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Spatial and Temporal Patterns of Ground-level Ozone within North-central Pennsylvania Forests
Eric R. Britzke, Price Sewell, Matthew G. Hohmann, Ryan Smith, and Scott R. Darling

Northeastern Naturalist, Volume 17, Issue 2 (2010): 247–260

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2010 NORTHEASTERN NATURALIST 17(2):247–260 Spatial and Temporal Patterns of Ground-level Ozone within North-central Pennsylvania Forests Teodora Orendovici-Best1, John M. Skelly2, and Donald D. Davis2,* Abstract - Ozone is the most important air pollutant impacting forests of the northeastern United States, including Pennsylvania. Spatial and temporal patterns of ambient, ground-level ozone were studied during 2002–2004 within north-central Pennsylvania hardwood forests. Ground-level ozone was monitored at 20 remote, forested sites using passive (non-electric) ozone samplers. Ten monitoring sites were established at (relatively) low-elevation (<350 m) locations in valleys and ten sites were located at (relatively) high-elevation locations (>550 m) on mountains. Realtime electronic ozone analyzers were co-located with the passive samplers at three sites that had access to electricity. Spatial maps were developed illustrating gradients of ozone across the region. During all 3 years, ambient ozone levels were positively correlated with elevation (2002, ρ = 0.813, P < 0.001; 2003, ρ = 0.877, P < 0.001; and 2004, ρ = 0.518, P < 0.019). Native forests at higher, mountainous sites may be at risk from higher ambient levels of ozone, despite their perceived “pristine” location. Future field surveys, designed to evaluate ozone injury to native vegetation, will use spatial maps developed from this study. Introduction Vertical gradients of ozone have been reported within the mountains of North Carolina (Berry 1964), Virginia (Winner et al. 1989), and parts of central Pennsylvania (Yuska et al. 2003). Levels of ambient ozone have been described for forested parts of north-central Pennsylvania in general terms (Comrie 1994, Simini et al. 1992, Skelly et al. 2001) and as related to elevation (Orendovici-Best et al. 2008). However, these studies did not report spatial ozone patterns across the region, nor did they report the precision and accuracy of passive ozone samplers. Accuracy and precision data are critical when reporting ambient ozone levels at remote forested sites, and when constructing spatial maps based on ozone data from passive samplers. Accurate maps, illustrating gradients of ambient ground-level ozone concentrations, are very useful when designing field surveys to evaluate ozone injury on native forest vegetation in north-central Pennsylvania, a goal of our ozone-effects program at The Pennsylvania State University. Forests across the region contain many ozone-sensitive tree species, including Fraxinus americana L. (White Ash), Fraxinus pennsylvanica Marsh. (Green Ash), Liriodendron tulipifera L. (Yellow-poplar), Pinus 1School of Forest Resources, Pennsylvania State University, University Park, PA 16802. 2Department of Plant Pathology and Penn State Institutes of Energy and the Environment, Pennsylvania State University, University Park, PA 16802. *Corresponding author - ddd2@psu.edu. 248 Northeastern Naturalist Vol. 17, No. 2 strobus L. (Eastern White Pine), Prunus pensylvanica L. (Pin Cherry), and Prunus serotina Ehrh. (Black Cherry) (US DOI 2003). On-going surveys of forest vegetation by the US Forest Service Ozone Biomonitoring Program (http://nrs.fs.fed.us/fia/topics/ozone/default.asp) demonstrate that ozone injury occurs on native vegetation in Pennsylvania and throughout the Northeast, most notably in the northern hardwood forest types that include Black Cherry (Coulston et al. 2003). Further, we reported foliar symptoms on artificial plantings of ozone-sensitive hybrid poplar ramets and ozone-sensitive selections of Black Cherry seedlings within the region (Orendovici-Best et al. 2008), confirming the potential for ozone injury to occur on native forest vegetation. However, to improve the design of future surveys, and enhance the interpretation of on-going regional surveys, spatial and temporal patterns of ambient ground-level concentrations of ozone need to be determined. The objectives of this study were to 1) develop spatial maps to graphically illustrate patterns of ozone concentrations across the forested region of north-central Pennsylvania, and 