Guest Editor: Schwietzke Stefan; University of Colorado Boulder, US
Surface ozone (O3), first identified in the 1940s and 1950s as an air pollutant that adversely impacts vegetation, human health, and crop yield (National Research Council, 1991; Lefohn et al., 1997; The Royal Society, 2008; Jerrett et al., 2009), is a widely recognized air quality problem in many regions around the world (Dentener et al., 2010). The globally averaged O3 tropospheric lifetime is approximately 23 days (Young et al., 2013), with the O3 lifetime being shorter near the surface and in urban areas because of deposition and chemical destruction. The resulting global tropospheric O3 distribution is highly variable by season, location, and altitude (Cooper et al., 2014). Elevated surface O3 and exceedances of the O3 National Ambient Air Quality Standard (NAAQS) are primarily determined by transport of O3 from outside the region, and local and regional production from photochemistry in the lower troposphere. Emissions and resulting concentrations of the O3 precursor gases nitrogen oxids (NOx) and volatile organic compounds (VOC), play a key role in local O3 production, as well as temperature and sunlight (Haagen-Smit, 1952; McKeen et al., 1991; Ryerson et al., 2001).
In the U.S., compliance with the O3 NAAQS is determined by the ‘Design Value’, which is calculated as the mean of three consecutive years of the 4th highest annual value for the maximum daily average 8-hour O3 value (MDA8) (CFR, 2017). The O3 NAAQS has been progressively lowered in recent years in consideration of the increasingly recognized health effects of prolonged O3 exposure. It was lowered from a value of 84 ppbv to 75 ppbv in 2007, and then further to 70 ppbv in 2015, which is the current standard.
Following an abundance of high O3 observations and exceedance of the then 84 ppbv NAAQS, the Northern Colorado Front Range (NCFR), including the Denver Metropolitan Area (DMA), the State of Colorado, and several regional agencies entered into an Early Action Compact (EAC) with the U.S. Environmental Protection Agency (EPA) in 2002. This agreement was voluntary and gave the opportunity to establish emission inventories, control strategies, and achieve compliance with the NAAQS (CDPHE, 2008a). The DMA and parts of Larimer and Weld County continued exceeding the NAAQS through 2007. In 2012, the DMA/NCFR, including the seven counties of Adams, Arapahoe, Boulder, Broomfield, Denver, Douglas, and Denver, as well as portions of Weld and Larimer counties, was designated as a ‘Marginal’ Non-Attainment Area (NAA) for the 2008 NAAQS. The area has remained in non-attainment since. With the lowering of the NAAQS from 75 to 70 ppb in 2015, the NCFR faced an even greater challenge to comply with the standard. A final rule, published by the EPA in 2016, reclassified the DMA/NCFR area from a ‘Marginal’ to a ‘Moderate’ O3 NAA (CDPHE, 2016).
Ozone chemistry, implementation of O3 control strategies, and compliance with the O3 NAAQS, are complicated and extraordinarily challenging in the NCFR for a number of reasons:
- The region has experienced remarkable growth, with an estimated 30% population increase for the NCFR from 2000 to 2015 (Supplemental Materials SM_Table_1). This population growth has been associated with urban sprawl, increase in transportation, power generation, and associated industrial stationary and mobile emission sources.
- The NCFR is subject to naturally elevated O3 and downfolding transport events that bring elevated O3 from the mid to upper troposphere to near the surface due to its elevation of 1500–1600 m asl and location on the eastern flanks of the Rocky Mountains. Occasions when such events led to significant enhancements in surface O3 and high MDA8 values have been reported (Langford et al., 2009). Musselman and Korfmacher (2014) showed that even remote high elevation areas of the southern Rocky Mountains can experience exceedance of the NAAQS value, in particular during springtime, when stratospheric intrusions contribute to elevated O3 at these elevations.
- Emissions from oil and natural gas (O&NG) industries are another complicating influence. In 2017, there were over 53,000 active O&NG wells in Colorado. The O&NG development is concentrated in a number of lower elevation basins (Figure 1),with 22,000 wells located in Weld County in the Denver Julesburg Basin (DJB), and thereby in the NAA (COGCC, 2014). Several recent studies have investigated the influence of O&NG emissions on Colorado O3. Building on the speciated measurements of O&NG-associated VOC, both Swarthout et al. (2013) and Gilman et al. (2013) found that emissions from the O&NG industry alone contribute to more than half of the local O3 production potential at the Boulder Atmospheric Observatory (BAO) in northern Denver. McDuffie et al. (2016), applying a box model, found that O&NG operations contribute approximately 20% to regional photochemical O3 production in the NCFR. These inferred influences have been confirmed by O3 monitoring results: A study conducted by the CDPHE in 2008, using O3 data from four sites along the NCFR, showed that for elevated O3 events during mid-May to mid-August 2006, air transport from the DJB was associated with the highest O3 values, whereas transport from surrounding areas, including the DMA, brought in air with lower O3 levels (CDPHE, 2008b). Using a correlation analysis of ambient O3 observations and winds, Evans and Helmig (2017) found that for the BAO and a site south of Boulder, during 2009–2012, an average of 65% of elevated O3 events were associated with transport from O&NG production regions. Based on case study comparisons near Greeley during the 2014 summer, Cheadle et al. (2017) estimated that O&NG emissions contribute up to ~20 ppbv to O3 production on high O3 days. Applying modeling of the same year’s data for the wider region, Pfister et al. (2017) concluded that, on average, O&NG emissions contribute to 30–40% of the O3 produced on high O3 days.
- During recent years, the region has been subjected to an unusual frequency and extent of nearby wildfires and transported wildfire plumes from outside of the state. These wildfire emissions are contributing to occurrences of elevated O3 production. Given the irregular and sporadic occurrences, thus far there is no quantitative assessment of the wildfire contribution to Colorado O3.
We investigated 2000–2015 O3 data from across the State of Colorado for the spatial distribution of O3, elevated O3 occurrences, O3 trends, and if and how measures that have been implemented for curbing O3 pollution are reflected in observational records. Besides investigating absolute O3 mixing ratios and their changes over time, we used two variables to examine changes in the O3 production efficiency. 1. We studied the low distribution of the O3 spectrum as an indicator of the degree of nighttime O3 destruction, which in urban areas is largely determined by emission and the abundance of nitric oxide (NO). Direct and long-term measurements of NOx are sparse, we therefore aim to yield insight into changes in NOx from the nighttime O3 behavior. 2. We determined diurnal amplitudes of the surface layer ambient O3 mixing ratio. The diurnal O3 change is driven by multiple processes, including nighttime O3 destruction by NO, diurnal boundary layer dynamics, and daytime rate of O3 production from photochemistry. We examine this variable to investigate changes over time in the chemical processes determining daytime O3 production and nighttime O3 destruction.
2. Experimental study
2.1.1. Location of study and data sources
We were able to retrieve surface O3 data from a total of 79 sites in Colorado for 2000–2015. Data for 70 sites were downloaded from the EPA Air Quality System (AQS) archive in September 2016. AQS includes Colorado O3 data from the Colorado Department of Public Health and Environment (CDPHE), the US Forest Service (USFS), Boulder County Public Health (BCPH), Garfield County, the US National Park Service (NPS), the Southern Ute Indian Tribe Reservation (SUIT), Meteorological Solutions Inc. (MSI), the Colorado Bureau of Land Management (CBLM), the City of Aspen, CH2M Hill, as well as from monitoring by the EPA. Additional data from three sites were obtained from the National Oceanic and Atmospheric Administration (NOAA) Global Monitoring Division (GMD). Data from six sites operated during the summer 2014 Front Range Air Pollution and Photochemistry Experiment (FRAPPE), and from the NSF-funded Long-Term Ecological Research (LTER) Niwot Ridge program, were collected by the Institute of Arctic and Alpine Research (INSTAAR) at the University of Colorado, Boulder. Data for Dinosaur National Monument (DNM) were received from the NPS. NOx data for 12 sites were downloaded from AQS.
