A source term can be unidentified when poisonous gas is released to the atmosphere at an unexpected accident. To make evacuation plans for preventing human damage, it is necessary to estimate the source term from the observation data quickly. A lot of people have been damaged by chemical leakage and radioactive materials from nuclear power plant in the past year (e.g. The Bhopal chemical plant accident in 1984 and Chernobyl nuclear power plant accident in 1986). The result of radiation dose calculated by World-wide version of System for Prediction of Environmental Emergency Dose Information1) (WSPEEDI) could not timely be used to define evacuation zones at the Fukushima Dai-ichi (1st) nuclear power plant accident in 2011, because the intensity of the source was unidentified and observed data were insufficient. The lesson from this accident highlights the needs of source term estimation methods.

The object of this study is the development of source intensity estimation method for emergency response. This method estimates source intensity from comparisons of concentration distribution obtained by observation and concentration distribution calculated by atmospheric dispersion simulations assuming a unit release. In this report, the validation targeted the source term estimation during nuclear power plant accident.

Conventional source term estimation method uses calculated results of dispersion model like meteorological model (e.g. WRF/CHEM, WSPEEDI and so on) and long-range observation data. We developed a new operational source term estimation method using calculated results by Gaussian plume model and short-range observation data. Most observation points managed by nuclear power plant are located near the boundary of nuclear power plant within a few km from the source. Although meteorological models can’t resolute the calculation domain with less than 1 km. Gaussian plume model can speedy calculate the distribution of radioactive material corresponding with short-range observation data.

Some estimation was attempted with observed data of radiation dose at the Fukushima Dai-ichi nuclear power plant accident. The date of source term estimation is the morning 15th Mar 2011 when the maximum leakage was occurred at Unit.2 of Fukushima Dai-ichi nuclear power plant. The estimated release rates are almost identical in the order of magnitude.

Particulate air pollution, most often measured as the concentration level of particles <10 or 2.5 μm in diameter (PM10 and PM2.5), are associated in epidemiological investigations with adverse health outcomes including respiratory diseases and its relevant hospitalizations and higher mortality rates. The health impact of air pollution is even higher in the high density urban environment in Hong Kong because the complex building morphology may reduce the ventilation, hamper the dispersion, consequently, and lead to a higher air pollution concentration level. Thus, there is a need to investigate the influence of building morphology on the spatial variability of particulate air pollution. In this study, a series of traverse measurement have been conducted during summer time of 2014 for observing the spatial variability of particulate air pollution concentration in typical high density intraurban area in Hong Kong: Kowloon peninsula and the north part of Hong Kong Island. The urban morphology parameters (e.g. building coverage ratio and building volume) were analyzed using different raster resolution in GIS. Exploratory regression analysis was used to quantify the correlation between the particulate air pollutant concentration level and the surrounding building morphology. The result of R2 close to 0.4 implies the significance of the influence of building morphology on the particulate air pollutant concentration level. The output regression model can help local urban planners and designers to understand the relationship between planning and design principles and air pollution concentration levels and dispersion potentials. With this better understanding, appropriate strategies and measures can be adopted in the practical high density urban planning and design to improve the urban air quality in Hong Kong.

