Evaluation of El Niño-Southern oscillation influence on ozone exceedances along the United States Gulf Coast

Evaluation of El Niño-Southern oscillation influence on ozone exceedances along the United States Gulf Coast

Atmospheric Environment xxx (xxxx) xxx Contents lists available at ScienceDirect Atmospheric Environment journal homepage: http://www.elsevier.com/l...

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Atmospheric Environment xxx (xxxx) xxx

Contents lists available at ScienceDirect

Atmospheric Environment journal homepage: http://www.elsevier.com/locate/atmosenv

~ o-Southern oscillation influence on ozone exceedances Evaluation of El Nin along the United States Gulf Coast Rebecca Paulsen Edwards a, *, Morgan Engle b, Gary Morris c a

Southwestern University Department of Physics, Georgetown, TX, USA Southwestern University Department of Mathematics, Georgetown, TX, USA c College of Natural Sciences, St. Edward’s University, Austin, TX, USA b

A B S T R A C T

An investigation into climate-scale influences on tropospheric ozone concentrations in cities along the United States Gulf Coast was performed using a thirty-year database of observed surface ozone data. Hourly surface ozone data were obtained from eight surface Environmental Protection Agency monitoring stations from Texas to Florida. Eight-hour peak concentrations were computed for each day in the record and a database created for further study. To account for regulatory changes, each time history was detrended over the thirty-year period. Days with precipitation, which tend to have low surface ozone concentrations due to low solar insolation and wet deposition of ozone precursors on surfaces, were also removed. The resulting database was stratified by Oceanic Ni~ no Index, which is a measure of the state of the El Ni~ no-Southern Oscillation (ENSO) based on water temperatures in the eastern Pacific Ocean. A common seasonal dependency was identified for all eight stations, with peaks in ozone concentrations in spring and autumn regardless of ENSO phase. The summer ozone minimum was more pronounced for the western Gulf of Mexico than the east. This extension of work done for the city of Houston, Texas confirmed that the influence of ENSO on surface air quality applies to the entire coast of the Gulf of Mexico. Statistically significant enhancements of 5–10 ppbv were found during the months of March and April for El Ni~ no years relative to neutral years. Distributions fit to each city’s dataset of 8-h peak ozone values for spring and fall confirmed the difference between the behavior of ozone con­ centrations in spring and fall for different ENSO phases. El Ni~ no spring data possessed a broader distribution more centered at a higher mean value than the neutral or La Ni~ na datasets for each city. Taken together, the higher mean and broader distribution of 8-h ozone concentrations lead to 30% more exceedances of the National Ambient Air Quality Standard of 70 ppbv for El Ni~ no years relative to neutral years for the composite Gulf Coast dataset. These changes in the ozone climate of the Gulf Coast during El Ni~ no years can be attributed in part to an area of anomalously low pressure in the eastern Gulf of Mexico which influences meridional and zonal flow along the coast. This feature leads to stagnation and a persistent continental airmass along the northern Gulf coast. Smaller but still statistically significant differences between El Ni~ no and neutral autumn were also identified for some stations and were attributed to increased frontal activity during El Ni~ no autumn which leads to an earlier, longer ozone season in previous research. This work extends and improves understanding of the influence of the El Ni~ no-Southern Oscillation on air quality in a large and economically important region of the United States.

1. Background Tropospheric ozone is a pollutant and respiratory irritant. It has detrimental effects on vulnerable human populations as well as on vegetation in areas where tropospheric concentrations are high (Berman et al., 2012; Choi et al., 2011; Bell et al., 2004; McConnell et al., 2002; Lippmann, 1991). Ozone is produced in the troposphere via photo­ chemical reactions among ozone precursors: oxides of nitrogen (NOx) and volatile organic compounds (VOC) (Jiang and Fast, 2004). The Gulf Coast of the United States (GCUS) is a region which merits particular attention with regard to air quality. The oil and gas industry, centered in Texas and Louisiana, is a significant source of volatile organic compounds (VOCs), an ozone precursor, as well as other air pollutants (Williams et al., 2009; Kim et al., 2011; Daum et al., 2003).

Shipping is a vital component of the region’s economy and the associ­ ated emissions from large container ships and auxiliary watercraft is another source of ozone precursors, oxides of nitrogen (NOx) and VOCs. Along the Gulf Coast of the United States (GCUS), the ozone climate is characterized by seasonal peaks in spring and autumn with minimums in the summer and winter (Nielsen-Gammon et al., 2005). The National Ambient Air Quality Standard (NAAQS), implemented as part of the Clean Air Act, require that the fourth highest 8 h daily peak ozone concentration, averaged over three years, not exceed 70 ppbv (Ozone Standards, 2015). Implementation of the NAAQS has led to significant improvement in concentrations of tropospheric ozone (Cooper et al., 2012), but many GCUS cities including Houston, Baton Rouge, and New Orleans are considered out of compliance with these standards (www. epa.gov). Exceedances of the NAAQS result in both poor air quality

* Corresponding author. E-mail address: [email protected] (R.P. Edwards). https://doi.org/10.1016/j.atmosenv.2019.117127 Received 27 June 2019; Received in revised form 6 November 2019; Accepted 8 November 2019 Available online 16 November 2019 1352-2310/© 2019 Elsevier Ltd. All rights reserved.

