Emission Parameters Research Articles

Influence of water saturation on mechanical characteristics and fracture evolution of coal rock assemblage with rough interfaces

To comprehensively investigate the influence of water content on the mechanical and crack propagation characteristics of coal rock assemblage (CRA) with a rough interface, uniaxial compression tests were conducted on specimens with varying water content. Nuclear magnetic resonance (NMR) and acoustic emission (AE) techniques were employed to monitor the water content and AE signals throughout the experiment. The physical and mechanical properties, as well as the extent of crack development and acoustic emission (AE) parameters, were comprehensively investigated under conditions of water erosion. The results demonstrate that a rough interface contributes to an enhancement in the compressive strength of the composite material. Moreover, the moisture content exerts a significant influence on various aspects of the composite specimen, including its compressive strength, time b value, crack development, and crack propagation. With the increase in water content, the initial single slope shear failure of the composite specimen gradually transitions into a multi-section shear failure mechanism. Under the influence of water-rock interaction, sandstone within the formation undergoes a metamorphosis from a densely cemented structure to an irregular honeycomb-like configuration. This transformative process engenders novel porosity and fractures, ultimately compromising the rock’s mechanical strength. The analysis focuses on the relationship between the AE parameter b and uniaxial stress and water content, with emphasis on its relevance to damage theory. A damage model based on water immersion rate was established to elucidate the correlation between damage variables and water content. This was achieved by considering the characteristics of water-rock coupling AE and constructing a structural model of the water absorption process in different pore throats, thereby providing valuable insights for stability design and evaluation of roadway rock masses.

Analyzing the impact of injection timing variations on the performance of multi-cylinder CNG direct injection spark-ignition engine

Abstract Objective: This study investigates the impact of Compressed Natural Gas (CNG) injection timing on the performance of a retrofitted CNG Direct Injection (CNG-DI) engine. The aim is to understand how varying injection timing affects key performance metrics such as torque, power, thermal efficiency, and fuel consumption in CNG-DI engines, providing insights for system optimization.
Methods: A 1298 cc, four-cylinder, four-stroke spark ignition engine with a compression ratio of 9 was retrofitted for CNG-DI operation. Modifications included a redesigned cylinder head for high-pressure injectors, controlled by a programmable gas ECU. The engine was tested with three injection timings: Early Injection (EI) at 230° BTDC, Optimal Injection (OI) at 180° BTDC, and Late Injection (LI) at 130° BTDC. Performance, Emission and Combustion parameters were evaluated across engine speeds from 1000 to 3100 rpm.
Results: Late Injection (LI) timing improved torque, power, BMEP, thermal efficiency, and volumetric efficiency by 4-16% within the 1000-2200 rpm range, attributed to better combustion dynamics. Optimal Injection (OI) timing achieved 4-12% higher performance in the 2500-2800 rpm range due to improved mixture formation. Early Injection (EI) timing resulted in 3-8% improvements at speeds above 2800 rpm, driven by faster combustion and increased peak power.
Conclusion: This study highlights the crucial role of injection timing in optimizing CNG-DI engine performance: Late Injection improves fuel efficiency at lower speeds, Optimal Injection enhances thermal efficiency at mid-range RPMs, and Early Injection maximizes power at higher RPMs. However, the study is limited by its focus on a single engine configuration and does not consider emissions or Life Cycle Assessment (LCA). Future research should investigate the environmental impact of injection timing through LCA and assess the long-term durability of engine performance.