2) determine precision and accuracy of passive ozone monitors under the environmental conditions of the region. Methods Research area and ozone monitoring The spatial distribution of tropospheric, ground-level ozone was investigated during the summers of 2002–2004 in the forested and sparsely populated areas of north-central Pennsylvania using closely paired study monitoring sites (Orendovici 2005). Ambient levels of ozone were studied by selecting 10 sites at relatively low elevations (“valley,” <350 m) and 10 sites at relatively high elevations (“mountain,” >550 m). Each low site was within 5–20 km of a high site, resulting in 10 pairs of matched monitoring sites (Table 1). The 20 sites were all located within well-exposed clearings in forests. Passive ozone samplers do not require electricity and can be used for monitoring ozone in remote forested areas (Bytnerowicz et al. 2002, Cox 2003). Ogawa passive ozone samplers (Ogawa 1998; Pompano Beach, fl) were placed at 1.5–2.0 m on poles at each of the 20 sites. Each sampler was placed under a plastic cap to provide protection from wind and rain, and contained two nitrite-saturated filters that were kept frozen in an insulated ice chest until placement. Samplers were replaced weekly at approximately the same time of day. Filters were returned to the laboratory and analyzed using ion chromatography to determine conversion of nitrite (NO2) to nitrate (NO3) for 1-week periods (Orendovici 2005). Real-time, electronic ozone analyzers were co-located with passive ozone samplers at three of the monitoring sites that had access to electricity (Table 1). TECO Model 49 (Hopkinton, MA) ozone analyzers were operated in 2002 and 2003, whereas an API Model 400A (San Diego, CA) was used in 2004. Ozone levels (ppb) were monitored at 5-min intervals and recorded 2010 T. Orendovici-Best, J.M. Skelly, and D.D. Davis 249 as 1-hr averages using an Odessa Engineering data-logger model DSM3260 (Austin, TX). Sensors were calibrated in early April of each year, and each analyzer performed a 2-point calibration check nightly. Calibration and quality control measures followed the standards set by the Pennsylvania Department of Environmental Protection, Bureau of Air Quality, Harrisburg, PA. Ozone monitoring was conducted from 13 June to 9 September 2002 (12 weeks), 9 June to 9 September 2003 (13 weeks), and 23 May to 31 August 2004 (14 weeks). At the co-located sites, temperature (oC), relative humidity (%), precipitation (mm), and wind speed (ms-1) were recorded with Campbell meteorological data systems (Campbell Scientific Inc., Logan, UT). Resulting data were used to evaluate the influence of meteorological factors on the precision and accuracy of the passive samplers. Data analyses The precision of the passive ozone samplers was determined by deploying duplicate samplers at three sites (Table 1) where a 1-week average ozone concentration was calculated. Sampler precision was determined by calculating the percentage difference between replicates (relative error * 100). Relative error is defined as the ratio of the absolute value of the difference of the replicates samplers and their average. The accuracy of the passive monitors was determined by comparing values from the passive monitors with those obtained from the (more accurate) co-located electronic ozone monitors. Table 1. Location of paired monitoring sites equipped with Ogawa passive ozone samplers in north-central Pennsylvania. Elevation Pair distance Site name County Latitude Longitude (m) Pair (Km) CURWENSVILLE CLEARFIELD 40 56 54 78 32 29 320 1 LUTHERSBURG CLEARFIELD 41 04 15 78 42 24 540 1 19.45 PENFIELD CLEARFIELD 41 13 05 78 35 21 390 2 MOSHANON SFA CLEARFIELD 41 07 02 78 32 01 660 2 11.67 MEDIX RUN ELK 41 17 35 78 24 07 300 3 PIPER CLEARFIELD 41 13 01 78 09 58 660 3 20.26 HYNER PARK CLINTON 41 21 49 77 38 14 285 4 PETE’S RUN CLINTON 41 15 10 77 45 50 690 4 16.46 CEDAR RUN LYCOMING 41 30 44 77 27 42 250 5 GAGE ROAD LYCOMING 41 24 09 77 32 37 570 5 14.24 PINE LAKE LYCOMING 41 22 20 77 21 47 250 6 TIADAGHTON A LYCOMING 41 20 05 77 27 35 550 6 9.07 ROTE CLINTON 41 05 24 77 28 30 250 7 PINE ROAD CLINTON 41 04 21 77 19 05 550 7 13.28 CANTON TIOGA 41 40 14 76 50 12 350 8 GLEASONA TIOGA 41 39 14 76 56 37 700 8 9.06 MT. PISGAH ST BRADFORD 41 48 39 76 40 27 350 9 MT. PISGAH CO BRADFORD 41 49 03 76 42 58 680 9 4.55 OGDONIA SULLIVAN 41 25 05 76 42 28 300 10 WORLD'S END SULLIVAN 41 26 03 76 36 43 600 10 8.18 ASite where duplicate passive ozone samplers were co-located with real-time ozone analyzers, and a meteorological station. All other sites contain only passive ozone samplers. 