| 基于因子分析法的宝鸡市PM10污染四季预报 |
| |
| 引用本文： | 周变红,陈卫东.基于因子分析法的宝鸡市PM10污染四季预报[J].宝鸡文理学院学报(自然科学版),2008,28(4):319-323. |
| |
| 作者姓名： | 周变红 陈卫东 |
| |
| 作者单位： | 宝鸡文理学院,灾害监测与机理模拟陕西省重点实验室,陕西,宝鸡,721013;西安建筑科技大学,环境与市政工程学院,陕西,西安,710055;宝鸡市气象局,陕西,宝鸡,721006 |
| |
| 基金项目： | The key research project of Baoji University of Arts&Sciences(ZK0797);;The Shaanxi Province key branch of natural geography |
| |
| 摘 要： | 目的以宝鸡市2003年3月1日-2006年2月28目的4个监测点的逐日PM10浓度监测值以及宝鸡市同期的地面气象要素监测值为研究对象，进行宝鸡市PM10污染四季预报研究。方法采用因子分析法，按春、夏、秋、冬四季分别建立PM10污染预报模型。结果通过四季气象要素的因子分析，春季、夏季、秋季、冬季的相关系数矩阵中各提取7个、8个、6个、7个公共因子，分别解释了原有变量总方差的85．779％、86．986％、88．693％、85．389％，总体上，原有变量的信息丢失较少，使用因子分析较为理想。结论由因子分析法建立的宝鸡市PM10污染浓度四季预报方程的准确率达到了81．70％、81．48％、78．19％、75．67%，等级命中率为100％，对宝鸡市空气中PM10的污染的控制与治理有一定的借鉴意义。
|
| 关 键 词： | PM10浓度 因子分析法 四季预报模型 |
The seasons forecast of PM_(10) pollution in Baoji City based on factorial analysis |
| |
| ZHOU Bian-hong,CHEN Wei-dong.The seasons forecast of PM_(10) pollution in Baoji City based on factorial analysis[J].Journal of Baoji College of Arts and Science(Natural Science Edition),2008,28(4):319-323. |
| |
| Authors: | ZHOU Bian-hong CHEN Wei-dong |
| |
| Institution: | 1.Key Lab.Disaster Monitoring and Mechanism Simulating of Shaanxi Province;Baoji Univ.Arts & Sci.;Baoji 721013;Shaanxi;China;2.School of Environmental and Municipal Engineering;Xi'an University of Architecture and Technology;Xi'an 710055;3.Baoji Administration Bureau;Baoji 721006;China |
| |
| Abstract: | Aim Taking the daily PM10 concentration observed values from 4 sampling spots in Baoji City,Shaanxi,China from Mar.2003 to Feb.2006 and the meteorological element observed values during the corresponding three years as study object,the paper studies the PM10 concentration pollution forecast in Baoji City.Methods Applying factorial analysis,the paper respectively establishes forecast models for the seasons from Mar.2003 to Feb.2006.Results Extracted the factors from the four seasons: seven,eight,six and seve... |
| |
| Keywords: | PM10 concentration factorial analysis the four seasons of forecast model |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
