Rainwater-Removal Image Conversion Learning with Training Pair Augmentation.

In this study, we proposed an image conversion method that efficiently removes raindrops on a camera lens from an image using a deep learning technique. The proposed method effectively presents a raindrop-removed image using the Pix2pix generative adversarial network (GAN) model, which can understand the characteristics of two images in terms of newly formed images of different domains. The learning method based on the captured image has the disadvantage that a large amount of data is required for learning and that unnecessary noise is generated owing to the nature of the learning model. In particular, obtaining sufficient original and raindrops images is the most important aspect of learning. Therefore, we proposed a method that efficiently obtains learning data by generating virtual water-drop image data and effectively identifying it using a convolutional neural network (CNN).

An estimation of vehicle kilometer traveled and on-road emissions using the traffic volume and travel speed on road links in Incheon City.

The objective of this study is to estimate the vehicle kilometer traveled (VKT) and on-road emissions using the traffic volume in urban. We estimated two VKT; one is based on registered vehicles and the other is based on traffic volumes. VKT for registered vehicles was 2.11 times greater than that of the applied traffic volumes because each VKT estimation method is different. Therefore, we had to define the inner VKT is moved VKT inner in urban to compare two values. Also, we focused on freight modes because these are discharged much air pollutant emissions. From analysis results, we found middle and large trucks registered in other regions traveled to target city in order to carry freight, target city has included many industrial and logistics areas. Freight is transferred through the harbors, large logistics centers, or via locations before being moved to the final destination. During this process, most freight is moved by middle and large trucks, and trailers rather than small trucks for freight import and export. Therefore, these trucks from other areas are inflow more than registered vehicles. Most emissions from diesel trucks had been overestimated in comparison to VKT from applied traffic volumes in target city. From these findings, VKT is essential based on traffic volume and travel speed on road links in order to estimate accurately the emissions of diesel trucks in target city. Our findings support the estimation of the effect of on-road emissions on urban air quality in Korea.

Characterization of particulate matter from diesel passenger cars tested on chassis dynamometers.

Emission characterization of particle number as well as particle mass from three diesel passenger cars equipped with diesel particulate filter (DPF), diesel oxidation catalyst (DOC) and exhaust gas recirculation (EGR) under the vehicle driving cycles and regulatory cycle. Total particle number emissions (PNEs) decreased gradually during speed-up of vehicle from 17.3 to 97.3km/hr. As the average vehicle speed increases, the size-segregated peak of particle number concentration shifts to smaller size ranges of particles. The correlation analysis with various particulate components such as particle number concentration (PNC), ultrafine particle number concentration (UFPNC) and particulate matter (PM) mass was conducted to compare gaseous compounds (CO, CO2, HC and NOx). The UFPNC and PM were not only emitted highly in Seoul during severe traffic jam conditions, but also have good correlation with hydrocarbons and NOx influencing high potential on secondary aerosol generation. The effect of the dilution temperature on total PNC under the New European Driving Cycle (NEDC), was slightly higher than the dilution ratio. In addition, the nuclei mode (DP: ≤13nm) was confirmed to be more sensitive to the dilution temperature rather than other particle size ranges. Comparison with particle composition between vehicle speed cycles and regulatory cycle showed that sulfate was slightly increased at regulatory cycle, while other components were relatively similar. During cold start test, semivolatile nucleation particles were increased due to effect of cold environment. Research on particle formation dependent on dilution conditions of diesel passenger cars under the NEDC is important to verify impact on vehicular traffic and secondary aerosol formation in Seoul.

Speed-dependent emission of air pollutants from gasoline-powered passenger cars.

In Korea emissions from motor vehicles are a major source of air pollution in metropolitan cities, and in Seoul a large proportion of the vehicle fleet is made up of gasoline-powered passenger cars. The carbon monoxide (CO), hydrocarbons (HC), oxides of nitrogen (NOx) and carbon dioxide (CO2) contained in the exhaust emissions from 76 gasoline-powered passenger cars equipped with three-way catalysts has been assessed by vehicle speed, vehicle mileage and model year. The results show that CO, HC, NOx and CO2 emissions remained almost unchanged at higher speeds but decreased rapidly at lower speeds. While a reduction in CO, HC and NOx emissions was noticeable in vehicles of recent manufacture and lower mileage, CO2 emissions were found to be insensitive to vehicle mileage, but strongly dependent on gross vehicle weight. Lower emissions from more recent gasoline-powered vehicles arose mainly from improvements in three-way catalytic converter technology following strengthened emission regulations. The correlation between CO2 emission and fuel consumption has been investigated with a view to establishing national CO2 emission standards for Korea.