Several broad features of AOP temporal variability are common to all or most
of the four sites. For the sake of brevity, these features are first discussed
collectively before moving on to a more detailed analysis of AOP variability
at each site and then to comparisons among the sites. Much of the seasonal
AOP variability at each site can be explained using the following: (1) published results of
seasonally dependent aerosol chemistry at the sites; (2) pollution-rose
diagrams, which simultaneously display percentage of hours with winds
arriving from each wind sector and the distribution of AOP values for each
sector; (3) known regional pollution sources; and (4) published seasonality
of PBL height and monthly median temperature and relative humidity at the
sites. Temperature dependence of σsp is also helpful. Diurnal
and weekly cycles of select AOPs and the seasonal dependence of these cycles
are used to estimate the relative influences of some local and regional
sources (mainly traffic) and PBL heights. Regional variability in AOPs is
discussed in the context of the annual AOP cycles and the above-listed
sources of seasonal variability at each site. Trends in AOPs at BND and SGP
are used to place results for the current period in a long-term context.
Systematic relationships among select AOPs at each site are used to help
interpret the temporal and regional AOP variability and to hypothesize
aerosol sources or processes at the sites. Numerous pieces of supporting
materials for the presented results are included as part of the Supplement. We reference those figures and tables with the
letter “S” (e.g., Fig. S13, Table S2) to distinguish them from figures
appearing in this paper.
Temporal variability of aerosol optical properties
Temporal variability common to all sites
The annual AOP cycle amplitudes are larger than the weekly and diurnal AOP
cycle amplitudes at all sites. Nearly all annual AOP cycles are significant,
with cycle amplitudes larger than the 95 % confidence intervals of both
the monthly mean AOPs (Fig. 2) and the measurement uncertainties (Table 3).
July and/or August σsp maxima are observed at all sites (Fig. 2a), with steeper σsp decreases from summer to fall than from
summer to spring. Summer-to-spring and summer-to-fall σsp
decreases at EGB and APP are approximately twice the magnitude of those
observed at BND and SGP. Scattering coefficient reaches a minimum during
October at all sites except APP, where it is lowest in December. Absorption
coefficient is highest in summer and lowest in winter at all sites (Fig. 2b), although the differences between summer σap maxima and the
surrounding months are only significant at BND and EGB. Summer-to-autumn
σsp decreases are larger than those of σap,
leading to minimum ω0 in October at all sites (Fig. 2e).
Hemispheric backscatter fraction is highest in October at all sites (Fig. 2d). The confluence of early autumn decreases in σsp and
ω0 and increases in b is indicative of less production and/or
more efficient removal of large, highly scattering particles during early
autumn, relative to summer. This effect is most noticeable at EGB and APP
(Fig. 2) and also is seen in the summer–spring differences at APP. October
ω0 minima contribute to DRFE maxima (least negative) at EGB and
BND, but no significant autumn DRFE changes are seen at APP and SGP (Fig. 2f). Photochemistry likely influences the summer σsp maxima and
σsp that are larger in spring than in fall at all sites. The
temperature dependence of σsp (Fig. S5) and differences in
monthly median temperatures (Fig. S23) combine to yield predicted
differences in σsp that are of similar magnitude to the large
observed summer–spring (July–April) σsp differences at EGB and
APP and to the observed summer–autumn (July–October) σsp
differences at EGB, BND, and SGP (Fig. 2a). The summer–autumn σsp difference based on temperature considerations is less at APP than
the observed σsp difference, leading us to hypothesize an
additional contributor to the autumn σsp decrease. Cloud and
fog scavenging of large, highly reflecting particles would be consistent
with cooler September temperatures (Fig. S23a), higher RH (Fig. S23b), and
cloud cover in September at APP. The inverse relationship between σsp and b seen in the annual cycles at all sites (Fig. 2a and d) is
indicative of the influence of particle growth (and possibly cloud or fog
scavenging) on σsp. Wet deposition likely impacts σsp most in summer and least in spring and fall, given the seasonality
of precipitation at the sites. Secondary σsp maxima are
observed during winter at all sites except APP (Fig. 2a). When combined with
winter σap minima, the result is a winter ω0
maxima at these sites (Fig. 2e).
In contrast to b, the annual Rsp and PM10 αsp cycles (Fig. 2c and
g) at APP, BND, and SGP (the sites where these AOPs are calculated) do not
demonstrate an obvious relationship with the annual σsp cycles.
Collaud Coen et al. (2007) conducted simulations based on Mie theory to show
that b at 550 nm is most sensitive to particle size changes for diameters
∼ 100–300 nm (their Fig. 7 and accompanying discussion).
Schuster et al. (2006) combined simulations based on Mie theory with volume
size distributions and AOD from AERONET to show that extinction
Ångström exponent is relatively insensitive to fine mode effective
radius for bi-modal aerosol size distributions and that extinction
Ångström exponent may serve as a better indicator of fine-mode
aerosol volume fraction than mean particle size. The stronger relationship
between the annual b and σsp cycles (relative to relationships
between the cycles of σsp with either αsp or Rsp) suggests
that the major seasonal changes in the aerosol size distributions at APP,
BND, and SGP may lie at the smaller end of the range of optically relevant
accumulation mode particles (100–300 nm), with shifts toward larger
particles in summer and smaller particles in fall. Photochemistry likely
plays a role in the observed seasonal cycle of b, especially at APP and EGB.
Gas-to-particle conversion onto existing particles is most efficient for the
100–500 nm diameter range, since this is where most of the aerosol surface
area typically lies (Seinfeld and Pandis, 1998). Reduced gas to particle
conversion in fall (when photochemistry and precursor levels are lower)
would impact b more than αsp and Rsp.
Absorption Ångström exponent is lowest during summer months and
highest during winter months (Fig. 2h) at APP, BND and SGP (the three sites
where αap can be calculated). The summer-to-winter difference
in αap is clearly larger at APP (∼ 0.9) than at
BND and SGP (∼ 0.5). Absorption Ångström exponent
values near and below 1 during May–September suggest that black carbon (BC)
contributes most to σap during these months (Gyawali et al.,
2009; Cazorla et al., 2013). Gyawali et al. (2009) performed simulations
using Mie theory to show that αap values much less than 1 are
possible (their Figs. 8 and 9) when absorbing particles are coated with
non-absorbing substances. Clarke et al. (2007) also reported a large number
of αap (470/660 nm) values clustered between 0.7 and 1.1 for
pollution plumes during extensive flights over North America as part the of
the INTEX/ICARTT experiment in summer 2004.
Weekly and diurnal cycles of geometric mean PM1 σsp
over full years (ANN traces) and for winter (DJF), spring (MAM), summer
(JJA), and fall (SON) at APP, BND, EGB, and SGP over the 2010–2013 period.
The value corresponding to the “ALL” data point of each trace is the mean
value over all days of the week or over all hours of the day. Error bars represent
95 % confidence intervals of mean σsp values.
Weekly and diurnal cycle amplitudes of σsp (Fig. 3) and
nearly all intensive AOPs observed at the four sites are much smaller than
the corresponding annual cycle amplitudes. Weekly and diurnal σap cycle amplitudes (Fig. 4) are larger than those of σsp
at all sites and are largest in summer. Weekly σap cycles at
all sites are marginally significant in fall with σap cycle
amplitudes approximately twice the σap measurement precision
uncertainty (Table 3). All sites demonstrate small and/or insignificant
weekly σsp cycle amplitudes (∼ 20 % or less)
and a lack of weekly σsp patterns across seasons (Fig. 3). This
suggests that weekly σsp cycles are driven by regional-scale
phenomena, where any weekend effects are smoothed out by mixing. The weekly
cycles of intensive AOPs are nearly always minimal at all sites (Figs. S9–S15).
