Methodology
Base case modeling
Air quality modeling for the NA domain and calendar year 2010 used CAMx
version 6.2 (Ramboll Environ, 2015) to simulate formation and transport of
O3. Gas-phase chemistry was included using the Carbon Bond (CB05)
mechanism (Yarwood et al., 2005), but heterogeneous-phase chemistry was not
included for efficiency and because the focus is on O3. The CAMx
modeling domain covers the continental US with 459 by 299 grid cells of
12 km by 12 km resolution and 26 vertical layers (Table S1 in the Supplement). The vertical height
of the first layer is 20 m. Model inputs were prepared from data
provided to all AQMEII participants supplemented by other data sources
(described later). The 2010 annual simulation was initialized on 22 December 2009
to limit the influence of initial concentrations.
This study uses reactive tracers with a chemical mechanism compiler (RTCMC)
in CAMx to track contributions from BCs. The RTCMC module simulates explicit
tracers in parallel to the host model and represents sources (emissions and
BCs), transport processes (advection and diffusion), deposition, and
user-defined chemistry (Yarwood et al., 2014). RTCMC chemistry can use
species concentrations from the host model, e.g., OH radical, in the
reactions of tracers. If no chemistry is defined for an O3 tracer, then
it becomes chemically inert and deposition is the only sink. Currently,
the RTCMC models dry deposition of tracers but not wet deposition, which will
result in conservative estimates of BC contributions.
CAMx can also track BC O3 contributions through the ozone source
apportionment technology (OSAT; Ramboll Environ, 2015) module, but we use
RTRAC because it offers flexibility to model reactive and inert tracers, and
to track BC O3 from specific groups of vertical layers. Vertical
attribution is valuable in identifying height ranges of transported O3
that are most influential to ground-level O3. Baker et al. (2015)
compared RTCMC and OSAT over North America and found that the two approaches
estimated very similar BC O3 contributions in warmer months. Baker et
al. also evaluated computational efficiency of RTCMC tracers. We use the
same RTCMC scheme for reactive O3 tracers as Baker et al. (2015)
(Table S2), which includes O3 destruction by odd hydrogen (i.e., HO2 and OH)
and alkenes but not O3 destruction by NO because this would entail
tracking conversion of BC O3 to/from several NOy species, including
NO2, PAN and HNO3. OSAT accounts for O3 destruction by NO and
Baker et al. show that omission of O3 destruction by NO in the RTCMC
scheme causes some positive bias in BC O3 estimates in winter months
(Baker et al., 2015).
The BC O3 contributions are analyzed in terms of MDA8 by season because
the MDA8 is relevant to the US National Ambient Air Quality Standard (NAAQS)
for O3, which is set at a level of 70 ppb. Seasonal averages are used to
evaluate how BC contributions depend upon transport patterns and photochemistry.
Meteorology
Meteorological data for calendar year 2010 were developed by the
US Environmental Protection Agency (EPA) for AQMEII phase 2 using the Weather
Research Forecast (WRF; Skamarock et al., 2008) model with 12 km resolution.
The WRF domain was defined in Lambert conformal projection with 471 by
311 grid cells and 35 vertical layers with a 20 m deep surface layer. The
WRF physics options were described in Gilliam et al. (2012). The WRFCAMx
pre-processor reformatted WRF output for CAMx and diagnosed vertical mixing
parameters. CAMx employed fewer vertical layers (26) than WRF (35) to reduce
the computational burden of the air quality simulations. The CAMx vertical
layers exactly matched those used in WRF for the lowest 10 layers (up to
577 m); above this height several WRF layers were combined to single CAMx layers
(Table S1). The minimum vertical diffusivity (Kv) was set to
0.1–1.0 m2 s-1 based on input landuse.
