Impact of atmospheric boundary layer depth variability and wind reversal on the diurnal variability of aerosol concentration at a valley site

Ozone modelling and mapping for risk assessment: An overview of different approaches for human and ecosystems health

Tropospheric ozone (O₃) is one of the most concernedair pollutants dueto its widespread impacts on land vegetated ecosystems and human health. Ozone is also the third greenhouse gas for radiative forcing. Consequently, it should be carefully and continuously monitored to estimate its potential adverse impacts especially inthose regions where concentrations are high. Continuous large-scale O₃ concentrations measurement is crucial but may be unfeasible because of economic and practical limitations; therefore, quantifying the real impact of O₃over large areas is currently an open challenge. Thus, one of the final objectives of O₃ modelling is to reproduce maps of continuous concentrations (both spatially and temporally) and risk assessment for human and ecosystem health. We here reviewedthe most relevant approaches used for O₃ modelling and mapping starting from the simplest geo-statistical approaches andincreasing in complexity up to simulations embedded into the global/regional circulation models and pro and cons of each mode are highlighted. The analysis showed that a simpler approach (mostly statistical models) is suitable for mappingO₃concentrationsat the local scale, where enough O₃concentration data are available. The associated error in mapping can be reduced by using more complex methodologies, based on co-variables. The models available at the regional or global level are used depending on the needed resolution and the domain where they are applied to. Increasing the resolution corresponds to an increase in the prediction but only up to a certain limit. However, with any approach, the ensemble models should be preferred.

Unexpected rise of atmospheric secondary aerosols from biomass burning during the COVID-19 lockdown period in Hangzhou, China

After the global outbreak of COVID-19, the Chinese government took many measures to control the spread of the virus. The measures led to a reduction in anthropogenic emissions nationwide. Data from a single particle aerosol mass spectrometer in an eastern Chinese megacity (Hangzhou) before, during, and after the COVID-19 lockdown (5 January to February 29, 2020) was used to understand the effect lockdown had on atmospheric particles. The collected single particle mass spectra were clustered into eight categories. Before the lockdown, the proportions of particles ranked in order of: EC (57.9%) < K-SN (13.6%) < Fe-rich (10.2%) < ECOC (6.7%) < K-Na (6.6%) < OC (3.4%) < K-Pb (1.0%) < K-Al (0.7%). During the lockdown period, the EC and Fe-rich particles decreased by 42.8% and 93.2% compared to before lockdown due to reduced vehicle exhaust and industrial activity. By contrast, the K-SN and K-Na particles containing biomass burning tracers increased by 155.2% and 45.2% during the same time, respectively. During the lockdown, the proportions of particles ranked in order of: K-SN (39.7%) < EC (38.1%) < K-Na (11.0%) < ECOC (7.7%) < OC (1.2%) < K-Pb (0.9%) < Fe-rich (0.8%) < K-Al (0.6%). Back trajectory analysis indicated that both inland (Anhui and Shandong provinces) and marine transported air masses may have contributed to the increase in K-SN and K-Na particles during the lockdown, and that increased number of fugitive combustion points (i.e., household fuel, biomass combustion) was a contributing factor. Therefore, the results imply that regional synergistic control measures on fugitive combustion emissions are needed to ensure good air quality.

Improving Air Quality Standards in Europe: Comparative Analysis of Regional Differences, with a Focus on Northern Italy

The study reports a consistent comparison of emission inventories, concentration trends, and PM source apportionment in different European regions and, mostly, a thorough investigation of meteorological parameters influencing atmospheric pollutants’ dispersion. The study focuses on the reasons why Northern Italy still has difficulties complying with EU air quality standards for PM10 and NO2, despite strong emission reductions. The study demonstrates that, in the colder seasons, wind speed, PBL height, and atmospheric pressure in the Po basin are three to five times less efficient at diluting and dispersing pollutants than those occurring in regions north of the Alps. Since air quality standards aim at countering health impacts, it is advisable to consider atmospheric particulate toxicity in addition to PM10/PM2.5 mass concentration as a limit value. A discussion is reported about PM toxicity factors depending on source-specific aerosols and PM composition. We obtained PM toxicity factors that can vary by 10 times (according to carbonaceous content) across Europe, suggesting that, even at the same mass concentration, the effects of PM10/PM2.5 on human health are significantly variable. Modern PM source apportionment and reliable toxicity and epidemiological analyses represent the correct tools to build a new consistent health metric for ambient PM.

