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Characteristic analysis of haze in Sichuan Basin and typical cities from 1980 to 2012 |
ZHOU-Wei1,2, KANG-Lan1,2, HAO Li-ping3 |
1. Sichuan Provincial Meteorology Observatory, Chengdu 610072, China;
2. Heavy Rain and Drought-Flood Disaster in Plateau and Basin Key Laboratory of Sichuan Province, Chengdu 610072, China;
3. Sichuan Provincial Meteorology Bureau, Chengdu 610072, China |
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Abstract The temporal and spatial distributions and long-term variation characteristics of haze were obtained for the Sichuan-Chongqing region from 1980 to 2012 by studying surface meteorological data and using a haze-days reconstruction method. Most haze occurred in the Sichuan Basin, where the average number of haze days was 63.5 days. The haze was mainly distributed in the northeastern, central and southern areas, with most haze occurring in winter (particularly December), late autumn and early spring. The annual average number of haze days had a rising trend before 1998, and then remained relatively stable before decreasing slightly in the last two years. According to different levels of visibility, "slight haze" was most widely distributed and most frequent, with the trend rising year by year, whereas the others ("mild haze", "moderate haze" and "heavy haze") decreased after 2000. From the long-term variation characteristics of typical cities in the region, the trend in Guangan and Mianyang featured a rise in the 1980s, a sharp decrease in the 1990s, and then an increase from the turn of the 21st century, with the number of haze days in the former of these two cities being considerably greater than that in the latter. Elsewhere, the number of haze days in Leshan, Weiyuan, Nanxi and Peiling rose over the years, with Nanxi experiencing the most haze days of all the cities in the basin, the number of days soared from 93 in 1980 to 237 in 2006. By contrast, the rising trend in the number of haze days in Peiling was relatively weak, whereas in another city (Rongchang) it was strong, mainly because of a two fold difference in the dispersion coefficient between the two.
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Received: 08 March 2017
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