Emissions
Anthropogenic and fire emissions for 2010 were provided by AQMEII (Pouliot
et al., 2015) separately for surface emissions and six elevated source
groups, namely fires, international marine shipping, electric generating
units (EGU), other point sources (non-EGU), Mexico point sources, and Canada
point sources. Biogenic emissions were obtained from the Model of Emissions
of Gases and Aerosols from Nature version 2.1 (MEGAN; Guenther et al.,
2006; Sakulyanontvittaya et al., 2008). MEGAN has a global database of
land cover derived from satellite data at 1 km resolution. Meteorological
input data for MEGAN (i.e., temperature and solar radiation) were taken from
the WRF predictions. Annual emissions in 2010 in the modeling domain for
each source sector are summarized in Table 1.
Boundary conditions
BCs were provided by the European Centre for Medium-Range Weather Forecasts (ECMWF).
The ECMWF BC data were based on the Composition-Integrated Forecast
System (C-IFS) model (Flemming et al., 2015), which outputs 3-hourly,
three-dimensional gridded concentrations which were formatted for CAMx.
We tracked contributions from O3 BCs in three height ranges defined at
the CAMx boundaries, namely from layers 1 to 16 (layers below 750 mb; lower
troposphere, LT), 17 to 23 (layers between 750 and 240 mb; middle
troposphere, MT), and 24 to 26 (layers above 250 mb; upper troposphere and
lower stratosphere, UTLS). We introduced both reactive and inert O3
tracers for the same vertical groups. Reactive tracers undergo chemical
decay according to chemistry scheme defined using the RTCMC, whereas inert
tracers only participate in physical processes with no chemical removal.
Table S2 presents the RTCMC chemistry scheme for reactive tracers as well as
the physical properties for both reactive and inert tracers.
Sensitivity scenarios
Two sensitivity simulations defined by AQMEII were conducted to quantify
O3 response to anthropogenic emission reductions. The GLO scenario
reduced all anthropogenic emissions by 20 % globally and the EAS scenario
reduced anthropogenic emissions in the East Asia by 20 %. In the GLO
scenario, the CAMx NA anthropogenic emissions were reduced by 20 % for the
entire modeling domain with no changes to fire and biogenic emissions. Under
the EAS scenario the CAMx NA emissions are the same as in the base case.
ECMWF provided BCs specific for each scenario. The ECMWF BCs inadvertently
omitted H2O2 for the EAS scenario and so we followed the AQMEII
suggestion to use H2O2 from the base case for both the EAS and GLO
scenarios. Other modeling inputs are unchanged from the base case. The
annual CAMx sensitivity simulations were conducted with the inert and active
boundary O3 tracers described above. Several metrics are used when
comparing sensitivity scenarios to the base case including the fourth highest
maximum daily 8 h average (H4MDA8), the average of the 30
highest MDA8 O3 days (Top 30), and seasonal average
MDA8. We show the results for the entire modeling domain and additionally
discuss our findings for 22 selected major cities in a wide variety of
climatic and geographic environments (Fig. S1 in the Supplement). Cities are represented by
the monitoring site with highest H4MDA8 in the metropolitan statistical area.
Annual emissions by source sector in 2010 (thousand short tons per year; 1 short ton = 0.907185 metric tons).
Sector
NOx
VOC
CO
Elevated sources
EGU (ptipm)
2141
41
691
Non-EGU (ptnonipm)
1558
323
2047
International shipping (c3marine)
1186
45
99
Mexico (mexpt)
384
50
153
Canada (canpt)
504
577
834
Fire (ptfire)
198
1783
13 172
Low-level sources
Anthropogenic surface
13 067
15 562
58 672
Biogenic
728
53 469
4309
Total
19 765
71 850
79 977
Results
Model performance evaluation (MPE) of ozone
We evaluate O3 model performance for the base case relative to
benchmarks that are accepted in NA. Predictions of MDA8 O3 are evaluated
against observations from the Clean Air Status and Trends Network (CASTNET;
rural) and the Air Quality System (AQS; urban and rural). Observations are
considered valid when at least 75 % of data are available. A 40 ppb
O3 cutoff is applied to focus on the upper end of O3 frequency
distributions. Statistical metrics used in this evaluation include two bias
metrics (normalized mean bias, NMB; fractional bias, FB) and two error
metrics (normalized mean error, NME; fractional error, FE) (Table 2). Table 3
shows that model biases (NMB, FB) are less than ±12 % and errors (NME,
FE) up to 15 % for all seasons and both networks, well within the
bias/error goals of less than ±15 % and 35 % recommended by
EPA (1991). The model tends to overestimate O3 in spring and summer,
while it underestimates in fall and winter. Model biases and errors are
slightly improved, by less than 2 %, at CASTNET sites. The AQS network
includes many urban sites that are heavily impacted by local emissions not
well resolved by our modeling grid.
