Minimum Emission Research Articles

Sustainability in Technology and Green IT

For the modern acceleration pace of tech development, especially the sustainability of green IT, significantly relates to it. Green IT refers to the use of resources at the computer machine level in an environmentally friendly way for the minimization of energy usage and carbon emissions as well as adverse impacts on the environment caused by IT-related activities [Murugesan, 2008]. The rising digital services also contribute to increased energy consumption from data center and cloud services, thus emitting more greenhouse gases [Baliga et al., 2011]. The paper deals with renewable energy in IT systems, the recycling of e-waste, sustainable design of a data center, and how computing can be made more energy-efficient [Hanne & Falk, 2010; Khan & Qureshi, 2018]. The study identifies whether practical applications and examples of Green IT solutions show benefits and challenges in real life. Industrial case studies. The study found that despite so much scope for Green IT to reduce the negativity in most developments, Environmental Impact of the IT sector: All these issues, such as high cost, scalability and regulatory, should be reduced [Murugesan, 2008; Berkhout, 2014]. In order to promote sustainability across IT industries, further technological developments and global policy reforms will be essential [Murugesan, 2008; Hanne & Falk, 2010; Khan & Qureshi, 2018].

Numerical Simulation Study on the Stable Combustion of a 660 MW Supercritical Unit Boiler at Ultra-Low Load

To investigate the safe, stable, and economically viable operation of a boiler under ultra-low-load conditions during the deep peaking process of coal-fired units, a numerical simulation study was conducted on a 660 MW front- and rear-wall hedge cyclone burner boiler. The current research on low load conditions is limited to achieving stable combustion by adjusting the operating parameters, and few effective boiler operating parameter predictions are given for very low-load conditions, i.e., below 20%. Various burner operation modes under ultra-low load conditions were analyzed using computational fluid dynamics (CFDs) methods; this operation was successfully tested with six types of pulverized coal combustion in this paper, and fitting models for outlet flue gas temperature and NOx emissions were derived based on the combustion characteristics of different types of pulverized coal. The results indicate that under 20% ultra-low-load conditions, the use of lower burners leads to a uniform temperature distribution within the furnace, achieving a minimum NOx emission of 112 ppm and a flue gas temperature of 743 K. Coal type 3, with the highest carbon content and a calorific value of 22,440 kJ/kg, has the highest average section temperature of 1435.76 K. In contrast, coal type 1 has a higher nitrogen content, with a maximum cross-sectional average NOx concentration of 865.90 ppm and an exit NOx emission concentration of 800 ppm. The overall lower NOx emissions of coal type 3 are primarily attributed to its reduced nitrogen content and increased oxygen content, which enhance pulverized coal combustion and suppress NOx formation. The fitting models accurately capture the influence of pulverized coal composition on outlet flue gas temperature and NOx emissions. This control strategy can be extended to the stable combustion of many kinds of coal. For validation, the fitting error bar for the predicted outlet flue gas temperature based on the elemental composition of coal type 6 was 8.09%, whereas the fitting error bar for the outlet NOx emissions was only 1.45%.

Ozone management in Colorado: Why aren’t we there yet?

ABSTRACT Since 2004, the state of Colorado in the United States of America has created multiple nonattainment State Implementation Plans (SIPs) that are supposed to comprise air pollution mitigation actions, that have so far been unsuccessful at ensuring Front Range Communities have reduced ozone levels to below the United States Environmental Protection Agency (EPA) standards. By interviewing eight stakeholders and decision-makers involved in ozone SIP rulemaking and drawing on secondary literature, this paper examines shortcomings in the SIP process in Colorado. We found that ozone precursor measurement and the modeling of attainment could be improved by better factoring in uncertainties in emissions inventories and conducting appropriate sensitivity analyses that would require more investment of state staff time and resources. Structural issues with the way the process is organized in Colorado limit optimum overlap between state: Air Pollution Control Division (APCD) and quasi-state: Regional Air Quality Council (RAQC) agencies during the SIP process. Specifically, although the RAQC is currently charged with developing and submitting SIPs to the State for approval, it does not have the power to implement control strategies for several key sources and therefore does not have the authority to propose key policies to be included in the SIP. In recent years, Colorado SIPs have largely focused on the bare minimum emissions controls to demonstrate attainment via modeling. Interviewees recommend that state political leaders take more of a leadership role to lower ground-level ozone levels and bring the Denver Metropolitan Area/North Front Range back into attainment with EPA standards. Implications We evaluate why the State Implementation Plan (SIP) process has failed to achieve the attainment of the ozone standards in the Denver Metropolitan and North Front Range Area. Specifically, through interviewing several experts we identified several problems, namely: 1) errors in emissions inventories and modeling of ozone levels that have resulted in incorrect determinations that the ozone standards would be met with proposed emissions controls, and 2) structural problems in the way the SIP process is organized in Colorado, and the lack of political leadership.

