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| Titel |
Influence of air quality model resolution on uncertainty associated with health impacts |
| VerfasserIn |
T. M. Thompson, N. E. Selin |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
1680-7316
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| Digitales Dokument |
URL |
| Erschienen |
In: Atmospheric Chemistry and Physics ; 12, no. 20 ; Nr. 12, no. 20 (2012-10-26), S.9753-9762 |
| Datensatznummer |
250011533
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| Publikation (Nr.) |
 copernicus.org/acp-12-9753-2012.pdf |
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| Zusammenfassung |
| We use regional air quality modeling to evaluate the impact of model
resolution on uncertainty associated with the human health benefits
resulting from proposed air quality regulations. Using a regional
photochemical model (CAMx), we ran a modeling episode with meteorological
inputs simulating conditions as they occurred during August through
September 2006 (a period representative of conditions leading to high
ozone), and two emissions inventories (a 2006 base case and a 2018 proposed
control scenario, both for Houston, Texas) at 36, 12, 4 and 2 km resolution.
The base case model performance was evaluated for each resolution against
daily maximum 8-h averaged ozone measured at monitoring stations. Results
from each resolution were more similar to each other than they were to
measured values. Population-weighted ozone concentrations were calculated
for each resolution and applied to concentration response functions (with
95% confidence intervals) to estimate the health impacts of modeled ozone
reduction from the base case to the control scenario. We found that
estimated avoided mortalities were not significantly different between the
2, 4 and 12 km resolution runs, but the 36 km resolution may over-predict
some potential health impacts. Given the cost/benefit analysis requirements
motivated by Executive Order 12866 as it applies to the Clean Air Act, the
uncertainty associated with human health impacts and therefore the results
reported in this study, we conclude that health impacts calculated from
population weighted ozone concentrations obtained using regional
photochemical models at 36 km resolution fall within the range of values
obtained using fine (12 km or finer) resolution modeling. However, in some
cases, 36 km resolution may not be fine enough to statistically replicate
the results achieved using 2, 4 or 12 km resolution. On average, when
modeling at 36 km resolution, an estimated 5 deaths per week during the May
through September ozone season are avoided because of ozone reductions
resulting from the proposed emissions reductions (95% confidence interval
was 2–8). When modeling at 2, 4 or 12 km finer scale resolution, on average
4 deaths are avoided due to the same reductions (95% confidence interval
was 1–7). Study results show that ozone modeling at a resolution finer than
12 km is unlikely to reduce uncertainty in benefits analysis for this
specific region. We suggest that 12 km resolution may be appropriate for
uncertainty analyses of health impacts due to ozone control scenarios, in
areas with similar chemistry, meteorology and population density, but that
resolution requirements should be assessed on a case-by-case basis and
revised as confidence intervals for concentration-response functions are
updated. |
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