Decrease CO2 Emissions Research Articles

Integrating Process Simulation and Life Cycle Assessment for Enhanced Process Efficiency and Reduced Environmental Impact in Ferromanganese Production

Process simulation was integrated with life cycle assessment to evaluate process efficiency and environmental impact of the production of manganese ferroalloys for various production modes and different ore mineralogies. Utilizing HSC Sim, the model was designed to evaluate the production process with or without a pretreatment step, where results for simulated cases using a four-zone ferromanganese furnace model were exported to openLCA for a complete life cycle assessment. Two main production scenarios were simulated: a closed ferromanganese furnace running on the duplex method and an open furnace running on the discard slag approach. The closed furnace scenario achieved a 17.5% reduction in energy consumption and a 16.2% decrease in direct CO2 emissions with CO-rich off-gas pretreatment. The open furnace scenario showed an 11.2% reduction in energy consumption with thermal solar energy pretreatment but no change in CO2 emissions.

Optimizing energy hub systems: A comprehensive analysis of integration, efficiency, and sustainability

This study introduces a novel application of modified particle swarm optimization (PSO) for optimizing multi-energy hub systems (EHSs) to enhance efficiency and sustainability. The proposed method leverages PSO to optimize the scheduling of various energy resources, including gas turbines, biomass units, and renewable sources such as solar and wind power. Unlike traditional optimization approaches that rely on genetic algorithm (GA) and complex encoding schemes, the PSO algorithm simplifies the process using real-valued vectors and direct communication within the swarm, which significantly reduces implementation complexity. Key contributions of this work include the development of a tailored PSO algorithm that integrates seamlessly with the multi-objective optimization of EHSs. The algorithm simultaneously targets a reduction in operational costs and carbon emissions, offering a comprehensive solution for energy hub design. The proposed PSO approach has demonstrated a 10.35 % reduction in operating costs and an 85.03 % decrease in CO2 emissions compared to traditional baseline setups. In comparative analysis, the integration of renewable sources using the PSO algorithm resulted in a 77.91 % reduction in total CO2 emissions and an 85.61 % decrease in operating costs, showcasing its effectiveness in advancing both economic and environmental objectives. Furthermore, the study provides a detailed evaluation of various scenarios, revealing that the PSO-optimized EHS configuration achieves a significant reduction in reliance on non-renewable energy sources (RES). For instance, the incorporation of photovoltaics and wind turbines in the EHS setup led to a 46.39 % increase in energy sold to the grid and a 26.82 % decrease in electricity purchased from external sources. These quantitative results underscore the robustness and practical benefits of the proposed PSO method in designing and optimizing energy systems for improved sustainability and cost-effectiveness.

Dynamic interactions between GDP, renewable energy, innovation, and CO2 emissions in Finland: a fourier-augmented ARDL analysis

This study uses the novel Fourier-augmented ARDL (FARDL) to explore the impact of renewable energy (REN), the number of patent applications (PA) and GDP per capita on CO2 emissions in Finland during 1990–2022. The findings reveal that in the long run, GDP rises CO2 emissions, while REN and PA decrease CO2 emissions. The FARDL short-run results indicate that both REN and PA have a significant negative impact on CO2 emissions, suggesting that higher adoption of renewable energy and technological innovation contribute to emission reductions. However, GDP does not show a significant effect in the short run, which may indicate a decoupling of economic growth from environmental degradation in the short term. Furthermore, the study highlights the need for policies that promote technological innovation and increased investment in renewable energy to achieve sustainable carbon reduction in the long term.

Thermodynamic analysis of supercritical CO2 power generation system for waste heat recovery with impurities in CO2

