This provides an update of a backward air trajectory analysis project conducted for the OTAG Air Quality Analysis Workgroup by VT DEC. Methods and previous results (based primarily on "location-based trajectory sorting") have been reported at: http://capita.wustl.edu/otag/Reports/Restime/Restime.html and http://capita.wustl.edu/otag/Reports/vtdecair/vtdecair.html. The current report presents results of "concentration-based trajectory sorting" for 7 Summers (1989-95) for 23 ozone monitoring sites in the OTAG domain, for selected subsets of the ozone distribution (lower 50th percentile and upper 50th, 25th, 10th and 5th percentile concentrations). The results are generally consistent with previous "location-based sorting" results, and suggest that: the OTAG region is geographically well-configured to address zone transport; local stagnation is most important in the South; and that industrial Midwest exhibits a high probability contributing to peak ozone concentrations at many sites throughout the OTAG domain.
The "Residence Time Analysis" techniques employed in
these studies involves tracking, sorting and aggregating large
numbers of backward HY-SPLIT trajectory calculations on a grid
of 1440 80x80 km squares. Trajectories arriving at a specific
receptor site are sorted either as a function of prior trajectory
location, or as a function of ozone concentration at the receptor.
Location-based sorting involves calculation of a descriptive statistic
(for example, the mean ozone concentration, or, more recently,
the mean Z-score derived from the geometric mean and standard
deviation of the ozone concentration) for all trajectories passing
through a specific grid square en route to the receptor. Resulting
plots address the question: if the air has previously been here
(or there), what's the average ozone concentration at this (or
that) receptor? Results of location-based sorting are described
in vtdecair.html. Advantages of location-based sorting
include: use of all available trajectories (large numbers) and
quantitative results (if the air was here, ozone at the receptor
averaged 10 ppb higher than average). Disadvantages include: relevance
only to changes in average (rather than peak) ozone, and inability
to identify potential contributions from areas close to the receptor.
This latter limitation is due to the constraint that all trajectories
arriving at a site must pass through the grid square containing
the receptor, through 1 of 8 squares surrounding the terminal
square, etc. Consequently, the average ozone for trajectories
passing over grid squares containing or close to the receptor
site will be similar to the average at the monitoring site (ie
ozone in air near Whiteface Mtn. will have ozone concentrations
similar to Whiteface Mtn.). An additional disadvantage is a disregard
of trajectory frequency - a relatively distant location may be
'conditionally' associated with high ozone at the receptor, but
may be infrequently upwind.
Concentration-based sorting involves sorting trajectories as a
function of associated ozone concentration at the receptor. Space/time
characteristics of trajectories associated with subsets of high
(low, very high, etc.) ozone concentrations are plotted as "residence-time
probabilities". Resulting plots address the question: if
ozone at the receptor was high (or low or very high), where did
the air come from? One advantage of concentration-based sorting
is an ability to focus on different portions of the ozone distribution
(including episodes). In addition, the results reflect both concentration
and frequency associated with upwind locations. A potential disadvantage
is that the highest residence-time probability, regardless of
which subset of trajectories is examined, will always be for grid
squares containing, or adjacent to the receptor square (all trajectories
must pass through the terminal square). In this analysis, we attempt
to remove this "near bias" by comparing residence-time
probabilities for specific subsets of the receptor ozone concentration
with residence-time probabilities for all trajectories arriving
at the receptor, regardless of associated ozone concentration.
This concept is referred to as "incremental probability",
and addresses the question: how much greater than "normal"
is the probability a location was upwind if the ozone was high?
Techniques for calculating residence-time probabilities are described
in: Poirot and Wishinski ((1986) Atmos. Environ., 20: 14571469)
and Wishinski and Poirot ((1996) at http://capita.wustl.edu/otag/Reports/Restime/Restime.html).
An "everyday" probability field is calculated for each
monitoring site by summing, for each grid square, the total hours
that all trajectories over the past 7 summers spent over that
grid square. That grid square's everyday probability is expressed
as the ratio of residence-time hours in that square to the total
hours for all grid squares. In a standard plotting routine, isopleths
are drawn to bound the smallest areas accounting for 25, 50 and
75% of the total residence time probabilities. These everyday
probability fields are analogous to a trajectory-based "airshed"
for each receptor site. They address the question: where is the
summertime air at site X most likely to have previously resided?
