Nanoparticle formation in the exhaust of vehicles running on ultra-low sulfur fuel

International audienceThe concern of adverse health impacts from exposure to vehicle-emitted nanoparticles has been escalating over the past few years. In order to meet more stringent EPA emission standards for particle mass emissions, advanced exhaust after-treatment systems such as continuously regenerating diesel particle filters (CRDPFs) have to be employed on vehicles and fuel with ultra-low sulfur is to be used. Although CRDPFs were found to be effective in reducing particle mass emissions, they were revealed to increase the potential of volatile nanoparticle formation. Significant nanoparticle concentrations have also been detected for vehicles running on ultra-low sulfur fuel but without CRDPFs. The main focus of this paper is the formation and evolution of nanoparticles in exhaust plume under ultra-low sulfur condition. Such study is necessary to project future nanoparticle emissions as fuel compositions and after-treatment systems change. We have carried out a comprehensive quantitative assessment of the effects of enhanced sulfur conversion efficiency, sulfur storage/release, and presence of non-volatile cores on nanoparticle formation using a detailed composition resolved aerosol microphysical model with a recently improved H2SO4-H2O homogeneous nucleation (BHN) module. Two well-controlled case studies show good agreement between model predictions and measurements in terms of particle size distribution and temperature dependence of particle formation rate, which leads us to conclude that BHN is the main source of nanoparticles for vehicles equipped with CRDPFs. We found that the employment of CRDPFs may lead to the higher number concentration of nanoparticles (but smaller size) in the exhaust of vehicles running on ultra-low sulfur fuel compared to those emitted from vehicles running on high sulfur fuel. We have also shown that the sulfate storage and release effect can lead to significant enhancement in nanoparticle production under favorable conditions. For vehicles running on ultra-low sulfur fuel but without CRDPFs, the BHN is negligible; however, the condensation of low volatile organic compounds on nanometer-sized non-volatile cores may explain the observed nucleation mode particles

Particle number concentrations and size distributions in the stratosphere : implications of nucleation mechanisms and particle microphysics

While formation and growth of particles in the troposphere have been extensively studied in the past two decades, very limited efforts have been devoted to understanding these in the stratosphere. Here we use both Cosmics Leaving OUtdoor Droplets (CLOUD) laboratory measurements taken under very low temperatures (205-223 K) and Atmospheric Tomography Mission (ATom) in situ observations of particle number size distributions (PNSDs) down to 3 nm to constrain nucleation mechanisms and to evaluate model-simulated particle size distributions in the lowermost stratosphere (LMS). We show that the binary homogenous nucleation (BHN) scheme used in most of the existing stratospheric aerosol injection (a proposed method of solar radiation modification) modeling studies overpredicts the nucleation rates by 3-4 orders of magnitude (when compared to CLOUD data) and particle number concentrations in the background LMS by a factor similar to 2-4 (when compared to ATom data). Based on a recently developed kinetic nucleation model, which gives rates of both ion-mediated nucleation (IMN) and BHN at low temperatures in good agreement with CLOUD measurements, both BHN and IMN occur in the stratosphere. However, IMN rates are generally more than 1 order of magnitude higher than BHN rates and thus dominate nucleation in the background stratosphere. In the Southern Hemisphere (SH) LMS with minimum influence of anthropogenic emissions, our analysis shows that ATom-measured PNSDs generally have four apparent modes. The model captures reasonably well the two modes (Aitken mode and the first accumulation mode) with the highest number concentrations and size-dependent standard deviations. However, the model misses an apparent second accumulation mode peaking around 300-400 nm, which is in the size range important for aerosol direct radiative forcing. The bimodal structure of accumulation mode particles has also been observed in the stratosphere well above tropopause and in the volcano-perturbed stratosphere. We suggest that this bimodal structure may be caused by the effect of charges on coagulation and growth, which is not yet considered in any existing models and may be important in the stratosphere due to high ionization rates and the long lifetime of aerosols. Considering the importance of accurate PNSDs for projecting a realistic radiation forcing response to stratospheric aerosol injection (SAI), it is essential to understand and incorporate such potentially important processes in SAI model simulations and to carry out further research to find out what other processes the present models might have missed.Peer reviewe

