scholarly journals A chemical transport model study of plume-rise and particle size distribution for the Athabasca oil sands

2018 ◽  
Vol 18 (12) ◽  
pp. 8667-8688 ◽  
Author(s):  
Ayodeji Akingunola ◽  
Paul A. Makar ◽  
Junhua Zhang ◽  
Andrea Darlington ◽  
Shao-Meng Li ◽  
...  
Keyword(s):  
High Resolution ◽  
Size Distribution ◽  
Oil Sands ◽  
Model Performance ◽  
Companion Paper ◽  
Meteorological Conditions ◽  
Aerosol Size Distribution ◽  
Plume Rise ◽  
Plume Height ◽  
Athabasca Oil Sands

Abstract. We evaluate four high-resolution model simulations of pollutant emissions, chemical transformation, and downwind transport for the Athabasca oil sands using the Global Environmental Multiscale – Modelling Air-quality and Chemistry (GEM-MACH) model, and compare model results with surface monitoring network and aircraft observations of multiple pollutants, for simulations spanning a time period corresponding to an aircraft measurement campaign in the summer of 2013. We have focussed here on the impact of different representations of the model's aerosol size distribution and plume-rise parameterization on model results. The use of a more finely resolved representation of the aerosol size distribution was found to have a significant impact on model performance, reducing the magnitude of the original surface PM2.5 negative biases 32 %, from −2.62 to −1.72 µg m−3. We compared model predictions of SO2, NO2, and speciated particulate matter concentrations from simulations employing the commonly used Briggs (1984) plume-rise algorithms to redistribute emissions from large stacks, with stack plume observations. As in our companion paper (Gordon et al., 2017), we found that Briggs algorithms based on estimates of atmospheric stability at the stack height resulted in under-predictions of plume rise, with 116 out of 176 test cases falling below the model : observation 1 : 2 line, 59 cases falling within a factor of 2 of the observed plume heights, and an average model plume height of 289 m compared to an average observed plume height of 822 m. We used a high-resolution meteorological model to confirm the presence of significant horizontal heterogeneity in the local meteorological conditions driving plume rise. Using these simulated meteorological conditions at the stack locations, we found that a layered buoyancy approach for estimating plume rise in stable to neutral atmospheres, coupled with the assumption of free rise in convectively unstable atmospheres, resulted in much better model performance relative to observations (124 out of 176 cases falling within a factor of 2 of the observed plume height, with 69 of these cases above and 55 of these cases below the 1 : 1 line and within a factor of 2 of observed values). This is in contrast to our companion paper, wherein this layered approach (driven by meteorological observations not co-located with the stacks) showed a relatively modest impact on predicted plume heights. Persistent issues with over-fumigation of plumes in the model were linked to a more rapid decrease in simulated temperature with increasing height than was observed. This in turn may have led to overestimates of near-surface diffusivity, resulting in excessive fumigation.

scholarly journals A chemical transport model study of plume rise and particle size distribution for the Athabasca oil sands

2018 ◽  
Author(s):  
Ayodeji Akingunola ◽  
Paul A. Makar ◽  
Junhua Zhang ◽  
Andrea Darlington ◽  
Shao-Meng Li ◽  
...  
Keyword(s):  
Size Distribution ◽  
Oil Sands ◽  
Model Performance ◽  
Pollutant Emissions ◽  
Aerosol Size Distribution ◽  
Plume Rise ◽  
Athabasca Oil Sands ◽  
Near Surface ◽  
Surface Diffusivity ◽  
The Impact

Abstract. We evaluate four high-resolution model simulations of pollutant emissions, chemical transformation and downwind transport for the Athabasca oil sands using the Global Environmental Multiscale – Modelling Air-quality and Chemistry (GEM-MACH) model using surface monitoring network and aircraft observations of multiple pollutants, for simulations spanning a time period corresponding to an aircraft measurement campaign in the region in summer 2013. We have focussed here on the impact of different representations of the model's aerosol size distribution and plume-rise parameterization on model results. The use of a more finely resolved representation of the aerosol size distribution was found to have a significant impact on model performance, reducing the magnitude of the original surface PM2.5 negative biases by 32 %. We compared model predictions of SO2, NO2, and speciated particulate matter concentrations from simulations employing the commonly-used Briggs (1984) plume-rise algorithms to redistribute emissions from large stacks with stack plume observations. As in our companion paper (Gordon et al., 2018), we found these algorithms resulted in under-predictions of plume rise, with 39 to 60 % of predicted plume heights falling below half of the observed plume heights. However, we found here that a layered buoyancy approach for stable to neutral atmospheres, coupled with the assumption of free rise in convectively unstable atmospheres, resulted in much better model performance, both for atmospheric constituent concentrations and the predicted height of the plumes. Persistent issues with over-fumigation of plumes in the model were linked to positive biases in the predicted temperatures between the surface and 1km elevation. These in turn may lead to overestimates of near-surface diffusivity, resulting in excessive fumigation.