Particulate pollution over an urban Himalayan site: Temporal variability, impact of meteorology and potential source regions

Five-year (2013-2017) particulate matter (PM) data observed at an urban site, Srinagar, Kashmir Himalaya, India was used to examine the temporal variability, meteorological impacts and potential source regions of PM. The daily mean PM₁₀ and PM_2.5 concentration was 135 ± 112 μg/m³ and 87 ± 93 μg/m³ respectively with significant intra- and inter-daily variation. The annual PM₁₀ and PM_2.5 concentration was 2.0-3.2 and 1.7-2.8 times higher than the annual Indian National Ambient Air Quality Standards (PM₁₀ = 60 μg/m³ and PM_2.5 = 40 μg/m³). PM concentration shows a bimodal diurnal pattern with morning and evening peaks, which coincide with the increased anthropogenic activity and shallow planetary boundary layer (PBL). The combined effect of the low temperature, low wind speed, shallow and stable PBL and geomorphic setup of Kashmir valley leads to the accumulation of particulate pollution during autumn and winter and the converse meteorological conditions leads to dispersion, dilution and deposition during spring and summer. High precipitation rate (>15 mm/day) removes the coarse particles (PM₁₀) more efficiently than fine particles (PM_2.5), while as the moderate to high humid conditions (55-95%) leads to the accumulation and growth of more PM. It was observed that ~80% of the air masses arriving at the site during spring, autumn and winter are westerlies. Source contribution analysis revealed that highly potential source regions of PM at the site are neighboring Pakistan, Afghanistan, parts of Iran and Trans-Gangetic Plains, which could contribute high concentration of the PM₁₀ (>250 μg/m³) and PM_2.5 (>150 μg/m³) during autumn and winter. The high PM load observed at the site during autumn and winter, with major contribution from the anthropogenic source emissions like biomass and coal burning, fossil fuel combustion and suspension of road dust, is aggravated by the geomorphic and meteorological setup of the Kashmir valley.

Evolution of Aerosols in the Atmospheric Boundary Layer and Elevated Layers during a Severe, Persistent Haze Episode in a Central China Megacity

Aerosol vertical profiling is crucial to understand the formation mechanism and evolution processes of haze, which have not yet been comprehensively clarified. In this study, we investigated a severe, persistent haze event in Wuhan (30.5° N, 114.4° E), China during 5–18 January 2013 by the use of a polarization lidar, a Cimel sun photometer, meteorological datasets, and the hybrid single-particle Lagrangian integrated trajectory (HYSPLIT) model, focusing on the time–height evolution of aerosols in both the atmospheric boundary layer (ABL) and elevated layers. During the haze period, the integrated particle depolarization ratio was 0.05 ± 0.02, and the fine mode fraction reached 0.91 ± 0.03, indicating haze particles were rather spherical and predominately submicron, that is, of anthropogenic nature. Compared with the clear period, columnar aerosol optical depth at 500 nm tripled to 1.32 ± 0.31, and the strongest enhancement in aerosol concentration occurred from near the ground to an altitude of 1.2 km during the haze period. The daytime evolution of aerosol vertical distribution in the ABL exhibited a distinct pattern under haze weather. Abundant particles accumulated below 0.5 km in the morning hours due to stable meteorological conditions, including a strong surface-based inversion (4.4–8.1 °C), late development (from 1000–1100 LT) of the convective boundary layer, and weak wind (<4 m∙s−1) in the lowermost troposphere. In the afternoon, improved ventilation delivered an overall reduction in boundary layer aerosols but was insufficient to eliminate haze. Particularly, the morning residual layer had an optical depth of 0.29–0.56. It influenced air quality indirectly by weakening convective activities in the morning and directly through the fumigation process around noon, suggesting it may be an important element in aerosol–ABL interactions during consecutive days with haze. Our lidar also captured the presence of the elevated aerosol layers (EALs) embodying regional/long-range transport. Most of the EALs were observed to subside to <1.2 km and exacerbate the pollution level. Backward trajectory analysis and lidar data revealed the EALs originated from the transport of anthropogenic pollutants from the Sichuan Basin, China, and of dust from the deserts in the northwest. They were estimated to contribute ~19% of columnar aerosol-loading, pointing to a non-negligible role of transport during the intense pollution episode. The results could benefit the complete understanding of aerosol–ABL interactions under haze weather and air quality forecasting and control in Wuhan.

