Introduction
Ozone (O3) is a well known and important product of photochemical
processes in the troposphere involving nitric oxide (NO), nitrogen dioxide
(NO2), and volatile organic compounds (VOCs). Ozone is of broad
interest for its adverse effects on humans and ecosystems, as reflected by
regulation through the US Clean Air Act (e.g., U.S. EPA, 2014, 2015a).
Regulatory actions address extreme O3 mixing ratios: the US
National Ambient Air Quality Standard (NAAQS), currently 70 ppbv, is
applicable to the annual fourth-highest daily 8 h maxima averaged over
3-year periods (U.S. EPA, 2015b, c). By the early 1990s, US emission
control efforts began to focus on nitrogen oxides
(NOx = NO + NO2) in addition to VOCs (NRC,
1991). O3 management has generally relied on precursor reduction
requirements estimated from models that integrate descriptions of nonlinear
chemical and atmospheric processes (e.g., Seigneur and Dennis, 2011), and
guidance has also derived from so-called “observation-based” models linking
O3 and its precursors based on chemical reactions that are believed
to drive ambient mixing ratios (e.g., NARSTO, 2000; Schere and Hidy, 2000).
Most of the work developing an observational basis for O3-precursor
chemistry derives from field campaigns, sometimes focusing on urban
conditions. Short-term data are available from aircraft flights, for example,
or summer field measurements made at a variety of locations. Such studies
usually are limited to a month or two of intense sampling. One example in the
southern US is the 1990 ROSE experiment at Kinterbish, a rural, forested
state park in western Alabama (Frost et al., 1998). This summer study of
rural O3 at low anthropogenic VOC and low NOx mixing
ratios provided important insights into rural O3 formation (Trainer
et al., 2000). Other examples of short-term campaigns across the US and
elsewhere are reviewed in Solomon et al. (2000). More recent field studies
include New England in 2002 (e.g., Griffin et al., 2004; Kleinman et al.,
2007), Texas in 2006 (e.g., Neuman et al., 2009), the
mid-Atlantic region in 2011 (He et al., 2013), California in 2010 (Ryerson et
al., 2013), Colorado in 2012 and 2014 (e.g., McDuffie et al., 2016), and the
southeastern US in 2013 (e.g., Neuman et al., 2016; Warneke et al., 2016).
These campaigns and accompanying analyses of O3 production and
accumulation typically address summer, which historically has the strongest
photochemical activity. However, strong photochemical O3 production
can occur under special circumstances in winter (e.g., Schnell et al., 2009).
Accounting for an O3 background is important. O3 background
is associated with biogenic influence, large-scale transport, or the
potential influence of the upper atmosphere (e.g., stratospheric intrusions,
especially during spring; Lin et al., 2012; Langford et al., 2015).
The nature and magnitude of background O3 remain an active area of
research in the US and Europe (Naja et al., 2003; Solberg et al., 2005;
Ordóñez et al., 2007; Cristofanelli and Bonasoni, 2009; Arif and
Abdullah, 2011; Zhang et al., 2011; Wilson et al., 2012). Hidy and
Blanchard (2015) discuss definitions of continental and regional background
O3. For this study, we adopt a definition of “background” that
includes both the non-anthropogenic component and the southeastern regional
component (Sect. 4.4.1).
Field studies have provided observational evidence of nonlinearity in
O3–NOz relationships (e.g., Trainer et al., 1993,
1995; Kleinman et al., 1994; Hirsch et al., 1996; Frost et al., 1998;
Kasibhatla et al., 1998; Nunnermacker et al., 1998; St. John et al., 1998;
Sillman et al., 1998; Zaveri et al., 2003; Griffin et al., 2004; Travis et
al., 2016). Long-term, post-1990s data are widely available for O3
and NO2 but detailed observations of total oxidized nitrogen
(NOy) and VOC, and especially their component species, are
typically lacking (e.g., Hidy and Blanchard, 2015). One of the longest
records of urban and suburban data, comprising a series of short-term
campaigns as well as continuous measurements, is from southern California.
This region exemplifies a photochemically active urban regime. An analysis of
multi-decadal (since the 1960s) data by Pollack et al. (2013) reveals how
changes in atmospheric chemical reactions have contributed to the observed
reductions of O3 in southern California since 1973. Long-term (more
than one decade) measurements characterizing O3 and
NOy relationships in both urban and rural conditions are
less common.
The photochemical regime in the southeast represents humid subtropical
conditions with urban emissions yielding elevated O3 levels
superimposed on a general regional background (Chameides and Cowling, 1995).
The EPA O3 and deposition data provide a regional basis for
characterizing trends since the early 1980s (U.S. EPA, 2016a, b). In
addition, the Southeastern Aerosol Research and Characterization (SEARCH)
project (Hansen et al., 2003; Hidy et al., 2014) provides measurements that
can be used to investigate changes in O3 production resulting from
changes in anthropogenic emissions in the southeastern US. The SEARCH network
of eight sites began with the Southeastern Oxidant Study (SOS) (Chameides and
Cowling, 1995; Meagher et al., 1998) rural locations, which were near
(1) Centreville, AL, ∼ 85 km southwest of Birmingham; (2) at
Yorkville, GA, ∼ 60 km northwest of Atlanta, GA; and (3) at Oak Grove,
MS, ∼ 40 km southeast of Hattiesburg, MS, and 75 km north of
Gulfport, MS, on private land within the confines of the De Soto National
Forest (Hansen et al., 2003). Measurements of some gas-phase species began at
these rural sites in 1992, thus providing a rural data record of over
20 years. Beginning in 1999, SEARCH added five sites in metropolitan Atlanta,
GA; Birmingham, AL; Pensacola, FL; and Gulfport, MS.
Our goal for this study is to extend earlier analyses of the photochemical
response of O3 to precursors through 2014, emphasizing relationships
between O3 and NOy. We first summarize relevant
O3 photochemistry to provide a context for the observational
analysis. We then describe trends in emissions and ambient pollutant
concentrations, and discuss O3, NOz, and
HNO3 observations at the SEARCH sites. The trends in O3
mixing ratio, NOx precursor emissions, and ambient nitrogen oxide mixing
ratios offer important insight into future changes in O3 and NOy.
Blanchard et al. (2014) previously explained the majority (66–80 %) of
the day-to-day variations in daily peak 8 h average O3 at SEARCH
sites during March–October of 2002–2011 using meteorological variables
coupled with ambient measurements of O3 precursors (NO, NO2;
limited measurements of VOCs) and NOx photochemical reaction
products (NOz) and a statistical model. The previous
analyses are extended here for data through 2014 to help understand ongoing
and potential future O3 changes in relation to changes in ambient
NOz and HNO3 mixing ratios in the southeastern US.
Results are discussed in relation to modeling predictions by Reynolds et
al. (2004) and others.
Ozone–nitrogen oxide chemistry
Key atmospheric reactions linking O3 with NOx
Net tropospheric O3 accumulation occurs when sunlight acts on VOC and
NOx emissions and the O3 production rate exceeds
O3 loss (Trainer et al., 2000). Tropospheric O3 mixing ratios
are affected by solar intensity, chemical formation and loss (e.g.,
deposition) rates of O3, the rate of dispersion of O3 and its
precursors, meteorological factors, and vertical entrainment and transport of
plumes. NO2 forms rapidly by reaction of NO with O3 and
photolysis of NO2 produces O3, yielding steady-state mixing
ratios of NO, NO2, and O3 in the absence of other species as
expressed by the photostationary state, or Leighton relationship (Seinfeld,
1986).
