Methyl ethyl ketone (MEK) enters the atmosphere following direct emission
from vegetation and anthropogenic activities, as well as being produced by
the gas-phase oxidation of volatile organic compounds (VOCs) such as
Methyl ethyl ketone (C
There are several known but poorly characterised sources of MEK to the atmosphere. Terrestrial vegetation (Bracho-Nunez et al., 2013; Brilli et al., 2014; Davison et al., 2008; De Gouw et al., 1999; Isidorov et al., 1985; Jardine et al., 2010; Kirstine et al., 1998; König et al., 1995; McKinney et al., 2011; Ruuskanen et al., 2011; Song and Ryu, 2013; Steeghs et al., 2004; Wilkins, 1996; Yáñez-Serrano et al., 2015), fungi (Wheatley et al., 1997) and bacteria (Song and Ryu, 2013; Wilkins, 1996) are known to emit MEK. It is also emitted directly by several anthropogenic sources, including anthropogenic biomass burning (Andreae and Merlet, 2001), solvent evaporation (Kim et al., 2015; Legreid et al., 2007) and vehicle exhaust (Bon et al., 2011; Brito et al., 2015; Liu et al., 2015; Verschueren, 1983). In addition, MEK can be formed via the atmospheric oxidation of other compounds (de Gouw et al., 2003; Jenkin et al., 1997; Neier and Strehlke, 2002; Sommariva et al., 2011).
Looking in more detail at biogenic sources, MEK emissions have been observed
from different types of vegetation, including forest canopies (Brilli et al.,
2014; Jordan et al., 2009b; Yáñez-Serrano et al., 2015), pasture
(Davison et al., 2008; De Gouw et al., 1999; Kirstine et al., 1998) and
clover (De Gouw et al., 1999; Kirstine et al., 1998). The MEK production and
release mechanisms are manifold but poorly understood. Studies show higher
MEK emissions after cutting and drying of leaves than under no-stress
conditions (Davison et al., 2008; De Gouw et al., 1999). Due to the water
solubility of MEK in leaves and on surfaces (Sander, 2015), Jardine et
al. (2010) suggested MEK emissions to be dependent on evaporation from
storage pools in leaves. It has been suggested that MEK takes part in
tri-trophic signalling following herbivore attack (Jardine et al., 2010; Song
and Ryu, 2013). The roots of plants have also been found to release MEK in
root–aphid interactions (Steeghs et al., 2004). Decaying plant tissue may
also act as a source of MEK to the atmosphere (Warneke et al., 1999).
Furthermore, some studies indicate the importance of MEK emissions by
microbes, such as
MEK not only enters the atmosphere via direct emissions but also results
from the atmospheric photooxidation of VOCs such as
In the atmosphere MEK reacts mainly with OH (
Anthropogenic biomass burning leads to significant MEK emissions of about
2 Tg a
Measurement sites, site environment, sampling dates, methods used and sampling heights.
Here we report recent findings on MEK from six different sites, including biogenic- and anthropogenic-dominated environments, in order to understand MEK sources in different environments. Our large dataset allows a closer view of this important, almost ubiquitous species in Earth's atmosphere.
The field sites compared in our study cover areas from pristine to remote anthropogenically influenced tropical forests, as well as boreal and Mediterranean regions. Measurements were performed using proton-transfer-reaction mass spectrometry (PTR-MS) and partly complemented by gas chromatography–flame ionisation detection (GC-FID) and gas chromatography–mass spectrometry (GC-MS) analytical techniques (Fig. 1, Table 1).
Online MEK measurements were performed with quadrupole PTR-MSs (Ionicon
Analytic GmbH, Austria; Lindinger et al., 1998) at all sites except for
CYPHEX, where a proton transfer reaction time-of-flight mass spectrometer (PTR-ToF-MS, Ionicon Analytic GmbH,
Austria; Jordan et al., 2009a) was used. The PTR-MSs were operated at
standard conditions (2.2 mbar drift pressure, 600 V drift voltage, 142 Td
for ATTO and SMEAR Estonia; 2.0 mbar drift pressure, 550 V drift voltage,
129 Td, for TT34; 2.2 mbar drift pressure, 600 V drift voltage, 135 Td for
O
Periodic background measurements and weekly humid calibrations were
performed at all sites. Gravimetrically prepared multicomponent standards
were obtained from Apel & Riemer, USA, for ATTO, TT34, T2 and CYPHEX and from Ionicon Analytik GmbH, Austria, for O
The Amazon Tall Tower Observatory (ATTO) site is located in central Amazonia,
150 km NE of Manaus, Brazil (Fig. 1), within a pristine primary tropical
rainforest. The site is equipped with a tall tower (325 m) and two 80 m
towers. One of them (02
Measurements for this study took place 18 February–15 March 2014. They were
carried out at seven different heights (0.05, 0.5, 4, 24, 53 and 79 m) with
the PTR-MS switching sequentially between each height in 2 min intervals.
