A review of the prospects, efficacy and sustainability of nanotechnology-based approaches for oil spill remediation.

Numerous marine oil spill incidents and their environmental catastrophe have raised the concern of the research community and environmental agencies on the topic of the offshore crude oil spill. The oil transport through oil tankers and pipelines has further aggravated the risk of the oil spill. This has led to the necessity to develop an effective, environment-friendly, versatile oil spill clean-up strategy. The current review article analyses various nanotechnology-based methods for marine oil spill clean-up, focusing on their recovery rate, reusability and cost. The authors weighed the three primary factors recovery, reusability and cost distinctively for the analysis based on their significance in various contexts. The findings and analysis suggest that magnetic nanomaterials and nano-sorbent have been the most effective nanotechnology-based marine oil spill remediation techniques, with the magnetic paper based on ultralong hydroxyapatite nanowires standing out with a recovery rate of over 99%. The chitosan-silica hybrid nano-sorbent and multi-wall carbon nanotubes are also promising options with high recovery rates of up to 95-98% and the ability to be reused multiple times. Although the photocatalytic biodegradation approach and the nano-dispersion method do not offer benefits for recovery or reusability, they can nevertheless help lessen the negative ecological effects of marine oil spills. Therefore, careful evaluation and selection of the most appropriate method for each marine oil spill situation is crucial. The current review article provides valuable insights into the current state of nanotechnology-based marine oil spill clean-up methods and their potential applications.

Multicriteria Decision-Making Technique for Choosing the Optimal Ammonia Energy Share in an Ammonia-Biodiesel-Fueled Reactivity-Controlled Compression Ignition Engine.

Low-temperature combustion paired with the use of carbon-free ammonia and carbon-neutral biofuels is a novel approach for improving performance, reducing greenhouse gases, and reducing regulated emissions. Reactivity-controlled compression ignition (RCCI), a low-temperature combustion technology, dramatically reduces NOx and smoke emissions compared to traditional engines. Ammonia can be projected as a good transit fuel in the journey toward achieving net zero emissions and cleaner energy. This study examines the impact of ammonia energy premixing fraction (AEPF) (20, 30, 40, and 50%) as a low-reactive fuel (LRF) and algal biodiesel as a high-reactive fuel on the performance and emission characteristics of a single-cylinder, water-cooled 3.5 kW CI engine at a constant speed of 1500 rpm under various loading conditions. The research results indicate that the 40% ammonia share RCCI mode exhibited a reduction in carbon dioxide (CO2) by 14.16%, nitrogen oxide (NOx) by 22.6%, and smoke by 42.1%, with an 11.5% improvement in thermal efficiency compared to the neat biodiesel-fueled conventional engine. Furthermore, the analytical hierarchy process (AHP) will be used in conjunction with the technique for order of preference by similarity to ideal solution (TOPSIS) of multiple criteria decision-making techniques to determine the optimal energy share in the RCCI combustion with the goal of achieving superior thermal efficiency and lower emissions. According to the AHP-TOPSIS study findings, AEPF40 is the best choice for all engine loads.

Experimental and numerical analysis of the thermal performance of pebble solar thermal collector.

In this work, pebbles of higher specific heat than the conventional absorber materials like aluminium or copper are proposed as a absorber in the solar flat plate collector. The proposed collector are integrated into the building design and constructed with masonry. Tests were conducted by varying the operating parameters which influence its performance, like the flow rate of the heat-absorbing medium, and the tilt of the collector using both coated and uncoated pebbles. The maximum temperature difference that could be measured for a conventional absorber was approximately 8 °C for a flow rate of 0.6 L/min. While for a coated and uncoated absorber, it was 7 °C and 5.5 °C respectively. This difference decreased with an increase in flow rates from 0.6 L/min to 1.2 L/min. For all the flow rates, it was observed that the average difference in efficiency between the coated and the conventional absorber collector is 5.82 %, while the difference between the coated and uncoated absorber collector is 15.68 %. Thus, it is very much evident that by replacing the conventional absorber with the proposed coated pebble absorber, the overall loss in efficiency is just 5.82 %, but the advantages are enormous. Along with the experimental study, numerical analysis was also carried out with CFD modeling. The numerical results agreed well with experimental results with the least error. Therefore, CFD simulation can be further used to optimize the design of the collector.

Investigation into the Ideal Concoction for Performance and Emissions Enhancement of Jatropha Biodiesel-Diesel with CuO Nanoparticles Using Response Surface Methodology.