Please cite this article as: Rebecca Paulsen Edwards, Atmospheric Environment, https://doi.org/10.1016/j.atmosenv.2019.117127

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including transport from other locations, variability in the ozone pre­ cursor NOx, and stratosphere-troposphere exchange (STE) of air, in which naturally occurring ozone from the stratosphere is transported downwards into the troposphere (Nielsen-Gammon et al., 2005; James et al., 2003; Stohl et al., 2003). Seasonal changes in the broad atmo­ spheric circulation create higher background ozone in spring and autumn by increasing the influence of the continental airmass, which contains ozone and ozone precursors, and causes higher total ozone when paired with local production (Nielsen-Gammon et al., 2005). Other influences lead to relative minimums of tropospheric ozone dur­ ing the summer (JJA) and winter (DJF) months along the GCUS. In summer, prevailing southerly flow resulting from broad anti-cyclonic flow around the Bermuda High provides an influx of clean marine air from over the Gulf of Mexico onto the coastline (Wang et al., 2016). In addition, Stohl et al. (2003) reported a decreasing influence of STE in the summer months, further reducing the tropospheric ozone concentration. In the winter months, a low solar declination angle results in limited local photochemical production of ozone. Mesoscale meteorological influences also influence the locally produced ozone climate along the GCUS. The oscillatory nature of the sea breeze front leads to a sloshing behavior of the airmass, which re-entrains more ozone precursors each time it moves back over land. In the presence of sunlight, photochemical production of ozone from these ozone precursors can lead to extremely poor tropospheric ozone conditions during these episodes (Anjaneyulu et al., 2010; Banta et al., 2009). ~ o, the warm phase of ENSO, has been found to increase El Nin tropospheric ozone in the United States via changes in the dynamics of the midlatitudes (Zhang et al., 2015; Chandra et al., 2007; Zeng and Pyle, 2005; Langford et al., 1998) which alters the tropopause and leads

Table 1 Station data for each EPA surface monitoring station in the dataset. Station Name

Lat/Long

Record Dates

Corpus Christi, TX Houston, TX Carlyss, LA Baton Rouge, LA New Orleans, LA Mobile, AL Pensacola, FL

27.77/-97.43 29.90/-95.33 30.14/-93.37 30.42/-91.18 29.99/-90.10 30.77/-88.089 30.37/-87.27

9/26/1981–12/1/2015 1/5/1980–12/31/2010 10/1/1983–11/5/2015 1/1/1980–11/12/2015 2/2/1981–11/6/2014 3/4/1982–10/30/2015 10/30/1980–12/29/2015

and economic costs to municipalities. Regulatory changes have affected primarily the local contribution to the total tropospheric ozone con­ centration. Background ozone concentrations, caused by long-range transport, STE, and regional meteorological configurations, can be more complicated to predict and mitigate, and often form the basis for a NAAQS exceedance (Nielson-Gammon, 2005). Long-range transport (Morris et al., 2006), temperature (Holloway et al., 2008, Nielsen-­ Gammon et al., 2005), climate change (Lin et al., 2015; Holloway et al., 2008; Doherty et al., 2013; Jacob and Winner, 2008; Chandra et al., 2007; Fiore et al., ), and policy (Chandra et al., 2007) all play a role in the concentration of tropospheric ozone, making it difficult for regula­ tory agencies to limit the concentration of ozone in a given local juris­ diction. Better understanding of the influence of long-range climate oscillations like ENSO provides one piece of the puzzle. A tropospheric ozone concentration represents the addition of two components: ozone produced locally (locally produced) and ozone transported into a given region from another location (background ozone). Background ozone originates from a number of sources

Fig. 1. Map of stations included in the dataset.

Fig. 2. Houston data stratified into El Ni~ no, La Ni~ na, and Neutral datasets by ONI (left) and by ONI lagged by four months (right). 2

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Fig. 3. A sample dataset before and after the trend was removed.

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Fig. 4. Averaged daily peak 8-h ozone concentrations for each month stratified by ENSO for each station. 4

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2014). The present study builds on Edwards et al. (2018), by expanding the analysis to seven additional sites situated along the GCUS.

Table 2 Stations with statistically significant differences in mean between a given ENSO phase and neutral in the spring and autumn ozone seasons. El

Ni~ no

La Ni~ na

April

May

August

Baton Rouge Beaumont Carlyss Corpus Christi Houston Mobile New Orleans Pensacola Composite Gulf Houston New Orleans Mobile Composite

