Abstract
Abstract. The San Joaquin Valley of California is known for excessive ozone air pollution owing to local production combined with terrain-induced flow patterns that channel air in from the highly populated San Francisco Bay area and stagnate it against the surrounding mountains. During the summer, ozone violations of the National Ambient Air Quality Standards (NAAQS) are notoriously common, with the San Joaquin Valley having an average of 115 violations of the current 70 ppb standard each year between 2012 and 2016. Because regional photochemical production peaks with actinic radiation, most studies focus on the daytime, and consequently the nocturnal chemistry and dynamics that contribute to these summertime high-ozone events are not as well elucidated. Here we investigate the hypothesis that on nights with a strong low-level jet (LLJ), ozone in the residual layer (RL) is more effectively mixed down into the nocturnal boundary layer (NBL) where it is subject to dry deposition to the surface, the rate of which is itself enhanced by the strength of the LLJ, resulting in lower ozone levels the following day. Conversely, nights with a weaker LLJ will sustain RLs that are more decoupled from the surface, retaining more ozone overnight, and thus lead to more fumigation of ozone the following mornings, giving rise to higher ozone concentrations the following afternoon. The relative importance of this effect, however, is strongly dependent on the net chemical overnight loss of Ox (here [Ox] ≡ [O3] + [NO2]), which we show is highly uncertain, without knowing the ultimate chemical fate of the nitrate radical (NO3). We analyze aircraft data from a study sponsored by the California Air Resources Board (CARB) aimed at quantifying the role of RL ozone in the high-ozone events in this area. By formulating nocturnal scalar budgets based on pairs of consecutive flights (the first around midnight and the second just after sunrise the following day), we estimate the rate of vertical mixing between the RL and the NBL and thereby infer eddy diffusion coefficients in the top half of the NBL. The average depth of the NBL observed on the 12 pairs of flights for this study was 210(±50) m. Of the average −1.3 ppb h−1 loss of Ox in the NBL during the overnight hours from midnight to 06:00 PST, −0.2 ppb h−1 was found to be due to horizontal advection, −1.2 ppb h−1 due to dry deposition, −2.7 ppb h−1 to chemical loss via nitrate production, and +2.8 ppb h−1 from mixing into the NBL from the RL. Based on the observed gradients of Ox in the top half of the NBL, these mixing rates yield eddy diffusivity estimates ranging from 1.1 to 3.5 m2 s−1, which are found to inversely correlate with the following afternoon's ozone levels, providing support for our hypothesis. The diffusivity values are approximately an order of magnitude larger than the few others reported in the extant literature for the NBL, which further suggests that the vigorous nature of nocturnal mixing in this region, due to the LLJ, may have an important control on daytime ozone levels. Additionally, we propose that the LLJ is a branch of what is colloquially referred to as the Fresno eddy, which has been previously proposed to recirculate pollutants. However, vertical mixing from the LLJ may counteract this effect, which highlights the importance of studying the LLJ and Fresno eddy as a single interactive system. The synoptic conditions that are associated with strong LLJs are found to contain deeper troughs along the California coastline. The LLJs observed during this study had an average centerline height of 340 m, average speed of 9.9 m s−1 (σ=3.1 m s−1), and a typical peak timing around 23:00 PST. A total of 7 years of 915 MHz radioacoustic sounding system and surface air quality network data show an inverse correlation between the jet strength and ozone the following day, further suggesting that air quality models need to forecast the strength of the LLJ in order to more accurately predict ozone violations.
Highlights
The main source of air for California’s southern San Joaquin Valley (SSJV) is incoming maritime flow from the San Francisco Bay area, which gets accelerated toward the southern end of the valley as a consequence of the valley–mountain circulation (Rampanelli et al, 2004; Schmidli and Rottuno, 2010)
We find that nocturnally and spatially averaged turbulent kinetic energy (TKE) in the nocturnal boundary layer (NBL) ranges from 0.35 to 1.02 m2 s−2, which is very comparable to values obtained in other NBL studies (Banta et al, 2006; Lenschow et al, 1988)
During the late-night flights in stable environments, the flight crew reported many patches of turbulence. While most of these subjective reports were during low approaches and likely attributable to wind shear between the level jet (LLJ) and the surface, they noted that some patches corresponded to what appeared to be elevated mixed layers, i.e., layers of air in which virtual potential temperature was observed to decrease with height
Summary
The main source of air for California’s southern San Joaquin Valley (SSJV) is incoming maritime flow from the San Francisco Bay area, which gets accelerated toward the southern end of the valley as a consequence of the valley–mountain circulation (Rampanelli et al, 2004; Schmidli and Rottuno, 2010). Entrainment has been shown to be a significant factor for near-surface air quality and more generally for scalar budgets, as the two interacting layers often have different trace gas concentrations (Lehning et al, 1998; Trousdell et al, 2016; Vilà-Guerau de Arellano et al, 2011) At night, another type of gas exchange can occur between the aforementioned NBL and the RL by shear-induced mixing. Extensive observations of the structure of the NBL indicate that a localized wind maximum near the top of the NBL, known as a low-level jet (LLJ), is often present (Banta et al, 2002; Garratt, 1985; Kraus et al, 1985) This LLJ is able to drive sheer production of turbulence, thereby promoting the mixing between these layers despite the stable stratification. We look at other metrics of NBL turbulence in our campaign data such as turbulent kinetic energy (TKE), bulk Richardson number (BRN), and elevated mixed layers in order to further support our findings (Sect. 3.5 and 3.6)
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