On the Relationship between Acid Rain and Cloud Type

Cana‐Cascallar, L.

doi:10.1080/10473289.2002.10470785

“…For instance, several studies (e.g. Dawson, 1978;Cana-Cascalar, 2002) analysed the relationship between ionic concentrations and storm type. The latter researchers found that short-lived convective conditions over Spain may cause rain to be more acidic.…”

Section: Introductionmentioning

confidence: 99%

“…Examples include time-series analyses using linear and nonlinear regression techniques (Buda and DeWalle, 2002;Seto et al, 2002;Nickerson and Madsen, 2005), cluster and principalcomponent analyses (e.g. Dorling et al, 1992;Cana-Cascalar, 2002), and spatial-pattern analyses of atmospheric circulation (Davies et al, 1991;Yarnal, 1991Yarnal, , 1993Dorling et al, 1992;Lamb, 2003, 2005). Typical studies employ the ionic concentrations, rather than the deposition flux itself, because precipitation composition is closely linked to the concentrations of precursors in air (Engelman, 1971;Davis et al, 1997;Hicks, 2005).…”

Section: Introductionmentioning

confidence: 99%

Influences of atmospheric circulation on the variability of wet sulfate deposition

Dayan

¹

,

Lamb

²

2007

Intl Journal of Climatology

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Precipitation chemistry data from the National Atmospheric Deposition Program were related to weather data from the Climate Diagnostics Center in order to reveal the influence of large-scale circulation patterns on the wet deposition of sulfate downwind of the Ohio River Valley, where SO 2 emissions were curtailed sharply in the mid-1990s. The chemistry data from five precipitation-sampling sites were combined to provide a regional average for each summer season over the 21-year period from 1984 to 2004. The long-term trend of sulfate concentration is associated to a statistically significant extent by composited flow patterns associated with the East Pacific-North Pacific index. The regional weather pattern for the sulfate-rich years is associated with an intensification of the Bermuda High over the southeastern United States at the surface in tandem with a weakening of the 500-hPa geopotential height (GPH) climatological trough located over the northeastern United States. The highest-sulfate concentration days for the Atmospheric Integrated Research Monitoring Network (AIRMoN) Pennsylvania site occurred during a similar synoptic pattern when intense convection over the eastern United States was favoured thermodynamically. This study suggests that temporal changes in the large-scale circulation pattern over North America need to be considered, in addition to changes in precursor emissions, as an explanation for the decreases in sulfate concentrations observed in summertime rains across the eastern United States.

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“…5 ) followed by the earliest smog advisory ever 1ssued dunng the normal smog season in April , 2005. As shown in Table 1, there has been an increase in smog advisories since 2002 [12), [13) , [14) and [15]. Since 1999, each air quality study completed states that the air quality in Ontario is improving [12][13][14][15][16][17][18].…”

Section: Introductionmentioning

confidence: 99%

“…As shown in Table 1, there has been an increase in smog advisories since 2002 [12), [13) , [14) and [15]. Since 1999, each air quality study completed states that the air quality in Ontario is improving [12][13][14][15][16][17][18]. In 2005, the Ontario Medical Association (OMA) announced air pollution costs were estimated to be $507,000,000 in direct health care costs [1 ].…”

Section: Introductionmentioning

confidence: 99%

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

Sylvestre-Williams¹

2021

Preprint

0

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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.

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“…5 ) followed by the earliest smog advisory ever 1ssued dunng the normal smog season in April , 2005. As shown in Table 1, there has been an increase in smog advisories since 2002 [12), [13) , [14) and [15]. Since 1999, each air quality study completed states that the air quality in Ontario is improving [12][13][14][15][16][17][18].…”

Section: Introductionmentioning

confidence: 99%

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

Sylvestre-Williams¹

2021

Preprint

0

View full text Add to dashboard Cite

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.

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On the Relationship between Acid Rain and Cloud Type

Cited by 5 publications

References 18 publications

Influences of atmospheric circulation on the variability of wet sulfate deposition

Influences of atmospheric circulation on the variability of wet sulfate deposition

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

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

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