250 Northeastern Naturalist Vol. 17, No. 2 Weekly ozone averages were used to compute seasonal ozone averages for each site. ANOVA was used to test for significant differences (P-value < 0.05) of seasonal ozone concentrations among sites and years. Seasonal averages were also used to compare ozone concentrations at different elevations and to reveal spatial patterns. Regression analysis was used to study the relationship between seasonal ozone concentrations and elevation. Spatial maps illustrating patterns of ozone distributions were generated using spatial analysis (Kaluzny et al. 1998) of the data within the monitored area. Intensity maps of ozone distributions were generated using an interpolation algorithm that estimated spatial ozone distribution. The algorithm was selected based on positive variance and the lowest errors criteria (Orendovici 2005). Data were analyzed using the Statistical Analysis System (SAS, Inc. 2000), MINITAB Release 14 (Minitab, Inc. 2003), and S-plus (S-plus 2003). Results Sampler precision and accuracy During the 2002 season, we did not employ duplicate samplers; therefore the precision and accuracy of the passive samplers was not studied. In 2003, the precision of the Ogawa passive samplers was between 0 and 20%, and the range of the differences (between the two replicate samplers over oneweek period) was (-5.25; 5.73 ppb), with one outlying value of 14.64 ppb. The precision of the Ogawa passive samplers in 2004 was between 0 and 20%, and the range of the differences was (-5.42; 4.77 ppb), with two outlying values of 15.42 and 10.34 ppb. Accuracy, as measured by the correlation coefficient between weekly average of ozone measured via passive samplers vs. electronically monitored ozone, was 0.853 (P < 0.001) in 2002, 0.911 (P < 0.001) in 2003, and 0.064 (P = 0.561) in 2004. When data from the Gleason site was removed in 2004, the accuracy increased to 0.712 (P < 0.001); therefore, passive data from that site was not used in 2004. These results revealed that mean ozone values from the passive samplers generally corresponded to the data from real-time electronic monitors. Ozone and elevation There were significant positive correlations between seasonal ozone concentrations and elevation in 2002 (ρ = 0.813, P < 0.001), 2003 (ρ = 0.877, P < 0.001), and 2004 (ρ = 0.518, P < 0.019), revealing that ozone concentration increased with elevation. The differences in ozone concentrations between low- and high-elevation sites were greater in 2002 and 2003 than in 2004 (Fig. 1). There were greater differences in seasonal ozone concentrations between paired sites when the high-elevation site was >600 m altitude. In 2004, the differences in seasonal ozone between sites were less than the previous 2 years, and the differences were not always significant. During all 2010 T. Orendovici-Best, J.M. Skelly, and D.D. Davis 251 Figure 1. Comparison of seasonal ozone between pair of sites (high vs. low elevation) during 2002–2004. H = high elevation and L = low elevation site; data represents means ± SE. 252 Northeastern Naturalist Vol. 17, No. 2 3 years of the investigation, the highest ozone concentrations were found at Mt. Pisgah County Park and Pete’s Run, two of the highest elevation sites. In contrast, the lowest ozone concentrations were found at Hyner Park, one of the lowest elevation sites (Table 1). Elevation was a significant factor in determining ozone concentrations, but meteorological conditions and hourly mean patterns influenced weekly ozone levels as well. Ozone values from the three monitoring sites were positively correlated with temperatures and wind speed values in 2002 and 2003, but negatively correlated in 2004 (Table 2). The correlation between ozone level and % relative humidity was negative for all 3 years. Table 2. Correlation coefficients between ambient ozone concentrations, temperature, relative humidity, and wind speed recorded at the air quality monitoring sites in north-central Pennsylvania during 2002–2004. Year Variables Correlation coefficient P-value 2002 O3, Temperature 0.738 <0.001 O3, Relative humidity -0.582 <0.001 O3, Wind speed 0.342 <0.001 2003 O3, Temperature 0.614 <0.001 O3, Relative humidity -0.575 <0.001 O3, Wind speed 0.478 <0.001 2004 O3, Temperature -0.034 0.003 O3, Relative humidity -0.101 <0.001 O3, Wind speed -0.070 <0.001 Figure 2. Hourly ozone behavior from 17 July 2002 to 23 July 2002 at the three sites equipped with real-time ozone monitors. 