Emissions and Particulate Characteristics of Spark-Ignition Engines Fueled with Bioethanol–Gasoline Blends

Abstract

This article presents the results of research on the effects of various bioethanol concentrations in gasoline blends (E0, E10, E30, E50, E100) and increased fuel dosage (+10% and +20%) on spark-ignition engine performance and exhaust emissions. Experiments were conducted on a chassis dynamometer under strictly controlled laboratory conditions using a MAHA MGT-5 exhaust gas analyzer and a MAHA MPM-4 particulate matter analyzer. Power, torque, carbon monoxide (CO), carbon dioxide (CO₂), hydrocarbons (HC), oxygen (O₂), and particulate matter emissions were analyzed. It was found that up to a 50% bioethanol content, power and torque remained stable, while with E100, a significant decrease in these parameters was observed, partially offset by the increased fuel dosage. CO emissions systematically decreased with increasing bioethanol content, reaching minimum values at E100, while HC emissions generally decreased. CO₂ content did not show clear trends, while O₂ levels in the exhaust gas increased with higher ethanol concentrations. Particulate matter emissions were irregular, with the lowest values at E30 for the nominal dose and at E10 for the increased dose. The studies revealed significant nonlinearities in the effect of ethanol concentration on emissions, challenging the common assumption of monotonic changes. The results have practical implications for optimizing the calibration of engine control systems, meeting emission standards, and assessing the potential of bioethanol as a road transport fuel.

1. Introduction

Growing demands for pollutant emission reductions and the need to diversify energy sources create the need to seek alternative fuels to traditional gasoline. Bioethanol, a renewable fuel, is becoming a leading candidate in this field due to its high octane rating, the potential to partially reduce harmful exhaust emissions, and the potential for integration with existing spark-ignition engine fuel systems.

However, the use of bioethanol poses a number of challenges resulting from its physicochemical properties, which can affect both engine performance and energy efficiency. In practical terms, the use of bioethanol requires consideration of varying levels of its content in fuel blends. Low ethanol concentrations (E10–E30) can lead to subtle changes in combustion characteristics and emissions, while high concentrations, including full ethanol fuel (E100), pose other challenges, such as difficulty starting at low temperatures, differences in combustion heat, and changes in CO₂ and hydrocarbon emissions. Analyzing the effects of interactions between ethanol concentration and engine operating parameters is crucial for assessing the feasibility of practical use of this fuel in vehicles operated under various conditions. Beyond technical considerations, bioethanol’s environmental impact is also crucial. Reducing emissions of particulate matter and certain harmful exhaust gases can contribute to improving air quality in cities and limiting the negative impact of transport on the climate. At the same time, energy efficiency must be considered, as different ethanol and gasoline blends can lead to changes in fuel consumption, which has both economic and ecological implications.

