Assessment of the Factors Influencing Sulfur Dioxide Emissions in Shandong, China

Sulfur dioxide (SO2) is a serious air pollutant emitted from different sources in many developing regions worldwide, where the contribution of different potential influencing factors remains unclear. Using Shandong, a typical industrial province in China as an example, we studied the spatial distribution of SO2 and used geographical detectors to explore its influencing factors. Based on the daily average concentration in Shandong Province from 2014 to 2019, we explored the influence of the diurnal temperature range, secondary production, precipitation, wind speed, soot emission, sunshine duration, and urbanization rate on the SO2 concentration. The results showed that the diurnal temperature range had the largest impact on SO2, with q values of 0.69, followed by secondary production (0.51), precipitation (0.46), and wind speed (0.42). There was no significant difference in the SO2 distribution between pairs of sunshine durations, soot emissions, and urbanization rates. The meteorological factors of precipitation, wind speed, and diurnal temperature range were sensitive to seasonal changes. There were nonlinear enhancement relationships among those meteorological factors to the SO2 pollution. There were obvious geographical differences in the human activity factors of soot emissions, secondary production, and urbanization rates. The amount of SO2 emissions should be adjusted in different seasons considering the varied effect of meteorological factors.

Strategies to Form Homogeneous Mixture and Methods to Control Auto-Ignition of HCCI Engine

Homogeneous charge compression ignition (HCCI) engine has emerged as a promising combustion technology. Theoretically, an HCCI engine can reduce both NOx and soot emissions significantly down to almost zero levels. This is possible as a result of two fundamental processes that occur in the HCCI engine, i.e. the homogeneous mixture and its autoignition characteristics. Neither spark plug nor injector is used in the HCCI engine. The autoignition of the homogeneous mixture is solely influenced by its chemical reactions inside the combustion chamber. However, this is where the problems start to occur. At low loads or too lean mixtures, misfire may occur, thus increasing the HC and CO emissions. At high loads or too rich mixtures, soot emissions and knocking tendency may increase. Moreover, an undesirable pressure rise due to knocking will increase the combustion temperature and potentially increase the probability of NOx formation. Therefore, the operating range of HCCI engine is very limited only to part loads. Controlling its combustion phasing play an important role to extend the narrow operating range of the HCCI engine. Despite numerous review articles have been published, classification of the approaches to achieve HCCI combustion in diesel engines were rarely presented clearly. Therefore, this review article aims to provide a concise and comprehensive classification of HCCI combustion so that the role and position of each strategy found in the literature could be understood distinctively. In short, two important questions must be solved to have successful HCCI combustion; (1) how to form a homogeneous mixture? and (2) how to control its auto-ignition?

An approach to the assessment of dimethyl carbonate and ethanol effect as gasoline oxygenating agents under engine conditions via a Computational Fluid Dynamics model

An ASTM-CFR engine was modeled through Computational Fluid Dynamics (CFD) coupled with chemical kinetics to evaluate the effect on combustion characteristics and engine emissions of dimethyl carbonate (DMC) and ethanol as gasoline components, the latter as reference oxygenating agent. Validation against experimental in-cylinder pressure data indicated adequate reproduction of these fuels combustion, all blends showing higher and earlier pressure peaks than neat gasoline (ca. 0.2 MPa and 2 CAD). Simulated temperatures were close for all fuels, though slightly advanced for the oxygenated blends (ca. 2 CAD). Similar behavior of the oxygenates was predicted regarding HC, CO and soot emissions: ca. 90% reduction in HC, CO, and soot emissions were observed, but ethanol displayed up to 3.5% CO2 reduction and 17% NOx increase, while DMC showed up to 7% decrease in CO2 and 6% increase in NOx. Considering the advantage of using chemical kinetics for combustion calculations in the CFD model, i.e., quantification of any species present in the reaction mechanism, including those difficult to observe/measure experimentally, concentrations of non-regulated emissions (e.g., formaldehyde) were studied. In particular, a minor increase in formaldehyde emissions was found with both oxygenated fuels. Albeit a first approach to assessing oxygenating compounds effects on gasoline combustion and emissions under engine conditions through a CFD + detailed chemistry model, the results underline the potential of DMC as gasoline oxygenating agent, and are a starting point for studying non-measured/non-regulated species and parametric engine analysis in future models.

Combustion and Emission Characteristics of Dual Fuel Engine for Different Parameters

The effects of compression ratio and fuel delivery advance angle on the combustion and emission characteristics of premixed methanol charge induced ignition by Fischer Tropsch diesel engine were investigated using a CY25TQ diesel engine. In the process of reducing the compression ratio from 16.9 to 15.4, the starting point of combustion is fluctuating, the peak of in-cylinder pressure and the maximum pressure increase rate decrease by 44.5% and 37.7% respectively. The peak instantaneous heat release rate increases by 54.4%. HC and CO emissions are on a rising trend. NOx and soot emissions were greatly decreased. The soot emission has the biggest drop of 50%. Reducing the fuel delivery advance angle will make the peak of in-cylinder pressure and the peak of pressure rise rate increase while the peak of heat release rate decreases. The soot emission is negatively correlated with the fuel delivery advance angle. When the fuel delivery advance angle is 16° CA, the soot emissions increased the most by 130%.

Hybrid Machine Learning Approaches and a Systematic Model Selection Process for Predicting Soot Emissions in Compression Ignition Engines

The standards for emissions from diesel engines are becoming more stringent and accurate emission modeling is crucial in order to control the engine to meet these standards. Soot emissions are formed through a complex process and are challenging to model. A comprehensive analysis of diesel engine soot emissions modeling for control applications is presented in this paper. Physical, black-box, and gray-box models are developed for soot emissions prediction. Additionally, different feature sets based on the least absolute shrinkage and selection operator (LASSO) feature selection method and physical knowledge are examined to develop computationally efficient soot models with good precision. The physical model is a virtual engine modeled in GT-Power software that is parameterized using a portion of experimental data. Different machine learning methods, including Regression Tree (RT), Ensemble of Regression Trees (ERT), Support Vector Machines (SVM), Gaussian Process Regression (GPR), Artificial Neural Network (ANN), and Bayesian Neural Network (BNN) are used to develop the black-box models. The gray-box models include a combination of the physical and black-box models. A total of five feature sets and eight different machine learning methods are tested. An analysis of the accuracy, training time and test time of the models is performed using the K-means clustering algorithm. It provides a systematic way for categorizing the feature sets and methods based on their performance and selecting the best method for a specific application. According to the analysis, the black-box model consisting of GPR and feature selection by LASSO shows the best performance with test R2 of 0.96. The best gray-box model consists of SVM-based method with physical insight feature set along with LASSO for feature selection with test R2 of 0.97.

Influence of Cavitation in Common-Rail Diesel Nozzles on the Soot Formation Process through Measuring Soot Emissions

The influence of cavitation in common-rail diesel nozzles on the soot formation process has been analysed experimentally. The soot formation process was characterized by measuring soot emissions in a single-cylinder engine, which was mounted on a test bench equipped with an opacimeter. In order to do this, operating conditions where the soot oxidation process was equivalent were chosen, whereby differences in the soot formation process were possible to be analysed. The results achieved confirm that cavitation provokes a soot formation process reduction. This reduction can be attributed by combining results of three effects: a reduction of the effective diameter, an increase in effective injection velocity, and an increase in turbulence level inside the nozzle orifice leading to a longer lift-off length. The three effects lead to a decrease in relative fuel/air ratio at the lift-off, therefore explaining the soot formation reduction.