Site information is summarized in Table 1, and Figure 2 depicts a map with all site locations. AQS sites are represented by yellow markers, NOAA sites by green markers, INSTAAR measurements by blue markers, and data obtained directly from the NPS in red. The NPS Dinosaur National Monument (DNM) site coordinates given in the data record placed the site within Colorado, but we later discovered that the actual measurement location is ~22 km west in the State of Utah. Nonetheless, we retained the DNM record for our analyses. The location setting column in Table 1 characterizes sites as rural, suburban, and urban. The amount of data varied widely among sites, from ~2 months to a maximum of 15 years; the fraction of data that were available for each site and year is summarized in SM_Table_2.
|Site No||Data Source||County||City||Site Name||Agency/Program||Latitude||Longitude||Elevation (masl)||Location Setting|
|4||AQS||Boulder||not in a City||Eldora Ski Area||USFS||39.94||–105.61||3201||rural|
|5||AQS||Boulder||Boulder||South Boulder Creek||CDPHE||39.96||–105.24||1669||suburban|
|6||AQS||Boulder||Boulder||Boulder Fire Station||BCCHD||40.01||–105.25||1662||rural|
|7||AQS||Boulder||not in a City||Longmont||BCCHD||40.15||–105.06||1499||suburban|
|8||AQS||Chaffee||not in a City||Trout Creek Pass||USFS||38.91||–106.00||2920||rural|
|9||AQS||Clear Creek||not in a City||Geneva Basin||USFS||39.58||–105.73||3474||rural|
|10||AQS||Clear Creek||not in a City||Goliath Peak||USFS||39.64||–105.59||3518||rural|
|11||AQS||Clear Creek||not in a City||Mount Evans||USFS||39.59||–105.64||4300||rural|
|12||AQS||Clear Creek||not in a City||Mines Peak||CDPHE||39.79||–105.76||3806||rural|
|13||AQS||Denver||Denver||Denver – Camp||CDPHE||39.75||–104.99||1593||urban|
|14||AQS||Denver||Denver||Denver – Carriage||CDPHE||39.75||–105.03||1621||suburban|
|15||AQS||Denver||Denver||Denver – Animal Shelter||CDPHE||39.70||–105.00||1594||urban|
|16||AQS||Denver||not in a City||La Casa||CDPHE||39.78||–105.01||1602||urban|
|17||AQS||Douglas||not in a City||Chatfield Reservoir||CDPHE||39.54||–105.07||1678||rural|
|18||AQS||Douglas||not in a City||Chatfield State Park||CDPHE||39.53||–105.07||1676||rural|
|19||AQS||El Paso||not in a City||U.S. Air Force Acad.||CDPHE||38.96||–104.82||1971||rural|
|20||AQS||El Paso||Manitou Springs||Manitou Springs||CDPHE||38.85||–104.90||1955||suburban|
|21||AQS||Garfield||Rifle||Rifle – Health Dept.||CDPHE||39.54||–107.78||1640||suburban|
|22||AQS||Garfield||not in a City||Bell Ranch||USFS||39.49||–107.66||1785||rural|
|23||AQS||Garfield||not in a City||Flattops #3||USFS||39.80||–107.62||2904||rural|
|24||AQS||Garfield||not in a City||Ripple Creek Pass||USFS||40.09||–107.31||2930||rural|
|25||AQS||Garfield||not in a City||Sunlight Mountain||USFS||39.43||–107.38||3224||rural|
|26||AQS||Garfield||not in a City||Wilson||USFS||39.49||–107.17||2358||rural|
|27||AQS||Garfield||Battlement Mesa||Battlement Mesa||Garfield Cty||39.44||–108.03||1690||suburban|
|28||AQS||Garfield||Glenwood Springs||Glenwood Springs||Garfield Cty||39.55||–107.33||1756||suburban|
|29||AQS||Garfield||not in a City||Carbondale||Garfield Cty||39.41||–107.23||1867||suburban|
|30||AQS||Gunnison||not in a City||McClure Pass||USFS||39.09||–107.23||2930||rural|
|31||AQS||Gunnison||not in a City||Gothic||USEPA||38.96||–106.99||2926||rural|
|32||AQS||Jackson||not in a City||Walden – Chandler Ranch||NPS||40.88||–106.31||2417||rural|
|35||AQS||Jefferson||not in a City||Rocky Flats – N||CDPHE||39.91||–105.19||1802||rural|
|36||AQS||Jefferson||Applewood||Golden – NREL||CDPHE||39.74||–105.18||1832||suburban|
|37||AQS||Jefferson||Golden||Lookout Mountain Rd||CDPHE||39.73||–105.25||2278||suburban|
|39||AQS||La Plata||not in a City||Shamrock Station||USFS||37.30||–107.48||2367||rural|
|40||AQS||La Plata||not in a City||Ignacio||SUIT||37.14||–107.63||1983||rural|
|41||AQS||La Plata||not in a City||Bondad||SUIT||37.10||–107.87||1920||rural|
|42||AQS||Larimer||not in a City||RMNP – Long’s Peak||NPS||40.28||–105.55||2742||rural|
|43||AQS||Larimer||Fort Collins||Fort Collins – West||CDPHE||40.59||–105.14||1571||rural|
|44||AQS||Larimer||not in a City||Rist Canyon||CDPHE||40.64||–105.28||2058||rural|
|45||AQS||Larimer||Fort Collins||Fort Collins – CSU||CDPHE||40.58||–105.08||1524||suburban|
|46||AQS||Larimer||not in a City||RMNP||USEPA||40.28||–105.55||2743||rural|
|48||AQS||Mesa||not in a City||Grand Mesa||USFS||38.93||–108.23||3040||rural|
|49||AQS||Mesa||not in a City||Silt – Collbran||USFS||39.34||–107.71||2485||rural|
|50||AQS||Mesa||not in a City||CO Nat. Mon.||NPS||39.11||–108.74||1740||rural|
|51||AQS||Moffat||not in a City||Lay Peak||CDPHE||40.51||–107.89||1902||rural|
|52||AQS||Moffat||not in a City||Elk Springs||CDPHE||40.33||–108.49||1902||rural|
|53||AQS||Montezuma||Cortez||Cortez – Health Dept.||CDPHE||37.35||–108.59||1890||urban|
|54||AQS||Montezuma||not in a City||Mesa Verde NP||NPS||37.20||–108.49||2170||rural|
|55||AQS||Morgan||not in a City||LS Power – High Plains Energy||MSI||40.39||–103.50||1260||rural|
|56||AQS||Park||not in a City||Kenosha Pass||USFS||39.42||–105.76||3098||rural|
|57||AQS||Park||not in a City||Fairplay||BLM||39.24||–105.98||3027||rural|
|58||AQS||Pitkin||not in a City||Ajax Mountain||USFS||39.15||–106.82||3415||rural|
|59||AQS||Pitkin||Aspen||Aspen||City of Aspen||39.20||–106.84||2415||suburban|
|60||AQS||Pueblo||Pueblo West||Black Hills||CH2M Hill||38.35||–104.69||1525||rural|
|61||AQS||Rio Blanco||not in a City||CO Plant Science Bldg.||NPS||40.04||–107.85||1994||rural|
|62||AQS||Rio Blanco||Rangely||Rangely – Golf Course||NPS||40.09||–108.76||1655||rural|
|63||AQS||San Miguel||not in a City||Miramonte Reservoir||USFS||38.01||–108.41||2357||rural|
|65||AQS||Teller||not in a City||Manitou Exp. Forest||USFS||39.10||–105.09||2360||rural|
