Tracing Evolution of Angle-Wavelength Spectrum along the 40-m Postfilament in Corridor Air

Postfilamentation channel resulting from filamentation of freely propagating 744-nm, 5-mJ, 110-fs pulse in the corridor air is examined experimentally and in simulations. The longitudinal extension of postfilament was determined to be 55–95 m from the compressor output. Using single-shot angle-wavelength spectra measurements, we observed a series of red-shifted maxima in the spectrum, localized on the beam axis with the divergence below 0.5 mrad. In the range 55–70 m, the number of maxima and their red-shift increase with the distance reaching 1 μm, while the pulse duration measured by the autocorrelation technique is approximately constant. Further on, for distances larger than 70 m and up to 95 m, the propagation is characterized by the suppressed beam divergence and unchanged pulse spectrum. The pulse duration increases due to the normal air dispersion.

Improved Wet Scavenging Schemes for Air Dispersion Modeling of Cs-137 in the Fukushima Accident

Wet scavenging process is critical for air dispersion modeling of Cs-137 in the Fukushima Daiichi Nuclear power plant (FDNPP) accident. Although intensively investigated, wet scavenging simulation is still subject to uncertainties caused by the biases in wet scavenging modeling and meteorological input. To reduce these uncertainties, the on-line coupled modeling feature of the Weather Research and Forecasting-Chemistry (WRF-Chem) model was utilized and both the in-cloud and below-cloud scavenging processes are considered. In this study, the in-cloud scheme Environ and below-cloud scheme Baklanov are combined with each other to form Environ-Bakla to simulate the wet deposition of Cs-137. The model is systematically compared with a previous WRF-Chem model with a single below-cloud scheme Baklanov, based on both the cumulative deposition and ambient concentration of Cs-137 based on the FDNPP accident observation. The results demonstrate that the in-cloud scavenging scheme substantially improves the cumulative deposition simulation in regions with light rain like Tochigi, Nakadori etc. With respect to the atmospheric concentration, the inclusion of in-cloud scavenging doesn’t necessarily improve the performances and the Environ-Bakla only shows fair performance under plume events with no rain or light rain.

SWIFT-RIMPUFF Modeling of Air Dispersion at a Nuclear Powerplant Site With Heterogeneous Upwind Topography

The SWIFT-RIMPUFF can provide refined atmospheric dispersion modeling for nuclear emergency response, but its performance for the mesoscale range in a nuclear power plant (NPP) site with highly complex topographies hasn’t been fully investigated. In this study, a validation of SWIFT-RIMPUFF was performed based on a wind tunnel experiment simulating a real China’s multi-reactor NPP site with heterogeneous upwind topography and dense buildings to understand the potential discrepancies or limits. The results demonstrate that the SWIFT-RIMPUFF can reproduce the sharp changes of wind flows for both speed and directions near the buildings, but usually overestimate the wind speed in the complex topography. For vertical wind profiles, the accuracies show high dependencies on the local topography and building layout, and the deviation of those near the building is more obvious. The simulated ground concentrations match the topographic changes of high-altitude mountains. The concentration predictions in the downwind building area are acceptable which displays that the influence of building effects can be well introduced, but the simulations in the building area still show noticeable discrepancies when compared with those in the sea area. However, such deviations do not propagate to the downwind mountainous and sea areas, which the accuracies are quite satisfactory.

An air dispersion model for the city of Toronto, Ontario, Canada

Air quality is a major concern for the public; therefore, the reliability of models in predicting the air quality accurately is of a major interest. The objective of this study was to develop an air dispersion model and demonstrate that it can be successfully used in place of or in conjunction with ambient air monitoring stations in determining the local Air Quality Index (AQI). This thesis begins with a review of existing atmospheric dispersion models, specifically, the Gaussian Plume models and their capabilities to handle the atmospheric chemistry of nitrogen oxides (NOx) and sulphur dioxides (SO₂). It also includes a review of wet deposition in the form of in-cloud, below-cloud, and snow scavenging. Existing dispersion models are investigated to assess their capability of representing atmospheric chemistry, specifically in the context of NOx and SO₂x substances and their applications to urban areas. A review was completed of previous studies where Gaussian dispersion models were applied to major cities around the world such as London, Helsinki, Kanto, and Prague, to predict ground level concentrations NOx and SO₂. For the purpose of this thesis, Gaussian air dispersion model was developed, known as the Air dispersion model for the Road Sources in Urban areas (ARSUS) model, which is capable of predicting ground level concentrations for a contaminant of interest. The ARSUS model was validated against the US EPA ISC3 model before it was used to conduct the two studies in this investigation. These two studies simulated weekday morning rush hour tailpipe emissions of CO and predicted ground level concentrations. The first study used the ARSUS model ARSUS model to predict ground level concentrations of CO from the tailpipe emissions of CO for roads and highways located in the vicinity of the Toronto West ambient air monitoring station. The second study involved an expansion of the domain to predict ground level concentrations of CO from tailpipe emissions from highways located in the City of Toronto. The modelled concentrations were then compared to the Toronto West ambient air monitoring station. ARSUS model’s results indicate that air quality in the immediate vicinity of roads or highways is highly impacted by the tailpipe emissions. Higher concentrations are observed for the areas adjacent to the road and highway sources. The tailpipe emissions of CO from highways have a higher contribution to the local air quality. The predicted ground level concentration from the ARSUS model do under-predict when compared to the observed data from the monitoring station; however, despite this a predictive model is viable.