Optimization and experimental investigation of compression ignition diesel engine performance and emission characteristics with Gulmohar biodiesel / diesel blends using Response Surface Methodology

Abstract This research focuses on biodiesel production from Gulmohar seeds using the transesterification method, with methanol as a catalyst at a 75% yield of Gulmohar oil biodiesel. Further, the biodiesel mixed with diesel at various blend ratios such as B20, B30, B40 and B50 and physicochemical characteristics are examined. The experimental investigation of performance and emission characteristics on single cylinder diesel engine using gulmohar biodiesel and diesel blends and compare the results with those from diesel. According to the findings, B20 blend emission characteristics and performance are very similar to the diesel fuel trend. Under full load, the Brake Specific Fuel Consumption (0.305 kg/kW.h) and Brake thermal efficiency (26.02%) for the B20 blend, which is closer to diesel and variations are 4.81% and 8.1%, respectively. Throughout the experiment, HC, CO, and smoke emission parameters were either less or equal for gulmohar biodiesel and its blends compared to diesel. However, the NOx emission of the biodiesel blends is 2 to 12% higher than diesel, but B20 has a 2.35% higher and lowest value among all the other blends. In addition, a central composite design (CCD) model using Response Surface Methodology (RSM) will be created, and the outcomes of a Compression Ignition (CI) engine will be optimized. Both analyses concluded that B20 is the most optimal blend among other blends and serves as a substitute for diesel.

A comparative study of diesel engine fueled by neem and ethanol biodiesel: performance, emissions, and sustainability assessment

Examining the emission characteristics of compression ignition (CI) engines using neem biodiesel in conjunction with ethanol and different percentages of exhaust gas recirculation (EGR) was the aim of the present research. In this experiment, a four-stroke, air-cooled, single-cylinder diesel engine with a rated power output of 5.2 kW was used to change the EGR percentage from 0% to 20%. Examining engine emission parameters and comparing them to diesel fuel was the aim of the research. The experiment indicates that as the EGR fraction in the fresh mixture rises, nitrogen oxide emissions fall. the most percentage of nitrogen oxide reduction as compared to diesel operating on its own. Using ethanol with varying EGR rates may lower emissions of hydrocarbons and carbon monoxide.

Analysis of the Energy and Emission Performance of an Automatic Biomass Boiler in the Context of Efficient Heat Management

Analysis of the Energy and Emission Performance of an Automatic Biomass Boiler in the Context of Efficient Heat Management

Mechanical properties and damage characterization of cracked granite after cyclic temperature action

Due to the unique geographical environment of the plateau, large-scale damage and destruction of fractured surrounding rock often occur during geotechnical engineering construction as a result of high-temperature cycles. Therefore, this study aims to investigate the mechanical properties and damage characteristics of fractured granite under the influence of cyclic temperature, uniaxial compression tests were conducted on granite specimens with pre-existing fractures at cyclic temperatures of 30 °C, 50 °C, 70 °C, 100 °C, and 130 °C. The study integrated analyses of characteristic stress, acoustic emission parameters, damage variables, fractal dimensions, and SEM to explore the mechanical properties and damage features of granite. The results indicated that at a 45° fracture inclination and a temperature of 70 °C, granite exhibited a distinct turning point in mechanical properties and damage characteristics. At the same cyclic temperature, granite with a 45° pre-existing fracture showed significant decreases in peak stress, elastic modulus, and σci/σm ratios, with the AE b-value drop point noticeably earlier, and both cumulative AE ring count and total energy reduced. The damage variable quickly reached its maximum, and the development of internal microcracks in the specimen is highly orderly. At the same fracture inclination, peak stress, elastic modulus, and σci/σm slightly increased at 70 °C, while AE ring counts and total energy were lower, indicating the degree of internal thermal damage in the specimen has significantly decreased, and the development of internal microcracks in the specimen has shown a marked reduction in orderliness. These findings provide theoretical insight into the meso-damage and failure mechanisms of granite influenced by different cyclic temperatures and fracture inclinations.

