Airborne observations and modeling of springtime stratosphere-to-troposphere transport over California

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Open Access Atmos. Chem. Phys., 13, 12481–12494, 2013 doi:10.5194/acp-13-12481-2013 © Author(s) 2013. CC Attribution 3.0 License. Atmospheric Chemistry and Physics Airborne observations and modeling of springtime stratosphere-to-troposphere transport over California E. L. Yates1, L. T. Iraci1, M. C. Roby2, R. B. Pierce3, M. S. Johnson4, P. J. Reddy5, J. M. Tadic´1,*, M. Loewenstein1, and W. Gore1 1Atmospheric Science Branch, NASA Ames Research Center, Moffett Field, CA 94035, USA 2Department of Meteorology, San Jose State University, San Jose, CA 95192-0104, USA 3NOAA/NESDIS Advanced Satellite Products Branch Madison, WI 53706, USA 4Biospheric Science Branch, NASA Ames Research Center, Moffett Field, CA 94035, USA 5Air Pollution Control Division, Colorado Department of Public Health & Environment, Denver, CO 80246, USA *now at: Department of Global Ecology, Carnegie Institution for Science, Stanford, CA 94305, USA Correspondence to: E. L. Yates ( Received: 6 March 2013 – Published in Atmos. Chem. Phys. Discuss.: 18 April 2013 Revised: 22 November 2013 – Accepted: 23 November 2013 – Published: 20 December 2013 Abstract. Stratosphere-to-troposphere transport (STT) results in air masses of stratospheric origin intruding into the free troposphere. Once in the free troposphere, ozone (O3)rich stratospheric air can be transported and mixed with tropospheric air masses, contributing to the tropospheric O3 budget. Evidence of STT can be identified based on the differences in the trace gas composition of the two regions. Because O3 is present in such large quantities in the stratosphere compared to the troposphere, it is frequently used as a tracer for STT events. This work reports on airborne in situ measurements of O3 and other trace gases during two STT events observed over California, USA. The first, on 14 May 2012, was associated with a cutoff low, and the second, on 5 June 2012, occurred during a post-trough, building ridge event. In each STT event, airborne measurements identified high O3 within the stratospheric intrusion, which were observed as low as 3 km above sea level. During both events the stratospheric air mass was characterized by elevated O3 mixing ratios and reduced carbon dioxide (CO2) and water vapor. The reproducible observation of reduced CO2 within the stratospheric air mass supports the use of non-conventional tracers as an additional method for detecting STT. A detailed meteorological analysis of each STT event is presented, and observations are interpreted with the Realtime Air Quality Modeling System (RAQMS). The implications of the two STT events are discussed in terms of the impact on the total tropospheric O3 budget and the impact on air quality and policy-making. 1 Introduction Transport of stratospheric air into the troposphere, referred to as stratosphere-to-troposphere transport (STT), contributes to and alters the trace gas composition of the troposphere, and as such STT has been extensively studied for over 50 yr (e.g., Danielsen, 1968; Danielsen and Mohnen, 1977; Lamarque and Hess, 1994; Sprenger et al., 2003; Thompson et al., 2007; Lefohn et al., 2011). Ozone (O3) is present in large quantities in the stratosphere compared to the troposphere and is commonly used as a tracer for STT. In the free troposphere, air masses of stratospheric origin can be transported and mixed with tropospheric air masses, typically forming filamentary structures, which appear as O3 laminae in O3 profiles detected by ozonesondes, in situ aircraft measurements and O3 lidar (Zanis et al., 2003; Cooper et al., 2005; Trickl et al., 2011; Langford et al., 2012). Understanding the dynamic processes that control the tropospheric O3 budget is of importance not only for understanding surface air quality in areas affected by STT, but also because upper tropospheric O3 is an important greenhouse gas affecting outgoing longwave radiation (Worden et al., 2008) and impacting surface temperature (IPCC, 2007). Published by Copernicus Publications on behalf of the European Geosciences Union. 