Enviro+
FeatherWing
PIM502
Care about air with Enviro+ FeatherWing. It's packed full of
environmental sensors that'll get you started in the world of
citizen science. Monitor weather, light level, noise pollution, and
air quality, in your local area and contribute your data to better
understand trends in air pollution.
Note: you'll need a Feather board to go with this FeatherWing. We'd recommend
the Feather M4 Express or Feather nRF52840 Express.
Tiny, feature-packed
Enviro+ FeatherWing is no larger than a couple of pound coins side-by-side, but it's
absolutely jam-packed with sensors. It has all the great features of the larger Enviro+ for
Raspberry Pi—a weather sensor, light sensor, microphone, gas and particulate sensing*,
and a gorgeous, colour LCD—but it's built for Adafruit's range of low-power Feather
boards that run CircuitPython.
Measure temperature, pressure, and humidity with the BME280 weather sensor; measure
light level with the LTR-559 light and proximity sensor; detect a range of pollutant gases
with the MICS6814 analog gas sensor; measure ambient noise level with the analog
MEMS microphone. Connect up a PMS5003 particulate matter (PM) sensor (*available
separately) and you can measure air quality too!
Enviro+ FeatherWing features
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BME280 temperature, pressure, humidity sensor (datasheet)
LTR-559 light and proximity sensor (datasheet)
MICS6814 analog gas sensor (datasheet)
ADS1015 analog to digital converter (ADC) (datasheet)
MEMS microphone (datasheet)
0.96" colour LCD (160x80)
Connector for particulate matter (PM) sensor (available separately)
FeatherWing format board
Includes two 1x16 male headers
Requires soldering
CircuitPython library
Schematic
Dimensions: 51x23x6.5mm (without headers attached)
Care about air!
Enviro+ FeatherWing is the smaller sibling to the Enviro+ for Raspberry Pi, developed in
collaboration with the University of Sheffield, with the aim of letting you contribute realtime air quality data from your local area to open data projects like Luftdaten.
The alarming drop in our air quality is something that's really important to understand.
Devices like Enviro+ FeatherWing allow fine-grained, detailed datasets that let us see
shifts in air quality through time and across different areas of cities. The more devices
that contribute data, the better quality the dataset becomes.
Particulate matter (PM) is made up of tiny particles that are a mix of sizes and types, like
dust, pollen, mould spores, smoke particles, organic particles and metal ions, and more.
Particulates are much of what we think of as air pollution. They can be measured, in size
and quantity, by particulate matter sensors like the PMS5003 that you can connect to
Enviro+ FeatherWing.
The analog gas sensor can be used to make qualitative measurements of changes in gas
concentrations, so you can tell broadly if the three groups of gases are increasing or
decreasing in abundance. Without laboratory conditions or calibration, you won't be able
to say "the concentration of carbon monoxide is n parts per million", for example.
Temperature, air pressure and humidity can all affect particulate levels (and the gas
sensor readings) too, so the BME280 sensor on Enviro+ FeatherWing is really important
to understanding the other data that it outputs.
Software
We've built a CircuitPython library just for Enviro+ FeatherWing, with support for all
the bits and bobs on it. We've also put together
thorough examples and documentation to help you to understand how to use it, and to
give you some ideas on how to take it further.
Have a good read through the documentation. It walks through everything you'll need in
terms of libraries, and tells you how to use all of the various functions of the library.
https://shop.pimoroni.com/products/enviro-plus-featherwing/11-4-20
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