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微宇宙环境下藻类生长与理化因子回归研究
引用本文:梁恒,陈忠林,瞿芳术,田家宇,李圭白. 微宇宙环境下藻类生长与理化因子回归研究[J]. 哈尔滨工业大学学报, 2010, 42(6): 841-844
作者姓名:梁恒  陈忠林  瞿芳术  田家宇  李圭白
作者单位:哈尔滨工业大学城市水资源与水环境国家重点实验室;哈尔滨工业大学城市水资源与水环境国家重点实验室;哈尔滨工业大学城市水资源与水环境国家重点实验室;哈尔滨工业大学城市水资源与水环境国家重点实验室;哈尔滨工业大学城市水资源与水环境国家重点实验室
基金项目:国家自然科学基金资助项目(50808051);哈尔滨工业大学城市水资源与水环境国家重点实验室开放基金资助项目(HIT.ES200803).
摘    要:为考察水库水中藻类生长与理化因子的相关性,用微宇宙环境模拟藻类生长过程并监测理化因子变化,建立相关回归统计方程.以微宇宙环境中鱼腥藻、微囊藻和中度营养状态水体中藻类的生长为研究对象,考察藻类生长过程中理化因子的变化,建立藻生长与环境因子的线性相关矩阵,并建立相关预测方程.实验结果表明:总磷和水温是影响藻类生长显著因子;通过总磷和水温建立起的相关预测方程,能够预测水体内藻细胞浓度变化.微宇宙环境下基于理化因子所建立起的藻类生长预测方程有助于水厂准确预测藻类浓度,及时调整水处理工艺.

关 键 词:微宇宙环境  藻类生长  理化因子  回归分析

Regression equations between algae propagation and physico-chemical factors under microcosm environment
LIANG Heng,CHEN Zhong-lin,QU Fang-shu,TIAN Jia-yu and LI Gui-bai. Regression equations between algae propagation and physico-chemical factors under microcosm environment[J]. Journal of Harbin Institute of Technology, 2010, 42(6): 841-844
Authors:LIANG Heng  CHEN Zhong-lin  QU Fang-shu  TIAN Jia-yu  LI Gui-bai
Affiliation:State Key Laboratory of Urban Water Resources and Environment,Harbin Institute of Technology,Harbin 150090,China;State Key Laboratory of Urban Water Resources and Environment,Harbin Institute of Technology,Harbin 150090,China;State Key Laboratory of Urban Water Resources and Environment,Harbin Institute of Technology,Harbin 150090,China;State Key Laboratory of Urban Water Resources and Environment,Harbin Institute of Technology,Harbin 150090,China;State Key Laboratory of Urban Water Resources and Environment,Harbin Institute of Technology,Harbin 150090,China
Abstract:In order to investigate the correlation between algae propagation and physico-chemical factors for reservoir water,the algae propagation was modelled and the factors were monitored under the microcosm environment for building regression equations. The linear matrix based on the biomass of anabaena(ACD),microcystis(ACM) and algae(AC) in moderate eutrophic situation was built. Results showed that the reservoir is phosphorous-limited and relative to total phosphorous (TP) and temperature. The prediction equations based on TP and temperature can predict algae concentration variations. The prediction equations bulit under microcosm conditions can help water plants predict algae concentrations and adjust water treatment processes according to the equations’results.
Keywords:microcosm environment  algae propagation  physico-chemical factors  regression analysis
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