Weekly and diurnal cycles of geometric mean PM1 σap
over full years (ANN traces) and for individual seasons at APP, BND, EGB,
and SGP over the 2010–2013 period. The value corresponding to the “ALL” data
point is the mean value over all days of the week or over all hours of the day.
Error bars represent 95 % confidence intervals of the mean values.
Similar to the weekly σap cycles, the diurnal σap cycles are also much larger than diurnal σsp cycles at all
sites. However, the diurnal σap variability is only significant
during summer and (at all sites except APP) fall. Diurnal cycles of nearly
all intensive AOPs are minimal and/or insignificant. Notable exceptions are
ω0 and DRFE during summer and fall. The amplitudes of the diurnal
ω0 cycles are ∼ 0.03–0.04 during summer and fall
at all sites (Fig. S12). In most of these cases, ω0 is lowest during
late evening and/or early morning and highest during afternoon. At APP, the
ω0 peak extends from around noon to the early morning hours.
Diurnal DRFE cycles (Fig. S13) in turn follow the diurnal ω0 cycles,
due to the lack of diurnal variability in b. Summer and fall DRFE is more
negative by ∼ 3 W m-2 AOD-1 during the afternoon
than during the surrounding hours (Fig. S13). The lack of diurnal and weekly
variability in mean b, Rsp, and αsp indicates that particle size
distributions at APP, BND, and SGP likely demonstrate little variability on
weekly or daily timescales. D&O2002 reported similar or slightly smaller
ω0 and b diurnal cycle amplitudes for BND and SGP, but they did not
consider the diurnal cycles for individual seasons.
Temporal variability at APP
Aerosol light scattering and absorption coefficients at APP are dominated by
PM1 for all seasons and the relative influence of PM1 varies little with
season, as seen by Rsp values of 0.80–0.88 (Fig. 2c), αsp values of
1.9–2.2 (Fig. 2g), and Rap values of 0.90–0.95 (Fig. S8c). Both σsp
and σap are moderately elevated for NE wind sectors, with
0–90∘ wind directions (Fig. 5). Median
σap is ∼ 20–30 % higher for NE wind sectors than for
the prevalent westerly wind sectors for all seasons except winter, when
σap for the NE wind sectors is ∼ 2 times higher than
σap for westerly wind sectors (not shown). Median σsp is
less elevated for the NE wind sectors (typically ∼ 10–15 %).
Wind sector does not strongly influence median or mean values of most
intensive AOPs, although low ω0 (< 0.80) is more frequently
associated with NE wind sectors (Fig. S17a). It should be noted that the
prevalent westerly wind sectors represent the confluence of 3–4
(seasonally dependent) different average air mass back-trajectories, which
all typically arrive at APP from the west. Link et al. (2015) reported that
aerosol and gas phase chemistry measured at APP displayed a generally
homogeneous distribution across source regions. One exception was elevated
levels of urban, oil and natural gas, combustion tracers, and OA mass
concentrations associated with air mass back-trajectories passing over the
polluted Ohio River valley and Appalachian mountain region before arriving
at APP with ∼ 0–90∘ wind directions
(Link et al., 2015).
PM1 σsp at APP and its seasonality (Fig. 2a) are largely
influenced by regional background SOA and sulfate. Biogenic SOA and sulfate
both exhibit summer maxima and winter minima in the SE US (Goldstein et al.,
2009; Hidy et al., 2014) and both summer and winter non-refractory PM1
aerosol mass at APP are dominated by SOA and sulfate (Supplement of Link et al., 2015). Summer σsp at APP is
correlated with both OA and sulfate mass concentrations (r=0.60 and
r=0.62, respectively). The temperature dependence of PM1 σsp
at APP during April–October (Fig. S7) also agrees well with the expected
temperature dependence of biogenic emissions (Guenther et al., 2006) and
with the temperature dependence of AOD over the SE US (Goldstein et al.,
2009). The summer σsp peak coincides with a distinct minima in
b (30–40 % lower than all other seasons) and maxima in ω0
(∼ 0.07 higher than during winter). Aerosol number
concentrations measured at APP are also lower in summer than during spring
and fall (unpublished result). The confluence of lower concentrations of
larger, highly reflective PM1 particles during months with high regional
temperatures, solar irradiance, and RH is consistent with gas-to-particle
conversion onto existing particles.
Pollution rose diagrams of PM1 σsp and σap for individual seasons at APP over the 2010–2013 period. The
percentages at a given radius represent the percentage of hourly profiles
for a given wind sector.
The annual σap cycle at APP (Fig. 2b) is out of phase with the
annual cycle of EC concentrations reported for rural eastern US IMPROVE
sites (Hand et al., 2012b). Hand et al. (2012b) cited sources such as
residential heating for the fall and winter EC concentration maxima.
Absorption coefficient at APP exhibits a summer maximum and a winter
minimum, though the summer σap maximum is not significantly
different from early fall and spring σap (to 95 % confidence).
Absorption Ångström exponents of ∼ 1.3–1.4 (Fig. 2h)
and αsp > 2 during colder months (Fig. 2h) suggest a
mixture of EC and light-absorbing OC (Fig. 2 of Cazorla et al., 2013). A
contribution to σap from OC is also consistent with a
biomass-burning OA factor in the winter aerosol mass spectra measured at APP
(Fig. S2 of Link et al., 2015) and may result from winter residential
wood-burning (US Census Bureau, 2010; Zhang et al., 2010). However, the
diurnal σap cycles (Fig. 4b) suggest an influence from local traffic
during all seasons and αap values of 1 or less for non-winter months
suggest that BC is the major contributor to σap during these months.
APP is the only site to demonstrate consistent weekly σsp and
σap cycles across seasons, with the exception of winter. Local
commuter traffic likely exerts the largest influence on the diurnal σap cycles (Fig. 4b) and possibly the weekly σap cycles
(Fig. 4a). Diurnal σap cycles are only significant at 95 %
confidence during summer, but a similar bi-modal structure is seen for all
seasons (Fig. 4b), with morning and late afternoon/early evening commuter
peaks. The only sign of weekend local traffic influence is an insignificant
Saturday morning peak Δσap∼ 0.1–0.2 Mm-1 present during most seasons (unpublished result), confirming the
primary influence of local commuter traffic. The absence of any influence of
diurnal PBL height variation on the diurnal σap cycles at APP
is consistent with the relatively small afternoon/morning PBL height
differences measured at the heavily forested APP site (unpublished result).
PBL height is often poorly defined at APP and may be related to the fact
that the APP site is situated on a ridge. The PBL and free troposphere do
not fully decouple during the evening. As a result, pronounced late-evening
through early morning σsp and σap maxima that are
characteristic of a PBL height influence are not a regular feature of the
diurnal cycles at APP (Figs. 3b and 4b). Diurnal variability of σsp and intensive AOPs is insignificant and/or minimal for all seasons
(Figs. S9–S15), with the exceptions of (1) morning ω0
decreases (by ∼ 0.02–0.03) DRFE increases (by 2–3 W m-2 AOD-1) during all seasons, coinciding with the commuter traffic; and
(2) a small summer daytime decrease (0.6 to 0.4) in αap,
possibly due to coating of absorbing particles (Gyawali et al., 2009) or an
artifact associated with filter-based σap measurements (Lack et
al., 2008, 2009).
The spring, summer, and fall weekly σsp and σap cycles at
APP (Figs. 3a and 4a) are characterized by early week increases leading to
broad Wednesday–Friday maxima. Both σsp and σap begin to
increase near the time of the Monday morning traffic peak (unpublished
result) and decrease over the weekend, coinciding with less weekend traffic.
