The use of an atmospheric dispersion model to determine influence regions in the Prince George, B.C. airshed from the burning of open wood waste piles

Ainslie, Bruce; Jackson, Peter L.

doi:10.1016/j.jenvman.2008.11.009

Cited by 22 publications

(11 citation statements)

References 15 publications

(22 reference statements)

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“…As a result, air-pollution-related health issues and the influence of air quality on the quality of life have been investigated in detail for at least 25 years in PG (Jørgensen et al, 1998;Michalos and Zumbo, 1999). Moreover, local continuous PM measurements started in 1992, and sampling of PM compositions and emission modeling studies have been conducted (Breed, Arocena, and Sutherland, 2002;Owens et al, 2011;Stantec, 2010;Ainslie and Jackson, 2009). …”

Section: Introductionmentioning

confidence: 99%

Assessment of background particulate matter concentrations in small cities and rural locations—Prince George, Canada

Veira

Jackson

Ainslie

et al. 2013

Journal of the Air & Waste Management Association

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This study investigates the development and application of a simple method to calculate annual and seasonal PM 2.5 and PM 10 background concentrations in small cities and rural areas. The Low Pollution Sectors and Conditions (LPSC) method is based on existing measured long-term data sets and is designed for locations where particulate matter (PM) monitors are only influenced by local anthropogenic emission sources from particular wind sectors. The LPSC method combines the analysis of measured hourly meteorological data, PM concentrations, and geographical emission source distributions. PM background levels emerge from measured data for specific wind conditions, where air parcel trajectories measured at a monitoring station are assumed to have passed over geographic sectors with negligible local emissions. Seasonal and annual background levels were estimated for two monitoring stations in Prince George, Canada, and the method was also applied to four other small cities (Burns Lake, Houston, Quesnel, Smithers) in northern British Columbia. The analysis showed reasonable background concentrations for both monitoring stations in Prince George, whereas annual PM 10 background concentrations at two of the other locations and PM 2.5 background concentrations at one other location were implausibly high. For those locations where the LPSC method was successful, annual background levels ranged between 1.8 AE 0.1 µg/m 3 and 2.5 AE 0.1 µg/m 3 for PM 2.5 and between 6.3 AE 0.3 µg/m 3 and 8.5 AE 0.3 µg/m 3 for PM 10 . Precipitation effects and patterns of seasonal variability in the estimated background concentrations were detectable for all locations where the method was successful. Overall the method was dependent on the configuration of local geography and sources with respect to the monitoring location, and may fail at some locations and under some conditions. Where applicable, the LPSC method can provide a fast and cost-efficient way to estimate background PM concentrations for small cities in sparsely populated regions like northern British Columbia.Implications: In rural areas like northern British Columbia, particulate matter (PM) monitoring stations are usually located close to emission sources and residential areas in order to assess the PM impact on human health. Thus there is a lack of accurate PM background concentration data that represent PM ambient concentrations in the absence of local emissions. The background calculation method developed in this study uses observed meteorological data as well as local source emission locations and provides annual, seasonal and precipitation-related PM background concentrations that are comparable to literature values for four out of six monitoring stations.

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Section: Introductionmentioning

confidence: 99%

Assessment of background particulate matter concentrations in small cities and rural locations—Prince George, Canada

Veira

Jackson

Ainslie

et al. 2013

Journal of the Air & Waste Management Association

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“…The program is a non-steady state puff distribution model. It can calculate impacts of meteorological conditions that vary over time as a result of area effect on transport, removal, and chemical conversions of the pollutants [25][26]. Furthermore, the program also includes algorithms based on the distribution coefficient approach and dry-wet accumulation model [27].…”

Section: Calpuffmentioning

confidence: 99%

Determining Performance and Application of Steady-State Models and Lagrangian Puff Model for Environmental Assessment of CO and NOx Emissions

Demirarslan¹,

Doğruparmak²

2016

Pol. J. Environ. Stud.

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Air quality modellings are highly useful systems used to investigate the possible impact of emissions diffusing into the atmosphere in any area they might have on that area. There are many modelling methods whose capacities are limited by their advantages and disadvantages or the equipment they use. In this study, therefore, both steady-state models (AERMOD and ISCST-3) and the Lagrangian model (CALPUFF) are used. This study has two purposes: one is to specify performance of the models. Performances were determined with various statistical methods such as fractional bias (FB), mean squared error (MSE), and geometric mean bias (MG). The other purpose of this study is to evaluate temporal and spatial variations of point (P), area (A), and line (L) -sourced CO and NO x emissions in the research area by using the modelling methods. The district of Körfez, which is one of the districts of the province of Kocaeli, was chosen as the study area.When the results obtained with modelling all P and A sources by three programs are analyzed, the highest annual concentration AERMOD, ISCST-3, and CALPUFF were found as 128.82, 86.96, and 201.30 µg/m 3 for CO, and 7.56, 26.31, and 6.10 µg/m 3 for NO x , respectively. On the other hand, when the results obtained with modelling all P and A and L sources by two programs are investigated, the highest annual concentration AERMOD and ISCST-3 were found to be 155.12, 92.46 µg/m 3 for CO, and 166.93 and 89.98 µg/m 3 for NO x , respectively. When contributions of the pollutant sources on pollution are evaluated, it was observed that area sources and line sources are more predominant than other sources for CO and NO x emissions. It was observed by analyzing the diffusion maps that residential areas in the district are more concentrated. Therefore, in the study the predicted and observed values were also compared with national and international limit values and determined to meet these limit values. According to the results obtained by evaluation of performances of the models with FB, MS, and MG statistical methods, performance sorting for NO x emissions was found to be ISCST-3 > CALPUFF > AERMOD, while for CO emissions it is given as

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“…), an airshed can be viewed as a set of air flows that merge to effect the pollution levels at a particular downwind site (see [3] for a further discussion of airsheds). Therefore, by inferring the airshed that effected a particular measurement, a considerable amount of information about the source(s) of radioxenon at the receptor is obtained.…”

Section: Motivationmentioning

confidence: 99%

Motivating the inclusion of meteorological indicators in the CTBT feature-space

Bellinger

Japkowicz

2011

2011 IEEE Symposium on Computational Intelligence for Security and Defense Applications (CISDA)

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Abstract-Verification of the Comprehensive Test-Ban-Treaty (CTBT), as a Pattern Recognition (PR) problem, has been proposed based on four radioxenon features. It has been noted, however, that in many cases this limited feature set is insufficient to distinguish radioxenon levels effected by an explosion from those that are solely products of industrial activities. As a means of improving the detectability of low-yield clandestine nuclear explosions, this paper motivates the inclusion of meteorological indicators in the CTBT feature-space, promotes further research into which meteorological indicators are most informative, and how they may be acquired. In doing so, we present classification results from four simulated scenarios. These results demonstrate that the inclusion of a simple wind direction feature can significantly increase the prospect of classifying challenging detonation events, and suggests the predictive power of meteorological features in general.

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The use of an atmospheric dispersion model to determine influence regions in the Prince George, B.C. airshed from the burning of open wood waste piles

Cited by 22 publications

References 15 publications

Assessment of background particulate matter concentrations in small cities and rural locations—Prince George, Canada

Assessment of background particulate matter concentrations in small cities and rural locations—Prince George, Canada

Determining Performance and Application of Steady-State Models and Lagrangian Puff Model for Environmental Assessment of CO and NOx Emissions

Motivating the inclusion of meteorological indicators in the CTBT feature-space

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