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.

Assessment of Spatio-Temporal Variations of Particulate Matter and Gaseous Pollutants in The Port City, Paradip, East Coast of India

This study aims to assess the spatial and temporal variations of aerosol pollutants within the nine selected ambient air monitoring stations, including residential, commercial, and industrial sites in Paradip city based on two seasons, i.e., winter and summer, from January 2019 to June 2019. The particulate matter (PM) like PM10 and PM2.5 and gaseous pollutants like sulphur dioxide (SO2), nitrogen dioxide (NO2), and ammonia (NH3) samples were collected at each monitoring stations. The 24-hour average concentrations of PM10 and PM2.5 showed the highest levels in the winter season and lowest in the summer season. The value exceeded the permissible limit of India-national ambient air quality standards (IND-NAAQS) at all the monitoring stations.

Comparability of calibration strategies for measuring mercury concentrations in gas emission sources and the atmosphere

A primary mercury gas standard was developed at VSL to establish an SI-traceable reference point for mercury concentrations at emission and background levels in the atmosphere. The majority of mercury concentration measurements are currently made traceable to the empirically determined vapour pressure of mercury. The primary mercury gas standard can be used for the accurate and precise calibration of analytical systems used for measuring mercury concentrations in air. It has been especially developed to support measurements related to ambient air monitoring (1 ng m−3–2 ng m−3), indoor and workplace related mercury concentration levels according to health standards (from 50 ng m−3 upwards) as well as to stationary source emissions (from 1 µg m−3 upwards). The primary mercury gas standard is based on diffusion according to ISO 6154-8. Calibration gas mixtures are obtained by combining calibrated mass flows of nitrogen and air through a generator holding diffusion cells, containing elemental mercury. In this paper, we present the results of comparisons between the primary standard and mercury calibration methods maintained by NPL, a National Metrology Institute (NMI), and JSI, a Designated Institute (DI). The calibration methods currently used at NPL and JSI are based on the bell-jar calibration apparatus in combination with the Dumarey equation or a NIST reference material. For the comparisons, mercury was sampled on sorbent traps to obtain transfer standards with levels between 2 ng and 1000 ng with an expanded uncertainty not exceeding 3 % (k = 2). The comparisons performed show that the results for the primary standard and the NIST reference material are comparable, whereas a difference of −8 % exists between results traceable to the primary standard and the Dumarey equation.

A Quantum Cascade Laser-Based Multi-Gas Sensor for Ambient Air Monitoring

A quantum cascade laser-based sensor for ambient air monitoring is presented and five gases, affecting the air quality, can be quantified. The light sources are selected to measure CO, NO, NO2, N2O and SO2. The footprint of the measurement setup is designed to fit in two standard 19” rack (48 cm × 65 cm) with 4 height units (18 cm) whereas one is holding the optical components and the other one contains the electronics and data processing unit. The concentrations of the individual analytes are measured using 2f-Wavelength Modulation Spectroscopy (2f-WMS) and a commercially available multipass gas cell defines the optical path. In addition, CO can also be measured with a dispersion-based technique, which allows one to cover a wider concentration range than 2f-WMS. The performance of this prototype has been evaluated in the lab and detection limits in the range of 1ppbv have been achieved. Finally, the applicability of this prototype for ambient air monitoring is shown in a five-week measurement campaign in cooperation with the Municipal Department for Environmental Protection (MA 22) of Vienna, Austria.