Aerosol and Air Quality Research, 16: 900–908, 2016 Copyright © Taiwan Association for Aerosol Research ISSN: 1680-8584 print / 2071-1409 online doi: 10.4209/aaqr.2015.05.0368 

Vertical Profiles and Seasonal Variations of Key Parameters Controlling Particle Formation and Growth at Storm Peak Laboratory Fangqun Yu1*, Gan Luo1, A. Gannet Hallar2

1 Atmospheric Sciences Research Center, State University of New York, 251 Fuller Road, Albany, New York 12203, USA 2 Desert Research Institute, Storm Peak Laboratory, Steamboat Springs, CO 80488, USA ABSTRACT

Here we compare model simulated number concentrations of condensation nuclei larger than 10 nm (CN10) in 2009 with those measured at the Storm Peak Laboratory (SPL), a high elevation mountain-top observatory in northwestern Colorado, US. We also investigate vertical profiles and seasonal variations of key parameters controlling particle formation and growth over this remote mountain-top site. The model overall captures absolute values of CN10 and their variations, especially in the spring months where regional scale new particle formation (NPF) occurred frequently. The model is able to predict the right magnitude of background CN10 values in July and August but it fails to reproduce the short-term spikes in CN10 and thus under-predicts the mean CN10 in these two months. The vertical profiles of key parameters relevant to NPF, including temperature and concentrations of SO2, secondary organic gases (SOG), OH, H2SO4 and low volatility SOG, show clear seasonal variations that lead to relatively high frequency of NPF in the spring and fall. Vertically, high concentrations of precursors and aerosol number concentrations are generally confined to the boundary layer and lower troposphere. Keywords: New particle formation; Condensation nuclei; Mountain-top observatory; Global aerosol model; Ion-mediated nucleation. INTRODUCTION

New particle formation (NPF), frequently observed at various locations around the globe (Kulmala et al., 2004; Yu et al., 2008), largely determines the particle number concentrations in most part of troposphere and is an important source of cloud condensation nuclei (CCN) (Spracklen et al., 2008; Pierce and Adams, 2009; Yu and Luo, 2009). Despite of the significant progress achieved with regard to mechanisms of NPF in the past decade, the key processes and parameters controlling NPF under different atmospheric environments remain elusive (Zhang et al., 2013). Most existing NPF measurements were taken at the surface stations (Kulmala et al., 2004). In the past, empirical nucleation parameterizations have been derived from surface measurements (Riipinen et al., 2007; Kuang et al., 2008) but their application in the model is generally limited to boundary layer (e.g., Spracklen et al., 2008). It is important to understand how NPF varies with altitudes and its contribution to CCN, especially at altitudes from the top * Corresponding author.

Tel.: 518-437-8767; Fax: 518-437-8758 E-mail address: fyu@albany.edu

of boundary layer to middle troposphere (3–5 km) where most liquid clouds form. Using long-term data from two different high altitude sites ‒ the Puy de Dôme research station (1465 m a.s.l.) and the Opme Station (660 m a.s.l.) in central France, Boulon et al. (2011) showed that NPF occurred more frequently at the higher elevation. In this regard, NPF measurements at mountain top sites with various elevations (Hallar et al., 2016) provide a unique set of data that can help to advance our understanding of the altitude-dependent NPF.

NPF has been observed frequently at Storm Peak Laboratory (SPL), a high elevation mountain-top observatory in northwestern Colorado. SPL is situated on a 70 km ridge oriented perpendicular to the prevailing westerly winds (Hallar et al., 2011). Yu and Hallar (2014) investigated in detail the NPF during the two contrasting months (March and July, 2012) at SPL, through comparisons of aerosol measurements with model simulations based on a global chemical transport model (GEOS-Chem) coupled with a size-resolved advanced particle microphysics (APM) model. They showed significant differences in NPF during the spring and summer months at SPL: Persistent long-lasting NPF occurred on a daily basis in March but was absent in July while short-lasting bursts of ultrafine particles appeared frequently in July. While the GEOS-Chem/APM model captures well the observed persistent daily nucleation events

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in March and the absence of regional scale NPF in July, it is not able to reproduce the short-lasting bursts of ultrafine particles in July (Yu and Hallar, 2014). The short-lasting bursts in July have been suggested to be associated with nucleation in sub-grid power plant plumes (Yu and Hallar, 2014). Another possible reason for the observed short-lasting bursts could be the quick mixing down of particles nucleated aloft during the summer. In this regard, it is also important to understand the difference in the NPF intensity at various altitudes in different seasons.

