlated with phytoplankton distribution. It is speculated that the insignificant correlation between phytoplankton biomass and physical factor was due to the same current which introduced similar water mass with higher water temperature and lower salinity into the study area. The mean values of major nutrients such as ammonia, nitrite, nitrate, phosphate, and silicate were $0.42{\pm}0.31{\mu}M,\;0.10{\pm}0.03{\mu}M,\;1.44{\pm}1.03{\mu}M,\;0.35{\pm}0.12{\mu}M,\;10.99{\pm}3.45{\pm}M$, respectively. The relations between phytoplankton biomass and nutrient concentration were not close, indicating that the surface nutrient concentrations during the study seem to be controlled by other physical factors such as input of fresh water (i.e. dilution effects).
Journal of Korean Society for Atmospheric Environment
/
v.31
no.5
/
pp.430-436
/
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.
Korea has recently suffered from severe hazes, largely being long-range transported from China but frequently mixed with domestic pollution. It is important to identify the origin of the frequently-occurring hazes, which is however hard to clearly determine in a quantitative term. In this regard, we suggest a possible classification procedure of various hazes into long-range transported haze (LH), Yellow Sand (YS), and urban haze (UH), based on mass loading of fine particles, time lag of PM mass concentrations between two sites aligned with dominant wind direction, backward trajectory of air mass, and the mass ratio of PM2.5 to PM10. The analysis sites are Seoul (SL) and Baengnyeongdo (BN), which are distant about 200 km from each other in the west to east direction. Aerosol concentrations at BN are overall lower than those of SL, indicative of BN being a background site for SL. We found distinct time lag of PM2.5 and PM10 concentrations between BN and SL in case of both LH and YS, but the intensity of YS being stronger than LH. Time scale (e-folding time scale) of LH appears to be longer and more variable than YS, which implies that LH covers much larger spatial scale. In addition, we found linear and significant correlations between ${\tau}_a$ obtained from sunphotometer and ${\tau}_{cal}$ calculated from surface aerosol scattering coefficient for LH episodes, relative to few correlation between those for YS, which might be associated with transported height of YS being much higher than LH. Therefore surface PM concentrations for the YS period are thought to be not representative for vertical integrated amount of aerosol loadings, probably by virtue of decoupled structure of aerosol vertical distribution. Improvement of various hazes classification based on the current result would provide the public as well as researchers with more accurate information of LH, UH, and YS, in terms of temporal scale, size, vertical distribution of aerosols, etc.
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