Analysis Of Greenhouse Gas Emissions Research Articles

Well‐to‐wheels analysis of greenhouse gas emissions for passenger vehicles in Middle East and North Africa

AbstractBattery electric vehicles (BEVs) are widely considered a pathway to achieve low carbon mobility. BEVs emit zero emissions from the tailpipe, but their life cycle carbon reduction compared to gasoline vehicles varies based on primary energy sources, electricity generation, and use efficiency. The Middle East and North Africa (MENA) region is an area rich in fossil fuels, meriting a detailed comparison between the emissions from BEV and other powertrains. We developed a MENA‐specific life cycle model that estimates well‐to‐wheel (WTW) greenhouse gas (GHG) emissions from passenger transport with internal combustion engine vehicles (ICEVs), hybrid electric vehicles (HEVs), plug‐in hybrid electric vehicles, and BEVs. MENA's average WTW GHG emissions for all supply chain steps including combustion emissions from vehicle operation are 767 g/kWh and 84 g CO2eq/MJ for electricity and gasoline, respectively, but are highly variable due to heterogeneity in upstream supply chains. The use of hybrid gasoline ICEVs provides the largest emission reduction opportunity for existing vehicle fleets in 9 of the 16 MENA countries. For these nine countries, replacing gasoline ICEVs with HEVs could, on average, reduce country‐level life cycle GHG emissions by 47%. There is a similar emission reduction opportunity for 14 of the 16 MENA countries when normalizing vehicle efficiencies irrespective of the powertrain shares and other trends in existing vehicle fleets. Future scenario analysis shows that BEVs would have the lowest WTW GHG emissions among all powertrains in most MENA countries only if significantly reduced electricity transmission losses and cleaner grid mix are realized, although a high cost of infrastructure developments is expected.

Carbon footprint analysis of fossil power plants in Bangladesh: measuring the impact of CO2\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${CO}_{2}$$\\end{document} and greenhouse gas emissions

Greenhouse gas (GHG) emissions have increased substantially due to industrialization and the rapid growth in energy demand in Bangladesh. The aim of this study is to conduct a comprehensive carbon footprint analysis of fossil power plants in Bangladesh, focusing on the impact of GHG emissions. We evaluate the carbon footprint of fossil power plants based on their power generation capacity, fuel type, specific emission rates, and global warming potential (GWp) for various GHGs. The emission factor approach has been used in conjunction with the International Panel on Climate Change (IPCC) methodology. Findings of the study indicate that fossil power plants in Bangladesh contribute significantly to the country's overall carbon footprint, with CO2\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${CO}_{2}$$\\end{document} and other GHG emissions being the primary drivers. Furthermore, we evaluate Bangladesh's GHG emissions in comparison with neighbouring countries to determine its position. In terms of greenhouse gas emissions from fossil-based power plants, we find that Bangladesh has relatively low emissions compared to its neighbours and developing countries in Asia. Nevertheless, Bangladesh has witnessed a significant increase in coal-fired power generation in recent years, which has emerged as a significant contributor to emissions. Following an analysis of GHG emissions from fossil fuel power plants, we recommend adopting advanced technologies such as carbon capture and storage (CCS) with improved energy efficiency systems and integrating renewable energy sources into the power generation mix. We conclude our analysis by highlighting the importance of transitioning to cleaner, sustainable energy sources to reduce future carbon emissions.

Do peak energy loads and peak GHG emissions correlate in buildings? Insights from emission duration curves and emission event duration curves analysis

This research proposes and applies emission duration curves (EDCs) and emission event duration curves (EEDCs) in a novel way for comprehensive analysis of greenhouse gas (GHG) emissions in correlation with building energy consumption. Examining a 2018 high-rise building in Ottawa, we found a moderate Pearson correlation of 0.3 between hourly energy and GHG emissions, despite a significant p-value. This indicates that peak energy loads and emissions peaks do not necessarily align, underscoring the need for a new operational strategy. The EDC and Load Duration Curve (LDC) patterns further accentuated these differences, suggesting that electrical emissions are more concentrated in specific periods compared to electrical loads. For our case study, 12.04% of yearly GHG emissions occurred within just 1% of the year, contrasting with only 2.14% of the annual energy use. The study also highlighted the potential of a demand response event through a simulated voluntary outage during peak emission intervals as a viable GHG mitigation strategy. Collectively, these insights stress the importance of a comprehensive perspective on building operations, their interactions with the grid, and the necessity for tailored sustainable building management strategies moving forward.