scholarly journals A comparison of plume rise algorithms to stack plume measurements in the Athabasca oil sands

2018 ◽  
Vol 18 (19) ◽  
pp. 14695-14714 ◽  
Author(s):  
Mark Gordon ◽  
Paul A. Makar ◽  
Ralf M. Staebler ◽  
Junhua Zhang ◽  
Ayodeji Akingunola ◽  
...  
Keyword(s):  
Oil Sands ◽  
Companion Paper ◽  
Classification Systems ◽  
Plume Rise ◽  
Athabasca Oil Sands ◽  
Obukhov Length ◽  
Athabasca Oil Sands Region ◽  
Boundary Layer Height ◽  
Meteorological Observations ◽  
Input Variables

Abstract. Plume rise parameterizations calculate the rise of pollutant plumes due to effluent buoyancy and exit momentum. Some form of these parameterizations is used by most air quality models. In this paper, the performance of the commonly used Briggs plume rise algorithm was extensively evaluated, through a comparison of the algorithm's results when driven by meteorological observations with direct observations of plume heights in the Athabasca oil sands region. The observations were carried out as part of the Canada-Alberta Joint Oil Sands Monitoring Plan in August and September of 2013. Wind and temperature data used to drive the algorithm were measured in the region of emissions from various platforms, including two meteorological towers, a radio-acoustic profiler, and a research aircraft. Other meteorological variables used to drive the algorithm include friction velocity, boundary-layer height, and the Obukhov length. Stack emissions and flow parameter information reported by continuous emissions monitoring systems (CEMSs) were used to drive the plume rise algorithm. The calculated plume heights were then compared to interpolated aircraft SO2 measurements, in order to evaluate the algorithm's prediction for plume rise. We demonstrate that the Briggs algorithm, when driven by ambient observations, significantly underestimated plume rise for these sources, with more than 50 % of the predicted plume heights falling below half the observed values from this analysis. With the inclusion of the effects of effluent momentum, the choice of different forms of parameterizations, and the use of different stability classification systems, this essential finding remains unchanged. In all cases, approximately 50 % or more of the predicted plume heights fall below half the observed values. These results are in contrast to numerous plume rise measurement studies published between 1968 and 1993. We note that the observations used to drive the algorithms imply the potential presence of significant spatial heterogeneity in meteorological conditions; we examine the potential impact of this heterogeneity in our companion paper (Akingunola et al., 2018). It is suggested that further study using long-term in situ measurements with currently available technologies is warranted to investigate this discrepancy, and that wherever possible, meteorological input variables are observed in the immediate vicinity of the emitting stacks.

scholarly journals Impact of Athabasca oil sands operations on mercury levels in air and deposition

2021 ◽  
Vol 21 (16) ◽  
pp. 12783-12807
Author(s):  
Ashu Dastoor ◽  
Andrei Ryjkov ◽  
Gregor Kos ◽  
Junhua Zhang ◽  
Jane Kirk ◽  
...  
Keyword(s):  
Oil Sands ◽  
Global Scale ◽  
Meteorological Conditions ◽  
Emission Sources ◽  
Athabasca Oil Sands ◽  
Deposition Fluxes ◽  
Annual Variations ◽  
Athabasca Oil Sands Region ◽  
The Impact ◽  
Air Concentrations

