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This study aims to analyze the effect of renewable energy, energy consumption, and Gross Domestic Product (GDP) per capita on carbon dioxide (CO2) emissions in Indonesia for the period 1995-2024. This study uses secondary data over time (time series) with the Ordinary Least Square (OLS) multiple linear regression analysis method corrected using the Newey-West Heteroskedasticity and Autocorrelation Consistent (HAC) approach. The results show that renewable energy does not have a significant effect on CO2 emissions, which is caused by the still low share of renewable energy in the national energy mix which only reaches 10.95% in 2024. Energy consumption has a positive and significant effect on CO2 emissions, where every 1% increase in energy consumption increases CO2 emissions by 84.23%. Gross Domestic Product (GDP) per capita has a positive and significant effect on CO2 emissions. Every 1% increase in GDP per capita increases CO2 emissions by 35.03%, indicating that Indonesia remains on the EKC curve. Simultaneously, all three variables have a significant effect, with an adjusted R-squared value of 53.63%. This finding confirms that Indonesia's energy mix, still dominated by fossil fuels, is a major factor in high carbon emissions. Comprehensive energy efficiency policies, accelerated renewable energy transitions, and greener and more sustainable economic growth strategies are needed.

Hydrogen-based hybrid microgrid systems have emerged as a promising solution to enhance renewable energy integration and improve energy supply reliability. By combining renewable sources such as solar and wind with hydrogen production and storage technologies, these systems address the intermittency of renewable power while ensuring continuous energy availability. This study evaluates the techno-economic feasibility, environmental impact, and scalability of hydrogen-based hybrid microgrids, with a focus on cost-effectiveness and system performance under varying operating conditions. Simulation tools, including HOMER Pro and MATLAB Simulink, are used to model the system and conduct sensitivity analyses on hydrogen production costs and demand fluctuations. Key performance indicators such as Levelized Cost of Energy (LCOE), Net Present Value (NPV), and CO₂ emissions reduction are assessed. The results show that although the system requires a high initial investment, it becomes economically viable over time due to reduced operational costs and improved efficiency. Additionally, the system demonstrates significant environmental benefits, outperforming conventional fossil fuel-based systems in terms of emissions reduction. Sensitivity analysis further indicates that advancements in hydrogen production technologies could substantially enhance economic feasibility. Overall, hydrogen-based hybrid microgrids offer a reliable and low-carbon energy solution, supporting sustainable energy transitions and reducing dependence on fossil fuels.

The increasing demand for electrical energy and the issue of climate change are driving the utilization of renewable energy, one of which is through Solar Power Plants (PLTS). The Province of Bali targets the development of PLTS of 108.2 MW, equivalent to 8.62% of the total solar energy potential of 1,254 MW by 2025. However, land limitations pose an obstacle to the construction of large-scale PLTS. Floating solar power plant design can be a solution to this issue. By utilizing 4,955.32 m² of water surface at the Telaga Tunjung Dam, the Floating Solar Power Plant at Telaga Tunjung Dam has a potential capacity of 141.4 kWp, using 280 Trina Solar modules of type TSM-DEG18MC.20(II) (505 Wp) combined with one SG110CX inverter with a capacity of 110 kW. The annual electricity production of the floating solar power plant, based on Helioscope software, is 201.1 MWh. The economic feasibility parameters used in this study include initial investment cost, Profitability Index (PI), and Payback Period (PP). The analysis results show that the 141.4 kWp floating solar power plant project at Telaga Tunjung Dam has an initial investment value of IDR 1,248,764,582, a PI of 1.26, and a PP of 3.91 years. Therefore, this project is considered economically feasible and contributes positively to reducing CO₂ emissions.