12482 E. L. Yates et al.: Springtime stratosphere-to-troposphere transport STT events are episodic in nature and vary considerably with latitude and season. In western North America (the end of the Pacific storm track) peak STT occurs during the late winter to late spring (e.g., Sprenger et al., 2003; Stohl et al., 2003; Skerlak et al., 2013), when synoptic-scale and mesoscale processes (e.g., tropopause folds in the vicinity of the polar and subpolar jets, cutoff lows, mesoscale convective complexes) facilitate the tropopause to fold, allowing for stratospheric air masses to be transported downward to the troposphere. Tropopause folds and cutoff lows, which emphasize the vertical structure (former) and horizontal structure (latter) in which a stratospheric intrusion can occur (Stohl et al., 2003), have been identified as the most important mechanisms to cause STT and have subsequently been the focus of STT investigations (e.g., Danielsen and Mohnen, 1977; Ebel, 1991; Vaughan et al., 1994; Bonasoni, et al., 2000; Søensen and Nielson, 2001; Lefohn et al., 2011). The frequency and magnitude of STT events are important factors in understanding the possible degree to which they affect surface and free troposphere O3 mixing ratios (Lefohn et al., 2011). The stratosphere and troposphere are separated by the tropopause. Traditionally the tropopause is defined by the “thermal tropopause”, which is the lowest level at which the temperature lapse rate decreases to 2 K km−1 or less and the averaged lapse rate between this level and any level within 2 km does not exceed 2 K km−1 (WMO, 1986). In the extratropics the tropopause corresponds well with a surface of constant potential vorticity (PV), allowing for a “dynamical tropopause” definition. Tropopause PV values in literature range from 1.6 to 3.5 potential vorticity units (PVU) with 2 PVU used most often (Stohl et al., 2003). Both of these tropopause definitions are routinely used in forecasting and modeling STT events (e.g., Sprenger et al., 2003; Stohl et al., 2003). Observations of STT have been reported in long-term data sets from mountain-top O3 sites measuring the free troposphere (e.g., Bonasoni et al., 2000; Stohl et al., 2000) and from O3 profiles measured by aircraft, ozonesondes and O3 lidar (e.g., Zanis et al., 2003; Cooper et al., 2005; Bowman et al., 2007; Bourqui and Trepainer, 2010; Langford et al., 2012). Identifying STT within the tropospheric boundary layer, especially at near-sea-level surface sites, is challenging. The stratospheric characteristics (high O3, low humidity, high PV) may be lost by the time this air is entrained into the boundary layer, making STT difficult to diagnose and forecast. In addition, the O3 mixing ratio within STT events is expected to be highly variable depending on the stratospheric origin and degree of mixing in the free troposphere. Although evidence of STT at sea-level surface sites has been presented (Chung and Dann, 1985; Langford et al., 2012; Lefohn et al., 2012; Lin et al., 2012), the magnitude of the effects of STT on boundary layer O3 mixing ratios is still under debate (Fiore et al., 2003; Langford et al., 2009; Lefohn et al., 2011; Lin et al., 2012). The United States Environmental Protection Agency (EPA) sets National Ambient Air Quality Standards (NAAQS) for ground-level O3, which are used to assess air quality. The 2008 NAAQS for O3 require that the 3 yr average of the annual fourth-highest daily maximum 8 h mean mixing ratio be less than or equal to 75 ppbv (parts per billion by volume) (US EPA, 2006), with a decision on the proposed reduction of the NAAQS O3 target to 60–70 ppbv due in 2014 (US EPA, 2010). The formulation of the NAAQS O3 standard relies on the accurate identification of a representative background mixing ratio of O3 that would occur in the United States in the absence of anthropogenic contributions. Current background O3 mixing ratios are estimated to be in the range of 15–35 ppbv (Fiore et al., 2003), contributing up to 47 % towards the current NAAQS O3 target of 75 ppbv. Some studies have reported higher background O3 mixing ratios, particularly in springtime, suggesting that STT has a significant influence on the background O3 mixing ratios (Cooper et al., 2005; Hocking et al., 2007; Lefohn et al., 2011; Langford et al., 2012, Lin et al., 2012). If the proposed reduction of NAAQS O3 target is approved, the identification of STT and evidence of its contribution towards background O3 mixing ratios will become increasingly important, as the gap between background O3 and the NAAQS O3 target is reduced. The western United States, due to its location at the end of the North Pacific mid-latitude storm track, has been identified as a preferred location for deep STT reaching below 700 mbar (Sprenger and Wernli, 2003). Understanding the boundary conditions coming into the western United States is important for air quality issues. However large areas in the western United States have limited or no O3 data. In addition, the existing positive vertical gradient for O3, complex mountainous