Vertical Profiles of Atmospheric Species Concentrations and Nighttime Boundary Layer Structure in the Dry Season over an Urban Environment in Central Amazon Collected by an Unmanned Aerial Vehicle

Nighttime vertical profiles of ozone, PM2.5 and PM10 particulate matter, carbon monoxide, temperature, and humidity were collected by a copter-type unmanned aerial vehicle (UAV) over the city of Manaus, Brazil, in central Amazon during the dry season of 2018. The vertical profiles were analyzed to understand the structure of the urban nighttime boundary layer (NBL) and pollution within it. The ozone concentration, temperature, and humidity had an inflection between 225 and 350 m on most nights, representing the top of the urban NBL. The profile of carbon monoxide concentration correlated well with the local evening vehicular congestion of a modern transportation fleet, providing insight into the surface-atmosphere dynamics. In contrast, events of elevated PM2.5 and PM10 concentrations were not explained well by local urban emissions, but rather by back trajectories that intersected regional biomass burning. These results highlight the potential of the emerging technologies of sensor payloads on UAVs to provide new constraints and insights for understanding the pollution dynamics in nighttime boundary layers in urban regions.

How to Get the Best from Low-Cost Particulate Matter Sensors: Guidelines and Practical Recommendations

Low-cost sensors based on the optical particle counter (OPC) are increasingly being used to collect particulate matter (PM) data at high space and time resolution. In spite of their huge explorative potential, practical guidelines and recommendations for their use are still limited. In this work, we outline a few best practices for the optimal use of PM low-cost sensors based on the results of an intensive field campaign performed in Bologna (44°30' N, 11°21' E; Italy) under different weather conditions. Briefly, the performances of a series of sensors were evaluated against a calibrated mainstream OPC with a heated inlet, using a robust approach based on a suite of statistical indexes capable of evaluating both correlations and biases in respect to the reference sensor. Our results show that the sensor performance is sensibly affected by both time resolution and weather with biases maximized at high time resolution and high relative humidity. Optimization of PM data obtained is therefore achievable by lowering time resolution and applying suitable correction factors for hygroscopic growth based on the inherent particle size distribution.

The Determination of Aerosol Distribution by a No-Blind-Zone Scanning Lidar

A homemade portable no-blind zone laser detection and ranging (lidar) system was designed to map the three-dimensional (3D) distribution of aerosols based on a dual-field-of-view (FOV) receiver system. This innovative lidar prototype has a space resolution of 7.5 m and a time resolution of 30 s. A blind zone of zero meters, and a transition zone of approximately 60 m were realized with careful optical alignments, and were rather meaningful to the lower atmosphere observation. With a scanning platform, the lidar system was used to locate the industrial pollution sources at ground level. The primary parameters of the transmitter, receivers, and detectors are described in this paper. Acquiring a whole return signal of this lidar system represents the key step to the retrieval of aerosol distribution with applying a linear joining method to the two FOV signals. The vertical profiles of aerosols were retrieved by the traditional Fernald method and verified by real-time observations. To effectively and reliably retrieve the horizontal distributions of aerosols, a composition of the Fernald method and the slope method were applied. In this way, a priori assumptions of even atmospheric conditions and the already-known reference point in the lidar equation were avoided. No-blind-zone vertical in-situ observation of aerosol illustrated a detailed evolution from almost 0 m to higher altitudes. No-blind-zone detection provided tiny structures of pollution distribution in lower atmosphere, which is closely related to human health. Horizontal field scanning experiments were also conducted in the Shandong Province. The results showed a high accuracy of aerosol mass movement by this lidar system. An effective quantitative way to locate pollution sources distribution was paved with the portable lidar system after validation by the mass concentration of suspended particulate matter from a ground air quality station.

Vertical Profiles of Ozone Concentration Collected by an Unmanned Aerial Vehicle and the Mixing of the Nighttime Boundary Layer over an Amazonian Urban Area

The nighttime boundary layer was studied in an urban area surrounded by tropical forest by use of a copter-type unmanned aerial vehicle (UAV) in central Amazonia during the wet season. Fifty-seven vertical profiles of ozone concentration, potential temperature, and specific humidity were collected from surface to 500 m above ground level (a.g.l.) at high vertical and temporal resolutions by use of embedded sensors on the UAV. Abrupt changes in ozone concentration with altitude served as a proxy of nighttime boundary layer (NBL) height for the case of a normal, undisturbed, stratified nighttime atmosphere, corresponding to 40% of the cases. The median height of the boundary layer was 300 m. A turbulent mixing NBL constituted 28% of the profiles, while the median height of the boundary layer was 290 m. The remaining 32% of profiles corresponded to complex atmospheres without clear boundary layer heights. The occurrence of the three different cases correlated well with relative cloud cover. The results show that the standard nighttime model widely implemented in chemical transport models holds just 40% of the time, suggesting new challenges in modeling of regional nighttime chemistry. The boundary layer heights were also somewhat higher than observed previously over forested and pasture areas in Amazonia, indicating the important effect of the urban heat island.