|66||AQS||Weld||Greeley||Greeley – 15th St.||CDPHE||40.42||–104.69||1420||urban|
|67||AQS||Weld||Greeley||Greeley – Weld Cty Twr||CDPHE||40.39||–104.74||1484||suburban|
|68||AQS||Weld||not in a City||Briggsdale||USFS||40.65||–104.33||1483||rural|
|69||AQS||Weld||not in a City||Pawnee Buttes||USFS||40.81||–104.04||1661||rural|
|70||INSTAAR||Boulder||Boulder||Boulder – INSTAAR||FRAPPE||40.01||–105.25||1607||urban|
|71||INSTAAR||Boulder||not in a City||Sugar Loaf Fire Dept.||FRAPPE||40.02||–105.36||1982||rural|
|72||INSTAAR||Boulder||not in a City||Coughlin Meadows||FRAPPE||40.00||–105.48||2527||rural|
|75||INSTAAR||Boulder||not in a City||Lost Angels Fire Dept.||FRAPPE||40.02||–105.40||2393||rural|
|76||NOAA||Boulder||Erie||Boulder Atmos. Observatory||NOAA||40.05||–105.00||1584||rural|
|77||NOAA||Boulder||not in a City||Niwot Ridge – Tundra||NOAA||40.05||–105.59||3538||rural|
|78||NOAA||Boulder||not in a City||Niwot Ridge – C1||NOAA||40.04||–105.54||3035||rural|
|79||INSTAAR||Boulder||not in a City||Niwot Ridge – Soddie||INSTAAR||40.04||–105.57||3340||rural|
|80||NPS||Moffat||not in a City||Dinosaur Nat. Monument1||NPS||40.29||–108.94||1463||rural|
2.1.2. Data processing
Data were downloaded as zip files, converted to .xlsx files, and then imported into Matlab. All data are reported as a molar ratio in air, i.e. units of parts per billion by volume (ppbv [nmol mol–1]). All data were converted to Mountain Standard Time. A few stray data values <–5 ppbv were removed from records. During the review of this manuscript, deviations in the O3 data for the southwestern Colorado sites Bondad and Ignacio were pointed out; after further investigation, the 2000–2004 data for these two sites were excluded from further analyses (SM_Text_1). Data were plotted as time series, and box-whisker plots were prepared when at least 80% of data were available for a given year. For box-whisker plots, the center line represents the data median, and the upper and lower horizontal bars of the box the 25 and 75 percentiles of the data, the whiskers are drawn to a length of 1.5 times the interquartile range away from the top and bottom of the boxes, and values outside the whisker range are marked as red crosses. As we particularly focus on summer O3 (June, July, August), when most exceedances of the O3 NAAQS occur, hourly O3 values from 1st June (12:00 am) until 31st August (11:00 pm) were extracted and used to compute the summer 5th, 50th, and 95th O3 percentile values for each year. When at least 80% of summer data were available and a site had at least 10 years of data, trends were calculated for the 5th, 50th, and 95th percentiles with a linear regression fit. The statistical significance of the linear regression result was evaluated from the p-value, tested against the null hypothesis, R2 = 0, which indicates no linear relationship by using the standard F-statistic. The null hypothesis was rejected with a confidence level ≥95% when the probability P associated with the F statistic p-value was ≤0.05. For the MDA8 and Design Value calculation, the Code of Federal Regulations (2017) protocol was used, with a linear regression line fit through the calculated annual data points for each year. In the maps showing the geographical distribution of trend analyses, slope values are given by the color scale, and the significance of each trend result is represented by the size of the marker: Statistically significant trend results are shown in 4 times larger size than statistically non-significant values.
For calculation of daily amplitudes, the hourly minimum O3 value occurring in the first 12 hours of a day was subtracted from the following daily maximum. Amplitudes were only calculated when at least 20 hourly data points were available for a given day. The seasonal change of O3 diurnal amplitude during the year was calculated from the 50th percentile amplitude for every month when at least 80% of data were available. For each site with at least 10 years of data, box-whisker plots show the year-to-year variability and change of diurnal amplitudes. As for the O3 mixing ratio, we focused again on the summer months’ O3 amplitudes, and computed the 5th, 50th, and 95th percentile values for each summer when at least 80% of data were available. For sites with at least 10 years of data, a linear regression fit was calculated to evaluate trends in the summer amplitude.
Additionally, all summer data that were available for the 5-year period of 2011–2015 (plus three 2007–2008 Boulder County site data sets) were used to calculate the 50th and 95th percentile summer O3 mixing ratio, and the median summer daily amplitude. In the maps displaying these results, the marker area is proportional to the square of the amount of available data.
3.1. O3 mixing ratio
3.1.1. O3 summer mixing ratios
The full time series records for all 80 sites are available in SM_Figure_1. 69 data sets have data for 2011–2015. The geographic distribution of the 50th and 95th percentile summer O3 mixing ratios for this time window is visualized in Figure 3. The amount of data considered for each point is reflected by the marker size; the smallest marker, i.e. site No. 52 (Elk Springs) represents 735 hourly data points, and the largest marker, site No. 47 (Palisade), had 10977 hourly data points. Overall, summer median O3 results span a range from 32–62 ppb across these Colorado sites (Table 2). Within the DMA, relatively low median mixing ratios of ~35 ppbv were found, whereas relatively higher values were calculated for suburban Denver (43–47 ppbv). The highest summer median O3 mixing ratios were seen at the high elevation mountain sites, with the highest elevation site, Mount Evans (4300 m), having the highest value of 62 ppbv, ~30 ppbv above those for the DMA sites.
