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Development of Hydro-Meteorological Hazard Early Warning System in Indonesia Susandi, Armi; Tamamadin, Mamad; Pratama, Alvin; Faisal, Irvan; Wijaya, Aristyo R.; Pratama, Angga F.; Pandini, Olgha P.; Widiawan, Destika Agustina
Journal of Engineering and Technological Sciences Vol 50, No 4 (2018)
Publisher : ITB Journal Publisher, LPPM ITB

This paper discusses the result of the development of a hydro-meteorological hazard early warning system (H-MHEWS) that combines weather prediction from Weather Research and Forecasting (WRF) and the hydrometeorological hazard index from the National Disaster Management Authority (BNPB), Indonesia. In its current development phase, the hazards that H-MHEWS predicts are floods, landslides, and extreme weather events. Potential hazard indices are obtained by using an overlay approach and resampling so that the data have a 100-m spatial resolution. All indices are classified into 4 status categories: âNo alertâ, âAdvisoryâ, âWatchâ, and âWarningâ. Flood potential is produced by overlaying rainfall prediction at 3-hour intervals with the flood index. Landslide potential is produced by overlaying rainfall prediction with the landslide index. Extreme weather potential is divided into 3 categories, i.e. heavy rain, strong winds, and extreme ocean waves. The whole prediction is dynamic, following weather predictions at 3-hour intervals. The hazard prediction results will trigger a âWarningâ alert in case of emergency status. This alert will be set up in a notification system to make it easier for the user to identify the most dangerous hydrometeorological hazard events.

ANALISIS DISPERSI PENCEMAR UDARA PM10 DI KOTA BANDUNG MENGGUNAKAN WRFCHEM DATA ASIMILASI Pratama, Alvin; Sofyan, Asep
Jurnal Teknik Lingkungan Vol 26, No 1 (2020)
Publisher : ITB Journal Publisher, LPPM ITB