Insights into the phenomenon of an explosive growth and sharp decline in haze: A case study in Beijing

A severe haze episode occurred in winter in the North China Plain (NCP), and the phenomenon of an explosive growth and sharp decline in PM_2.5 (particulate matter with an aerodynamic diameter equal to or less than 2.5 μm) concentration was observed. To study the systematic causes for this phenomenon, comprehensive observations were conducted in Beijing from November 26 to December 2, 2015; during this period, meteorological parameters, LIDAR data, and the chemical compositions of aerosols were determined. The haze episode was characterized by rapidly varying PM_2.5 concentration, and the highest PM_2.5 concentration reached 667 μg/m³. During the haze episode, the NCP was dominated by a weak high-pressure system and continuously low PBL (planetary boundary layer) heights, which are unfavorable conditions for the diffusion of pollutants. The large increases in the concentrations of SNA (SO₄^2-, NO₃^- and NH₄⁺) during the haze implied that the formation of SNA was the largest contribution. Water vapor also played a vital role in the formation of haze by promoting the chemical transformation of secondary pollutants, which led to higher PM_2.5 concentrations. The spatial distributions of PM_2.5 in Beijing at different times and the backward trajectories of the air masses also indicated that pollutants from surrounding provinces in particular, contributed to the higher PM_2.5 concentration.

A novel bagging ensemble approach for predicting summertime ground-level ozone concentration

Ozone pollution appears as a major air quality issue, e.g. for the protection of human health and vegetation. Formation of ground level ozone is a complex photochemical phenomenon and involves numerous intricate factors most of which are interrelated with each other. Machine learning techniques can be adopted to predict the ground level ozone. The main objective of the present study is to develop the state-of-the-art ensemble bagging approach to model the summer time ground level ozone in an industrial area comprising a hazardous waste management facility. In this study, the feasibility of using ensemble model with seven meteorological parameters as input variables to predict the surface level O3 concentration. Multilayer perceptron, RTree, REPTree, and Random forest were employed as the base learners. The error measures used for checking the performance of each model includes IoAd, R2, and PEP. The model results were validated against an independent test data set. Bagged random forest predicted the ground level ozone better with higher Nash-Sutcliffe coefficient 0.93. This study scaffolded the current research gap in big data analysis identified with air pollutant prediction. Implications: The main focus of this paper is to model the summer time ground level O₃ concentration in an Industrial area comprising of hazardous waste management facility. Comparison study was made between the base classifiers and the ensemble classifiers. Most of the conventional models can well predict the average concentrations. In this case the peak concentrations are of importance as it has serious effect on human health and environment. The models developed should also be homoscedastic.

Long-term observations of the background aerosol at Cabauw, The Netherlands

Long-term measurements of PM_2.5 mass concentrations and aerosol particle size distributions from 2008 to 2015, as well as hygroscopicity measurements conducted over one year (2008-2009) at Cabauw, The Netherlands, are compiled here in order to provide a comprehensive dataset for understanding the trends and annual variabilities of the atmospheric aerosol in the region. PM_2.5 concentrations have a mean value of 14.4μgm^-3 with standard deviation 2.1μgm^-3, and exhibit an overall decreasing trend of -0.74μgm^-3year^-1. The highest values are observed in winter and spring and are associated with a shallower boundary layer and lower precipitation, respectively, compared to the rest of the seasons. Number concentrations of particles smaller than 500nm have a mean of 9.2×10³particles cm^-3 and standard deviation 4.9×10³particles cm^-3, exhibiting an increasing trend between 2008 and 2011 and a decreasing trend from 2013 to 2015. The particle number concentrations exhibit highest values in spring and summer (despite the increased precipitation) due to the high occurrence of nucleation-mode particles, which most likely are formed elsewhere and are transported to the observation station. Particle hygroscopicity measurements show that, independently of the air mass origin, the particles are mostly externally mixed with the more hydrophobic mode having a mean hygroscopic parameter κ of 0.1 while for the more hydrophilic mode κ is 0.35. The hygroscopicity of the smaller particles investigated in this work (i.e., particles having diameters of 35nm) appears to increase during the course of the nucleation events, reflecting a change in the chemical composition of the particles.