|Site No||Site Name||Median Summer O3 [ppbv]||95th Percentile Summer O3 [ppbv]||Median Daily Summer Amplitude [ppbv]||95th Percentile Daily Summer Amplitude [ppbv]|
|4||Eldora Ski Area||58||76||14||36|
|5||South Boulder Creek||43||71||42||67|
|6||Boulder Fire Station||32||57||42||62|
|8||Trout Creek Pass||50||65||18||33|
|13||Denver – Camp||35||62||48||68|
|14||Denver – Carriage||41||72||59||81|
|15||Denver – Animal Shelter||38||67||52||76|
|19||U.S. Air Force Acad.||45||68||50||68|
|21||Rifle – Health Dept.||35||59||42||55|
|24||Ripple Creek Pass||51||64||10||23|
|32||Walden – Chandler Ranch||37||57||41||54|
|36||Golden – NREL||48||75||38||67|
|42||RMNP – Longs Peak||51||70||23||48|
|43||Fort Collins – West||45||73||42||64|
|45||Fort Collins – CSU||37||66||46||70|
|46||RMNP – Collocated||49||68||23||47|
|49||Silt – Collbran||50||64||17||29|
|50||CO Nat. Mon.||49||64||26||36|
|54||Mesa Verde NP||50||64||16||29|
|61||CO Plant Science Bldg.||41||58||27||39|
|67||Greeley – Weld Cty Twr||43||71||51||75|
|70||Boulder – INSTAAR||39||65||41||65|
|71||Sugar Loaf Fire Dept.||40||65||35||57|
|75||Lost Angels Fire Dept.||46||66||26||48|
|76||Boulder Atmos. Obs.||41||68||43||65|
|77||Niwot Ridge – Tundra||59||74||14||31|
|78||Niwot Ridge – C1||48||66||23||49|
|79||Niwot Ridge – Soddie||47||62||19||38|
|80||Dinosaur Nat. Mon.||45||64||39||55|
A different spatial pattern was found for the 95th percentile summer O3 mixing ratios, where the the high elevation locations on the eastern slopes and the greater DMA sites exhibited the highest values. Most of the DMA sites in the blue enlargement box have values greater than 67 ppbv. 95th percentile values were on the order of 20 ppbv or less above the 50th percentile vales for many of the rural low elevation, and for high elevation sites. In contrast, a more dynamic O3 range was found for sites located in the NCFR. These sites all show a wider distribution, with 95th percentile values exceeding the median by ~30 ppbv or more. The relationship between the 50th and 95th percentile mixing ratios and the site altitude is shown in Figure 4. There is a statistically significant increase of the summer O3 50th percentile value with altitude of 6.5 ± 1.6 ppbv km–1 (p-value < 0.05). In contrast, the 95th percentile O3 values are much more variable and do not show a statistically significant dependence on elevation.
3.1.2. O3 hourly time series data
Three sites with different characteristics were chosen for illustrating the data records and emphasizing main features; their results are displayed in Figure 5: 1. Mesa Verde National Park (MVNP), in the southwestern part of Colorado, representing a rural reference site, 2. Welby (WEL), a suburban site located northeast of Denver, at the southern edge of the DJB, and 3. the Golden – National Renewable Energy Laboratory (NREL) site, close to and west of Denver, in a densely populated area within the NCFR O3 NAA.
Of the sites shown here, MVNP is the one with the lowest total O3 variability over the year, indicated by the lowest spread of the data in the summary box-whisker plots included as the right series of graphs in Figure 5. Ozone mixing ratios at MVNP oscillate around a value of 40 ppbv in winter, and ~55 ppbv during summer; summer maxima are ~70 ppbv. A strong seasonal variability can be seen in the NREL data. Here, winter values are between 0–40 ppbv. NREL has the highest summer values of these three example sites; 1-hour O3 maxima in the summer exceeded 100 ppbv on a total of 69 occasions. WEL O3 values are not quite as high as for NREL, with all 1-hour values remaining below 100 ppbv. WEL is characterized by a high abundance of low winter values, when O3 frequently drops to near 0 ppbv. WEL shows the most evident increasing trend in the data, most notable in the first part of the record.
3.1.3. Summer O3 trends
Summer O3 trends were investigated by conducting a linear regression fit to the entire summer data record. Results for the three sample sites are shown in Figure 6; graphs for all other sites are available in SM_Figure_2.
MVNP shows signs for decreasing O3 at all percentile values, with the 95th percentile value of –0.35 ± 0.34 ppbv yr–1 being a statistically significant negative trend. The O3 mixing ratios at NREL show a steeply increasing trend of 0.55 ± 0.44 ppbv yr–1 for the 5th percentile values. Changes in the median values (increasing) and 95th percentile values (decreasing) are not statistically significant. The WEL results are characterized by statistically significant increasing trends for the 5th, 50th, and 95th percentiles. Details of the trend analyses results for sites that had long enough records to fulfill the selection criteria are listed in Table 3. Maps showing the geographical distribution of trend results for the 5th, 50th, and 95th values are given in Figure 7. In Table 3 we also include trends for the annual 4th highest MDA8 and Design Value, (time series graphs for the Design Value and MDA8 trend determinations are shown in SM_Figure_3) for comparison of those regulatory metrics with the 95th percentile results that are presented throughout this paper. Given the longer data coverage needed for calculation of the Design Value (i.e. a three-year running mean through continuous data), this calculation was only possible for a subset of the site records.
|Site No||Site Name||5th Percentile||50th Percentile||95th Percentile||4th highest MDA8||Design Value|
|Slope ± 95% confidence limit, ppbv yr–1||Slope ± 95% confidence limit, ppbv yr–1||Slope ± 95% confidence limit, ppbv yr–1||Slope ± 95% confidence limit, ppbv yr–1||Slope ± 95% confidence limit, ppbv yr–1|
|1||Welby||0.20 ± 0.13||0.99 ± 0.46||0.55 ± 0.48||0.61 ± 0.46||0.68 ± 0.51|
|2||Highland Reservoir||0.88 ± 0.45||0.29 ± 0.45||–0.18 ± 0.57||–0.20 ± 0.95|
|5||South Boulder Creek||0.39 ± 0.31||0.16 ± 0.44||0.00 ± 0.50||–0.04 ± 0.57||–0.10 ± 0.69|
|14||Denver – Carriage||0.66 ± 0.23||1.01 ± 0.61||–0.01 ± 0.72||–0.09 ± 0.91||–0.44 ± 0.85|
|18||Chatfield State Park||0.24 ± 0.59||0.05 ± 0.79||–0.21 ± 0.87||–0.34 ± 1.03|
|19||U.S. Air Force Acad.||0.60 ± 0.25||0.35 ± 0.47||–0.30 ± 0.49||–0.30 ± 0.52||–0.27 ± 0.67|
|20||Manitou Springs||0.87 ± 0.80||0.37 ± 0.93||–0.16 ± 0.98||–0.81 ± 0.94|
|33||Arvada||0.78 ± 0.30||0.85 ± 0.69||0.26 ± 0.85||0.08 ± 0.99||–0.02 ± 0.94|
|34||Welch||0.94 ± 0.49||0.59 ± 0.56||0.55 ± 0.72||0.55 ± 0.70||0.62 ± 0.70|
|35||Rocky Flats – N||0.44 ± 0.41||0.07 ± 0.42||–0.31 ± 0.54||–0.31 ± 0.65||–0.33 ± 0.66|
|36||Golden – NREL||0.56 ± 0.44||0.06 ± 0.38||–0.28 ± 0.51||–0.30 ± 0.71||–0.33 ± 0.83|
|39||Shamrock Station||–0.10 ± 0.74||–0.31 ± 0.70||–0.39 ± 0.82||–0.55 ± 0.75|
|41||Bondad||0.04 ± 0.42||0.00 ± 0.99||–0.21 ± 0.45||0.03 ± 0.49|
|42||RMNP – Long’s Peak||0.01 ± 0.43||–0.13 ± 0.57||–0.40 ± 0.64||–0.50 ± 0.59||–0.56 ± 0.56|
|43||Fort Collins – West||–0.36 ± 0.64||–0.56 ± 0.80||–0.64 ± 0.83|
|45||Fort Collins – CSU||0.49 ± 0.22||0.33 ± 0.37||–0.13 ± 0.42||0.01 ± 0.54||–0.03 ± 0.74|
|54||Mesa Verde NP||–0.16 ± 0.33||–0.31 ± 0.32||–0.35 ± 0.34||–0.23 ± 0.35||–0.19 ± 0.51|
|67||Greeley – Weld Cty Twr||0.12 ± 0.26||0.01 ± 0.36||–0.37 ± 0.50||–0.41 ± 0.80||–0.30 ± 0.89|
|78||Niwot Ridge – C1||–0.56 ± 0.53||–0.53 ± 0.59||–0.55 ± 0.79||–0.58 ± 0.68|
|80||Dinosaur Nat. Mon.||0.47 ± 0.68||0.01 ± 0.52||0.03 ± 0.83|
For the 5th percentile values, most sites (16 out of 20) show increasing O3 values, with 11 of these passing the statistical significance test. Five of these results are >0.63 ppbv yr–1, equivalent to a remarkable >10 ppbv increase in the 5th percentile O3 value over the 16-year record. For the 50th percentile, 15 sites show increasing O3 results, 4 being statistically significant. For the 95th percentile values most (15) sites show a decrease in O3, with one of these being statistically significant; four rates of change are positive, with one site (WEL) being a statistically significant positive trend. The increasing trend results in the 95th percentile value at WEL are consistent with trend results for the annual 4th highest MDA8 and Design Value. WEL is the only site that showed statistically significant increasing O3 trends at all (5th/50th/95th) percentile levels. The geographical distribution of these trend analyses (Figure 7) shows that the increase in the low percentile O3 values is prominent and consistent at the urban and NCFR sites. Increases in median O3 are most pronounced in the DMA.
