Exploring regional air pollution transition dynamics: A multi-state markov model approach

Air pollution, commonly measured by the Air Quality Index (AQI), is a significant global health risk, yet its transition dynamics remain poorly understood. This study aims to investigate the regional air pollution transition dynamics across different air quality states.

We analyzed weekly average Air Quality Index (AQI) data from January to September 2024 for 19 countries across Asia, Africa, and Europe, collected from an open-access air quality monitoring platform. According to international standards, AQI was categorized into three states (Good, Unhealthy, Very Unhealthy). We applied a multi-state Markov model to assess weekly transitions between these states and estimate the average time spent in one state before transition.

Findings indicate that in Asia and Africa, air quality tends to deteriorate more frequently than it improves, with low transition rates from "Very Unhealthy" to better states. Transitions from Unhealthy to Good were less frequent in Asia (HR: 0.09, 95% CI: 0.04, 0.19) and Africa (HR:0.25, 95% CI: 0.11, 0.55) compared to Europe, where air quality showed more stability and improvement. The Good and Unhealthy states in Asia had similar sojourn times of 6.80 (±1.77) and 6.64 (±1.38) weeks, while the Very Unhealthy state lasted 3.36 (±0.98) weeks. The Very Unhealthy state persisted for 0.95 (±0.48) weeks in Africa. Europe maintained the "Good" state longest at 7.68 (±1.98) weeks, with shorter durations for Unhealthy and Very Unhealthy states.

The study highlights lengthy pollution incidents in Asia and Africa, while Europe demonstrates effective pollution control. These insights can guide policymakers in formulating strategies to mitigate pollution based on regional AQI transition trends.