The increasing demand for cloud computing services has led to the rapid expansion of cloud data centers, which consume significant amounts of energy and contribute substantially to global CO2 emissions. As the IT industry grows, the environmental impact of these data centers becomes an urgent concern. Green Cloud Computing (GCC) has emerged as a solution to mitigate this impact by focusing on energy efficiency and reducing carbon footprints while maintaining the necessary functionality and performance of cloud infrastructures. However, traditional blockchain consensus algorithms such as Proof of Work (PoW) and Proof of Stake (PoS) face limitations regarding energy consumption and scalability, which exacerbates the environmental burden. This study proposes a quantum-inspired blockchain consensus algorithm designed to optimize energy consumption and reduce latency in cloud data centers. By integrating quantum principles such as superposition and entanglement, the algorithm enhances task scheduling and resource utilization, enabling more energy-efficient operations without sacrificing performance. Simulations in a green cloud environment showed that the quantum-inspired algorithm resulted in up to a 30% reduction in energy usage compared to traditional consensus methods, with a 40% improvement in consensus processing time. These results suggest that quantum-inspired algorithms hold significant potential for enhancing the sustainability of cloud infrastructures by improving energy efficiency and scalability. Furthermore, this study discusses the feasibility of implementing quantum-inspired algorithms on classical hardware, addressing challenges in scalability and integration into existing blockchain frameworks. The findings provide valuable insights into the potential of quantum-inspired technologies to drive energy-efficient solutions in cloud computing.

Urban logistics is a significant source of carbon emissions in Indonesia, and effective decarbonization strategies are required. EVs offer a promising solution, but their impact requires quantitative evaluation within the local context. This study analyzes the effect of adopting an electric van fleet on total well-to-wheel carbon emissions within an urban distribution network in Indonesia. This study employs a comparative case study method. A baseline scenario consisting of 25 diesel vans is compared to an intervention scenario where electric vans replace the entire fleet. The emission analysis was conducted using the WtW framework, utilizing specific emission factors for diesel fuel from the IPCC (2006) and the Java-Madura-Bali (JAMALI) grid emission factor from IESR (2023) to ensure contextual relevance. The transition to an electric fleet successfully reduces the total well-to-wheel carbon footprint by 13.63%. This reduction is equivalent to an absolute CO2 emission decrease of nearly 3 tons of CO₂ per month. Nevertheless, indirect emissions from electricity generation still contribute a significant carbon footprint, indicating that the national energy mix is highly dependent on the environmental benefits of EVs. This study concludes that fleet electrification is a viable and effective decarbonization strategy for Indonesia’s logistics sector, even with the current state of the electricity grid. However, fleet decarbonization efforts must run in parallel with policies for a national transition toward renewable energy to maximize the emission reduction potential of electric mobility. Future research should include the total cost of ownership (TCO) and life cycle assessment (LCA) for a more holistic evaluation.

This study analyzes the flexural behavior of reinforced geopolymer concrete beams through numerical simulation based on the Finite Element Method (FEM) using ANSYS software, comparing it with conventional reinforced concrete beams. The background of this research focuses on the need for environmentally friendly construction materials, considering the high CO₂ emissions from Portland cement production. The numerical model was developed based on parameters and loading schemes from previous experimental studies, utilizing SOLID65 elements for concrete, LINK180 for steel reinforcement, and SOLID185 for supports. Simulation results show that the flexural behaviour of geopolymer beams is comparable to conventional beams in terms of load-deflection relationships, flexural capacity, and crack patterns, with deviations from experimental data generally below 10%. The patterns and propagation of cracks also exhibited similarities, starting from the tensile zone at mid-span. Furthermore, the analysis demonstrates consistency with the analytical approach based on SNI 2847:2019. This research supports the validity of using geopolymer concrete as a sustainable structural material alternative and shows that the FEM numerical method is effective in evaluating the flexural performance of concrete structural elements.

Background: The global energy transition requires low-carbon solutions that can be integrated into existing thermal systems without drastic infrastructure changes. Hydrogen blending in conventional combustion systems has emerged as a promising pathway to reduce carbon emissions while maintaining operational flexibility. Objective: This study aims to experimentally evaluate the effect of hydrogen blending ratios (0–100% by volume) on thermal efficiency, CO₂ emissions, and NOx emissions, and to determine the optimal blending range based on technical and economic feasibility. Methods: An experimental thermal system prototype was developed and tested under controlled conditions with three repetitions per operating point. Performance parameters included combustion temperature, fuel consumption rate, and thermal efficiency, while emissions of CO₂ and NOx were measured using a calibrated gas analyzer. Data were analyzed using descriptive statistics, one-way ANOVA at a 0.05 significance level, confidence interval estimation, and linear regression to examine the relationship between hydrogen fraction and emission reduction. Results: The findings indicate that increasing hydrogen fraction significantly improves thermal efficiency, reaching 87.5% at 100% hydrogen, while CO₂ emissions decrease linearly to zero. However, NOx emissions increase with higher hydrogen content due to elevated combustion temperatures. Statistical analysis confirms that hydrogen ratio has a significant effect on efficiency and emissions, with a strong linear correlation between hydrogen fraction and CO₂ reduction. A blending range of 40–60% hydrogen provides the most balanced performance in terms of efficiency improvement, emission reduction, and cost feasibility.

