ALBERT

Description: Total number concentrations of particles having a diameter larger than 10 nm (NCN), cloud condensation nuclei at several supersaturation (S) values (NCCN) and number size distributions of particles with 10–414 nm diameter were measured in Seoul between 2004 and 2010. Overall average values of NCN and geometric mean diameter were 17 811 ± 5581 cm−3 and 48 ± 6 nm. Average NCCN at 0.4, 0.6 and 0.8% S were 4145 ± 2016, 5323 ± 2453 and 6067 ± 2780 cm−3 and corresponding NCCN / NCN were 0.26 ± 0.11, 0.33 ± 0.11 and 0.37 ± 0.12. There is a clear seasonal variation in aerosol concentration, which seems to be due to the monsoon. NCN and NCCN are also found to depend on the volume of traffic and the height of the planetary boundary layer, respectively. During aircraft campaigns in 2009 and 2011, NCN and NCCN at 0.6% S (N0.6%) were measured in and around the Korean Peninsula. During the 2011 campaign, the aerosol scattering coefficient was also measured. NCN and N0.6% in the lower altitudes were generally higher than at higher altitudes, except for cases when particle formation and growth events were thought to occur at higher altitudes. NCN and N0.6% generally show a positive correlation with aerosol scattering coefficients but this correspondence tends to vary with altitude. Occasional instances of low (〈 0.3) N0.6% / NCN in the boundary layer are demonstrated to be associated with particle formation and growth events. With the support of ground measurements, it is confirmed that a particle formation and growth event did indeed occur over the Yellow Sea on a flight day, and the areal extent of this event is estimated to be greater than 100 km × 450 km. With the combination of the current and several relevant previous studies, a composite map of NCN and NCCN in and around the Korean Peninsula is produced. Overall, the exhibited concentrations are typical of values measured over polluted regions elsewhere on the globe. Moreover, there is a generally decreasing trend from west to east over the region, implying that the region is constantly under the dominant influence of continental outflow.

Description: Rapid and accurate assessment of the state of buildings in the aftermath of a disaster event is critical for an effective and timely response. For rapid damage assessment of buildings, the utility of remote sensing (RS) technology has been widely researched, with focus on a range of platforms and sensors. However, RS-based approach still have limitations to assess structural integrity and the specific damage status of individual buildings. Consequently, ground-based assessment conducted by structural engineers and first responders is still required. This paper demonstrates the concept of mobile Augmented Reality (mAR) to improve performance of building damage and safety assessment in situ. Mobile AR provides a means to superimpose various types of reference or pre-disaster information (virtual data) on actual post-disaster building data (real building). To adopt mobile AR, this study defines a conceptual framework based on Level of Complexity (LOC). The framework consists of four LOCs, and for each of these the data types, required processing steps, AR implementation, and use for damage assessment, are described. Based on this conceptualization we demonstrate prototypes of mAR for both indoor and outdoor purposes. Finally, we conduct a user evaluation of the prototypes to validate the mAR approach for building damage and safety assessment.

Description: Rapid and accurate assessment of the state of buildings in the aftermath of a disaster event is critical for an effective and timely response. For rapid damage assessment of buildings, the utility of remote sensing (RS) technology has been widely researched, with focus on a range of platforms and sensors. However, RS-based approaches still have limitations to assess structural integrity and the specific damage status of individual buildings. Structural integrity refers to the ability of a building to hold the entire structure. Consequently, ground-based assessment conducted by structural engineers and first responders is still required. This paper demonstrates the concept of mobile augmented reality (mAR) to improve performance of building damage and safety assessment in situ. Mobile AR provides a means to superimpose various types of reference or pre-disaster information (virtual data) on actual post-disaster building data (real buildings). To adopt mobile AR, this study defines a conceptual framework based on the level of complexity (LOC). The framework consists of four LOCs, and for each of these, the data types, required processing steps, AR implementation and use for damage assessment are described. Based on this conceptualization we demonstrate prototypes of mAR for both indoor and outdoor purposes. Finally, we conduct a user evaluation of the prototypes to validate the mAR approach for building damage and safety assessment.

