Process-based and observation-constrained SOA simulations in China: the role of semivolatile and intermediate-volatility organic compounds and OH levels

Organic aerosol (OA) is a major component of tropospheric submicron aerosol that contributes to air pollution and causes adverse effects on human health. Chemical transport models have difficulties in reproducing the variability in OA concentrations in polluted areas, hindering understanding of the OA budget and sources. Herein, we apply both process-based and observation-constrained schemes to simulate OA in GEOS-Chem. Comprehensive data sets of surface OA, OA components, secondary organic aerosol (SOA) precursors, and oxidants were used for model–observation comparisons. The base models generally underestimate the SOA concentrations in China. In the revised schemes, updates were made on the emissions, volatility distributions, and SOA yields of semivolatile and intermediate-volatility organic compounds (SVOCs and IVOCs) and additional nitrous acid sources. With all the model improvements, both the process-based and observation-constrained SOA schemes can reproduce the observed mass concentrations of SOA and show spatial and seasonal consistency with each other. Our best model simulations suggest that anthropogenic SVOCs and IVOCs are the dominant source of SOA, with a contribution of over 50 % in most of China, which should be considered for pollution mitigation in the future. The residential sector may be the predominant source of SVOCs and IVOCs in winter, despite large uncertainty remaining in the emissions of IVOCs from the residential sector in northern China. The industry sector is also an important source of IVOCs, especially in summer. More SVOC and IVOC measurements are needed to constrain their emissions. Besides, the results highlight the sensitivity of SOA to hydroxyl radical (OH) levels in winter in polluted environments. The addition of nitrous acid sources can lead to over 30 % greater SOA mass concentrations in winter in northern China. It is important to have good OH simulations in air quality models.

Process-based and Observation-constrained SOA Simulations in China: The Role of Semivolatile and Intermediate-Volatility Organic Compounds and OH Levels

Organic aerosol (OA) is a major component of tropospheric submicron aerosol that contributes to air pollution and causes adverse effects on human health. Chemical transport models have difficulties to reproduce the variability of OA concentrations in polluted areas, hindering understanding of the OA budget. Herein, we applied both process-based and observation-constrained schemes to simulate OA in GEOS-Chem. Comprehensive data sets of surface OA, OA components, secondary organic aerosol (SOA) precursors, and oxidants were used for model-observation comparisons. In the revised schemes, updates of the emissions, volatility distributions, and SOA yields of semivolatile and intermediate volatility organic compounds (S/IVOCs) were made. These updates are however insufficient to reproduce the SOA concentrations in observations. The addition of nitrous acid sources is an important model modification, which improves the simulation of surface concentrations of hydroxyl radical (OH) in winter in northern China. The increased surface OH concentrations enhance the SOA formation and lead to greater SOA mass concentrations by over 30 %, highlighting the importance of having good OH simulations in air quality models. There is a greater sensitivity of the SOA formation to the oxidant levels in winter than in summer in China. With all the model improvements, both the process-based and observation-constrained SOA schemes can reproduce the observed mass concentrations of SOA and show spatial and seasonal consistency with each other. Our best model simulations suggest that anthropogenic S/IVOCs are the dominant source of SOA in China with a contribution of over 50 %. The residential sector may be the predominant source of S/IVOCs in winter, despite large uncertainty remains in the emissions of IVOCs from the residential sector in northern China. The industry sector is also an important source of IVOCs, especially in summer. More S/IVOC measurements are needed to constrain their emissions.

Grid-independent high-resolution dust emissions (v1.0) for chemical transport models: application to GEOS-Chem (12.5.0)

The nonlinear dependence of the dust saltation process on wind speed poses a challenge for models of varying resolutions. This challenge is of particular relevance for the next generation of chemical transport models with nimble capability for multiple resolutions. We develop and apply a method to harmonize dust emissions across simulations of different resolutions by generating offline grid-independent dust emissions driven by native high-resolution meteorological fields. We implement into the GEOS-Chem chemical transport model a high-resolution dust source function to generate updated offline dust emissions. These updated offline dust emissions based on high-resolution meteorological fields strengthen dust emissions over relatively weak dust source regions, such as in southern South America, southern Africa and the southwestern United States. Identification of an appropriate dust emission strength is facilitated by the resolution independence of offline emissions. We find that the performance of simulated aerosol optical depth (AOD) versus measurements from the AERONET network and satellite remote sensing improves significantly when using the updated offline dust emissions with the total global annual dust emission strength of 2000 Tg yr−1 rather than the standard online emissions in GEOS-Chem. The updated simulation also better represents in situ measurements from a global climatology. The offline high-resolution dust emissions are easily implemented in chemical transport models. The source code and global offline high-resolution dust emission inventory are publicly available.