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5614/j.tl.2020.26.1.2

Abstrak: Pencemaran udara merupakan salah satu permasalahan utama di kota-kota besar di Indonesia, salah satunya Kota Bandung. Permasalahan ini muncul akibat semakin tingginya kebutuhan dan tingkat aktivitas yang dilakukan oleh manusia. Hal ini menjadi salah satu pemicu semakin tingginya konsentrasi polutan di atmosfer yang dapat memengaruhi kehidupan manusia ataupun ekosistem. Di atmosfer, tingkat konsentrasi dan pergerakan polutan dipengaruhi oleh berbagai faktor, seperti kondisi meteorologi, karakteristik topografi, dan sumber emisi. Untuk mengetahui pesebaran dan tingkat konsentrasi polutan tersebut, dilakukan simulasi menggunakan model WRFCHEM. Simulasi ini memanfaatkan data Automatic Weather Station dan data inventarisasi emisi Kota Bandung menggunakan metode asimilasi. Dari hasil simulasi diperoleh bahwa emisi terbesar kota Bandung bersumber dari kendaraan bermotor yang didominasi di bagian selatan yaitu tol Padaleunyi dan Jalan Soekarno Hatta. Sedangkan pemanfaatan data asimilasi dalam model WRFDA, mampu meningkatkan akurasi parameter meteorologi dari hingga 7%. Pesebaran polutan di kota Bandung sangat dipengaruhi oleh faktor lokal dan fenomena monsun. Pada bulan kering, polutan cenderung tersebar ke arah utara dan barat, sedangkan pada bulan basah cenderung tersebar ke arah selatan dan timur. Selain itu, tingginya kecepatan angin pada bulan kering (dari arah selatan dan tenggara) dan karakter topografi yang datar (di selatan) menyebabkan PM10 tersebar hingga keluar Kota Bandung. Sedangkan pada bulan basah, pelemahan kecepatan angin akibat topografi yang komplek di utara Kota Bandung meyebabkan PM10 cenderung tidak terdispersi dengan baik. Dari hasil simulasi tersebut, juga terdapat beberapa daerah yang perlu menjadi prioritas pengelolaan kualitas udara jika dibandingkan dengan baku mutu berdasarkan PP 41 Tahun 1999. Daerah-daerah yang perlu mendapatkan perhatian khusus diantaranya Rancabolang, Mekarjaya dan Pasirluyu. Kata kunci: Pencemaran Udara, WRFCHEM, Asimilasi data, PM10, Kota Bandung Abstract: Air pollution is one of the main problems in big cities in Indonesia, one of which is the city of Bandung. This problem arises due to the increasing needs and level of activity carried out by humans. This has become one of the triggers of higher concentrations of pollutants in the atmosphere that can affect human life or ecosystems. In the atmosphere, the level of concentration and movement of pollutants is influenced by various factors, such as meteorological conditions, topographic characteristics, and emission sources. To find out the distribution and concentration level of these pollutants, simulations were carried out using the WRFCHEM model. This simulation utilizes Automatic Weather Station data and Bandung City emissions inventory data using the assimilation method. From the simulation results it was found that the biggest emissions of the city of Bandung were sourced from motor vehicles dominated in the southern part of the Padaleunyi toll road and Jalan Soekarno Hatta. While the use of assimilation data in the WRFDA model, can improve the accuracy of meteorological parameters from up to 7%. The spread of pollutants in the city of Bandung is strongly influenced by local factors and the phenomenon of the monsoon. In the dry month, pollutants tend to spread to the north and west, while in the wet months tend to spread to the south and east. In addition, the high wind speed in the dry months (from the south and southeast) and the flat topographic character (in the south) causes PM10 to spread out of the city of Bandung. Whereas in the wet month, the weakening of the wind speed due to the complex topography in the north of Bandung city causes PM10 to not be well dispersed. From the results of the simulation, there are also some areas that need to be prioritized in air quality management when compared with the quality standards based on PP 41 of 1999. Areas that need special attention include Rancabolang, Mekarjaya and Pasirluyu. Keywords: Air Pollution, WRFCHEM, Data assimilation, PM10, Bandung City

Development of Hydro-Meteorological Hazard Early Warning System in Indonesia Armi Susandi; Mamad Tamamadin; Alvin Pratama; Irvan Faisal; Aristyo R. Wijaya; Angga F. Pratama; Olgha P. Pandini; Destika Agustina Widiawan
Journal of Engineering and Technological Sciences Vol. 50 No. 4 (2018)
Publisher : Institute for Research and Community Services, Institut Teknologi Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5614/j.eng.technol.sci.2018.50.4.2

This paper discusses the result of the development of a hydro-meteorological hazard early warning system (H-MHEWS) that combines weather prediction from Weather Research and Forecasting (WRF) and the hydrometeorological hazard index from the National Disaster Management Authority (BNPB), Indonesia. In its current development phase, the hazards that H-MHEWS predicts are floods, landslides, and extreme weather events. Potential hazard indices are obtained by using an overlay approach and resampling so that the data have a 100-m spatial resolution. All indices are classified into 4 status categories: "No alert", "Advisory", "Watch", and "Warning". Flood potential is produced by overlaying rainfall prediction at 3-hour intervals with the flood index. Landslide potential is produced by overlaying rainfall prediction with the landslide index. Extreme weather potential is divided into 3 categories, i.e. heavy rain, strong winds, and extreme ocean waves. The whole prediction is dynamic, following weather predictions at 3-hour intervals. The hazard prediction results will trigger a 'Warning' alert in case of emergency status. This alert will be set up in a notification system to make it easier for the user to identify the most dangerous hydrometeorological hazard events.

