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2016~2018年中国城市臭氧浓度时空聚集变化规律
引用本文:周明卫,康平,汪可可,张小玲,胡成媛.2016~2018年中国城市臭氧浓度时空聚集变化规律[J].中国环境科学,2020,40(5):1963-1974.
作者姓名:周明卫  康平  汪可可  张小玲  胡成媛
作者单位:成都信息工程大学大气科学学院, 高原大气与环境四川省重点实验室, 四川 成都 610225
基金项目:国家重点研发计划项目(2018YFC0214001,2018YFC0214002);四川省重大科技专项课题(2018SZDZX0023);四川省科技计划重大前沿项目(2018JY0011);四川省教育厅理科重点项目(18ZA0086)
摘    要:为揭示中国O3浓度的时空格局及聚集变化规律,通过对2016~2018年全国338个城市1144个监测站点的O3浓度观测数据,使用空间插值及空间自相关等方法进行分析研究.结果表明:2016~2018年全国O3浓度(第90百分位数)总体呈现上升趋势(由2016年的141.54μg/m3上升到2018年的153.21μg/m3),污染态势逐年加重,且华北及长江中下游等人口稠密地区O3浓度最高,O3浓度的空间分布呈现显著的聚集性和相似性规律,且聚集性逐年增强,O3浓度的年聚集区主要呈现北高南低的分异,高高值聚集区主要集中在北方(城市占比22.19%~29.59%),低低值聚集区则主要集中在南方(城市占比15.98%~22.19%),此外,O3浓度高高值聚集区与低低值聚集区空间分布的季节变化规律以顺时针周期性变化为主:3a来,春季集聚区分布与年集聚情况相同,夏季高高值,低低值聚集区逐渐向西扩大聚集范围,秋季则顺时针转变为东高西低的分异情况,随后高高值(低低值)聚集区沿顺时针方向南(北)移动,到冬季则转变为南高北低的空间分异情况.

关 键 词:臭氧  空间自相关  聚集变化  时空特征  
收稿时间:2019-10-14

The spatio-temporal aggregation pattern of ozone concentration in China from 2016 to 2018
ZHOU Ming-wei,KANG Ping,WANG Ke-ke,ZHANG Xiao-ling,HU Cheng-yuan.The spatio-temporal aggregation pattern of ozone concentration in China from 2016 to 2018[J].China Environmental Science,2020,40(5):1963-1974.
Authors:ZHOU Ming-wei  KANG Ping  WANG Ke-ke  ZHANG Xiao-ling  HU Cheng-yuan
Institution:Plateau Atmosphere and Environment Key Laboratory of Sichuan Province, School of Atmospheric Sciences, Chengdu University of Information Technology, Chengdu 610225, China
Abstract:In order to reveal the spatio-temporal aggregation pattern of O3, the observation data of O3 concentration from 1144 monitoring stations in 338 cities of China was analyzed by using spatial interpolation and spatial self-correlation during 2016 to 2018. The results indicated an overall upward trend of O3 concentration (90 percentile) in China (from 141.54µg/m3 in 2016 to 153.21µg/m3 in 2018). The O3 concentration was the highest in densely populated areas such as North China, the middle and lower reaches of the Yangtze River. The spatial distribution of O3 concentration showed a significant clustering pattern and similarity characteristic. And the clustering and similarity characteristic increased from 2016 to 2018. There was a differentiation from the north to the south of the annual cluster zones, which was presented in the form of the high-value cluster zones in the north while the low-value ones in the south. The high-value cluster zones were located in North China (22.19%~29.59%), while the low-value zones were located in South China (15.98%~22.19%). In addition, seasonally, the cluster pattern of high-value and low-value zones of O3 concentration showed an evidently periodical clockwise variation. Over the three years, the spring cluster zones were identical to the annual ones. In summer, both high-value zones and low-value zones had gradually expanded towards the west. While in autumn, the cluster pattern differentiated from the east to the west changed by a clockwise-shift, after which the high-value zones (the low-value zones) move toward south (north) gradually by a clockwise-shift. In winter, the cluster zones differentiated from the north to the south, in the pattern of the high-value cluster zones in the south while the low-value ones in the north.
Keywords:ozone  space self-correlation  aggregation change  temporal and spatial characteristics  
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