Data Assimilation as a Tool to Improve Chemical Transport Models Performance in Developing Countries

Particulate matter (PM) is one of the most problematic pollutants in urban air. The effects of PM on human health, associated especially with PM of ≤2.5μm in diameter, include asthma, lung cancer and cardiovascular disease. Consequently, major urban centers commonly monitor PM2.5 as part of their air quality management strategies. The Chemical Transport models allow for a permanent monitoring and prediction of pollutant behavior for all the regions of interest, different to the sensor network where the concentration is just available in specific points. In this chapter a data assimilation system for the LOTOS-EUROS chemical transport model has been implemented to improve the simulation and forecast of Particulate Matter in a densely populated urban valley of the tropical Andes. The Aburrá Valley in Colombia was used as a case study, given data availability and current environmental issues related to population expansion. Using different experiments and observations sources, we shown how the Data Assimilation can improve the model representation of pollutants.

Chemical transport models often underestimate inorganic aerosol acidity in remote regions of the atmosphere

The inorganic fraction of fine particles affects numerous physicochemical processes in the atmosphere. However, there is large uncertainty in its burden and composition due to limited global measurements. Here, we present observations from eleven different aircraft campaigns from around the globe and investigate how aerosol pH and ammonium balance change from polluted to remote regions, such as over the oceans. Both parameters show increasing acidity with remoteness, at all altitudes, with pH decreasing from about 3 to about −1 and ammonium balance decreasing from almost 1 to nearly 0. We compare these observations against nine widely used chemical transport models and find that the simulations show more scatter (generally R2 < 0.50) and typically predict less acidic aerosol in the most remote regions. These differences in observations and predictions are likely to result in underestimating the model-predicted direct radiative cooling effect for sulfate, nitrate, and ammonium aerosol by 15–39%.

Non-equilibrium interplay between gas–particle partitioning and multiphase chemical reactions of semi-volatile compounds: mechanistic insights and practical implications for atmospheric modeling of polycyclic aromatic hydrocarbons

Polycyclic aromatic hydrocarbons (PAHs) are carcinogenic air pollutants. The dispersion of PAHs in the atmosphere is influenced by gas–particle partitioning and chemical loss. These processes are closely interlinked and may occur at vastly differing timescales, which complicates their mathematical description in chemical transport models. Here, we use a kinetic model that explicitly resolves mass transport and chemical reactions in the gas and particle phases to describe and explore the dynamic and non-equilibrium interplay of gas–particle partitioning and chemical losses of PAHs on soot particles. We define the equilibration timescale τeq of gas–particle partitioning as the e-folding time for relaxation of the system to the partitioning equilibrium. We find this metric to span from seconds to hours depending on temperature, particle surface area, and the type of PAH. The equilibration time can be approximated using a time-independent equation, τeq≈1kdes+kads, which depends on the desorption rate coefficient kdes and adsorption rate coefficient kads, both of which can be calculated from experimentally accessible parameters. The model reveals two regimes in which different physical processes control the equilibration timescale: a desorption-controlled and an adsorption-controlled regime. In a case study with the PAH pyrene, we illustrate how chemical loss can perturb the equilibrium particulate fraction at typical atmospheric concentrations of O3 and OH. For the surface reaction with O3, the perturbation is significant and increases with the gas-phase concentration of O3. Conversely, perturbations are smaller for reaction with the OH radical, which reacts with pyrene on both the surface of particles and in the gas phase. Global and regional chemical transport models typically approximate gas–particle partitioning with instantaneous-equilibration approaches. We highlight scenarios in which these approximations deviate from the explicitly coupled treatment of gas–particle partitioning and chemistry presented in this study. We find that the discrepancy between solutions depends on the operator-splitting time step and the choice of time step can help to minimize the discrepancy. The findings and techniques presented in this work not only are relevant for PAHs but can also be applied to other semi-volatile substances that undergo chemical reactions and mass transport between the gas and particle phase.