In the troposphere, NO2 also forms by reaction of NO with peroxy
(HO2) and alkyl peroxy (RO2) free radical species, which
derive in turn from the reaction of VOCs with hydroxyl (HO), HO2,
RO2, and alkyl radicals (Seinfeld, 1986). Radical production from
VOCs creates a pathway for conversion of NO to NO2 that does not
consume O3 (Atkinson, 2000), which then leads to higher O3
mixing ratios.
O3 accumulation is typically associated with high solar radiation
intensity and temperatures favoring atmospheric reactions, lower wind speeds,
and high anthropogenic emission rates (NARSTO, 2000). O3 accumulation
requires NO mixing ratios exceeding approximately 10 to 30 pptv (Atkinson,
2000; Logan, 1985), along with the presence of HO2 and
RO2 radicals that react with NO to form NO2. The former
conditions are normally met in urban air; NOx mixing ratios
are much lower under typical conditions in rural southeastern areas, but
still well above 30 pptv (e.g., Hudman et al., 2007; Travis et al., 2016).
Under these conditions, the O3 photochemical production rate is
proportional to the ambient NO multiplied by the sum of HO2 and
RO2 radical mixing ratios, where the latter are weighted by their
rates of reaction with NO (Trainer et al., 2000). Field studies show that
observed rates of rural O3 production are proportional to the rate of
oxidation of NOx. Where VOCs are present for radical
production and NOx is rate limiting (Trainer et al., 2000),
regional O3 production can be expressed in terms of the derivative
d[O3]/d[NOx], denoted as the O3
production efficiency (OPE) (Liu et al., 1987). OPE is understood as the
number of molecules of O3 formed per molecule of NOx
oxidized and OPE increases as NOx mixing ratios decrease
(Liu et al., 1987; Trainer et al., 2000). OPE reflects the mean number of
NO–NO2 cycles occurring, in which each photolysis of one NO2
molecule generates one O3 molecule until that NO2 molecule is
oxidized to nitric acid (HNO3) or to other species such as
peroxyacetyl nitrate (PAN). NOx reaction products, including
HNO3 and PAN, comprise NOz. For chemical reactions,
the quantity d[O3]/d[NOz] is equivalent
to d[O3]/d[NOx], but with opposite sign,
and has therefore been used to estimate OPE; limitations due to confounding
influences of emissions, transport, and deposition are discussed in Sect. 4.3
and 4.4.
Empirically, the slope of a linear fit of afternoon O3 (or
Ox = O3 + NO2) versus
NOz has been used to estimate OPE (e.g., Trainer et al.,
1993; Pollack et al., 2013). This estimate is subject to certain limitations
because it does not explicitly account for (1) day-to-day variability in
“old” (baseline or regional background) O3 mixing ratios,
(2) mixing of air masses having different emission histories, (3) rapid loss
of HNO3 (primarily through dry deposition, but also through
gas-to-particle conversion) (Trainer et al., 2000), and (4) regeneration of
NO2 from PAN and certain other species. Because PAN regenerates
NO2, it can serve as a reservoir rather than a true NO2 sink
(Singh and Hanst, 1981; Singh, 1987). In contrast, HNO3 largely
terminates the cycling between NO and NO2. Therefore, the relative
yields of PAN and HNO3 are of importance. Despite such limitations in
using measurements to quantify OPE, data from field studies have been used
since the 1990s to determine upper bounds for OPE and the results have
continued to appear in the literature as an indicator of relevance to
O3 chemistry (e.g., Berkowitz et al., 2004; Neuman et al., 2009; Kim
et al., 2016). Investigators caution that field measurements reveal the net
of production and loss, which potentially overestimates actual OPE by factors
of 3 to 6 due to rapid chemical and deposition losses of HNO3 and
other NOz species (e.g., Trainer et al., 2000). Additional
discussion is found in Sect. 4.4.
In southern California, changes in the relative proportions of
NOx-oxidation products have occurred and are thought to be
instrumental in driving the rapid rates of O3 decline in that area
(Pollack et al., 2013). These results indicate that measurements of
HNO3 or PAN are needed to identify important changes in chemical
pathways.
National O3 response to emission reductions
Between 1980 and 2013, the national average of the annual fourth-highest peak
daily 8 h O3 mixing ratios, a metric relevant to the US O3
NAAQS, declined by 33 % (U.S. EPA, 2015d) as national VOC and
NOx emissions decreased by 53 and 52 %, respectively
(U.S. EPA, 2015e). Across the US and on multiple spatial scales from
continental to urban, annual fourth-highest daily peak 8 h O3 mixing
ratios between 1980 and 2013 show a statistically significant
(p < 0.05) linear fit to either annual average or to 98th percentile
daily maximum hourly NO2 mixing ratios; regression slopes are less
than 1 : 1 and intercepts are in the range of 30 to 50 ppbv O3
(Hidy and Blanchard, 2015). Proportionalities between O3 and
NO2 that are less than 1 : 1 are expected, and the observed
intercept terms are approximately consistent with typical O3 mixing
ratios of ∼ 20–50 ppbv observed at remote monitoring sites (Oltmans
et al., 2008, 2013; U.S. EPA, 2012; Fiore et al., 2014; Lefohn et al., 2010,
2014; Cooper et al., 2012, 2014).
Although nonlinearity of O3 production and accumulation with respect
to ambient VOC and NOx is well established (Lin et al.,
1988), a tendency toward linearity is expected at sufficiently low
NOx mixing ratios. As an example, the O3
photochemical production rate during June 1990 at Kinterbish, AL, was
approximately linear over a range of ambient NOx from 0.1 to
2 ppbv (Trainer et al., 2000). Observed O3 extrema can also exhibit
an apparent linear or near-linear response to ambient NOx
mixing ratios if the extrema consistently fall within the lower-right
quadrant (NOx-sensitive regime) of an
O3–VOC–NOx diagram, a concise graphical
representation first established empirically from southern California data
and later generated using the Empirical Kinetic Modeling Approach (EKMA)
(illustrated in Hidy and Blanchard, 2015). The
O3–VOC–NOx diagram has been adopted by many
investigators for displaying the output of box models (e.g., Fujita et al.,
2003, 2015) and grid-based photochemical models (e.g., Reynolds et al., 2003,
2004).
Southern California historically has exhibited the highest peak O3
mixing ratios in the US since the 1960s. Because of high ambient O3
and precursor mixing ratios there and the complexity of the relationships of
O3 with NOx and VOC, some investigators have
described southern California O3 and precursor trends in terms of
percentage changes. For example, Pollack et al. (2013) report that peak 8 h
O3 mixing ratios in southern California declined exponentially over
time at a rate of 2.8 % per year between 1973 and 2010, thus decreasing
O3 levels by approximately a factor of 3. This rate of O3
decline exceeds rates occurring in other metropolitan areas (Hidy and
Blanchard, 2015). O3 extrema in southern California decreased along
with declining mixing ratios of ambient VOCs and NOx
(7.3 % yr-1 and 2.6 % yr-1, respectively, 1960–2010) and
declining ratios of VOC / NOx (4.8 % yr-1)
(Pollack et al., 2013). The rates of atmospheric oxidation of
NOx increased over time and changes in NOx
oxidation reactions increasingly favored production of HNO3, a
NOx reaction product associated with radical termination and
quenching of the O3 formation cycle (Pollack et al., 2013). To our
knowledge, changes in the relative proportions of atmospheric reaction
products accounting for rapid rates of O3 reduction have not been
reported for locations other than southern California.