Abstract. Oil sands upgrading facilities in the Athabasca oil sands region (AOSR) in Alberta, Canada, have been reporting mercury (Hg) emissions to public government databases (National Pollutant Release Inventory (NPRI)) since the year 2000, yet the relative contribution of these emissions to ambient Hg deposition remains unknown. The impact of oil sands emissions (OSE) on Hg levels in and around the AOSR, relative to contributions from global (anthropogenic, geogenic and legacy) emissions and regional biomass burning emissions (BBE), was assessed using a global 3D-process-based Hg model, GEM-MACH-Hg, from 2012 to 2015. In addition, the relative importance of year-to-year changes in Hg emissions from the above sources and meteorological conditions to inter-annual variations in Hg deposition was examined. Surface air concentrations of Hg species and annual snowpack Hg loadings simulated by the model were found comparable to measured levels in the AOSR, suggesting consistency between reported Hg emissions from oil sands activities and Hg levels in the region. As a result of global-scale transport and the long lifetime of gaseous elemental Hg (Hg(0)), surface air concentrations of Hg(0) in the AOSR reflected the background Hg(0) levels in Canada. By comparison, average air concentrations of total oxidized Hg (efficiently deposited Hg species) in the AOSR were elevated up to 60 % within 50 km of the oil sands Hg emission sources. Hg emissions from wildfire events led to episodes of high ambient Hg(0) concentrations and deposition enrichments in northern Alberta, including the AOSR, during the burning season. Hg deposition fluxes in the AOSR were within the range of the deposition fluxes measured for the entire province of Alberta. On a broad spatial scale, contribution from imported Hg from global sources dominated the annual background Hg deposition in the AOSR, with present-day global anthropogenic emissions contributing to 40 % (< 1 % from Canada excluding OSE) and geogenic and legacy emissions contributing to 60 % of the background Hg deposition. In contrast, oil sands Hg emissions were responsible for significant enhancements in Hg deposition in the immediate vicinity of oil sands Hg emission sources, which were ∼ 10 times larger in winter than summer (250 %–350 % in winter and ∼ 35 % in summer within 10 km of OSE, 2012–2013). The spatial extent of the influence of oil sands emissions on Hg deposition was also greater in winter relative to summer (∼ 100 km vs. 30 km from Hg-emitting facilities). In addition, inter-annual changes in meteorological conditions and oil sands emissions also led to significantly higher inter-annual variations in wintertime Hg deposition compared to summer. In 2015, within 10 km of major oil sands sources, relative to 2012, Hg deposition declined by 46 % in winter but 22 % annually, due to a larger OSE-led reduction in wintertime deposition. Inter-annual variations in meteorological conditions were found to both exacerbate and diminish the impacts of OSE on Hg deposition in the AOSR, which can confound the interpretation of trends in short-term environmental Hg monitoring data. Hg runoff in spring flood, comprising the majority of annual Hg runoff, is mainly derived from seasonal snowpack Hg loadings and mobilization of Hg deposited in surface soils, both of which are sensitive to Hg emissions from oil sands developments in the proximity of sources. Model results suggest that sustained efforts to reduce anthropogenic Hg emissions from both global and oil sands sources are required to reduce Hg deposition in the AOSR.

scholarly journals Numerical simulations of homogeneous freezing processes in the aerosol chamber AIDA

2002 ◽  
Vol 2 (5) ◽  
pp. 1467-1508
Author(s):  
W. Haag ◽  
B. Kärcher ◽  
S. Schaefers ◽  
O. Stetzer ◽  
O. Möhler ◽  
...  
Keyword(s):  
Numerical Simulations ◽  
Size Distribution ◽  
Time History ◽  
Companion Paper ◽  
Aerosol Size Distribution ◽  
Size Spectrum ◽  
Mixing Ratio ◽  
Atmospheric Conditions ◽  
Aerosol Chamber ◽  
Homogeneous Freezing

Abstract. The homogeneous freezing of supercooled H2SO4/H2O aerosols in an aerosol chamber is investigated with a microphysical box model using the activity parameterization of the nucleation rate by Koop et al (2000). The simulations are constrained by measurements of pressure, temperature, total water mixing ratio, and the initial aerosol size distribution, described in a companion paper Möhler et al. (2002). Model results are compared to measurements conducted in the temperature range between 194 and 235 K, with cooling rates in the range between 0.5 and 2.6 K min-1, and at air pressures between 170 and 1000 hPa. The simulations focus on the time history of relative humidity with respect to ice, aerosol size distribution, partitioning of water between gas and particle phase, onset times of freezing, freezing threshold relative humidities, aerosol chemical composition at the onset of freezing, and the number of nucleated ice crystals. The latter three parameters can directly be inferred from the experiments, the former three aid in interpreting the measurements. Sensitivity studies are carried out to address the relative importance of uncertainties of basic quantities such as temperature, H2O mixing ratio, aerosol size spectrum, and deposition coefficient of H2O molecules on ice. The ability of the numerical simulations to provide detailed explanations of the observations greatly increases confidence in attempts to model this process under real  atmospheric conditions, for instance with regard to the formation of cirrus clouds or type-II polar stratospheric clouds, provided that accurate temperature and humidity measurements are available.