Description: The performance of various empirical linear models to estimate the concentrations of surface-level particulate matter with a~diameter less than 10 μm (PM10) was evaluated using Aerosol Robotic Network (AERONET) sunphotometer and Moderate Resolution Imaging Spectroradiometer (MODIS) data collected in Seoul during the Distributed Regional Aerosol Gridded Observation Network (DRAGON)-Asia campaign from March to May 2012. An observed relationship between the PM10 concentration and the aerosol optical depth (AOD) was accounted for by several parameters in the empirical models, including boundary layer height (BLH), relative humidity (RH), and effective radius of the aerosol size distribution (Reff), which was used here for the first time in empirical modeling. Results show the strong influence of BLH and (Reff on the PM10 estimates, while the role of RH was negligible during the campaign period when, in general, RH was lower than in other seasons. A large spatial dependency of the empirical model performance was found by categorizing the locations of the collected data into three different site types, which varied in terms of the distances between instruments and source locations. When both AERONET and MODIS datasets were used in the PM10 estimation, the highest correlations between measured and estimated values ((R = 0.76 and 0.76 using AERONET and MODIS data, respectively) were found for the residential area (RA) site type, while the poorest correlations ((R = 0.61 and 0.68 using AERONET and MODIS data, respectively) were found for the near source (NS) site type. Significant seasonal variations of empirical model performances for PM10 estimation were found using the data collected at Yonsei University (one of the DRAGON campaign sites) over a~period of 17 months including the DRAGON campaign period. The best correlation between measured and estimated PM10 concentrations ((R = 0.81) was found in winter, due to the presence of a stagnant air mass and low ext{BLH} conditions, which may have resulted in relatively homogeneous aerosol properties within the BLH. On the other hand, the poorest correlation between measured and estimated PM10 concentrations ((R = 0.54) was found in spring, due to the influence of the long-range transport of dust to both within and above the BLH.

Description: Total number concentrations of particles having diameter larger than 10 nm (NCN), cloud condensation nuclei at several supersaturation (S) values (NCCN), and the number size distribution of particles for 10–414 nm particle diameter range were measured in Seoul between 2004 and 2010. Overall average values of NCN and geometric mean diameter are 17 811 ± 5581 cm−3 and 48 ± 6 nm, respectively. Average NCCN at 0.4, 0.6, and 0.8% S are 4145 ± 2016, 5323 ± 2453 and 6067 ± 2780 cm−3, respectively and corresponding NCCN / NCN are 0.26 ± 0.11, 0.33 ± 0.11 and 0.37 ± 0.12. There is a clear seasonal variation of aerosol concentration, which seems to be due to the monsoon. NCN and NCCN are also found to be dependent on the volume of traffic and the height of planetary boundary layer, respectively. During the two aircraft campaigns in 2009 and 2011, NCN and NCCN at 0.6% S were measured in and around the Korean Peninsula. During the 2011 campaign, aerosol scattering coefficient was also measured. NCN and NCCN 0.6 in the lower altitudes were generally higher than at higher altitudes, except for the cases when particle formation and growth events are thought to occur at higher altitudes. NCN and NCCN 0.6 show generally a positive correlation with aerosol scattering coefficients but its correspondence tends to vary with altitude. Occasional instances of low (〈 0.3) NCCN 0.6 / NCN in the boundary layer are demonstrated to be associated with particle formation and growth events. With the support of ground measurements, it is confirmed that a particle formation and growth event indeed occurred on a flight day over the Yellow Sea and the areal extent of the event is estimated to be greater than 100 km × 450 km. With the combination of the current and several relevant previous studies, a composite map of NCN and NCCN in and around the Korean Peninsula is produced. Overall, the exhibited concentrations are typical of the values measured over the polluted regions elsewhere in the globe. Moreover, there is a generally decreasing trend from west to east over the region, implying that the region is constantly under the dominant influence of continental outflow.

