苏州市空气质量的时间序列变化过程研究  

Change Process of Time Series in Air Quality of Suzhou

作　　者：黄进[1] 张金池[1] 

机构地区：[1]南京林业大学,江苏南京210037

出　　处：《环境科学与技术》2009年第6期49-52,共4页Environmental Science & Technology

基　　金：国家"十一五"科技支撑项目(2006BAD03A16)

摘　　要：城市空气质量水平是以空气质量指数(API)来表征的,API的时空变化可以反映城市空气质量的变化过程。文章以苏州市2002～2007年各月API值为研究对象,将其构成一组时间序列,采用时间序列理论中的小波分析原理和差分自回归滑动平均模型(ARIMA)原理对这组API序列进行趋势的辨识和数值预测,结果表明(1)苏州市近年来的空气质量水平不断提高,并将稳定保持在一个良好的水平上;(2)差分自回归滑动平均模型ARIMA(2,2,2)在拟合该地区API值时间尺度上的变化趋势效果较好,能够较好的预测苏州市月空气质量水平。Urban air quality level is token by air quality index（API）, whose spatio-temporal change can reflect the change of urban air quality. Based on the analysis of monthly API of Suzhou City, Jiangsu Province in 2002-2007, wavelet analysis and auto regressive integrated moving average （ARIMA） principle of time series theory were used to differentiate and forecast the series of time, and results indicated that air quality of the City is improving continually, and keeps in a favorable level. Model ARIMA （2,2,2） which had better effect in fitting the change trend of the City under the time scale can better forecast the monthly level of air quality.

关 键 词：空气质量指数 小波分析 差分自回归滑动平均模型 时间序列 

分 类 号：X131.1[环境科学与工程—环境科学]