ACS Publications. Most Trusted. Most Cited. Most Read
Natural Marine Precursors Boost Continental New Particle Formation and Production of Cloud Condensation Nuclei
More

OR SEARCH CITATIONS

My Activity
Publications

Figure 1Loading Img
Download Hi-Res ImageDownload to MS-PowerPointCite This:Environ. Sci. Technol. 2024, 58, 25, 10956-10968
  • Open Access
Energy and Climate

Natural Marine Precursors Boost Continental New Particle Formation and Production of Cloud Condensation Nuclei
Click to copy article linkArticle link copied!

  • Robin Wollesen de Jonge*
    Robin Wollesen de Jonge
    Department of Physics, Lund University, Professorsgatan 1, Lund SE-22363, Sweden
    *Email: [email protected]
    More by Robin Wollesen de Jonge
    Orcidhttps://orcid.org/0000-0003-4043-6709
  • Carlton Xavier
    Carlton Xavier
    Department of Physics, Lund University, Professorsgatan 1, Lund SE-22363, Sweden
    Swedish Meteorological and Hydrological Institute (SMHI), Norrköping SE-60176, Sweden
    More by Carlton Xavier
    Orcidhttps://orcid.org/0000-0001-8120-0431
  • Tinja Olenius
    Tinja Olenius
    Swedish Meteorological and Hydrological Institute (SMHI), Norrköping SE-60176, Sweden
    More by Tinja Olenius
  • Jonas Elm
    Jonas Elm
    Department of Chemistry, Aarhus University, Langelandsgade 140, Aarhus DK-8000, Denmark
    More by Jonas Elm
    Orcidhttps://orcid.org/0000-0003-3736-4329
  • Carl Svenhag
    Carl Svenhag
    Department of Physics, Lund University, Professorsgatan 1, Lund SE-22363, Sweden
    More by Carl Svenhag
  • Noora Hyttinen
    Noora Hyttinen
    Finnish Meteorological Institute, Kuopio FI-70211, Finland
    Department of Chemistry, Nanoscience Center, University of Jyväskylä, Jyväskylä FI-40014, Finland
    More by Noora Hyttinen
    Orcidhttps://orcid.org/0000-0002-6025-5959
  • Lars Nieradzik
    Lars Nieradzik
    Department of Physical Geography and Ecosystem Science, Lund University, Lund SE-22362, Sweden
    More by Lars Nieradzik
  • Nina Sarnela
    Nina Sarnela
    Institute for Atmospheric and Earth System Research/Physics, Faculty of Science, University of Helsinki, Helsinki FI-00014, Finland
    More by Nina Sarnela
  • Adam Kristensson
    Adam Kristensson
    Department of Physics, Lund University, Professorsgatan 1, Lund SE-22363, Sweden
    More by Adam Kristensson
  • Tuukka Petäjä
    Tuukka Petäjä
    Institute for Atmospheric and Earth System Research/Physics, Faculty of Science, University of Helsinki, Helsinki FI-00014, Finland
    Joint International Research Laboratory of Atmospheric and Earth System Sciences, School of Atmospheric Sciences, Nanjing University, Nanjing CN-210023, China
    More by Tuukka Petäjä
  • Mikael Ehn
    Mikael Ehn
    Institute for Atmospheric and Earth System Research/Physics, Faculty of Science, University of Helsinki, Helsinki FI-00014, Finland
    More by Mikael Ehn
    Orcidhttps://orcid.org/0000-0002-0215-4893
  • Pontus Roldin
    Pontus Roldin
    Department of Physics, Lund University, Professorsgatan 1, Lund SE-22363, Sweden
    Swedish Environmental Research Institute IVL, Malmö SE-21119, Sweden
    More by Pontus Roldin
Open PDFSupporting Information (1)

Environmental Science & Technology

Cite this: Environ. Sci. Technol. 2024, 58, 25, 10956–10968
Click to copy citationCitation copied!
https://doi.org/10.1021/acs.est.4c01891
Published June 13, 2024

Copyright © 2024 The Authors. Published by American Chemical Society. This publication is licensed under

CC-BY 4.0 .

Abstract

Click to copy section linkSection link copied!
High Resolution Image
Download MS PowerPoint Slide

Marine dimethyl sulfide (DMS) emissions are the dominant source of natural sulfur in the atmosphere. DMS oxidizes to produce low-volatility acids that potentially nucleate to form particles that may grow into climatically important cloud condensation nuclei (CCN). In this work, we utilize the chemistry transport model ADCHEM to demonstrate that DMS emissions are likely to contribute to the majority of CCN during the biological active period (May-August) at three different forest stations in the Nordic countries. DMS increases CCN concentrations by forming nucleation and Aitken mode particles over the ocean and land, which eventually grow into the accumulation mode by condensation of low-volatility organic compounds from continental vegetation. Our findings provide a new understanding of the exchange of marine precursors between the ocean and land, highlighting their influence as one of the dominant sources of CCN particles over the boreal forest.

This publication is licensed under

CC-BY 4.0 .
  • cc licence
  • by licence
Copyright © 2024 The Authors. Published by American Chemical Society

Subjects

what are subjects

Keywords

what are keywords

Note Added after ASAP Publication

Due to a production error, this paper was published ASAP on June 13, 2024, with an error in Table 3. The corrected version was reposted on June 25, 2024.

Synopsis

Little is known on the role of natural marine precursors in the formation of aerosol particles over land. Here we demonstrate that dimethyl sulfide in particular gives rise to a substantial fraction of aerosol particles in the cloud condensation nuclei size range observed over the Nordic boreal forest.

1. Introduction

Click to copy section linkSection link copied!
Atmospheric aerosol particles play a critical role in controlling the Earth’s radiative balance. They absorb and scatter incoming solar radiation and govern the formation, radiative properties, and lifetime of clouds by acting as cloud condensation nuclei (CCN). Aerosols are produced naturally throughout various ecosystems and processes. In the oceans, phytoplankton blooms and bacteria provide the precursors necessary to form strong acids and bases capable of initiating the formation and growth of new particles from gases in the marine boundary layer. (1−3) Important precursors include dimethyl sulfide (DMS: (CH3)2S) and iodine species CH3I, I2, and HOI, which oxidize in the atmosphere to produce sulfuric acid (SA: H2SO4), methanesulfonic acid (MSA: CH3SO3H), iodic acid (IA: HIO3), and iodous acid (HIO2), respectively. (4−8) All acids are thought to nucleate, some among themselves and some in the presence of ammonia or alkylamines (9−13) formed naturally in the surface ocean (2) or emitted by anthropogenic sources. All acids along with ammonia and DMA continue to grow the newly formed particles from molecular clusters to CCN unless scavenged by larger particles. (3,14)
Over the continents, biogenic volatile organic compounds (BVOCs) are emitted from vegetation and oxidize in the atmosphere to produce low-volatility vapors that contribute to the growth of preexisting aerosol particles. (15,16) Certain compounds of extremely low volatility (ELVOCs) also enable the growth of newly formed clusters. (17) Monoterpenes (MTs) in particular (e.g., α-pinene) produce highly oxygenated organic molecules (HOMs) via the process of autoxidation. (18) At least a fraction of these compounds are ELVOCs. (11)
Processes leading to the formation and growth of aerosol particles in both marine and continental environments have been studied extensively. (4,5,19,20) Yet the interactions between marine and continental aerosols remain poorly understood. Other marine-continental exchanges are nevertheless described thoroughly in the literature. Water vapor is known to be transported from the oceans to the continents via the hydrological cycle, where it eventually condenses on available aerosol particles and leaves the atmosphere by precipitation. Therefore, it appears likely that marine precursors such as DMS, iodine species, and their oxidation products are also transported inland via air masses arriving from the oceans.
In the remote Arctic and Antarctic regions, IA, and DMS-derived SA along with ammonia and alkylamines are thought to be the main drivers of new particle formation (NPF) over land. (14,21−26) Growth events are predominant in summertime during periods of high biological activity and occur when air masses arrive from the open ocean or retracting sea-ice regions. (23,25,26)
Over the boreal forest, NPF events correlate with elevated concentrations of MSA and alkylamines in the gas-phase and nucleation mode particles. (27−29) The link between MSA, alkylamines, and NPF could suggest that precursors arriving from the marine environment affect aerosol processes over forested land. Various studies also report that particle formation and growth events are more frequent in the boreal forest when air masses arrive from the ocean. (29−32) Lawler et al. (29) argue that the effect is mainly caused by the low condensation sink conditions typical of air masses arriving from pristine marine regions, allowing for a larger fraction of the low volatile vapors to take part in NPF. They speculate, however, that precursors transported from the marine (e.g., DMS and iodine) in combination with the low condensation sink creates the optimal conditions for the formation and growth of new particles. While similar speculations have been presented in the literature, the impact of marine species such as DMS, iodine, NH3 and alkylamines on the formation and growth of aerosol particles over land has not been quantified.
In this work, we present model simulations of the gas-phase composition, NPF and secondary organic aerosol (SOA) growth over the boreal forest, with an emphasis on periods in which the air masses arrive from the marine environment. These simulations are able to estimate the scale to which marine precursors are transported inland from the ocean and quantify their effect on the formation and growth of aerosol particles in combination with condensable organic compounds produced over the forest. We use our model results to emphasize an until now poorly understood connection between the aerosol processes taking place over the forest and over the ocean and use this interaction to highlight the importance of marine precursors in the production of CCN sized aerosol particles over land. Finally, we demonstrate the influence of these marine-derived CCN sized particles on the formation of clouds and thereby the climate.

2. Materials and Methods

Click to copy section linkSection link copied!

ADCHEM Model Description

In order to verify the effect of marine precursors on the formation and growth of aerosol particles over the boreal forest, we utilize the chemical transport model ADCHEM to explicitly model the gas-phase chemistry, particle formation, and particle growth along the air-mass trajectories moving from the North Atlantic Ocean toward the boreal forest region. ADCHEM considers detailed aerosol dynamics including Brownian coagulation, wet and dry deposition along with condensation, dissolution, and evaporation of 873 organic and inorganic gas-phase species. The model comprises 20 vertical layers (spaced logarithmically) spanning 2100 m and considers mixing between all layers. Oxidation chemistry is treated in both the gas and aqueous phases, comprising a total of 5005 species and 13062 reactions. The chemical mechanism used includes MCMv3.3.1, (33,34) the work on marine DMS oxidation by Wollesen de Jonge et al. (6) and Hoffmann et al., (5) the work on iodine chemistry by Finkenzeller et al., (8) halogen chemistry from HM2.0 by Bräuer et al. (35) and organic autoxidation from PRAM. (20) The complete mechanism comprises the most advanced representation of the oxidation of DMS available in the current literature, including all potential reaction pathways in both the gas-phase and aqueous-phase. This includes the recently discovered compound hydroperoxymethyl thioformate (HPMTF), the formation of which was proposed in theory by Wu et al., (36) quantified experimentally by Berndt et al. (37) and observed in the ambient atmosphere by Veres et al. (38) The model also treats the aqueous-phase processing of 50 water-soluble species including DMS, methane sulphinic acid (MSIA), MSA, SA, SO2, O3, etc. in the deliquesced aerosol particle and cloud droplet, the latter of which was assumed to form at RH > 100% and activated at a constant cloud supersaturation of 0.3%.
Besides the base model setup (termed BaseCase), different sensitivity runs were performed to validate the effect of marine species on the formation and growth of aerosol particles over the boreal forest. An outline of the different sensitivity runs is given in Table 1. The first (named woDMS) represents a scenario without natural DMS emissions from the open ocean. The second (named woIodine) did not consider HIO3-HIO2 and HIO3-DMA clustering. The third (named woAnthro) did not include any anthropogenic particle and gas-phase emissions.
Table 1. Overview of the ADCHEM Model Base Case Setup and Sensitivity Runs
Model RunEmissionsChemistryNPF
BaseCaseCAMS-GLOB-ANTMCMv3.3.1 |HM2.0SA-NH3 |SA-DMA
CAMS-GLOB-BIOPRAM |DMSa |IodinebHIO3-HIO2 |HIO3-DMA
CAMS-GLOB-OCE
woDMSWithout emissions of DMS
woIodineWithout HIO3–HIO2 and HIO3-DMA nucleation
woAnthroWithout anthropogenic emissions of SO2, NOx, NH3, BC, CO, and AVOCs
a

DMS chemistry mechanism from Wollesen de Jonge et al. (6)

b

Iodine chemistry from Finkenzeller et al. (8)

Simulations Period, Location, and Measurement Data

ADCHEM was used to reproduce the gas and aqueous-phase chemistry along with particle formation and growth at the SMEARII field station in Hyytiälä, Finland (61.84°N, 24.28°E); (39,40) Pallas field station, Finland (67.58° N, 24.07° E); and Hyltemossa field station, Sweden (56.06°N, 13.25°E), during 120 days in 2018 (first of May -28th of August). This period was chosen to match the occurrence of phytoplankton blooms forming in the North Atlantic and Arctic Ocean which govern the emission of DMS to the marine atmosphere. Due to the substantial data availability at SMEARII, the model performance was mainly evaluated against observation from said station. Modeled results from the Pallas and Hyltemossa stations can be found in the Supporting Information (see Figures S6 and S7). SMEARII nevertheless proved ideal to study the impact of DMS and other marine species in the aerosol dynamics taking place over the boreal forest, due to marine air masses arriving frequently at the station (see SI Figure S2). Model simulations of HOM monomers, SA, MSA, and HIO3 were validated against observations measured at 1.0 and 35.0 m by nitrate-ion-based chemical ionization atmospheric pressure-interface time-of-flight mass spectrometer (CI-APi-TOF). The instrument was calibrated for SA, with a calibration factor of 2.4 × 109 molecules cm–3. The same calibration factor was used for HOM monomers, MSA and HIO3. Measurements of MTs and isoprene were obtained at 4.2 and 125 m by a proton-transfer-reaction mass spectrometer (PTR-MS) while particle number size distributions were measured by a differential mobility particle sizer (DMPS). ADCHEM was operated as an Lagrangian vertical column model (20,21) along a total of 984 back-trajectories starting 7 days upwind from SMEARII, Pallas, and Hyltemossa and arriving at the field stations every third hour. All trajectories were generated by the Hybrid Single Particle Lagrangian Integrated Trajectory Model (HYSPLIT) and included meteorological data from the Global Data Assimilation System (GDAS). (41,42)

Gas and Primary Particle Emissions

Daily emissions of marine BVOCs, DMS, and CH3I were obtained from the Copernicus Atmosphere Monitoring Service (CAMS) global ocean inventory at a 0.5° × 0.5° resolution. (43−46) CAMS also provided monthly emissions of SO2, NH3, NOx, etc. from the global anthropogenic inventory at a 0.1° × 0.1° resolution. (47) Emissions of continental BVOCs including isoprene along with MTs α-pinene, β-pinene, carene, and limonene were obtained from the CAMS global biogenic inventory. (48) Emissions of isoprene over the boreal forest were scaled by a factor five in accordance with emissions simulations made by the global dynamic vegetation model LPJ-GUESS (Smith et al.; (49) Arneth et al. (50)), which estimated isoprene emissions to be significantly higher than the ones presented in the CAMS-GLOB-BIO database. The ocean-atmosphere exchange of NH3 was calculated in accordance with the method described by Carpenter et al. (2) taking into account the dependence of pKa for the NH3–NH4+ equilibrium on sea surface temperature and salinity. Sea surface concentrations of NH4+ in the North Atlantic Ocean were estimated using results from Paulot et al. (51) Emissions of DMA were treated similarly assuming a similar sea surface temperature and salinity dependence. Due to the uncertainty in the sea surface concentrations of NH4+ and DMA, natural emissions of NH3 and DMA are likewise uncertain. In addition to the emissions of organic iodine species treated in CAMS, inorganic iodine emissions of I2 and HOI where treated in accordance with the study by Carpenter et al. (52) Sea spray was implemented in accordance with the parametrization by Sofiev et al. (53) taking into account the 10 m wind speed and the sea surface temperature. The organic mass fraction of the sea spray aerosol was derived from the sea surface chlorophyll-a concentration as demonstrated by Gantt et al. (54)

New Particle Formation

In this work, we simulated new particle formation by employing a molecular cluster plugin (ClusterIn) that simulates gas-cluster-aerosol interactions and feedbacks by explicitly coupling the cluster and aerosol dynamics. (55) This method enables explicit temporal simulation of the concentrations of clusters and gas-phase clustering species, and coagulation between clusters and aerosols that constitutes a sink for clusters and a growth process for aerosols, in addition to growth by vapor condensation. This approach circumvents artifacts that may arise from commonly applied simplifications in particle formation dynamics, thereby enabling improved assessment of the importance of given chemical pathways for particle formation. (55) To assess the role of different NPF mechanisms, namely ion-induced and neutral SA-NH3 and, SA-DMA, neutral HIO3-HIO2, and neutral HIO3-DMA, we employ the most recent molecular thermochemistry data sets as input for ClusterIn. The SA-NH3 and SA-DMA data sets are both computed at the DLPNO-CCSD(T)/aug-cc-pVTZ//ωB97X-D/6-31++G(d,p) quantum chemical level of theory, while the HIO3-HIO2 data set applies the DLPNO–CCSD(T)/M06–2 × 7/def2-TZVp level, and the HIO3-DMA data set applies the RI-CC2/aug-cc-pVTZ-PP//ωB97XD/6-311++G(3df,3pd) level. (56−59) Steady-state particle formation rates simulated using the thermochemical data sets SA-NH3 and HIO3-HIO2 have previously been compared to experimental data from the CLOUD chamber and have agreed well with measurements performed at low temperatures and moderate-to-high base concentrations (for NH3 and the SA-NH3 data). (56,57) This good agreement with CLOUD measurements can be expected to be due to the application of the state-of-the art DLPNO method for single-point energy calculations, (60,61) and the quasi-harmonic corrections employed in the calculations which generally reduce cluster overbinding. (57) Myllys et al. (58) compared formation rates based on the SA-DMA quantum chemical data set and found good agreement with the CLOUD experiments at both low and high DMA gas concentrations. One should note that since the HIO3-DMA cluster thermochemical data involves single-point energy calculations by the RICC2 method that has a tendency toward overprediction of cluster stabilities and thereby formation rates, quantitative assessments of the relative importance or contribution of HIO3-HIO2 (based on DLPNO) and HIO3-DMA to iodine-driven particle formation cannot be performed. This implies that the HIO3-DMA particle formation rates should be considered to be an upper limit to the real NPF rate.

Henry’s Law Solubility and pKa

Henry’s law solubility and pKa of MSIA, MSA, HIO3, and HIO2 in water were estimated using the conductor-like screening model for real solvents (COSMO-RS (62−64)) implemented in the COSMOtherm21 program. (65) COSMOtherm was used in order to describe the dependency of the Henry’s law solubility and pKa values on temperature, thus providing the ADCHEM model with a more realistic representation of the uptake and dissolution of these water-soluble species under different atmospheric conditions. These calculations combine density functional theory calculations at the BP/def2-TZVPD-FINE//BP/def-TZVP level of theory (66,67) and statistical thermodynamics using the most recent parametrization of COSMOtherm, BP_TZVPD_FINE_21. Both properties were computed for temperatures from 250 to 300 K with 10 K intervals.
Henry’s law solubility is calculated from the activity coefficient of the compound in the infinite dilution in the solvent γ∞ saturation vapor pressure of the pure compound psat, as well as the density (ρ) and molar mass (M) of the solvent water:
Hsol=ρsolventMsolventpsatγ∞
(1)
The pKa of a compound is estimated by using the free energy (G) of the neutral and ionic species at infinite dilution with the linear free energy relationship (LFER):
pKa=c+d(Gneutral−Ganion)
(2)
The LFER parameters of the BP_TZVPD_FINE_21 parametrization for water as a solvent are c = −130.024 and d = 0.486 mol kcal–1. It should be noted that the pKa calculation in COSMOtherm is parametrized only for room temperature (around 300 K).

Adiabatic Cloud Parcel Model

The amount of activated cloud droplets was estimated by using an adiabatic cloud parcel model. (68,69) Calculations were done at two different up-draft velocities, w = 0.1 m/s and w = 1.0 m/s, using the size distribution, size resolved chemical composition, and gas-phase concentration of SO2, H2O2, NH3, HNO3, SA, and HCl obtained from the ADCHEM model BaseCase, woDMS, woIodine, and woAnthro runs as input. The air parcel was assumed to rise from ground-level at a relative humidity (RH) of 98%, ultimately reaching 160 m of altitude. Upon reaching supersaturation (RH > 100%) with respect to water, aerosol particles in the CCN size range would activate into cloud droplets. The time by which supersaturation was reached in the air parcel depended on the updraft velocity.

Air-Mass Origin Analysis

Particle number size distributions obtained by DMPS measurements from SMEARII, Pallas, and Hyltemossa were grouped into percentiles based on the amount of time that their corresponding air masses spend over the ocean before reaching each station. The separation was done for observations obtained between 2006 and 2020 at SMEARII, 2015–2018 at Pallas and 2018–2020 at Hyltemossa, considering only spring and summertime data in order to represent the peak period in north Atlantic and Arctic ocean marine phytoplankton activity and thus DMS emission. Furthermore, only daytime observations between 6.00 and 18.00 representative of local NPF and growth at the stations were used. HYSPLIT back-trajectories were calculated at one h intervals starting 7 days upwind from each station, comprising in total 24655, 6570, and 4932 individual air masses arriving at SMEARII, Pallas, and Hyltemossa, respectively. Marine impact in terms of time spend over the ocean was obtained for each back-trajectory (see SI Figure S3) and used to classify the corresponding particle number size distribution.

Statistical Methods

Model and observational means, medians, and percentiles were calculated using the built in functions mean, median, and prctile provided by MATLABR2022a. Correlation coefficients R were obtained by the fitlm function, while the normalized mean bias (NMB) and the fraction of model predictions (M) within a factor of 2 from observations (O) (FAC2) were calculated using eq 3 and eq 4, respectively.
NMB=∑i=1n(Mi−Oi)∑i=1nOi
(3)
FAC2=0.5<MO<2.0
(4)

3. Results and Discussion

Click to copy section linkSection link copied!

Air Mass History and Aerosol Size Distributions

Air mass origin has a profound impact on the gas-phase chemistry, new particle formation, and particle growth over the boreal forest. Various regions emit different types of primary particles and precursor gases, all of which are mixed and moved around by large-scale weather systems. Figure 1a illustrates the regions that are particularly prone to affect aerosol processes at the Hyltemossa (56°06′N, 13°25′E), SMEARII (61°51′N, 24°17′E), and Pallas (67°58′ N, 24°07′ E) research stations, of which SMEARII and Pallas are located in the Finnish boreal forest and Hyltemossa in the southern Swedish temperate forest. Clean air masses from the North Atlantic Ocean are known to transport DMS, sea spray and NH3 emitted from natural processes in the surface ocean, while air masses from the southwest and southeast are dominated by anthropogenic emissions of SO2, NH3, NOx and black carbon (BC). Natural emissions of biogenic volatile organic compounds (BVOCs) such as MTs and isoprene influence the aerosol processes close to the stations.

Figure 1

Figure 1. Effect of marine versus continental air mass history on the aerosol number size distribution in a boreal forest environment. Panel (a) depicts the typical summertime source regions of DMS (purple), MTs (green), NH3 (blue), and anthropogenic SO2 (yellow), along with their position in relation to the Hyltemossa, SMEARII, and Pallas measurements stations. These colors indicate only the spatial locations of the emissions of the different species between May and August, 2018. Panels (b), (c), and (d) show the spring and summertime (March-August) mean aerosol number size distributions measured at the Hyltemossa, SMEARII, and Pallas stations during the periods 2018–2020, 2006–2020, and 2015–2018, respectively. The size distributions in panel (b), (c,) and (d) are separated based on the marine influence on their air mass history.

High Resolution Image
Download MS PowerPoint Slide
The effect of different air mass origins on the aerosol processes over the boreal forest becomes evident when separating the observed aerosol number size distributions at the Hyltemossa, SMEARII, and Pallas research stations based on the influence of air masses from different source regions. Figure 1b, 1c and 1d depicts the mean aerosol number size distribution during spring and summertime at the Hyltemossa, SMEARII and Pallas stations during years 2018–2020, 2006–2020, and 2015–2018, respectively. Each size distribution is grouped and colored based on the amount of time that its associated air-mass back-trajectory spent over the ocean before reaching the station (see Methods). Consequently, the purple size distributions are dominated by air masses arriving from the marine, while the green size distributions are dominated by air masses arriving from the continent. All stations show a tendency toward a higher particle number concentration in the nucleation and Aitken mode particle size range (PN<25 nm and PN25–100 nm, respectively) when marine regions dominate the air mass history, while air masses with continental influence are shifted toward the accumulation mode size range (PN100–1000 nm). PN<25 nm at Hyltemossa, SMEARII and Pallas are 14.7, 5.3, and 9.3 times higher, respectively, for size distributions with an marine air-mass influence above the 90th percentile compared to size distributions with an marine air-mass influence below the 10th percentile. PN25–100 nm are correspondingly 2.7, 2.2, and 1.6 higher for periods of high versus low marine influence while PN100–1000 nm is 0.29, 0.36, and 0.34 times as high. This result suggests that marine air masses favor the formation of particles in the nucleation mode size range along with their subsequent growth into the Aitken mode size range over the boreal forest. A possible explanation may be the low condensation sink associated with the clean air masses arriving from the North Atlantic Ocean. This would inevitable lower the loss of locally emitted anthropogenic SO2-derived SA and NH3 to the accumulation and coarse mode particles and allow these gases to contribute to NPF instead. At the same time, DMS-derived SA, HIO3, NH3 and DMA naturally emitted from the ocean may also contribute to NPF upwind from and over the boreal forest, thereby adding to the nucleation and Aitken mode particle number concentration observed at the SMEARII, Hyltemossa and Pallas stations.
In conclusion, separating multiple years of aerosol number size distributions measured at three boreal forest stations based on the influence of marine air masses shows an increase in the nucleation mode and Aitken mode particle number concentration for air masses having spent most of their time over the ocean.

Marine Air-Mass Influence on the Gas-Phase Chemistry over the Boreal Forest

Anthropogenic SA and NH3 along with HOM produced from the oxidation of BVOCs are often thought to be the main drivers behind the formation and growth of aerosol particles over the boreal forest. Size distributions separated by marine impact on the other hand suggests that marine species and their oxidation products may promote the nucleation and Aitken mode particle production during periods of high marine air-mass impact. We assess the impact of marine species in the gas and particle phase over the boreal forest using the ADCHEM model and evaluate the performance of ADCHEM in reproducing the precursors, oxidation species, and oxidation products that govern the aerosol processes at the SMEARII, Pallas and Hyltemossa stations (see the Supporting Information).
Figure 2 compares the modeled and measured long-term and diurnal gas-phase concentrations of MTs, HOM monomers, isoprene, SA, MSA, and O3 at the SMEARII station during four distinct periods spanning from the 17th of May to the 28th of August, 2018. Marine period one, two and three (MP1:17/5–10/6, MP2:19/6–8/7 and MP3:5/8–28/8) denotes periods of high marine air-mass impact, while continental period one (CP1:10/7–3/8) denotes a period of high continental air-mass impact. Table 2 summarizes the modeled and measured median gas-phase concentrations, the correlation coefficient (R), the normalized mean bias (NMB) and the fraction of model predictions within a factor of 2 of the measurements (FAC2). Additional concentrations of modeled gas-phase species can be found in the SI (see SI Figure S1). Considering the measurement uncertainty of HOMs, SA and MSA observations obtained by HR-ToF-CIMS, ADCHEM is able to reproduce gas-phase species at the SMEARII station. SA and MSA, while overestimated in the model (NMB(SA) = 2.19, NMB(MSA) = 5.69) show relatively low but significant correlation for the long-term time series (R(SA) = 0.24, R(MSA) = 0.29) and relatively high correlation for the diurnal cycle (R(SA) = 0.96, R(MSA) = 0.84). The modeled MSA gas-phase concentration does nevertheless undergo higher variability compared to the measured concentration, which could indicate that MSA is more volatile than currently predicted by COSMOtherm calculations in the model. (6,70) BVOCs isoprene and MTs show relatively low although significant correlation with measurements for the whole time period (R(Iso) = 0.36, R(MT) = 0.32), and are both within a factor of 2 from the observations for 45% of the time. The discrepancy between model and measurements appears to arise from the diurnal cycle, which may be captured less well by the model due to the simplified representation of the boundary layer dynamics. HOM monomers are consistently underestimated by the model (NMB(HOMm) = −0,89), with a relatively low but significant correlation for the total time series (R(HOMm) = 0.39) and the diurnal cycle (R(HOMm) = 0.23). We speculate if the discrepancy between model and measurement is caused by different definitions of HOM. While ADCHEM only classifies molecules produced via MT autoxidation as HOM, the estimated HOM concentrations from the HR-ToF-CIMS include all detected molecules with six or more oxygen atoms. Ozone, which plays a key part in the oxidation of MTs and DMS, shows relatively high correlation for the diurnal cycle (R(O3) = 0.61) and stays within a factor of 2 from the observations for 86% of the time. While the long-term ozone correlation is relatively low (R(O3) = 0.39), the low normalized mean bias (NMB(O3) = −0.03) suggests that the absolute ozone concentration is reproduced by the model.

