Chemical characterization of biogenic SOA generated from plant emissions under baseline and stressed conditions: inter- and intra-species variability for six coniferous species

Abstract

Abstract. The largest global source of secondary organic aerosol in the atmosphere is derived from the oxidation of biogenic emissions. Plant stressors associated with a changing environment can alter both the quantity and composition of the compounds that are emitted. Alterations to the biogenic VOC profile could impact the characteristics of the SOA formed from those emissions. This study investigated the impacts of one global change stressor, increased herbivory, on the composition of SOA derived from real plant emissions. Herbivory was simulated via application of methyl jasmonate, a proxy compound. Experiments were repeated under pre- and post-treatment conditions for six different coniferous plant types. VOCs emitted from the plants were oxidized to form SOA via dark ozone-initiated chemistry. The SOA particle size distribution and chemical composition were measured using a scanning mobility particle sizer (SMPS) and Aerodyne high-resolution time-of-flight aerosol mass spectrometer (HR-AMS), respectively. The aerosol mass spectra of pre-treatment biogenic SOA from all plant types tended to be similar with correlations usually greater than or equal to 0.90. The presence of a stressor produced characteristic differences in the SOA mass spectra. Specifically, the following m/z were identified as a possible biogenic stress AMS marker with the corresponding HR ion(s) shown in parentheses: m/z 31 (CH3O+), m/z 58 (C2H2O2+, C3H6O+) m/z 29 (C2H5+), m/z 57 (C3H5O+), m/z 59 (C2H3O2+, C3H7O+), m/z 71 (C3H3O2+, C4H7O+), and m/z 83 (C5H7O+). The first aerosol mass spectrum of SOA generated from the oxidation of the plant stress hormone, methyl jasmonate, is also presented. Elemental analysis results demonstrated an O:C range of baseline biogenic SOA between 0.3–0.47. The O:C of standard methyl jasmonate SOA was 0.52. Results presented here could be used to help identify a biogenic plant stress marker in ambient datasets collected in forest environments.