scholarly journals Modelling the contribution of biogenic volatile organic compounds to new particle formation in the Jülich plant atmosphere chamber

2015 ◽  
Vol 15 (18) ◽  
pp. 10777-10798 ◽  
Author(s):  
P. Roldin ◽  
L. Liao ◽  
D. Mogensen ◽  
M. Dal Maso ◽  
A. Rusanen ◽  
...  
Keyword(s):  
Gas Phase ◽  
Organic Compounds ◽  
Particle Surface ◽  
Particle Formation ◽  
Heterogeneous Reactions ◽  
Chemical Mechanism ◽  
Particle Phase ◽  
New Particle Formation ◽  
Aerosol Dynamics ◽  
Phase Chemistry

Abstract. We used the Aerosol Dynamics gas- and particle-phase chemistry model for laboratory CHAMber studies (ADCHAM) to simulate the contribution of BVOC plant emissions to the observed new particle formation during photooxidation experiments performed in the Jülich Plant-Atmosphere Chamber and to evaluate how well smog chamber experiments can mimic the atmospheric conditions during new particle formation events. ADCHAM couples the detailed gas-phase chemistry from Master Chemical Mechanism with a novel aerosol dynamics and particle phase chemistry module. Our model simulations reveal that the observed particle growth may have either been controlled by the formation rate of semi- and low-volatility organic compounds in the gas phase or by acid catalysed heterogeneous reactions between semi-volatility organic compounds in the particle surface layer (e.g. peroxyhemiacetal dimer formation). The contribution of extremely low-volatility organic gas-phase compounds to the particle formation and growth was suppressed because of their rapid and irreversible wall losses, which decreased their contribution to the nano-CN formation and growth compared to the atmospheric situation. The best agreement between the modelled and measured total particle number concentration (R2 > 0.95) was achieved if the nano-CN was formed by kinetic nucleation involving both sulphuric acid and organic compounds formed from OH oxidation of BVOCs.

scholarly journals Modelling non-equilibrium secondary organic aerosol formation and evaporation with the aerosol dynamics, gas- and particle-phase chemistry kinetic multilayer model ADCHAM

2014 ◽  
Vol 14 (15) ◽  
pp. 7953-7993 ◽  
Author(s):  
P. Roldin ◽  
A. C. Eriksson ◽  
E. Z. Nordin ◽  
E. Hermansson ◽  
D. Mogensen ◽  
...  
Keyword(s):  
Gas Phase ◽  
Early Stage ◽  
Particle Surface ◽  
Organic Aerosol ◽  
Particle Phase ◽  
Organic Salts ◽  
Heterogeneous Oxidation ◽  
Aerosol Dynamics ◽  
Smog Chambers ◽  
Phase Chemistry