Figure 2

Figure 2. Modeled and measured long-term and diurnal gas-phase concentrations of MTs, HOM monomers, isoprene, SA, MSA, and O3 at the Station for Measuring Ecosystem-Atmosphere Relations II (SMEARII) between the 17th of May and 28th of August, 2018. Gray and black dots denote the surface and above-canopy measurements, respectively, while the colored lines represent the above-canopy model results. Marine periods 1, 2, and 3 (MP1, MP2, and MP3) denote periods of particularly high marine air-mass impact, while continental period 1 (CP1) denotes a period of particularly high continental air-mass impact. The back-trajectory heat-maps displayed above each period illustrate the regions from which the air-masses arrived during MP1, MP2, MP3, and CP1. The shaded areas denote the measured and modeled data range within the 25th and 75th percentile.

High Resolution Image
Download MS PowerPoint Slide
Table 2. Evaluation of the Modeled Gas-Phase Concentration of MTs, HOM Monomers (HOMm), Isoprene, SA, MSA, and O3 at the Station for Measuring Ecosystem-Atmosphere Relations II (SMEARII)a
SpeciesO̅ (cm–3)bM̅ (cm–3)RNMBFAC2
MT3.74 × 1092.20 × 1090.32 (0.81)–0.48 (−0.38)0.45 (1.00)
HOMm1.09 × 1081.37 × 1070.39 (0.23)–0.87 (−0.87)0.03 (0.00)
Isoprene3.31 × 1093.49 × 1090.36 (0.38)0.31 (−0.01)0.45 (1.0)
SA5.25 × 1051.10 × 1060.24 (0.96)2.19 (2.19)0.23 (0.25)
MSA1.82 × 1051.80 × 1050.29 (0.84)5.69 (2.17)0.17 (0.50)
O332.5 (ppb)30.66 (ppb)0.39 (0.61)–0.03 (−0.18)0.86 (1.00)
a

A comparison between the modeled and measured concentrations is provided for the full period between May and August and for the diurnal variability in the gas-phase concentrations averaged over the entire period.

b

O̅denotes the observed median gas-phase concentration of each species,M̅ the modeled median gas-phase concentration, R the correlation coefficient, NMB the normalized mean bias, and FAC2 the fraction of predictions within a factor two of the observations. Diurnal results are reported in parentheses.

DMS constitutes a significant source of SA at the SMEARII station. Comparing model results from the BaseCase setup with that of the woDMS sensitivity run suggests that DMS contributes to 65% of the gas-phase and particle-phase SA observed at the station for the total simulation period. The fraction of DMS-derived SA increases to 66%, 79%, and 68% during MP1, MP2, and MP3, respectively. While the majority of SA related to the oxidation of DMS resides in the particle-phase upon reaching the SMEARII station, DMS-derived SO2 ensures a steady production of gas-phase SA over the boreal forest due to its prolonged lifetime. Consequently, DMS provides 47% of the gas-phase SO2 observed at the station for the entire simulation period along with 63%, 71%, and 44% during MP1, MP2, and MP3, respectively. The inland transport of DMS and its associated oxidation products is also evident from the woAnthro sensitivity run. Running the model without any emissions of anthropogenic sulfurous compounds suggests that DMS alone is able to maintain a mean SO2 gas-phase concentrations at the SMEARII station of 3.3 × 109 cm–3, 3.7 × 109 cm–3, and 2.1 × 109 cm–3 during MP1, MP2, and MP3, respectively. The consequent SA gas-phase concentration was found to be 5.1 × 106 cm–3 during MP1, 3.7 × 106 cm–3 during MP2, and 2.2 × 106 cm–3 during MP3.
These results suggests that DMS constitutes an important if not dominant source of SO2 and SA to the present day spring and summertime Scandinavian boreal forest atmosphere, but also that DMS would be likely to ensure significant SO2 and SA gas-phase concentrations in said forest without anthropogenic influence. Results from the woAnthro sensitivity run also indicate that the mean NH3 concentrations may reach 2.2 × 108 cm–3, 9.1 × 108 cm–3 and 2.2,·109 cm–3 during MP1, MP2 and MP3, respectively, from natural marine sources alone. While this is but a fraction of the NH3 gas-phase concentration caused by anthropogenic sources, it does provide the amount necessary to initiate NPF over the boreal forest in combination with SA derived from DMS under certain favorable conditions.
The inland transport of iodine species CH3I, I2, and HOI produces an HIO3 concentration at the SMEARII station of 3.3 × 105 cm–3, 3.3 × 105 cm–3, 6.8 × 105 cm–3, and 2.1 × 106 cm–3 during MP1, MP2, MP3, and CP1, respectively (see SI Figure S1b). The increased HIO3 concentration during CP1 coincides with the continental dominated air masses spending a significant fraction of time over coastal areas (see Figure S2), most of which are rich in kelp and algae, which favors the emission of CH3I.
BVOCs (isoprene and MTs) along with their associated oxidation products are dominant during periods of high continental impact. Consequently the gas-phase and particle-phase concentration of all condensable HOM species is 1.8, 1.7, and 2.0 times higher during CP1, compared to MP1, MP2 and MP3, respectively. The production of low-volatility organic compounds nevertheless remains high during periods of high marine impact, with the potential to grow newly formed particles from both natural and anthropogenic SA and NH3 into larger aerosol particles.
Overall, the model results together with the observations at SMEARII indicate that DMS has a profound impact on the gas-phase and particle-phase concentration of SA and SO2 over the boreal forest during periods of high marine air-mass impact and high biological activity. Furthermore, sensitivity runs indicate that natural marine species alone are capable of providing significant concentrations of SA, IA, and NH3 at the SMEARII station without any impact from anthropogenic sources.

Marine Air-Mass Impact on Particle Formation and Growth over the Boreal Forest

Considering the influence of marine species on the gas-phase concentration of SO2, SA, HIO3, and NH3 both at and upwind from the SMEARII station, air masses arriving from the ocean are likely to affect the formation and growth of aerosol particles over the boreal forest. Figure 3 compares the measured and modeled particle number size distributions during MP1, MP2, MP3, and CP1, along with median size distributions separated into periods dominated by marine or continental air-mass history. Model results without the influence of DMS (Figure 3c), without the influence of iodine-derived NPF (3d), and without the influence of anthropogenic precursors (Figure 3e) are illustrated by the woDMS, woIodine, and woAnthro sensitivity runs. Considering the BaseCase model setup, ADCHEM predicts the trends in particle formation and growth at the SMEARII station. The modeled median size distribution during periods of predominant marine air-mass impact (time spent over the ocean >50th prct) shows relativly high correlation with measurements (R = 0.96) with a small underestimate in the absolute particle number concentration (NMB = −0.24) (Figure 3g). Periods of low marine air-mass impact (time spent over the ocean <50th prct.) also shows relatively high correlation with observations (R = 0.98) but underestimates the absolute particle number concentration to a larger extent (NMB = −0.33) (Figure 3l). Similar results for the Pallas and Hyltemossa stations are provided in the Supporting Information (see Figure S6 and Figure S7, respectively).

Figure 3

Figure 3. Measured and modeled (a–e) time-dependent and (f–o) median particle number size distributions at the Station for Measuring Ecosystem Atmosphere Relations II (SMEARII) between the 17th of May and 28th of August. Marine periods 1, 2, and 3 (MP1, MP2, and MP3) denote periods of particular high marine air-mass impact, while continental period 1 (CP1) denotes a period of particular high continental air-mass impact. The back-trajectory heat-maps displayed above each period illustrates the regions from which the air-masses arrived during MP1, MP2, MP3, and CP1. The median size distributions are separated into (f–j) periods of predominant marine air-mass impact (time spent over the ocean >50th prct., purple), and (k–o) periods of predominant continental impact (time spent over the ocean <50th prct., green). The averaging for the median size distributions is done for the whole simulation period and not just during MP1, MP2, MP3, and CP1. The model results include data from the base case run (BaseCase), the without DMS emissions simulation (woDMS), the without iodine nucleation simulation (woIodine), and the without anthropogenic emissions simulation (woAnthro). The shaded areas denote the measured and modeled data range within the 25th and 75th percentile.

High Resolution Image
Download MS PowerPoint Slide
ADCHEM is able to reproduce the increase in nucleation and Aitken mode particle production during periods of high marine air-mass impact as presented in previous sections. Consequently, the median particle number concentration is 2.8 times higher in the nucleation mode and 1.7 times higher in the Aitken mode during periods of high marine impact (>50th prct.) as opposed to periods of low marine impact (<50th prct.), respectively (Figure 3g,l). The increase in the number of nucleation and Aitken mode particles may to some extent be explained by the low condensation sink associated with air masses arriving from the ocean. During CP1 the average modeled condensation sink was found to be 4.0 × 10–3 s–1 as opposed to 2.8 × 10–3 s–1, 3.2 × 10–3 s–1, and 2.7 × 10–3 s–1 during MP1, MP2 and MP3, respectively. However, according to the woDMS and woIodine sensitivity run the nucleation and Aitken mode particle production cannot be explained by the combination of low condensation sink and anthropogenic sources of SA and NH3 alone. Running the model without DMS emissions decreases the Aitken mode (PN25–100nm) and accumulation mode (PN>100nm) particle number concentration by 12% and 42% for the entire simulation period and by 26% and 68% during periods of predominant marine air-mass impact (time spent over the ocean >50th prct.), respectively (Figure 3h). At the Pallas and Hyltemossa stations the particle number concentrations across all particle sizes are reduced by 71% and 25% for the entire simulation period, respectively (Figures S6 and S7). These results show the importance of DMS in the formation and growth of aerosol particles both locally and upwind from the SMEARII, Pallas and Hyltemossa research stations and implies that DMS plays a much larger role over the boreal forest than previously anticipated. Consequently, the low condensation sink associated with marine air masses make up ideal conditions for DMS-derived NPF via SA, DMA, and NH3 over the oceans and land, which eventually act as seed particles for condensational growth of organics over the forest. The effect of running the model without DMS at the SMEARII station is particularly prominent during the fourth, fifth and sixth of June where the nucleation, Aitken and accumulation mode is close to nonexistent in the model, and similar cases are seen consistently throughout MP1, MP2, and MP3 (Figure 3c). This would suggest that DMS not only contributes sporadically to the formation of aerosol particles over the boreal forest but also dominates the NPF and growth during certain periods of strong marine air-mass impact.
Iodine constitutes a smaller but nevertheless noticeable effect on the formation of particles at the SMEARII station. Running the model without the HIO3-HIO2 and HIO3-DMA nucleation mechanisms decreases the nucleation mode (PN<25nm) and Aitken mode (PN25–100nm) particle number concentration by 7% and 2% during periods of predominant marine air-mass impact (time spent over the ocean >50th prct.) and by 13% and 8% during periods of predominant continental air-mass impact (time spent over the ocean <50th prct.), respectively (Figure 3i,n). The effect of HIO3–HIO2 and HIO3-DMA nucleation on the accumulation mode (PN>100nm) particle number concentration remains negligible at the SMEARII station. The influence of iodine in the formation of nucleation and Aitken mode particles during periods of predominant continental air-mass impact corresponds with the air masses spending less time over the open ocean and more time over coastal areas (see SI Figure S2). These areas are rich in emissions of organic iodine species such as CH3I, emitted from kelp or algea, and adds a significant source of HIO3 and HIO2 during a period otherwise dominated by VOC emissions over the continent. The effect is evident during CP1, where small bursts in nucleation and Aitken mode particles are observed in the BaseCase simulation but not in the woIodine sensitivity run (Figure 3d).
The influence of DMS and iodine in combination with the natural emissions of NH3 and DMA is also illustrated by the woAnthro sensitivity run (Figure 3d). Running the model without anthropogenic emissions of SO2, NH3, NOx, etc., suggests that marine species alone are capable of forming new particles over the ocean and land, while emissions of BVOCs and their associated oxidation products grow said particles into the accumulation mode and potential CCN size range. Although this scenario is nonrepresentative of the present day polluted atmosphere over the boreal forest, it provides an insight to the role of marine species in the NPF and thus ultimately CCN production over land during preindustrial times.
Overall, modeling the influence of marine species on the aerosol processes taking place over the boreal forest suggests that DMS and iodine have a substantial impact on the formation and growth of aerosol particles both locally and upwind from the SMEARII, Pallas, and Hyltemossa stations during the biological active period of phytoplankton in the north Atlantic and Arctic ocean. Furthermore, DMS in particular not only adds sporadically to the nucleation, Aitken, and accumulation mode particle number concentration but dominates the particle production in said modes during periods of high marine air-mass impact.

Impact of Marine Species on Clouds and Climate Over the Boreal Forest

The contribution of DMS and iodine to the formation, lifetime, and precipitation of clouds and consequently climate depends on their ability to produce aerosol particles in the CCN size range. Figure 4 illustrates the process by which DMS and iodine may do so. In order to quantify the production of CCN from DMS and iodine, the modeled particle number size distribution, size resolved chemical composition, and gas-phase concentrations at the SMEARII station were used as input to an adiabatic cloud parcel model. (68,69) Using this model, we calculated the amount of aerosol particles that activated into cloud droplets at various updraft velocities (w) (see Materials and Methods).

Figure 4

Figure 4. Schematic depiction of the influence of DMS and various iodine species on the formation and growth of aerosol particles both over the ocean and over land. (1) DMS, CH3I, I2, and HOI oxidize over the ocean and land to form the strong acids SA, MSA, HIO3, and HIO2, which nucleate (3) among themselves or (2) in the presence of NH3 or DMA. These particles in turn are (4) grown by condensation of low volatile organic compounds over the boreal forest, ultimately reaching (5) the CCN size range, where they (6) affect the formation, lifetime, and precipitation of clouds. Created with BioRender.com.

High Resolution Image
Download MS PowerPoint Slide
Table 3 summarizes the change in the CCN particle number concentration at updraft velocities w = 0.1 ms–1 and w = 1.0 ms–1 due to running the ADCHEM model without emissions of DMS, without iodine-derived NPF and without anthroprogenic emissions. According to the model, DMS has a substantial effect on the formation of CCN particles at both updraft velocities. Running the model without emissions of DMS decreases the number concentration of CCN by 78%, 82%, and 69% at w = 0.1 ms–1 and by 61%, 39%, and 51% at w = 1.0 ms–1 during MP1, MP2, and MP3, respectively. Updraft velocities in the range of 1.0 ms–1 are typical for the formation of cumulus clouds, whereas an updraft velocity of 0.5 ms–1 and below are more often seen in stratiform clouds. (71) In accordance with the adiabatic cloud model, DMS constitutes a large source of CCN particles in both types of clouds and thus both ends of the CCN size range. This coincides with the median minimum dry diameters of the particles that activate into cloud droplets being 167 nm at 0.1 ms–1 and only 75 nm at 1.0 ms–1. Consequently, DMS produces both small and large CCN sized particles throughout periods dominated by marine air masses.
Table 3. Median CCN Number Concentration Changes Due to Running The ADCHEM Model without DMS Emissions (woDMS), without Iodine Nucleation (woIodine), and without Anthroprogenic Emissions (woAnthro) Relative to The BaseCase Simulation During MP1, MP2, MP3, and CP1
 CCN change at w = 0.1 ms–1 (%)CCN change at w = 1.0 ms–1 (%)
Model RunMP1MP2MP3CP1MP1MP2MP3CP1
woDMS–78.3–81.5–68.6–6.0%–60.8–39.4–51.2–2.8
woIodinea4.0–2.44.2–3.9–2.1–2.5–0.3–8.4
woAnthro8.05.626.8–14.2–32.6–30.3–31.7–23.3
a

Iodine nucleation includes HIO3-HIO2 and HIO3-DMA. Anthroprogenic emissions comprise SO2, NOx, NH3, CO, BC, and AVOCs.

It is also evident that DMS alone constitutes a larger source of CCN sized particles at the SMEARII station compared to the effect from anthropogenic species. While running ADCHEM without anthropogenic emissions decreases the CCN number concentration by up to 33% at w = 1.0 ms–1, it also increases concentrations during periods dominated by marine air masses by up to 27% at w = 0.1 ms–1. This effect is likely caused by the anthropogenic contribution to NPF, resulting in more numerous but smaller particles that cannot activate into cloud droplets at low updraft velocities (low water vapor supersaturation). (20)
As discussed previously, iodine was found to have a minor impact on the accumulation mode particle concentration observed at the SMEARII station. Similarly, iodine has less of an effect on the CCN number concentration according to the cloud up-draft velocity model. Running ADCHEM without iodine derived NPF increases and decreases the amount of CCN particles by no more than ∼4% during periods of high marine air-mass impact (Table 3). Removing iodine NPF from the model does, however, decrease CCN productions by 8% at w = 1.0 m/s during CP1, where the air masses frequently arrived from coastal areas.
Based on the adiabatic cloud parcel model, it is clear that DMS influences the CCN particle number concentration and thus ultimately the local climate over the boreal forest. DMS initiates NPF over the oceans and land, forming aerosols in the nucleation and Atiken mode size range, which act as seed particles for the condensation of low volatile organic compounds when transported over forested land (Figure 4). This consequently leads to a significant increase in CCN particle number concentration over the boreal forest during periods of high marine air-mass impact. Iodine was found to have little influence on the CCN concentration locally at SMEARII, while still contributing to the nucleation and Aitken mode particle concentration during CP1. This effect corresponds with iodine-derived NPF originating from coastal emissions of iodine species, which do not have time to grow into the CCN size range upon reaching the SMEARII station. However, these particles may in turn reach CCN sizes further downwind from the station, ultimately affecting continental cloud processes and thus climate.
Besides DMS and iodine influencing the formation and growth of aerosol particles over the ocean and land in the present day atmosphere, it also appears likely that they may have had a significant impact on these aerosol processes in a preindustrial atmosphere. Even without anthropogenic precursors, DMS was found to contribute to relatively high concentrations of SO2 and SA at the SMEARII station, which in combination with natural emissions of NH3, DMA, iodine, and low volatile organics was found to drive the formation and growth of aerosol particles over the ocean and over land. Given the scale by which DMS and iodine is emitted globally from phytoplankton and open ocean, respectively, this process might also be relevant in other parts of the world. Furthermore, it may also have been the dominant driver in NPF and CCN production in the preindustrial atmosphere, and could become important in the future, as anthropogenic emissions of sulfur and NH3 continues to decrease while emissions of DMS and iodine continue to increase as a consequence of the global climate change. (8,72)

Supporting Information

Click to copy section linkSection link copied!

The Supporting Information is available free of charge at https://pubs.acs.org/doi/10.1021/acs.est.4c01891.

  • Figure S1 contains modeled and measured gas-phase concentrations of SO2, HIO3, and NOx, along with modeled gas-phase concentrations of OH, NH3, and DMA; Figure S2 illustrates the back trajectory heat maps for the full simulation period along with MP1, MP2, MP3, and CP1; Figure S3 demonstrates the method behind the air-mass origin analysis; Figure S4 contains the modeled size resolved chemical composition of SO4, NO3, Cl, NH4, Na, MSA, HIO3, DMA, SOA, and POA between 1 nm and 1 μm; Figure S5 illustrates the modeled and measured median particle number size distribution, including results from the woDMS, woIodine, and woAnthro sensitivity runs; Figure S6 contains modeled and measured particle numbers size distributions from Pallas, while Figure S7 contains similar results from Hyltemossa; Figure S8 illustrates the DMS, SO2, and OH gas-phase concentration along with the SA-NH3 nucleation rate along one of the HYSPLIT trajectories moving from the Norwegian Sea toward the SMEARII stationl Table S1 comprises COSMOtherm-derived Henry’s law solubilities, while Table S2 contains COSMOtherm-derived pKa values (PDF)

Terms & Conditions

Most electronic Supporting Information files are available without a subscription to ACS Web Editions. Such files may be downloaded by article for research use (if there is a public use license linked to the relevant article, that license may permit other uses). Permission may be obtained from ACS for other uses through requests via the RightsLink permission system: http://pubs.acs.org/page/copyright/permissions.html.

Author Information

Click to copy section linkSection link copied!
  • Corresponding Author
  • Authors
    • Carlton Xavier - Department of Physics, Lund University, Professorsgatan 1, Lund SE-22363, Sweden;  Swedish Meteorological and Hydrological Institute (SMHI), Norrköping SE-60176, Sweden;  Orcidhttps://orcid.org/0000-0001-8120-0431
    • Tinja Olenius - Swedish Meteorological and Hydrological Institute (SMHI), Norrköping SE-60176, Sweden
    • Jonas Elm - Department of Chemistry, Aarhus University, Langelandsgade 140, Aarhus DK-8000, Denmark;  Orcidhttps://orcid.org/0000-0003-3736-4329
    • Carl Svenhag - Department of Physics, Lund University, Professorsgatan 1, Lund SE-22363, Sweden
    • Noora Hyttinen - Finnish Meteorological Institute, Kuopio FI-70211, Finland;  Department of Chemistry, Nanoscience Center, University of Jyväskylä, Jyväskylä FI-40014, Finland;  Orcidhttps://orcid.org/0000-0002-6025-5959
    • Lars Nieradzik - Department of Physical Geography and Ecosystem Science, Lund University, Lund SE-22362, Sweden
    • Nina Sarnela - Institute for Atmospheric and Earth System Research/Physics, Faculty of Science, University of Helsinki, Helsinki FI-00014, Finland
    • Adam Kristensson - Department of Physics, Lund University, Professorsgatan 1, Lund SE-22363, Sweden
    • Tuukka Petäjä - Institute for Atmospheric and Earth System Research/Physics, Faculty of Science, University of Helsinki, Helsinki FI-00014, Finland;  Joint International Research Laboratory of Atmospheric and Earth System Sciences, School of Atmospheric Sciences, Nanjing University, Nanjing CN-210023, China
    • Mikael Ehn - Institute for Atmospheric and Earth System Research/Physics, Faculty of Science, University of Helsinki, Helsinki FI-00014, Finland;  Orcidhttps://orcid.org/0000-0002-0215-4893
    • Pontus Roldin - Department of Physics, Lund University, Professorsgatan 1, Lund SE-22363, Sweden;  Swedish Environmental Research Institute IVL, Malmö SE-21119, Sweden
  • Author Contributions

    R.W.J., C.X., M.E., and P.R. designed research; R.W.J., C.X., T.O., J.E., C.S., N.H., L.N., and P.R. performed research; N.S., A.K., and T.P. performed measurements ; R.W.J., C.X., T.O., J.E., C.S., N.H., L.N., and P.R. developed the models ; R.W.J., C.X., T.O., J.E., C.S., N.H., L.N., and P.R. analyzed data ; R.W.J., C.X., N.H., and P.R. wrote the paper.

  • Notes
    The authors declare no competing financial interest.

Acknowledgments

Click to copy section linkSection link copied!

The authors would like to thank Markku Kulmala and Pasi Aalto for DMPS measurements obtained at SMEARII and Niku Kivekäs and Sami Seppälä for DMPS measurements obtained at Pallas. This project has received funding from the Swedish Research Council Formas (project no. 2018-01745-COBACCA), the Swedish Research Council VR (project no. 2019-05006), the Crafoord foundation (project no. 20210969), the Horizon Europe project AVENGERS (project no. 101081322) and the Academy of Finland (grant no. 338171). We thank the Swedish Strategic Research Program MERGE, the Profile Area Aerosols at the Faculty of Engineering at Lund University and the Profile Area Nature-Based Future Solutions at Lund University for strategic support. We gratefully acknowledge the Centre for Scientific and Technical Computing at Lund University, LUNARC, the Swedish National Infrastructure for Computing, SNIC and CSC - IT Center for Science, Finland, for computational resources. We thank ECCAD for archiving and distribution of data from CAMS. LUNARC is partially funded by the Swedish Research Council through grant agreement no. 2016-07213. J.E. thanks the Independent Research Fund Denmark grant number 9064-00001B for financial support. T.O. acknowledges the Swedish Research Council VR (grant no. 2019-04853) and the Swedish Research Council for Sustainable Development FORMAS (grant no. 2019-01433) for financial support. Funding through the European Commission Horizon Europe project FOCI,20 ”Non-CO2 Forcers and Their Climate, Weather, Air Quality and Health Impacts (project 101056783), FORCeS (grant agreement 821205) and Academy of Finland (ACCC Flagship, project 337549; academy projects 334792, 325681, 333397. The observations at SMEAR II are supported via Academy of Finland (328616, 345510) and via University of Helsinki (HY-ACTRIS).

References

Click to copy section linkSection link copied!

This article references 72 other publications.

