A new technique was used to directly measure O3 response to changes in
precursor NOx and volatile organic compound (VOC) concentrations in the atmosphere using three
identical Teflon smog chambers equipped with UV lights. One chamber
served as the baseline measurement for O3 formation, one chamber added
NOx, and one chamber added surrogate VOCs (ethylene, m-xylene,
n-hexane). Comparing the O3 formation between chambers over a
3-hour UV cycle provides a direct measurement of O3 sensitivity to
precursor concentrations. Measurements made with this system at Sacramento,
California, between April–December 2020 revealed that the
atmospheric chemical regime followed a seasonal cycle. O3 formation was
VOC-limited (NOx-rich) during the early spring, transitioned to
NOx-limited during the summer due to increased concentrations of
ambient VOCs with high O3 formation potential, and then returned to
VOC-limited (NOx-rich) during the fall season as the concentrations of
ambient VOCs decreased and NOx increased. This seasonal pattern of
O3 sensitivity is consistent with the cycle of biogenic emissions in
California. The direct chamber O3 sensitivity measurements matched
semi-direct measurements of HCHO/NO2 ratios from the TROPOspheric
Monitoring Instrument (TROPOMI) aboard the Sentinel-5 Precursor (Sentinel-5P) satellite. Furthermore, the satellite observations showed that
the same seasonal cycle in O3 sensitivity occurred over most of the
entire state of California, with only the urban cores of the very large
cities remaining VOC-limited across all seasons. The O3-nonattainment
days (MDA8 O3>70 ppb) have O3 sensitivity in the
NOx-limited regime, suggesting that a NOx emissions control
strategy would be most effective at reducing these peak O3
concentrations. In contrast, a large portion of the days with MDA8 O3
concentrations below 55 ppb were in the VOC-limited regime, suggesting that
an emissions control strategy focusing on NOx reduction would increase
O3 concentrations. This challenging situation suggests that emissions
control programs that focus on NOx reductions will immediately lower
peak O3 concentrations but slightly increase intermediate O3
concentrations until NOx levels fall far enough to re-enter the
NOx-limited regime. The spatial pattern of increasing and decreasing
O3 concentrations in response to a NOx emissions control strategy
should be carefully mapped in order to fully understand the public health
implications.
Introduction
Ground-level ozone (O3) is an oxidant that inflames airways and damages
tissue in the respiratory tract, leading to increased coughing, wheezing,
shortness of breath, and other asthmatic symptoms (US EPA,
2020b). Maximum daily average 8 h (MDA8) O3 concentrations designed
to protect public health are codified in the National Ambient Air Quality
Standards (NAAQS) (US EPA, 2021) and the California Ambient Air
Quality Standards (CAAQS) (California Air Resources Board,
2007). Seven of the 10 cities across the United States with the highest
O3 concentrations are located in California (American Lung
Association, 2020), making O3 pollution a continued public health
threat for millions of California residents more than four decades after
O3 abatement efforts began.
O3 levels are often described by the maximum daily average 8 h
concentration. The annual fourth-highest MDA8 O3 concentration averaged
over 3 years has special regulatory significance. This design value
determines whether the region containing the monitor complies with the
O3 NAAQS. O3 design values in California decreased steadily
between the years 1980 and 2019 (Fig. 1) due to
the success of emissions control programs that reduced concentrations of
precursors broadly divided into two groups: oxides of nitrogen (NOx)
and volatile organic compounds (VOCs) (Parrish et al., 2016; Simon et
al., 2015). Continued progress after the year 2010 has been slower, and
O3 design values even increased in some air basins between the years
2015–2018 (Fig. 1). Multiple factors have been proposed to explain the
lack of further reductions in O3 concentrations in recent years. These
potential factors include (i) growing importance of precursor VOC emissions
not previously accounted for in the planning process as major sources such
as transportation have been controlled (McDonald
et al., 2018; Shah et al., 2020), (ii) an imbalance in the historical degree
of NOx and VOC reductions (Cox
et al., 2013; Parrish et al., 2016; Pollack et al., 2013a; Steiner et al.,
2006), or (iii) more frequent heat waves (Jacob
and Winner, 2009; Jing et al., 2017; Pusede et al., 2015; Rasmussen et al.,
2013; Weaver et al., 2009) and wildfires (Jaffe
et al., 2013; Lindaas et al., 2017; Lu et al., 2016; Singh et al., 2012) as
a consequence of climate change. All these theories are supported to varying
degrees by indirect measurements or model predictions, but there is an
absence of strong direct evidence that identifies dominant factors
contributing to the increased O3 concentrations. The uncertainty that
lingers over the recent O3 trends suggests that fresh approaches are
needed to directly verify the optimum emissions control path.
The 8 h O3 design value in five air basins in California from
1980 to 2019. The dash line is the 2015 8 h O3 NAAQS (=70 ppb). The five air
basins include the Sacramento Valley (SAC), San Francisco Bay Area (Bay), San
Joaquin Valley (SJV), South Coast Air Basin (SoCAB), and San Diego County (SD).
Data collected from the California Air Resources Board (https://www.arb.ca.gov/adam, last access: 9 June 2021).
O3 formation has been studied for decades in California, using both
measurements and model simulations (Kroll et al.,
2020). These past studies provide important background information about the
effects of precursor NOx and VOC species and help build the foundation
for new studies. Statistical analyses of long-term surface measurements have
determined that lower NOx concentrations are associated with higher
O3 concentrations on weekends (Pollack
et al., 2012; Pusede and Cohen, 2012) and higher temperatures are associated
with increased VOC emissions and chemical reaction rates, leading to higher
O3 concentrations during warm stagnation events (Lafranchi et al.,
2011; Nussbaumer and Cohen, 2020). These long-term studies suggest that VOCs
are the limiting precursor for O3 formation in the center of large
cities, while NOx is the limiting precursor in downwind areas (Lafranchi
et al., 2011; Pusede and Cohen, 2012). Neither long-term analysis method
clearly explains the recent trend of increasing O3 concentrations in
Los Angeles.
O3 sensitivity has also been analyzed over shorter timescales using
ratios of photochemical indicator species including
H2O2/HNO3 and HCHO/NO2 (Sillman, 1995;
Tonnesen and Dennis, 2000). Satellite retrievals of HCHO/NO2 from the
Global Ozone Monitoring Experiment (GOME), the SCanning Imaging Absorption
spectroMeter for Atmospheric CHartograpHY (SCIAMACHY), the Ozone Monitoring
Instrument (OMI), and the TROPOspheric Monitoring Instrument (TROPOMI) have
extended these O3 sensitivity calculations over broad geographical
regions (Chossière
et al., 2021; Duncan et al., 2010; Jin et al., 2017; Martin et al., 2004;
Schroeder et al., 2017a). The short-term measurements generally support the
findings from the long-term studies but once again fail to identify the
dominant factor(s) driving the recent increase in O3 design values.
Reactive chemical transport models (CTMs) have been used extensively to
predict the effectiveness of candidate emissions control programs (Brown,
2018; California Air Resources Board, 2018; Meng et al., 1997; Sillman,
1999), and so one might expect that they would provide the most detailed
explanation for recent O3 trends. Models are necessarily incomplete
approximations to highly complex real-world systems, and so they are often
incapable of predicting subtle features in pollutant trends. No model
calculation has been able to reproduce the observed increase in O3
design values (Parrish
et al., 2017). It is unclear whether this failure stems from a lack of
accurate emissions trends, an incomplete description of atmospheric
chemistry, or an incomplete representation of the effects of shifting
climate on O3 formation mechanisms.