Model performance metrics, where 〈o〉 is the mean and
σo is the standard deviation of the observed (o) or modeled (m)
concentrations (C).
Metric (potential range)
Equation
Normalized mean bias (%)
NMB=∑i=1NCm-Co∑i=1NCoNME=∑i=1NCm-Co∑i=1NCo
(-100 % to +∞)
Normalized mean error (%)
(0 % to +∞)
Fractional bias (%)
FE=1N∑i=1NCm-CoCo+Cm2FB=1N∑i=1NCm-CoCo+Cm2
(-200 to +200 %)
Fractional error (%)
(0 to +200 %)
Correlation coefficient
r = 1N-1∑i=1NCm-CmσmCo-Coσo
Root mean square error
RMSE = ∑i=1NCm-Co2N
Seasonal and annual model performance statistics for MDA8 O3 (with
40 ppb cutoff) at AQS and CASTNET sites.
Season
Network
No. obs.
Mean
NMB
NME
FB
FE
r
RMSE
(%)
(%)
(%)
(%)
Spring
AQS
71 074
53.6
2.7
10.9
2.6
10.8
0.61
7.44
CASTNET
5737
54.2
1.9
10.3
1.9
10.2
0.63
7.11
Summer
AQS
72 548
57.3
5.6
13.4
5.4
13.0
0.61
9.53
CASTNET
5029
56
5.5
12.4
5.6
12.1
0.63
8.47
Fall
AQS
41 729
48.7
-5.9
12.1
-6.4
12.4
0.68
8.26
CASTNET
3597
47.3
-7.3
10.9
-7.6
11.2
0.71
7.24
Winter
AQS
11 823
40
-10.6
14.0
-11.8
15.1
0.30
8.35
CASTNET
2328
41.3
-9.0
12.1
-10.0
13.1
0.51
6.67
Annual
AQS
197 174
53.1
1.3
12.3
0.9
12.2
0.64
8.48
CASTNET
16 691
51.5
-0.4
11.3
-0.7
11.4
0.66
7.52
See Table 2 for definitions of the statistical metrics.
The seasonal spatial distributions of NMB, NME, and Pearson's correlation
coefficient (r) at individual CASTNET and AQS sites are shown in Figs. S2–S5.
The springtime performance is weakest (|r| < 0.5)
in the western US, where high terrain prevails. Stratospheric O3
intrusions are influential in the high terrain of the western US during
spring (Langford et al., 2009, 2015; Lin et al., 2012b; Emery et al., 2012)
but models do not always represent this process accurately. In summer, the
performance is weakest along the Gulf Coast and California coast. Model
performance against AQS observations is presented separately for selected
22 major cities. CAMx performs well at these cities, with NMB of -12 to
12 % and NME of 12 to 21 % for MDA8 with zero threshold (Table S3),
satisfying the bias/error goals. The performance statistics improve when
applying a 40 ppb threshold (Table S4). We additionally provide
quantile–quantile (Q–Q) plots (Fig. S8) which compare independently sorted
(time-unpaired; space-paired) observed and modeled O3 for each city.
The Q–Q plots suggest good model distributions (e.g., data pairs near the
1 : 1 line) for Los Angeles, Sacramento, Phoenix, Denver, Dallas, Houston,
Pittsburgh, and Philadelphia.
Observed (black circle) and CAMx-predicted (red line) daily MDA8 O3
at Galveston (a; coordinates: 29.254474, -94.861289∘), and
Sabine Pass (b; coordinates: 29.727931, 93.894081∘) monitoring
sites located on the Texas Gulf Coast near Houston and Beaumont, respectively.