Abstract. We have developed the novel Aerosol Dynamics, gas- and particle-phase chemistry model for laboratory CHAMber studies (ADCHAM). The model combines the detailed gas-phase Master Chemical Mechanism version 3.2 (MCMv3.2), an aerosol dynamics and particle-phase chemistry module (which considers acid-catalysed oligomerization, heterogeneous oxidation reactions in the particle phase and non-ideal interactions between organic compounds, water and inorganic ions) and a kinetic multilayer module for diffusion-limited transport of compounds between the gas phase, particle surface and particle bulk phase. In this article we describe and use ADCHAM to study (1) the evaporation of liquid dioctyl phthalate (DOP) particles, (2) the slow and almost particle-size-independent evaporation of α-pinene ozonolysis secondary organic aerosol (SOA) particles, (3) the mass-transfer-limited uptake of ammonia (NH3) and formation of organic salts between ammonium (NH4+) and carboxylic acids (RCOOH), and (4) the influence of chamber wall effects on the observed SOA formation in smog chambers. ADCHAM is able to capture the observed α-pinene SOA mass increase in the presence of NH3(g). Organic salts of ammonium and carboxylic acids predominantly form during the early stage of SOA formation. In the smog chamber experiments, these salts contribute substantially to the initial growth of the homogeneously nucleated particles. The model simulations of evaporating α-pinene SOA particles support the recent experimental findings that these particles have a semi-solid tar-like amorphous-phase state. ADCHAM is able to reproduce the main features of the observed slow evaporation rates if the concentration of low-volatility and viscous oligomerized SOA material at the particle surface increases upon evaporation. The evaporation rate is mainly governed by the reversible decomposition of oligomers back to monomers. Finally, we demonstrate that the mass-transfer-limited uptake of condensable organic compounds onto wall-deposited particles or directly onto the Teflon chamber walls of smog chambers can have a profound influence on the observed SOA formation. During the early stage of the SOA formation the wall-deposited particles and walls themselves serve as an SOA sink from the air to the walls. However, at the end of smog chamber experiments the semi-volatile SOA material may start to evaporate from the chamber walls. With these four model applications, we demonstrate that several poorly quantified processes (i.e. mass transport limitations within the particle phase, oligomerization, heterogeneous oxidation, organic salt formation, and chamber wall effects) can have a substantial influence on the SOA formation, lifetime, chemical and physical particle properties, and their evolution. In order to constrain the uncertainties related to these processes, future experiments are needed in which as many of the influential variables as possible are varied. ADCHAM can be a valuable model tool in the design and analysis of such experiments.

scholarly journals Modelling non-equilibrium secondary organic aerosol formation and evaporation with the aerosol dynamics, gas- and particle-phase chemistry kinetic multi-layer model ADCHAM

2014 ◽  
Vol 14 (1) ◽  
pp. 769-869 ◽  
Author(s):  
P. Roldin ◽  
A. C. Eriksson ◽  
E. Z. Nordin ◽  
E. Hermansson ◽  
D. Mogensen ◽  
...  
Keyword(s):  
Gas Phase ◽  
Early Stage ◽  
Particle Surface ◽  
Organic Aerosol ◽  
Particle Phase ◽  
Organic Salts ◽  
Heterogeneous Oxidation ◽  
Aerosol Dynamics ◽  
Smog Chambers ◽  
Phase Chemistry

Abstract. We have developed the novel Aerosol Dynamics, gas- and particle-phase chemistry model for laboratory CHAMber studies (ADCHAM). The model combines the detailed gas phase Master Chemical Mechanism version 3.2, an aerosol dynamics and particle phase chemistry module (which considers acid catalysed oligomerization, heterogeneous oxidation reactions in the particle phase and non-ideal interactions between organic compounds, water and inorganic ions) and a kinetic multilayer module for diffusion limited transport of compounds between the gas phase, particle surface and particle bulk phase. In this article we describe and use ADCHAM to study: (1) the mass transfer limited uptake of ammonia (NH3) and formation of organic salts between ammonium (NH4+) and carboxylic acids (RCOOH), (2) the slow and almost particle size independent evaporation of α-pinene secondary organic aerosol (SOA) particles, and (3) the influence of chamber wall effects on the observed SOA formation in smog chambers. ADCHAM is able to capture the observed α-pinene SOA mass increase in the presence of NH3(g). Organic salts of ammonium and carboxylic acids predominantly form during the early stage of SOA formation. These salts contribute substantially to the initial growth of the homogeneously nucleated particles. The model simulations of evaporating α-pinene SOA particles support the recent experimental findings that these particles have a semi-solid tar like amorphous phase state. ADCHAM is able to reproduce the main features of the observed slow evaporation rates if low-volatility and viscous oligomerized SOA material accumulates in the particle surface layer upon evaporation. The evaporation rate is mainly governed by the reversible decomposition of oligomers back to monomers. Finally, we demonstrate that the mass transfer limited uptake of condensable organic compounds onto wall deposited particles or directly onto the Teflon chamber walls of smog chambers can have profound influence on the observed SOA formation. During the early stage of the SOA formation the wall deposited particles and walls themselves serve as a SOA sink from the air to the walls. However, at the end of smog chamber experiments the semi-volatile SOA material may start to evaporate from the chamber walls. With these three model applications, we demonstrate that several poorly quantified processes, i.e. mass transport limitations within the particle phase, oligomerization, heterogeneous oxidation, organic salt formation, and chamber wall effects can have substantial influence on the SOA formation, lifetime, chemical and physical particle properties, and their evolution. In order to constrain the uncertainties related to these processes, future experiments are needed where as many of the influential variables as possible are varied. ADCHAM can be a valuable model tool in the design and analysis of such experiments.

