Advantages and challenges of the implementation of a low-cost particulate matter monitoring system as a decision-making tool.

The integration of monitoring technologies in the last decades has been a key factor in the development of new ways to track air pollutants and supplementing the network of traditional monitoring systems. In this regard, the appearance of affordable and accurate sensor devices to monitor air quality has made possible to obtain relevant data about the state of the air, and moreover, eminent institutions are interested in promoting the use of novel and more affordable tools for air pollution, such as the United States Environmental Protection Agency and European institutions, within a new approach to environmental surveillance, known as Next Generation Compliance and Enforcement technologies. On other hand, in order to get more reliable measurements, the use of machine learning to support adjustment or calibration process has been used in some studies to improve the performance of monitoring devices.