Literature analysis indicates that one of the key directions of research on alternative fuels is determining the effect of different ethanol concentrations in gasoline blends on the performance and emissions of spark-ignition engines [1]. Numerous experimental results indicate that adding approximately 20% ethanol to gasoline provides an optimal compromise between fuel consumption, efficiency, and exhaust emissions, confirming the validity of further research on blends with moderate bioethanol concentrations. In recent years, modern predictive methods, including machine learning algorithms, have been increasingly used in this area, enabling more effective and faster adjustment of engine operating parameters to changing operating conditions [2]. One of the less studied aspects is the effect of bioethanol on engine noise emissions. Available studies indicate that both increasing the ethanol content in fuel and modifying the injection dose can significantly affect acoustic emission levels. However, there is a lack of research comprehensively combining this issue with the analysis of exhaust emissions and operating parameters, which constitutes a significant research gap [3]. Despite the wide availability of data on the effect of fuel mixture composition on emissions and fuel consumption, there is still a lack of detailed analyses encompassing the simultaneous effect of ignition timing modifications and fuel dose changes at various ethanol concentrations. This is particularly true for small-capacity engines with simplified injection systems [4]. The literature also emphasizes the need for research on the stability of fuel mixtures and their impact on the combustion process in specific engine configurations for which experimental data are lacking. Furthermore, in recent years, experimental studies have been published examining the possibility of optimizing the combustion process by enriching ethanol–gasoline mixtures with hydrogen. Initial results of these studies are promising and indicate improved combustion efficiency, but they remain sparse and do not cover the full range of engine operating parameter adjustments [5]. An important element of the development of the biofuels market is also their growing importance in various regions of the world, including Latin America, where the dynamic growth of bioethanol production plays an important role in the energy strategies of countries such as Brazil, Argentina, and Colombia [6]. At the same time, the role of biofuels in sustainable energy microgrids is gaining increasing importance, representing a significant step towards carbon neutrality and the development of a low-emission economy [7]. However, statistical data show that despite the intensification of pro-ecological activities, global primary energy consumption is still largely based on fossil fuels, which maintains pressure on the search for and implementation of alternative energy sources [8]. Progress in bioethanol production technology encompasses both innovative fermentation processes and the use of unconventional plant raw materials. An example is the use of pomegranate peel as a biomass source, which allows for waste reduction and increased bioethanol production efficiency [9]. In the context of assessing the environmental impact of biofuels, guidelines for life-cycle energy analysis of first-, second-, and third-generation biofuels are also important, providing a basis for comparing them with fossil fuels [10]. Further research on the use of pomegranate peels with new yeast strains, such as Kluyveromyces marxianus, indicates the possibility of further optimization of the efficiency of fermentation processes [11]. Another interesting direction is the production of bioethanol from hard-to-find raw materials, such as coconut shell fiber, which opens up prospects for local, low-cost biofuel production technologies [12]. In turn, research on the potential of first- to fourth-generation biofuels emphasizes the need to combine innovative production methods with analysis of energy efficiency and impact on emissions [13]. Practical effects of using bioethanol in blends with gasoline were presented, among others, in studies on small ignition engines, where power, torque, and exhaust gas composition were analyzed, which provides a valuable source of comparative data [14]. A broad review of biofuel applications in combustion engines indicates that alcohols, including ethanol, can effectively replace fossil fuels, reducing emissions and improving the operating parameters of engine units [15]. In recent years, there has been a growing interest in the use of vegetable oils for the production of biodiesel, which is due to their more environmentally friendly nature, and renewable nature compared with traditional diesel oil [16]. Numerous studies have also examined bioethanol, both as an additive to conventional fuels and as a standalone fuel used in internal combustion engines [17]. These experiments focused on assessing the impact of different ethanol concentrations on engine performance, exhaust emissions, and drive system durability, demonstrating, among other things, improved fuel blend octane rating, reduced carbon monoxide (CO) and hydrocarbon (HC) emissions, and the potential to reduce fossil fuel consumption [18]. At the same time, studies indicate certain limitations in the use of bioethanol, such as increased aldehyde emissions, higher fuel consumption resulting from ethanol’s lower calorific value, and limited availability of arable land, which prevents full satisfaction of the global demand for biofuels [19]. The literature also highlights environmental issues related to the production of biofuels from non-native plants, which may become invasive species, causing disruptions in local ecosystems [20]. The development of biofuel technology also requires a critical assessment of alternative raw material sources, such as microalgae, which are presented in many studies as a promising solution due to their high photosynthetic efficiency and lack of competition with food production [21]. At the same time, further analyses are necessary on the impact of biofuels on the combustion process and pollutant emissions in the context of the dynamic development of engine technologies and the changing properties of renewable fuels, which may significantly differ from those studied in the past [22]. It is also worth noting that the development of fuel technologies, including the increasing use of biofuels, may indirectly impact road safety. One of the serious challenges of modern transport remains road accidents; in 2018, 31,674 such events were recorded on Polish roads, resulting in 2862 deaths and over 37,000 injuries [23].

In the context of analyzing the effects of such events, Multi-Body System (MBS) simulations are increasingly being used, which allow for detailed modeling of collision mechanics and are widely used in forensic expertise to assess vehicle damage [24]. An analysis of recent publications indicates the growing importance of methods for measuring fuel consumption in laboratory and near-real-world conditions. Skrucany and co-authors developed a practical methodology for precisely detecting and assessing fuel consumption in spark-ignition engine vehicles using a chassis dynamometer [25]. The proposed approach allows everyday vehicle users to obtain reliable measurement results while maintaining test repeatability and limiting the impact of external factors. Interesting results regarding biofuels can be found in the work of Jan Gandolfo, who found that EGR was effective in suppressing combustion knock for E10 fuels, but high EGR values are required to achieve knock suppression for E30 and E50 fuels [26]. A compression-ignition engine fueled by biofuel is described in detail in [27], which allows us to familiarize ourselves with climate requirements and regulations.

