This study assessed the urban air quality in 16 large Indonesian cities on the islands of Java, Sumatra, Kalimantan, Sulawesi, Maluku, and Papua from 2010 till 2017. 24-h samples of airborne particulate matter (PM) in two size fractions, PM 2.5 (< 2.5 µm in aerodynamic diameter) and PM 2.5-10 (2.5-10 µm in aerodynamic diameter), were collected weekly using a Gent stacked filter unit sampler and then analyzed for their mass concentrations, black carbon (BC) content, and elemental compositions. The majority of the average annual PM 2.5 concentrations measured at the Java sites (Bandung, Jakarta, Semarang, and Surabaya) exceeded the Indonesian annual ambient air quality standard (15 µg m-3), although the other tested locations, excluding Pekanbaru and Palangka Raya, exhibited values below the standard. During the forest fire episodes of 2015, the average daily PM 2.5 concentrations in Pekanbaru and Palangka Raya rose above the national daily ambient standard (65 µg m-3). The percentage of BC, which is associated with traffic emission and biomass burning, averaged between 15% and 26% (a significant fraction) in the PM 2.5. The concentrations of the major elements in the PM 2.5 , viz., Si, S, K, Fe, Zn, and Pb, varied widely from site to site, although all of the locations displayed enhanced levels of the crustal elements Si and S, which originated from unpaved roads and volcanic eruptions, and vehicle fuel, forest fires, and volcanic emissions, respectively. Significantly higher concentrations of heavy metals (Fe, Zn, and Pb in Surabaya and Pb in Tangerang) were found at the heavily industrialized sites, demonstrating the effect of local industrial emissions on air quality. Our results, which are based on a crucial survey of PM concentrations and compositions in Indonesia, provide a scientific basis for * Corresponding author.
22, 19.63, 20.34, 3.86, and 2.57 ppm respectively. The results of the elemental contents of volcanic ash that has been obtained can be used as the scientific based data for volcanic material utilization by considering the economic potential of elements contained and also the danger of the heavy metals content. IntroductionMount Sinabung is a stratovolcano, located in Karo Regency, North Sumatra Province of Indonesia. It is a solitary volcano that has a single peak, and classified as B -Type, because since the 1600's there was no record of eruptive activity [1]. But on November 24, 2013, Mount Sinabung were erupted and reach the highest alert level (level 4) since it spat out black and thick smog, followed by rain sand and volcanic ash which covered thousands of hectares of farmer crops under the radius of six kilometers [2]. Volcanic ash is fragments of magma and consists of mineral, volcanic glass and also a material containing high silica and aluminum [2,3]. The composition of particles from volcanic eruptions should reflect the matrix composition of the magma. 06, 14.66, 1.88, 0.07, 0.6, 1.99, 4.18, 2.89, 0.2 % respectively [5]. These materials in the ash can provide important information on the nature of magma because chemical compositions of magma usually show distinct features of each volcano and because the assemblages and compositions of minerals
/ ABSTRAK The growth of air passengers has increased in line with the population and economic growth of the country. Revenue passenger kilometers (RPK) around in the world during ten years (2000-2010) grew on average of 4.7 % per year, and in the Southeast Asian region. RPK growth in the same period was 6.6% per year. The growth of passenger air transport is very rapid course must be balanced with the provision of air transport infrastructure, while the government budget in transport infrastructure sector has a constraint. Development of airports in Indonesia is still a burden for the reason it, needed the government's policy instruments if want to involve the role of private sector in the airport development. The one of policy istruments is define a model demand forecasting using a dynamic systems approach to support financial analysis in the development of airport infrastructure. Air traffic analysis is an important thing because concerning with the capacity utilization and it helps make decisions regarding the development of infratructure facilities. The robust model of demand forecasting could support to analyze a decision making on an airport development that involves the participation of private investment. Pertumbuhan penumpang angkutan udara mengalami peningkatan sejalan dengan pertumbuhan penduduk dan perekonomian di suatu negara. Revenue passenger kilometers (RPK) wilayah Asia Tenggara dalam kurun waktu 10 Tahun (2000-2010) adalah sebesar 6,6 % per tahun. Pertumbuhan penumpang angkutan udara yang sangat pesat tersebut harus diimbangi dengan penyediaan infrastruktur transportasi udara, Namun saat ini alokasi anggaran pemerintah di bidang infrastruktur transportasi sangat terbatas.untuk itu diperlukan berbagai instrumen kebijakan apabila ingin melibatkan peran swasta. Salah satu upaya untuk mendukung keterlibatan peran swasta dapat dikembangkan model "demand forecasting" menggunakan pendekatan sistem dinamis guna mendukung analisa finansial dalam pengembangan infrastruktur bandar udara. Dengan model demand forecasting penumpang angkutan udara yang komprehensif tersebut diharapkan dapat membantu dalam menganalisa pengambilan sebuah keputusan dalam pengembangan bandar udara yang melibatkan peran serta investasi swasta.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.