Anomalously Strong Effect of the Ion Sign on the Thermochemistry of Hydrogen Bonded Aqueous Clusters of Identical Chemical Composition

The sign preference of hydrogen bonded aqueous ionic clusters X±(H2O)i (n =1–5, X = F; Cl; Br) has been investigated using the Density Functional Theory and ab initio MP2 method. The present study indicates the anomalously large difference in formation free energies between cations and anions of identical chemical composition. The effect of vibrational anharmonicity on stepwise Gibbs free energy changes has been investigated, and possible uncertainties associated with the harmonic treatment of vibrational spectra have been discussed

Effect of Ammonia on the Gas-Phase Hydration of the Common Atmospheric Ion HSO4−

Hydration directly affects the mobility, thermodynamic properties, lifetime and nucleation rates of atmospheric ions. In the present study, the role of ammonia on the formation of hydrogen bonded complexes of the common atmospheric hydrogensulfate (HSO4−) ion with water has been investigated using the Density Functional Theory (DFT). Our findings rule out the stabilizing effect of ammonia on the formation of negatively charged cluster hydrates and show clearly that the conventional (classical) treatment of ionic clusters as presumably more stable compared to neutrals may not be applicable to pre-nucleation clusters. These considerations lead us to conclude that not only quantitative but also qualitative assessment of the relative thermodynamic stability of atmospheric clusters requires a quantum-chemical treatment

Global-regional nested simulation of particle number concentration by combing microphysical processes with an evolving organic aerosol module

Aerosol microphysical processes are essential for the next generation of global and regional climate and air quality models to determine particle size distribution. The contribution of organic aerosols (OAs) to particle formation, mass, and number concentration is one of the major uncertainties in current models. A new global–regional nested aerosol model was developed to simulate detailed microphysical processes. The model combines an advanced particle microphysics (APM) module and a volatility basis set (VBS) OA module to calculate the kinetic condensation of low-volatility organic compounds and equilibrium partitioning of semi-volatile organic compounds in a 3-D framework using global–regional nested domain. In addition to the condensation of sulfuric acid, the equilibrium partitioning of nitrate and ammonium, and the coagulation process of particles, the microphysical processes of the OAs are realistically represented in our new model. The model uses high-resolution size bins to calculate the size distribution of new particles formed through nucleation and subsequent growth. The multi-scale nesting enables the model to perform high-resolution simulations of the particle formation processes in the urban atmosphere in the background of regional and global environments. By using the nested domains, the model reasonably reproduced the OA components obtained from the analysis of aerosol mass spectrometry measurements through positive matrix factorization and the particle number size distribution in the megacity of Beijing during a period of approximately a month. Anthropogenic organic species accounted for 67 % of the OAs of secondary particles formed by nucleation and subsequent growth, which is considerably larger than that of biogenic OAs. On the global scale, the model well predicted the particle number concentration in various environments. The microphysical module combined with the VBS simulated the universal distribution of organic components among the different aerosol populations. The model results strongly suggest the importance of anthropogenic organic species in aerosol particle formation and growth at polluted urban sites and over the whole globe.Aerosol microphysical processes are essential for the next generation of global and regional climate and air quality models to determine particle size distribution. The contribution of organic aerosols (OAs) to particle formation, mass, and number concentration is one of the major uncertainties in current models. A new global-regional nested aerosol model was developed to simulate detailed microphysical processes. The model combines an advanced particle microphysics (APM) module and a volatility basis set (VBS) OA module to calculate the kinetic condensation of low-volatility organic compounds and equilibrium partitioning of semi-volatile organic compounds in a 3-D framework using global-regional nested domain In addition to the condensation of sulfuric acid, the equilibrium partitioning of nitrate and ammonium, and the coagulation process of particles, the microphysical processes of the OAs are realistically represented in our new model. The model uses high-resolution size bins to calculate the size distribution of new particles formed through nucleation and subsequent growth. The multi-scale nesting enables the model to perform high-resolution simulations of the particle formation processes in the urban atmosphere in the background of regional and global environments. By using the nested domains, the model reasonably reproduced the OA components obtained from the analysis of aerosol mass spectrometry measurements through positive matrix factorization and the particle number size distribution in the megacity of Beijing during a period of approximately a month. Anthropogenic organic species accounted for 67 % of the OAs of secondary particles formed by nucleation and subsequent growth, which is considerably larger than that of biogenic OAs. On the global scale, the model well predicted the particle number concentration in various environments. The microphysical module combined with the VBS simulated the universal distribution of organic components among the different aerosol populations. The model results strongly suggest the importance of anthropogenic organic species in aerosol particle formation and growth at polluted urban sites and over the whole globe.Peer reviewe

