Composition and reactivity of volatile organic compounds in the South Coast Air Basin and San Joaquin Valley of California

Comprehensive aircraft measurements of volatile organic compounds (VOCs) covering the South Coast Air Basin (SoCAB) and San Joaquin Valley (SJV) of California were obtained in the summer of 2019. Combined with the CO, CH₄, and NO_x data, the total calculated gas-phase hydroxyl radical reactivity (cOHR_TOTAL) was quantified to be 6.1 and 4.6 s⁻¹ for the SoCAB and SJV, respectively. VOCs accounted for ∼ 60 %–70 % of the cOHR_TOTAL in both basins. In particular, oxygenated VOCs (OVOCs) contributed >60 % of the cOHR of total VOCs (cOHR_VOC) and the total observed VOC mixing ratio. Primary biogenic VOCs (BVOCs) represented a minor fraction (<2 %) of the total VOC mixing ratio but accounted for 21 % and 6 % of the cOHR_VOC in the SoCAB and SJV, respectively. Furthermore, the contribution of BVOCs to the cOHR_VOC increased with increasing cOHR_VOC in the SoCAB, suggesting that BVOCs were important ozone precursors during high ozone episodes. Spatially, the trace gases were heterogeneously distributed in the SoCAB, with their mixing ratios and cOHR being significantly greater over the inland regions than the coast, while their levels were more evenly distributed in SJV. The results highlight that a better grasp of the emission rates and sources of OVOCs and BVOCs is essential for a predictive understanding of the ozone abundance and distribution in California.

1 Introduction

Ambient ozone (O₃) is a criteria pollutant that forms from complex photochemical reactions of volatile organic compounds (VOCs) and oxides of nitrogen (${\mathrm{NO}}_x=\mathrm{NO}+{\mathrm{NO}}_{\mathrm{2}}$) in the presence of sunlight. Exposure to O₃ can lead to adverse health problems such as airway inflammation and decreased lung function, especially in susceptible populations such as children (Nuvolone et al., 2017; Kampa and Castanas, 2008). Persistent NO_x emission control measures in California have resulted in the substantially reduced ambient O₃ levels, e.g., the ozone design value (ODV) decreased by over 60 % in California's South Coast Air Basin (SoCAB) from 273 parts per billion (ppb) in 1980 to 102 ppb in 2015 (Parrish et al., 2017). However, the SoCAB and San Joaquin Valley (SJV) continue to exceed the health-based, 8 h National Ambient Air Quality Standard (NAAQS) of 70 ppb, particularly during the warm summer months (Faloona et al., 2020; Parrish et al., 2017). The plateauing of O₃ levels since 2010 (Wu et al., 2022) poses additional challenges for California's air pollution reduction pathways.

Further reducing ambient O₃ may be more difficult than expected due to the nonlinear O₃ production rate in response to decreases in NO_x and VOCs and the relatively high O₃ background. For example, Parrish et al. (2017) showed that the observational-based background ODV for southern California was 62±1.9 ppb, which was comparable to the modeled background ODV of 45–65 ppb, with an outlier of ∼92 ppb. This background ODV has decreased very slowly at ∼1 ppb per decade since the mid-2000s (Parrish et al., 2021). Compared to NO_x, VOCs are more complex in their emission sources, composition, and reactivity. VOCs are emitted to the atmosphere from a variety of anthropogenic, pyrogenic, and biogenic sources (Goldstein and Galbally, 2007). After emission, VOCs undergo complex photochemical reactions resulting in the production of O₃. VOCs are comprised of hundreds of molecules with different functionalities. The composition of VOCs in California has been rapidly changing over the past few years (Warneke et al., 2012), due in large part to the aggressive emission control measures implemented for on-road mobile sources. This emission source of VOCs is expected to decrease in California over the next few decades, driven by the governor's Executive Order (N-79-20), with a goal of 100 % zero emission vehicle sales of new passenger cars and light-duty trucks by 2035. In contrast, the relative contributions of industrial activities and consumer products to ambient VOCs are growing (Mcdonald et al., 2018; Kim et al., 2022). With a clear path for NO_x reduction in the state, it is critical that the current sources of VOCs and their potential for O₃ formation are better characterized to guide future policies that effectively reduce ambient O₃.

In this study, we analyzed an extensive set of VOCs and other key trace gases measured from the National Aeronautics and Space Administration (NASA) DC-8 research aircraft that flew over the SoCAB and SJV in the summer of 2019. We characterized the composition and the source signatures of the VOCs in these two basins. By examining the calculated hydroxyl radical (OH) reactivity of VOCs (cOHR_VOC), we further determined the key VOC species that are responsible for O₃ production. The spatial distributions of the cOHR_VOC in the SoCAB and SJV are also investigated and compared.

