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All Journal Jurnal Presipitasi : Media Komunikasi dan Pengembangan Teknik Lingkungan Journal of Engineering and Technological Sciences
Fawzia, Annisa Ayu
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Aerospace Engineering Agriculture, Biological Sciences & Forestry Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Earth & Planetary Sciences Electrical & Electronics Engineering

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Emissions Analysis of Railway Transportation in Java Island Indonesia for Climate Change Mitigation – Study Case in 2023 Nurjani, Emilya; Astuti, Bernadetta Indri Dwi; Firmansyah, Anugrah Jorgi; Fawzia, Annisa Ayu; Sekaranom, Andung Bayu; Suarma, Utia
Journal of Engineering and Technological Sciences Vol. 58 No. 1 (2026): Vol. 58 No. 1(2026): February
Publisher : Directorate 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.2026.58.1.3

Abstract

Rail transportations are among the most environmentally friendly modes of transportation due to their low per capita emissions and carbon footprint. This study aims to analyze the total CO2 emissions and per capita emissions of long-distance and local rail transports operating on the island of Java in 2023. Emission calculations were conducted using the IPCC methodology and Sebos’s approach, incorporating factors such as locomotive types, which predominantly use B30 biodiesel and electricity as energy sources. The results are presented in the form of spatial maps for a comprehensive visualization. Key findings indicate that high emissions and per capita emissions are not exclusively associated with rail transports operating in urban areas. Areas with high long-distance train emissions (> 30,000 tons of CO2) are OP VI Yogyakarta and OP VIII Surabaya. High per capita emissions (> 0.005 tons of CO2/capita/year) are OP I Jakarta and OP VII Madiun. Instead, factors such as travel frequency, route length, locomotive type, fuel type, and passenger volume significantly influence emission outcomes. Commuter trains contribute higher emissions than long-distance trains and local non-commuter trains. The highest total emissions were recorded for the Jabodetabek Commuter Line, amounting to 14,545,676 tons of CO2. This line also exhibited the highest per capita emissions due to its high operational frequency and daily service schedule. These findings highlight the need for strategies to optimize rail transports operations and minimize environmental impacts, particularly in high-frequency commuter services.
Economic Activity and Greenhouse Gas Emissions: An Empirical Study of the Indonesian Manufacturing Industry Fawzia, Annisa Ayu; Fawzia, Aulia Valerie; Nurjani, Emilya; Ahmada, Benarifo
Jurnal Presipitasi : Media Komunikasi dan Pengembangan Teknik Lingkungan Article in Press 2026 (For Upcoming Issue)
Publisher : Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/presipitasi.v0i0.%p

Abstract

Manufacturing industry plays significant role in the Indonesian economy. However, this sector was the largest contributor to greenhouse gas (GHG) emissions in 2022, reaching 38% of total emissions released by all sectors. The purposes of this study are to identify characteristics and trends of economic activity and GHG emissions from fuel consumption across 24 manufacturing subsectors, and to analyze the effect of some economic variables on GHG emissions of the manufacturing industry in Indonesia. Economic variables from 2012-2022, including machinery maintenance intensity, labor intensity, resource-use intensity, value-added, and GHG intensity, were analyzed using descriptive statistics and fixed-effect model panel regression. The results show that labor intensity in the manufacturing subsector tends to decline, while resource use intensity and value-added are increasing. Meanwhile, machinery maintenance intensity shows considerable variation without consistent concentration in particular subsectors. Panel data regression indicates that maintenance intensity and labor intensity have significant positive effect on GHG intensity, while resource-use intensity and value-added have significant negative effect. Based on these results, interventions on economic variables can influence GHG emission levels. This study recommends fiscal policy interventions, such as subsidies for environmentally friendly equipment and incentives for green industries, to strengthen the performance of environmentally friendly industries
Co-Authors Ahmada, Benarifo Andung Bayu Sekaranom Astuti, Bernadetta Indri Dwi Emilya Nurjani Fawzia, Aulia Valerie Firmansyah, Anugrah Jorgi Utia Suarma