Introduction
      Lefohn et al. (2008) summarized their trends
      analyses for surface ozone monitoring sites across the United
      States. Using statistical trending on a site-by-site basis of
      the (1) health-based annual 2nd highest 1-hour average concentration
      and annual 4th highest daily maximum 8-hour average concentration
      and (2) vegetation-based annual seasonally corrected 24-hour
      W126 cumulative exposure index, they investigated temporal and
      spatial statistically significant changes that occurred in surface
      ozone in the United States for the periods 1980-2005 and 1990-2005
      and explored whether differences in trending occur depending
      upon the selection of the exposure metric. Using the trending
      results, the analyses quantitatively explore the evidence for
      the higher hourly average ozone concentrations decreasing faster
      than the mid- and lower-values.
      Results
      Figure 1 below from Lefohn et al. (2008) summarizes
      the findings for the trending of the 4th highest 8-hour ozone
      metric for the 1980-2005 and 1990-2005 periods.
       
      Figure 1. Trend of 4th highest 8-hour average
      ozone metric for the (a) 1980-2005 and (b) 1990-2005 periods.
      This figure was published in Lefohn et. al. (2008). Copyright
      Elsevier. Please see reference below. Permission granted by Elsevier
      to reproduce the above figure only on this web page.
      
      Most of the surface ozone monitoring sites
      analyzed in the study experienced decreasing or no trends. Few
      monitoring sites experienced increasing trends. For those monitoring
      sites with declining ozone levels, an initial pattern of rapid
      decrease in the higher hourly average concentrations, followed
      by a much slower decrease in mid-level concentrations was observed.
      In some cases, they observed shifts from the lower hourly average
      ozone concentrations to the mid-level values. On a site-by-site
      basis, the majority of monitoring sites (1) changed from negative
      trend to no trend, (2) continued a negative trend, or (3) remained
      in the no trend status, when comparing trends for the 1980-2005
      to the 1990-2005 time periods. For the three exposure metrics
      (i.e., annual 2nd highest 1-hour average concentration, annual
      4th highest daily maximum 8-hour average concentration, and vegetation-based
      annual seasonally corrected 24-hour W126 cumulative exposure
      index, approximately 60% of the monitoring sites shifted from
      negative trending to no trending status. All regions of the United
      States were equally affected by the shift in status.
      Lefohn et al. (2008) in their paper provide
      several figures that illustrate the spatial patterns of trends
      across the United States. The greatest statistically significant
      decreases in the 2nd highest 1-hour average concentrations and
      the annual 4th highest daily maximum 8-hour average concentration
      for the two temporal periods occurred in southern California.
      Monitoring sites in other portions of the United States experienced
      lesser decreases than this geographic area. In contrast to the
      two exposure indices, the vegetation-based 24-hour W126 ozone
      cumulative index for 1980-2005 experienced significant declines
      in the midwestern states and the northeastern United States,
      as well as in southern California. For the 1990-2005 period,
      monitoring sites in southern California and the northeastern
      United States experienced the greatest decreases in the W126
      exposure metric.
      When trending was observed, not all months
      experienced trending. Lefohn et al. (2008) tested for statistically
      significant changes in the number of hourly average concentrations
      within specified concentration intervals and identified specific
      months that experienced shifts in the distribution of the hourly
      average concentrations. As an example, Figures 2 and 3 below
      illustrate the changes in the distribution of the hourly average
      ozone concentrations for a monitoring site located in Reseda
      in Los Angeles County as reductions occurred over the 1980-2005
      and 1990-2005 periods.
       
      Figure 2. Distribution of changes by month
      for a monitoring site located in Los Angeles County, California
      (AQS 060371201) for 1980-2005 for the months with significant
      changes.
       
      Figure 3. Distribution of changes by month
      for a monitoring site located in Los Angeles County, California
      (AQS 060371201) for 1990-2005 for the months with significant
      changes.
      The two figures show the reductions in the
      number of hourly average concentrations in the higher hourly
      average concentrations and the increases in the mid-level concentrations
      as the peak values were reduced.
      The Theil estimate was used to estimate trending.
      The Theil estimate is determined as the median of slope estimates
      calculated as the slope of the line passing through two points
      for all pairs of points in the data set of interest. To test
      for statistical significance, Kendall's tau test was used to
      determine significance at the 10% level.
      The Mann-Kendall (M-K) nonparametric test
      is utilized to test for a significant trend. Advantages of the
      M-K test are
      
        
          - No distributional assumption is made;
        
 
        
          - No assumption of any specific functional
          form for the behavior of the data through time is made. Thus,
          the M-K test is universally applicable across all sites, seasons,
          and different continuous summary exposure metrics (e.g., percentiles,
          means, and cumulative exposure indices, such as the W126 and
          AOT40 vegetation exposure metrics); and
        
 
        
          - The M-K test is resistant to the effects
          of outlying observations. The results are not unduly affected
          by particularly high or low values that occur during time series
          analyses.
        