3.2. O3 Daily summer amplitudes
3.2.1. Seasonal cycle of O3 diurnal amplitudes
Time series results for diurnal O3 amplitudes for the full data records are presented in SM_Figure_4. The full record of O3 diurnal amplitudes for the case study sites is shown in Figure 8. The same data, binned by month for illustrating the mean seasonal cycle, are shown in Figure 9 (see SM_Figure_5 for results for other sites). At all sites, diurnal amplitudes are highest during the summer months. Absolute values differ largely between sites, with MVNP having the lowest values, ranging from (median) i.e. ~10 ppbv in winter to ~20 ppbv in summer. These are on the order of 30–50% of those observed at NREL. WEL has an even larger seasonal cycle than NREL, and interestingly, the seasonal cycle shows a wider spread summer maximum.
3.2.2. Daily summer amplitude for 2011–2015
The same sites for which the 50th and 95th percentile summer O3 mixing ratios were determined (Figure 3) were subjected to a statistical analysis of the summer diurnal O3 amplitude: Tabulated results were included in Table 2, and the geographical distribution is shown in Figure 10. Urban areas consistently show higher daily amplitudes than rural areas. Median DMA amplitude values are on the order of 55 ppbv. Values in suburban Denver are somewhat lower, on the order of 35–45 ppbv. Within the inner city, on high O3 production summer days, the diurnal O3 increase is on the order of 60–80 ppbv. Rural and high elevation sites show significantly lower diurnal O3 changes, with median daily amplitude values of 10–15 ppbv for the most remote locations. There are likely two contributing processes determining the larger urban amplitudes. Some portion is due to the low nighttime values from titration with NO, and mixing of air from aloft with higher O3 during the breakup of the nocturnal surface layer. The remainder is due to daytime photochemical production. The linear regression analyses between amplitude and site elevation yielded statistically significant negative slope relationships for both the 50th and 95th percentiles, as shown in Figure 11a, b. The O3 diurnal amplitude is inversely correlated with median O3 (Figure 11c).
3.2.3. Summer daily amplitude trend analyses
Trend analyses on the diurnal amplitude data were prepared to investigate changes in the summertime dynamic O3 behavior. Results for the case study sites are shown in the right side set of graphs in Figure 8, results for all other sites are presented in SM_Figure_6. At MVNP, summer diurnal amplitudes have been moving towards slightly lower values over the study period. While slope values are small, the median and 95th percentile results (–0.16 ± 0.14/–0.37 ± 0.25 ppbv yr–1) are statistical significant changes. At NREL, there has been a downward trend of dirnal amplitudes, with statistical significant decreases of the median and 95th percentile slope values of –0.67 ± 0.37 and 0.94 ± 0.54 ppbv yr–1, respectively. Results from WEL contrast the other two sites. Here, amplitudes have been increasing at all chosen percentile values; but none of these changes are statistically significant.
The results for all datasets are listed in Table 4. The geographical distribution of the slopes is shown in Figure 12. Notably, the majority of sites exhibit declining amplitudes, with those being reflected at all percentile values. Ten of the negative median slope values passed the statistical significance test. Negative values were determined for most of the sites in the DMA and NCFR. WEL is the only DMA site that shows positive slopes at all percentile values.
|Site No||Site Name||5th Percentile||50th Percentile||95th Percentile|
|Slope ± 95% confidence limit, ppbv yr–1||Slope ± 95% confidence limit, ppbv yr–1||Slope ± 95% confidence limit, ppbv yr–1|
|1||Welby||0.55 ± 0.83||0.30 ± 0.50||0.38 ± 0.62|
|2||Highland Reservoir||–0.27 ± 0.73||–0.70 ± 0.35||–0.66 ± 0.59|
|5||South Boulder Creek||0.09 ± 0.53||–0.19 ± 0.38||–0.06 ± 0.62|
|14||Denver – Carriage||–0.16 ± 1.27||–0.68 ± 0.66||–0.71 ± 1.07|
|18||Chatfield State Park||0.21 ± 0.74||–0.37 ± 0.62||–0.23 ± 0.58|
|19||U.S. Air Force Acad.||–0.72 ± 0.69||–0.86 ± 0.35||–0.76 ± 0.47|
|20||Manitou Springs||–0.34 ± 0.48||–0.68 ± 0.34||–0.91 ± 0.77|
|33||Arvada||0.19 ± 1.35||–0.31 ± 0.79||–1.05 ± 1.23|
|34||Welch||0.27 ± 0.55||–0.21 ± 0.40||–0.30 ± 0.69|
|35||Rocky Flats – N||0.01 ± 0.37||–0.42 ± 0.31||–0.69 ± 0.48|
|36||Golden – NREL||–0.03 ± 0.41||–0.67 ± 0.37||–0.94 ± 0.54|
|39||Shamrock Station||–0.22 ± 0.58||–0.49 ± 0.38||–0.14 ± 0.38|
|41||Bondad||–0.33 ± 0.58||–0.30 ± 0.23||–0.43 ± 0.76|
|42||RMNP – Long’s Peak||–0.09 ± 0.29||–0.24 ± 0.33||–0.07 ± 0.48|
|43||Fort Collins – West||0.11 ± 0.55||–0.20 ± 0.62||0.02 ± 1.27|
|45||Fort Collins – CSU||0.13 ± 0.68||–0.41 ± 0.33||–0.44 ± 0.67|
|54||Mesa Verde NP||–0.05 ± 0.20||–0.16 ± 0.14||–0.37 ± 0.25|
|67||Greeley – Weld Cty Twr||0.23 ± 0.69||–0.56 ± 0.53||–0.69 ± 0.89|
|78||Niwot Ridge – C1||–0.10 ± 0.34||–0.25 ± 0.39||0.12 ± 0.69|
|80||Dinosaur Nat. Mon.a||–0.65 ± 0.73||–0.51 ± 1.23||–0.40 ± 1.84|
4.1. Year-to-year variability
Surface O3 is dependent on numerous influences, causing significant year-to-year variability (Strode et al., 2015). The range (spread), representing the year-to-year variability, of the median O3 summer values within individual records was between 8–18 ppbv for these Colorado sites. Study of causal relationships determining O3 have been an active field of research, motivated by the necessity to elucidate the effect of human influences. Processes determining year-to-year changes include prevalence of high pressure weather systems (Reddy and Pfister, 2016), occurrences of stratospheric intrusions (Langford et al., 2009; Langford et al., 2015), wildfires (Jaffe et al., 2008; Jaffe and Wigder, 2012; Jaffe et al., 2013; Baylon et al., 2016; Lu et al., 2016), long-range to trans-continental transport events (Jaffe and Ray, 2007; Zhang et al., 2008; Reidmiller et al., 2009; Zhang et al., 2009), and changes in anthropogenic O3 precursor emissions. In Colorado, elevation and proximity to urban centers are two factors further influencing absolute levels and variability. The individual contribution of these effects on the O3 data considered here is beyond the objective of this study. However, recognition of these multiple influencing factors is of importance for evaluating the trend results presented here. While the 10-year minimum cutoff and 95% p-test confidence interval provide robust trend results, it cannot be completely excluded that trend results are influenced by multi-year extremes of any or a combination of the above listed factors.