terrain of the western United States and resulting mesoscale dynamics further complicate efforts to model O3 concentrations. In this paper, a detailed analysis of two STT events occurring during spring 2012 over California, USA, is presented. This work reports airborne in situ measurements of O3 and other trace gases, providing supporting evidence towards of the use of a non-traditional stratospheric tracer (carbon dioxide, CO2), which can be used in conjunction with O3 to help identify and interpret STT. In support of the observations and the case for STT, the following evidence is provided: analyses of the meteorological situations and an evaluation of Realtime Air Quality Modeling System (RAQMS) used to forecast and interpret observations. Finally a discussion of the implications of the two events on air quality and policymaking is also presented. Atmos. Chem. Phys., 13, 12481–12494, 2013 E. L. Yates et al.: Springtime stratosphere-to-troposphere transport 12483 2 Experimental approach 2.1 Airborne instrumentation In situ measurements of O3 vertical profiles were carried out on board the Alpha Jet research aircraft as part of the Alpha Jet Atmospheric eXperiment (AJAX). The aircraft is based at and operated from NASA Ames Research Center at Moffett Field, CA (37.415 N, 122.050 W). Scientific instrumentation is housed within one of two externally mounted wing pods, each of which has a maximum payload weight of 136 kg. The aircraft was flown with one instrumented wing pod attached, containing an O3 monitor (described below) and a CO2 analyzer (Picarro Inc., model G2301-m), modified for flight installation The aircraft also carries GPS and inertial navigation systems that provide altitude, temperature and position information time-stamped with coordinated universal time (UTC) for each research flight. Measurements of O3 mixing ratios were performed using a commercial O3 monitor (2B Technologies Inc., model 205) based on ultraviolet (UV) absorption techniques and modified for flight worthiness. The dual-beam instrument uses two detection cells to measure simultaneously the UV light intensity differences between O3-scrubbed air and un-scrubbed air to give precise measurements of O3. The monitor has been modified by upgrading the pressure sensor and pump to allow measurements at high altitudes, including a lamp heater to improve the stability of the UV source, and the addition of heaters, temperature controllers and vibration isolators to control the monitor’s physical environment. The air intake is through Teflon tubing (perfluoroalkoxy polymer, PFA) with a backward-facing inlet positioned on the underside of the instrument wing pod. Air is delivered through a 5 µm PTFE (polytetrafluoroethylene) membrane filter to remove fine particles prior to analysis. The O3 monitor has undergone thorough instrument testing in the laboratory to determine the precision, linearity and overall accuracy. Eight-point calibration tests (ranging from 0 to 300 ppbv) were performed before and after each flight using an O3 calibration source (2B Technologies, model 306 referenced to the WMO scale). Calibration settings for the O3 monitor were left at manufacturer default settings, and corrections to account for linearity offset and zero offset were applied during data processing. For the flights reported here, the linearity offset was determined to be 1.01 and the zero offset was −2.4 ppbv. Calibrations in a pressure- and temperature-controlled environmental chamber were performed using the O3 calibration source over the pressure range 200–800 mbar and temperature range −15 to +25 C, typical pressure and temperature ranges observed in the wing-mounted instrument pod during flight. Precision during chamber tests, determined from the standard deviation of O3 measurements taken every 10 s, when sampling O3 mixing ratios of 50 ppbv over 2 min duration and during simulated descent profiles, was found to be 2 ppbv. The zero offset, observed when sampling O3scrubbed air during simulated descent profiles, was found to increase linearly by 0.6 ppbv with decreasing chamber pressure (typical zero offset of −2.4 ppbv at ground level and −3 ppbv at 200 mbar). Instrument drift estimated based on 1 h of sampling 50 ppbv O3 was 1.5 ppbv. Overall uncertainty of the airborne O3 measurements is estimated to be 3.0 ppbv. In situ O3 measurements, taken every 10 s, were performed over the San Joaquin Valley, CA (SJV) (Castle airport, Merced: 37.381 N, 120.568 W), and offshore (RAINS Intersection: 37.169 N, 123.235 W). Takeoff time from Moffett Field was at 18:00 UTC on 14 May 2012 and 5 June 2012. The aircraft