This study is unique in that it covers the full range of ethanol content—from low concentrations (E10) to full ethanol fuel (E100)—in combination with variants of increased fuel injection doses, allowing for the assessment of synergistic or compensatory effects between these factors. Furthermore, the measurements were conducted using high-end research equipment, including a MAHA MGT-5 (Figure 1) exhaust gas analyzer (MAHA Maschinenbau Haldenwang GmbH & Co. KG, Haldenwang, Germany) and a MAHA MPM-4 particulate matter analyzer, under strictly controlled environmental conditions (temperature, pressure, humidity). The applied test procedure allows for high repeatability of results and their comparability with other studies. In a practical context, the obtained results can be used to

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optimize the calibration of engine control systems when fueled with bioethanol–gasoline blends;

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assess compliance with the requirements of current and future emission standards;

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develop recommendations for the use of bioethanol in vehicles operated in real world traffic conditions.

The analyses presented in this paper fill an important gap in the literature, providing both experimental data and interpretation from the point of view of energy efficiency and environmental impact.

Figure 1. MGT5 exhaust gas analyzer.

Figure 1. MGT5 exhaust gas analyzer.

2. Objective and Scope of the Study

The aim of this study is to evaluate the impact of bioethanol blends with gasoline at various concentrations (E0, E10, E30, E50, E100) and increased fuel injection (+10% and +20%) on spark-ignition engine performance and exhaust emissions. The analysis encompasses both dynamic engine characteristics, such as power and torque, as well as CO, CO₂, HC, O₂, and particulate matter emissions.

The scope of the research includes identifying the relationship between the bioethanol content in the fuel and its effect on energy and environmental parameters, including possible synergistic or compensatory interactions resulting from the use of increased fuel injection. The work focuses on determining trends in the impact of various fuel mixtures and injection dose combinations on engine performance and exhaust emissions, with an emphasis on practical implications for the use of bioethanol in road vehicles. The scope of the study also includes assessing the applicability of the results to

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optimizing the calibration of engine control systems for bioethanol–gasoline blends;

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supporting compliance with current and future emission standards;

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identifying directions for further research on the energy and environmental efficiency of blended fuels.

By focusing on these goals, the work provides a comprehensive analysis that can be used by both scientists and engineers working on implementing alternative fuels in real-world operating conditions.

3. Research Plan and Program

The study was designed to comprehensively assess the impact of bioethanol concentration in the fuel and increased injection rate on engine performance and exhaust emissions. The main variables in the experiment were the bioethanol concentration in the fuel mixture (E0, E10, E30, E50, E100) and the increased fuel rate (+10% and +20%). This approach allows for the analysis of synergistic and compensatory effects between these factors, representing a significant contribution to research on alternative fuels. The experiment included measurements of the engine’s dynamic characteristics, including power and torque, as well as exhaust emissions (CO, CO₂, HC, O₂, and particulate matter). The research program was divided into the following stages:

• Preparation of the fuel mixture and calibration of the injection system for each combination of bioethanol concentration and fuel rate.
• Conducting measurements under strictly controlled environmental conditions (temperature, pressure, humidity) using a repeatable engine warm-up procedure.
• Recording measurement data and preliminary analysis to identify trends and relationships between variables.

Table 1. Research variables.

Category of Variables	Description
Independent variable	- Injection computer settings, - Percentage share of bioethanol in the fuel mixture: 0%, 10%, 20%, 30%, 50%, 100%
Dependent variables	- Engine operating parameters: power, torque, noise level, - Exhaust gas composition: oxygen (O2), carbon monoxide (CO), carbon dioxide (CO2), hydrocarbons (HC) content.
Experimental data	- Engine type: 8-valve, spark-ignition, multi-point fuel injection, displacement 1242 cm3, power 44 kW (60 HP), torque 102 Nm, - Test conditions: temperature 15 °C, pressure 1000.4 hPa.

presents the categories of research variables and a detailed description of the independent and dependent parameters, as well as the experimental data.

Scheme 1 provides a graphical supplement to the technical description of this article. Figure 2 shows the tested vehicle placed on an engine dynamometer.

