Abstract
Secondary organic aerosol (SOA) is one of the least understood constituents of fine particles; current widely-used models cannot predict its loadings or oxidation state. Recent laboratory experiments demonstrated the importance of several new processes, including aging of SOA from traditional precursors, aging of primary organic aerosol (POA), and photo-oxidation of intermediate volatility organic compounds (IVOCs). However, evaluating the effect of these processes in the real atmosphere is challenging. Most models used in previous studies are over-simplified and some key reaction trajectories are not captured, and model parameters are usually phenomenological and lack experimental constraints. Here we comprehensively assess the effect of organic aerosol (OA) aging and intermediate-volatility emissions on regional-scale OA pollution with a state-of-the-art model framework and experimentally constrained parameters. We find that OA aging and intermediate-volatility emissions together increase OA and SOA concentrations in Eastern China by about 40% and a factor of 10, respectively, thereby improving model-measurement agreement significantly. POA and IVOCs both constitute over 40% of OA concentrations, and IVOCs constitute over half of SOA concentrations; this differs significantly from previous apportionment of SOA sources. This study facilitates an improved estimate of aerosol-induced climate and health impacts, and implies a shift from current fine-particle control policies.
Highlights
The overall organic gas emissions[9,10,11]. All of these new processes could lead to elevated secondary organic aerosol (SOA) levels and oxidation state, but they are not accounted for in most chemical transport models (CTMs); inclusion can help explain the differences between model predictions and measurements
We simulated a series of SOA formation smog-chamber experiments with a 2D-VBS box model to determine the 2D-VBS parameters that agree best with measurements; there optimal parameters are subsequently used in three-dimensional CTMs
Based on simulation results for toluene (10 experiments), α-pinene (6 experiments), pentadecane and C13 linear oxygenated precursors (6 experiments)[32], we propose to use two parallel layers of the 2D-VBS in CTMs to simulate the aging of SOA derived from anthropogenic NMVOCs (AVOCs) and biogenic NMVOCs (BVOCs)
Summary
Having assessed the overall effect of OA aging and intermediate-volatility emissions, we will evaluate the effect of individual processes, including aging of SOA derived from AVOCs and BVOCs, aging of POA, and photo-oxidation of IVOCs. The differences between the contributions of individual precursor classes (AVOCs, BVOCs, POA, and IVOCs) to OA concentrations derived from CMAQv5.0.1 and the High-Yield VBS (Fig. 4, Supplementary Table 7,8, Supplementary Section 4) represent the impact of these individual processes. Cappa et al.[28] showed that accounting for vapor wall losses leads to substantial increases in the simulated SOA concentrations from NMVOCs by factors of 2–5 and 5–10 for the low and high vapor wall-loss rate scenarios, respectively This should not alter our main conclusions that OA aging and intermediate-volatility emissions greatly increase SOA concentrations, and that IVOCs and POA make a substantial contribution to SOA concentrations.
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