Global climate change demands immediate technological advancements, particularly in the transport industry that continues to use fossil fuels. One viable solution is to reduce the size of vehicle engines to make them more fuel-efficient and lower carbon emissions. The purpose of this research is to assess the effect of reducing engine size on fuel consumption and CO₂ emissions in low-cost green car hatchbacks in Indonesia. The technique employed is straightforward analytical modeling, employing Pearson correlation analysis and linear regression among three significant variables: engine capacity, fuel economy, and CO₂ emission. The data are obtained from the technical specifications of four hatchback automobile models, all of which have an engine capacity of less than 1,200 cc. Findings indicate that smaller engine capacity is accompanied by greater fuel economy and lower carbon emissions. The lowest engine size of 998 cc is used in the Toyota Agya, which demonstrates the most efficient fuel and lowest emissions. The statistical analysis shows that there is an inverse relationship between engine size and fuel efficiency, but a positive relationship between engine size and CO₂ emissions. The limitation of sample size causes reduced statistical power of the model. In conclusion, engine downsizing can prove to be a productive approach in promoting green schemes, but additional research with a larger data set and other determinants must be undertaken to establish a more advanced and precise model.

This study evaluates the impact of distributed solar-battery systems on urban electricity resilience and community carbon emissions reduction. As urban areas continue to grow, the demand for electricity has placed considerable strain on traditional centralized grids, resulting in increased vulnerabilities. The integration of decentralized energy resources (DERs), particularly solar photovoltaic (PV) systems paired with battery energy storage systems (BESS), has emerged as a promising solution to enhance grid resilience, reduce carbon emissions, and support the transition to more sustainable energy systems. This research uses a simulation-based approach to model the integration of solar-battery systems into residential blocks, assessing their impact on grid reliability, downtime reduction, and the frequency of power outages. Additionally, the study estimates the reduction in carbon dioxide (CO₂) emissions achieved by shifting from fossil-fuel-based energy generation to renewable sources such as solar PV. The results demonstrate that solar-battery systems significantly improve electricity reliability by providing backup power during outages, while also reducing CO₂ emissions by decreasing reliance on conventional grids. The study also discusses the technical and financial challenges associated with the integration of these systems, such as energy storage capacity, system efficiency, and upfront installation costs. Policy recommendations emphasize the importance of government incentives, grid modernization, and long-term financial benefits to encourage the adoption of decentralized energy solutions. Finally, the study highlights areas for future research, including advanced storage technologies and the integration of electric vehicles with solar-battery systems to further enhance energy resilience and sustainability.

The use of natural gas to replace liquefied petroleum gas (LPG) is a strategic step to reduce dependence on imported energy and support a sustainable energy transition. The purpose of this study is to analyze the possibilities, challenges, and impacts of using natural gas as a source of household energy in Indonesia. The research method used is a qualitative approach that collects primary data through questionnaires and interviews with household users and secondary data from related magazines. The results of the study indicate that Indonesia has great potential in meeting energy needs because it is rich in natural gas reserves. From an economic perspective, the use of natural gas is cheaper than liquefied gas, especially in the long term. However, the main challenges are limited distribution infrastructure, lack of public awareness of the benefits of natural gas, and the need for regulations to support the implementation of this energy transition. The results are positive impacts such as reduced CO2 emissions, increased energy efficiency and savings in foreign exchange. In summary, the use of natural gas as a substitute for LPG is feasible, but requires strategic steps such as expanding natural gas infrastructure, educating the public, and strengthening the regulatory framework. This study recommends that the government, energy companies, and the community work together to ensure an effective and sustainable energy transition.