2 Methods and data processing

The study was conducted in partnership with the Fire Influence on Regional to Global Environments and Air Quality (FIREX-AQ) campaign in the summer of 2019 (Warneke et al., 2022). We used data from the two California flights (Fig. S1) which were designed to study the spatial distribution of VOCs from non-fire emissions over the SoCAB and SJV in California. The measurements were carried out during ∼ 11:00–18:00 LT (local time) on board the NASA DC-8 research aircraft on 22 July and 5 September 2019, both of which were weekdays. The flights covered SJV by flying in a raster pattern. In the SoCAB, the measurements were made over the northern and inland regions of the SoCAB, where the O₃ peak events usually occur (Cai et al., 2019). The flights had fewer measurements in the coastal areas and no measurements over central Los Angeles due to flight restrictions (Fig. 1).

To demonstrate the representativeness of the two flights, we synthesized data from the surface monitoring network (https://aqs.epa.gov/aqsweb/airdata/download_files.html, last access: 24 August 2022) in the SoCAB and SJV for the summer of 2019. We then compared the diurnal profiles of the air pollutants and meteorological parameters between the 2 measurement days with the days during July–September 2019. Examples are shown for Los Angeles County in the SoCAB and Kern County in SJV (Fig. S2). The O₃ and air temperature profiles from the 2 measurement days overlapped with those from July–September. These comparisons show that the measurement days are representative of typical summer days in the SoCAB and SJV. It is expected that the summer period features high O₃ pollution, high biogenic VOC (BVOC) emissions, and high secondary oxygenated VOC (OVOC) productions.

Figure 1 Spatial distribution of (a) O₃, (b) NO_x, (c) VOCs, and (d) cOHR_VOC. The flight tracks and sample locations are represented by colored lines and points, respectively. The points are sized by flight altitude and colored by the mixing ratios of O₃, NO_x, VOCs, and cOHR_VOC values in panels (a), (b), (c), and (d), respectively, with the scales shown in the legend. The background map (gray) shows the boundaries of the California air basins, with black indicating the SoCAB and SJV.

Table 1 Summary of measurements^a.

^a The following abbreviations are used: CSL represents the Chemical Science Laboratory, LaRC represents the Langley Research Center, ACOM represents the Atmospheric Chemistry Observation and Modeling Laboratory, HR-ToF-GC/MS represents high-resolution time-of-flight gas chromatography and mass spectrometry, H₃O⁺ ToF-CIMS represents hydronium ions time-of-flight chemical ionization mass spectrometer.

Here we present analyses of the VOCs, CO, NO_x, and O₃ measured by eight research groups operating instrumentation on board the DC-8 (Table 1). The technical details of the instruments are described in the Supplement. Since the diverse techniques have different sampling frequencies, the data were merged to the sampling time (∼40 s in duration) of the whole air samples collected by the University of California Irvine (UCI-WAS). The merged data set was created using the data merge tool provided in the FIREX-AQ data archive (https://www-air.larc.nasa.gov/cgi-bin/ArcView/firexaq?MERGE=1, last access: 24 August 2022). Specifically, the measurements from data set nos. 1 to 10 in Table 1 were sequentially merged. The duplicated measurements were removed during each merging step, i.e., if the measurement of a compound existed in the merged data set and was above detection limit, then additional measurements of that compound were not added to the merged data set during the following merging steps.

Figure S3 shows the comparison of the study-averaged mixing ratios and standard deviations calculated from the merged data set (a subset of the original data sets) and the original data sets for the species merged to the UCI-WAS measurements. Each data set was pre-processed such that only the measurements covering the SoCAB and SJV were used for the comparison. The agreement (slope of 1.07 and r² of 1.00) between the merged data set and the original data set suggests that the merged data set can represent the original measurements.