  1. 1
    Lovelock, J. E.; Maggs, R. J.; Rasmussen, R. A. Atmospheric Dimethyl Sulfide and the Natural Sulfur Cycle. Nature 1972, 237, 452– 453,  DOI: 10.1038/237452a0
    Google Scholar
    1
    Atmospheric dimethyl sulfide and the natural sulfur cycle
    Lovelock, J. E.; Maggs, R. J.; Rasmussen, R. A.
    Nature (London, United Kingdom) (1972), 237 (5356), 452-3CODEN: NATUAS; ISSN:0028-0836.
    The av. concn. of dimethyl sulfide (DMS) [75-18-3] in seawater was 1.2 .tim. 10-11 g/ml and the distribution coeff. of DMS between air and seawater was 0.30, corresponding to an atm. concn. of 1.2 ppb at equil. The emission rates of DMS were 50-400 .tim. 10-12 g/g wet wt./hr from marine algae, 21-84 .tim. 10-12 g/g/hr from soils, and 2-43 .tim. 10-12 g/g dry wt./hr from the living intact leaves of oak, cotton, spruce, and pine trees. DMS may be involved in the transfer of biol. sulfur [7704-34-9] in nature.
    >> More from SciFinder ®
    https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADyaE3sXisVOmug%253D%253D&md5=c6d0495b981f24e9fef6102dd86617ee
  2. 2
    Carpenter, L.; Archer, S.; Beale, R. Ocean-atmosphere trace gas exchange. Chem. Soc. Rev. 2012, 41, 6473– 506,  DOI: 10.1039/c2cs35121h
    Google Scholar
    2
    Ocean-atmosphere trace gas exchange
    Carpenter, Lucy J.; Archer, Stephen D.; Beale, Rachael
    Chemical Society Reviews (2012), 41 (19), 6473-6506CODEN: CSRVBR; ISSN:0306-0012. (Royal Society of Chemistry)
    A review. The oceans contribute significantly to the global emissions of a no. of atmospherically important volatile gases, notably those contg. sulfur, nitrogen, and halogens. Such gases play crit. roles not only in global biogeochem. cycling but also in a wide range of atm. processes including marine aerosol formation and modification, tropospheric ozone formation and destruction, photooxidant cycling, and stratospheric ozone loss. A no. of marine emissions are greenhouse gases, others influence the Earth's radiative budget indirectly through aerosol formation and/or by modifying oxidant levels and thus changing the atm. lifetime of gases such as methane. Reviewed is current literature concerning the phys., chem., and biol. controls on the sea-air emissions of a wide range of gases including di-Me sulfide (DMS), halocarbons, nitrogen-contg. gases including NH3, amines (including dimethylamine, DMA, and diethylamine, DEA), alkyl nitrates (RONO2) and N2O, non-methane hydrocarbons (NMHC) including isoprene and oxygenated (O)VOCs, CH4 and CO. Where possible the current global emission budgets of these gases as well as known mechanisms for their formation and loss in the surface ocean are reviewed.
    >> More from SciFinder ®
    https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC38Xhtlaktr%252FP&md5=12993bba4892e6ceadc7b6dc4d8e9432
  3. 3
    Zheng, G.; Wang, Y.; Wood, R.; Jensen, M. P.; Kuang, C.; McCoy, I. L.; Matthews, A.; Mei, F.; Tomlinson, J. M.; Shilling, J. E. New particle formation in the remote marine boundary layer. Nat. Commun. 2021, 12, 527,  DOI: 10.1038/s41467-020-20773-1
    Google Scholar
    3
    New particle formation in the remote marine boundary layer
    Zheng, Guangjie; Wang, Yang; Wood, Robert; Jensen, Michael P.; Kuang, Chongai; McCoy, Isabel L.; Matthews, Alyssa; Mei, Fan; Tomlinson, Jason M.; Shilling, John E.; Zawadowicz, Maria A.; Crosbie, Ewan; Moore, Richard; Ziemba, Luke; Andreae, Meinrat O.; Wang, Jian
    Nature Communications (2021), 12 (1), 527CODEN: NCAOBW; ISSN:2041-1723. (Nature Research)
    Abstr.: Marine low clouds play an important role in the climate system, and their properties are sensitive to cloud condensation nuclei concns. While new particle formation represents a major source of cloud condensation nuclei globally, the prevailing view is that new particle formation rarely occurs in remote marine boundary layer over open oceans. Here we present evidence of the regular and frequent occurrence of new particle formation in the upper part of remote marine boundary layer following cold front passages. The new particle formation is facilitated by a combination of efficient removal of existing particles by pptn., cold air temps., vertical transport of reactive gases from the ocean surface, and high actinic fluxes in a broken cloud field. The newly formed particles subsequently grow and contribute substantially to cloud condensation nuclei in the remote marine boundary layer and thereby impact marine low clouds.
    >> More from SciFinder ®
    https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BB3MXit1alsb4%253D&md5=cb0000d7b4413432690fd0ddf779d694
  4. 4
    Barnes, I.; Hjorth, J.; Mihalopoulos, N. Dimethyl Sulfide and Dimethyl Sulfoxide and Their Oxidation in the Atmosphere. Chem. Rev. 2006, 106, 940– 975,  DOI: 10.1021/cr020529+
    Google Scholar
    4
    Dimethyl Sulfide and Dimethyl Sulfoxide and Their Oxidation in the Atmosphere
    Barnes, Ian; Hjorth, Jens; Mihalopoulos, Nikos
    Chemical Reviews (Washington, DC, United States) (2006), 106 (3), 940-975CODEN: CHREAY; ISSN:0009-2665. (American Chemical Society)
    A review concerning the gas phase chem., atm. oxidn., and chem. products of the atm. oxidn. of di-Me sulfide (DMS) and dimethylsulfoxide (DMSO) is given. Topics discussed include: DMS chem. (reaction with OH-, NO3-, halogen atoms and halogen oxides [kinetics, primary reaction mechanisms, reaction products]); DMSO chem. (reaction with OH-, NO3-, halogen atoms and halogen oxides [kinetics, primary reaction mechanisms, reaction products]); and current state of field measurements and their interpretation (multi-phase chem. involved in atm. oxidn. of DMS; field and modeling study evidence of the role of multi-phase reactions in the DMS cycle; aq.-phase reactions of DMS, DMSO, di-Me sulfone, methane sulfinic acid [MSIA], and methane sulfonic acid [MSA]; atm. implication of aq.-phase reactions of DMS, DMSO, MSIA, and MSA; and modeling study recommendations).
    >> More from SciFinder ®
    https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD28Xhs1Grtr4%253D&md5=c2a51fd2de3a72676c30eb83aeed4fb1
  5. 5
    Hoffmann, E. H.; Tilgner, A.; Schrödner, R.; Bräuer, P.; Wolke, R.; Herrmann, H. An advanced modeling study on the impacts and atmospheric implications of multiphase dimethyl sulfide chemistry. Proc. Natl. Acad. Sci. U. S. A. 2016, 113, 11776– 11781,  DOI: 10.1073/pnas.1606320113
    Google Scholar
    5
    An advanced modeling study on the impacts and atmospheric implications of multiphase dimethyl sulfide chemistry
    Hoffmann, Erik Hans; Tilgner, Andreas; Schroedner, Roland; Braeuer, Peter; Wolke, Ralf; Herrmann, Hartmut
    Proceedings of the National Academy of Sciences of the United States of America (2016), 113 (42), 11776-11781CODEN: PNASA6; ISSN:0027-8424. (National Academy of Sciences)
    Oceans dominate di-Me sulfide (DMS) emissions, the major natural S source. DMS is important for formation of non-sea salt sulfate (nss-SO42-) aerosols and secondary particulate matter over oceans; thus, it significantly affects global climate. The DMS oxidn. mechanism has been examd. in several different model studies; however, these studies had restricted oxidn. mechanisms which mainly under-represented important aq.-phase chem. processes. These neglected but highly effective processes strongly affect the direct product yields of DMS oxidn., thereby affecting the climatic influence of aerosols. To address these shortfalls, an extensive multiphase DMS chem. mechanism, the Chem. Aq. Phase Radical Mechanism DMS Module 1.0, was developed and used in detailed model assessments of multiphase DMS chem. in the marine boundary layer. Model studies confirmed the importance of aq. phase chem. for the fate of DMS and its oxidn. products. Aq. phase processes significantly reduced the SO2 yield and increased the Me sulfonic acid (MSA) yield, which is needed to close the gap between modeled and measured MSA concns. Simulations implied that multi-phase DMS oxidn. produces equal amts. of MSA and SO42-, a result with significant implications for nss-SO42- aerosol formation, cloud condensation nuclei concn., and cloud albedo over oceans. Results showed the deficiencies of parameterizations currently used in higher-scale models which only treat gas phase chem. Overall, the results showed treatment of DMS chem. in gas and aq. phases is essential to improve model prediction accuracy.
    >> More from SciFinder ®
    https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC28XhsFyrsb%252FO&md5=97c54638e0a27847d0f959788895cd49
  6. 6
    Wollesen de Jonge, R.; Elm, J.; Rosati, B.; Christiansen, S.; Hyttinen, N.; Lüdemann, D.; Bilde, M.; Roldin, P. Secondary aerosol formation from dimethyl sulfide - improved mechanistic understanding based on smog chamber experiments and modelling. Atmospheric Chemistry and Physics 2021, 21, 9955– 9976,  DOI: 10.5194/acp-21-9955-2021
    Google Scholar
    There is no corresponding record for this reference.
  7. 7
    Gomez Martin, J. C.; Lewis, T. R.; Blitz, M. A.; Plane, J. M. C.; Kumar, M.; Francisco, J. S.; Saiz-Lopez, A. A gas-to-particle conversion mechanism helps to explain atmospheric particle formation through clustering of iodine oxides. Nat. Commun. 2020, 11, 4521,  DOI: 10.1038/s41467-020-18252-8
    Google Scholar
    There is no corresponding record for this reference.
  8. 8
    Finkenzeller, H.; Iyer, S.; He, X.-C.; Simon, M.; Koenig, T. K.; Lee, C. F.; Valiev, R.; Hofbauer, V.; Amorim, A.; Baalbaki, R. The gas-phase formation mechanism of iodic acid as an atmospheric aerosol source. Nat. Chem. 2023, 15, 129– 135,  DOI: 10.1038/s41557-022-01067-z
    Google Scholar
    There is no corresponding record for this reference.
  9. 9
    Korhonen, P.; Kulmala, M.; Laaksonen, A.; Viisanen, Y.; McGraw, R.; Seinfeld, J. H. Ternary nucleation of H2SO4, NH3, and H2O in the atmosphere. Journal of Geophysical Research: Atmospheres 1999, 104, 26349– 26353,  DOI: 10.1029/1999JD900784
    Google Scholar
    9
    Ternary nucleation of H2SO4, NH3, and H2O in the atmosphere
    Korhonen, P.; Kulmala, M.; Laaksonen, A.; Viisanen, Y.; McGraw, R.; Seinfeld, J. H.
    Journal of Geophysical Research, [Atmospheres] (1999), 104 (D21), 26349-26353CODEN: JGRDE3 ISSN:. (American Geophysical Union)
    Classical theory of binary homogeneous nucleation is extended to the ternary system H2SO4-NH3-H2O. For NH3 mixing ratios exceeding about 1 ppt, the presence of NH3 enhances the binary H2SO4-H2O nucleation rate by several orders of magnitude. The Gibbs free energies of formation of the crit. H2SO4-NH3-H2O cluster, as calcd. by two independent approaches, are in substantial agreement. The finding that the H2SO4-NH3-H2O ternary nucleation rate is independent of relative humidity over a large range of H2SO4 concns. has wide atm. consequences. The limiting component for ternary H2SO4-NH3-H2O nucleation is, as in the binary H2SO4-H2O case, H2SO4; however, the H2SO4 concn. needed to achieve significant nucleation rates is several orders of magnitude below that required in the binary case.
    >> More from SciFinder ®
    https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADyaK1MXotFWqurk%253D&md5=d5ca8b589881057516ae0bb3ec62b4a9
  10. 10
    Almeida, J.; Schobesberger, S.; Kürten, A.; Ortega, I.; Kupiainen-Määttä, O.; Praplan, A.; Adamov, A.; Amorim, A.; Bianchi, F.; Breitenlechner, M. Molecular understanding of sulphuric acid-amine particle nucleation in the atmosphere. Nature 2013, 502, 359– 363,  DOI: 10.1038/nature12663
    Google Scholar
    10
    Molecular understanding of sulphuric acid-amine particle nucleation in the atmosphere
    Almeida, Joao; Schobesberger, Siegfried; Kuerten, Andreas; Ortega, Ismael K.; Kupiainen-Maeaettae, Oona; Praplan, Arnaud P.; Adamov, Alexey; Amorim, Antonio; Bianchi, Federico; Breitenlechner, Martin; David, Andre; Dommen, Josef; Donahue, Neil M.; Downard, Andrew; Dunne, Eimear; Duplissy, Jonathan; Ehrhart, Sebastian; Flagan, Richard C.; Franchin, Alessandro; Guida, Roberto; Hakala, Jani; Hansel, Armin; Heinritzi, Martin; Henschel, Henning; Jokinen, Tuija; Junninen, Heikki; Kajos, Maija; Kangasluoma, Juha; Keskinen, Helmi; Kupc, Agnieszka; Kurten, Theo; Kvashin, Alexander N.; Laaksonen, Ari; Lehtipalo, Katrianne; Leiminger, Markus; Leppae, Johannes; Loukonen, Ville; Makhmutov, Vladimir; Mathot, Serge; McGrath, Matthew J.; Nieminen, Tuomo; Olenius, Tinja; Onnela, Antti; Petaejae, Tuukka; Riccobono, Francesco; Riipinen, Ilona; Rissanen, Matti; Rondo, Linda; Ruuskanen, Taina; Santos, Filipe D.; Sarnela, Nina; Schallhart, Simon; Schnitzhofer, Ralf; Seinfeld, John H.; Simon, Mario; Sipilae, Mikko; Stozhkov, Yuri; Stratmann, Frank; Tome, Antonio; Troestl, Jasmin; Tsagkogeorgas, Georgios; Vaattovaara, Petri; Viisanen, Yrjo; Virtanen, Annele; Vrtala, Aron; Wagner, Paul E.; Weingartner, Ernest; Wex, Heike; Williamson, Christina; Wimmer, Daniela; Ye, Penglin; Yli-Juuti, Taina; Carslaw, Kenneth S.; Kulmala, Markku; Curtius, Joachim; Baltensperger, Urs; Worsnop, Douglas R.; Vehkamaeki, Hanna; Kirkby, Jasper
    Nature (London, United Kingdom) (2013), 502 (7471), 359-363CODEN: NATUAS; ISSN:0028-0836. (Nature Publishing Group)
    Aerosol particle nucleation from trace atm. vapor is thought to provide up to half the global cloud condensation nuclei. Aerosols can cause net climate cooling by scattering sunlight and leading to smaller, but more numerous cloud droplets, making clouds brighter and extending their lifetimes. Atm. aerosols from human activities are thought to have compensated for a large fraction of warming caused by greenhouse gases; however, despite its importance for climate, atm. nucleation is poorly understood. It was recently shown that H2SO4 and NH3 cannot explain particle formation rates obsd. in the lower atm. It is thought amines may enhance nucleation, but until now there has been no direct evidence for amine ternary nucleation under atm. conditions. This work used the CLOUD (cosmics leaving outdoor droplets) chamber at CERN to det. that dimethylamine >3 parts per trillion by vol. can enhance particle formation rates >1000-fold vs. NH3, sufficient to account for atm. obsd. particle formation rates. Mol. anal. of clusters showed that faster nucleation is explained by a base-stabilization mechanism involving acid-amine pairs, which strongly decrease evapn. The ion-induced contribution is generally small, reflecting the high stability of H2SO4-dimethylamine clusters and indicating that galactic cosmic rays exert only a small effect on their formation, except at low overall formation rates. Exptl. measurements were well reproduced by a dynamic model based on quantum chem. calcns. of mol. cluster binding energies without any fitted parameters. Results showed that in regions of the atm. near amine sources, amines and SO2 should be considered when assessing the effect of anthropogenic activity on particle formation.
    >> More from SciFinder ®
    https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3sXhsFOit73N&md5=06460967339b7bcd3d231102fd2d96db
  11. 11
    Kurten, A.; Li, C.; Bianchi, F.; Curtius, J.; Dias, A.; Donahue, N. M.; Duplissy, J.; Flagan, R. C.; Hakala, J.; Jokinen, T. New particle formation in the sulfuric acid-dimethylamine-water system: Reevaluation of CLOUD chamber measurements and comparison to an aerosol nucleation and growth model. Atmospheric Chemistry and Physics 2018, 18, 845– 863,  DOI: 10.5194/acp-18-845-2018
    Google Scholar
    There is no corresponding record for this reference.
  12. 12
    Rong, H.; Liu, J.; Zhang, Y.; Du, L.; Zhang, X.; Li, Z. Nucleation mechanisms of iodic acid in clean and polluted coastal regions. Chemosphere 2020, 253, 126743,  DOI: 10.1016/j.chemosphere.2020.126743
    Google Scholar
    12
    Nucleation mechanisms of iodic acid in clean and polluted coastal regions
    Rong, Hui; Liu, Jiarong; Zhang, Yujia; Du, Lin; Zhang, Xiuhui; Li, Zesheng
    Chemosphere (2020), 253 (), 126743CODEN: CMSHAF; ISSN:0045-6535. (Elsevier Ltd.)
    In coastal regions, intense bursts of particles are frequently obsd. with high concns. of iodine species, esp. iodic acid (IA). However, the nucleation mechanisms of IA, esp. in polluted environments with high concns. of sulfuric acid (SA) and ammonia (A), remain to be fully established. By quantum chem. calcns. and atm. cluster dynamics code (ACDC) simulations, the self-nucleation of IA in clean coastal regions and that influenced by SA and A in polluted coastal regions are investigated. The results indicate that IA can form stable clusters stabilized by halogen bonds and hydrogen bonds through sequential addn. of IA, and the self-nucleation of IA can instantly produce large amts. of stable clusters when the concn. of IA is high during low tide, which is consistent with the observation that intense particle bursts were linked to high concns. of IA in clean coastal regions. Besides, SA and A can stabilize IA clusters by the formation of more halogen bonds and hydrogen bonds as well as proton transfers, and the binary nucleation of IA-SA/A rather than the self-nucleation of IA appears to be the dominant pathways in polluted coastal regions, esp. in winter. These new insights are helpful to understand the mechanisms of new particle formation induced by IA in clean and polluted coastal regions.
    >> More from SciFinder ®
    https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BB3cXnsFait7s%253D&md5=661c4cafce75612ebd720a3f33d3416b
  13. 13
    He, X.-C.; Tham, Y. J.; Dada, L.; Wang, M.; Finkenzeller, H.; Stolzenburg, D.; Iyer, S.; Simon, M.; Kürten, A.; Shen, J. Role of iodine oxoacids in atmospheric aerosol nucleation. Science 2021, 371, 589– 595,  DOI: 10.1126/science.abe0298
    Google Scholar
    13
    Role of iodine oxoacids in atmospheric aerosol nucleation
    He, Xu-Cheng; Tham, Yee Jun; Dada, Lubna; Wang, Mingyi; Finkenzeller, Henning; Stolzenburg, Dominik; Iyer, Siddharth; Simon, Mario; Kurten, Andreas; Shen, Jiali; Rorup, Birte; Rissanen, Matti; Schobesberger, Siegfried; Baalbaki, Rima; Wang, Dongyu S.; Koenig, Theodore K.; Jokinen, Tuija; Sarnela, Nina; Beck, Lisa J.; Almeida, Joao; Amanatidis, Stavros; Amorim, Antonio; Ataei, Farnoush; Baccarini, Andrea; Bertozzi, Barbara; Bianchi, Federico; Brilke, Sophia; Caudillo, Lucia; Chen, Dexian; Chiu, Randall; Chu, Biwu; Dias, Antonio; Ding, Aijun; Dommen, Josef; Duplissy, Jonathan; El Haddad, Imad; Gonzalez Carracedo, Loic; Granzin, Manuel; Hansel, Armin; Heinritzi, Martin; Hofbauer, Victoria; Junninen, Heikki; Kangasluoma, Juha; Kemppainen, Deniz; Kim, Changhyuk; Kong, Weimeng; Krechmer, Jordan E.; Kvashin, Aleksander; Laitinen, Totti; Lamkaddam, Houssni; Lee, Chuan Ping; Lehtipalo, Katrianne; Leiminger, Markus; Li, Zijun; Makhmutov, Vladimir; Manninen, Hanna E.; Marie, Guillaume; Marten, Ruby; Mathot, Serge; Mauldin, Roy L.; Mentler, Bernhard; Mohler, Ottmar; Muller, Tatjana; Nie, Wei; Onnela, Antti; Petaja, Tuukka; Pfeifer, Joschka; Philippov, Maxim; Ranjithkumar, Ananth; Saiz-Lopez, Alfonso; Salma, Imre; Scholz, Wiebke; Schuchmann, Simone; Schulze, Benjamin; Steiner, Gerhard; Stozhkov, Yuri; Tauber, Christian; Tome, Antonio; Thakur, Roseline C.; Vaisanen, Olli; Vazquez-Pufleau, Miguel; Wagner, Andrea C.; Wang, Yonghong; Weber, Stefan K.; Winkler, Paul M.; Wu, Yusheng; Xiao, Mao; Yan, Chao; Ye, Qing; Ylisirnio, Arttu; Zauner-Wieczorek, Marcel; Zha, Qiaozhi; Zhou, Putian; Flagan, Richard C.; Curtius, Joachim; Baltensperger, Urs; Kulmala, Markku; Kerminen, Veli-Matti; Kurten, Theo; Donahue, Neil M.; Volkamer, Rainer; Kirkby, Jasper; Worsnop, Douglas R.; Sipila, Mikko
    Science (Washington, DC, United States) (2021), 371 (6529), 589-595CODEN: SCIEAS; ISSN:1095-9203. (American Association for the Advancement of Science)
    Iodic acid (HIO3) is known to form aerosol particles in coastal marine regions, but predicted nucleation and growth rates are lacking. Using the CERN CLOUD (Cosmics Leaving Outdoor Droplets) chamber, we find that the nucleation rates of HIO3 particles are rapid, even exceeding sulfuric acid-ammonia rates under similar conditions. We also find that ion-induced nucleation involves IO3- and the sequential addn. of HIO3 and that it proceeds at the kinetic limit below +10°C. In contrast, neutral nucleation involves the repeated sequential addn. of iodous acid (HIO2) followed by HIO3, showing that HIO2 plays a key stabilizing role. Freshly formed particles are composed almost entirely of HIO3, which drives rapid particle growth at the kinetic limit. Our measurements indicate that iodine oxoacid particle formation can compete with sulfuric acid in pristine regions of the atm.
    >> More from SciFinder ®
    https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BB3MXjsFCrtr8%253D&md5=f7b67dfba68a1d92579197f81529327b
  14. 14
    Baccarini, A.; Karlsson, L.; Dommen, J.; Duplessis, P.; Vullers, J.; Brooks, I. M.; Saiz-Lopez, A.; Salter, M.; Tjernstrom, M.; Baltensperger, U. Frequent new particle formation over the high Arctic pack ice by enhanced iodine emissions. Nat. Commun. 2020, 11, 4924,  DOI: 10.1038/s41467-020-19533-y
    Google Scholar
    14
    Frequent new particle formation over the high Arctic pack ice by enhanced iodine emissions
    Baccarini, Andrea; Karlsson, Linn; Dommen, Josef; Duplessis, Patrick; Vullers, Jutta; Brooks, Ian M.; Saiz-Lopez, Alfonso; Salter, Matthew; Tjernstrom, Michael; Baltensperger, Urs; Zieger, Paul; Schmale, Julia
    Nature Communications (2020), 11 (1), 4924CODEN: NCAOBW; ISSN:2041-1723. (Nature Research)
    In the central Arctic Ocean the formation of clouds and their properties are sensitive to the availability of cloud condensation nuclei (CCN). The vapors responsible for new particle formation (NPF), potentially leading to CCN, have remained unidentified since the first aerosol measurements in 1991. Here, we report that all the obsd. NPF events from the Arctic Ocean 2018 expedition are driven by iodic acid with little contribution from sulfuric acid. Iodic acid largely explains the growth of ultrafine particles (UFP) in most events. The iodic acid concn. increases significantly from summer towards autumn, possibly linked to the ocean freeze-up and a seasonal rise in ozone. This leads to a one order of magnitude higher UFP concn. in autumn. Measurements of cloud residuals suggest that particles smaller than 30 nm in diam. can activate as CCN. Therefore, iodine NPF has the potential to influence cloud properties over the Arctic Ocean.
    >> More from SciFinder ®
    https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BB3cXhvFyqt7jM&md5=8ce5a303b90658edab0b26febba072cb
  15. 15
    Jimenez, J. L.; Canagaratna, M. R.; Donahue, N. M.; Prevot, A. S. H.; Zhang, Q.; Kroll, J. H.; DeCarlo, P. F.; Allan, J. D.; Coe, H.; Ng, N. L. Evolution of Organic Aerosols in the Atmosphere. Science (New York, N.Y.) 2009, 326, 1525– 9,  DOI: 10.1126/science.1180353
    Google Scholar
    15
    Evolution of Organic Aerosols in the Atmosphere
    Jimenez, J. L.; Canagaratna, M. R.; Donahue, N. M.; Prevot, A. S. H.; Zhang, Q.; Kroll, J. H.; DeCarlo, P. F.; Allan, J. D.; Coe, H.; Ng, N. L.; Aiken, A. C.; Docherty, K. S.; Ulbrich, I. M.; Grieshop, A. P.; Robinson, A. L.; Duplissy, J.; Smith, J. D.; Wilson, K. R.; Lanz, V. A.; Hueglin, C.; Sun, Y. L.; Tian, J.; Laaksonen, A.; Raatikainen, T.; Rautiainen, J.; Vaattovaara, P.; Ehn, M.; Kulmala, M.; Tomlinson, J. M.; Collins, D. R.; Cubison, M. J.; Dunlea, J.; Huffman, J. A.; Onasch, T. B.; Alfarra, M. R.; Williams, P. I.; Bower, K.; Kondo, Y.; Schneider, J.; Drewnick, F.; Borrmann, S.; Weimer, S.; Demerjian, K.; Salcedo, D.; Cottrell, L.; Griffin, R.; Takami, A.; Miyoshi, T.; Hatakeyama, S.; Shimono, A.; Sun, J. Y.; Zhang, Y. M.; Dzepina, K.; Kimmel, J. R.; Sueper, D.; Jayne, J. T.; Herndon, S. C.; Trimborn, A. M.; Williams, L. R.; Wood, E. C.; Middlebrook, A. M.; Kolb, C. E.; Baltensperger, U.; Worsnop, D. R.
    Science (Washington, DC, United States) (2009), 326 (5959), 1525-1529CODEN: SCIEAS; ISSN:0036-8075. (American Association for the Advancement of Science)
    Org. aerosol (OA) particles affect climate forcing and human health, but their sources and evolution are poorly characterized. A unifying model framework describing the atm. evolution of OA which is constrained by high time resolved measurements of its compn., volatility, and oxidn. state is presented. OA and OA precursor gases evolve by becoming increasingly oxidized, less volatile, and more hygroscopic, leading to the formation of oxygenated org. aerosols (OOA), with concns. comparable to those of SO42- aerosols throughout the Northern Hemisphere. This model framework captures the dynamic aging behavior obsd. in the atm. and lab.; it serves as a basis to improve regional and global model parameterizations.
    >> More from SciFinder ®
    https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD1MXhsFensbjE&md5=dd5505995c2591c0540180493b0020ee
  16. 16
    Petaja, T.; Tabakova, K.; Manninen, A.; Ezhova, E.; O’Connor, E.; Moisseev, D.; Sinclair, V. A.; Backman, J.; Levula, J.; Luoma, K. Influence of biogenic emissions from boreal forests on aerosol-cloud interactions. Nature Geoscience 2022, 15, 42– 47,  DOI: 10.1038/s41561-021-00876-0
    Google Scholar
    There is no corresponding record for this reference.
  17. 17
    Tröstl, J.; Chuang, W.; Gordon, H.; Heinritzi, M.; Yan, C.; Molteni, U.; Ahlm, L.; Frege, C.; Bianchi, F.; Wagner, R. The role of low-volatility organic compounds in initial particle growth in the atmosphere. Nature 2016, 533, 527– 531,  DOI: 10.1038/nature18271
    Google Scholar
    17
    The role of low-volatility organic compounds in initial particle growth in the atmosphere
    Trostl, Jasmin; Chuang, Wayne K.; Gordon, Hamish; Heinritzi, Martin; Yan, Chao; Molteni, Ugo; Ahlm, Lars; Frege, Carla; Bianchi, Federico; Wagner, Robert; Simon, Mario; Lehtipalo, Katrianne; Williamson, Christina; Craven, Jill S.; Duplissy, Jonathan; Adamov, Alexey; Almeida, Joao; Bernhammer, Anne-Kathrin; Breitenlechner, Martin; Brilke, Sophia; Dias, Antonio; Ehrhart, Sebastian; Flagan, Richard C.; Franchin, Alessandro; Fuchs, Claudia; Guida, Roberto; Gysel, Martin; Hansel, Armin; Hoyle, Christopher R.; Jokinen, Tuija; Junninen, Heikki; Kangasluoma, Juha; Keskinen, Helmi; Kim, Jaeseok; Krapf, Manuel; Kurten, Andreas; Laaksonen, Ari; Lawler, Michael; Leiminger, Markus; Mathot, Serge; Mohler, Ottmar; Nieminen, Tuomo; Onnela, Antti; Petaja, Tuukka; Piel, Felix M.; Miettinen, Pasi; Rissanen, Matti P.; Rondo, Linda; Sarnela, Nina; Schobesberger, Siegfried; Sengupta, Kamalika; Sipila, Mikko; Smith, James N.; Steiner, Gerhard; Tome, Antonio; Virtanen, Annele; Wagner, Andrea C.; Weingartner, Ernest; Wimmer, Daniela; Winkler, Paul M.; Ye, Penglin; Carslaw, Kenneth S.; Curtius, Joachim; Dommen, Josef; Kirkby, Jasper; Kulmala, Markku; Riipinen, Ilona; Worsnop, Douglas R.; Donahue, Neil M.; Baltensperger, Urs
    Nature (London, United Kingdom) (2016), 533 (7604), 527-531CODEN: NATUAS; ISSN:0028-0836. (Nature Publishing Group)
    About half of present-day cloud condensation nuclei originate from atm. nucleation, frequently appearing as a burst of new particles near midday. Atm. observations show that the growth rate of new particles often accelerates when the diam. of the particles is between one and ten nanometers. In this crit. size range, new particles are most likely to be lost by coagulation with pre-existing particles, thereby failing to form new cloud condensation nuclei that are typically 50 to 100 nm across. Sulfuric acid vapor is often involved in nucleation but is too scarce to explain most subsequent growth, leaving org. vapors as the most plausible alternative, at least in the planetary boundary layer. Although recent studies predict that low-volatility org. vapors contribute during initial growth, direct evidence has been lacking. The accelerating growth may result from increased photolytic prodn. of condensable org. species in the afternoon, and the presence of a possible Kelvin (curvature) effect, which inhibits org. vapor condensation on the smallest particles (the nano-Kohler theory), has so far remained ambiguous. The authors presented expts. performed in a large chamber under atm. conditions that investigate the role of org. vapors in the initial growth of nucleated org. particles in the absence of inorg. acids and bases such as sulfuric acid or ammonia and amines, resp. Using data from the same set of expts., it has been shown that org. vapors alone can drive nucleation. They focused on the growth of nucleated particles and find that the org. vapors that drive initial growth have extremely low volatilities (satn. concn. less than 10-4.5 micrograms per cubic meter). As the particles increase in size and the Kelvin barrier falls, subsequent growth is primarily due to more abundant org. vapors of slightly higher volatility (satn. concns. of 10-4.5 to 10-0.5 micrograms per cubic meter). They present a particle growth model that quant. reproduces measurements. They implement a parameterization of the first steps of growth in a global aerosol model and find that concns. of atm. cloud concn. nuclei can change substantially in response, i.e., by up to 50 per cent in comparison with previously assumed growth rate parameterizations.
    >> More from SciFinder ®
    https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC28Xoslyrur4%253D&md5=7e09ef77e9daeb1f54cb52383f4feb68
  18. 18
    Crounse, J.; Nielsen, L.; Jørgensen, S.; Kjaergaard, H.; Wennberg, P. Autoxidation of Organic Compounds in the Atmosphere. JOURNAL OF PHYSICAL. CHEMISTRY LETTERS 2013, 4, 3513– 3520,  DOI: 10.1021/jz4019207
    Google Scholar
    There is no corresponding record for this reference.
  19. 19
    Bianchi, F.; Kurtén, T.; Riva, M.; Mohr, C.; Rissanen, M.; Roldin, P.; Berndt, T.; Crounse, J.; Wennberg, P.; Mentel, T.; Wildt, J.; Junninen, H.; Jokinen, T.; Kulmala, M.; Worsnop, D.; Thornton, J.; Donahue, N.; Kjaergaard, H.; Ehn, M. Highly Oxygenated Molecules (HOM) from Gas-Phase Autoxidation Involving Organic Peroxy Radicals: A Key Contributor to Atmospheric Aerosol. Chem. Rev. 2019, 119, 3472– 3509,  DOI: 10.1021/acs.chemrev.8b00395
    Google Scholar
    19
    Highly Oxygenated Molecules (HOM) from Gas-Phase Autoxidation Involving Organic Peroxy Radicals: A Key Contributor to Atmospheric Aerosol
    Bianchi, Federico; Kurten, Theo; Riva, Matthieu; Mohr, Claudia; Rissanen, Matti P.; Roldin, Pontus; Berndt, Torsten; Crounse, John D.; Wennberg, Paul O.; Mentel, Thomas F.; Wildt, Jurgen; Junninen, Heikki; Jokinen, Tuija; Kulmala, Markku; Worsnop, Douglas R.; Thornton, Joel A.; Donahue, Neil; Kjaergaard, Henrik G.; Ehn, Mikael
    Chemical Reviews (Washington, DC, United States) (2019), 119 (6), 3472-3509CODEN: CHREAY; ISSN:0009-2665. (American Chemical Society)
    A review which defines highly oxygenated org. mols. (HOM) formed in the atm. via auto-oxidn. involving peroxy radicals arising from volatile org. compds. describing currently available techniques for their identification/quantification, followed by a summary of the current knowledge on their formation mechanisms and physicochem. properties, is given. Major aims are to provide a common frame for the currently quite fragmented literature on HOM studies and highlighting existing gaps, and suggesting directions for future HOM research. Topics discussed include: introduction; HOM background (defining key concepts, HOM in relation to other classification schemes, historical naming conventions); HOM detection (gas and particle phases, uncertainties and anal. challenges of HOM detection); HOM formation mechanisms (auto-oxidn. involving peroxy radical as HOM source, bimol. RO2 reactions, factors affecting HOM formation); HOM properties and atm. fate (physicochem. properties, removal mechanisms); HOM atm. observations and impact (ambient HOM observation, atm. impact); and summary and perspectives.
    >> More from SciFinder ®
    https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC1MXjsFSrsb0%253D&md5=860f5dce6415fbbdee9f45b7afeff559
  20. 20
    Roldin, P.; Ehn, M.; Kurten, T.; Olenius, T.; Rissanen, M. P.; Sarnela, N.; Elm, J.; Rantala, P.; Hao, L.; Hyttinen, N. The role of highly oxygenated organic molecules in the Boreal aerosol-cloud-climate system. Nat. Commun. 2019, 10, 1– 15,  DOI: 10.1038/s41467-019-12338-8
    Google Scholar
    There is no corresponding record for this reference.
  21. 21
    Xavier, C.; de jonge, R. W.; Jokinen, T.; Beck, L.; Sipilä, M.; Olenius, T.; Roldin, P. Role of Iodine-Assisted Aerosol Particle Formation in Antarctica. Environ. Sci. Technol. 2024, 58, 7314– 7324,  DOI: 10.1021/acs.est.3c09103
    Google Scholar
    There is no corresponding record for this reference.
  22. 22
    Brean, J.; Dall’Osto, M.; Simo, R.; Shi, Z.; Beddows, D. C. S.; Harrison, R. M. Open ocean and coastal new particle formation from sulfuric acid and amines around the Antarctic Peninsula. Nature Geoscience 2021, 14, 383– 388,  DOI: 10.1038/s41561-021-00751-y
    Google Scholar
    There is no corresponding record for this reference.
  23. 23
    Jokinen, T.; Sipila, M.; Kontkanen, J.; Vakkari, V.; Tisler, P.; Duplissy, E.-M.; Junninen, H.; Kangasluoma, J.; Manninen, H. E.; Petaja, T. Ion-induced sulfuric acid-ammonia nucleation drives particle formation in coastal Antarctica. Science Advances 2018, 4, eaat9744,  DOI: 10.1126/sciadv.aat9744
    Google Scholar
    There is no corresponding record for this reference.
  24. 24
    Lee, H.; Lee, K.; Lunder, C.; Krejci, R.; Aas, W.; Jiyeon, P.; Park, K.-t.; Lee, B.; Yoon, Y.-J.; Park, K. Atmospheric new particle formation characteristics in the Arctic as measured at Mount Zeppelin, Svalbard, from 2016 to 2018. Atmospheric Chem. Phys. 2020, 20 (21), 13425– 13441
    Google Scholar
    There is no corresponding record for this reference.
  25. 25
    Kecorius, S.; Vogl, T.; Paasonen, P.; Lampilahti, J.; Rothenberg, D.; Wex, H.; Zeppenfeld, S.; van Pinxteren, M.; Hartmann, M.; Henning, S. New particle formation and its effect on cloud condensation nuclei abundance in the summer Arctic: a case study in the Fram Strait and Barents Sea. Atmospheric Chemistry and Physics 2019, 19, 14339– 14364,  DOI: 10.5194/acp-19-14339-2019
    Google Scholar
    There is no corresponding record for this reference.
  26. 26
    DallÓsto, M.; Geels, C.; Beddows, D. C. S.; Boertmann, D.; Lange, R.; Nøjgaard, J. K.; Harrison, R. M.; Simo, R.; Skov, H.; Massling, A. Regions of open water and melting sea ice drive new particle formation in North East Greenland. Sci. Rep. 2018, 8, 6109,  DOI: 10.1038/s41598-018-24426-8
    Google Scholar
    There is no corresponding record for this reference.
  27. 27
    Mäkelä, J.; Yli-Koivisto, S.; Hiltunen, V.; Seidl, W.; Swietlicki, E.; Teinilä, K.; Sillanpää, M.; Koponen, I.; Paatero, J.; Rosman, K.; Hämeri, K. Chemical composition of aerosol during particle formation events in boreal forest. Tellus B 2001, 53, 380– 393,  DOI: 10.1034/j.1600-0889.2001.530405.x
    Google Scholar
    27
    Chemical composition of aerosol during particle formation events in boreal forest
    Makela, J. M.; Yli-Koivisto, S.; Hiltunen, V.; Seidl, W.; Swietlicki, E.; Teinila, K.; Sillanpaa, M.; Koponen, I. K.; Paatero, J.; Rosman, K.; Hameri, K.
    Tellus, Series B: Chemical and Physical Meteorology (2001), 53B (4), 380-393CODEN: TSBMD7; ISSN:0280-6509. (Munksgaard International Publishers Ltd.)
    Size-segregated chem. aerosol anal. of 5 integrated samples was performed for atm. aerosols during new particle formation events in spring 1999 during the BIOFOR 3 measurement campaign at a boreal forest site in southern Finland. Aerosol samples collected by a cascade low-pressure impactor were taken selectively to distinguish particle formation event aerosols from non-event aerosols. The division into event and non-event cases was done in-situ in the field, based on the online submicron no. size distribution. Results of chem. ionic compn. of particles showed only small differences between event and non-event sample sets. Event samples had lower concns. of total SO42- and NH4+ and light dicarboxylic acids, e.g., oxalate, malonate, and succinate. In event samples, nucleation mode particle MSA (methane sulfonic acid) was present in concns. exceeding those obsd. in non-event samples; however, at larger particle sizes, sample sets contained rather similar MSA concns. The most significant difference between event and non-event sets was obsd. for dimethylammonium, the ionic component of dimethylamine ((CH3)2NH), which seemed to be present in the particle phase during particle formation periods and/or during subsequent particle growth. The abs. event sample dimethylamine concns. were >30-fold greater than non-event concns. in the accumulation mode size range. The non-event back-up filter stage for sub-30 nm particles contained more dimethylamine than event samples. This fractionation is probably a condensation artifact from impactor sampling. A simple mass balance est. was performed to evaluate the quality and consistency of results for overall mass concn.
    >> More from SciFinder ®
    https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD3MXns1Gktrs%253D&md5=ce371260e6101c15c4bbaac0a5473bb1
  28. 28
    Hemmilä, M.; Hellén, H.; Virkkula, A.; Makkonen, U.; Praplan, A.; Kontkanen, J.; Ahonen, L.; Kulmala, M.; Hakola, H. Amines in boreal forest air at SMEAR II station in Finland. Atmospheric Chemistry and Physics 2018, 18, 6367– 6380,  DOI: 10.5194/acp-18-6367-2018
    Google Scholar
    There is no corresponding record for this reference.
  29. 29
    Lawler, M.; Rissanen, M.; Ehn, M.; Mauldin, R.; Sarnela, N.; Sipilä, M.; Smith, J. Evidence for Diverse Biogeochemical Drivers of Boreal Forest New Particle Formation. Geophys. Res. Lett. 2018, 45, 2038– 2046,  DOI: 10.1002/2017GL076394
    Google Scholar
    There is no corresponding record for this reference.
  30. 30
    Sogacheva, L.; Saukkonen, L.; Nilsson, E.; Dal Maso, M.; Schultz, D.; de Leeuw, G.; Kulmala, M. New aerosol particle formation in different synoptic situations at Hyytiälä, Southern Finland. Tellus B 2022, 60, 485– 494,  DOI: 10.1111/j.1600-0889.2008.00364.x
    Google Scholar
    There is no corresponding record for this reference.
  31. 31
    Nieminen, T.; Yli-Juuti, T.; Manninen, H. E.; Petäjä, T.; Kerminen, V.-M.; Kulmala, M. Technical note: New particle formation event forecasts during PEGASOS-Zeppelin Northern mission 2013 in Hyytiälä, Finland. Atmospheric Chemistry and Physics 2015, 15, 12385– 12396,  DOI: 10.5194/acp-15-12385-2015
    Google Scholar
    There is no corresponding record for this reference.
  32. 32
    Öström, E.; Putian, Z.; Schurgers, G.; Mishurov, M.; Kivekäs, N.; Lihavainen, H.; Ehn, M.; Rissanen, M. P.; Kurtén, T.; Boy, M.; Swietlicki, E.; Roldin, P. Modeling the role of highly oxidized multifunctional organic molecules for the growth of new particles over the boreal forest region. Atmospheric Chemistry and Physics 2017, 17, 8887– 8901,  DOI: 10.5194/acp-17-8887-2017
    Google Scholar
    There is no corresponding record for this reference.
  33. 33
    Jenkin, M. E.; Saunders, S. M.; Pilling, M. J. The tropospheric degradation of volatile organic compounds: a protocol for mechanism development. Atmos. Environ. 1997, 31, 81– 104,  DOI: 10.1016/S1352-2310(96)00105-7
    Google Scholar
    33
    The tropospheric degradation of volatile organic compounds: a protocol for mechanism development
    Jenkin, Michael E.; Saunders, Sandra M.; Pilling, Michael J.
    Atmospheric Environment (1996), 31 (1), 81-104CODEN: AENVEQ; ISSN:1352-2310. (Elsevier)
    Kinetic and mechanistic data relevant to the tropospheric oxidn. of volatile org. compds. (VOCs) were used to define a series of rules for the construction of detailed degrdn. schemes for use in numerical models. These rules are intended to apply to the treatment of a wide range of non-arom. hydrocarbons and oxygenated and chlorinated VOCs, and are currently used to provide an up-to-date mechanism describing the degrdn. of a range of VOCs, and the formation of secondary oxidants, for use in a model of the boundary layer over Europe. The schemes constructed using this protocol are applicable, however, to a wide range of ambient conditions, and may be employed in models of urban, rural, or remote tropospheric environments, or for the simulation of secondary pollutant formation for a range of NOx or VOC emission scenarios. These schemes are believed to be particularly appropriate for comparative assessments of the formation of oxidants, such as ozone, from the degrdn. of org. compds. The protocol is divided into a series of subsections dealing with initiation reactions, the reactions of the radical intermediates and the further degrdn. of first and subsequent generation products. The present work draws heavily on previous reviews and evaluations of data relevant to tropospheric chem. Where necessary, however, existing recommendations are adapted, or new rules are defined, to reflect recent improvements in the database, particularly with regard to the treatment of peroxy radical (RO2) reactions for which there have been major advances, even since comparatively recent reviews. The present protocol aims to take into consideration work available in the open literature up to the end of 1994, and some further studies known by the authors, which were under review at that time. A major disadvantage of explicit chem. mechanisms is the very large no. of reactions potentially generated, if a series of rules is rigorously applied. The protocol aims to limit the no. of reactions in a degrdn. scheme by applying a degree of strategic simplication, while maintaining the essential features of the chem. These simplication measures are described, and their influence is demonstrated and discussed. The resultant mechanisms are believed to provide a suitable starting point for the generation of reduced chem. mechanisms.
