基于时间序列的上海市空气质量变化与污染物特征分析

Analysis of Air Quality Change and Pollutant Characteristics in Shanghai Based on Time Series

摘要: 本文收集了上海市2014年1月至2020年10月期间的空气质量与主要污染物数据的共计七项指标，在建立时间序列的基础上，采用时间序列季节模型与Holt-Winters指数平滑法对数据进行拟合，并预测未来五期数据。拟合结果表明，上海市空气质量与污染物含量长期以来呈总体下降趋势，并且具有明显的季节性周期变化特征。

Abstract: This paper collects a total of seven indicators of air quality and major pollutant data in Shanghai from January 2014 to October 2020. Based on the establishment of time series, the time series seasonal model and Holt-Winters exponential smoothing method are used to fit the data and predict the next five periods of data. The fitting results show that the air quality and pollutant content in Shanghai have shown an overall downward trend for a long time, and have obvious seasonal and periodic changes.