OH reactivity from different tree species: Investigating the missing reactivity in a boreal forest

In forested area, a large fraction of total hydroxyl radical (OH) reactivity remain unaccounted for. Very few studies have been looking at total OH reactivity from biogenic emissions and its variations. In the present study, we investigate the total OH reactivity from three common boreal tree species (Scots pine, Norway spruce, and Downy birch), by comparing it with the calculated reactivity from the chemically identified emissions. Total OH reactivity was measured using the Comparative 5 Reactivity Method (CRM), and the chemical composition of the emissions was quantified with two gas chromatographs coupled to mass spectrometers (GC-MSs). Dynamic branch enclosures were used and emissions from one branch of a tree at the time were measured by rotating between them periodically. Results show that birch had the highest values of total OH reactivity of the emissions (TOHRE), while pine had the lowest. The main drivers for the known reactivity of pine and spruce were monoterpenes and sesquiterpenes. For birch, emissions were 10 dominated by sesquiterpenes, even though monoterpenes and GLVs could be found too. However, calculated reactivity values remained low leading to the highest missing fraction of reactivity (>96 %), while pine and spruce had similar missing reactivity fractions between 56 % and 82 % (higher in the spring and decreasing as the summer proceeded). The high average values were driven by low reactivity periods and the fraction of missing reactivity got smaller for pine and spruce when the TOHRE values increased. Important exceptions were identified for periods when the emission profiles changed from terpenes to Green Leaf 15 Volatiles (GLVs), a family of compounds containing a 6 carbon atoms backbone with various functionalities (e.g. alcohols, aldehydes, esters) that indicate that the plant is suffering from stress. Then, very high TOHRE values were measured and the missing fraction remained high. This study found a different trend in the missing OHRE fraction of Norway spruce from spring to autumn compared to one previous study (Nölscher et al., 2013), which indicates that additional studies are required to fully understand the complexity 20 of biogenic reactive emissions. Future studies of boreal trees in situ should be conducted to confirm the findings presented.

(Philips KTY 80/110, Royal Philips Electronics, Amsterdam, Netherlands) and the Photosynthetically Active Radiation (PAR) was measured with a quantum sensor (LI-190SZ, LI-COR, Biosciences, Lincoln, USA) placed on top of the enclosure frame. 90 In this study, three branch enclosures were used so that they could be set up one or two weeks before the measurements of the emissions in order to reduce the stress caused by handling the branches to a minimum. During that time, the enclosure was left open and only when the measurement started, the enclosure was carefully closed, with transparent Teflon film, which could nevertheless result in some level of stress.
The temperature difference between ambient conditions and inside the enclosure are presented in the Appendix ( Figure C1). 95 For a large majority of the data (74 %), the difference lies within 3 • C. For another 22 % of the data the difference is comprised between 3 and 10 • C. The maximum temperature difference is 27.5 • C. Large temperature differences happened when prolonged direct sunlight heated up the enclosure.

In-situ measurements of Volatile Organic Compounds
Volatile Organic Compounds (VOCs) were measured with two in situ GC-MSs, which have been previously described in 100 more detail by Hellén et al. (2017Hellén et al. ( , 2018. One GC-MS measured the concentrations of mono-and sesquiterpenes, isoprene, 2-methyl-3-butenol (MBO) and C 5−10 aldehydes in the emissions. These compounds were collected for 30 minutes from a 40 ml min −1 subsample flow of the CRM instrument sampling flow in the cold trap (Carbopack B/Tenax TA) of the thermal desorption unit (TurboMatrix, 650, Perkin-Elmer) connected to the GC (Clarus 680, Perkin-Elmer) coupled to the MS (Clarus SQ 8 T, Perkin-Elmer). A HP-5 column (60m, i.d. 0.25 mm, film thickness 1 µm) was used for separation. 105 The other GC-MS measured the concentrations of alcohols and volatile organic acids (VOAs). Every other hour a sample was taken for 60 minutes and analysed with a thermal desorption unit (Unity 2 + Air Server 2, Markes International LTD, Llantrisant, UK) connected to the GC (Agilent 7890A, Agilent Technologies, Santa Clara, CA, USA) and the MS (Agilent 5975C, Agilent Technologies, Santa Clara, CA, USA). A polyethylene glycol column i.d. 0.25 mm, a film thickness 0.25 µm) was used for the separation.