scholarly journals Aerosol mass yields of selected biogenic volatile organic compounds – a theoretical study with nearly explicit gas-phase chemistry

2019 ◽  
Vol 19 (22) ◽  
pp. 13741-13758
Author(s):  
Carlton Xavier ◽  
Anton Rusanen ◽  
Putian Zhou ◽  
Chen Dean ◽  
Lukas Pichelstorfer ◽  
...  
Keyword(s):  
Volatile Organic Compounds ◽  
Gas Phase ◽  
Organic Compounds ◽  
Chemical Mechanism ◽  
Biogenic Volatile Organic Compounds ◽  
Gas Phase Chemistry ◽  
Mass Load ◽  
Volatile Organic ◽  
Phase Chemistry ◽  
Good Agreement

Abstract. In this study we modeled secondary organic aerosol (SOA) mass loadings from the oxidation (by O3, OH and NO3) of five representative biogenic volatile organic compounds (BVOCs): isoprene, endocyclic bond-containing monoterpenes (α-pinene and limonene), exocyclic double-bond compound (β-pinene) and a sesquiterpene (β-caryophyllene). The simulations were designed to replicate an idealized smog chamber and oxidative flow reactors (OFRs). The Master Chemical Mechanism (MCM) together with the peroxy radical autoxidation mechanism (PRAM) were used to simulate the gas-phase chemistry. The aim of this study was to compare the potency of MCM and MCM + PRAM in predicting SOA formation. SOA yields were in good agreement with experimental values for chamber simulations when MCM + PRAM was applied, while a stand-alone MCM underpredicted the SOA yields. Compared to experimental yields, the OFR simulations using MCM + PRAM yields were in good agreement for BVOCs oxidized by both O3 and OH. On the other hand, a stand-alone MCM underpredicted the SOA mass yields. SOA yields increased with decreasing temperatures and NO concentrations and vice versa. This highlights the limitations posed when using fixed SOA yields in a majority of global and regional models. Few compounds that play a crucial role (>95 % of mass load) in contributing to SOA mass increase (using MCM + PRAM) are identified. The results further emphasized that incorporating PRAM in conjunction with MCM does improve SOA mass yield estimation.

scholarly journals Development and evaluation of the aerosol dynamics and gas phase chemistry model ADCHEM

2011 ◽  
Vol 11 (12) ◽  
pp. 5867-5896 ◽  
Author(s):  
P. Roldin ◽  
E. Swietlicki ◽  
G. Schurgers ◽  
A. Arneth ◽  
K. E. J. Lehtinen ◽  
...  
Keyword(s):  
Gas Phase ◽  
Size Structure ◽  
Particle Phase ◽  
Organic Mass ◽  
Product Model ◽  
Aerosol Dynamics ◽  
Gas Phase Chemistry ◽  
Urban Plume ◽  
Phase Chemistry ◽  
Urban Plumes