To better represent the near-surface mixing ratios, the samples collected at altitudes higher than 4000 ft (1.2 km) above ground level (a.g.l.) were removed from the merged data set. The samples collected over the ocean were also excluded. After screening, the final data set for this study has 69 and 95 samples for the SoCAB and SJV, respectively. These samples are shown in Fig. 1. A total of 168 gas-phase compounds were measured, of which 137 had a detectable mixing ratio (Table 2). Given that the aircraft speed was about 125 m s⁻¹ and the sample collection time was about 40 s, the measurements represented approximately 5 km integrated space along the flight track. The average altitude (± standard deviation) of the samples was 625 (±237) m a.g.l. and 360 (±107) m a.g.l. in the SoCAB and SJV, respectively. Observations have shown that the daily maximum planetary boundary layer (PBL) height was approximately 1–1.5 km in the SoCAB and 0.5–1 km in SJV (Cui et al., 2019; Bianco et al., 2011). Therefore, the samples were most likely collected within the PBL. Since the samples were collected at least a few hundred meters away from emission sources, the reactive VOCs likely have undergone photochemical processing. Using the NO_x and NO_y measurements and assuming that the ambient [OH] was 4×10⁶ molec. cm⁻³, the photochemical age of the samples was estimated to be approximately 12 h on average (Cappa et al., 2012). This means that a species with an OH rate coefficient of 10⁻¹¹ cm³ molec.⁻¹ s⁻¹ had lost ∼80 % of its mass before they were sampled by the aircraft. Compounds with higher rate coefficients (e.g., the BVOCs) had more loss. The statistics of the observed mixing ratios of the gas-phase species and their OH rate coefficients are summarized in Table 2.

3 Results and discussion

3.1 Mixing ratio and spatial distribution of O₃, VOCs, and NO_x

The study-averaged aircraft-measured O₃ (±1σ) mixing ratio was 70.2±26.7 ppb in the SoCAB and 73.5±9.5 ppb in SJV. The maximum observed O₃ mixing ratio was 122.0 and 101.0 ppb in the SoCAB and SJV, respectively. The average non-CH₄ VOC mixing ratio (±1σ) in the SoCAB and SJV was 36.9.0±7.3 and 45.8±5.6 ppb, respectively (for simplicity, we use VOC to represent non-CH₄ VOC hereafter). The higher VOC levels in SJV were mainly driven by methanol. The average observed methanol was 17.1 ppb in SJV, which doubled the average 7.7 ppb observed in the SoCAB. The average aircraft-measured NO_x (±1σ) was 3.8±4.8 ppb in the SoCAB, which was 3.5 times the NO_x (±1σ) of 1.1±0.6 ppb in SJV. The high NO_x levels in the SoCAB resulted in a relatively lower VOC-to-NO_x ratio of 9.7±12.4 compared to 41.6±23.3 in SJV.

The spatial distributions of O₃, VOCs, and NO_x are shown in Fig. 1a–c. In the SoCAB, the mixing ratios of O₃, VOCs, and NO_x generally increased from coastal to inland regions, with the highest mixing ratios occurring near the northern boundary of the SoCAB. The coast–inland gradient likely resulted from the accumulation and chemical aging of the air pollutants as they were transported eastwards. In SJV, the mixing ratios of O₃, VOCs, and NO_x were more homogeneously distributed, i.e., the occurrence frequency of the high mixing ratios was smaller compared to that in the SoCAB (Figs. S4–S6). Since the very high mixing ratios determine the design values (Parrish et al., 2017), the result suggests that O₃ in the SoCAB is more prone to exceeding the NAAQS. This is consistent with the higher O₃ design values in the SoCAB compared to SJV that resulted from analyses using the monitoring network data (Parrish et al., 2017).

Table 2 Statistics of the mixing ratios (median, average, 1σ standard deviation, and maximum values in parts per trillion (ppt), unless otherwise specified) and OH reaction rate coefficients of the measured VOCs in the SoCAB and SJV.

^a The following species were measured but not reported as their mixing ratios were below detection limit: cis-2-butene, 1,2-butadiene, 1-buten-3-yne, 1,3-butadiyne, 1-butyne, 2-butyne, cis-2-pentene, 3-methyl-1-pentene/4-methyl-1-pentene, 1-decene, cyclopentene, ethynylbenzene, chlorobenzene, tricyclene, camphene, myrcene, limonene, Δ3-carene, 2-methylfuran, 3-methylfuran, benzofuran, 1,3-butadiyne, chloroiodomethane, 2-methyl-3-buten-2-ol, methylacrylonitrile, pyrrole, 2-ethylfuran, dimethylfurans, vinylfuran, 3-furaldehyde, and 1,3-pentadiene. The mixing ratios of carbon suboxide, 2,3-butanedione, tetrahydrofuran, ethyl acetate, methyl propionate, and methanthiol from the HR-ToF-GC/MS measurement was estimated using relative sensitivities. The sum of these species accounted for less than 0.2 % of the total VOC mixing ratio in the SoCAB and SJV. The following abbreviations are used: D5 represents decamethylcyclopentasiloxane, PAN represents peroxyacetyl nitrate, PPN represents peroxylpropionyl nitrate, APAN represents peroxyacryloyl nitrate, and PBN represents peroxybutyryl nitrate. ^b n/a represents not applicable because the VOCs are below the detection limit. ^c The unit for k_OH is 10⁻¹² cm³ molec.⁻¹ s⁻¹. k_OH values are given at 298 K. References for the k_OH values are provided in the text. ^d WAS refers to the UC Irvine (University of California Irvine) WAS, unless otherwise stated. The H₃O⁺ ToF-CIMS measurements and the formic acid mixing ratio (from iodide ToF-CIMS) were only available during the flight on 5 September 2019. Hydrogen cyanide was measured by the CalTech (California Institute of Technology) CIMS and HR-ToF-GC/MS. The high time resolution (1 Hz) of the CalTech CIMS measurement was used. The mixing ratio of isobutyl nitrate was derived from the difference between the sum of isobutyl nitrate and 2-butyl nitrate (measured by the HR-ToF-GC/MS) and 2-butyl nitrate (measured by the UC Irvine WAS).