2010 T. Orendovici-Best, J.M. Skelly, and D.D. Davis 253 Hourly patterns of ozone The real-time electronic ozone monitors co-located with passive samplers monitors at three sites provided the means to not only study the accuracy of the passive sampler devices, but also to study daily ozone patterns. Diurnal distribution of ozone at the Tiadaghton and Moshannon monitoring sites expressed the typical ozone fluctuation, having daily maxima during early afternoon hours and daily minima at night. However, a significant drop did not follow the maximum daily ozone values at the Gleason site at night in 2002 (Fig. 2) and 2003 (data not shown). Spatial and seasonal variation Seasonal means of ozone concentrations were compared to determine significant differences among monitoring sites (Table 3). When two-way ANOVA was used, it revealed that both year of study and location were Table 3 (continued on next page). Results of ANOVA test for significant differences in ozone concentrations measured with Ogawa passive samplers in north-central Pennsylvania during 2002–2004. Seasonal ozone Year Site Elevation (m) mean (ppb) Std. Tukey groupingA 2002 GLEASON 700 54.08 10.35 A MT. PISGAH CO 680 53.38 10.87 A PETE’S RUN 690 53.04 8.19 A MOSHANNON 660 46.39 8.35 B A WORLD’S END 600 46.08 10.23 B A PIPER 660 44.11 4.04 B A C CANTON 350 40.25 8.19 B D C MT. PISGAH ST 350 40.10 7.13 B D C TIADAGHTON 550 37.10 8.51 B E D C PINE ROAD 550 36.46 5.04 B E D C LUTHERSBURG 540 35.77 5.83 B E D C CURWENSVILLE 320 34.89 4.85 E D C GAGE ROAD 570 34.01 9.10 E D C PINE LAKE 250 33.91 4.99 E D C ROTE 250 32.31 5.07 E D CEDAR RUN 250 32.14 5.30 E D PENFIELD 390 30.98 4.78 E D MEDIX RUN 300 30.38 3.90 E D OGDONIA 300 28.46 7.69 E HYNER PARK 285 26.77 5.54 E 2003 PETE’S RUN 690 47.73 11.50 A MT. PISGAH CO 680 47.22 8.66 B A GLEASON 700 45.41 7.37 B A C MOSHANNON 660 40.12 7.29 B D A C WORLD’S END 600 37.61 8.46 B D E C PIPER 660 37.18 8.03 B D E C TIADAGHTON 550 32.76 6.00 F D E G MT. PISGAH ST 350 30.96 8.45 H F D E G LUTHERSBURG 540 30.35 5.22 H F E G PINE ROAD 550 29.06 7.09 H F E G GAGE ROAD 570 28.96 5.76 H F E G CANTON 350 28.54 7.16 H F E G 254 Northeastern Naturalist Vol. 17, No. 2 significant sources of variance, and that there was a year-by-location interaction (all P-values < 0.001). In 2004, ozone concentrations decreased at high-elevation monitoring sites and increased at low-elevation sites; therefore, there was not a significant difference between ozone means in 2003 and 2004 (Fig. 1). One-way ANOVA Tukey’s test showed that seasonal ozone concentrations were different in 2002 (μ = 38.479, σ = 10.704), as compared to 2003 (μ = 32.858, σ = 10.535) or 2004 (μ = 33.142, σ = 5.192), and that in 2002 and 2003, ozone concentrations at sites >600 m were grouped in similar classes (A and B), with none of the sites <600 m being in class A; however, in 2004, ozone concentrations grouped differently and some of the sites <500 m were in class A of ozone values (Table 3). Maps describing seasonal averages for each year were constructed to evaluate spatial and temporal patterns of ozone (Fig. 3a, b, c). Weekly ozone distribution maps (Orendovici 2005) showed similar weekly and seasonal trends in 2002 and 2003, with little spatial variability of ozone distribution from week to week. Temporal variation was minimal during 2002 and 2003. The highest temporal variability of ozone distribution was observed in 2004, Table 3, continued from previous page. Seasonal ozone Year Site Elevation (m) mean (ppb) Std. Tukey groupingA CURWENSVILLE 320 27.88 6.94 H F G PENFIELD 390 27.78 5.91 H F G ROTE 250 26.58 5.86 H G OGDONIA 300 25.14 7.76 H G PINE LAKE 250 24.82 4.90 H G CEDAR RUN 250 23.76 6.02 H G MEDIX RUN 300 23.29 5.02 H G HYNER PARK 285 22.30 7.05 H 2004 MT. PISGAH CO 680 38.76 4.11 A WORLD’S END 600 37.95 5.40 A PETE’S RUN 690 37.79 3.19 A PIPER 660 36.98 6.85 B A MOSHANNON 660 36.39 1.62 B A C CURWENSVILLE 320 34.84 4.93 B D A C PINE ROAD 550 34.68 4.95 B D A C CANTON 350 34.57 4.52 B D A C GAGE ROAD 570 33.91 4.95 B D A C LUTHERSBURG 540 33.71 4.71 B D A C MT. PISGAH ST 350 32.34 3.48 B D C OGDONIA 300 32.10 4.27 B D C PENFIELD 390 31.99 4.33 B D C TIADAGHTON 550 31.59 2.17 B D E C ROTE 250 31.41 4.64 D E C CEDAR RUN 250 31.01 4.23 D E PINE LAKE 250 30.82 4.03 D E MEDIX RUN 300 30.60 4.87 D E HYNER PARK 285 29.90 4.54 E GLEASON 700 26.46 2.76 E AMeans followed the same letter are not statistically different at the 0.05 level of significance. 