For 2 days, from 7 to 8 April 2023, 16 cities in Thailand and Laos had PM2.5 at least twice their usual for the time of year. The worst reading was Mae Sai, Chiang Rai, Thailand: 345.0 µg/m³ on 7 April, about 4.5× its usual 76.4.
No cause namedWe have no fire or smoke records for these days, so we only say what the measurements show.
Cities reached16in 2 countries
Days27 to 8 April 2023
Worst day7 April14 cities counted
Furthest above usual4.5×Mae Sai
Day by day
Every measured city in the area, coloured by its PM2.5 that day; a dark ring marks a city at twice its usual or more. Bars: cities counted each day, coloured by their median level. Choose a day or press play; without JavaScript, the days link to that day's world ranking.
How it spread
Every counted city, in the order the episode reached them, 3 days before to 3 after. Each square is a day, coloured by that day's PM2.5; outlined: at twice the city's usual or more.
Daily means in µg/m³, over the days each city counted in this episode. Highest: its highest of those days. Usual: the city's median for the time of year of that day (its days within 21 days of the date, every year, leaving out the week around it). Above usual: its highest day against that, with a usual under 5 µg/m³ taken as 5.
Against other episodes in Thailand and Laos
Number 13 of 23 episodes in Thailand and Laos since our records began, by cities reached.
Bars: cities reached; colour: the level of the episode's highest daily reading. All 23.
Use this page
SmogRank, Northern Thailand and Laos, April 2023: 16 cities with PM2.5 at twice their usual or more, 7 to 8 April 2023, smogrank.com/episodes/2023-04-northern-thailand-and-laos (accessed 4 October 2026).
You're welcome to reuse a single chart, image or figure with this citation and a link. Terms.
An episode is a run of days when many cities close to each other (four or more within 350 km on a day, 8 or more in all) each had a daily PM2.5 mean of at least 25 µg/m³ and at least 2 times their usual for that time of year. Found in our own measurements, not picked by hand. How we find episodes. Values are each city's daily mean of its own monitors; causes are the usual kinds for a pattern like this, not a confirmed source.