    >> More from SciFinder ®
    https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADyaK28XntVOnt78%253D&md5=44dc875e8e1a9456ed2b570393d450c6
  34. 34
    Jenkin, M. E.; Saunders, S. M.; Wagner, V.; Pilling, M. J. Protocol for the development of the Master Chemical Mechanism, MCM v3 (Part B): tropospheric degradation of aromatic volatile organic compounds. Atmospheric Chemistry and Physics 2003, 3, 181– 193,  DOI: 10.5194/acp-3-181-2003
    Google Scholar
    34
    Protocol for the development of the master chemical mechanism, MCM v3 (part B): tropospheric degradation of aromatic volatile organic compounds
    Jenkin, M. E.; Saunders, S. M.; Wagner, V.; Pilling, M. J.
    Atmospheric Chemistry and Physics (2003), 3 (1), 181-193CODEN: ACPTCE; ISSN:1680-7324. (European Geophysical Society)
    Kinetic and mechanistic data relevant to the tropospheric degrdn. of arom. volatile org. compds. (VOC) were used to define a mechanism development protocol, which was used to construct degrdn. schemes for 18 arom. VOC as part of version 3 of the Master Chem. Mechanism (MCM v3). This is complementary to the treatment of 107 nonarom. VOC, presented in a companion paper. The protocol is divided into subsections describing initiation reactions, the degrdn. chem. to 1st generation products via a no. of competitive routes, and the further degrdn. of 1st and subsequent generation products. Emphasis is placed on describing where the treatment differs from that applied to the nonarom. VOC. The protocol is based on work available in the open literature up to the beginning of 2001, and some other studies known by the authors which were under review at the time. Photochem. Ozone Creation Potentials (POCP) were calcd. for the 18 arom. VOC in MCM v3 for idealized conditions appropriate to north-west Europe, using a photochem. trajectory model. The POCP values provide a measure of the relative ozone forming abilities of the VOC. These show distinct differences from POCP values calcd. previously for the aroms., using earlier versions of the MCM, and reasons for these differences are discussed.
    >> More from SciFinder ®
    https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD3sXns1Sntrw%253D&md5=cbb782c7d9ee66115b9c13f14758d095
  35. 35
    Braeuer, P.; Tilgner, A.; Wolke, R.; Herrmann, H. Mechanism development and modelling of tropospheric multiphase halogen chemistry: The CAPRAM Halogen Module 2.0 (HM2). JOURNAL OF ATMOSPHERIC CHEMISTRY 2013, 70, 19– 52,  DOI: 10.1007/s10874-013-9249-6
    Google Scholar
    There is no corresponding record for this reference.
  36. 36
    Wu, R.; Wang, S.; Wang, L. A New Mechanism for The Atmospheric Oxidation of Dimethyl Sulfide. The Importance of Intramolecular Hydrogen Shift in CH3SCH2OO Radical. journal of physical chemistry. A 2015, 119, 112,  DOI: 10.1021/jp511616j
    Google Scholar
    There is no corresponding record for this reference.
  37. 37
    Berndt, T.; Scholz, W.; Mentler, B.; Fischer, L.; Hoffmann, E.; Tilgner, A.; Hyttinen, N.; Prisle, N. L.; Hansel, A.; Herrmann, H. Fast Peroxy Radical Isomerization and OH Recycling in the Reaction of OH Radicals with Dimethyl Sulfide. J. Phys. Chem. Lett. 2019, 10, 6478,  DOI: 10.1021/acs.jpclett.9b02567
    Google Scholar
    37
    Fast Peroxy Radical Isomerization and OH Recycling in the Reaction of OH Radicals with Dimethyl Sulfide
    Berndt, T.; Scholz, W.; Mentler, B.; Fischer, L.; Hoffmann, E. H.; Tilgner, A.; Hyttinen, N.; Prisle, N. L.; Hansel, A.; Herrmann, H.
    Journal of Physical Chemistry Letters (2019), 10 (21), 6478-6483CODEN: JPCLCD; ISSN:1948-7185. (American Chemical Society)
    Di-Me sulfide (DMS), produced by marine organisms, represents the most abundant, biogenic sulfur emission into the Earth's atm. The gas-phase degrdn. of DMS is mainly initiated by the reaction with the OH radical forming first CH3SCH2O2 radicals from the dominant H-abstraction channel. It is exptl. shown that these peroxy radicals undergo a two-step isomerization process finally forming a product consistent with the formula HOOCH2SCHO. The isomerization process is accompanied by OH recycling. The rate-limiting first isomerization step, CH3SCH2O2 → CH2SCH2OOH, followed by O2 addn., proceeds with k = (0.23 ± 0.12) s-1 at 295 ± 2 K. Competing bimol. CH3SCH2O2 reactions with NO, HO2, or RO2 radicals are less important for trace-gas conditions over the oceans. Results of atm. chem. simulations demonstrate the predominance (≥95%) of CH3SCH2O2 isomerization. The rapid peroxy radical isomerization, not yet considered in models, substantially changes the understanding of DMS's degrdn. processes in the atm.
    >> More from SciFinder ®
    https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC1MXhvFWltrjP&md5=0d91ffa9cadc1365ffbfb0a48fe0373b
  38. 38
    Veres, P. R.; Neuman, J. A.; Bertram, T. H.; Assaf, E.; Wolfe, G. M.; Williamson, C. J.; Weinzierl, B.; Tilmes, S.; Thompson, C. R.; Thames, A. B.; Schroder, J. C.; Saiz-Lopez, A.; Rollins, A. W.; Roberts, J. M.; Price, D.; Peischl, J.; Nault, B. A.; Møller, K. H.; Miller, D. O.; Meinardi, S.; Li, Q.; Lamarque, J.-F.; Kupc, A.; Kjaergaard, H. G.; Kinnison, D.; Jimenez, J. L.; Jernigan, C. M.; Hornbrook, R. S.; Hills, A.; Dollner, M.; Day, D. A.; Cuevas, C. A.; Campuzano-Jost, P.; Burkholder, J.; Bui, T. P.; Brune, W. H.; Brown, S. S.; Brock, C. A.; Bourgeois, I.; Blake, D. R.; Apel, E. C.; Ryerson, T. B. Global airborne sampling reveals a previously unobserved dimethyl sulfide oxidation mechanism in the marine atmosphere. Proc. Natl. Acad. Sci. U. S. A. 2020, 117, 4505– 4510,  DOI: 10.1073/pnas.1919344117
    Google Scholar
    38
    Global airborne sampling reveals a previously unobserved dimethyl sulfide oxidation mechanism in the marine atmosphere
    Veres, Patrick R.; Neuman, J. Andrew; Bertram, Timothy H.; Assaf, Emmanuel; Wolfe, Glenn M.; Williamson, Christina J.; Weinzierl, Bernadett; Tilmes, Simone; Thompson, Chelsea R.; Thames, Alexander B.; Schroder, Jason C.; Saiz-Lopez, Alfonso; Rollins, Andrew W.; Roberts, James M.; Price, Derek; Peischl, Jeff; Nault, Benjamin A.; Moeller, Kristian H.; Miller, David O.; Meinardi, Simone; Li, Qinyi; Lamarque, Jean-Francois; Kupc, Agnieszka; Kjaergaard, Henrik G.; Kinnison, Douglas; Jimenez, Jose L.; Jernigan, Christopher M.; Hornbrook, Rebecca S.; Hills, Alan; Dollner, Maximilian; Day, Douglas A.; Cuevas, Carlos A.; Campuzano-Jost, Pedro; Burkholder, James; Bui, T. Paul; Brune, William H.; Brown, Steven S.; Brock, Charles A.; Bourgeois, Ilann; Blake, Donald R.; Apel, Eric C.; Ryerson, Thomas B.
    Proceedings of the National Academy of Sciences of the United States of America (2020), 117 (9), 4505-4510CODEN: PNASA6; ISSN:0027-8424. (National Academy of Sciences)
    Di-Me sulfide (DMS), emitted from the oceans, is the most abundant biol. source of sulfur to the marine atm. Atm. DMS is oxidized to condensable products that form secondary aerosols that affect Earth's radiative balance by scattering solar radiation and serving as cloud condensation nuclei. We report the atm. discovery of a previously unquantified DMS oxidn. product, hydroperoxymethyl thioformate (HPMTF, HOOCH2SCHO), identified through global-scale airborne observations that demonstrate it to be a major reservoir of marine sulfur. Observationally constrained model results show that more than 30% of oceanic DMS emitted to the atm. forms HPMTF. Coincident particle measurements suggest a strong link between HPMTF concn. and new particle formation and growth. Analyses of these observations show that HPMTF chem. must be included in atm. models to improve representation of key linkages between the biogeochem. of the ocean, marine aerosol formation and growth, and their combined effects on climate.
    >> More from SciFinder ®
    https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BB3cXksVSqsr0%253D&md5=0d957baa667a2543cd9a4f3c467790a5
  39. 39
    Hari, P.; Kulmala, M. Station for Measuring Ecosystem-Atmosphere Relations (SMEAR II). Boreal Environment Research 2005, 10, 315– 322
    Google Scholar
    39
    Station for Measuring Ecosystem-Atmosphere Relations (SMEAR II)
    Hari, Pertti; Kulmala, Markku
    Boreal Environment Research (2005), 10 (5), 315-322CODEN: BEREF7; ISSN:1239-6095. (Finnish Environment Institute)
    Here we present the ongoing SMEAR (Station for Measuring Forest Ecosystem-Atm. Relations) research program and also related future views. The main idea of SMEAR-type infrastructures is continuous, comprehensive measurements of fluxes, storages and concns. in the land ecosystem-atm. continuum. The major coupling mechanisms between atm. and land surface are the fluxes of energy, momentum, water, carbon dioxide, atm. trace gases and atm. aerosols. Understanding of couplings and feedbacks is the basis for the prediction of changes in the system formed by atm., vegetation and soil. A better quantification of the agents that cause climate change, as well as the emissions and removals of species, will provide more accurate projections of future atm. compn. and hence climate.
    >> More from SciFinder ®
    https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD2MXht1GhurvP&md5=fbd8465f76a998b3a0958c12089db374
  40. 40
    Neefjes, I.; Laapas, M.; Liu, Y.; Médus, E.; Miettunen, E.; Ahonen, L.; Quéléver, L.; Aalto, J.; Bäck, J.; Kerminen, V.-M.; Lamplahti, J.; Luoma, K.; Maki, M.; Mammarella, I.; Petäjä, T.; Räty, M.; Sarnela, N.; Ylivinkka, I.; Hakala, S.; Lintunen, A. 25 years of atmospheric and ecosystem measurements in a boreal forestSeasonal variation and responses to warm and dry years. Boreal Environment Research 2022, 27, 1– 31
    Google Scholar
    There is no corresponding record for this reference.
  41. 41
    Stein, A. F.; Draxler, R. R.; Rolph, G. D.; Stunder, B. J. B.; Cohen, M. D.; Ngan, F. NOAAs HYSPLIT Atmospheric Transport and Dispersion Modeling System. Bulletin of the American Meteorological Society 2015, 96, 2059– 2077,  DOI: 10.1175/BAMS-D-14-00110.1
    Google Scholar
    There is no corresponding record for this reference.
  42. 42
    Rolph, G.; Stein, A.; Stunder, B. Real-time Environmental Applications and Display sYstem: READY. Environmental Modelling & Software 2017, 95, 210– 228,  DOI: 10.1016/j.envsoft.2017.06.025
    Google Scholar
    There is no corresponding record for this reference.
  43. 43
    Lennartz, S. T.; Marandino, C. A.; von Hobe, M.; Cortes, P.; Quack, B.; Simo, R.; Booge, D.; Pozzer, A.; Steinhoff, T.; Arevalo-Martinez, D. L. Direct oceanic emissions unlikely to account for the missing source of atmospheric carbonyl sulfide. Atmospheric Chemistry and Physics 2017, 17, 385– 402,  DOI: 10.5194/acp-17-385-2017
    Google Scholar
    There is no corresponding record for this reference.
  44. 44
    Ziska, F.; Quack, B.; Abrahamsson, K.; Archer, S. D.; Atlas, E.; Bell, T.; Butler, J. H.; Carpenter, L. J.; Jones, C. E.; Harris, N. R. P. Global sea-to-air flux climatology for bromoform, dibromomethane and methyl iodide. Atmospheric Chemistry and Physics Discussions 2013, 13, 8915– 8934,  DOI: 10.5194/acp-13-8915-2013
    Google Scholar
    44
    Global sea-to-air flux climatology for bromoform, dibromomethane and methyl iodide
    Ziska, F.; Quack, B.; Abrahamsson, K.; Archer, S. D.; Atlas, E.; Bell, T.; Butler, J. H.; Carpenter, L. J.; Jones, C. E.; Harris, N. R. P.; Hepach, H.; Heumann, K. G.; Hughes, C.; Kuss, J.; Krueger, K.; Liss, P.; Moore, R. M.; Orlikowska, A.; Raimund, S.; Reeves, C. E.; Reifenhaeuser, W.; Robinson, A. D.; Schall, C.; Tanhua, T.; Tegtmeier, S.; Turner, S.; Wang, L.; Wallace, D.; Williams, J.; Yamamoto, H.; Yvon-Lewis, S.; Yokouchi, Y.
    Atmospheric Chemistry and Physics (2013), 13 (17), 8915-8934, 20 pp.CODEN: ACPTCE; ISSN:1680-7324. (Copernicus Publications)
    Volatile halogenated org. compds. contg. bromine and iodine, which are naturally produced in the ocean, are involved in ozone depletion in both the troposphere and stratosphere. Three prominent compds. transporting large amts. of marine halogens into the atm. are bromoform (CHBr3), dibromomethane (CH2Br2) and Me iodide (CH3I). The input of marine halogens to the stratosphere has been estd. from observations and modeling studies using low-resoln. oceanic emission scenarios derived from top-down approaches. In order to improve emission inventory ests., we calc. data-based high resoln. global sea-to-air flux ests. of these compds. from surface observations within the HalOcAt (Halocarbons in the Ocean and Atm.) database. Global maps of marine and atm. surface concns. are derived from the data which are divided into coastal, shelf and open ocean regions. Considering phys. and biogeochem. characteristics of ocean and atm., the open ocean water and atm. data are classified into 21 regions. The available data are interpolated onto a 1° × 1° grid while missing grid values are interpolated with latitudinal and longitudinal dependent regression techniques reflecting the compds.' distributions. With the generated surface concn. climatologies for the ocean and atm., global sea-to-air concn. gradients and sea-to-air fluxes are calcd. Based on these calcns. we est. a total global flux of 1.5/2.5 Gmol Br yr-1 for CHBr3, 0.78/0.98 Gmol Br yr-1 for CH2Br2 and 1.24/1.45 Gmol Br yr-1 for CH3I (robust fit/ordinary least squares regression techniques). Contrary to recent studies, neg. fluxes occur in each sea-to-air flux climatol., mainly in the Arctic and Antarctic regions. "Hot spots" for global polybromomethane emissions are located in the equatorial region, whereas Me iodide emissions are enhanced in the subtropical gyre regions. Inter-annual and seasonal variation is contained within our flux calcns. for all three compds. Compared to earlier studies, our global fluxes are at the lower end of ests., esp. for bromoform. An under-representation of coastal emissions and of extreme events in our est. might explain the mismatch between our bottom-up emission est. and top-down approaches.
    >> More from SciFinder ®
    https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3sXhslehtrbL&md5=d13f982b82d94c732ab4dc017908098c
  45. 45
    Nightingale, P. D.; Malin, G.; Law, C. S.; Watson, A. J.; Liss, P. S.; Liddicoat, M. I.; Boutin, J.; Upstill-Goddard, R. C. In situ evaluation of air-sea gas exchange parameterizations using novel conservative and volatile tracers. Global Biogeochemical Cycles 2000, 14, 373– 387,  DOI: 10.1029/1999GB900091
    Google Scholar
    45
    In situ evaluation of air-sea gas exchange parameterizations using novel conservative and volatile tracers
    Nightingale, Philip D.; Malin, Gill; Law, Cliff S.; Watson, Andrew J.; Liss, Peter S.; Liddicoat, Malcolm I.; Boutin, Jacqueline; Upstill-Goddard, Robert C.
    Global Biogeochemical Cycles (2000), 14 (1), 373-387CODEN: GBCYEP; ISSN:0886-6236. (American Geophysical Union)
    Measurements of air-sea gas exchange rates are reported from 2 deliberate tracer expts. in the southern North Sea during Feb. 1992 and 1993. A conservative tracer, spores of Bacillus globigii var. Niger, was used for the 1st time in an in situ air-sea gas exchange expt. This nonvolatile tracer is used to correct for dispersive diln. of the volatile tracers and allows 3 estns. of the transfer velocity for the same time period. The 1st estn. of the power dependence of gas transfer on mol. diffusivity in the marine environment is reported. This allows the impact of bubbles on ests. of the transfer velocity derived from changes in the He/SF6 ratio to be assessed. Data from earlier dual tracer expts. are reinterpreted, and findings suggest that results from all dual tracer expts. are mutually consistent. The complete data set is used to test published parameterizations of gas transfer with wind speed. A gas exchange relation that shows a dependence on wind speed intermediate between those of Liss and Merlivat (1986) and Wanninkhof (1992) is optimal. The dual tracer data are shown to be reasonably consistent with global ests. of gas exchange based on the uptake of natural and bomb-derived radiocarbon. The degree of scatter in the data when plotted against wind speed suggests that parameters not scaling with wind speed are also influencing gas exchange rates.
    >> More from SciFinder ®
    https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD3cXhvVGms7s%253D&md5=d317f0ad2e899416471475672bd335f3
  46. 46
    Lana, A.; Bell, T. G.; Simó, R.; Vallina, S. M.; Ballabrera-Poy, J.; Kettle, A. J.; Dachs, J.; Bopp, L.; Saltzman, E. S.; Stefels, J. An updated climatology of surface dimethlysulfide concentrations and emission fluxes in the global ocean. Global Biogeochemical Cycles 2011, 25, 886,  DOI: 10.1029/2010GB003850
    Google Scholar
    There is no corresponding record for this reference.
  47. 47
    Granier, C. S.; Darras, H.; Denier van der Gon, J.; Doubalova, N.; Elguindi, B.; Galle, M.; Gauss, M.; Guevara, J.; Jalkanen, J.; Kuenen, C.; Liousse, B.; Quack, D.; Simpson, K. The Copernicus Atmosphere Monitoring Service global and regional emissions. Sindelarova The Copernicus Atmosphere Monitoring Service global and regional emissions (April 2019 version) 2019, 16,  DOI: 10.24380/d0bn-kx16
    Google Scholar
    There is no corresponding record for this reference.
  48. 48
    Sindelarova, K.; Granier, C.; Bouarar, I.; Guenther, A.; Tilmes, S.; Stavrakou, T.; Muller, J.-F.; Kuhn, U.; Stefani, P.; Knorr, W. Global dataset of biogenic VOC emissions calculated by the MEGAN model over the last 30 years. Atmospheric Chemistry and Physics 2014, 14, 9317,  DOI: 10.5194/acp-14-9317-2014
    Google Scholar
    48
    Global data set of biogenic VOC emissions calculated by the MEGAN model over the last 30 years
    Sindelarova, K.; Granier, C.; Bouarar, I.; Guenther, A.; Tilmes, S.; Stavrakou, T.; Muller, J.-F.; Kuhn, U.; Stefani, P.; Knorr, W.
    Atmospheric Chemistry and Physics (2014), 14 (17), 9317-9341, 25 pp.CODEN: ACPTCE; ISSN:1680-7324. (Copernicus Publications)
    The Model of Emissions of Gases and Aerosols from Nature (MEGANv2.1) together with the Modern-Era Retrospective Anal. for Research and Applications (MERRA) meteorol. fields were used to create a global emission data set of biogenic volatile org. compds. (BVOC) available on a monthly basis for the time period of 1980-2010. This data set, developed under the Monitoring Atm. Compn. and Climate project (MACC), is called MEGAN-MACC. The model estd. mean annual total BVOC emission of 760 Tg (C) yr-1 consisting of isoprene (70%), monoterpenes (11%), methanol (6%), acetone (3%), sesquiterpenes (2.5%) and other BVOC species each contributing less than 2%. Several sensitivity model runs were performed to study the impact of different model input and model settings on isoprene ests. and resulted in differences of up to ±17% of the ref. isoprene total. A greater impact was obsd. for a sensitivity run applying parameterization of soil moisture deficit that led to a 50% redn. of isoprene emissions on a global scale, most significantly in specific regions of Africa, South America and Australia. MEGAN-MACC ests. are comparable to results of previous studies. More detailed comparison with other isoprene inventories indicated significant spatial and temporal differences between the data sets esp. for Australia, Southeast Asia and South America. MEGAN-MACC ests. of isoprene, α-pinene and group of monoterpenes showed a reasonable agreement with surface flux measurements at sites located in tropical forests in the Amazon and Malaysia. The model was able to capture the seasonal variation of isoprene emissions in the Amazon forest.
    >> More from SciFinder ®
    https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2cXhs1yktbjO&md5=978d8465b40240c42347d621604c1516
  49. 49
    Smith, B.; Wårlind, D.; Arneth, A.; Hickler, T.; Leadley, P.; Siltberg, J.; Zaehle, S. Implications of incorporating N cycling and N limitations on primary production in an individual-based dynamic vegetation model. Biogeosciences 2014, 11, 2027– 2054,  DOI: 10.5194/bg-11-2027-2014
    Google Scholar
    There is no corresponding record for this reference.
  50. 50
    Arneth, A.; Niinemets, U.; Pressley, S.; Bäck, J.; Hari, P.; Karl, T.; Noe, S.; Prentice, I. C.; Serça, D.; Hickler, T.; Wolf, A.; Smith, B. Process-based estimates of terrestrial ecosystem isoprene emissions: incorporating the effects of a direct CO2-isoprene interaction. Atmospheric Chemistry and Physics 2007, 7, 31– 53,  DOI: 10.5194/acp-7-31-2007
    Google Scholar
    There is no corresponding record for this reference.
  51. 51
    Paulot, F.; Jacob, D. J.; Johnson, M. T.; Bell, T. G.; Baker, A. R.; Keene, W. C.; Lima, I. D.; Doney, S. C.; Stock, C. A. Global oceanic emission of ammonia: Constraints from seawater and atmospheric observations. Global Biogeochemical Cycles 2015, 29, 1165– 1178,  DOI: 10.1002/2015GB005106
    Google Scholar
    There is no corresponding record for this reference.
  52. 52
    Carpenter, L.; MacDonald, S.; Shaw, M.; Kumar, R.; Saunders, R.; Parthipan, R.; Wilson, J.; Plane, J. Atmospheric iodine levels influenced by sea surface emissions of inorganic iodine. Nature Geoscience 2013, 6, 108– 111,  DOI: 10.1038/ngeo1687
    Google Scholar
    52
    Atmospheric iodine levels influenced by sea surface emissions of inorganic iodine
    Carpenter, Lucy J.; MacDonald, Samantha M.; Shaw, Marvin D.; Kumar, Ravi; Saunders, Russell W.; Parthipan, Rajendran; Wilson, Julie; Plane, John M. C.
    Nature Geoscience (2013), 6 (2), 108-111CODEN: NGAEBU; ISSN:1752-0894. (Nature Publishing Group)
    Naturally occurring bromine- and iodine-contg. compds. substantially reduce regional, and possibly even global, tropospheric ozone levels. As such, these halogen gases reduce the global warming effects of ozone in the troposphere, and its capacity to initiate the chem. removal of hydrocarbons such as methane. The majority of halogen-related surface ozone destruction is attributable to iodine chem. So far, org. iodine compds. have been assumed to serve as the main source of oceanic iodine emissions. However, known org. sources of atm. iodine cannot account for gas-phase iodine oxide concns. in the lower troposphere over the tropical oceans. Here, we quantify gaseous emissions of inorg. iodine following the reaction of iodide with ozone in a series of lab. expts. We show that the reaction of iodide with ozone leads to the formation of both mol. iodine and hypoiodous acid. Using a kinetic box model of the sea surface layer and a one-dimensional model of the marine boundary layer, we show that the reaction of ozone with iodide on the sea surface could account for around 75% of obsd. iodine oxide levels over the tropical Atlantic Ocean. According to the sea surface model, hypoiodous acid-not previously considered as an oceanic source of iodine-is emitted at a rate ten-fold higher than that of mol. iodine under ambient conditions.
    >> More from SciFinder ®
    https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3sXntFyqsw%253D%253D&md5=fccd3f2ce8410029ba975238eb11da97
  53. 53
    Sofiev, M.; Soares, J.; Prank, M.; de Leeuw, G.; Kukkonen, J. A regional-to-global model of emission and transport of sea salt particles in the atmosphere. Journal of Geophysical Research (Atmospheres) 2011, 116, 21302,  DOI: 10.1029/2010JD014713
    Google Scholar
    There is no corresponding record for this reference.
  54. 54
    Gantt, B.; Meskhidze, N.; Facchini, M. C.; Rinaldi, M.; Ceburnis, D.; O'Dowd, C. D. Wind speed dependent size-resolved parameterization for the organic mass fraction of sea spray aerosol. Atmospheric Chemistry and Physics - ATMOS CHEM PHYS 2011, 11, 8777– 8790,  DOI: 10.5194/acp-11-8777-2011
    Google Scholar
    There is no corresponding record for this reference.
  55. 55
    Olenius, T.; Roldin, P. Role of gas-molecular cluster-aerosol dynamics in atmospheric new-particle formation. Sci. Rep. 2022, 12, 10135,  DOI: 10.1038/s41598-022-14525-y
    Google Scholar
    There is no corresponding record for this reference.
  56. 56
    Ning, A.; Liu, L.; Zhang, S.; Yu, F.; Du, L.; Ge, M.; Zhang, X. The critical role of dimethylamine in the rapid formation of iodic acid particles in marine areas. npj Climate and Atmospheric Science 2022, 5, 92,  DOI: 10.1038/s41612-022-00316-9
    Google Scholar
    There is no corresponding record for this reference.
  57. 57
    Besel, V.; Kubecka, J.; Kurtén, T.; Vehkamäki, H. Impact of Quantum Chemistry Parameter Choices and Cluster Distribution Model Settings on Modeled Atmospheric Particle Formation Rates. J. Phys. Chem. A 2020, 124, 5931,  DOI: 10.1021/acs.jpca.0c03984
    Google Scholar
    57
    Impact of Quantum Chemistry Parameter Choices and Cluster Distribution Model Settings on Modeled Atmospheric Particle Formation Rates
    Besel, Vitus; Kubecka, Jakub; Kurten, Theo; Vehkamaki, Hanna
    Journal of Physical Chemistry A (2020), 124 (28), 5931-5943CODEN: JPCAFH; ISSN:1089-5639. (American Chemical Society)
    Various parameters effect on the rate of new particle formation predicted for a H2SO4-NH3 system using quantum chem. and cluster distribution dynamics simulations, here, Atm. Cluster Dynamics Code, was tested. Consistent consideration of the rotational symmetry no. of monomers (H2SO4 and NH3 mols., bisulfate ion and NH4+) led to a significant rise in predicted particle formation rate; including the rotational symmetry no. of clusters only slightly changed results, and only for conditions where charged clusters dominate particle formation rate. This was because most of clusters stable enough to participate in new particle formation have a rotational symmetry no. of 1; few exceptions to this rule are pos. charged clusters. Applying quasi-harmonic correction for low frequency vibrational modes tended to generally decrease predicted new particle formation rates and significantly altered the slope of the formation rate curve plotted against H2SO4 concn., a typical convention in atm. aerosol science. Cluster max. size effect explicitly included in simulations depended on simulation conditions. Errors arising from a limited set of clusters were higher for higher evapn. rates and tended increase with temp. Errors tended to be higher for lower vapor concns. Boundary conditions for out-growing clusters (counted as formed particles) had only a small effect on results, provided the definition was chem. reasonable and the set of simulated clusters was sufficiently large. A comparison of data from cosmics leaving outdoor droplets (CLOUD) chamber and a cluster distribution dynamics model using older quantum chem. input data showed improved agreement when using new input data and the proposed combination of symmetry/quasi-harmonic corrections.
    >> More from SciFinder ®
    https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BB3cXht1alsLvK&md5=8e749fba9da93b18694e415c1c060662
  58. 58
    Myllys, N.; Kubečka, J.; Besel, V.; Alfaouri, D.; Olenius, T.; Smith, J. N.; Passananti, M. Role of base strength, cluster structure and charge in sulfuric-acid-driven particle formation. Atmospheric Chemistry and Physics 2019, 19, 9753– 9768,  DOI: 10.5194/acp-19-9753-2019
    Google Scholar
    There is no corresponding record for this reference.
  59. 59
    Zhang, R.; Xie, H.-B.; Ma, F.; Chen, J.; Iyer, S.; Simon, M.; Heinritzi, M.; Shen, J.; Tham, Y. J.; Kurtén, T.; Worsnop, D. R.; Kirkby, J.; Curtius, J.; Sipilä, M.; Kulmala, M.; He, X.-C. Critical Role of Iodous Acid in Neutral Iodine Oxoacid Nucleation. Environ. Sci. Technol. 2022, 56, 14166– 14177,  DOI: 10.1021/acs.est.2c04328
    Google Scholar
    59
    Critical Role of Iodous Acid in Neutral Iodine Oxoacid Nucleation
    Zhang, Rongjie; Xie, Hong-Bin; Ma, Fangfang; Chen, Jingwen; Iyer, Siddharth; Simon, Mario; Heinritzi, Martin; Shen, Jiali; Tham, Yee Jun; Kurten, Theo; Worsnop, Douglas R.; Kirkby, Jasper; Curtius, Joachim; Sipila, Mikko; Kulmala, Markku; He, Xu-Cheng
    Environmental Science & Technology (2022), 56 (19), 14166-14177CODEN: ESTHAG; ISSN:1520-5851. (American Chemical Society)
    Nucleation of neutral iodine particles has recently been found to involve both iodic acid (HIO3) and iodous acid (HIO2). However, the precise role of HIO2 in iodine oxoacid nucleation remains unclear. Herein, we probe such a role by investigating the cluster formation mechanisms and kinetics of (HIO3)m(HIO2)n (m = 0-4, n = 0-4) clusters with quantum chem. calcns. and atm. cluster dynamics modeling. When compared with HIO3, we find that HIO2 binds more strongly with HIO3 and also more strongly with HIO2. After accounting for ambient vapor concns., the fastest nucleation rate is predicted for mixed HIO3-HIO2 clusters rather than for pure HIO3 or HIO2 ones. Our calcns. reveal that the strong binding results from HIO2 exhibiting a base behavior (accepting a proton from HIO3) and forming stronger halogen bonds. Moreover, the binding energies of (HIO3)m(HIO2)n clusters show a far more tolerant choice of growth paths when compared with the strict stoichiometry required for sulfuric acid-base nucleation. Our predicted cluster formation rates and dimer concns. are acceptably consistent with those measured by the Cosmic Leaving Outdoor Droplets (CLOUD) expt. This study suggests that HIO2 could facilitate the nucleation of other acids beyond HIO3 in regions where base vapors such as ammonia or amines are scarce.
    >> More from SciFinder ®
    https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BB38XisVajsLrM&md5=529b05e9e166104af0dc3f36a5a4445f
  60. 60
    Schmitz, G.; Elm, J. Assessment of the DLPNO Binding Energies of Strongly Noncovalent Bonded Atmospheric Molecular Clusters. ACS Omega 2020, 5, 7601– 7612,  DOI: 10.1021/acsomega.0c00436
    Google Scholar
    60
    Assessment of the DLPNO Binding Energies of Strongly Noncovalent Bonded Atmospheric Molecular Clusters
    Schmitz, Gunnar; Elm, Jonas
    ACS Omega (2020), 5 (13), 7601-7612CODEN: ACSODF; ISSN:2470-1343. (American Chemical Society)
    This work assessed the performance of DLPNO-CCSD(T0), DLPNO-MP2, and d. functional theory methods in calcg. binding energies of a representative test set of 45 atm. acid/acid, acid/base, and acid/water dimer clusters. Approx. method performance was compared to high level, explicitly correlated CCSD(F12*)(T)/complete basis set (CBS) ref. calcns. Of the tested d. functionals, ωB97X-D3(BJ) had the best performance with a mean deviation of 0.09 kcal/mol and a max. deviation of 0.83 kcal/mol. The RI-CC2/aug-cc-pV(T+d)Z level of theory severely over-predicted cluster binding energies with a mean deviation of -1.31 kcal/mol and a max. deviation up to -3.00 kcal/mol. Thus, RI-CC2/aug-cc-pV(T+d)Z should not be used to study atm. mol. clusters. DLPNO variants were tested with/without the inclusion of explicit correlation (F12) in the wave function, with different pair natural orbital (PNO) settings (loosePNO, normalPNO, tightPNO) and using double and triple zeta basis sets. Performance of DLPNO-MP2 methods was independent of PNO settings and yielded low mean deviations (≤-0.84 kcal/mol). However, DLPNO-MP2 required explicitly correlated wave functions to yield max. deviations <1.40 kcal/mol. To obtain high accuracy with max. deviation <∼1.0 kcal/mol, DLPNO-CCSD(T0)/aug-cc-pVTZ (normalPNO) calcns. or DLPNO-CCSD(T0)-F12/cc-pVTZ-F12 (normalPNO) calcns. were required. The most accurate level of theory was DLPNO-CCSD(T0)-F12/cc-pVTZ-F12 using a tightPNO criterion which yielded a mean deviation of 0.10 kcal/mol, with a max. deviation of 0.20 kcal/mol, vs. the CCSD(F12*)(T)/CBS ref.
    >> More from SciFinder ®
    https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BB3cXlt1yktL0%253D&md5=865ba10b3e9832494d960adb64b36715
  61. 61
    Elm, J.; Kristensen, K. Basis Set Convergence of the Binding Energies of Strongly Hydrogen-Bonded Atmospheric Clusters. Phys. Chem. Chem. Phys. 2017, 19, 1122– 1133,  DOI: 10.1039/C6CP06851K
    Google Scholar
    61
    Basis set convergence of the binding energies of strongly hydrogen-bonded atmospheric clusters
    Elm, Jonas; Kristensen, Kasper
    Physical Chemistry Chemical Physics (2017), 19 (2), 1122-1133CODEN: PPCPFQ; ISSN:1463-9076. (Royal Society of Chemistry)
    We investigate the basis set convergence of second order Moller Plesset perturbation theory for the binding energies of 11 strongly hydrogen-bonded clusters relevant to the atm. The binding energies are calcd. both as the uncorrected (UC) value, as well as by employing the counterpoise (CP) and the Same No. Of Optimized Parameters (SNOOP) correction schemes, with and without explicit correlation (F12). We find that the use of the F12 corrections is of utter importance for obtaining converged binding energies. Without F12 corrections at least a quadruple-ζ basis set is generally required to yield errors below 1 kcal mol-1 compared to the complete basis set (CBS) limit. Using coupled cluster methods we obtain a best est. of the CCSD(T) CBS limit of the binding energies of the considered clusters and compare it with approx. DLPNO-CCSD(T) and DFT methods. We identify a pragmatic approach, relying solely on a series of double-ζ basis set calcns., for obtaining results in remarkably good agreement with our CBS est.
    >> More from SciFinder ®
    https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC28XhvFKjtb%252FO&md5=c44dbe667e0a1605a94c77283fbf5b08
  62. 62
    Klamt, A. Conductor-like screening model for real solvents: a new approach to the quantitative calculation of solvation phenomena. J. Phys. Chem. 1995, 99, 2224– 2235,  DOI: 10.1021/j100007a062
    Google Scholar
    62
    Conductor-like Screening Model for Real Solvents: A New Approach to the Quantitative Calculation of Solvation Phenomena
    Klamt, Andreas
    Journal of Physical Chemistry (1995), 99 (7), 2224-35CODEN: JPCHAX; ISSN:0022-3654. (American Chemical Society)
    Starting from the question of why dielec. continuum models give a fairly good description of mols. in water and some other solvents, a totally new approach for the calcn. of solvation phenomena is presented. It is based on the perfect, i.e., conductor-like, screening of the solute mol. and a quant. calcn. of the deviations from ideality appearing in real solvents. Thus, a new point of view to solvation phenomena is presented, which provides an alternative access to many questions of scientific and tech. importance. The whole theory is based on the results of MO continuum solvation models. A few representative solvents are considered, and the use of the theory is demonstrated by the calcn. of vapor pressures, surface tensions, and octanol/water partition coeffs.
    >> More from SciFinder ®
    https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADyaK2MXjsFaisb0%253D&md5=74ff536ca20d353b9f8525d9f25c51d5
  63. 63
    Klamt, A.; Jonas, V.; Bürger, T.; Lohrenz, J. C. W. Refinement and parametrization of COSMO-RS. J. Phys. Chem. A 1998, 102, 5074– 5085,  DOI: 10.1021/jp980017s
    Google Scholar
    63
    Refinement and Parametrization of COSMO-RS
    Klamt, Andreas; Jonas, Volker; Buerger, Thorsten; Lohrenz, John C. W.
    Journal of Physical Chemistry A (1998), 102 (26), 5074-5085CODEN: JPCAFH; ISSN:1089-5639. (American Chemical Society)
    The continuum solvation model COSMO and its extension beyond the dielec. approxn. (COSMO-RS) have been carefully parametrized in order to optimally reproduce 642 data points for a variety of properties, i.e., ΔG of hydration, vapor pressure, and the partition coeffs. for octanol/water, benzene/water, hexane/water, and di-Et ether/water. Two hundred seventeen small to medium sized neutral mols., covering most of the chem. functionality of the elements H, C, N, O, and Cl, have been considered. An overall accuracy of 0.4 (rms) kcal/mol for chem. potential differences, corresponding to a factor of 2 in the equil. consts. under consideration, has been achieved. This was using only a single radius and one dispersion const. per element and a total no. of eight COSMO-RS inherent parameters. Most of these parameters were close to their theor. est. The optimized cavity radii agreed well with the widely accepted rule of 120% of van der Waals radii. The whole parametrization was based upon d. functional calcns. using DMol/COSMO. As a result of this sound parametrization, we are now able to calc. almost any chem. equil. in liq./liq. and vapor/liq. systems up to an accuracy of a factor 2 without the need of any addnl. exptl. data for solutes or solvents. This opens a wide range of applications in phys. chem. and chem. engineering.
    >> More from SciFinder ®
    https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADyaK1cXjs1Srs7Y%253D&md5=e9043dfbc9123e2a9b7e7a77216db911
  64. 64
    Eckert, F.; Klamt, A. Fast solvent screening via quantum chemistry: COSMO-RS approach. AIChE J. 2002, 48, 369– 385,  DOI: 10.1002/aic.690480220
    Google Scholar
    64
    Fast solvent screening via quantum chemistry: COSMO-RS approach
    Eckert, Frank; Klamt, Andreas
    AIChE Journal (2002), 48 (2), 369-385CODEN: AICEAC; ISSN:0001-1541. (American Institute of Chemical Engineers)
    Conductor-like Screening Model for Real Solvents (COSMO-RS), a general and fast methodol. for the a priori prediction of thermophys. data of liqs. is presented. It is based on cheap unimol. quantum chem. calcns., which, combined with exact statistical thermodn., provide the information necessary for the evaluation of mol. interactions in liqs. COSMO-RS is an alternative to structure interpolating group contribution methods. The method is independent of exptl. data and generally applicable. A methodol. comparison with group contribution methods is given. The applicability of the COSMO-RS method to the goal of solvent screening is demonstrated at various examples of vapor-liq.-, liq.-liq.-, solid-liq.-equil. and vapor-pressure predictions.
    >> More from SciFinder ®
    https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD38XhsFSksLg%253D&md5=0f1996a34219de62fa735128a95020a1
  65. 65
    BIOVIA COSMOtherm, Release 2021; Dassault Systèmes. http://www.3ds.com. 2021.
    Google Scholar
    There is no corresponding record for this reference.
  66. 66
    BIOVIA COSMOconf 2021; Dassault Systèmes. http://www.3ds.com. 2021.
    Google Scholar
    There is no corresponding record for this reference.
  67. 67
    Turbomole, V7.5.1; University of Karlsruhe and Forschungszentrum Karlsruhe GmbH, 2020.
    Google Scholar
    There is no corresponding record for this reference.
  68. 68
    Roldin, P.; Swietlicki, E.; Massling, A.; Kristensson, A.; Löndahl, J.; Eriksson, A.; Pagels, J.; Gustafsson, S. Aerosol ageing in an urban plume - implication for climate. Atmospheric Chemistry and Physics - ATMOS CHEM PHYS 2011, 11, 5897– 5915,  DOI: 10.5194/acp-11-5897-2011
    Google Scholar
    There is no corresponding record for this reference.
  69. 69
    Jacobson, M. Z. Fundamentals of Atmospheric Modeling, 2nd ed.; Cambridge University Press, 2005.
    Google Scholar
    There is no corresponding record for this reference.
  70. 70
    BIOVIA COSMOtherm, version C3.0, Release 19; Dassault Systemes, 2019.
    Google Scholar
    There is no corresponding record for this reference.
  71. 71
    Pruppacher, H.; Klett, J.; Wang, P. Microphysics of Clouds and Precipitation. Aerosol Sci. Technol. 1998, 28, 381– 382,  DOI: 10.1080/02786829808965531
    Google Scholar
    There is no corresponding record for this reference.
  72. 72
    Kurosaki, Y.; Matoba, S.; Iizuka, Y.; Fujita, K.; Shimada, R. Increased oceanic dimethyl sulfide emissions in areas of sea ice retreat inferred from a Greenland ice core. Communications Earth & Environment 2022, 3, 327,  DOI: 10.1038/s43247-022-00661-w
    Google Scholar
    There is no corresponding record for this reference.