2010 T. Orendovici-Best, J.M. Skelly, and D.D. Davis 255 Figure 3. Maps of estimated seasonal ozone concentration in northcentral Pennsylvania for 2002 (a), 2003 (b), and 2004 (c). 256 Northeastern Naturalist Vol. 17, No. 2 when high-elevation monitoring sites experienced higher ozone variability, whereas other locations showed less variation in ozone concentration (Orendovici 2005). In 2002 and 2003, there was a consistent trend of lower ozone concentrations in the central part of the study region. Even during periods of overall high ozone concentrations, the central region exhibited low ozone levels. In 2003, average ozone values were significantly lower than in 2002, but the spatial trend was consistent with that observed in 2002. That is, areas with higher ozone concentrations surrounded the central part of the region that had lower ozone concentrations. Seasonal ozone averages were not significantly different between 2003 and 2004, but the spatial patterns were different. In 2004, ozone concentrations were more uniformly distributed throughout the entire region. Nevertheless, the central area exhibited lower ozone concentrations regardless of season (Fig. 3c). Discussion Passive samplers for quantification of cumulative ozone exposures are inexpensive, easy to deploy, reliable, and of necessity in rural forested areas without electricity. Generally, passive samplers are not affected by temperature, humidity, or interference with other co-pollutants (Koutrakis et al. 1993). Nevertheless, there are limitations and uncertainties that need consideration. Interferences from other oxidants besides ozone may occasionally cause overestimation or underestimation of the cumulative ozone concentration measured with passive samplers (Campbell et al. 1994). Turbulent transfer caused by wind incursion into the open-ended tube sampler may result in overestimation of the gas concentrations by as much as 30% (Campbell et al. 1994). It is recommended that some electronic monitors be co-located with passive monitors to obtain estimates of accuracy and reduction of uncertainties (Cox 2003). Our 3-year ozone monitoring investigation revealed that passive samplers are useful in remote areas, but accuracy of passive samplers is highly dependent upon wind velocity, ambient temperatures, and relative humidity. During years of low temperature and high winds (i.e., 2004), the accuracy of passive samplers is lower. Care in placement and protection of the samplers did not always minimize the problem, and diffusion barriers did not always provide protection against changing wind turbulence. Also, since meteorological data are often not available in rural areas, it may not be possible to use wind data to adjust passive sampler values. During all 3 years of study, there was a significant positive correlation between elevation and seasonal ozone. In a typical year, monitoring sites at higher elevations exhibited higher ozone values. Yuska et al. (2003) also reported greater ozone levels at higher elevations in central Pennsylvania, but did not utilize paired sites. Our results with paired monitoring sites indicate that the difference between ozone at low/high sites is due to elevation (Fig. 1). Sites >600 m elevation generally exhibited greater ozone 2010 T. Orendovici-Best, J.M. Skelly, and D.D. Davis 257 concentrations than valleys. For sites <600 m, the differences in ozone concentrations between mountain and valley were not significant. In 2004, there was an exception from the higher elevation higher ozone pattern when two sites at lower elevations (Curwensville and Canton) exhibited greater ozone concentrations than their paired higher elevation sites (Table 3). The hourly data from the real-time monitors was used to study the ozone and elevation relationship. The diurnal distribution of ozone in the study area followed the typical daily pattern, exemplified by data from the Tiadaghton and Moshannon monitoring sites, wherein maximum concentrations occurred during early afternoon and minimum concentrations occurred at night (Fig. 2). However, this diurnal pattern was not observed at the Gleason monitoring site (Fig. 2), where ozone levels remained high at night. Differences in average ozone concentrations among sites may be partially due to