“两尘四气”空气污染数据的校准模型

Calibration Model of Air Pollution Data "Two Dusts and Four Gases"

通过Excel软件对监测点收集的空气质量数据进行拆分及构造函数的方法,拟合了“两尘四气”的六个方程,这些方程可用于对自建点数据进行校准。在对所收集的数据标准化后,利用SPSS软件对“两尘四气”数据误差产生的原因进行回归分析,建立了多元线性回归方程。方程显示:压强、温度和风速更容易导致自建点数据误差,可使用对上述三种因素不敏感的材质制造检测仪的传感器。以上使用Excel和SPSS软件对大数据进行比对处理及建模的方法可用于环境监测、农业生产等领域促进高质量生态文明建设。

In this paper,by using Excel software to split and construct air quality data,six equations of "two dust and four gas" were fitted to calibrate the data of self-built points.After data standardization,multiple regression of SPSS software was used to conduct regression analysis on the causes of data errors of "two dusts and four gas",and a multiple linear regression equation was established.The equation showed that the pressure,temperature and wind speed have great influence on the error,and the sensor can be made with materials insensitive to the above three factors.The above data processing and modeling methods using Excel and SPSS software can be used in fields such as atmospheric environmental protection and agricultural production to promote high-quality ecological progress.