OH reactivity
The OH reactivity is the inverse of the OH lifetime. OH reactivity, R OH can be calculated from the sum of the concentration of individually emitted compounds X i , [X i ], multiplied by their respective reaction rate coefficient with OH (k OH+Xi ): The experimental total OH reactivity, R exp , can be measured with the Comparative Reactivity Method (CRM, Sinha et al.,115 2008; Michoud et al., 2015). The specific instrument used for this study is described in Praplan et al. (2017Praplan et al. ( , 2019 and the measurement principle briefly explained in the following section together with the application of the method to measure the OH Reactivity of Emissions (OHRE).

Total OH reactivity measurements: the Comparative Reactivity Method
The CRM is based on monitoring the signal change of pyrrole (C 4 H 5 N) exposed to OH in a reactor together with either clean 120 (zero) air or air sampled from the branch enclosure. OH is produced by the photolysis of water (H 2 O) in a nitrogen flow (99.9999% N 2 ) using ultraviolet (UV) radiation and a gas chromatograph (GC, SYNTECH SPECTRAS Analyser GC955, Synspec BV, Groningen, The Netherlands) equipped with a photon ionization detector (PID) measures the pyrrole concentration in the CRM instrument reactor every two minutes. Based on pyrrole calibrations for the GC-PID detector, a sensitivity of 1678 ppb −1 v measured on 11 May was used for data until 14 June, then a sensitivity of 1833 −1 v measured on 15 June was used 125 for data until 28 June. On 28 June, a lower sensitivity of 1193 −1 v was measured and used for rest of the measurement periods. During zero air measurements all OH is consumed by pyrrole (labelled C 2 level). This zero air is produced by passing the sampled air through a platinum catalyst heated at ca. 450 • C to remove reactive species. When zero air is replaced with the sampled air other reactive compounds compete for OH, leading to an increased pyrrole concentration (C 3 level). The instrument alternates measurements of zero air and sampled air every 8 minutes. The conditions in the reactor after switching stabilize 130 within one minute and therefore the first pyrrole measurement after each switch is discarded. The amount of pyrrole in the reactor in the absence of OH with the UV light on (C 1 level) is slightly lower than the amount of pyrrole introduced into the reactor in the dark (C 0 level), due to photolysis of pyrrole (5.6-9.3 %). C 1 is measured by introducing a large concentration of a 0.6 % propane (C 3 H 8 ) in nitrogen (N 2 ) gas mixture to act as an OH scavenger (Zannoni et al., 2015). From the difference between C 2 and C 3 pyrrole levels and taking into account the amount of available pyrrole (C 1 ), the total OH reactivity in the 135 reactor R eqn can be derived from the following equation: with k p the reaction rate of pyrrole with OH (1.2 · 10 −10 cm 3 s −1 , Atkinson et al., 1985). However, this equation has been derived under a pseudo first-order kinetics assumption (i.e. [C 4 H 5 N]>>[OH]), but the pyrrole-to-OH ratio (pyr:OH) varies between 1.0 and 3.5 in the present study.