3.2 Composition and source signatures of VOCs

The measured VOCs are grouped into chemical families based on their characteristic functional groups or emission sources (for biogenic VOCs and their oxidation products). The average VOC composition from the two research flights was similar, so the study-averaged composition (i.e., average of all samples collected during the two flights) is presented (Fig. 2). The mean, median, and maximum mixing ratios for each VOC measured in this study are listed in Table 2. Oxygenated VOCs (OVOCs) and alkanes dominated the measured VOC mixing ratios, accounting for 91 %–96 % of the total measured VOC mixing ratio in both the SoCAB and SJV. This is comparable to the measurements conducted at Pasadena in 2010 during the California Research at the Nexus of Air Quality and Climate Change (CalNex) field study, where OVOCs and alkanes comprised ∼80 % of the measured reactive organic carbon (ROC) mass (Heald et al., 2020). They are also the two most abundant chemical families in other regions of the world, e.g., in Seoul, South Korea (Simpson et al., 2020; Kim et al., 2018), and Hong Kong (Ling et al., 2014). Specifically, OVOCs accounted for 74 % and 91 % of the total measured VOC mixing ratio in the SoCAB and SJV, respectively, and the contributions of alkanes were 17 % and 5 % in the SoCAB and SJV, respectively. In contrast, primary biogenic VOCs (BVOCs) are a minor fraction (<2 %) of the total measured VOC mixing ratio in both basins.

Figure 2 The campaign-averaged VOC composition for the SoCAB and SJV.

Methanol was the most abundant OVOC in both basins, which was responsible for 28 % and 41 % of the OVOC mixing ratio in the SoCAB and SJV, respectively. Methanol in the SoCAB (7.7 ppb) was about half of the methanol levels in SJV (17.1 ppb). Very high methanol (>25 ppb) was observed over the southeastern (e.g., Delano, Tulare, and Visalia) regions of Fresno, where dense, confined animal farming operations (CAFOs) are located, suggesting direct methanol emissions from dairy operations. Similar to methanol, formic acid in the SoCAB (4.3 ppb) was about half of the formic acid in SJV (9.7 ppb). Formic acid has been identified as a major fatty acid from dairy operations (Page et al., 2014; Mårtensson et al., 1999). Formic acid also increased with methanol (r²=0.7), suggesting that dairies may be a major source of formic acid in SJV. The region with a high methanol mixing ratio also features high ethanol levels, which likely resulted from dairy emissions as well. Studies have shown that methanol and ethanol are the dominant VOCs emitted from dairy cows and their waste (Gentner et al., 2014; Shaw et al., 2007; Sun et al., 2008). In addition, ethanol is likely the most abundant VOC species emitted from dairy silages in SJV (Malkina et al., 2011; Yuan et al., 2017b), while consumer product use has a sizable contribution to its ambient mixing ratios in urban cores (Mcdonald et al., 2018; Coggon et al., 2021). Vehicle operations also emit ethanol into the atmosphere due to the increasing use of the E10 and E85 ethanol–gasoline blends (De Gouw et al., 2012; Gkatzelis et al., 2021). More detailed surface-level source apportionment methods must be employed to determine the specificity of its origin. The high ethanol levels in SJV may lead to high mixing ratios of its oxidation product, e.g., acetaldehyde, which was 16 % higher in SJV than that in the SoCAB.