Life cycle greenhouse gas emission analysis of co-processing of algal bio-oil and vacuum gas oil in an existing refinery

The co-processing of algal bio-oil and vacuum gas oil (VGO) within existing refineries to generate gasoline and diesel represents a financially advantageous strategy for the integration of third-generation biofuels. Microalgae cultivation can be facilitated through the utilization of algal turf scrubbers (ATS) and open raceway ponds (ORP), with algal bio-oil extraction achievable via hydrothermal liquefaction (HTL) and fast pyrolysis (FP). Four distinct algal bio-oil production processes, namely ORP&HTL, ORP&FP, ATS&FP, and ATS&HTL, have been identified for the integration of algae cultivation and algal bio-oil production. To assess the global warming potential (GWP) of the five co-processing scenarios, the four algal bio-oils co-processed with VGO, along with pure VGO cracking, underwent evaluation utilizing the CML 2001 method. The investigation revealed that the ORP&HTL scenario exhibited the lowest GWP among the five scenarios. In the ORP scenarios, KNO3 and Ca(H2PO4)2·CaHPO4 were utilized as nitrogen (N) and phosphorus (P) sources during the algae production stage, resulting in a GWP 3.86 and 2.01 times higher than that observed in the ATS scenarios during this phase. Subsequent sensitivity analysis demonstrated that optimizing the reduction of GWP entails diminishing electricity and nutrient consumption within the algal production processes, alongside augmenting the proportion of algal bio-oil in the feed. This strategic approach effectively mitigates the GWP associated with the co-processing endeavor.

Uncertainty analysis of greenhouse gas emissions of monorail transit during the construction.

This paper examines the uncertainty of greenhouse gas (GHG) emissions during monorail construction. Firstly, a deterministic analysis is conducted. Subsequently, the obtained data are evaluated using the data quality indicator (DQI), and a Markov chain Monte Carlo (MCMC) simulation method is employed to assume different parameter distributions. The results of the deterministic calculation indicate that the calculated emissions per unit area of the station amount to 1.97 ton CO2e/m2, while the calculated emissions per unit section length reach 7.55 ton CO2e/m2. To simulate parameter distribution, we utilize a Beta distribution with good shape applicability. Furthermore, we establish scenarios involving system boundary reduction, low-emission factors, and reduced material and energy inputs in order to analyze scenario uncertainties. Regarding model uncertainty, this paper assumes that the material and energy quantity data conform to the normal, log-normal, uniform, and triangular distributions, respectively, subsequently analyzing the uncertainty distributions. This paper analyzes the GHG emission uncertainty evaluation of 16 monorail stations and sections during the construction period, which is divided into parameter, scenario, and model uncertainty. We provide a concrete framework for studying uncertainties related to GHG emissions at stations and sections during the monorail construction period. The scenario analysis results will help to make decisions about the choice of parameters, system boundaries, and other settings. It provides new guidance for emission reduction policies, such as reducing the use of steel-related products or using alternative environmentally friendly materials, considering emission reduction factors more comprehensively and setting emission reduction factors according to uniform distribution principle as far as possible.

Comparative analysis of Greenhouse Gas Emissions from Biological Wastewater Treatment Processes: A Case Study in Gyeongsangbuk-do, Korea

Objectives:This study compared greenhouse gas emissions from various biological treatment processes at wastewater treatment plants in City A, Gyeongsangbuk-do. Methods:Four wastewater treatment plants were selected by size and treatment process, and flow rate and water quality parameters from 2020 to 2022 were used. The amount of greenhouse gases such as methane, nitrous oxide, and carbon dioxide generated was calculated according to the IPCC and Ministry of Environment calculation formulas. Results and Discussion:Regardless of the biological wastewater treatment processes, the greenhouse gas emissions of all plants were higher according to the Ministry of Environment standards than the IPCC method. However, this may be because it was not applied to variables that are difficult to confirm, such as correction coefficients. Among biological treatment processes, the greenhouse gas emissions of A2O were higher than those of SBR.Conclusion:The results of this study can be used to calculate greenhouse gas emissions from biological wastewater treatment processes and prepare their reduction plans.