Baton Rouge Beaumont Carlyss Houston Composite Gulf

Baton Rouge Beaumont Composite Gulf

Beaumont Mobile

Baton Rouge Houston Composite Gulf

2. Methods

September

2.1. Data Surface monitor data were obtained through the Environmental Protection Agency (EPA) data repository. Stations were chosen based on data availability and proximity to the coastline, with an effort made to ensure as uniform an east-west distribution as possible. To be included in the dataset, stations must be located in a city situated on the coast of the Gulf of Mexico and possess continuous records from 1985 through 2015. Eight stations were chosen for the analysis (Table 1). Each station was adjacent to the Gulf Coast with the exception of Baton Rouge, which is approximately 100 km north of the Gulf Coast and Mobile, which is located on the northwest side of Mobile Bay (Fig. 1). In addition to the individual stations, a composite dataset containing data from all of the individual stations was evaluated. The peak 8-h ozone concentration, based on a moving 8-h average, was found for each day of data. Days with measurable precipitation were removed from each dataset using a precipitation dataset from a nearby surface observing station. Because this study is concerned with longterm, climatological influences on tropospheric ozone, days during which more than 0.01 inch of rain was recorded at the closest available weather station were removed from the dataset. Precipitation leads to wet-deposition of ozone and ozone precursors, which lowers the ozone concentration in the troposphere. Furthermore, cloudy conditions associated with rain reduce the amount of photochemical production possible, which further reduces the concentration. A similar methodo­ logical choice was made by Nielson-Gammon (2005) who found an in­ crease in average ozone values in Houston when precipitation days were removed from the dataset. However, removing precipitation days from the dataset ensures that comparisons made among datapoints reflects the most uniform conditions possible. Because the ENSO cycle can in­ fluence the amount of precipitation received for a location, it is possible that this choice would impact the resulting statistics.

Baton Rouge Beaumont

to an increased incidence of STE (Rappengluck et al., 2008). Volugarakis et al. (2010) investigated whether a change in stratospheric ozone ~o concentration and associated increase in STE events during El Nin periods was the cause of an observed global increase in tropospheric ~ o events. In a subsequent study, Voulgarakis et al. ozone during El Nin (2010) clarified this distinction, using a chemical transport model to show that changes in midlatitude dynamics led to the conditions which facilitate STE. Shen and Mickley (2017), noted a spatial dependence for ~o the variation of summertime ozone concentrations due to El Nin events. Southern Atlantic states experienced an increase of 1–2 ppbv ~ o events while south central states saw a decrease of 0.5–2 during El Nin ppbv. That study identified stratospheric waves which control the large scale flow at the surface, altering the ozone climate. This result also ~ o on the tropospheric ozone suggests a change in the effect of El Nin climate as one moves from west to east in the contiguous United States. Chandra et al. (2007) used satellite data to examine the global distri­ ~ o event and found a bution of tropospheric ozone during an El Nin geographic dependency on the effect with lower tropospheric ozone over the Eastern and higher tropospheric ozone over the Western Pacific Ocean during the warm phase of ENSO. Langford et al. 2009 attribute a low frequency oscillation identified in tropospheric ozone using lidar data to changes in the large-scale circulation caused by ENSO, going on to say that the increased area of tropospheric ozone over the Pacific Ocean advects eastward to cause an increase in tropospheric ozone over Colorado after a six-month lag time. Sea surface temperature fluctua­ tions associated with ENSO influence the magnitude of STE, with the warm phase causing an increase and the cool phase causing a decrease (Ganguly and Iyer, 2014; Zeng and Pyle, 2005). Bridging the gap be­ tween studies of synoptic and mesoscale conditions, a pair of studies by Singh and Palazoglu (2011, 2012) use a statistical technique to evaluate meteorological conditions over the past fifty years to identify days on which ozone and particulate matter (another criteria pollutant) were likely to be in exceedance of national standards and found some dependence of high pollution days on ENSO for several regions in the United States. A 2018 study (Edwards et al., 2018) which examined the long-term surface ozone monitor records in Houston, Texas in an effort to identify climate-scale influences on the city’s air quality noted an influence by ~ o-Southern Oscillation phenomenon (ENSO) which led to 26% the El Nin ~ o year more exceedances in the Houston area during an average El Nin compared to an average neutral year and 23% fewer exceedances during ~ a year. This finding was attributed to changes in the an average La Nin ~ o years that led to synoptic pattern over the midlatitudes during El Nin an increase in the number of cold fronts which passed over the city. Cold fronts increase tropospheric ozone concentrations in Houston in two ways. First, they lead to a change in airmass from the cleaner Gulf air­ mass that dominates during prevailing southerly winds, to a continental airmass laden with ozone and ozone precursors. Cold fronts also lead to a perturbation in the tropopause that causes STE (Ganguly and Iyer,

2.2. Stratification by ENSO The Oceanic Ni~ no Index is based on a three-month moving average of ~ o 3.4 region of the eastern Pacific temperature anomalies in the Nin Ocean (Trenberth and Stepaniak, 2001). Values above 0.5 represent El ~ o conditions. Values below 0.5 represent La Nin ~ a conditions. Nin Values between 0.5 and 0.5 represent neutral conditions. Previous research has shown a lag between the peak of the ENSO cycle and tel­ econnective effects on the atmosphere in the midlatitudes (Garcia-­ Serrano et al., 2017; Shen and Mickley, 2017; Liang et al., 2015; Kumar and Hoerling, 2003). The delay has been attributed to a number of

Fig. 5. Averaged daily peak 8-h ozone concentrations for each month stratified by ENSO for the composite dataset. 5

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Table 3 Monthly exceedance rates (exceedances/month) for each city and the Gulf Coast Composite station. Baton Rouge