Methods
Emissions and ambient air quality measurements
Air quality monitoring data were obtained from the EPA Air Quality System
(AQS) data archives for all sites in Georgia, Alabama, and Mississippi (U.S.
EPA, 2016a). Daily measurement values (i.e., peak daily 8 h O3
mixing ratio) as well as annual summary statistics (e.g., maxima, annual
averages) were acquired. We obtained deposition data from the two EPA Clean
Air Status and Trends Network (CASTNET) monitoring sites located within the
study region: Sand Mountain, AL (125 km east-northeast of the SEARCH site at
Centreville), and Georgia Station, GA (102 km SE of the SEARCH site at
Yorkville) (U.S. EPA, 2016b).
Annual, state-level emission trends data were obtained from the U.S. EPA (2016c,
d), Xing et al. (2013), and
Hidy et al. (2014). The comparability of inventories
is discussed in the Supplement (Fig. S1).
Because the EPA trend inventory utilized different methods for estimating
mobile-source emissions prior to 2002 compared with 2002 and later years, we
combined EPA trend estimates for 2002–2016 with the 1996–2001 emission
estimates of Hidy et al. (2014), which are consistent with more recent EPA
methods (see Supplement).
Hourly measurements of gases (NO, NO2, NOy,
HNO3, and O3) were obtained from SEARCH public archives
(ARA, 2017). All parameters measured at the sites are calibrated and audited
to conventional reference standards, as described in ARA (2015). Network
operations, sampling, and measurement methods are documented in Hansen et
al. (2003, 2006); see also Table S1 in the Supplement. The network consisted
of eight extensively instrumented monitoring sites located in the
southeastern US along the Gulf of Mexico and inland (Fig. S2): Pensacola,
Florida (PNS), and Gulfport, Mississippi (GFP), urban coastal sites
(∼ 5 and 1.5 km from the shoreline, respectively); Pensacola –
outlying (aircraft) landing field (OLF) and Oak Grove, Mississippi (OAK),
non-urban coastal sites near the Gulf (∼ 20 and 80 km inland,
respectively); Atlanta, Georgia – Jefferson Street (JST) and North
Birmingham, Alabama (BHM), urban inland sites; and Yorkville, Georgia (YRK),
and Centreville, Alabama (CTR), non-urban inland sites. PNS, OAK, and GFP
were closed at the end of 2009, 2010, and 2012, respectively. SEARCH site
locations are described in detail, including discussion of possible emission
influences, in Hansen et al. (2003) and Hidy et al. (2014). SEARCH VOC data
are available for JST as daily data from 1999 through 2008, and U.S. EPA VOC
measurements are available for YRK as summer hourly data and as 24 h samples
collected every sixth day throughout the year (Blanchard et al., 2010a). EPA
VOC samples are also available for three other sites in the Atlanta area;
only one of these additional sites reported data through 2014.
SEARCH meteorological parameters and gases are sampled at a height of 10 m,
characteristic of lower-tropospheric mixing ratios near the surface (Hansen et al., 2003, 2006; Edgerton et al.,
2007; Saylor et al., 2010). Gas and meteorological measurements commenced in
1992 at the rural sites of CTR, OAK, and YRK. The measurements at rural
SEARCH sites included O3, NO, and NOy beginning in
1992, and NO2 and HNO3 measurements began in 1996. Consistent
measurement methods have been utilized for all gases except NO2.
NO2 measurements commenced network-wide in 2002, and three
NO2 measurement methods have been employed during the network
operations (Table S3). All three methods are NO2-specific, differing
primarily in the light source used for photolysis of NO2. The
NO2 data exhibit consistency with NO and NOy
measurements but with some variations occurring during specific years (e.g.,
2001 and 2002, Fig. S3). Because changes in NO2 measurement methods
could affect the computed NOz
(NOy–NO–NO2), we repeat some data analyses using
HNO3 in place of NOz. As noted, HNO3 data
also provide useful insight into NO2 termination reactions.
HNO3 measurements are the difference between NOy and
denuded NOy (Table S1; Hansen et al., 2006). The SEARCH
measurements of NOy were designed to capture particulate
nitrate and organic nitrates, as well as NO, NO2, HNO3, and
other oxidized nitrogen species. The NOy sampler derives
from the instrument identified in Williams et al. (1998) as
Environmental Science and Engineering (ESE), which was one of
five instruments for which measurements of NOy reproduced
the sum of separately measured NOy species. Additional
testing in 2013 showed that SEARCH NOy measurements agreed
with the sum of measured mixing ratios of NO, NO2, HNO3,
particulate nitrate, alkyl nitrates, and peroxy–alkyl nitrates (Hidy et al.,
2014).
Trace gas calibrations were done daily for O3 and every third day for
other gases. Reported detection limits (Table S1) are 0.05–0.1 ppbv for
oxidized nitrogen species and 1 ppbv for O3 (Hansen et al., 2003,
2006). NO2 measurement uncertainties are estimated as
∼ 30 % prior to 2002 and ∼ 10 % after 2002 (Hansen et
al., 2006). Measurement uncertainties are estimated to be 10 % or less
for other oxidized nitrogen species and 5 % or less for ozone (2σ
in all cases). Propagation of errors indicates corresponding 2σ
measurement uncertainties averaging 0.5 ppbv for mid-afternoon
NOz (< 0.1 ppbv for NOz < 1 ppbv)
and 0.16 for the ratio NOz / NOy.
Data analysis
Multiple methods were employed to characterize the variability of ambient
O3 and NOy mixing ratios. Analyses of seasonal
variability used data from all months of each year. Diurnal hourly average
mixing ratios were computed by year to characterize patterns of temporal
change and to identify hours associated with O3 maxima. Observed
slopes of regressions of O3 versus NOz were computed
as previously done in measurement studies using afternoon O3 and
NOz data (Trainer et al., 1993, 1995; Kleinman et al., 1994;
Hirsch et al., 1996; Kasibhatla et al., 1998; Nunnermacker et al., 1998; St.
John et al., 1998; Sillman et al., 1998; Zaveri et al., 2003; Griffin et al.,
2004; Travis et al., 2016). Because past studies have examined O3
formation in photochemically aged air (i.e., at locations distant from fresh
emissions, where atmospheric reactions have acted on emissions from earlier
times) during summers (e.g., Trainer et al., 1993), our analyses focus on the
months of June and July to select weeks nearest maximum solar radiation
(∼ -20, +40 days). Additional analyses were carried out for other
months to facilitate comparisons across seasons. As for earlier studies, the
calculations are based on afternoon times, using hourly values starting at
14:00 local standard time to represent the daily peak O3 after
morning production and before mixing ratios decline with decreasing
photochemical reaction in later afternoon. In addition to characterizing
O3 / NOz and its change with time, corresponding
supporting analyses are presented for O3 / HNO3. As a
supplemental analysis, rates of maximum diurnal increase of O3 and
HNO3 during late morning and early afternoon were computed for
comparison of ΔO3 with ΔHNO3.
Results and discussion
Trends
Hidy et al. (2014) report a 63 % reduction of NOx
emissions in the southeastern US between 1996 and 2014. The largest
NOx emission changes in the southeast occurred between 2007
and 2009 due to reductions of emissions from electric generating units (EGUs)
and from diesel engine vehicles, and they were accompanied by more gradual
year-to-year reductions of gasoline-engine mobile-source NOx
emissions (de Gouw et al., 2014; Hidy et al., 2014). NOx
emission reductions led to approximately proportional responses of mean
ambient NOy and NOz mixing ratios at SEARCH
sites (Hidy et al., 2014).