In this study, we compare the year-long (2009) model predicted particle number concentrations with measurements at SPL and study the vertical profiles and seasonal variations of key parameters controlling particle formation and growth over this remote mountain-top site. SPL Site Information and Aerosol Measurements

SPL, located on the west summit of Mt. Werner in the Routt National Forest and approximately 1150 m above the agricultural Yampa Valley in northwestern Colorado, is a high elevation (3210 m above sea level) mountain top research facility maintained and operated by the Desert Research Institute (DRI) (Borys and Wetzel, 1997; Hindman, 2001; Hallar et al., 2011; http://stormpeak.dri.edu). The SPL site is an ideal location for long-term research on chemistry-aerosol-cloud-radiation interactions as the ridge-top location produces almost daily transition from free-tropospheric to boundary layer air and thus allows for time-extended measurements of free tropospheric, in-cloud, and boundary layer air (Borys and Wetzel, 1997; Lowenthal et al., 2002). Both long-term and short-term intensive aerosol measurements have been made in SPL (e.g., Hallar et al., 2011; Friedman et al., 2013; Hallar et al., 2013, 2016). In the present study, we use long-term total number concentrations of particles larger than 10 nm (CN10) obtained with a stand-alone TSI (model 3010) condensation particle counter (CPC). Particles were sampled from an insulated, six-inch diameter manifold within four feet of its horizontal entry point through an outside wall. The 4 m high vertical section outside the building is capped with an inverted can to exclude large particles (diameter > ~8 µm) as well as precipitation. All data are collected and then pre-screened by SPL staff prior to generation of the final quality controlled data set. Local contamination sources (e.g., snowmobiles and snow cat passing SPL during the ski season) were removed from the final data set.  GEOS-Chem-APM Model Description and Modeling Information

The GEOS-Chem model is a global 3-D model of atmospheric composition developed and used by many research groups, and contains a number of state-of-the-art modules treating various chemical and aerosol processes (e.g., Bey et al., 2001; Chung and Seinfeld, 2002; Martin et al., 2003; Park et al., 2004; Evans and Jacob, 2005; Liao et al., 2007; Henze et al., 2008). Yu and Luo (2009) incorporated an advanced particle microphysics (APM) model into GEOS-Chem. The APM model in GEOS-Chem is optimized to accurately simulate the formation of secondary particles

and their growth to CCN sizes, using very high size resolution (30 bins) for particles in the size range of 1.2–120 nm (10 additional bins for 0.12–12 µm particles) (Yu and Luo, 2009) and considering explicitly the kinetic condensation of aged low volatility secondary organic gases (Yu, 2011). The APM model employs 20 bins for sea salt to cover the dry diameter size range of 0.012 µm to 12 µm, and 15 bins for dust particles to cover size range of 0.03 µm to 50 µm. Because of large differences in the median sizes of black carbon (BC) and primary organic carbon (POC) from fossil fuel combustion and biomass burning, we employ two log-normal modes (one for fossil fuel and another for biomass burning) to represent hydrophobic BC and another two log-normal modes for hydrophilic BC (Yu and Luo, 2009). Similarly, 4 log-normal modes are used to represent hydrophobic and hydrophilic POC. The GEOS-Chem model is driven by assimilated meteorological observations from the Goddard Earth Observing System (GEOS) of the NASA Global Modeling and Assimilation Office (GMAO). The emission inventories and schemes used in the model have been summarized in Yu and Hallar (2014) and are not repeated here. More detailed information of GEOS-Chem model can also be found in the model webpage (http://geos-chem.org/).

