Modeling the formation and composition of secondary organic aerosol from diesel exhaust using parameterized and semi-explicit chemistry and thermodynamic models

Sailaja Eluri,Beth Friedman,Delphine K Farmer,Christopher D Cappa,Shantanu H Jathar

doi:10.5194/acp-18-13813-2018

Sailaja Eluri, Beth Friedman + Show 3 more

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https://doi.org/10.5194/acp-18-13813-2018

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Abstract

Abstract. Laboratory-based studies have shown that combustion sources emit volatile organic compounds that can be photooxidized in the atmosphere to form secondary organic aerosol (SOA). In some cases, this SOA can exceed direct emissions of primary organic aerosol (POA). Jathar et al. (2017a) recently reported on experiments that used an oxidation flow reactor (OFR) to measure the photochemical production of SOA from a diesel engine operated at two different engine loads (idle, load), two fuel types (diesel, biodiesel), and two aftertreatment configurations (with and without an oxidation catalyst and particle filter). In this work, we used two different SOA models, the Volatility Basis Set (VBS) model and the Statistical Oxidation Model (SOM), to simulate the formation and composition of SOA for those experiments. Leveraging recent laboratory-based parameterizations, both frameworks accounted for a semi-volatile and reactive POA; SOA production from semi-volatile, intermediate-volatility, and volatile organic compounds (SVOC, IVOC and VOC); NOx-dependent parameterizations; multigenerational gas-phase chemistry; and kinetic gas–particle partitioning. Both frameworks demonstrated that for model predictions of SOA mass to agree with measurements across all engine load–fuel–aftertreatment combinations, it was necessary to model the kinetically limited gas–particle partitioning in OFRs and account for SOA formation from IVOCs, which were on average found to account for 70 % of the model-predicted SOA. Accounting for IVOCs, however, resulted in an average underprediction of 28 % for OA atomic O : C ratios. Model predictions of the gas-phase organic compounds (resolved in carbon and oxygen space) from the SOM compared favorably to gas-phase measurements from a chemical ionization mass spectrometer (CIMS), substantiating the semi-explicit chemistry captured by the SOM. Model–measurement comparisons were improved on using SOA parameterizations corrected for vapor wall loss. As OFRs are increasingly used to study SOA formation and evolution in laboratory and field environments, models such as those developed in this work can be used to interpret the OFR data.

Highlights

Combustion-related aerosols are an important contributor to urban and global air pollution and have impacts on climate (Pachauri et al, 2014) and human health (Anderson et al, 2012)
The calculations were performed for two different initial particle sizes (10 and 100 nm) since the condensation of secondary organic aerosol (SOA) mass would grow the initial condensational sink for the two particles at different rates; i.e., for the same starting initial condensational sink, smaller particles would experience quicker growth in the condensational sink compared to larger particles for the same amount of condensing mass
Across the four scenarios explored, the SOA formation predicted under the kinetic partitioning assumption was an order of magnitude or more lower than that predicted under the instantaneous partitioning assumption over a large portion of the input range explored, e.g., when the initial condensational sink was smaller than ∼ 0.1 min−1 and the maximum SOA formed was lower than ∼ 100 μ m−3 for the 10 nm simulations and lower than ∼ 1000 μg m−3 for the 100 nm simulations

Summary

Introduction

Combustion-related aerosols are an important contributor to urban and global air pollution and have impacts on climate (Pachauri et al, 2014) and human health (Anderson et al, 2012). While direct particle emissions from combustion sources are dominated by primary organic aerosol (POA) and black carbon (Bond et al, 2004), these sources emit volatile organic compounds (VOCs) that can photochemically react in the atmosphere to form secondary organic aerosol (SOA) (Robinson et al, 2007). SOA production from combustion emissions is poorly understood and not very well represented in models in terms of its precursors, gas–particle partitioning, composition, and properties (Fuzzi et al, 2015). S. Eluri et al.: Modeling the formation and composition of secondary organic aerosol from diesel exhaust from urban, combustion-related emissions (Ensberg et al, 2014)

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