arrived on-station at the SJV site at ∼ 18:20 UTC (local time is UTC − 7 h) on each day and performed a descending spiral profile from ∼ 8.8 km to < 0.5 km with a descent rate of ∼ 370 m min−1. A second descending spiral profile was performed over the offshore location each day starting at ∼ 19:05 UTC. On the 14 May 2013, the profile extended from ∼ 8.5 km to 1.5 km; the aircraft was prevented from flying any lower on this day due to a thick marine stratus layer with a top at 1.5 km. The lowest altitude of the offshore profile on 5 June 2012 was < 0.5 km. Total flight time each day was 100 min. 2.2 RAQMS model description Global in-line O3 and meteorological forecasts from RAQMS (Pierce et al., 2007, 2009) are used in conjunction with reverse domain filling (RDF) techniques (Sutton et al., 1994; Fairlie et al., 2007) to provide a large scale context for the interpretation of the airborne observations and to assess the fidelity of the RAQMS O3 forecasts. Forecasts are initialized with satellite-based O3 analyses and are archived at 6 h intervals at a horizontal resolution of 1 × 1 with 35 hybrid η–θ vertical levels extending from the surface to approximately 60 km. Stratospheric O3 analyses are constrained through assimilation of near-real-time (NRT) O3 profiles from the Microwave Limb Sounder (MLS) (Waters et al., 2006) above 50 mbar and NRT cloud-cleared total column O3 retrievals from the Ozone Monitoring Instrument (OMI) (Levelt et al., 2006). The RAQMS dynamical core is the University of Wisconsin (UW) hybrid isentropic–eta coordinate (UW hybrid) model (Zapotocny et al., 1997; Schaack et al., 2004), which uses isentropic coordinates above 380 K and hybrid eta coordinates between 380 K and the surface. The vertical resolution depends on the vertical gradient of potential temperature and varies between ∼ 200 m and 1 km (Pierce et al., 2007). Meteorological forecasts are initialized with operational analyses from the National Centers for Environmental Prediction (NCEP) Global Data Assimilation System (GDAS) (Kleist et al., 2009). Six-hour chemical and meteorological forecasts provide chemical and meteorological input for the RDF calculations. Analyzed O3 results are plotted as curtains along the flight track for comparison to the in situ data. Atmos. Chem. Phys., 13, 12481–12494, 2013 12484 E. L. Yates et al.: Springtime stratosphere-to-troposphere transport Ozone (ppbv) 20 37 53 70 87 103 120 10000 8000 Altitutde (m) 6000 4000 2000 0 37.6 37.5 Latitude3(7)o.4 37.3 37.2 37.1 -123.0 -122.5 -121.5 -122L.o0ngitude (o ) -121.0 -120.5 Fig. 1. 3-D projection of O3 mixing ratio (ppbv) as observed during flight on 14 May 2012 (takeoff time: 18:00 UTC). The O3 monitor requires a 10 min warm-up period before stable measurements are made, which results in data acquisition starting at 8.4 km during the transit to the San Joaquin Valley (inland) site. The RDF technique has been shown to represent coarsely resolved constituent fields at higher resolution, with higher information content, than originally observed (Sutton et al., 1994) or modeled (Fairlie et al., 2007). The RAQMS RDF calculations are based on analysis of back trajectories initialized along the aircraft flight track. Three-dimensional 6-day back trajectory calculations were conducted using the Langley Trajectory Model (LTM) (Pierce and Fairlie, 1993; Pierce et al., 1994). Back trajectories are initialized at model hybrid levels every 5 min along the flight track to construct a curtain. The back trajectories sample and archive RAQMS chemical and dynamical quantities so that Lagrangian averages could be determined. The Lagrangian averages, time averages following a given trajectory, are then mapped back onto the initial flight curtain to produce the RDF products. For the STT analysis we focus on RDF O3, large-scale mixing efficiency, and continental planetary boundary layer (PBL) exposure. 3 Results and discussion 3.1 A cutoff low event: 14 May equilibrium value of MeCpG steps (,+14 deg.) [31,44]. In comparison, methylation has a significantly lower stability cost when happening at major groove positions, such as 211 and 21 base pair from dyad (mutations 9 and 12), where the roll of the nucleosome bound conformation (+10 deg.) is more compatible with the equilibrium geometry of MeCpG steps. The nucleosome destabilizing effect of cytosine methylation increases with the number of methylated cytosines, following the same position dependence as the single methylations. The multiple-methylation case reveals that each major groove meth- PLOS Computational Biology | 3 November 2013 | Volume 9 | Issue 11 | e1003354 DNA