The average ratio of the daily UV-B to total solar (75) irradiance at Busan (35.23$^{\circ}$N, 129.07$^{\circ}$E) in Korea is found as 0.11%. There is also a high exponential relationship between hourly UV-B and total solar irradiance: UV-B=exp (a$\times$(75-b))(R$^2$=0.93). The daily variation of total ozone is compared with the UV-B irradiance at Pohang (36.03$^{\circ}$N, 129.40$^{\circ}$E) in Korea using the Total Ozone Mapping Spectrometer (TOMS) data during the period of May to July in 2005. The total ozone (TO) has been maintained to a decreasing trend since 1979, which leading to a negative correlation with the ground-level UV-B irradiance doting the given period of cloudless day: UV-B=239.23-0.056 TO (R$^2$=0.52). The statistical predictions of daily total ozone are analyzed by using the data of the Brewer spectrophotometer and TOMS in East Asia including the Korean peninsula. The long-term monthly averages of total ozone using the multiplicative seasonal AutoRegressive Integrated Moving Average (ARIMA) model are used to predict the hourly mean UV-B irradiance by interpolating the daily mean total ozone far the predicting period. We also can predict the next day's total ozone by using regression models based on the present day's total ozone by TOMS and the next day's predicted maximum air temperature by the Meteorological Mesoscale Model 5 (MM5). These predicted and observed total ozone amounts are used to input data of the parameterization model (PM) of hourly UV-B irradiance. The PM of UV-B irradiance is based on the main parameters such as cloudiness, solar zenith angle, total ozone, opacity of aerosols, altitude, and surface albedo. The input data for the model requires daily total ozone, hourly amount and type of cloud, visibility and air pressure. To simplify cloud effects in the model, the constant cloud transmittance are used. For example, the correlation coefficient of the PM using these cloud transmissivities is shown high in more than 0.91 for cloudy days in Busan, and the relative mean bias error (RMBE) and the relative root mean square error (RRMSE) are less than 21% and 27%, respectively. In this study, the daily variations of calculated and predicted UV-B irradiance are presented in high correlation coefficients of more than 0.86 at each monitoring site of the Korean peninsula as well as East Asia. The RMBE is within 10% of the mean measured hourly irradiance, and the RRMSE is within 15% for hourly irradiance, respectively. Although errors are present in cloud amounts and total ozone, the results are still acceptable.
Fresh PM2.5 smokes emitted from combustion of four biomass materials (pellet, palm fruit fiber (PFF), PKS, and sawdust) in a laboratory-controlled environment were characterized using an attenuated total reflectance-fourier transform infrared (ATR-FTIR) technique. In smoke samples emitted from combustion of pellets, PFF and PKS, which is being used as boiler fuels for greenhouses in rural areas, the organic carbon/elemental carbon (OC/EC) ratios in PM2.5 were very high (14.0-35.5), whereas in sawdust smoke samples they were significantly low (<4.0) due to the combustion method close to flaming combustion. ATR-FTIR analysis showed that OH(3400-3250 cm-1), CH3(2958-2840 cm-1), CH2(2910 cm-1 and 2850 cm-1), ketone(1726-1697 cm-1), C=C(1607-1606 cm-1 and 1515-1514 cm-1), lignin (1463-1462 cm-1 and 1430-1428 cm-1) and -NO2(1360-1370 cm-1) peaks were identified in all biomass burning (BB) smoke samples. However, additional peaks appeared depending on the type of biomass. Among the four types of biomass materials, an additional peak of the methylene group CH3(2872-2870 cm-1) appeared only in PFF and PKS smoke samples, and a peak of C=O(1685 cm-1) was also confirmed. And in the case of PKS smoke samples, a peak of aromatic C=C(1593 cm-1 and 1476 cm-1) that did not appear in other BB samples was also observed. This indicates that the molecular structure of organic compounds emitted during BB differs depending on the type of biomass materials. The results of this study are expected to provide valuable information to more specifically reveal the effect of BB on PM2.5 collected in the atmospheric environment.