Formaldehyde (HCHO) was the second and third most abundant OVOC, with a comparable mixing ratio (∼4.5 ppb) in the SoCAB and SJV, respectively. HCHO contributed to 16 % and 10 % to the OVOC mixing ratio in the SoCAB and SJV, respectively. Primary sources of HCHO include automotive exhaust (Anderson et al., 1996), industrial emissions (Salthammer et al., 2010), biomass burning (Holzinger et al., 1999), and off-gassing from building materials (Gilbert et al., 2008; Liu et al., 2016). HCHO can also form from the photooxidation of VOCs, such as alkenes and BVOCs (Choi et al., 2010; Parrish et al., 2012). Given the contrast between anthropogenic emission sources in the SoCAB and SJV (e.g., the CO emissions in the SoCAB are 1.4 times the CO emissions in SJV, as estimated from California Air Resources Board's emission inventory), the similarity of HCHO mixing ratio between the two regions during the 2 flight days suggests that photooxidation of non-anthropogenic emissions (e.g., BVOCs) may be the dominant regional driver of HCHO, which is consistent with the findings from previous studies in North America (Lee et al., 1998; Palmer et al., 2003). The high methanol, ethanol, and formic acid mixing ratios in SJV made the OVOC level in SJV 52 % higher compared to the OVOC level in the SoCAB. Acetone also had sizable contributions to the OVOC mixing ratio (Fig. 2).

The composition of alkanes in the SoCAB and SJV was similar, but the total alkane mixing ratio was 2.6 times higher in the SoCAB. Ethane and propane were the dominant species. Specifically, ethane accounted for ∼40 %–50 % of the total alkane mixing ratio, followed by propane (∼25 %) in both regions. The linear regressions of propane versus ethane for the SoCAB and SJV fell on the same line, with a Pearson's r value of 0.96 and a slope of 0.6. Peischl et al. (2013) summarized the propane versus ethane slope values from different sources. The slope obtained from this study is consistent with the aircraft observation over the SoCAB in 2010 and fell within the slope range for local oil and gas well emissions (Peischl et al., 2013). In contrast, the propane-to-ethane ratios for pipeline quality natural gas are ∼0.15, as heavier alkanes are removed during processing (Wennberg et al., 2012; Peischl et al., 2013). On-road emission ratios of propane to ethane are also very low, but relatively minor, as gasoline and diesel do not contain large amounts of these alkanes (Fraser et al., 1998). This result suggests that oil and gas production activities are likely the major source of propane and ethane in the SoCAB and SJV. Isopentane and n-pentane were tightly correlated in both basins but with different slopes. The isopentane/n-pentane ratio was 2.4 in the SoCAB. This value is consistent with ratios of 2.3–3.8 observed for regions highly impacted by vehicular emissions (Gilman et al., 2013). In contrast, the isopentane/n-pentane ratio was 1.8 for SJV, suggesting that the air mass was mixed with non-urban emissions.

The BVOCs accounted for <2 % of the total VOC mixing ratio in both basins. In the BVOC category, isoprene is assumed to be only from biogenic emissions, and anthropogenically driven isoprene emissions are negligible in summer (Guenther et al., 2012; Reimann et al., 2000). The BVOCs were dominated by isoprene and its oxidation products methacrolein (MAC) and methyl vinyl ketone (MVK; Wennberg et al., 2018), the sum of which accounted for ∼95 % of the total observed BVOC mixing ratio. MVK was the most abundant BVOC species that contributed ∼50 % of the BVOC mixing ratio, followed by nearly equal contributions of isoprene and MAC. The monoterpenes (such as α- and β-pinene) were minor, with their average mixing ratios smaller than 10 ppt.

3.3 Total OH reactivity

Quantifying the OH reactivity (cOHR) of reactive gases provides estimates of the potential roles of individual O₃ precursors (Ling et al., 2014; Gilman et al., 2009; Mcdonald et al., 2018). The cOHR of a compound is calculated from the compound concentration multiplied by its reaction rate coefficient with the OH radical. The total cOHR is the sum of the cOHR of all reactants in the atmosphere, which is given by the following equation:

$$\begin{array}{}\text{(1)}& \begin{array}{rl}& {\mathrm{cOHR}}_{\mathrm{TOTAL}}={\mathrm{cOHR}}_{{\mathrm{CH}}_{\mathrm{4}}}+{\mathrm{cOHR}}_{\mathrm{CO}}+{\mathrm{cOHR}}_{{\mathrm{NO}}_x}\\ & +{\mathrm{cOHR}}_{\mathrm{VOC}}=k_{\mathrm{OH}+{\mathrm{CH}}_{\mathrm{4}}}\left[{\mathrm{CH}}_{\mathrm{4}}\right]+k_{\mathrm{OH}+\mathrm{CO}}\left[\mathrm{CO}\right]\\ & +k_{\mathrm{OH}+{\mathrm{NO}}_x}\left[{\mathrm{NO}}_x\right]+\sum \left(k_{\mathrm{OH}+\mathrm{VOC}}\left[\mathrm{VOC}\right]\right),\end{array}\end{array}$$