The weekly σsp and σap cycles are likely the result of a
build-up of scattering and absorbing aerosols in the PBL during the first
half of the week. Sunday σap minima and weekly cycle amplitudes of
∼ 25–35 % during spring and fall are consistent with the
timing and amplitudes of weekly EC concentration cycles reported for the
rural US (Murphy et al., 2008) and with weekday–weekend EC concentration
differences in the urban US (Bae et al., 2004; Blanchard et al., 2008).
Smaller but significant weekly σsp cycle amplitudes of
∼ 15–20 % during spring, summer, and fall are larger than
weekly cycles in OC and sulfate reported by Murphy et al. (2008). Absorption
coefficient exhibits a larger summer weekly cycle amplitude of
∼ 50 % (Fig. 4a) than σsp (Fig. 3a). Local traffic
is less during summer, but construction activity and road repairs on the
Appalachian State University campus and in town are higher so a larger
influence from diesel emissions could be a source for the larger σap
cycle during summer. Local traffic influences on the weekly and diurnal
σap cycles during winter may be masked by other sources of EC, such
as wood-burning. Small weekly cycles in several intensive AOPs are
consistent with the above-discussed local traffic influence.
Single-scattering albedo decreases by ∼ 0.02 from Sunday to Wednesday
during fall/winter (Fig. S12) with smaller decreases during spring/summer.
DRFE increases by ∼ 2 W m-2 AOD-1 from Sunday to Wednesday
during fall/winter, with smaller insignificant increases in spring/summer
(Fig. S13). Absorption Ångström exponent increases during the week
by ∼ 0.2 (0.4 to 0.6) during summer, with smaller,
insignificant increases (∼ 0.1) during fall and winter (Fig. S15).
Temporal variability at BND
PM1 particles contribute ∼ 76 % (72 %) to the summer
(winter) PM10 σsp and 88 % (∼ 80 %) to the
summer (winter) PM10 σap at BND (Figs. 2c and S8c). The
annual PM1 and PM10 σap and σsp cycles are similar
for all seasons (Figs. 2 and S8) so the PM1 AOP cycles at BND are
representative of the PM10 aerosol. Many of the same general features of the
σsp annual cycle at BND (Fig. 2a) have been reported by others
(D&O2002; Koloutsou-Vakakis et al., 2001), including the July–August
σsp maximum and early autumn σsp minimum.
D&O2002 reported similar summer–autumn and summer–spring σsp
differences, with median σsp values in July approximately 2 times larger than σsp in October–November and ∼ 1.5 times larger than σsp in April–May. The σap
annual cycle reported by D&O2002 was also very similar to that shown in
Fig. 2b, except for an October σap maxima in their study.
Planetary boundary layer heights reported for nearby Joliet, IL by Holzworth (1964) were approximately 3 times higher in summer than in winter,
suggesting that summer aerosol production must be much higher (and/or sinks
be much lower) to maintain the observed higher summer aerosol loading in the
mixed layer.
Pollution rose diagrams of PM1 σsp and σap for individual seasons at BND over the 2010–2013 period. The
percentages at a given radius represent the percentage of hourly profiles
for a given wind sector.
Regional aerosol transport associated with southerly wind sectors (SE to SW
wind directions) exerts a large influence on σsp during all
seasons (Fig. 6a). Northerly wind sectors (NW to NE wind directions) exert a
comparable or larger influence on σsp during winter months. Much of
the light-scattering aerosol arriving from the south is likely secondary
sulfate associated with the high-density of coal-burning power plants in
southern Illinois and the Ohio River valley region (Buzcu-Guven et al.,
2007). Summer σsp may also be influenced by biogenic SOA. Median
summer temperatures are ∼ 3 ∘C higher for SW winds at BND
than for SE winds and the forests over SW Illinois and SE Missouri emit high
amounts of isoprene during summer (Fig. 3 of Parworth et al., 2015).
Scattering coefficient for SW wind directions exhibits a sharp July peak and
the temperature dependence of σsp at BND during April–October
demonstrates modest agreement (r=0.47, as shown in Fig. S7) with the
exponential temperature dependence of biogenic volatile organic compound
emissions (Guenther et al., 2006). The secondary PM1 σsp peak during
winter months at BND (Fig. 2a) may be influenced by temperature dependent
gas-to-particle partitioning of regional ammonia and nitric acid into
ammonium nitrate. Rupakheti et al. (2005) reported that gas-phase ammonia
correlated positively with particulate ammonium and nitrate mass
concentrations for temperatures below 12 ∘C and that more ammonia
remained in the gas phase for T > 12 ∘C. The temperature
dependence of median PM1 σsp at BND changes sign (positive to
negative) for temperatures less than ∼ 10 ∘C, nearly
doubling as temperature decreases from ∼ 10 to
∼ -5 ∘C (Fig. S5). The σsp increase is
accompanied by an increase in median ω0 from 0.89 to 0.96 (Fig. S6); and a decrease in median b from 0.15 to 0.13. Addition of large,
highly scattering PM1 particles at low temperatures is consistent with high
winter ammonium nitrate concentrations reported for BND (Buzcu-Guven et al.,
2007). Much of the winter σsp increase is likely due to
regional transport from the north. Winter σsp exhibits the
largest increase for northerly wind sectors (Fig. 6a) with winter σsp a factor of ∼ 1.5–3 larger than spring and fall
σsp. Winter ω0 and b are highest for the northerly
wind directions, with ω0≥ 0.93 and b < 0.15 for a
majority of the arriving air masses (Fig. S19). Northerly wind sectors are
typically associated with colder air mass traveling over regions with high
concentrations of ammonium and nitrate precursor gases (Hand et al., 2012b).
Temperature-dependent ammonium nitrate production is also consistent with
the highly variable timing and magnitude of the winter σsp peak
for individual years (Fig. S2). Lower winter PBL heights during winter
(Holzworth, 1964) likely also contribute to elevated winter σsp. Variability in winter PBL heights could conceivably contribute to
winter σsp variability.
Diurnal σsp cycles are insignificant for all seasons except for a
marginally significant fall amplitude of ∼ 25 % (Fig. 3d).
Diurnal σap cycle amplitudes (Fig. 4d) are much larger than those of
σsp during all seasons except winter. Differences between σap and σsp diurnal cycle amplitudes are largest in summer
(∼ 60 vs. 10 %) and are also non-negligible in fall
(∼ 50 vs. ∼ 25 %) and spring
(∼ 40 vs. ∼ 20 %). Diurnal σap
and σsp cycles are both smallest during winter, with cycle
amplitudes of ∼ 10 %. The influence of diurnal PBL height
cycle is clearly seen in the diurnal σap cycles (Fig. 4d) and a
smaller PBL height influence is seen in the σsp cycles. The
differences between σap and σsp cycle amplitudes during
summer and (to a lesser degree) fall and spring suggests a large additional
source of scattering aerosols during summer daytime hours. Photochemical
aerosol processing is the only source of scattering particles whose diurnal
and seasonal dependence can explain the seasonality of differences between
the σap and σsp cycle amplitudes. It is also consistent with
the seasonality of sulfate mass concentrations reported for BND (Buzcu-Guven
et al., 2007). Weekly σsp cycles are statistically significant for
all seasons, but the cycle amplitudes are less than 15 % for all seasons
except fall. Our weekly σsp cycle amplitude for the entire year
(Fig. 3c) is similar to that of Murphy et al. (2008).
Regional pollution transport associated with southerly wind sectors also
influences the annual σap cycle at BND over all seasons (Fig. 6b). Highest σap for the southerly wind sectors occurs during
summer and fall and southerly winds are most common in summer (Fig. 6a),
leading to the summer σap maxima (Fig. 2b). Lowest σap for the southerly wind sectors occurs during winter and air masses
from the less anthropogenically perturbed W/NW reach the site most
frequently in winter (Fig. 6b), leading to the winter σap
minima. The difference between the month of maximum σap
(August) and that reported by D&O2002 (October) could be due to
differences in the seasonality of wind directions between the two periods.