RURAL SUSTAINABILITY IN BULGARIA: MULTI-CRITERIA ANALYSIS

Sustainable development is essential for long-term evolution of the society as a whole, considering the future generation as well. It is a key concept of the 21st century reflecting the present and the future of humanity. Within the European Union, it is of primary interest and a fundamental goal. Currently, the European Green Deal serves as a strategic framework for the transition and policy development to accomplish this goal. It recognizes rural areas as important to contribute in terms of land use, biodiversity conservation, economic activity, and prosperity of society. Rural areas are important as a main source of supplies and resources for the society and as a space for living and working. The current challenges, such as economic crises, depopulation, and climate change, may limit their sustainable development. The active rural development policy and its growing role within the European policies supports the processes of adaptation and transformation towards the sustainability goals. Addressing these challenges requires a comprehensive approach as achieving sustainability requires considering the economic, social, and environmental dimensions of rural development. It means to consider a range of social, economic, and environmental factors and their interrelationships in order to identify and prioritize sustainable development options for rural areas. Therefore, the multiple criteria analysis of the various aspects of rural development, taking into account different sustainability indicators is a required precondition. This paper assesses rural areas sustainability in Bulgaria based on the multi-criteria analysis exploring the time-related changes of the available Sustainable Development Indicators and comparing them to the observed indicators at the European level. The findings indicate progress in some aspects (ecological based on the analysis of greenhouse gas and ammonia emissions from agriculture). The study also identified serious barriers in economic and social dimensions analysing the performance of rural economy, the developments in business structures, employment and unemployment rates, and the rural demography (population, migrations and at-risk-of-poverty rate). The paper concludes with recommendations for promoting sustainable development that enhance economic opportunities and improve social demography. Keywords: sustainable development, environmental sustainability, social sustainability, economic sustainability, sustainable development indicators JEL code: Q01, R51, O18

Quantifying and Comparing Greenhouse Gas Emissions in Monsoon Rice Production: A Comprehensive Analysis of Transplanting and Broadcasting Sowing Methods in Myanmar

Introduction Rice is a staple food, an economic crop, and the second-highest source of greenhouse gas (GHG) emissions in the agricultural sector in Myanmar. To develop the rice sector in a sustainable way, this study aimed to determine the comparative GHG emissions between the two major sowing methods used in monsoon rice production. Methods Next, comparative GHG emissions analysis was done by using the Student t-test. This study first quantified GHG emissions from land preparation to straw burning by using emission factors for agricultural inputs and the formulation, default values, and scaling factors of a carbon footprint calculator customized for rice products (CF-Rice). Results Soil and water management was the largest contributor among the management practices in monsoon rice production and accounted for 64.8% of the total GHG emissions. At 4,479.5 kg CO2 eq. ha-1, GHG emissions from the broadcasting (BC) method were significantly higher than those from the transplanting (TP) method. Conclusion Therefore, the TP method is a better sowing technique than the BC method for reducing GHG emissions without reducing grain yield.

Greenhouse gas emissions in Danish environmental assessments: a critical review

ABSTRACT Climate change is a key focus in society, and environmental assessments (EAs) are seen as key instruments to inform decision-makers about climate consequences of plans and projects. Previous research has, however, identified shortcomings of practice of assessing greenhouse gas (GHG) emissions and their significance, and this paper aims to unfold current practices with a focus on Denmark. From an initial set of 762 Danish EA reports published between 2017 and 2021, researchers scrutinized 102 of them to assess their handling of GHG emissions. The findings show that climate change mitigation receives continuous sparse attention and is only to a limited extent included in the scope of the EA. Moreover, analysis of GHG emissions only involves few phases in a life-cycle perspective, GHG emissions are seldomly deemed significant, and justifications provided are varied and frequently inadequate. The results contrast with the increasing focus in society on climate change as a pivotal concern across numerous societal activities. The repercussions of this current practice are discussed. Finally, a research agenda to support better practice is outlined.

Analysis of greenhouse gas emissions from the surface of the reservoir

The article examines the relationship between the release of greenhouse gases and the level of eutrophication and toxicity of a water body by monitoring the spatiotemporal level of eutrophication of surface waters of the Pavlovsk reservoir, and determines the eutrophication coefficient, which considers the combined influence of eutrophication and toxicity. The article is devoted to testing the developed method for determining the eutrophication coefficient of surface rivers. The laboratory experiment was carried out in accordance with the approved methodology for determining the toxicity of various water bodies and solutions of chemical substances PND F T 14.1: 2: 4.19-20131. The developed methodology was tested on water bodies experiencing the maximum impact of anthropogenic and technogenic factors. Mathematical processing of data on the content of climatically active gases obtained from field measurements was carried out. It is shown that the proposed method can be used to study the integral toxicity of not only surface and groundwater, but also wastewater. It can record the dynamics of their toxicity in space and time.