Jan

Feb

Mar

Apr

May

Jun

Jul

Aug

Sep

Oct

Nov

Dec

Total

El Nino La Nina Neutral Beaumont El Nino La Nina Neutral Carlyss El Nino La Nina Neutral Corpus El Nino La Nina Neutral Houston El Nino La Nina Neutral Mobile El Nino La Nina Neutral New Orleans El Nino La Nina Neutral Pensacola El Nino La Nina Neutral Composite Gulf El Nino La Nina Neutral

0.0 0.1 0.0 Jan 0.0 0.0 0.3 Jan 0.0 0.0 0.3 Jan 0.0 0.0 0.0 Jan 0.0 0.3 0.2 Jan 0.0 0.0 0.0 Jan 0.0 0.0 0.0 Jan 0.1 0.0 0.1 Jan 0.02 0.03 0.06

0.0 0.0 0.1 Feb 0.0 0.0 0.3 Feb 0.3 0.2 0.1 Feb 0.2 0.1 0.2 Feb 0.0 0.1 0.1 Feb 0.0 0.0 0.0 Feb 0.0 0.0 0.3 Feb 0.6 0.2 0.4 Feb 0.14 0.08 0.21

0.8 0.4 0.8 Mar 1.1 0.7 1.1 Mar 0.8 0.5 0.5 Mar 0.3 0.4 0.8 Mar 0.7 0.1 0.0 Mar 0.2 0.5 0.2 Mar 0.6 0.1 0.3 Mar 1.6 1.0 1.8 Mar 0.58 0.38 0.58

3.1 2.3 1.5 Apr 3.5 1.4 1.4 Apr 2.4 1.4 0.3 Apr 2.3 1.3 0.8 Apr 2.6 0.5 0.7 Apr 0.1 0.2 2.0 Apr 0.7 1.1 0.1 Apr 4.3 2.1 1.2 Apr 1.50 0.98 0.85

6.1 4.1 3.9 May 5.2 1.1 3.9 May 3.6 1.4 1.5 May 1.7 1.0 1.1 May 2.8 1.5 2.3 May 1.8 1.0 5.6 May 2.9 1.8 1.8 May 7.0 3.7 4.7 May 1.85 1.22 1.73

3.6 4.1 3.7 Jun 4.1 2.7 2.5 Jun 2.3 1.9 1.1 Jun 1.4 1.1 0.7 Jun 5.4 2.3 3.3 Jun 1.7 1.2 2.8 Jun 0.9 0.4 1.0 Jun 4.1 2.7 3.0 Jun 1.57 1.26 1.34

4.2 4.7 3.0 Jul 0.6 2.0 2.0 Jul 0.8 2.0 1.2 Jul 0.2 0.3 0.5 Jul 1.2 2.0 2.3 Jul 1.6 2.7 2.5 Jul 0.2 1.0 0.5 Jul 2.4 3.4 2.2 Jul 1.35 1.25 1.20

5.2 6.4 4.3 Aug 4.2 3.4 2.8 Aug 2.6 2.8 1.4 Aug 1.6 1.4 0.9 Aug 1.8 2.0 3.9 Aug 1.8 4.6 2.2 Aug 0.4 0.8 0.4 Aug 3.2 4.6 3.1 Aug 1.85 1.88 1.57

5.6 2.8 4.1 Sep 5.2 1.5 3.0 Sep 3.4 1.2 1.7 Sep 4.4 3.8 2.6 Sep 7.2 4.8 5.2 Sep 3.0 1.5 1.2 Sep 0.4 0.3 0.3 Sep 3.8 2.5 2.7 Sep 2.20 1.50 1.47

1.7 1.8 1.4 Oct 4.4 0.5 1.5 Oct 2.0 1.8 0.9 Oct 2.4 2.0 1.5 Oct 5.0 1.3 1.9 Oct 0.9 2.3 0.1 Oct 0.6 0.0 0.2 Oct 2.4 3.0 1.1 Oct 1.71 1.19 0.78

0.0 0.2 0.0 Nov 0.0 0.0 0.1 Nov 0.2 0.4 0.0 Nov 0.0 0.6 0.2 Nov 0.2 0.2 0.5 Nov 0.0 0.0 0.0 Nov 0.0 0.0 0.0 Nov 0.0 0.0 0.0 Nov 0.18 0.15 0.14

0.0 0.0 0.1 Dec 0.3 0.0 0.0 Dec 0.2 0.0 0.1 Dec 0.0 0.0 0.0 Dec 0.0 0.0 0.0 Dec 0.0 0.0 0.0 Dec 0.0 0.0 0.0 Dec 0.0 0.0 0.0 Dec 0.08 0.02 0.04

