Calibration of a cluster of low-cost sensors for the measurement of air pollution in ambient air

Using a clustered system of sensors able to measure O
₃
, NO/NO
₂
, CO and CO
₂
, we want to compare the performance of several calibration methods. Based on the outcome of the single sensor's evaluation, the suitability of this cluster is investigated using deterministic or statistical methods such as multivariate regression and neural networks. The objective of the study is to assess if the measurement uncertainty of sensors can reach the Data Quality Objective of the European Air Quality Directive for indicative methods.