How to raise consumer awareness of the environmental impact of vehicle attributes? A big data analysis

The introduction of the Euro 7 emission standard is expected to significantly change the typology of the European passenger car. This study analyzes the environmental impact resulting from future trends in fleet composition and proposes an innovative vehicle classification system focused on raising consumer awareness of the importance of their choices with regard to key attributes such as body type, engine power and vehicle weight. A sensitivity analysis of the fleet's greenhouse gas emissions to deviations in their composition is carried out, considering the preferences expressed by the consumers in 2022 and the vehicle's specifications reported by the automotive industry on European digital platforms embodying Industry 4.0 principles. The findings show that internal combustion fleet emissions are expected to rise 0.30% per 1% increase in engine power and 0.44% to 0.69% per 1% increase in weight, according to the Worldwide Harmonised Light Vehicle Test Procedure (WLTP). The plug-in electric vehicle (PHEV) segment is the fastest growing in terms of market share. This trend will continue in the future, as this is the segment best suited to comply with the emissions targets imposed on manufacturers. Another relevant conclusion is that the environmental impact of PHEV vehicles is potentially very negative if the drivers' charging habits do not reflect the manufacturer's design intention. Thus, the development of consumer environmental awareness tools is urgent. This is the study's main motivation: to develop a tool in the scope of the Industry 4.0 while promoting the emergent concept of Industry 5.0, sustainability based and human-centered.

Time Series Analysis of Greenhouse Gas Emission Based on ARIMA and LSTM

Greenhouse gas emissions have become a topic of great concern, and research on the prediction of greenhouse gas emissions is urgently needed. In this paper, based on the GHG emission data from 1990-2018, it applied ARIMA model and LSTM model to predict future GHG emissions, and evaluated their prediction performance using MAE. According to the analysis, the results show that the ARIMA model can more accurately capture the trend and seasonal characteristics in the greenhouse gas emission data, and generate prediction results that match the actual observations. Moreover, this study confirmed the effectiveness and feasibility of ARIMA and LSTM models in greenhouse gas emission prediction. At the same time, one must also be aware that greenhouse gas emission forecasts still face limitations such as data reliability, model assumptions, and policy uncertainties. Future research can further improve model performance and explore more comprehensive predictive models to improve accuracy. Overall, these results shed light on guiding further exploration of gas emission analysis.

Evaluation of the GRAMM/GRAL model for high-resolution wind fields in Heidelberg, Germany

Independent verification of mitigation efforts for climate and air quality action in cities relies on inferring emissions from atmospheric concentration measurements. As emissions are dispersed in the atmosphere before they reach an instrument, the quantitative estimation of emissions requires an understanding of the atmospheric transport and associated uncertainties. In this study, we analyse the catalogue of steady-state flow fields generated by the Graz Mesoscale Model (GRAMM) coupled to the Graz Lagrangian Model (GRAL) for an entire year in Heidelberg, Germany. We use a loss function for the wind field selection, which assigns a best-matching catalogue entry to any given hour by exploiting observation data. We introduce a new loss function which finds an optimal balance between differences in wind speed and wind direction. We evaluate the performance of the model based on 15 meteorological measurement sites, of which 14 are in the inner high-resolution and building-resolving GRAL domain (12.5 km × 12.5 km, 10 m resolution). Performance metrics include mean bias (MB) and root mean square errors (RMSEs) of simulated and observed wind speed and wind direction for all individual stations. On average, we find a mean underestimation of wind speed of 0.14 ms−1 corresponding to about 7 % of the mean wind speed and a mean RMSE of 1.03 ms−1. For wind direction, a mean overall bias smaller than 1° is achieved, but individual stations show larger biases (mean absolute bias: 37°), especially at stations where wind speeds are low on average. Evaluation benchmarks for mean biases of wind direction and wind speed of mesoscale models provided by the European Environmental Agency (EEA) are met at 11 and 14 out of 15 stations at low measurement heights, respectively. Recently suggested extended benchmarks for complex terrain are met at almost all stations. Additionally, for the first time, we analyse the model's ability to simulate the vertical wind profile and we analyse the benefit of implementing a wind profile measurement into the process. We find that the model does not fully capture the vertical profile in our setting. We further study the required measurement network size and find that a high number (> 6) of meteorological stations improves the selection of flow fields over the entire GRAL domain substantially. The conducted comprehensive analysis of the wind fields in the GRAL domain are the basis for detailed quantitative analysis of greenhouse gas and air pollutant emissions using the GRAMM/GRAL modelling framework.