The construction industry is one of the sectors that has a significant impact on environmental damage due to high energy consumption, exploitation of natural resources, and carbon emissions. In response to these challenges, this study aims to analyze the potential for implementing sustainable construction materials to support the development of green infrastructure. Using qualitative methods through literature studies, documentation, observation, and in-depth interviews, this study evaluates the advantages, challenges, and economic and environmental impacts of various innovative materials, such as foam glass, green wall systems, bamboo composites, eco-cement, and mycelium-based blocks. The results show that these materials are able to reduce carbon emissions, increase building energy efficiency, and offer long-term cost savings. Mycelium-based blocks, in particular, are recorded as the most effective material in reducing construction costs by up to 25% and CO₂ emissions by 250 kg per project. However, the implementation of sustainable materials in Indonesia still faces obstacles such as cost, material availability, and technical regulations. Therefore, synergy is needed between the government, academics, and industry in encouraging research, preparing technical standards, and public awareness campaigns to expand the adoption of environmentally friendly materials in the national construction sector.

Rapid urbanization in major cities has led to the decreasing availability of green spaces, exacerbating urban challenges such as the Urban Heat Island (UHI) effect, high energy consumption in buildings, and air pollution. In response, green architecture innovations like green roofs and vertical farming present opportunities for reducing carbon footprints and improving urban sustainability. This study explores the potential for life-cycle carbon footprint reduction through the integration of green roofs and vertical farming systems in high-rise buildings, focusing on energy savings, environmental impact, and air quality improvements. Using Life-Cycle Assessment (LCA) methodology, the research evaluates carbon emissions reduction, operational energy savings, and ecosystem benefits from different building scenarios. Simulation models were developed for conventional high-rise buildings and those incorporating green roofs and vertical farming. EnergyPlus, SketchUp, and SimaPro software were used for energy consumption calculations and carbon emissions modeling. The study analyzes various intervention scenarios-baseline (no vegetation), green roof only, vertical farming only, and a combined system-based on tropical climate data from cities like Jakarta, Surabaya, and Kuala Lumpur. Results reveal that the integration of both green technologies significantly reduces cooling demand, lowers CO₂ emissions, and improves urban microclimates by reducing surface temperatures and enhancing air quality. Policy recommendations and guidelines for adopting green construction practices in tropical regions are provided, alongside suggestions for future research on optimizing these technologies, conducting economic modeling, and evaluating multi-building approaches at a district scale.

Developing and developed countries rely heavily on the use of electrical energy to carry out social and economic activities. The purpose of this study is to analyze economic growth and its influencing factors in the period 2004-2023. This research uses time series data. The data method used is the VECM model. The results of this study indicate that there is a one-way causality relationship between variables. In the short term only CO2 emission variables affect economic growth, while in the long term all variables such as electricity and population can affect economic growth.

Urbanization has significantly impacted air quality in cities, with vehicular emissions being a major contributor to pollution. This study explores the potential benefits of electrifying urban transportation, specifically through the adoption of electric vehicles (EVs). The findings indicate that EVs substantially reduce key pollutants such as CO₂, NOx, and PM₂.₅, improving urban air quality and mitigating climate change. The analysis shows that EV adoption can lead to a 50% reduction in CO₂ emissions in high EV adoption scenarios (70% EVs). Additionally, EVs are more energy-efficient than conventional vehicles, consuming significantly less energy per kilometer. This transition not only reduces dependence on fossil fuels but also supports sustainable urban development. Furthermore, the study highlights the public health benefits of electrification, with reduced levels of harmful pollutants leading to lower incidences of respiratory and cardiovascular diseases. Public health surveys reveal strong support for EV adoption, with respondents believing it would significantly improve air quality and health outcomes. In conclusion, the electrification of urban transportation presents a multifaceted approach to environmental sustainability, energy efficiency, and public health improvement.

This study employs a linear regression algorithm to measure CO2 emissions from motor vehicles based on the type of fuel used—gasoline, premium, diesel, and ethanol—as well as the distance traveled per kilometer. With growing concerns about the environmental impact of vehicle emissions, this research aims to develop a predictive model to estimate CO2 emissions based on these variables. Despite the limited data used, the results indicate that the linear regression model has high accuracy in predicting CO2 emissions. This model can serve as an effective tool to mitigate the environmental impact of motor vehicles and assist policymakers in designing better emission mitigation strategies  