      For estimating the magnitude of a trend, the
      Theil-Sen (also called Sen-Theil, Theil, or Sen) estimator can
      be used. It possesses the same attributes described above for
      the M-K test (i.e., there are no distributional or functional
      form assumptions and the estimator is resistant to outliers).
      The Theil-Sen (T-S) estimator, similar to the M-K technique,
      is also universally applicable. In cases where simple linear
      regression is appropriate (assuming key assumptions are met),
      the slope of the regression line and the T-S estimator are asymptotically
      equivalent.
      For more information about the Theil estmate
      and the Kendall's tau test, please see the discussion in Section
      3 in Lefohn et al. (2018).
      Note that the months of March and April exhibited
      statistically significant trending in the 1980-2005 period, but
      did not exhibit statistically significant trending over the 1990-2005
      period. Over the 1990-2005 period, the month of September exhibited
      statistically significant trending but did not over the 1980-2005
      period.
      Lefohn et al. (2010a) updated the trending
      results reported in Lefohn et al. (2008). The updated trending
      periods were 1980-2008 (29 years) and 1994-2008 (15 years). In
      addition to updating the trends analysis, the authors focused
      on 12 urban and 15 rural monitoring sites. The trending results
      provide examples on why it is important
      to investigate the change in the trending pattern with time (e.g.,
      moving 15-year trending) in order to assess how year-to-year
      variability may influence the trend calculation. Several research
      investigations have explored trending from the beginning of a
      data series until the latest date for collection of data. However,
      these types of trends analyses do not take into consideration
      the possibility that the rate of trending over the period of
      record has changed and in some cases the trending has ceased.
      Lefohn et al. (2010a) took a closer look at changes in the rate
      of trending and drew conclusions about the importance of using
      15-year moving trends to quantify trending rates. The paper's
      abstract is available on our publications web page.
      Conclusions and Recommendations
      Most of the surface ozone monitoring sites
      analyzed in the Lefohn et al. (2008, 2010a) studies experienced
      decreasing or no trends. Few monitoring sites experienced increasing
      trends. Lefohn et al. (2008, 2010a) observed that a statistically
      significant trend at a specific monitoring site, using one exposure
      index, did not necessarily result in a similar trend using the
      other two indices. The authors recommended that because different
      trending patterns were observed when applying the various exposure
      indices, a careful selection of ozone exposure metrics is required
      when assessing trends for specific purposes, such as human health,
      vegetation, and climate change effects. Lefohn et al. (2017)
      performed a detailed analysis using several human health and
      vegetation exposure metrics and quantified the differences in
      trends using different metrics for sites in the US, EU, and China.
      As in previous analyses, Lefohn et al. (2017) noted that using
      the identical hourly average ozone concentrations, different
      trend patterns occurred based on the selection of the specific
      exposure indices (e.g., metrics focused on the higher end of
      the distribution versus those indices focused on the lower end
      of the distribution). In some cases, the high end of the distribution
      moved downward, while the low end of the distribution shifted
      upward. The lower hourly averaged ozone concentrations moved
      upward due to less titration of ozone by NO as reduction in NOx
      emissions occurred (Lefohn et al., 1998; Lefohn et al., 2010a;
      Tørseth et al., 2012; Simon et al., 2015; Lefohn et al.,
      2017, 2018; Aas et al., 2024; Real et al., 2024). For
      assessing biological effects, the highest hourly average ozone
      concentrations are more important than the mid- and low-level
      values for human health (Hazucha and Lefohn, 2007; Lefohn et
      al., 2010b) and vegetation (Musselman et al., 2006; Hogsett et
      al., 1985; Lefohn et al., 2018).
       