Methylation and Nucleosome Positioning ylation destabilizes the nucleosome by around 1 kJ/mol (close to the average estimate of 2 kJ/mol obtained for from individual methylation studies), while each minor groove methylation destabilizes it by up to 5 kJ/mol (average free energy as single mutation is around 6 kJ/mol). This energetic position-dependence is the reverse of what was observed in a recent FRET/SAXS study [30]. The differences can be attributed to the use of different ionic conditions and different sequences: a modified Widom-601 sequence of 157 bp, which already contains multiple CpG steps in mixed orientations, and which could assume different positioning due to the introduction of new CpG steps and by effect of the methylation. The analysis of our trajectories reveals a larger root mean square deviation (RMSD) and fluctuation (RMSF; see Figures S2– S3 in Text S1) for the methylated nucleosomes, but failed to detect any systematic change in DNA geometry or in intermolecular DNA-histone energy related to methylation (Fig. S1B, S1C, S4–S6 in Text S1). The hydrophobic effect should favor orientation of the methyl group out from the solvent but this effect alone is not likely to justify the positional dependent stability changes in Figure 2, as the differential solvation of the methyl groups in the bound and unbound states is only in the order of a fraction of a water molecule (Figure S5 in Text S1). We find however, a reasonable correlation between methylation-induced changes in hydrogen bond and stacking interactions of the bases and the change in nucleosome stability (see Figure S6 in Text S1). This finding suggests that methylation-induced nucleosome destabilization is related to the poorer ability of methylated DNA to fit into the required conformation for DNA in a nucleosome. Changes in the elastic deformation energy between methylated and un-methylated DNA correlate with nucleosomal differential binding free energies To further analyze the idea that methylation-induced nucleosome destabilization is connected to a worse fit of methylated DNA into the required nucleosome-bound conformation, we computed the elastic energy of the nucleosomal DNA using a harmonic deformation method [36,37,44]. This method provides a rough estimate of the energy required to deform a DNA fiber to adopt the super helical conformation in the nucleosome (full details in Suppl. Information Text S1). As shown in Figure 2, there is an evident correlation between the increase that methylation produces in the elastic deformation energy (DDE def.) and the free energy variation (DDG bind.) computed from MD/TI calculations. Clearly, methylation increases the stiffness of the CpG step [31], raising the energy cost required to wrap DNA around the histone octamers. This extra energy cost will be smaller in regions of high positive roll (naked DNA MeCpG steps have a higher roll than CpG steps [31]) than in regions of high negative roll. Thus, simple elastic considerations explain why methylation is better tolerated when the DNA faces the histones through the major groove (where positive roll is required) that when it faces histones through the minor groove (where negative roll is required). Nucleosome methylation can give rise to nucleosome repositioning We have established that methylation affects the wrapping of DNA in nucleosomes, but how does this translate into chromatin structure? As noted above, accumulation of minor groove methylations strongly destabilizes the nucleosome, and could trigger nucleosome unfolding, or notable changes in positioning or phasing of DNA around the histone core. While accumulation of methylations might be well tolerated if placed in favorable positions, accumulation in unfavorable positions would destabilize the nucleosome, which might trigger changes in chromatin structure. Chromatin could in fact react in two different ways in response to significant levels of methylation in unfavorable positions: i) the DNA could either detach from the histone core, leading to nucleosome eviction or nucleosome repositioning, or ii) the DNA could rotate around the histone core, changing its phase to place MeCpG steps in favorable positions. Both effects are anticipated to alter DNA accessibility and impact gene expression regulation. The sub-microsecond time scale of our MD trajectories of methylated DNAs bound to nucleosomes is not large enough to capture these effects, but clear trends are visible in cases of multiple mutations occurring in unfavorable positions, where unmethylated and methylated DNA sequences are out of phase by around 28 degrees (Figure S7 in Text S1). Due