Diurnal and Daily Variations of PM2.5 and its Multiple-Wavelet Coherence with Meteorological Variables in Indonesia
Abstract PM2.5 is a fine particle that has adverse health effects. Characterizing the diurnal variations and the influence of meteorology is critical for understanding the drivers of air pollution and planning effective mitigation strategies. We studied the diurnal variation of PM2.5 and its relatio...
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| Format: | Article |
| Language: | English |
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Springer
2024-01-01
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| Series: | Aerosol and Air Quality Research |
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| Online Access: | https://doi.org/10.4209/aaqr.230158 |
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| author | Nani Cholianawati Tiin Sinatra Ginaldi Ari Nugroho Didin Agustian Permadi Asri Indrawati Halimurrahman Meta Kallista Moch Syarif Romadhon Ilma Fauziah Ma’ruf Dipo Yudhatama Tesalonika Angela Putri Madethen Asif Awaludin |
| author_facet | Nani Cholianawati Tiin Sinatra Ginaldi Ari Nugroho Didin Agustian Permadi Asri Indrawati Halimurrahman Meta Kallista Moch Syarif Romadhon Ilma Fauziah Ma’ruf Dipo Yudhatama Tesalonika Angela Putri Madethen Asif Awaludin |
| author_sort | Nani Cholianawati |
| collection | DOAJ |
| description | Abstract PM2.5 is a fine particle that has adverse health effects. Characterizing the diurnal variations and the influence of meteorology is critical for understanding the drivers of air pollution and planning effective mitigation strategies. We studied the diurnal variation of PM2.5 and its relationship with meteorological variables in seven cities representing Indonesia’s three different rainfall patterns during 2021. We used half-hourly PM2.5 concentrations obtained by air quality monitoring system (AQMS), planetary boundary layer height (PBLH) estimation from radiosonde, and meteorological parameters from meteorological stations. A bimodal pattern with two peaks appears in Padang, Manado, Palu, and Pangkalpinang, while in Jakarta, Surabaya, and Pontianak, the diurnals have a unimodal pattern with one peak at night until morning. All cities generally present higher diurnal PM2.5 concentrations in the dry season than in the wet season. The relationship between PM2.5 concentration and PBLH shows Jakarta, Surabaya, Padang, and Pontianak have a strong anti-correlation for different seasons, while the unusual positive correlation occurs in Padang. The Pearson correlation between PM2.5 concentration with each meteorological factor is significant in monthly data and insignificant in daily data. Implementation of Multiple Wavelet Coherence (MWC) with various meteorological variables reveals that the combination of four parameters provides a stronger influence on the PM2.5 concentration in all the observed locations. Wavelet analysis also observes distinct scale periods that represent higher haze concentrations in Jakarta and Surabaya from May to September. Meanwhile, the investigation on the extreme rise of PM2.5 in Pontianak due to peatland forest fires using HYSPLIT shows that emission from the surrounding area significantly raises the maximum half-hourly in Pontianak to 700 μg m−3. |
| format | Article |
| id | doaj-art-79211db6dfa241229bcd2f2e6a065749 |
| institution | Kabale University |
| issn | 1680-8584 2071-1409 |
| language | English |
| publishDate | 2024-01-01 |
| publisher | Springer |
| record_format | Article |
| series | Aerosol and Air Quality Research |
| spelling | doaj-art-79211db6dfa241229bcd2f2e6a0657492025-02-09T12:23:54ZengSpringerAerosol and Air Quality Research1680-85842071-14092024-01-0124311810.4209/aaqr.230158Diurnal and Daily Variations of PM2.5 and its Multiple-Wavelet Coherence with Meteorological Variables in IndonesiaNani Cholianawati0Tiin Sinatra1Ginaldi Ari Nugroho2Didin Agustian Permadi3Asri Indrawati4Halimurrahman5Meta Kallista6Moch Syarif Romadhon7Ilma Fauziah Ma’ruf8Dipo Yudhatama9Tesalonika Angela Putri Madethen10Asif Awaludin11Research Center for Climate and Atmosphere, National Research and Innovation AgencyResearch Center for Climate and Atmosphere, National Research and Innovation AgencyResearch Center for