Inverse modeling of NH3 sources using CrIS remote sensing measurements

Spatiotemporal uncertainty in emissions in the US hinders prediction of environmental effects of atmospheric . We conducted 4D-Var inversions using CrIS remote-sensing observations and GEOS-Chem to estimate monthly emissions over the contiguous US at the 0.25&deg;&times; 0.3125&deg; resolution in 2014, finding they are 33% higher than the prior emissions which likely underestimated most agricultural emissions, especially intense springtime fertilizer and livestock sources over the Central US. However, decreases were found in the Central Valley, southern Minnesota, northern Iowa and southeastern North Carolina during warm months. These updates increased the correlation coefficient between modeled monthly mean and surface observations from 0.53 to 0.84, and reduced the normalized mean bias of annual mean simulated and wet by a factor of 1.3 to 12.7. Our satellite-based inversion approach thus holds promise for improving estimates of and reactive nitrogen deposition throughout the world where measurements are scarce.</p

Limitations in representation of physical processes preven successful simulation of PM2.5 during KORUS-AQ

High levels of fine particulate matter (PM2.5) pollution in East Asia often exceed local air quality standards. Observations from the Korea United States-Air Quality (KORUS-AQ) field campaign in May and June 2016 showed that development of extreme pollution (haze) occurred through a combination of long-range transport and favorable meteorological conditions that enhanced local production of PM2.5. Atmospheric models often have difficulty simulating PM2.5 chemical composition during haze, which is of concern for the development of successful control measures. We use observations from KORUS-AQ to examine the ability of the GEOS-Chem chemical transport model to simulate PM2.5 composition throughout the campaign and identify the mechanisms driving the pollution event. In the surface level, the model underestimates campaign average sulfate aerosol by −64 % but overestimates nitrate aerosol by 36 %. The largest underestimate in sulfate occurs during the pollution event in conditions of high relative humidity, where models typically struggle to generate the high concentrations due to missing heterogeneous chemistry in aerosol liquid water in the polluted boundary layer. Hourly surface observations show that the model nitrate bias is driven by an overestimation of the nighttime peak. In the model, nitrate formation is limited by the supply of nitric acid, which is biased by +100 % against aircraft observations. We hypothesize that this is due to a missing sink, which we implement here as a factor of five increase in dry deposition. We show that the resulting increased deposition velocity is consistent with observations of total nitrate as a function of photochemical age. The model does not account for factors such as the urban heat island effect or the heterogeneity of the built-up urban landscape resulting in insufficient model turbulence and surface area over the study area that likely results in insufficient dry deposition. Other species such as NH3 could be similarly affected but were not measured during the campaign. Nighttime production of nitrate is driven by NO2 hydrolysis in the model, while observations show that unexpectedly elevated nighttime ozone (not present in the model) should result in N2O5 hydrolysis as the primary pathway. The model is unable to represent nighttime ozone due to an overly rapid collapse of the afternoon mixed layer and excessive titration by NO. We attribute this to missing nighttime heating driving deeper nocturnal mixing that would be expected to occur in a city like Seoul. This urban heating is not considered in air quality models run at large enough scales to treat both local chemistry and long-range transport. Key model failures in simulating nitrate, mainly overestimated daytime nitric acid, incorrect representation of nighttime chemistry, and an overly shallow and insufficiently turbulent nighttime mixed layer, exacerbate the model’s inability to simulate the buildup of PM2.5 during haze pollution. To address the underestimate in sulfate most evident during the haze event, heterogeneous aerosol uptake of SO2 is added to the model which previously only considered aqueous production of sulfate from SO2 in cloud water. Implementing a simple parameterization of this chemistry improves the model abundance of sulfate but degrades the SO2 simulation implying that emissions are underestimated. We find that improving model simulations of sulfate has direct relevance to determining local vs. transboundary contributions to PM2.5. During the haze pollution event, the inclusion of heterogeneous aerosol uptake of SO2 decreases the fraction of PM2.5 attributable to long-range transport from 66 % to 54 %. Locally-produced sulfate increased from 1 % to 46 % of locally-produced PM2.5, implying that local emissions controls would have a larger effect than previously thought. However, this additional uptake of SO2 is coupled to the model nitrate prediction which affects the aerosol liquid water abundance and chemistry driving sulfate-nitrate-ammonium partitioning. An additional simulation of the haze pollution with heterogeneous uptake of SO2 to aerosol and simple improvements to the model nitrate simulation results in 30 % less sulfate due to 40 % less nitrate and aerosol water, and results in an underestimate of sulfate during the haze event. Future studies need to better consider the impact of model physical processes such as dry deposition and boundary layer mixing on the simulation of nitrate and the effect of improved nitrate simulations on the overall simulation of secondary inorganic aerosol (sulfate+nitrate+ammonium) in East Asia. Foreign emissions are rapidly changing, increasing the need to understand the impact of local emissions on PM2.5 in South Korea to ensure continued air quality improvements