The EPA CASTNET data show wet and dry nitrate deposition since the late 1990s
declining at rates of ∼ 5 % per year (-0.045 ± 0.005 and
-0.056 ± 0.005 yr-1), nearly identical to NOx
emission changes of -0.046 ± 0.001 and
-0.051 ± 0.003 yr-1 (Fig. 1). Total (wet plus dry) nitrate
deposition fluxes decreased linearly in proportion to reductions of
NOx emissions in Alabama and Georgia (Fig. 1). Linear
regression slopes indicate that the annual nitrate deposition fluxes at the
Georgia and Alabama CASTNET sites correspond to 30 % of Georgia emissions
and 36 % of Alabama emissions on an annual and statewide basis (Fig. 1).
Emissions are not spatially homogeneous and deposition losses likely vary
with distance from emission sources. The two sites are situated differently
in relation to metropolitan areas, possibly affecting deposition fluxes; Sand
Mountain (SND) is northeast of Birmingham and Georgia Station (GAS) is south
of Atlanta. The linearity and statistical significance of the regressions
indicate that the fraction of NOx emissions lost to
deposition has not changed over time (ratios of annual
deposition to state emissions varied without trend from 0.23–0.34 at GAS and
0.30–0.45 at SND). Mean annual SEARCH NOy mixing ratios at
rural CTR and YRK declined at ∼ 5–7 % yr-1 (Fig. S4). SEARCH
and EPA CASTNET sites exhibit downward trends in mean annual HNO3
concentrations of ∼ 9–11 and ∼ 6–7 % yr-1,
respectively (Fig. S4). Ambient NOy and HNO3 trends
are not statistically different from state-level NOx
emission trends.
Comparison of nitrate deposition (wet plus dry) to
NOx emission densities in Georgia and Alabama
as (a) temporal trends and (b) regression of deposition
against emissions (with same color coding in both panels). Nitrate deposition
and NOx emission densities are expressed as
kg ha-1 yr-1. NOx emissions are from all source
sectors (see Supplement). Panel (a) shows natural logarithms vs.
year and indicates that emissions and deposition trended downward at the same
rates. Panel (b) slopes are statistically significant
(p < 0.0001) and intercepts are not (p > 0.1).
Annual fourth-highest daily peak 8 h O3 mixing ratios at compliance
monitoring sites in Georgia, Alabama, and Mississippi exhibit
statistically significant (p < 0.0001) linear correlations with annual
NOx emissions in those states between 1996 and 2015
(Fig. 2), qualitatively consistent with past work indicating that high
O3 would respond to reductions of NOx emissions
(Chameides and Cowling, 1995; Jacob et al., 1995; Kasibhatla et al., 1998).
Intersite differences in the annual fourth-highest daily peak 8 h O3
mixing ratios have decreased (Fig. 2), consistent with an analysis of data
from a larger number of US and European locations (Paoletti et al., 2014).
The annual fourth-highest daily peak 8 h O3 mixing ratios are declining
toward nonzero values, as indicated by the statistically significant
(p < 0.0001) intercepts of ∼ 45–50 ppbv (Fig. 2). SEARCH data
are used to characterize the southeastern O3 response to emission
changes in greater detail. Between 1999 and 2014, the highest peak daily 8 h
O3 mixing ratios occurring each month (monthly O3 maxima)
declined at all SEARCH sites at statistically significant (p < 0.01)
rates averaging ∼ 1–1.5 ppbv yr-1 (Fig. 3). These declines are
comparable to the trend in the 95th percentile summer peak daily 8 h
O3 mixing ratios in the southeastern US of ∼ -0.8 to
-1.8 ppbv yr-1 reported by Lin et al. (2017), with downward trends
occurring in other seasons as well. The observed SEARCH O3 trends are
also consistent with other analyses of North American observations (e.g.,
Chan, 2009; Lefohn et al., 2010; Paoletti, 2014; Simon et al., 2015) and with
the trends occurring at EPA monitors in the southeast (Fig. 2). Both EPA
(Fig. 2) and SEARCH (Fig. 3) data suggest that O3 mixing ratios
increased during the 1990s, then began declining. This result is consistent
with modeling by Reynolds et al. (2004), which predicted an initially slow
response of Atlanta-area O3 to emission reductions between 1996 and
2000, followed by increasing sensitivity to reductions of
NOx emissions. The observed O3 decreases exceed
those predicted by Reynolds et al. (2004) because actual NOx
emission reductions (∼ 60 % between 1996 and 2014) exceeded the
projected emission reductions (∼ 40 % by 2010 and ∼ 55 %
by 2020) that were anticipated based on known and anticipated emission
control rules at the time of the modeling study. The SEARCH trends are
compared with emission changes in the southeast and with emission and
O3 trends in southern California, in Table S2.
Comparison of annual fourth-highest daily peak 8 h O3 to
NOx emissions in Georgia and Alabama (a) trends
(±90th and 10th percentile sites) and (b) regressions
(high = 90th percentile site, median, and low = 10th percentile site
annual fourth-highest daily peak 8 h O3). NOx
emissions are from all source sectors (see Supplement). O3 data
include all EPA AQS monitors in Georgia and Alabama for each year having at
least 75 % data completeness (mean = 55 monitors, low of 32–36 in
1990–1993). Slopes and intercepts are statistically significant
(p < 0.0001).
More complete understanding of regional O3 trends requires
consideration of both regional emission changes and possible changes in
background O3. Multiple definitions of the term “background
O3” may be found in the literature, including global background,
continental background, non-anthropogenic background, and regional
background, among others. For the O3 trends shown in Figs. 2 and 3,
the most relevant consideration is the amount of O3 transported into
the study domain across upwind boundaries (denoted here as regional
background or transported O3). The percentage reductions of
O3 are larger if transported O3 can be estimated and
subtracted from observed O3 mixing ratios, and this adjustment
potentially provides a better assessment of the effects of regional emission
reductions on the fraction of O3 that is manageable by means of local
and regional emission control measures. For example, Parrish et al. (2017a)
report that the O3 enhancement above background in southern
California decreased by 4.5 % yr-1, which is larger than the
unadjusted O3 decline of 2.8 % yr-1 given by Pollack et
al. (2013). Similarly, rates of decline in southeastern US O3 are
larger if regional background O3 is considered (Table S2).
Monthly maxima of daily peak 8 h average O3 mixing ratios.
All monthly maxima are determined from 24 or more days with 18 or more
sampling hours per day. PNS and GFP (not shown) exhibit trends of
-1.64 ± 0.45 and -0.60 ± 0.32 ppbv yr-1, respectively.
Trends are statistically significant (p < 0.01) at CTR, JST, OAK, OLF,
PNS, and YRK.
Monthly means of daily peak 8 h average O3 mixing ratios.
All monthly means are determined from 24 or more days with 18 or more
sampling hours per day. Standard errors of the means average 2 (range
0.8–5) ppbv.
Defining and estimating regional background (or transported) O3 are
each challenging. We interpret the intercepts in Fig. 2 as indicators of mean
O3 levels that would occur on days with weather conducive to high
O3 in the absence of NOx emissions from AL and GA
sources, i.e., as estimators of O3 transported into the region from
outside the study domain (as discussed subsequently, multi-day carryover of
local and regional emissions during stagnation events could also affect
intercepts and slopes). Days with weather that is not conducive to high
O3 likely have different levels of transported O3. The
statistically significant slopes in Fig. 2 indicate O3 enhancements
that are attributable to AL–GA emissions, except as noted next, and a
comparison of the O3 decline to intercept-corrected O3 would
then reveal the proportionality between AL–GA emissions and AL–GA O3
enhancements over O3 originating outside the study domain (i.e., in
excess of regional background O3). Although the
∼ 30–35 % O3 declines are less than proportional to the
∼ 60 % decrease in NOx emissions, the decline in
the median O3 is ∼ 60 % if the 50 ppbv intercept shown in
Fig. 2 is subtracted from the O3 mixing ratios.