Recent advances in measurement techniques provide new tools to study O3
sensitivity directly. Mobile smog chambers bridge the gap between laboratory
studies and the real atmosphere. Past studies have designed mobile smog
chambers to measure the aging of secondary pollutants (i.e., O3, SOA)
from certain emission sources (Howard
et al., 2008, 2010b; Li et al., 2019; Platt et al., 2013; Presto et al.,
2011). It is difficult to evaluate sensitivity of secondary pollutants
formed from multiple sources using a single smog chamber. Recently, a mobile
dual-smog-chamber system has been used to directly measure the SOA formation
in ambient air (Jorga et
al., 2020; Kaltsonoudis et al., 2019). The design used in the current study
consists of three chambers that can simultaneously measure the non-linear
response of O3 formation to NOx and VOC perturbations. The
automated valve and sampling incorporated into this design also allows
long-term remote field measurements to evaluate the seasonal trends in
O3 sensitivity. At the same time, the satellite TROPOMI launched by the European Space Agency (ESA) in October
2017 provides measurements of HCHO and NO2 tropospheric vertical column
densities (TVCDs) with 3.5 km × 5.5 km spatial resolution that can
start to resolve O3 perturbations around major sources such as
wildfires (Ialongo
et al., 2020; Veefkind et al., 2012; Vigouroux et al., 2020b). The purpose
of this study is to combine these two new measurement techniques into a
detailed analysis of O3 sensitivity to precursor NOx and VOC
emissions spanning an entire spring–summer–fall cycle in California. Daily
measurements from smog chamber perturbation experiments are analyzed for
short-term trends (day of week) and long-term trends (seasonal variation) to
reveal the effects of traffic, natural vegetation, and wildfires. The direct
O3 sensitivity measurements are then combined with TROPOMI
HCHO/NO2 ratios to extend our understanding of the O3 sensitivity
across the entire state of California.
MethodsGround-based measurement
Three identical transportable smog chambers were used to directly measure
base case O3 concentration and O3 sensitivity to precursor NOx
and VOC. Each chamber was constructed from fluorinated ethylene propylene (FEP) with a volume of 1 m3 housed in an enclosure measuring 2.13 m H× 1.22 m L× 1.22 m W. UV lamp panels were placed on the floor and the roof of
the chamber support frame. Each panel can hold up to six UV lamps (Sylvania,
F40BL 40W T12) that emit at wavelengths between 280–400 nm. The lamp panels
were configured to produce 50 W m-2 to replicate the mid-day
photochemistry in California during the summer. The enclosure walls were
constructed from polished aluminum with total reflectivity of
∼95 %. Figure S1 in the Supplement represents the
cross-sectional view of the transportable smog chamber system.
One cubic meter of ambient air was injected into the FEP chambers at the
start of an experiment using a Teflon diaphragm pump (model DOA-V751-FB, Gas
Manufacturing, Benton Harbor, MI, USA) operating at a flow rate of 10 L min-1 for each chamber. Solenoid valves were configured to
inject perturbation gases NOx (8 ppb NO2) and VOC surrogates (4.4 ppb ethylene, 2.8 ppb n-hexane, and 0.8 ppb m-xylene) respectively into
chambers no. 1 and no. 3 for comparison to base case chamber no. 2.
Perturbation gases were added halfway through the chamber filling operation
so that they would be thoroughly mixed with the ambient air during the
remainder of the chamber filling process. The composition of the VOC
perturbation was based on the VOC mixture used to determine ozone formation
potential (Carter et al., 1995). The magnitude of the
perturbations was selected to be as small as possible while still generating
an observable change in monitored ozone concentrations. A single set of
monitors sequentially measured concentrations within each chamber to
increase the precision of the inter-chamber comparisons. The current
experiment includes measurements of NOx (model nCLD-855-Yh, Eco
Physics, Dürnten, Switzerland), NOy (sum of all oxidized atmospheric
odd-nitrogen species) (model 42i, Thermo Fisher, Franklin, MA, USA), O3 (model 205, 2B technology, Boulder, CO, USA), and temperature–relative
humidity sensor (model RH-USB, Omega Engineering, Norwalk, CT, USA). The
total sample flow rate for all monitors was approximately 3 L min-1. Seven
measurements with a duration of 10 min were made from each chamber, resulting
in a total sample volume of 210 L air, or approximately 21 % of the
chamber volume (leaving 79 % of the total air in the chamber). The shape
of the chambers was not greatly distorted at any point during the
experiment. Chambers were drained at the conclusion of an experiment using a
rotary vane vacuum pump (model 0523-101Q-G588DX, Gast Manufacturing, Benton
Harbor, MI, USA). All chamber operations were controlled automatically using
a program written in LabVIEW that interfaced with a customized set of data
acquisition devices and solenoid valves (DAQ-SV).
The consistency of the O3 formation rates across chambers was tested in
a controlled laboratory environment prior to deployment in the field. All
three 1 m3 FEP chambers were filled with laboratory air and were
perturbed by an equal mixture of both NOx and VOC prior to 180 min of
UV exposure. Several blank tests were performed by adding zero air (AI
0.0Z-K, Praxair) into all three chambers as part of the consistency tests to
further develop confidence in the chamber measurements.
Figure S2 in the Supplement illustrates the agreement between
chamber no. 1 and no. 3 O3 measurements vs. chamber no. 2 O3
measurements during a typical QA/QC check. Uncertainty between chamber
measurements is ∼1 % across a wide range of concentrations.
The loss rate of O3 to chamber walls was determined in the dark for all
three 1 m3 FEP chambers filled with identical NOx–VOC mixtures.
Average loss rates of 5 % h-1 were calculated over the 3 h
experiments. Loss rates were identical for all chambers in the system, and so
this issue will not influence the comparisons between chambers in the
current study.
To confirm that chamber measurements represent the behavior observed in the
atmosphere, weekly-averaged O3 concentrations in the base case chamber
were compared to weekly-averaged ambient O3 concentrations measured at
the nearby monitoring station (marked in Fig. S5 in the Supplement) from April to December
2020 in Fig. S3 in the Supplement. The O3 concentrations in the base case chamber at the start of each experiment were similar to the ambient O3 concentrations,
indicating that the gas-phase chemical composition related to O3
formation was not changed while injecting ambient air into the chamber. The
O3 formation in the chamber generally reflects the O3 chemical
production from the in situ ambient air around 10:00–12:00 local time, while the ambient O3 is influenced by chemical
production, mixing, and deposition (Cazorla et al., 2012). As expected, the
initial rate of O3 formation in the chamber is therefore higher than
the initial rate of change in the ambient O3 concentrations. The
current experiment is focused on measuring the response of this chemical
production rate to changes in precursor NOx and VOC concentrations
because this most closely approximates the local effects of potential
emissions control programs.
VOC measurements are useful to help interpret O3 formation trends and
to identify the chemical regime on the NOx-VOC isopleth for O3 (Seinfeld and Pandis, 2016).
Ground-level daily VOC measurements from Photochemical Assessment Monitoring
Stations (PAMS) are only available for a limited number of summer months, and
so alternative indicator species were investigated. Baker (2008) found that non-methane
hydrocarbon (NMHC) concentrations were correlated with CO concentrations in 28 US cities during the years 1999–2005. This may reflect situations
where dominant sources that emit CO also emit large amounts of NMHC, or it
may reflect situations where relatively constant sources of CO and NMHC are
correlated because they are diluted by the same amount of atmospheric
mixing. The success of emissions control programs targeting anthropogenic
VOCs has increased the relative importance of residual biogenic VOCs in many
urban atmospheres across the United States (US EPA, 2020a). Biogenic
sources do not emit CO, but biogenic VOCs can react in the atmosphere to
produce CO (Hudman et
al., 2008). CO also acts as an indicator of atmospheric mixing that equally
affects all primary sources. In an effort to improve the ability of CO to
represent biogenic VOCs in the current study, an additional metric was
calculated by multiplying the measured CO concentrations by the enhancement factor for isoprene emissions induced by temperature
and relative humidity (Guenther et al., 1991).