scholarly journals A Comparison of Plume Rise Algorithms to Stack Plume Measurements in the Athabasca Oil Sands

2017 ◽  
Author(s):  
Mark Gordon ◽  
Paul A. Makar ◽  
Ralf M. Staebler ◽  
Junhua Zhang ◽  
Ayodeji Akingunola ◽  
...  
Keyword(s):  
Oil Sands ◽  
Plume Rise ◽  
Athabasca Oil Sands ◽  
Obukhov Length ◽  
Athabasca Oil Sands Region ◽  
Boundary Layer Height ◽  
Direct Observations ◽  
Research Aircraft ◽  
Meteorological Observations ◽  
Stack Emissions

Abstract. Plume rise parameterizations calculate the rise of pollutant plumes due to effluent buoyancy and exit momentum. Some form of these parameterizations are used by most air quality models. In this paper, the performance of the commonly used Briggs plume rise algorithm was extensively evaluated through a comparison of the algorithm's results when driven by meteorological observations with direct observations of plume heights in the Athabasca oil sands region. The observations were carried out as part of the Canada–Alberta Joint Oil Sands Monitoring Plan in August and September of 2013. Wind and temperature data used to drive the algorithm were measured in the region of emissions from various platforms, including two meteorological towers, a radio-acoustic profiler, and a research aircraft. Other meteorological variables used to drive the algorithm include friction velocity, boundary-layer height, and the Obukhov length. Stack emissions and flow parameter information reported by Continuous Emissions Monitoring Systems (CEMS) were used to drive the plume rise algorithm. The calculated plume heights were then compared to interpolated aircraft SO2 measurements, in order to evaluate the algorithm's prediction for plume rise. We demonstrate that the Briggs algorithm, when driven by ambient observations, significantly underestimated plume rise for these sources, with more than a third of the predicted plume heights falling below half the observed values from this analysis. Including the effects of effluent momentum and choosing between different forms of the parameterizations improve results slightly, but there remains an average underestimation between 4 and 21 %, depending on the measurement platform used to drive the algorithm. These results are in contrast to numerous plume rise measurement studies published between 1968 and 1993. It is suggested that further investigation using long-term in-situ measurements with currently available technologies is warranted to investigate this discrepancy.

scholarly journals Numerical simulations of homogeneous freezing processes in the aerosol chamber AIDA

2003 ◽  
Vol 3 (1) ◽  
pp. 195-210 ◽  
Author(s):  
W. Haag ◽  
B. Kärcher ◽  
S. Schaefers ◽  
O. Stetzer ◽  
O. Möhler ◽  
...  
Keyword(s):  
Numerical Simulations ◽  
Size Distribution ◽  
Time History ◽  
Companion Paper ◽  
Aerosol Size Distribution ◽  
Size Spectrum ◽  
Mixing Ratio ◽  
Atmospheric Conditions ◽  
Aerosol Chamber ◽  
Homogeneous Freezing

Abstract. The homogeneous freezing of supercooled H2SO4/H2O aerosols in an aerosol chamber is investigated with a microphysical box model using the activity parameterization of the nucleation rate by Koop et al. (2000). The simulations are constrained by measurements of pressure, temperature, total water mixing ratio, and the initial aerosol size distribution, described in a companion paper Möhler et al. (2003). Model results are compared to measurements conducted in the temperature range between 194 and 235 K, with cooling rates in the range between 0.5 and 2.6 K min-1, and at air pressures between 170 and 1000 hPa. The simulations focus on the time history of relative humidity with respect to ice, aerosol size distribution, partitioning of water between gas and particle phase, onset times of freezing, freezing threshold relative humidities, aerosol chemical composition at the onset of freezing, and the number of nucleated ice crystals. The latter four parameters can be inferred from the experiments, the former three aid in interpreting the measurements. Sensitivity studies are carried out to address the relative importance of uncertainties of basic quantities such as temperature, total H2O mixing ratio, aerosol size spectrum, and deposition coefficient of H2O molecules on ice. The ability of the numerical simulations to provide detailed explanations of the observations greatly increases confidence in attempts to model this process under real atmospheric conditions, for instance with regard to the formation of cirrus clouds or polar stratospheric ice clouds, provided that accurate temperature and humidity measurements are available.

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