Results on an Inter-model Comparison on Secondary Aerosol Formation

&lt;p&gt;This study aims at comparing the gas-to-particle conversion mechanisms adopted by regional chemical transport models (CTMs). We use the results from twelve regional CTMs from the third phase of the Model Inter-Comparison Study for Asia (MICS-Asia III). The simulations are conducted over East Asia for the whole year of 2010. The models used are WRF-CMAQ (version 4.7.1 and v5.0.2), WRF-Chem (v3.6.1 and v3.7.1), GEOS-Chem, NHM-Chem, NAQPMS and NU-WRF. Measurements from 54 EANET sites, 86 sites of the Air Pollution Indices (API) and 35 local sites, remote sensing products from AERONET and satellite data from MODIS are used to evaluate model performance on PM&lt;sub&gt;10&lt;/sub&gt;, PM&lt;sub&gt;2.5&lt;/sub&gt; and its components and aerosol optical depth (AOD). To investigate the inter-model differences in secondary aerosol formation, we compare the Sulfur Oxidation Ratio (SOR) and Nitrogen Oxidation Ratio (NOR) values by different models with observations at the EANET sites. The preliminary results show that the inter-model differences in the oxidation ratio (50%) are almost of the same magnitude as those in simulating the concentrations of particles. The results suggest large uncertainties in the gas-particle conversion process in modelling secondary aerosol formation.&lt;/p&gt;

Improving the simulation of Intermediate Volatility Compounds (IVOCs) in chemical transport models

&lt;p&gt;Secondary organic aerosol (SOA) can be formed in the atmosphere through oxidation of volatile (VOCs), intermediate volatility (IVOCs) and semivolatile organic compounds (SVOCs), and condensation of their less volatile products to the particulate phase. While there has been a lot of progress with the simulation of the VOC chemistry, the simulation of the IVOCs remains challenging. In this study, we develop a new approach for the treatment of these compounds in chemical transport models, treating them as lumped species, similar to the VOCs. The new species are implemented in the SAPRC gas-phase chemical mechanism. We introduce four new lumped species representing larger alkanes, two species for polyaromatic hydrocarbons (PAHs) and one new lumped species representing aromatics, all in the IVOC volatility range. Their gas-phase chemistry is assumed to be analogous to that of the large alkanes and aromatics currently in the SAPRC mechanism but with appropriate parameters. The SOA yields for these additional species were estimated for low and high-NOx conditions following the Volatility Basis Set framework and using the available results of smog chamber studies. As most emission inventories do not include IVOCs, we estimated their emissions starting from road transport using existing non-methane hydrocarbons emissions and emission factors of individual IVOCs from laboratory studies. The total IVOC emissions from diesel vehicles for Europe were significantly higher than those coming from gasoline vehicles. The emissions and extended mechanism were implemented in PMCAMx and were used to simulate the EUCAARI intensive period. Cyclic alkanes, which have both high SOA yields and high emissions, were a major SOA precursor group. The contribution of the various IVOCs to SOA formation, and their overall role is discussed. Significant remaining uncertainties are summarized.&lt;/p&gt;

Error induced by neglecting subgrid chemical segregation due to inefficient turbulent mixing in regional chemical-transport models in urban environments

We employed direct numerical simulations to estimate the error on chemical calculation in simulations with regional chemical-transport models induced by neglecting subgrid chemical segregation due to inefficient turbulent mixing in an urban boundary layer with strong and heterogeneously distributed surface emissions. In simulations of initially segregated reactive species with an entrainment-emission configuration with an A–B–C second-order chemical scheme, urban surface emission fluxes of the homogeneously emitted tracer A result in a very large segregation between the tracers and hence a very large overestimation of the effective chemical reaction rate in a complete-mixing model. This large effect can be indicated by a large Damköhler number (Da) of the limiting reactant. With heterogeneous surface emissions of the two reactants, the resultant normalised boundary-layer-averaged effective chemical reaction rate is found to be in a Gaussian function of Da, and it is increasingly overestimated by the imposed rate with an increased horizontal scale of emission heterogeneity. Coarse-grid models with resolutions commensurable to regional models give reduced yet still significant errors for all simulations with homogeneous emissions. Such model improvement is more sensitive to the increased vertical resolution. However, such improvement cannot be seen for simulations with heterogeneous emissions when the horizontal resolution of the model cannot resolve emission heterogeneity. This work highlights particular conditions in which the ability to resolve chemical segregation is especially important when modelling urban environments.