Modelling the influence of biotic plant stress on atmospheric aerosol

Most trees emit volatile organic compounds (VOCs) continuously throughout their life, but the rate of emission, 13 and spectrum of emitted VOCs, become substantially altered when the trees experience stress. Still, models to predict the 14 emissions of VOCs do not account for perturbations caused by biotic plant stress. Considering that such stresses have general ly 15 been forecast to increase in both frequency and severity in future climate, the neglect of plant stress-induced emissions in 16 models might be one of the key obstacles for realistic climate change predictions, since changes in VOC concentrations are 17 known to greatly influence atmospheric aerosol processes. Thus, we constructed a model to study the impact of biotic plant 18 stresses on new particle formation and growth throughout a full growing season. We simulated the influence on aerosol 19 processes caused by herbivory by European gypsy moth (Lymantria dispar) and autumnal moth (Epirrita autumnata) feeding 20 on pedunculate oak (Quercus robur) and mountain birch (Betula pubescens var. pumila), respectively, and also fungal 21 infections of pedunculate oak and balsam poplar (Populus balsamifera var. suaveolens) by oak powdery mildew (Erysiphe 22 alphitoides) and poplar rust (Melampsora larici-populina), respectively. Our modelling results indicate that all the investigated 23 plant stresses are capable of substantially perturbing both the number and size of aerosol particles in atmospherically relevant 24 conditions, with increases in the amount of newly formed particles by up to about one order of magnitude and additional daily 25 growth of up to almost 50 nm. We also showed that it can be more important to account for biotic plant stresses in models for 26 local and regional predictions of new particle formation and growth during the time of infestation/infection than significant 27 variations in e.g. leaf area index, and temperature and light conditions, which are currently the main parameters controlling 28 predictions of VOC emissions. Our study, thus, demonstrates that biotic plant stress can be highly atmospherically relevant. 29 To validate our findings, field measurements are urgently needed to quantify the role of stress emissions in atmospheric aerosol 30 processes and for making integration of biotic plant stress emission responses into numerical models for prediction of 31 atmospheric chemistry and physics, including climate change projection models, possible. 32

alphitoides) and poplar rust (Melampsora larici-populina), respectively. Our modelling results indicate that all the investigated 23 plant stresses are capable of substantially perturbing both the number and size of aerosol particles in atmospherically relevant 24 conditions, with increases in the amount of newly formed particles by up to about one order of magnitude and additional daily 25 growth of up to almost 50 nm. We also showed that it can be more important to account for biotic plant stresses in model s for 26 local and regional predictions of new particle formation and growth during the time of infestation/infection than significant 27 variations in e.g. leaf area index, and temperature and light conditions, which are currently the main parameters controllin g 28 predictions of VOC emissions. Our study, thus, demonstrates that biotic plant stress can be highly atmospherically relevant. 29 To validate our findings, field measurements are urgently needed to quantify the role of stress emissions in atmospheric aerosol 30 processes and for making integration of biotic plant stress emission responses into numerical models for prediction of 31 atmospheric chemistry and physics, including climate change projection models, possible.

Meteorological conditions 276
The daily maximum radiation during the entire growing season was fixed to 1000 μmol m -2 s -1 (Table 2) For simulations of oak and poplar, we utilised the maximum and minimum temperatures for southern Germany averaged over 283 the past three decades (data obtained via https://www.currentresults.com/Weather/Germany/average -annual-284 temperatures.php). This was done due to availability and restriction of data obtained at the Hohenpeißenberg Meteorological 285 Observatory and since our aim was not as such to simulate the atmospheric impact at Hohenpeißenberg, but instead at any 286 relevant location, i.e. where oaks and poplars, including the biotic stresses of interests, are common. The monthly averaged 287 daily maximum and minimum temperatures ranged from 15 to 26 ºC, and from 6 to 16 ºC, respectively, in the time period of 288 interest (April -September, Fig. 4b). For simplicity, the daily temperature pattern followed that of the solar zenith angle with 289 a forward shift of 1 h. The default daytime mixing length was kept constant to a value of 700 m (simulations of mountain 290 birch) and 2000 m (simulations of oak and poplar) above ground level (Seidel et al., 2012) (  Fig. 11a-b,f-g,k-l,p-q). Thus, in our simulations, the default daily maximum concentration of OH is therefore fixed 313 to 6·10 6 molec cm -3 (Petäjä et al., 2009) and 8·10 5 molec cm -3 (calculated using observed summertime UVB radiation from 314 the SMEAR I station and the proxy presented by Petäjä et al. (2009)) for simulations of Hohenpeißenberg and Lapland, 315 respectively ( Table 2). The daily pattern of the OH concentration then follows the solar zenith angle. The concentration of 316 ozone is kept constant to a value of 45 ppb (Naja et al., 2003) and 30 ppb (Ruuskanen et al., 2003) for simulations of oak and 317 poplar (Hohenpeißenberg conditions) and mountain birch (SMEAR I conditions), respectively (Table 2). NO3 was not 318 considered, since emission and atmospheric processes were only simulated during day time, when the concentration of NO3 is 319 insignificant. 320 The only source of sulfuric acid (H2SO4), in our model, is the reaction between OH and SO2, while the only sink is 321 the condensation sink. The concentration of SO2 is chosen such that the default daytime maximum concentration of H2SO4 is 322 exact compounds, which are emitted from the tree species considered in this study. Thus, the yields applied for the production 332 of HOM in the model (Appendix C) are connected with a large degree of uncertainty. The influence of changing HOM yields 333 on our results was therefore also investigated (Sec. 3.2, Fig. 11e,j,o,t). Formation of oxygenated or ganics from oxidation of 334 sesquiterpenes and methyl salicylate are also included (Appendix C). The sum of all organic compounds, which contribute to 335 aerosol processes, is referred to as "OxOrg". 336 337

