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Long-term Changes in Extreme Air Pollution Meteorology and the Implications for Air Quality.

Hou P, Wu S - Sci Rep (2016)

Bottom Line: We have identified significant increasing trends for the occurrences of extreme air pollution meteorological events in the past six decades, especially over the continental regions.Statistical analysis combining air quality data and meteorological data further indicates strong sensitivities of air quality (including both average air pollutant concentrations and high pollution episodes) to extreme meteorological events.We have also identified significant seasonal and spatial variations in the sensitivity of air quality to extreme air pollution meteorology.

View Article: PubMed Central - PubMed

Affiliation: Atmospheric Sciences Program, Michigan Technological University, Houghton, MI, 49931, USA.

ABSTRACT
Extreme air pollution meteorological events, such as heat waves, temperature inversions and atmospheric stagnation episodes, can significantly affect air quality. Based on observational data, we have analyzed the long-term evolution of extreme air pollution meteorology on the global scale and their potential impacts on air quality, especially the high pollution episodes. We have identified significant increasing trends for the occurrences of extreme air pollution meteorological events in the past six decades, especially over the continental regions. Statistical analysis combining air quality data and meteorological data further indicates strong sensitivities of air quality (including both average air pollutant concentrations and high pollution episodes) to extreme meteorological events. For example, we find that in the United States the probability of severe ozone pollution when there are heat waves could be up to seven times of the average probability during summertime, while temperature inversions in wintertime could enhance the probability of severe particulate matter pollution by more than a factor of two. We have also identified significant seasonal and spatial variations in the sensitivity of air quality to extreme air pollution meteorology.

No MeSH data available.


Related in: MedlinePlus

Cumulative probability plots for concentrations of air pollutants.Red triangle: event group; blue circle: no-event group. (a) ozone mean concentrations of heat wave group and no heat wave group; (b) PM2.5 mean concentrations of temperature inversion group and no temperature inversion group; (c) PM2.5 mean concentrations of atmospheric stagnation group and no atmospheric stagnation group.
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f4: Cumulative probability plots for concentrations of air pollutants.Red triangle: event group; blue circle: no-event group. (a) ozone mean concentrations of heat wave group and no heat wave group; (b) PM2.5 mean concentrations of temperature inversion group and no temperature inversion group; (c) PM2.5 mean concentrations of atmospheric stagnation group and no atmospheric stagnation group.

Mentions: We further examine the impacts of extreme air pollution meteorology on the cumulative probability distributions of ozone and PM2.5 concentrations (Fig. 4). For each season, the cumulative probability distributions of ozone mixing ratios for days with heat waves were compared with those without heat waves (Fig. 4a). We can see that extreme air pollution meteorology usually has the greatest impacts on the high end of the distributions, which represents the high pollution episodes. For example, during summer time, the 95th percentile ozone is increased by about 25% while the 50th percentile ozone is only increased by about 19% due to heat waves. Similar feature is found for the impacts on PM2.5 from temperature inversions and atmospheric stagnation episodes. In winter time, the 95th percentile PM2.5 concentration is increased by 65% while the 50th percentile PM2.5 concentration only increases by 28% in response to temperature inversions (Fig. 4b). Similarly, atmospheric stagnation episodes are found to have little effects on the low end of PM2.5 distributions (which represent the clean conditions) but significant impacts on the high pollution episodes for each season (Fig. 4c).


Long-term Changes in Extreme Air Pollution Meteorology and the Implications for Air Quality.

Hou P, Wu S - Sci Rep (2016)

Cumulative probability plots for concentrations of air pollutants.Red triangle: event group; blue circle: no-event group. (a) ozone mean concentrations of heat wave group and no heat wave group; (b) PM2.5 mean concentrations of temperature inversion group and no temperature inversion group; (c) PM2.5 mean concentrations of atmospheric stagnation group and no atmospheric stagnation group.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4815017&req=5

f4: Cumulative probability plots for concentrations of air pollutants.Red triangle: event group; blue circle: no-event group. (a) ozone mean concentrations of heat wave group and no heat wave group; (b) PM2.5 mean concentrations of temperature inversion group and no temperature inversion group; (c) PM2.5 mean concentrations of atmospheric stagnation group and no atmospheric stagnation group.
Mentions: We further examine the impacts of extreme air pollution meteorology on the cumulative probability distributions of ozone and PM2.5 concentrations (Fig. 4). For each season, the cumulative probability distributions of ozone mixing ratios for days with heat waves were compared with those without heat waves (Fig. 4a). We can see that extreme air pollution meteorology usually has the greatest impacts on the high end of the distributions, which represents the high pollution episodes. For example, during summer time, the 95th percentile ozone is increased by about 25% while the 50th percentile ozone is only increased by about 19% due to heat waves. Similar feature is found for the impacts on PM2.5 from temperature inversions and atmospheric stagnation episodes. In winter time, the 95th percentile PM2.5 concentration is increased by 65% while the 50th percentile PM2.5 concentration only increases by 28% in response to temperature inversions (Fig. 4b). Similarly, atmospheric stagnation episodes are found to have little effects on the low end of PM2.5 distributions (which represent the clean conditions) but significant impacts on the high pollution episodes for each season (Fig. 4c).

Bottom Line: We have identified significant increasing trends for the occurrences of extreme air pollution meteorological events in the past six decades, especially over the continental regions.Statistical analysis combining air quality data and meteorological data further indicates strong sensitivities of air quality (including both average air pollutant concentrations and high pollution episodes) to extreme meteorological events.We have also identified significant seasonal and spatial variations in the sensitivity of air quality to extreme air pollution meteorology.

View Article: PubMed Central - PubMed

Affiliation: Atmospheric Sciences Program, Michigan Technological University, Houghton, MI, 49931, USA.

ABSTRACT
Extreme air pollution meteorological events, such as heat waves, temperature inversions and atmospheric stagnation episodes, can significantly affect air quality. Based on observational data, we have analyzed the long-term evolution of extreme air pollution meteorology on the global scale and their potential impacts on air quality, especially the high pollution episodes. We have identified significant increasing trends for the occurrences of extreme air pollution meteorological events in the past six decades, especially over the continental regions. Statistical analysis combining air quality data and meteorological data further indicates strong sensitivities of air quality (including both average air pollutant concentrations and high pollution episodes) to extreme meteorological events. For example, we find that in the United States the probability of severe ozone pollution when there are heat waves could be up to seven times of the average probability during summertime, while temperature inversions in wintertime could enhance the probability of severe particulate matter pollution by more than a factor of two. We have also identified significant seasonal and spatial variations in the sensitivity of air quality to extreme air pollution meteorology.

No MeSH data available.


Related in: MedlinePlus