Statistical distributions of mean monthly species mixing ratios (all
SEARCH sites, 1992–2014). Distributions indicate the 10th, 25th, 50th, 75th,
and 90th percentiles of the monthly averages.
If the amount of O3 that has been transported from upwind regions has
been changing over time, e.g., declining as NOx emissions
and ambient O3 decline in adjacent regions, the slopes shown in
Fig. 2 would reflect changes in both the O3 that originated upwind
and in the O3 enhancements attributable to AL–GA emissions,
confounding attribution. Related studies do not provide consistent evidence
for a trend, either upward or downward, in regional background O3 in
the southeastern US. For example, baseline O3 concentrations in air
flowing into Texas from the Gulf of Mexico during May through October did not
change significantly between 1998 and 2012 (Berlin et al., 2013). Mean
regional background O3 mixing ratios were 48 to 59 ppbv in the
Houston, TX, area on days with O3 levels exceeding the NAAQS, which
includes O3 contributions from transport to the area from other
regions of the US (Berlin et al., 2013). Observed trends in the 5th
percentile O3 have previously been used as indicators of changes in
either regional or continental background O3 (e.g., Wilson et al.,
2012). The 5th percentile peak daily 8 h O3 mixing ratios decreased
during summer at rural sites throughout the southeastern US between 1988 and
2014 (Lin et al., 2017). By this measure, regional background O3
levels did not increase in the southeastern US during our study period.
Large-scale transport affecting O3 in the boundary layer and at the
surface is a function of altitude. For example, during June 2013,
anthropogenic emissions and long-range transport (long-range
tropospheric + stratospheric) O3 each accounted for about
40 % (15–20 ppbv each) of model-predicted O3 below 1 km
altitude at Huntsville, AL, while long-range transport accounted for
∼ 80 % of model-predicted O3 above 4 km altitude (Johnson
et al., 2016). This variation of source contributions with altitude provides
an opportunity to differentiate between emission-related and
transport-related trends derived from vertical soundings of upper-air
O3 mixing ratios. Using ozonesondes that are generally launched on a
weekly schedule, vertical O3 mixing ratio profiles have been
determined by the University of Alabama in Huntsville, Alabama, since 1999
(Newchurch et al., 2003; Johnson et al., 2016; University of Alabama Huntsville, 2017;
NOAA, 2017). We obtained these ozonesonde data (n=940 days) and
identified the following statistically significant trends in the lower layers
that are relatively more influenced by local and regional emissions according
to Johnson et al. (2016): -0.25 ± 0.11 ppbv yr-1
(p < 0.05) in daily measurements at 0.5 km,
-0.40 ± 0.10 ppbv yr-1 (p < 0.0001) at 1 km (daily),
-0.42 ± 0.09 ppbv yr-1 (p < 0.0001) at 2 km (daily),
and -0.57 ± 0.13 ppbv yr-1 in monthly averages of O3
measurements made throughout the interval 1–2 km (p < 0.001). At
higher altitudes where Johnson et al. (2016) predicted that long-range
transport is the dominant source of O3, no trends occurred:
0.06 ± 0.08 ppbv yr-1 (p > 0.1) at 4 km (daily) and
0.09 ± 0.19 ppbv yr-1 (p > 0.1) at 8 km (daily).
Global background is one component of regional background and trends in
global background are expected to contribute to trends in regional
background. Lin et al. (2017) show that rising NOx emissions
in Asia have increased modeled North American background O3 levels
(based on model simulations with zero North American emissions) by
∼ 0.2 ppbv yr-1 in the southeastern US in summer, which is a
small effect even when accumulated
over 20 years in comparison with the ∼ 25 ppbv reduction in the median
annual fourth-highest peak daily 8 h O3 shown in Fig. 2. Multiple
studies have demonstrated increasing trends in global background O3
mixing ratios (Ordóñez et al., 2007; Oltmans et al., 2008; Arif and
Abdullah, 2011; Wilson et al., 2012). Parrish et al. (2017a) report that the
highest O3 design values (the 3-year running mean of the annual
fourth-highest peak daily 8 h O3 mixing ratio) in southern
California are converging toward a limit of 62.0 ± 1.9 ppb, which they
identify as the O3 design values that would result from US background
O3 concentrations. Parrish et al. (2017b) report decreasing
O3 transported across the Pacific into the western US after 2000. As
noted, regional background O3 in the southeastern US does not appear
to be trending either upward or downward, even though trends in background
O3 have been established in other areas or globally.
In the southeastern US, the simple conceptual model of O3 transported
into a study region across upwind boundaries is incomplete. High O3
typically occurs during multi-day stagnation episodes, which are associated
with the presence of high barometric pressure over the domain and limited
transport (Blanchard et al., 2013). Transport distances determined from 24 h
back-trajectory computations are less than 300 km for the highest decile
O3 (Blanchard et al., 2013). Mean 24 h transport distances are less
than 350 km during June and less than 380 km during July (Blanchard et al.,
2014). These distances are approximately equivalent to distances from
Birmingham to Mobile, AL, or from Atlanta to Savannah, GA. Local and regional
emissions can accumulate over multiple days and potentially could contribute
to observed O3 concentrations (e.g., aloft) that are considered as
regional background. In contrast to emissions originating upwind, carryover
from emission sources within the study domain is a manageable component of
efforts to reduce O3.
(a) Daily-average isoprene mixing ratios vs. date,
(b) statistical distributions of daily-average isoprene mixing
ratios vs. year, and (c) statistical distributions of daily-average
isoprene mixing ratios vs. month. Samples were obtained every day at JST and
once every 6 days at YRK and SDK (Blanchard et al., 2010a). Distributions
indicate the 10th, 25th, 50th, 75th, and 90th percentiles.
Seasonal variations of O3, NOy,
NOz, HNO3, and VOCs
The seasonal oscillations of monthly O3 maxima in the southeast are
coupled to local or regional meteorology, solar radiation, and emissions
(e.g., Blanchard et al., 2013, 2014; Hidy et al., 2014). Variations of daily
maximum temperature and midday relative humidity (RH) are associated with
variations of daily peak 8 h O3 mixing ratios by
∼ ±30 % from mean peak 8 h O3 mixing ratios, after
also accounting for variations of other meteorological factors (Blanchard et
al., 2014). Air mass back trajectories originating from the south
(∼ 150 to 200∘) exhibit peak 8 h O3 that is
∼ 5–10 % lower than average; daily peak O3 decreases as
24 h back-trajectory distances increase from zero to ∼ 600 km,
consistent with association of higher O3 concentrations with air mass
stagnation rather than transport (Blanchard et al., 2013, 2014). At SEARCH
sites, the monthly O3 maxima (highest daily peak 8 h O3 each
month) and mean daily peak 8 h O3 mixing ratios typically occurred
in summer months, especially inland, and declined more than other monthly
maxima (Figs. 3 and 4). Summer means were not always higher than spring
averages, especially at rural and coastal sites and during more recent years
(Fig. 4). Roughly constant winter monthly peak 8 h maxima of
∼ 40 ppbv occurred throughout the period of record (Fig. 3). The
seasonal variability of the highest peak daily 8 h O3 therefore
declined over time (see also Table S3). Similar results were found for
monthly means of hourly measurements, discussed in Sect. 4.3 on diurnal
variations. Other recent studies have reported decreasing seasonal
variability of O3 across the US using data from large numbers of
monitoring sites (Chan, 2009; Chan and Vet, 2010; Cooper et al., 2012;
Paoletti et al., 2014; Simon et al., 2015). Declines in seasonal variability
are thought to result from changing rates of O3 formation as
precursor emissions have declined or from increasing influence of
intercontinental background O3, not from changes in seasonal
variations of temperature and other meteorological factors (Chan, 2009;
Cooper et al., 2012; Simon et al., 2015).