Study of bond-slip performance of steel tube with UHPC based on acoustic emission parameter analysis

Conventional methods for assessing bond performance are hindered by challenges in measuring strain and a lack of sufficient sensitivity to internal structural damage. This paper examines the bond behavior between steel and ultra-high-performance concrete (UHPC) based on acoustic emission (AE). The tests included a total of 2 concrete-filled steel tube (CFST) specimens and 4 concrete-encased CFST specimens. The bonding test was analyzed using AE parameters in combination with the damage process, damage morphology, and loading curve of the test specimens. Furthermore, damage correspondence was explored for the AE parameter indexes and the bond damage indexes of the conventional method. The findings reveal that the AE peak frequencies associated with the bond failure between steel tube and concrete span 30–100 kHz, 110–130 kHz, and 220–260 kHz. The AE event rate, cumulative absolute energy, Ib-curve, and percentage of tensile cracks can be used as judgmental and early warning features for interface damage. The damage process at the interface and the concrete crack development can be characterized by the severity index HI and the severity value Sr. The measurement curves obtained from various AE sensor positions exhibit remarkable similarity. A correlation can be discerned between the severity index (Sr) of the AE and the bond damage degree (Dt) ascertained through conventional methods, effectively mirroring the structural damage progression.

Direction‐Decoupled Light‐Emitting Metasurface via Guided‐Photoluminescence Manipulation

AbstractOn‐demand manipulation of light emissions is crucial for a variety of practical applications, including bio‐imaging and optical display, etc. Within this realm, the invention of metasurfaces provides powerful light–matter interaction capabilities for the control of multitudinous emission parameters. However, due to the omnidirectional, random, and incoherent nature of photoluminescence (PL) emission, the multiplexing modulation of PL remains a challenge and is rarely realized. Here, a direction‐decoupled light‐emitting metasurface (LEM) is originally demonstrated to display dual‐channel independent incoherent‐emission images based on guided‐PL manipulation. Utilizing the wavevector differences of guided‐PL between opposite pumping directions, the LEM is designed to enable selective unidirectional emission, thereby decoupling the directional freedom for PL multiplexing and realizing dual meta‐display. Besides, the direction‐multiplexed LEM can be integrated simultaneously with pumping‐light holography for multi‐dimensional meta‐display. Such programmable unidirectional emission manipulation and direction‐multiplexed PL meta‐display approaches promise light‐emitting techniques and can potentially find applications in multiplexing display, optical storage and encryption, etc.

Relationship Between Road Traffic Composition and Noise Emission: an Investigation Based on Hungarian National Public Road Traffic Data

Different vehicles contribute to the noise emission of the total road traffic in different ways and degrees. Therefore, emission calculation methods classify road vehicles based on their typical noise emission parameters. This article investigated the role of the four vehicle categories of CNOSSOS-EU method (light motor vehicles, medium heavy vehicles, heavy vehicles, and powered two-wheelers) in generating road traffic noise emissions. Based on traffic data available for national public roads in Hungary, the proportion of each vehicle category in the total road traffic was determined, providing the average distribution and other statistical parameters for each road category. The impact of changes in the traffic composition on noise emission was analysed based on the statistical parameters. The results show the dominance of light vehicles for all road categories (76–89% on average). The average proportion of heavy vehicles is also significant on controlled-access highways (motorways: 21%, expressways: 15%) and main roads (9%). The deviation from the average traffic composition can cause a noticeable difference in road traffic noise emission (up to nearly 3 dB). It was found that the impact of changing the proportion of heavy and light vehicles on noise emission is higher on roads inside built-up areas.

Performance, combustion and emission parameters of Scenedesmus obliquus methyl ester in single-cylinder CI engine: an experimental study

Performance, combustion and emission parameters of Scenedesmus obliquus methyl ester in single-cylinder CI engine: an experimental study

A Comparative Analysis of Advanced Machine Learning Models for the Prediction of Combustion, Emission and Performance Characteristics Using Endoscopic Combustion Flame Image of a Pine Oil–Gasoline Fuelled Spark Ignition Engine