Waste heat recovery from gas turbines is an effective method for meeting the demand for a more efficient and cleaner energy system with decreased CO2 emissions and lower environmental pollution. The supercritical CO2 Brayton cycle is a promising power conversion system for waste heat recovery. The advantage of the supercritical CO2 Brayton cycle can be attained based on its physical characteristics. However, when another fluid is mixed as an impurity in a system using pure CO2, physical characteristics of working fluid was changed and operation at the design point can be challenging. Therefore, it is important to verify the purity of CO2 and understand the effect of impurities in CO2 in advance. This study examined the effects of impurities in the working fluid of a supercritical CO2 power generation system for actual demonstration facilities. The effect of impurity, a CO2-based mixture, in a supercritical CO2 power generation system on waste heat recovery from an LM500 gas turbine was investigated. A purity test of industrial grade CO2, which was noted as 99.9 % pure by the supplier, was conducted to verify the composition of the working fluid. The results of the purity test showed that the supplied CO2 consisted of 99.076 % CO2 along with nitrogen, argon, oxygen, water, and methane. Based on the results of the purity test, sensitivity analyses of the CO2-based binary mixtures and industrial mixtures were performed. A design point analysis was conducted for the CO2-based industrial mixture in comparison with pure CO2, which has cycle efficiency of 16.15 %, gross power of 510.03 kW, mass flow rate of 12.55 kg/s, and waste heat recovery of 2119.06 kW. In the case of fixed waste heat with mass flow rate of 14.417 kg/s, the cycle efficiency decreased by 0.39 % and gross power increased by 66.14 kW. In the case of fixed mass flow rate with 1844.598 kW waste heat, the cycle efficiency decreased by 0.32 % and gross power decreased by 9.84 kW. In addition, the influence of the performance of the major components on the system performance was investigated.

Can green buildings reduce carbon dioxide emissions?

Green buildings are a pivotal strategy for realizing the low-carbon evolution within the construction industry. However, the emission reduction effect of green buildings remains unexplored. This study utilizes prefecture-level data from green building projects in Jiangsu Province, China, from 2008 to 2019, to systematically analyze the nonlinear effects, heterogeneous impacts, and mechanisms of influence that green buildings have on carbon dioxide (CO2) emissions. The research findings are as follows: first, during the early stages of green building development, when the scale of green buildings is relatively small, green buildings lead to an increase in CO2 emissions. However, as the scale of green buildings expands, they can exhibit a significant effect on decreasing CO2 emissions. Second, green buildings have heterogeneous impacts on CO2 emissions: lower-rated green buildings (one or two-star) have an increasing impact on CO2 emissions, while the emission reduction effect of green buildings mainly comes from higher-rated green buildings (three-star). These high-rated green buildings substantially affect the advancement of low-carbon technologies, playing an essential role in achieving emission reduction. Third, the mechanisms through which green buildings influence CO2 emissions are identified: on the one hand, green buildings provide a technical effect that decreases CO2 emissions; on the other hand, by promoting the growth of the construction industry, green buildings would cause an increase in CO2 emissions. Lastly, this study proposes relevant policy implications centered around leveraging the emission reduction potential of green buildings.

A novel algorithm for optimizing genset operations to minimize fuel consumption in remote diesel-RES microgrids

This paper addresses the challenge of reducing fuel consumption in Diesel-RES (Renewable Energy Sources) isolated microgrids, particularly focusing on Diesel Genset’s (DG) operation. The study introduces a basic rule based energy management system that serves as a platform to test out various DG operational strategies with a novel approach. Two optimization strategies—load dispatch optimization and unit commitment optimization—are explored to unequally distribute loads among different grid-connected DGs and sequence their start/stop based on predictive demand profiles respectively. Additionally, the integration of a spinning reserve-providing battery is investigated to alleviate DGs from their spinning reserve constraint, resulting in higher operational loads and consequently higher efficiency. The proposed model is applied on a case study of the Tahitian power system, demonstrating reductions in fuel consumption. The combined application of the proposed DG load dispatch and unit commitment optimizations, along with the integration a spinning-reserve-providing battery, yielded a 2.6 % reduction in fuel consumption and 6kt decrease in CO2 emissions over a year compared to a basic DG operation without a battery.