30.3 26.9 22.8 Total 28.7 13.2 18.9 Total 18.6 13.5 9.0 Total 14.6 12.0 9.2 Total 26.9 15.0 20.2 Total 11.1 14.0 16.6 Total 6.6 5.6 4.9 Total 29.5 23.2 20.2 Total 13.0 9.9 10.0

causes, from the time required for stratospheric waves to propagate across the continent from west to east (Shen and Mickley, 2017) to the growth of an area of tropospheric warming, which begins at the equator just before the warm phase reaches its peak and spreads into the sub­ tropics over a period of several months, lingering well into the decay phase of the oscillation (Kumar and Hoerling, 2003). The lagged rela­ tionship has appeared in various features of the earth’s system, including tropical Atlantic sea surface temperatures (Garcia-Serrano et al., 2017), the Great Plains Low Level Jet (Liang et al., 2015), and ozone air quality along the Eastern seaboard of the United States during the summer (Shen and Mickley, 2017). Comparison of the statistics for the regular versus the lagged version of the ONI seemed to support this approach. This analysis will use the lagged form of the ONI for ENSO stratification by assigning each ozone observation the ONI value cor­ responding to that day four months prior based on the four month lag between a change in sea surface temperatures in the eastern Equatorial Pacific Ocean and a response in the midlatitude stratospheric conditions. A similar lag was identified and employed by Shen and Mickley (2017) and Langford et al. (1998). The results from the lagged ONI index were closely aligned with the results of the original ONI dataset. The Houston dataset merits closer investigation in this regard because the same composite dataset was used in both Edwards et al. (2018) and the present study. Data stratified by the original ONI dataset and data stratified by the lagged ONI dataset are provided in Fig. 2 (left panel and right panel, respectively). The main conclusions regarding the behavior of tropospheric ozone concentration with ONI are unchanged between the two approaches. Enhancements are present during spring and autumn for both plots. The ozone season ~ o springs for both the lagged and the base begins earlier during El Nin ~ o spring enhancement in the lagged ONI plot is dataset. The El Nin continuous from April to June in line with established seasonality of ozone, without the relative minimum found in May using the original

data. The similarities between the two approaches suggest that the pe­ riods of high ozone values in spring and autumn do not appear to be significantly altered when switching to a lagged ONI dataset. Using the lagged ONI values, the dataset for each site was stratified into the three ENSO categories. Observations with an ONI greater than ~ o events, less than or equal to or equal to 0.5 were classified as El Nin ~ a events, and observations with ONIs 0.5 were classified as La Nin falling between 0.5 and 0.5 were classified as neutral events. In all, 96 ~ o months, 101 were months of the dataset were classified as El Nin ~ a events, and 175 were classified as neutral events. classified as La Nin 2.3. Detrending Policy changes, in particular the Clean Air Act, have restricted the emission of ozone precursors via the implementation of the National Ambient Air Quality Standards (NAAQS). This regulatory change has been shown to cause significant reductions in tropospheric ozone con­ centrations at most monitoring stations in the United States (Chandra et al., 2007). Edwards et al. (2018) also observed this effect in long-term records of tropospheric ozone in Houston. Because the focus of this investigation was to evaluate the air quality impact of ENSO, which varies on a three to seven year timescale, it was necessary to remove the effect of this long-term influence. Each city’s dataset was detrended by finding the difference between the linear regression line fit to the entire record and the average value for the last year in the record. This dif­ ference was then subtracted from each surface 8-h concentration. This detrending technique preserves the short-term variability in the record while controlling for long-term influences, as can be seen in the com­ parison of one dataset before and after detrending in Fig. 3.

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Fig. 6. Weibull fits for each ENSO phase for the springtime period (April and May) for each station. Stations are arranged from west to east. 7

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exception of Pensacola, these stations, including Houston, which does ~ o Septembers despite not being exhibit an enhancement during El Nin statistically significant (Fig. 3), are all located within the same general region on the upper Texas/Louisiana coastline. Given their similar latitude, these sites would be expected to have similar influence on the local environment from frontal passages and other synoptic features which influence both local meteorology and background ozone. Modeling and observational studies (Shuckburgh et al., 2009; Zhang et al., 2015) have observed excess ozone building in the upper ~ o events. troposphere-lower stratosphere (UTLS) during spring El Nin These changes in upper level dynamics result from enhanced tropical convection and allow flux of stratospheric ozone into the troposphere leading to higher background ozone. The Mobile and New Orleans sta­ tions’ average ozone concentrations are similar for all three ENSO re­ gimes in September, with higher concentrations during the preceding ~ a years. summer months in La Nin In addition to higher average ozone concentrations, there are tem­ poral differences in the peak ozone seasons, which can be seen in Figs. 4 and 5. During El Ni~ no spring, the concentration begins its seasonal in­ crease earlier and its summer decline later in Houston, Beaumont, Carlyss, Baton Rouge, New Orleans, and Pensacola, as well as the composite Gulf station. The temporal change was also identified by Edwards et al. (2018) in Houston and was attributed to the more active ~ o jet stream, which increases frontal activity and the resulting El Nin incidence of STE. The lengthening of the springtime ozone season in these stations, paired with higher average 8-h ozone concentrations, leads to a large difference in the rate of exceedances of the National Ambient Air Quality Standards (NAAQS) of 70 ppbv that occur in each city for each ENSO phase (Table 3). Table 3 was created by totaling the number of exceedances per month for each station for each ENSO phase for the whole 30-year dataset, then normalizing by the number of times that month occurred in each phase during the thirty years. Some initial differences in the rate of exceedances were apparent by comparing the ~ o year exceedance rates three ENSO phases for each month. Spring El Nin were higher than neutral exceedance rates in April and May in Beau­ mont, Baton Rouge, Carlyss, Corpus Christi, Houston, New Orleans, and ~ o months Pensacola. In autumn, exceedance rates were highest for El Nin in September for all stations. In September, despite only three stations having higher mean 8-h concentrations (Fig. 4 and Table 3), exceedance ~ o years relative to neutral years, leading to rates were higher for El Nin the conclusion that exceedances of the NAAQS are not always tied to or reflective of higher monthly mean values. Yearly total exceedance rates, the total number of exceedances expected to occur in a year comprised completely of months belonging to a given ENSO phase, were consis­ ~ o years relative to both neutral and La Nin ~a tently much higher for El Nin conditions. This difference is caused partly by higher rates of exceed­ ances during individual months, with the elongation of the ozone season ~ o springs playing a more significant role. The Composite during El Nin Gulf dataset reflects both of these features, with both higher mean ozone ~ o springs and a markedly elongated spring concentrations for El Nin ozone season. For the composite dataset, the rate of exceedance occur­ rence is 35% higher in El Ni~ no years than neutral conditions while av­ ~ a years were only 3.5% higher than neutral years. erages during La Nin Fundamental differences among the three ENSO phases which tie together the higher rate of exceedances and higher mean values observed during El Ni~ no springs are reflected in the Weibull distribu­ tions fit to the daily 8-h peak data for April and May for individual stations (Fig. 6) and composite Gulf Coast data (Fig. 7). Distributions of ~ o years are both broader and centered 8-h peaks observed during El Nin at a higher value than the neutral or La Ni~ na distributions for all stations. The distribution shape reflects the wider range of ozone values which ~ o years, which paired with the higher mean, con­ occur during El Nin tributes to the large rate of 70 ppbv NAAQS exceedances in Table 3. The most pronounced difference between distributions for the three ENSO phases exists for the four stations in the middle of the array: Houston, Beaumont, Carlyss, and Baton Rouge. These stations are located in a