An air dispersion model for the city of Toronto, Ontario, Canada

Air quality is a major concern for the public; therefore, the reliability of models in predicting the air quality accurately is of a major interest. The objective of this study was to develop an air dispersion model and demonstrate that it can be successfully used in place of or in conjunction with ambient air monitoring stations in determining the local Air Quality Index (AQI). This thesis begins with a review of existing atmospheric dispersion models, specifically, the Gaussian Plume models and their capabilities to handle the atmospheric chemistry of nitrogen oxides (NOx) and sulphur dioxides (SO₂). It also includes a review of wet deposition in the form of in-cloud, below-cloud, and snow scavenging. Existing dispersion models are investigated to assess their capability of representing atmospheric chemistry, specifically in the context of NOx and SO₂x substances and their applications to urban areas. A review was completed of previous studies where Gaussian dispersion models were applied to major cities around the world such as London, Helsinki, Kanto, and Prague, to predict ground level concentrations NOx and SO₂. For the purpose of this thesis, Gaussian air dispersion model was developed, known as the Air dispersion model for the Road Sources in Urban areas (ARSUS) model, which is capable of predicting ground level concentrations for a contaminant of interest. The ARSUS model was validated against the US EPA ISC3 model before it was used to conduct the two studies in this investigation. These two studies simulated weekday morning rush hour tailpipe emissions of CO and predicted ground level concentrations. The first study used the ARSUS model ARSUS model to predict ground level concentrations of CO from the tailpipe emissions of CO for roads and highways located in the vicinity of the Toronto West ambient air monitoring station. The second study involved an expansion of the domain to predict ground level concentrations of CO from tailpipe emissions from highways located in the City of Toronto. The modelled concentrations were then compared to the Toronto West ambient air monitoring station. ARSUS model’s results indicate that air quality in the immediate vicinity of roads or highways is highly impacted by the tailpipe emissions. Higher concentrations are observed for the areas adjacent to the road and highway sources. The tailpipe emissions of CO from highways have a higher contribution to the local air quality. The predicted ground level concentration from the ARSUS model do under-predict when compared to the observed data from the monitoring station; however, despite this a predictive model is viable.

A Study on the Prediction of Damage Ranges by Leakages of Seaport-Stored Substances

In order to check the risk of hydrogen peroxide leakage from the seaport, the leakage amount was changed from 1.0 ton to 10.0 tons, with the maximum and minimum diffusion distances per month in 2020 being subsequently calculated. A total of 82 scenarios were created to confirm the change in the diffusion distance according to the amount of leakage. The scenario was analyzed based on the distance at which the risk concentration was maintained through the ALOHA Air Dispersion Models. As indicated by the analysis, when the amount of leakage is relatively large, the temperature is also high and the wind speed is fast - resulting in the maximum spread. However, when the amount of leakage was relatively minimal, the temperature was low and the wind speed remained fast - this kept diffusion to the minimum. Concerning characteristics of fast wind speeds, the dispersion length changed based on amounts of leakages where PAC-1 contains 2.0 tons, PAC-2 contains 4.0 tons, and PAC-3 contains 5.0 tons. In addition, when the amount of leakage equaled 10.0 tons, and the wind speed was high, the dispersion length reached up to 10 kms. In light of this, it was confirmed that even adjacent administrative districts were affected. Therefore, it is necessary to establish appropriate measures to prevent damage by utilizing the diffusion distance caused by chemical leakages.