Description: An aerosol model optimized for East Asia is improved by applying inversion data from both long-term monitoring of the Aerosol Robotic Network (AERONET) sun photometer and the Distributed Regional Aerosol Gridded Observation Networks (DRAGON)-Asia campaign from 2012. This model plays an important role in retrieving accurate aerosol optical depth (AOD) from satellite-based measurements. In particular, the performance of a single visible channel algorithm, limited to a specific aerosol type, from real-time measurements is strongly affected by the assumed aerosol optical properties (AOPs) for the measured scene. In sensitivity tests, a 4% difference in single scattering albedo (SSA) between modeled and measured values can cause a retrieval error in AOD of over 20%, and the overestimation of SSA leads to an underestimation of AOD. Based on the AERONET inversion datasets obtained over East Asia before 2011, seasonally analyzed AOPs can be summarized by SSAs (measured at 675 nm) of 0.92, 0.94, 0.92, and 0.91 for spring (March, April, and May), summer (June, July, and August), autumn (September, October, and November), and winter (December, January, and February), respectively. After DRAGON-Asia 2012, the SSA during spring shows a slight increase to 0.93. The large volume of data and spatially concentrated measurements from this campaign can be used to improve the representative aerosol model for East Asia. Accordingly, the AOD datasets retrieved from a single channel algorithm, which uses a pre-calculated look-up table (LUT) with the new aerosol model, show an improved correlation with the measured AOD during the DRAGON-Asia campaign (March to May 2012). Compared with the correlation of the AOD retrieved using the original aerosol model, the regression slope between the new AOD and the AERONET values is reduced from 1.08 to 1.00, while the change of the y-offset of −0.08 is significant. The correlation coefficients for the comparisons are 0.87 and 0.85, respectively. The tendency of the original aerosol model to overestimate the retrieved AOD is significantly improved by using the SSA values obtained using the new model.

Description: The Geostationary Ocean Color Imager (GOCI) onboard the Communication, Ocean, and Meteorology Satellites (COMS) is the first multi-channel ocean color imager in geostationary orbit. Hourly GOCI top-of-atmosphere radiance has been available for the retrieval of aerosol optical properties over East Asia since March 2011. This study presents improvements to the GOCI Yonsei Aerosol Retrieval (YAER) algorithm over ocean and land together with validation results during the DRAGON-NE Asia 2012 campaign. Optical properties of aerosol are retrieved from the GOCI YAER algorithm including aerosol optical depth (AOD) at 550 nm, fine-mode fraction (FMF) at 550 nm, single scattering albedo (SSA) at 440 nm, Angstrom exponent (AE) between 440 and 860 nm, and aerosol type from selected aerosol models in calculating AOD. Assumed aerosol models are compiled from global Aerosol Robotic Networks (AERONET) inversion data, and categorized according to AOD, FMF, and SSA. Nonsphericity is considered, and unified aerosol models are used over land and ocean. Different assumptions for surface reflectance are applied over ocean and land. Surface reflectance over the ocean varies with geometry and wind speed, while surface reflectance over land is obtained from the 1–3 % darkest pixels in a 6 km × 6 km area during 30 days. In the East China Sea and Yellow Sea, significant area is covered persistently by turbid waters, for which the land algorithm is used for aerosol retrieval. To detect turbid water pixels, TOA reflectance difference at 660 nm is used. GOCI YAER products are validated using other aerosol products from AERONET and the MODIS Collection 6 aerosol data from "Dark Target (DT)" and "Deep Blue (DB)" algorithms during the DRAGON-NE Asia 2012 campaign from March to May 2012. Comparison of AOD from GOCI and AERONET gives a Pearson correlation coefficient of 0.885 and a linear regression equation with GOCI AOD =1.086 × AERONET AOD – 0.041. GOCI and MODIS AODs are more highly correlated over ocean than land. Over land, especially, GOCI AOD shows better agreement with MODIS DB than MODIS DT because of the choice of surface reflectance assumptions. Other GOCI YAER products show lower correlation with AERONET than AOD, but are still qualitatively useful.

Description: The formation of a longitudinally periodic plasma density structure in the low-latitude F region by the effect of vertical E×B drift was investigated by analyzing the ROCSAT-1 satellite data and conducting SAMI2 model simulations. The daytime equatorial ionosphere observed during the equinox in 1999–2002 from ROCSAT-1 showed the formation of wave number-4 structures in the plasma density and vertical plasma drift. The coincidence of the longitudes of the peak density with the longitudes of the peak upward drift velocity during the daytime supported the association of the longitudinal density structure with the vertical E×B drift. The reproduction capability of the observed wave-4 structure by the effect of vertical E×B drift was tested by conducting SAMI2 model simulations during the equinox under solar maximum condition. When the ROCSAT-1 vertical drift data were used, the SAMI2 model could reproduce the observed wave-4 density structure in the low-latitude F region. On the other hand, the SAMI2 model could not reproduce the observed wave-4 structure using the Scherliess and Fejer vertical E×B drift model. The observation and model simulation results demonstrated that the formation of the longitudinally periodic plasma density structure can be explained by the longitudinal variation of the daytime vertical E×B drift.

