Understanding the formation processes of particles and cloud condensation nuclei (CCN) in pristine environments is a major challenge in assessing the anthropogenic impacts on climate change. Using a ...state‐of‐the‐art model that systematically simulates the new‐particle formation (NPF) from condensable vapors and multi‐scale transport of chemical species, we find that NPF contributes ∼90% of the particle number and ∼80% of the CCN at 0.5% supersaturation (CCN0.5%) in the pristine Amazon boundary layer during the wet season. The corresponding contributions are only ∼30% and ∼20% during the dry season because of prevalent biomass burning. In both seasons, ∼50% of the NPF‐induced particles and ∼85% of the NPF‐induced CCN0.5% in the boundary layer originate from the long‐range transport of new particles formed hundreds to thousands of kilometers away. Moreover, about 50%–65% of the NPF‐induced particles and 35%–50% of the NPF‐induced CCN0.5% originate from the downward transport of new particles formed aloft.
Plain Language Summary
Aerosol particles affect Earth's climate partly by acting as the seeds for cloud droplet formation, called cloud condensation nuclei (CCN). It is important to understand the processes that control the particle and CCN concentrations in pristine environments, such as the Amazon rainforest, because the radiative forcing of climate is estimated using the pristine conditions as a baseline. However, these processes are still poorly understood. Here we quantify them using a state‐of‐the‐art atmospheric model. This model is configured with advanced treatment of the initial formation of particles from condensable gases, termed new‐particle formation (NPF), as well as a state‐of‐the‐art treatment of horizontal and vertical transport of chemical species across different spatial scales. We find that NPF contributes ∼90% of the particle number and ∼80% of the CCN in the pristine Amazon boundary layer during the wet season. About half of the NPF‐induced particles and up to 85% of the NPF‐induced CCN in the boundary layer originate from the long‐range transport of new particles formed hundreds to thousands of kilometers away. About 50%–65% of the NPF‐induced particles and 35%–50% of the NPF‐induced CCN originate from the downward transport of new particles formed at high altitudes (>2 km).
Key Points
New‐particle formation (NPF) contributes ∼90% of the particle number and ∼80% of the cloud condensation nuclei (CCN) at 0.5% supersaturation in the pristine wet‐season Amazon boundary layer
About 85% of the NPF‐induced CCN in the boundary layer is contributed by new particles formed hundreds to thousands of kilometers away
About 35%–50% of the NPF‐induced CCN originates from the downward transport of new particles formed at high altitudes (>2 km)
A new fully coupled meteorology‐chemistry‐aerosol model is used to simulate the urban‐ to regional‐scale variations in trace gases, particulates, and aerosol direct radiative forcing in the vicinity ...of Houston over a 5 day summer period. Model performance is evaluated using a wide range of meteorological, chemistry, and particulate measurements obtained during the 2000 Texas Air Quality Study. The predicted trace gas and particulate distributions were qualitatively similar to the surface and aircraft measurements with considerable spatial variations resulting from urban, power plant, and industrial sources of primary pollutants. Sulfate, organic carbon, and other inorganics were the largest constituents of the predicted particulates. The predicted shortwave radiation was 30 to 40 W m−2 closer to the observations when the aerosol optical properties were incorporated into the shortwave radiation scheme; however, the predicted hourly aerosol radiative forcing was still underestimated by 10 to 50 W m−2. The predicted aerosol radiative forcing was larger over Houston and the industrial ship channel than over the rural areas, consistent with surface measurements. The differences between the observed and simulated aerosol radiative forcing resulted from transport errors, relative humidity errors in the upper convective boundary layer that affect aerosol water content, secondary organic aerosols that were not yet included in the model, and uncertainties in the primary particulate emission rates. The current model was run in a predictive mode and demonstrates the challenges of accurately simulating all of the meteorological, chemical, and aerosol parameters over urban to regional scales that can affect aerosol radiative forcing.
Recent studies have shown that instantaneous gas-particle equilibrium partitioning assumptions fail to predict SOA formation, even at high relative humidity (∼85%), and photochemical aging seems to ...be one driving factor. In this study, we probe the minimum aging time scale required to observe nonequilibrium partitioning of semivolatile organic compounds (SVOCs) between the gas and aerosol phase at ∼50% RH. Seed isoprene SOA is generated by photo-oxidation in the presence of effloresced ammonium sulfate seeds at <1 ppbv NO x , aged photochemically or in the dark for 0.3–6 h, and subsequently exposed to fresh isoprene SVOCs. Our results show that the equilibrium partitioning assumption is accurate for fresh isoprene SOA but breaks down after isoprene SOA has been aged for as short as 20 min even in the dark. Modeling results show that a semisolid SOA phase state is necessary to reproduce the observed particle size distribution evolution. The observed nonequilibrium partitioning behavior and inferred semisolid phase state are corroborated by offline mass spectrometric analysis on the bulk aerosol particles showing the formation of organosulfates and oligomers. The unexpected short time scale for the phase transition within isoprene SOA has important implications for the growth of atmospheric ultrafine particles to climate-relevant sizes.