The adopted research plan enables a detailed analysis of the impact of bioethanol concentration and injection settings on engine performance and pollutant emissions, ensuring high repeatability and comparability of results. The obtained data allows for drawing practical conclusions regarding the optimization of engine control systems and assessing compliance with current and future exhaust emission standards.

4. Research Methodology

To ensure the reliability and accuracy of the obtained results, a detailed experimental procedure was developed to create conditions enabling reliable and independent measurements of engine operating parameters and exhaust emissions. A universal control module was installed in the vehicle (engine parameters

Table 2. Engine properties.

Engine type	Internal combustion, with spark ignition
Cylinder arrangement	inline engine
Type of injection	Multi-point MPI
Displacement [ccm]	1242
Compression ratio	10.0
Number of cylinders	4
Number of valves per cylinder	2
Turbocharging	none
Nominal power [KW]	44
Torque [Nm]	102
Exhaust emission standard	Euro 5

) replacing the factory control computer, allowing for flexible programming of engine operating parameters and precise changes to fuel injection dose. After installing the manufacturer’s standard software, the engine’s power and torque characteristics were verified. An external programming computer was then connected, allowing for controlled and repeatable adjustments to the engine control unit settings. To prepare the fuel mixture and increase the precision of the experiment, an additional 5 L tank was installed in the fuel system, allowing for non-invasive fuel changes and a 10% increase in fuel dose. Fuel blends containing ethanol at concentrations of 10%, 30%, 50%, and 100% were carefully filtered, and the standard fuel filter was temporarily removed to minimize the risk of system contamination. After each fuel change, the engine was run for 10 min to flush out the remains of the previous mixture, which ensured the cleanliness of the system and the repeatability of measurements.

Before starting the actual measurements, the engine was warmed up to a coolant temperature of 75 °C, and all tests were conducted in a room maintained at a constant temperature of 15 °C and a pressure of 1000.4 hPa, ensuring stable environmental conditions and comparable results. A chassis dynamometer equipped with an electrodynamic brake (

Table 3. Parameters of the stationary dynamometer.

Type of dynamometer	DC 2WD single-axle dynamometer (DynoTech DS04 2WD, Kościerzyna, Poland)
Weight	1180 kg
Width	3600 mm
Length	1120 mm
Height	350 mm
Maximum speed	260 km/h
Lifting capacity of the elevator	3500 kg

) and stabilizers to immobilize the vehicle was used for the measurements. The exhaust system was simultaneously connected to an exhaust gas analyzer and a particulate analyzer, enabling a comprehensive assessment of exhaust gas composition, including hydrocarbons (HC), oxygen (O₂), carbon monoxide (CO), and carbon dioxide (CO₂). All measurements were conducted at maximum engine load, simulating real-world operating conditions and ensuring the representativeness of the results. The collected data were subjected to detailed statistical analysis, taking into account the impact of changes in fuel parameters on specific engine performance and pollutant emissions indicators. Thanks to the adopted methodology, it was possible to determine the relationship between the share of bioethanol and energy efficiency and environmental impact, as well as to identify potential synergistic effects resulting from combining different levels of ethanol concentration with modifications of the injection dose.

To ensure the highest measurement accuracy, all measuring devices were initially calibrated according to the manufacturer’s recommendations. The MAHA MGT-5 exhaust gas analyzer and the MAHA MPM-4 particulate matter analyzer were calibrated using reference gases with known component compositions, minimizing systematic errors and increasing the repeatability of results. Each measurement set was tested before the actual tests began, and the control results were used to verify the system’s stability during the experiments. During the experiments, each fuel mixture variant was tested three times, and the data obtained from subsequent repetitions were statistically analyzed to eliminate potential random variations and ensure the reliability of the final results. In particular, mean values and standard deviations were calculated, and the variability of engine operating parameters and exhaust emissions depending on bioethanol concentration and fuel injection dose modifications was analyzed. This approach allowed for obtaining results that were not only repeatable but also fully comparable to other studies in the literature. Additionally, the use of high-quality equipment and controlled environmental conditions allowed for the identification of subtle synergistic and compensatory effects between different ethanol levels and fuel injection parameters, significantly enhancing the scientific value of the research. The data obtained also allow for a detailed assessment of the impact of bioethanol on engine energy efficiency, pollutant emissions, and the potential practical implications of using biofuels in vehicles operated under real-world conditions. The results can be used to

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optimize the calibration of engine control systems when fueled with bioethanol–gasoline blends;

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assess and optimize compliance with current and future exhaust emission standards;

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develop practical recommendations for vehicle manufacturers and end users.