It could also arise due to differences in the seasonality of removal
mechanisms such as precipitation between the periods, but this would have
likely also shifted the month of maximum σsp.
The weekly and diurnal σap cycles during summer and autumn
(Fig. 4c, d) are consistent with a large influence from regional diesel
emissions during these seasons and possibly during other seasons, although
the weekly and diurnal σap cycles are only significant in
summer and autumn. Maximum σap extends from sunset to sunrise
for all seasons (Fig. 4d), with a broad minimum extending from just after
sunrise to just before sunset. Large seasonality of PBL heights is obvious
in the diurnal σap cycles (Fig. 4d), consistent with large
(factor of 3) summer-to-winter PBL height differences reported for the
region by Holzworth (1964). The absence of early morning and late afternoon
local commuter peaks at BND is not surprising, since emissions from
interstate highway traffic and agricultural activity represent the largest
local sources of absorbing aerosols. Long-distance trucking comprises a
large portion of interstate highway traffic in the region and both this and
farming activities typically persist throughout the day. The diurnal σap cycles for individual days of the week show the same broad features
as the corresponding weekly integrated diurnal σap cycles (Fig. 4d) for all seasons, with the exception of differences between post-dusk and
pre-dawn σap for individual days of the week (unpublished
result). During summer, post-dusk σap is slightly larger than
pre-dawn σap for each day during Monday–Friday, leading to a
gradual build-up of absorbing aerosols in the PBL. Post-dusk σap is less than pre-dawn σap on Saturday and Sunday. The
resulting weekly σap cycle (Fig. 4c) and the σap
cycles for individual days suggest a nearly constant source of absorbing
aerosols from sunrise to sunset, with the largest emissions from Monday to Friday.
Both interstate truck traffic and farming activities are consistent with the
observed diurnal and weekly patterns during summer, but truck traffic is
likely the source more capable of contributing to the large summer diurnal
and weekly σap cycle amplitudes (60 and 40 %,
respectively), given the higher summer PBL heights in the region. The fall
weekly σap cycle (Fig. 4c) also exhibits a build-up of
absorbing aerosols from Monday to Tuesday, followed by lower aerosol loading
during the remainder of the week. This cycle is not consistent with known
weekly cycles in truck traffic or agricultural practices near the site.
Scattering coefficient exhibits a similar weekly cycle as σap
during autumn (Fig. 3c) and the weekly σap and σsp
cycle amplitudes are similar (∼ 25 %) during fall.
Similarities in the autumn weekly σap and σsp cycles could simply be the result of a smaller compensating effect on
σsp from daytime secondary aerosol production during autumn
(e.g., less photochemistry) or it could be due to sources of scattering and
absorbing aerosols that are more similar in autumn than in summer. Diesel
emissions from agricultural activity would seem more capable of contributing
to the weekly σap cycle during autumn, when PBL heights are
lower. Biomass burning is a less likely source, even though Buzcu-Guven et
al. (2007) reported a significant biomass-burning influence on OM mass
(38 %) at BND. Absorption Ångström exponent demonstrates minimal
day of week variability during autumn (Fig. S15) and αap values of 1.1–1.2 are not statistically different from the theoretical
value of 1 for BC (Bergstrom et al., 2002).
Pollution rose diagrams of PM1 σsp and σap for individual seasons at EGB over the 2010–2013 period. The
percentages at a given radius represent the percentage of hourly profiles
for a given wind sector.
Temporal variability at EGB
Annual PM1 σsp and σap cycles at EGB (Fig. 2a
and b) are influenced by more polluted southerly air masses
(120–240∘ wind directions) during all
seasons, along with comparable contributions from less
anthropogenically perturbed W/NW wind sectors during summer months (Fig. 7).
Liggio et al. (2010) reported that S/SE wind directions were generally
associated with transport from the greater Toronto area and that SW wind
directions were often associated with more aged aerosol transported from the
Ohio River valley region or other urban areas. Wind speeds are lower in
May–October and polluted air masses from the south are typically associated
with stagnant air masses ahead of fronts (Yang et al., 2011).
Scattering coefficient is elevated for all wind sectors during summer (Fig. 7a). Warm-season aerosol chemistry at EGB is influenced by
temperature-dependent biogenic SOA from forests to the north (Leaitch et
al., 2011; Slowik et al., 2010) and by photo-oxidation of anthropogenic
pollutants from the south (Chan et al., 2010; Liggio et al., 2010).
Scattering coefficients exhibit larger summer increases for the less
anthropogenically perturbed wind sectors (all except 120–240∘ wind directions) than for the southerly wind sectors
(Fig. 7a). Monthly median σsp for the southerly wind sectors
are ∼ 1.5 times higher in summer than in spring and autumn,
with larger summer σsp increases (factor of 2–5) for the other
wind sectors (unpublished result). The largest summer σsp
increases are for NW wind sectors (Fig. 7a). In addition to biogenic SOA,
the NW wind sectors are influenced in summer by regional tourist traffic and
by episodic long-range transport of smoke during peak fire season in
northwest Canada. However, it is not possible to distinguish the effects of
aged smoke from biogenic SOA from forests, based on the available aerosol
optical measurements during the 2010–2013 period at EGB. The secondary
σsp peak in winter is influenced by higher σsp
associated with air masses from the S/SW (Fig. 7a), relative to spring and
autumn. Winter σsp for wind directions 150–240∘ is ∼ 2 times higher than σsp from other wind sectors (not shown). Single-scattering albedo is
also highest for the 150–240∘ wind sectors
in winter, with values often 0.95 or above (Fig. S20a). Rupakheti et al. (2007) reported episodic high nitrate concentrations associated with air
masses transported from urban areas south of EGB, mostly occurring during
cold, humid conditions. Scattering coefficient does not exhibit a noticeable
increase with decreasing winter temperatures at EGB during the 2010–2013
period (Fig. S5). Meteorology likely plays a role in the elevated winter
σsp, as PBL heights in the region are lowest in winter at EGB
(Horzworth, 1964).
The annual σap cycle (Fig. 2b) is qualitatively similar to
annual EC mass concentration cycles reported for EGB (Yang et al., 2011) and
for rural IMPROVE sites in the Great Lakes region (Spak and Holloway, 2009).
Yang et al. (2011) reported mean EC concentrations (in units of µg m-3) at EGB of 0.83 for summer, 0.71 for fall, 0.49 for winter, and
0.36 for spring. Spak and Holloway (2009) reported highest regional EC mass
concentrations in summer and lowest in winter, with the June EC maxima
∼ 2.2 times higher than the February EC minima. Our reported
summer σap maxima in August is 2–2.5 times larger than the
broad November–April minima (Fig. 2b).
Urban-influenced SE/S wind sectors are associated with highest
σap and lowest ω0 for all seasons (Figs. 7b and
S20a). Chan et al. (2010) attributed higher σap, higher EC
concentrations, and lower OC / EC ratios in air masses arriving at EGB from
the south to diesel emissions. Absorption coefficients are lowest in winter
for all wind sectors and are largest for southerly wind sectors during
summer and autumn (Fig. 7b), with monthly median σap
∼ 1.5 times higher in summer/autumn than in spring for these
wind sectors. Much larger summer σap increases (factors of
∼ 3–7) are seen for westerly and northwesterly wind sectors
(wind directions ∼ 240–360∘). Episodic long-distance NW transport during the Canadian wildfire season
may contribute to summer σap, but local/regional tourism traffic
is more consistent with the observed summer weekly and diurnal σap cycles.