Figure S4 in the Supplement shows the correlation between
measured VOC reactivity (VOCR) and CO × biogenic at Sacramento during summer
months between 2010–2019. VOCR was calculated from PAMS measurements of
VOC concentrations multiplied by their reaction rate constant with OH (Chen
et al., 2010; Kleinman, 2005; Steiner et al., 2008). VOCR and CO × biogenic
are reasonably well correlated (r=0.6, p<0.001), while VOCR
and CO were less correlated (r=0.39). This analysis supports the
preference for CO × biogenic as an approximate surrogate for VOCR in the
current study, with the understanding that real-time measurements of VOCR
would be highly preferred in future studies.
Satellite data
Tropospheric HCHO and NO2 retrievals (level 2; unit: mol m-2) over
California were obtained from the TROPOMI for February–October 2020. The
TROPOMI is aboard the Sentinel-5 Precursor (Sentinel 5-P) satellite, which
was launched by the ESA in October 2017. The polar-orbiting satellite
enables quantitative information on trace gases to be retrieved
approximately at 13:30 local sun time (ascending node) each day on a global
scale. The retrieval algorithms for TROPOMI NO2 data use the
measurements of the earth's radiance in the visible absorption wavelengths (405–465 nm) made by the hyperspectral imaging spectrometer. The
algorithms first derive the total slant column density of NO2 using a
differential optical absorption spectroscopy (DOAS) method. The total slant
column NO2 is then separated into stratospheric and tropospheric slant
column densities of NO2 while utilizing information from a data
assimilation system. Finally, the tropospheric vertical column density of
NO2 is obtained by applying conversion factors, called air mass factors (AMFs), to the tropospheric slant column density of NO2. The retrievals
of TROPOMI HCHO data apply a similar DOAS method to the ultraviolet (UV)
wavelengths (328.5–359 nm) of the solar spectrum. Further details about
the TROPOMI data are provided by Veefkind et al. (2012), Van
Geffen et al. (2020), and De
Smedt et al. (2018).
The spatial resolution of TROPOMI NO2 and HCHO TVCDs is 3.5 km × 5.5 km, which is finer than that of the predecessor OMI (13 km × 24 km). Quality assurance (QA) values were obtained alongside the
HCHO and NO2 data, and only measurements with QA values >0.50
were retained to ensure good data quality and sufficient data points when
computing monthly averages (Van Geffen et al., 2021).
Correction factors were not applied to TROPOMI data in the current study.
Verhoelst et al. (2021) and
Vigouroux et al. (2020a) analyzed the
accuracy of the TROPOMI data using ground-based measurement sites across the
globe. Measurements were not made in California, but several of the
evaluation sites had attributes similar to locations in California. Bias in
daily TROPOMI NO2 retrievals varied between -15 % and -56 % in
moderately polluted areas with NO2 column measurements between
3×1015–14×1015 molec cm-2 (typical for
moderate-sized cities in California). The bias in TROPOMI HCHO measurements
ranged between +26 % ± 5 % at low HCHO levels and -30.8 % ± 1.4 % at high HCHO levels. HCHO levels measured in Sacramento (∼0.6×1015 molec cm-2) had a bias of
approximately zero. These results suggest that TROPOMI measurements over
California almost certainly contain some amount of bias that could only be
removed through a comparison to measurements from a ground-based network.
Application of global-average bias correction factors would not change the
trends in HCHO and NO2 in time and space even if they would change the
absolute magnitude of those values. The current analysis will therefore
focus on trends in the TROPOMI measurements.
Experimental description
O3 sensitivities to precursor NOx/VOC concentrations were measured
in central Sacramento, CA (38.57∘ N, 121.49∘ W), from April–December 2020 (222 experiment days out of a total of 251 d). Sources in the vicinity
of the site include commercial office buildings, restaurants, two major
highways, freight and passenger rail lines, a shipping port, and suburban
residences (see map in Fig. S5). Grab samples of ambient air were collected between 10:00 and 12:00 local time to characterize the
daytime O3 formation rates in the presence of variable atmospheric
mixing and regional emissions. Sensitivities were based on perturbation
concentrations of approximately 8 ppb of NOx injected into chamber no. 1 and 8 ppb of VOC surrogates injected into chamber no. 3. Initial gas
concentrations were measured from the full chambers in the dark over a 30 min period (10 min for each chamber). The UV lamp panels were then
illuminated for 180 min, and the chamber concentrations were measured in a
continuous cycle of 10 min intervals over a total of seven cycles. Each
active monitoring period lasted 210 min (=30 min of dark measurements +180 min of light measurements). Measurements in different chambers are made
at different times, making it difficult to compare chamber results at the
conclusion of the experiment. It was noted that O3 concentrations
within each chamber averaged in each 10 min sampling interval increased
linearly over the 180 min period when the UV lights were on. A linear
regression model was therefore applied to extrapolate O3 concentrations
in each chamber to the end of the measurement period to facilitate direct
comparisons between the base case chamber no. 2 and perturbed chambers no. 1
and no. 3. The difference of
O3 concentration after 3 h UV exposure was calculated between chamber no. 1 and chamber no. 2 (ΔO3+NOx) and chamber no. 3 to
chamber no. 2 ΔO3+VOC to quantify
the O3 sensitivity. An example of a typical day of O3 results
analysis is shown in SI.
Chamber model description
A chamber model developed by Howard et al (2008,
2010a, b) was employed as a part of this analysis to quantify the
sensitivity of the O3 response to NOx perturbations under
different experimental configurations. The chemical reaction system used by
the chamber model is based on the SAPRC11 chemical mechanism (Carter and Heo, 2013) with wall loss rates
based on the measured value of 5 % h-1. The time integration
procedures used to solve the set of differential equations that predict
concentrations as a function of time are taken from the full University of
California Davis and California Institute of
Technology (UCD/CIT)
chemical transport model (Venecek
et al., 2018; Ying et al., 2007). Day-specific values of NO, NO2, and
O3 initial concentrations used in the chamber simulations are based on
measurements near the study location. VOC initial concentrations used in the
chamber simulations are based on UCD/CIT simulations over the study
location. The seasonal profile of the simulated VOC concentrations matches
the CO × biogenic trends illustrated in Fig. 2, but the amplitude of the
simulated seasonal trend was damped. VOC initial concentrations used in the
chamber simulations were therefore scaled to match the amplitude of the
CO × biogenic factor. Section 4.1 presents a sensitivity study on the chamber
measurement result using the chamber model described here.
Monthly concentrations of NO2(a) and
CO × biogenic/HCHO/isoprene (b) from February to December 2020.
Ground-based chamber measurements use the left axis with results shown as
box-and-whisker plots. TROPOMI measurements use the right axis and are shown
as diamonds. Isoprene from the ground monitoring station is shown as blue
triangles. The open box and points show the results after removing wildfire
days.
ResultsChamber measurement and satellite results in SacramentoMonthly variation of ambient gas concentrations
Figure 2 compares the ground-based measurements and
the TROPOMI column measurements of NOx and VOC surrogate concentrations
at the Sacramento sampling site. Good agreement is observed between the time
trends of the chamber and TROPOMI satellite remote sensing measurements.
Both techniques identify strong seasonal patterns for the concentrations of
the O3 precursors.