ANALISIS DISPERSI PENCEMAR UDARA PM10 DI KOTA BANDUNG MENGGUNAKAN WRFCHEM DATA ASIMILASI Alvin Pratama; Asep Sofyan
Jurnal Teknik Lingkungan Vol. 26 No. 1 (2020)
Publisher : ITB Journal Publisher, LPPM ITB

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5614/j.tl.2020.26.1.2

Abstrak: Pencemaran udara merupakan salah satu permasalahan utama di kota-kota besar di Indonesia, salah satunya Kota Bandung. Permasalahan ini muncul akibat semakin tingginya kebutuhan dan tingkat aktivitas yang dilakukan oleh manusia. Hal ini menjadi salah satu pemicu semakin tingginya konsentrasi polutan di atmosfer yang dapat memengaruhi kehidupan manusia ataupun ekosistem. Di atmosfer, tingkat konsentrasi dan pergerakan polutan dipengaruhi oleh berbagai faktor, seperti kondisi meteorologi, karakteristik topografi, dan sumber emisi. Untuk mengetahui pesebaran dan tingkat konsentrasi polutan tersebut, dilakukan simulasi menggunakan model WRFCHEM. Simulasi ini memanfaatkan data Automatic Weather Station dan data inventarisasi emisi Kota Bandung menggunakan metode asimilasi. Dari hasil simulasi diperoleh bahwa emisi terbesar kota Bandung bersumber dari kendaraan bermotor yang didominasi di bagian selatan yaitu tol Padaleunyi dan Jalan Soekarno Hatta. Sedangkan pemanfaatan data asimilasi dalam model WRFDA, mampu meningkatkan akurasi parameter meteorologi dari hingga 7%. Pesebaran polutan di kota Bandung sangat dipengaruhi oleh faktor lokal dan fenomena monsun. Pada bulan kering, polutan cenderung tersebar ke arah utara dan barat, sedangkan pada bulan basah cenderung tersebar ke arah selatan dan timur. Selain itu, tingginya kecepatan angin pada bulan kering (dari arah selatan dan tenggara) dan karakter topografi yang datar (di selatan) menyebabkan PM10 tersebar hingga keluar Kota Bandung. Sedangkan pada bulan basah, pelemahan kecepatan angin akibat topografi yang komplek di utara Kota Bandung meyebabkan PM10 cenderung tidak terdispersi dengan baik. Dari hasil simulasi tersebut, juga terdapat beberapa daerah yang perlu menjadi prioritas pengelolaan kualitas udara jika dibandingkan dengan baku mutu berdasarkan PP 41 Tahun 1999. Daerah-daerah yang perlu mendapatkan perhatian khusus diantaranya Rancabolang, Mekarjaya dan Pasirluyu. Kata kunci: Pencemaran Udara, WRFCHEM, Asimilasi data, PM10, Kota Bandung Abstract: Air pollution is one of the main problems in big cities in Indonesia, one of which is the city of Bandung. This problem arises due to the increasing needs and level of activity carried out by humans. This has become one of the triggers of higher concentrations of pollutants in the atmosphere that can affect human life or ecosystems. In the atmosphere, the level of concentration and movement of pollutants is influenced by various factors, such as meteorological conditions, topographic characteristics, and emission sources. To find out the distribution and concentration level of these pollutants, simulations were carried out using the WRFCHEM model. This simulation utilizes Automatic Weather Station data and Bandung City emissions inventory data using the assimilation method. From the simulation results it was found that the biggest emissions of the city of Bandung were sourced from motor vehicles dominated in the southern part of the Padaleunyi toll road and Jalan Soekarno Hatta. While the use of assimilation data in the WRFDA model, can improve the accuracy of meteorological parameters from up to 7%. The spread of pollutants in the city of Bandung is strongly influenced by local factors and the phenomenon of the monsoon. In the dry month, pollutants tend to spread to the north and west, while in the wet months tend to spread to the south and east. In addition, the high wind speed in the dry months (from the south and southeast) and the flat topographic character (in the south) causes PM10 to spread out of the city of Bandung. Whereas in the wet month, the weakening of the wind speed due to the complex topography in the north of Bandung city causes PM10 to not be well dispersed. From the results of the simulation, there are also some areas that need to be prioritized in air quality management when compared with the quality standards based on PP 41 of 1999. Areas that need special attention include Rancabolang, Mekarjaya and Pasirluyu. Keywords: Air Pollution, WRFCHEM, Data assimilation, PM10, Bandung City

