The effect of various urea-in-water solution types on exhaust particle number emission.

In order to qualitatively evaluate the impact of urea-in-water solution on the particle number emission, five different urea types were chosen under diesel engine bench test. The results show that compared to the instantaneous particle concentrations without injection, the instantaneous particle concentrations with injection increase distinctly, which are larger around 0.3-1.2 times than that without urea-in-water solution. At high speed phase, the instantaneous particle concentrations with urea-in-water solution injection rise obviously, especially for C and E solutions. In addition, the particle size distribution characteristic does not change with the urea-in-water solution dosing. The PN emission factors follow the sequence of C solution > E solution > A solution > B solution > D solution. It is deduced that the metallic element contents in the urea-in-water solution play a key role for the PN emission factor. In the future, the particle formation due to urea-in-water solution injection should be given more attention.

NOx emission deterioration in modern heavy-duty diesel vehicles based on long-term real driving measurements.

NOx emissions from diesel vehicles generally deteriorate with increased durability mileage owing to the wear and deterioration of engines and after-treatment systems. Three China-VI heavy-duty diesel vehicles (HDDVs) were selected for four-phase long-term real driving emission (RDE) tests using the portable emission measurement system (PEMS). After 200,000 km of on-road driving, the maximum NOx emission factor of the test vehicles (387.06 mg/kWh) was found to be significantly lower than the NOx limit of 690 mg/kWh. Under all driving conditions, the NOx conversion efficiency of selected catalytic reduction (SCR) decreased almost linearly as the durability mileage increased. Importantly, the deterioration rate of the NOx conversion efficiency in low-temperature intervals was discernibly higher than that in high-temperature intervals. The NOx conversion efficiency at 200 °C dropped by 16.67-19.82% with higher durability mileage; however, the highest values at 275-400 °C only decreased by 4.11%. Interestingly, the SCR catalyst at 250 °C showed strong NOx conversion efficiency and durability (maximum decline of 2.11%). Overall, the poor de-NOx performance of SCR catalysts at low temperatures significantly challenges the long-term effective control of NOx emissions from HDDVs. Thus, improving the NOx conversion efficiency and durability at low-temperature intervals is the top priority for SCR catalyst optimization; NOx emissions from HDDVs at low velocities and loads should also be monitored by environmental authorities. The linear fitting coefficient for the NOx emission factors of the four-phase RDE tests was 0.90-0.92, indicating that NOx emissions deteriorated linearly with an increase in mileage. Based on the linear fitting results, the NOx emission control of the test vehicles during 700,000 km of on-road driving was highly likely to be qualified. These results can be used by environmental authorities to supervise the NOx emission conformity of in-use HDDVs after validation using other types of vehicles.

Strategies for the content determination of capsaicin and the identification of adulterated pepper powder using a hand-held near-infrared spectrometer.

To achieve the goals of rapid content determination of capsaicin and adulteration detection of pepper powder. The method based on the hand-held near-infrared spectrometer combined with ensemble preprocessing was proposed. DoE-based ensemble preprocessing technique was utilized to develop the partial least squares regression models of red pepper [Capsicum annuum L. var. conoides (Mill.) Irish] powders. The performance of final models was evaluated using coefficient of determination (R2), root mean square error of prediction (RMSEP) and residual predictive deviation (RPD). Model development using selective ensemble preprocessing gave the best prediction of capsaicin in Yanjiao pepper powder (R2 = 0.9800, RPD = 7.090, RMSEP = 0.00689) and Tianying pepper powder (R2 = 0.8935, RPD = 3.017, RMSEP = 0.06154). Moreover, the potential of grey wolf optimizer-support vector machine (GWO-SVM) to detect adulterated pepper powder was investigated. The samples were composed of two authentic products and three different adulterants with different adulteration levels. The results showed that the classification accuracy of GWO-SVM model for Yanjiao peppers was over 90 %, which realized the adulteration detection of Yanjiao pepper. And GWO-SVM showed better performance in detecting adulterated Tianying pepper compared to hierarchical cluster analysis, orthogonal partial least squares discriminant analysis and random forest. In summary, the quality control strategy established in this paper can provide a solution for the adulteration detection and quality evaluation of pepper powder in a rapid and on-site way.