Time Series Analysis of Air Quality Index (AQI) in Beijing from 2014 to 2021

Authors

  • Yuqi Zhang

DOI:

https://doi.org/10.54097/hset.v11i.1355

Keywords:

ARIMA multiplication model, On-stationary series, Intervention analysis.

Abstract

Air problems seriously affect people's physical health, quality of life and happiness in life. Beijing as the capital of China, air quality problems should be paid more attention to. This paper analyzes the monthly data (AQI values) of air pollution in Beijing from 2014 to 2021, discusses the trend effects and seasonal effects of AQI data, constructs the ARIMA multiplication model with the highest degree of matching, and predicts the future air quality of Beijing. The results show that the air quality in Beijing from 2014 to 2021 will improve year by year, and the air quality will be better in the next three years. This paper also analyzes whether the improvement of air quality in Beijing is relevant to the document promulgated in 2018 whose name is “Beijing's Three-Year Action Plan to Win the Blue Sky Defence War”, and whether the impact is sustainable. The results show that the promulgation of the document has effectively improved the air quality in Beijing without delay effect, and we can reasonably predict that the air quality will improve further on the basis of this impact in 2022-2024.

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References

Yu Ping. Application of Time Series Analysis in Air Quality Index (AQI) Prediction. Diss. Liaoning Normal University, 2016.

Ren Huanhuan. Research on the relationship between economic development and ambient air quality in economic zones and provincial capital cities in my country from 2014 to 2017. Diss. Lanzhou University.2017.

Ma Pan et al. "Analysis and Fitting Research of Beijing AQI Based on Meteorological Conditions." The 31st Annual Meeting of the Chinese Meteorological Society. 2020.

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Published

23-08-2022

How to Cite

Zhang, Y. (2022). Time Series Analysis of Air Quality Index (AQI) in Beijing from 2014 to 2021. Highlights in Science, Engineering and Technology, 11, 142-151. https://doi.org/10.54097/hset.v11i.1355