The results presented below are based on a one-year simulation (10/2008–12/2009, with the first 3 months as spin-up) using GEOS-Chem v8-03-02 + APM. The model calculates nucleation rates based on the ion-mediated nucleation (IMN) of the H2SO4–H2O binary system (Yu, 2010a). The IMN scheme calculates formation rates of particles at wet sizes of ~1.5 nm (Yu, 2010a) and the nucleated particles are added into the first bin (wet size ~1.5 nm) of the secondary particles, The processes to grow nucleated particles to large sizes include kinetic condensation of H2SO4 and low volatility secondary organic gases (SOGs), equilibrium uptake of nitrate and ammonium, partitioning uptake of other SOGs with relatively high volatility, and self-coagulation (Yu, 2011). The horizontal resolution is 2° × 2.5° and there are 47 vertical layers (sigma coordinate, with 14 layers from surface to ~2 km above surface). Concentrations of all tracers and values of relevant parameters in the first 28 layers over SPL (750 mb–270 mb) were output at each chemistry time step (30 minutes) and used here to study vertical profiles and seasonal variations of key parameters controlling particle formation and growth. RESULTS

Fig. 1 shows the time series of both observed and modeled hourly mean CN10 at SPL site for 2009 whole year (a) and two zoomed in months (b. March and c. August). Table 1 compares the monthly mean CN10 values. It should be noted that the pressure of model surface layer in the SPL region is ~750 mb, corresponding to that of Yampa Valley. The pressure at SPL is ~680–700 mb, corresponding to the 7th model layer from the surface. In the comparison shown in Fig. 1, the modeled values in the 7th model layer are used to compare with the SPL measurements. As it has been emphasized in Yu and Hallar (2014), one needs to pay attention to the limitations in comparing aerosol properties

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Fig. 1. Time series of observed and modeled hourly mean CN10 at SPL site for 2009 whole year (a) and two zoomed in months (b. March and c. August). The pressure of SPL is ~680–700 mb, corresponding to the 7th model layer from the surface. The modeled CN10 in the 7th model layer are used to compare with the measurements.

simulated with a global model to detailed measurements at a mountain top site as the global model (with a horizontal resolution of 2° × 2.5°) is unable to resolve the sub-grid scale topography, mixing, and processes. With these limitations kept in mind, it can be seen from Fig. 1 and Table 1 that the model overall captures absolute values of CN10 and their variations, especially in the spring months (March–May) where regional scale NPF occurred frequently (Fig. 1(b)). Corresponding to the time periods where hourly CN10 data are available as shown in Fig. 1 (total 6773 data points), the observed and simulated mean CN10 values are 2295

and 2432 cm–3, respectively. The correlation coefficient is 0.3 and the mean model bias is 6.0% for the whole period. The correlation coefficient reaches 0.63 for March but is negative for July and August. The model is able to predict the right magnitude of background CN10 values (~1000 cm–3) in July and August, but it fails to reproduce the short-term spikes in hourly mean CN10 (Fig. 1(c)) and thus under-predicts the mean CN10 in these two months. In addition to the spring, the model predicts significant NPF in the fall (September–November) but unfortunately CN10 data is not available after Day 290. The predicted relatively high

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Table 1. Comparisons of observed and simulated monthly mean CN10. Mean simulated CN10 and model bias were calculated for the periods when observations were available (indicated by the column “# of hourly data”).

Month # of hourly

data Observed CN10

(# cm–3) Simulated CN10

(# cm–3) Correlation Coefficient

Mean model bias(%)

1 631 1780 1087 0.18 –38.9 2 667 2360 2978 0.47 26.2 3 733 2972 3412 0.63 14.8 4 719 2265 2792 0.23 23.3 5 743 2939 3139 0.38 6.8 6 719 2334 3084 0.24 32.1 7 740 2552 989 –0.20 –61.2 8 709 2567 1445 –0.01 –43.7 9 710 1408 1791 0.16 27.2

10 393 1168 4341 0.46 272.0

Fig. 2. Vertical profiles of (a) temperature (T), (b) relative humidity (RH), and (c) wind direction as a function of Day of Year (DOY) in 2009. The shown T and RH are daytime-averaged (8 am to 5 pm local time) values.

frequency of regional NPF events in the spring and fall is consistent with that derived from multiple-year NPF climatology analysis reported in Hallar et al. (2016).