Tailpipe emissions and fuel consumption of a heavy-duty diesel vehicle using palm oil biodiesel blended fuels

Biodiesel application, such as using waste cooking oil biodiesel in Shanghai, China, is a sustainable solution that addresses the challenges posed by escalating air pollution, energy security, and climate change. Future efforts may involve blending biodiesel from alternative sources like crude palm oil with diesel in China. This study tested a China V heavy-duty diesel vehicle equipped with a selective catalytic reduction (SCR) system using various palm oil biodiesel blended fuels (B0, B5, B10, and B20). The findings indicated that using biodiesel blends led to decreased carbon monoxide (CO), hydrocarbon (HC), and particle number (PN) emissions compared to B0, while nitrogen oxide (NOX) emissions remained similar. Higher biodiesel content significantly reduced petroleum diesel consumption, but no statistically significant differences were found in total carbon dioxide (CO2) emissions and fuel consumption. Various factors such as vehicle speed, payload, and cold starts influence tailpipe emissions and fuel consumption. Specifically, high-speed phases notably reduced CO, HC, and PN emissions with the use of biodiesel blends. Lower payloads were linked to decreased CO2 emissions and fuel consumption but increased NOX emissions. Cold starts increased HC and NOX emissions, especially with higher biodiesel blending ratios. These results can provide valuable empirical insights into palm oil biodiesel emissions.

Circulation of self-supplied water for significant energy recovery through heat integration

This study introduces an overhead heat-integrated distillation column (OHIDiC), a novel approach that maximizes heat recovery by multiple heat exchanges and product circulation. By utilizing the overhead vapor as a direct heat source, low-temperature feed and product water were used as cooling agents, thereby significantly reducing the condenser duty and reliance on cooling utilities. Additionally, the heated feed transfers heat to the column, leading to a substantial reduction of reboiler heat duty. Some of the heated product water is recycled back to the decanter for product cycling, while the rest is released as the final product. This circulation process ensures a continuous coolant supply, which contributes the reduction of condenser duty. Two processes were considered in this study, utilizing the water product from a non-reactive, and from a reactive separation within the system. When applied to the separation of a water-dodecanol mixture, OHIDiC reduced the condenser duty by 69.21% compared to a traditional distillation column, with a 31.46% reduction in the total utility consumption. When reactive distillation was incorporated into the OHIDiC, the higher overhead vapor temperature facilitated high heat transfer in the multiple heat exchange sections, thereby significantly reducing the total thermal load. This resulted in a reduction of up to 46.96% in total heat duty and a 36.06% decrease in CO2 emissions. These findings confirm that the OHIDiC achieves significant energy savings through the utilization of process-derived substances, with pronounced benefits when the temperature of the overhead vapor becomes higher.

Sustainability in radiation oncology: opportunities for enhancing patient care and reducing CO2 emissions in breast cancer radiotherapy at selected German centers.

Radiotherapy often entails asubstantial travel burden for patients accessing radiation oncology centers. The total travel distance for such treatments is primarily influenced by two factors: fractionation schedules and the distances traveled. Specific data on these aspects are not well documented in Germany. This study aims to quantify the travel distances for routine breast cancer patients of five radiation oncology centers located in metropolitan, urban, and rural areas of Germany and to record the CO2 emissions resulting from travel. We analyzed the geographic data of breast cancer patients attending their radiotherapy treatments and calculated travelling distances using Google Maps. Carbon dioxide emissions were estimated assuming astandard 40-miles-per-gallon petrol car emitting 0.168 kg of CO2 per kilometer. Addresses of 4198breast cancer patients treated between 2018 and 2022 were analyzed. Our sample traveled an average of 37.2 km (minimum average: 14.2 km, maximum average: 58.3 km) for each radiation fraction. This yielded an estimated total of 6.2 kg of CO2 emissions per visit, resulting in 156.2 kg of CO2 emissions when assuming 25visits (planning, treatment, and follow-up). Our study highlights the environmental consequences associated with patient commutes for external-beam radiotherapy, indicating that reducing the number of treatment fractions can notably decrease CO2 emissions. Despite certain assumptions such as the mode of transport and possible inaccuracies in patient addresses, optimizing fractionation schedules not only reduces travel requirements but also achieves greater CO2 reductions while keeping improved patient outcomes as the main focus.