Cited By

Click to copy section linkSection link copied!
Citation Statements
Explore this article's citation statements on scite.ai
powered by  Scite

This article is cited by 4 publications.

  1. Jiangyi Zhang, Jian Zhao, Robin Wollesen de Jonge, Nina Sarnela, Pontus Roldin, Mikael Ehn. Evaluating the Applicability of a Real-Time Highly Oxygenated Organic Molecule (HOM)-Based Indicator for Ozone Formation Sensitivity at a Boreal Forest Station. Environmental Science & Technology Letters 2024, 11 (11) , 1227-1232. https://doi.org/10.1021/acs.estlett.4c00733
  2. Kuanyun Hu, Jie Hu, Narcisse Tsona Tchinda, Christian George, Jianlong Li, Lin Du. Revealing the composition and optical properties of marine carbonaceous aerosols: A case of the eastern China marginal seas. Science of The Total Environment 2025, 958 , 178136. https://doi.org/10.1016/j.scitotenv.2024.178136
  3. Xueqi Ma, Kun Li, Shan Zhang, Narcisse Tsona Tchinda, Jianlong Li, Hartmut Herrmann, Lin Du. Molecular characteristics of sea spray aerosols during aging with the participation of marine volatile organic compounds. Science of The Total Environment 2024, 954 , 176380. https://doi.org/10.1016/j.scitotenv.2024.176380
  4. Yu Jiang, Juan Yu, Ji-Yuan Tian, Gui-Peng Yang, Long-Fei Liu, Xin-Ran Song, Rong Chen. Microplastics and copper impacts on feeding, oxidative stress, antioxidant enzyme activity, and dimethylated sulfur compounds production in Manila clam Ruditapes philippinarum. Marine Pollution Bulletin 2024, 208 , 117022. https://doi.org/10.1016/j.marpolbul.2024.117022
Download PDF
Go to Environmental Science & Technology
Get e-Alerts
Get e-Alerts

Environmental Science & Technology

Cite this: Environ. Sci. Technol. 2024, 58, 25, 10956–10968
Click to copy citationCitation copied!
https://doi.org/10.1021/acs.est.4c01891
Published June 13, 2024

Copyright © 2024 The Authors. Published by American Chemical Society. This publication is licensed under

CC-BY 4.0 .

Article Views

1881

Altmetric

-

Citations

4
Learn about these metrics

Article Views are the COUNTER-compliant sum of full text article downloads since November 2008 (both PDF and HTML) across all institutions and individuals. These metrics are regularly updated to reflect usage leading up to the last few days.

Citations are the number of other articles citing this article, calculated by Crossref and updated daily. Find more information about Crossref citation counts.

The Altmetric Attention Score is a quantitative measure of the attention that a research article has received online. Clicking on the donut icon will load a page at altmetric.com with additional details about the score and the social media presence for the given article. Find more information on the Altmetric Attention Score and how the score is calculated.

  • Abstract

    High Resolution Image
    Download MS PowerPoint Slide

    Figure 1

    Figure 1. Effect of marine versus continental air mass history on the aerosol number size distribution in a boreal forest environment. Panel (a) depicts the typical summertime source regions of DMS (purple), MTs (green), NH3 (blue), and anthropogenic SO2 (yellow), along with their position in relation to the Hyltemossa, SMEARII, and Pallas measurements stations. These colors indicate only the spatial locations of the emissions of the different species between May and August, 2018. Panels (b), (c), and (d) show the spring and summertime (March-August) mean aerosol number size distributions measured at the Hyltemossa, SMEARII, and Pallas stations during the periods 2018–2020, 2006–2020, and 2015–2018, respectively. The size distributions in panel (b), (c,) and (d) are separated based on the marine influence on their air mass history.

    High Resolution Image
    Download MS PowerPoint Slide

    Figure 2

    Figure 2. Modeled and measured long-term and diurnal gas-phase concentrations of MTs, HOM monomers, isoprene, SA, MSA, and O3 at the Station for Measuring Ecosystem-Atmosphere Relations II (SMEARII) between the 17th of May and 28th of August, 2018. Gray and black dots denote the surface and above-canopy measurements, respectively, while the colored lines represent the above-canopy model results. Marine periods 1, 2, and 3 (MP1, MP2, and MP3) denote periods of particularly high marine air-mass impact, while continental period 1 (CP1) denotes a period of particularly high continental air-mass impact. The back-trajectory heat-maps displayed above each period illustrate the regions from which the air-masses arrived during MP1, MP2, MP3, and CP1. The shaded areas denote the measured and modeled data range within the 25th and 75th percentile.

    High Resolution Image
    Download MS PowerPoint Slide

    Figure 3

    Figure 3. Measured and modeled (a–e) time-dependent and (f–o) median particle number size distributions at the Station for Measuring Ecosystem Atmosphere Relations II (SMEARII) between the 17th of May and 28th of August. Marine periods 1, 2, and 3 (MP1, MP2, and MP3) denote periods of particular high marine air-mass impact, while continental period 1 (CP1) denotes a period of particular high continental air-mass impact. The back-trajectory heat-maps displayed above each period illustrates the regions from which the air-masses arrived during MP1, MP2, MP3, and CP1. The median size distributions are separated into (f–j) periods of predominant marine air-mass impact (time spent over the ocean >50th prct., purple), and (k–o) periods of predominant continental impact (time spent over the ocean <50th prct., green). The averaging for the median size distributions is done for the whole simulation period and not just during MP1, MP2, MP3, and CP1. The model results include data from the base case run (BaseCase), the without DMS emissions simulation (woDMS), the without iodine nucleation simulation (woIodine), and the without anthropogenic emissions simulation (woAnthro). The shaded areas denote the measured and modeled data range within the 25th and 75th percentile.