Figure 2a shows the monthly-averaged TROPOMI
satellite NO2 measurements and the boxplot of daily chamber NO2
measurements at Sacramento between February–December 2020. NO2
concentrations remained relatively stable between April and July and then
sharply increased in August–September possibly due to increased wildfires
in the late summer months. Enrichment of NO2 and other pollutants in
wildfire plumes has been noted in previous research (Jaffe and Wigder, 2012). The open boxes in
Fig. 2a represent days within the months of August–November that were not influenced by wildfire smoke (Anderson and Kuwayama, 2022), leading to reduced NO2
concentrations. The upward trend in NO2 concentrations in October–December 2020 is likely associated with decreased boundary layer heights
and increased fuel consumption for heating during the colder fall–winter
season. This seasonal association can also be viewed in the decreasing
TROPOMI NO2 levels measured during the warmer spring season (February–April, 2020). TROPOMI column measurements will not directly depend on
boundary layer height, but increased boundary layer heights are usually
associated with higher average boundary layer wind speeds, leading to
downwind advection and dispersion of pollutants. The effects of reduced
transportation emissions in March–April 2020 caused by COVID-19
shelter-in-place orders are notably minor in the ambient NO2
measurements. Although light-duty vehicle traffic decreased by as much as
50 % during this time period, heavy-duty truck traffic was more constant (Liu et al.,
2020; Parker et al., 2020). The ground-based measurement site is 0.8 and 1.8 km from two major freeways, but NOx concentrations at this site do not
appear to be strongly influenced by the COVID-19 reduction in light-duty
traffic activity. Increasing NOx emissions from residences and
relatively quick recovery of the heavy-duty traffic compared to the
light-duty traffic may also minimize COVID-19 effects on NOx
concentrations (Liu et al.,
2021). The seasonal pattern of NOx concentrations driven by wildfires,
reduced boundary layer height, and increased residential fuel consumption
appears to dominate at the urban Sacramento location.
Figure 2b shows the monthly-averaged TROPOMI
satellite HCHO levels and the daily ground-based CO × biogenic concentration
at the Sacramento sampling site. The agreement between the seasonal trend in
the CO × biogenic and TROPOMI HCHO builds confidence in the use of CO × biogenic
as a ground-based indicator of VOC concentrations at this location. Both
indicators suggest that VOC concentrations increased from April–August
2020 and sharply declined in October 2020. Wildfires can emit large amounts
of VOCs that can be transported to urban areas (Zhang et al., 2018). It is possible
that wildfires contributed to the highest VOC concentrations observed
between August and September 2020. Removing the days influenced by wildfires (open box) still leaves a strong seasonal trend with increasing VOC
concentrations between April–August 2020, which is consistent with
increasing VOC emissions from biogenic sources. Biogenic VOC (BVOC)
emissions increase during warmer spring months and continue to increase as
temperatures rise into summer (Guenther
et al., 2006, 1991). The CO × biogenic factor inherently incorporates this
effect, but the strong agreement between the TROPOMI HCHO levels and the
CO × biogenic metric in Fig. 2b suggests that the
seasonal pattern of the biogenic emissions is a real feature of the dataset
and not an artifact of how the CO × biogenic metric was constructed.
Similarly, the declining VOC concentration observed in October 2020 and
beyond matched the expected decrease in biogenic emissions during the
colder fall and winter seasons when vegetation becomes dormant. The seasonal
pattern illustrated in Fig. 2b suggests that BVOC
is an important precursor of HCHO in Sacramento.
PAMS measurements of ground-level isoprene concentrations in Sacramento are
shown as blue diamonds in Fig. 2b. Isoprene is highly reactive in the
atmosphere, and so PAMS-measured concentrations are lower than 4 ppb. The
limited time period of available measurements makes it difficult to discern
seasonal trends, but the slightly lower measured isoprene concentrations in
July and slightly higher isoprene concentrations in August followed by
decreasing (non-wildfire) isoprene concentrations in September generally
match the VOC trends generated using both TROPOMI HCHO and CO × biogenic. Once
again, the agreement between the three independent techniques builds
confidence in the overall assessment of VOC seasonal trends.
Volatile chemical products (VCPs) are another important category of VOC
emissions (McDonald et al., 2018).
The expanded usage of spray disinfectant and sanitization products during
the COVID-19 pandemic might have been a significant source of VOCs in the
urban area, but the expected usage pattern of these products does not
include a sharp decline in the fall period. The seasonal pattern of VOC
concentrations increasing during spring–summer and decreasing during fall–winter is more consistent with a combination of biogenic sources and
wildfires, as discussed above.
Seasonal trends in O<inline-formula><mml:math id="M207" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula> sensitivity
Figure 3a shows the monthly trends in measured
ΔO3+NOx and TROPOMI HCHO/NO2 from February 2020 to
December 2020 at the Sacramento site. The ΔO3+NOx value
represents the change in O3 concentrations in response to a +8 ppb
NOx perturbation. O3 formation is NOx-limited when the
ΔO3+NOx value is positive and VOC-limited when the
ΔO3+NOx value is negative. Changes in the absolute
magnitudes of the ΔO3+NOx values reflect the degree of
O3 sensitivity to the NOx perturbation. ΔO3+NOx and TROPOMI HCHO/NO2 both increase from April to
August 2020 and then sharply decline in October 2020. By comparing the
transition points of ΔO3+NOx=0 and TROPOMI HCHO/NO2=4.6 (discussed in Sect. 3.2), it is evident
that O3 formation evolved from VOC-limited conditions in spring towards
NOx-limited conditions from June to August, followed by a return to
VOC-limited conditions after October 2020. It is notable that the seasonal
trend for ΔO3+NOx matches the trend of increased BVOC
emissions during the summer and increased NOx emissions during the
winter. The travel restrictions associated with COVID-19 that occurred in
March–May 2020 appeared to have little impact on the overall seasonal
trends in ΔO3+NOx behavior.
Monthly variation of TROPOMI HCHO/NO2 (diamond) and ΔO3 (box) due to NOx addition (ΔO3+NOx, a) and VOC
addition (ΔO3+VOC, b) from
April to December including wildfire days (shaded box) and without wildfire days (open box).
The median ground-based ΔO3+NOx<0 indicates
VOC-limited conditions in September 2020, but the TROPOMI satellite
HCHO/NO2>4.6 indicates NOx-limited conditions for
this same month. Removing the wildfire days from the analysis period (open
box in Fig. 3a) did not reconcile the two
measurements. The divergence of the ground-based measurements and satellite
measurements in this month may reflect the presence of elevated plumes of
wildfire smoke above the monitoring site that were detected by the satellite
measurements (Jin et al., 2017).
Cleaner air at the ground-based monitors, therefore, yielded ΔO3+NOx values in a different chemical regime than the satellite
measurements that are based on the tropospheric vertical column densities.
This comparison suggests that ground-based measurements may be required to
supplement satellite-based measurements to fully characterize the surface
O3 formation regime under special circumstances that generate
concentrated pollution layers above the ground-level.
Removing the days influenced by wildfires from the chamber measurement (open
box) and TROPOMI satellite measurement (open diamond) in
Fig. 3a reduces both ΔO3+NOx
and TROPOMI HCHO/NO2. Figure S7 in the Supplement compares TROPOMI HCHO and NO2 on
wildfire days and non-wildfire days. Median TROPOMI HCHO measurements
increased by 44 % and TROPOMI NO2 measurements increased by 14 % on
wildfire days. The comparison between wildfire vs. non-wildfire days implies
that wildfires emit more VOC than NOx, which is in agreement with
previous studies (Jaffe and Wigder, 2012). It
is also notable that the decrease in ΔO3+NOx is larger
than the decrease in TROPOMI HCHO/NO2. This observation might once
again reflect the fact that the wildfire identification algorithm (Anderson and Kuwayama, 2022) was based on ground-level
measurements that do not flag all of the days with elevated plumes above the
monitoring site that could differentially affect the satellite measurements.
Figure 3b shows the monthly variation of
ground-based ΔO3+VOC and TROPOMI satellite HCHO/NO2
from February–December 2020 at the Sacramento sampling site. ΔO3+VOC (Fig. 3b) has an inverse time trend
compared to ΔO3+NOx and TROPOMI HCHO/NO2 (Fig. 2a).
The ΔO3+VOC trend is well correlated to the TROPOMI HCHO/NO2 trend plotted on a reversed axis between April–August 2020,
but the two trends diverge in September–October 2020 when wildfires were
prevalent. Removing the wildfire days from August to October (open box)
increased the ground-based ΔO3+VOC, once again suggesting that
wildfires contributed more VOCs than NOx to the atmosphere (Altshuler et al., 2020). The divergence between the
ground-based ΔO3+VOC measurements and TROPOMI satellite HCHO/NO2 measurements during the wildfire season once again reflects
the presence of elevated plumes that were measured by the satellite but not
by the ground-based monitors (Schroeder et al., 2017a).