Weekly and diurnal σap cycles at EGB are significant in summer,
marginally significant in autumn, and insignificant in winter and spring
(Fig. 4e and f). Summer and autumn diurnal σap cycle
amplitudes are ∼ 50 % and summer and autumn weakly σap cycle amplitudes are ∼ 40 %. The diurnal and weekly
cycles in σap during summer and autumn at EGB are more
complicated than those at the other sites and are likely influenced to
varying degrees by several sources, including (1) high volume of regional
traffic during summer, largest on weekends; (2) transport of
urban-influenced aerosol from the south; (3) diurnal PBL height evolution;
and (4) local commuter traffic. Diurnal σap cycles for
individual days of the week reveal morning commuter peaks from Monday to Friday
(unpublished result). Daytime σap decreases due to lifting of
the PBL height are dampened on each of these days by a large source of
absorbing aerosol. Larger summer increases in σap for westerly
wind sectors suggests a source in addition to transport from the south. The
large additional source is likely regional tourism traffic. Differences
between post-dusk and pre-dawn σap are small on Monday–Thursday
(not shown) but are much larger on Friday (∼ 1 Mm-1) and
Saturday (∼ 2 Mm-1) due to high volumes of weekend
traffic. Post-dusk σap on Sunday is ∼ 3 Mm-1 lower than pre-dawn σap. The composite effect of
these sources is the weekend σap maxima and Monday minima
during summer (Fig. 4e). The weekend σap increase gives rise to
a small decrease (0.02 to 0.03) in ω0 and a small increase
(∼ 2 W m-2 AOD-1) in DRFE (Figs. S12, S13)
Diurnal σsp cycles for individual days of the week during
summer reveal some of the same features as σap (unpublished
result) but are further complicated by an additional large source of daytime
scattering aerosol, likely photochemical production and transport of SOA.
The autumn diurnal σap cycle (Fig. 4e) appears to be more
influenced by frequent transport from the south (Fig. 7b), along with less
regional traffic than during summer. Monthly averaged σap
during September–October (Fig. 2b) remains near summer levels (except for
August), but σap is much lower for all wind sectors except the
urban-influenced southerly wind sectors, for which σap was
similar in value to summer (Fig. 7b). The diurnal σap and
σsp cycles exhibit very little structure during fall so lower
fall PBL heights may be partially offset by lower production of scattering
and absorbing aerosol and/or more efficient removal mechanisms. Some
additional source may be responsible for the early week increase in σap, similar to that observed during autumn at BND (Fig. 4c). The
source of absorbing aerosol persists throughout the day and into the evening
(not shown) and may be local agricultural activities.
Temporal variability at SGP
PM1 particles contribute ∼ 66 % (78 %) to the summer
(winter) PM10 σsp and ∼ 85 % to both summer and
winter PM10 σap at SGP (Figs. 2c and S8c). The annual PM1 and
PM10 σap and σsp cycles are similar (Figs. 2a
and S8a) so the PM1 AOP cycles at SGP are representative of the PM10
aerosol. The annual PM1 σap cycle (Fig. 2b) demonstrates good
overall agreement with the annual PM10 σap cycle reported by
D&O2002 for 1997–2000, with the exception that their winter σap minima extends from November to February, while our σap
minima extends from January to February. The annual PM1 σsp cycle
during 2010–2013 (Fig. 2a) also agrees well with that reported by D&O2002
for most non-winter months. D&O2002 reported a broad summer maxima, with
monthly median σsp values lying ∼ 30–40 % above
spring and autumn months. Our σsp cycle during non-winter
months differs only by a larger summer-to-autumn σsp decrease
of close to factor of 2. Agreement is worse for winter months. Both
D&O2002 and Sheridan et al. (2001) reported minimum σsp in
December and maximum in February, with median February σsp a
factor of ∼ 4 higher than December. Box plots of
monthly binned σsp for individual 2010–2013 years (Fig. S4)
show that median February σsp at SGP varies by up to a factor
of 4 for different years, with somewhat smaller differences between
individual January months (factor of ∼ 2) and between
individual March months (factor of ∼ 2–3). Much of the
inter-annual variability is smoothed out in the monthly binned σsp box plot for the entire period (Fig. S3), giving rise to relatively
constant monthly mean σsp during winter for the current period
(Fig. 2a). Lower December σsp and much higher February σsp occurred during the period reported by D&O2002 and Sheridan et
al. (2001), compared to the period reported here.
Pollution rose diagrams of PM1 σsp and σap for individual seasons at SGP over the 2010–2013 period. The
percentages at a given radius represent the percentage of hourly profiles
for a given wind sector.
Pollution transport from the S/SE impacts PM1 σap and σsp throughout the year (Fig. 8). Wind directions are primarily from
the S/SE for non-winter months (especially summer). Air mass
back-trajectories show that air masses arriving at SGP from the S/SE often
travel over or near large regional populations centers, including Oklahoma
City, Tulsa, and (in summer) Dallas/Fort Worth (Parworth et al., 2015).
Single-scattering albedo is generally lower for S/SE wind sectors than for
the less anthropogenically influenced westerly and northerly wind sectors,
except during summer (Fig. S22a). A large fraction of non-refractory PM1
aerosol mass (∼ 70 %) is aged SOA during April–October
(Parworth et al., 2015). Many SE trajectories pass over regions of high
summer isoprene emissions (Parworth et al., 2015), but the
temperature dependence of σsp (Figs. S5 and S7) is less than
for the sites with known biogenic SOA influence (EGB and APP). Absorption
Ångström exponent values close to 1 for all seasons (Fig. 2h)
suggest that despite high organic composition, light-absorbing OC exerts a
minimal influence on the annual σap cycle and that most of
the absorbing aerosol is BC. Daily averages of αap can have
values that extend to as high as 2.5 (unpublished result), which is
consistent with observed plumes of biomass-burning aerosol reported by
Parworth et al. (2015). Other than lower σsp during autumn,
σsp and σap for the S/SE wind sectors do not
demonstrate much seasonality (Fig. 8). The lack of seasonal variability in
mean σap and σsp during non-winter months
(relative to the other sites) may be due to a longer distance from the
population centers (increased aerosol dispersion) and higher PBL heights at
SGP during spring, summer, and autumn. Removal processes may also be more
efficient in late spring and summer, when monthly averaged rainfall at SGP
is highest.
The frequency of episodic transport of ammonium nitrate to SGP likely exerts
some influence on winter σsp and its variability. Parworth et
al. (2015) reported that ammonium nitrate comprised approximately half of
the non-refractory PM1 mass at SGP during the 2010–2011 and 2011–2012
winters and early springs (e.g., March) (their Figs. 2 and 6). Ammonia and
NOx concentrations near SGP are relatively small and high nitrate
episodes (mass concentrations > 3 µg m-3) were nearly
always associated with temperatures < 3 ∘C and long-distance
transport from agricultural states in the central Great Plains region.
Colder temperatures and more frequent long-distance transport passing over
these states likely contributed to nearly a factor of 2 higher average
ammonium nitrate concentrations during the 2010–2011 winter than the
2011–2012 winter (Parworth et al., 2015). Average OA concentrations were
similar between the two winters so variability in ammonium nitrate likely
exerted an influence on the ∼ 50 % higher average PM1 mass
concentration during the 2010–2011 winter. Lower relative humidity during
the 2010–2011 winter indicates that less wet deposition could also have
contributed to higher PM1 aerosol mass during that winter (Parworth et al.,
2015). The frequency of episodically transported biomass-burning aerosol
also influences σsp and σsp at SGP. Biomass-burning aerosol is most prevalent in the spring, when prescribed crop
burning in preparation of planting is more common. Parworth et.al. (2015)
reported a much larger biomass-burning aerosol influence in spring 2011 than
spring 2012, primarily in March–April. Differences are observed in the mean
σsp and σap between the two springs, in addition
to differences in the 50th, 75th, and 95th percentiles
between the two springs (Fig. S4). Differences between the 2 years are
more noticeable for σap than for σsp.