The microbial metagenome characteristics of bioaerosols and particulate matter (PM) in the outdoor atmospheric environment and the effects of climate and environmental factors on the metagenome were analyzed. The concentrations of bacteria and fungi in bioaerosols and PM were determined by sampling different regions with different environmental properties. A variety of culture-independent methods were used to analyze the microbial metagenome in aerosols and PM samples. In addition, the effects of meteorological and environmental factors on the diversity and metagenomes of bacteria and fungi were investigated. The survival, growth, and dispersal of the microorganisms in the atmosphere were markedly affected by local weather conditions and the air pollutant concentration. The concentration of airborne microorganisms increased as the temperature increased, but their concentration decreased in summer, due to the effects of high temperatures and strong ultraviolet rays. Humidity and microbial concentration were positively correlated, but when the humidity was too high, the dispersion of airborne microorganisms was inhibited. These comprehensive data on the microbial metagenome in bioaerosols and PM may be used to understand the roles and functions of microorganisms in the atmosphere, and to develop strategies and abatement techniques to address the environmental and public health problems caused by these microorganisms.
Air-borne pollen, biogenically created aerosol particle, influences Earth's radiative balance, visibility impairment, and human health. The importance of pollens has resulted in numerous experimental studies aimed at characterizing their dispersion and transport, as well as health effects. There is, however, limited scientific information concerning the optical properties of airborne pollen particles contributing to total ambient aerosols. In this study, for the first time, optical characteristics of pollen such as aerosol backscattering coefficient, aerosol extinction coefficient, and depolarization ratio at 532 nm and their effect to the atmospheric aerosol were studied by lidar remotes sensing technique. Dual-Lidar observations were carried out at the Gwangju Institute of Science & Technology (GIST) located in Gwagnju, Korea ($35.15^{\circ}E$, $126.53^{\circ}N$) for a spring pollen event from 5 to 7 May 2009. The pollen concentration was measured at the rooftop of Gwangju Bohoon hospital where the building is located 1.0 km apart from lidar site by using Burkard trap sampler. During intensive observation period, high pollen concentration was detected as 1360, 2696, and $1952m^{-3}$ in 5, 6, and 7 May, and increased lidar return signal below 1.5km altitude. Pollen optical depth retrieved from depolarization ratio was 0.036, 0.021, and 0.019 in 5, 6, and 7 May, respectively. Pollen particles mainly detected in daytime resulting increased aerosol optical depth and decrease of Angstrom exponent.
This study analyzed mass concentrations of PM10 and PM2.5, as measured at Tae-ahn and Gang-nae, Cheongju in central Korea over the period from 2011 to 2015. Higher mass concentrations of PM10, with the exception of dustfall cases during the period of winter and spring, reflected the influence of a prevailing westerly airflow, while the level of PM10 stayed at a low level in summer, reflecting the influence of North Pacific air mass and frequent rainfall. Accordingly, cases where a daily PM10 average of $81{\mu}gm^{-3}$ or over (exceeding the status of fine dust particles being 'a little bit bad') were often observed during the period of winter and spring, with more cases occurring in parts of Tae-ahn that are located close to the sources of pollutant emission in eastern China. Dustfall usually originated from dust storms made up of particles $2.5{\mu}m$ or over in diameter. However, anthropogenic haze displayed a high composition ratio of particulate less than $2.5{\mu}m$ in diameter. Accordingly, brightness temperature difference (BTD) values from the Communication, Ocean and Meteorological Satellite (COMS) were $-0.5^{\circ}K$ or over in haze with fine particulate. PM10 mass concentrations and NOAA 19 satellite BTD for haze cases were analyzed. Though PM10 mass concentrations were found to be lower than $200{\mu}g\;m^{-3}$, the mass concentration ratio of PM2.5/PM10 was measured as higher than 0.4 and BTD was found to be distributed in the range from -0.3 to $0.5^{\circ}K$. However, the BTD of dustfall cases exceeding $190{\mu}g\;m^{-3}$, were found to be less than 0.4 and BTD was found to be distributed in the range less than $-0.7^{\circ}K$. The result of applying BTD threshold values of the large-scale transport of haze proved to fall into line with the range over which aerosols of MODIS AOD and OMI AI were distributed.
