# Investigation of the Relationship Between the Air Pollution and Solar   Activity

**Authors:** Chengming Tan (1,2,3), Baolin Tan (1,2,3), Bisong Liu (4) ((1) CAS Key, Laboratory of Solar Activity, National Astronomical Observatories of Chinese, Academy of Sciences, Beijing, China, (2) Sate Key Laboratory of Space, Weather, Chinese Academy of Sciences, Beijing, China, (3) School of Astronomy, and Space Sciences, University of Chinese Academy of Sciences, Beijing,, China, (4) Beidou Intelligence Information, Network Technology Limited, Company, Beijing, China)

arXiv: 1706.06864 · 2017-06-22

## TL;DR

This study explores the weak and indirect relationship between solar activity and air pollution on Earth from 2000 to 2016, using various correlation analyses to identify patterns and potential influences.

## Contribution

It provides a comprehensive analysis of the correlation between solar activity indicators and air pollution indices, highlighting the complex and weak nature of their relationship.

## Key findings

- Higher air pollution cities show increased API with rising SSN up to a point
- Lower pollution cities exhibit lower correlation between API and SSN
- Solar activity influences Earth's atmosphere indirectly affecting air quality

## Abstract

How did the Sun affect the air pollution on the Earth? There are few papers about this question. This work investigates the relationship between the air pollution and solar activity by using the geophysical and environmental data during the period of 2000-2016. It is quite certain that the solar activity may impact on the air pollution, but the relationship is very weak and indirect. The Pearson correlation, Spearman rank correlation, Kendalls rank correlation, and conditional probability were adopted to analyze the air pollution index (API), air quality index (AQI), sunspot number (SSN), radio flux at wavelength of 10.7 cm (F10.7), and total solar irradiance (TSI). The analysis implies that the correlation coefficient between API and SSN is weak ($-0.17<r<0.32$) with complex variation. The main results are: (1) For cities with higher air pollution, the probability of high API will be increased along with SSN, then reach to a maximum, and then decreased; (2) For cities with lower air pollution, the API has lower correlation with SSN; (3) The relationship between API and F10.7, or API and TSI are also similar as API and SSN. The solar activities take direct effect on TSI and the energetic particle flux, and indirect and long-term effect on lower atmosphere and weather near the Earth. All of these factors contribute to the air pollution on the Earth.

## Full text

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## Figures

7 figures with captions in the complete paper: https://tomesphere.com/paper/1706.06864/full.md

## References

13 references — full list in the complete paper: https://tomesphere.com/paper/1706.06864/full.md

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Source: https://tomesphere.com/paper/1706.06864