The diffusivity of semivolatile organic compounds (SVOCs) in the bulk particle phase of a viscous atmospheric secondary organic aerosol (SOA) can have a profound impact on aerosol growth and size ...distribution dynamics. Here, we investigate the bulk diffusivity of SVOCs formed from photo-oxidation of isoprene as they partition to a bimodal aerosol consisting of an Aitken (potassium sulfate) and accumulation mode (aged α-pinene SOA) particles as a function of relative humidity (RH). The model analysis of the observed size distribution evolution shows that liquid-like diffusion coefficient values of D b > 10–10 cm2 s–1 fail to explain the growth of the Aitken mode. Instead, much lower values of D b between 2.5 × 10–15 cm2 s–1 at 32% RH and 8 × 10–15 cm2 s–1 at 82% RH were needed to successfully reproduce the growth of both modes. The diffusivity within the aged α-pinene SOA remains appreciably slow even at 80% RH, resulting in hindered partitioning of SVOCs to large viscous particles and allowing smaller and relatively less viscous particles to effectively absorb the available SVOCs and grow much faster than would be possible otherwise. These results have important implications for modeling SOA formation and growth in the ambient atmosphere.
Secondary organic aerosol (SOA) accounts for a large fraction of the tropospheric particulate matter. Although SOA production rates and mechanisms have been extensively investigated, loss pathways ...remain uncertain. Most large-scale chemistry and transport models account for mechanical deposition of SOA but not chemical losses such as photolysis. There is also a paucity of laboratory measurements of SOA photolysis, which limits how well photolytic losses can be modeled. Here, we show, through a combined experimental and modeling approach, that photolytic loss of SOA mass significantly alters SOA budget predictions. Using environmental chamber experiments at variable relative humidity between 0 and 60%, we find that SOA produced from several biogenic volatile organic compounds undergoes photolysis-induced mass loss at rates between 0 and 2.2 ± 0.4% of nitrogen dioxide (NO2) photolysis, equivalent to average atmospheric lifetimes as short as 10 h. We incorporate our photolysis rates into a regional chemical transport model to test the sensitivity of predicted SOA mass concentrations to photolytic losses. The addition of photolysis causes a ∼50% reduction in biogenic SOA loadings over the Amazon, indicating that photolysis exerts a substantial control over the atmospheric SOA lifetime, with a likely dependence upon the SOA molecular composition and thus production mechanisms.
To improve predictions of air quality, visibility, and climate change, knowledge of the viscosities and diffusion rates within organic particulate matter consisting of secondary organic material ...(SOM) is required. Most qualitative and quantitative measurements of viscosity and diffusion rates within organic particulate matter have focused on SOM particles generated from biogenic volatile organic compounds (VOCs) such as α-pinene and isoprene. In this study, we quantify the relative humidity (RH)-dependent viscosities at 295 ± 1 K of SOM produced by photo-oxidation of toluene, an anthropogenic VOC. The viscosities of toluene-derived SOM were 2 × 10−1 to ∼ 6 × 106 Pa s from 30 to 90 % RH, and greater than ∼ 2 × 108 Pa s (similar to or greater than the viscosity of tar pitch) for RH ≤ 17 %. These viscosities correspond to Stokes–Einstein-equivalent diffusion coefficients for large organic molecules of ∼ 2 × 10−15 cm2 s−1 for 30 % RH, and lower than ∼ 3 × 10−17 cm2 s−1 for RH ≤ 17 %. Based on these estimated diffusion coefficients, the mixing time of large organic molecules within 200 nm toluene-derived SOM particles is 0.1–5 h for 30 % RH, and higher than ∼ 100 h for RH ≤ 17 %. As a starting point for understanding the mixing times of large organic molecules in organic particulate matter over cities, we applied the mixing times determined for toluene-derived SOM particles to the world's top 15 most populous megacities. If the organic particulate matter in these megacities is similar to the toluene-derived SOM in this study, in Istanbul, Tokyo, Shanghai, and São Paulo, mixing times in organic particulate matter during certain periods of the year may be very short, and the particles may be well-mixed. On the other hand, the mixing times of large organic molecules in organic particulate matter in Beijing, Mexico City, Cairo, and Karachi may be long and the particles may not be well-mixed in the afternoon (15:00–17:00 LT) during certain times of the year.
Soot particles form during combustion of carbonaceous materials and impact climate and air quality. When freshly emitted, they are typically fractal-like aggregates. After atmospheric aging, they can ...act as cloud condensation nuclei, and water condensation or evaporation restructure them to more compact aggregates, affecting their optical, aerodynamic, and surface properties. Here we survey the morphology of ambient soot particles from various locations and different environmental and aging conditions. We used electron microscopy and show extensive soot compaction after cloud processing. We further performed laboratory experiments to simulate atmospheric cloud processing under controlled conditions. We find that soot particles sampled after evaporating the cloud droplets, are significantly more compact than freshly emitted and interstitial soot, confirming that cloud processing, not just exposure to high humidity, compacts soot. Our findings have implications for how the radiative, surface, and aerodynamic properties, and the fate of soot particles are represented in numerical models.