Contributions are shown for inert (green line) and reactive (blue line) BC
O3 tracers summed over boundary height ranges.
We evaluated vertical profiles of O3 at Trinidad Head (41.0541,
-124.151∘) on the northern coast of California (Figs. S6 and S7). This
location is indicative of O3 entering the US with prevailing winds from
the Pacific Ocean and useful for evaluating O3 BCs over the Pacific.
CAMx reproduces the strong gradient in O3 starting at the tropopause
(between ∼ 10 and ∼ 14 km) but sometimes
underestimates O3 near the model top (∼ 16 km). In the
free troposphere (∼ 1 to ∼ 10 km), CAMx
performance is reasonable with a mix of over- and underpredictions. In the
marine boundary layer (MBL; < 500 m), CAMx tends to overpredict
surface O3 because the model lacks a consistently observed gradient
toward lower O3 (typically lower than 50 ppb) at the surface.
Potential causes are too little O3 deposition to the ocean, a lack of
O3 destruction by halogen chemistry in the MBL, too strong vertical
mixing in the MBL, or a combination of factors. The influence of low bias in
the Pacific MBL will be confined to west coast states because this air is
blocked effectively by western mountain ranges (see Sect. 3.5). However,
similar biases in the MBL over the Gulf of Mexico and Atlantic Ocean could
influence O3 across the southern and eastern US (see Sect. 3.2).
Further analysis is required to address this uncertainty.
Regional MPE analysis at remote sites along the Gulf Coast
We found a consistent high bias for summer O3 at sites near the Gulf
Coast and investigated potential causes using our tracer simulation results.
Global modeling studies have reported high-O3 bias simulated in air
arriving along the Texas coast (Fiore et al., 2002, 2014; McDonald-Buller et
al., 2011; Zhang et al., 2011). The high-O3 bias over 10 ppb has been
reported by a regional modeling study (Sarwar et al., 2015; Smith et al.,
2015). Adding reactions of halogens (especially iodine; Smith et al., 2015)
to the O3 chemistry in CAMx mitigated (e.g., ∼ 3 ppb
reduction of MDA8 O3 at coastal sites) but did not eliminate this bias.
This study provides an opportunity to examine whether bias in O3 BCs
could contribute to O3 bias along the Gulf Coast.
Time series of daily MDA8 O3 together with O3 BC contributions
are shown in Fig. 1 for Galveston and Sabine Pass in Texas. CAMx tends to
overpredict O3 during summer months when onshore winds are prevalent
(TCEQ, 2016) due to the enhancement of the Bermuda High bringing warm air from
the Gulf of Mexico (Zhu and Liang, 2013). During this period CAMx has a
large overprediction bias exceeding 15 ppb at the two sites when
observations are low (∼ 20 ppb). Reactive O3 tracers
exceed observed O3 by an average of 2–3 ppb, which explains only a
portion of the total model bias, so other factors must be contributing (not
examined here). Inert O3 tracers are on average higher than the
reactive tracers by 10–12 ppb, demonstrating that inert tracers can overestimate BC contributions.
BC ozone contributions to surface ozone
BC contributions based on the active tracers to seasonal average MDA8
O3 over the US are higher in spring than summer (Fig. 2). Spring
contributions are over 40 ppb across the western US, which is the region most
influenced by pollution transported from Asia (Jaffe et al., 2003; Zhang et
al., 2011; Lin et al., 2012a; Emery et al., 2012). In particular,
high-O3 events over the high terrain in the western US have been linked to
intercontinental transport and stratospheric intrusions (Lin et al., 2012a, b).
The highest modeled contributions occur in spring, which is consistent
with observations (Parish et al., 2012; Cooper et al., 2012) and previous
modeling studies (Emery et al., 2012; Fiore et al., 2014). BC contributions
in the eastern US are generally below 40 ppb in spring and below 30 ppb in other seasons.
BC contributions to seasonal average MDA8 O3 from reactive tracers
summed over boundary height ranges.