where the subscript of cOHR indicates the species X used to calculate the cOHR, [X] is the mixing ratio of X, and k_OH+X is the reaction rate coefficient of X with the OH radical. The k_OH+X values were obtained from the literature or kinetic databases (Atkinson and Arey, 2003; Atkinson et al., 1997, 2004, 2006, 2008; Kwok and Atkinson, 1995; Burkholder et al., 2015; Alton and Browne, 2020; Atkinson, 1986; Bierbach et al., 1994, 1995; Borduas et al., 2016; Lauraguais et al., 2015; Roberts et al., 2003; Semadeni et al., 1995; National Institute of Standards and Technology Chemical Kinetics Database) and are tabulated in Table 2. We used the rate constants at 298 K. This is reasonable, as the average ambient air temperature (± standard deviation) of the samples was 26.7(±2.1) and 31.0(±1.6) ^∘C in the SoCAB and SJV, respectively. There is likely missing cOHR from unmeasured VOCs due to the limitation of the quantification methods. Previous studies show that the fraction of the missing cOHR ranges from 5 % to 80 %, depending on the sampling location, time, and the number of measured VOC species (Yang et al., 2016; Hansen et al., 2021). With the extensive VOC measurements in this study, it is expected that the fraction of the missing cOHR is close to the lower end of the 5 %–80 % range. Nevertheless, the cOHR_VOC reported in this study should be interpreted as a minimum for the cOHR of the total VOCs.

Figure 3 The total measured cOHR for the SoCAB and SJV.

The cOHR_TOTAL was 6.1 and 4.6 s⁻¹ for the SoCAB and SJV, respectively (Fig. 3). The O₃ mixing ratio generally increased nonlinearly with increasing cOHR_VOC, cOHR_CO, cOHR${}_{{\mathrm{CH}}_{\mathrm{4}}}$, and cOHR${}_{{\mathrm{NO}}_x}$ in both basins, especially for O₃ >40 ppb (Fig. S7). The cOHR_TOTAL values observed in this study are generally less than half of the cOHR_TOTAL reported in Pasadena and central California 10–20 years ago (Table S1). However, we note that the comparison may be biased, as the previous studies are from ground measurements. The percentage contributions of CH₄, CO, NO_x, and VOCs to cOHR_TOTAL were similar between the SoCAB and SJV, with the VOCs accounting for ∼60 % of the cOHR_TOTAL (Fig. 3). For reference, the global annual mean contribution of VOCs to cOHR_TOTAL is ∼50 % from a recent review study (Heald and Kroll, 2020). The large contribution of VOCs to cOHR_TOTAL is consistent with previous measurements in California (Table S1), suggesting that VOCs remain a high potential for O₃ formation in the SoCAB and SJV. CO was the second most important species following VOCs and was responsible for ∼18 % of the cOHR_TOTAL in both basins. The contribution of NO_x to cOHR_TOTAL was 17 % in the SoCAB and 6 % in SJV.

3.4 OH reactivity of individual VOCs

The cOHR of the individual species for the SoCAB and SJV generally follows a similar order. The linear regression of the cOHR_SOCAB versus the cOHR_SJV for the individual species shows a slope of 1.3 and r² of 0.8 (Fig. 4), confirming that the overall cOHR in the SoCAB was 30 % higher than that in SJV. The top five VOCs that have the largest cOHR in the SoCAB were HCHO, acetaldehyde, isoprene, methanol, and MVK in descending order. In SJV, the top five most abundant VOCs in terms of cOHR were formaldehyde, acetaldehyde, methanol, ethanol, and formic acid. The sum of these species accounted for 63 % and 73 % of the calculated cOHR_VOC in the SoCAB and SJV, respectively. These results suggest that (i) aldehydes are the key compounds contributing to cOHR in both basins, (ii) biogenic VOCs are important for cOHR in the SoCAB, and (iii) dairy emissions are likely important for cOHR in SJV. Compared to the cOHR of the VOCs measured in Pasadena in 2010 during the CalNex campaign (57 species measured in common), the majority of the species measured in the SoCAB (52 out of 57) in 2019 had smaller cOHR values, with a mean percentage decrease of 53 %.

Figure 4 Scatterplot of cOHR_SOCAB versus cOHR_SJV for the individual species in the (a) linear scale and (b) logarithmic scale. The red line represents linear regression using the orthogonal distance regression method.

