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Ambient air quality monitoring is performed to monitor pollutants concentration levels in atmosphere that might have harmful effect to human health. Based on PP no. 41 tahun 1999, some pollutants such as SO2, NOx, and PM10 required to be measured for 24 hours. However, the full measurement often can...

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Main Author: SURYA MARTEDA (NIM : 15309069), GEDE
Format: Final Project
Language:Indonesia
Online Access:https://digilib.itb.ac.id/gdl/view/27471
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Institution: Institut Teknologi Bandung
Language: Indonesia
id id-itb.:27471
spelling id-itb.:274712018-03-09T16:32:54Z#TITLE_ALTERNATIVE# SURYA MARTEDA (NIM : 15309069), GEDE Indonesia Final Project INSTITUT TEKNOLOGI BANDUNG https://digilib.itb.ac.id/gdl/view/27471 Ambient air quality monitoring is performed to monitor pollutants concentration levels in atmosphere that might have harmful effect to human health. Based on PP no. 41 tahun 1999, some pollutants such as SO2, NOx, and PM10 required to be measured for 24 hours. However, the full measurement often cannot be done due to weather condition or technical problems. The objective of this research is to identify the most significant time duration attributed to urban activity that affect diurnal concentration of SO2, NOx, and PM10. The statistical models developed in this study were used for estimating 24-hour concentrations from less than 24-hour measurement at each type of land-use in the area of DKI Jakarta. At the early stages, the daily fluctuation of SO2, NOx, and PM10 in each type of land-use were identified. Then, the concentration of these pollutants of various durations (12, 16, 18, 20, and 24 hours) which were expected to represent urban activity within the 24-hours average concentration were analyzed using paired-t test and scatter plot. The plots described the ratio of measurement duration and 24-hour (T/T24) versus the ratio of associated concentration and 24-hours concentration (C/C24). It is concluded that the model can reasonably predict the 24-hour average concentration with 20-hours minimum measurement provide the best estimation (R2 average is 0.9). The models were validated against manual active concentration. The validation result shows on average of 5.43% (0.168 μg/m3 and 2,974 μg/m3) ranging between 0,6% (0.52 μg/m3 ) to10,9% (2,965 ppb). text
institution Institut Teknologi Bandung
building Institut Teknologi Bandung Library
continent Asia
country Indonesia
Indonesia
content_provider Institut Teknologi Bandung
collection Digital ITB
language Indonesia
description Ambient air quality monitoring is performed to monitor pollutants concentration levels in atmosphere that might have harmful effect to human health. Based on PP no. 41 tahun 1999, some pollutants such as SO2, NOx, and PM10 required to be measured for 24 hours. However, the full measurement often cannot be done due to weather condition or technical problems. The objective of this research is to identify the most significant time duration attributed to urban activity that affect diurnal concentration of SO2, NOx, and PM10. The statistical models developed in this study were used for estimating 24-hour concentrations from less than 24-hour measurement at each type of land-use in the area of DKI Jakarta. At the early stages, the daily fluctuation of SO2, NOx, and PM10 in each type of land-use were identified. Then, the concentration of these pollutants of various durations (12, 16, 18, 20, and 24 hours) which were expected to represent urban activity within the 24-hours average concentration were analyzed using paired-t test and scatter plot. The plots described the ratio of measurement duration and 24-hour (T/T24) versus the ratio of associated concentration and 24-hours concentration (C/C24). It is concluded that the model can reasonably predict the 24-hour average concentration with 20-hours minimum measurement provide the best estimation (R2 average is 0.9). The models were validated against manual active concentration. The validation result shows on average of 5.43% (0.168 μg/m3 and 2,974 μg/m3) ranging between 0,6% (0.52 μg/m3 ) to10,9% (2,965 ppb).
format Final Project
author SURYA MARTEDA (NIM : 15309069), GEDE
spellingShingle SURYA MARTEDA (NIM : 15309069), GEDE
#TITLE_ALTERNATIVE#
author_facet SURYA MARTEDA (NIM : 15309069), GEDE
author_sort SURYA MARTEDA (NIM : 15309069), GEDE
title #TITLE_ALTERNATIVE#
title_short #TITLE_ALTERNATIVE#
title_full #TITLE_ALTERNATIVE#
title_fullStr #TITLE_ALTERNATIVE#
title_full_unstemmed #TITLE_ALTERNATIVE#
title_sort #title_alternative#
url https://digilib.itb.ac.id/gdl/view/27471
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