Evaluating the Governing Factors of Variability in Nocturnal Boundary Layer Height Based on Elastic Lidar in Wuhan

The atmospheric boundary layer (ABL), an atmospheric region near the Earth’s surface, is affected by surface forcing and is important for studying air quality, climate, and weather forecasts. In this study, long-term urban nocturnal boundary layers (NBLs) were estimated by an elastic backscatter light detection and ranging (LiDAR) with various methods in Wuhan (30.5° N, 114.4° E), a city in Central China. This study aims to explore two ABL research topics: (1) the relationship between NBL height (NBLH) and near-surface parameters (e.g., sensible heat flux, temperature, wind speed, and relative humidity) to elucidate meteorological processes governing NBL variability; and (2) the influence of NBLH variations in surface particulate matter (PM) in Wuhan. We analyzed the nocturnal ABL-dilution/ABL-accumulation effect on surface particle concentration by using a typical case. A long-term analysis was then performed from 5 December 2012–17 June 2016. Results reveal that the seasonal averages of nocturnal (from 20:00 to 05:00 next day, Chinese standard time) NBLHs are 386 ± 161 m in spring, 473 ± 154 m in summer, 383 ± 137 m in autumn, and 309 ± 94 m in winter. The seasonal variations in NBLH, AOD, and PM_2.5 display a deep (shallow) seasonal mean NBL, consistent with a small (larger) seasonal mean PM_2.5 near the surface. Seasonal variability of NBLH is partly linearly correlated with sensible heat flux at the surface (R = 0.72). Linear regression analyses between NBLH and other parameters show the following: (1) the positive correlation (R = 0.68) between NBLH and surface temperature indicates high (low) NBLH corresponding to warm (cool) conditions; (2) the slight positive correlation (R = 0.52) between NBLH and surface relative humidity in Wuhan; and (3) the weak positive correlation (R = 0.38) between NBLH and wind speed inside the NBL may imply that the latter is not an important direct driver that governs the seasonal variability of NBLH.

On the factors governing water vapor turbulence mixing in the convective boundary layer over land: Concept and data analysis technique using ground-based lidar measurements

The convective boundary layer (CBL) turbulence is the key process for exchanging heat, momentum, moisture and trace gases between the earth's surface and the lower part of the troposphere. The turbulence parameterization of the CBL is a challenging but important component in numerical models. In particular, correct estimation of CBL turbulence features, parameterization, and the determination of the contribution of eddy diffusivity are important for simulating convection initiation, and the dispersion of health hazardous air pollutants and Greenhouse gases. In general, measurements of higher-order moments of water vapor mixing ratio (q) variability yield unique estimates of turbulence in the CBL. Using the high-resolution lidar-derived profiles of q variance, third-order moment, and skewness and analyzing concurrent profiles of vertical velocity, potential temperature, horizontal wind and time series of near-surface measurements of surface flux and meteorological parameters, a conceptual framework based on bottom up approach is proposed here for the first time for a robust characterization of the turbulent structure of CBL over land so that our understanding on the processes governing CBL q turbulence could be improved. Finally, principal component analyses will be applied on the lidar-derived long-term data sets of q turbulence statistics to identify the meteorological factors and the dominant physical mechanisms governing the CBL turbulence features.

Annual and diurnal variations of gaseous and particulate pollutants in 31 provincial capital cities based on in situ air quality monitoring data from China National Environmental Monitoring Center

