22 research outputs found
(A) study on receptor concentration distribution by applying for grid size to ISCST3 air dispersion model.
ํ๊ฒฝ๊ด๋ฆฌํ๊ณผ/์์ฌ[ํ๊ธ]
์ฐ์
ํ์ ๋๋ถ์ด ๋๊ธฐ์ค์ผ์ ๋ณตํฉํ, ์ง์ ํ ์์์ ๋ ๊ณ ์์ผ๋ฉฐ, ์ธ๊ตฌ์ ๋์์ง์คํ์ ํจ๊ป ๋๊ท๋ชจ ์ฐ์
๋จ์ง ์กฐ์ฑ ๋ฑ์ผ๋ก ์ธํด ๋๊ธฐ์ค์ผ์ด ๋์ฑ ๊ฐ์ํ๋๊ณ ์๋ ์ค์ ์ด๋ค. ์ด๋ฌํ ๋๊ธฐ์ค์ผ์ ํจ๊ณผ์ ์ธ ๊ด๋ฆฌ๋ฅผ ์ํด์๋ ๋๊ธฐ์ค์ผํ์ฐ๋ชจ๋ธ์ ์ด์ฉํ ๋๊ธฐ์ค์ผ๋ฌผ์ง ํ์ฐ์์ธก์ ์ค์์ฑ์ด ๋ถ๊ฐ๋๊ณ ์๋ค.
๋๊ธฐ์ค์ผํ์ฐ๋ชจ๋ธ์ ์ ์ ์ ์์ธก์กฐ๊ฑด๊ณผ ๋์์ค์ผ๋ฌผ์ง, ์ค์ผ์์ ์ข
๋ฅ, ๊ธฐ์์๋ฃ, ์งํ์๋ฃ ๋ฑ์ ์ข
ํฉ์ ์ผ๋ก ๊ณ ๋ คํ์ฌ ํน์ฑ์ ๋ง๊ฒ ์ ์ ๋์ด์ผ ํ๋, ๋๊ธฐ์ค์ผํ์ฐ๋ชจ๋ธ์ ํ๊ณ์ ,์ ํ์ ์ ๋ํ ๊ณ ๋ ค์์ด ๋๊ธฐ์ค์ผํ์ฐ๋ชจ๋ธ์ ์ ์ฉํ์ฌ ๋๊ธฐ์ค์ผ์์ธก์ ์ค์ํจ์ผ๋ก์จ ๋ค์ํ ๋๊ธฐ์ค์ผ์ ํน์ฑ์ ์ถฉ๋ถํ ๊ณ ๋ คํ์ง ๋ชปํ๊ณ ์๋ ์ค์ ์ด๋ค.
์ด๋ฌํ ๋ฌธ์ ์ ๋ํ ๊ฐ์ ๋ฐฉ์์ ๋์ถ์ ์ํด ์ ํ์ฐ๊ตฌ์์ ๋ํ๋ ๋ฐ์ ๊ฐ์ด ๋ค๋ฅธ ๋ชจ๋ธ์ ๋นํด ์์ธก๋ ฅ์ด ์ฐ์ํ ๊ฒ์ผ๋ก ๋ํ๋ ISCST3 ๋ชจ๋ธ์ ๋์์ผ๋ก ๊ฐ์ ์๋๋ฆฌ์ค๋ฅผ ์์ฑํ์ฌ ๋ชจ๋ธ๋ง์ ์ค์ํ๊ณ ์์ธก๊ฒฐ๊ณผ์ ๋ถํฌ ๋ฐ ๋ณํํน์ฑ์ ๋ถ์์ ํตํด ๋ชจ๋ธ์ด ๊ฐ์ง๋ ์ ํ์
์ ํ์ธ ๋ฐ ๊ฐ์ ๋ฐฉ์์ ์ ์ํ๊ณ ์ ๋ณธ ์ฐ๊ตฌ๋ฅผ ์ํํ์๋ค.
๊ฐ ์๋๋ฆฌ์ค๋ ๋ฐ์์ ๊ฒฉ์ 3๊ฐ์ง์ ์์ฉ์ ๊ฒฉ์ 5๊ฐ์ง๋ฅผ ๊ต์ฐจ ์กฐํฉํ์ฌ ์ด 15๊ฐ์ ์๋๋ฆฌ์ค๋ฅผ ๊ตฌ์ฑํ์์ผ๋ฉฐ, ์
๋ ฅ๋ณ์ ์ฐ์ ์ ์ํด ์๋น ๋ชจ๋ธ๋ง์ ํตํด ์
๋ ฅ๋ณ์๋ฅผ ๊ฒฐ์ ํ์๋ค.