(See http://capita.wustl.edu/otag/Reports/Restime/Images/IMG18.GIF).
Similar probability fields can be calculated for any subset of
the total trajectories, such as for the upper 50% of the receptor's
ozone concentration (http://capita.wustl.edu/otag/Reports/Restime/Images/IMG04.GIF).
The incremental probability for any subset of trajectories is calculated by subtracting the everyday probability from the high (or low) ozone subset probability. For consistency, isopleths bound areas accounting for 25, 50 and 75% of the total incremental probability. Plotted areas are those more likely to be upwind if ozone is high (or low), regardless of their proximity to the receptor. Locations close to and moderately distant from the receptor may be implicated.
Upper 50% Probability minus Everyday Probability = Upper 50% Incremental
Probability
Figure one.
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Incremental Probability plots for all 23 sites and for several different percentiles of ozone concentration are stored in a series of .avi animations (for which CAPITA Movie Program is recommended) as follows:
50hilo.avi - shows incremental probabilities for upper and lower 50th % ozone at all sites
25hi10.avi - shows incremental probabilities for upper 25th % and 10th% ozone at all sites
50hi5.avi - shows incremental probabilities for upper 50th % and 5th% ozone at all sites
Example frames from 50hilo.avi for selected sites and site groups
are pasted below in Figures 2 - 7. In each figure, the left panel
shows locations associated with the lowest 50% of ozone values
at the receptor(s); the right panel shows locations associated
with the highest 50% of ozone values.
The Incremental Probability plots based on all 23 trajectory sites
are displayed in Figure 8. As with the previously-reported results
of location-based sorting, these results suggest that the OTAG
domain is geographically well-formulated for addressing ozone
transport. Clean air at sites throughout OTAG is associated with
locations external to OTAG, while higher ozone concentrations
are associated with areas internal to OTAG. By contrast, the 13-State
OTR is not so well configured (see Figure 7), as high ozone levels
at OTR sites include high incremental residence-time probabilities
in areas external to the OTR.
Figure 8. Incremental Probability: All 23 Trajectory
Sites, for Lower 50% (left) and Upper 50% Ozone (right)
Figure 10. Examples of Sites with Similar Incremental
Residence-Time Probabilities for
Upper 50 Percentile (left) and Upper 5 Percentile (right)
Ozone Concentrations
As displayed above in Figure 10, for a majority of sites there
are relatively small differences between incremental probabilities
for areas upwind for moderately high (upper 50%) and extremely
high (upper 5%) ozone levels. Two notable exceptions to this pattern
are at the high elevation Shenandoah National Park and Great Smokey
Mtn. National park sites. During the highest episode days, Shenandoah
exhibits relatively more influence from the due west and due south,
and relatively less influence from the southwest direction, while
Gt. Smokey mountain NP shows an increased prevalence of southwesterly
flows during episodes (see Figure 11).
Figure 11. Examples of Sites with Different Incremental
Residence-Time Probabilities for
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Upper 50 Percentile (left) and Upper 5 Percentile (right)
Ozone Concentrations
Figure 10 shows sites with very similar incremental probabilities
for moderately high and extremely high ozone. Figure 11 results
represent the most extreme exceptions to this general pattern
of similarity. A third group of sites show both similarities and
differences between upwind areas for moderately high and extremely
high ozone Specifically, the areas with highest probability of
being upwind for upper 5%, also have high incremental probability
for upper 50%. However, other areas upwind for upper 50% are not
implicated during episodes (see Figure 12).
Figure 12. Examples of Sites with "Similar and Different" Incremental Probabilities for
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For Whiteface Mtn., NY, moderately high ozone is spatially associated
with a broad area extending south to southwest to west of the
site. For extremely high ozone, there is relatively low probability
that the air resided due south of the site, with higher probability
from areas to the west (along the lower Great Lakes) ans southwest
(Ohio River Valley). Farther east, at Port Clyde ME, there's a
high probability for moderately high (upper 50%) ozone concentrations
that the air had previously resided to the south of the site (east
coast corridor). But this 'southerly' influence is less evident
for extremely high concentrations, when southwesterly flows (residence
over Midwestern industrial areas) are more probable. For moderately
high ozone at Mark Twain State Park, MO, incremental probabilities
are high for areas extending both to the south and northeast of
the site. During episodes, the southerly influence is much less
evident, while the northeasterly influence (industrial Midwest)
remains. A similar pattern is evident for Boone County, KY. Thus,
for a number of sites in different regions, moderately high ozone
is associated with prior residence time over a broad range of
upwind areas. But when only peak ozone concentrations are considered,
the industrial Midwest appears to be the region most consistently
upwind for a number of different sites and regions throughout
the northern half of the OTAG domain (see Figures 12, and 13).