This research focuses on using machine learning to predict the spark ignition engine’s combustion, performance, and emission parameters with bio-fuel blends such as pine oil blend, which significantly diminishes the environmental impact of traditional fuels, reduces the limitations of repeated engine experimentation and addresses the nonlinearities in engine test results contributing to sustainable cleaner fuel and energy solutions. The models used were Ensemble Decision Tree Bagging, Ensemble Least Squares Boosting, Gaussian Process Regression and Support Vector Machine Regression, with good generalization ability. Brake Specific Fuel Consumption data from the test engine trials and endoscopic image flame area data after spark timing at different crank angles (320, 400, 480, 560, and 640 after Spark Timing) were fed into the machine-learning models as predictors. The response variables were Brake thermal efficiency, Unburnt Hydrocarbons, Carbon monoxide, Carbon dioxide, Oxides of nitrogen, maximum In-cylinder pressure, and maximum heat release rate. The bootstrap technique was used to generate numerous datasets from the experimental data for data-driven model training and tested using both interpolative and extrapolative data. The experimental and predicted values for all these algorithms were subjected to repeated hyperparameter optimization trials and the best machine learning method was identified using the performance and error metrics. The Ensemble Least Squares Boost model showed the overall best correlation (R2) in the range of 0.97 - 0.99 for gasoline and pine oil PN20 blend for the predicted versus experimental engine parameters. The root-mean-squared error (RMSE) at maximum load ranged between 0.0086 - 0.3044 for gasoline and 0.0049 - 0.2046 for the Pine oil PN20 fuel blend respectively. Therefore, employing an Ensemble Least Squares Boosting machine learning framework can effectively predict the characteristics of gasoline engines using pine oil and blends. This approach serves as a virtual engine model, efficiently overcoming the limitations and complexities inherent in conventional engine experiments.

Optimizing emissions reduction investments in livestock-producing farms under non-linear holding cost and power demand: A comparative analysis of carbon tax and cap-and-trade environmental regulations

Investment in reducing emissions for many diverse companies is a practical strategy to achieve the emissions objectives as outlined by the United Nations Framework Convention on Climate Change. Livestock-producing farms often fall short of sustainability goals, even though many businesses have already adopted an investment strategy towards sustainability with success. Thereby, livestock-producing farms come under increasing responsibility to reduce their environmental impact, and it is now crucial to make simultaneous decision-making of inventory replenishment and emissions reduction investment to ensure the livestock farming industry's sustainability. In this study, a new path towards sustainable development is designed for livestock-producing farms by investigating the optimal investment plan for controlling emissions under carbon tax (CT) and cap-and-trade (C&T) environmental emissions guidelines. Taking into account both edible and non-edible parts of slaughtering mature growing items (GIs), as well as a non-linear holding cost structure and a power demand pattern for edible components, a comprehensive analytical approach implementing mathematical modeling methodology, economic evaluation, and carbon accounting approaches is accomplished. The most economical investment level that not only improves the environment but also adds to the farm's financial stability is identified by examining the interplay between the investments in emissions reduction and replenishment carried out by the farm. The numerical studies demonstrate that implementing an emission reduction strategy under both CT and C&T guidelines results in a 2.45% reduction in carbon emissions for a tax rate of $4.5. In order to further highlight the impacts of investment accessibility and emission parameters, several outcomes of a numerical analysis are reported. The findings demonstrate that implementation of investment strategy is always beneficial in achieving sustainability goals of the farm by lowering emissions under both CT and C&T emissions regulations.

Incremental Efficiency of Electricity Generation Based on Thermal Consumption at CHPPs and its Importance in Reducing Carbon Emissions

The aim of the study is to develop a methodological approach to assessing the incremental efficiency of electricity generation at CHPPs (specific heat consumption for changing electric power of turbine) in operating modes, taking into account both energy and environmental indicators. To achieve this goal, the following tasks were solved: the methodology, based on mathematical models of cogeneration steam turbines, both integral and differential indicators of heat rate per unit of electricity generation increment, was justified; a comprehensive generalization of the calculation data on the tur-bine T-50-12.8 type was performed; a quantitative assessment of the integral electricity generation and greenhouse gas emissions parameters was made at various loads and its comparison with the corre-sponding indicators in condensation mode. The most significant results are the following: generalized dependences of the integral specific heat consumption per unit of increase in electricity generation and carbon footprint were calculated for a wide range of changes in operating conditions; boundary condi-tions were established under which obtaining these parameters by opening the sliding grid of low-pressure section turns out to be energetically and ecologically feasible; it was determined that when increasing the capacity without bypassing the delivery water, the carbon footprint increment with an increase in the capacity of cogeneration turbines by opening the sliding grid will be less than for con-densing turbines. The significance of the results obtained lies in their applicability for solving prob-lems of ensuring maximum efficiency during involving cogeneration turbines in regulating electric load schedules in different boundary conditions.