An experimental investigation of the impacts of titanium dioxide (TiO2) and ethanol on performance and emission characteristics on diesel engines run with castor Biodiesel ethanol blended fuel

Investigating the impact of ethanol and TiO2 on the performance and emission characteristics of diesel engines running on a blend of ethanol and castor biodiesel is the primary goal of this study. The nanoparticles of ethanol, biodiesel, and TiO2 diesel fuel were combined at several concentrations. Diesel, B10, B20, B30, B10E10T, B20E10T, B30E10T, B10E20T, B20E20T, and B30E20T were among the various fuels that were investigated. The physiochemical properties of all the sample fuels were assessed, including density, pour point, cloud point, fire point, flash point, and kinematic viscosity. Following this, other engine performance indicators, such as torque, power, and fuel-consumption, were examined. Studies were also carried out on the properties of emissions, including CO, CO2, HC, and NO. Peak braking power and engine torque were found for each fuel under investigation at around 2750 and 2500 rpm, respectively. The addition reduced the brake-specific fuel consumption for B10E20T by 7.41 % while increasing the braking engine's torque and power by 8.64 and 3.86 %, respectively, in compared to blends without the TiO2 additions. When compared to diesel, the exhaust emission data without the addition of TiO2 revealed a decrease in CO and HC emissions but an increase in CO2 and NO emissions. On the other hand, using ethanol blend reduced NO emissions. According to the overall findings, diesel engine performance, combustion characteristics, and exhaust gas emissions were enhanced averagely by 7.43 % when a certain ratio of ethanol, biodiesel, and TiO2 additives (B10E20 + 50 ppm) was used.

Laboratory Tests in Cyber-Physical Mode for an Energy Management System Including Renewable Sources and Industrial Symbiosis

Abstract The aim of this paper regards the laboratory validation of an energy management system (EMS) for an industrial site on the Eigerøy island (Norway). It will be the demonstration district in the ROBINSON project for a consequent concept replication. This activity in cyber-physical mode is an innovative approach to finalize the EMS tool with real measurement data with prime movers available at laboratory level, considering the necessary EMS robustness and flexibility for replication on other industrial islands. This EMS was designed and developed to minimize variable costs, producing on/off and set-point signals that, through a model predictive control (MPC) software, establish the system status. This smart grid includes renewable sources (e.g., solar panels, a wind turbine, and syngas) and traditional prime movers, such as a steam boiler for the industry needs. Moreover, an energy storage device is installed composed of an electrolyzer with a hydrogen pressure vessel. The main results reported in this work regard 26-h tests performed in cyber-physical mode thanks to the real-time interaction of hardware and software. So, a real microturbine and real photovoltaic (PV) panels were managed by the EMS in conjunction with software models for components not physically present in the laboratory. Although the optimization target was cost minimization, significant improvement was also obtained in terms of efficiency increase and CO2 emission decrease.

Harnessing the Power of Renewable Energy: A Study of Sustainable Sources and Technologies

This research investigates the capacity of renewable energy technologies to fulfill global energy requirements while mitigating environmental effects, concentrating on primary sources like sun, wind, hydropower, biomass, and geothermal energy. It evaluates the efficacy of various technologies for energy production, efficiency, economic viability, and reduction of carbon emissions. The findings underscore notable progress in solar and wind energy, demonstrating considerable efficiency enhancements (5% for solar PV, 10% for wind turbines) and cost reductions (67% and 64%, respectively) during the last decade. Hydropower is the most efficient energy source, converting 90% of available energy, albeit it is geographically constrained. The research highlights the environmental advantages, noting that renewable technologies substantially decrease CO₂ emissions—hydropower and wind energy prevent 250,000 and 120,000 metric tons of CO₂ annually, respectively. Nonetheless, obstacles such as the variability of solar and wind energy, elevated expenses associated with biomass and geothermal energy, and regional variations in implementation persist as substantial impediments. The research highlights the need for further developments in energy storage, grid modernization, and legislative assistance to expedite the worldwide shift towards renewable energy. This study synthesizes current statistics and trends, emphasizing the vital role of renewable energy in attaining a sustainable, low-carbon future, while also tackling ongoing economic and infrastructural problems.