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Therefore we apply a correction described in detail in (Praplan et al., 2019) for this deviation from pseudo first-order kinetics, based on experimental reactivity calibrations with α-pinene (see section 2.5.3). The only difference here compared to Praplan et al. (2019) who applied the correction factor to ambient measurements is that the background reactivity of the empty enclosure (R eqn,blank ) is also taken into account. R eqn,blank was determined between 28 September and 4 October and is 2.6 ± 3.0 s −1 (1 σ, see Fig. C2 in the Appendix). Based on this, the reactivity in the reactor (R CRM ) is derived according to the following 145 equation: https://doi.org/10.5194/bg-2020-37 Preprint. Discussion started: 3 March 2020 c Author(s) 2020. CC BY 4.0 License.
In addition, because of the dilution of the sampled air with humid nitrogen, the calculation of the total OH reactivity of the sampled air R exp requires the use of the dilution factor D (ratio of sampling flow over total flow through the reactor, comprised between 0.63 and 0.69): Other correction factors need to be applied during CRM data analysis. However, corrections due to the presence of ozone (O 3 ) and nitrogen oxides (NO x ) described elsewhere (e.g. Michoud et al., 2015;Fuchs et al., 2017;Praplan et al., 2017Praplan et al., , 2019 are not required in the present study due to the use of zero air through the dynamic branch enclosure. Only the correction due to the difference in relative humidity (RH) in the reactor between C 2 and C 3 levels and the correction due to the deviation 155 from pseudo-first-order kinetics need to be taken into account. A detailed description of these corrections can be found in the following subsections.
Finally, the Total OH Reactivity of Emissions (TOHRE) measured using a dynamic branch enclosure can be derived from where f is the total flow through the enclosure and m dw is the dry weight of the leaves or needles in the enclosure. In a 160 similar way, the Calculated OH Reactivity of Emissions (COHRE), based on the known air composition, can be calculated.
2.5.2 Correction due to the difference in RH Equation (2) assumes that RH (i.e. OH levels) are identical during C 2 and C 3 measurements. In order to minimize the difference of RH between C 2 and C 3 , zero air is produced in the CRM instrument by passing sampled air from the dynamic 165 branch enclosure through a catalytic converter (1 % wt. platinum on aluminium oxide pellets, Sigma-Aldrich, Co., St. Louis, MO, USA), which remove VOCs, but does not affect RH levels much. However, the small decrease in RH after the catalytic converted for C 2 measurements needs t o be taken into account. Figure 1 show the pyrrole signal as a function of RH while measuring zero air. The applied correction is then: 170 2.5.3 Correction due to deviation from pseudo first-order kinetics As mentioned previously, this correction is necessary as Eq. (2) is derived under the assumption of a pseudo-first-order kinetics ([C 4 H 5 N] [OH]), while the experimental pyrrole-to-OH ratio (pyr:OH) is comprised between 1.0 and 3.5. Originally, Sinha the observed response of pyrrole in the reactor, despite alterations to take into account secondary OH chemistry. In the present study we use the experimental results derived in Praplan et al. (2019) based on α-pinene calibrations, which show that the measured OH reactivity (R eqn ) is roughly half the expected reactivity, so that the exact relationship between the reactivity in the reactor (R CRM ) and R eqn is the following:

Emission models
We used a typical model for VOC emissions (Guenther et al., 1993(Guenther et al., , 1995 to test the light and temperature dependence of TOHRE. The temperature-only dependence is the same dependence as the one for monoterpene emissions and is expressed with the following equation: TOHRE S is the TOHRE at standard temperature T S (303 K) and T the temperature in the enclosure. In the present study, we assume that the leaf surface temperature is the same as the temperature inside the enclosure. β describes the temperature dependence (so-called β-factor) and is estimated to be 0.09 K −1 for monoterpenes.
A hybrid algorithm based on both temperature and light can be used to model emissions which follow also changes in illumination (Guenther, 1997;Ghirardo et al., 2010). The dependence on light and temperature for TOHRE is then formulated 190 as follow: with TOHRE 0,pool and TOHRE 0,synth the standard TOHRE potentials pool emissions (stored compounds, temperature dependent) and synthesis emissions (newly synthesised compounds, light and temperature dependent), respectively. c L and c T are light and temperature activity coefficients, respectively, defined such as: T and T S are the same as above and Q is the PAR measured just above the enclosure. α (0.0027), c L1 (1.066), c T 1 (95000 mol J −1 ), c T 2 (230000 mol J −1 ), and T M (314 K) are empirical coefficients. Finally, R is the gas constant (8.314 J K −1 mol −1 ).