The present work covers the preparation of biodiesel from jatropha oil through the transesterification process followed by its characterization, and furthermore, performance and emission analyses were done in terms of blending biodiesel with fossil diesel and CuO nanoparticles. Jatropha biodiesel blends (B10, B20, and B30) were chosen for this preliminary investigation based on the observation that B20 outperformed other blends. Next stage B20 with copper oxide (CuO) nanoparticle concentrations of 25, 50, 75, and 50 ppm are used to examine the performance and emission characteristics of a constant speed single cylinder, 4-stroke, 3.5 kW compression ignition (CI) engine. Finally, The response surface methodology (RSM) was utilized to determine the optimal nanoparticle concentration for B20. The results revealed that the blend of B20 with 80 ppm nanoparticles had the highest desirability (0.9732), and the developed RSM model was able to predict engine responses with a mean absolute percentage error (MAPE) of 3.113%. A confirmation test with an error in prediction of less than 5% verified the model's adequacy. When comparing optimized B20CuO80 to diesel, brake specific energy consumption (BSEC) increased by 8.49% and brake thermal efficiency (BTE) was lowered by 3.34%. Hydrocarbon (HC), carbon monoxide (CO), carbon dioxide (CO2), nitrogen oxide (NOx), and smoke emissions were reduced by 3.66% and 2.88%, 4.78%, 22.9%, and 20.54%, respectively, at 80% load. As a result, the B20 blend with nanoparticle concentrations of 80 ppm may be used in current diesel engines without engine modification.

Investigation on Ammonia-Biodiesel Fueled RCCI Combustion Engine Using a Split Injection Strategy.

Advanced combustion concepts in compression ignition are emerging as one of the most promising solutions to reduce nitrogen oxides (NOx) and particle emissions without sacrificing fuel efficiency. Among many advanced combustion concepts, reactive controlled compression ignition (RCCI) can achieve a wider working range. In this study, to implement RCCI operation, ammonia gas is introduced through the manifold as a low-reactive fuel, and biodiesel is injected directly as a high-reactivity fuel with a 40:60 energy ratio. The effect of biodiesel split ratio in a split injection strategy (pre- and main injections) is examined under varied load conditions, and the results are compared with ammonia/biodiesel single injection. Results indicate that the use of the 45% biodiesel split ratio at full load boosts the peak in-cylinder pressure and heat release rate and shifts the peak occurrence toward the top dead center (TDC). An increase in brake thermal efficiency (BTE) to 36.22% and reduced brake specific energy consumption (BSEC) to 8.75 MJ/kWh are 12.33% higher and 19.31% lower than ammonia/biodiesel single injection. Emissions of HC, CO, and smoke opacity were reduced to 50 ppm, 0.098% vol, and 15.6%, which are 34.21, 39.13, and 33.89% lower, while the emission of NOx was increased to 615 ppm, which is 36.06% higher than the single-injection ammonia/biodiesel RCCI combustion.

Solar Salt with Carbon Nanotubes as a Potential Phase Change Material for High-Temperature Applications: Investigations on Thermal Properties and Chemical Stability.

Nano-enhanced phase change materials are highly employed for an enhanced heat-transfer process. The current work reports that the thermal properties of solar salt-based phase change materials were enhanced with carbon nanotubes (CNTs). Solar salt (60:40 of NaNO3/KNO3) with a phase change temperature and enthalpy of 225.13 °C and 244.76 kJ/kg, respectively, is proposed as a high-temperature PCM, and CNT is added to improve its thermal conductivity. The ball-milling method was employed to mix CNTs with solar salt at various concentrations of 0.1, 0.3, and 0.5% by weight. SEM images display the even distribution of CNTs with solar salt, with the absence of cluster formations. The thermal conductivity, phase change properties, and thermal and chemical stabilities of the composites were studied before and after 300 thermal cycles. FTIR studies indicated only physical interaction between PCM and CNTs. The thermal conductivity was enhanced with an increase in CNT concentration. The thermal conductivity was enhanced by 127.19 and 125.09% before and after cycling, respectively, in the presence of 0.5% CNT. The phase change temperature decreased by around 1.64% after adding 0.5% CNT, with a decrease of 14.67% in the latent heat during melting. TGA thermograms indicated the weight loss was initiated at about 590 and 575 °C before and after thermal cycling, after which it was rapid with an increase in temperature. Thermal characterization of CNT-enhanced solar salt indicated that the composites could be used as phase change materials for enhanced heat-transfer applications.