Average O3 mixing ratios vs. hour, by year. Each data point
is the mean of all hourly measurements during June through August. Sites at
PNS and GFP (not shown) exhibit similar diurnal profiles and trends (sampling
at those sites ended after 2009 and 2012, respectively). Standard errors of
the means are 0.3–4 ppbv (∼ 2 % of mean O3 mixing
ratios).
The SEARCH data indicate that seasonal variations occur in ambient
O3, NOy, NOz, HNO3, and the
ratio of NOz / NOy (Fig. 5). Seasonal
variations of temperature and other meteorological factors are known to cause
seasonal variations of O3 and NOy species
concentrations. The monthly average NOz and HNO3
mixing ratios indicate that active photochemical processing of
NOx occurs during well over half the year in the warm
climate of the southeastern US. The effects of VOC species on O3
formation depend on both their ambient concentrations and their reactivities.
To describe VOC variations at sites with long-term VOC measurements, we use
isoprene data as an indicator of biogenic VOCs and toluene as an indicator of
anthropogenic VOCs (nominally emitted as a gasoline vapor). The importance of
isoprene emissions for O3 production in the southeastern US is well
established (e.g., Chameides et al., 1988; Chameides and Cowling, 1995; Frost
et al., 1998; Starn et al., 1998; Wiedinmyer et al., 2006; Zhang et al.,
2014; Lin et al., 2017). We also consider other reactive VOC species of
interest, including α-pinene (biogenic) as well as ethylene and
xylenes (anthropogenic). Summer (June–August) months exhibit elevated
ambient mixing ratios of rural and urban isoprene, typically about
5–10 ppbC, that are 1 to 2 orders of magnitude greater than those occurring
between October and April (Fig. 6). Transitions between low and high ambient
isoprene mixing ratios occur in mid-May and mid-September in northern Georgia
(Fig. 6). Annual mean isoprene mixing ratios were relatively constant,
∼ 2.5–3 ppbC, between 1998 and 2014. Biogenic VOCs, primarily
isoprene, represent ∼ 20 % of the VOC reactivity at JST,
∼ 30 % at South DeKalb (SDK, located in metropolitan Atlanta
∼ 16 km southeast of JST), and ∼ 50 % at YRK, averaged over
all samples collected between 1999 and 2007 (Blanchard et al., 2010a).
Through precursor interactions, seasonal variations in isoprene mixing ratios
are expected to affect seasonal variations in O3 mixing ratios and
production rates.
(a) O3 vs. NOz at JST,
(b) O3 vs. HNO3 at JST, (c) O3 vs.
NOz at YRK, and (d) O3 vs. HNO3 at
YRK. Each point is the 14:00–15:00 hourly average on 1 day, limited
to days in June or July and delineated by year. The 2001 and 2002
NOz data may be biased high due to lower NO2 mixing
ratios obtained by the instrumentation used at that time (Fig. S2).
Mean mixing ratios of ethylene and aromatic compounds vary substantially
between urban and rural sites and exhibit less, and a different, seasonal
variation than does isoprene, peaking in the fall rather than in the summer
(compare Figs. 6, S5, S6). Daily-average mixing ratios of toluene, xylenes,
and ethylene decline over the years, consistent with regulatory reductions of
anthropogenic VOC emissions (Figs. S5, S6). Seasonal variations in ambient
mixing ratios and trends in the anthropogenic emissions of aromatic compounds
are expected to influence O3 mixing ratios and production in urban
settings (rural anthropogenic VOC mixing ratios are lower but detectable).
The 24 h average VOC mixing ratios are of somewhat limited value for showing
the influence of VOCs on O3 formation and accumulation. VOC influence
is dependent on NOx mixing ratios, which vary depending on
proximity to emission sources and time of day. Meteorological variability,
including diurnal and day-to-day changes in temperature, vertical mixing,
cloud cover, photolysis, and air mass transport, further obscures the
quantitative effects of VOCs on seasonal and interannual variations of
O3. Influences of anthropogenic VOCs at SEARCH sites have previously
been reported (Blanchard et al., 2010b, 2014) and are not analyzed beyond
this summary.
Diurnal variations of O3, NOy,
NOz, and HNO3
Summer (June–August) mean O3 mixing ratios exhibit characteristic
nocturnal minima and midday (noon to 16:00, midpoint
∼ 14:00) maxima at all SEARCH sites (Fig. 7). This diurnal
pattern remained essentially the same at both the urban and rural sites from
1999 through 2014, but the daytime maxima decreased. Between 1999 and 2014,
the summer mean midday maxima declined by ∼ 30 ppbv at all sites,
while nocturnal means exhibited variable responses (Fig. 7). Similar diurnal
variations occur throughout the year, with smaller decreases in the mean
midday O3 maxima occurring during seasons other than summer
(Figs. S7–S9). By the end of the study period, diurnal O3 profiles
were higher during spring (March through May) than summer at the rural sites
(CTR and YRK, Figs. S7 and S8), consistent with the reduction in summer mean
monthly daily peak 8 h O3 averages (Fig. 4). Decreasing summer
diurnal mean NOy, HNO3, and NOz
mixing ratios were also observed, with a general flattening of the profiles
and with the times of maxima remaining consistent (Figs. S10–S12).
O3 changes are discussed in relation to changes in
NOy and NOz in Sect. 4.4, with emphasis on
summer and additional consideration of spring months.
O3 vs. NOz during June and July 2013. Each
point is the 14:00–15:00 hourly average on 1 day. The data were selected to
represent the approximate midpoint of the midday O3 maxima and to
span a period around the summer solstice (∼ -20, ∼ +40 days)
when solar radiation is highest on average. The regression slopes show higher
rural than urban values: BHM = 13.05 ± 1.19 ppbv ppbv-1,
JST = 14.82 ± 0.88 ppbv ppbv-1,
YRK = 18.78 ± 1.38 ppbv ppbv-1, and
CTR = 25.73 ± 2.76 ppbv ppbv-1. Corresponding regression
slopes for Ox vs. NOz are BHM = 12.00 ± 1.16 ppbv ppbv-1, JST = 13.88,± 0.93 ppbv ppbv-1,
YRK = 18.85 ± 1.37 ppbv ppbv-1, and
CTR = 25.79 ± 2.79 ppbv ppbv-1. Symbols indicate the
favorability of weather to O3 formation and accumulation:
(1) favorable – T > 25 ∘C, RH < 70 %, and solar
radiation > 500 W m-2; (2) intermediate – neither favorable nor
unfavorable; (3) unfavorable – T < 25 ∘C, RH > 70 %,
and solar radiation < 500 W m-2. Regression results are shown for
all days and for the days with favorable weather.