The optical properties of an internally mixed aerosol with a lognormal size distribution can be approximated in terms of analytic functions of the wet surface mode radius with coefficients that can ...be related to the wet refractive index. The wet radius is calculated from the dry radius and relative humidity using either the Köhler theory or the MOSAIC thermodynamic model. The hydration state of the aerosol in the hysteresis region between the crystallization and deliquescence relative humidities is diagnosed by comparing the aerosol water from the previous time step with the current water content of the hydrated aerosol. The wet refractive index is estimated from the volume fractions and refractive indices of all components of the aerosol, including water, using volume mixing for soluble components and an effective medium approximation for the insoluble components. The parameterization is evaluated by comparing with Mie solutions for ammonium sulfate, black carbon, and a 50:50 mixture for a wide range in size distributions and relative humidity. Errors are usually less than 20% and are less then 30% for all conditions except when absolute values are small. The parameterization is suitable for any aerosol model that uses lognormal size distributions composed of internal mixtures of multiple aerosol components.
Black carbon (BC) plays an important role in the climate system because of its strong warming effect, yet the magnitude of this effect is highly uncertain owing to the complex mixing state of ...aerosols. Here we build a unified theoretical framework to describe BC's mixing states, linking dynamic processes to BC coating thickness distribution, and show its self-similarity for sites in diverse environments. The size distribution of BC-containing particles is found to follow a universal law and is independent of BC core size. A new mixing state module is established based on this finding and successfully applied in global and regional models, which increases the accuracy of aerosol climate effect estimations. Our theoretical framework links observations with model simulations in both mixing state description and light absorption quantification.
Mounting evidence from field and laboratory observations coupled with atmospheric model analyses shows that primary combustion emissions of organic compounds dynamically partition between the vapor ...and particulate phases, especially as near-source emissions dilute and cool to ambient conditions. The most recent version of the Community Multiscale Air Quality model version 5.2 (CMAQv5.2) accounts for the semivolatile partitioning and gas-phase aging of these primary organic aerosol (POA) compounds consistent with experimentally derived parameterizations. We also include a new surrogate species, potential secondary organic aerosol from combustion emissions (pcSOA), which provides a representation of the secondary organic aerosol (SOA) from anthropogenic combustion sources that could be missing from current chemical transport model predictions. The reasons for this missing mass likely include the following: (1) unspeciated semivolatile and intermediate volatility organic compound (SVOC and IVOC, respectively) emissions missing from current inventories, (2) multigenerational aging of organic vapor products from known SOA precursors (e.g., toluene, alkanes), (3) underestimation of SOA yields due to vapor wall losses in smog chamber experiments, and (4) reversible organic compounds-water interactions and/or aqueous-phase processing of known organic vapor emissions. CMAQ predicts the spatially averaged contribution of pcSOA to OA surface concentrations in the continental United States to be 38.6 and 23.6 % in the 2011 winter and summer, respectively. Whereas many past modeling studies focused on a particular measurement campaign, season, location, or model configuration, we endeavor to evaluate the model and important uncertain parameters with a comprehensive set of United States-based model runs using multiple horizontal scales (4 and 12 km), gas-phase chemical mechanisms, and seasons and years. The model with representation of semivolatile POA improves predictions of hourly OA observations over the traditional nonvolatile model at sites during field campaigns in southern California (CalNex, May-June 2010), northern California (CARES, June 2010), the southeast US (SOAS, June 2013; SEARCH, January and July, 2011). Model improvements manifest better correlations (e.g., the correlation coefficient at Pasadena at night increases from 0.38 to 0.62) and reductions in underprediction during the photochemically active afternoon period (e.g., bias at Pasadena from -5.62 to -2.42 μg m
). Daily averaged predictions of observations at routine-monitoring networks from simulations over the continental US (CONUS) in 2011 show modest improvement during winter, with mean biases reducing from 1.14 to 0.73μg m
, but less change in the summer when the decreases from POA evaporation were similar to the magnitude of added SOA mass. Because the model-performance improvement realized by including the relatively simple pcSOA approach is similar to that of more-complicated parameterizations of OA formation and aging, we recommend caution when applying these more-complicated approaches as they currently rely on numerous uncertain parameters. The pcSOA parameters optimized for performance at the southern and northern California sites lead to higher OA formation than is observed in the CONUS evaluation. This may be due to any of the following: variations in real pcSOA in different regions or time periods, too-high concentrations of other OA sources in the model that are important over the larger domain, or other model issues such as loss processes. This discrepancy is likely regionally and temporally dependent and driven by interferences from factors like varying emissions and chemical regimes.
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