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3 Results and discussion

Overview
An overview of monthly averages for TOHRE and missing TOHRE (absolute and fraction) can be found in Table 1. The highest TOHRE monthly averages were found for birch in May and June (1.6-2.6 10 −3 m 3 s −2 g −1 dw ), which is mostly unaccounted for (missing OHRE fraction 96-99 %). The monthly TOHRE averages from spruce were high in July and August (1.1-1.5 10 −3 m 3 205 s −2 g −1 dw ), while the highest monthly average for TOHRE from pine was in July (6.1 10 −4 m 3 s −2 g −1 dw ). A few compounds per class of biogenic VOCs were identified as the main drivers of the reactivity and this will be discussed in the following subsections for each tree individually.
The results illustrate as well how biogenic reactivity is influenced by the time of the year and the tree species found in the forested areas. In addition, high measured TOHRE is related to a change in the emission profiles with a larger fraction of Green 210 Leaf Volatiles (GLVs). GLVs form a family of C 6 compounds, including aldehydes, alcohols and esters, which are emitted rapidly and in large amount during stress periods (e. g. Scala et al., 2013). Stress can have various abiotic and biotic causes (e. g. drought, attack by pathogens or herbivores). Table 1. Monthly averages of temperature in the enclosure (Te), relative humidity (RH), Photosynthetically Active Radiation (PAR) and Total OH Reactivity of the Emissions (TOHRE), as well as missing OHRE (absolute and relative). The number of observations, n, for missing OHRE is lower than for other parameters due to incomplete overlap between calculated OHRE (VOC data) and TOHRE.
seedling are similar. Here COHRE is mostly driven by α-pinene, limonene, and ∆ 3 -carene. Sesquiterpenes (mostly α-and β-farnesene) contribute up to 15 % to the known OH reactivity and MBO represent an important fraction, especially in June and July. TOHRE qualitatively follows COHRE.
The highest TOHRE values from pine were measured in early July and early October. These two periods (3-5 July and 4-11 October) are marked with a fraction of Green Leaf Volatiles (GLVs) up to roughly 35 % (mostly due to cis-3-hexenol). At the 235 same time, emissions from monoterpenes previously mentioned as well as terpinolene increase as well. Between 3 and 5 July TOHRE increased and was high even at night, when it is otherwise close to zero at night. Interestingly 3 July marks the end of a warm and sunny period with the maximum temperature in the branch enclosure between 30 and 40 • C for 5 days in a row and the beginning of a cooler and cloudier period with some precipitations. It is not clear though if stress emissions are related to the change in environmental conditions or are a result of stress experienced during the previous days.

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For the other periods, TOHRE follows COHRE quantitatively but is usually higher than it. Only in September the missing fraction is the lowest, due to the low TOHRE values measured, which are in the same range as the COHRE values (only with a much larger scatter). Nölscher et al. (2012) found higher missing reactivity for ambient measurement at SMEAR II, a boreal site dominated by Scots Pine, for stress periods (elevated temperature). While here the stress emissions were not due to elevated temperature 245 (see section3.5), the missing OHRE was generally higher during these periods, indicating that some of these stress-related emissions are not terpenoids or oxidized volatile organic compounds.

