APPLICATION AND PERFORMANCE EVALUATION OF CALPUFF DAN AERMOD MODELING SYSTEM TO SIMULATE TSP, SO2, AND NO2 POLLUTANT DISPERSIONI : A CASE STUDY AT PT. X
Air pollution is the entry or inclusion of substances, energy, from other components into the ambient air by human activities so that air quality decreases to a certain level. To protect an area from air pollution, it is necessary to have a strategy to manage air quality, one of which is by predic...
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Format: | Final Project |
Language: | Indonesia |
Online Access: | https://digilib.itb.ac.id/gdl/view/69375 |
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Institution: | Institut Teknologi Bandung |
Language: | Indonesia |
Summary: | Air pollution is the entry or inclusion of substances, energy, from other components into the
ambient air by human activities so that air quality decreases to a certain level. To protect an area from air
pollution, it is necessary to have a strategy to manage air quality, one of which is by predicting the dispersion of
pollutants from a source using a modeling application. study area, and accuracy of prediction results with actual
concentrations in ambient. In this study, two modeling applications were used, namely the Lagrangian-based
CALPUFF model, non-steady state, and the Gaussian Plume-based, steady state AERMOD model. This research
was conducted in Central Cikarang District, Bekasi Regency, with pollutant emission sources TSP, SO2, and NO2
from the chimney of PT. X. To determine the accuracy of the two models, several types of statistical tests are
used, namely correlation coefficient (R), Index of Agreement (IOA), Fractional Bias (FB), Root Mean Square
Error (RMSE), Error, and Mean Bias (MB). The results of this study indicate that the highest concentration for
each pollutant and its location has different values in CALPUFF and AERMOD. CALPUFF always yielded
higher values in the highest predicted concentrations (0.4129 µg/m3
for TSP, 0.6183 µg/m3
for SO2, and 0.5016
µg/m3
for NO2) than AERMOD (0.1256 µg/m3
for TSP, 0.2787 µg/m3
for SO2, and 0.2258 µg/m3
for NO2).
Overall, CALPUFF has a better performance in modeling TSP, SO2, and NO2 pollutants than AERMOD as
evidenced by statistical tests on the results of the dispersion of the two models.
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