Elevated emissions of volatile and nonvolatile nanoparticles from heavy-duty diesel engine running on diesel-gas co-fuels.

This study experimentally examines the effects of four diesel-gas co-fuels, two engine loads and an aftertreatment on regulated and unregulated emissions from a 6-cylinder natural-aspirated direct-injection heavy-duty diesel engine (HDDE) with an engine dynamometer. Fuel energy of ultra-low-sulfur diesel was substituted with 10% and 20% of gas fuels, including pure H2, CH4, and two CH4-CO2 blends. The particle number size distributions of volatile and nonvolatile nanoparticles were measured under ambient temperature and after 300 °C heating, respectively. The results show that the gas fuels caused increases of hydrocarbon emission, slight changes of NOx emission, and decreases of opacity. All four gas fuels resulted in elevated emissions of both volatile and nonvolatile nanoparticles at 25% and 75% load, in the range of 29% to 390%. The increased emissions of volatile nanoparticles were variable and without obvious trends. Special attentions should be given to the addition of H2 under high load, during which significant increases of volatile nanoparticles could be formed not only post-combustion (up to 1376%), but also post-diesel oxidation catalyst plus diesel particulate filter (DOC + DPF). The nonvolatile nanoparticles, on the other hand, could be effectively removed by the retrofitted DOC + DPF, with efficiency >98.2%. A noteworthy fraction of solid particles of sizes <23 nm were found in the exhaust, not being accounted for by current regulatory emission standard.

Features Importance Analysis of Diesel Vehicles' NOx and CO2 Emission Predictions in Real Road Driving Based on Gradient Boosting Regression Model.

In order to have an accurate and fast prediction of the artificial intelligence (AI) model, the choice of input features is at least as important as the choice of model. The effect of input features selection on the emission models of light diesel vehicles driven on real roads was investigated in this paper. The gradient boosting regression (GBR) model was used to train and to predict the emissions of nitrogen oxide (NOx), carbon dioxide (CO2), and the fuel consumption of real driving diesel vehicles in urban scenarios, the suburbs, and on highways. A portable emissions measurement system (PEMS) system was used to collect data of vehicles as well as environmental conditions. The vehicle was run on two routes. The model was trained with the first route data and was used to predict the emissions of the second route. There were ten features related to the NOx model and nine features associated with the CO2 model. The importance of each feature was sorted, and a different number of features were used as input to train the models. The best NOx model had the coefficient of determination (R2) values of 0.99, 0.99, and 0.99 in each driving pattern (urban, suburbs, and highways). Predictions of the second route had the R2 values of 0.88, 0.89, and 0.96 respectively. The best CO2 model had the R2 values of 0.98, 0.99, and 0.99 in each driving pattern, respectively. Predictions of the second route had the R2 values are 0.79, 0.82, and 0.83, respectively. The most important features for the NOx model are mass air flow rate (g/s), exhaust flow rate (m3/min), and CO2 (ppm), while the important features for the CO2 model are exhaust flow rate (m3/min) and mass air flow rate (g/s). It is noted that the regression models based on the top three features may give predictions very close to the measured data.

Carbonaceous composition changes of heavy-duty diesel engine particles in relation to biodiesels, aftertreatments and engine loads.

Three biodiesels and two aftertreatments were tested on a heavy-duty diesel engine under the US FTP transient cycle and additional four steady engine loads. The objective was to examine their effects on the gaseous and particulate emissions, with emphasis given to the organic and elemental carbon (OC and EC) in the total particulate matter. Negligible differences were observed between the low-sulfur (B1S50) and ultralow-sulfur (B1S10) biodiesels, whereas small reductions of OC were identified with the 10% biodiesel blend (B10). The use of diesel oxidation catalyst (DOC1) showed moderate reductions of EC and particularly OC, resulting in the OC/EC ratio well below unity. The use of DOC plus diesel particulate filter (DOC2+DPF) yielded substantial reductions of OC and particularly EC, resulting in the OC/EC ratio well above unity. The OC/EC ratios were substantially above unity at idle and low load, whereas below unity at medium and high load. The above changes in particulate OC and EC are discussed with respect to the fuel content, pollutant removal mechanisms and engine combustion conditions. Overall, the present study shows that the carbonaceous composition of PM could change drastically with engine load and aftertreatments, and to a lesser extent with the biodiesels under study.

Reducing emissions of persistent organic pollutants from a diesel engine by fueling with water-containing butanol diesel blends.

The manufacture of water-containing butanol diesel blends requires no excess dehydration and surfactant addition. Therefore, compared with the manufacture of conventional bio-alcohols, the energy consumption for the manufacture of water-containing butanol diesel blends is reduced, and the costs are lowered. In this study, we verified that using water-containing butanol diesel blends not only solves the tradeoff problem between nitrogen oxides (NOx) and particulate matter emissions from diesel engines, but it also reduces the emissions of persistent organic pollutants (POPs), including polycyclic aromatic hydrocarbons, polychlorinated dibenzo-p-dioxins and dibenzofurans, polychlorinated biphenyls, polychlorinated diphenyl ethers, polybrominated dibenzo-p-dioxins and dibenzofurans, polybrominated biphenyls and polybrominated diphenyl ethers. After using blends of B2 with 10% and 20% water-containing butanol, the POP emission factors were decreased by amounts in the range of 22.6%-42.3% and 38.0%-65.5% on a mass basis, as well as 18.7%-78.1% and 51.0%-84.9% on a toxicity basis. The addition of water-containing butanol introduced a lower content of aromatic compounds and most importantly, lead to more complete combustion, thus resulting in a great reduction in the POP emissions. Not only did the self-provided oxygen of butanol promote complete oxidation but also the water content in butanol diesel blends could cause a microexplosion mechanism, which provided a better turbulence and well-mixed environment for complete combustion.

Effects of biodiesel, engine load and diesel particulate filter on nonvolatile particle number size distributions in heavy-duty diesel engine exhaust.

Diesel engine exhaust contains large numbers of submicrometer particles that degrade air quality and human health. This study examines the number emission characteristics of 10-1000 nm nonvolatile particles from a heavy-duty diesel engine, operating with various waste cooking oil biodiesel blends (B2, B10 and B20), engine loads (0%, 25%, 50% and 75%) and a diesel oxidation catalyst plus diesel particulate filter (DOC+DPF) under steady modes. For a given load, the total particle number concentrations (N(TOT)) decrease slightly, while the mode diameters show negligible changes with increasing biodiesel blends. For a given biodiesel blend, both the N(TOT) and mode diameters increase modestly with increasing load of above 25%. The N(TOT) at idle are highest and their size distributions are strongly affected by condensation and possible nucleation of semivolatile materials. Nonvolatile cores of diameters less than 16 nm are only observed at idle mode. The DOC+DPF shows remarkable filtration efficiency for both the core and soot particles, irrespective of the biodiesel blend and engine load under study. The N(TOT) post the DOC+DPF are comparable to typical ambient levels of ≈ 10(4)cm(-3). This implies that, without concurrent reductions of semivolatile materials, the formation of semivolatile nucleation mode particles post the after treatment is highly favored.