์ฐ๊ตฌ์ํ๊ฒฐ๊ณผ ๋ฐ์์ ๊ฒฉ์ํฌ๊ธฐ๋ฅผ ํฌ๊ฒ ์ค์ ํ ๊ฒฝ์ฐ ์์ฉ์ ๋๋๋ ์ฆ๊ฐํ๋ ๊ฒ์ผ๋ก ๋ํ๋ฌ์ผ๋ฉฐ, ์ต๋์ฐฉ์ง๋๋๋ฅผ ๋ฐ์์ ๊ฒฉ์๋ฉด์ ์ผ๋ก ๋๋ ๋จ์ ๋ฉด์ ๋น ์ฐฉ์ง๋๋ ์ฐ์ ๊ฒฐ๊ณผ ์๋๋ฆฌ์ค๋ณ ์ต๋ ์ฐฉ์ง๋๋๋ ์ ์ฌํ ๊ฐ์ผ๋ก ๋ํ๋ฌ๋ค.
์๋๋ฆฌ์ค๋ณ ๋์ผ๋ฉด์ ์ฐฉ์ง๋๋ ๋ถ์๊ฒฐ๊ณผ ์์ฉ์ ๊ฒฉ์ํฌ๊ธฐ 25ร25m๋ฅผ ๊ธฐ์ค์ผ๋ก ๊ฒฉ์ํฌ๊ธฐ๊ฐ 50ร50m์ธ ๊ฒฝ์ฐ ์ค์ผ๋ฌผ์ง ๋๋๊ฐ 1.42๏ผ
๊ฐ์ค๋๋ ๊ฒ์ผ๋ก ๋ํ๋ฌ์ผ๋ฉฐ, ์์ฉ์ ๊ฒฉ์ํฌ๊ธฐ 100ร100m์ ๊ฒฝ์ฐ 5.03๏ผ
, ์์ฉ์ ๊ฒฉ์ํฌ๊ธฐ 200ร200m์ ๊ฒฝ์ฐ 13.58๏ผ
, ์์ฉ์ ๊ฒฉ์ํฌ
๊ธฐ 400ร400m์ ๊ฒฝ์ฐ 80.58๏ผ
์ค์ผ๋ฌผ์ง๋๋๊ฐ ๊ฐ์ค๋์ด ๋ํ๋ฌ๋ค.
์์ฉ์ ๊ฒฉ์ํฌ๊ธฐ์ ๋ณํ์ ๋ฐ๋ฅธ ์์ฉ์ ๋๋์ ๊ฐ์์จ์ ๋ถ์ํ ๊ฒฐ๊ณผ ์์ฉ์ ๊ฒฉ์ํฌ๊ธฐ๋ฅผ์๊ฒ ์ค์ ํ ๊ฒฝ์ฐ ์ต๋์ฐฉ์ง๋๋์์ ํ์๋๋๋ก์ ๊ฐ์์จ์ด ๊ฐ์ํ๋ ๊ฒ์ผ๋ก ๋ํ๋ฌ์ผ๋ฉฐ,์์ฉ์ ๊ฒฉ์ํฌ๊ธฐ๋ฅผ 200ร200m ์ดํ๋ก ์ค์ ํ์ฌ ๋ชจ๋ธ๋ง์ ์ํํ ๊ฒฝ์ฐ ์์ฉ์ ๊ฒฉ์ํฌ๊ธฐ ๋ณํ์ ๋ฐ๋ฅธ ์์ฉ์ ๋๋ ์ค์ฐจ๋ฅผ ์ค์ผ ์ ์์ ๊ฒ์ผ๋ก ๋ํ๋ฌ๋ค.
