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A. Ciccone et al.
Burlington Ave E and at the intersection of Highway 403 and Highway 8, depending
on the compound of interest. Ozone and NO 2 spatial plots show concentrations
correlating with the major roadways.
19.4 Source Apportionment Results
To complete the source apportionment for HAMS a “zero-out” approach was used
where emissions from selected source groups are removed from the inventory. The
importance of that source is assessed by evaluating the change in ambient air quality
as the difference (absolute and percentage) in compound concentration between the
base case (with the source group) minus the scenario without the source group.
Simulations were carried out evaluate the contribution to the air quality compounds
of interest from: on-road mobile sources; industrial sources; non-road mobile (rail,
airport and marine) sources; and transboundary only (all sources within Tier IV were
removed).
The source apportionment simulations were carried out for a selected month of
each season for 2012 as well as for an ensemble average of all four months to represent a year for the Tier IV domain. The Tier III domain results were used for initial
conditions and a minimum of a five day spin up time was used for each simulation. Results indicate a strong transboundary influence in the Hamilton region, with
transboundary influences contributing upwards of 90% for particulate matter (PM 2.5
and PM 10 ). Local industrial emissions contribute less than 20% by compound to air
quality in the Hamilton region, except for B(a)P where it is the main source (47%).
Local on-road sources are a major contributor (34%) to NO 2 levels in the domain,
after transboundary (44%). Transportation related emissions are the major contributor to transboundary emissions for all compounds except SO 2 which is dominated
by industrial sources.
19.5 Conclusion
The results of the HAMS demonstrate that the model is conservative in the simulation of air quality levels within the Hamilton region. While most compounds are
over-predicted, they are within a factor of two of the observations. The source apportionment demonstrates a strong transboundary influence across the domain, heavily influenced by transportation (on-road and non-road) emissions. Local industrial
emissions have a comparatively small influence, apart from B(a)P. Further studies
are needed to strengthen the source apportionment and provide more detailed information to support policy development to improve the air quality in the Hamilton
region.
A. Ciccone et al.
Burlington Ave E and at the intersection of Highway 403 and Highway 8, depending
on the compound of interest. Ozone and NO 2 spatial plots show concentrations
correlating with the major roadways.
19.4 Source Apportionment Results
To complete the source apportionment for HAMS a “zero-out” approach was used
where emissions from selected source groups are removed from the inventory. The
importance of that source is assessed by evaluating the change in ambient air quality
as the difference (absolute and percentage) in compound concentration between the
base case (with the source group) minus the scenario without the source group.
Simulations were carried out evaluate the contribution to the air quality compounds
of interest from: on-road mobile sources; industrial sources; non-road mobile (rail,
airport and marine) sources; and transboundary only (all sources within Tier IV were
removed).
The source apportionment simulations were carried out for a selected month of
each season for 2012 as well as for an ensemble average of all four months to represent a year for the Tier IV domain. The Tier III domain results were used for initial
conditions and a minimum of a five day spin up time was used for each simulation. Results indicate a strong transboundary influence in the Hamilton region, with
transboundary influences contributing upwards of 90% for particulate matter (PM 2.5
and PM 10 ). Local industrial emissions contribute less than 20% by compound to air
quality in the Hamilton region, except for B(a)P where it is the main source (47%).
Local on-road sources are a major contributor (34%) to NO 2 levels in the domain,
after transboundary (44%). Transportation related emissions are the major contributor to transboundary emissions for all compounds except SO 2 which is dominated
by industrial sources.
19.5 Conclusion
The results of the HAMS demonstrate that the model is conservative in the simulation of air quality levels within the Hamilton region. While most compounds are
over-predicted, they are within a factor of two of the observations. The source apportionment demonstrates a strong transboundary influence across the domain, heavily influenced by transportation (on-road and non-road) emissions. Local industrial
emissions have a comparatively small influence, apart from B(a)P. Further studies
are needed to strengthen the source apportionment and provide more detailed information to support policy development to improve the air quality in the Hamilton
region.