Mechanical carbon emission assessment during prefabricated building deconstruction based on BIM and multi-objective optimization

Machinery operation is a major source of carbon emissions in building deconstruction. Early intervention through Design for Deconstruction (DfD) is crucial for emission reduction, yet the factors influencing these emissions are underexplored. This study integrates parametric BIM with multi-objective optimization (MOO) to assess mechanical carbon emissions in deconstruction. Using the Octopus solver in Grasshopper for Rhino, the study analyzes independent variables—possible working hours (PWH), vertical speed (VS), and horizontal speed (HS)—and dependent variables—minimum mechanical carbon emissions (MCE (min)), minimum deconstruction period (DP (min)), and maximum working efficiency (WE (max)). A lightweight steel roof truss structure is analyzed, comparing real-world deconstruction with optimized DfD schemes. Sensitivity analysis for BIM-MOO optimized results reveal that: (1) Adjusting PWH, VS, and HS significantly affects WE and DP, though with limited impact on carbon emissions; (2) VS influences WE and DP more than HS; (3) Limiting DP is essential for balancing WE, DP, and MCE, with WE adjusted to 20–60% and modifications to PWH and VS achieving balanced management. This study underscores the importance of early design and real-time adjustments for efficient, low-emission deconstruction, supporting the advancement of green building practices.

Durability and hardened characteristics of cement mortar incorporating waste plastic and Polypropylene exposed to MgSO4 attack

Annual waste plastic disposal has grown, harming nature. Utilising this waste in concrete production may help preserve building resources. This study tested cement mortar with polyvinyl chloride (PVC) and polypropylene (PP) substituted for sand aggregate at 0, 5, 10, 15, and 20 %. The samples were nevertheless exposed to a 10 % and 20 % MgSO4 solution for a month. The properties of both fresh and hardened materials under these circumstances have been evaluated and contrasted with those evaluated under typical circumstances. For mixes including PP and PVC, the flow diameter increased. The rounded plastic particles provided fewer contact surfaces and less friction among mixtures, which reduced water consumption and improved workability, leading to an increase in slump flow. As the amount of plastic aggregate increases, the compressive strength decreased. Moreover, this pattern might be explained by the weakening of the bond between the surfaces of the plastic aggregate and cement paste. The hydration of cement may also be hampered by the hydrophobic properties of plastic aggregate. Like compressive strength, the splitting tensile strength decreased as the replacement level of plastic ratio increased regardless of its type under all conditions (normal and exposing to MgSO4). PP and PVC fine aggregate in mortar increases sorptivity under all situations. Following screening, those circumstances and PVC have the most impact on compressive strength. increasing PVC and PP at 10 % for each of them leads to lower values of compressive and tensile strength. An optimization process was implemented to determine the optimum value of PVC, PP, and MgSO4. It shows that using PVC of 3.9 %, PP of 10.1 %, and MgSO4 of 19.59 % leads to maximum compressive and tensile strength with the minimum cost and CO2 emissions.

Offline and Online Exergy-Based Strategies for Hybrid Electric Vehicles

Abstract Exergy-based control strategies for ground hybrid electric vehicles (HEVs) enable to pursue unconventional optimization goals that are inaccessible when standard energy-based modeling frameworks based on fuel consumption minimization are used. In this work, we formulate and solve offline and online exergy-based optimization strategies for military HEVs aimed at the minimization of genset exergy destruction and thermal emissions to increase vehicle efficiency and minimize the risk of thermal imaging detection, respectively. We refer to the offline version of these strategies as exergy minimization strategies (ExMSs). Adaptive ExMSs (A-ExMSs) are then formulated for online implementation. Moreover, charge increasing (CI) ExMSs and A-ExMSs are developed to charge the battery as much as possible during a driving mission that is followed by a silent watch phase. To assess the performance of the proposed strategies, the results obtained by the ExMSs and A-ExMSs are compared to the benchmark solutions obtained by Dynamic Programming.

