# Significant Impact of Rossby Waves on Air Pollution Detected by Network Analysis

## TL;DR

This study uses network analysis to reveal that Rossby waves significantly influence daily air pollution variability by affecting atmospheric stability and wind patterns, highlighting their impact on human health and potential climate change effects.

## Contribution

Developed a multi-layered network analysis method to identify Rossby waves as key drivers of air pollution fluctuations in China and the USA.

## Key findings

- Rossby waves significantly impact air pollution fluctuations.
- Development of cyclone and anticyclone systems affects local air stability.
- Arctic warming may slow Rossby waves, increasing health risks.

## Abstract

Air pollution is associated with human diseases and has been found to be related to premature mortality. In response, environmental policies have been adopted in many countries, to decrease anthropogenic air pollution for the improvement of long-term air quality, since most air pollutant sources are anthropogenic. However, air pollution fluctuations have been found to strongly depend on the weather dynamics. This raises a fundamental question: What are the significant atmospheric processes that affect the local daily variability of air pollution? For this purpose, we develop here a multi-layered network analysis to detect the interlinks between the geopotential height of the upper air (~5 km) and surface air pollution in both China and the USA. We find that Rossby waves significantly affect air pollution fluctuations through the development of cyclone and anticyclone systems, and further affect the local stability of the air and the winds. The significant impacts of Rossby waves on air pollution are found to underlie most of the daily fluctuations in air pollution. Thus, the impact of Rossby waves on human life is greater than previously assumed. The rapid warming of the Arctic could slow down Rossby waves, thus increasing human health risks. Our method can help to determine the risk assessment of such extreme events and can improve potential predictability.