Diurnal σap cycle amplitudes (Fig. 4h) are near 40 % for all
seasons except spring (25 %). Only the summer and autumn cycles are
statistically significant. Diurnal PBL height effects are clearly visible in
the diurnal σap cycles (Fig. 4h), as is a lack of commuter
influence. Similar to BND, there is no local commuter traffic that would be
expected to influence AOP cycles at SGP. No obvious features are seen in the
individual day of week σap cycles (unpublished result) to
indicate a possible role of interstate traffic or agricultural influences in
the weekly or diurnal σap cycles (Fig. 4g, h). This is
complicated by biased SGP σap observations during the weekends.
The diurnal σsp cycle is insignificant for all seasons (Fig. 3h), which may reflect increased daytime photochemical processing that is
somewhat less in the winter months. Larger mid-day decreases in σap than σsp lead to increases in ω0 of
∼ 0.03. The hemispheric backscatter fraction varies negligibly
during the day. The midday increase in ω0 leads to more
negative midday DRFE, by ∼ 3 W m-2 AOD-1 in all
and 2 W m-2 AOD-1 in summer. The aerosol parameters related to
size show contrasting trends. No visible diurnal or weekly trend is apparent
in b while αsp shows a decline with larger aerosol in the early
evening. The trend in declining afternoon αsp values starts
earlier in the day during the winter and is weakest during the summer and
spring.
Regional variability of aerosol optical properties
Regional differences in some annually averaged AOPs (Fig. 2; Table S5) are
unbiased by single months or seasons. PM1 σsp is highest at BND
and lowest at EGB, with annual-mean σsp 70 % higher at BND
than at EGB (Fig. 2a). The regional differences in σsp reflect
the fact that the upper midwestern US is more anthropogenically influenced
than the other three regions, with more large population centers, high
concentrations of coal-burning power plants, higher volumes of traffic, and
more agricultural activity. Spak and Holloway (2009) concluded that “PM2.5 is a year-round air quality problem in the upper midwestern
US and southern Canada, driven by nitrate in the winter, sulfate in the summer, and ammonium, OA, EC, and other components year-round”. The
largest winter σsp peak at BND may be due to higher levels of
regional ammonium nitrate precursors and cold, humid winter conditions
favorable for ammonium nitrate production in the upper midwestern US, where
winter ammonium nitrate concentrations are higher than almost all other
regions in the US (Hand et al., 2012b). The annual σsp cycle at
APP (Fig. 2a) is driven almost completely by the seasonality of regional SOA
and sulfate production (Goldstein et al., 2009; Hidy et al., 2014) due to
the lack of urban influence on AOPs at APP. Both SGP and EGB are located
downwind at times from large urban centers, but both sites receive only a
small anthropogenic contribution from all but southerly wind sectors. More
frequent polluted air masses from the south may be the reason for higher
σsp at SGP than at EGB for all but summer months (Figs. 7a
and 8a).
PM1 aerosol contributes a larger fraction to PM10 σsp and
σap at APP than at BND and SGP, as evidenced by higher Rsp
(Fig. 2c) and higher Rap (Fig. S8c). Both Rsp and Rap are the
highest at APP for all months. The regional differences in Rsp are
significant for all months (Fig. 2c). Differences in Rap between APP
and BND are only significant for November–March (Fig. S8c). The regional
differences in Rsp and Rap are likely due to a larger influence
of soil dust to PM10 AOPs at SGP and BND. Sea salt concentrations are
minimal in all three regions, and soil dust concentrations are higher in the
agriculturally influenced midwestern US and southern Great Plains than in
the Appalachian mountain region (Hand et al., 2012b). Given the higher
density of forests near EGB than near BND and SGP, it is likely that
Rsp and Rap would be higher at EGB (if measured there) than at
SGP and BND. A larger regional agricultural influence near EGB than near APP
may give rise to Rsp and Rap that are slightly lower than those at
APP. Other indicators of aerosol size distribution (PM1 b and PM10 αsp) also follow similar seasonal cycles at BND and SGP (Fig. 2d and
g). One notable difference is lower αsp at SGP (by
∼ 0.3) for nearly all months. Similar Rsp and b values
but different αsp could be indicative of differences in the
larger part of the accumulation mode (particle diameters close to 1 µm). APP and EGB have very similar b values for warm-season months
(May–October), which is likely due to large biogenic SOA influences during
the warm season in both regions (Goldstein et al., 2009; Link et al., 2015;
Leaitch et al., 2011; Slowik et al., 2010). The highest annually averaged
b at APP amongst the sites (Fig. 2d) is influenced by cold-season months
(November–April). EGB is influenced by large, highly scattering PM1
particles from the south during winter months (Fig. S20). Winter PM1 aerosol
at APP is largely regional SOA and sulfate, with some influence from
biomass-burning aerosol (Supplement to Link et al., 2015).
Higher b at APP during winter and the surrounding months could be due to
less particle growth (photochemistry).
The differences between annually averaged σap among the sites
is insignificant (Fig. 2b), based on σap precision measurement
uncertainties (Table 3). Differences in monthly mean σap among
the sites are insignificant for most months. The only exceptions are that (1) EGB
σap is lower than APP in April and lower than APP and BND in
November and (2) that SGP σap is lower than BND in August. The annual
σap cycle amplitudes are larger at BND and EGB than at APP and
SGP. Larger σap increases during summer and the surrounding
months at BND and EGB are consistent with higher levels of regional traffic
during these months. The smaller annual σap cycle amplitudes at
APP and SGP may be influenced by their further proximity from large urban
centers. Biomass-burning aerosols also influence σap to some
degree at APP during winter (Supplement to Link et al., 2015)
and at SGP during winter and spring (Parworth et al., 2015) and may also
dampen the σap cycles at APP and SGP. Absorption
Ångström exponents (Fig. 2h) support the assertion that biomass-burning aerosol may influence winter monthly mean σap at APP in
November–February (Cazorla et al., 2013). Monthly mean αap,
however, is not significantly greater than 1 during any other months at SGP,
BND, and APP, given the αap measurement precision uncertainty
(Table 3).
Time series of monthly averaged PM1 σsp, Rsp,
and b at 550 nm for BND (1996–2013) and SGP (1997–2013). Trend lines,
representing least-squared fits of the data, are also shown.
Annually averaged PM1 ω0 and DRFE are statistically similar for
APP, BND, and SGP. Lower annually averaged ω0 (Fig. 2e) and
higher (less-negative) annually averaged DRFE (Fig. 2f) at EGB are
marginally significant (at 95 % confidence), and these differences are
heavily biased by September and October. The simple use of annually averaged
values to discuss regional ω0 variability (Fig. 2e) is a bit
misleading, given the large seasonal ω0 variability at BND and
EGB (and to a lesser degree-APP and SGP). Monthly averaged ω0
at EGB is close to 0.10 lower than that at APP and SGP during
September–October and is also 0.08 lower than annually averaged ω0 at EGB. Single-scattering albedo differences between APP and BND are
nearly this large in winter, despite the fact that annually averaged
ω0 is statistically indistinguishable at the two sites. The
regional ω0 differences are at least as large as reported
ω0 differences among BND, SGP, and two North American coastal
sites – Barrow, Alaska and Sable Island, Nova Scotia (D&O2002). In spite
of the high seasonality in ω0 and b, the co-variation of these
two intensive properties lead to insignificant annual DRFE cycles at APP and
SGP. Larger DRFE cycle amplitudes are observed at EGB (∼ 9 W m-2 AOD-1) and BND (∼ 6 W m-2 AOD-1),
with September–October DRFE maxima (least negative DRFE) at both sites
(Fig. 2f).
