摘要
基于滇池10个监测点(1991~2010年)表层沉积物中主要污染物(Cd、Cr、Cu、Hg、Pb、Sn、Zn、TP以及KN)含量数据,利用SOM自组织映射神经网络对污染物时间演变特征进行识别.将1991~2010年分为4个阶段,1991~1995年低含量阶段;1996~2001年高含量阶段;2002~2006年含量波动阶段;2007—2010年含量回落阶段.各沉积物中污染物的变化模式不尽相同,但各类重金属含量峰值多集中出现在1996~1999年、2005~2007年2个时间段内.在污染物含量变化的时序分析基础上,参考入湖污染负荷、污染源普查数据等相关资料,分析人类活动对滇池沉积物中主要污染物的影响,发现人类活动对沉积物中污染物含量变化的影响很大,在污染物排放量大的时期,沉积物中污染物含量也会随之出现明显升高,在采取污染控制及治理措施后,沉积物中污染物含量会随之下降.
The statistical technique self-organizing maps (SOM) was applied for stages analysis of Lake Dianchi sediments, southwestern China. The dataset of nine pollutants, including Cd,Cr,Cu, Hg, Pb,Sn,Zn,TP and KN, was observed and collected for 10 monitoring sites from 1991 to 2010. The results show that the 20 years' study could be divided into 4 stages. In stage one ( 1991 to 1995 ) , concentrations of sediments are relativity low. In the second stage ( 1996 to 2001 ), concentrations of most sediments are higher than the stage before and show increasing trends. In the following stage (2002 to 2006), majority of the observed sediments exhibit fluctuation characteristics. Nevertheless, different concentration patterns exist among different pollutants, the concentration climaxes of most pollutants have been observed during the year 1996 to 1999 and 2005 to 2007. According to the relevant information gathering from yearly lake pollution load, the national survey of pollution sources etc. , the reason for the above stages and concentration patterns of observed sediments are analyzed. The result shows that sediment concentration is sensitive to human activities in the basin, such as pollution emission as well as controlling.
出处
《环境科学》
EI
CAS
CSCD
北大核心
2014年第1期194-201,共8页
Environmental Science
基金
国家自然科学基金项目(41222002)
国家水体污染控制与治理科技重大专项(2013ZX07102-006)