Antilope, A Portable Low-Cost Sensor System for the Assessment of Indoor and Outdoor Air Pollution Exposure

Fabian Lenartz,Benjamin Bergmans,Marie Dury,Sylvain Guichaux,Virginie Hutsemékers,Christophe Brose,Valéry Broun

doi:10.3389/fsens.2021.679908

Abstract

The increasing availability of low-cost sensors and open source projects make it easier than ever for a maker to build his own air quality node. Nonetheless, depending on one’s goal and its related data quality objective, to customize an existing project or to build a specific printed circuit board may still be very useful. In the framework of the Outdoor and Indoor Exposure project, a portable mini-station has been developed, tested and then used in two experiments: exposure assessment and complementary network measurement. The present paper focuses on the description of the equipment that was designed and prototyped, as well as on the tests that were made in the lab and in the field to evaluate its overall performance and that of its different sensors. Finally, we present what we consider to be its main drawbacks and our perspectives for further development and tests.

Highlights

When we wrote the OIE (Outdoor and Indoor Exposure) project proposal in 2016, we were aware of the existence of some commercial and prototype LCSS but had only limited knowledge about their technologies and potential uses
We identified two main applications in the framework of our project: personal exposure assessment and complementary network measurement
The paper is divided as follows: in Materials and Methods section, we present the hardware and software of our ministation, in Results section, we display the preliminary results of a side-by-side exercise and a personal exposure assessment experiment and in Discussion section, we discuss the main drawbacks of our system and possible improvements

Summary

Introduction

When we wrote the OIE (Outdoor and Indoor Exposure) project proposal in 2016, we were aware of the existence of some commercial and prototype LCSS (low-cost sensor systems) but had only limited knowledge about their technologies and potential uses. We decided to design, prototype and build our own system, using commercial sensors and breakouts This approach allows us to master most of the measurement chain but requires more man power, mainly to perform data management and some maintenance operations. This approach demands an initial financial investment. We consider to have recouped it after the production of the 35th device but this strongly depends on the structure of one’s organization. Peltier et al (2020) shows an example of costs linked to the use of low-cost sensors and Karagulian et al (2019) a price comparison of various commercial sensors and LCSS

Methods

Results

Conclusion