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The use of diesel locomotives in transport is gradually decreasing due to electrification and the introduction of high-speed electric rails. However, in Korea, up to 30% of passenger and cargo transport still relies on diesel locomotives and vehicles. Many studies have shown that the exhaust gas from diesel locomotives poses a threat to human health. This study examined the characteristics of particulate matter (PM) in diesel locomotive engine exhaust. In a previous study, PM emissions were found to increase as the throttle was moved to a higher notch. The use of a portable emission measurement system (PEMS) in this study did not detect the highest emissions at notch 5, as is commonly found in gravimetric analyses. When comparing the mass concentrations, the notch 1 and 5 results were similar. However, at notch 8, there was a large difference between the mass concentrations collected on the filters. Further, to reduce the fine PM emitted from diesel locomotives, the ionic components, which account for the largest proportion of the total materials in fine PM, should be clearly identified. Therefore, in this study, an analysis of the weight, ionic composition, and metal components of fine PM discharged from a diesel locomotive was performed. Based on the results, Na+ (31%), Ca2+ (27%), NO3&minus, (24%), and SO42&minus, (13%), were the main ionic components, and the most abundant metal components being Ca (45%) and S (20%). In this study, the chemical components generated in diesel engines of other sources were compared, and as a result, different results were shown depending on the engine load and material ingredients. For the first time, a PEMS was used to measure PM from diesel vehicles, and a comparison was made with the results obtained by a gravimetric method. This is the first report of measuring PM concentrations by connecting a PEMS to a diesel locomotive, and of the distribution and characteristics of ions and heavy metals contained in the particles collected in the filter analyzed. The results indicate the importance of identifying the characteristics of fine PM emitted from a diesel locomotive and establishing an effective reduction measurement.

The indoor air quality of subway systems can significantly affect the health of passengers since these systems are widely used for short-distance transit in metropolitan urban areas in many countries. The particles generated by abrasion during subway operations and the vehicle-emitted pollutants flowing in from the street in particular affect the air quality in underground subway stations. Thus the continuous monitoring of particulate matter (PM) in underground station is important to evaluate the exposure level of PM to passengers. However, it is difficult to obtain indoor PM data because the measurement systems are expensive and difficult to install and operate for significant periods of time in spaces crowded with people. In this study, we predicted the indoor PM concentration using the information of outdoor PM, the number of subway trains running, and information on ventilation operation by the artificial neural network (ANN) model. As well, we investigated the relationship between ANN's performance and the depth of underground subway station. ANN model showed a high correlation between the predicted and actual measured values and it was able to predict 67∼80% of PM at 6 subway station. In addition, we found that platform shape and depth influenced the model performance.

Exposure to airborne particulate matter (PM) causes several diseases in the human body. The smaller particles, which have relatively large surface areas, are actually more harmful to the human body since they can penetrate deeper parts of the lungs or become secondary pollutants by bonding with other atmospheric pollutants, such as nitrogen oxides. The purpose of this study is to present the number of PM inhaled by subway users as a possible reference material for any analysis of the hazards to the human body arising from the inhalation of such PM. Two transfer stations in Seoul, Korea, which have the greatest number of users, were selected for this study. For 0.3–0.422 μm PM, particle number concentration (PNC) was highest outdoors but decreased as the tester moved deeper underground. On the other hand, the PNC between 1 and 10 μm increased as the tester moved deeper underground and showed a high number concentration inside the subway train as well. An analysis of the particles to which subway users are actually exposed to (inhaled particle number), using particle concentration at each measurement location, the average inhalation rate of an adult, and the average stay time at each location, all showed that particles sized 0.01–0.422 μm are mostly inhaled from the outdoor air whereas particles sized 1–10 μm are inhaled as the passengers move deeper underground. Based on these findings, we expect that the inhaled particle number of subway users can be used as reference data for an evaluation of the hazards to health caused by PM inhalation.