Weekend effect
Figure 4 separately plots concentrations of O3
precursors and O3 sensitivity on weekdays (shaded bars) and weekends (open bars) during the current study period. Direct wildfire days have been
removed from the analysis (Anderson and Kuwayama, 2022) to
focus on the day-of-week patterns. Hypothesis tests were carried out to
determine if weekday and weekend responses were similar in each month. The
results indicate that weekend reductions in NO2 concentrations were
significant at a 90 % confidence level (or higher) before July. The
similarity between weekday and weekend NO2 concentrations after July
may be associated with increased NOx emissions from wildfires in the
late summer and space heating in the fall–winter since neither of these
sources follows a weekday/weekend pattern. Although days directly affected
by the wildfire smoke were removed from the analysis, residual emissions
from smoldering fires and multi-day recirculation of air mass that have been
affected by wildfire smoke may have contributed to elevated regional
NOx concentrations through the formation of reactive nitrogen reservoir
species such as peroxyacetyl nitrate (PAN) that can be transported over long
distances (Lindaas et al., 2017). The
CO × biogenic VOC surrogate did not display statistically significant
differences between weekdays vs. weekends except in June and July. Extremely
hot days (>35∘C) occurred on weekdays in June and
weekends in July, driving the CO × biogenic factor higher.
Weekday (solid box) and weekend (open box) monthly-average
concentrations of NO2 and CO × biogenic (a, b) and
ΔO3+NOx
and ΔO3+VOC(c, d) from April to December 2020 after removing wildfire days. The asterisks above each box-and-whisker plot represent the significance of the
weekday vs. weekend difference. (∗:p value <0.1; ∗∗:p value
<0.05; ∗∗∗:p value <0.01; ∗∗∗∗:p value <0.001;
ns (not significant): p value >=0.1).
Reduced NOx emissions on weekends are reflected in the O3
sensitivity to precursors shown in Fig. 4c and d.
The median ΔO3+NOx sensitivity is higher on
weekends for most months, indicating that the atmosphere was more
NOx-limited. Large variability in the data makes the weekend vs.
weekday ΔO3+NOx response statistically significant
at the 90 % (or higher) level only in April, September, and October. The
large weekend reductions in median NO2 concentrations detected in May
and June did not lead to significantly higher weekend ΔO3+NOx, possibly because of higher weekday median VOC
concentrations in these months. Median O3 sensitivity was
NOx-limited (ΔO3+NOx>0) on both
weekdays and weekends from June to August when BVOC emissions are expected
to be highest. In spring and early fall (April, May, and September), the
median weekday O3 sensitivity is VOC-limited but the median weekend
O3 sensitivity is NOx-limited. In late fall and winter (October–November), the median O3 sensitivity is VOC-limited on
both weekends and weekdays. Weekend NOx reductions have an inverse
effect on ΔO3+VOC shown in Fig. 4d
compared to ΔO3+NOx. The median ΔO3+VOC is lower on weekends than weekdays because the O3 formation is more
NOx-limited on weekends.
Figure 5 summarizes the NOx, CO × biogenic,
O3, ΔO3+NOx, and ΔO3+VOC measurements
in Sacramento from April to December in 2020 in the format of an O3
isopleth diagram. Each data point in Fig. 5
corresponds to measurements on a single day. The color of each symbol
represents the O3 concentration in the base case chamber after 3 h
of UV irradiation. The NOx and CO × biogenic
factors are calculated as the daily value divided by averaged value. The arrow attached to each data symbol points in
the direction of maximum ΔO3 in response to NOx and VOC
addition. The magnitude of the arrow corresponds to the strength of the
ΔO3 response. All arrows generally point right, meaning that
VOC addition increased O3 concentrations. Arrows pointing to the bottom
right indicate that NOx addition decreased the O3 concentration,
while arrows pointing to the upper right indicate that NOx addition
increased the O3 concentrations. The most effective emissions control
program acts in the direction opposite to each arrow.
Measured O3 isopleth diagram. The NOx and CO × biogenic
factor is calculated by the daily value divided by averaged value. The
O3 concentration is the daily O3 concentration in the base case
chamber after 3 h UV exposure. Arrows represent the O3 sensitivity.
The blue dots are the monthly-averaged values, and the blue line shows the
seasonal cycle in the O3 isopleth diagram. Days influenced by wildfires
are removed from the plot.
The mixture of daily data points (yellow to red points) shows the O3
isopleth pattern where higher O3 concentration (darker color) exists at
higher NOx and VOC concentrations. The combination of the colors and
the arrows illustrated in the isopleth diagram helps to define the measured
ridgeline in the O3 isopleth diagram that denotes the transition
between VOC-limited chemistry and NOx-limited chemistry at Sacramento.
Arrows in the upper left of the diagram point downwards (VOC-limited)
towards the ridgeline, while arrows in the lower right of the diagram point
upwards (NOx-limited) towards the ridgeline. The atmospheric system
experiences a range of conditions throughout the 9-month study period
that moved the measurements around the O3 isopleth diagram. The average
seasonal cycle is illustrated in Fig. 5 using
monthly-average points shown as blue circles with white month numbers. The
monthly-average O3 chemical regime traces an oval path through the isopleth diagram as NOx concentrations decrease and CO × biogenic (proxy
of VOC) concentrations increase moving from spring to summer months.
NOx concentrations increase rapidly in fall while CO × biogenic
concentrations simultaneously decrease at the Sacramento sampling location,
transitioning the O3 chemistry to VOC-limited conditions. The pattern
is expected to reverse for the months of January–March (not shown) to
produce a repeatable annual cycle. The direct measurement of the seasonal
pattern of the O3 chemical regime clearly illustrates the effects of
NOx and VOC emissions controls at different times of the year.
Extreme value analysis for O<inline-formula><mml:math id="M380" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula> sensitivity
The days with the highest measured O3 concentrations are of particular
interest in the current study since emissions control programs are
traditionally tailored to reduce the O3 design value, which is
determined by MDA8 O3 concentration. Figure 6 illustrates
box-and-whisker plots of measured ΔO3+NOx and ΔO3+VOC at Sacramento binned according to the MDA8 O3
concentration measured at the monitoring station near the chamber
measurement site. The right two bins, corresponding to the
O3-nonattainment days (MDA8 O3>70 ppb), have O3
sensitivity in the NOx-limited regime where NOx addition increases
O3 concentrations and VOC addition has minor effects on O3
concentrations. These measurements suggest that a NOx emissions control
strategy would be most effective at reducing these peak O3
concentrations. In contrast, a large portion of the days with MDA8 O3
concentrations below 55 ppb were in the VOC-limited regime, suggesting that
an emissions control strategy focusing on NOx reduction would increase
O3 concentrations. VOC controls on these intermediate days would be
difficult, however, if biogenic VOCs account for the majority of the O3
formation. This challenging situation suggests that emissions control
programs that focus on NOx reductions will immediately lower peak
O3 concentrations but slightly increase intermediate O3
concentrations until NOx levels fall far enough to re-enter the
NOx-limited regime.
Boxplot of O3 sensitivity to NOx and VOC as a function
of MDA8 O3 concentration. Points indicate the data point in each range
of MDA8 O3 concentration.