BC contributions on high-O3 days are compared to the summer average BC
contributions in Fig. 3 for 22 major cities. The metrics for high O3
are the H4MDA8, which is relevant to the NAAQS but is a single day, and the
Top 30, which includes a variety of conditions that can lead to high O3.
They are compared to the summer average MDA8 O3 metric which includes
high- and low-O3 days. In 15 of the 22 major cities (Los Angeles,
Sacramento, Dallas, Kansas City, St. Louis, Chicago, Atlanta, Cincinnati,
Columbus, Detroit, Pittsburgh, Baltimore, Philadelphia, New York, and
Boston), the BC contribution to the Top 30 and summer average days differs
by less than 15 %, indicating that higher O3 on the Top 30 days is
mainly attributable to larger O3 production within the modeling domain.
BC contributions to the H4MDA8 are smaller than to the Top 30 in 16 of the
22 cities, which is consistent with greater destruction of BC O3 by
local photochemistry on the highest O3 days in these cities. Los
Angeles and Sacramento fall in this category with BC contributions to H4MDA8
below 20 ppb. For the cities east of the Rocky Mountains the H4MDA8
contributions range from 19 ppb (St. Louis) to 34 ppb (Detroit) and the
differences among the three metrics are generally within 5 ppb with no
metric consistently being highest or lowest. In contrast, for cities in the
Intermountain West (Boise, Phoenix, Salt Lake, and Denver) the BC
contribution is consistently lower for summer average than the two high-O3 day metrics (i.e., differences are more than 8 ppb). For Denver, our
model estimates 57 ppb of BC contribution to the Top 30 and 72 ppb to the
H4MDA8. However, the modeled 72 ppb BC contribution to the Denver H4MDA8 is
certainly overstated, because the observed MDA8 on this day was only 50 ppb,
and we place more emphasis on metrics like the Top 30 that consider
multiple days. BC contributions tend to be higher in the western than the
eastern US because of higher terrain and deeper planetary boundary layer (PBL)
that can efficiently transport mid-tropospheric O3 to ground
level, and longer O3 lifetimes in the PBL (Fiore et al., 2002).
BC O3 contributions to the H4MDA (blue dot), average MDA8 on the
Top 30 MDA8 O3 days (red triangle), and summer average MDA8 (green square)
at 22 major cities.
Box-and-whisker plots comparing modeled total MDA8 O3 to modeled
BC contribution in 10 ppb ranges paired in time and space for Phoenix, Denver,
Philadelphia, and New York.
We further investigated how total O3 changes as the modeled BC
contributions increase (in 10 ppb increments) as shown in Fig. 4 for several
cities. The relationships vary between cities and the model captures this
variation with the western cities (Denver and Phoenix) showing different
patterns than eastern cities (Philadelphia and Atlanta). For Denver and
Phoenix in the Intermountain West, total O3 increases with BC
contribution and approaches the 1 : 1 line at higher BC contribution, revealing
small groups of days when MDA8 O3 exceeded 60 ppb (11 days for Denver
and 7 days for Phoenix) and the modeling indicates that BCs accounted for
almost all of this O3. In other words, BC contributions alone
distinguish high-O3 days from low days. These groups of high BC-contributed
days are important because local emission reductions, or even US-wide
emission reductions, would be ineffective at reducing O3. However,
there are other days in Denver when total MDA8 O3 exceeded 60 ppb
with modeled BC contribution below 30 ppb (see first and second bars in
Fig. 4) on which reducing local or US emissions would lower O3. Air
quality managers need methods to identify dates when emission reductions
would be ineffective so that those dates can be excluded from emission
strategy development. Nonetheless, these results should be interpreted with
consideration given to model performance. As shown in the Q–Q plot for
Denver (Fig. S8), the model can capture the O3 distribution quite well,
although it underestimates MDA8 O3 over 65 ppb and overestimates MDA8
O3 over 80 ppb. For this reason, we encourage making use of multi-day
metrics (such as Top 30) rather than a single-day metric (e.g., H4MDA8).