Abstract. The aim of this work was to develop a model suited for detailed studies of aerosol dynamics, gas and particle phase chemistry within urban plumes, from local scale (1 × 1 km2) to regional scale. This article describes and evaluates the trajectory model for Aerosol Dynamics, gas and particle phase CHEMistry and radiative transfer (ADCHEM). The model treats both vertical and horizontal dispersion perpendicular to an air mass trajectory (2-space dimensions). The Lagrangian approach enables a more detailed representation of the aerosol dynamics, gas and particle phase chemistry and a finer spatial and temporal resolution compared to that of available regional 3D-CTMs. These features make it among others well suited for urban plume studies. The aerosol dynamics model includes Brownian coagulation, dry deposition, wet deposition, in-cloud processing, condensation, evaporation, primary particle emissions and homogeneous nucleation. The organic mass partitioning was either modeled with a 2-dimensional volatility basis set (2D-VBS) or with the traditional two-product model approach. In ADCHEM these models consider the diffusion limited and particle size dependent condensation and evaporation of 110 and 40 different organic compounds respectively. The gas phase chemistry model calculates the gas phase concentrations of 61 different species, using 130 different chemical reactions. Daily isoprene and monoterpene emissions from European forests were simulated separately with the vegetation model LPJ-GUESS, and included as input to ADCHEM. ADCHEM was used to simulate the ageing of the urban plumes from the city of Malmö in southern Sweden (280 000 inhabitants). Several sensitivity tests were performed concerning the number of size bins, size structure method, aerosol dynamic processes, vertical and horizontal mixing, coupled or uncoupled condensation and the secondary organic aerosol formation. The simulations show that the full-stationary size structure gives accurate results with little numerical diffusion when more than 50 size bins are used between 1.5 and 2500 nm, while the moving-center method is preferable when only a few size bins are selected. The particle number size distribution in the center of the urban plume from Malmö was mainly affected by dry deposition, coagulation and vertical dilution. The modeled PM2.5 mass was dominated by organic material, nitrate, sulfate and ammonium. If the condensation of HNO3 and NH3 was treated as a coupled process (pH independent) the model gave lower nitrate PM2.5 mass than if considering uncoupled condensation. Although the time of ageing from that SOA precursors are emitted until condensable products are formed is substantially different with the 2D-VBS and two product model, the models gave similar total organic mass concentrations.

scholarly journals Kinetic modeling of formation and evaporation of secondary organic aerosol from NO<sub>3</sub> oxidation of pure and mixed monoterpenes

2020 ◽  
Vol 20 (24) ◽  
pp. 15513-15535
Author(s):  
Thomas Berkemeier ◽  
Masayuki Takeuchi ◽  
Gamze Eris ◽  
Nga L. Ng
Keyword(s):  
Kinetic Model ◽  
Gas Phase ◽  
Secondary Organic Aerosol ◽  
Organic Aerosol ◽  
Chemical Mechanism ◽  
Phase Reaction ◽  
Particle Phase ◽  
Environmental Chamber ◽  
Gas Phase Chemistry ◽  
Phase Chemistry