4.2. Dependency of ozone on elevation
Highest O3 median values were observed at the high elevation sites. The summer elevation gradient of 6.5 ± 1.6 ppbv km–1 found in the data considered here is significantly lower than the 15 ppb km–1 reported by Brodin et al. (2010) for a ~30 km horizontal/2 km elevation east-west transect west of Boulder. These different results are likely due to the abundance of considered network sites within the NCFR for the study presented here, and the wide spread seen in the low elevation data (Figure 4). While Brodin et al. (2010) referenced their data to a single downtown Boulder site, where O3 values were relatively low, many of the lower elevation sites that went into the calculation here are in suburban areas, where median O3 levels are higher overall because these sites have less nighttime O3 loss from titration by NO. While median O3 increases with elevation, there is not as much of a dynamic diurnal O3 change at the high elevation sites, as a larger fraction of O3 at these sites is due to long-range transport and the increase of O3 with elevation. The lower elevation sites, in contrast, are influenced more by local O3 production, causing larger diurnal O3 amplitudes. Those two dependencies determine the inverse relationship and scatter in the data in Figure 11.
4.3. Ozone trends at rural sites
For rural locations in the U.S., O3 trends have been inconsistent and smaller than in urban areas. The behavior in the western U.S. contrasts that in eastern regions of the country, where more homogenous, downward O3 trends have occurred (Cooper et al., 2012, 2014). Results from the analyses presented here provide further evidence for this conclusion, as most of the rural and higher elevation sites showed neutral to only slightly downward summer O3 for the 50th and 95th percentile values.
4.4. Ozone trends at high mountain sites
Seasonal studies have reported an increase in O3 at western U.S. mountain sites (Parrish et al., 2012; Cooper et al., 2014; Gratz et al., 2015). This has mostly been associated to increasing O3 in transcontinental transport from Asia, with this effect being most influential in spring. Two high mountain sites on the U.S. west coast that have been central in demonstrating O3 increases stemming from outflow from Asia are Lassen NP (1756 m asl), and Mt Bachelor (2763 m) (Jaffe et al., 2003; Jaffe and Ray, 2007; Parrish et al., 2012; Gratz et al., 2015). Incorporating O3 sonde data in their analyses, Cooper et al. (2012) calculated that springtime free tropospheric O3 over western North America increased at a rate of 0.41 ± 0.27 ppbv yr–1 between 1995–2011.
Available trends from two sites in the Colorado network above 2500 m asl, i.e. Niwot Ridge C1 (3035 m), and Rocky Mountain NP Longs Peak (2742 m) offer a comparison with these west coast high elevation sites. Remarkably, the mean (of these two, ± standard deviation) 5th/50th/95th percentile O3 trends are all negative, i.e. –0.23 ± 0.40/–0.33 ± 28/–0.48 ± 0.11 ppbv yr–1, and inconsistent with the observations from the U.S. west coast. This difference is probably due to the high elevation west coast sites being relatively isolated from North American influence, whereas the two Rocky Mountain sites are more responsive to the changes in background ozone in continental North America and the NCFR.
4.5. Ozone regulatory considerations
There are two groups of sites with MDA8 and Design Values over the >70 ppbv threshold (SM_Table_3, and SM_Figure_7 showing the geographical distribution): 1. high elevation mountain sites and 2. suburban NCFR sites. Sunlight Mountain, the 7th highest elevation site at 3225 m, has the highest average number of exceedances per year (32). This site record, however, is relatively short (3 years), which makes these data more susceptible to biases from interannual variability, and places a relatively high uncertainty on this ranking. There are several other high mountain sites where the MDA8 regularly exceeds 70 ppbv, such as Niwot Ridge, and Rocky Mountain NP Longs Peak. These observations are in line with previous elaborations that pointed out the high O3 at these mountain sites, and the significant contribution from long-range continental and upper troposphere/lower stratosphere transport on elevated O3 (Langford et al., 2009; Lin et al., 2012; Cooper et al., 2015). The second group are NCFR sites, and here, in particular, the suburban locations on the western periphery of the City of Denver. This chain of stations along the eastern foothills of the Rocky Mountains shows a consistent behavior of a year after year high number of high O3 days, with an average of 10–27 days per year when the O3 MDA8 exceeds 70 ppbv. A contributing factor appears to be the diurnal air flow pattern along the NCFR, where predominantly upslope flow conditions during mid-day to late afternoon bring air that has been enriched in O3 precursors towards the mountain slopes, causing elevated O3 in the afternoon at the Plains-Rocky Mountain transition zone (Evans and Helmig, 2017). The analyses presented here expand upon the observational study from two sites near Boulder (Evans and Helmig, 2017), and recent modeling work (Pfister et al., 2017), demonstrating this spatial elevated O3 distribution along a ~30 km wide belt extending some 150 km north-south (Fort Collins to Chatfield) along the NCFR foothills.
4.6. Ozone changes in relation to NOx and VOC
Mandated by the Clean Air Act, emission reductions of O3 precursors in NAAs have been remarkably successful in many U.S. urban regions, in particular in the mid-western U.S. (Lurmann et al., 2015; Sather and Cavender, 2016). For instance, reductions for the MDA8 ranging from 18–38 ppbv have been reported for Baton Rouge, Houston, El Paso, Houston, and Dallas-Fort Worth over the past 30 years. The most dramatic improvements have been achieved in Southern California, where on average the O3 MDA8 has decreased by 2.6 ± 0.2% yr–1 between 1973–2010 (Pollack et al., 2013). Nationwide, a 17% decrease has been reported for 2000–2015, with a regional decrease of 10% for the Southwest in 2000–2015, which includes the state of Colorado (EPA, 2016). Averaging the O3 trend results for DMA sites (#1, 2, 5, 14, 18, 33, 34, 35, 36) yields median 50th/95th summer O3 trends of 0.29 ± 0.41/–0.01 ± 0.34 ppbv yr–1. None of these results are indicative of declining O3. A major finding from these comparisons is that, despite the NOx reductions, O3 changes in Colorado do not mirror the O3 improvements (reductions) noted in the above mentioned literature from other western U.S. cities.