Climate change and greenhouse gas emissions from soils under the winter wheat agroecosystem in Ukraine

The issue of global climate change is one of the most important challenges for modern environmental science. In this regard, assessment of greenhouse gas emissions from soils under agroecosystems is an extremely important task. The main purpose of the study was to assess the potential emissions of greenhouse gases (CO2 and N2O) from the soils under the winter wheat agroecosystem during its spring-summer growing season under the climate change in Ukraine. A comprehensive model of greenhouse gas emissions from agroecosystem soils was used as a theoretical basis. The study considered the main agroclimatic regions of Ukraine, such as Polissia, Forest-Steppe, Northern Steppe, and Southern Steppe. The modelling was performed for average long-term conditions of 1981–2020 and under scenario conditions (using the RCP4.5 climate scenario) for the decades of 2021–2030, 2031–2040, and 2041–2050. Estimates of CO2 emissions were obtained for the agroclimatic regions of Ukraine. According to the results, the largest CO2 emissions (0.886-0.940 t C-CO2/ha) will be expected when the average productive moisture supplies in the arable soil layer for the spring-summer period of winter wheat vegetation are 20–40 mm and the air temperature is 12–15 °C. Rise in the level of moisture reserves, averaged for the period, for more than 40 mm and the air temperature of 11–12 °C is accompanied by decrease in the level of CO2 emission (0.645–0.658 t C-CO2/ha). In arid conditions, with a decrease in the period-average moisture supplies in the arable soil layer to less than 20 mm and heightened average air temperatures (14.5–15.2 °C), a decrease in CO2 emissions is expected (0.755–0.770 t C-CO2/ha). The study showed that the highest N2O emission (1.087–1.703 kg N-N2O/ha) is expected at a high level of moistening (Md being equal to 0.474–0.713 relative units and air temperature – 11.3–13.0 °C) with a high intensity of nitrification and denitrification processes. Conditions characterizing the average level of N2O emission (0.657–0.890 kg N-N2O/ha) are formed under the moistening at a level of Md equaling 0.296–0.447 relative units and air temperature of 13.4–14.7 °C. There is a slowdown in denitrification processes and an increase in the share of emissions owing to nitrification. It has been found that the lowest N2O emission (0.508–0.537 kg N–N2O/ha) is expected under conditions of severe and very severe drought (according to the Md criterion), with a heightened temperature averaged at the level of 14.5–15.2 °C during the spring-summer period of winter wheat vegetation.

Examining macroeconomic factors and environmental sustainability: An OLS regression analysis of the impact of exports, imports, governmental budget, and oil products on CO2 emissions in Jordan

This study aims to investigate the relationship between macroeconomic factors and CO2 emissions. The study used a sample of data covering the period from 1991 to 2019 and employed ordinary least squares (OLS) method to estimate the relationship. The study found that there is a strong relationship between CO2 emissions and the macroeconomic factors of exports, imports, governmental budget, and oil products. The R-squared value of 0.717668 suggests that these variables explain approximately 72% of the variation in CO2 emissions. The coefficients for exports, imports and oil products are statistically significant at the 5% level. A negative coefficient for exports indicates that an increase in exports is associated with a decrease in CO2 emissions. On the other hand, a positive coefficient for imports suggests that an increase in imports is associated with an increase in CO2 emissions. Additionally, the positive coefficient for oil products indicates that an increase in oil product consumption is associated with a significant increase in CO2 emissions. The coefficient for the government budget variable is not statistically significant, which suggests that changes in the government budget do not have a significant impact on CO2 emissions. The results are robust and reliable as the assumptions of linearity, normality and homoscedasticity of errors were met. The study results could help policy makers in taking potential actions to mitigate CO2 emissions in the country.

An experimental investigation on performance, emission and combustion characteristics of IC engine using liquid fuel produced through catalytic co-pyrolysis of pressed oil cake and mixed plastics with the addition of nanoparticles