Figure 13. Comparative Incremental Probabilities for Groups of 6 Midwestern & 6 Eastern Sites for
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Figure 14. Incremental Residence-Time
Probabilities for 23 Sites for
Upper 50% (left) and Upper 5% (right) Ozone Concentrations
Upper 50th and upper 5th percentile incremental probabilities
for all 23 ozone monitoring sites are combined in Figure 14. Note
that at both the upper 50% and 5% ozone levels, there are areas
of relatively high incremental probability surrounding/adjacent
to all the most southerly sites (consistent with local stagnation
influences). Note also that at moderately high and extremely high
ozone levels, there are no areas of high probability at/near any
of the New England sites (consistent with a predominant influence
of transport). As increasingly high ozone levels at all sites
are considered, the area of highest incremental probability becomes
increasingly focused on the industrial Midwest (Ohio River Valley).
It should be noted that the synoptic-scale trajectory model and
associated NGM windfields are not well-suited for evaluation of
local-scale influences (nor is evaluation of local influences
the objective of this study). It is also emphasized that the methods
employed here to process ensemble trajectory results do not explicitly
include estimates of emissions and chemical reactions (nor is
it the intent of this analysis to distinguish among the influences
of emissions, chemistry and meteorology). The basic assumption
employed here is that the ambient ozone at a given place and time
represents (exactly) the sum total of all forces which have acted
upon it (emissions - anthropogenic and natural; chemistry - formation
and destruction; and meteorology - including stagnation, mixing,
transport, wet and dry deposition, etc.). If a specific "source
region" is persistently upwind of one (or many) receptors
when ozone concentrations are highest, this does not necessarily
implicate any specific emissions sources or source categories
in that source region. Note, for example in Figures 3 and 5, high
probabilities for upper 50th percentile ozone levels at VT and
FL receptor sites over marine areas where emissions are presumably
quite low, but which may act to protect transported ozone levels
from chemical and physical destruction processes.
Conceivably, the Ohio River Valley may be "innocently" upwind of the various receptor sites. The region is spatially large (compared to individual urban areas) and centrally located (geographically and meteorologically) relative to many ozone non-attainment areas. Adverse meteorological conditions such as a high potential for subsiding high pressure systems may cause this region to act as a sort of accumulation area for ozone and precursors from surrounding areas. However, the Ohio River Valley is also characterized by high densities of elevated stationary source NOx emissions (and current geography and adverse meteorology are beyond our control). Historical modeling results (as summarized in the 2/96 ENVIRON review) suggest that reductions in elevated stationary source NOx emissions are relatively ineffective in reducing surface ozone concentrations. The long-term trajectory-based results presented here are clearly at odds with that observation, and suggest that control of stationary source NOx emissions may be an effective means of reducing peak and chronic ozone levels over a broad range of receptors.
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1. The OTAG region (unlike the OTR) is geographically well-configured
to address ozone transport, as low ozone concentrations are consistently
associated with prior airmass residence over areas (north, south,
east and west) external to OTAG, and high ozone is consistently
associated with prior airmass residence over areas (throughout
and) internal to OTAG (Figures 2-8).
2. Local stagnation (high residence time near the receptor) appears
to be a much more important characteristic of high ozone concentrations
in the South than in the Northeast (Figures 4, 5, 9, 10, 14).
3. For most receptor sites, upwind areas associated with moderately
high ozone are also associated with extremely high ozone concentrations
at these sites (Figure 10).
4. While there are unique upwind areas associated with moderately
high (above median) ozone levels for each site, the industrial
Midwest appears to be a common source area for moderately high
ozone levels many sites throughout OTAG (Figures 6-8).
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