    High Resolution Image
    Download MS PowerPoint Slide

    Figure 4

    Figure 4. Schematic depiction of the influence of DMS and various iodine species on the formation and growth of aerosol particles both over the ocean and over land. (1) DMS, CH3I, I2, and HOI oxidize over the ocean and land to form the strong acids SA, MSA, HIO3, and HIO2, which nucleate (3) among themselves or (2) in the presence of NH3 or DMA. These particles in turn are (4) grown by condensation of low volatile organic compounds over the boreal forest, ultimately reaching (5) the CCN size range, where they (6) affect the formation, lifetime, and precipitation of clouds. Created with BioRender.com.

    High Resolution Image
    Download MS PowerPoint Slide

  • References

    This article references 72 other publications.

    1. 1
      Lovelock, J. E.; Maggs, R. J.; Rasmussen, R. A. Atmospheric Dimethyl Sulfide and the Natural Sulfur Cycle. Nature 1972, 237, 452– 453,  DOI: 10.1038/237452a0
      1
      Atmospheric dimethyl sulfide and the natural sulfur cycle
      Lovelock, J. E.; Maggs, R. J.; Rasmussen, R. A.
      Nature (London, United Kingdom) (1972), 237 (5356), 452-3CODEN: NATUAS; ISSN:0028-0836.
      The av. concn. of dimethyl sulfide (DMS) [75-18-3] in seawater was 1.2 .tim. 10-11 g/ml and the distribution coeff. of DMS between air and seawater was 0.30, corresponding to an atm. concn. of 1.2 ppb at equil. The emission rates of DMS were 50-400 .tim. 10-12 g/g wet wt./hr from marine algae, 21-84 .tim. 10-12 g/g/hr from soils, and 2-43 .tim. 10-12 g/g dry wt./hr from the living intact leaves of oak, cotton, spruce, and pine trees. DMS may be involved in the transfer of biol. sulfur [7704-34-9] in nature.
      >> More from SciFinder ®
      https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADyaE3sXisVOmug%253D%253D&md5=c6d0495b981f24e9fef6102dd86617ee
    2. 2
      Carpenter, L.; Archer, S.; Beale, R. Ocean-atmosphere trace gas exchange. Chem. Soc. Rev. 2012, 41, 6473– 506,  DOI: 10.1039/c2cs35121h
      2
      Ocean-atmosphere trace gas exchange
      Carpenter, Lucy J.; Archer, Stephen D.; Beale, Rachael
      Chemical Society Reviews (2012), 41 (19), 6473-6506CODEN: CSRVBR; ISSN:0306-0012. (Royal Society of Chemistry)
      A review. The oceans contribute significantly to the global emissions of a no. of atmospherically important volatile gases, notably those contg. sulfur, nitrogen, and halogens. Such gases play crit. roles not only in global biogeochem. cycling but also in a wide range of atm. processes including marine aerosol formation and modification, tropospheric ozone formation and destruction, photooxidant cycling, and stratospheric ozone loss. A no. of marine emissions are greenhouse gases, others influence the Earth's radiative budget indirectly through aerosol formation and/or by modifying oxidant levels and thus changing the atm. lifetime of gases such as methane. Reviewed is current literature concerning the phys., chem., and biol. controls on the sea-air emissions of a wide range of gases including di-Me sulfide (DMS), halocarbons, nitrogen-contg. gases including NH3, amines (including dimethylamine, DMA, and diethylamine, DEA), alkyl nitrates (RONO2) and N2O, non-methane hydrocarbons (NMHC) including isoprene and oxygenated (O)VOCs, CH4 and CO. Where possible the current global emission budgets of these gases as well as known mechanisms for their formation and loss in the surface ocean are reviewed.
      >> More from SciFinder ®
      https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC38Xhtlaktr%252FP&md5=12993bba4892e6ceadc7b6dc4d8e9432
    3. 3
      Zheng, G.; Wang, Y.; Wood, R.; Jensen, M. P.; Kuang, C.; McCoy, I. L.; Matthews, A.; Mei, F.; Tomlinson, J. M.; Shilling, J. E. New particle formation in the remote marine boundary layer. Nat. Commun. 2021, 12, 527,  DOI: 10.1038/s41467-020-20773-1
      3
      New particle formation in the remote marine boundary layer
      Zheng, Guangjie; Wang, Yang; Wood, Robert; Jensen, Michael P.; Kuang, Chongai; McCoy, Isabel L.; Matthews, Alyssa; Mei, Fan; Tomlinson, Jason M.; Shilling, John E.; Zawadowicz, Maria A.; Crosbie, Ewan; Moore, Richard; Ziemba, Luke; Andreae, Meinrat O.; Wang, Jian
      Nature Communications (2021), 12 (1), 527CODEN: NCAOBW; ISSN:2041-1723. (Nature Research)
      Abstr.: Marine low clouds play an important role in the climate system, and their properties are sensitive to cloud condensation nuclei concns. While new particle formation represents a major source of cloud condensation nuclei globally, the prevailing view is that new particle formation rarely occurs in remote marine boundary layer over open oceans. Here we present evidence of the regular and frequent occurrence of new particle formation in the upper part of remote marine boundary layer following cold front passages. The new particle formation is facilitated by a combination of efficient removal of existing particles by pptn., cold air temps., vertical transport of reactive gases from the ocean surface, and high actinic fluxes in a broken cloud field. The newly formed particles subsequently grow and contribute substantially to cloud condensation nuclei in the remote marine boundary layer and thereby impact marine low clouds.
      >> More from SciFinder ®
      https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BB3MXit1alsb4%253D&md5=cb0000d7b4413432690fd0ddf779d694
    4. 4
      Barnes, I.; Hjorth, J.; Mihalopoulos, N. Dimethyl Sulfide and Dimethyl Sulfoxide and Their Oxidation in the Atmosphere. Chem. Rev. 2006, 106, 940– 975,  DOI: 10.1021/cr020529+
      4
      Dimethyl Sulfide and Dimethyl Sulfoxide and Their Oxidation in the Atmosphere
      Barnes, Ian; Hjorth, Jens; Mihalopoulos, Nikos
      Chemical Reviews (Washington, DC, United States) (2006), 106 (3), 940-975CODEN: CHREAY; ISSN:0009-2665. (American Chemical Society)
      A review concerning the gas phase chem., atm. oxidn., and chem. products of the atm. oxidn. of di-Me sulfide (DMS) and dimethylsulfoxide (DMSO) is given. Topics discussed include: DMS chem. (reaction with OH-, NO3-, halogen atoms and halogen oxides [kinetics, primary reaction mechanisms, reaction products]); DMSO chem. (reaction with OH-, NO3-, halogen atoms and halogen oxides [kinetics, primary reaction mechanisms, reaction products]); and current state of field measurements and their interpretation (multi-phase chem. involved in atm. oxidn. of DMS; field and modeling study evidence of the role of multi-phase reactions in the DMS cycle; aq.-phase reactions of DMS, DMSO, di-Me sulfone, methane sulfinic acid [MSIA], and methane sulfonic acid [MSA]; atm. implication of aq.-phase reactions of DMS, DMSO, MSIA, and MSA; and modeling study recommendations).
      >> More from SciFinder ®
      https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD28Xhs1Grtr4%253D&md5=c2a51fd2de3a72676c30eb83aeed4fb1
    5. 5
      Hoffmann, E. H.; Tilgner, A.; Schrödner, R.; Bräuer, P.; Wolke, R.; Herrmann, H. An advanced modeling study on the impacts and atmospheric implications of multiphase dimethyl sulfide chemistry. Proc. Natl. Acad. Sci. U. S. A. 2016, 113, 11776– 11781,  DOI: 10.1073/pnas.1606320113
      5
      An advanced modeling study on the impacts and atmospheric implications of multiphase dimethyl sulfide chemistry
      Hoffmann, Erik Hans; Tilgner, Andreas; Schroedner, Roland; Braeuer, Peter; Wolke, Ralf; Herrmann, Hartmut
      Proceedings of the National Academy of Sciences of the United States of America (2016), 113 (42), 11776-11781CODEN: PNASA6; ISSN:0027-8424. (National Academy of Sciences)
      Oceans dominate di-Me sulfide (DMS) emissions, the major natural S source. DMS is important for formation of non-sea salt sulfate (nss-SO42-) aerosols and secondary particulate matter over oceans; thus, it significantly affects global climate. The DMS oxidn. mechanism has been examd. in several different model studies; however, these studies had restricted oxidn. mechanisms which mainly under-represented important aq.-phase chem. processes. These neglected but highly effective processes strongly affect the direct product yields of DMS oxidn., thereby affecting the climatic influence of aerosols. To address these shortfalls, an extensive multiphase DMS chem. mechanism, the Chem. Aq. Phase Radical Mechanism DMS Module 1.0, was developed and used in detailed model assessments of multiphase DMS chem. in the marine boundary layer. Model studies confirmed the importance of aq. phase chem. for the fate of DMS and its oxidn. products. Aq. phase processes significantly reduced the SO2 yield and increased the Me sulfonic acid (MSA) yield, which is needed to close the gap between modeled and measured MSA concns. Simulations implied that multi-phase DMS oxidn. produces equal amts. of MSA and SO42-, a result with significant implications for nss-SO42- aerosol formation, cloud condensation nuclei concn., and cloud albedo over oceans. Results showed the deficiencies of parameterizations currently used in higher-scale models which only treat gas phase chem. Overall, the results showed treatment of DMS chem. in gas and aq. phases is essential to improve model prediction accuracy.
      >> More from SciFinder ®
      https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC28XhsFyrsb%252FO&md5=97c54638e0a27847d0f959788895cd49
    6. 6
      Wollesen de Jonge, R.; Elm, J.; Rosati, B.; Christiansen, S.; Hyttinen, N.; Lüdemann, D.; Bilde, M.; Roldin, P. Secondary aerosol formation from dimethyl sulfide - improved mechanistic understanding based on smog chamber experiments and modelling. Atmospheric Chemistry and Physics 2021, 21, 9955– 9976,  DOI: 10.5194/acp-21-9955-2021
      There is no corresponding record for this reference.
    7. 7
      Gomez Martin, J. C.; Lewis, T. R.; Blitz, M. A.; Plane, J. M. C.; Kumar, M.; Francisco, J. S.; Saiz-Lopez, A. A gas-to-particle conversion mechanism helps to explain atmospheric particle formation through clustering of iodine oxides. Nat. Commun. 2020, 11, 4521,  DOI: 10.1038/s41467-020-18252-8
      There is no corresponding record for this reference.
    8. 8
      Finkenzeller, H.; Iyer, S.; He, X.-C.; Simon, M.; Koenig, T. K.; Lee, C. F.; Valiev, R.; Hofbauer, V.; Amorim, A.; Baalbaki, R. The gas-phase formation mechanism of iodic acid as an atmospheric aerosol source. Nat. Chem. 2023, 15, 129– 135,  DOI: 10.1038/s41557-022-01067-z
      There is no corresponding record for this reference.
    9. 9
      Korhonen, P.; Kulmala, M.; Laaksonen, A.; Viisanen, Y.; McGraw, R.; Seinfeld, J. H. Ternary nucleation of H2SO4, NH3, and H2O in the atmosphere. Journal of Geophysical Research: Atmospheres 1999, 104, 26349– 26353,  DOI: 10.1029/1999JD900784
      9
      Ternary nucleation of H2SO4, NH3, and H2O in the atmosphere
      Korhonen, P.; Kulmala, M.; Laaksonen, A.; Viisanen, Y.; McGraw, R.; Seinfeld, J. H.
      Journal of Geophysical Research, [Atmospheres] (1999), 104 (D21), 26349-26353CODEN: JGRDE3 ISSN:. (American Geophysical Union)
      Classical theory of binary homogeneous nucleation is extended to the ternary system H2SO4-NH3-H2O. For NH3 mixing ratios exceeding about 1 ppt, the presence of NH3 enhances the binary H2SO4-H2O nucleation rate by several orders of magnitude. The Gibbs free energies of formation of the crit. H2SO4-NH3-H2O cluster, as calcd. by two independent approaches, are in substantial agreement. The finding that the H2SO4-NH3-H2O ternary nucleation rate is independent of relative humidity over a large range of H2SO4 concns. has wide atm. consequences. The limiting component for ternary H2SO4-NH3-H2O nucleation is, as in the binary H2SO4-H2O case, H2SO4; however, the H2SO4 concn. needed to achieve significant nucleation rates is several orders of magnitude below that required in the binary case.
      >> More from SciFinder ®
      https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADyaK1MXotFWqurk%253D&md5=d5ca8b589881057516ae0bb3ec62b4a9
    10. 10
      Almeida, J.; Schobesberger, S.; Kürten, A.; Ortega, I.; Kupiainen-Määttä, O.; Praplan, A.; Adamov, A.; Amorim, A.; Bianchi, F.; Breitenlechner, M. Molecular understanding of sulphuric acid-amine particle nucleation in the atmosphere. Nature 2013, 502, 359– 363,  DOI: 10.1038/nature12663
      10
      Molecular understanding of sulphuric acid-amine particle nucleation in the atmosphere
      Almeida, Joao; Schobesberger, Siegfried; Kuerten, Andreas; Ortega, Ismael K.; Kupiainen-Maeaettae, Oona; Praplan, Arnaud P.; Adamov, Alexey; Amorim, Antonio; Bianchi, Federico; Breitenlechner, Martin; David, Andre; Dommen, Josef; Donahue, Neil M.; Downard, Andrew; Dunne, Eimear; Duplissy, Jonathan; Ehrhart, Sebastian; Flagan, Richard C.; Franchin, Alessandro; Guida, Roberto; Hakala, Jani; Hansel, Armin; Heinritzi, Martin; Henschel, Henning; Jokinen, Tuija; Junninen, Heikki; Kajos, Maija; Kangasluoma, Juha; Keskinen, Helmi; Kupc, Agnieszka; Kurten, Theo; Kvashin, Alexander N.; Laaksonen, Ari; Lehtipalo, Katrianne; Leiminger, Markus; Leppae, Johannes; Loukonen, Ville; Makhmutov, Vladimir; Mathot, Serge; McGrath, Matthew J.; Nieminen, Tuomo; Olenius, Tinja; Onnela, Antti; Petaejae, Tuukka; Riccobono, Francesco; Riipinen, Ilona; Rissanen, Matti; Rondo, Linda; Ruuskanen, Taina; Santos, Filipe D.; Sarnela, Nina; Schallhart, Simon; Schnitzhofer, Ralf; Seinfeld, John H.; Simon, Mario; Sipilae, Mikko; Stozhkov, Yuri; Stratmann, Frank; Tome, Antonio; Troestl, Jasmin; Tsagkogeorgas, Georgios; Vaattovaara, Petri; Viisanen, Yrjo; Virtanen, Annele; Vrtala, Aron; Wagner, Paul E.; Weingartner, Ernest; Wex, Heike; Williamson, Christina; Wimmer, Daniela; Ye, Penglin; Yli-Juuti, Taina; Carslaw, Kenneth S.; Kulmala, Markku; Curtius, Joachim; Baltensperger, Urs; Worsnop, Douglas R.; Vehkamaeki, Hanna; Kirkby, Jasper
      Nature (London, United Kingdom) (2013), 502 (7471), 359-363CODEN: NATUAS; ISSN:0028-0836. (Nature Publishing Group)
      Aerosol particle nucleation from trace atm. vapor is thought to provide up to half the global cloud condensation nuclei. Aerosols can cause net climate cooling by scattering sunlight and leading to smaller, but more numerous cloud droplets, making clouds brighter and extending their lifetimes. Atm. aerosols from human activities are thought to have compensated for a large fraction of warming caused by greenhouse gases; however, despite its importance for climate, atm. nucleation is poorly understood. It was recently shown that H2SO4 and NH3 cannot explain particle formation rates obsd. in the lower atm. It is thought amines may enhance nucleation, but until now there has been no direct evidence for amine ternary nucleation under atm. conditions. This work used the CLOUD (cosmics leaving outdoor droplets) chamber at CERN to det. that dimethylamine >3 parts per trillion by vol. can enhance particle formation rates >1000-fold vs. NH3, sufficient to account for atm. obsd. particle formation rates. Mol. anal. of clusters showed that faster nucleation is explained by a base-stabilization mechanism involving acid-amine pairs, which strongly decrease evapn. The ion-induced contribution is generally small, reflecting the high stability of H2SO4-dimethylamine clusters and indicating that galactic cosmic rays exert only a small effect on their formation, except at low overall formation rates. Exptl. measurements were well reproduced by a dynamic model based on quantum chem. calcns. of mol. cluster binding energies without any fitted parameters. Results showed that in regions of the atm. near amine sources, amines and SO2 should be considered when assessing the effect of anthropogenic activity on particle formation.
      >> More from SciFinder ®
      https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3sXhsFOit73N&md5=06460967339b7bcd3d231102fd2d96db
    11. 11
      Kurten, A.; Li, C.; Bianchi, F.; Curtius, J.; Dias, A.; Donahue, N. M.; Duplissy, J.; Flagan, R. C.; Hakala, J.; Jokinen, T. New particle formation in the sulfuric acid-dimethylamine-water system: Reevaluation of CLOUD chamber measurements and comparison to an aerosol nucleation and growth model. Atmospheric Chemistry and Physics 2018, 18, 845– 863,  DOI: 10.5194/acp-18-845-2018
      There is no corresponding record for this reference.
    12. 12
      Rong, H.; Liu, J.; Zhang, Y.; Du, L.; Zhang, X.; Li, Z. Nucleation mechanisms of iodic acid in clean and polluted coastal regions. Chemosphere 2020, 253, 126743,  DOI: 10.1016/j.chemosphere.2020.126743
      12
      Nucleation mechanisms of iodic acid in clean and polluted coastal regions
      Rong, Hui; Liu, Jiarong; Zhang, Yujia; Du, Lin; Zhang, Xiuhui; Li, Zesheng
      Chemosphere (2020), 253 (), 126743CODEN: CMSHAF; ISSN:0045-6535. (Elsevier Ltd.)
      In coastal regions, intense bursts of particles are frequently obsd. with high concns. of iodine species, esp. iodic acid (IA). However, the nucleation mechanisms of IA, esp. in polluted environments with high concns. of sulfuric acid (SA) and ammonia (A), remain to be fully established. By quantum chem. calcns. and atm. cluster dynamics code (ACDC) simulations, the self-nucleation of IA in clean coastal regions and that influenced by SA and A in polluted coastal regions are investigated. The results indicate that IA can form stable clusters stabilized by halogen bonds and hydrogen bonds through sequential addn. of IA, and the self-nucleation of IA can instantly produce large amts. of stable clusters when the concn. of IA is high during low tide, which is consistent with the observation that intense particle bursts were linked to high concns. of IA in clean coastal regions. Besides, SA and A can stabilize IA clusters by the formation of more halogen bonds and hydrogen bonds as well as proton transfers, and the binary nucleation of IA-SA/A rather than the self-nucleation of IA appears to be the dominant pathways in polluted coastal regions, esp. in winter. These new insights are helpful to understand the mechanisms of new particle formation induced by IA in clean and polluted coastal regions.
      >> More from SciFinder ®
      https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BB3cXnsFait7s%253D&md5=661c4cafce75612ebd720a3f33d3416b
    13. 13
      He, X.-C.; Tham, Y. J.; Dada, L.; Wang, M.; Finkenzeller, H.; Stolzenburg, D.; Iyer, S.; Simon, M.; Kürten, A.; Shen, J. Role of iodine oxoacids in atmospheric aerosol nucleation. Science 2021, 371, 589– 595,  DOI: 10.1126/science.abe0298
      13
      Role of iodine oxoacids in atmospheric aerosol nucleation
      He, Xu-Cheng; Tham, Yee Jun; Dada, Lubna; Wang, Mingyi; Finkenzeller, Henning; Stolzenburg, Dominik; Iyer, Siddharth; Simon, Mario; Kurten, Andreas; Shen, Jiali; Rorup, Birte; Rissanen, Matti; Schobesberger, Siegfried; Baalbaki, Rima; Wang, Dongyu S.; Koenig, Theodore K.; Jokinen, Tuija; Sarnela, Nina; Beck, Lisa J.; Almeida, Joao; Amanatidis, Stavros; Amorim, Antonio; Ataei, Farnoush; Baccarini, Andrea; Bertozzi, Barbara; Bianchi, Federico; Brilke, Sophia; Caudillo, Lucia; Chen, Dexian; Chiu, Randall; Chu, Biwu; Dias, Antonio; Ding, Aijun; Dommen, Josef; Duplissy, Jonathan; El Haddad, Imad; Gonzalez Carracedo, Loic; Granzin, Manuel; Hansel, Armin; Heinritzi, Martin; Hofbauer, Victoria; Junninen, Heikki; Kangasluoma, Juha; Kemppainen, Deniz; Kim, Changhyuk; Kong, Weimeng; Krechmer, Jordan E.; Kvashin, Aleksander; Laitinen, Totti; Lamkaddam, Houssni; Lee, Chuan Ping; Lehtipalo, Katrianne; Leiminger, Markus; Li, Zijun; Makhmutov, Vladimir; Manninen, Hanna E.; Marie, Guillaume; Marten, Ruby; Mathot, Serge; Mauldin, Roy L.; Mentler, Bernhard; Mohler, Ottmar; Muller, Tatjana; Nie, Wei; Onnela, Antti; Petaja, Tuukka; Pfeifer, Joschka; Philippov, Maxim; Ranjithkumar, Ananth; Saiz-Lopez, Alfonso; Salma, Imre; Scholz, Wiebke; Schuchmann, Simone; Schulze, Benjamin; Steiner, Gerhard; Stozhkov, Yuri; Tauber, Christian; Tome, Antonio; Thakur, Roseline C.; Vaisanen, Olli; Vazquez-Pufleau, Miguel; Wagner, Andrea C.; Wang, Yonghong; Weber, Stefan K.; Winkler, Paul M.; Wu, Yusheng; Xiao, Mao; Yan, Chao; Ye, Qing; Ylisirnio, Arttu; Zauner-Wieczorek, Marcel; Zha, Qiaozhi; Zhou, Putian; Flagan, Richard C.; Curtius, Joachim; Baltensperger, Urs; Kulmala, Markku; Kerminen, Veli-Matti; Kurten, Theo; Donahue, Neil M.; Volkamer, Rainer; Kirkby, Jasper; Worsnop, Douglas R.; Sipila, Mikko
      Science (Washington, DC, United States) (2021), 371 (6529), 589-595CODEN: SCIEAS; ISSN:1095-9203. (American Association for the Advancement of Science)
      Iodic acid (HIO3) is known to form aerosol particles in coastal marine regions, but predicted nucleation and growth rates are lacking. Using the CERN CLOUD (Cosmics Leaving Outdoor Droplets) chamber, we find that the nucleation rates of HIO3 particles are rapid, even exceeding sulfuric acid-ammonia rates under similar conditions. We also find that ion-induced nucleation involves IO3- and the sequential addn. of HIO3 and that it proceeds at the kinetic limit below +10°C. In contrast, neutral nucleation involves the repeated sequential addn. of iodous acid (HIO2) followed by HIO3, showing that HIO2 plays a key stabilizing role. Freshly formed particles are composed almost entirely of HIO3, which drives rapid particle growth at the kinetic limit. Our measurements indicate that iodine oxoacid particle formation can compete with sulfuric acid in pristine regions of the atm.
      >> More from SciFinder ®
      https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BB3MXjsFCrtr8%253D&md5=f7b67dfba68a1d92579197f81529327b
    14. 14
      Baccarini, A.; Karlsson, L.; Dommen, J.; Duplessis, P.; Vullers, J.; Brooks, I. M.; Saiz-Lopez, A.; Salter, M.; Tjernstrom, M.; Baltensperger, U. Frequent new particle formation over the high Arctic pack ice by enhanced iodine emissions. Nat. Commun. 2020, 11, 4924,  DOI: 10.1038/s41467-020-19533-y
      14
      Frequent new particle formation over the high Arctic pack ice by enhanced iodine emissions
      Baccarini, Andrea; Karlsson, Linn; Dommen, Josef; Duplessis, Patrick; Vullers, Jutta; Brooks, Ian M.; Saiz-Lopez, Alfonso; Salter, Matthew; Tjernstrom, Michael; Baltensperger, Urs; Zieger, Paul; Schmale, Julia
      Nature Communications (2020), 11 (1), 4924CODEN: NCAOBW; ISSN:2041-1723. (Nature Research)
      In the central Arctic Ocean the formation of clouds and their properties are sensitive to the availability of cloud condensation nuclei (CCN). The vapors responsible for new particle formation (NPF), potentially leading to CCN, have remained unidentified since the first aerosol measurements in 1991. Here, we report that all the obsd. NPF events from the Arctic Ocean 2018 expedition are driven by iodic acid with little contribution from sulfuric acid. Iodic acid largely explains the growth of ultrafine particles (UFP) in most events. The iodic acid concn. increases significantly from summer towards autumn, possibly linked to the ocean freeze-up and a seasonal rise in ozone. This leads to a one order of magnitude higher UFP concn. in autumn. Measurements of cloud residuals suggest that particles smaller than 30 nm in diam. can activate as CCN. Therefore, iodine NPF has the potential to influence cloud properties over the Arctic Ocean.
      >> More from SciFinder ®
      https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BB3cXhvFyqt7jM&md5=8ce5a303b90658edab0b26febba072cb
    15. 15
      Jimenez, J. L.; Canagaratna, M. R.; Donahue, N. M.; Prevot, A. S. H.; Zhang, Q.; Kroll, J. H.; DeCarlo, P. F.; Allan, J. D.; Coe, H.; Ng, N. L. Evolution of Organic Aerosols in the Atmosphere. Science (New York, N.Y.) 2009, 326, 1525– 9,  DOI: 10.1126/science.1180353
      15
      Evolution of Organic Aerosols in the Atmosphere
      Jimenez, J. L.; Canagaratna, M. R.; Donahue, N. M.; Prevot, A. S. H.; Zhang, Q.; Kroll, J. H.; DeCarlo, P. F.; Allan, J. D.; Coe, H.; Ng, N. L.; Aiken, A. C.; Docherty, K. S.; Ulbrich, I. M.; Grieshop, A. P.; Robinson, A. L.; Duplissy, J.; Smith, J. D.; Wilson, K. R.; Lanz, V. A.; Hueglin, C.; Sun, Y. L.; Tian, J.; Laaksonen, A.; Raatikainen, T.; Rautiainen, J.; Vaattovaara, P.; Ehn, M.; Kulmala, M.; Tomlinson, J. M.; Collins, D. R.; Cubison, M. J.; Dunlea, J.; Huffman, J. A.; Onasch, T. B.; Alfarra, M. R.; Williams, P. I.; Bower, K.; Kondo, Y.; Schneider, J.; Drewnick, F.; Borrmann, S.; Weimer, S.; Demerjian, K.; Salcedo, D.; Cottrell, L.; Griffin, R.; Takami, A.; Miyoshi, T.; Hatakeyama, S.; Shimono, A.; Sun, J. Y.; Zhang, Y. M.; Dzepina, K.; Kimmel, J. R.; Sueper, D.; Jayne, J. T.; Herndon, S. C.; Trimborn, A. M.; Williams, L. R.; Wood, E. C.; Middlebrook, A. M.; Kolb, C. E.; Baltensperger, U.; Worsnop, D. R.
      Science (Washington, DC, United States) (2009), 326 (5959), 1525-1529CODEN: SCIEAS; ISSN:0036-8075. (American Association for the Advancement of Science)
      Org. aerosol (OA) particles affect climate forcing and human health, but their sources and evolution are poorly characterized. A unifying model framework describing the atm. evolution of OA which is constrained by high time resolved measurements of its compn., volatility, and oxidn. state is presented. OA and OA precursor gases evolve by becoming increasingly oxidized, less volatile, and more hygroscopic, leading to the formation of oxygenated org. aerosols (OOA), with concns. comparable to those of SO42- aerosols throughout the Northern Hemisphere. This model framework captures the dynamic aging behavior obsd. in the atm. and lab.; it serves as a basis to improve regional and global model parameterizations.
      >> More from SciFinder ®
      https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD1MXhsFensbjE&md5=dd5505995c2591c0540180493b0020ee
    16. 16
      Petaja, T.; Tabakova, K.; Manninen, A.; Ezhova, E.; O’Connor, E.; Moisseev, D.; Sinclair, V. A.; Backman, J.; Levula, J.; Luoma, K. Influence of biogenic emissions from boreal forests on aerosol-cloud interactions. Nature Geoscience 2022, 15, 42– 47,  DOI: 10.1038/s41561-021-00876-0
      There is no corresponding record for this reference.
    17. 17
      Tröstl, J.; Chuang, W.; Gordon, H.; Heinritzi, M.; Yan, C.; Molteni, U.; Ahlm, L.; Frege, C.; Bianchi, F.; Wagner, R. The role of low-volatility organic compounds in initial particle growth in the atmosphere. Nature 2016, 533, 527– 531,  DOI: 10.1038/nature18271
      17
      The role of low-volatility organic compounds in initial particle growth in the atmosphere
      Trostl, Jasmin; Chuang, Wayne K.; Gordon, Hamish; Heinritzi, Martin; Yan, Chao; Molteni, Ugo; Ahlm, Lars; Frege, Carla; Bianchi, Federico; Wagner, Robert; Simon, Mario; Lehtipalo, Katrianne; Williamson, Christina; Craven, Jill S.; Duplissy, Jonathan; Adamov, Alexey; Almeida, Joao; Bernhammer, Anne-Kathrin; Breitenlechner, Martin; Brilke, Sophia; Dias, Antonio; Ehrhart, Sebastian; Flagan, Richard C.; Franchin, Alessandro; Fuchs, Claudia; Guida, Roberto; Gysel, Martin; Hansel, Armin; Hoyle, Christopher R.; Jokinen, Tuija; Junninen, Heikki; Kangasluoma, Juha; Keskinen, Helmi; Kim, Jaeseok; Krapf, Manuel; Kurten, Andreas; Laaksonen, Ari; Lawler, Michael; Leiminger, Markus; Mathot, Serge; Mohler, Ottmar; Nieminen, Tuomo; Onnela, Antti; Petaja, Tuukka; Piel, Felix M.; Miettinen, Pasi; Rissanen, Matti P.; Rondo, Linda; Sarnela, Nina; Schobesberger, Siegfried; Sengupta, Kamalika; Sipila, Mikko; Smith, James N.; Steiner, Gerhard; Tome, Antonio; Virtanen, Annele; Wagner, Andrea C.; Weingartner, Ernest; Wimmer, Daniela; Winkler, Paul M.; Ye, Penglin; Carslaw, Kenneth S.; Curtius, Joachim; Dommen, Josef; Kirkby, Jasper; Kulmala, Markku; Riipinen, Ilona; Worsnop, Douglas R.; Donahue, Neil M.; Baltensperger, Urs
      Nature (London, United Kingdom) (2016), 533 (7604), 527-531CODEN: NATUAS; ISSN:0028-0836. (Nature Publishing Group)
      About half of present-day cloud condensation nuclei originate from atm. nucleation, frequently appearing as a burst of new particles near midday. Atm. observations show that the growth rate of new particles often accelerates when the diam. of the particles is between one and ten nanometers. In this crit. size range, new particles are most likely to be lost by coagulation with pre-existing particles, thereby failing to form new cloud condensation nuclei that are typically 50 to 100 nm across. Sulfuric acid vapor is often involved in nucleation but is too scarce to explain most subsequent growth, leaving org. vapors as the most plausible alternative, at least in the planetary boundary layer. Although recent studies predict that low-volatility org. vapors contribute during initial growth, direct evidence has been lacking. The accelerating growth may result from increased photolytic prodn. of condensable org. species in the afternoon, and the presence of a possible Kelvin (curvature) effect, which inhibits org. vapor condensation on the smallest particles (the nano-Kohler theory), has so far remained ambiguous. The authors presented expts. performed in a large chamber under atm. conditions that investigate the role of org. vapors in the initial growth of nucleated org. particles in the absence of inorg. acids and bases such as sulfuric acid or ammonia and amines, resp. Using data from the same set of expts., it has been shown that org. vapors alone can drive nucleation. They focused on the growth of nucleated particles and find that the org. vapors that drive initial growth have extremely low volatilities (satn. concn. less than 10-4.5 micrograms per cubic meter). As the particles increase in size and the Kelvin barrier falls, subsequent growth is primarily due to more abundant org. vapors of slightly higher volatility (satn. concns. of 10-4.5 to 10-0.5 micrograms per cubic meter). They present a particle growth model that quant. reproduces measurements. They implement a parameterization of the first steps of growth in a global aerosol model and find that concns. of atm. cloud concn. nuclei can change substantially in response, i.e., by up to 50 per cent in comparison with previously assumed growth rate parameterizations.
      >> More from SciFinder ®
      https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC28Xoslyrur4%253D&md5=7e09ef77e9daeb1f54cb52383f4feb68
    18. 18
      Crounse, J.; Nielsen, L.; Jørgensen, S.; Kjaergaard, H.; Wennberg, P. Autoxidation of Organic Compounds in the Atmosphere. JOURNAL OF PHYSICAL. CHEMISTRY LETTERS 2013, 4, 3513– 3520,  DOI: 10.1021/jz4019207
      There is no corresponding record for this reference.
    19. 19
      Bianchi, F.; Kurtén, T.; Riva, M.; Mohr, C.; Rissanen, M.; Roldin, P.; Berndt, T.; Crounse, J.; Wennberg, P.; Mentel, T.; Wildt, J.; Junninen, H.; Jokinen, T.; Kulmala, M.; Worsnop, D.; Thornton, J.; Donahue, N.; Kjaergaard, H.; Ehn, M. Highly Oxygenated Molecules (HOM) from Gas-Phase Autoxidation Involving Organic Peroxy Radicals: A Key Contributor to Atmospheric Aerosol. Chem. Rev. 2019, 119, 3472– 3509,  DOI: 10.1021/acs.chemrev.8b00395
      19
      Highly Oxygenated Molecules (HOM) from Gas-Phase Autoxidation Involving Organic Peroxy Radicals: A Key Contributor to Atmospheric Aerosol
      Bianchi, Federico; Kurten, Theo; Riva, Matthieu; Mohr, Claudia; Rissanen, Matti P.; Roldin, Pontus; Berndt, Torsten; Crounse, John D.; Wennberg, Paul O.; Mentel, Thomas F.; Wildt, Jurgen; Junninen, Heikki; Jokinen, Tuija; Kulmala, Markku; Worsnop, Douglas R.; Thornton, Joel A.; Donahue, Neil; Kjaergaard, Henrik G.; Ehn, Mikael
      Chemical Reviews (Washington, DC, United States) (2019), 119 (6), 3472-3509CODEN: CHREAY; ISSN:0009-2665. (American Chemical Society)
      A review which defines highly oxygenated org. mols. (HOM) formed in the atm. via auto-oxidn. involving peroxy radicals arising from volatile org. compds. describing currently available techniques for their identification/quantification, followed by a summary of the current knowledge on their formation mechanisms and physicochem. properties, is given. Major aims are to provide a common frame for the currently quite fragmented literature on HOM studies and highlighting existing gaps, and suggesting directions for future HOM research. Topics discussed include: introduction; HOM background (defining key concepts, HOM in relation to other classification schemes, historical naming conventions); HOM detection (gas and particle phases, uncertainties and anal. challenges of HOM detection); HOM formation mechanisms (auto-oxidn. involving peroxy radical as HOM source, bimol. RO2 reactions, factors affecting HOM formation); HOM properties and atm. fate (physicochem. properties, removal mechanisms); HOM atm. observations and impact (ambient HOM observation, atm. impact); and summary and perspectives.
      >> More from SciFinder ®
      https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC1MXjsFSrsb0%253D&md5=860f5dce6415fbbdee9f45b7afeff559
    20. 20
      Roldin, P.; Ehn, M.; Kurten, T.; Olenius, T.; Rissanen, M. P.; Sarnela, N.; Elm, J.; Rantala, P.; Hao, L.; Hyttinen, N. The role of highly oxygenated organic molecules in the Boreal aerosol-cloud-climate system. Nat. Commun. 2019, 10, 1– 15,  DOI: 10.1038/s41467-019-12338-8
      There is no corresponding record for this reference.
    21. 21
      Xavier, C.; de jonge, R. W.; Jokinen, T.; Beck, L.; Sipilä, M.; Olenius, T.; Roldin, P. Role of Iodine-Assisted Aerosol Particle Formation in Antarctica. Environ. Sci. Technol. 2024, 58, 7314– 7324,  DOI: 10.1021/acs.est.3c09103
      There is no corresponding record for this reference.
    22. 22
      Brean, J.; Dall’Osto, M.; Simo, R.; Shi, Z.; Beddows, D. C. S.; Harrison, R. M. Open ocean and coastal new particle formation from sulfuric acid and amines around the Antarctic Peninsula. Nature Geoscience 2021, 14, 383– 388,  DOI: 10.1038/s41561-021-00751-y
      There is no corresponding record for this reference.
    23. 23
      Jokinen, T.; Sipila, M.; Kontkanen, J.; Vakkari, V.; Tisler, P.; Duplissy, E.-M.; Junninen, H.; Kangasluoma, J.; Manninen, H. E.; Petaja, T. Ion-induced sulfuric acid-ammonia nucleation drives particle formation in coastal Antarctica. Science Advances 2018, 4, eaat9744,  DOI: 10.1126/sciadv.aat9744
      There is no corresponding record for this reference.
    24. 24
      Lee, H.; Lee, K.; Lunder, C.; Krejci, R.; Aas, W.; Jiyeon, P.; Park, K.-t.; Lee, B.; Yoon, Y.-J.; Park, K. Atmospheric new particle formation characteristics in the Arctic as measured at Mount Zeppelin, Svalbard, from 2016 to 2018. Atmospheric Chem. Phys. 2020, 20 (21), 13425– 13441
      There is no corresponding record for this reference.
    25. 25
      Kecorius, S.; Vogl, T.; Paasonen, P.; Lampilahti, J.; Rothenberg, D.; Wex, H.; Zeppenfeld, S.; van Pinxteren, M.; Hartmann, M.; Henning, S. New particle formation and its effect on cloud condensation nuclei abundance in the summer Arctic: a case study in the Fram Strait and Barents Sea. Atmospheric Chemistry and Physics 2019, 19, 14339– 14364,  DOI: 10.5194/acp-19-14339-2019
      There is no corresponding record for this reference.
    26. 26
      DallÓsto, M.; Geels, C.; Beddows, D. C. S.; Boertmann, D.; Lange, R.; Nøjgaard, J. K.; Harrison, R. M.; Simo, R.; Skov, H.; Massling, A. Regions of open water and melting sea ice drive new particle formation in North East Greenland. Sci. Rep. 2018, 8, 6109,  DOI: 10.1038/s41598-018-24426-8
      There is no corresponding record for this reference.
    27. 27
      Mäkelä, J.; Yli-Koivisto, S.; Hiltunen, V.; Seidl, W.; Swietlicki, E.; Teinilä, K.; Sillanpää, M.; Koponen, I.; Paatero, J.; Rosman, K.; Hämeri, K. Chemical composition of aerosol during particle formation events in boreal forest. Tellus B 2001, 53, 380– 393,  DOI: 10.1034/j.1600-0889.2001.530405.x
      27
      Chemical composition of aerosol during particle formation events in boreal forest
      Makela, J. M.; Yli-Koivisto, S.; Hiltunen, V.; Seidl, W.; Swietlicki, E.; Teinila, K.; Sillanpaa, M.; Koponen, I. K.; Paatero, J.; Rosman, K.; Hameri, K.
      Tellus, Series B: Chemical and Physical Meteorology (2001), 53B (4), 380-393CODEN: TSBMD7; ISSN:0280-6509. (Munksgaard International Publishers Ltd.)
      Size-segregated chem. aerosol anal. of 5 integrated samples was performed for atm. aerosols during new particle formation events in spring 1999 during the BIOFOR 3 measurement campaign at a boreal forest site in southern Finland. Aerosol samples collected by a cascade low-pressure impactor were taken selectively to distinguish particle formation event aerosols from non-event aerosols. The division into event and non-event cases was done in-situ in the field, based on the online submicron no. size distribution. Results of chem. ionic compn. of particles showed only small differences between event and non-event sample sets. Event samples had lower concns. of total SO42- and NH4+ and light dicarboxylic acids, e.g., oxalate, malonate, and succinate. In event samples, nucleation mode particle MSA (methane sulfonic acid) was present in concns. exceeding those obsd. in non-event samples; however, at larger particle sizes, sample sets contained rather similar MSA concns. The most significant difference between event and non-event sets was obsd. for dimethylammonium, the ionic component of dimethylamine ((CH3)2NH), which seemed to be present in the particle phase during particle formation periods and/or during subsequent particle growth. The abs. event sample dimethylamine concns. were >30-fold greater than non-event concns. in the accumulation mode size range. The non-event back-up filter stage for sub-30 nm particles contained more dimethylamine than event samples. This fractionation is probably a condensation artifact from impactor sampling. A simple mass balance est. was performed to evaluate the quality and consistency of results for overall mass concn.
      >> More from SciFinder ®
      https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD3MXns1Gktrs%253D&md5=ce371260e6101c15c4bbaac0a5473bb1
    28. 28
      Hemmilä, M.; Hellén, H.; Virkkula, A.; Makkonen, U.; Praplan, A.; Kontkanen, J.; Ahonen, L.; Kulmala, M.; Hakola, H. Amines in boreal forest air at SMEAR II station in Finland. Atmospheric Chemistry and Physics 2018, 18, 6367– 6380,  DOI: 10.5194/acp-18-6367-2018
      There is no corresponding record for this reference.
    29. 29
      Lawler, M.; Rissanen, M.; Ehn, M.; Mauldin, R.; Sarnela, N.; Sipilä, M.; Smith, J. Evidence for Diverse Biogeochemical Drivers of Boreal Forest New Particle Formation. Geophys. Res. Lett. 2018, 45, 2038– 2046,  DOI: 10.1002/2017GL076394
      There is no corresponding record for this reference.
    30. 30
      Sogacheva, L.; Saukkonen, L.; Nilsson, E.; Dal Maso, M.; Schultz, D.; de Leeuw, G.; Kulmala, M. New aerosol particle formation in different synoptic situations at Hyytiälä, Southern Finland. Tellus B 2022, 60, 485– 494,  DOI: 10.1111/j.1600-0889.2008.00364.x
      There is no corresponding record for this reference.
    31. 31
      Nieminen, T.; Yli-Juuti, T.; Manninen, H. E.; Petäjä, T.; Kerminen, V.-M.; Kulmala, M. Technical note: New particle formation event forecasts during PEGASOS-Zeppelin Northern mission 2013 in Hyytiälä, Finland. Atmospheric Chemistry and Physics 2015, 15, 12385– 12396,  DOI: 10.5194/acp-15-12385-2015
      There is no corresponding record for this reference.
    32. 32
      Öström, E.; Putian, Z.; Schurgers, G.; Mishurov, M.; Kivekäs, N.; Lihavainen, H.; Ehn, M.; Rissanen, M. P.; Kurtén, T.; Boy, M.; Swietlicki, E.; Roldin, P. Modeling the role of highly oxidized multifunctional organic molecules for the growth of new particles over the boreal forest region. Atmospheric Chemistry and Physics 2017, 17, 8887– 8901,  DOI: 10.5194/acp-17-8887-2017
      There is no corresponding record for this reference.
    33. 33
      Jenkin, M. E.; Saunders, S. M.; Pilling, M. J. The tropospheric degradation of volatile organic compounds: a protocol for mechanism development. Atmos. Environ. 1997, 31, 81– 104,  DOI: 10.1016/S1352-2310(96)00105-7
      33
      The tropospheric degradation of volatile organic compounds: a protocol for mechanism development
      Jenkin, Michael E.; Saunders, Sandra M.; Pilling, Michael J.
      Atmospheric Environment (1996), 31 (1), 81-104CODEN: AENVEQ; ISSN:1352-2310. (Elsevier)
