Abstract. Atmospheric organic vapors play essential roles in the formation of secondary organic aerosol. Source identification of these vapors is thus fundamental to understand their emission sources and chemical evolution in the atmosphere and their further impact on air quality and climate change. In this study, a Vocus proton-transfer-reaction time-of-flight mass spectrometer (PTR-TOF) was deployed in two forested environments, the Landes forest in southern France and the boreal forest in southern Finland, to measure atmospheric organic vapors, including both volatile organic compounds (VOCs) and their oxidation products. For the first time, we performed binned positive matrix factorization (binPMF) analysis on the complex mass spectra acquired with the Vocus PTR-TOF and identified various emission sources as well as oxidation processes in the atmosphere. Based on separate analysis of low- and high-mass ranges, fifteen PMF factors in the Landes forest and nine PMF factors in the Finnish boreal forest were resolved, showing a high similarity between the two sites. Factors representing monoterpenes dominate the biogenic VOCs in both forests, with less contributions from the isoprene factors and sesquiterpene factors. Particularly, various terpene reaction products were separated into individual PMF factors with varying oxidation degrees, such as lightly oxidized compounds from both monoterpene and sesquiterpene oxidations, monoterpene-derived organic nitrates, and monoterpene more oxidized compounds. These factors display similar mass profiles and diurnal variations between the two sites, revealing similar terpene reaction pathways in these forests. With the distinct characteristics of VOCs and oxygenated VOCs measured by the Vocus PTR-TOF, this study identified various primary emission sources and secondary oxidation processes of atmospheric organic vapors in the European pine forests, providing a more comprehensive understanding of gas-phase atmospheric chemistry.
Source Identification of Emission Sources
for Hydrocarbon with Backward Trajectory Model
and Statistical Methods