The adopted research methodology guarantees high reproducibility of results and enables a thorough analysis of the relationships between fuel parameters, engine operating characteristics, and pollutant emissions, thus filling a significant gap in existing research on the use of bioethanol in combustion engines.

5. Analysis of Results

This chapter presents the results of research into the impact of bioethanol content in fuel on engine performance and exhaust emissions. The analysis includes three fuel delivery settings: nominal (

Table 4. Average values obtained for standard fuel dose settings.

Ethanol content	0%	10%	30%	50%	100%
Power [kW]	46.47	46.32	46.76	45.00	25.37
Torque [Nm]	100.9	100.8	102.4	101.2	68.6
Particulate matter [ppm]	143	104	70.8	121	101
CO [%]	2.3	0.89	0.25	0.30	0.08
CO2 [%]	10.6	12.7	11.5	9.7	10.0
HC [%]	334	292	356	183	142
O2 [%]	2.3	0.76	6.60	8.3	5.87

), increased by 10% (

Table 5. Average values obtained for the fuel dose increased by 10%.

Ethanol content	0%	10%	30%	50%	100%
Power [kW]	46.84	45.74	46.62	46.99	33.82
Torque [Nm]	100.7	100.4	103.1	103.9	84.1
Particulate matter [ppm]	111	122	102	125	128
CO [%]	3.9	0.45	0.85	0.20	0.05
CO2 [%]	14.0	11.6	11.7	10.7	10.7
HC [%]	260	161	217	104	55.7
O2 [%]	1.9	3.23	4.2	6.93	6.8

), and increased by 20% (

Table 6. Average values obtained for fuel dose increased by 20%.

Ethanol content	0%	10%	30%	50%	100%
Power [kW]	46.25	45.81	47.35	46.69	37.06
Torque [Nm]	100.1	98.8	102.4	102.2	92.1
Particulate matter [ppm]	115	106	114	119	107
CO [%]	2.99	1.95	2.89	0.26	0.04
CO2 [%]	11.5	10.6	10.2	12.0	12.5
HC [%]	232	210	268	88.5	63.0
O2 [%]	4.31	2.95	3.26	4.37	4.76

).

Table 4 presents the average values of engine operating parameters and exhaust emissions with standard fuel rates. Increasing the ethanol content in the fuel resulted in a slight decrease in engine power. These changes were not statistically significant for blends up to 50% bioethanol. However, for the fuel composed of 100% bioethanol, a significant power drop of over 45% was observed compared with the fuel without bioethanol. Maximum power (46.47 kW) was recorded for the conventional fuel, and minimum power (25.37 kW) for pure ethanol. Torque remained relatively stable for bioethanol content up to 50%, while for 100% bioethanol it dropped significantly to 68.6 Nm, representing a decrease of over 31% compared with the value for the standard fuel. Particulate matter emissions did not show a clear trend. The highest value (143 ppm) was observed with ethanol-free fuel, and the lowest (70.8 ppm) with 30% ethanol. Carbon monoxide (CO) content systematically decreased with increasing bioethanol content, indicating more complete fuel combustion. Carbon dioxide (CO₂) content did not change significantly, although a slight downward trend was noticeable with higher bioethanol content. Hydrocarbon (HC) content decreased with increasing bioethanol content; for pure bioethanol, HC emissions were 57% lower compared with conventional fuel. Oxygen (O₂) content in the exhaust showed irregular changes, with the highest concentration recorded for 50% bioethanol and the lowest for 10%, which may indicate inhomogeneous combustion of the mixture and requires further investigation.