๋ฉด์ค์ผ์์ ์ ์ฉํ ๋๊ธฐ์ค์ผ๋ฌผ์งํ์ฐ ์์ธก์ ์ค์ฐจ์ ์ ์ด๋ฐฉ์์ผ๋ก๋ ๋ชจ๋ธ์ด ๊ฐ์ง๋ ํ๊ณ๋ด์์ ์์ฉ์ ๊ฒฉ์ํฌ๊ธฐ๋ฅผ ์ต๋ํ ์ธ๋ถํํ์ฌ ๋ชจ๋ธ๋ง์ ์ค์ํ์ฌ ์์ธกํธ์ฐจ๋ฅผ ์ต์ํ๋ ๋ฐฉ์์ด ์์ผ๋ฉฐ, ์์ธก๋ฒ์๊ฐ ๊ด๋ฒ์ํ์ฌ ์์ฉ์ ๊ฒฉ์ํฌ๊ธฐ๋ฅผ ์ถฉ๋ถํ ์๊ฒ ํ์ง ๋ชปํ ๊ฒฝ์ฐ ์
์ฉ์ ๊ฒฉ์ํฌ๊ธฐ์ ๋ฐ๋ฅธ ์ค์ผ๋ฌผ์ง์ ๊ฐ์ค์จ์ ๊ณ ๋ คํ์ฌ ์์ฉ์ ๋๋์ ๋ณด์ ๊ณผ์ ์ ๊ฑฐ์น ๊ฒฝ์ฐ ์์ฉ์ ๊ฒฉ์๋ฅผ ๋์ฑ ์ธ๋ถํํ์์ ๋์ ์ ์ฌํ ์์ธก๊ฒฐ๊ณผ์ ๋์ถ์ด ๊ฐ๋ฅํ ๊ฒ์ผ๋ก ํ๋จ๋์๋ค.
์ด์ ์ ์ํ ์ ์ ์์ฉ์ ๊ฒฉ์ํฌ๊ธฐ ์ค์ ๋ฐฉ์๊ณผ ์์ฉ์ ๊ฒฉ์ํฌ๊ธฐ ์ธ๋ถํ ๋ฐฉ์๊ณผ ์์ฉ์ ๋๋์ ๋ณด์ ๋ฐฉ์์ ์ ์ฉํ์ฌ ๋๊ธฐ์ค์ผ์์ธก์ ์ค์ํ ๊ฒฝ์ฐ ๋ชจ๋ธ์ด ๊ฐ์ง๋ ์ ํ์ ์ ๊ฐ์ ํ์ฌ ๋์ฑ ์ ํํ ๋๊ธฐ์ง ์์ธก์ ์ ๋๊ฐ ๊ฐ๋ฅํ ๊ฒ์ด๋ค.
[์๋ฌธ]
As the world becomes industrialized, the air pollution is taking on being complex and accumulation. Furthermore, as the population is concentrated on cities and large-scale industrial complexes are being built,air pollution is being accelerated
.The significance emerges surrounding the forecasting on air pollutants dispersion using the air dispersion models.
We need to select optimum air dispersion models that fit the air pollution features, in comprehensive consideration of forecasting conditions and target pollutants, the kind of pollution sources, meteorological data, topographical data, etc. However, when we perform air pollution forecasting, we have not given sufficient consideration to the limit and restriction of air dispersion
distribution models, and then applied the models. Hence,we do not sufficiently take the air pollution characters into account.
Through this paper, this researcher seeks to identify the limit of the models and present measures for improving it, as he drafted scenarios against the ISCST3 model deemed to have superior forecasting ability to other models as prior researches
revealed, performed modeling, analyzed the forecasting result distribution and change characteristics.
The author created a total of 15 scenarios by cross-combining three source grids with five receptor grids, and determined input variables through preliminary modeling.
As a result of the research, it was revealed that the larger the source grid size was set, the more the receptor concentration increased.In addition, when the author calculated the receptor concentration per unit area by dividing the largest receptor concentrator by the source grid area, it was revealed that the largest concentration according to the scenarios was similar.
The analysis of the receptor concentration per identical area by scenario revealed that, with the receptor grid size with 25 25m as the basis, the pollutants concentration increased 1.42๏ผ
with the grid size of 50 50m, 5.03๏ผ
with the size of 100 100m, 13.58๏ผ
with 200 200m, and 80.58๏ผ
with 400 400m, respectively.
The analysis of the receptor concentration decrease ratio according to the change in the receptor grid size revealed that in case the receptor grid size was set as small, the decrease ratio from the largest receptor concentration to lower concentration was reduced, and that in case we set the receptor grid size below 200 200m and perform modeling, we can reduce the error in the receptor concentration according to the receptor grid size.
When we forecast air pollutants dispersion applying asbestos pollution source, we can control and minimize the error in forecasting by maximizing the segmentation of the receptor grid size within the models limit and performing modeling. In case,
with the forecasting scope extensive, we cannot sufficiently minimize the receptor grid size, and thus undergo the correction of the receptor concentration given the pollutants increase ratio according to the receptor grid size, we can induce forecasting results similar to those obtained when we have further segmented the receptor grid.
In case we apply above-presented methods for setting optimum receptor grid size, methods for segmenting the receptor grid size, and methods for correcting the receptor concentration to perform the air pollution forecasting, then we can improve the limit of models and forecast the air quality more accurately.ope