Additional statistical analysis was carried out to characterize the extreme
values in the O3 sensitivity plots (Coles, 2001;
Gilleland and Katz, 2016). Extreme value analysis characterizes high
concentrations using return levels corresponding to a specified time
period (T). In the context of the current analysis, the return level is the
ΔO3 perturbation response that is expected to be exceeded once
during the specified time period. The probability of exceeding the return
level is therefore 1/T. Figure 7 shows the 90 d
return level for ΔO3+NOx and ΔO3+VOC
sensitivity based on statistical analysis of the measured perturbation
response in each month. The 90 d time period was chosen to correspond to
the time period inherent in the O3 design value values that are based
on the annual fourth-highest O3 concentration averaged in 3 years
(12 exceedances / 1095 d equals approximately 1 exceedance / 90 d). The 90 d return value of O3 sensitivity can therefore be
viewed as the design value for O3 sensitivity. Figure 7 shows that the
90 d return levels for O3 sensitivity and the median O3
sensitivity follow similar seasonal trends, but the extreme values are
shifted higher such that they are NOx-limited from April to December,
except November, which is slightly VOC-limited. The positive 90 d return
levels of ΔO3+NOx once again
suggest the NOx control is an efficient strategy to reduce peak O3
concentrations in Sacramento.
Three-year return level (red dot) and 95 % confidence interval (red
open dot) from extreme value analysis of O3 sensitivity to NOx and
VOC.
Chamber and TROPOMI data correlation
The consistency between the NOx and VOC measurements made using
ground-based chambers and satellite observations enables a joint analysis to
directly calculate the TROPOMI HCHO/NO2 ratio at the transition between
NOx and VOC-limited O3 formation regimes. Three circular buffers (2.5, 5, and 7.5 km radii) centered on the monitoring location were used to
generate the TROPOMI HCHO/NO2 ratio that was then compared to the
measured ΔO3+NOx ratio at the monitoring site. The
HCHO/NO2 ratio generated using the 5 km radius buffer shows the best
correlation with ground-based chamber results shown in
Fig. 8a (results from other buffers are shown in
Fig. S8 in the Supplement). Linear regression analysis between
1-week-averaged ΔO3+NOx and HCHO/NO2 with and
without wildfires shows that removing the wildfires always improves the
correlation coefficient (R), likely because the elevated wildfire plumes
have different effects on surface vs. integrated column measurements. The
regression carried out using a 5 km buffer radius with wildfires removed
yielded a correlation coefficient R=0.62 (p<0.001). The
transition point between NOx-limited and VOC-limited conditions (corresponding to ΔO3+NOx=0) occurs when
HCHO/NO2=4.6 (95 % confidence interval: 4.39–5.90). When the TROPOMI satellite HCHO/NO2 ratio fell below 4.6, then
the ground-based measurement of ΔO3+NOx was usually
negative, and when the satellite HCHO/NO2 ratio rose above 4.6, then the
ground-based measurement of ΔO3+NOx was usually positive.
Ordinary lease squares (OLS) regression was used to estimate the transition
point HCHO/NO2=4.6 between chemical regimes. This approach does not
account for uncertainty in chamber ΔO3+NOx. Repeating the analysis using reduced
major axis (RMA) regression that accounts for errors in both x and y yields
an estimated transition point HCHO/NO2=4.4 between chemical regimes (Fig. S9 in the Supplement).
Ordinary least squares (OLS) regression between weekly-averaged
TROPOMI HCHO/NO2 at 5 km circular buffers and the weekly-averaged
ΔO3+NOx
from ground-based measurement. The shaded area shows the 95 % confidence
interval of the mean response of the predicted value.
The HCHO/NO2 transition point directly measured in the current study
is consistent with previous estimates constructed from the combination of
satellite measurements and routine ground-based O3 monitoring data (Jin et al., 2020). Other previous efforts to estimate HCHO/NO2 value at the transition point between NOx-limited and VOC-limited regimes typically couple satellite
HCHO/NO2 measurements with O3 sensitivity or O3 sensitivity
indicators (i.e., LNOx/LROx) predicted using reactive chemical
transport models. These hybrid studies predict HCHO/NO2 transition
points lower than the value of 4.6 derived in the current study. Martin (2004) used HCHO/NO2 from GOME to calculate the
regime transition value HCHO/NO2=1.0 for polluted areas across the
globe. Duncan et al. (2010) used OMI to estimate the regime transition value
HCHO/NO2=1–2 across the continental United States. Schroeder (2017b) found the transition range
could between HCHO/NO2=1.3–5.0 during DISCOVER-AQ in
Houston. These estimated HCHO/NO2 transition values vary due to the
different satellite resolution, retrieval algorithms, and inherent air
pollution patterns over the different study areas. The finer-resolution
satellite data used in the current study combined with direct ground-based
measurements of O3 sensitivity should provide accurate information for
the HCHO/NO2 transition point between chemical regimes over California.
TROPOMI O<inline-formula><mml:math id="M490" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula> sensitivity in California
Figure 9 displays the monthly-average
spatial distribution of TROPOMI HCHO/NO2 ratios across California for
the time period April–October 2020. Overall, TROPOMI HCHO/NO2 was
the lowest (mean (standard deviation) =3.5 (1.2)) in April and the
highest (mean (standard deviation) =9.7 (3.2)) in July. The seasonal
pattern of increasing NOx limitation during the summer months at
Sacramento (Fig. 3a, b) is mirrored across most of
California (Fig. 9), especially in the mountainous
areas with dense vegetation. The majority of California is in the
VOC-limited regime in April and May due to the low BVOC emissions. Only very
remote regions with low NOx concentrations are still in the
NOx-limited regime during these spring months. Most areas outside of
major urban centers transition toward NOx-limited conditions between
June and September as ambient temperature and BVOC emissions increase. These
areas then transition back to the VOC-limited regime in the fall months
beginning in October as temperatures decrease and vegetation becomes
dormant.
Spatial distribution of TROPOMI satellite (HCHO/NO2) ratios
in California for April–October 2020. TROPOMI NO2 and HCHO data are
re-gridded to 5 km resolution when calculating monthly-average ratios. The
black bold line circles the burned area in each month detected by MODIS from
Fire Information for Resource Management System (FIRMS). The NOx-limited
conditions correspond to HCHO/NO2 ratios above 4.6.
Large urban centers including Los Angeles, San Diego, and the San Francisco
Bay Area exhibit low HCHO/NO2 ratios (VOC-limited conditions)
throughout the study period. These urban areas contain less vegetation and
larger numbers of NOx sources than outlying suburban and rural areas.
Therefore, reducing NOx emissions in these urban centers may increase
monthly-average O3 concentrations throughout the year. The
HCHO/NO2 ratio in California's Central Valley is lower than the
HCHO/NO2 ratio in the surrounding mountainous area during all months of
the study period. This spatial pattern reflects the high BVOC emissions from
coniferous forests in the mountainous regions compared to the cropland in
the Central Valley (Misztal et al.,
2014).
Past studies have found that wildfire smoke plumes mixing with high urban
NOx emissions can lead to enhanced urban O3 concentrations (Jaffe and Wigder, 2012). The effects of
wildfires during August–September 2020 can be observed in
Fig. 9 as zones of reduced HCHO/NO2
immediately around the active burn areas followed by a larger halo zone
of increased HCHO/NO2 as the VOCs emitted from wildfires have time to
react to form HCHO. This halo pattern is most obvious in October 2020,
when the seasonal cycle of biogenic emissions declined sufficiently to shift
the O3 sensitivity back to the VOC-limited regime for the majority of
the state except for the region surrounding a wildfire in the Sierra Nevada
mountain range east of Fresno (near Yosemite National Park). VOCs emitted
from the wildfire in October 2020 reacted to produce HCHO in the halo
region, keeping the HCHO/NO2 ratio in the NOx-limited regime. The
extensive wildfires that occurred in 2020 appear to have extended the
natural peak of the HCHO/NO2 ratio from July into August, September,
and even October 2020. It is unknown whether this satellite observation
accurately represents conditions at ground level. The results at the
Sacramento monitoring site in September 2020 (Fig. 3a and b) suggest that elevated smoke plumes can dominate the satellite
observations, but they may not accurately represent conditions at ground
level.
The seasonal variation of O3 sensitivity can be observed over the
entire state of California using the TROPOMI HCHO/NO2 (Table S1).
