Air quality and noise assessments are important components of the environmental impact assessment process.  These components include an evaluation of:

• Current or baseline conditions
• Project contribution relative to baseline conditions
• Cumulative effects
• Comparison of changes to regulatory criteria
• Need for mitigation and follow-up monitoring

Such assessments help evaluate the effect of airborne emissions on sensitive receptors and the environment. Air quality dispersion models simulate plume behaviour and consider local ambient air quality, meteorology, land use, terrain and other local factors. For noise emissions, a wide range of predictive noise models are available. 

The assessment methods are flexible and can be tailored to achieve results within the scope of the problem, balancing the level of effort with technical complexity.  The assessment results can be used for follow-up studies that can include health risk and economic feasibility.

RWDI has participated in a number of multidisciplinary Environmental Impact Assessments teams to evaluate major oil sands, pipeline transmission, landfill, energy, industrial, and transportation projects throughout Canada.

The air quality and noise components of these assessments typically require a high level of interaction with the project design engineering teams and other environmental disciplines.  For larger projects, other services typically include public consultation, public presentation, expert testimony and peer review.

Oil Sands Area - Northeastern Alberta

Source Characterization

• RWDI developed a substantial oil sands region emission database for environmental assessment purposes with specific information on:
  • Stack parameters
  • Containment emission rates
  • Emission factors
  • Operator information
  • Location
• Emission scenarios were developed for baseline, project, and cumulative emission scenarios

Ambient Air Quality

• Review of Wood Buffalo Environmental Association / air quality stations was undertaken to determine baseline air quality characteristics

Meteorology

• CALMET model was used to develop 3-D meteorological fields for the region based on:
  • MM5 mesoscale model predictions
  • Surface observations from meteorological stations

Modeling

• CALPUFF dispersion model was used to predict:
  • Ambient concentrations
  • Secondary formation of particulates (sulphate, nitrate)
  • Potential acid input (PAI) deposition
• Baseline predictions were compared to ambient air quality measurements
• Baseline, project and cumulative scenario predictions were compared to ambient criteria to determine significance

Reporting

• Model predictions communicated to other environmental disciplines
• Assessment results summarized in tabular and graphical contour plot formats created using ArcGIS

800MW Combined Cycle Power Plant - Southern Ontario

Source Characterization

• Detailed review of equipment emission characteristics and site layout with engineering design team, including predicted reaction chemistry prior to exhaust
• Incremental modelling of facility to determine optimum stack height and noise mitigation solutions
• RWDI has substantial experience with power plants and large industrial facilities allowing assessment and feedback on:
• • Stack parameters
  • Containment emission rates
  • Emission factors

Public Consultation

• RWDI experts attend multiple stakeholder information sessions, open houses, presentations and meetings to respond to public concerns
• Generation of graphical presentation materials to communicate results to public
• Positive public feedback

Light Rail Transit - Eastern Ontario

Source Characterization

• Review of diesel train characteristics to determine expected emissions including odour
  Evaluation of potential emission sources such as:
• • Train movements
  • Idling trains at stations
  • Exhaust 'slug' from tunnels exits
  • Tunnel ventilation exhaust
• RWDI has substantial experience with major transportation projects allowing assessment and feedback on:
  • Corridor configuration
  • Idling and mobile emission rates
  • Source characterization
  • Compliance with applicable emission regulations

Ambient Air Quality

• Data from local MOE and federal measurement stations used to determine baseline air quality conditions and trends

Modeling

• U.S. EPA dispersion models used to predict combined air quality impacts along the corridor from stationary and moving train sources.
• Modeling of multiple operational scenarios
• Consideration of diesel odor impacts in addition to combustion pollutants

Reporting

• Presented in tabular and graphical contour plot formats
• Comparison of predicted results to ambient air quality and odor criteria
• Results integrated with other RWDI services for noise and vibration assessments