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基于逐步回归分析方法的PM10浓度预报模型
引用本文:张云海,孙财涛,杨洪斌. 基于逐步回归分析方法的PM10浓度预报模型[J]. 环境科学与技术, 2009, 32(5)
作者姓名:张云海  孙财涛  杨洪斌
作者单位:中国气象局沈阳大气环境研究所,辽宁,沈阳,110016;中国气象局沈阳大气环境研究所,辽宁,沈阳,110016;中国气象局沈阳大气环境研究所,辽宁,沈阳,110016
基金项目:中国气象局沈阳大气环境研究所大气环境实验室项目 
摘    要:根据沈阳市2003~2005年的PM10浓度资料以及同期的气象要素资料,采用逐步回归方法建立了分季节的空气污染物PM10与气象因子的关系模型,并且利用2006年PM10资料和气象资料对模型进行了验证。结果表明:PM10预报浓度准确率和等级准确率最好的是夏秋两季,最差的是春季。春季当PM10日均浓度出现很高值时,预报结果与实测值有较大的误差,但趋势是一致的。秋季趋势的一致性不好,但波动比较小。冬季和夏季预报值与实测值的变化趋势基本上一致。

关 键 词:逐步回归  预报模型  空气污染  气象要素

PM_(10) Concentration Forecast Model Based on Stepwise Regression Analysis
ZHANG Yun-hai,SUN Cai-tao,YANG Hong-bin. PM_(10) Concentration Forecast Model Based on Stepwise Regression Analysis[J]. Environmental Science and Technology, 2009, 32(5)
Authors:ZHANG Yun-hai  SUN Cai-tao  YANG Hong-bin
Affiliation:1.Shenyang Institute of Atmospheric Environment;China Meteorology Administration;Shenyang 110016;China;2.Dandong Chemical Institute of Light Industry;Dandong 118002;China
Abstract:Based on meteorology data and PM10 concentration during 2003 to 2005,the relation seasonal model based on stepwise regression between PM10 concentration and meteorological factors was established and tested by data of 2006.Results indicated that PM10 concentration and grade can be forecasted with good accuracy in summer and fall forecast equation,and the worst accuracy was in spring forecast equation.Spring forecast value had in accordance with monitoring data but the error was a little bigger when daily PM...
Keywords:stepwise regression  forecast model  air pollution  meteorological factor  
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