AirGradient Forum

Enhanced Air Quality Monitoring in Lao PDR: Deployment of 160 AirGradient Monitors Marks Significant Advancement of Nationwide Air Quality Information

AirGradient Blog
#1

Air pollution represents a critical environmental health challenge globally, particularly in rapidly developing nations. In Lao People’s Democratic Republic (PDR), the escalating levels of air pollution necessitate robust monitoring and mitigation strategies to safeguard public health, especially that of vulnerable populations such as children. Historically, access to real-time air quality data in Lao PDR has been severely limited.

This is a companion discussion topic for the original entry at https://www.airgradient.com/blog/uniced-airgradient-lao-deployment/
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#2

This UNICEF project is one of the most exciting ones we as AirGradient have been involved in.

Not only is the impact we are having such striking but also it is such an enriching experience for the whole AirGradient team to work together with the people at UNICEF.

And this is only the beginning. We are working hard on making our monitoring hardware and air quality data platform / map much more impactful. Stay tuned for more!

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#4

Congratulations! As a NE Thailand resident, we’re often affected by neighbouring countries—and our own practices are no better than theirs, but we’ve often had to rely on NASA data to confirm the presence of such fires—so it’s great to see AirGradient expanding coverage like this. The more people know, the better. As an example, with my new outdoor installation, I recently noticed that PM2.5 quite often spikes in the middle of the night/early hours of the morning. I took this up with the local village chiefs and they confirmed that some farmers are attempting to escape detection by burning stubble at night and that they’ve even had the fire brigade out to quell fires that have gotten out of control at such times. This kind of occurrence doesn’t show up when 8 hour averages are displayed, so I support and advocate for publication of the most frequent data intervals that are feasible.