Descriptions are provided of the automated aerosol-type classification and mass concentration calculation algorithm for real-time data processing and aerosol products in Korea Aerosol Lidar Observation Network (KALION, http://www.kalion.kr). The KALION algorithm provides aerosol-cloud classification and three aerosol types (clean continental, dust, and polluted continental/urban pollution aerosols). It also generates vertically resolved distributions of aerosol extinction coefficient and mass concentration. An extinction-to-backscatter ratio (lidar ratio) of 63.31 sr and aerosol mass extinction efficiency of $3.36m^2g^{-1}$ ($1.39m^2g^{-1}$ for dust), determined from co-located sky radiometer and $PM_{10}$ mass concentration measurements in Seoul from June 2006 to December 2015, are deployed in the algorithm. To assess the robustness of the algorithm, we investigate the pollution and dust events in Seoul on 28-30 March, 2015. The aerosol-type identification, especially for dust particles, is agreed with the official Asian dust report by Korean Meteorological Administration. The lidar-derived mass concentrations also well match with $PM_{10}$ mass concentrations. Mean bias difference between $PM_{10}$ and lidar-derived mass concentrations estimated from June 2006 to December 2015 in Seoul is about $3{\mu}g\;m^{-3}$. Lidar ratio and aerosol mass extinction efficiency for each aerosol types will be developed and implemented into the KALION algorithm. More products, such as ice and water-droplet cloud discrimination, cloud base height, and boundary layer height will be produced by the KALION algorithm.
Journal of Korean Society of Environmental Engineers
/
v.29
no.1
/
pp.113-125
/
2007
To know the differences in ionic compositions in rain and snow as well as snow influence on the chemical characteristics of winter precipitation, precipitation samples were collected by the wet-only automatic precipitation sample, in winter(November-February) in the Iksan located in the northwest of Chonbuk from 1995 to 2000. The samples were analyzed for concentrations of water-soluble ion species, in addition to pH and electrical conductivity. The mean pH of winter precipitation was 4.72. According to the type of winter precipitation, the mean pH of rain was 4.67 and lower than 5.05 in snow. The frequencies of pH below 5.0 in rain were about 73%, while those in snow were about 30%. Snow contained 3 times higher concentrations of sea salt ion components originated from seawater than did rain in winter, mainly $Cl^-,\;Na^+$, and $Mg^{2+}$. Neglecting sea salt ion components, $nss-SO_4^{2-}$ and $NO_3^-$ were important anions and $NH_4^+$ and $nss-Ca^{2+}$ were important cations in both of rain and snow. Concentrations of $nss-SO_4^{2-}$ was 1.3 times higher in rain than in snow, while those of $nss-Ca^{2+}$ and $NO_3^-$ were 1.5 and 1.3 times higher in snow, respectively. The mean equivalent concentration ratio of $nss-SO_4^{2-}/NO_3^-$ in winter precipitation were 2.4, which implied that the relative contribution of sulfuric and nitric acids to the precipitation acidity was 71% and 29%, respectively. The ratio in rain was 2.7 and higher than 1.5 in snow. These results suggest that the difference of $NO_3^-$ in rain and snow could be due to the more effective scavenging of $HNO_3$ vapor than particulate sulfate or nitrate by snow. The lower ratio in snow than rain is consistent with the measurement results of foreign other investigators and with scavenging theory of atmospheric aerosols. Although substantial $nss-SO_4^{2-}$ and $NO_3^-$ were observed in both of rain and snow, the corresponding presence of $NH_4^+,\;nss-Ca^{2+},\;nss-K^+$ suggested the significant neutralization of rain and snow. Differences in chemical composition of non-sea salt ions and neutralizing rapacity of $NH_4^+,\;nss-Ca^{2+}$, and $nss-K^+$ between rain and snow could explain the acidity difference of rain and snow. Snow affected that winter precipitation could be less acidic due to its higher neutralizing rapacity.