As pointed out earlier, the pressure of SPL site (~690 mb) corresponds to the 7th layer of the model which is around in the top of the boundary layer, consistent with the well-established almost daily transition from free-tropospheric to boundary layer air at the ridge-top site SPL (Obrist et al., 2008). The reasonable agreement between simulated and observed CN10 and seasonal variations of NPF at the SPL site (Fig. 1, also Yu and Hallar, 2014) may indicate that the model captures the main processes controlling regional scale particle formation and growth at this remote ridge-top site. Below we look into the modeled vertical

profiles and seasonal variations of key parameters controlling the formation and growth of particles over the SPL region. Many parameters have strong diurnal variations and NPF events at SPL occur only during daytime. In order to show the seasonal variations more clearly, all parameters presented in Figs. 2–4 are daytime-averaged (8 am to 5 pm local time) values except wind directions which we use un-averaged 30-min model output.

Apparently meteorology is important for chemistry and resulting NPF. Fig. 2 gives vertical profiles of temperature (T), relative humidity (RH), and wind direction based on GEOS-5 assimilated meteorology as a function of Day of Year (DOY) in 2009. T at SPL can reach above 290 K in the summer while is generally below 280 K in other seasons.

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The decrease of T with altitudes is more obvious in the summer, down to < 280 K above ~600 mb. RH is generally lower in the summer and the high RH time periods shown in Fig. 2(b) mostly correspond to the presence of clouds. SPL is dominated by westerly winds, although winds from other directions can still occur during certain time periods (Fig. 2(c)). The vertical variations of wind directions are generally small above ~700 mb but it appears that there

exist a shift in wind directions from more southerly winds at the surface (~750 mb) to more westerly winds at the boundary layer top (~700 mb).

Previous measurements of particle compositions indicate that the mass of particles at SPL is dominated by sulfate in March (Friedman et al., 2013) and by organic compounds (OC) in July (Hallar et al., 2013). In addition to the sulfur chemistry, GEOS-Chem considers fairly detailed chemistry

Fig. 3. Vertical profiles of (a) [SO2], (b) [SOG1], (c) [SOG4], (d) [OH], (e) PH2SO4, and (f) PLVSOG as a function of Day of Year (DOY) in 2009. All shown parameters are daytime-averaged (8 am to 5 pm local time) values.

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of reactive biogenic volatile organic compounds (VOCs) (Chung and Seinfeld, 2002; Liao et al., 2007). The reactive VOCs on the mountain surrounding SPL are dominated by isoprene and monoterpenes. In GEOS-Chem v8-3-2 on which this study is based, reactive VOCs and their oxidation products are lumped into different groups. The first generation oxidation products of monoterpenes are lumped into 1st group of secondary organic gases (SOG1) while those of isoprene are lumped into 4th group (SOG4). Fig. 3 presents the vertical profiles of [SO2], [SOG1], [SOG4], and [OH] as well as the gas-phase production rates of H2SO4 (denoted as PH2SO4) and the gas-phase production rates of low-volatility SOG (LVSOG) (denoted as PLVSOG). LVSOG represents the multiple generation oxidation products from successive oxidation aging of the first generation oxidation

products (i.e., SOG1, SOG4, etc.), calculated using the scheme described in Yu (2011). LVSOG has a saturation vapor concentration in the range of ~0.0001–0.03 µg m–3, corresponding to the extremely low volatility SOG observed by and reported in Ehn et al. (2014).