Abstract. Organic aerosol constitutes a major fraction of the global aerosol burden and is predominantly formed as secondary organic aerosol (SOA). Environmental chambers have been used extensively to study aerosol formation and evolution under controlled conditions similar to the atmosphere, but quantitative prediction of the outcome of these experiments is generally not achieved, which signifies our lack in understanding of these results and limits their portability to large-scale models. In general, kinetic models employing state-of-the-art explicit chemical mechanisms fail to describe the mass concentration and composition of SOA obtained from chamber experiments. Specifically, chemical reactions including the nitrate radical (NO3) are a source of major uncertainty for assessing the chemical and physical properties of oxidation products. Here, we introduce a kinetic model that treats gas-phase chemistry, gas–particle partitioning, particle-phase oligomerization, and chamber vapor wall loss and use it to describe the oxidation of the monoterpenes α-pinene and limonene with NO3. The model can reproduce aerosol mass and nitration degrees in experiments using either pure precursors or their mixtures and infers volatility distributions of products, branching ratios of reactive intermediates and particle-phase reaction rates. The gas-phase chemistry in the model is based on the Master Chemical Mechanism (MCM) but trades speciation of single compounds for the overall ability of quantitatively describing SOA formation by using a lumped chemical mechanism. The complex branching into a multitude of individual products in MCM is replaced in this model with product volatility distributions and detailed peroxy (RO2) and alkoxy (RO) radical chemistry as well as amended by a particle-phase oligomerization scheme. The kinetic parameters obtained in this study are constrained by a set of SOA formation and evaporation experiments conducted in the Georgia Tech Environmental Chamber (GTEC) facility. For both precursors, we present volatility distributions of nitrated and non-nitrated reaction products that are obtained by fitting the kinetic model systematically to the experimental data using a global optimization method, the Monte Carlo genetic algorithm (MCGA). The results presented here provide new mechanistic insight into the processes leading to formation and evaporation of SOA. Most notably, the model suggests that the observed slow evaporation of SOA could be due to reversible oligomerization reactions in the particle phase. However, the observed non-linear behavior of precursor mixtures points towards a complex interplay of reversible oligomerization and kinetic limitations of mass transport in the particle phase, which is explored in a model sensitivity study. The methodologies described in this work provide a basis for quantitative analysis of multi-source data from environmental chamber experiments but also show that a large data pool is needed to fully resolve uncertainties in model parameters.

scholarly journals Improvement and further development in CESM/CAM5: gas-phase chemistry and inorganic aerosol treatments

2014 ◽  
Vol 14 (17) ◽  
pp. 9171-9200 ◽  
Author(s):  
J. He ◽  
Y. Zhang
Keyword(s):  
Air Quality ◽  
Gas Phase ◽  
Power Law ◽  
Global Scale ◽  
Particle Formation ◽  
New Particle Formation ◽  
Gas Phase Chemistry ◽  
Model Version ◽  
Inorganic Aerosol ◽  
Phase Chemistry

Abstract. Gas-phase chemistry and subsequent gas-to-particle conversion processes such as new particle formation, condensation, and thermodynamic partitioning have large impacts on air quality, climate, and public health through influencing the amounts and distributions of gaseous precursors and secondary aerosols. Their roles in global air quality and climate are examined in this work using the Community Earth System Model version 1.0.5 (CESM1.0.5) with the Community Atmosphere Model version 5.1 (CAM5.1) (referred to as CESM1.0.5/CAM5.1). CAM5.1 includes a simple chemistry that is coupled with a 7-mode prognostic Modal Aerosol Model (MAM7). MAM7 includes classical homogenous nucleation (binary and ternary) and activation nucleation (empirical first-order power law) parameterizations, and a highly simplified inorganic aerosol thermodynamics treatment that only simulates particulate-phase sulfate and ammonium. In this work, a new gas-phase chemistry mechanism based on the 2005 Carbon Bond Mechanism for Global Extension (CB05_GE) and several advanced inorganic aerosol treatments for condensation of volatile species, ion-mediated nucleation (IMN), and explicit inorganic aerosol thermodynamics for sulfate, ammonium, nitrate, sodium, and chloride have been incorporated into CESM/CAM5.1-MAM7. Compared to the simple gas-phase chemistry, CB05_GE can predict many more gaseous species, and thus could improve model performance for PM2.5, PM10, PM components, and some PM gaseous precursors such as SO2 and NH3 in several regions as well as aerosol optical depth (AOD) and cloud properties (e.g., cloud fraction (CF), cloud droplet number concentration (CDNC), and shortwave cloud forcing, SWCF) on the global scale. The modified condensation and aqueous-phase chemistry could further improve the prediction of additional variables such as HNO3, NO2, and O3 in some regions, and new particle formation rate (J) and AOD on the global scale. IMN can improve the prediction of secondary PM2.5 components, PM2.5, and PM10 over Europe as well as AOD and CDNC on the global scale. The explicit inorganic aerosol thermodynamics using the ISORROPIA II model improves the prediction of all major PM2.5 components and their gaseous precursors in some regions as well as downwelling shortwave radiation, SWCF, and cloud condensation nuclei at a supersaturation of 0.5% on the global scale. For simulations of 2001–2005 with all the modified and new treatments, the improved model predicts that on global average, SWCF increases by 2.7 W m−2, reducing the normalized mean bias (NMB) of SWCF from −5.4 to 1.2%. Uncertainties in emissions can largely explain the inaccurate prediction of precursor gases (e.g., SO2, NH3, and NO) and primary aerosols (e.g., black carbon and primary organic matter). Additional factors leading to the discrepancies between model predictions and observations include assumptions associated with equilibrium partitioning for fine particles assumed in ISORROPIA II, irreversible gas/particle mass transfer treatment for coarse particles, uncertainties in model treatments such as dust emissions, secondary organic aerosol formation, multi-phase chemistry, cloud microphysics, aerosol–cloud interaction, dry and wet deposition, and model parameters (e.g., accommodation coefficients and prefactors of the nucleation power law) as well as uncertainties in model configuration such as the use of a coarse-grid resolution.