Long-term air quality data with high temporal and spatial resolutions are needed to understand some important processes affecting the air quality and corresponding environmental and health effects. The annual and diurnal variations of each criteria pollutant including PM2.5 and PM10 (particulate matter with aerodynamic diameter less than 2.5 μm and 10 μm, respectively), CO (carbon monoxide), NO2 (nitrogen dioxide), SO2 (sulfur dioxide) and O3 (ozone) in 31 provincial capital cities between April 2014 and March 2015 were investigated by cluster analysis to evaluate current air pollution situations in China, and the cities were classified as severely, moderately, and slightly polluted cities according to the variations. The concentrations of air pollutants in winter months were significantly higher than those in other months with the exception of O3, and the cities with the highest CO and SO2 concentrations were located in northern China. The annual variation of PM2.5 concentrations in northern cities was bimodal with comparable peaks in October 2014 and January 2015, while that in southern China was unobvious with slightly high PM2.5 concentrations in winter months. The concentrations of particulate matter and trace gases from primary emissions (SO2 and CO) and NO2 were low in the afternoon (~16:00), while diurnal variation of O3 concentrations was opposite to that of other pollutants with the highest values in the afternoon. The most polluted cities were mainly located in North China Plain, while slightly polluted cities mostly focus on southern China and the cities with high altitude such as Lasa. This study provides a basis for the formulation of future urban air pollution control measures in China.

PM2.5 Spatiotemporal Variations and the Relationship with Meteorological Factors during 2013-2014 in Beijing, China

Objective

Limited information is available regarding spatiotemporal variations of particles with median aerodynamic diameter < 2.5 μm (PM_2.5) at high resolutions, and their relationships with meteorological factors in Beijing, China. This study aimed to detect spatiotemporal change patterns of PM_2.5 from August 2013 to July 2014 in Beijing, and to assess the relationship between PM_2.5 and meteorological factors.

Methods

Daily and hourly PM_2.5 data from the Beijing Environmental Protection Bureau (BJEPB) were analyzed separately. Ordinary kriging (OK) interpolation, time-series graphs, Spearman correlation coefficient and coefficient of divergence (COD) were used to describe the spatiotemporal variations of PM_2.5. The Kruskal-Wallis H test, Bonferroni correction, and Mann-Whitney U test were used to assess differences in PM_2.5 levels associated with spatial and temporal factors including season, region, daytime and day of week. Relationships between daily PM_2.5 and meteorological variables were analyzed using the generalized additive mixed model (GAMM).

Results

Annual mean and median of PM_2.5 concentrations were 88.07 μg/m³ and 71.00 μg/m³, respectively, from August 2013 to July 2014. PM_2.5 concentration was significantly higher in winter (P < 0.0083) and in the southern part of the city (P < 0.0167). Day to day variation of PM_2.5 showed a long-term trend of fluctuations, with 2–6 peaks each month. PM_2.5 concentration was significantly higher in the night than day (P < 0.0167). Meteorological factors were associated with daily PM_2.5 concentration using the GAMM model (R² = 0.59, AIC = 7373.84).

Conclusion

PM_2.5 pollution in Beijing shows strong spatiotemporal variations. Meteorological factors influence the PM_2.5 concentration with certain patterns. Generally, prior day wind speed, sunlight hours and precipitation are negatively correlated with PM_2.5, whereas relative humidity and air pressure three days earlier are positively correlated with PM_2.5.

The Nevada Rural Ozone Initiative (NVROI): Insights to understanding air pollution in complex terrain

The Nevada Rural Ozone Initiative (NVROI) was established to better understand O3 concentrations in the Western United States (US). The major working hypothesis for development of the sampling network was that the sources of O3 to Nevada are regional and global. Within the framework of this overarching hypothesis, we specifically address two conceptual meteorological hypotheses: (1) The high elevation, complex terrain, and deep convective mixing that characterize Nevada, make this state ideally located to intercept polluted parcels of air transported into the US from the free troposphere; and (2) site specific terrain features will influence O3 concentrations observed at surface sites. Here, the impact of complex terrain and site location on observations are discussed. Data collected in Nevada at 6 sites (1385 to 2082 m above sea level (asl)) are compared with that collected at high elevation sites in Yosemite National Park and the White Mountains, California. Average daily maximum 1-hour concentrations of O3 during the first year of the NVROI ranged from 58 to 69 ppbv (spring), 53 to 62 ppbv (summer), 44 to 49 ppbv (fall), and 37 to 45 ppbv (winter). These were similar to those measured at 3 sites in Yosemite National Park (2022 to 3031 m asl), and at 4 sites in the White Mountains (1237 to 4342 m asl) (58 to 67 ppbv (summer) and 47 to 58 ppbv (fall)). Results show, that in complex terrain, collection of data should occur at high and low elevation sites to capture surface impacts, and site location with respect to topography should be considered. Additionally, concentrations measured are above the threshold reported for causing a reduction in growth and visible injury for plants (40 ppbv), and sustained exposure at high elevation locations in the Western USA may be detrimental for ecosystems.