Emission Control Technologies Research Articles

Comparative LCA of thermal power plant with CCS and solar PV system: sustainability assessment in Indian context.

The study's objective is to evaluate and compare the sustainability of power production techniques for India's transition to clean power generation. It specifically focuses on coal-based power generation with emission control technologies, flue gas desulfurization (FGD) with carbon capture and storage (CCS), and compares it with solar photovoltaic (PV) systems. The study conducted a life cycle assessment (LCA) to determine the environmental impact of electricity generation in each scenario. Inventory data has been collected for each case through plant visits, emission modelling, and literature searches. The study evaluated midpoint and endpoint impact indicators utilizing the ReCiPe (H) assessment methodology. The economic viability of all the cases was determined by calculating the levelized cost of electricity (LCOE). The results showed that retrofitting an existing power plant with flue gas desulfurization (FGD) and carbon capture and storage (CCS) reduced efficiency by 30%, required 1.2 times more auxiliary power, and increased heat rates. The LCA results showed that the global warming potential (GwP) for FGD and CCS together was 0.614 kg CO2 eq. per kWh of power generation. On the other hand, the GwP for the solar PV system was much lower, at 0.043 kg CO2 eq. per kWh. There were trade-offs in both cases, but solar PV plants are more environmentally friendly than thermal power plants equipped with CCS systems in almost all categories. Furthermore, the LCOE results showed Rs 3.87 per kWh for an on-grid solar PV plant and Rs 5.33 for thermal power, with CCS and FGD showing solar as an economically more feasible option. Retrofitting thermal power facilities with emission control technology is necessary to achieve net zero emissions, but transition torenewable energy sources isinevitable.

Enhancing biodiesel engine performance and emission reduction using Fe and Zn coated zeolite catalytic converters

ABSTRACT This study evaluates the performance and emission characteristics of diesel, fish biodiesel (comprising 20% fish oil and 80% diesel), and fish biodiesel using Fe and Zn-coated zeolite catalytic converters. The research aims to mitigate environmental challenges associated with diesel engines by exploring the efficacy of metal-doped zeolite catalysts in reducing harmful emissions. Fish biodiesel was derived from fish waste via transesterification and tested in a single-cylinder diesel engine. Key performance metrics, including Brake Specific Fuel Consumption, Brake Thermal Efficiency, Exhaust Gas Temperature, cylinder pressure, Heat Release Rate, and ignition delay, were measured. Emission characteristics such as carbon monoxide, hydrocarbon, nitrogen oxide, and smoke opacity were also analyzed. Results showed diesel had the lowest Specific fuel consumption, ranging from 730 g/kWh at 25% load to 320 g/kWh at full load. Fish biodiesel exhibited higher Specific fuel consumption, from 770 g/kWh to 350 g/kWh. Regarding emissions, the NOx of the biodiesel increased significantly compared to diesel; the use of a catalytic converter has reduced the NOx emission to a maximum extent of 37.5% at full load for a Fe-coated converter. The Zn-coated converter also improved emissions by up to 33% for NO but was slightly less effective than the Fe-coated converter. The study concludes that Fe-coated zeolite catalytic converters significantly enhance biodiesel-fueled diesel engines’ performance and emission characteristics. Both catalytic converters reduced the smoke emission significantly. These findings highlight the potential for developing more efficient and eco-friendly emission control technologies and promoting using renewable transportation fuels.