scholarly journals Improvement and further development in CESM/CAM5: gas-phase chemistry and inorganic aerosol treatments

2013 ◽  
Vol 13 (10) ◽  
pp. 27717-27777 ◽  
Author(s):  
J. He ◽  
Y. Zhang
Keyword(s):  
Air Quality ◽  
Gas Phase ◽  
Particle Formation ◽  
Cloud Microphysics ◽  
Specific Humidity ◽  
New Particle Formation ◽  
Gas Phase Chemistry ◽  
Model Version ◽  
Inorganic Aerosol ◽  
Phase Chemistry

Abstract. Gas-phase chemistry and subsequent gas-to-particle conversion processes such as new particle formation, condensation, and thermodynamic partitioning have large impacts on air quality, climate, and public health through influencing the amounts and distributions of gaseous precursors and secondary aerosols. Their roles in global air quality and climate are examined in this work using the Community Earth System Model version 1.0.5 (CESM1.0.5) with the Community Atmosphere Model version 5.1 (CAM5.1) (referred to as CESM1.0.5/CAM5.1). CAM5.1 includes a simple chemistry that is coupled with a 7-mode prognostic Modal Aerosol Model (MAM7). MAM7 includes classical homogenous nucleation (binary and ternary) and activation nucleation (empirical first-order power law) parameterizations, and a highly-simplified inorganic aerosol thermodynamics treatment that only simulates sulfate (SO42−) and ammonium (NH4+). In this work, a new gas-phase chemistry mechanism based on the 2005 Carbon Bond Mechanism for Global Extension (CB05_GE) and several advanced inorganic aerosol treatments for condensation of volatile species, ion-mediated nucleation (IMN), and explicit inorganic aerosol thermodynamics have been incorporated into CESM/CAM5.1-MAM7. Comparing to the simple gas-phase chemistry, CB05_GE can predict many more gaseous species, and improve model performance for PM2.5, PM10, PM2.5 components, and some PM gaseous precursors such as SO2 and NH3 in several regions, as well as aerosol optical depth (AOD) and cloud properties (e.g., cloud fraction (CF), cloud droplet number concentration (CDNC), and shortwave cloud forcing (SWCF)) on globe. The modified condensation and aqueous-phase chemistry further improves the predictions of additional variables such as HNO3, NO2, and O3 in some regions, and new particle formation rate (J) and AOD over globe. IMN can improve the predictions of secondary PM2.5 components, PM2.5, and PM10 over Europe, as well as AOD and CDNC over globe. The explicit inorganic aerosol thermodynamics using ISORROPIA II improves the predictions of all major PM2.5 components and their gaseous precursors in some regions, as well as near-surface temperature and specific humidity, precipitation, downwelling shortwave radiation, SWCF, and cloud condensation nuclei at a supersaturation of 0.5% over globe. With all the modified and new treatments, the improved model predicts that on a global average, SWCF decreases by 2.9 W m−2, reducing the overprediction of SWCF from 7.9% to 0.9%. Uncertainties in emissions can explain largely the inaccurate predictions of precursor gases (e.g., SO2, NH3, and NO) and primary aerosols (e.g., black carbon and primary organic matter). Additional factors leading to discrepancies between model predictions and observations include uncertainties in model treatments such as dust emissions, secondary organic aerosol formation, multiple-phase chemistry, cloud microphysics, aerosol-cloud interaction, and dry and wet deposition.