Comparative Study of Soft Computing and Metaheuristic Models in Developing Reduced Exhaust Emission Characteristics for Diesel Engine Fueled with Various Blends of Biodiesel and Metallic Nanoadditive Mixtures: An ANFIS-GA-HSA Approach.

Since the discovery of petrol-based products, a surge in energy-requiring equipment has been established across the world. Recent depletion of the existing crude oil resources has motivated researchers to opt for and analyze potential fuels that could potentially provide a cost-effective and sustainable solution. The current study selects a waste plant known as Eichhornia crassipes through which biodiesel is generated, and its blends are tested in diesel engines for feasibility. Different models using soft computing and metaheuristic techniques are employed for the accurate prediction of performance and exhaust characteristics. The blends are further mixed with nanoadditives, thereby exploring and comparing the changes in performance characteristics. The input attributes considered in the study comprise engine load, blend percentage, nanoparticle concentration, and injection pressure, while the outcomes are brake thermal efficiency, brake specific energy consumption, carbon monoxide, unburnt hydrocarbon, and oxides of nitrogen. Models were further ranked and chosen based on their set of attributes using the ranking technique. The ranking criteria for models were based on cost, accuracy, and skill requirement. The ANFIS harmony search algorithm (HSA) reported a lower error rate, while the ANFIS model reported the lowest cost. The optimal combination achieved was 20.80 kW, 2.48047, 150.501 ppm, 4.05025 ppm, and 0.018326% for brake thermal efficiency (BTE), brake specific energy consumption (BSEC), oxides of nitrogen (NOx), unburnt hydrocarbons (UBHC), and carbon monoxide (CO), respectively, thereby furnishing better results than the adaptive neuro-fuzzy interface system (ANFIS) and the ANFIS-genetic algorithm model. Henceforth, integrating the results of ANFIS with an optimization technique with the harmony search algorithm (HSA) yields accurate results but at a comparatively higher cost.

4E analysis of a two-stage refrigeration system through surrogate models based on response surface methods and hybrid grey wolf optimizer.

Refrigeration systems are complex, non-linear, multi-modal, and multi-dimensional. However, traditional methods are based on a trial and error process to optimize these systems, and a global optimum operating point cannot be guaranteed. Therefore, this work aims to study a two-stage vapor compression refrigeration system (VCRS) through a novel and robust hybrid multi-objective grey wolf optimizer (HMOGWO) algorithm. The system is modeled using response surface methods (RSM) to investigate the impacts of design variables on the set responses. Firstly, the interaction between the system components and their cycle behavior is analyzed by building four surrogate models using RSM. The model fit statistics indicate that they are statistically significant and agree with the design data. Three conflicting scenarios in bi-objective optimization are built focusing on the overall system following the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) and Linear Programming Technique for Multidimensional Analysis of Preference (LINMAP) decision-making methods. The optimal solutions indicate that for the first to third scenarios, the exergetic efficiency (EE) and capital expenditure (CAPEX) are optimized by 33.4% and 7.5%, and the EE and operational expenditure (OPEX) are improved by 27.4% and 19.0%. The EE and global warming potential (GWP) are also optimized by 27.2% and 19.1%, where the proposed HMOGWO outperforms the MOGWO and NSGA-II. Finally, the K-means clustering technique is applied for Pareto characterization. Based on the research outcomes, the combined RSM and HMOGWO techniques have proved an excellent solution to simulate and optimize two-stage VCRS.

Performance evaluation of using evacuated tubes solar collector, perforated fins, and pebbles in a solar still - experimental study and CO2 mitigation analysis.

The combination of various methods of increasing evaporation rate can highly impact the performance of solar desalination. This investigation aims to find the impact of using evacuated tubes solar collector, perforated fins, and pebbles on the performance enhancement of a solar still. Simultaneously six-evacuated-tube solar collector to raise the evaporation rate of the system, the perforated fins to increase the heat transfer surface between water and absorber, and the immersed pebbles stone in the water to keep the high water temperature at low solar radiation were considered. The hourly and cumulative distillate output (DO) values are presented separately for the daytime and nighttime to provide extensive insight. The results indicate that on a sample day from the six months of experiments, which was in February 2019, the time for DO peak shifts from 1 to 3 p.m. Moreover, the temperature values for MSS experience almost 43 ℃ jumps on the peak and almost 19 ℃ increase on average compared to CSS. Furthermore, the cumulative DO in the daytime reaches from 2.515 to 6.662 L, while during the nighttime, an increase from 0.057 to 0.872 L is observed. Additionally, during the six months, the average DO jumps from 2.88 to 7.03 L, which means a significant enhancement of 144.1%. Moreover, the costs per liter of MSS and CSS are 0.0051 and 0.0056 dollars per liter, respectively. The net amount of CO2 reduction of MSS was improved by about 2.44 times higher than CSS.