The inlet lines were made of PTFE (9.5 mm OD), insulated and heated to
50
Additionally, ambient samples for offline measurements with GC-FID were
taken on 11 March 2014 from 08:30 to 11:00 LT. They were collected at 24 m
using a GSA SG-10-2 personal sampler pump and adsorber tubes (130 mg of Carbograph
1 (90 m
The ZF2 site is located in the Reserva Biologica do Cuieiras in central
Amazonia, 60 km NNW of Manaus (2
Measurements for this study were made from 1 September 2013 to 20 July 2014
at 41 m, at a fast rate (0.5 Hz) for virtual disjunct eddy covariance
(vDEC) flux derivations techniques (Karl et al., 2002; Langford et al., 2009;
Rinne et al., 2002). The high-resolution data were further averaged to give
30 min concentration and flux data. Wind vector data were obtained with a
sonic anemometer (Gill R3, USA) mounted at the top of the tower close to the
PTR-MS inlet. The PTR-MS inlet line was made of PFA (12.7 mm OD)
(PFA-T8-062-100, Swagelok) and was insulated and heated to 40
World map showing the location of the different sites. The names are
colour-coded to show whether they have primarily biogenic influence (green)
or a primarily anthropogenic influence (red). Source: outline world map,
The Station for Measuring Ecosystem-Atmosphere Relations (SMEAR Estonia) site
is located in the Järvselja Experimental Forestry station in Tartumaa, SE
Estonia (58
The measurements were made between 3 and 17 October 2012. Sampling was done
using a dynamic, automated glass enclosure with measurement cycles of 36 s.
The inlet line (9.5 mm OD) was made of glass and was insulated and heated
to 70
Furthermore, at SMEAR Estonia, offline measurements with a GC-MS were
carried out for periods of 3 days each in June and July 2012, with
samples taken every 4 h at two heights (2 and 20 m). Samples for GC-MS
analysis were also taken from cuvettes enclosing some common plant species at
the site (Table 1). In addition, VOC emissions from soil litter were
monitored monthly. The air samples were drawn into multi-bed stainless steel
cartridges (10.5 cm length, 3 mm inner diameter, Supelco, Bellefonte, PA,
USA) filled with Carbotrap C 20/40 mesh (0.2 g), Carbopack C 40/60 mesh
(0.1 g) and Carbotrap X 20–40 mesh (0.1 g) adsorbents (Supelco). Even
though the site usually experiences low ozone mixing ratios of 10–30 ppb
(Noe et al., 2012), a catalytic Cu(II) ozone scrubbing system (Sun et al.,
2012) was applied. Three constant-flow air sample pumps (1003-SKC, SKC Inc.,
Huston, TX, USA) and one multisample constant-flow air sample pump
(224-PCXR8, SKC Inc., Huston, TX, USA) allowed four samples to be collected
at the same time. Each sample took 30 min with a flow of 200 mL min
The oak observatory (O
Hourly average diel cycles of MEK at the ATTO (left),
SMEAR Estonia (middle) and O
The measurements took place during 29 May–12 June 2014 as part of the CANOPÉE project (Biosphere-atmosphere exchange of organic compounds: impact of intra-canopy processes). Ambient measurements were carried out at 2 m (inside the canopy) on consecutive days in intervals of 5 min. The 9.5 mm OD Teflon inlet lines were insulated and heated above ambient temperature and had no particle filter. The LOD and uncertainty of the PTR-MS were 0.11 ppb and 20 %, respectively. In addition, light non-methane hydrocarbons (from ethane to hexane) were measured with a GC-FID (Chromatotec, Saint-Antoine, France) in line with the PTR-MS as described in Zannoni et al. (2016).