Fig. 3 demonstrates that all parameters have clear season variations. [SOG1] and [SOG4], as well as PLVSOG, are much higher in the summer (June–August), mainly as a result of much larger emissions of biogenic VOCs in the summer. In contrast, [SO2] is lowest in the summer due to stronger vertical mixing rate and increased oxidation. It is interesting to note that [OH] in the spring and fall is higher than that in the summer. The relatively lower [OH] in July and August is mainly due to the depletion of OH by isoprene (Fig. 3(c)) (Kiendler-Scharr et al., 2009). Relatively low [OH]

Fig. 4. Vertical profiles of (a) CS, (b) [H2SO4], (c) [LVSOG], (d) J, and (e) CN10 as a function of Day of Year (DOY) in 2009. All shown parameters are daytime-averaged (8 am to 5 pm local time) values.

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and [SO2] leads to lower PH2SO4 in the summer. Vertically, high [SO2] and PH2SO4 are generally confined to the lower troposphere (~750–700 mb) due to weak mixing but can extend to 500–600 mb in the summer. In the summer, SOG1 and SOG4 are well mixed in the lower troposphere (surface to ~500 mb) but their concentrations drop quickly above ~500 mb. Throughout the winter, spring, and fall, [SOG4] values are higher in the middle/upper troposphere; In fact, values found in this region are similar to those in the lower troposphere, indicating the transport of SOG4 formed elsewhere to the SPL region. The shape of PLVSOG (Fig. 3(f)) is closer to that of SOG1 (Fig. 3(b)) as SOG1 is a major source of LVSOG. Compared to [SOG1 + SOG4] and PLVSOG, [SO2] and PH2SO4 are much larger in the spring but is much smaller in the summer. This is consistent with the observed dominance of SPL particle mass by sulfate in the spring and by OC in the summer.

PH2SO4 and PLVSOG, together with condensation sink (CS), determine [H2SO4] and [LV-SOG] respectively. Fig. 4 gives the profiles of CS, [H2SO4], [LV-SOG], particle nucleation rate (J) calculated based on IMN mechanism, and CN10. CS, depending on particle size distributions and RH, has no obvious seasonal variations. This is consistent with previous calculated CS values (1 ± 0.5 × 10–3 s–1) based on observations at SPL (Hallar et al., 2011) across the spring, summer and winter seasons. As a result, both vertical profiles and seasonal variations of [H2SO4] (Fig. 4(b)) and [LVSOG] (Fig. 4(c)) follow the pattern of PH2SO4 and PLVSOG, respectively. Based on the IMN mechanism (Yu, 2010a), [H2SO4] and T are the two most important parameters (or limiting factors) determining nucleation rates under typical atmospheric conditions. In the present study, the possible role of LVSOG in enhancing NPF is not considered but the contribution of LVSOG to particles through kinetic condensation is explicitly simulated. The relatively higher [H2SO4] (Fig. 4(b)) and lower T (Fig. 2(a)) in the spring and fall lead to strongest NPF. In the winter, NPF also occurs but it is mostly limited to lower boundary layer (750 mb–~700 mb). The relatively lower [H2SO4] and higher T in the summer result in negligible regional scale nucleation at SPL. Vertically, most NPF occurs in the lower troposphere (below ~600 mb) and there appears to be a moderate nucleation zone around 600 mb in the summer (Fig. 4(d)). The vertical profiles and seasonal variations of CN10 (Fig. 4(e)) are close to those of J, indicating the dominance of particle number concentrations by nucleation process. CN10 in the boundary layer is much higher than that above the boundary in all seasons except the summer. As shown earlier (Fig. 1), the model under-predicts CN10 in the summer.

SUMMARY AND DISCUSSION

Long-term measurements of new particle formation (NPF) at mountain top sites provide unique dataset important for understanding key processes and parameters controlling particle formation and number concentrations within the altitude ranges where clouds form. NPF has been observed frequently at Storm Peak Laboratory (SPL), a high elevation mountain-top observatory in northwestern Colorado, US.