The most robust results (according to the statistical significance tests and number of sites) of the trend analyses are the increases in summer low percentile O3 values, and increases of median O3 in the DMA (Table 3, Figure 7). These changes in the distribution of absolute mixing ratios are paralleled by declining diurnal O3 amplitudes (Table 4, Figure 8). Since nighttime O3 minima are largely determined by O3 loss from titration with NO, the changes in nighttime O3 are indicative of gradually declining NOx concentrations in the urban corridor. Similar, albeit weaker, nighttime O3 changes are observed at the rural Colorado locations, suggesting a declining NOx signature on the regional scale as well. In these rural areas, increasing nighttime O3 levels are likely due to 1. a declining nighttime O3 destruction in air transported to the sites, and 2. a decline in the local nighttime O3 destruction. These indirectly inferred changes in NOx are confirmed by surface NOx monitoring data in the state. All five of the 12 records overall (SM_Figure_8) that are long enough for a trend analysis show declining NOx (SM_Figure_9) at all percentiles, with 11 out of these 15 NOx percentile changes being statistically significant downward trends (SM_Table_4). An overall 26.3 ± 5.4% 2005–2013 reduction in tropospheric NOx has been estimated from satellite observations for the Denver area (Lamsal et al., 2015; Lurmann et al., 2015), with indications that the rate of decline has become smaller during the most recent years of the record. These declines in Colorado NOx are consistent with results from other nationwide studies, building on surface monitoring, remote sensing, emission inventories, and modeling (Cooper et al., 2014; Lamsal et al., 2015; Strode et al., 2015; Lin et al., 2016; Sather and Cavender, 2016).
Changes in VOC and VOC reactivity are more difficult to assess than changes in NOx. Tailpipe emissions, constituting a major to dominant source of VOC in urban air, have been decreasing throughout U.S. cities, including in the DMA (Bishop and Stedman, 2008). Despite the growth of the automobile fleet and miles driven per vehicle, the signature of these declining emissions can be seen in declining urban air VOC (Warneke et al., 2012; Rossabi and Helmig, 2018). In the NCFR, VOC emissions from the O&NG industries are the dominant VOC source within and downwind of O&NG activities (Gilman et al., 2013; Swarthout et al., 2013; Thompson et al., 2014). Several studies have demonstrated increasing atmospheric VOC trends linked to O&NG fugitive emissions from the rapid growth of this industry across the U.S. (Schade and Roest, 2015; Vinciguerra et al., 2015; Helmig et al., 2016). Within Colorado, CDPHE has been conducting VOC monitoring at four locations. While some of these records indicate potentially declining VOC, at this time these records are too short, and/or the sampling has been inconsistent, and data are too variable for obtaining robust trend results.
In Figure 13 we plot available paired median summer O3 amplitudes against the summer median NOx values from the records shown in SM_Figure_8 to investigate the O3-NOx/VOC relationship further. Data markers for WEL and Denver Camp (DCP) are color-coded by the year of observation. There are several dependencies: 1. Lowest NOx and diurnal amplitudes were observed at rural and suburban locations; highest values were measured at WEL and DCP. 2. At sites with lower NOx (0–5 ppbv summer median), the median O3 amplitude scales close to linearly with increasing NOx. This behavior then reverses to a slightly negative relationship between 10–25 ppbv of NOx. 3. Despite DCP having the overall highest NOx, at equivalent NOx, O3 amplitudes at DCP are consistently lower (by ~10 ppbv) in comparison to WEL. 4. The color-coding of the WEL and DCP data shows that while for both sites NOx has been decreasing over the available record, O3 amplitudes have changed very little, possibly increasing slightly at WEL.
4.7. Ozone at Welby
Data in Figure 13 point towards overall increasing diurnal O3 changes at WEL. Given the decreasing rate of nighttime O3 destruction by NO (as reflected in the statistically significant positive 5th percentile O3 trend), these data argue for an increase in O3 production chemistry at WEL. This conclusion is confirmed by the O3 trend analyses: WEL is the only site with (statistically significant) increasing O3 trends at all (5/50/95) percentiles (Table 3), and the only site where O3 diurnal amplitudes have been increasing at all percentiles. This behavior clearly shows that, thus far, there have been no improvements in O3 at WEL despite the achieved statewide reductions in NOx. Conversely, it appears that local O3 production has increased under declining NOx. Similar conclusions were derived from a recent analysis of trends in weekday/weekend differences in O3 and NOx at selected NCFR sites by Abeleira and Farmer (2017). Their study found that “most sites in the NFRMA were NOx-saturated, but are transitioning to, and in one case may already have reached, the peak P(O3) cross-over point between NOx-saturated and NOx-limited regimes”. Our analyses, relying on further site data and different analytical approaches, confirm the first part of their conclusion.
4.8. Ozone and O&NG development
WEL is situated on the northeastern outskirts of the DMA, within 2 miles of I–76, and with other busy roadways a bit further away. The site is also within the southwestern edge of the DJB (Figure 1). A map showing well pad locations surrounding the site is provided in SM_Figure_10; 20 well pads are located within a 10-km distance, and 1445 wells within a 20-km radius. The association of increasing O3 with the proximity to O&NG operations might suggest that emissions from this growing industry have contributed to increases in O3. Atmospheric VOC have been shown to increase along transects from the periphery towards the center of the DJB (Thompson et al., 2014; Helmig et al., 2015; Rossabi et al., 2017), and VOC have been reported at highly elevated concentrations, largely driven by O&NG emission within the DJB and downwind (Gilman et al., 2013; Swarthout et al., 2013; Thompson et al., 2014). Unfortunately, there are no VOC monitoring data available for WEL. The seasonal cycles of the diurnal amplitudes (Figure 9) show a wider summer maximum than at NREL. This may be linked to differences in VOC/NOx ratios at both sites. There is most likely more NOx, causing lower VOC/NOx ratios at NREL, or higher VOC, causing higher VOC/NOx at WEL. Lower VOC/NOx may inhibit O3 production more during the spring/fall shoulder season when there are fewer photochemically productive hours than during mid-summer (at NREL) in comparison to possibly higher VOC/NOx conditions at WEL.
Greeley – Weld County Tower (site #67) is another site within the DJB to further investigate this dependency. The monitoring location is surrounded by intense O&NG development in all directions. While the site, with a summer 95% percentile value of 71 ppbv, and a median diurnal O3 amplitude of 51 ppbv, is ranked among the top ten of the Colorado sites for highest O3 and diurnal production, trend analyses for the O3 higher percentile values and O3 diurnal amplitudes show signs for decreasing local O3 production (Tables 3 and 4). VOC monitoring in Platteville ~25 km to the southwest has shown highly elevated O&NG associated VOC (Thompson et al., 2014; Halliday et al., 2016). There are, however, indications of potentially declining O&NG related VOC concentrations during recent years at Platteville (Pierce, 2017).
Other recent research building on campaign observations has provided observational and modeling evidence that O&NG emissions significantly contribute to summer O3 production within the DJB and NCFR downwind regions (Gilman et al., 2013; Swarthout et al., 2013; McDuffie et al., 2016; Pfister et al., 2017; Cheadle et al., 2017). This association is difficult to prove with the data and tools that were applied here. Unfortunately, the DJB and its periphery are not well covered by the Colorado surface O3 monitoring network, and regrettably, a valuable site in the SW sector of the DJB, i.e. the Boulder Atmospheric Observatory, was decommissioned in 2017. Further, given the lack of parallel O3, VOC, and NOx monitoring, it is impossible to deconvolute the influence of precursor emissions and their changes over time on the contrasting behavior seen in the data from these DJB sites.