Kim, Hakyoung;Lee, Meehye;Kim, Saewung;Guenther, Alex.B.;Park, Jungmin;Cho, Gangnam;Kim, Hyun Seok
Korean Journal of Agricultural and Forest Meteorology
/
v.17
no.3
/
pp.217-226
/
2015
To investigate the distributions of BVOCs (Biogenic Volatile Organic Compounds) from mountain near mega city and their role in forest atmospheric, BVOCs and their oxidized species were measured at a 41 m tower in Mt. Taehwa during May, June and August 2013. A proton transfer reaction-mass spectrometer (PTR-MS) was used to quantify isoprene and monoterpenes. In conjunction with BVOCs, $O_3$, meteorological parameters, PAR (Photosynthetically Active Radiation) and LAI (Leaf Area Index) were measured. The average concentrations of isoprene and monoterpenes were 0.71 ppbv and 0.17 ppbv, respectively. BVOCs showed higher concentrations in the early summer (June) compared to the late summer (August). Isoprene started increasing at 2 PM and reached the maximum concentration around 5 PM. In contrast, monoterpenes concentrations began to increase 4 PM and stayed high at night. The $O_3$ maximum was generally found at 3 PM and remained high until 5 PM or later, which was concurrent with the enhancement of $O_3$. The concentrations of BVOCs were higher below canopy (18 m) than above canopy, which indicated these species were produced by trees. At night, monoterpenes concentrations were negatively correlated with these of $O_3$ below canopy. Using MEGAN (Model of Emissions of Gases and Aerosols from Nature), the emissions of isoprene and monoterpenes were estimated at 1.1 ton/year and 0.9 ton/year, respectively at Mt. Taehwa.
The spatial and temporal variations of aerosol optical depth (AOD) over Northeast Asia regions have special importance in the aerosol research for estimation of aerosol radiative forcing parameters and climate change. Aerosol optical and physical properties (AOD and ${\AA}$ngstrom parameter) have been investigated by using Moderate Resolution Imaging Spectroradiometer (MODIS) and Total Ozone Mapping Spectrometer (TOMS) Aerosol Index (AI) to estimate aerosol characteristics over the study region during 2001. Additionally, aerosol characteristics over the Korean peninsular during Aerosol Characteristic Experiment in Asia (ACE-Asia) Intensive Observation Period (IOP) have been investigated by using satellite observations. The results showed that the daily-observed aerosol data indicate seasonal variations with relatively higher aerosol loading in the spring and very low during the winter. The typical Asian dust case showed higher AOD (>0.7) with lower Angstrom exponent (<0.5) and higher AI (>0.5) that is mainly due to the composition of coarse particles in the springtime. Mean AOD for 2001 at 4 different places showed 0.65$\pm$0.37 at Beijing, 0.31$\pm$0.19 at Gosan, 0.54$\pm$0.26 at Seoul, and 0.38$\pm$0.19 at Kwangju, respectively. An interesting result was found in the present study that polluted aerosol events with small size dominated-aerosol loading around the Korean peninsular are sometimes observed. The origin of these polluted aerosols was thought to East China. Aerosol distribution from satellite images and trajectory results shows the proof of aerosol transport. Therefore, aerosol monitoring using satellite data is very useful.
With the development of sensor and satellite technology, numerous high-resolution and multi-spectral satellite images have been available. Due to their wavelength-dependent reflection, transmission, and scattering characteristics, multi-spectral satellite images can provide complementary information for earth observation. In particular, the short-wave infrared (SWIR) band can penetrate certain types of atmospheric aerosols from the benefit of the reduced Rayleigh scattering effect, which allows for a clearer view and more detailed information to be captured from hazed surfaces compared to the visible band. In this study, we proposed a multi-resolution transform-based image fusion method to combine visible and SWIR satellite images. The purpose of the fusion method is to generate a single integrated image that incorporates complementary information such as detailed background information from the visible band and land cover information in the haze region from the SWIR band. For this purpose, this study applied the Laplacian pyramid-based multi-resolution transform method, which is a representative image decomposition approach for image fusion. Additionally, we modified the multiresolution fusion method by combining a haze-guided weight map based on the prior knowledge that SWIR bands contain more information in pixels from the haze region. The proposed method was validated using very high-resolution satellite images from Worldview-3, containing multi-spectral visible and SWIR bands. The experimental data including hazed areas with limited visibility caused by smoke from wildfires was utilized to validate the penetration properties of the proposed fusion method. Both quantitative and visual evaluations were conducted using image quality assessment indices. The results showed that the bright features from the SWIR bands in the hazed areas were successfully fused into the integrated feature maps without any loss of detailed information from the visible bands.
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