Biofuel blends and nano-additives: a sustainable approach to diesel engine performance and emissions improvement

Abstract The utilization of compression ignition (CI) diesel engines has seen a substantial increase in recent years owing to their numerous advantages. However, the widespread adoption of these engines has also significantly contributed to environmental pollution issues, with diesel engines being recognized as major global contributors to exhaust emissions-related pollution. To address this issue, comprehensive research has been carried out on both emissions from diesel exhaust pollutants and advanced after-treatment technologies for emission control. This study aims to evaluate the efficiency and emissions of diesel fuel mixed with various ratios of biofuel derived from Karanja seeds (B10, B15, and B20). Among the different blends examined, B20 demonstrated superior performance in terms of brake thermal efficiency (BTE) and brake-specific fuel consumption (BSFC), along with lower levels of hydrocarbon (HC) and carbon dioxide (CO2) emissions compared to pure diesel. Further, the impact of nanoadditives, specifically titanium dioxide (TiO2), at different concentrations (80 ppm, 100 ppm, and 120 ppm), on B20 blends was evaluated. The findings indicated that B20 blended with 100 ppm of TiO2 exhibited superior performance in terms of BTE, BSFC, and lower emissions of HC, CO2, nitrogen oxides (NOx), and carbon monoxide (CO). From the results, the BTE increases from 1% to 33%, illustrating enhanced thermal efficiency under similar conditions. The average BSFC across all loads and speeds in the table is approximately 0.89 kg/kWh, while the average BTE stands at approximately 23.1%.

Online characterization of primary and secondary emissions of particulate matter and acidic molecules from a modern fleet of city buses

Abstract. The potential impact of transitioning from conventional fossil fuel to a non-fossil-fuel vehicle fleet was investigated by measuring primary emissions via extractive sampling of bus plumes and assessing secondary mass formation using the Gothenburg Potential Aerosol Mass (Go:PAM) reactor from 76 in-use transit buses. Online chemical characterization of gaseous and particulate emissions from these buses was conducted using chemical ionization mass spectrometry (CIMS) with acetate as the reagent ion, coupled with the Filter Inlet for Gases and AEROsols (FIGAERO). Acetate reagent ion chemistry selectively ionizes acidic compounds, including organic and inorganic acids, as well as nitrated and sulfated organics. A significant reduction (48 %–98 %) in fresh particle emissions was observed in buses utilizing compressed natural gas (CNG), biodiesels like rapeseed methyl ester (RME) and hydrotreated vegetable oil (HVO), and hybrid-electric HVO (HVOHEV) compared to diesel (DSL). However, secondary particle formation from photooxidation of emissions was substantial across all the fuel types. The median ratio of particle mass emission factors of aged to fresh emissions increased in the following order: DSL buses at 4.0, HVO buses at 6.7, HVOHEV buses at 10.5, RME buses at 10.8, and CNG buses at 84. Of the compounds that can be identified by CIMS, fresh gaseous emissions from all Euro V/EEV (Enhanced Environmentally friendly Vehicle) buses, regardless of fuel type, were dominated by nitrogen-containing compounds such as nitrous acid (HONO), nitric acid (HNO3), and isocyanic acid (HNCO), alongside small monoacids (C1−C3). Notably, the emission of nitrogen-containing compounds was lower in Euro VI buses equipped with more advanced emission control technologies. Secondary gaseous organic acids correlated strongly with gaseous HNO3 signals (R2=0.85–0.99) in Go:PAM, but their moderate to weak correlations with post-photooxidation secondary particle mass suggest that they are not reliable tracers of secondary organic aerosol formation from bus exhaust. Our study highlights that non-regulated compounds and secondary pollutant formation, not currently addressed in legislation, are crucial considerations in the evaluation of environmental impacts of future fuel and engine technology shifts.

Atomic-Scale Behavior of Perovskite-Supported Ir-Pd-Ru Nanoparticles under Redox Atmospheres.

An advanced materials solution utilizing the concept of "smart catalysts" could be a game changer for today's automotive emission control technology, enabling the efficient use of precious metals via their two-way switching between metallic nanoparticle forms and ionic states in the host perovskite lattice as a result of the cyclical oxidizing/reducing atmospheres. However, direct evidence for such processes remains scarce; therefore, the underlying mechanism has been an unsettled debate. Here, we use advanced scanning transmission electron microscopy to reveal the atomic-scale behaviors for a LaFe0.95Pd0.05O3-supported Ir-Pd-Ru nanocatalyst under fluctuating redox conditions, thereby proving the reversible dissolution/exsolution for Ir and Ru but with a limited occurrence for Pd. Despite such selective dissolution during oxidation, all three elements remain cooperatively alloyed in the subsequent reduction, which is a key factor in preserving the catalytic activity of the ternary nanoalloy while displaying its self-regenerating functionality and control of particle agglomeration.