Mann–Kendall slopes (%/decade) and trend significance∗ for
long-term trends in several PM10 and PM1 aerosol optical properties measured
at BND and SGP. Monthly averaged data are used for the calculations. BND data
for the time period 1996–2013 are used; SGP data for the time period
1997–2013 are used. Trends that are significant at or above the p < 0.05 level are in bold.
BND slope (%/10 yr), significance
SGP Slope (%/10 yr), significance
σsp,10
-16.3,p<0.01
-19.6,p<0.001
σsp,1
-23.1,p<0.001
-24.0,p<0.001
σap,10
-15.2, not significant
N/A
σap,1
-10.5, p < 0.1
N/A
αsp,10
1.9, not significant
-5.3,p<0.05
b10
7.6,p<0.001
11.2,p<0.001
b1
11.8,p<0.001
15.1,p<0.001
Rsp
-8.1,p<0.001
-9.1,p<0.001
ω0,10
-0.5, not significant
N/A
ω0,1
-1.55,p<0.01
N/A
∗ Slopes and significance were obtained using the function “TheilSen” in
the R package “openair” (Carslaw and Ropkins, 2012, Carslaw, 2015). Data were
de-seasonalized and autocorrelation was accounted for using options supplied
with the TheilSen function. Decadal slopes (%/10 year) were calculated by
multiplying the yearly slope by 10, i.e., 10 × %/year.
Long-term aerosol optical property trends at BND and SGP
Trends in AOPs are calculated for the PM10 and PM1 size cuts at BND and SGP.
In general, the sign of the AOP trends are the same for both size cuts,
although the magnitudes of the trends differ. With the exception of αsp, where the PM10 value is more meaningful, we focus on the PM1 AOP
trends for consistency with the rest of the paper. Statistically significant
trends in PM1 σsp (decreasing), Rsp (decreasing), and PM1
b (increasing) are found at BND from 1996 to 2013 and at SGP from 1997 to 2013
(Table 4). Visual examination of Fig. 9 reveals that the trends in these
AOPs since ∼ 2009 are somewhat more pronounced than in earlier
years, pointing out the pitfalls associated with trend analysis on
short-term time series. Additionally, there is a statistically significant
decreasing trend in PM10 αsp at SGP (Table 4; Fig. S24); the
BND trend in σap is negative but not statistically significant.
BND also demonstrates a slight, but statistically significant negative trend
in ω0 (Table 4; Fig. S25). The significant decrease in σsp at both sites is consistent with other studies (CC2013; Hand et
al., 2014) that reported large decreases in near-surface aerosol light
scattering and light extinction coefficients in North America during the
past decade. The concurrent decreasing trend in Rsp implies that
scattering by PM1 is decreasing at a faster rate than scattering by
super-1 µm particles (which may or may not be decreasing) at both BND
and SGP. One possible source for reductions in PM1 σsp at BND
and SGP could be decreasing SO2 emissions by regional power plants.
Annual US SO2 emissions from power plants decreased at a rate of
∼ 6 % per year from 2001 to 2010, with similar reductions in
sulfate concentrations at rural US sites (Hand et al., 2012a).
CC2013, performed trend analyses on σsp, σap,
αsp, and b at BND and SGP as part of a larger study looking at
long term changes in in situ aerosol properties measured around the globe.
There are several key differences between our analysis and that of CC2013 so
the magnitudes of the trends should not be directly compared, but the signs
of the trends (positive/negative) can be compared. Differences between the
two studies include the following: (1) monthly data are used in our analysis (CC2013 used
daily); (2) our trend analysis extends the data sets 3 more years past
that of CC2013; (3) we report trends for both PM10 and PM1 AOPs (CC2013 used
PM10 AOPs); and (4) we reference the percent slope to the first year value,
while CC2013 referenced their slope to the median value of the parameter for
the entire data set.
For σsp and σap, the direction (positive/negative)
of the trends in CC2013 and this study are the same. CC2013 reported larger
trends for σap and σsp than are found here, likely
due to a combination of the differences between the two analyses noted
above. One noticeable difference between CC2013 and this study is that
CC2013 found a statistically significant decrease in BND PM10 σap at the p < 0.05 level, while the decreasing trend for PM10
σap calculated here is not statistically significant. CC2013's
analysis also included b and αsp trends at BND and SGP.
Unlike the analysis performed here, they found no statistically significant
trends in either b or αsp when using the Mann–Kendall test with
Sen's slope (MK), although the signs of their MK slopes match what is
reported in Table 4 for this study. CC2013 found significant positive trends
in b at both sites and a negative trend in αsp at SGP when
they applied the generalized least square trend test with autoregressive
bootstrap confidence intervals (GLS/ARB). CC2013 hypothesized that this
discrepancy could be the result of lower sensitivity of the MK method for
trends in normally distributed data. Most intensive AOPs are closer to
normally distributed than are σsp and σap, a point
noted by C2013 and confirmed by the authors using data at the four sites
reported in our study. CC2013's trend slope in b using the GLS/ARB method
was nearly identical in magnitude (7.7 %/10 year) to our slope for BND
(Table 4), while their trend slope in b at SGP was smaller (7.8 %/10 year) than our slope. The trend slope in αsp reported by CC2013
for SGP (-4.2 % at SGP) is very similar to our trend slope (Table 4).
CC2013 did not analyze trends in ω0.
Systematic relationships among aerosol optical properties
Most systematic relationships amongst AOPs are qualitatively similar for all
seasons at each site and are suitably represented by the annual
relationships. Several of these annual relationships have also been reported
for BND and SGP by others (D&O2002; Andrews et al., 2011) and most are
similar to the relationships reported here for BND and SGP. We briefly
summarize these relationships (Sect. 4.4.1) and highlight any differences in
the BND and SGP relationships for our study period (compared to D&O2002
and Andrews et al., 2011), in addition to any differences in the
relationships at BND and SGP and those at APP and EGB, which have not been
studied. Relationships involving αap are seasonally dependent
(especially at APP) and are hence presented for individual seasons at APP,
BND, and SGP in Sect. 4.4.2.
Annual systematic relationships among AOPs
Single scattering albedo increases and b decreases with increasing σsp at all sites (Fig. 10a, b). Hemispheric backscatter fraction
demonstrates an inverse relationship with ω0 over the entire
ω0 range at EGB and for ω0 > 0.85 at
the other sites (Fig. 10c), a condition representative of all months
(Fig. 2d, e). The co-variability of ω0 and b leads to a DRFE
dependence on σsp that is statistically insignificant for all
sites, with the exception of the lowest σsp conditions at APP
(Fig. 10d). Greater influences by smaller, darker particles under
low-loading conditions and by larger, brighter particles under high-loading
conditions are seen in the annual σsp, b, and ω0
cycles for the four sites in this paper (Fig. 2a, d, and e) and have
been reported for SGP and BND by D&O2002. The tendency toward lower
ωo and higher b for low-loading conditions is consistent with
preferential removal of large, less-absorbing particles by cloud scavenging
and/or wet deposition. It can also be the result of new particle formation
with growth by condensation and/or coagulation to optically active sizes
(Andrews et al., 2011). Scattering Ångström exponent and Rsp
are both relatively insensitive to changes in σsp at APP over
the entire σsp range (Fig. 10e, f). Scattering
Ångström exponent is insensitive to changes in σsp for
all but the lowest aerosol loading levels at BND and SGP (Fig. 10e). PM1
scattering fraction shows a modest decrease with increasing σsp
for σsp > 20 Mm-1 at BND and SGP (Fig. 10f).
