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Biodiesels have gained much popularity because they are cleaner alternative fuels and they can be used directly in diesel engines without modifications. In this paper, a brief review of the key studies pertaining to the engine performance and exhaust emission characteristics of diesel engines fueled with biodiesel blends, exhaust aftertreatment systems, and low-temperature combustion technology is presented. In general, most biodiesel blends result in a significant decrease in carbon monoxide and total unburned hydrocarbon emissions. There is also a decrease in carbon monoxide, nitrogen oxide, and total unburned hydrocarbon emissions while the engine performance increases for diesel engines fueled with biodiesels blended with nano-additives. The development of automotive technologies, such as exhaust gas recirculation systems and low-temperature combustion technology, also improves the thermal efficiency of diesel engines and reduces nitrogen oxide and particulate matter emissions.

The engineering method for the prediction of high-altitude rocket exhaust plume characteristics is proposed, which is based on Cai’s gas kinetic model and virtual collision method and the consideration of the influence on free flow. This engineering method can obtain the main characteristics such as plume range, species separation, flow characteristic distribution, and other main flow characteristics of high-altitude rockets. The single-phase gas of the axisymmetric circular nozzle of solid and liquid engines is taken as the research object, and the reliability of the prediction using the engineering method is verified by comparing the calculation results of the engineering method with the publication data and DSMC results. It provides a reference for the prediction of rocket exhaust plume characteristics at high altitudes.

Monitoring and prediction of exhaust gas emissions for heavy trucks is a promising way to solve environmental problems. However, the emission data acquisition is time delayed and the pattern of emission is usually irregular, which makes it very difficult to accurately predict the emission state. To deal with these problems, in this paper, we interpret emission prediction as a time series prediction problem and explore a deep learning model, a time-series forecasting Transformer (TSF-Transformer) for exhaust gas emission prediction. The exhaust emission of the heavy truck is not directly predicted, but indirectly predicted by predicting the temperature and pressure changes of the exhaust pipe under the working state of the truck. The basis of our research is based on real-time data feeds from temperature and pressure sensors installed on the exhaust pipe of approximately 12,000 heavy trucks. Therefore, the task of time series forecasting consists of two key stages: monitoring and prediction. The former utilizes the server to receive the data sent by the sensors in real-time, and the latter uses these data as samples for network training and testing. The training of the network throughout the prediction process is done in an unsupervised manner. Also, to visualize the forecast results, we weight the forecast data with the truck trajectories and present them as heatmaps. To the best of our knowledge, this is the first case of using the Transformer as the core component of the prediction model to complete the task of exhaust emissions prediction from heavy trucks. Experiments show that the prediction model outperforms other state-of-the-art methods in prediction accuracy.

The current study aimed to measure real-world emissions of three-wheeled autorickshaws powered by CNG and parameters (such as speed, acceleration, air-fuel (A/F) ratio, and rpm) influencing 3-wheeler emission rates. Test vehicles manufactured under Bharat Standards BS-III and BS-IV were monitored for exhaust emissions in Delhi city using a portable exhaust emission measurement system (AVL Ditest Gas 1000). The average emission rates of CO, HC, and NO gases for on-road autorickshaws were found to be 0.015 ± 0.017, 0.003 ± 0.0017, and 0.007 ± 0.005 g/s, respectively. Further, the highest emission factor values of 3.98 g/km and 3.93 g/km were estimated for CO and HC+NO gases, respectively. These values were found to be 1.4–3.2 times higher than the respective BS emission norms (BS III-CO =1.25 g/km, HC+NO = 1.25 g/km; BS-IV-CO = 0.94 g/km and HC+NO = 0.94 g/km). In this study, it was observed that the driving pattern and emissions were affected by traffic characteristics, driver behavior (constant acceleration and deceleration), and vehicle characteristics. The air-fuel ratio (A/F) was found to correlate highly with emission rates, followed by acceleration/deceleration and speed. Further analysis found that more than 70% of the aggregated emissions were due to acceleration and deceleration, which contributed to nearly 70% of the travel time. This was followed by the breakdown of speed and emissions into different bins, which found that 20–30 kmph has a higher emission rate and 40–50 kmph bin has a lower emission rate.

We investigated the impact of exhaust emissions from hydraulic support transporters on the air quality in roadways in mines. The dispersion distribution of diesel exhaust pollutants emitted by hydraulic support transporters was simulated with a dynamic mesh and computational fluid dynamics (CFD) simulations. More specifically, the dispersion and distribution of the main exhaust pollutants CO, HC, and NOx emitted by vehicles under the influence of the roadway wind flow were simulated with CFD simulations; in addition, the dispersion characteristics of exhaust pollutants from hydraulic support transporters during multiple driving phases in an alleyway (from transporting material, being unloaded at idle speed, to driving off without load) were predicted. The simulation results show that exhaust pollutants emitted by moving hydraulic support transporters can pollute the air in roadways and negatively affect the performance of gas monitoring devices in the roadway. Therefore, coal mining companies should optimize the ventilation design scheme to improve the air quality in roadways: they should increase the ventilation volume to dilute the emitted pollutants; in addition, the positions of underground gas monitoring devices should be adjusted to prevent interference from exhaust pollutants emitted by vehicles. This paper provides the theoretical basis and results of a preliminary investigation of the dispersion and transportation characteristics of exhaust pollutants emitted by vehicles in roadways. The results in this paper can serve as guidance for reducing the risk of occupational diseases.