5. Summary and conclusions
Ozone behavior in Colorado is rather diverse, both along the horizontal scale and the ~2000 m elevation change from the Eastern Rocky Mountain Plains to the peaks of the Continental Divide. Elevated O3 is prominent at higher elevation sites, and in the NCFR. However, in the NCFR, highest O3 is not recorded within the central DMA, but instead mostly at suburban sites to the north and west of Denver along the eastern foothills of the Colorado Rocky Mountains.
There is high year-to-year variability in O3 in the NCFR which adds to the uncertainty of surface O3 trend results. Ozone trends at considered non-urban sites, as well as at the highest mountain sites, do not show increasing O3 during the observation period. This contradicts the argument that NCFR elevated O3 can (in part) be explained by increasing O3 transport into the state. Analyses presented here underscore that NCFR O3 trends are primarily determined by local/regional emissions and production.
Our analyses for DMA sites do not show the clear O3 decreases at the higher percentiles as seen for the vast majority of urban areas across the U.S., including the southwestern states during the past 1–2 decades. Only five locations (collocated with O3) in the State of Colorado have NOx data records suitable for trend analyses. Declining trends seen in those NOx data, and the clear signature of decreasing O3 amplitudes, are in agreement with remote sensing and modeling results. Together, these records provide solid evidence for a steady decline of NOx in the region. The lack of the higher percentile O3 response to the NOx decline indicates that O3 in the region has not been sensitive to these NOx reductions thus far.
While we were able to consider data from an impressive 80 O3 monitoring sites for this study, there is only one site that provides a long-term surface O3 record from within the DJB, Colorado’s largest O&NG basin. Sites on the southern and western periphery of the DJB are subject to influence by urban development and changes in emission from non-O&NG emission sectors, which complicates assessing the O&NG influence and how its importance is changing over time. Further O3 monitoring within the DJB and at its northern and eastern boundaries would be beneficial for addressing these questions. With the predominant daytime upslope (east to west) air circulation conditions during summer days, those sites could provide data from upwind of the DJB, which, together with the existing chain of sites along the foothills, would allow assessing daytime O3 production as air travels over the DJB and becomes enriched with O&NG emissions. This would largely enhance capabilities for studying the role of O&NG operations in the NCFR O3 production, and the effectiveness of regulations for curbing O&NG O3 precursor emissions.
The sparseness of direct surface NOx observations poses a severe limitation for understanding O3 responses to emission changes and for directing O3 policy decisions. Continuous, high quality, year-round observations of VOC and NOx, co-located with O3 monitoring, are needed for a more comprehensive evaluation of changing influences and regional differences in the Colorado O3 production chemistry. Here, we explored the use of summer diurnal O3 amplitudes as an indirect indicator for site comparisons and for NOx trend analyses, and found this variable to be a sensitive and valuable tool for this research. The lack of response in O3 amplitudes to declining NOx at two DMA sites indicates that O3 daily production dynamics have been relatively non-responsive to decreasing NOx at those locations, which agrees with the interpretation of the O3 trend analyses for the wider NCFR.
Data Accessibility Statement
McClure-Begley, A., Petropavlovskikh, I., Oltmans, S. (2014) NOAA Global Monitoring Surface O3 Network. National Oceanic and Atmospheric Administration, Earth Systems Research Laboratory Global Monitoring Division. Boulder, CO; accessed September 2016; ftp://aftp.cmdl.noaa.gov/data/ozwv/SurfaceOzone/. US Environmental Protection Agency (EPA) Air Quality System (AQS) archive; accessed September 2016; https://aqsdr1.epa.gov/aqsweb/aqstmp/airdata/download_files.html. Dinosaur National Monument (DNM) data were obtained from the U.S. National Park Service; accessed October 2016; https://ard-request.air-resource.com/.
The supplemental files for this article can be found as follows:
- SM_Table_1. Population growth in the Northern Colorado Front Range and La Plata County between 2000–2015. DOI: https://doi.org/10.1525/elementa.300.s1
- SM_Table_2. Fraction of data (in %) for each site and year. DOI: https://doi.org/10.1525/elementa.300.s1
- SM_Table_3. Average number of days per year with the MDA8 exceeding 70 ppbv and the number of years considered. All sites with at least 75% of data for one year during this period are included. DOI: https://doi.org/10.1525/elementa.300.s1
- SM_Table_4. Linear regression results for the trend analysis of the summer NOx of all sites with at least 10 years and 80% of data for a given summer, categorized by the 5th, 50th, and 95th percentile levels. Statistically significant trend results are highlighted in bold font. DOI: https://doi.org/10.1525/elementa.300.s1
- SM_Figure_1. Ozone time series results for the full 1-hour record of all sites considered in this study with yearly statistical box-whisker plot analysis for years with more than 80% of data coverage shown to the right of the time series. Sites are sorted according to the order of Table 1 in the article. DOI: https://doi.org/10.1525/elementa.300.s1
- SM_Figure_2. Box-whisker plot analyses of the hourly summer ozone data for every year. Shown are all sites that had records with more than 10 years of data. Straight linear regression fits trough the 5th, 50th, and 95th percentile of the data for each year show the trend behaviour, with slope results in the legends in ppbv yr–1. DOI: https://doi.org/10.1525/elementa.300.s1
- SM_Figure_3. Ozone Design Value for each year for all sites with at least 10 years of data. The 70 ppbv ozone NAAQS is visualized by a black line. The linear regression fit with the 95% confidence bounds is shown by the red line. The same analysis for the 4th MDA8 is shown in the series of graphs underneath. Trend analyses results are shown in manuscript Table 3. DOI: https://doi.org/10.1525/elementa.300.s1
- SM_Figure_4. Amplitude in daily ozone for the full record and for all sites considered in this study. DOI: https://doi.org/10.1525/elementa.300.s1
- SM_Figure_5. Statistical box-whisker plot analyses of the monthly change of the ozone diurnal amplitude for all sites. Shown are all sites that have at least 10 years of data with 80% of data coverage for a given year. DOI: https://doi.org/10.1525/elementa.300.s1
- SM_Figure_6. Statistical box-whisker plot analyses of the diurnal ozone amplitude during the summer for sites with more than 10 years of data. Straight linear regression fits through the 5th, 50th and 95th percentile of the data for each year show the trend behaviour. Regression analysis slope results (in ppbv yr–1) are given in the legends. DOI: https://doi.org/10.1525/elementa.300.s1
- SM_Figure_7. Geographical distribution of the 2000-2015 average number of days per year with the MDA8 exceeding 70 ppbv. All sites with at least 75% of data for one year during this period are included. Please note that the number of years going into the calculation may vary from 1–16. DOI: https://doi.org/10.1525/elementa.300.s1
- SM_Figure_8. NOx time series results for the full 1-hour resolution record of those sites that had both NOx and ozone data available. DOI: https://doi.org/10.1525/elementa.300.s1
- SM_Figure_9. Box-whisker plot analyses of the hourly summer NOx data. Shown are all sites that had records with more than 10 years of data. Straight linear regression fits trough the 5th, 50th, and 95th percentile of the data for each year show the trend behaviour, with slope results in the legends in ppbv yr–1. DOI: https://doi.org/10.1525/elementa.300.s1
- SM_Figure_10. Location of the Welby ozone monitoring site indicated by the red square, with oil and natural gas wells within a 10 km and 20 km radius indicated by blue dots, and further wells outside that radius with red markers. The total well count within the drawn radius is indicated in the lower right corner. DOI: https://doi.org/10.1525/elementa.300.s1
- SM_Text_1. Examination of the ozone data for the sites Ignacio and Bondad. DOI: https://doi.org/10.1525/elementa.300.s1