Climate and air quality impact of using ammonia as an alternative shipping fuel

As carbon-free fuel, ammonia has been proposed as an alternative fuel to facilitate maritime decarbonization. Deployment of ammonia-powered ships is proposed as soon as 2024. However, NO x , NH3 and N2O from ammonia combustion could impact air quality and climate. In this study, we assess whether and under what conditions switching to ammonia fuel might affect climate and air quality. We use a bottom–up approach combining ammonia engine experiment results and ship track data to estimate global tailpipe NO x , NH3 and N2O emissions from ammonia-powered ships with two possible engine technologies (NH3–H2 (high NO x , low NH3 emissions) vs pure NH3 (low NO x , very high NH3 emissions) combustion) under three emission regulation scenarios (with corresponding assumptions in emission control technologies), and simulate their air quality impacts using GEOS–Chem high performance global chemical transport model. We find that the tailpipe N2O emissions from ammonia-powered ships have climate impacts equivalent to 5.8% of current shipping CO2 emissions. Globally, switching to NH3–H2 engines avoids 16 900 mortalities from PM2.5 and 16 200 mortalities from O3 annually, while the unburnt NH3 emissions (82.0 Tg NH3 yr−1) from pure NH3 engines could lead to 668 100 additional mortalities from PM2.5 annually under current legislation. Requiring NH3 scrubbing within current emission control areas leads to smaller improvements in PM2.5-related mortalities (22 100 avoided mortalities for NH3–H2 and 623 900 additional mortalities for pure NH3 annually), while extending both Tier III NO x standard and NH3 scrubbing requirements globally leads to larger improvement in PM2.5-related mortalities associated with a switch to ammonia-powered ships (66 500 avoided mortalities for NH3–H2 and 1200 additional mortalities for pure NH3 annually). Our findings suggest that while switching to ammonia fuel would reduce tailpipe greenhouse gas emissions from shipping, stringent ammonia emission control is required to mitigate the potential adverse effects on air quality.

The denitrification characteristics of Na2S2O8 solution in a falling film reactor

ABSTRACT Wet scrubbing technology is an effective emission control technology for marine diesel engines. Nitric oxide (NO) is one of the main component of ship emissions, the sodium persulfate (Na2S2O8) can facilitate the NO mass transfer process to a rapid reaction. Falling film reactors are widely used in rapid gas–liquid reactions, however, the reaction characteristics of denitrification using Na2S2O8 solution in a falling film reactor are not clear, which were investigated in this paper. The factors of NO mass transfer flux were tested with the liquid–gas ratio of 15 L/m3. The effects of solution properties and temperatures on the reaction driving force were studied by calculating the chemical reaction equilibrium constants and Gibbs free energy changes. The results showed that the NO mass transfer flux increased with the increase of temperature, Na2S2O8 concentration, O2 concentration and NO concentration. NO mass transfer flux increased by 41.00% and then decreased by 2.12% as the pH value increased from 7 to 10 and then rising to 12. The Gibbs free energy changes of alkaline solutions were 114.22%−130.99% lower than those of acidic solution at 303–343 K, and the chemical reaction equilibrium constants were higher. Na2S2O8/seawater system has great application potential in marine exhaust gas purification.

