Abstract
Assessment of spatial and temporal variation in the impacts of ozone on human health, vegetation, and climate requires appropriate metrics. A key component of the Tropospheric Ozone Assessment Report (TOAR) is the consistent calculation of these metrics at thousands of monitoring sites globally. Investigating temporal trends in these metrics required that the same statistical methods be applied across these ozone monitoring sites. The nonparametric Mann-Kendall test (for significant trends) and the Theil-Sen estimator (for estimating the magnitude of trend) were selected to provide robust methods across all sites. This paper provides the scientific underpinnings necessary to better understand the implications of and rationale for selecting a specific TOAR metric for assessing spatial and temporal variation in ozone for a particular impact. The rationale and underlying research evidence that influence the derivation of specific metrics are given. The form of 25 metrics (4 for model-measurement comparison, 5 for characterization of ozone in the free troposphere, 11 for human health impacts, and 5 for vegetation impacts) are described. Finally, this study categorizes health and vegetation exposure metrics based on the extent to which they are determined only by the highest hourly ozone levels, or by a wider range of values. The magnitude of the metrics is influenced by both the distribution of hourly average ozone concentrations at a site location, and the extent to which a particular metric is determined by relatively low, moderate, and high hourly ozone levels. Hence, for the same ozone time series, changes in the distribution of ozone concentrations can result in different changes in the magnitude and direction of trends for different metrics. Thus, dissimilar conclusions about the effect of changes in the drivers of ozone variability (e.g., precursor emissions) on health and vegetation exposure can result from the selection of different metrics.
Highlights
Tropospheric ozone is a pollutant that is detrimental to human health and crop and ecosystem productivity (REVIHAAP, 2013; US Environmental Protection Agency (EPA), 2013; Monks et al, 2015; CLRTAP, 2017)
Observational metrics calculated at individual sites can provide insight into the physical and chemical processes that determine ozone and its variations on different timescales (e.g., Logan, 1985; Oltmans and Levy II, 1994). Comparison of these metrics calculated at surface sites with modeled ozone levels is one method used to evaluate the performance of global models in predicting tropospheric ozone
We extend the analysis of Lefohn et al (2017) by comparing the trend patterns of other Tropospheric Ozone Assessment Report (TOAR) metrics between 1995 and 2014 with patterns observed in the case study for gaining insight about the relationships of TOAR metrics among one another (Section 4.2)
Summary
Tropospheric ozone is a pollutant that is detrimental to human health and crop and ecosystem productivity (REVIHAAP, 2013; US EPA, 2013; Monks et al, 2015; CLRTAP, 2017). Data from widespread observational networks, operational since the 1970s, provide hourly average ozone data from thousands of surface monitoring sites across the globe, and vertical information is available from ozonesondes, aircraft, and satellites (Schultz et al, 2017, hereinafter referred to as TOAR-Surface Ozone Database). The data from these networks continue to increase our understanding of ambient ozone levels and their possible impacts on human health, vegetation, and climate change. We rely on global chemistry models to fill gaps in these areas to improve our understanding of long-term changes in tropospheric ozone (Young et al, 2018, hereinafter referred to as TOAR-Model Performance)
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