Modern diesel engines are struggling to enhance the power density. This is usually realized by being equipped with a turbocharger, which demands higher performances on exhaust flow and exhaust waste energy recovery (WER). In the present study, we investigated the variations of exhaust flow and exhaust energy recovery performance with different geometrical parameters of exhaust system and proposed an evaluation and optimal design method of the exhaust system for a turbocharging diesel engine with a module pulse converter (MPC) system. The macro engine performances and the micro flow fields in exhaust system are obtained from the one/three dimensional (1D-3D) coupling simulation, and the energy of exhaust gas is quantified and analyzed with a concept of air power. It can be concluded that with a view to the exhaust performance and exhaust energy utilization, the diameter of the exhaust pipe should be set equal to the outlet diameter of the manifold and there is an optimized value of the contraction rate of the exhaust manifold. Besides, a parameter of the exhaust system called power potential coefficient is proposed to qualitatively evaluate the exhaust performance and exhaust energy.

NH 3 -SCR (selective catalytic reduction) is important process for removal of NOx. However, water vapor included in exhaust gases critically inhibits the reaction in a low temperature range. Here, we report bulk W-substituted vanadium oxide catalysts for NH 3 -SCR at a low temperature (100–150 °C) and in the presence of water (~20 vol%). The 3.5 mol% W-substituted vanadium oxide shows >99% (dry) and ~93% (wet, 5–20 vol% water) NO conversion at 150 °C (250 ppm NO, 250 ppm NH 3 , 4% O 2 , SV = 40000 mL h −1 g cat −1 ). Lewis acid sites of W-substituted vanadium oxide are converted to Brønsted acid sites under a wet condition while the distribution of Brønsted and Lewis acid sites does not change without tungsten. NH 4 + species adsorbed on Brønsted acid sites react with NO accompanied by the reduction of V 5+ sites at 150 °C. The high redox ability and reactivity of Brønsted acid sites are observed for bulk W-substituted vanadium oxide at a low temperature in the presence of water, and thus the catalytic cycle is less affected by water vapor. NH 3 selective catalytic reduction is an important technique for NOx removal but water vapor critically inhibits the reaction at a low temperature. Here the authors show bulk W-substituted VOx exhibits higher NOx removal ability than the TiO 2 supported vanadia catalyst in the presence of water.

Increasingly stricter regulations for vehicle emissions require more competitive exhaust emission control systems. Three-way catalysis is a major up-to-date emission control technology, though the activity could be limited during the cold start as well as steady state operation including the three regimes: rich (λ<1), lean (λ>1), and stoichiometric (λ=1). Periodic rich/lean switching emerges as a promising strategy to address this challenge. In this work, we investigate the influence of the switching process, using a fixed lambda air-to-fuel ratio amplitude of λ = 1±0.02 (0.5 Hz), on pollutant conversion from 100 to 400 °C, under a complex matrix including nitrogen monoxide (NO), carbon monoxide (CO), hydrogen (H 2 ), and hydrocarbons (C 1 -C 5 ), simulating the typical car exhaust gas. Moreover, two catalysts were tested: one homogeneously coated with Pd, and another zone-coated with Pd, both containing the same total amount of Pd, in order to identify the effect of the catalyst zone-coating and rationalize the use of increasingly scarce platinum group metals. Simple binary pollutant oxidation reactions were also performed to determine the reactivity of individual pollutant gases. Interestingly, NO, CH 4 and C 5 H 12 displayed highest conversions during the switching regime compared to steady-state periods, attributed to the beneficial balance between active site poisoning/regeneration during the rich/lean regimes respectively. The zone-coated catalyst showed an overall higher activity under the full gas mixture that could be explained by a slightly higher Pd content, more effective Pd-support interactions, exothermic effect or the better OSC properties.

The global shipping industry facilitates the movement of approximately 80% of goods across the world but accounts for nearly 3% of total greenhouse gas (GHG) emissions every year, and other pollutants. One challenge in reducing shipping emissions is understanding and quantifying emission characteristics. A detailed method for calculating shipping emissions should be applied when preparing exhaust gas inventory. This research focused on quantifying CO2, NOx, and SOx emissions from tankers, containers, bulk carriers, and general cargo in the Republic of Korea using spatio-temporal analysis and maritime big data. Using the bottom-up approach, this study calculates vessel emissions from the ship engines while considering the fuel type and operation mode. It leveraged the Geographic Information System (GIS) to generate spatial distribution maps of vessel exhausts. The research revealed variability in emissions according to ship types, sizes, and operational modes. CO2 emissions were dominant, totaling 10.5 million tons, NOx 179,355.2 tons, and SOx 32,505.1 tons. Tankers accounted for about 43.3%, containers 33.1%, bulk carriers 17.3%, and general cargo 6.3%. Further, emissions in hoteling and cruising were more significant than during maneuvering and reduced speed zones (RSZs). This study contributes to emission databases, providing a basis for the establishment of targeted emission control policies.

Scientists are rushing to study the tiny plastic specks that are in marine animals — and in us. Scientists are rushing to study the tiny plastic specks that are in marine animals — and in us. Credit: Will Parson/Chesapeake Bay Program Microplastics from the Magothy River are pictured at the laboratory of Dr. Lance Yonkos at the University of Maryland.