In this study, one-year (2009) simulations based on a global chemistry transport model with size-resolved aerosol microphysics are analyzed to investigate vertical profiles and seasonal variations of key parameters controlling particle formation and growth over this remote mountain-top site. The vertical profiles of key parameters relevant to NPF, including temperature and concentrations of SO2, secondary organic gases (SOG), OH, H2SO4 and low volatility SOG, show clear seasonal variations that lead to relatively high frequency of NPF in the spring and fall. [SO2] is relatively lower in the summer due to strong vertical mixing and oxidation while [SOG] is much higher in the summer as a result of large biogenic emissions. [OH] in July and August is lower than that in the spring and fall, likely because of the depletion of OH by isoprene. The relatively high [H2SO4] and lower temperature in the spring and fall explain the observed relatively high frequency of NPF during the two seasons. A comparison of model simulated number concentrations of condensation nuclei larger than 10 nm (CN10) with those measured at SPL show that the model overall captures absolute values of CN10 and their variations, especially in the spring months where regional scale NPF occurred frequently. In July and August, the model is able to predict the right magnitude of background CN10 values but it fails to reproduce the short-lasting spikes in CN10 and hence under-predicts the mean CN10. One possible explanation of the short-lasting CN10 spikes is the NPF in sub-grid power plant plumes (Yu, 2011; Stevens and Pierce, 2013). Stevens and Pierce (2014) developed parameterization for sub-grid NPF in power-plant plumes and implemented it in a recent version of the GEOS-Chem model. Further research is needed to study if the short-lasting CN10 spikes during the summer at SPL can be explained by sub-grid NPF in power-plant plumes and how much the sub-grid NPF parameterization can improve the agreement of global model simulation at the SPL site with observations. In this regard, simulations with models of high spatial resolution are needed. In addition, the possible roles of other nucleation processes such as ammonia, amine, and/or organics assisted nucleation (Zhang et al., 2012) in the formation of new particles at SPL in different seasons should be investigated. ACKNOWLEDGMENTS

This study was supported by NASA under grant NNX13AK20G. The authors appreciate the Steamboat Ski Resort for providing logistical support and in-kind donations towards this study. The DRI’s SPL is an equal opportunity service provider and employer and is a permittee of the Medicine-Bow Routt National Forests. The GEOS-Chem model is managed by the Atmospheric Chemistry Modeling Group at Harvard University with support from NASA’s Atmospheric Chemistry Modeling and Analysis Program.

REFERENCES Bey, I., Jacob, D.J., Yantosca, R.M., Logan, J.A., Field, B.D.,

Fiore, A.M., Li, Q., Liu, H.Y., Mickley, L.J. and Schultz,

Yu et al., Aerosol and Air Quality Research, 16: 900–908, 2016  907

M.G. (2001). Global Modeling of Tropospheric Chemistry with Assimilated Meteorology: Model Description and Evaluation. J. Geophys. Res. 106, 23073–23096.

Borys, R.D. and Wetzel, M.A. (1997). Storm Peak Laboratory: A Research, Teaching and Service Facility for the Atmospheric Sciences. Bull. Am. Meteorol. Soc. 78: 2115–2123.

Boulon, J., Sellegri, K., Hervo, M., Picard, D., Pichon, J.M., Fréville, P. and Laj, P. (2011). Investigation of Nucleation Events Vertical Extent: A Long Term Study at Two Different Altitude Sites. Atmos. Chem. Phys. 11: 5625–5639.

Chung, S.H. and Seinfeld, J.H. (2002). Global Distribution and Climate Forcing of Carbonaceous Aerosols. J. Geophys. Res. 107: 4407, doi: 10.1029/2001JD001397.

Ehn, M., Thornton, J.A., Kleist, E., Sipila, M., Junninen, H., Pullinen, I., Springer, M., Rubach, F., Tillmann, R., Lee, B., Lopez-Hilfiker, F., Andres, S., Acir, I.H., Rissanen, M., Jokinen, T., Schobesberger, S., Kangasluoma, J., Kontkanen, J., Nieminen, T., Kurten, T., Nielsen, L.B., Jorgensen, S., Kjaergaard, H.G., Canagaratna, M., Maso, M.D., Berndt, T., Petaja, T., Wahner, A., Kerminen, V.M., Kulmala, M., Worsnop, D.R., Wildt, J. and Mentel, T.F. (2014). A Large Source of Low-volatility Secondary Organic Aerosol. Nature 506: 476–479, doi: 10.1038/na ture13032.

