The biomass company Glefaran issues nocive particles to the air, close to the town of Zalla. So, we want to measure those levels of pollution by building and installing a weather/pollution station. The data collected about contamination levels will be published here, as well as meteorological data.

What is biomass?

The biomass is an organic material used as a power source. Biomass is generated after a biological process (it can be either natural or artificial), and it can be generated in four different ways: combustion, anaerobic digestion, gasification and pyrolysis. Out of all of them, Glefaran uses the combustion method to generate energy from wood, as an alternative energy source to gas or petroleum.

As good as it sounds, wood combustion generates multiple particles, some of them harmful (like NO2 or CO). Glefaran is located less than 2.5 km away from Zalla, whereas the minimum distance between such industries and inhabited towns should be around 5 kilometres.

That’s the reason we want to install multiple stations (at least one) to measure those pollution levels, and it’s the reason this web exists too, to inform about our project and to show the data we collect from those stations.


Our objective is to create and install at least one meteorological a pollution-measuring station. We will use an Arduino Uno alongside temperature, humidity, particle, etc. sensors, as well as a 3D printed case. The collected data will be sent and displayed graphically in the telemetry webpage.

What about the data?

To show the data recollected by the sensors, we use ThingSpeak. Using the ESP8266, we send the data to ThingSpeak, where the values are processed and multiple charts are generated. After that, we insert the charts in the telemetry section and we show the measured values.

Where is the sensor located?

Our sensor is located near the institute of Zalla because we are interested in knowing how the air quality is where we learn and live. We intend to locate another sensor and we will probably put it in a strategic point: in the Town Hall, in the library, etc.

Here’s a map of the location of the first sensor.