      Part 2 - Ozone
      Trends of Special Monitoring Stations for Assessing Background
      Ozone Trending
      Introduction
      Over the past several years,
      there have been several articles quoting other sources indicating
      that surface ozone concentrations are increasing everywhere.
      Our research results do not support this claim. Our research
      efforts monitor the status of worldwide ozone levels by performing
      sophisticated analyses using surface ozone and ozonesonde data
      (e.g., Oltmans et al., 1998; Oltmans et al., 2006; Oltmans et
      al., 2013). Our research focuses on the results from the available
      data from four decades of observations for the longest records
      (ozonesondes). Several key stations have 30-40 years of observations
      for both surface and ozonesondes. The key ozone monitoring stations
      provide good data for the purpose of assessing possible changes
      in background levels of ozone. Some of the sites offer the opportunity
      to study records representative of broad geographic regions where
      local effects are minimized.
      Oltmans et al. (2013) discusses the longer-term (i.e., 20-40 years) tropospheric
      ozone time series obtained from surface and ozonesonde observations
      that we analyzed to assess possible changes with time through
      2010. The time series have been selected to reflect relatively
      broad geographic regions and where possible minimize local scale
      influences, generally avoiding sites close to larger urban areas.
      Several approaches have been used to describe the changes with
      time, including application of a time-series model, running 15-year
      trends, and changes in the distribution by month in the ozone
      mixing ratio. Changes have been investigated utilizing monthly
      averages, as well as exposure metrics that focus on specific
      parts of the distribution of hourly average concentrations (e.g.,
      low-, mid-, and high-level concentration ranges). Oltmans et
      al. (2013) noted that many of the longer time series (~30 years)
      in mid-latitudes of the Northern Hemisphere, including those
      in Japan, show a pattern of significant increase in the earlier
      portion of the record, with a flattening over the last 10-15
      years. It is uncertain if the flattening of the ozone change
      over Japan reflects the impact of ozone transported from continental
      East Asia in light of reported ozone increases in China. In the
      Canadian Arctic, declines from the beginning of the ozonesonde
      record in 1980 have mostly rebounded with little overall change
      over the period of record. The limited data in the tropical Pacific
      suggest very little change over the entire record. In the southern
      hemisphere subtropics and midlatitudes, the significant increase
      observed in the early part of the record has leveled off in the
      most recent decade. At the South Pole, a decline observed during
      the first half of the 35-year record has reversed, and ozone
      has recovered to levels similar to the beginning of the record.
      Our understanding of the causes of the longer-term changes is
      limited, although it appears that in the mid-latitudes of the
      Northern Hemisphere, controls on ozone precursors have likely
      been a factor in the leveling off or decline from earlier ozone
      increases.
      As indicated earlier in the
      Part 1 discussion, it is important to investigate the rate-of-change
      in trending and not just analyze for trends using the beginning
      and ending periods of monitoring. For example, Logan et al. (2012)
      described the decrease in ozone over Europe since 1998, with
      the largest decrease during the summertime. Using Zugspitze data
      for 1978-1989 and the mean time series from three Alpine stations
      since 1990, Logan et al. (2012) found that the ozone increased
      substantially in 1978-1989 (i.e., 6.5-10 ppb but began to exhibit
      a reduced rate of increase in the 1990s (i.e., 2.5-4.5 ppb) with
      decreases in the 2000s (i.e., 4 ppb) in summer with no significant
      changes in other seasons. Overall in summer no trend was noted
      for the 1990-2009 period.
      Conclusions and Recommendations
      Our results suggest
      that on a hemispheric scale it is currently difficult to observe
      the projected increases in tropospheric ozone that models indicate
      may occur from Asian emissions. This may result from the lack
      of such ozone increases or that changes resulting from precursor
      reductions in North America and Europe have made the influence
      of Asian precursor emissions more difficult to detect. Parrish
      et al. (2017) noted that over the past decades, a long-term increase
      in baseline ozone has been observed at the North American west
      coast, They have concluded based on their analyses that this
      increase has ended. These results complement our observation
      that changes in hourly average ozone distributions at the low-,
      mid and high-level ranges for sites investigated in our most
      recent study do not indicate that background ozone concentrations
      continue to increase in the most recent decades. As indicated
      in our analysis and others, at many of the investigated sites
      earlier ozone increases have reached a plateau and in some cases
      begun to decrease. In order to follow future trend patterns,
      it will be important to use techniques that capture the time
      evolution of ozone changes, such as the 15-year trend periods
      used by Lefohn et al. (2010a) and Oltmans et al. (2013) or other
      methods that detect these changes. Due to the increase in the
      frequency of wildfires, it will be important to identify changing
      trend patterns associated with changing ozone precursors so as
      to better understand how climate change affects current ozone
      levels.
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