Fig. 7. Weibull fits for each ENSO phase for the springtime period for the Composite Gulf Coast station.

3. Results and discussion 3.1. Ozone climatology Monthly averaged 8-h daily peak data for each station stratified by the ONI with the four-month lag applied are provided for each station in Fig. 4 (individual station) and 5 (Gulf Coast composite). Peaks in 8 h tropospheric ozone concentration during spring and fall are present at each station and are indicative of the higher available insolation and intermittent presence of the continental airmass after frontal passages. While each dataset exhibited a period of low ozone during summer, the magnitude of the decrease characterizing the summertime low ozone period varied. Stations situated further to the west (Corpus Christi, Houston, Beaumont, and Carlyss) exhibited the largest summertime decrease in surface ozone. The summer minimum was less distinct for the eastern stations (Baton Rouge, New Orleans, Mobile, and Pensacola). Wang et al. (2016) reported that while Houston, New Orleans, Mobile, and Pensacola each had reasonable correlation between the position of the Bermuda High and the strength of the summertime ozone low period, the correlation was highest in Houston (R2 ¼ 0.71 in June) due to the more direct relationship between Bermuda High ventilation and Houston’s locally produced ozone precursors (from transportation and industrial sources). As a result, this interaction is the dominant driver of low summertime ozone concentrations in Houston. The diminishing summertime low ozone period further east in the dataset reflects either a weakening influence of the Bermuda High in the eastern stations or some other mechanism. Peaks in 8 h tropospheric ozone concentration during spring and fall at each station are indicative of the intermittent presence of the continental airmass after frontal passages. As expected, wintertime ozone concentrations are low at the surface due to a lack of insolation which inhibits local production of ozone. 3.2. ENSO influences on surface ozone concentrations Statistically significant (α < 0.05) differences were found between ~ o and neutral years and La Nin ~ a and peak 8-h concentrations from El Nin neutral years (Table 2) in nearly all stations during at least some of the springtime months:(April and May) Both the four eastern and the four western stations as well as the composite dataset had statistically sig­ ~ o Aprils. In Beaumont, Car­ nificant ozone enhancements during El Nin lyss, Corpus Christi, Houston, and Pensacola the springtime peak during El Ni~ no years was 5 ppbv or more greater than that of the neutral case. The effect of ENSO on autumn’s ozone distribution is more mixed, with enhancements in Beaumont, Carlyss, Baton Rouge, and Pensacola during at least one month in the late summer, early fall period. With the 8

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Corpus Chris

Houston

Beaumont

Carlyss

Baton Rouge

New Orleans

Mobile

Pensacola

Fig. 8. Weibull fits for each ENSO phase for the late summer-early autumn period for each station. Stations are organized from west to east. 9