Climate and Atmosphere, National Research and Innovation AgencyEnvironmental Engineering Department, Institut Teknologi Nasional BandungResearch Center for Climate and Atmosphere, National Research and Innovation AgencyResearch Center for Climate and Atmosphere, National Research and Innovation AgencyComputer Engineering Department, School of Electrical Engineering, Telkom UniversityResearch Center for Climate and Atmosphere, National Research and Innovation AgencyResearch Center for Climate and Atmosphere, National Research and Innovation AgencyResearch Center for Climate and Atmosphere, National Research and Innovation AgencyResearch Center for Climate and Atmosphere, National Research and Innovation AgencyResearch Center for Climate and Atmosphere, National Research and Innovation AgencyAbstract PM2.5 is a fine particle that has adverse health effects. Characterizing the diurnal variations and the influence of meteorology is critical for understanding the drivers of air pollution and planning effective mitigation strategies. We studied the diurnal variation of PM2.5 and its relationship with meteorological variables in seven cities representing Indonesia’s three different rainfall patterns during 2021. We used half-hourly PM2.5 concentrations obtained by air quality monitoring system (AQMS), planetary boundary layer height (PBLH) estimation from radiosonde, and meteorological parameters from meteorological stations. A bimodal pattern with two peaks appears in Padang, Manado, Palu, and Pangkalpinang, while in Jakarta, Surabaya, and Pontianak, the diurnals have a unimodal pattern with one peak at night until morning. All cities generally present higher diurnal PM2.5 concentrations in the dry season than in the wet season. The relationship between PM2.5 concentration and PBLH shows Jakarta, Surabaya, Padang, and Pontianak have a strong anti-correlation for different seasons, while the unusual positive correlation occurs in Padang. The Pearson correlation between PM2.5 concentration with each meteorological factor is significant in monthly data and insignificant in daily data. Implementation of Multiple Wavelet Coherence (MWC) with various meteorological variables reveals that the combination of four parameters provides a stronger influence on the PM2.5 concentration in all the observed locations. Wavelet analysis also observes distinct scale periods that represent higher haze concentrations in Jakarta and Surabaya from May to September. Meanwhile, the investigation on the extreme rise of PM2.5 in Pontianak due to peatland forest fires using HYSPLIT shows that emission from the surrounding area significantly raises the maximum half-hourly in Pontianak to 700 μg m−3.https://doi.org/10.4209/aaqr.230158PM2.5Diurnal variationMeteorological factorMultiple-wavelet coherenceIndonesia |
| spellingShingle | Nani Cholianawati Tiin Sinatra Ginaldi Ari Nugroho Didin Agustian Permadi Asri Indrawati Halimurrahman Meta Kallista Moch Syarif Romadhon Ilma Fauziah Ma’ruf Dipo Yudhatama Tesalonika Angela Putri Madethen Asif Awaludin Diurnal and Daily Variations of PM2.5 and its Multiple-Wavelet Coherence with Meteorological Variables in Indonesia Aerosol and Air Quality Research PM2.5 Diurnal variation Meteorological factor Multiple-wavelet coherence Indonesia |
| title | Diurnal and Daily Variations of PM2.5 and its Multiple-Wavelet Coherence with Meteorological Variables in Indonesia |
| title_full | Diurnal and Daily Variations of PM2.5 and its Multiple-Wavelet Coherence with Meteorological Variables in Indonesia |
| title_fullStr | Diurnal and Daily Variations of PM2.5 and its Multiple-Wavelet Coherence with Meteorological Variables in Indonesia |
| title_full_unstemmed | Diurnal and Daily Variations of PM2.5 and its Multiple-Wavelet Coherence with Meteorological Variables in Indonesia |
| title_short | Diurnal and Daily Variations of PM2.5 and its Multiple-Wavelet Coherence with Meteorological Variables in Indonesia |
| title_sort | diurnal and daily variations of pm2 5 and its multiple wavelet coherence with meteorological variables in indonesia |
| topic | PM2.5 Diurnal variation Meteorological factor Multiple-wavelet coherence Indonesia |
| url | https://doi.org/10.4209/aaqr.230158 |
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