Figure 10a shows how the O3 sensitivity seasonal pattern differs among
different air basins. The air basins with the highest populations have
suppressed seasonal variation of O3 sensitivity because of the higher
anthropogenic NOx emissions. The SoCAB had the lowest HCHO/NO2
ratio among all the air basins in California during the study period. This
is noteworthy since the SoCAB has the highest population and the highest
O3 concentrations. The San Francisco Bay Area and San Diego County, two
other heavily populated areas in California, also have relatively low
HCHO/NO2 ratios compared to other air basins. Using HCHO/NO2=4.6 as the transition point, even these highly urbanized air basins appear
to transition from VOC-limited to NOx-limited O3 formation
chemistry in summer 2020. It is noteworthy, however, that the urban cores of
these regions remain VOC-limited across all months due to very high NOx
emissions (see persistently green regions in Fig. 9). Figure 10b
illustrates the TROPOMI HCHO/NO2 monthly variation for different cities
in SoCAB between February and October 2020. The cities inside/around the LA
urban core have HCHO/NO2<4.6 throughout the entire year with
a weak seasonal variation. This might be caused by reduced BVOC emissions in
the urban center. The remote areas (darker colors in Fig. 10b) have
greater seasonal variation and higher peak HCHO/NO2. The sharp increase
in HCHO/NO2 in summer leads to a shift in O3 sensitivity from the
NOx-saturated regime to the NOx-limited regime in the cities
further away from the urban core. Due to the different seasonal variation of
HCHO/NO2 at different sites, the NOx-saturated region around the
urban core will shrink in the summer and expand in the winter. Figure S10 in the Supplement shows this seasonal pattern of O3 sensitivity regime distribution in
Los Angeles as an example. Thus, the optimal emissions control strategy for
the entire air basin may differ from the optimal emissions control strategy
for urban cores areas.
Monthly variation of TROPOMI HCHO/NO2 in different air
basins (a) and in different cities in Southern California (b). The darker colors in the right panel indicate increasing distance
from the urban center of Los Angeles.
DiscussionSensitivity analysis
The chamber measurements made in the current study capture the sensitivity
of the O3 chemical production term in response to the concentration of
NOx and VOC. The experiment does not directly account for atmospheric
processes such as mixing and deposition, but the chemical production term represents
the dominant processes that determine how local emissions affect local
O3 concentrations. The good agreement between ground-based chamber
measurements and satellite O3 sensitivity measurements in the current
study builds confidence in the reported seasonal trend of O3
sensitivity. Limitations and uncertainties associated with the temperature,
UV intensity, and NOx/VOC perturbations used in the ground-based chamber
measurements are discussed in this section to build further confidence in
the results. The potential of these issues to influence the results is
analyzed through a combination of measurements and model calculations. The
configuration of the chamber model is described in Sect. 2.4. Figure 11
shows that the chamber model can accurately predict the measured seasonal
trends in O3 sensitivity, providing a solid foundation for sensitivity
tests.
Monthly variation of the ΔO3+NOx(a) and
ΔO3+VOC(b) predicted by the chamber model (solid box) and directly measured in the
chamber (open box) from April to December 2020 at the Sacramento
measurement site.
Temperature
The temperature in the reaction chambers was higher than the ambient
temperature due to the heating effects of the UV lights. Figure S11 in the Supplement shows
that the difference between the chamber gas temperature and the ambient
temperature increased by 5–10 ∘C over the course of each experiment,
with the exact temperature profile depending on the measurement month.
Despite this temperature increase, all three chambers experience the same
temperature profile, and so the comparison of O3 formation between the
chambers is not strongly biased by this issue. Figure 12a shows the
calculated ΔO3+NOx during each
month of the experiment under the chamber and ambient temperature profiles.
The difference between the chamber and ambient temperature has little effect
on the O3 sensitivity in each month. Temperature effects do not
significantly modify the seasonal variation of the measured O3
sensitivity in the current study. Similar behavior was shown in
ΔO3+VOC in Fig. S12a.
Effect of temperature, radiation, and perturbation amount on the
monthly variation of the predicted chamber ΔO3+NOx from April
to December 2020 at the Sacramento measurement site. Open boxes show the
predicted response under chamber measurement conditions (chamber
temperature, radiation, and 8 ppb NO2 perturbation). Solid boxes show
the predicted response when conditions are updated: (a) using the ambient
temperature profile; (b) using clear-sky solar radiation; (c) using a 2 ppb NOx perturbation; and (d) using the combination of ambient temperature, solar
radiation, and 2 ppb NO2 perturbation.
UV intensity
The UV intensity in the chambers was intentionally maintained at a constant
level through all seasons so that the changes in O3 sensitivity could
be directly attributed to the changes in the ambient concentrations. A
representative average UV intensity was selected for this purpose. As was
the case with temperature, all chambers experience the same UV conditions,
and so this factor is not expected to overly bias the comparison between
chambers that acts as the core of the current study. The actual seasonal
cycle of UV radiation would generate higher photolysis rates in the summer
and lower photolysis rates in the winter that would further amplify the
seasonal signal already detected by the measurements with constant UV
intensity. SAPRC11 chamber model simulations were used to quantify the
effect of seasonal variations in UV intensity. Simulations were carried out
using the measured constant UV radiation in the chambers and using the clear-sky UV intensity calculated with the routines in the UCD/CIT CTM based on
the latitude–longitude of the measurement site and the day of year. The calculations
summarized in Fig. 12b show that the difference associated with the use of
constant UV radiation does not change the seasonal pattern of O3
sensitivity to NOx perturbations. The seasonal changes to UV intensity
slightly amplify the magnitude of the seasonal trend in O3 sensitivity (increase the absolute value of ΔO3+NOx), but the overall seasonal pattern is
unchanged. Similar behavior was shown in ΔO3+VOC in Fig. S12b in the Supplement.
Perturbation size
The constant 8 ppb NO2 perturbations used in the current study are
greater than or equal to ambient NOx concentrations during the summer
season at Sacramento. O3 formation chemistry is non-linear, meaning
that the size of the perturbation may complicate the interpretation of the
sensitivity results. O3 sensitivity measurements were conducted using
NOx perturbations ranging from 1–10 ppb at the UC Davis campus from
December 2021 to January 2022 to investigate the non-linear behavior of the
O3 formation chemistry. The results summarized in Fig. S13 in the Supplement show the
O3 response expressed as ΔO3 (final O3 concentration
in the base case chamber minus final O3 concentration in the NOx perturbed
chamber). The ΔO3 is negative in all NOx perturbed tests
due to the low VOC emission in winter in Davis, CA (similar to Sacramento).
Increasing the magnitude of the NOx perturbation increased the absolute
magnitude of the ΔO3 value but did not shift the chemistry into
a different regime.
The size of the NOx and VOC perturbation used in the chamber
experiments is most important when ambient conditions are close to the
ridgeline on the O3 isopleth diagram (spring and fall in the current
experiment). An 8 ppb NO2 perturbation may jump over the ridgeline in
this case, suggesting that the chemistry is NOx-rich rather than
NOx-limited. SAPRC11 chamber model simulations were used to quantify
the effect of the 8 ppb NO2 perturbation vs. a smaller 2 ppb NO2
perturbation. As shown in Fig. 12c, the 8 ppb NO2 perturbations used
in the current study do not affect the shape of the seasonal trend in
O3 sensitivity measurement, but the 8 ppb NO2 perturbation (open
box in Fig. 12c) does affect the transition months when the atmospheric
system changes to NOx-limited behavior. This issue may influence the
estimated value of HCHO/NO2 that characterizes the transition to
NOx-limited behavior in Sect. 3.2, but it should be noted that the
value of 4.6 derived in the current study is in good agreement with the
value of 4.5 reported by Jin et al. (2020). The
non-linearities associated with VOC chemistry are less severe, and so the
size of the VOC perturbation does not complicate the interpretation of
results (see ΔO3+VOC in Fig. S12c).