The T2 site is part of a set of experimental sites within the GoAmazon
project to study the effect of the pollution plume from the city of Manaus on
the otherwise pristine Amazonian atmosphere. The T2 site is located 8 km
downwind, i.e. to the west, of Manaus (3
The measurements for this study took place between 15 February and
15 November 2014. They were carried out at 12 m above the laboratory
container with 30 min cycles. The inlet line was made of insulated Teflon
(9.5 mm OD) without a PTFE particle filter. The LOD and uncertainty of the
PTR-MS were 0.02 ppb and
The Cyprus Photochemistry Experiment (CYPHEX) campaign took place at a site
located in the NW inshore part of Cyprus, in the Paphos region
(34
The measurements took place during July and August 2014 without a single rain
event. Instruments were installed inside containers and connected to a stack
inlet that reached up 5 m above the container roofs. Air was drawn through
the 8 m stack inlet of 0.5 m with high flow rate (10 L min
All the pristine or remote sites studied were characterised by relatively low
mixing ratios of nitrogen oxides (NO
The vertical observations at ATTO revealed a strong diel variability in the magnitude and vertical distribution of MEK mixing ratios throughout the forest canopy and in the atmosphere above. Figure 3 shows an example of an hourly vertical profile of MEK for 1 day (7 March 2014) from 13:00 to 15:00 LT, from the ground to the atmosphere, suggesting that the canopy top is the major source of MEK at the site on such days. Similar concentration gradients were found for 83 % (for the afternoon hours) and 45 % (for the morning hours) of all days of measurements. In addition, MEK mixing ratios decreased significantly beneath the canopy towards the forest floor, possibly due to dry deposition or generally smaller vegetation emissions due to less light and temperature. However, a possible production from the ozonolysis of alkanes or bidirectional plant exchange cannot be ruled out. For a seasonal comparison, Yáñez-Serrano et al. (2015) reported 0.43 ppb of MEK for the dry season (September 2013) and 0.13 ppb of MEK for the wet season (February–March 2013) at 38 m. Curiously, at 24 m, MEK mixing ratios for the wet season were 0.38 ppb, very close to the measured values for this study. Possible differences in canopy structure temperature and solar radiation among years may be the cause for this discrepancy.
Hourly average vertical profiles of MEK mixing ratios at ATTO for 7 March 2014 for 13:00 LT (dashed lines), 14:00 LT (dotted and dashed lines) and 15:00 LT (thick lines). Error bars of vertical profiles are the standard deviations.
At the TT34 rainforest site, ecosystem-scale fluxes were directly calculated
from the PTR-MS measurements using the method of virtual disjunct eddy
covariance (vDEC) (Karl et al., 2001; Fig. 4). The fluxes averaged over the
entire 11-month measurement period (covering parts of both the dry and the
wet season) clearly demonstrate an emission of MEK by the rainforest during
daytime with the highest emissions around noon, and no emissions during
nighttime. In terms of seasonal variation, MEK mixing ratios were observed to
be higher during the dry season (September–October 2013,
Online ambient mixing ratios of MEK, as measured by the PTR-MS in the
hemiboreal forest at the SMEAR Estonia site during autumn 2012, were on
average 0.15
The rural Mediterranean temperate forest site at O
Hourly average MEK fluxes at the TT34 tower for the period September 2013–July 2014. The light-green circles represent means and associated error bars are 1 standard deviation. The central line of the box plots (dark green) indicates the median, the bottom and top lines are the 25th and 75th percentile, respectively, and whiskers are the 5th and 95th percentiles. Red dashed lines indicate the propagated limit of detection calculated according to the method outlined by Langford et al. (2015).
Emission rates of MEK for typical hemiboreal plant species and soil litter measured by GC-MS technique at the SMEAR site.
During the CANOPÉE campaign at the O
The measurements obtained by PTR-MS at the presented sites dominated by
biogenic emissions were occasionally confirmed by GC-FID and GC-MS, which are
compound-selective. At ATTO the same range of MEK mixing ratios for the same
hour of the day and height for the GC-FID and the PTR-MS measurements was
found, indicating that the PTR-MS signal was only or at least dominated by
MEK. To identify sources, canopy measurements at SMEAR Estonia were
complemented by emission measurements using cuvettes with GC-MS
identification. Common hemiboreal forest species, such as
Hourly average diel cycles of MEK at the T2 (left) and CYPHEX (right) sites, for the period of measurements (wet season 2014 for T2 at 14 m, July and August 2014 for CYPHEX at 12 m). For T2 a separation between polluted (dotted black line) and clean (thick blue line) air masses was done. Hourly mean diel cycles of temperature and PAR are also shown in red and grey, respectively. Error bars represent the standard deviations.