Observed relationships between O3 and NOz
As discussed above, O3 mixing ratios vary seasonally and diurnally in
response to variations in emissions, weather, background O3, and
other factors. To reduce the influence of seasonal and diurnal variability,
this section focuses on mixing ratios of NOz, HNO3,
and O3 at 14:00 during June and July. Both temperature and
solar radiation are typically high during June and July, and multi-day
stagnation events occur frequently in association with high barometric
pressure (Blanchard et al., 2013). Exceptions exist during the passage of
frontal systems (Blanchard et al., 2013; Fig. S13). The 14:00 hour has
the highest, or close to highest, average hourly O3 for all sites and
years (Fig. 7). The atmosphere is well mixed by midday. Over the range of
ambient mixing ratios observed across 15 years, the June–July 14:00
O3 values are distinctly nonlinear in relation to ambient
NOz and HNO3 mixing ratios (Fig. 8). More
variability is evident at urban sites than at rural sites, consistent with
influence of urban NOx and perhaps VOC emissions on
O3. The nonlinearity indicated in Fig. 8 is also evident when the
data are restricted to days having the highest peak daily 8 h O3
mixing ratios (Fig. S14).
Linear models
Linear regressions are fit to the afternoon data by year, as shown in Fig. 9
for 2013 and in Table S4 for all years. During multi-week periods within any
summer, all sites exhibit near-linear relationships of midday O3 to
NOz. Because the ranges of NOx and
NOz mixing ratios within each year are limited,
year-specific relationships are close to linear and linear models are
statistically significant. Steeper slopes at rural sites than at urban sites
in Fig. 9 suggest that either more O3 molecules formed per molecule
of NOx consumed in rural locales than in urban areas or
that greater losses of NOz occurred at the rural sites, as
discussed below. At all sites, similar results are obtained for regressions
of Ox (O3 + NO2) vs. NOz compared
with O3 vs. NOz (Fig. 9, caption). At 14:00,
rural O3 mixing ratios are nearly identical with Ox mixing
ratios and with other metrics (e.g., O3–[NOy–NO])
(Fig. S15). At urban sites, 14:00 NO2 mixing ratios are
non-negligible, but this difference alters the intercepts rather than the
slopes of the regressions of Ox vs. NOz compared with
O3 vs. NOz (Fig. 9). As previously noted (Fig. S13),
even during the 2-month periods that we analyzed, the weather is not always
conducive to O3 formation and such days could influence the observed
slopes and intercepts. However, regression results restricted to days with
weather that favors O3 formation (as defined in Fig. 9) do not differ
from the unrestricted regressions.
Plotting the year-specific (June–July) computed regression slopes versus
mean June–July 14:00 NOz shows significant increases
over time as ambient NOz mixing ratios have decreased,
subject to year-to-year variability (Fig. 10, Table S4). Similar urban–rural
differences and patterns of increasing regression slopes are also observed
when data are restricted to March and April (spring) at YRK and JST
(Fig. S16). The results for spring show more variability than the summer
year-specific linear models. One key difference between spring and summer
days is that cumulative solar radiation between sunrise and 14:00 is greater
on summer days than on spring days, presumably fostering greater
photochemical extent of reaction and accumulation of O3 during
summer.
(a) Summer CTR, JST, and YRK slope of daily (14:00)
O3 and NOz vs. mean (14:00)
NOz mixing ratios and (b) summer regression slope
vs. year. NO2 data were not available for 1999 through 2001. Vertical
and horizontal error bars are 1 standard error of the regression slopes and
1 standard error of the NOz means, respectively. Mean
NOz measurement uncertainty is estimated as 0.2 ppbv
(1σ).
The regression slopes determined from 14:00 data could reflect day-to-day
differences in transported O3 if background O3 is
consistently higher on high-O3 days than on low-O3 days and
NOz is not (in contrast, random variations in day-to-day
background O3 and NOz would introduce variations, or
scatter, around the regression lines). We checked for an effect of this type
by repeating the analyses using differences in mixing ratios. Two sets of
difference-based regressions are used: (1) the differences between
14:00 and 10:00 hourly measurements and (2) the differences
between 11:00 and 10:00 hourly measurements. The differences are computed for
each day to minimize or eliminate the unknown day-specific background levels
and are then used in the regressions. These hours were selected to focus on
times of day when the atmosphere is well mixed. The morning rise in mixing
heights is expected to contribute to increases in the mixing ratios of
secondary species as aged air aloft is incorporated into the mixed layer. The
most rapid rates of increase in diurnally averaged O3,
NOz, and HNO3 values occur between ∼ 08:00 and
12:00 noon local time (Figs. 7, S8–S9). By mid- to late-morning hours during
summer, considerable vertical entrainment has occurred, and subsequent
changes in the mixing ratios of secondary species likely reflect same-day
atmospheric chemical reactions. Computing afternoon–morning differences and
late morning–mid-morning differences helps account for day-to-day variations
in regional background O3 but also introduces higher relative
uncertainties because four measurements (two differences) are used in the
regressions. Results for all three approaches are tabulated in Table S5, by
site and year. Like the regressions based on 14:00 measurements, the
difference-based regressions indicate that observed slopes have increased
over time (Table S5). The difference-based regressions exhibit lower slopes
than the non-differenced afternoon regressions, which could be due to lesser
statistical fit, or to better accounting for regional background O3,
or to a combination of these factors. The difference-based regressions
suggest that O3–NOz slopes increased from less than
5 : 1 in the late 1990s and early 2000s to values between 5 : 1 and
10 : 1 after 2010 (Table S5). These lower slope values are consistent with
our previous results in which observed O3–NOz
relationships were determined while also accounting for day-to-day variations
in meteorology, which indicated that JST, YRK, and CTR
O3 / NOz slopes were 3.5, 5.0, and 7.1,
respectively, within the range of 1 to 5 ppbv NOz, for
measurements made during March–October of 2002–2011 (Blanchard et al.,
2014).
A second potential effect on the temporal changes in the regression slopes
could be due to changes in NO2 measurement methods (previously
described); this possibility was checked by using regressions of O3
vs. HNO3 (Fig. S17). The results indicate that the relationship in
Fig. 10 is not an artifact of changes in NO2 measurement methods. The
record is more complete for the regressions of O3 vs. HNO3,
because the HNO3 measurements were made over a longer time than the
NO2 measurements (and the latter are needed for computing
NOz). As shown for YRK, the year-specific slopes of
14:00 O3 vs. NOz and for O3 vs.
HNO3 each increased substantially after about 2008 (Figs. 10, S17).
The O3 vs. NOz and O3 vs. HNO3
regression slopes tend to level out after 2011, and possibly decrease
somewhat, but variability is too high to project beyond the observed data
ranges (Figs. 10, S17). Similar results are obtained for spring for JST and
YRK (Figs. S18 and S19).