Numerical study on carbon emissions and economics of a high temperature heat pump system for an industrial process

Research to achieve net-zero is actively being carried out. In industrial processes, large amounts of carbon are emitted to product thermal energy, and there is a growing interest in electrification technologies to reduce this. While electric heaters and heat pumps are representative technologies for electrification, research to determine which technologies can economically contribute to carbon reduction is necessary. In this study, transient model for a heat pump and thermal energy storage (TES) was developed, and the CO2 emissions and economic feasibility were analyzed. When coupled with photovoltaic power and battery energy storage (BESS), it was found that the heat pump can reduce CO2 emissions more economically than electric heater. Transient analysis was performed for the case of coupling TES with heat pump instead of BESS and it was found that CO2 emissions vary from 276 to 231 g/kWhth with and without the TES, respectively. When combining the heat pump and photovoltaic system with TES or BESS, the nominal levelized cost of heat to reach the same level of CO2 emissions is 11.6 % higher for the BESS-coupled system. Up to certain level of CO2 emissions, the TES-coupled system is economically viable, but minimum emissions can be achieved with the BESS-coupled system.

Carbon Footprint Optimization with Data Resolution Conversion via Kalman Filter for Smart Energy Hub

The severe climate changes due to global warming pushed the world to strive to reduce carbon emissions. And transitioning to renewable energy sources is essential for achieving sustainability and combating climate change. This study aims to minimize the carbon emissions for a proposed smart energy hub. This paper prioritizes the minimization of carbon emissions, considering the minimization of operational running costs, and the maximization of profit. In this paper, two optimization scenarios were studied to compare the results. In the first scenario, the minimization of carbon emissions was achieved. In the second scenario, the minimization of running costs and the maximization of profit from the hub assets were studied. The proposed model was designed in MATLAB. Then, the results were verified by CPLEX and validated by RTDS. The multi-objective model was presented to obtain the optimal operation. The mitigation of data uncertainty was achieved by applying the Kalman filter. In this work, a novel method was proposed for the estimation of the quarter-hour resolution data from the hourly ones via the Kalman filter rather than by applying the classic polynomial interpolation methods.

Multi-objective model for designing hydrogen refueling station powered using on-grid photovoltaic-wind system

This study formulated a multi-objective model to size a sustainable hydrogen refueling station energized by integrated Photovoltaic-wind system connected to grid. The model takes into account practical constraints alongside three objective functions: maximization of renewable energy fraction, minimization of overall costs, and minimization of greenhouse gas emissions. An exact algorithm is employed to obtain the best solution, and a multi-criteria decision-making approach is utilized to choose the optimal solution from Pareto-optimal solutions. The performance of the model is validated on a hydrogen station that fulfills the daily hydrogen requirements for a fleet of 100 taxis in Tabuk city, Saudi Arabia. Different scenarios are analyzed to demonstrate the trade-offs between the three objectives. For example, the first configuration consists of 6527 photovoltaic panels and 296 wind turbines with capacities of 2.219 MW and 0.888 MW, respectively. The energy deficit is covered by the grid and the excess is exported to the grid. The economic assessment of this configuration reveals a hydrogen cost of 7.53 $/kg. Additionally, this study considered a scenario of powering the station using off-grid Photovoltaic-wind battery system. This analysis explores these differences, focusing on cost-effectiveness and environmental implications of using renewable energy for hydrogen production.

An innovative quick-decision strategy for evaluating the applicability of extractive distillation process with a preconcentration column in separating high-concentration organic waste liquid

In the face of the high energy consumption challenge in separating high-concentration organic waste liquid through extractive distillation (ED), the concept of preconcentration provides a new strategic direction. Therefore, it has become crucial to determine the suitability of the ED process with a preconcentration column for processing such complex mixture. Taking this into consideration, the study proposes an innovative quick-decision method that utilizes thermodynamic analysis of ternary phase diagram to determine the ratio of theoretical product flowrate at the bottom of the preconcentration column to the feed flowrate, which serves as the basis for deciding whether to choose the ED process with a preconcentration column for handling such separation tasks. Three azeotropic systems with different thermodynamic characteristics are chosen as case studies: cyclohexane/ethyl acetate/ethanol (Case 1), ethyl acetate/ethanol/water (Case 2), and n-hexane/ethyl acetate/acetonitrile (Case 3). The task of separating the above three systems is accomplished through the application of both three-column extractive distillation configuration (TCED), and four-column extractive distillation configuration (FCED). The objective functions for multi-objective optimization of all separation configurations include the minimum total annual cost (TAC), the minimum entropy generation and the minimum CO2 emissions. The research findings indicate that when the ratio of theoretical product flowrate at the bottom of the preconcentration column to the feed flowrate is not less than 0.56, or when there is a significant concentration difference among the components in the feed stream, the FCED configuration exhibits clear advantages over the TCED configuration in terms of economic, environmental, and thermodynamic aspects.

