Search

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., (Copyright © 2017 Elsevier B.V. All rights reserved.)

Emission reduction is one of the most efficient control measures in fuel-powered locomotives. The purpose of this study was to determine the reduction in particulate matter (PM) and black carbon (BC) emissions following the installation of a fuel activation device (FAD). The FAD was developed to enhance fuel combustion by atomizing fuel and to increase the surface area per unit volume of injected fuel. Emission reduction by the FAD was evaluated by installing a FAD in an operating diesel locomotive in Mongolia. The test was conducted on a train operating on a round-trip 238-km route between Ulaanbaatar and Choir stations in Mongolia. The fuel consumption rate was slightly reduced following the FAD installation. The FAD installation decreased PM and BC emissions in the diesel locomotive, especially coarse PM. The PM 10 reductions achieved after FAD installation were 58.0, 69.7, and 34.2% for the constant velocity, stopping, and acceleration stages of the train's operation, respectively. The BC reduction rates were 29.5, 52.8, and 27.4% for the constant velocity, stopping, and acceleration stages, respectively., (Copyright © 2016 Elsevier B.V. All rights reserved.)

Given that around eight million commuters use the Seoul Metropolitan Subway (SMS) each day, the indoor air quality (IAQ) of its stations has attracted much public attention. We have monitored the concentration of particulate matters (PMx) (i.e., PM10, PM2.5, and PM1) in six major transfer stations per minute for three weeks during the summer, autumn, and winter in 2014 and 2015. The data were analyzed to investigate the relationship between PMx concentration and multivariate environmental factors using statistical methods. The average PM concentration observed was approximately two or three times higher than outdoor PM10 concentration, showing similar temporal patterns at concourses and platforms. This implies that outdoor PM10 is the most significant factor in controlling indoor PM concentration. In addition, the station depth and number of trains passing through stations were found to be additional influences on PMx. Principal component analysis (PCA) and self-organizing map (SOM) were employed, through which we found that the number of trains influences PM concentration in the vicinity of platforms only, and PMx hotspots were determined. This study identifies the external and internal factors affecting PMx characteristics in six SMS stations, which can assist in the development of effective IAQ management plans to improve public health., (Copyright © 2015 Elsevier B.V. All rights reserved.)

Numerous reports have shown that fine particulates threaten human health. Since their health impact is associated with both mass and number concentrations, it is necessary to evaluate the emission standards for particulate mass accordingly. This study examined the particulate matter characteristics of diesel locomotive engine exhaust at various engine ratings. Diesel engine exhaust was collected via a dilution tunnel and the concentration and size distribution of fine particles were measured by a scanning mobility particle sizer. Exhaust gasses were measured simultaneously by a stack sampler. The maximum carbon monoxide emission was reached at 59% of the maximum rating, after which emissions decreased. The particle count median diameter increased with the engine rating, until a maximum was reached at 40% of the maximum rating. Most exhaust particles were nanoparticles with the nuclei mode range, a particle diameter (D(P))<50 nm. The increase in particles with the accumulation mode range, 50