The OVOCs category was the largest contributor to the cOHR_VOC among all the categories (Fig. 5; Table S2). The cOHR_OVOC was 3.6 s⁻¹ in the SoCAB and 3.1 s⁻¹ in SJV, which was responsible for 59 % and 68 % of the cOHR_VOC in the SoCAB and SJV, respectively. The contribution of the OVOCs to the cOHR_VOC was among the highest compared to the cOHR_OVOC measurements in other parts of the world (Table S2). For example, the percentage of the OVOC contribution was substantially higher than that in mainland China (calculated from emission inventories), Seoul (South Korea, surface measurement), and Mexico City (Mexico, surface measurement; Table S2; we note that part of the difference may be due to the different study approaches, e.g., ground vs. flight measurements.) HCHO was the most important OVOC in terms of cOHR, which was responsible for 45 % and 36 % of the cOHR_OVOC in the SoCAB and SJV, respectively. This percentage translates to HCHO, accounting for ∼30 % of the cOHR_VOC in both basins. Acetaldehyde contributed 21 % of the cOHR_OVOC and ∼15 % of the cOHR_VOC in both basins. Since ambient measurements of HCHO and acetaldehyde are scant compared to many other VOCs (e.g., aromatics), much remains to be learned about the sources and fate of these species. Methanol contributed 8 % and 15 % of the cOHR_OVOC in the SoCAB and SJV, respectively, while the ethanol contribution to the cOHR_OVOC was ∼7 % in both basins. The sum of HCHO, acetaldehyde, methanol, and ethanol accounted for 51 % and 69 % of the cOHR_VOC in the SoCAB and SJV, respectively. Our measurements are consistent with modeling results showing that 30 %–50 % of cOHR_VOC in California is due to aldehydes and other oxygenated species from over a decade prior (Steiner et al., 2008).

Although BVOCs were only responsible for <2 % of the total measured VOC mixing ratio, they contributed 21 % and 6 % of the cOHR_VOC in the SoCAB and SJV, respectively. Therefore, it is important that the reactivity of BVOCs is well represented in photochemical models, especially in the SoCAB. The relatively high cOHR_BVOC is due to the high chemical reactivity of the BVOCs, i.e., the reaction rate constants of BVOCs with OH radicals are generally 100 times greater than those of alkanes (Table 2). Among the BVOCs, isoprene accounted for 59 % and 44 % of the cOHR_BVOC in the SoCAB and SJV, respectively. The isoprene oxidation products MAC and MVK, together, accounted for ∼45 % of cOHR_BVOC in both regions. The contribution of monoterpenes to cOHR_BVOC was <10 % in both basins. This should be considered as a lower limit, as a large fraction of monoterpenes may have reacted away by the time they were measured from the aircraft. The dominance of isoprene and its oxidation products in cOHR_BVOC is consistent with the high isoprene emissions from the oak woodlands throughout the foothills of the Sierra Nevada mountains and near the northern boundaries of the SoCAB (Fig. S8a; Arey et al., 1995; Benjamin et al., 1997; Misztal et al., 2014).

Figure 5 The measured cOHR of VOCs in the SoCAB and SJV.

In contrast, the non-CH₄ alkanes only contributed 7 % and 3 % of the cOHR_VOC in the SoCAB and SJV, respectively, despite their greater atmospheric abundances. The sum of cOHR_ethane and cOHR_propane accounted for 21 % and 31 % of the cOHR_alkanes in the SoCAB and SJV, respectively. The substantially smaller contribution of alkanes to cOHR_VOC, compared to their contribution to the total VOC mixing ratio, is due to their low chemical reactivity. On the other hand, the longer-chain alkanes dominated cOHR_alkanes. Alkenes, aromatics, and other uncategorized VOCs (see “Other VOCs” in Table 2) together accounted for <10 % of the cOHR_VOC in both basins.

3.5 Spatial variability in cOHR_VOC

The cOHR_VOC showed distinct frequency distributions in the SoCAB and SJV (Fig. 6). The cOHR_VOC in the SoCAB spanned from 0 to 8 s⁻¹, with the highest occurrence frequency at 0–1 s⁻¹ and lowest at 7–8 s⁻¹. Higher cOHR_VOC occurred in more inland regions (Fig. 1), which was similar to the spatial distribution of O₃. This is likely due to the accumulation of air pollutants in downwind locations as they were transported from west to east during the day in the SoCAB (Carreras-Sospedra et al., 2006). In contrast, the cOHR_VOC in SJV was narrowly distributed and centered at 1–3 s⁻¹. In addition, the BVOCs in the SoCAB showed increasing contribution to the cOHR_VOC as the cOHR_VOC increased (see the pie charts in Fig. 6a). The BVOC contribution reached up to 20 %–30 % when the cOHR_VOC was above 4 s⁻¹ near the northern boundary of the SoCAB (Figs. 1, S8b). This result suggests that BVOCs are likely key O₃ precursors during high O₃ episodes in the SoCAB. A similar result was not observed in SJV, i.e., the OVOCs dominated the cOHR_VOC across the cOHR_VOC range. The minor role of the BVOCs in O₃ formation in SJV was likely because of the daytime up-valley winds that prevented the entrainment of the BVOCs emitted over the Sierra Nevada mountains into the valley (Zhong et al., 2004).