Strength and damage constitutive model of backfill body after high temperature treatment

Constructing mine heat storage reservoirs with water-blocking capabilities using functional filling technology is an innovative approach for underground high-temperature heat storage. However, high-temperature environments can easily cause thermal damage to the backfill body, posing significant risks to the safety of the heat storage reservoir. In this study, we conducted mechanical and microstructural tests on heated backfill body samples to observe changes in their mechanical properties and microstructure at varying temperatures. The test results show that as the temperature goes from room temperature (25 °C) to 350 °C, the backfill body’s compressive strength goes down a lot, with peak stress dropping from about 7 MPa to 3 MPa. At the same time, its ductility and ability to deform go up. Higher temperatures intensify shear failure, leading to the extension of cracks along the shear direction and subsequent surface spalling. The proportion of shear failure increased from 27.86 % to 68.21 %. The microstructure of ettringite, calcium silicate hydrate, and calcium hydroxide breaks down at different temperatures, which makes the pores bigger and the structure less rigid. This study developed a thermal damage constitutive model that incorporates acoustic emission parameters. We can use this model to evaluate and predict the deformation and strength characteristics of backfill after exposure to high-temperature treatment.

Effect of hybrid nanoparticles dispersed ternary fuel blend on diesel engine performance and emissions: Experimental and Taguchi-Grey relation study

The present study deals with the influence of hybrid nanoparticles dispersed in ternary fuel mixtures on the evaluation of the performance and emission characteristics of a single cylinder diesel engine. The fuel blend consists of 70 % diesel, 20 % Madhuca longifolia biodiesel, and 10 % ethanol (by volume). The hybrid nanoparticles of ferric chloride (FeCl3) and graphene nanoparticles were then added to this ternary fuel mixture in different proportions, namely 50 mg/L and 75 mg/L, together with the surfactant and the dispersant in a ratio of 1:1. Moreover, the experiments were conducted on a diesel engine to evaluate the performance and emission parameters by varying different fuel samples, different loads (3, 6, 9, and 12 kgf) and injection pressures (i.e. 200, 225,and 250 bar). In addition, the Taguchi-Grey relation analysis was used for optimization, and the input parameters are fuel samples, loads and injection pressures. Experimental performance metrics, including brake specific fuel consumption (BSFC) and brake thermal efficiency (BTE), were improved when hybrid nanoparticles were added to the ternary fuel blend compared to diesel. At the same time, smoke opacity, nitrogen oxides (NOx), unburned hydrocarbons (UHC) and carbon monoxide (CO) emissions were reduced. Increasing the injection pressure also led to positive results, apart from NOx. Both performance and emissions were better for hybrid nanofuel based on surfactants and dispersants than for the base fuel, and it performed better of all dispersant-added nanofuels. The better results were obtained with D70B20E10NPs75QPAN75 mg/L than with the other fuel samples. The maximum BTE and lowest BSFC are 33.26 % and 0.206 kg/kWh, while the minimized CO, UHC, NOx and smoke values at full load are 0.019 %, 21 ppm, 833 ppm and 36.25 %, respectively, at full load and injection pressure of 250 bar By combining experimental investigations with the Taguchi -Grey method, a comprehensive and rapid assessment of the effects on the performance and emission characteristics of diesel engines was achieved.