scholarly journals Aerosol Mass yields of selected Biogenic Volatile Organic Compounds – a theoretical study with near explicit gas-phase chemistry

2019 ◽  
Author(s):  
Carlton Xavier ◽  
Anton Rusanen ◽  
Putian Zhou ◽  
Chen Dean ◽  
Lukas Pichelstorfer ◽  
...  
Keyword(s):  
Volatile Organic Compounds ◽  
Gas Phase ◽  
Organic Compounds ◽  
Chemical Mechanism ◽  
Seed Particle ◽  
Biogenic Volatile Organic Compounds ◽  
Gas Phase Chemistry ◽  
Mass Load ◽  
Volatile Organic ◽  
Phase Chemistry

Abstract. In this study we modeled secondary organic aerosols (SOA) mass loadings from the oxidation (by O3, OH and NO3) of five representative Biogenic Volatile Organic compounds (BVOCs): isoprene, endocyclic bond containing monoterpenes (α-pinene and limonene), exocyclic double bond compound (β-pinene) and a sesquiterpene (β-caryophyllene). The simulations were designed to replicate idealized smog chamber and oxidative flow reactors (OFR). The master chemical mechanism (MCM) together with the peroxy radical autoxidation mechanism (PRAM), were used to simulate the gas-phase chemistry. The aim of this study was to compare the potency of MCM and MCM+PRAM in predicating SOA formation. SOA yields were in good agreement with experimental values for chamber simulations when MCM+PRAM mechanism was applied, while a standalone MCM under-predicted the SOA yields. Compared to experimental yields, the OFR simulations using the MCM+PRAM mechanism over-predicted SOA mass yields for BVOCs oxidized by O3 and OH, probably owing to increased seed particle surface area used in the OFR simulations. SOA yields increased with decreasing temperatures and NO concentrations and vice-versa. This highlights the limitations posed when using fixed SOA yields in a majority of global and regional models. Few compounds that play a crucial role (> 95 % of mass load) in contributing to SOA mass increase (using MCM+PRAM) are identified. The results further emphasized that incorporating PRAM in conjunction with MCM does improve SOA mass yields estimation.

scholarly journals Modelling the contribution of biogenic VOCs to new particle formation in the Jülich plant atmosphere chamber

2014 ◽  
Vol 14 (20) ◽  
pp. 27973-28018 ◽  
Author(s):  
L. Liao ◽  
M. Dal Maso ◽  
D. Mogensen ◽  
P. Roldin ◽  
A. Rusanen ◽  
...  
Keyword(s):  
Organic Compounds ◽  
Particle Number ◽  
Particle Formation ◽  
Oxidation Products ◽  
New Particle Formation ◽  
Particle Volume ◽  
Aerosol Dynamics ◽  
Total Particle Number ◽  
Total Particle ◽  
Air Chemistry