Figure 6 Frequency distribution of cOHR_VOC in the (a) SoCAB and (b) SJV. Also shown above each 1 s⁻¹ binned cOHR_VOC range is a pie chart presenting the average contribution to the cOHR_VOC by VOC categories (shown in the legend).

4 Conclusions and implications

In this work, we have updated the mixing ratios and cOHR of a wide range of speciated VOCs in the SoCAB and SJV of California. The limited number of flights is compensated by the wide range of speciated VOCs analyzed. The spatially resolved data set and analyses can be used to evaluate the performance of photochemical models. Our measurements suggest that OVOCs are an important chemical class contributing to the cOHR in California. Specifically, HCHO, acetaldehyde, methanol, and ethanol are the key OVOC species, the sum of which accounted for ∼ 50 %–70 % of the cOHR_VOC in the SoCAB and SJV. The observation is consistent with previous field and modeling studies, showing that OVOCs play critical roles in atmospheric chemistry (Lou et al., 2010; Wu et al., 2020). OVOCs have also been suggested to be responsible for a major fraction of the “missing OH reactivity” (Dolgorouky et al., 2012; Karl et al., 2009; Lou et al., 2010), i.e., the difference between directly measured OHR_TOTAL and the sum of the cOHR from individually measured species. However, quantifying OVOCs is still challenging, and measurements of their ambient mixing ratios are still lacking in many regions. Our work reinforces that elucidating the chemical composition of OVOCs and their sources will advance our capability to predict O₃ abundance and develop O₃ reduction strategies.

Biogenic emissions represent a significant source of VOCs for O₃ formation, especially in the SoCAB. On average, 21 % and 6 % of the cOHR_VOC are contributed by primary BVOCs in the SoCAB and SJV, respectively, assuming that isoprene is solely from biogenic sources. The contribution of BVOCs to cOHR_VOC was greatest near the northern edge of the SoCAB. This is consistent with the measurements in Pasadena, California, during the CalNex campaign, where isoprene was the single largest contributor to the cOHR_VOC (Heald et al., 2020). The importance of BVOCs as a contributor to cOHR has also been reported for other urban environments, such as London, United Kingdom (Whalley et al., 2016), Beijing, China (Mo et al., 2018), and Seoul, South Korea (Kim et al., 2018). The cOHR_BVOC reported in this study should be considered as an underestimation, since a fraction of HCHO may be produced from the oxidation of BVOCs (Choi et al., 2010). Source apportionment of HCHO on the regional scale is thus critical for improving our future understanding of the contribution of biogenic emissions to O₃ production. Besides reacting with the OH radical, HCHO is also a source of HO_x radicals (${\mathrm{HO}}_x=\mathrm{HO}+{\mathrm{HO}}_{\mathrm{2}}+{\mathrm{RO}}_{\mathrm{2}}$) via photolysis. Reducing HCHO has the added benefit of reducing the production rate of HO_x, thereby lowering the production rate of O₃ (Pusede and Cohen, 2012).

As policies continue to curb anthropogenic emissions, BVOCs will continue to become increasingly important in atmospheric chemistry and O₃ formation (Gu et al., 2021). The temperature rise due to a warming climate will likely further enhance the emissions of BVOCs in the immediate future. Since BVOCs are highly reactive, a small increase in BVOCs will disproportionately enhance their contribution to the total hydroxyl radical reactivity. This effect makes BVOCs even more critical during peak O₃ events that may lead to O₃ exceedance. Our current knowledge of the role of BVOCs in the O₃ formation in the SoCAB region is still highly uncertain, e.g., a recent photochemical modeling study suggests that there is a significant underestimation of biogenic emissions in the SoCAB (Cai et al., 2019). As the contribution of BVOCs to O₃ production may represent a substantial fraction of the background O₃ that determines how stringent the O₃ standards will be, a more precise understanding of the magnitude and timing of BVOCs in O₃ formation is warranted. Such evaluation must be carefully paired with our evolving understanding of the biospheric feedback in response to changing climate to improve mitigation and adaptation actions and future air quality management planning.