differences in ozone levels between day and night, but as related to elevation. The Tiadaghton monitoring site, located at 550 m, exhibited lower ozone even when surrounding areas exhibited high levels of ozone. Moshannon, located at 660 m, showed high ozone values during daytime, but dropped significantly at night. Gleason, located at 700 m, showed little day-to-night variation in ozone concentrations, and thus exhibited higher daily averages. Apparently, 600 m in elevation within the study region separates higher ozone exposure areas from lower ozone exposure areas. Lefohn et al. (1992) described the relationship between ozone and elevation as being dependent upon time of day. In our study, daily minimum and maximum concentrations were dependent upon site, elevation, and meteorological conditions. When meteorological conditions were conducive to major ozone episodes, the difference in ozone concentrations between lower and higher elevations was likely imposed by the difference between day and night ozone values. During the day, ozone concentrations were quite similar at sites of varying elevation. However, due to vertical mixing and depositions at night, lower elevation sites exhibited lower average ozone levels. There have been reports of sometimes significant nocturnal leaf conductance resulting in nocturnal ozone uptake, which might be more harmful to plants than diurnal ozone uptake (Emberson et al. 2000, Matyssek et al. 1993, Musselman and Minnick 2000). Further study is needed to determine if native vegetation is subject to a greater risk of injury from high night ozone levels at higher elevation sites in Pennsylvania. Intensity maps (Fig. 3) of ozone distribution over north-central Pennsylvania revealed a persistent pattern of low ozone in the central part of the region, surrounded by higher ozone concentrations. This pattern was also reported by Jagodzinski (2000), Skelly et al. (1994), and Simini et al. (1992), but never explained. Simini et al. (1992) reported a west-to-east decreasing gradient of ozone concentrations across north-central Pennsylvania. However, their easternmost monitoring site was located at Tiadaghton. In our study, we monitored ozone farther east of Tiadaghton and observed that ozone concentrations were 258 Northeastern Naturalist Vol. 17, No. 2 actually increasing with increasing elevation. Skelly et al. (2001) suggested that the pattern of lower ozone concentrations in the north-central region of Pennsylvania was likely related to regional air masses that originate in the northwest part of the state (Great Lakes), usually characterized by low ozone concentrations. However, our study revealed that monitoring sites exhibiting the greatest ozone concentrations in that area were all >600 m, and had signifi- cantly greater ozone levels than sites <600 m elevation (Table 3). Prior to this study, lower ozone concentrations in the central area of north-central Pennsylvania had not been related to topography. This study resulted in the production of spatial maps that illustrate patterns of ground-level ambient ozone within forested areas of north-central Pennsylvania. We also described the relationship between elevation and ambient ozone concentrations, and confirmed that passive ozone samplers were useful devices to monitor ozone within the environmental constraints of forested north-central Pennsylvania. These results, along with those of Orendovici et al. (2008), form a solid platform from which to launch impact studies on ozone-sensitive tree species, including Eastern White Pine, Green Ash, Pin Cherry, Black Cherry, White Ash, and Yellow-poplar (US DOI 2003) within the high-risk (i.e., high-elevation, high-ozone) areas delineated by this study. Acknowledgments The authors thank the Pennsylvania Department of Environmental Protection, Bureau of Air Quality for the main financial support for this study. Allegheny Energy Supply of Greensburg, PA and Reliant Energy of Johnstown, PA also supported this project. We wish to thank the Pennsylvania Bureau of Forestry, the Tiadaghton Sportsman’s Club, The Mountain Run Hunt Club, and many other local landowners for allowing the placement of the PA-DEP buildings, electrical supply lines, and the passive samplers on their properties, and to Penn State Institutes for Energy and the Environment for the laboratory analyses. The authors gratefully acknowledge technical assistance from J. 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