Abstract. We used the MALTE-BOX model including near-explicit air chemistry and detailed aerosol dynamics to study the mechanisms of observed new particle formation events in the Jülich Plant Atmosphere Chamber. The modelled and measured H2SO4 (sulfuric acid) concentrations agreed within a factor of two. The modelled total monoterpene concentration was in line with PTR-MS observations, and we provided the distributions of individual isomers of terpenes, when no measurements were available. The aerosol dynamic results supported the hypothesis that H2SO4 is one of the critical compounds in the nucleation process. However, compared to kinetic H2SO4 nucleation, nucleation involving OH oxidation products of monoterpenes showed a better agreement with the measurements, with R2 up to 0.97 between modelled and measured total particle number concentrations. The nucleation coefficient for kinetic H2SO4 nucleation was 2.1 × 10−11 cm3 s−1, while the organic nucleation coefficient was 9.0 × 10−14 cm3 s−1. We classified the VOC oxidation products into two sub-groups including extremely low-volatility organic compounds (ELVOCs) and semi-volatile organic compounds (SVOCs). These ELVOCs and SVOCs contributed approximately equally to the particle volume production, whereas only ELVOCs made the smallest particles to grow in size. The model simulations revealed that the chamber walls constitute a major net sink of SVOCs on the first experiment day. However, the net wall SVOC uptake was gradually reduced because of SVOC desorption during the following days. Thus, in order to capture the observed temporal evolution of the particle number size distribution, the model needs to consider reversible gas-wall partitioning.

scholarly journals Kinetic modelling of formation and evaporation of SOA from NO<sub>3</sub> oxidation of pure and mixed monoterpenes

2020 ◽  
Author(s):  
Thomas Berkemeier ◽  
Masayuki Takeuchi ◽  
Gamze Eris ◽  
Nga L. Ng
Keyword(s):  
Kinetic Model ◽  
Gas Phase ◽  
Organic Aerosol ◽  
Chemical Mechanism ◽  
Phase Reaction ◽  
Particle Phase ◽  
Aerosol Formation ◽  
Environmental Chamber ◽  
Gas Phase Chemistry ◽  
Phase Chemistry

Abstract. Organic aerosol constitutes a major fraction of the global aerosol burden and is predominantly formed as secondary organic aerosol (SOA). Environmental chambers have been used extensively to study aerosol formation and evolution under controlled conditions similar to the atmosphere, but quantitative prediction of the outcome of these experiments is generally not achieved, which signifies our lack in understanding of these results and limits their portability to large scale models. In general, kinetic models employing state-of-the-art explicit chemical mechanisms fail to describe the mass concentration and composition of SOA obtained from chamber experiments. Specifically, chemical reactions involving nitrate radical (NO3) oxidation of volatile organic compounds (VOCs) are a source of major uncertainty for assessing the chemical and physical properties of oxidation products. Here, we introduce a kinetic model that treats gas-phase chemistry, gas-particle partitioning, particle-phase oligomerization, and chamber wall loss and use it to describe the oxidation of the monoterpenes α-pinene and limonene with NO3. The model can reproduce aerosol mass and nitration degrees in experiments using either pure precursors or their mixtures and infers volatility distributions of products, branching ratios of reactive intermediates as well as particle-phase reaction rates. The gas-phase chemistry in the model is based on the Master Chemical Mechanism (MCM), but trades speciation of single compounds for the overall ability of quantitatively describing SOA formation by using a lumped chemical mechanism. The complex branching into a multitude of individual products in MCM is replaced in this model with product volatility distributions, detailed peroxy (RO2) and alkoxy (RO) radical chemistry and amended by a particle-phase oligomerization scheme. The kinetic parameters obtained in this study are constrained by a set of SOA formation and evaporation experiments conducted in the Georgia Tech Environmental Chamber (GTEC) facility. For both precursors, we present volatility distributions of nitrated and non-nitrated reaction products that are obtained by fitting the kinetic model systematically to the experimental data using a global optimization method, the Monte Carlo Genetic Algorithm (MCGA). The results presented here provide new mechanistic insight into the processes leading to formation and evaporation of SOA. Most notably, much of the non-linear behavior of precursor mixtures can be understood by RO2 fate and reversible oligomerization reactions in the particle phase, but some effects could be accredited to kinetic limitations of mass transport in the particle phase. The methodologies described in this work provide a basis for quantitative analysis of multi-source data from environmental chamber experiments with manageable computational effort.

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