Inert vs. active ozone BCs
Contributions to seasonal average MDA8 from reactive and inert tracers are
shown in Fig. 5, where positive differences indicate larger contributions
from inert tracers in all seasons. In summer, when photochemistry is active,
the differences are more than 10 ppb. At the Galveston and Sabine Pass
sites, the differences frequently exceed 20 ppb in summer days (Fig. 1).
During spring and fall, contributions from inert tracers are 5 ppb higher
than contributions from active tracers in southern regions and less than
5 ppb elsewhere. In winter, when photochemistry is less active, the estimated
contributions from the inert and active tracers are similar. Such seasonal
variation is consistent across all three groups of vertical layers (Figs. S9–S11).
These results emphasize the critical role of O3 chemistry
and highlight the estimation bias inherent to the inert tracer approach.
Differences between inert and reactive BC O3 tracer contributions
to seasonally averaged MDA8 O3 (inert – reactive) summed over all boundary
height ranges.
O3 contributions by boundary height range
The largest BC contributions to seasonal average MDA8 O3 over the US
are from the MT with small contributions from the UTLS (Fig. 6). The
contributions from the MT are highest in spring, followed by summer, fall,
and winter. The attribution of the MT to spring maxima is over 40 ppb across
the western US, but less than 25 ppb in the eastern US. The contributions
from the LT are highest (more than 30 ppb) along the western boundary but
decrease sharply at the coastline as a result of dilution as the boundary
layer moves onshore along with higher O3 deposition velocities over
land. Dissipating contributions from the model boundaries with distance are
seen at all lateral sides because O3 deposits to the earth's surface
and is destroyed by chemical reactions in the atmosphere. The penetration of
LT BC O3 inland O3 peaks in winter, when chemistry and deposition
are least active. The UTLS BC tracers contribute only a few ppb, mostly over
the highest western terrain, and up to 6 ppb in summer when vertical
convection is most active.
Sensitivity to changing anthropogenic emissions (GLO and EAS scenarios)
Reducing emissions in East Asia by 20 % (EAS scenario) decreases average
O3 across the US in all seasons (Fig. 7, first-column panels). As expected,
decreases are highest in the west because the western US is closest to Asia
and has high terrain. The O3 decreases are small: below 1 ppb in spring
and below 0.5 ppb in other seasons. Decreases in O3 BC reactive tracers
(Fig. 7, second-column panels) are almost identical to modeled O3 decreases
but slightly smaller (e.g., generally within 0.1 ppb) because the reactive
tracers omit some chemical interactions.
Seasonal average MDA8 O3 contributions from boundary height ranges
using reactive BC O3 tracers.
We examine more closely the relationship between changes in O3 and
reactive tracers in the EAS scenario. In each surface grid cell, we regress
hourly O3 changes against reactive tracer concentration changes (summed
over boundary height ranges) to compute slope and r as demonstrated in the
two scatter plots for Denver in spring and summer. Slope and r values of 1
indicate that the O3 changes are explained entirely by the changes in
O3 BC reactive tracers. The delta total O3 and delta tracer
O3 relationship is near-linear at Denver with a slope of 0.87 and r
of 0.9. The 16 panels in Fig. 7 show the regression parameters for each grid
surface cell and match the scatter plots for Denver. The slope and
r (Fig. 7, third- and fourth-column panels) values have similar spatial
patterns in all seasons. In winter and fall the slope values are near 1 with
r of 0.8 to 1 across the US, suggesting strong influence of O3 transport
from Asia during these seasons. In spring, strong correlation (r = 0.8 to 1)
is seen in the western US, but areas in the eastern US have a slope lower
than 0.2 and r lower than 0.4, indicating that the O3 BC tracers can
explain only a fraction of the total O3 change. The lowest correlation
(r < 0.2) is in the summertime over the southeastern US in a region
where the EAS scenario produces almost no change in surface O3,
indicating that transport from Asia becomes unimportant. High correlation in
the western US in all seasons emphasizes the influence of O3 transport
from Asia in this region.