Assessing the impact of three emission (3E) parameters on environmental quality in Canada: A provincial data analysis using the quantiles via moments approach

ABSTRACT Existing studies rarely examine the simultaneous effects of three emitting indicators (3E) – full emitting non-renewable, non-emitting renewable, and low-emitting nuclear - on three specific greenhouse gases: CO2, CH4, and N2O. We investigate the impact of three energy types on environmental quality, using Canadian data from 1990-2022. It incorporates macroeconomic policies, economic uncertainty, geopolitical risks, and eco-innovation, and employs the quantiles via moments method to explore the evolving relationships among these factors, considering provincial variances. Findings reveal that non-renewable energy sources deteriorate environmental quality by increasing CO2, CH4, and N2O emissions across all quantiles (from q.5 to q.95), while renewable and nuclear energies, along with eco-innovation initiatives, have a beneficial effect by reducing greenhouse gas emissions across all quantiles. Economic policy uncertainty is a contributing factor to greenhouse gas emissions across all quantiles, whereas geopolitical risks primarily impact the middle to upper quantiles (from q.50 to q.95). To counteract the lack of cross-sectional dependence in the quantiles via moments methodology, this paper employs Driscoll and Kraay’s standard errors approach to fortify its findings’ reliability. It concludes with policy suggestions promoting renewable energy and eco-innovation through increased investment, vibrant long-term policies, provincial collaboration, and adoption of green technologies.

Ductility and cracking behavior of UHPC-RC composite beam under bending test based on acoustic emission parameters

Ultrahigh-performance concrete (UHPC) possesses improved mechanical properties due to its high strength, durability, and toughness. Currently, there is a single method for detecting the cracking behavior and evaluating the ductility of the UHPC-reinforced concrete (RC) composite beam. As an important part of structural non-destructive monitoring techniques, the acoustic emission (AE) technique can be used to analyze the damage pattern of the structure by the variation characteristics of its individual parameters. On this basis, four-point bending tests were carried out on the RC beam and UHPC-RC composite beam, and the AE technique was used for ductility analysis and cracking behavior monitoring. The results showed that the UHPC material enhanced the flexural capacity of the UHPC-RC composite beam. The AE ring counts and energy parameters could be used to analyze the cracking process of the UHPC-RC composite beam during flexural damage. The proposed new ductility indices, AE ring counts ductility index (ARD) and AE energy ductility index (AED), differed from the displacement ductility indices within the range of 2 %, providing a new method for calculating ductility indices of concrete structures. During the failure stage, the UHPC-RC composite beam produced more tensile cracks at the early stage of cracking and the stage of damage compared to the RC beam. In addition, the b value of the RC beam had a large range of fluctuations during the failure stage, indicating that the RC beam produced more micro-cracks and macro-cracks and more damage compared to the UHPC-RC composite beam.

Model Test on Acoustic Emission Monitoring of Loess Slope Failure.

The three stages of loess collapse are characterized by notable concealment and sudden onset due to the sudden nature of loess collapse and the prolonged duration of the peristaltic deformation stage. Traditional displacement monitoring methods struggle to detect early signals of instability and failure, leading to poor timeliness in disaster warnings. This project begins by examining non-force field information related to the loess collapse process. It focuses on acoustic emission monitoring and employs model tests to identify effective waveguide rods for monitoring loess collapse. Additionally, the project investigates the evolution anomalies of acoustic emission parameters before and after loess collapse failure, aiming to establish early warning criteria for loess collapse based on acoustic emission. This work provides a theoretical basis for monitoring and early warning of loess collapses. This study evaluates five parameters of the active waveguide system: sensor installation method, filling material, waveguide rod wall thickness, outer wrapping material, and outer wrapping wall thickness. The densities of the filler materials were tested using the optimal parameters derived from the tests to identify the best configurations for active acoustic emission (AE) waveguide systems suitable for monitoring loess collapse. Subsequently, a one-sided connected loess collapse model was employed for indoor tests, integrating real-time AE monitoring with the active waveguide method. This model facilitates the exploration of AE response characteristics during loess collapse and the analysis of destructive forms of loess collapse and time-sequence evolution of AE ringing counts throughout the deformation and destruction process. Results indicate that using filler materials with high elasticity modulus, high compactness, and low Poisson's ratio, along with thin outer wrapping and waveguide rod walls, leads to strong AE signals. As deformation damage of loess collapse intensifies, the number of AE ringing counts notably increases. A rapid rise in cumulative ringing counts can indicate a "sudden increase", or the b-value may stabilize, providing precursor information for loess collapse.