Emission characteristics and control technology of heavy metals during collaborative treatment of municipal solid waste incineration fly ash in iron ore sintering process

Emission characteristics and control technology of heavy metals during collaborative treatment of municipal solid waste incineration fly ash in iron ore sintering process

Non-PGM hollow fibre-based after-treatment for emission control under real diesel engine exhaust gas conditions

Hollow fibre (HF)-based technologies for emission control, as an alternative to the traditional monolithic technology, offers a promising route to the uptake of non-PGM catalytic systems. In this work, a series of Cu-doped LaCoO3 perovskites were investigated as potential non-PGM Diesel Oxidation Catalysts (DOC). Two HF-based modules, comprising single-channel (i.e., 1CM) and four-channel (i.e., 4CM) HFs respectively, were impregnated with the best catalyst candidate, and their performance was tested under real exhaust gas conditions, using a single-cylinder diesel engine. Compared to the 1CM, the 4CM demonstrated enhanced CO conversion, and reduced performance towards Total Hydrocarbon (THC) conversion. Overall, these findings reveal the influence of HF morphology on catalytic performance, and in turn, will contribute towards the refinement of HF-based technology for emission control, as well as enabling the transition towards non-PGM catalytic systems.

Reducing Tyre Wear Emissions of Automated Articulated Vehicles through Trajectory Planning.

Effective emission control technologies and eco-friendly propulsion systems have been developed to decrease exhaust particle emissions. However, more work must be conducted on non-exhaust traffic-related sources such as tyre wear. The advent of automated vehicles (AVs) enables researchers and automotive manufacturers to consider ways to further decrease tyre wear, as vehicles will be controlled by the system rather than by the driver. In this direction, this work presents the formulation of an optimal control problem for the trajectory optimisation of automated articulated vehicles for tyre wear minimisation. The optimum velocity profile is sought for a predefined road path from a specific starting point to a final one to minimise tyre wear in fixed time cases. Specific boundaries and constraints are applied to the problem to ensure the vehicle's stability and the feasibility of the solution. According to the results, a small increase in the journey time leads to a significant decrease in the mass loss due to tyre wear. The employment of articulated vehicles with low powertrain capabilities leads to greater tyre wear, while excessive increases in powertrain capabilities are not required. The conclusions pave the way for AV researchers and manufacturers to consider tyre wear in their control modules and come closer to the zero-emission goal.

Environmental reporting in Italian thermal power plants: insights from a comprehensive analysis of EMAS environmental statements

The global energy sector heavily relies on fossil fuels, significantly contributing to climate change. The ambitious European emissions' reduction targets require sustainable processes and alternatives. This study presents a comprehensive analysis of 73 Italian thermal power plants registered to the European Eco-Management and Audit Scheme (EMAS) aimed at assessing EMAS effectiveness in addressing and quantifying the environmental impacts of this relevant industrial sector. The analysis was based on EMAS environmental statements, publicly disclosing verified and certified data, with the secondary objective of evaluating if EMAS could be an efficient tool to improve the plants’ environmental performances. An inventory of technical and environmental aspects, adopted indicators, and allocated budgets was based on 2023 data. A strong correlation was found between the significance of the environmental aspects and the number of adopted indicators. Gaps were observed in describing aspects like “biodiversity” and “local issues”. Improvement objectives and budget allocation showed discrepancies and lacked correlation with the significance of the related environmental aspects. “Energy production” accounted for 68% of the total allocated budget; “environmental risks”, “emissions to air”, “electricity consumption”, and “local issues” were also key focus areas. Insufficient information on emission control technologies and progress tracking of improvement objectives was detected. This study highlights the need for thermal power installations to improve the selection of appropriate indicators and to better relate allocated budget to improvement objectives when implementing EMAS. Such measures would facilitate the quantification of the effective environmental impacts of the energy production sector, supporting future research on this topic, allowing stakeholders a better comparison among plants, and driving industry-wide improvements.

