• Analytical Science and Technology
• /
• v.29 no.5
• /
• pp.209-218
• /
• 2016

PM₁₀ and PM_2.5 samples were collected at the 1100 site of Mt. Halla in Jeju Island during 2011~2012, and their ionic and elemental species were analyzed, in order to investigate the characteristics of emission sources as well as aerosol compositions. The mass concentrations of PM₁₀ and PM_2.5 were 22.0±13.1 µg/m³ and 11.3±6.1 µg/m³, respectively, showing 2.4~2.6 times lower than those of the capital city area of Korea. The composition ratios of major secondary pollutants (nss-SO₄²⁻, NH₄⁺, and NO₃⁻) were the highest as 85.5 % for PM₁₀ and 91.3 % for PM_2.5, and followed by the order of marine (Na⁺, Cl⁻, and Mg²⁺), organic acid (HCOO⁻ and CH₃COO⁻), and soil (nss-Ca²⁺) sources. Among the elemental species in PM₁₀, soil-originated components (Al, Fe, and Ca) were consisted of 50.9 %, which was higher proportion than marine and anthropogenic elements. The acidification of the fine particulate matters was found to be influenced mostly by sulfuric and nitric acids, and these acids were mainly neutralized by calcium carbonate in PM₁₀ and by ammonia in PM_2.5. The clustered back trajectories showed that 47 % of total air mass inflows was from the China, and the concentrations of NO₃⁻ and nss-Ca²⁺ were especially high corresponding to the inflows.

• Korean Journal of Remote Sensing
• /
• v.39 no.6_2
• /
• pp.1591-1604
• /
• 2023

In ocean color remote sensing, atmospheric correction is a vital process for ensuring the accuracy and reliability of ocean color products. Furthermore, in recent years, the remote sensing community has intensified its requirements for understanding errors in satellite data. Accordingly, research is currently addressing errors in remote sensing reflectance (R_rs) resulting from inaccuracies in meteorological variables (total ozone, pressure, wind field, and total precipitable water) used as auxiliary data for atmospheric correction. However, there has been no investigation into the error in R_rs caused by the variability of the water vapor profile, despite it being a recognized error source. In this study, we used the Second Simulation of a Satellite Signal Vector version 2.1 simulation to compute errors in water vapor transmittance arising from variations in the water vapor profile within the GOCI-II observation area. Subsequently, we conducted an analysis of the associated errors in ocean color products. The observed water vapor profile not only exhibited a complex shape but also showed significant variations near the surface, leading to differences of up to 0.007 compared to the US standard 62 water vapor profile used in the GOCI-II atmospheric correction. The resulting variation in water vapor transmittance led to a difference in aerosol reflectance estimation, consequently introducing errors in R_rs across all GOCI-II bands. However, the error of R_rs in the 412-555 nm due to the difference in the water vapor profile band was found to be below 2%, which is lower than the required accuracy. Also, similar errors were shown in other ocean color products such as chlorophyll-a concentration, colored dissolved organic matter, and total suspended matter concentration. The results of this study indicate that the variability in water vapor profiles has minimal impact on the accuracy of atmospheric correction and ocean color products. Therefore, improving the accuracy of the input data related to the water vapor column concentration is even more critical for enhancing the accuracy of ocean color products in terms of water vapor absorption correction.