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Time-Correlated Single Photon Counting. However, it was also shown that top-down approaches, i. Thus, accounting for interfacial photochemistry might aid in closing, or at least minimizing, this discrepancy between bottom-up and top-down approaches in global and regional models. In the same way, we infer total emissions of organic vapors from abiotic interfacial photochemistry in the range of Comparison of current global isoprene emission estimates and the results of our study 0.

The bottom-up estimates are based on direct biological emissions only, whereas top-down refers to expected total isoprene emissions from global model calculations. We note that the approach presented here can solely give an estimate on average monthly VOC fluxes from interfacial photochemistry. Thus, more sophisticated models with higher time and space resolution will be necessary, to predict photochemical VOC fluxes on a daily or even hourly basis.

Remarkably, for almost all studies even the maximum predicted values do not exceed the range of observed isoprene emission fluxes. This general underprediction of isoprene emission fluxes compared to field studies is consistent with the assumption that interfacial photochemistry represents an additional VOC source besides direct biological emissions, significantly contributing to total marine VOC fluxes. In particular, photochemical production and emission of larger unsaturated VOCs, such as isoprene, seems important, since few other abiotic formation pathways are known for such compounds in the marine environment.

In contrast, the contribution to fluxes of smaller VOCs, such as acetone, or acetaldehyde, is probably less significant, since a large variety of strong sources exists in both the atmosphere and the ocean. As an example, Yang et al. However, our calculations merely predict emission fluxes in the range of 0. To approximate background aerosol concentrations, primary OA emissions are estimated based on biological activity and surface wind speeds 17 , 18 , 31 Supplementary Fig. As depicted in Fig.

SPR - Photochemistry

As an example, we obtain similar trends for OA mass concentrations as reported from long term observations on Amsterdam Island As already seen for the calculation of VOC fluxes, we typically observe a certain underprediction of total OA mass concentrations. This is, however, supporting again the hypothesis that SOA from photochemically produced VOCs is adding up on biologically derived SOA mass, which we omit in our calculations. In total, we estimate the additional annual SOA mass due to interfacial photochemistry to be in the range of 0.

Nonetheless, our estimations probably represent a lower limit, since we do not account for additional oxidation pathways of the formed VOCs, e. In addition, we assume instantaneous mixing of the emitted VOCs into the entire volume of the MBL, probably leading to a rather diluted scenario compared to ambient conditions.

Here, only OH oxidation of unsaturated volatile organic compounds was taken into account, assuming similar secondary organic aerosol yields as given by Tsimpidi et al. Despite remaining uncertainties, our study demonstrates that abiotic VOC production from interfacial photochemistry might serve as a major contributor to marine VOC levels and OA mass loadings.

Isoprene emissions from photochemistry are expected to be in the same range as direct biological emissions and might even dominate depending on location and season. Moreover, SOA formation from oxidation of photochemically produced VOCs might explain field observations of new particle formation events which are occurring decoupled from biological activity. Therefore, we suggest that VOC and SOA production from interfacial photochemistry should be taken into account to accurately model and predict atmospheric chemistry and related processes, such as ozone cycling and cloud formation.

All data processing was conducted using Matlab version 8. A general overview on all data sources and calculations is given in Supplementary Fig. For all calculations on photochemical VOC production presented here, we used the following three major assumptions. We note that this simplification might eventually lead to an underestimation of VOC production, since it neglects increases in surface area, e. In contrast to other common parameterization, this cubic k — U 10 relationship is predicting non-zero emissions at zero wind speed, which is in agreement with laboratory studies on interfacial photochemistry and VOC production 10 , 11 , As shown in Supplementary Fig.

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However, we note that there remains significant uncertainty of at least a factor of two in transfer velocities, as it is commonly the case for all trace gas emissions from the ocean into the atmosphere up to now 35 , Second, photochemical VOC production correlates linearly with solar radiation, whereas a logarithmic decay with decreasing surfactant concentrations is observed 10 , This assumption is corroborated by measurements of Rossignol et al.