Comprehensive assessment of the carbon neutrality actions from the automotive sector

AbstractThe aim of this paper is to analyse and demonstrate the carbon neutrality actions of a special facility in the context of the automotive sector. In order to analyse the emissions, a carbon simulation model is developed. Offsetting options are also overviewed in a systematic way. We provide a methodology for a systematic analysis of greenhouse gas (GHG) emissions and offsetting opportunities of an automotive facility. We compile an inventory of the carbon emissions, identify offsetting options and prepare a cost–benefit analysis of the mitigation actions. The relevance of United Nations Sustainable Development Goals (SDGs) is also assessed. We examine the GHG emissions of an automotive proving ground, ZalaZone in Zalaegerszeg, Hungary, as a case study. Four scenarios with various shares of decarbonisation options have been proposed to achieve the vision of net zero GHG emissions. It was found that net zero emission is achievable. The CBA concluded that the net present value is negative; however, there are significant external benefits. It was revealed that the operation of the facility contributes to multiple SDGs and provides different pathways to carbon neutrality.

Positive climate and health impacts from upscaled use of heat pumps and solar panels in technology packages in EU-27 by 2050

Achieving the European Union's (EU-27) climate targets for 2050 requires moving away from fossil fuels, for which the necessary heating and cooling (H&C) technologies are mostly already available in the domestic sector. These H&C technologies, such as heat pumps and solar panels (photovoltaic, thermal and hybrid photovoltaic-thermal), reduce air pollution and thus have positive climate and health effects, but require the increased use of limited materials. Although the integration of such technologies into technology packages (TPs) further increases energy efficiency, monetary values of the climate and health effects of these TPs have not been assessed from a life cycle perspective including the production phase. Therefore, we monetize the full impacts of adopting such innovative H&C TPs in refurbished and new residential and tertiary buildings in the EU-27. With that aim, we combine an analysis of air pollutants and greenhouse gas emissions from the life cycle assessment of the TPs with long-term scenarios of H&C demand, to generate country-specific emissions (2030 and 2050). Accordingly, climate and health impacts are estimated using the Greenhouse gas and Air pollution Interactions and Synergies and Alpha RiskPoll models. The total estimated monetary benefits of TP implementation in the EU-27, including its health effects (dominated by reduced premature mortality) and climate impacts, are approximately 15–49 billion €2015 in 2030 and 34–123 billion €2015 in 2050. Furthermore, the benefits are 13 %–15 % higher if the health effects on all European countries are considered. These substantial benefits can justify the broader deployment of TP technologies in the future.

From garbage to global warming: a bibliometric analysis of greenhouse gas emissions from municipal solid waste and its relationship with climate change

From garbage to global warming: a bibliometric analysis of greenhouse gas emissions from municipal solid waste and its relationship with climate change

RETRACTED: An innovative simulation-based methodology for evaluating cooling strategies in climate change-induced overheating

As global climate change progresses the built environment grapples with the increasing challenge of overheating. In response to these challenges, this study introduces an innovative simulation-based methodology aimed at enhancing the resilience and sustainability of cooling strategies. The proposed methodology utilizes weather and building data characterization, user clothing behavior, and cooling strategy selection. The methodology relies on three main indicators: Indoor Overheating Degree (IOD), Ambient Warmness Degree (AWD), and Climate Change Overheating Resistivity (CCOR). It also considers sub-indexes like analysis of greenhouse gas emissions, energy consumption, Exceedance Hours, and the average Predicted Percentage of Dissatisfaction. This comprehensive approach allows for a multi-zonal assessment of indoor overheating risk and resilience to climate change, to validate the methodology ‘s effectiveness, we conducted a thorough comparison, focusing on Packaged Terminal Heat Pumps (PTHP) (C01) and Fan Coil Units (FCU) (C02) in six selected reference cities with different climates. The case study employs a shoebox model to depict a double-zone office and administration building. In general, C01 demonstrates greater resistance to climate change-induced overheating compared to C02. The highest CCOR value, 58.16, is found in C01 in Vienna, while the lowest CCOR value, 12.7, is observed in C02 in Montreal, indicating the lowest resistance. Furthermore, this study underscores the pivotal importance of meticulously evaluating the susceptibility of cold cities to the imminent impacts of climate change and the urgency of implementing proactive strategies to bolster their resilience.