Computational Fluid Dynamics (CFD) models, based on the resolution of the Reynolds Average Navier Stokes (RANS) Equations are being increasingly used to simulate the dispersion of air pollutants in urban areas. Their ability to reproduce the flow modifications induced by the buildings at a fraction of the computational time required by Large Eddy Simulations (LES) models, make them an attractive choice for those real world applications (regulatory purposes, microscale abatement strategies, etc.) where mean values of pollutants concentrations are required. Parra et al. (Atmospheric Environment, 2010) and Santiago et al. (Science of the Total Enviroment,2013) developed a methodology based on a set of steady state simulations for a range of wind directions, that allowed to compute average concentration maps over large periods of time (weeks, months). In this work this methodology is further validated using measurements of NO2 from an intensive 4-week experimental campaign, which was carried out deploying a large number of passive samplers distributed in a heavily trafficked district in the city centre. The CFD-RANS simulations were done assuming that: a) the dominant air pollutant source is the road traffic, b) neglecting chemical reactions, and c) neglecting thermal induced circulations. Data of traffic intensity are from the regional traffic-demand model and were provided by the Madrid City Council were used. Results of the time averaged NO2 concentrations at the location of passive samplers were computed and compared with the measurements using statistical metrics and graphical plots. A good correlation between model estimates and measurements was obtained showing that this methodology, based on the CFD-RANS modelling is able to reproduce the spatial gradients of the pollutant distribution over several days average, with resolution of the order of meters. As for the temporal variation, hourly resolved concentrations were compared with measurements from an air quality monitoring station within the modelling domain. The maps of concentration produced with this methodology can have several practical applications related to air quality assessment and planning, personal exposure or estimating spatial representativeness of air quality stations.

Urban green development has influence on pedestrian comfort and pollutant dispersion. For this reason, the development of public open spaces is adapted to the new lifestyle in compact cities by upgrading the public environments used by pedestrians. Not only visual aspects like compacity, technical or social criteria, but also environmental, urban climate, air quality and thermal comfort must be highly considered. In this context, a framework for urban greening in a new undeveloped area in Madrid was developed in the ‘ECO-Valle Mediterranean Verandahways' project within LIFE Program. Previous studies were focused on evaluate the influence of artificial structures imitating trees (passive systems) on thermal conditioning. In the present work the same undeveloped urban zone in Madrid is studied, but it is focused on the effect of different types of vegetation in the main boulevard on air quality. Two main impacts are induced by urban vegetation: 1) pollutant concentration decreases by means of the deposition of pollutant on the leaves, and 2) concentration can increase because of trees alter flow and dispersion reducing the ventilation of traffic-emitted pollutants within streets.

The purpose of this study is to evaluate the effect of different urban green design on air quality in the main boulevard of this residential area using a computational fluid dynamics (CFD) model. Simulations are performed for steady state conditions applying 3D RANS equations with realizable k-epsilon turbulence model over an urban area with horizontal dimensions of 1 km x 0.8 km. Passive tracer are emitted at the bottom part of the boulevard and in the nearest streets representing traffic emissions. Different meteorological conditions and different types of vegetation design (locations, heights or leaf area density) within the boulevard are simulated. For the same meteorological conditions, concentration maps are compared for each scenario with no-vegetation case (base case) in order to determine the influence of the presence of vegetation. The results indicate that vegetation design (location and type) induces a great impact on pollutant concentration breathed by pedestrian. Therefore, selecting suitable urban vegetation designs are important for air quality.

In high density mega cities, air pollution has a higher impact on public health than cities of lower population density. Apart from higher pollution emissions due to human activities of densely populated street canyons, stagnated air flow due to closely packed tall buildings means lower dispersion potentials. The coupled result leads to high air pollution indexes being reported frequently at street side stations in Hong Kong. High density urban morphology need to be carefully designed to lessen the ill effects of high density urban living. This study addresses the knowledge-gap between planning and design principles and air pollution dispersion potentials in high density cities. The air ventilation assessment understandings for projects in high density Hong Kong are advanced to relate the air pollutant dispersion issues. The methods in this study are CFD simulation and parametric study. The SST κ- ω model was adopted after balancing the accuracy and computational cost in the comparative study. Urban-scale parametric studies were conducted to clarify the effects of urban permeability and building geometries on air pollution dispersion, for both the outdoor pedestrian environment and the indoor environment in the roadside buildings. Given the finite land resources in high-density cities and the numerous planning and design restrictions for development projects, the effectiveness of mitigation strategies is evaluated to optimize the benefits. A real urban case study was finally conducted to demonstrate that the suggested design principles from the parametric study was feasible in the practical high density urban design.