Single particle mass spectral signatures from on-road and non-road vehicle exhaust particles and their application in refined source apportionment using deep learning

With advances in vehicle emission control technology, updating source profiles to meet the current requirements of source apportionment has become increasingly crucial. In this study, on-road and non-road vehicle particles were collected, and then the chemical compositions of individual particles were analyzed using single particle aerosol mass spectrometry. The data were grouped using an adaptive resonance theory neural network to identify signatures and establish a mass spectral database of mobile sources. In addition, a deep learning-based model (DeepAerosolClassifier) for classifying aerosol particles was established. The objective of this model was to accomplish source apportionment. During the training process, the model achieved an accuracy of 98.49 % for the validation set and an accuracy of 93.36 % for the testing set. Regarding the model interpretation, ideal spectra were generated using the model, verifying its accurate recognition of the characteristic patterns in the mass spectra. In a practical application, the model performed hourly source apportionment at three specific field monitoring sites. The effectiveness of the model in field measurement was validated by combining traffic flow and spatial information with the model results. Compared with other machine learning methods, our model achieved highly automated source apportionment while eliminating the need for feature selection, and it enables end-to-end operation. Thus, in the future, it can be applied in refined and online source apportionment of particulate matter.

The Impact of Vehicle Technology, Size Class, and Driving Style on the GHG and Pollutant Emissions of Passenger Cars

Although technical improvements to engines and aftertreatment systems have the greatest impact on pollutant emissions, there is also potential for reducing emissions through driver behavior. This potential can be realized in the very short term, while better emission-control technologies only take effect once they have penetrated the market. In addition to a change in driving style, the vehicle owner’s choice of vehicle technology and size class will also have an impact on the future emissions of the vehicle fleet. The effects of different driving styles, the tire choice, the vehicle size class, and propulsion technologies on energy consumption and tailpipe and non-exhaust emissions are analyzed in this paper for different traffic situations and start temperatures for cars with petrol and diesel combustion engines and for battery electric vehicles. The analysis is completed with the corresponding upstream emissions from fuel and electricity production. The analysis is based on a vehicle simulation using the Passenger car and Heavy-duty Emission Model (PHEM), which is based on a large database of vehicles created using measurements of real driving conditions. For the assessment of the driving style, a novel method was developed in an H2020 project, which reproduces a measured trip with a virtual eco-driver. Carbon dioxide equivalent emissions (CO2eq) increase with increasing vehicle size, but can be reduced by around 20% for conventional vehicles and 17% for battery electric vehicles (BEVs) through an environmentally conscious driving style. On average, BEVs have around 50% lower CO2eq emissions than conventional vehicles, if the emissions from vehicle production are also taken into account. On an average journey of 35 km, the cold start of modern diesel vehicles accounts for around half of the total NOx emissions, while the proportion of cold starts for petrol vehicles is around 25%. Tire and brake wear together generate a similar amount of PN23 emissions as the exhaust gases from new cars.

CO2 solubility and amine volatility data for low-concentration solutions of MEA, AMP, PZ and CESAR-1 blend (AMP/PZ)

Water-wash section(s) effectively reduce amine compound emissions in amine-based carbon capture processes. Reliable predictions of the behavior of these emission control technologies depend on detailed understanding of the vapor-liquid equilibrium (VLE) of water wash system. However, existing vapor-liquid equilibrium data in the literature focus primarily on solvent-like amine concentrations in amine–CO2–H2O systems; hence, new low-concentration VLE data are needed. In this work, the CO2 solubility in low-concentration solutions of monoethanolamine (MEA), piperazine (PZ), 2-amino-2-methyl-1-propanol (AMP), and AMP/PZ blend (CESAR-1) was investigated for temperatures between 303 and 353 K at atmospheric pressure. Additionally, amine volatility measurements for CO2-loaded low-concentration solutions of MEA, PZ, AMP and CESAR-1 were performed in the range of 313–373 K and 8–96 kPa. Overall, the data show that the CO2 partial pressure increases with increasing CO2 loading and temperature. Similarly, the amine partial pressure increases with increasing pressure and temperature. The new experimental data were compared with two existing VLE models using electrolyte non-random two-liquid activity coefficient models to evaluate the ability of the latter to predict vapor-liquid equilibrium behavior. Both CO2 solubility and amine volatility predictions by the models tend to show significant deviations. The comparison highlight the need for such low-concentration data for all systems studied. This data shall serve to improve existing water-wash modeling tools.