Quantitative Analysis of Solar Photovoltaic Panel Performance with Size-Varied Dust Pollutants Deposition Using Different Machine Learning Approaches.

In this paper, the impact of dust deposition on solar photovoltaic (PV) panels was examined, using experimental and machine learning (ML) approaches for different sizes of dust pollutants. The experimental investigation was performed using five different sizes of dust pollutants with a deposition density of 33.48 g/m2 on the panel surface. It has been noted that the zero-resistance current of the PV panel is reduced by up to 49.01% due to the presence of small-size particles and 15.68% for large-size (ranging from 600 µ to 850 µ). In addition, a significant reduction of nearly 40% in sunlight penetration into the PV panel surface was observed due to the deposition of a smaller size of dust pollutants compared to the larger size. Subsequently, different ML regression models, namely support vector machine (SVMR), multiple linear (MLR) and Gaussian (GR), were considered and compared to predict the output power of solar PV panels under the varied size of dust deposition. The outcomes of the ML approach showed that the SVMR algorithms provide optimal performance with MAE, MSE and R2 values of 0.1589, 0.0328 and 0.9919, respectively; while GR had the worst performance. The predicted output power values are in good agreement with the experimental values, showing that the proposed ML approaches are suitable for predicting the output power in any harsh and dusty environment.

Laminated glazing for buildings: energy saving, natural daylighting, and CO2 emission mitigation prospective.

Operational energy use and energy-based GHG emissions of air-conditioning in the building sector are increasing aggressively due to occupants' higher thermal and visual comfort aspirations. Window glazing is the critical building component that affects the thermal performance of the conditioned space. The existing glazing in the buildings allows huge heat gain/loss, leading to additional energy requirements for HVAC systems. Novel laminated glasses with various solar control film interlayers were studied in this article to improve the thermal performance of the conditioned space. Solar-optical properties and thermal indices of proposed laminated glasses were explored to study the potential energy savings and carbon emission mitigations. Thermal loads and energy savings were calculated with the help of a validated mathematical model across three distinct Indian climates (hot, cold, and composite). Substantial reductions in heat gain/loss and energy requirements were found with laminated glasses compared to monolithic clear glass. The laminated glass with reflective solar control film glazing (LGRF) had concluded a cost saving of 100.84 $/year with a payback period of 1.7 years for cold climate in S-E orientation. CO2 emission mitigation of building with laminated glasses was calculated for the energies conserved with carbon emission factors. The LGRF had reported a carbon emission mitigation of 2.1 tCO2/year for cold climates and comparable results for hot and composite climates. Daylight performance was carried out with the DesignBuilder simulation tool to assess the daylight accession in building interiors with laminated glasses. The laminated glasses were able to reduce annual energy requirements without greatly affecting the daylight inflow.

Heat Transfer Characteristics of Fullerene and Titania Nanotube Nanofluids under Agitated Quench Conditions.

Distilled water and aqueous fullerene nanofluids having concentrations of 0.02, 0.2, and 0.4 vol % and titania (titanium dioxide, TiO2) nanofluids of 0.0002, 0.002, and 0.02 vol % were analyzed for heat transfer characteristics. Quenching mediums were stirred at impeller speeds of 0, 500, 1,000, and 1,500 RPMs in a typical Tensi agitation system. During the quenching process, a metal probe made of ISO 9950 Inconel was used to record the temperature history. The inverse heat conduction method was used to calculate the spatial and temporal heat flux. The nanofluid rewetting properties were measured and matched to those of distilled water. The maximum mean heat flux was 3.26 MW/m2, and the quickest heat extraction was 0.2 vol % fullerene nanofluid, according to the results of the heat transfer investigation.

Transforming waste disposals into building materials to investigate energy savings and carbon emission mitigation potential.