Lower-Carbon Hydrogen Production from Wastewater: A Comprehensive Review

Hydrogen has the capability of being a potential energy carrier and providing a long-term solution for sustainable, lower-carbon, and ecologically benign fuel supply. Because lower-carbon hydrogen is widely used in chemical synthesis, it is regarded as a fuel with no emissions for transportation. This review paper offers a novel technique for producing hydrogen using wastewater in a sustainable manner. The many techniques for producing hydrogen with reduced carbon emissions from wastewater are recognized and examined in detail, taking into account the available prospects, significant obstacles, and potential future paths. A comparison of the assessment showed that water electrolysis and dark fermentation technologies are the most effective methods for hydrogen generation from wastewater, with microbial electrolysis and photofermentation. Thus, the incorporation of systems that are simultaneously producing lower-carbon hydrogen and meant for wastewater treatment is important for the minimization of emissions from greenhouse gases and recovering the energy utilized in the treatment of wastewater.

Cofiring of hydrogen and pulverized coal in rotary kilns using one integrated burner

The grate-kiln process for iron-ore pellet induration utilizes pulverized coal fired burners. In a developed infrastructure for H2, it might be desirable to heat the existing rotary kilns with renewably produced H2. Technical challenges of H2 heating of grate-kilns include high emissions of NOX and maintaining sufficient heat transfer to the pellet bed. This article examined cofiring (70% coal/30% H2) in 130 kW experiments using two different integrated burner concepts. Compared to pure coal combustion, cofiring creates a more intense, smaller flame with earlier ignition and less fluctuations. The process temperature and heat transfer are enhanced in the beginning of the kiln. The co-fired flames emit 32% and 78% less NOX emissions compared to pure coal and H2 combustion, respectively. We can affect the combustion behavior and NOX emissions by the burner design. H2/coal cofiring using integrated burners is probably an attractive solution for emission minimization in rotary kilns.

Scheduling and assessment of multi-area virtual power plant including flexible resources using swarm intelligence technique

A virtual power plant (VPP) makes the distributed energy resources (DERs) visible to support grid services, promoting clean energy use by offering an alternative to reduce reliance on conventional sources. This paper proposes optimized operation and scheduling of VPP by forming a group of flexible resources that includes renewables i.e., solar, wind power, fuel cell, and co-generation units along with storage facilities to form a holistic network in a multi-area interconnected system framework. Initially, the scheduling is performed for a single area system in which a comparison is made with the available work relevant to the proposed formulation. In addition, the scheduling is further extended to the proposed multi-area based virtual power plant (MAVPP) performed on a day-ahead (DA) basis and the target objective(s) i.e., net profit and emission are optimized. Furthermore, a recently developed marine predator optimization algorithm (MPOA) is employed to solve the proposed problem formulation and the results are compared and discussed extensively with conventional techniques. Also, the analysis pertaining to MAVPP is carried out which is beneficial in terms of economic and environmental perspective. The result reveals that the maximum value of net profit for MAVPP is converging to an optimum value of 59,351.88 $ followed by the attained value of minimum emission of 51,700.73 Kg by consuming an elapsed time of 92.96 and 104.76 s., respectively in 200 iterations. The outcomes are promising and upon comparison with the available literature work, the superiority of the selected technique is evident in terms of computational time, improvement of net profit and reduction in emission followed by the ease of convergence behaviour in fewer iterations.

Mild one-pot production of glycerol carbonate from CO2 with separation from ionic liquid catalyst

Carbon capture and utilization stands as way forward in the minimization of CO2 emissions. It complements the search for clean and effective energy, as it is challenging to achieve zero to negative CO2 net emissions. The glycerol carbonate product opens a new strategy based on a double-residue approach (glycerol and CO2) to contribute, together with ionic liquids (ILs), drafting a new one-pot concept (intensified three phase reactor) at mild conditions and using homogeneous catalysts. In this work, the catalytic activity of [P666,14][Br] in the cycloaddition of CO2 to glycidol has been demonstrated to be highly effective under mild conditions of 45 °C and 5 bar. In addition, liquid–liquid extraction approach is found to be an efficient separation strategy for carbonate product and IL catalyst. 1-Decanol (DOH) is selected as efficient extracting solvent, due to its almost complete immiscibility with glycerol carbonate, as well as the high distribution ratio of the IL catalyst in DOH rich phase. It implies an easy product separation and, simultaneously, an easy catalyst recovery. A preliminary kinetic validation of the three-phase reactor performance has been properly described, enabling the intensified concept. Finally, combining COSMO/Aspen simulation and life cycle assessment (LCA) methodologies, low energy consumption (avoiding heating) and low GWP scenarios for the CO2 conversion process have been concluded. This work enables a new concept together with concluding the path to developing this CCU technology in the search of zero to negative CO2 emissions to sustainably capture and convert CO2 into value-added products.