A Study on Competency Mapping Factor in Faurecia Emissions Control Technologies India Pvt Ltd

The research is conducted to identify the key competencies required for the Information Technology professionals who all are in Faurecia Emissions Control Technologies India Pvt Ltd. The competencies used for the study were based on the following key areas such as Personal competencies, Technical Competency, Knowledge level competencies, Job-related competencies, Interpersonal Competencies and Management competencies which is involved with the performance of the employees and it also make them to become successful in their career. In order to attain the competitive position in the business field, every employee in the organization should involve in increasing the productivity and efficiency at the workplace. Similarly, the organization also has a challenging part in retaining the employees and motivating them to update themselves relevant to their specialization or key performance areas. Therefore, the competency mapping will be helpful for the researcher in identifying the expected skills of every individual with the actual skill set of the job. Based on the observed gaps, specific training and necessary steps to be taken to overcome the skill deficiency of the employees.

Towards sustainable charcoal production: Designing an economical brick kiln with enhanced emission control technology

In this research, a brick kiln integrated with pollutant emission control technology was designed and applied in order to produce charcoal from Eucalyptus Globules wood. The batch operation carbonization of wood biomass was undertaken in a 1.25 m3 volume brick kiln. A wet-packed scrubber was designed and constructed by filling gravels in a depth of 40 cm with aggregate sizes of 48–60 mm, 27–33 mm and 16–20 mm from the bottom to the top respectively aiming to treat emission from the charcoal-producing unit. The characteristics of the charcoal produced were determined to be composed of 9% moisture content, 1.5% ash content, 38% charcoal yield and a heating value of 27.53 MJ/kg. On the other hand, the wet scrubber integrated into a brick kiln was found to remove Hydrocarbons, CO2 and CO by 97.8%, 98.5% and 99% respectively, which makes it efficient and practical way of controlling the gasses released during producing of charcoal.

Adaptive time-step unscented kalman filtering (ATS-UKF) based observer design for urea selective catalytic reduction (SCR) performance of diesel engines

To reduce the number of sensors in the SCR catalyst, state feedback and fault diagnosis information are provided. Firstly, a model based on the coupling of flow, heat transfer, and gas-solid phase catalytic reaction in the SCR system is investigated in this paper. The parabolic partial differential equations are simplified by the variable substitution method and the method of lines approach (MOL). The simplified system of equations is solved by backward differentiation formulas (BDF) with adaptive adjustment time step strategy. Meanwhile, the chemical reaction parameters are accurately calibrated per second using the Levenberg-Marquardt method. Secondly, the ATS-UKF is designed in this paper, and to ensure the synchronisation between the ATS-UKF and the SCR model calculations, the time step of solving the BDF by the SCR model is taken as the time step of propagating the sigma points. Two observation scenarios are assumed: (1) no downstream NH3 concentration sensor, ammonia coverage and downstream NH3 concentration are observed by ATS-UKF; (2) no downstream NOx sensor, ammonia coverage and downstream NOx concentration are observed by ATS-UKF. Finally, the paper carries out bench tests. In the first case, the ammonia coverage obtained by the ATS-UKF reached 0.99 with respect to the model-calculated value R². The mean absolute error (MAE) between the observed and experimental values of the ATS-UKF for the downstream NH3 concentration was 2.76 ppm. In the second case, the ammonia coverage obtained by the ATS-UKF reached 0.99 with respect to the model-calculated value R², and the MAE between the observed and experimental values of the ATS-UKF for the downstream NOx concentration was 1.53 ppm. Environmental ImplicationThe Adaptive Time-Step Unscented Kalman Filtering (ATS-UKF) enhances urea Selective Catalytic Reduction (SCR) in diesel engines, improving environmental outcomes. This method minimizes sensor dependence, enabling more precise SCR system management and effective emission reduction. By advancing emission control technologies, ATS-UKF contributes to global air pollution mitigation efforts, supporting cleaner air and environmental sustainability. Its innovative approach in monitoring and predicting SCR performance marks a significant step towards eco-friendly diesel engine operation.

