Abstract
Abstract. Organic aerosol (OA) particles are recognized as key factors influencing air quality and climate change. However, highly time-resolved long-term characterizations of their composition and sources in ambient air are still very limited due to challenging continuous observations. Here, we present an analysis of long-term variability of submicron OA using the combination of an aerosol chemical speciation monitor (ACSM) and a multiwavelength Aethalometer from November 2011 to March 2018 at a peri-urban background site of the Paris region (France). Source apportionment of OA was achieved via partially constrained positive matrix factorization (PMF) using the multilinear engine (ME-2). Two primary OA (POA) and two oxygenated OA (OOA) factors were identified and quantified over the entire studied period. POA factors were designated as hydrocarbon-like OA (HOA) and biomass burning OA (BBOA). The latter factor presented a significant seasonality with higher concentrations in winter with significant monthly contributions to OA (18 %–33 %) due to enhanced residential wood burning emissions. HOA mainly originated from traffic emissions but was also influenced by biomass burning in cold periods. OOA factors were distinguished between their less- and more-oxidized fractions (LO-OOA and MO-OOA, respectively). These factors presented distinct seasonal patterns, associated with different atmospheric formation pathways. A pronounced increase in LO-OOA concentrations and contributions (50 %–66 %) was observed in summer, which may be mainly explained by secondary OA (SOA) formation processes involving biogenic gaseous precursors. Conversely, high concentrations and OA contributions (32 %–62 %) of MO-OOA during winter and spring seasons were partly associated with anthropogenic emissions and/or long-range transport from northeastern Europe. The contribution of the different OA factors as a function of OA mass loading highlighted the dominant roles of POA during pollution episodes in fall and winter and of SOA for highest springtime and summertime OA concentrations. Finally, long-term trend analyses indicated a decreasing feature (of about −175 ng m−3 yr−1) for MO-OOA, very limited or insignificant decreasing trends for primary anthropogenic carbonaceous aerosols (BBOA and HOA, along with the fossil-fuel and biomass-burning black carbon components) and no statistically significant trend for LO-OOA over the 6-year investigated period.
Highlights
Organic aerosol (OA) particles account for a large mass fraction of submicron particulate matter (PM1) in the atmosphere (Zhang et al, 2007) and play a key role in regional air pollution and climate (Boucher et al, 2013)
The distinction between cooking OA (COA) and hydrocarbon-like OA (HOA) factors based solely on aerosol chemical speciation monitor (ACSM) measurements remains challenging due to highly similar mass spectra and uncertainties associated with the ACSM low mass spectral resolution (Petit et al, 2014; Fröhlich et al, 2015b)
Results obtained from these preliminary individual positive matrix factorization (PMF) runs showed very good consistency between them with two unconstrained oxygenated OA (OOA) factors – MO-OOA and LO-OOA – always appearing in the 4-factor and 5-factor solutions
Summary
Organic aerosol (OA) particles account for a large mass fraction of submicron particulate matter (PM1) in the atmosphere (Zhang et al, 2007) and play a key role in regional air pollution and climate (Boucher et al, 2013). Time-limited (typically, 1–2 months) measurement campaigns demonstrated that primary fine aerosols are mainly influenced there by traffic emissions all over the year and residential wood burning during cold seasons, while secondary aerosols originate from both local production and regional transport (Sciare et al, 2011; Crippa et al, 2013a, b; Petit et al, 2014; Srivastava et al, 2018b). Such a background site can be considered representative of air quality at a regional scale, including neighboring northwestern countries (Bressi et al, 2013, 2014). The geographical origins of high loadings of SOA factors were investigated using air mass back-trajectory analyses
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