Combined effects of temperature, UV intensity, and perturbation size
The O3 sensitivity calculated with the combined effects of temperature,
UV intensity, and lower perturbation size was compared to the base case
calculated O3 sensitivity in Figs. 12d and S12d (in the Supplement). The NO2
perturbation size has the largest effect on the chamber O3 sensitivity
results, with relatively minor changes introduced by temperature and UV
intensity. None of these issues changes the basic pattern of increasing
NOx limitations during summer months transitioning to VOC limitations
during winter months. It should be noted that operation of the mobile smog
chamber system in cities with higher ambient NOx concentrations is
expected to give O3 sensitivity results that are even less dependent on
the NO2 perturbation size.
O<inline-formula><mml:math id="M615" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:math></inline-formula> control strategies in California
California's current O3 control strategies mainly focus on NOx
emissions from motor vehicles (Barcikowski et al., 2017) and
especially heavy-duty trucks (Burke, 2020). Additional control
strategies would require cleaner engines and zero/near-zero emission
technologies (Brown, 2018; South Coast AQMD, 2021). VOC
sources that dominate O3 formation are still not clear due to the large
numbers of activities that release VOCs and the complex reactions that VOCs
undergo in the atmosphere. Controls on VOC emissions have been more
effective than controls on NOx emissions over the past decades, mainly
because of reduced emissions from large stationary sources (Barcikowski et al., 2017). The estimated VOC emissions
decreased by a factor of 3 while NOx emission decreased by a factor of 1.5 between 1980 and 2010 according to the California inventory (Cox et al., 2013; Rasmussen et al., 2013).
Long-term ambient measurements in the SoCAB confirm that ambient VOC
concentrations decreased at an average rate of 7.5 % yr-1, while
ambient NOx concentrations decreased at an average rate of 2.6 % yr-1 between the years 1980 and 2010 (Pollack
et al., 2013b; Warneke et al., 2012). These ambient measurements suggest
emissions reduction by a factor of 10 for VOCs and a factor of 2.2 for NOx.
Recent studies have shown that VOCs from consumer products are
underestimated in the emission inventory (McDonald et al., 2018). However,
the clear seasonal pattern in the measured O3 sensitivity and the
corresponding pattern for concentrations of VOC proxies (HCHO and
CO × biogenic) suggest that BVOCs are also important.
The 2016 California State Implementation Plan calls for a 34 % reduction
in NOx emissions and a 30 % reduction in VOC emissions (California Air Resources Board, 2018), which will increase the
VOC/NOx ratio. This will reduce peak O3 concentrations in most
areas across California that become NOx-limited in the middle of the
summer. In contrast, the NOx emissions control program could cause a
short-term increase in peak O3 concentrations in the urban cores that
are currently VOC-limited, and it could increase intermediate O3
concentrations in late spring or early fall as regions transition back to
VOC-limited conditions. These regions do not currently violate the O3
NAAQS, but they could experience future violations depending on the timing
of the transition to lower NOx concentrations. Despite these penalties,
controls on NOx emissions may be the only alternative for long-term
O3 reductions in regions where VOC emissions are dominated by biogenic
sources. As the NOx keeps decreasing, the O3 photochemical regime
will eventually transition back to NOx-limited conditions, and all
further NOx reductions will yield decreasing O3 concentrations.
Previous studies have observed such a transition between VOC-limited and
NOx-limited conditions in polluted urban areas with high NOx
concentrations. Jin et al. (2020)
observed a suppression of the NOx-limited area between 2013–2016 vs.
1996–2000 in Los Angeles by analyzing satellite HCHO/NO2 ratios.
Baidar et al. (2015) observed a
weakening of the higher O3 concentrations on weekends in the SoCAB
between 1996 and 2014, reflecting a transition towards more NOx-limited
conditions. These studies suggest that continued reductions in NOx
emissions will eventually yield a transition to fully NOx-limited
conditions in Los Angeles, albeit this transition may not be fully complete
for decades.
Wildfires are an unpredictable factor that enhances O3 formation in
California. O3 formation during wildfire events shifts towards more
NOx-limited conditions, making reductions in NOx emissions
attractive. The frequency and scale of wildfires in the western United States have
increased over time due to the effects of drought and climate change (USGCRP, 2017). Abatement strategies may focus on wildfire
prevention as an effective way to reduce incidental O3 concentrations.
Conclusion
Direct measurements of O3 sensitivity to precursor NOx and VOC
concentrations using a mobile smog chamber system in Sacramento, CA, from
April to December 2020 show that O3 sensitivity follows a seasonal
cycle. O3 formation is VOC-limited in the spring, is NOx-limited in
the summer, and returns to VOC-limited in fall–winter. This seasonal
pattern reflects higher emissions of reactive VOCs during the summer season
and increased NOx concentrations during the other seasons. The most
obvious potential source of increased VOC emissions during the summer season
is biogenics. Comparing the ground-based chamber measurements to satellite
measurements from TROPOMI suggests that the transition between
NOx-limited and VOC-limited chemical regimes for O3 formation
occurs at a TROPOMI HCHO/NO2 ratio of 4.6. Monthly-averaged TROPOMI
measurements show that O3 sensitivity across most of California follows
a seasonal cycle similar to Sacramento, but locations with higher population
density are more VOC-limited. The urban cores of most large cities remain
VOC-limited in all seasons even when the surrounding areas become
NOx-limited in the middle of summer. The variability of the chemical
regime for O3 formation across space and time makes it difficult to
design an emissions control strategy that will equitably reduce O3
concentrations for all California residents currently living in air basins
that violate the 8 h O3 NAAQS. Reductions in NOx emissions will
be the most efficient control strategy to reduce present-day peak O3
concentrations, but this strategy will lead to increasing O3
concentrations in urban cores during the middle of summer and increasing
O3 concentrations in surrounding regions during late spring and early
fall. These penalties will persist until NOx emissions are reduced
sufficiently to push the entire region into NOx-limited conditions
sometime in the coming decades. VOC emissions reductions never cause
increasing O3 concentrations, and O3 formation is VOC-limited
during some seasons. It may be advisable to augment NOx emissions
control programs with some amount of controls on volatile consumer products (VCPs) and mitigation of wildfires in an attempt to reduce any near-term
increases in O3 concentrations. Continued deep NOx emissions
reductions should eventually transition all locations across California into
the NOx-limited regime and will effectively push the state toward
8 h O3 NAAQS attainment.
Data availability
Daily chamber measurement data including O3 concentration, O3 sensitivity, and NOx concentration can be accessed through https://datadryad.org/stash/share/ktJh3AxAs0K7y8Iku8-VL3v7ZuGwBGQodYhRT-wHZ04 (Wu et al., 2022).
The supplement related to this article is available online at: https://doi.org/10.5194/acp-22-4929-2022-supplement.
Author contributions
SW made field measurements and wrote the initial draft of each version of
the manuscript. HJL processed TROPOMI data. AR analyzed wildfire vs.
no-wildfire periods. SL provided project management. TK constructed the
initial version of the chambers. JHS hosted initial measurements and helped
revise the manuscript. MJK designed the experiment, directed the data analysis,
coded the chamber model, and revised the manuscript.
Competing interests
The contact author has declared that neither they nor their co-authors have any competing interests.
Disclaimer
This document is disseminated in the interest of information exchange and does not necessarily reflect the official views or policies of the State of California, the California Air Resources Board, or the Coordinating Research Council.
Publisher's note: Copernicus Publications remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Acknowledgements
The authors thank Michael Miguel, Anthony Esparza, and Aimee Davis of the
California Air Resources Board (CARB) for their logistical support
surrounding the siting of the chamber experiments.
Financial support
This research has been supported by the California Air Resources Board (grant no. 19RD012), the Coordinating Research Council (grant nos. A-121 and A-121-2), and the University of California Institute of Transportation Studies through funding from the State of California via the Public Transportation Account and the Road Repair and Accountability Act of 2017 (SB 1).
Review statement
This paper was edited by Andreas Hofzumahaus and reviewed by William Stockwell, David Parrish, and two anonymous referees.
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