Calculation of the formation and growth of secondary organic aerosol particles 341
The clustering and activation of new particles are expressed by a formation rate of neutral 2 nm sized clusters, J2 (cm -3 s -1 ), 342 which is computed by Eq. 20, using coefficients (α1-3) from (2) 344 It is here assumed that new particles are formed via heteromolecular homogeneous nucleation between sulfuric acid and 345 oxidised organic compounds (OxOrg) as well as via homogeneous nucleation of sulfuric acid and OxOrg alone. For 346 simplification, we only operated with one growing aerosol mode and therefore included a unit-less correction term (KK), 347 which determines how large a fraction of the activated clusters reaches the growing mode (Kerminen and Kulmala, 2002): 348 where CS (s -1 ) is the condensation sink. When used together with Eq. 3, the value of CS is that of sulfuric acid. The 353 condensational particle diameter growth rate (GR, nm h -1 ) of newly formed 2-3 nm particles is calculated according to 354 non-infested oak stand are comparable, and in the case of gypsy moth infested oak stands, often much higher than observations 455 from forests with intense new particle formation events. 456 The formation rates of new particles are always higher in oak powdery mildew infected oak stands than in a non-457 infected oak stand (Fig. 7f), though the fungus is not able to perturb the formation rates as strongly (increase by up to a factor 458 of ~2.3 (J2), ~3.0 (J3), and ~5.3 (J10)) as herbivory by gypsy moth larvae. 459 Simulations of poplar stands suggest that particles will be formed at high rates in the range ~3.6-11.4 cm -3 s -1 (J2) and 460 ~2.7-10.6 cm -3 s -1 (J 3 ) during the late summer when the full leaf state has been attained, and our simulations suggest that new 461 particles will be formed the fastest in severely rust infected stands (increase by up to a factor of ~3.2 (J2), and ~3.9 (J3)). 462 In our simulations, herbivory by autumnal moth increases the formation rates of new particles in mountain birch 463 stands by up to a factor of ~2.5 (J2) and ~2.6 (J3). The formation rates of 2 and 3 nm particles are predicted to vary between 464 0.38 cm -3 s -1 and 2.5 cm -3 s -1 (J2), and 0.31 cm -3 s -1 and 2.5 cm -3 s -1 (J3) in stressed stands, and between 0.32 cm -3 s -1 and 1. 2020), where autumnal moth larvae are prominent defoliators of mountain birches, did, however, not find any evidence that 477 herbivory by autumnal moth would enhance the formation, nor growth, of atmospheric aerosol particles during the summer of 478 infestation. Instead there was some evidence of elevated total particle concentrations for a few years after summers with lar val 479 infestation, which was speculated to be caused by delayed defense responses of mountain birches. It is, however, possible that 480 the total foliage mass of mountain birches in the area is too small, or that the level of infestation was too low during the number of produced particles in a non-infested oak stand (~1.1⨉10 4 cm -3 ; Fig. 6f) is comparable to e.g. the number of new 486 particles produced during a typical new particle formation event in Hyytiälä (~1-2⨉10 4 cm -3 ; Dal Maso et al., 2008; Nieminen 487 et al., 2014), but significantly higher than observations from a Missouri oak forest, where sub-5 nm particles were measured 488 to be up to ~2⨉10 4 cm -3 , and 5-25 nm particles to ~3000 cm -3 , during typical new particle formation events (Yu et al., 2014). 489 After the period of stress, the number of particles in the growing mode is predicted to range between ~7⨉10 3 cm -3 and ~17⨉10 3 490 cm -3 in a non-infested stand, ~6⨉10 3 cm -3 and ~12⨉10 3 cm -3 in a 30 % defoliated stand and between ~3⨉10 3 cm -3 and ~5⨉10 3 491 cm -3 in a 80 % defoliated oak stand (Fig. 6f). Oak powdery mildew is predicted to enhance the number of particles in the 492 growing mode by up to a factor of ~4 compared to the corresponding non-infected stand, resulting in a maximum of ~1.7⨉10 4 493 cm -3 in an infected stand, under the used border conditions (Fig 7g). Under the same environmental conditions, a severely 494 poplar rust infected poplar stand is predicted to produce up to about five times as many new particles as a non-infected poplar 495 stand, leading to a maximum of about 1.1⨉10 5 cm -3 in a severely infected stand (Fig 8h). Finally, it is predicted that herbivory 496 by autumnal moth enhances the amount of produced particles by up to a factor of ~2.7, with a maximum number of particles 497 in the growing mode of ~3⨉10 4 cm -3 in an infested birch stand (Fig. 9j). The predicted amount of particles in a non-infested 498 mountain birch stand is in the same order as observations from Finnish Lapland (Komppula et al., 2006). 499 500

