Test Chamber for Particulate Matter Sensors Measurements in Controlled Environment Through a Python GUI

The lifestyle of humankind in recent years has resulted in inordinate levels of air pollution. This has generated a trend in the design and manufacture of portable, personal and fixed-site PM monitoring systems to prevent exposure to air pollutants. However, these devices still need to be improved and properly evaluated to compete with environmental monitors on the market. In this work, a test chamber with controlled environmental conditions was developed for the evaluation of low cost portable and personal PM sensors. The developed system guarantees quick evaluation tests spanning from seconds to hours, to corroborate prolonged operation and correct calibration. It is controlled by a Python-based graphical user interface (GUI). The prototype ensures the recording of PM, altitude, relative humidity, atmospheric pressure, luminescence, and temperature measurements. Thirty measurement tests were carried out to ensure robust performance and data transfer. Thereafter, three tests were conducted to measure PM2.5 using burned wood smoke. In the aforementioned tests, Pearson correlation (r) analyses between two commercial PM personal monitors and a low cost PM test sensor were done. Rvalues over 0.98 were obtained in all the tests. This device could help evaluate the developed sensors to determine if the equipment meets appropriate calibration.

I. Introduction

Nowadays, many of the activities of daily life such as the use of electricity at home depends mostly on non-renewable fuel power plants (coal, natural gas, etc.) [1]. However, these technologies generate harmful residues which are introduced into the atmosphere causing adverse effects on human health and the environment. Currently, air pollution in urban areas has a dynamic and complex behavior, being caused by a mixture of natural and anthropogenic (human-made) pollutant sources [2]. The most common air pollutants found are: particulate matter (PM) which includes PM₁₀ (aerodynamic diameter ≤ 10 micrometers) and PM_2.5 (aerodynamic diameter ≤ 2.5 micrometers), ozone (O₃), sulfur dioxide (SO₂), nitrogen oxides (NO_x), carbon monoxide (CO) and lead [3]. Air pollution attributed deaths in 2019 were estimated to be approximately 6.7 million worldwide [4]. To determine the concentration levels and of pollutants with the highest concentration levels in each locality, a PM monitoring is necessary [3], [5], [6]. In addition, PM₁₀ and PM_2.5 are considered highly harmful to health. Furthermore, due to its size, PM_2.5 can easily enter the respiratory system and subsequently cause cardiovascular problems by inducing an inflammatory condition in the system or affecting the autonomic nervous system [7]. Therefore, it is important to monitor and take care of PM exposure using personal monitor PM sensors. However, a disadvantage of personal systems for PM monitoring is the high acquisition cost, complex calibration process requiring shipment of equipment, process delay, and additional costs.