Experimental Design, Statistical Analysis, and Modeling of the Reduction in Methane Emissions from Dam Lake Treatment Using Agro-Industrial Biochar: A New Methane Capture Index

This study aimed to reduce the methane (CH4) emissions originating from dam lake treatment using malt dust-derived biochar, which is an agro-industrial byproduct of the brewery industry. Optimum operating and water quality parameters for CH4 reduction were determined using statistical analyses based on the Box–Behnken design method. Also, a Monte Carlo simulation was performed to determine the correlation between CH4 emissions and operating parameters. According to the simulation, dissolved oxygen (DO) and the oxidation–reduction potential (ORP) had the highest correlation with CH4 emissions, with values of 92.03% and 94.57%, respectively. According to the Box–Behnken design methodology, the optimum operating parameters were 4 mg/L of dissolved oxygen, −359 mV of ORP, and 7.5 pH for the minimum CH4 emissions. There was a reported reduction of up to 19.4% in CH4 emissions for the dam lake treatment using malt dust-derived biochar. Finally, a new methane capture index, based on the biochar application (MCI), was developed and validated. The largest methane capture capacity was related to the malt dust-derived biochar produced at the lowest temperature (M1).

Strategic decision-making for sustainable production and distribution in automotive industry: a machine learning enabled dynamic multi-objective optimisation

ABSTRACT Over the last decade, numerous researchers have disclosed that major automotive companies do not conform to regulatory or societal expectations regarding their environmental and social performances. This paper explores the dynamic capabilities of production distribution within the sustainability practices of automotive industries. It offers insights to better grasp and articulate the environmental, economic, and social dimensions of sustainable supply chains. The research framework encloses all supply chain phases, from raw material sourcing to retailing finished products. Three conflicting objective functions are identified: social advantages maximisation, cost minimisation, and emission minimisation. Specifically, the study tackles a dynamic multi-objective optimisation model where each automobile type faces a series of dynamic demands. The dynamic nature of the problem poses significant challenges to conventional evolutionary algorithms for detecting the optimal solutions over time. Therefore, we introduce an interconnected prediction-based dynamic non-dominated sorting algorithm (ICP-DNSGA-II). Finally, extensive computational experiments are conducted to assess the effectiveness of this holistic approach. The findings offer valuable insights for automotive industry stakeholders and policymakers, illustrating its potential to enhance operational efficiency and sustainability performance across the supply chain. Most importantly, this paper proposes an automated decision-making approach to generate optimal solutions with dynamic changes in market demands.

Carbon footprint in choosing the best sustainable mode of intercity passenger transport

The carbon footprint, which measures greenhouse gas emissions, is a good environmental indicator for choosing the best sustainable mode of transportation. The available emission factors depend heavily on the calculation methodology and are hardly comparable. The minimum and maximum scenarios are one way of making the results comparable. The best sustainable passenger transport modes between Rijeka and Split were investigated and compared by calculating the minimum and maximum available emission factors. The study aims to select the best sustainable mode of transport on the chosen route and to support the decision-making process regarding the electrification of the Lika railroad, which partially connects the two cities. In the minimum scenario, ferry transport without vehicles was the best choice when the transportation time factor was not relevant, and electric rail transport when it was. In the maximum scenario, the electric train and the ferry with vehicles were equally good choices. Road transportation between cities was not competitive at all. The comparison of the carbon footprint based on minimum and maximum scenarios gives a clear insight into the ratio of greenhouse gas emissions from vehicles in passenger transport. It supports the electrification of the Lika railroad as the best sustainable transport solution on the route studied.