The study focuses on using a combination of diesel and a liquid fuel derived from the co-pyrolysis of pressed neem cake (PNC) and mixed waste plastics (MWP) containing waste polyethylene terephthalate (PET) and low density polyethylene (LDPE) in equal amounts with the help of cupric oxide (CuO) catalyst. The engine analysis was carried out using diesel and five different blends of co-pyrolysis oil with diesel in proportions of 20 % (20 % pyrolysis oil + 80 % diesel = PD20), 40 % (PD40), 50 % (PD50) and 100 % pyrolysis oil (PD100), respectively. Initially, the co-pyrolysis oil was produced using PNC and MWP in a ratio of 1:2 under different operating temperatures between 350 °C and 650 °C. The process temperature was optimized to yield maximum liquid oil, and the characterization study was performed. In addition to that, CeO2 nanoadditives were used to improve the properties of PD20 fuel. Different dosages of nanoadditives were blended with PD20 to prepare PD20@25 (PD20 + 25 ppm CeO2), PD20@50, PD20@75, and PD20@100. The objective of the study is to assess the performance, emission, and combustion characteristics of a diesel engine utilizing co-pyrolysis oil-diesel blend by including the nanoadditives. The analysis was carried out on a single-cylinder water-cooled diesel engine mounted with an eddy current dynamometer. The experiments demonstrated that the combination of PD20 and 50 ppm CeO2 resulted in a 6 % increase in thermal efficiency when compared to other blended fuels and diesel. When compared to all fuels, the PD20@50 produced a higher decrease in CO and HC emissions by roughly 30 and 6.2 %, respectively. The combustion analysis showed that the heat release rate (HRR) and maximum cylinder pressure were also found to have improved by adding nanoparticles.

RESEARCH OF THE COMBUSTION PARAMETERS OF GASOLINE WITH ADDITIONAL HYDROGEN IN A SPARK-IGNITION ENGINE IN EXTERNAL SPEED CHARACTERISTIC MODES

The directions of development and improvement of road transport around the world are inextricably linked to the desire to reduce the use of cars “on traditional fuels” due to limited oil and environmental safety of mankind. Since the modes of external speed characteristic are the most typical for the operation of cars in cities, the study of environmental performance of engines in these modes is an urgent task. Therefore, finding ways to reduce carbon dioxide emissions from automobile engines at high-speed modes is an urgent task. The rapid growth in the number of cars with internal combustion engines and the inevitable decline in world oil reserves necessitate the development and implementation of energy-saving technologies and the use of alternative fuels. Research aimed at finding ways to improve the fuel efficiency and environmental performance of automotive engines is relevant. One of the promising areas is the influence on the combustion process in gasoline engines by using additives of alternative fuels, which include hydrogen. The presented study of the parameters of combustion of gasoline with hydrogen additive in a spark ignition engine at external speed characteristics is a comprehensive analysis of the combustion process of a gasoline-hydrogen mixture and determination of its effect on the concentration of carbon dioxide in exhaust gases by developing a mathematical model that takes into account the composition of the mixture components and features of the combustion process, allows for sufficiently accurate calculation of the operating process of an engine with hydrogen additive at ψ ≤ 10%, its identification by the results of experiments. In the course of the study, dependencies were developed to determine the combustion parameters of the Wiebe model, taking into account the addition of hydrogen to gasoline in the modes of external speed characteristics, and the effect of hydrogen addition on the concentration of CO2 in exhaust gases was analyzed. It is shown that with an increase in the hydrogen additive to 10% by mass fraction to gasoline, there is a decrease in CO2 emissions to almost 30% in the external speed characteristic modes, which corresponds to modern environmental standards for gasoline internal combustion engines.

Hubungan antara Pendapatan, Konsumsi Energi, FDI, Perdagangan, Pariwisata, dan Lingkungan: Analisis Data 5 Negara ASEAN

Climate change is still becoming a huge problem in many countries in the world including ASEAN. One of the causes is global warming due to greenhouse gas emission, including CO2. Since very few literatures discuss about the nexus of income, energy consumption, FDI, trade, tourism, and environment using panel data in ASEAN, this research tries to fill that gap. This topic needed to be studied because those variables are still pioneers for ASEAN countries to achive economy growth and development. The purpose of this paper is to estimate the impact of income, energy consumption, FDI, trade, in this case export and import, and tourism on CO2 emission. This paper uses panel data from five ASEAN countries during 1995-2014. This paper uses pooled mean group (PMG) or known as panel ARDL as method. The results show that FDI tends to increase CO2 emission, in line with Pollution Haven hypothesis. Energy consumption, export, and tourism also increase CO2 emission. Another result shows that rise of import helps decrease CO2 emission in those countries.