      Kinetic and mechanistic data relevant to the tropospheric oxidn. of volatile org. compds. (VOCs) were used to define a series of rules for the construction of detailed degrdn. schemes for use in numerical models. These rules are intended to apply to the treatment of a wide range of non-arom. hydrocarbons and oxygenated and chlorinated VOCs, and are currently used to provide an up-to-date mechanism describing the degrdn. of a range of VOCs, and the formation of secondary oxidants, for use in a model of the boundary layer over Europe. The schemes constructed using this protocol are applicable, however, to a wide range of ambient conditions, and may be employed in models of urban, rural, or remote tropospheric environments, or for the simulation of secondary pollutant formation for a range of NOx or VOC emission scenarios. These schemes are believed to be particularly appropriate for comparative assessments of the formation of oxidants, such as ozone, from the degrdn. of org. compds. The protocol is divided into a series of subsections dealing with initiation reactions, the reactions of the radical intermediates and the further degrdn. of first and subsequent generation products. The present work draws heavily on previous reviews and evaluations of data relevant to tropospheric chem. Where necessary, however, existing recommendations are adapted, or new rules are defined, to reflect recent improvements in the database, particularly with regard to the treatment of peroxy radical (RO2) reactions for which there have been major advances, even since comparatively recent reviews. The present protocol aims to take into consideration work available in the open literature up to the end of 1994, and some further studies known by the authors, which were under review at that time. A major disadvantage of explicit chem. mechanisms is the very large no. of reactions potentially generated, if a series of rules is rigorously applied. The protocol aims to limit the no. of reactions in a degrdn. scheme by applying a degree of strategic simplication, while maintaining the essential features of the chem. These simplication measures are described, and their influence is demonstrated and discussed. The resultant mechanisms are believed to provide a suitable starting point for the generation of reduced chem. mechanisms.
      >> More from SciFinder ®
      https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADyaK28XntVOnt78%253D&md5=44dc875e8e1a9456ed2b570393d450c6
    34. 34
      Jenkin, M. E.; Saunders, S. M.; Wagner, V.; Pilling, M. J. Protocol for the development of the Master Chemical Mechanism, MCM v3 (Part B): tropospheric degradation of aromatic volatile organic compounds. Atmospheric Chemistry and Physics 2003, 3, 181– 193,  DOI: 10.5194/acp-3-181-2003
      34
      Protocol for the development of the master chemical mechanism, MCM v3 (part B): tropospheric degradation of aromatic volatile organic compounds
      Jenkin, M. E.; Saunders, S. M.; Wagner, V.; Pilling, M. J.
      Atmospheric Chemistry and Physics (2003), 3 (1), 181-193CODEN: ACPTCE; ISSN:1680-7324. (European Geophysical Society)
      Kinetic and mechanistic data relevant to the tropospheric degrdn. of arom. volatile org. compds. (VOC) were used to define a mechanism development protocol, which was used to construct degrdn. schemes for 18 arom. VOC as part of version 3 of the Master Chem. Mechanism (MCM v3). This is complementary to the treatment of 107 nonarom. VOC, presented in a companion paper. The protocol is divided into subsections describing initiation reactions, the degrdn. chem. to 1st generation products via a no. of competitive routes, and the further degrdn. of 1st and subsequent generation products. Emphasis is placed on describing where the treatment differs from that applied to the nonarom. VOC. The protocol is based on work available in the open literature up to the beginning of 2001, and some other studies known by the authors which were under review at the time. Photochem. Ozone Creation Potentials (POCP) were calcd. for the 18 arom. VOC in MCM v3 for idealized conditions appropriate to north-west Europe, using a photochem. trajectory model. The POCP values provide a measure of the relative ozone forming abilities of the VOC. These show distinct differences from POCP values calcd. previously for the aroms., using earlier versions of the MCM, and reasons for these differences are discussed.
      >> More from SciFinder ®
      https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD3sXns1Sntrw%253D&md5=cbb782c7d9ee66115b9c13f14758d095
    35. 35
      Braeuer, P.; Tilgner, A.; Wolke, R.; Herrmann, H. Mechanism development and modelling of tropospheric multiphase halogen chemistry: The CAPRAM Halogen Module 2.0 (HM2). JOURNAL OF ATMOSPHERIC CHEMISTRY 2013, 70, 19– 52,  DOI: 10.1007/s10874-013-9249-6
      There is no corresponding record for this reference.
    36. 36
      Wu, R.; Wang, S.; Wang, L. A New Mechanism for The Atmospheric Oxidation of Dimethyl Sulfide. The Importance of Intramolecular Hydrogen Shift in CH3SCH2OO Radical. journal of physical chemistry. A 2015, 119, 112,  DOI: 10.1021/jp511616j
      There is no corresponding record for this reference.
    37. 37
      Berndt, T.; Scholz, W.; Mentler, B.; Fischer, L.; Hoffmann, E.; Tilgner, A.; Hyttinen, N.; Prisle, N. L.; Hansel, A.; Herrmann, H. Fast Peroxy Radical Isomerization and OH Recycling in the Reaction of OH Radicals with Dimethyl Sulfide. J. Phys. Chem. Lett. 2019, 10, 6478,  DOI: 10.1021/acs.jpclett.9b02567
      37
      Fast Peroxy Radical Isomerization and OH Recycling in the Reaction of OH Radicals with Dimethyl Sulfide
      Berndt, T.; Scholz, W.; Mentler, B.; Fischer, L.; Hoffmann, E. H.; Tilgner, A.; Hyttinen, N.; Prisle, N. L.; Hansel, A.; Herrmann, H.
      Journal of Physical Chemistry Letters (2019), 10 (21), 6478-6483CODEN: JPCLCD; ISSN:1948-7185. (American Chemical Society)
      Di-Me sulfide (DMS), produced by marine organisms, represents the most abundant, biogenic sulfur emission into the Earth's atm. The gas-phase degrdn. of DMS is mainly initiated by the reaction with the OH radical forming first CH3SCH2O2 radicals from the dominant H-abstraction channel. It is exptl. shown that these peroxy radicals undergo a two-step isomerization process finally forming a product consistent with the formula HOOCH2SCHO. The isomerization process is accompanied by OH recycling. The rate-limiting first isomerization step, CH3SCH2O2 → CH2SCH2OOH, followed by O2 addn., proceeds with k = (0.23 ± 0.12) s-1 at 295 ± 2 K. Competing bimol. CH3SCH2O2 reactions with NO, HO2, or RO2 radicals are less important for trace-gas conditions over the oceans. Results of atm. chem. simulations demonstrate the predominance (≥95%) of CH3SCH2O2 isomerization. The rapid peroxy radical isomerization, not yet considered in models, substantially changes the understanding of DMS's degrdn. processes in the atm.
      >> More from SciFinder ®
      https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC1MXhvFWltrjP&md5=0d91ffa9cadc1365ffbfb0a48fe0373b
    38. 38
      Veres, P. R.; Neuman, J. A.; Bertram, T. H.; Assaf, E.; Wolfe, G. M.; Williamson, C. J.; Weinzierl, B.; Tilmes, S.; Thompson, C. R.; Thames, A. B.; Schroder, J. C.; Saiz-Lopez, A.; Rollins, A. W.; Roberts, J. M.; Price, D.; Peischl, J.; Nault, B. A.; Møller, K. H.; Miller, D. O.; Meinardi, S.; Li, Q.; Lamarque, J.-F.; Kupc, A.; Kjaergaard, H. G.; Kinnison, D.; Jimenez, J. L.; Jernigan, C. M.; Hornbrook, R. S.; Hills, A.; Dollner, M.; Day, D. A.; Cuevas, C. A.; Campuzano-Jost, P.; Burkholder, J.; Bui, T. P.; Brune, W. H.; Brown, S. S.; Brock, C. A.; Bourgeois, I.; Blake, D. R.; Apel, E. C.; Ryerson, T. B. Global airborne sampling reveals a previously unobserved dimethyl sulfide oxidation mechanism in the marine atmosphere. Proc. Natl. Acad. Sci. U. S. A. 2020, 117, 4505– 4510,  DOI: 10.1073/pnas.1919344117
      38
      Global airborne sampling reveals a previously unobserved dimethyl sulfide oxidation mechanism in the marine atmosphere
      Veres, Patrick R.; Neuman, J. Andrew; Bertram, Timothy H.; Assaf, Emmanuel; Wolfe, Glenn M.; Williamson, Christina J.; Weinzierl, Bernadett; Tilmes, Simone; Thompson, Chelsea R.; Thames, Alexander B.; Schroder, Jason C.; Saiz-Lopez, Alfonso; Rollins, Andrew W.; Roberts, James M.; Price, Derek; Peischl, Jeff; Nault, Benjamin A.; Moeller, Kristian H.; Miller, David O.; Meinardi, Simone; Li, Qinyi; Lamarque, Jean-Francois; Kupc, Agnieszka; Kjaergaard, Henrik G.; Kinnison, Douglas; Jimenez, Jose L.; Jernigan, Christopher M.; Hornbrook, Rebecca S.; Hills, Alan; Dollner, Maximilian; Day, Douglas A.; Cuevas, Carlos A.; Campuzano-Jost, Pedro; Burkholder, James; Bui, T. Paul; Brune, William H.; Brown, Steven S.; Brock, Charles A.; Bourgeois, Ilann; Blake, Donald R.; Apel, Eric C.; Ryerson, Thomas B.
      Proceedings of the National Academy of Sciences of the United States of America (2020), 117 (9), 4505-4510CODEN: PNASA6; ISSN:0027-8424. (National Academy of Sciences)
      Di-Me sulfide (DMS), emitted from the oceans, is the most abundant biol. source of sulfur to the marine atm. Atm. DMS is oxidized to condensable products that form secondary aerosols that affect Earth's radiative balance by scattering solar radiation and serving as cloud condensation nuclei. We report the atm. discovery of a previously unquantified DMS oxidn. product, hydroperoxymethyl thioformate (HPMTF, HOOCH2SCHO), identified through global-scale airborne observations that demonstrate it to be a major reservoir of marine sulfur. Observationally constrained model results show that more than 30% of oceanic DMS emitted to the atm. forms HPMTF. Coincident particle measurements suggest a strong link between HPMTF concn. and new particle formation and growth. Analyses of these observations show that HPMTF chem. must be included in atm. models to improve representation of key linkages between the biogeochem. of the ocean, marine aerosol formation and growth, and their combined effects on climate.
      >> More from SciFinder ®
      https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BB3cXksVSqsr0%253D&md5=0d957baa667a2543cd9a4f3c467790a5
    39. 39
      Hari, P.; Kulmala, M. Station for Measuring Ecosystem-Atmosphere Relations (SMEAR II). Boreal Environment Research 2005, 10, 315– 322
      39
      Station for Measuring Ecosystem-Atmosphere Relations (SMEAR II)
      Hari, Pertti; Kulmala, Markku
      Boreal Environment Research (2005), 10 (5), 315-322CODEN: BEREF7; ISSN:1239-6095. (Finnish Environment Institute)
      Here we present the ongoing SMEAR (Station for Measuring Forest Ecosystem-Atm. Relations) research program and also related future views. The main idea of SMEAR-type infrastructures is continuous, comprehensive measurements of fluxes, storages and concns. in the land ecosystem-atm. continuum. The major coupling mechanisms between atm. and land surface are the fluxes of energy, momentum, water, carbon dioxide, atm. trace gases and atm. aerosols. Understanding of couplings and feedbacks is the basis for the prediction of changes in the system formed by atm., vegetation and soil. A better quantification of the agents that cause climate change, as well as the emissions and removals of species, will provide more accurate projections of future atm. compn. and hence climate.
      >> More from SciFinder ®
      https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD2MXht1GhurvP&md5=fbd8465f76a998b3a0958c12089db374
    40. 40
      Neefjes, I.; Laapas, M.; Liu, Y.; Médus, E.; Miettunen, E.; Ahonen, L.; Quéléver, L.; Aalto, J.; Bäck, J.; Kerminen, V.-M.; Lamplahti, J.; Luoma, K.; Maki, M.; Mammarella, I.; Petäjä, T.; Räty, M.; Sarnela, N.; Ylivinkka, I.; Hakala, S.; Lintunen, A. 25 years of atmospheric and ecosystem measurements in a boreal forestSeasonal variation and responses to warm and dry years. Boreal Environment Research 2022, 27, 1– 31
      There is no corresponding record for this reference.
    41. 41
      Stein, A. F.; Draxler, R. R.; Rolph, G. D.; Stunder, B. J. B.; Cohen, M. D.; Ngan, F. NOAAs HYSPLIT Atmospheric Transport and Dispersion Modeling System. Bulletin of the American Meteorological Society 2015, 96, 2059– 2077,  DOI: 10.1175/BAMS-D-14-00110.1
      There is no corresponding record for this reference.
    42. 42
      Rolph, G.; Stein, A.; Stunder, B. Real-time Environmental Applications and Display sYstem: READY. Environmental Modelling & Software 2017, 95, 210– 228,  DOI: 10.1016/j.envsoft.2017.06.025
      There is no corresponding record for this reference.
    43. 43
      Lennartz, S. T.; Marandino, C. A.; von Hobe, M.; Cortes, P.; Quack, B.; Simo, R.; Booge, D.; Pozzer, A.; Steinhoff, T.; Arevalo-Martinez, D. L. Direct oceanic emissions unlikely to account for the missing source of atmospheric carbonyl sulfide. Atmospheric Chemistry and Physics 2017, 17, 385– 402,  DOI: 10.5194/acp-17-385-2017
      There is no corresponding record for this reference.
    44. 44
      Ziska, F.; Quack, B.; Abrahamsson, K.; Archer, S. D.; Atlas, E.; Bell, T.; Butler, J. H.; Carpenter, L. J.; Jones, C. E.; Harris, N. R. P. Global sea-to-air flux climatology for bromoform, dibromomethane and methyl iodide. Atmospheric Chemistry and Physics Discussions 2013, 13, 8915– 8934,  DOI: 10.5194/acp-13-8915-2013
      44
      Global sea-to-air flux climatology for bromoform, dibromomethane and methyl iodide
      Ziska, F.; Quack, B.; Abrahamsson, K.; Archer, S. D.; Atlas, E.; Bell, T.; Butler, J. H.; Carpenter, L. J.; Jones, C. E.; Harris, N. R. P.; Hepach, H.; Heumann, K. G.; Hughes, C.; Kuss, J.; Krueger, K.; Liss, P.; Moore, R. M.; Orlikowska, A.; Raimund, S.; Reeves, C. E.; Reifenhaeuser, W.; Robinson, A. D.; Schall, C.; Tanhua, T.; Tegtmeier, S.; Turner, S.; Wang, L.; Wallace, D.; Williams, J.; Yamamoto, H.; Yvon-Lewis, S.; Yokouchi, Y.
      Atmospheric Chemistry and Physics (2013), 13 (17), 8915-8934, 20 pp.CODEN: ACPTCE; ISSN:1680-7324. (Copernicus Publications)
      Volatile halogenated org. compds. contg. bromine and iodine, which are naturally produced in the ocean, are involved in ozone depletion in both the troposphere and stratosphere. Three prominent compds. transporting large amts. of marine halogens into the atm. are bromoform (CHBr3), dibromomethane (CH2Br2) and Me iodide (CH3I). The input of marine halogens to the stratosphere has been estd. from observations and modeling studies using low-resoln. oceanic emission scenarios derived from top-down approaches. In order to improve emission inventory ests., we calc. data-based high resoln. global sea-to-air flux ests. of these compds. from surface observations within the HalOcAt (Halocarbons in the Ocean and Atm.) database. Global maps of marine and atm. surface concns. are derived from the data which are divided into coastal, shelf and open ocean regions. Considering phys. and biogeochem. characteristics of ocean and atm., the open ocean water and atm. data are classified into 21 regions. The available data are interpolated onto a 1° × 1° grid while missing grid values are interpolated with latitudinal and longitudinal dependent regression techniques reflecting the compds.' distributions. With the generated surface concn. climatologies for the ocean and atm., global sea-to-air concn. gradients and sea-to-air fluxes are calcd. Based on these calcns. we est. a total global flux of 1.5/2.5 Gmol Br yr-1 for CHBr3, 0.78/0.98 Gmol Br yr-1 for CH2Br2 and 1.24/1.45 Gmol Br yr-1 for CH3I (robust fit/ordinary least squares regression techniques). Contrary to recent studies, neg. fluxes occur in each sea-to-air flux climatol., mainly in the Arctic and Antarctic regions. "Hot spots" for global polybromomethane emissions are located in the equatorial region, whereas Me iodide emissions are enhanced in the subtropical gyre regions. Inter-annual and seasonal variation is contained within our flux calcns. for all three compds. Compared to earlier studies, our global fluxes are at the lower end of ests., esp. for bromoform. An under-representation of coastal emissions and of extreme events in our est. might explain the mismatch between our bottom-up emission est. and top-down approaches.
      >> More from SciFinder ®
      https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3sXhslehtrbL&md5=d13f982b82d94c732ab4dc017908098c
    45. 45
      Nightingale, P. D.; Malin, G.; Law, C. S.; Watson, A. J.; Liss, P. S.; Liddicoat, M. I.; Boutin, J.; Upstill-Goddard, R. C. In situ evaluation of air-sea gas exchange parameterizations using novel conservative and volatile tracers. Global Biogeochemical Cycles 2000, 14, 373– 387,  DOI: 10.1029/1999GB900091
      45
      In situ evaluation of air-sea gas exchange parameterizations using novel conservative and volatile tracers
      Nightingale, Philip D.; Malin, Gill; Law, Cliff S.; Watson, Andrew J.; Liss, Peter S.; Liddicoat, Malcolm I.; Boutin, Jacqueline; Upstill-Goddard, Robert C.
      Global Biogeochemical Cycles (2000), 14 (1), 373-387CODEN: GBCYEP; ISSN:0886-6236. (American Geophysical Union)
      Measurements of air-sea gas exchange rates are reported from 2 deliberate tracer expts. in the southern North Sea during Feb. 1992 and 1993. A conservative tracer, spores of Bacillus globigii var. Niger, was used for the 1st time in an in situ air-sea gas exchange expt. This nonvolatile tracer is used to correct for dispersive diln. of the volatile tracers and allows 3 estns. of the transfer velocity for the same time period. The 1st estn. of the power dependence of gas transfer on mol. diffusivity in the marine environment is reported. This allows the impact of bubbles on ests. of the transfer velocity derived from changes in the He/SF6 ratio to be assessed. Data from earlier dual tracer expts. are reinterpreted, and findings suggest that results from all dual tracer expts. are mutually consistent. The complete data set is used to test published parameterizations of gas transfer with wind speed. A gas exchange relation that shows a dependence on wind speed intermediate between those of Liss and Merlivat (1986) and Wanninkhof (1992) is optimal. The dual tracer data are shown to be reasonably consistent with global ests. of gas exchange based on the uptake of natural and bomb-derived radiocarbon. The degree of scatter in the data when plotted against wind speed suggests that parameters not scaling with wind speed are also influencing gas exchange rates.
      >> More from SciFinder ®
      https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD3cXhvVGms7s%253D&md5=d317f0ad2e899416471475672bd335f3
    46. 46
      Lana, A.; Bell, T. G.; Simó, R.; Vallina, S. M.; Ballabrera-Poy, J.; Kettle, A. J.; Dachs, J.; Bopp, L.; Saltzman, E. S.; Stefels, J. An updated climatology of surface dimethlysulfide concentrations and emission fluxes in the global ocean. Global Biogeochemical Cycles 2011, 25, 886,  DOI: 10.1029/2010GB003850
      There is no corresponding record for this reference.
    47. 47
      Granier, C. S.; Darras, H.; Denier van der Gon, J.; Doubalova, N.; Elguindi, B.; Galle, M.; Gauss, M.; Guevara, J.; Jalkanen, J.; Kuenen, C.; Liousse, B.; Quack, D.; Simpson, K. The Copernicus Atmosphere Monitoring Service global and regional emissions. Sindelarova The Copernicus Atmosphere Monitoring Service global and regional emissions (April 2019 version) 2019, 16,  DOI: 10.24380/d0bn-kx16
      There is no corresponding record for this reference.
    48. 48
      Sindelarova, K.; Granier, C.; Bouarar, I.; Guenther, A.; Tilmes, S.; Stavrakou, T.; Muller, J.-F.; Kuhn, U.; Stefani, P.; Knorr, W. Global dataset of biogenic VOC emissions calculated by the MEGAN model over the last 30 years. Atmospheric Chemistry and Physics 2014, 14, 9317,  DOI: 10.5194/acp-14-9317-2014
      48
      Global data set of biogenic VOC emissions calculated by the MEGAN model over the last 30 years
      Sindelarova, K.; Granier, C.; Bouarar, I.; Guenther, A.; Tilmes, S.; Stavrakou, T.; Muller, J.-F.; Kuhn, U.; Stefani, P.; Knorr, W.
      Atmospheric Chemistry and Physics (2014), 14 (17), 9317-9341, 25 pp.CODEN: ACPTCE; ISSN:1680-7324. (Copernicus Publications)
      The Model of Emissions of Gases and Aerosols from Nature (MEGANv2.1) together with the Modern-Era Retrospective Anal. for Research and Applications (MERRA) meteorol. fields were used to create a global emission data set of biogenic volatile org. compds. (BVOC) available on a monthly basis for the time period of 1980-2010. This data set, developed under the Monitoring Atm. Compn. and Climate project (MACC), is called MEGAN-MACC. The model estd. mean annual total BVOC emission of 760 Tg (C) yr-1 consisting of isoprene (70%), monoterpenes (11%), methanol (6%), acetone (3%), sesquiterpenes (2.5%) and other BVOC species each contributing less than 2%. Several sensitivity model runs were performed to study the impact of different model input and model settings on isoprene ests. and resulted in differences of up to ±17% of the ref. isoprene total. A greater impact was obsd. for a sensitivity run applying parameterization of soil moisture deficit that led to a 50% redn. of isoprene emissions on a global scale, most significantly in specific regions of Africa, South America and Australia. MEGAN-MACC ests. are comparable to results of previous studies. More detailed comparison with other isoprene inventories indicated significant spatial and temporal differences between the data sets esp. for Australia, Southeast Asia and South America. MEGAN-MACC ests. of isoprene, α-pinene and group of monoterpenes showed a reasonable agreement with surface flux measurements at sites located in tropical forests in the Amazon and Malaysia. The model was able to capture the seasonal variation of isoprene emissions in the Amazon forest.
      >> More from SciFinder ®
      https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC2cXhs1yktbjO&md5=978d8465b40240c42347d621604c1516
    49. 49
      Smith, B.; Wårlind, D.; Arneth, A.; Hickler, T.; Leadley, P.; Siltberg, J.; Zaehle, S. Implications of incorporating N cycling and N limitations on primary production in an individual-based dynamic vegetation model. Biogeosciences 2014, 11, 2027– 2054,  DOI: 10.5194/bg-11-2027-2014
      There is no corresponding record for this reference.
    50. 50
      Arneth, A.; Niinemets, U.; Pressley, S.; Bäck, J.; Hari, P.; Karl, T.; Noe, S.; Prentice, I. C.; Serça, D.; Hickler, T.; Wolf, A.; Smith, B. Process-based estimates of terrestrial ecosystem isoprene emissions: incorporating the effects of a direct CO2-isoprene interaction. Atmospheric Chemistry and Physics 2007, 7, 31– 53,  DOI: 10.5194/acp-7-31-2007
      There is no corresponding record for this reference.
    51. 51
      Paulot, F.; Jacob, D. J.; Johnson, M. T.; Bell, T. G.; Baker, A. R.; Keene, W. C.; Lima, I. D.; Doney, S. C.; Stock, C. A. Global oceanic emission of ammonia: Constraints from seawater and atmospheric observations. Global Biogeochemical Cycles 2015, 29, 1165– 1178,  DOI: 10.1002/2015GB005106
      There is no corresponding record for this reference.
    52. 52
      Carpenter, L.; MacDonald, S.; Shaw, M.; Kumar, R.; Saunders, R.; Parthipan, R.; Wilson, J.; Plane, J. Atmospheric iodine levels influenced by sea surface emissions of inorganic iodine. Nature Geoscience 2013, 6, 108– 111,  DOI: 10.1038/ngeo1687
      52
      Atmospheric iodine levels influenced by sea surface emissions of inorganic iodine
      Carpenter, Lucy J.; MacDonald, Samantha M.; Shaw, Marvin D.; Kumar, Ravi; Saunders, Russell W.; Parthipan, Rajendran; Wilson, Julie; Plane, John M. C.
      Nature Geoscience (2013), 6 (2), 108-111CODEN: NGAEBU; ISSN:1752-0894. (Nature Publishing Group)
      Naturally occurring bromine- and iodine-contg. compds. substantially reduce regional, and possibly even global, tropospheric ozone levels. As such, these halogen gases reduce the global warming effects of ozone in the troposphere, and its capacity to initiate the chem. removal of hydrocarbons such as methane. The majority of halogen-related surface ozone destruction is attributable to iodine chem. So far, org. iodine compds. have been assumed to serve as the main source of oceanic iodine emissions. However, known org. sources of atm. iodine cannot account for gas-phase iodine oxide concns. in the lower troposphere over the tropical oceans. Here, we quantify gaseous emissions of inorg. iodine following the reaction of iodide with ozone in a series of lab. expts. We show that the reaction of iodide with ozone leads to the formation of both mol. iodine and hypoiodous acid. Using a kinetic box model of the sea surface layer and a one-dimensional model of the marine boundary layer, we show that the reaction of ozone with iodide on the sea surface could account for around 75% of obsd. iodine oxide levels over the tropical Atlantic Ocean. According to the sea surface model, hypoiodous acid-not previously considered as an oceanic source of iodine-is emitted at a rate ten-fold higher than that of mol. iodine under ambient conditions.
      >> More from SciFinder ®
      https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC3sXntFyqsw%253D%253D&md5=fccd3f2ce8410029ba975238eb11da97
    53. 53
      Sofiev, M.; Soares, J.; Prank, M.; de Leeuw, G.; Kukkonen, J. A regional-to-global model of emission and transport of sea salt particles in the atmosphere. Journal of Geophysical Research (Atmospheres) 2011, 116, 21302,  DOI: 10.1029/2010JD014713
      There is no corresponding record for this reference.
    54. 54
      Gantt, B.; Meskhidze, N.; Facchini, M. C.; Rinaldi, M.; Ceburnis, D.; O'Dowd, C. D. Wind speed dependent size-resolved parameterization for the organic mass fraction of sea spray aerosol. Atmospheric Chemistry and Physics - ATMOS CHEM PHYS 2011, 11, 8777– 8790,  DOI: 10.5194/acp-11-8777-2011
      There is no corresponding record for this reference.
    55. 55
      Olenius, T.; Roldin, P. Role of gas-molecular cluster-aerosol dynamics in atmospheric new-particle formation. Sci. Rep. 2022, 12, 10135,  DOI: 10.1038/s41598-022-14525-y
      There is no corresponding record for this reference.
    56. 56
      Ning, A.; Liu, L.; Zhang, S.; Yu, F.; Du, L.; Ge, M.; Zhang, X. The critical role of dimethylamine in the rapid formation of iodic acid particles in marine areas. npj Climate and Atmospheric Science 2022, 5, 92,  DOI: 10.1038/s41612-022-00316-9
      There is no corresponding record for this reference.
    57. 57
      Besel, V.; Kubecka, J.; Kurtén, T.; Vehkamäki, H. Impact of Quantum Chemistry Parameter Choices and Cluster Distribution Model Settings on Modeled Atmospheric Particle Formation Rates. J. Phys. Chem. A 2020, 124, 5931,  DOI: 10.1021/acs.jpca.0c03984
      57
      Impact of Quantum Chemistry Parameter Choices and Cluster Distribution Model Settings on Modeled Atmospheric Particle Formation Rates
      Besel, Vitus; Kubecka, Jakub; Kurten, Theo; Vehkamaki, Hanna
      Journal of Physical Chemistry A (2020), 124 (28), 5931-5943CODEN: JPCAFH; ISSN:1089-5639. (American Chemical Society)
      Various parameters effect on the rate of new particle formation predicted for a H2SO4-NH3 system using quantum chem. and cluster distribution dynamics simulations, here, Atm. Cluster Dynamics Code, was tested. Consistent consideration of the rotational symmetry no. of monomers (H2SO4 and NH3 mols., bisulfate ion and NH4+) led to a significant rise in predicted particle formation rate; including the rotational symmetry no. of clusters only slightly changed results, and only for conditions where charged clusters dominate particle formation rate. This was because most of clusters stable enough to participate in new particle formation have a rotational symmetry no. of 1; few exceptions to this rule are pos. charged clusters. Applying quasi-harmonic correction for low frequency vibrational modes tended to generally decrease predicted new particle formation rates and significantly altered the slope of the formation rate curve plotted against H2SO4 concn., a typical convention in atm. aerosol science. Cluster max. size effect explicitly included in simulations depended on simulation conditions. Errors arising from a limited set of clusters were higher for higher evapn. rates and tended increase with temp. Errors tended to be higher for lower vapor concns. Boundary conditions for out-growing clusters (counted as formed particles) had only a small effect on results, provided the definition was chem. reasonable and the set of simulated clusters was sufficiently large. A comparison of data from cosmics leaving outdoor droplets (CLOUD) chamber and a cluster distribution dynamics model using older quantum chem. input data showed improved agreement when using new input data and the proposed combination of symmetry/quasi-harmonic corrections.
      >> More from SciFinder ®
      https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BB3cXht1alsLvK&md5=8e749fba9da93b18694e415c1c060662
    58. 58
      Myllys, N.; Kubečka, J.; Besel, V.; Alfaouri, D.; Olenius, T.; Smith, J. N.; Passananti, M. Role of base strength, cluster structure and charge in sulfuric-acid-driven particle formation. Atmospheric Chemistry and Physics 2019, 19, 9753– 9768,  DOI: 10.5194/acp-19-9753-2019
      There is no corresponding record for this reference.
    59. 59
      Zhang, R.; Xie, H.-B.; Ma, F.; Chen, J.; Iyer, S.; Simon, M.; Heinritzi, M.; Shen, J.; Tham, Y. J.; Kurtén, T.; Worsnop, D. R.; Kirkby, J.; Curtius, J.; Sipilä, M.; Kulmala, M.; He, X.-C. Critical Role of Iodous Acid in Neutral Iodine Oxoacid Nucleation. Environ. Sci. Technol. 2022, 56, 14166– 14177,  DOI: 10.1021/acs.est.2c04328
      59
      Critical Role of Iodous Acid in Neutral Iodine Oxoacid Nucleation
      Zhang, Rongjie; Xie, Hong-Bin; Ma, Fangfang; Chen, Jingwen; Iyer, Siddharth; Simon, Mario; Heinritzi, Martin; Shen, Jiali; Tham, Yee Jun; Kurten, Theo; Worsnop, Douglas R.; Kirkby, Jasper; Curtius, Joachim; Sipila, Mikko; Kulmala, Markku; He, Xu-Cheng
      Environmental Science & Technology (2022), 56 (19), 14166-14177CODEN: ESTHAG; ISSN:1520-5851. (American Chemical Society)
      Nucleation of neutral iodine particles has recently been found to involve both iodic acid (HIO3) and iodous acid (HIO2). However, the precise role of HIO2 in iodine oxoacid nucleation remains unclear. Herein, we probe such a role by investigating the cluster formation mechanisms and kinetics of (HIO3)m(HIO2)n (m = 0-4, n = 0-4) clusters with quantum chem. calcns. and atm. cluster dynamics modeling. When compared with HIO3, we find that HIO2 binds more strongly with HIO3 and also more strongly with HIO2. After accounting for ambient vapor concns., the fastest nucleation rate is predicted for mixed HIO3-HIO2 clusters rather than for pure HIO3 or HIO2 ones. Our calcns. reveal that the strong binding results from HIO2 exhibiting a base behavior (accepting a proton from HIO3) and forming stronger halogen bonds. Moreover, the binding energies of (HIO3)m(HIO2)n clusters show a far more tolerant choice of growth paths when compared with the strict stoichiometry required for sulfuric acid-base nucleation. Our predicted cluster formation rates and dimer concns. are acceptably consistent with those measured by the Cosmic Leaving Outdoor Droplets (CLOUD) expt. This study suggests that HIO2 could facilitate the nucleation of other acids beyond HIO3 in regions where base vapors such as ammonia or amines are scarce.
      >> More from SciFinder ®
      https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BB38XisVajsLrM&md5=529b05e9e166104af0dc3f36a5a4445f
    60. 60
      Schmitz, G.; Elm, J. Assessment of the DLPNO Binding Energies of Strongly Noncovalent Bonded Atmospheric Molecular Clusters. ACS Omega 2020, 5, 7601– 7612,  DOI: 10.1021/acsomega.0c00436
      60
      Assessment of the DLPNO Binding Energies of Strongly Noncovalent Bonded Atmospheric Molecular Clusters
      Schmitz, Gunnar; Elm, Jonas
      ACS Omega (2020), 5 (13), 7601-7612CODEN: ACSODF; ISSN:2470-1343. (American Chemical Society)
      This work assessed the performance of DLPNO-CCSD(T0), DLPNO-MP2, and d. functional theory methods in calcg. binding energies of a representative test set of 45 atm. acid/acid, acid/base, and acid/water dimer clusters. Approx. method performance was compared to high level, explicitly correlated CCSD(F12*)(T)/complete basis set (CBS) ref. calcns. Of the tested d. functionals, ωB97X-D3(BJ) had the best performance with a mean deviation of 0.09 kcal/mol and a max. deviation of 0.83 kcal/mol. The RI-CC2/aug-cc-pV(T+d)Z level of theory severely over-predicted cluster binding energies with a mean deviation of -1.31 kcal/mol and a max. deviation up to -3.00 kcal/mol. Thus, RI-CC2/aug-cc-pV(T+d)Z should not be used to study atm. mol. clusters. DLPNO variants were tested with/without the inclusion of explicit correlation (F12) in the wave function, with different pair natural orbital (PNO) settings (loosePNO, normalPNO, tightPNO) and using double and triple zeta basis sets. Performance of DLPNO-MP2 methods was independent of PNO settings and yielded low mean deviations (≤-0.84 kcal/mol). However, DLPNO-MP2 required explicitly correlated wave functions to yield max. deviations <1.40 kcal/mol. To obtain high accuracy with max. deviation <∼1.0 kcal/mol, DLPNO-CCSD(T0)/aug-cc-pVTZ (normalPNO) calcns. or DLPNO-CCSD(T0)-F12/cc-pVTZ-F12 (normalPNO) calcns. were required. The most accurate level of theory was DLPNO-CCSD(T0)-F12/cc-pVTZ-F12 using a tightPNO criterion which yielded a mean deviation of 0.10 kcal/mol, with a max. deviation of 0.20 kcal/mol, vs. the CCSD(F12*)(T)/CBS ref.
      >> More from SciFinder ®
      https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BB3cXlt1yktL0%253D&md5=865ba10b3e9832494d960adb64b36715
    61. 61
      Elm, J.; Kristensen, K. Basis Set Convergence of the Binding Energies of Strongly Hydrogen-Bonded Atmospheric Clusters. Phys. Chem. Chem. Phys. 2017, 19, 1122– 1133,  DOI: 10.1039/C6CP06851K
      61
      Basis set convergence of the binding energies of strongly hydrogen-bonded atmospheric clusters
      Elm, Jonas; Kristensen, Kasper
      Physical Chemistry Chemical Physics (2017), 19 (2), 1122-1133CODEN: PPCPFQ; ISSN:1463-9076. (Royal Society of Chemistry)
      We investigate the basis set convergence of second order Moller Plesset perturbation theory for the binding energies of 11 strongly hydrogen-bonded clusters relevant to the atm. The binding energies are calcd. both as the uncorrected (UC) value, as well as by employing the counterpoise (CP) and the Same No. Of Optimized Parameters (SNOOP) correction schemes, with and without explicit correlation (F12). We find that the use of the F12 corrections is of utter importance for obtaining converged binding energies. Without F12 corrections at least a quadruple-ζ basis set is generally required to yield errors below 1 kcal mol-1 compared to the complete basis set (CBS) limit. Using coupled cluster methods we obtain a best est. of the CCSD(T) CBS limit of the binding energies of the considered clusters and compare it with approx. DLPNO-CCSD(T) and DFT methods. We identify a pragmatic approach, relying solely on a series of double-ζ basis set calcns., for obtaining results in remarkably good agreement with our CBS est.
      >> More from SciFinder ®
      https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC28XhvFKjtb%252FO&md5=c44dbe667e0a1605a94c77283fbf5b08
    62. 62
      Klamt, A. Conductor-like screening model for real solvents: a new approach to the quantitative calculation of solvation phenomena. J. Phys. Chem. 1995, 99, 2224– 2235,  DOI: 10.1021/j100007a062
      62
      Conductor-like Screening Model for Real Solvents: A New Approach to the Quantitative Calculation of Solvation Phenomena
      Klamt, Andreas
      Journal of Physical Chemistry (1995), 99 (7), 2224-35CODEN: JPCHAX; ISSN:0022-3654. (American Chemical Society)
      Starting from the question of why dielec. continuum models give a fairly good description of mols. in water and some other solvents, a totally new approach for the calcn. of solvation phenomena is presented. It is based on the perfect, i.e., conductor-like, screening of the solute mol. and a quant. calcn. of the deviations from ideality appearing in real solvents. Thus, a new point of view to solvation phenomena is presented, which provides an alternative access to many questions of scientific and tech. importance. The whole theory is based on the results of MO continuum solvation models. A few representative solvents are considered, and the use of the theory is demonstrated by the calcn. of vapor pressures, surface tensions, and octanol/water partition coeffs.
      >> More from SciFinder ®
      https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADyaK2MXjsFaisb0%253D&md5=74ff536ca20d353b9f8525d9f25c51d5
    63. 63
      Klamt, A.; Jonas, V.; Bürger, T.; Lohrenz, J. C. W. Refinement and parametrization of COSMO-RS. J. Phys. Chem. A 1998, 102, 5074– 5085,  DOI: 10.1021/jp980017s
      63
      Refinement and Parametrization of COSMO-RS
      Klamt, Andreas; Jonas, Volker; Buerger, Thorsten; Lohrenz, John C. W.
      Journal of Physical Chemistry A (1998), 102 (26), 5074-5085CODEN: JPCAFH; ISSN:1089-5639. (American Chemical Society)
      The continuum solvation model COSMO and its extension beyond the dielec. approxn. (COSMO-RS) have been carefully parametrized in order to optimally reproduce 642 data points for a variety of properties, i.e., ΔG of hydration, vapor pressure, and the partition coeffs. for octanol/water, benzene/water, hexane/water, and di-Et ether/water. Two hundred seventeen small to medium sized neutral mols., covering most of the chem. functionality of the elements H, C, N, O, and Cl, have been considered. An overall accuracy of 0.4 (rms) kcal/mol for chem. potential differences, corresponding to a factor of 2 in the equil. consts. under consideration, has been achieved. This was using only a single radius and one dispersion const. per element and a total no. of eight COSMO-RS inherent parameters. Most of these parameters were close to their theor. est. The optimized cavity radii agreed well with the widely accepted rule of 120% of van der Waals radii. The whole parametrization was based upon d. functional calcns. using DMol/COSMO. As a result of this sound parametrization, we are now able to calc. almost any chem. equil. in liq./liq. and vapor/liq. systems up to an accuracy of a factor 2 without the need of any addnl. exptl. data for solutes or solvents. This opens a wide range of applications in phys. chem. and chem. engineering.
      >> More from SciFinder ®
      https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADyaK1cXjs1Srs7Y%253D&md5=e9043dfbc9123e2a9b7e7a77216db911
    64. 64
      Eckert, F.; Klamt, A. Fast solvent screening via quantum chemistry: COSMO-RS approach. AIChE J. 2002, 48, 369– 385,  DOI: 10.1002/aic.690480220
      64
      Fast solvent screening via quantum chemistry: COSMO-RS approach
      Eckert, Frank; Klamt, Andreas
      AIChE Journal (2002), 48 (2), 369-385CODEN: AICEAC; ISSN:0001-1541. (American Institute of Chemical Engineers)
      Conductor-like Screening Model for Real Solvents (COSMO-RS), a general and fast methodol. for the a priori prediction of thermophys. data of liqs. is presented. It is based on cheap unimol. quantum chem. calcns., which, combined with exact statistical thermodn., provide the information necessary for the evaluation of mol. interactions in liqs. COSMO-RS is an alternative to structure interpolating group contribution methods. The method is independent of exptl. data and generally applicable. A methodol. comparison with group contribution methods is given. The applicability of the COSMO-RS method to the goal of solvent screening is demonstrated at various examples of vapor-liq.-, liq.-liq.-, solid-liq.-equil. and vapor-pressure predictions.
      >> More from SciFinder ®
      https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD38XhsFSksLg%253D&md5=0f1996a34219de62fa735128a95020a1
    65. 65
      BIOVIA COSMOtherm, Release 2021; Dassault Systèmes. http://www.3ds.com. 2021.
      There is no corresponding record for this reference.
    66. 66
      BIOVIA COSMOconf 2021; Dassault Systèmes. http://www.3ds.com. 2021.
      There is no corresponding record for this reference.
    67. 67
      Turbomole, V7.5.1; University of Karlsruhe and Forschungszentrum Karlsruhe GmbH, 2020.
      There is no corresponding record for this reference.
    68. 68
      Roldin, P.; Swietlicki, E.; Massling, A.; Kristensson, A.; Löndahl, J.; Eriksson, A.; Pagels, J.; Gustafsson, S. Aerosol ageing in an urban plume - implication for climate. Atmospheric Chemistry and Physics - ATMOS CHEM PHYS 2011, 11, 5897– 5915,  DOI: 10.5194/acp-11-5897-2011
      There is no corresponding record for this reference.
    69. 69
      Jacobson, M. Z. Fundamentals of Atmospheric Modeling, 2nd ed.; Cambridge University Press, 2005.
      There is no corresponding record for this reference.
    70. 70
      BIOVIA COSMOtherm, version C3.0, Release 19; Dassault Systemes, 2019.
      There is no corresponding record for this reference.
    71. 71
      Pruppacher, H.; Klett, J.; Wang, P. Microphysics of Clouds and Precipitation. Aerosol Sci. Technol. 1998, 28, 381– 382,  DOI: 10.1080/02786829808965531
      There is no corresponding record for this reference.
    72. 72
      Kurosaki, Y.; Matoba, S.; Iizuka, Y.; Fujita, K.; Shimada, R. Increased oceanic dimethyl sulfide emissions in areas of sea ice retreat inferred from a Greenland ice core. Communications Earth & Environment 2022, 3, 327,  DOI: 10.1038/s43247-022-00661-w
      There is no corresponding record for this reference.