to this repositioning, large or small, DNA could move and the nucleosome structure could assume a more compact and distorted conformation, as detected by Lee and Lee [29], or a slightly open conformation as found in Jimenez-Useche et al. [30]. Using the harmonic deformation method, we additionally predicted the change in stability induced by cytosine methylation for millions of different nucleosomal DNA sequences. Consistently with our calculations, we used two extreme scenarios to prepare our DNA sequences (see Fig. 3): i) all positions where the minor grooves contact the histone core are occupied by CpG steps, and ii) all positions where the major grooves contact the histone core are occupied by CpG steps. We then computed the elastic energy required to wrap the DNA around the histone proteins in unmethylated and methylated states, and, as expected, observed that methylation disfavors DNA wrapping (Figure 3A). We have rescaled the elastic energy differences with a factor of 0.23 to match the DDG prediction in figure 2B. In agreement with the rest of our results, our analysis confirms that the effect of methylation is position-dependent. In fact, the overall difference between the two extreme methylation scenarios (all-in-minor vs all-in-major) is larger than 60 kJ/mol, the average difference being around 15 kJ/ mol. We have also computed the elastic energy differences for a million sequences with CpG/MeCpG steps positioned at all possible intermediate locations with respect to the position (figure 3B). The large differences between the extreme cases can induce rotations of DNA around the histone core, shifting its phase to allow the placement of the methylated CpG steps facing the histones through the major groove. It is illustrative to compare the magnitude of CpG methylation penalty with sequence dependent differences. Since there are roughly 1.5e88 possible 147 base pairs long sequence combinations (i.e., (4n+4(n/2))/2, n = 147), it is unfeasible to calculate all the possible sequence effects. However, using our elastic model we can provide a range of values based on a reasonably large number of samples. If we consider all possible nucleosomal sequences in the yeast genome (around 12 Mbp), the energy difference between the best and the worst sequence that could form a nucleosome is 0.7 kj/mol per base (a minimum of 1 kJ/mol and maximum of around 1.7 kJ/mol per base, the first best and the last worst sequences are displayed in Table S3 in Text S1). We repeated the same calculation for one million random sequences and we obtained equivalent results. Placing one CpG step every helical turn gives an average energetic difference between minor groove and major groove methylation of 15 kJ/ mol, which translates into ,0.5 kJ/mol per methyl group, 2 kJ/ mol per base for the largest effects. Considering that not all nucleosome base pair steps are likely to be CpG steps, we can conclude that the balance between the destabilization due to CpG methylation and sequence repositioning will depend on the PLOS Computational Biology | 4 November 2013 | Volume 9 | Issue 11 | e1003354 DNA Methylation and Nucleosome Positioning Figure 3. Methylated and non-methylated DNA elastic deformation energies. (A) Distribution of deformation energies for 147 bplong random DNA sequences with CpG steps positioned every 10 base steps (one helical turn) in minor (red and dark red) and major (light and dark blue) grooves respectively. The energy values were rescaled by the slope of a best-fit straight line of figure 2, which is 0.23, to source of circulating FGF-21. The lack of association between circulating and muscle-expressed FGF-21 also suggests that muscle FGF-21 primarily works in a local manner regulating glucose metabolism in the muscle and/or signals to the adipose tissue in close contact to the muscle. Our study has some limitations. The number of subjects is small and some correlations could have been significant with greater statistical power. Another aspect is that protein levels of FGF-21 were not determined in the muscles extracts, consequently we cannot be sure the increase in FGF-21 mRNA is followed by increased protein expression. In conclusion, we show that FGF-21 mRNA is increased in skeletal muscle in HIV patients and that FGF-21 mRNA in muscle correlates to whole-body (primarily reflecting muscle) insulin resistance. These findings add to the evidence that FGF-21 is a myokine and that muscle FGF-21 might primarily work in an autocrine manner. Acknowledgments We thank the subjects for their participation in this study. 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