Study on the Emission Characteristics of Typical City Buses under Actual Road Conditions

Five typical in-use city buses in Tangshan with different emission standards, fuel power types, and emission control technology routes were selected as the research objects. PEMSs (Portable Emissions Measurement Systems) and OBD (On-Board Diagnostic) remote monitoring technologies were used to conduct research on actual road conditions and emission characteristics. The research aimed to analyze the driving characteristics of different power types of bus engines and after-treatment systems, as well as their impact on emissions. The results indicated that the actual road driving is mainly in the urban and suburban areas of the local region. Additionally, the VSP (Vehicle Specific Power) was found to be distributed in the low- and medium-speed range of mode Bin0~Bin24. The emission rates of each pollutant showed an increasing trend with the increase in VSP. THC and NOx emissions of CNG and LNG buses are significantly higher than those of gas–electric hybrid buses. However, the PM emissions are lower. Therefore, it is necessary to strengthen the NOx emission control of CNG and LNG buses. With the improvement in emission standards and the use of hybrid technology, CO2 and NOx emissions of China IV buses can be reduced by 13% and 53.5% compared with China III buses of the same tonnage. The CO2 and NOx emissions of China V buses using natural gas combustion and an electric mixture are 20% and 18.8% lower than those of China V buses of the same tonnage using only natural gas. In the actual operation of the diesel–electric hybrid bus equipped with the SCR (Selective Catalytic Reduction) system, the working time of the engine is about 35.5 ± 5%, and the working time of the SCR system only accounts for 65.5 ± 12%. The low working conditions of the SCR system and the low temperature of SCR system are the reasons for the high NOx concentration at the rear end of the SCR system when the hybrid electric bus is running at low speeds.

Prediction of transient NOX emission from a non-road diesel engine using a model combining Bayesian search and Population-based training

Due to the rising environmental concerns, particularly air quality, the emission regulations for non-road mobile machinery are becoming increasingly strict. Real-time emission prediction from diesel engines is significant for emission control and regional pollution estimation. This study aims to develop a machine learning model and optimize its hyperparameters by using a hyperparameter optimization method to NOX emission. Firstly, we collected NOX emission data from test under the non-road transient test cycle (NRTC) and built a significant dataset to choose a best model. Then, the model was trained by dataset and the hyperparameters were automatically optimized by combining Bayesian and Population based training. The accuracy of the optimized was indicated by an R2 value of 0.9784 with the 8 input features. The relative error in the cycle level was 1.3%. Lastly, the quality of NOX emissions during the cycle and the effect of each parameter on NOX emissions were analyzed. The results show that the model is able to predict the real-time concentration changes of NOX more accurately. It can provide a reference for the research and development of emission control technology for non-road mobile machinery.

Estimation of on-road mobile emissions based on the vehicle technology in a high-traffic avenue in Panama City, Panama

This study addresses the emissions from mobile sources in a busy avenue. Latest mobile emission inventories estimated pollutants based on fuel sales activities in the country. While this is an approved methodology, it does not consider the characteristics of vehicles and their emissions control systems. Applying the International Vehicle Emissions (IVE) model involves low costs, the vehicle fleet’s technology features, and the study region’s environmental parameters. The IVE model allows a better understanding of how vehicle technology impacts air quality. This study aims to generate information about vehicle emissions in Panama using a model that considers factors like vehicle technology, driving patterns, and local conditions, all of which influence air pollution in the region. The focuses are on passenger vehicles, the most common in the country, particularly in one of the densest districts. Carbon monoxide (CO), sulfates (SOx), nitrogen oxide (NO, and particulate matter (PMx) emissions were estimated with the IVE model, the first one stood out, represented 98% (6479.82 g/km) of the air pollutants emitted into the atmosphere by these four gases. Finally, it is established that the combination of emission control technologies and vehicle features is what will determine its emission reduction efficiency. Only in diesel vehicles, an increase in PMx emissions was identified.