A similar lack of sensitivity of αsp to changes in σsp at SGP and BND was reported by D&O2002. PM1 scattering fraction
increases proportionally with αsp at APP, BND, and SGP (Fig. 10g). D&O2002 reported similar Rsp vs. αsp
relationships for SGP and BND. The fact that the Rsp vs αsp relationship is much stronger than either of their relationships
with σsp suggests that αsp is a better indicator
of the relative contributions of coarse and fine mode aerosol to PM10
σsp than an indicator of average particle size-at least for
APP, BND, and SGP. Based on the range of Rsp values measured at SGP,
BND, and APP (Fig. 2c), the aerosol size distributions are on average
bi-modal (with higher coarse mode fractions at SGP and BND than at APP) and
care must be exercised when using αsp to infer average particle
size or aerosol type. The Rsp vs αsp relationship (Fig. 10g) is consistent with decreasing trends in both Rsp and αsp at SGP (Table 4) but seems inconsistent with the lack of change in
αsp at BND, despite reductions in Rsp similar in
magnitude to those at SGP.
Systematic relationships among mean AOPs over full annual cycles
of the 2010–2013 period at APP, BND, EGB, and SGP: (a) PM1 ω0
vs. PM1 σsp; (b) PM1 b vs. PM1 σsp; (c) PM1
b vs. PM1 ω0; (d) PM1 DRFE vs. PM1 σsp;
(e) PM10 αsp vs. PM1 σsp; (f) Rsp vs. PM1
σsp ; and (g) Rsp vs. PM10
αsp.
AOPs at the rural continental sites reported here have similar relationships
(Fig. 10) as those at a majority of mountain sites reported on by Andrews et
al. (2011). Andrews et al. (2011) also reported relationships amongst AOPs
based on long-term aircraft measurements made over BND and SGP, although
their free tropospheric AOP relationships for BND and SGP only extended up
to σsp ∼ 25 Mm-1. Most of the free
troposphere AOP relationships reported for SGP (Andrews et al., 2011) are
similar to the corresponding near-surface AOP relationships (Fig. 10), but
there are some noticeable differences for BND. Andrews et al. (2011)
reported the following AOP relationships as σsp increased from
zero to 25 Mm-1 at BND: (1) b increased slightly (0.12 to 0.13); (2) ωo remained nearly constant
(less than 0.01 increase); and (3) αsp increased by a larger amount (∼ 0.12 to 0.17)
than in our study (Fig. 10e). The differences between these relationships
and those in Fig. 10a, b, and e could be due to smaller particles
that undergo less atmospheric processing (particle growth, cloud scavenging,
and deposition) in the free troposphere above BND, relative to particles
near the surface.
Seasonal relationships involving absorption Ångström
exponent
The relationships between αap and σsp for
individual seasons and the annual relationship are most different at APP
(Fig. 11a) and least different at BND (Fig. 11b). Absorption
Ångström exponent at APP is statistically higher than 1 (αap≥ 1.2) for all σsp bins during winter and is
statistically lower than 1 (αap≤ 0.8) for all σsp bins during summer and for higher-loading conditions (σsp≥ 50 Mm-1) during spring and autumn (Fig. 11a).
Absorption Ångström exponent at BND (Fig. 11b) and SGP (Fig. 11c) is
not statistically different from 1 for any σsp bins except for
(1) summer loading σsp≥ 30 Mm-1; and (2) spring and
autumn loading σsp≥ 80 Mm-1 (SGP only).
Relationships among αap and intensive AOPs (αsp
and ω0) can be used to identify contributions to σap by sources other than BC, such as dust, OC, and coated BC (Cazorla,
et al., 2013; Costabile et al., 2013; Gyawali et al., 2009). Absorption
Ångström exponent exhibits a systematic decrease with increasing
αsp for all seasons at SGP (Fig. 11f) and αsp
decreases in a step-wise manner for all seasons except summer at BND (Fig. 11e). The αap-αsp relationship is more
complicated at APP (Fig. 11d), where αap demonstrates a
similar decrease with increasing αsp during summer to that
observed at BND but a marginally significant increase with increasing
αsp during winter. Values of αap that are
statistically higher than 1 (αsp≥ 1.2) tend to be
associated with αsp≥ 1.5 at APP (Fig. 11d), suggesting a
mix of EC and OC (Fig. 2 of Cazorla, et al., 2013). Values of αsp≥ 1.2 at BND and SGP are most often associated with αsp < 1 (Fig. 11e, f), suggesting a mix of EC and dust
(Fig. 2 of Cazorla et al., 2013). Dust influences σap at SGP
during all seasons and also influences BND σap during autumn,
as seen by the number of data points with αsp≥ 1.2 and
αsp < 1 in Fig. 11e, f. Episodic biomass burning that
impacts SGP during spring (Parworth et al., 2015) also contributes to high
αap values, which can reach ∼ 2.5 for individual
days (unpublished result). Summer values of αap are lower than
those of other seasons for all αsp bins at BND and APP and for
all but the lowest αsp bins at SGP (where dust likely
influenced absorption). The slopes of the αap vs αsp curves indicates that αap values significantly lower
than 1 during summer coincide with higher fractions of fine-mode aerosol
(higher αsp).
Systematic relationships among mean AOPs involving PM1 absorption
Ångström exponent (αap) for individual seasons of the
2010–2013 period at APP, BND, and SGP: (a) αap vs. σsp at APP; (b) αap vs. σsp at BND;
(c) αap vs. σsp at SGP; (d) αap vs. αsp at APP; (e) αap vs. αsp at
BND; (f) αap vs. αsp at SGP; (g) αap vs. ω0 at APP; (h) αap vs. ω0 at BND; (i) αap vs. ω0 at SGP.
The annual αap–ω0 relationships for all individual
seasons are also most similar at BND (Fig. 11h) and least similar at APP
(Fig. 11g), where the summer and winter αap–ω0
relationships are noticeably different. Absorption Ångström exponent
is lowest over the entire ω0 range during summer at all sites.
All of the individual season αap–ω0 curves are
similar in that αap remains constant or slightly increasing
with increasing ω0 until ω0 approaches 0.90
(specifically the ω0 bin centered at 0.875). This is followed
by sharp decreases in αap with further increases in ω0. Absorption Ångström exponents significantly less than 1
(αap≤ 0.8) during summer months coincide with ω0≥ 0.85 at APP, ω0≥ 0.90 at BND, and ω0≥ 0.95 at SGP. Absorption Ångström exponent at APP is
also significantly less than 1 for ω0≥ 0.95 during
autumn. From the b vs. ω0 relationships (Fig. 10c), the lower
mean αap values at all sites during summer also coincide with
lower mean b values. When combined, these relationships indicate that lower
αap values are associated with larger, less-absorbing,
fine-mode particles. Gyawali et al. (2009) reported a similar αap–ω0 relationship for summer months with no biomass-burning influence in Reno, NV. Single-scattering albedo was near constant
(αap∼ 1.1–1.2) up to ω0∼ 0.90, followed by αap values mostly below one
for higher ω0. Gyawali et al. (2009) attributed this wavelength
dependence of absorption to EC particles coated with non-absorbing organic
and inorganic matter. It should be noted that Gyawali et al. (2009) used a
photo-acoustic spectrometer, as compared to the filter-based techniques that
are employed at the sites in this study. Gyawali et al. (2009) also used
different wavelengths (405 and 870 nm) so the results are not directly
comparable. The summer values of αap at APP are also much lower
for all ω0 than those reported by Gyawali et al. (2009).
Possible biases in filter-based absorption measurements made in high-OA
environments could in principle contribute to this result (e.g., Lack et
al., 2008, 2009). A detailed analysis of the effects, both real
and artifact, of absorbing and non-absorbing coatings on the
wavelength dependence of light absorption by black carbon is beyond the
scope of this paper.