| dc.contributor.advisor | Turyanti, Ana | |
| dc.contributor.advisor | Azzah, Nofi Rahmawati | |
| dc.contributor.author | Sari, Alyssa Wulan | |
| dc.date.accessioned | 2024-12-30T13:30:49Z | |
| dc.date.available | 2024-12-30T13:30:49Z | |
| dc.date.issued | 2024 | |
| dc.identifier.uri | http://repository.ipb.ac.id/handle/123456789/160397 | |
| dc.description.abstract | Pada musim kemarau kualitas udara sering kali menjadi isu penting terutama
di wilayah Jakarta. Peningkatan jumlah hari tanpa hujan menyebabkan
berkurangnya faktor pembersih udara. Kondisi cuaca ekstrem turut mendorong
peningkatan jumlah hari tanpa hujan berturut-turut atau dikenal dengan istilah
Consecutive Dry Day/CDD, memberi peluang akumulasi polutan di udara termasuk
partikulat. Tujuan penelitian ini adalah untuk menganalisis pengaruh panjang hari
kering berturut-turut dengan fluktuasi konsentrasi Particulate Matter (PM)
khususnya di wilayah Jakarta. Data pengukuran hujan harian dan konsentrasi
partikulat dari 5 stasiun di Jakarta tahun 2019-2023 digunakan sebagai input untuk
menganalisis karakteristik spasial dan temporal CDD dan partikulat. Hasil
penelitian menunjukkan bahwa nilai CDD dan PM berbanding lurus tertinggi pada
periode transisi musim (Maret-April-Mei) dengan korelasi mencapai 0,735 untuk
PM10 dan 0,828 untuk PM2.5. Tren spasial bulanan dari tahun 2019-2023
menunjukkan tren positif CDD dan PM, khususnya di bagian timur Jakarta dengan
nilai slope maksimum 0,62 untuk PM10 dan 0,58 untuk PM2.5. Hal ini
mengindikasikan bahwa semakin panjang hari tanpa hujan, berkontribusi terhadap
peningkatan konsentrasi partikulat di wilayah Jakarta. Dari penelitian ini
didapatkan bahwa ketika deret hari kering melebihi 17 hari untuk PM10 dan 21 hari
untuk PM2.5, perlu diwaspadai konsentrasi partikulat yang berpotensi melebihi
Baku Mutu Udara Ambien 24 jam | |
| dc.description.abstract | In the dry season, air quality is often an important issue, especially in the
Jakarta area. The increase in the number of days without rain leads to a reduction
in factors that help clean the air. Extreme weather conditions also encourage an
increase in the number of consecutive days or known as a series of consecutive dry
days (CDD), providing opportunities for the accumulation of pollutants in the air,
including particulates. The purpose of this study is to analyze the effect of the length
of consecutive dry days with fluctuations in Particulate Matter (PM) concentrations,
especially in the Jakarta area. Data on daily rainfall measurements and particulate
concentrations from 5 stations in Jakarta in 2019-2023 were used as inputs to
analyze the spatial and temporal characteristics of CDD and particulate. The results
showed that the values of CDD and PM were directly proportional to the highest in
the seasonal transition period (March-April-May) with a correlation reaching 0,735
for PM10 and 0,828 for PM2.5. Monthly spatial trends from 2019-2023 show positive
trends in CDD and PM, especially in the eastern part of Jakarta with a maximum
slope value of 0,62 for PM10 and 0,58 for PM2.5. This indicates that the longer the
day without rain can contribute to the increase in particulate concentration in the
Jakarta area. The study also found that when the series of dry days exceeds 17 days
for PM10 and 21 days for PM2.5, it is necessary to be aware of particulate
concentrations that have the potential to exceed the 24-hour Ambient Air Quality
Standard. | |
| dc.description.sponsorship | | |
| dc.language.iso | id | |
| dc.publisher | IPB University | id |
| dc.title | Analisis Hubungan Deret Hari Kering (Consecutive Dry Days) dan Konsentrasi Partikulat (Studi kasus: Provinsi Daerah Khusus Jakarta) | id |
| dc.title.alternative | Analysis of the Relationship between Consecutive Dry Days and Particulate Concentration (Case study: the Special Region Province of Jakarta) | |
| dc.type | Skripsi | |
| dc.subject.keyword | partikulat | id |
| dc.subject.keyword | Polusi Udara | id |
| dc.subject.keyword | cuaca ektrim | id |
| dc.subject.keyword | deret hari kering berturut-turut | id |
| dc.subject.keyword | tren partikulat | id |