2020, Vol.29, No.4

Journal of Environmental Impact Assessment 2023 KCI Impact Factor : 0.51

pISSN : 1225-7184
https://journal.kci.go.kr/kseia

The Off-site Risk Assessment (ORA) for preventing chemical accidents estimates the chemical accident risk at chemical plants. The method of estimating the risk is made by multiplying the number of residents within the effect area of the chemical accident and the frequency of accidents at a chemical plant. At present, the ORA does not quantitatively consider environmental receptors when the damage types within the scope of the accident are environmental receptors. In order to solve this problem, this study proposes a method of estimating the risk considering resident and environmental receptors. Through these studies, it was confirmed that the ORA impact for the prevention of chemical accidents requires risk analysis considering environmental receptors in the medium and long term.

In this study, we investigated physical and chemical properties such as grain size, heavy metal pollution, magnetic properties, and their environmental impacts of road dusts (RD) collected from 14 sampling points in Daebul industrial Complex. Heavy metal concentrations in RD were in the order of Fe>Zn>Cu>Pb>Cr>Ni>As>Cd>Hg, and this pollution pattern was related to major industries and traffic activities in this area. The results of the correlation analysis between heavy metal elements and particle size in RD showed that Fe and all of analyzed heavy metals had a significant correlation with each other and metal concentrations had a significantly negative correlation (p<0.05). However, due to the input of large metal particles some heavy metal concentrations in the particle fraction of >1000 μm were highest. Pollution load per unit area of this fraction was the highest among the grain size fractions. Cr, Ni, Cu, Zn, Cd, Pb levels in RD decreased and the levels of Cr, Ni, Cu, Zn, Cd, and Pb were reduced to 85 (As) -22 (Ni)% of the whole after removal of MFs fraction from RD. The mean heavy metal levels in the study area did not exceed the soil contamination guide value of Korea, indicating that heavy metal levels in RD were not a concern. However, at some sampling points, Zn concentrations were exceeded the soil contamination guide value for the 3rd areas of Korea and this result indicated that further studies of the impact of RD on the surrounding environment through re-suspension or non-point pollution, and of effective management methods are required.

We investigated statistical evaluation parameters for 3D meteorological and air quality models and selected several quantitative indicator references, and summarized the reference values of the statistical parameters for domestic air quality modeling researcher. The finally selected 9 statistical parameters are MB (Mean Bias), ME (Mean Error), MNB (Mean Normalized Bias Error), MNE (Mean Absolute Gross Error), RMSE (Root Mean Square Error), IOA (Index of Agreement), R (Correlation Coefficient), FE (Fractional Error), FB (Fractional Bias), and the associated reference values are summarized. The results showed that MB and ME have been widely used in evaluating the meteorological model output, and NMB and NME are most frequently used for air quality model results. In addition, discussed are the presentation diagrams such as Soccer Plot, Taylor diagram, and Q-Q (Quantile-Quantile) diagram. The current results from our study is expected to be effectively used as the statistical evaluation parameters suitable for situation in Korea considering various characteristics such as including the mountainous surface areas.