Spruce
For spruce TOHRE follows qualitatively COHRE as well. Branches were cut on 21 June, 9 August, and 5 November. The known reactivity of the emissions in May (first branch) is dominated by monoterpenes, which is expected from earlier studies 250 (Yassaa et al., 2012;Hakola et al., 2017;Wang et al., 2017). The main drivers are limonene, β-pinene, and β-phellandrene.
The highest TOHRE values is observed at the beginning of July (for the second branch) with one extremely high peak over 0.06 m 3 s −2 g −1 dw on 9 July and another TOHRE peak on the next day. However, almost all reactivity can be explained by monoterpenes and GLVs during that period (mostly cis-3-hexen-1-ol and cis-3-hexenylacetate, as well as limonene). 9 and 10 July were dry and sunny days, with mximum temperatures in the branch enclosure close to 40 • C. After that, when the weather 255 gets cooler and cloudier with some precipitations between 11 and 14 July, the GLV fraction decreases and monoterpenes and sesquiterpenes are accounting for most of the known reactivity. This is in stark contrast with the observed stress emissions from pine in this study, which increased during the colder period, after a warm spell.
However, between 19 and 23 August (third branch) high TOHRE values (up to 0.01 m 3 s −2 g −1 dw ) were measured (including at night), similarly to the stress period observed for pine. It can be seen that during these periods with larger fraction of GLVs 260 some needles were drying and falling (Appendix A), which confirms that the tree suffered stress (most probably drought).
Other environmental conditions did not change much during that period, which was relatively cool and cloudy.
In contrast to stress periods in pine, monoterpene emissions from spruce were low when the GLV fraction increased. During this period, cis-3-hexen-1-ol, cis-3-hexenylacetate, and trans-2-hexenal mostly contribute to COHRE. In September, this branch had low TOHRE and the known reactivity of the emissions was caused by monoterpenes and sesquiterpenes, similarly 265 to the period between 16 and 19 August, before the large stress episode. α-Farnesene contributes most to the sesquiterpene reactivity fraction (here and for other periods as well). The increase of the sesquiterpene fraction in the emissions is in agreement with observations from Hakola et al. (2017) (up to 75 % of the emissions in late summer, mostly β-farnesene).
A direct comparison with the results for TOHRE and missing OHRE of spruce from Nölscher et al. (2013) is difficult due to the many factors affecting the emissions. While they found that the missing OHRE was lower in the spring and increased in 270 the late summer and autumn to 70-84 %, the present study suggest that the missing OHRE fraction is decreasing from May to August. As discussed earlier, lots of high missing OHRE in the present study stem from low reactivity periods with high scatter for TOHRE and values close to zero for COHRE. However, because Nölscher et al. (2013) assume a constant emission profile (measured in spring) throughout the year and otherwise rely on PTR-MS data (without speciation), it is imaginable that the chemical compositions of the emissions changed with the season to more reactive monoterpenoids or sesquiterpenes, leading 275 to an underestimation of the calculated OH reactivity. 13 https://doi.org/10.5194/bg-2020-37 Preprint. Discussion started: 3 March 2020 c Author(s) 2020. CC BY 4.0 License.

Birch
Birch branches were cut on 21 June, 9 August and 6 September. The observed TOHRE shows relatively high values (due to the low dry weight mass) with almost no diurnal pattern. In late June a weak pattern can be observed and in mid-July a few reactivity peaks can be observed (second branch). It is possible that the constant blank value subtracted from the measurements 280 underestimates at time the actual background of the measurements.
Here TOHRE follows COHRE quantitatively once more, but the missing fraction of OHRE is consistently high. This is partly due to the generally low values of COHRE, which is dominated by sesquiterpenes for the first two branches (until 9 August), with a significant amount of monoterpenes (up to 40 %). Periods when the known reactivity is dominated by organic acids are missing terpene measurements. In May for the first branch β-caryophyllene, α-humulene, and another unidentified 285 sesquiterpene, as well as sometimes cis-3-hexenylacetate contribute most to the reactivity of the emissions. For the second branch in June and July, the emission profile is slightly different with β-caryophyllene, α-farnesene, and linalool as well as sometimes cis-3-hexenylacetate and cis-3-hexen-1-ol (co-emitted) contributing most.