Anthropogenically influenced sites are characterised by air masses that have
passed over polluted cities or industrialised regions. This air typically
has elevated mixing ratios of NO
The T2 dataset was sorted for polluted periods (air masses loaded with CO,
black carbon, high aerosol loading, aromatic compounds) and non-polluted
periods. Periods with CO higher than 130 ppb during the tropical wet season
and higher than 160 ppb during the dry season were considered polluted. As
shown in Fig. 5, MEK mixing ratios strongly increase with pollution. The T2
site in Brazil is located on the bank of the Rio Negro and is affected by
both the tropical rainforest (biogenic) and the megacity of Manaus
(anthropogenic). The location of the T2 site downwind of Manaus and upwind of
the rainforest minimises the biogenic influence. MEK mixing ratios were
generally lower for the clean conditions at T2 than mixing ratios found at
ATTO or TT34 (Figs. 2 and 5). Nevertheless, the mixing ratios of MEK during
polluted conditions (0.7
Polar surface plot for average MEK mixing ratios at a given wind
direction (angle, 1–5 m s
Mixing ratios of MEK at T2 were found to be significantly enhanced during polluted conditions for both dry and wet season (Fig. 7). The relative enhancement within polluted periods at 13:00 LT ranged around a factor of 1.5 for the wet season and of 1.8 for the dry season. During the dry season, the day-to-day variability was more intense, as reflected by the standard deviations which increased by 360 % for the clean conditions and 410 % for the polluted conditions relative to the wet season clean and polluted values, respectively. This may indicate a difference in the sources and sinks regulating MEK mixing ratios among the different seasons. Examples of this difference could be an increase in MEK due to biomass burning, more abundant during the dry season, or changes in the deposition rates due to changes in rain frequency.
The CYPHEX campaign took place at Ineia, north-west Cyprus, at a location
that has very little significant vegetation nearby. The air masses that pass
through the site are either from western Europe, passing across France and
Spain and then the Mediterranean Sea, or from south-eastern Europe (e.g. Turkey,
Greece). During the CYPHEX campaign, the hourly median MEK mixing ratios did
not show any distinct diel cycle or relations to temperature or net radiation
(Fig. 5), strongly suggesting that no significant local sources were present.
Furthermore, backward air mass trajectories, as calculated by the HYSPLIT
model (NOAA Air Resources Laboratory, USA; Stein et al., 2015) (Fig. 8), can
be used to delineate times when Cyprus was affected by easterly and westerly
flow. These trajectories were started at 650 m height with the ensemble
mode. The periods (east, west) were chosen on the basis of the FLEXPART
model. Further information can be found in Derstroff et al. (2016). On
average, easterly air masses contained 0.13
In order to investigate the origin and characteristics of MEK in the
atmosphere, we calculated the correlation coefficient (
Hourly average concentrations of MEK in ppb for the clean conditions (blue) and the polluted conditions (red) at the T2 site. Dashed lines represent the dry season and thick lines represent the wet season. Error bars represent the standard deviation.
Timeline of MEK mixing ratios divided into periods when the air was coming from either eastern or western Europe. The HYSPLIT backward trajectories from 14 July and 28 August 2014 are shown based on the origin of the air masses. The black line represents the average of the whole campaign.