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closely to features of synoptic meteorology, which is influenced more directly by the kinds of changes which occur in the midlatitude UTLS ~ o. This direct relationship between ENSO region in response to El Nin and mid-latitude wave behavior may explain the more readily apparent link between surface ozone concentrations along the USGC during the months of April and May compared to September. The late summer-early autumn ozone environment at the surface is controlled by a more diverse array of factors, including the Bermuda High (Wang et al., 2016), stagnation due to semi-permanent high pressure over the central United States, and the seabreeze circulation (Banta et al., 2009) ~ o. The in addition to any alteration of the jet stream caused by El Nin larger number of potential influences on tropospheric ozone make the ENSO signal less clear in the autumn USGC ozone data when compared to the spring. 3.3. Attribution Previous work and general understanding of ENSO indicates that the cycle plays an important role in the regional meteorology of the Gulf Coast (Garcia-Serrano et al., 2017; Liang et al., 2015; Lin et al., 2015; Wang et al., 2012; Kumar and Hoerling, 2003; Alexander and Scott, 2002; Rassmusson and Wallace, 1983). To investigate the effect the warm phase of the ENSO cycle has on the regional meteorology of the USGC and its implications for air quality, climate composites were created using National Center for Environmental Prediction (NCEP) reanalysis data. The composites in Fig. 10 top (bottom) represent the average 1000 mb meridional (zonal) flow for the months of April and ~ o years in the dataset minus the average May for all of the El Nin meridional (zonal) flow for the months of April and May for all of the neutral years in the dataset. The resulting plot shows the anomaly be­ ~ o years relative to neutral years. Negative values indicate tween El Nin that the El Ni~ no year average of the quantity is lower than the neutral average. The top panel of Fig. 10 indicates a broad area of negative anomaly meridional wind extending from the Central Texas coast to the ~ o years. Along the USGC, reduced Florida peninsula during the El Nin meridional flow indicates less inbound transport of relatively low-ozone air from the Gulf of Mexico and an increase in stagnation (Wang et al., 2016; Banta et al., 2005; Shen and Mickely, 2015), which would support the higher ozone concentrations and exceedance rates observed in this ~ o springs. The positive zonal wind anomaly identified area during El Nin in the bottom panel of Fig. 10 is also in agreement with the observed ~o higher mean ozone concentrations and exceedance rates during El Nin springs, as this wind configuration, when paired with the anomalously low meridional flow, leads to transport of ozone precursor-laden con­ tinental air into the study region. In fact, an increase in zonal flow aligned with the coast in this way causes mixing and transport of ozone and ozone precursors from all of the industrial centers along the USGC from west to east. This continental air would be suited for prolific tropospheric ozone production. Furthermore, lower meridional and higher zonal flow may be indicative of a post-frontal configuration that has been shown to influence tropospheric ozone both by introducing a continental airmass and by perturbing the tropopause and causing downward transport of ozone from the stratosphere to the troposphere. These changes in the broad circulation in the region are caused by a low pressure anomaly located in the eastern Gulf of Mexico (Fig. 11). Alexander and Scott (2002) found similar synoptic-scale changes in the ~ o springs, reporting flow over the contiguous United States during El Nin southward transport of cold, continental air along the Atlantic and Gulf of Mexico coastlines. These features were also attributed to a low pres­ sure anomaly in the eastern Gulf of Mexico. The low pressure anomaly in the eastern Gulf of Mexico was also identified by Liang et al. (2015), who observed the anomaly during the spring and early summer period during decaying warm phase ENSO events. Cyclonic flow around the anomaly led to stagnation or weak offshore flow along the northern coast of the Gulf of Mexico during the spring months following an El Ni~ no event. Composite meridonal flow data (Fig. 12, top) reflect this stagnation and

Fig. 9. Weibull fits for each ENSO phase for the late summer-early autumn period for the Composite Gulf Coast station.

similar position on the central Gulf Coast and are situated at a similar latitude, which implies similar synoptic influences. All four stations are also in a part of the USGC central to oil and gas production and possess a similar local production environment. When considered together, dis­ tributions fit to the composite dataset also reflect a broader distribution ~ o years, which supports the larger with a higher mean value for El Nin ~a number of exceedances found in Table 3. In contrast, while the La Nin composite distribution has a slightly different shape than the neutral distribution, the right tails, and hence the behavior of the high end of the distribution, follows the neutral distribution closely, indicating similar ~ a composite numbers of exceedances or both regimes. Neutral/La Nin exceedance rates for April and May were 0.85/0.98 and 1.73/1.22, respectively, all of which were lower than the rate of exceedances for the ~ o regime, 1.50 and 1.85 for April and May. El Nin Pensacola’s Weibull fits reflect a similar rightward shift as expected ~ o years. The right tail given the higher mean concentration during El Nin ~ o distribution for Pensacola is elongated. These two results of the El Nin are reflected by the number of yearly exceedances for Pensacola, which ~ o relative to neutral years. Mobile’s distri­ was 37% higher for El Nin bution data, exceedance data, and mean data all indicate fewer ~ o spring exceedances and a lower mean concentration during El Nin despite Pensacola and New Orleans on either side and the Gulf Coast Composite having ozone enhancements during spring. This behavior is not well understood and could reflect a local or synoptic influence that merit further investigation. Weibull distributions fit to 8-h daily peak concentration datasets for September (Fig. 8, composite Gulf station in Fig. 9) are more similar across the three ENSO phases than was true for the spring. Slight dif­ ferences in the right tails of the three phases’ distributions appear in Carlyss, Corpus Christi, New Orleans, and Pensacola, with more sub­ ~ o distribution relative to neutral in stantial rightward shift for the El Nin Beaumont. These distribution results are in agreement with the varied behavior of the three ENSO phases during the month of September and the autumn period as a whole seen in Fig. 4 and the exceedance rate data ~ a years are typically characterized found in Table 3. Interestingly, La Nin by quiescent conditions with clear skies, conditions which would favor ~ o conditions are known for more local ozone production, while El Nin frequent disturbed weather as a result of the more active jet stream (Goodman et al., 2000; Rasmusson and Wallace, 1983). Work by Neil­ son-Gammon et al. (2005) proposed that background ozone concentra­ tions, not local production, was responsible for these seasonal peaks, primarily due to the cycle of frontal passages in the spring and autumn which both introduce higher ozone/ozone precursor continental air into the region and also cause STE. Discussion in Zhang et al. (2015) ties springtime ozone concentrations in the southern United States more 10