Constraining remote oxidation capacity with ATom observations

The global oxidation capacity, defined as the tropospheric mean concentration of the hydroxyl radical (OH), controls the lifetime of reactive trace gases in the atmosphere such as methane and carbon monoxide (CO). Models tend to underestimate the methane lifetime and CO concentrations throughout the troposphere, which is consistent with excessive OH. Approximately half of the oxidation of methane and non-methane volatile organic compounds (VOCs) is thought to occur over the oceans where oxidant chemistry has received little validation due to a lack of observational constraints. We use observations from the first two deployments of the NASA ATom aircraft campaign during July-August 2016 and January-February 2017 to evaluate the oxidation capacity over the remote oceans and its representation by the GEOS-Chem chemical transport model. The model successfully simulates the magnitude and vertical profile of remote OH within the measurement uncertainties. Comparisons against the drivers of OH production (water vapor, ozone, and NOy concentrations, ozone photolysis frequencies) also show minimal bias, with the exception of wintertime NOy. The severe model overestimate of NOy during this period may indicate insufficient wet scavenging and/or missing loss on sea-salt aerosols. Large uncertainties in these processes require further study to improve simulated NOy partitioning and removal in the troposphere, but preliminary tests suggest that their overall impact could marginally reduce the model bias in tropospheric OH. During the ATom-1 deployment, OH reactivity (OHR) below 3 km is significantly enhanced, and this is not captured by the sum of its measured components (cOHRobs) or by the model (cOHRmod). This enhancement could suggest missing reactive VOCs but cannot be explained by a comprehensive simulation of both biotic and abiotic ocean sources of VOCs. Additional sources of VOC reactivity in this region are difficult to reconcile with the full suite of ATom measurement constraints. The model generally reproduces the magnitude and seasonality of cOHRobs but underestimates the contribution of oxygenated VOCs, mainly acetaldehyde, which is severely underestimated throughout the troposphere despite its calculated lifetime of less than a day. Missing model acetaldehyde in previous studies was attributed to measurement uncertainties that have been largely resolved. Observations of peroxyacetic acid (PAA) provide new support for remote levels of acetaldehyde. The underestimate in both model acetaldehyde and PAA is present throughout the year in both hemispheres and peaks during Northern Hemisphere summer. The addition of ocean sources of VOCs in the model increases cOHRmod by 3 % to 9 % and improves model-measurement agreement for acetaldehyde, particularly in winter, but cannot resolve the model summertime bias. Doing so would require 100 Tg yr-1 of a longlived unknown precursor throughout the year with significant additional emissions in the Northern Hemisphere summer. Improving the model bias for remote acetaldehyde and PAA is unlikely to fully resolve previously reported model global biases in OH and methane lifetime, suggesting that future work should examine the sources and sinks of OH over land

