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Seasonal variation in surface ozone and its regional characteristics at global atmosphere watch stations in China

机译:中国全球大气监视站表面臭氧的季节性变化及其区域特征

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We investigated the seasonal and spatial ozone variations in China by using three-yearsurface ozone observation data from the six Chinese Global Atmosphere Watch (GAW) stations and tropospheric column ozone data from satellite retrieval over the period 2010–2012. It is shown that the seasonal ozone variations at these GAW stations are rather different, particularly between the western and eastern locations. Compared with western China, eastern China has lower background ozone levels. However, the Asian summer monsoon (ASM) can transport photochemical pollutants from the southern to the northern areas in eastern China, leading to a northward gradual enhancement of background ozone levels at the eastern GAW stations. Over China, the tropospheric column ozone densities peak during spring and summer in the areas that are directly and/or indirectly affected by the ASM, and the peak time lags from the south to the north in eastern China. We also investigated the regional representativeness of seasonal variations of ozone at the six Chinese GAW stations using the yearly maximum tropospheric column month as indicator. The results show that the seasonal variation characteristics of ozone revealed by the Chinese GAW stations are typical, with each station having a considerable large surrounding area with the ozone maximum occurring at the same month. Ozone variations at the GAW stations are influenced by many complex factors and their regional representativeness needs to be investigated further in a broader sense.
机译:我们通过使用来自六个中国全球气氛观察(GAW)站和来自2010 - 2012年期间的卫星检索的卫星检索的TroposhiC专栏臭氧数据来调查了中国的季节性和空间臭氧变化。结果表明,这些GAW站的季节性臭氧变化是相当不同的,特别是在西部和东部地区之间。与中国西部相比,中国东部的背景臭氧水平较低。然而,亚洲夏季季风(ASM)可以将来自中国东部北部地区的南部地区的光化学污染物运输,导致东部GAW站的背景臭氧水平北方逐步提高。在中国,在春季和夏季的地区直接和/或间接受到亚马逊的地区,以及来自中国东部的南部的高峰时间延迟的地区。我们还使用年度最大的对流层柱作为指标调查了六个中国GAW站的臭氧季节性变化的区域代表性。结果表明,中国GAW站揭示的臭氧的季节变化特性是典型的,每个车站具有相当大的周围区域,同期发生臭氧最大值。 GAW站的臭氧变化受许多复杂因素的影响,需要在更广泛的意义上进一步调查其区域代表性。

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