Description: The performance of various empirical linear models to estimate the concentrations of surface-level particulate matter with a diameter less than 10 μm (PM10) was evaluated using Aerosol Robotic Network (AERONET) sun photometer and Moderate-Resolution Imaging Spectroradiometer (MODIS) data collected in Seoul during the Distributed Regional Aerosol Gridded Observation Network (DRAGON)-Asia campaign from March to May 2012. An observed relationship between the PM10 concentration and the aerosol optical depth (AOD) was accounted for by several parameters in the empirical models, including boundary layer height (BLH), relative humidity (RH), and effective radius of the aerosol size distribution (Reff), which was used here for the first time in empirical modeling. Among various empirical models, the model which incorporates both BLH and Reff showed the highest correlation, which indicates the strong influence of BLH and Reff on the PM10 estimations. Meanwhile, the effect of RH on the relationship between AOD and PM10 appeared to be negligible during the campaign period (spring), when RH is generally low in northeast Asia. A large spatial dependency of the empirical model performance was found by categorizing the locations of the collected data into three different site types, which varied in terms of the distances between instruments and source locations. When both AERONET and MODIS data sets were used in the PM10 estimation, the highest correlations between measured and estimated values (R = 0.76 and 0.76 using AERONET and MODIS data, respectively) were found for the residential area (RA) site type, while the poorest correlations (R = 0.61 and 0.68 using AERONET and MODIS data, respectively) were found for the near-source (NS) site type. Significant seasonal variations of empirical model performances for PM10 estimation were found using the data collected at Yonsei University (one of the DRAGON campaign sites) over a period of 17 months including the DRAGON campaign period. The best correlation between measured and estimated PM10 concentrations (R = 0.81) was found in winter, due to the presence of a stagnant air mass and low BLH conditions, which may have resulted in relatively homogeneous aerosol properties within the BLH. On the other hand, the poorest correlation between measured and estimated PM10 concentrations (R = 0.54) was found in spring, due to the influence of the long-range transport of dust to both within and above the BLH.

Description: An aerosol model optimized for northeast Asia is updated with the inversion data from the Distributed Regional Aerosol Gridded Observation Networks (DRAGON)-northeast (NE) Asia campaign which was conducted during spring from March to May 2012. This updated aerosol model was then applied to a single visible channel algorithm to retrieve aerosol optical depth (AOD) from a Meteorological Imager (MI) on-board the geostationary meteorological satellite, Communication, Ocean, and Meteorological Satellite (COMS). This model plays an important role in retrieving accurate AOD from a single visible channel measurement. For the single-channel retrieval, sensitivity tests showed that perturbations by 4 % (0.926 ± 0.04) in the assumed single scattering albedo (SSA) can result in the retrieval error in AOD by over 20 %. Since the measured reflectance at the top of the atmosphere depends on both AOD and SSA, the overestimation of assumed SSA in the aerosol model leads to an underestimation of AOD. Based on the AErosol RObotic NETwork (AERONET) inversion data sets obtained over East Asia before 2011, seasonally analyzed aerosol optical properties (AOPs) were categorized by SSAs at 675 nm of 0.92 ± 0.035 for spring (March, April, and May). After the DRAGON-NE Asia campaign in 2012, the SSA during spring showed a slight increase to 0.93 ± 0.035. In terms of the volume size distribution, the mode radius of coarse particles was increased from 2.08 ± 0.40 to 2.14 ± 0.40. While the original aerosol model consists of volume size distribution and refractive indices obtained before 2011, the new model is constructed by using a total data set after the DRAGON-NE Asia campaign. The large volume of data in high spatial resolution from this intensive campaign can be used to improve the representative aerosol model for East Asia. Accordingly, the new AOD data sets retrieved from a single-channel algorithm, which uses a precalculated look-up table (LUT) with the new aerosol model, show an improved correlation with the measured AOD during the DRAGON-NE Asia campaign. The correlation between the new AOD and AERONET value shows a regression slope of 1.00, while the comparison of the original AOD data retrieved using the original aerosol model shows a slope of 1.08. The change of y-offset is not significant, and the correlation coefficients for the comparisons of the original and new AOD are 0.87 and 0.85, respectively. The tendency of the original aerosol model to overestimate the retrieved AOD is significantly improved by using the SSA values in addition to size distribution and refractive index obtained using the new model.