Reducing global emissions by 20 % (GLO scenario), including US emissions,
decreases summertime average O3 by up to 4 ppb (Fig. 8). The largest
reductions occur over the eastern US, where US emissions cause domestic
O3 production. O3 reductions in fall and winter are small,
generally lower than 1–2 ppb. Many NOx-rich areas (e.g., urban cores) show
O3 increases as a result of NOx emission reductions (i.e., NOx
disbenefit) in all seasons. The spatial pattern and magnitude of the changes
in BC O3 tracers differs from the changes in surface O3 (Fig. 8,
first- and second-column panels) except near the boundaries and in winter. The
correlation between changes in surface O3 and BC tracers is low
(|r| < 0.4) in all seasons except winter (Fig. 8, fourth-column panels). Overall, in the GLO scenario US surface O3 is more
sensitive to domestic emission reductions than changes in BCs.
We use summer average MDA O3 to show how the two emission scenarios
change BC contributions for the 22 major cities (Fig. 9). The EAS scenario
reduces BC contribution in all cities with reductions range from 0.06 ppb
(Houston) to 0.3 ppb (Boise). Reductions are larger in the western US and
more northern latitude in the eastern US (e.g., larger reduction in Columbus
than Atlanta). These reductions result mostly from smaller MT and LT BC
contributions because the EAS scenario scaled back the contribution of each
height range about equally. The EAS scenario changed the UTLS BC
contributions by less than 0.01 ppb. The GLO scenario produced larger
reductions than the EAS scenario and they range from 0.4 ppb (Boston) to
1.2 ppb (Los Angeles). These reductions are mainly driven by the MT BCs in all
of the cities except Dallas and Houston. Higher influence from the LT in the
GLO scenario than the EAS scenario for most cities is consistent with the
GLO scenario reducing emissions just outside the CAMx domain, whereas in the
EAS scenario the emission reductions occur only in East Asia.
Scatter plots on the top show delta daily average O3 (y axis)
and reactive tracer BC O3 contribution (x axis) for Denver in spring
and summer for 20 % reduction in East Asia emissions (EAS scenario). The
16 panels summarize the same information showing seasonal delta total
O3 (c) and reactive tracer BC O3 contribution (d)
for each grid surface. The correlation (r) and slope of a linear regression
of (d) against column are shown in columns (e) and (f), respectively.
Changes to seasonal average O3 (a) and reactive tracer
BC O3 contribution (b) for 20 % reduction of global emissions
(GLO scenario). The correlation (r) and slope of a linear regression of (b)
against column are shown in (c) and (d), respectively.
Changes in BC contribution (ppb) to summer average MDA8 O3 by
height range for the EAS (a) and GLO (b) scenarios from the base case.
Differences in seasonally averaged MDA8 contributions from inert BC
O3 tracers in CAMx and CMAQ (CAMx–CMAQ).
Comparing BC O3 contributions in two regional models
The AQMEII activity permits comparison of BC O3 contributions in
different regional models. US EPA applied the CMAQ model over the NA domain
with the same model input data as we used with CAMx except for biogenic
emissions. The WRF-CMAQ system was configured using WRFv3.4 and CMAQv5.0.2
(Appel et al., 2013; see also Foley et al., 2010, and Byun and Schere, 2006).
Options in CMAQ include wet deposition as described in Byun and Schere (2006)
and dry deposition as described in Pleim and Ran (2011). Additional
details on the CMAQ configuration used in these simulations can be found in
Solazzo et al. (2017). Figure 10 compares BC O3 contributions to
seasonal average MDA8 O3 estimated by CAMx and CMAQ using inert BC
O3 tracers (CMAQ was not run with reactive tracers). Differences
between the CMAQ and CAMx inert tracer impacts are smaller than the
differences between inert and reactive tracers in CAMx, which exceed 10 ppb
(Fig. 5), but they are notable, in a range of 4–8 ppb in summer and 2–6 ppb
in spring with CAMx being higher. Factors contributing to these differences
may include fewer vertical layers in CAMx (26, compared to 35 in CMAQ),
allowing greater transport of UTLS O3 to ground level (Emery et al.,
2012), omission of wet scavenging for the CAMx inert tracers, treatment of
deep convective transport in CMAQ, or differences in model treatments of
O3 dry deposition. Liu et al. (2017) performed multi-model
process comparisons with four AQMEII models and draw similar conclusions
regarding factors that can contribute to differences in tracer impacts.
