Abstract. Total peroxy nitrate ( ∑ PN) concentrations have been measured using a thermal dissociation laser-induced fluorescence (TD-LIF) instrument during the BORTAS campaign, which focused on the impact of boreal biomass burning (BB) emissions on air quality in the Northern Hemisphere. The strong correlation observed between the  ∑ PN concentrations and those of carbon monoxide (CO), a well-known pyrogenic tracer, suggests the possible use of the  ∑ PN concentrations as marker of the BB plumes. Two methods for the identification of BB plumes have been applied: (1)  ∑ PN concentrations higher than 6 times the standard deviation above the background and (2)  ∑ PN concentrations higher than the 99th percentile of the  ∑ PNs measured during a background flight (B625); then we compared the percentage of BB plume selected using these methods with the percentage evaluated, applying the approaches usually used in literature. Moreover, adding the pressure threshold ( ∼  750 hPa) as ancillary parameter to  ∑ PNs, hydrogen cyanide (HCN) and CO, the BB plume identification is improved. A recurrent artificial neural network (ANN) model was adapted to simulate the concentrations of  ∑ PNs and HCN, including nitrogen oxide (NO), acetonitrile (CH₃CN), CO, ozone (O₃) and atmospheric pressure as input parameters, to verify the specific role of these input data to better identify BB plumes.