Climate controls on air quality in the Northeastern U.S.: An examination of summertime ozone statistics during 1993–2012

Oswald, Evan M.; Dupigny‐Giroux, Lesley‐Ann; Leibensperger, E. M.; Poirot, Richard L.; Merrell, Jeff

doi:10.1016/j.atmosenv.2015.04.019

Cited by 23 publications

(13 citation statements)

References 34 publications

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“…The ASI is described in detail in Horton et al (2012,2014), and the use of the ASI for air quality applications is ubiquitous in the literature (e.g. Leung and Gustafson Jr 2005, Horton et al 2012, 2014, Oswald et al 2015, Strode et al 2015, Hou and Wu 2016, Schnell and Prather 2017, Sun et al 2017. The ASI is a binary index based on absolute thresholds.…”

Section: Methodsmentioning

confidence: 99%

“…These conditions lead to elevated pollutant concentrations on daily to interannual timescales (e.g. Logan 1989, Vukovich 1995, Wang and Angell 1999, Vautard et al 2005, Leibensperger et al 2008, Tai et al 2010, He et al 2013b, Dawson et al 2014, Oswald et al 2015, Hou and Wu 2016, Schnell and Prather 2017, Sun et al 2017; however, the change in pollutant concentrations due to stagnant conditions is small and the connections between stagnation and pollution are weak in some of these studies. Thus, there remains uncertainty in the exact impact of stagnation on air pollution.…”

Section: Introductionmentioning

confidence: 97%

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Connections between summer air pollution and stagnation

Kerr

Waugh

2018

Environ. Res. Lett.

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The body of literature on ambient air pollution suggests that atmospheric stagnation events trigger high levels of air pollution. In this paper we use fifteen years (2000)(2001)(2002)(2003)(2004)(2005)(2006)(2007)(2008)(2009)(2010)(2011)(2012)(2013)(2014) of summertime in situ air quality measurements together with meteorological reanalysis data to examine the temporal correlation of pollutants with the Air Stagnation Index (ASI) on daily timescales. We find that while the direction of the relationship between the ASI and summertime PM 2.5 and O 3 ranges from near-zero to positive throughout regions comprising the contiguous United States (US), the strength of the relationship is very weak (e.g. in the Northeast the correlation coefficient between the ASI and PM 2.5 is 0.09). Moreover, similar to our analysis of the correlation of day-to-day variations of the ASI and pollutants, the percentage of co-occurring extreme pollution and stagnation events is small (e.g. days with a high coverage of stagnation only co-occur with extreme pollution events about one-third of the time in the Northeast). The southern US is an exception to our overall findings as the strength of the relationship between the ASI and pollution is stronger and the percentage of co-occurring events is higher compared with other regions. The results of this study suggest a reevaluation of the ASI as an index to assess meteorological and climatic impacts to air quality.

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Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 97%

Connections between summer air pollution and stagnation

Kerr

Waugh

2018

Environ. Res. Lett.

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“…There have been a large number of studies that characterize potential O 3 increases caused by future climate-driven meteorological changes (Steiner et al, 2006;Tagaris et al, 2007;Wu et al, 2008;Zeng et al, 2008;Nolte et al, 2008;Doherty et al, 2013;Fann et al, 2015). Some investigations have looked at correlations between changing meteorological parameters and O 3 in the recent past (Camalier et al, 2007;Leibensperger et al, 2008;Bloomer et al, 2009;Oswald et al, 2015;Jhun et al, 2015). Many of these studies focus on future climate change.…”

Section: 1mentioning

confidence: 99%

Responses of human health and vegetation exposure metrics to changes in ozone concentration distributions in the European Union, United States, and China

Lefohn¹,

Malley

Simon

et al. 2017

Atmospheric Environment

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The impacts of surface ozone (O 3) on human health and vegetation have prompted O 3 precursor emission reductions in the European Union (EU) and United States (US). In contrast, until recently, emissions have increased in East Asia and most strongly in China. As emissions change, the distribution of hourly O 3 concentrations also changes, as do the values of exposure metrics. The distribution changes can result in the exposure metric trend patterns changing in a similar direction as trends in emissions (e.g., metrics increase as emissions increase) or, in some cases, in opposite directions. This study, using data from 481 sites (276 in the EU, 196 in the US, and 9 in China), investigates the response of 14 human health and vegetation O 3 exposure metrics to changes in hourly O 3 concentration distributions over time. At a majority of EU and US sites, there was a reduction in the frequency of both relatively high and low hourly average O 3 concentrations. In contrast, for some sites in mainland China and Hong Kong, the middle of the distribution shifted upwards but the low end did not change and for other sites, the entire distribution shifted upwards. The responses of the 14 metrics to these changes at the EU, US, and Chinese sites were varied, and dependent on (1) the extent to which the metric was determined by relatively high, moderate, and low concentrations and (2) the relative magnitude of the shifts occurring within the O 3 concentration distribution. For example, the majority of the EU and US sites experienced decreasing trends in the magnitude of those metrics associated with higher concentrations. For the sites in China, all of the metrics either increased or had no trends. In contrast, there were a greater number of sites that had no trend for those metrics determined by a combination of moderate and high O 3 concentrations. A result of our analyses is that trends in mean or median concentrations did not appear to be well associated with some exposure metrics applicable for assessing human health or vegetation effects. The identification of shifting

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“…First, ozone may be impacted by changes in meteorology induced by year-to-year variations in weather conditions and by long-term changes associated with climate change. Relationships have been demonstrated between observed surface ozone and individual meteorological variables, such as temperature, humidity, cloud cover, wind speed, surface radiation, boundary layer depth, and boundary layer ventilation and stagnation ( Camalier et al, 2007 ; Oswald et al, 2015 ; also see extensive reviews of Jacob and Winner 2009 ; Kirtman et al, 2013 ; Fiore et al, 2015 ). Modeling studies also indicate that future climate change may lead to both (1) increases in surface ozone, especially in polluted areas ( Kirtman et al, 2013 ; Fiore et al, 2015 ), and (2) potentially some decreases in surface ozone levels through enhanced boundary layer ventilation ( Trail et al, 2014 ).…”

Section: Introductionmentioning

confidence: 99%

Tropospheric ozone assessment report: Global ozone metrics for climate change, human health, and crop/ecosystem research

Lefohn¹,

Malley

Smith

et al. 2018

Elementa: Science of the Anthropocene

241

183

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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.

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Climate controls on air quality in the Northeastern U.S.: An examination of summertime ozone statistics during 1993–2012

Cited by 23 publications

References 34 publications

Connections between summer air pollution and stagnation

Connections between summer air pollution and stagnation

Responses of human health and vegetation exposure metrics to changes in ozone concentration distributions in the European Union, United States, and China

Tropospheric ozone assessment report: Global ozone metrics for climate change, human health, and crop/ecosystem research

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