Evaluasi Satellite Precipitation Product (GSMaP, CHIRPS, dan IMERG) di Kabupaten Lampung Selatan Alvin Pratama; Hayim Muhammad Agiel; Ade Ayu Oktaviana
Journal of Science and Applicative Technology Vol 6 No 1 (2022): Journal of Science and Applicative Technology June Chapter
Publisher : Lembaga Penelitian dan Pengabdian Masyarakat (LPPM), Institut Teknologi Sumatera, Lampung Selatan, Lampung, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35472/jsat.v6i1.702

The availability of rainfall data is an important requirement in various activities. The limitations of observational data make the satellit precipitation product (SPPs) as an alternative. However, the data must be verified before being used. Verification methods are done by using matric statistic methods such as correlation, error and relative bias. Meanwhile, to see the ability of SPPs in detecting rainfall events, it uses a contingency table method. The purpose of this research is to evaluate the ability of SPPs against observation data. Evaluation of SPPs rainfall data is carried out based on a time scale, namely monthly, 10 daily, and daily. This research uses the data from 2018–2020. On a monthly and 10 daily scale, the CHIRPS data shows excellent linearity and rain detection ability. On a daily scale, IMERG shows better linearity than GSMaP and CHIRPS in every season, with moderate to strong correlation coefficients. However, these data tend to be underestimated with a very large bias. In terms of detecting daily rain, GSMaP tends to be better than CHIRPS and IMERG on every season based on the CSI index. However, in the dry season and transition II, the ability tends to be lower. In general, for the amount of rainfall intensity, the three SPPs data still has a fairly large error against the observation data eventhough the ability to detect rainfall is good.

Analysis distribution sulfur dioxide and nitrogen dioxide concentration from PLTU Pangkalan susu with callpuff method Zulkarnain, Randy; Suryati, Isra’; Pratama, Alvin
Jurnal Pendidikan Teknologi Kejuruan Vol 3 No 4 (2020): Regular Issue
Publisher : Universitas Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/jptk.v3i4.15923

Coal-fired power plants will emit several types of pollutants into the ambient air such as particulates and gases. One way to estimate the extent of the impact distribution of these pollutants is by using air quality modeling. The model used in this study is Calpuff, where this model is a non-steady state model and is influenced by variations in meteorological factors. The research location is PLTU Pangkalan Susu (2x200 MW) with SO2 and NO2 parameters. The purpose of this study was to calculate the concentrations of SO2 and NO2 with Calpuff, to validate modeling with field observations and to simulate the distribution of impacts. The results showed that the concentration of SO2 model obtained was 0.32 - 3.57 µg/m3 and NO2 was 0.51 - 5.15 µg/m3. Meanwhile, the observation results showed that the SO2 concentration was 27 - 39.88 µg/m3 and NO2 was 19.77 - 29.73 µg/m3. The simulation results of the distribution of SO2 and NO2 concentrations with the Calpuff model show that the impact distribution area is in the direction of the wind in the windrose and the affected area is in the southwest of the PLTU Pangkalan Susu. The results of model validation for the values of d = 0.97, r = 0.616 - 0.665 and FB = -1.719 - -1.849, which means that the Calpuff model is quite valid and can be applied to predict the impact distribution area at PLTU Pangkalan Susu.

