Impact of biomass burning emission on total peroxy nitrates: fire plume identification during the BORTAS campaign
Eleonora Aruffo1,2,Fabio Biancofiore1,Piero Di Carlo1,2,a,Marcella Busilacchio1,Marco Verdecchia1,2,Barbara Tomassetti1,2,Cesare Dari-Salisburgo1,Franco Giammaria1,Stephane Bauguitte3,James Lee4,Sarah Moller4,James Hopkins4,Shalini Punjabi4,Stephen J. Andrews4,Alistair C. Lewis4,Paul I. Palmer5,Edward Hyer6,Michael Le Breton7,and Carl Percival7Eleonora Aruffo et al.Eleonora Aruffo1,2,Fabio Biancofiore1,Piero Di Carlo1,2,a,Marcella Busilacchio1,Marco Verdecchia1,2,Barbara Tomassetti1,2,Cesare Dari-Salisburgo1,Franco Giammaria1,Stephane Bauguitte3,James Lee4,Sarah Moller4,James Hopkins4,Shalini Punjabi4,Stephen J. Andrews4,Alistair C. Lewis4,Paul I. Palmer5,Edward Hyer6,Michael Le Breton7,and Carl Percival7
Received: 11 Feb 2016 – Discussion started: 21 Mar 2016 – Revised: 29 Sep 2016 – Accepted: 11 Oct 2016 – Published: 23 Nov 2016
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.
During the BORTAS aircraft campaign, we measured NO2 and their oxidtation products (as peroxy nitrates) with a custom laser-induced fluorescence instrument. Because of the high correlation between known pyrogenic tracers (i.e., carbon monoxide) and peroxy nitrates, we provide two methods to use these species for the identification of biomass burning (BB) plumes. Using an artifical neural network, we improved the BB identification taking into account of a meteorological parameter (pressure).
During the BORTAS aircraft campaign, we measured NO2 and their oxidtation products (as peroxy...