An overview of mesoscale aerosol processes, comparisons, and validation studies from DRAGON networks

Holben, Brent N.,Kim, Jhoon,Sano, Itaru,Mukai, Sonoyo,Eck, Thomas F.,Giles, David M.,Schafer, Joel S.,Sinyuk, Aliaksandr,Slutsker, Ilya,Smirnov, Alexander,Sorokin, Mikhail,Anderson, Bruce E.,Che, Huiz Copernicus GmbH 2018 Atmospheric Chemistry and Physics Vol.18 No.2

<P>Abstract. Over the past 24 years, the AErosol RObotic NETwork (AERONET) program has provided highly accurate remote-sensing characterization of aerosol optical and physical properties for an increasingly extensive geographic distribution including all continents and many oceanic island and coastal sites. The measurements and retrievals from the AERONET global network have addressed satellite and model validation needs very well, but there have been challenges in making comparisons to similar parameters from in situ surface and airborne measurements. Additionally, with improved spatial and temporal satellite remote sensing of aerosols, there is a need for higher spatial-resolution ground-based remote-sensing networks. An effort to address these needs resulted in a number of field campaign networks called Distributed Regional Aerosol Gridded Observation Networks (DRAGONs) that were designed to provide a database for in situ and remote-sensing comparison and analysis of local to mesoscale variability in aerosol properties. This paper describes the DRAGON deployments that will continue to contribute to the growing body of research related to meso- and microscale aerosol features and processes. The research presented in this special issue illustrates the diversity of topics that has resulted from the application of data from these networks. </P>

Observations of the Interaction and Transport of Fine Mode Aerosols With Cloud and/or Fog in Northeast Asia From Aerosol Robotic Network and Satellite Remote Sensing

Eck, T. F.,Holben, B. N.,Reid, J. S.,Xian, P.,Giles, D. M.,Sinyuk, A.,Smirnov, A.,Schafer, J. S.,Slutsker, I.,Kim, J.,Koo, J.-H.,Choi, M.,Kim, K. C.,Sano, I.,Arola, A.,Sayer, A. M.,Levy, R. C.,Munchak American Geophysical Union 2018 Journal of Geophysical Research: Atmospheres Vol.123 No.10

<P>Analysis of Sun photometer measured and satellite retrieved aerosol optical depth (AOD) data has shown that major aerosol pollution events with very high fine mode AOD (>1.0 in midvisible) in the China/Korea/Japan region are often observed to be associated with significant cloud cover. This makes remote sensing of these events difficult even for high temporal resolution Sun photometer measurements. Possible physical mechanisms for these events that have high AOD include a combination of aerosol humidification, cloud processing, and meteorological covariation with atmospheric stability and convergence. The new development of Aerosol Robotic Network Version 3 Level 2 AOD with improved cloud screening algorithms now allow for unprecedented ability to monitor these extreme fine mode pollution events. Further, the spectral deconvolution algorithm (SDA) applied to Level 1 data (L1; no cloud screening) provides an even more comprehensive assessment of fine mode AOD than L2 in current and previous data versions. Studying the 2012 winter-summer period, comparisons of Aerosol Robotic Network L1 SDA daily average fine mode AOD data showed that Moderate Resolution Imaging Spectroradiometer satellite remote sensing of AOD often did not retrieve and/or identify some of the highest fine mode AOD events in this region. Also, compared to models that include data assimilation of satellite retrieved AOD, the L1 SDA fine mode AOD was significantly higher in magnitude, particularly for the highest AOD events that were often associated with significant cloudiness.</P>

Identification of column-integrated dominant aerosols using the archive of AERONET data set

Choi, Y.,Ghim, Y. S.,Holben, B. N. Copernicus GmbH 2013 Atmospheric chemistry and physics discussions Vol.13 No.10

<P>@@<@@p@@>@@@@<@@strong@@>@@Abstract.@@<@@/strong@@>@@ Dominant aerosols were distinguished from level 2 inversion products for the Anmyon Aerosol Robotic Network (AERONET) site between 1999 and 2007. Secondary inorganic ions, black carbon (BC) and organic carbon (OC) were separated from fine mode aerosols, and mineral dust (MD), MD mixed with carbon, mixed coarse particles were separated from coarse mode aerosols. Four parameters (aerosol optical depth, single scattering albedo, absorption Angstrom exponent, and fine mode fraction) were used for this classification. Monthly variation of the occurrence rate of each aerosol type reveals that MD and MD mixed with carbon are frequent in spring. Although the fraction among dominant aerosols and occurrence rates of BC and OC tend to be high in cold season for heating, their contributions are variable but consistent due to various combustion sources. Secondary inorganic ions are most prevalent from June to August; the effective radius of these fine mode aerosols increases with water vapor content because of hygroscopic growth. To evaluate the validity of aerosol types identified, dominant aerosols at worldwide AERONET sites (Beijing, Mexico City, Goddard Space Flight Center, Mongu, Alta Floresta, Cape Verde), which have distinct source characteristics, were classified into the same aerosol types. The occurrence rate and fraction of the aerosol types at the selected sites confirm that the classification in this study is reasonable. However, mean optical properties of the aerosol types are generally influenced by the aerosol types with large fractions. The present work shows that the identification of dominant aerosols is effective even at a single site, provided that the archive of the data set is properly available.@@<@@/p@@>@@ </P>