Crack evolution and fractal characteristics of fractured red sandstone based on acoustic emission parameters

Rock is a widely used engineering material, and accurate understanding of its internal microcrack evolution process during loading can provide a theoretical basis for preventing instability and failure in rock engineering. The rock pressure test system and acoustic emission equipment were used to carry out uniaxial loading and acoustic emission monitoring tests on fractured red sandstone. Based on the RA and AF values of acoustic emission and the fractal theory, the internal crack patterns and evolution rules of red sandstone with different crack angles were explored. The results show that the compressive strength of red sandstone varies with the crack Angle in the shape of “U”, and there is an obvious stress drop after the elastic stage of 30° and 45° crack red sandstone, which has a good correspondence with the acoustic emission ringing count rate. During the loading process, the damage mainly caused by tension cracks first appears inside the rock, and then the tension cracks increase steadily and the shear cracks gradually increase, indicating that the rock enters the stage of fracture instability development. With the development of shear cracks, the peak strength is finally reached and the instability failure occurs. During the loading process of 30° fracture red sandstone, the corresponding stress drop phenomenon of “shear crack group” appears. According to the D/S statistical analysis of different crack samples based on acoustic emission ringing count, the fractal dimension presents a decreasing-rising-decreasing trend with the increase of crack inclination, which corresponds to the change of the complexity of crack development in rock.

Performance Characteristics of a Compression Ignition (CI) Engine Using an Environmentally Friendly Waste Plastic Fuel

Due to growing demands and depleting reserves of petroleum-based fuel, there is a necessity to find an alternative fuel for IC engines. Also, environmental concerns and globally faced problems like lots of garbage generated through plastics is a major issue in India. There is a significant disparity between plastic production and waste plastic generation. Therefore, the need for alternative fuels derived from municipal plastic waste has emerged to enhance the performance of IC engines, decrease emissions, and address other environmental concerns in line with the “Swachh Bharat Mission of India”. In this study, the alternative fuel was produced from a municipal mix of plastic waste by pyrolysis process. The experiments were carried out with a constant speed of 1500 rpm at different load conditions and fueled with standard diesel, waste plastic fuel and other blends to investigate IC engine performance and combustion and emissions in terms of brake thermal efficiency, brake power, brake specific fuel consumption, cylinder pressure, net heat release, mean gas temperature, rate of pressure rise, andbrake specific CO2, NOx, CO and HC emissions parameters were investigated and it is compared with standard diesel. The overall result shows that WPO20D80 and WPO30D70 exhibit the peak performance (torque, BP, BTE and BSFC) and lowest emissions (HC, CO, NOx) at all load conditions. Moreover, according to all the performance results, the lowest BSFC with maximum brake thermal efficiency and variations was 24.01% and 0.346 Kg/kWh for the WPO30D70 blend at part load condition. The minimum brake-specific NOx produced by the diesel blend at peak load conditions (WPO20D80) is 138.66 ppm, which is higher than other blends. This phenomenon may be attributed to an elevated proportion of pre-combustion and an extended ignition duration, resulting in a high cylinder temperature and an enhanced rate of heat release. This analysis contributes to a deeper understanding of the environmental implications associated with different fuel blends and load conditions. Notably, the blends ranging from 10% to 50% showed good tendencies to be utilized with diesel engines and consistently exhibit favourable brakespecific emission profiles, suggesting its potential as an environmentally friendly alternative fuel.