Life cycle-based multi-objective model for optimal gaseous fuel generation and portfolio allocation in gas grids: A strategic decarbonization

Biomethane and hydrogen are acknowledged as transformative opportunities for decarbonizing the conventional gas grid. Essential to this transformation is the modeling of the gaseous fuel supply chain, particularly with hydrogen and biomethane, offering crucial insights for decision-makers. This study introduces a life cycle thinking-based multi-objective optimization model for the integrated design of biomethane and hydrogen gaseous fuel supply chain networks. The model determines optimal resource allocation for the production of the two fuels, integrating them into the conventional gas network. Moreover, it allocates conventional natural gas, biomethane, and hydrogen optimally across building, industry, and transport sectors, considering the life cycle environmental and economic performance of fuel integration paths. Objective functions include minimization of life cycle emissions and levelized cost of energy while maximizing revenue from fuel sales. Integrating life cycle assessment and cost analysis tools, the optimization model quantifies emissions and life cycle costs for biomethane and hydrogen paths. Results identify Pareto-optimal fuel production paths and portfolios, revealing that integrating the alternative fuels into the current gas grid can significantly reduce emissions (up to 250 tonCO2eq/year) and generate substantial carbon tax savings (up to $16,250/year). This model is useful for gaseous fuel industry stakeholders, offering a comprehensive view of supply chain costs and detailed insights into emission benefits when integrating alternative fuels into existing gas networks.

Experimental and Numerical Simulation Research on Different Shapes of Flame-Stabilizing Baffles in the Furnace

The use of fully premixed combustion in small gas boilers can improve denitrification efficiency. On the basis of fully premixed combustion, adding flame stabilizers inside the boiler can further reduce production of oxides of nitrogen. Four types of flame-stabilizing baffles were added at a certain position inside the furnace after the fully premixed burner. Experiments were conducted separately on the Noporous baffle, and numerical calculations were performed for 36 operating conditions of the four baffles. The experimental results and numerical calculations indicate that under experimental conditions, NOx emissions were all below 40 mg/m3, and the net heat efficiency of the boiler was above 80%. Under a maximum firing rate, CO emissions are below 20 ppm, and the minimum error between the calculated and experimental values is 2.2%. The calculation error of CO emissions under various working conditions does not exceed 6.8%, indicating that the impact of different-shaped baffles on CO emissions is relatively small. When installing a Nonporous baffle, the error between the experimental and calculated exhaust temperature values under minimum firing rates is 6.6%, the error between the calculated and measured values under middle firing conditions is 2.9%, and the error between the calculated and measured values under maximum firing rate conditions is 3.0%. Among the four different partition conditions, the exhaust temperature of the Nonporous baffle is the lowest. Under the same excess air coefficient, the pressure in the furnace for the middle and maximum firing rate is higher than that of the minimum firing rate, and the experimental values are in good agreement with the calculated values. When installing the Strip baffle, the calculated CO2 emission is the lowest. The experimental results show that the NOx in the flue gas inside the furnace is mainly NO, and the NO content exceeds 75%, reaching a maximum of 85%. The experimental results show that the minimum NOx emission value is 26.9 mg/m3. The error between the measured and calculated NOx values when installing a Nonporous baffle is 20.4%. All of the above indicate that installing a flame-stabilizing baffle at an appropriate position in the furnace can further reduce NOx emissions, and the optimization amplitude is related to the shape of the baffle.

Development and Characterization of Basalt Fiber-Reinforced Green Concrete Utilizing Coconut Shell Aggregates

Lightweight aggregate concrete (LWAC) is gaining interest due to its reduced weight, high strength, and durability while being cost-effective. This research proposes a method to design an LWAC by integrating coconut shell (CS) as coarse lightweight aggregate and a high volume of wet-grinded ultrafine ground granulated blast furnace slag (UGGBS). To optimize the mix design of LWAC, a particle packing model was employed. A comparative analysis was conducted between normal-weight concrete (M40) and the optimized LWAC reinforced with basalt fibers (BF). The parameters analyzed include CO2 emissions, density, surface crack conditions, water absorption and porosity, sorptivity, and compressive and flexural strength. The optimal design was determined using the packing density method. Also, the impact of BF was investigated at varying levels (0%, 0.15%, and 1%). The results revealed that the incorporation of UGGBS had a substantial enhancement to the mechanical properties of LWAC when BF and CS were incorporated. As a significant finding of this research, a grade 30 LWAC with demolded density of 1864 kg/m3 containing only 284 kg/m3 cement was developed. The LWAC with high-volume UGGBS and BF had the minimum CO2 emissions at 390.9 kg/t, marking a reduction of about 31.6% compared to conventional M40-grade concrete. This research presents an introductory approach to sustainable, environmentally friendly, high-strength, and low-density concrete production by using packing density optimization, thereby contributing to both environmental conservation and structural outcomes.