Temperature and light dependence of TOHRE
In order to also study the dependence of TOHRE on temperature, TOHRE has been plotted against the temperature in the enclosure and regressions derived from Eq. (9) have been performed (Fig. 5 and Table 2). Similar figures for COHRE, and missing OHRE can be found in Appendix E showing similar findings than for the TOHRE dependence on temperature.
Good correlations with temperature are found for the TOHRE of pine in June and August (R = 0.70 and 0.61, respectively),  Tarvainen et al., 2005;Hakola et al., 2006;Duhl et al., 2008), even though values as low as 0.025, 0.05 and 0.056 were found as well (Tarvainen et al., 2005;Helmig et al., 2007;Ruuskanen et al., 2007, respectively). For pine, which is dominated by monoterpene emissions, β-factors are about 0.09-0.10 • C −1 except for stress periods, when the β-factor is then smaller than 0.003. For spruce, β-factors increase from 0.02 to 0.19 • C −1 between May and 310 July, demonstrating a clear regime change in the temperature dependence of the emissions, with an increasing contribution of less volatile compounds (sesquiterpenes and GLVs). For birch, the β-factor in July when a good correlation with temperature was found remains low, even though emissions are dominated by sesquiterpenes. This might be an indication of emissions of non-terpenoid volatile compounds.
Results of using Eq. (10) to include the effect of light on TOHRE (Hybrid algorithm, Table 2) show that in general only 315 small improvements (increases of R) are achieved. In a few cases R was even slightly reduced. One notable exception is a large improvement of the coefficient of correlation R from 0.5 to 0.9 for spruce in July. The addition of a small TOHRE 0,synth term seemed to be enough to capture the large peak that was reported as stress, indicating a radiation-induced stress in this case.
β-Factors are in general very similar to the results of the regression for the temperature-only dependence (when a good correlation was found in the first place). Note that in September (and to some extend in August) the temperature range remain 320 small (about 10 K) and towards small temperature, so that nothing conclusive can be inferred from these results. In summary the effect of light on reactive remissions remains limited in the present study, but other factors can play a major role on the type and amount of reactive emissions.  trees were seedlings (in pots) placed outside the measurement container at the SMEAR II station in Hyytiälä, Finland. Instruments to measure TOHRE with the comparative reactivity method (CRM) and the chemical composition of the emissions (two on-line GC-MS systems) were located inside the container. Three dynamic branch enclosure (one for each tree species) were set up, but VOC and TOHRE measurements were performed from one enclosure at a time for periods ranging from a few days to over a week.

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The results show that the chemical composition of the emissions varies greatly between tree species but also for the same tree depending on environmental conditions. The emissions of the seedlings were classified as stress-induced on several occasions.
During these periods, TOHRE increased greatly and did not return to values close to zero at night and the emission profiles changed with an increased fraction of Green Leaf Volatiles (GLVs) and different terpene emissions.
Pine emissions were dominated by monoterpenes for all measurement periods with varying fractions of MBO and sesquiter-335 penes mostly. GLVs were found to be up to almost 40 % of the known reactivity in July and October for two short stress periods. Spruce emissions were also dominated by monoterpenes and from July onwards sesquiterpenes contributed almost equally to TOHRE. Exceptions are the two stress periods, where GLVs and aldehydes were the major compounds. Birch emissions were dominated by various fractions of monoterpenes and sesquiterpenes with GLVs also present, especially in mid-July and August.

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In absolute terms the highest TOHRE values were measured for birch, mostly due to the low reactivity (because of the small biomass) and higher influence of the measurement background, compared to the other two tree species. Also higher TOHRE averages were found for spruce, compared to pine, indicating that knowledge of the tree composition of a forest is important in order to assess reactive emissions.
In general the missing OHRE fraction remain high, but for pine and spruce it was driven by low reactivity periods (low 345 COHRE and scatter of the TOHRE measurements) and the missing OHRE fraction was smaller for periods with higher TOHRE. However for birch, we found consistently high missing fraction throughout the measurement periods, which emphasise the need to look for emitted compounds with different functionalities than the ones studied so far.
Moreover, TOHRE exhibited various degrees of temperature dependence. In particular for spruce this temperature dependence had a strong seasonality: a high temperature dependence was found in July and August (when less volatile compounds 350 are emitted, such as sesquiterpenes), but a low dependence was measured in May, and September. For pine and birch the temperature difference was varying less with the seasons. Stress emissions for pine in July were not temperature dependent at all and no correlation could be found. Taking into account photosynthetically active radiation (PAR) with an hybrid model did not improve significantly the correlations, except for the notable exception of pine emissions in July (including very large peak on 9 July).

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Because this type of characterization of TOHRE is rare, only a comparison with a study by Nölscher et al. (2013) is possible.