Moreover, Ciuraru et al. In addition, these assumptions are also consistent with the hypothesis that especially photosensitized reactions are driving VOC production from interfacial photochemistry Nonetheless, we note that these laboratory studies use single compounds as surfactants, whereas the ambient SML is a highly complex and dynamically changing composition of organic and inorganic compounds. Thus, we cannot exclude deviations for specific SML samples from these simplified assumptions. Furthermore, laboratory observations commonly used this wavelength range to infer photochemical production and fluxes of VOC 10 , 11 , 12 , 13 , As depicted in Supplementary Fig.

First, oligo-, meso- and eutrophic regions of the ocean were identified from global maps of net primary production NPP , based on the Vertically Generalized Production Model After averaging the data for each month and lowering the resolution from 0. These values were reported earlier as maximum surface wind speed for SML formation 2 , 24 , Then, the monthly data were refined from 2. All regions exceeding the selected wind speed limit were considered as free of SMLs and, thus, considered as photochemically not active. Furthermore, we assumed photochemical VOC production to exhibit a logarithmic decay with decreasing surfactant concentrations 10 , F surfactant was therefore expressed as shown in Eq.

The effect of this correction factor on photochemical VOC production is illustrated in Supplementary Fig. For mesotrophic conditions, i. We stress that up to now this correction is solely based on laboratory studies for single compounds, whereas the ambient SML is a complex mixture of organic and inorganic compounds. Therefore, we suggest focusing in future studies on more complex mixtures of surfactants, ambient SML samples, and also the relationship between surface pressure and VOC production. Values for VOC lab can readily be obtained from photochemical experiments under controlled conditions, using common VOC measurement techniques such as proton transfer reaction mass spectrometry PTR-MS.

In this study we used such data from previous work of George and co-workers 10 , 11 , For example, to estimate global emissions of isoprene from interfacial photochemistry, we used previously reported values for VOC lab from marine SML and biofilm samples 10 , 11 , 14 , which are in the range of 3. We attempted to approximate the reaction rate constant k OH for the mixture of unsaturated VOCs by averaging known k OH constants of similar compounds In addition, we estimated primary organic aerosol POA mass fluxes and concentrations above the ocean, in order to model accurately the partitioning of VOC oxidation products.

POA was, however, solely regarded as background aerosol, which was not taking part in partitioning, i. Here we applied established POA emission schemes, which infer POA fluxes from sea surface temperature, chlorophyll-a concentration, and surface wind speed 18 , As a simplified example, Supplementary Fig.

In this case, the following parameters were used: a POA mass concentration of 0. Both VOC formation from interfacial photochemistry and oxidation of the gas-phase products start at time 0. The resulting mixing ratio of, yet unreacted, unsaturated VOCs is depicted in the left panel of the figure, reaching a steady state of ca. This equilibrium mixing ratio might seem quite low, however, we note that here we assume instantaneous mixing of the emitted VOCs into the entire volume of the MBL.

Nonetheless, even for this dilute scenario we observe significant SOA formation from VOC oxidation products, as depicted in the right panel of Supplementary Fig. This delayed increase in particle mass is due to the enhanced partitioning of oxidation products to the gas phase until a critical gas-phase concentration is reached. After this initial period, low volatile oxidation products start to partition into the particle phase, resulting in an increase in OA particle mass concentration.

This increase is then accelerating with ongoing formation of VOC oxidation products. In this simplified example, eventually a total increase of 0. Again, this value represents solely a lower limit of enhanced SOA formation, since we excluded ozone chemistry, which would generate additional low volatility oxidation products, probably enhancing OA particle mass concentrations. Further data sets generated during this study are available from the corresponding author upon reasonable request.

The authors became aware of a mistake in the data displayed in the original version of the paper. Specifically, for the calculation of the total emission estimates i. Eventually, this additional sum resulted in a doubling of emission estimates.

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As a result of this, the following changes have been made to the originally published version of this Article:. While the new estimates are lower than previously reported this error does not affect the original discussion or conclusions of the Article. The authors apologize for the confusion caused by this mistake. George, C. Heterogeneous photochemistry in the atmosphere. Wurl, O.

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