Different trends in extreme and median surface aerosol extinction coefficients over China inferred from quality-controlled visibility data

Li, Jing; Li, Chengcai; Zhao, Chunsheng

Although the temporal changes in aerosol properties have been widely investigated, the majority of studies has focused on average conditions without much emphasis on the extremes. However, the latter can be more important in terms of human health and climate change. This study uses a previously validated, quality-controlled visibility dataset to investigate the long-term trends (expressed in terms of relative changes) in extreme surface aerosol extinction coefficient (AEC) over China and compares them with the median trends. Two methods are used to independently evaluate the trends, which arrive at consistent results. The signs of extreme and median trends are generally coherent, whereas their magnitudes show distinct spatial and temporal differences. In the 1980s, an overall positive trend is found throughout China with the extreme trend exceeding the mean trend, except for northwest China and the North China Plain. In the 1990s, AEC over northeast and northwest China started to decline while the rest of the country still exhibited an increase. The extreme trends continued to dominate in the south while they yielded to the mean trend in the north. After the year 2000, the extreme trend became weaker than the mean trend overall in terms of both the magnitude and significance level. The annual trend can be primarily attributed to winter and fall trends. The results suggest that the decadal changes in pollution in China may be governed by different mechanisms. Synoptic conditions that often result in extreme air quality changes might have dominated in the 1980s, whereas emission increase might have been the main factor for the 2000s.

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Li, Jing / Li, Chengcai / Zhao, Chunsheng: Different trends in extreme and median surface aerosol extinction coefficients over China inferred from quality-controlled visibility data. 2018. Copernicus Publications.

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