Evans M.J. and Jacob D.J. (2005). Impact of New Laboratory Studies of N2O5 Hydrolysis on Global Model Budgets of Tropospheric Nitrogen Oxides, Ozone, and OH. Geophys. Res. Lett. 32: L09813.

Friedman, B., Zelenyuk, A., Beránek, J., Kulkarni, G., Pekour, M., Hallar, A.G., McCubbin, I.B., Thornton, J.A. and Cziczo, D.J. (2013). Aerosol Measurements at a High-elevation Site: Composition, Size, and Cloud Condensation Nuclei Activity. Atmos. Chem. Phys. 13: 11839–11851, doi: 10.5194/acp-13-11839-2013.

Hallar, A.G., Lowenthal, D.H., Chirokova, G., Wiedinmyer, C. and Borys, R.D. (2011). Persistent Daily New Particle Formation at a Mountain-top Location. Atmos. Environ. 45: 4111–4115, doi: 10.1016/j.atmosenv.2011.04.044.

Hallar, A.G., Lowenthal, D.H., Clegg, S.L., Samburova, V., Taylor, N., Mazzoleni, L.R., Zielinska, B.K., Kristensen, T.B., Chirokova, G., McCubbin, I.B., Dodson, C. and Collins, D. (2013). Chemical and Hygroscopic Properties of Aerosol Organics at Storm Peak Laboratory. J. Geophys. Res. 118: 4767–4779, doi: 10.1002/jgrd.50373.

Hallar, A.G., Petersen, R., McCubbin, I.B., Lowenthal, D., Lee, S., Andrews, E. and Yu, F. (2016). Climatology of New Particle Formation and Corresponding Precursors at Storm Peak Laboratory. Aerosol Air Qual. Res. 16: 816–826.

Henze, D.K., Seinfeld, J.H., Ng, N.L., Kroll, J.H., Fu, T.M., Jacob, D.J. and Heald, C.L. (2008). Global Modeling of Secondary Organic Aerosol Formation from Aromatic Hydrocarbons: High- vs. Low-Yield Pathways. Atmos. Chem. Phys. 8: 2405–2420.

Hindman, E.E. (2001). The Cloud Catchers. Weatherwise 54: 30–36.

Kiendler-Scharr, A., Wildt, J., Dal Maso, M., Hohaus, T.,

Kleist, E., Mentel, T.F., Tillmann, R., Uerlings, R., Schurr, U. and Wahner, A. (2009). New Particle Formation in Forests Inhibited by Isoprene Emissions. Nature 461: 381–384.

Kuang, C., McMurry, P.H., McCormick, A.V. and Eisele, F.L. (2008), Dependence of Nucleation Rates on Sulfuric Acid Vapor Concentration in Diverse Atmospheric Locations. J. Geophys. Res. 113: D10209, doi: 10.1029/ 2007JD009253.

Kulmala, M., Vehkamäki, H., Petäjä, T., Dal Maso, M., Lauri, A., Kerminen, V.M., Birmili, W. and McMurry, P.H. (2004). Formation and Growth Rates of Ultrafine Atmospheric Particles: A Review of Observations. J. Aerosol Sci. 35: 143–176.

Liao, H., Henze, D.K., Seinfeld, J.H., Wu, S. and Mickley, L.J. (2007). Biogenic Secondary Organic Aerosol over the United States: Comparison of Climatological Simulations with Observation. J. Geophys. Res. 112: D06201.

Lowenthal, D.H., Borys, R.D. and Wetzel, M.A. (2002). Aerosol Distributions and Cloud Interactions at a Mountaintop Laboratory. J. Geophys. Res. 108: 4345–4351.

Martin, R.V., Jacob, D.J., Yantosca, R.M., Chin, M. and Ginoux, P. (2003), Global and Regional Decreases in Tropospheric Oxidants from Photochemical Effects of Aerosols, J. Geophys. Res. 108: 4097.