Conclusions
The overall MDA8 O3 performance is within evaluation goals. We do not
see evidence of systematic problems with the model setup, although
performance at individual monitor does vary, and the potential for hidden
biases and errors always exists. Future studies could benefit from refining
model assumptions that may be important at specific sites. For example,
overstated MBL O3 at Trinidad Head is partly attributable to the lack
of O3 destruction by oceanic halogen chemistry. Other possible reasons
include insufficient O3 deposition to the ocean, too strong vertical
mixing in the MBL, or a combination of factors. The model tendency to
overestimate O3 in spring may suggest overstated BC contributions as
seen at the Denver site. Perfecting model performance at individual sites across
the US is not pursued in the current study. If accuracy in estimating BC
contributions is critical, such as in demonstrating attainment of O3
standards, model performance and BC contributions cannot be overlooked, especially on high-O3
days.
Inert BC O3 tracers consistently estimate higher BC contributions to
seasonal average MDA8 O3 across the US than reactive tracers,
particularly in summer. The inherent bias in the inert tracer approach
(i.e., omitting chemical destruction) can exceed 10 ppb in seasonally
averaged MDA8 O3, which is substantial in comparison to the 70 ppb level
of the O3 NAAQS. This information is critical for interpreting results
obtained with inert tracers in AQMEII-3 and other studies.
Comparing inert tracers in two regional models that used substantially the
same input data found differences in MDA8 O3 that were generally within
5 ppb, smaller than the differences between inert and reactive tracers run
in a single model (CAMx), but nevertheless those inert model differences
were notable. Potential causes include differing numbers of model vertical
layers (influencing movement of UTLS O3 to ground level) and
differences in model treatments of deposition. This exercise emphasizes that
source contribution analyses of BC O3 (or other non-inert pollutants)
using the inert tracer approach should only be interpreted qualitatively,
especially during the spring and summer period. Making tracers reactive is a
simple improvement that is very important to this type of analysis. Future
studies should consider adopting the reactive tracer approach.
Contributions from O3 BCs in three height ranges (LT, MT and UTLS)
differ spatially and temporally. The LT BC tracers do not penetrate very far
inland, with contributions to MDA8 O3 up to 20 ppb in coastal states.
The largest contributions to MDA are from the MT BCs with springtime maxima
exceeding 40 ppb in the high terrain of the western US. The high
contribution of BC O3 to ground level O3 in portions of the
western US presents a significant challenge to air quality management
approaches based solely on local emission reductions. Nonetheless, model
comparison with observations suggests that estimated high BC contributions in
the Intermountain West could be overstated and that the bias inherited in
O3 BCs can affect model performance. Replicating the highest end of
observed O3 distribution is particularly challenging. We encourage
making use of multi-day metrics (such as Top 30) as an alternative to a
single-day metric (e.g., H4MDA8) when examining contributions from
international transport.
Reducing emissions in East Asia (EAS scenario) revealed a near-linear
relationship between changes in BC O3 and changes in surface O3 in
the western US in all seasons and across the US in fall and winter with a
near 1 : 1 slope. However, the surface O3 decreases are small: below
1 ppb in spring and below 0.5 ppb in other seasons. These reductions result
mostly from smaller MT and LT BC contributions because the EAS scenario
scaled back the contribution from each height range about equally. In the
GLO scenario US surface O3 is more sensitive to domestic emission
reductions than changes in the BCs. Our 2010 EAS contribution results are
slightly higher than the estimates of 0.35–0.45 ppb from a multi-model
experiment that also simulated the EAS scenario but for the year 2001
(Reidmiller et al., 2009). This is expected as East Asia emissions have
increased over the last decade. Assuming a linear relationship, our study
suggests an EAS total contribution of 2.5 ppb in certain seasons based on
0.5 ppb O3 reduction with 20 % emission decrease. It is
difficult to quantify how the model biases affect the O3 response to
emission perturbations because the sources of biases are unknown.