Evaluation of global simulations of aerosol particle and cloud condensation nuclei number, with implications for cloud droplet formation

A total of 16 global chemistry transport models and general circulation models have participated in this study; 14 models have been evaluated with regard to their ability to reproduce the near-surface observed number concentration of aerosol particles and cloud condensation nuclei (CCN), as well as derived cloud droplet number concentration (CDNC). Model results for the period 2011-2015 are compared with aerosol measurements (aerosol particle number, CCN and aerosol particle composition in the submicron fraction) from nine surface stations located in Europe and Japan. The evaluation focuses on the ability of models to simulate the average across time state in diverse environments and on the seasonal and short-term variability in the aerosol properties. There is no single model that systematically performs best across all environments represented by the observations. Models tend to underestimate the observed aerosol particle and CCN number concentrations, with average normalized mean bias (NMB) of all models and for all stations, where data are available, of -24 % and -35 % for particles with dry diameters > 50 and > 120 nm, as well as -36 % and -34 % for CCN at supersaturations of 0.2 % and 1.0 %, respectively. However, they seem to behave differently for particles activating at very low supersaturations (<0.1 %) than at higher ones. A total of 15 models have been used to produce ensemble annual median distributions of relevant parameters. The model diversity (defined as the ratio of standard deviation to mean) is up to about 3 for simulated N-3 (number concentration of particles with dry diameters larger than 3 nm) and up to about 1 for simulated CCN in the extra-polar regions. A global mean reduction of a factor of about 2 is found in the model diversity for CCN at a supersaturation of 0.2 % (CCN0.2) compared to that for N-3, maximizing over regions where new particle formation is important. An additional model has been used to investigate potential causes of model diversity in CCN and bias compared to the observations by performing a perturbed parameter ensemble (PPE) accounting for uncertainties in 26 aerosol-related model input parameters. This PPE suggests that biogenic secondary organic aerosol formation and the hygroscopic properties of the organic material are likely to be the major sources of CCN uncertainty in summer, with dry deposition and cloud processing being dominant in winter. Models capture the relative amplitude of the seasonal variability of the aerosol particle number concentration for all studied particle sizes with available observations (dry diameters larger than 50, 80 and 120 nm). The short-term persistence time (on the order of a few days) of CCN concentrations, which is a measure of aerosol dynamic behavior in the models, is underestimated on average by the models by 40 % during winter and 20 % in summer. In contrast to the large spread in simulated aerosol particle and CCN number concentrations, the CDNC derived from simulated CCN spectra is less diverse and in better agreement with CDNC estimates consistently derived from the observations (average NMB -13 % and -22 % for updraft velocities 0.3 and 0.6 m s(-1), respectively). In addition, simulated CDNC is in slightly better agreement with observationally derived values at lower than at higher updraft velocities (index of agreement 0.64 vs. 0.65). The reduced spread of CDNC compared to that of CCN is attributed to the sublinear response of CDNC to aerosol particle number variations and the negative correlation between the sensitivities of CDNC to aerosol particle number concentration (partial derivative N-d/partial derivative N-a) and to updraft velocity (partial derivative N-d/partial derivative w). Overall, we find that while CCN is controlled by both aerosol particle number and composition, CDNC is sensitive to CCN at low and moderate CCN concentrations and to the updraft velocity when CCN levels are high. Discrepancies are found in sensitivities partial derivative N-d/partial derivative N-a and partial derivative N-d/partial derivative w; models may be predisposed to be too "aerosol sensitive" or "aerosol insensitive" in aerosol-cloud-climate interaction studies, even if they may capture average droplet numbers well. This is a subtle but profound finding that only the sensitivities can clearly reveal and may explain intermodel biases on the aerosol indirect effect.Peer reviewe