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Fig. 10. NCEP reanalysis composites of meridional (top) and zonal (bottom) wind for April–May of El Ni~ no years minus neutral years. 11

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Fig. 11. 1000 mb geopotential height anomaly for April–May of El Ni~ no years relative to neutral years.

database for surface ozone concentrations in eight cities along the coast of the Gulf of Mexico in the United States from Texas to Florida. Days with precipitation were removed and each time history was detrended to control for the influence of regulatory changes. Each station exhibited a bimodal spring-autumn peak in tropospheric ozone concentration with a winter minimum and summer low-period. This summer decrease was smaller in magnitude for the eastern stations relative to the western stations. Stratification by ENSO revealed a dependency of the peak 8-h averaged tropospheric ozone concentration along the USGC, particu­ larly during the spring months (March, April, and May). A statistically significant enhancement of ozone on the order of 5–10 ppbv was found for each of the eight stations in the months of March and April for El ~ o relative to neutral conditions. Changes in mean were accompanied Nin by an increase in the length of the springtime ozone season, and together these factors led to an increase in the number of NAAQS exceedances for ~ o year. 27% more exceedances of the NAAQS 70 ppbv a given El Nin ~o standard were reported for the composite USGC station during El Nin years relative to neutral years. For individual stations, the difference ~ o years for the ranged from 28% more exceedances during El Nin Houston station to 69% more exceedances for the Carlyss station. These differences were observed both in the mean data and in the shape of the distribution of daily peak 8 h concentrations for each dataset. The ~ o spring months is related to changes in synopticenhancement in El Nin scale circulation governed by a broad area of low pressure centered over the eastern Gulf of Mexico which creates stagnant or weak offshore flow along the coast, increasing the concentration of ozone and ozone pre­ cursors. In addition to this regional effect, changes in the UTLS driven by anomalous convection in the tropical Pacific causes excess ozone to accumulate in the stratosphere where it is then susceptible to downward flux into the troposphere. A smaller enhancement observed for some stations during the month of September is caused by an increase in frontal activity during that season, which both increases STE and also increases the time during which the region is under the influence of a

contribute to higher concentrations of tropospheric ozone during the ~ o years. In contrast, an enhanced area of meridional flow spring in El Nin ~ a springtimes covers the western half of the dataset during La Nin (Fig. 12, top) resulting in mean monthly ozone concentrations similar to those of the neutral dataset (Fig. 4) and similar or lower exceedance rates to the neutral dataset (Table 3). This change in circulation is driven by an area of low pressure centered over the central United States ~ a and neutral springs (Fig. 12, bot­ (Fig. 13). Zonal flow during La Nin tom) is characterized by a smaller anomaly along the Texas coast and a larger anomaly over the four eastern stations. This is reflected by the ~ a and mean 8-h concentration values which are similar for the La Nin neutral conditions for stations on the west side of the dataset (Corpus Christi, Houston, Baton Rouge, and New Orleans) but slightly higher for ~ a conditions for the remaining eastern stations. Edwards et al. La Nin (2018) attributed the observed enhancements in the spring to changes in the frequency and temporal distribution of frontal passages, which enhance tropospheric ozone via transport of continental air (Rappen­ gluck et al., 2018) and via STE (Ganguly and Iyer, 2014). By including the entire Gulf Coast in this study, it is possible to identify a second, larger regional influence in these synoptic pressure anomalies. Similar climate composites (not shown for brevity) developed for El ~ o and La Nin ~ a autumns (September) reveal a more complex setup, Nin with some coastal areas experiencing a small enhancement in meridi­ onal flow and others experiencing a small reduction, and negligible anomalies in other areas. The magnitude of the meridional and zonal flow anomalies in September are small compared with those of the spring, leading to conditions closer to the average meridional and zonal flow, which is reflected by the similar values for average 8 h ozone concentrations among the three ENSO phases. 4. Conclusions Thirty years of surface ozone monitor data were leveraged to create a 12

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Fig. 12. As in Fig. 10, but for La Ni~ na years. 13

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Fig. 13. 1000 mb geopotential height anomaly for April–May of El Ni~ no years relative to neutral years.

continental airmass. Each of these situations increases the background component of the tropospheric ozone concentration, which when com­ bined with the local production, leads to higher daily peak 8-h average values. These higher concentrations have led to considerably more exceedances of the NAAQS standard for El Ni~ no years relative to neutral ~ a years, underscoring the importance of understanding how or La Nin these climate-scale and seasonal changes influence air quality in cities along the coast of the Gulf of Mexico. Extending the work of Edwards et al. (2018) to the entire USGC has shown that the earlier effect iden­ ~ o years is part of a larger synoptic trend that tified for Houston in El Nin influences air quality for the whole region.

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