Our increases in year-specific slopes of O3 versus
NOz potentially could be due to increasing losses of
NOz species, especially HNO3, over the long-term
SEARCH record. As previously noted, however, the CASTNET data show declining
rates of both wet and dry nitrate deposition since the late 1990s, with no
change in the ratio of deposition to emissions (Fig. 1). Therefore, the
long-term slope increases cannot be attributed to increasing deposition
losses of HNO3 (whether absolute or fractional). Qualitatively, the
CASTNET data suggest that the observed slopes would likely be at least a
factor of 2 smaller if adjusted for deposition losses. This adjustment
would be comparable to the 1990s studies discussed in Sect. 4.4.2. In Fig. 9,
the intercepts of year-specific regressions for 2013 approach 20 ppbv
O3, which could be interpreted as a regional background O3
level relatively unaffected by local chemistry. These values are lower than
those in Fig. 2 and lower than the estimated range of 48 to 59 ppbv for air
transported into the Houston area. They are also lower than modeled western
non-US-anthropogenic regional background O3 levels of
∼ 40–50 ppbv (Lefohn et al., 2014; Dolwick et al., 2015) but are
consistent with model estimates of non-US-anthropogenic background O3
less than ∼ 30 ppbv in Atlanta (Lefohn et al., 2014). Since regression
intercepts restricted to days with weather that favors O3 formation
do not differ much from the intercepts of the unrestricted regressions
(Fig. 9), our low intercepts for recent years do not appear to be linked to
meteorological conditions that specifically favor O3 loss over
formation. However, when considered over the full set of years, the
O3–NOz relationships on the highest O3 days
differ from those on larger subsets of the data (Fig. S14). Possibly, the
intercept terms cannot be fully interpreted without additional consideration
of O3 carryover in multi-day episodes, as previously noted. The
intercept terms for earlier years are higher than for later years; for
example, the intercepts for the YRK regressions range from 27 ± 3 to
42 ± 4 ppbv prior to 2009 (for all but 2 of these years, intercepts
are 36–38 ppbv). The intercept terms for earlier years are consistent with
1997–2006 eastern US summer baseline O3 levels (32 ± 12 ppbv
in the absence of continental influences) reported by Chan and Vet (2010).
Higher intercepts during early years could be due to fitting a linear
regression to the upper portion or the midrange of the nonlinear relationship
between O3 and NOz, as shown in Figs. 8 and S14. The
nonlinearity and the downward trends in mean NOz and
HNO3 mixing ratios mean that slopes of regressions computed at higher
mean NOz and HNO3 mixing ratios should not be
extrapolated beyond their range of applicability to the y intercept.
Alternatively, the trend toward lower intercepts could reflect declining
mixing ratios upwind of the study sites, consistent with documented long-term
reductions of ambient O3 mixing ratios throughout the US (e.g., Chan
and Vet, 2010; Lefohn et al., 2010; Paoletti et al., 2014; Simon et al.,
2015; Hidy and Blanchard, 2015). As previously discussed, however, regional
background O3 in the southeastern US does not appear to be trending
either upward or downward.
Comparisons with observational and modeling studies
The preceding section demonstrates that the slopes of the regressions of
O3 versus NOz increased over time and examines the
potential influence of measurement artifacts, weather, deposition, and
pollutant transport on the results; none of these plausible influences
adequately explains why the slopes of the regressions of O3 versus
NOz increased. The increasing slopes appear to indicate that
relationships between O3 and NOz changed over time,
yet the physical processes associated with the changes remain ambiguous.
Modeling studies offer insights. Modeling process analysis by Reynolds et
al. (2004) for the eastern US predicted that the number of NO cycles (i.e.,
the ratio of new plus recreated NO to new NO) would increase from 8 to 14
(∼ 75 %) in central (metropolitan) Atlanta and from 9 to 11
(∼ 20 %) northwest of Atlanta in response to a 60 % reduction
of NOx emissions from a 1996 emissions base case. Both the
modeled emission reduction (60 %; compare to Fig. 2) and the modeling
subregions (central Atlanta, JST; northwest Atlanta, YRK) are directly
comparable to our study period and domain. NO cycling is relevant to our
regressions of O3 versus NOz because an O3
molecule is produced, with some loss, each time NO cycles through a set of
reactions until NO cycling terminates in reaction products that are
components of NOz (e.g., HNO3, PAN). Thus, the
observed increases in the slopes of the regressions of O3 versus
NOz are directionally consistent with modeling predictions
but larger than the predicted 20–75 % increases in NO cycling.
The data were selected to represent periods that have consistent weather from
day to day to minimize the influence of meteorological variability, and
regressions of subsets of the data yield slopes and intercepts comparable to
those based on all days of June and July (Fig. 9). However, the observed
O3 decreases that have occurred in the region (Figs. 2 and 3) could
not have occurred if O3 formation rates increased by factors of
∼ 3 to 4 (as suggested by Fig. 10) or even by a factor of 2
(Table S5), since NOx emissions declined by
∼ 60 %, or ∼ 5 % per year over 20 years (Fig. 1; Hidy et
al., 2014). This consideration suggests that increased NO cycling, while
likely linked with our observational results, cannot be the only factor
involved. The regression slopes are nonetheless consistent with related
studies when a basis for comparison exists.
The SEARCH-observed afternoon slope values of ∼ 5 : 1 prior to
2003–2007 are comparable to, or lower than, similar regression results
obtained in studies during the 1990s – which showed observed summer slope
values of 11 : 1 in rural Georgia in 1991 (Kleinman et al., 1994);
8.5 : 1 at rural eastern sites (Trainer et al., 1993); 7 : 1 near
Birmingham, AL, in 1992 (Trainer et al., 1995); 5.7 : 1 near Nashville, TN,
in 1995 (Sillman et al., 1998); and 4.7 : 1 near Nashville, TN, in 1999
(Zaveri et al., 2003) – and to modeling results and observations with
composite regression slope values of 6.7 and 7.6, respectively, within the
afternoon planetary boundary layer in the eastern US during the summer of
2002 (Godowitch et al., 2011). The SEARCH regression slope values prior to
2003–2007 are, as expected, higher than other 1990s values that were
corrected for deposition losses, which, for example, yielded adjusted
estimated values between 3 : 1 and 5 : 1 near Nashville in 1995
(Nunnermacker et al., 1998; St. John et al., 1998; Sillman et al., 1998). Our
higher observed slope values after 2010 are consistent with aircraft
measurements made in the southeast in August and September 2013, which show
an Ox (= O3 + NO2) versus
NOz slope of 17.4, and they are also consistent with model
calculations, which show slopes of 14.1 to 16.7 (Travis et al., 2016).
Consistent with our regressions, Travis et al. (2016) did not adjust for
variations in background O3 and NOz. For
comparability, we note that our O3 versus NOz
regression slopes were 13.1 to 18.8 (±1.2 to 1.4) in June and July 2013
at three of four sites (25.7 ± 2.8 at the fourth site, which is the
most rural in character) and our Ox versus NOz slopes
were 12.0 to 18.9 (±1.2 to 1.4) at three of the four sites (25.8 ± 2.8 at the fourth site). The increase in recently observed slope values
that we report is therefore supported by the 2013 data of Travis et
al. (2016). Our apparently high regression slope values are comparable to
observations that averaged 12.9 in ship plumes and 33.5 in assumed background
marine air, as reported by Kim et al. (2016) using data from a 2002 study of
ship emission plumes off the coast of southern California, though the
specific conditions associated with these two studies are different from ours
and thus limit the applicability of the comparisons.
The increase in regression slopes with decreasing ambient
NOx and NOz is also directionally
consistent with computations by Liu et al. (1987), which showed increasing
OPE as NOx declines. The numerical results of the modeling
calculations by Liu et al. (1987) are specific to the modeled conditions,
which represented complete oxidation of VOCs over a period of months.
However, increases in model-predicted NOx OPE with declining
NOx result from multiple factors, such as radical reactions
involving VOCs and NOx, that are pertinent to other
situations (Lin et al., 1988).
In contrast to southern California, where Pollack et al. (2013) reported a
shift from PAN to HNO3 production, the SEARCH data do not
definitively show a changing fraction of HNO3 relative to
NOy. Increasing formation of PAN (which regenerates
NO2) and decreasing formation of HNO3 (which terminates
cycling between NO and NO2) could facilitate O3
accumulation as ambient NOx and NOz mixing
ratios continue to decline. Since the long-term SEARCH data record does not
include measurements of PAN, this possible effect could not be investigated.