In general, biogenic sites, namely ATTO, SMEAR Estonia, and O
At the anthropogenically influenced sites, T2 and CYPHEX, correlation
coefficient (
Most of the measurements in this study were performed with a quadrupole
PTR-MS, a technique that monitors selected VOC ions, online and with fast
time response. A disadvantage is the separation by masses with a mass
resolution of only 1 amu. For some masses, several compounds and/or
compound fragments may be detected as one signal. The quadrupole PTR-MS
signal at
Correlation coefficients (
Methyl glyoxal is a likely contributor to the observed signal at the PTR-MS
protonated mass
Even though a contribution of butanal to
The data obtained at the biologically influenced sites demonstrated that MEK was emitted by vegetation. This is clearly supported by the canopy-scale net flux observations of MEK at the TT34 rainforest site (Fig. 4) as well as the diel cycles of the mixing ratios at the other biogenically influenced sites (Fig. 2). Furthermore, the leaf-level cuvette measurements at SMEAR Estonia also corroborated the MEK emission by vegetation. In addition, a contribution by other biogenic sources such as dead and decaying plant matter was also observed at SMEAR Estonia to be of similar magnitude to boreal plant species emissions and indicative of a source from plant litter, in accordance with the results from Warneke et al. (1999) that measured MEK emission from the abiotic processes of plant decaying matter. This is not the case for the tropical sites where vertical profiles show that canopy emissions dominate.
High correlation coefficients suggested strong relations between the emission
processes for MEK and other biogenic compounds (Table 3). A similar approach
has been used previously by Goldstein and Schade (2000) to unveil the sources
of acetone. Similarly, Davison et al. (2008) found a high correlation
coefficient between MEK and acetone of
Plant physiological production pathways have been reported for MEK formation. MEK can be formed, similarly to acetone, as a by-product of a cyanohydrin lyase reaction during cyanogenesis (Fall, 2003; Vetter, 2000). This chemical defence pathway was also identified in clover by Kirstine et al. (1998) and de Gouw et al. (1999) as a result of mechanical stress, and can be of special importance for tropical rainforests (Miller et al., 2006). On the other hand, in places such as SMEAR Estonia, dominating plant species are not cyanogenic, and other processes for MEK formation are probably more dominant. In pine trees, acetone is produced from light-dependent and independent processes that can be associated with the decarboxylation of acetoacetate occurring in microorganisms and animals (Fall, 2003), from oxidation of fatty acids leading to ketone emissions (Niinemets et al., 2014), from pyruvic acid leading to acetyl-CoA (Kesselmeier and Staudt, 1999), or from uncharacterised biochemical reactions (Fall, 2003). Such processes could also be related to MEK emissions.
Even though extensive laboratory measurements are needed to identify the dominant plant process or processes responsible for MEK emission, this study demonstrated the role that temperature can exert on such emissions. Hence, forests around the world may act as very different sources for atmospheric MEK. This can be seen for boreal forests (SMEAR Estonia), with distinctly lower temperatures, where MEK levels were significantly lower. However, other factors must be considered (Schade et al., 2011), such as leaf area index (LAI) and plant species composition, as well as the environmental factors, water availability and mechanical stress, the latter having already been observed by de Gouw et al. (1999) to act as a driver for MEK emissions.
Due to its relatively long atmospheric lifetime (
A clear difference could be observed between the anthropogenic and biogenic
influenced sites presented in this study. The T2 site represented a site with
mixed influence by urban area and tropical rainforest. Affected by
anthropogenic and biogenic sources, ambient mixing ratios of MEK were higher
than at the pristine ATTO rainforest site. Polluted episodes (from the Manaus
plume) with an increase in MEK could be distinguished for both the wet and
the dry season, suggesting a short-range transport of air masses. On the
other hand, when the wind is blowing from the north, MEK mixing ratios were
also present, showing an influence from biogenic forest emissions (Fig. 7),
thus having a mix of biogenic and anthropogenic influence at the T2 site. A
strong seasonality of MEK mixing ratios at T2 reflected biomass burning as a
common occurrence in the Amazon region during the dry season (Artaxo et al.,
2013). In addition to MEK, a higher contribution of butanal affecting
Literature compilation of MEK mixing ratios measurements in different ecosystems around the globe from a wide range of atmospheric environments.