  • Supporting Information

    Supporting Information

    The Supporting Information is available free of charge at https://pubs.acs.org/doi/10.1021/acs.est.4c01891.

    • Figure S1 contains modeled and measured gas-phase concentrations of SO2, HIO3, and NOx, along with modeled gas-phase concentrations of OH, NH3, and DMA; Figure S2 illustrates the back trajectory heat maps for the full simulation period along with MP1, MP2, MP3, and CP1; Figure S3 demonstrates the method behind the air-mass origin analysis; Figure S4 contains the modeled size resolved chemical composition of SO4, NO3, Cl, NH4, Na, MSA, HIO3, DMA, SOA, and POA between 1 nm and 1 μm; Figure S5 illustrates the modeled and measured median particle number size distribution, including results from the woDMS, woIodine, and woAnthro sensitivity runs; Figure S6 contains modeled and measured particle numbers size distributions from Pallas, while Figure S7 contains similar results from Hyltemossa; Figure S8 illustrates the DMS, SO2, and OH gas-phase concentration along with the SA-NH3 nucleation rate along one of the HYSPLIT trajectories moving from the Norwegian Sea toward the SMEARII stationl Table S1 comprises COSMOtherm-derived Henry’s law solubilities, while Table S2 contains COSMOtherm-derived pKa values (PDF)


    Terms & Conditions

    Most electronic Supporting Information files are available without a subscription to ACS Web Editions. Such files may be downloaded by article for research use (if there is a public use license linked to the relevant article, that license may permit other uses). Permission may be obtained from ACS for other uses through requests via the RightsLink permission system: http://pubs.acs.org/page/copyright/permissions.html.