文献类型：会议论文

英文题名：Construction and Application of a Mathematical Model for Air Quality Data Calibration Based on Time Series Analysis Method

作者：Liu, Xiaoyu[1]; Hu, Zhengkun[1]; Chen, Zhansheng[1]

第一作者：刘晓宇

机构：[1] College of Applied Science and Technology, Beijing Union University, Beijing, 100012, China

第一机构：北京联合大学应用科技学院

会议论文集：12th International Symposium on Project Management, ISPM 2024

会议日期：June 28, 2024 - June 30, 2024

会议地点：Beijing, China

语种：英文

外文关键词：Air pollution control - Air quality - Data quality - Network security - Time series

摘要：Air pollution is a great hazard to the ecosystems, climate and human health. Therefore, it is of great research significance to fully utilize the accuracy of " national monitor stations " and the economy of " locality control points " to monitor the concentration of "two dust and four gases" (PM2.5, PM10, CO, NO2, SO2, O3) in real time. Firstly, SPSS was used to perform correlation analysis on the parameters, and it was found that PM2.5 and PM10 have a strong correlation (0.816), while PM2.5, PM10, and CO have a strong correlation (0.662/0.582). Secondly, taking the collection time of national monitor stations as a reference, the data of locality control points was first screened and organized, and then the time offset processing of the self-built points data was conducted, and the correlation between national monitor stations and locality control points data was established with time as a link. Thirdly, based on the periodic characteristics of the data difference between the national monitor stations and the locality control points and the continuity of the data collected from the locality control points, the locality control points data was calibrated by using SPSS tools and ARIMA, a time series analysis method. According to the results of several models, over 83% of R2>0.75, with a maximum value of 0.976, indicating a high degree of fit. This indicated that the model was reasonable and can achieve good calibration results. ? 2024 ISPM. All Rights Reserved.