Comment on research article: Emissions databases for polycyclic aromatic compounds in the Athabasca Oil Sands Region – development using current knowledge and evaluation with passive sampling and air dispersion modeling data, acp-2017-1091

2018 ◽  
Author(s):  
Anonymous
2017 ◽  
Author(s):  
Xin Qiu ◽  
Irene Cheng ◽  
Fuquan Yang ◽  
Erin Horb ◽  
Leiming Zhang ◽  
...  

Abstract. Two speciated and spatially-resolved emissions databases for polycyclic aromatic compounds (PAC) in the Athabasca oil sands region (AOSR) were developed. The first database was derived from volatile organic compound (VOC) emissions data provided by the Cumulative Environmental Management Association (CEMA) and the second database was derived from additional data collected within the Joint Canada-Alberta Oil Sands Monitoring (JOSM) program. CALPUFF modelling results for atmospheric polycyclic aromatic hydrocarbons (PAH), alkylated PAH, and dibenzothiophenes (DBT), obtained using each of the emissions databases, are presented and compared with measurements from a passive air monitoring network. The JOSM-derived emissions resulted in better model-measurement agreement in the total PAH concentrations and for most PAH species concentrations, compared to results using CEMA-derived emissions. At local sites near oil sands mines, the percent error of the model compared to observations decreased from 30 % using the CEMA-derived emissions to 17 % using the JOSM-derived emissions. The improvement at local sites was likely attributed to the inclusion of updated tailings pond emissions estimated from JOSM activities. In either the CEMA-derived or JOSM-derived emissions scenario, the model underestimated PAH concentrations by a factor of 3 at remote locations. Potential reasons for the disagreement include forest fire emissions, re-emissions of previously deposited PAHs, and long-range transport not considered in the model. Alkylated PAH and DBT concentrations were also significantly underestimated. The CALPUFF model is expected to predict higher concentrations because of the limited chemistry and deposition modelling. Thus the model underestimation of PACs is likely due to gaps in the emissions database for these compounds and uncertainties in the methodology for estimating the emissions. Future work is required that focuses on improving the PAC emission estimation and speciation methodologies and reducing the uncertainties in VOC emissions which are subsequently used in PAC emissions estimation.


2018 ◽  
Vol 18 (5) ◽  
pp. 3457-3467 ◽  
Author(s):  
Xin Qiu ◽  
Irene Cheng ◽  
Fuquan Yang ◽  
Erin Horb ◽  
Leiming Zhang ◽  
...  

Abstract. Two speciated and spatially resolved emissions databases for polycyclic aromatic compounds (PACs) in the Athabasca oil sands region (AOSR) were developed. The first database was derived from volatile organic compound (VOC) emissions data provided by the Cumulative Environmental Management Association (CEMA) and the second database was derived from additional data collected within the Joint Canada–Alberta Oil Sands Monitoring (JOSM) program. CALPUFF modelling results for atmospheric polycyclic aromatic hydrocarbons (PAHs), alkylated PAHs, and dibenzothiophenes (DBTs), obtained using each of the emissions databases, are presented and compared with measurements from a passive air monitoring network. The JOSM-derived emissions resulted in better model–measurement agreement in the total PAH concentrations and for most PAH species concentrations compared to results using CEMA-derived emissions. At local sites near oil sands mines, the percent error of the model compared to observations decreased from 30 % using the CEMA-derived emissions to 17 % using the JOSM-derived emissions. The improvement at local sites was likely attributed to the inclusion of updated tailings pond emissions estimated from JOSM activities. In either the CEMA-derived or JOSM-derived emissions scenario, the model underestimated PAH concentrations by a factor of 3 at remote locations. Potential reasons for the disagreement include forest fire emissions, re-emissions of previously deposited PAHs, and long-range transport not considered in the model. Alkylated PAH and DBT concentrations were also significantly underestimated. The CALPUFF model is expected to predict higher concentrations because of the limited chemistry and deposition modelling. Thus the model underestimation of PACs is likely due to gaps in the emissions database for these compounds and uncertainties in the methodology for estimating the emissions. Future work is required that focuses on improving the PAC emissions estimation and speciation methodologies and reducing the uncertainties in VOC emissions which are subsequently used in PAC emissions estimation.


2006 ◽  
Vol 5 (4) ◽  
pp. 731-741
Author(s):  
Fatih Taspinar ◽  
Ertan Durmusoglu ◽  
Aykan Karademir

Author(s):  
James G. Droppo ◽  
Bruce A. Napier ◽  
Jeremy P. Rishel ◽  
Richard W. Bloom

The current cleanup of structures related to cold-war production of nuclear materials includes the need to demolish a number of highly alpha-contaminated structures. The process of planning for the demolition of such structures includes unique challenges related to ensuring the protection of both workers and the public. Pre-demolition modeling analyses were conducted to evaluate potential exposures resulting from the proposed demolition of a number of these structures. Estimated emission rates of transuranic materials during demolition are used as input to an air-dispersion model. The climatological frequencies of occurrence of peak air and surface exposures at locations of interest are estimated based on years of hourly meteorological records. The modeling results indicate that downwind deposition is the main operational limitation for demolition of a highly alpha-contaminated building. The pre-demolition modeling directed the need for better contamination characterization and/or different demolition methods—and in the end, provided a basis for proceeding with the planned demolition activities. Post-demolition modeling was also conducted for several contaminated structures, based on the actual demolition schedule and conditions. Comparisons of modeled and monitoring results are shown. Recent monitoring data from the demolition of a UO3 plant shows increments in concentrations that were previously identified in the pre-demolition modeling predictions; these comparisons confirm the validity and value of the pre-demolition source-term and air dispersion computations for planning demolition activities for other buildings with high levels of radioactive contamination.


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