This work aims to enhance the energy cost-saving potential of conventional mud-brick by including natural waste materials as insulators. The solid waste materials considered for mud bricks are rice husk, sawdust, coir pith, and fly ash. This work investigates the structural and thermoeconomic performance of four types of insulated mud bricks and three roofs of ferrocement, clay, and ceramic materials. The thermal properties of walls and roofs were measured as per ASTM D 5334 standards. The utilization of solid waste in mud bricks enhanced the structural properties and air-conditioning cost-saving potential of the mud bricks. The results also showed the mitigation of greenhouse gas emissions with the usage of insulated bricks for buildings. The rice husk mud-brick wall showed better results of higher time lag, lower decrement factor, higher air-conditioning cost-savings, acceptable payback periods, and higher annual carbon mitigation values of 11.11 h, 0.24, 1.74 $/m2, 1.17 years, and 33.35 kg/kWh, respectively, among all the studied multilayer walls. Among the roofs, clay tile roof showed a lower decrement factor (0.989), higher time lag (0.73 h), higher air-conditioning cost-savings (2.58 $/m2), lower payback periods (0.61 years), and higher annual carbon mitigation (21.73 kg/kWh). The results are in designing eco-friendly and energy-efficient envelopes for buildings.

Investigation on thermodynamic performance analysis and environmental effects of various new refrigerants used in air conditioners.

The main aim of this present investigation is to evaluate performance and environmental impact analysis of various novel mixture refrigerants as R22 replacements theoretically. Refrigerants with lower global warming potential (GWP) can be adequate for bringing down emissions which are concerned for air conditioners. In this investigation, twenty-seven refrigerants were developed at several compositions. Important studies such as computation of CO2 emissions using total equivalent warming impact (TEWI), toxicity and flammability analysis of various considered refrigerants were also carried out in this investigation. Performance analysis of refrigerants was conducted under different operating conditions. Results showed that the energy efficiency ratios (EERs) of refrigerants such as R1270, RM30 (R152a/R1270/RE170 of 25/71/4 by mass percentage) and RM50 (R152a/R1270/RE170 of 10/85/5 by mass percentage) were closer to that of R22 and they are relatively lower than R22 by 0.95%, 1.34% and 1.80%, respectively. Toxicity investigation exhibited that all the refrigerants studied were classified into nontoxic category (A) whereas flammability investigation revealed that all the novel refrigerant mixtures (RM10 to RM50) were classified into flammable category (A3). CO2 emissions (TEWI) released from air conditioner working with R1270, RM30 and RM50 were 7.41%, 6.85% and 6.51%, respectively, lower than that of R22. In terms of several thermodynamic aspects, the performance of refrigerants such as R1270, RM30 and RM50 were superior to those of R22 and its various considered alternatives working under different operating conditions, although their EERs are fairly lower than R22 and hence, these refrigerants could be considered suitable environment-friendly alternatives to R22 used in air conditioners. The present study gives essential information and a road map towards the development of low GWP R22 alternative refrigerant blends from the viewpoint of toxicity, flammability, performance aspects, environmental and safety aspects, respectively.

Optimizing the position of insulating materials in flat roofs exposed to sunshine to gain minimum heat into buildings under periodic heat transfer conditions.

Building roofs are responsible for the huge heat gain in buildings. In the present work, an analysis of the influence of insulation location inside a flat roof exposed directly to the sun's radiation was performed to reduce heat gain in buildings. The unsteady thermal response parameters of the building roof such as admittance, transmittance, decrement factor, and time lags have been investigated by solving a one-dimensional diffusion equation under convective periodic boundary conditions. Theoretical results of four types of walls were compared with the experimental results available in literature. The results reveal that the roof with insulation placed at the outer side and at the center plane of the roof is the most energy efficient from the lower decrement factor point of view and the roof with insulation placed at the center plane and the inner side of the roof is the best from the highest time lag point of view among the seven studied configurations. The composite roof with expanded polystyrene insulation located at the outer side and at the center plane of the roof is found to be the best roof from the lowest decrement factor (0.130) point of view, and the composite roof with resin-bonded mineral wool insulation located at the center plane and at the inner side of the roof is found to be energy efficient from the highest time lag point (9.33 h) of view among the seven configurations with five different insulation materials studied. The optimum fabric energy storage thicknesses of reinforced cement concrete, expanded polystyrene, foam glass, rock wool, rice husk, resin-bonded mineral wool, and cement plaster were computed. From the results, it is concluded that rock wool has the least optimum fabric energy storage thickness (0.114 m) among the seven studied building roof materials.