Table 5 presents the average values of engine performance and emissions parameters with a 10% fuel increase. Engine power remained relatively stable for blends containing up to 50% bioethanol. The highest power (46.99 kW) was achieved with fuel containing 50% ethanol, and the lowest (33.82 kW) with 100% bioethanol—a 27.8% decrease compared with the nominal power. Torque remained stable for blends up to 50% bioethanol, while for pure bioethanol it dropped to 84.1 Nm, a 16.5% decrease compared with standard fuel. Particulate emissions showed fluctuations without a clear trend; the highest value (128 ppm) was recorded for 100% bioethanol fuel, and the lowest (102 ppm) for fuel with 30% bioethanol. CO content decreased already at 10% bioethanol and reached its lowest value (0.05%) at 100% bioethanol. HC emissions showed a variable but clear downward trend with increasing bioethanol content. The lowest HC value (55.7%) was measured for 100% bioethanol. O₂ content increased proportionally with increasing bioethanol content, being more than 3.5 times higher for 100% bioethanol than for standard fuel.

Table 6 presents the average values of the parameters for a 20% increase in fuel delivery. For blends containing up to 50% bioethanol, the changes in engine power were small and statistically insignificant. For 30% bioethanol, a slight increase in power was noted, which requires confirmation in future studies. For 100% bioethanol, however, the power decrease was 12.5% compared with the factory settings, while a 20% increase in fuel delivery improved power by 32.5% compared with the nominal settings. Torque changed slightly, significant only for pure bioethanol, where the decrease was 7.9%. Particulate matter emissions showed variability; the lowest values were recorded for 10% and 100% bioethanol, and the highest for 30% and 50%. CO decreased with increasing bioethanol content, except for 30%, where a temporary increase was noted.

Figure 3 shows that maximum engine power remains stable for ethanol content up to 50% at all fuel rates. The differences are not statistically significant. For 100% ethanol, a significant power drop is observed, which is partially offset by increasing the fuel rate. The largest power drop was measured for the factory settings when fueled with fuel containing 100% ethanol. This drop was over 45%. A 20% increase in fuel rate resulted in a 31.5% power increase compared with the factory settings and 100% ethanol fuel. Nevertheless, the power for the 100% ethanol fuel and a 20% increase in fuel rate was slightly over 20% lower than for gasoline with the factory settings.

Torque changes follow a similar pattern to power. As the ethanol content in the fuel increases to 50%, the torque drop is statistically insignificant. Only when the engine is fueled with fuel containing 100% ethanol does a significant drop occur, reaching almost 45% for the factory settings. Increasing the fuel dose reduces the torque drop compared with the factory settings, reaching approximately 8%. As with power changes, the drop is caused by the lower energy content of the fuel. The torque change pattern is shown in Figure 4.

The pattern of changes in particulate matter, shown in Figure 5, was irregular. The lowest values were achieved with a 30% ethanol fuel content and for the factory injection dose. The particulate matter was more than 50% lower than for the fuel without ethanol, with the same (factory) injection dose settings. A similarly low particulate matter content was measured with a 10% increase in the fuel dose, also for the 30% ethanol fuel. This irregular pattern of changes in particulate matter may result from incomplete fuel combustion, resulting from incomplete fuel vaporization.

Figure 6 shows that the carbon monoxide content in the exhaust gases decreases even when using fuel containing 10% ethanol. The lowest carbon monoxide content in the exhaust gases was observed for all fuel delivery settings when the engine was fueled with fuel containing 100% ethanol. This indicates complete fuel combustion.

Figure 7 shows that the carbon dioxide content in the exhaust gases varies heterogeneously. The highest carbon dioxide content in the exhaust gases was found for the engine fueled with fuel containing no ethanol, with the fuel dose increased by 10%. The lowest content was measured for the factory settings and fuel containing 50% ethanol. The amount of carbon dioxide in the exhaust gases depends on a number of factors; a reduction in carbon monoxide, indicating more complete combustion, is not simply reflected in an increase in carbon dioxide content in the exhaust gases, as it is most likely compounded by an increase in the amount of fuel consumed. Despite various statements regarding carbon dioxide as a harmful factor, it should be noted that, especially when using fuel in the form of alcohol, especially obtained from renewable sources, it can be considered a positive effect.

Figure 8 shows that despite the disproportionate changes in the hydrocarbon content in the exhaust gases, it can be concluded that increasing the ethanol content in the fuel reduces the amount of hydrocarbons in the exhaust gases. Regardless of the fuel injection settings, the lowest hydrocarbon content in the exhaust gases was always achieved when using fuel containing 100% ethanol. This indicates a positive effect on the fuel combustion process.