Harnessing the power of AI and IoT for real-time CO2 emission monitoring

Global CO2 emissions have been an essential topic of the environmental discussion. Still, empirical data is needed to support arguments that high-quality government actions could reduce these emissions. By analyzing data from 137 nations from 2000 to 2020, we offer strong evidence that state policies focused on promoting healthy ecosystems, sustainable economic growth, and transcendent legislative changes are capable of decreasing CO2 emissions. Based on our findings, there are essentially three critical institutional factors that need to be improved for environmental policies to be efficient: the concept of law, which protects citizens' intellectual property rights; citizens' speech, which allows them to participate in elections and represent themselves freely, and the management of corruption. Policies aimed at promoting economic growth, lowering oil and gas use, enhancing the usage of green energy by the public and private sectors, and enhancing such institutional factors are all necessary components of a climate-friendly financial strategy.

Multi-objective modeling of price and pollution in large-scale energy hubs with load management

This study introduces a novel multi-objective model that addresses emission costs, large-scale user operational expenses, and the efficiency of the electric storage system within an integrated energy hub encompassing heating, water, power, and gas sources. A key objective of this model is to maximize the performance of the electrical storage system. The study employs the epsilon-constraint method to construct the Pareto front, aiming to balance profitability and emission reduction from virtual power plant units. The final decision-making process utilizes a fuzzy decision-making technique. Additionally, demand response program (DRP) is incorporated to optimize peak-hour demand and align the load profile with defined objectives. The proposed approach is evaluated across various operational scenarios within a sample system, demonstrating its effectiveness and potential benefits in terms of cost reduction and environmental impact mitigation. Focusing on environmental impact, the carbon dioxide (CO2) emissions are also lower under the DRP scenario, amounting to 10253.92 kg without DRP versus 10127.74 kg with DRP. This reduction in emissions aligns with sustainable energy management goals, showcasing DRP's capability to mitigate environmental impacts associated with energy generation and consumption. The percentage improvements in total costs and emissions further highlight the advantages of employing DRP. The reductions in total costs range from approximately 1.2%–1.4%, demonstrating cost savings across different cost categories. Similarly, the decrease in CO2 emissions by approximately 1.2% underscores DRP's role in promoting environmentally friendly energy practices.

BIO-NANOTECHNOLOGY-BASED SOLUTIONS FOR SUSTAINABLE WASTE MANAGEMENT AND POLLUTION

Waste management and pollution reduction are critical global challenges that demand innovative and sustainable solutions. Traditional methods often fall short in terms of efficiency and environmental impact. Biological nanotechnology, particularly the use of biosurfactants and nanoenzymes, offers promising alternatives for addressing environmental pollutants such as hydrocarbons, textile dyes, and heavy metals. Objective: This study aimed to evaluate the effectiveness of bio-nanotechnology-based solutions, specifically biosurfactants and nanoenzymes, in waste management and pollution reduction, focusing on sustainability and environmental impact. Methods: A quantitative research approach was employed to assess the efficacy of bio-nanotechnology in waste treatment and pollution reduction. Laboratory experiments were conducted to explore the degradation capacity of biosurfactants and nanoenzymes on various pollutants. The study also involved a survey of 167 industry professionals to evaluate the potential of bio-nanotechnology in enhancing waste treatment efficiency and environmental sustainability. Data on pollutant elimination efficacy, degradation rates, soil health, metal contaminant levels, and CO2 emissions were collected. Statistical analysis was performed to compare the outcomes of nano-bioremediation with traditional methods. Results: The laboratory experiments demonstrated a high treatment capacity, with pollutant elimination efficacy exceeding 86% and degradation rates significantly faster than conventional treatments. The survey results indicated that bio-nanotechnology could enhance waste treatment efficiency and environmental friendliness by 20-40%. Nano-bioremediation led to a 23% improvement in soil health, a 32% reduction in metal contaminants, and a 14-19% decrease in CO2 emissions from waste processing compared to conventional methods. Conclusion: The study's findings suggest that bio-nanotechnology presents a novel, sustainable solution for waste management and pollution reduction. The significant improvements in pollutant elimination, soil health, and reduction of metal contaminants and CO2 emissions highlight the potential of this approach to address global environmental challenges more effectively than traditional methods. Further research and development are recommended to optimize and scale up these technologies for broader application.