Green Open Space (GOS) is one of the efforts to deal with increasing GHG emissions because it has the ability to absorb CO2 emissions. Development Area IV Pekanbaru is one of the Development Areas that has the potential to produce carbon dioxide (CO2) emissions, specifically in Bukit Raya Pekanbaru District. This research was conducted to determine the number of motorized vehicles and the value of CO2 emissions produced each day, as well as the value of the capacity of GOS to absorb CO2 emissions from transportation activities in Bukit Raya Pekanbaru District. The method used is recording traffic activities to calculate the amount of CO2 emissions and calculating all public green open spaces with vegetation cover in the form of grasslands and trees with a diameter of ≥ 20 cm, as well as calculating the percentage of green open space absorption capacity. The research results obtained were that the value of CO2 emissions from transportation in Bukit Raya Pekanbaru District was 67,007,898 tons of CO2/year. Meanwhile, the capacity to absorb CO2 by public green open spaces is only 1,992.32 tons of CO2/year. The results show that public green open space in Bukit Raya Pekanbaru District in terms of absorbing CO2 emissions from transportation is still insufficient with a percentage of only 2.97%.

Renewable energy microgrids integrated with smart control systems are emerging as a sustainable solution for electrifying rural industrial zones, offering substantial improvements in energy efficiency and reductions in carbon emissions. This study explores the implementation of hybrid renewable energy systems, combining solar and wind energy, and the integration of Internet of Things (IoT) sensors to optimize energy consumption in real-time. The findings highlight that the combination of solar and wind energy in microgrids leads to up to a 30% increase in energy efficiency, with a significant reduction in CO₂ emissions, reaching up to 50% compared to traditional grid systems. IoT sensors play a crucial role in load forecasting, optimization, and system stability, enabling real-time monitoring and proactive adjustments to energy distribution. Additionally, the implementation of these systems in rural industrial zones not only provides reliable, clean energy but also reduces reliance on fossil fuels, making them economically viable and environmentally sustainable. However, challenges such as high initial investment costs, integration complexities, and the need for skilled technicians remain. Despite these barriers, the long-term benefits of reduced energy costs, improved energy security, and lower carbon footprints make renewable energy microgrids a promising solution. The study suggests that these systems can be scaled to other rural regions facing similar challenges in energy access and carbon emissions, offering a path to sustainable development. Further research is recommended to explore alternative renewable energy combinations and advancements in IoT applications to improve system scalability and efficiency.

This study investigates the performance and sustainability of a hybrid solar-biomass drying system for agricultural products, focusing on its efficiency, environmental impact, and economic feasibility. The hybrid system combines solar energy and biomass combustion to create a continuous and reliable drying process. The key findings reveal that the hybrid system achieves over a 20% improvement in drying efficiency compared to solar-only and biomass-only dryers. This efficiency gain is attributed to the synergistic use of solar energy during the day and biomass energy during periods of low sunlight or at night, ensuring consistent drying conditions and reduced drying time. Additionally, the hybrid system significantly reduces CO₂ emissions, contributing to a more sustainable approach to agricultural processing. The environmental benefits of using renewable energy sources, as opposed to fossil fuels, align with the growing need for energy-efficient and eco-friendly agricultural technologies. Economic analysis suggests that the hybrid system is a cost-effective solution for small- to medium-scale farmers, particularly in rural areas where access to grid electricity is limited. The use of locally available biomass fuels further enhances the system’s sustainability and affordability. This study also discusses the practicality of implementing hybrid dryers in rural farming communities, emphasizing their potential to improve drying efficiency, reduce environmental impacts, and boost economic opportunities for farmers. Future research should focus on optimizing system integration, expanding biomass fuel options, and exploring automation to enhance the performance and scalability of hybrid drying systems.

Increasing carbon emissions have the unintended consequence of worsening environmental quality as a result of the use of fossil fuels for green economic activities. The green economy concept is being applied in relation to social and economic difficulties, as well as sectors in one of the global strategic areas aimed at overcoming very rapid climate change. The green economy's quality is determined by CO2 emission levels and creates sustainable development, which can improve environmental quality in some countries (Brazil, Russia, India, Indonesia, Japan, and China), particularly during epidemics. In data analysis, various test procedures are utilized. According to the study findings, there was a considerable increase in CO2 emissions in the BRIIJC country during Covid 19, which had an impact on environmental quality, culminating in ozone layer depletion and climate change. The implementation of a green economy can affect environmental circumstances by requiring economic operations to use more ecologically friendly energy, and boosting energy can boost economic growth.