Figure 9 shows that the oxygen content in the exhaust gases changes irregularly. However, it can be noted that for fuels containing ethanol, the oxygen content is most often high. The highest oxygen content in the exhaust gases was found for the fuel containing 50% ethanol at the factory settings. The lowest oxygen content was also found for the factory settings for the fuel containing 10% ethanol. This corresponds to a relatively high carbon dioxide content and a low carbon monoxide content at identical parameters. The authors expected an increase in oxygen content in the exhaust gases with increasing ethanol content in the fuel (reduced oxygen demand). However, these changes overlap with a reduction in hydrocarbon content (more complete combustion), resulting in ambiguous changes in the oxygen content in the exhaust gases. Determining the causes of such changes will be the goal of further research, which will allow for a more comprehensive analysis of the combustion process of fuels containing ethanol.

6. Conclusions

The conducted research provided a comprehensive and multifaceted picture of the impact of varying bioethanol content in the fuel mixture on the operating parameters of a spark-ignition engine and the composition of exhaust gases. The methodology used, based on precise control of fuel dosage and ethanol concentration under precisely defined environmental conditions, ensured high reliability and repeatability of the obtained results. Importantly, the adopted approach allowed the identification of both expected and nonlinear effects, which in many cases might have gone unnoticed in studies conducted with less experimental control. One of the most noticeable results is a systematic decrease in carbon monoxide (CO) emissions with increasing bioethanol content, except for the fuel containing 30% ethanol, where a temporary increase in CO emissions was noted. For pure ethanol (100%), the CO content reached a minimum value of 0.04%, representing a significant reduction compared with the base fuel without ethanol. This confirms bioethanol’s potential as an effective additive for reducing incomplete combustion products and improving the overall efficiency of the combustion process. These results are particularly important in the context of increasingly stringent exhaust emission standards in the automotive sector. No clear monotonic relationship was observed between carbon dioxide (CO₂) and bioethanol content. A statistically significant 11.3% reduction in emissions compared with the reference fuel occurred only for blends containing 10% and 30% ethanol. For the remaining variants, the differences were not statistically significant, suggesting that other factors, such as combustion temperature, air excess ratio, and engine load characteristics, also influence CO₂ levels, which interact in complex ways with the fuel’s chemical composition. Analysis of hydrocarbon (HC) emissions showed a general downward trend with increasing bioethanol content, which is consistent with expectations resulting from the higher oxygen content in the ethanol molecule and the cleaner combustion process. The exception was the 30% ethanol blend, which recorded the highest HC emissions (268 ppm), exceeding even the value for pure gasoline (232 ppm). This may be related to deterioration in combustion stability or changes in the fuel atomization process within this concentration range. The lowest HC concentration was recorded for pure ethanol (63.0 ppm), which is only 27.2% of the baseline value. The oxygen (O₂) content in the exhaust gases had a nonlinear relationship with the bioethanol content. The highest O₂ level was recorded for the full ethanol fuel, while the lowest was for the 10% ethanol blend. The lack of direct proportionality may be due to the physical properties of ethanol—particularly its higher heat of vaporization—which affect combustion conditions and thus the instantaneous oxygen availability in the exhaust gas.

From a scientific perspective, this research makes several important, original contributions:

A three-stage fuel dosing strategy—using factory settings, a 10% increase, and a 20% increase—captured the subtle effects of interactions between ethanol concentration and engine fueling characteristics, a feat rarely seen in similar studies. Identification of nonlinear effects—detection of CO and HC emission anomalies at intermediate ethanol concentrations challenges the common assumption of monotonic changes, opening new directions for combustion engineering research. Tightly controlled measurement conditions—ensuring stable environmental parameters and a repeatable engine preparation procedurę—allowed for reliable isolation of the effect of fuel composition on the studied parameters.

Practical significance for sustainable transport—the obtained results support the development of strategies for reducing pollutant emissions while maintaining engine performance parameters. In summary, the research results confirm that bioethanol—especially at high concentrations—has significant potential for reducing toxic exhaust emissions, although its impact on engine power and efficiency requires precise calibration of the fuel dose. The observed nonlinearities in emissions highlight the need for further research, particularly with blends containing 20–40% ethanol, where the combustion process exhibits instability. The originality of this study stems from both the methodology used and the identification of complex relationships between fuel composition, fueling conditions, and pollutant emissions, which adds value to scientific discussions and engineering practice.