Correlation Analysis Of PM10 With Tropospheric Ozone (O3) During Forest And Land Fire Event In Sumatera Ade Ayu Oktaviana; Alvin Pratama; Ikhsan Buyung Arifin; Joni Hermana
Jurnal Serambi Engineering Vol. 9 No. 4 (2024): Oktober 2024
Publisher : Faculty of Engineering, Universitas Serambi Mekkah

Show Abstract | Download Original | Original Source | Check in Google Scholar

Indonesia has a forest area of 120,495,702.96 hectares which is vital for human survival. However, significant forest fires, such as those in 1997/1998 and 2015, have caused widespread damage and impacted neighboring countries. These forest fires contribute to an increase in tropospheric ozone (O3) concentrations which are dangerous for human health. This study aims to evaluate the correlation between PM10 and tropospheric ozone in Sumatra during forest fires, using data from the Bukit Kototabang Global Atmospheric Monitoring Station. The analysis method involves measuring PM10 and O3 concentrations using the BAM1020 and Ozone Analyzer Model 49 I, as well as Pearson correlation and linear regression analysis. Results show that there is a positive correlation (r = 0.53) between PM10 and tropospheric ozone, with PM10 increasing as O3 concentrations increase during extreme conditions. The average monthly concentrations of PM10 and O3 during 2016-2020 were 21.75 µg/m3 and 11.61 ppb respectively, with peak concentrations of PM10 in September and O3 in February. Increases in PM10 during forest fires contribute to increases in ozone precursors and photochemical processes, accelerating the formation of tropospheric ozone.

Identifikasi Potensi Daerah Terdampak Pencemaran Udara di Indonesia Menggunakan Pendekatan Model WRF-Chem Pratama, Alvin
Jurnal Serambi Engineering Vol. 10 No. 2 (2025): April 2025
Publisher : Faculty of Engineering, Universitas Serambi Mekkah

Show Abstract | Download Original | Original Source | Check in Google Scholar

Air pollution is a major environmental problem in Indonesia, especially in urban and industrial areas. This study aims to identify regions potentially affected by air pollution using the WRFChem model. Simulations were conducted to analyze the distribution of PM10 pollutants in July, during the Australian monsoon. The simulation results show that most regions in Indonesia remain within safe limits, with PM10 concentrations below the threshold of 75 μg/m³. However, several major cities on the island of Java, such as Jakarta, Tangerang, Yogyakarta and Surabaya, experienced elevated concentrations exceeding the air quality standard. In addition, monsoon wind patterns caused pollutants to spread northward, increasing concentrations in the provinces of Lampung and South Sumatra. These findings highlight the importance of monitoring air quality and implementing mitigation strategies to reduce the impact of air pollution on public health and the environment.

Climate change and antimicrobial resistance: a global public health crisis at the environmental nexus Purwaningrum, Dyah; Pratama, Alvin
Pharmacy Reports Vol. 4 No. 1 (2024): Pharmacy Reports
Publisher : Indonesian Young Scientist Group and UPN Veteran Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51511/pr.94

Antimicrobial resistance (AMR) and climate change are major global public health challenges, with growing evidence indicating interconnected relationships. This review explores the multifaceted links between climate change and AMR, focusing on how rising temperatures influence bacterial resistance mechanisms, alter pathogen distribution patterns, and affect environmental reservoirs of resistance genes. Evidence synthesized in this review indicates that rising temperatures correlate with increased AMR rates across multiple regions, with each 1°C temperature increase linked to higher resistance prevalence. Climate change affects environmental transmission dynamics via soil ecosystems, aquatic environments, and cryosphere degradation, which can release long-dormant resistance determinants from permafrost and glaciers. Rising temperatures facilitate the geographic spread of resistant pathogens, as observed in Vibrio species expanding to higher latitudes and the emergence of Candida auris as a clinically significant pathogen from environmental sources. Wildlife and livestock act as potential reservoirs, while climate-driven habitat changes increase human-animal interactions that may facilitate transmission. The bidirectional relationship between these challenges—where rising temperatures contribute to AMR spread and resistant infections may hinder climate resilience—requires integrated One Health approaches. Strategies proposed include enhanced surveillance, climate-informed antimicrobial stewardship, and ecosystem-based interventions to address these interconnected issues. Importantly, integrating climate-informed health policies that align climate adaptation with AMR control should be prioritized globally to safeguard antimicrobial efficacy amid accelerating environmental changes.