PF8)한반도 배경지역 에어러솔 광학 깊이의 계절변화

김지영,조경숙,최병철,최재천,차주완,Brent N. Holben,Chuck McClain 한국대기환경학회 2003 한국대기환경학회 학술대회논문집 Vol.- No.-

Microbial Ecology : Use of Gene Probes for Tracking 2,4 - Dichlorophenoxyacetic Acid - Degrading Microbial Populations in Soil

Jong Ok Ka,W . E . Holben,J . M . Tiedje 한국미생물생명공학회(구 한국산업미생물학회) 1995 FUNCTIONAL BIOMATERIALS Vol.- No.-

AERONET과 GOCI 원격 관측을 활용한 2015 MAPS-Seoul 캠페인 기간 에어로졸 광학 특성 분석

최명제,김준,이재화,이서영,Brent Holben,Thomas F. Eck 한국대기환경학회 2015 한국대기환경학회 학술대회논문집 Vol.2015 No.11

KORUS-AQ 기간 중 국내외 배출원이 국내 대기오염에 미치는 영향 분석

이서영,구자호,홍재민,최명제,김준,임현광,Brent Holben,Thomas F. Eck,안준영,박정후,김상균 한국대기환경학회 2017 한국대기환경학회 학술대회논문집 Vol.2017 No.11

Estimation of PM10 concentrations over Seoul using multiple empirical models with AERONET and MODIS data collected during the DRAGON-Asia campaign

Seo, S.,Kim, J.,Lee, H.,Jeong, U.,Kim, W.,Holben, B. N.,Kim, S.-W.,Song, C. H.,Lim, J. H. Copernicus GmbH 2015 Atmospheric Chemistry and Physics Vol.15 No.1

<P>Abstract. 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. </P>

GOCI Yonsei aerosol retrieval version 2 products: an improved algorithm and error analysis with uncertainty estimation from 5-year validation over East Asia

Choi, Myungje,Kim, Jhoon,Lee, Jaehwa,Kim, Mijin,Park, Young-Je,Holben, Brent,Eck, Thomas F.,Li, Zhengqiang,Song, Chul H. Copernicus GmbH 2018 Atmospheric measurement techniques Vol.11 No.1

<P><p><strong>Abstract.</strong> The Geostationary Ocean Color Imager (GOCI) Yonsei aerosol retrieval (YAER) version 1 algorithm was developed to retrieve hourly aerosol optical depth at 550&amp;thinsp;nm (AOD) and other subsidiary aerosol optical properties over East Asia. The GOCI YAER AOD had accuracy comparable to ground-based and other satellite-based observations but still had errors because of uncertainties in surface reflectance and simple cloud masking. In addition, near-real-time (NRT) processing was not possible because a monthly database for each year encompassing the day of retrieval was required for the determination of surface reflectance. This study describes the improved GOCI YAER algorithm version 2 (V2) for NRT processing with improved accuracy based on updates to the cloud-masking and surface-reflectance calculations using a multi-year Rayleigh-corrected reflectance and wind speed database, and inversion channels for surface conditions. The improved GOCI AOD <span class='inline-formula'><i>τ</i>_G</span> is closer to that of the Moderate Resolution Imaging Spectroradiometer (MODIS) and Visible Infrared Imaging Radiometer Suite (VIIRS) AOD than was the case for AOD from the YAER V1 algorithm. The V2 <span class='inline-formula'><i>τ</i>_G</span> has a lower median bias and higher ratio within the MODIS expected error range (0.60 for land and 0.71 for ocean) compared with V1 (0.49 for land and 0.62 for ocean) in a validation test against Aerosol Robotic Network (AERONET) AOD <span class='inline-formula'><i>τ</i>_A</span> from 2011 to 2016. A validation using the Sun-Sky Radiometer Observation Network (SONET) over China shows similar results. The bias of error (<span class='inline-formula'><i>τ</i>_G−<i>τ</i>_A)</span> is within <span class='inline-formula'>−</span>0.1 and 0.1, and it is a function of AERONET AOD and Ångström exponent (AE), scattering angle, normalized difference vegetation index (NDVI), cloud fraction and homogeneity of retrieved AOD, and observation time, month, and year. In addition, the diagnostic and prognostic expected error (PEE) of <span class='inline-formula'><i>τ</i>_G</span> are estimated. The estimated PEE of GOCI V2 AOD is well correlated with the actual error over East Asia, and the GOCI V2 AOD over South Korea has a higher ratio within PEE than that over China and Japan.</p> </P>

Aerosol optical properties derived from the DRAGON-NE Asia campaign, and implications for a single-channel algorithm to retrieve aerosol optical depth in spring from Meteorological Imager (MI) on-board the Communication, Ocean, and Meteorological Satelli

Kim, M.,Kim, J.,Jeong, U.,Kim, W.,Hong, H.,Holben, B.,Eck, T. F.,Lim, J. H.,Song, C. K.,Lee, S.,Chung, C.-Y. Copernicus GmbH 2016 Atmospheric Chemistry and Physics Vol.16 No.3

<P>Abstract. 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. </P>