Carbon footprint of a conventional wastewater treatment plant: An analysis of water-energy nexus from life cycle perspective for emission reduction

Reducing greenhouse gas (GHG) emissions is of far-reaching implications for the sustainable development of a conventional domestic wastewater treatment plant (WWTP). GHG emissions of the WWTP in different working loads were monitored to quantify the influence of critical processes on GHG emissions and shed light on the relations between direct and indirect GHG emissions with the water-energy nexus. The life cycle carbon footprint of the WWTP was assessed to find the most critical impact factor. A conceptual model of direct and indirect GHG emissions was established based on the water-energy nexus and life cycle assessment (LCA). Results showed that direct GHG emissions were highest in medium working load in May. While high indirect GHG emissions were in February, with the highest working load. Methane (CH4) emission rates, from 44.39 ± 42.49 to 4.94 ± 2.29 kg CO2e·d−1, decreased along the treatment processes due to oxidation. Dissolved CH4 in wastewater mainly came from the influent that was 0.08 ± 0.04 kg CH4·d−1. The increase of nitrous oxide (N2O) emissions and dissolved N2O occurred in the secondary treatment stage and was affected by the C/N ratio. The operation and maintenance phase had the most significant carbon footprint due to 86.4% of indirect GHG emissions from electricity usage through LCA. Electricity usage and glucose dosing were significantly correlated with N2O emissions but had no contribution to CH4 emissions. The conceptual model qualitatively demonstrated that direct and indirect GHG emissions reduced as electricity usage decreased based on the water-energy nexus. This study provided new insight into the analysis of GHG emissions from WWTPs.

Multi-information integration-based life cycle analysis of greenhouse gas emissions for prefabricated construction: A case study of Shenzhen

Prefabricated buildings have gained significant attention in the global construction sector due to their potential to reduce construction time, improve process efficiency, save resources, and mitigate pollution. It is crucial to quantify the greenhouse gas (GHG) emissions associated with prefabrication technologies for sustainable development. However, there is a lack of comprehensive research utilizing advanced technological tools to examine and visualize GHG emissions in prefabrication. To address this gap, this study employed a multi-information method that combines Building Information Modeling (BIM) and Geographic Information System (GIS) with a life cycle assessment (LCA) approach to analyze and calculate the spatial distribution of GHG emissions from prefabricated components and buildings during the production, transportation, and construction stages in China. The results indicate the following: (1) GHG emissions per cubic meter for the prefabricated exterior wall, balcony, and stair are 1080.77 kgCO2eq/m3, 867.84 kgCO2eq/m3, and 1902.63 kgCO2eq/m3, respectively, with an overall average of 1138.58 kgCO2eq/m3 for prefabricated components. (2) The production phase is responsible for the largest share of GHG emissions, accounting for 96.11%, while the transportation and construction phases contribute 3.30% and 0.59% of the total emissions, respectively. (3) The selection of prefabricated construction can lead to a 31.62% reduction in total GHG emissions per square meter, with emissions of 269.16 kgCO2eq/m2, compared to traditional construction with emissions of 393.63 kgCO2eq/m2. The study contributes to the knowledge body by providing a systematic method for calculating GHG emissions and offering traceability and visibility of GHG emissions for prefabricated components and prefabricated buildings. These findings can serve as practical references for future research to achieve the construction industry's green and low-carbon goals.

Analysis of Economic and Environmental Feasibility of Using Biodiesel as an Alternative Fuel for Fishing Vessels in Indonesia

This research aims to analyze the economic and environmental feasibility of using biodiesel as an alternative fuel for fishing vessels in Indonesia. This research uses cost-benefit analysis, greenhouse gas emission analysis, and sensitivity analysis methods to evaluate the impact of biodiesel use on economic and environmental aspects. The results show that the use of biodiesel as an alternative fuel for fishing vessels in Indonesia is economically feasible, as it can save fuel costs, reduce dependence on imported diesel, and increase the added value of fishery products. The use of biodiesel is also environmentally feasible, as it can reduce energy consumption, greenhouse gas emissions, and other pollutant emissions generated by fishing vessels. The economic and environmental feasibility of using biodiesel as an alternative fuel for fishing vessels in Indonesia is quite stable and not sensitive to changes in conditions that may occur in the future. This research provides recommendations for the government, fishery industry, and society to support the development and implementation of biodiesel as an environmentally friendly alternative fuel for fishing vessels in Indonesia.