Park, R.J., Jacob, D.J., Field, B.D., Yantosca, R.M. and Chin, M. (2004). Natural and Transboundary Pollution Influences on Sulfate-nitrate-ammonium Aerosols in the United States: Implications for Policy. J. Geophys. Res. 109: D15204.

Pierce, J.R. and Adams, P.J. (2009). Uncertainty in Global CCN Concentrations from Uncertain Aerosol Nucleation and Primary Emission Rates. Atmos. Chem. Phys. 9: 1339–1356.

Riipinen, I., Sihto, S.L., Kulmala, M., Arnold, F., Dal Maso, M., Birmili, W., Saarnio, K., Teinilä, K., Kerminen, V.M., Laaksonen, A. and Lehtinen, K.E.J. (2007). Connections between Atmospheric Sulphuric Acid and New Particle Formation during QUEST III–IV Campaigns in Heidelberg and Hyytiälä, Atmos. Chem. Phys. 7: 1899–1914.

Spracklen, D.V., Carslaw, K.S., Kulmala, M., Kerminen, V.M., Sihto, S.L., Riipinen, I., Merikanto, J., Mann, G.W., Chipperfield, M.P., Wiedensohler, A., Birmili, W. and Lihavainen, H. (2008). Contribution of Particle Formation to Global Cloud Condensation Nuclei Concentrations. Geophys. Res. Lett. 35: L06808, doi: 10.1029/2007GL033038.

Stevens, R.G. and Pierce, J.R. (2013). A Parameterization of Sub-grid Particle Formation in Sulfur-rich Plumes for Global- and Regional-scale Models. Atmos. Chem. Phys. 13: 12117–12133, doi: 10.5194/acp-13-12117-2013.

Stevens, R.G. and Pierce, J.R. (2014). The Contribution of Plume-scale Nucleation to Global and Regional Aerosol and CCN Concentrations: Evaluation and Sensitivity to Emissions Changes. Atmos. Chem. Phys. 14: 13661–13679, doi: 10.5194/acp-14-13661-2014.

Yu, F., Wang, Z., Luo, G. and Turco, R.P. (2008). Ion-

Yu et al., Aerosol and Air Quality Research, 16: 900–908, 2016 908

mediated Nucleation as an Important Source of Tropospheric Aerosols. Atmos. Chem. Phys. 8: 2537–2554.

Yu, F. and Luo, G. (2009). Simulation of Particle Size Distribution with a Global Aerosol Model: Contribution of Nucleation to Aerosol and CCN Number Concentrations. Atmos. Chem. Phys. 9: 7691–7710.

Yu, F. (2010a). Ion-mediated Nucleation in the Atmosphere: Key Controlling Parameters, Implications, and Look-up Table. J. Geophys. Res. 115: D03206, doi: 10.1029/2009 JD012630.

Yu, F. (2010b). Diurnal and Seasonal Variations of Ultrafine Particle Formation in Anthropogenic SO2 Plumes. Environ. Sci. Technol. 44: 2011–2015, doi: 10.1021/es903228a.

Yu, F. (2011). A Secondary Organic Aerosol Formation Model Considering Successive Oxidation Aging and Kinetic Condensation of Organic Compounds: Global

Scale Implications. Atmos. Chem. Phys. 11: 1083–1099, doi: 10.5194/acp-11-1083-2011.

Yu, F. and Hallar, G. (2014). Difference in Particle Formation at a Mountain-top Location during the Spring and Summer: Implications for the Role of Sulfuric acid and Organics in Nucleation. J. Geophys. Res. 119, doi: 10.1002/2014JD022136.

Zhang, R., Khalizov, A.F., Wang, L., Hu, M. and Wen, X. (2012). Nucleation and Growth of Nanoparticles in the Atmosphere. Chem. Rev. 112: 1957–2011, doi: 10.1021/ cr2001756.

Received for review, May 28, 2015 Revised, August 17, 2015

Accepted, September 15, 2015