We regarded CYPHEX as an anthropogenically influenced site with weak or no
apparent direct sources but which was affected by anthropogenic air masses after
long-range transport over marine areas. Losses by transport over the sea and
chemical decomposition led to the lowest averaged MEK mixing ratios of all
compared sites. Correlation coefficients (
The comparison of MEK mixing ratios in different parts of the world is
necessary in order to understand how this ubiquitous compound occurs and
behaves in the atmosphere. To summarise, Table 4 aims to provide a numerical
comparison of MEK mixing ratios reported around the globe. While MEK mixing
ratios in our study are relatively constant, MEK has been measured in many
different ecosystems ranging from 0.073 ppb to 4 ppb. Therefore, it
is important to consider the variability in this compound as MEK can lead to
PAN and ozone formation in the atmosphere (Pinho et al., 2005). Photochemical
odd-hydrogen production in the upper troposphere (Atkinson, 2000; Baeza
Romero et al., 2005; De Gouw et al., 1999) can further enhance the MEK ozone
forming potential (Folkins et al., 1998; Prather and Jacob, 1997). Of the
widely used atmospheric chemistry models, only GEOS-Chem explicitly computes
MEK but only with regard to anthropogenic origin. On the basis of the data
presented here from forest sites, it is necessary for atmospheric chemistry
models to also include biogenic MEK emissions to better estimate its effects
on the environment. Sites under biogenic influence showed marked diel
variability, matching biogenic VOC emissions and temperature. Structural
forest features seem to affect turbulent mixing and diluting of trace gases
like MEK, as in the case of O
This study presents the first compilation and comparison of ambient measurements of MEK at different sites. MEK patterns and mixing ratios differ around the globe depending on sources and transport. Vegetation and litter have been identified as sources of MEK and magnitude of sources varied among the tropical rainforest, the Mediterranean temperate forest and the hemiboreal forest following a likely temperature dependence. However, via different filtering methodologies (CO filtering and backward trajectories), the anthropogenic input from polluted regions, such as the mixed urban and tropical rainforest and mixed marine environment, is often found to be the dominant contribution.
Even though the data are still not available in any public repository, as the authors are still working on other parts of the data collected during the campaigns, the data are available upon request from the main author.
For ATTO, we thank the Max Planck Society and the Instituto Nacional de Pesquisas da Amazonia for continuous support. Furthermore, we acknowledge the support by the ATTO project (German Federal Ministry of Education and Research, BMBF funds 01LB1001A; Brazilian Ministério da Ciência, Tecnologia e Inovação FINEP/MCTI contract 01.11.01248.00), UEA and FAPEAM, LBA/INPA, and SDS/CEUC/RDS-Uatumã. We would especially like to thank all the people involved in the logistical support of the ATTO project, in particular Reiner Ditz and Hermes Braga Xavier. We acknowledge the micrometeorological group of INPA/LBA for their collaboration concerning the meteorological parameters, with special thanks to Marta Sá, Antonio Huxley and Leonardo Oliveira. We would like to acknowledge Stefan Wolff for the construction, support and maintenance of the inlet system. We are grateful to Nina Knothe for logistical help. We would also like to thank Thomas Klüpfel for all the great support provided with the PTR-MS operation in the laboratory as well as in the field. This paper contains results of research conducted under the Technical/Scientific Cooperation Agreement between the National Institute for Amazonian Research, the State University of Amazonas, and the Max-Planck-Gesellschaft e.V.; the opinions expressed are the entire responsibility of the authors and not of the participating institutions.
For TT34, we thank the Natural Environment Research Council for funding the CLAIRE-UK project (reference NE/I012567/1), A. Valach, B. Davison and M. Shaw for assistance and A. R. MacKenzie for valuable discussions.
For SMEAR, we would like to acknowledge the EU Regional Development Foundation: “Environmental Conservation and Environmental Technology R&D Programme” project BioAtmos (3.2.0802.11-0043), “Internationalization of Science Programme” project INSMEARIN (10.1-6/13/1028), and the “Estonian Research Infrastructures Roadmap” project Estonian Environmental Observatory (3.2.0304.11-0395). We express our gratitude to the Archimedes Foundation (international programme DoRa) and the “Freunde und Förderer der Goethe Universität” that provided funding to E. Bourtsoukidis for conducting research in Estonia. We would like to additionally thank Dominika Radacki, Javier Roales, Beate Noe, Eero Talts, Ahto Kangur and Miguel P. Estrada for providing valuable help with the setup and transportation. Special thanks to Boris Bonn for the insightful discussions and comments during the production of this article.
For O
For T2, we thank Bruno Takeshi for all the logistical support. Furthermore, we acknowledge the support by FAPESP grant 2013/25058-1 and 2013/05014-0.
For CYPHEX, the authors gratefully acknowledge the NOAA Air Resources
Laboratory (ARL) for the provision of the HYSPLIT transport and dispersion
model and READY website (