Comparative Analysis of GEOS-Chem, SAPRC99, and MOZART Mechanisms in WRF-Chem for Simulating Pollutant Dispersion from Forest Fires: Analisis Perbandingan Mekanisme GEOS-Chem, SAPRC99, dan MOZART dalam WRF-Chem untuk Simulasi Dispersi Polutan dari Kejadian Kebakaran Hutan Oktaviana, Ade Ayu; Pratama, Alvin; Kombara, Prawira Yudha; Mareta, Lesi
Jurnal Teknologi Lingkungan Vol. 26 No. 2 (2025)
Publisher : BRIN Publishing (Penerbit BRIN)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55981/jtl.2025.3956

Abstrak Mekanisme kimia polutan dan parameter meteorologi merupakan bagian penting dalam menentukan sebaran polutan. Dengan mengetahui parameter tersebut, maka dapat diestimasi arah persebaran polutan dan besaran dampak yang ditimbulkan di lingkungan. Hal ini dapat diestimasi menggunakan pemodelan numerik seperti WRF-Chem. Model ini merupakan kombinasi dari prediksi cuaca dan proses kimia atmosfer. Penggunaan mekanisme kimia yang berbeda dalam menjalankan model WRF-Chem akan berdampak pada keluaran model. Oleh karena itu, perlu dilakukan analisis lebih lanjut tentang penggunaan mekanisme kimia yang berbeda dalam model WRF-Chem. Penelitian ini memanfaatkan fire inventory untuk mekanisme kimia polutan yang dikeluarkan oleh NCAR, yaitu GEOS-Chem, SAPRC99, dan MOZART. Studi kasus yang digunakan dalam penelitian ini adalah saat kejadian kebakaran hutan di Provinsi Riau pada bulan September 2019, dengan fokus analisis pada karbon monoksida dan particulate matter (PM10). Metode yang digunakan dalam penelitian ini adalah melakukan analisis menggunakan parameter statistik, seperti korelasi, bias, dan RMSE untuk mengetahui tingkat akurasi model. Dari hasil simulasi, skema MOZART merupakan skema terbaik dengan korelasi sedang hingga kuat. Namun, seluruh skema dalam simulasi ini cenderung underestimate dan memiliki nilai error yang tinggi terhadap observasi. Hal ini menunjukkan bahwa skema kimia dari fire inventory masih mempunyai tantangan besar dalam memprediksi nilai konsentrasi polutan. Untuk arah sebaran, MOZART, dan SAPRC99 menunjukkan pola spasial yang mirip dengan citra satelit. Abstract The chemical mechanisms of pollutants and meteorological parameters play a crucial role in determining the distribution of pollutants. Understanding these factors enables the estimation of pollutant dispersion direction and its potential environmental impact. It can be estimated using numerical models, such as WRF-Chem, a coupled system integrating weather prediction and atmospheric chemical processes. The use of different chemical mechanisms within WRF-Chem influences the model output. This study aimed to evaluate the spatial and statistical performance of the WRF-Chem model using three different chemical mechanisms—MOZART, GEOS-Chem, and SAPRC99—from the FINN emission inventory, during a forest fire episode in Riau Province in September 2019. The analysis focused on carbon monoxide (CO) and particulate matter (PM₁₀), using statistical metrics such as correlation, bias, and RMSE, along with spatial validation against Sentinel-5P satellite imagery. Simulation results showed that the MOZART mechanism provided the best overall performance, exhibiting moderate to strong correlation with observational data. However, all chemical schemes tended to underestimate pollutant concentrations and showed relatively high error margins. Spatially, MOZART and SAPRC99 demonstrated dispersion patterns closely aligned with satellite observations. These findings highlight the potential and limitations of current chemical mechanisms in accurately simulating pollutant dispersion during forest fire events.

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