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中国农学通报 ›› 2015, Vol. 31 ›› Issue (14): 200-205.doi: 10.11924/j.issn.1000-6850.casb14110162

所属专题: 农业气象

• 资源 环境 生态 土壤 气象 • 上一篇    下一篇

近10年尺度成都市空气污染指数变化小波分析

谭 壮1,谭亚玲2,罗明良1,张 颖1,张 斌1   

  1. (1西华师范大学国土资源学院,四川南充 637009;2西华师范大学校医院,四川南充 637009)
  • 收稿日期:2014-11-26 修回日期:2015-03-02 接受日期:2015-03-24 出版日期:2015-06-02 发布日期:2015-06-02
  • 通讯作者: 罗明良
  • 基金资助:
    国家自然科学基金项目“基于DEM的黄土高原流域侵蚀基准体系研究”(41101348);四川省科技厅应用基础规划项目“基于DEM的川东丘陵区地面光热资源模拟研究”(2010JY0089);西华师范大学教学改革项目“师范院校地理信息科学专业人才培养三三制的探索”(403265)。

Wavelet Analysis of API Changes of Chengdu About 10 Years

Tan Zhuang1, Tan Yaling2, Luo Mingliang1, Zhang Ying1, Zhang Bin1   

  1. (1College of Land and Resource, China West Normal University, Nanchong Sichuan 637009;2The Hospital, China West Normal University, Nanchong Sichuan 637009)
  • Received:2014-11-26 Revised:2015-03-02 Accepted:2015-03-24 Online:2015-06-02 Published:2015-06-02

摘要: 为了找出成都市空气污染的变化规律与影响因素,为空气污染治理提供依据。基于一维连续Meyer小波,对2000年6月底以来近10年成都市逐日空气污染指数(air pollution index, API)的时间序列进行小波分析,得到该市API时间序列的多尺度变化特征、主周期,对影响因素进行了分析。结果表明:成都市API“高—低”交替演化规律明显,主周期约320天,次周期约120天;受盆地地形与气候等条件影响,大气污染呈“冬重夏轻”格局,春季污染次高峰常伴随北方沙尘暴而产生;成都市10年来大气污染状况总体趋向于好转,但局部时段污染加重的现象时有发生。结果表明,小波变换分析对于研究API时间序列的变化规律非常有效,也适用于其他污染物的时间演变规律的研究。

关键词: 土壤, 土壤, 重金属, 生态风险评价

Abstract: The paper aims to find out the multiscale variations and influencing factors of air pollution in Chengdu, and to provide evidence for air pollution control. The time series of daily Air Pollution Index (API) in Chengdu for the past decade was obtained, the primary period of API time series was analyzed by using continuous Meyer wavelet transformation, and then the influencing factors were discussed. The results showed that API varied at diverse timescales with periodic ‘high-low’ fluctuations. The primary period of the daily variations was around 320 days and the secondary period was around 120 days. Due to topographical conditions, API was serious in winter and light in summer in most scales. A secondary peak often occurred in spring which was affected by the sand-dust in north China, the inflection points of serious to light API each year were the vernal and autumnal equinoxes. The general status of air pollution tended to be getting better during the last 10 years in Chengdu, while serious air pollution sometimes occurred because of the rapid economic development. Wavelet analysis is an effective method to study the variation of API time series and the multiscale variations of other pollutants.