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School-age children are particularly susceptible to exposure to air pollutants. To quantify factors affecting children's exposure at school, indoor and outdoor microenvironmental air pollutant concentrations were measured at 32 selected primary and secondary schools in Hong Kong. Real-time PM10, PM2.5, NO2, and O3 concentrations were measured in 76 classrooms and 23 non-classrooms. Potential explanatory factors related to building characteristics, ventilation practice, and occupant activities were measured or recorded. Their relationship with indoor measured concentrations was examined using mixed linear regression models. Ten factors were significantly associated with indoor microenvironmental concentrations, together accounting for 74%, 61%, 46%, and 38% of variations observed for PM2.5, PM10, O3, and NO2 microenvironmental concentrations, respectively. Outdoor concentration is the single largest predictor for indoor concentrations. Infiltrated outdoor air pollution contributes to 90%, 70%, 75%, and 50% of PM2.5, PM10, O3, and NO2 microenvironmental concentrations, respectively, in classrooms during school hours. Interventions to reduce indoor microenvironmental concentrations can be prioritized in reducing ambient air pollution and infiltration of outdoor pollution. Infiltration factors derived from linear regression models provide useful information on outdoor infiltration and help address the gap in generalizable parameter values that can be used to predict school microenvironmental concentrations.

School-age children are particularly susceptible to exposure to air pollutants. To quantify factors affecting children's exposure at school, indoor and outdoor microenvironmental air pollutant concentrations were measured at 32 selected primary and secondary schools in Hong Kong. Real-time PM10, PM2.5, NO2, and O3 concentrations were measured in 76 classrooms and 23 non-classrooms. Potential explanatory factors related to building characteristics, ventilation practice, and occupant activities were measured or recorded. Their relationship with indoor measured concentrations was examined using mixed linear regression models. Ten factors were significantly associated with indoor microenvironmental concentrations, together accounting for 74%, 61%, 46%, and 38% of variations observed for PM2.5, PM10, O3, and NO2 microenvironmental concentrations, respectively. Outdoor concentration is the single largest predictor for indoor concentrations. Infiltrated outdoor air pollution contributes to 90%, 70%, 75%, and 50% of PM2.5, PM10, O3, and NO2 microenvironmental concentrations, respectively, in classrooms during school hours. Interventions to reduce indoor microenvironmental concentrations can be prioritized in reducing ambient air pollution and infiltration of outdoor pollution. Infiltration factors derived from linear regression models provide useful information on outdoor infiltration and help address the gap in generalizable parameter values that can be used to predict school microenvironmental concentrations. © 2020 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd

On-road mobile emission source is becoming one of the most important air pollution sources in the urbanized area, especially in urban regions with high traffic volume. This thesis presents a bottom-up methodology based on the results from large-scale microscopic agent-based transport model and associated with the use of local vehicle emission model, the Emission-FACtor-Hong Kong (EMFAC-HK) which developed from the Environmental Protection Department (EPD), to establish a high-resolution vehicle emission inventory for Hong Kong. With the aims of accurate vehicle emissions estimation, the vehicle emissions from this inventory were disaggregated with the vehicle emissions estimated by territory-wide vehicle emissions from the EPD. The multi-lateral detail analysis of this inventory was assessed with respect to different traffic parameters. This bottom-up method indicates that the diurnal cycle and spatial distribution of vehicle emissions rely on much up-to-date information. The deviation between the simulation result for the establishment of this emission inventory and the up-to-date traffic information has been investigated. Furthermore, this research proved that the introduction of an external source of new traffic data to MATSim can improve the accuracy of transport model, which in turn, the emission inventory accuracy can also be improved. This is the valuable tool when traffic counts or traffic information are not periodically updated, avoiding the use of arbitrary weighting factors to the roads and maintaining the validity of the emission inventory data for future improvements and studies. Based on the results of this study, it can improve the downstream air quality simulation work and the contribution of vehicle emissions to a different area or different road type have been investigated in this thesis

by King-wai Frank Leung., Questionaire in Chinese., Thesis (M.Phil.)--Chinese University of Hong Kong, 1992., Includes bibliographical references (leaves 50-58)., p.5, Chapter, Chapter I. --- Introduction --- p.6, The Importance of Personality and Social Background to Delinquency --- p.6, Brief Description of the MMPI --- p.8, Development of the MMPI Scales --- p.9, The Use of MMPI with Adolescents --- p.12, The Use of MMPI with Juvenile Delinquents --- p.15, The Use of MacAndrev Alcoholic Scales vith Adolescents --- p.17, Cross-Cultural Application of MMPI in Hong Kong… --- p.18, Purpose of the Study --- p.20, Chapter II. --- Methodoiogy --- p.28, Subjects --- p.23, Instruments --- p.30, Procedure --- p.32, Chapter III. --- Results --- p.34, Chapter IV. --- Discussion --- p.42, References --- p.50, Appendices --- p.59, Acknowledgement --- p.81, Notes --- p.82, http://library.cuhk.edu.hk/record=b5887080, Use of this resource is governed by the terms and conditions of the Creative Commons “Attribution-NonCommercial-NoDerivatives 4.0 International” License (http://creativecommons.org/licenses/by-nc-nd/4.0/)