New particle growth 501
New particles are assumed to grow by sulfuric acid and OxOrg (Sec. 2.7, Eq. 5-8), hence the seasonal patterns of formation 502 rates and OxOrg concentration are reflected in the pattern of the growth rates (Figs. 6g, 7h, 8g, 9k), and therefore also in the 503 season pattern of the number (Figs. 6f, 7g, 8h, 9j) and size (Figs. 6h, 7g, 8g, 9l) of the growing particle mode. We predict that 504 the 10:00-16:00 median growth rate in a gypsy moth infested oak stand is at maximum ~5.9 nm h -1 under the assumed boundary 505 conditions, whereas the corresponding growth rate in a non-infested oak stand is around 1.6 nm h -1 , when the full leaf state has 506 been attained (Fig. 6g). For comparison, the growth rate of new particles has been reported to range from 0. . Thus, we can conclude that our predicted growth rates are 516 comparable to atmospheric observations from several different rural sites. Growth rates obtained from areas influenced by 517 anthropogenic pollution are generally higher than our simulated rates, but this is expected, since our model is constrained by 518 conditions representative for rural sites. 519 Growth rates are predicted to be lower in an oak powdery mildew infected oak forest, than in a gypsy moth infested 520 oak forest. The rates are predicted to, at maximum, be ~2.0 nm h -1 (80 % of leaf area covered by mildew), ~1.6 nm h -1 (30 % 521 of leaf area covered by mildew) and ~1.2 nm h -1 (non-infected, in the same environmental conditions as the infected trees) 522 ( Fig. 7h). Thus, the growth rates are similar to the lower end of the observed range.
The growth of small particles in non-infected and rust infected poplar stands are predicted to range between ~2.1 nm 524 h -1 and ~5.7 nm h -1 , during the late summer when the full leaf state has been attained, with the fastest growth in a heavily rust 525 infected forest stand (Fig. 8g). This range in growth rates is thus similar to simulation results of herbivory infested oak ( see 526 above; Fig. 6g). 527 The predicted growth rates are smallest in simulations of non-infested mountain birch stands in Lapland. The 10:00-528 16:00 median growth rate is at maximum predicted to be ~1.4 nm h -1 in an infested stand and varies between ~0.6 nm h -1 and 529 ~2.0 nm h -1 in a non-infested stand (Fig. 9k) According to our predictions, new particles will grow up to about 46 nm larger in an oak gypsy moth infested oak 534 stand compared to a non-infested oak stand within one day (Fig. 6h). Simulation results for the other species/stressors show 535 that new particles will grow up to about 8 nm more in an oak powdery mildew infected stand (Fig. 7g), ~28 nm more in a 536 poplar rust infected poplar stand (Fig. 8g), and ~26 nm larger in an autumnal moth infested mountain birch stand (Fig. 9l), 537 within one day, compared to their corresponding non-infected stands. In our simulations, the newly formed particles in non-538 infected oak stands are always mainly formed and grown by sulfuric acid (Figs. 6h, 7g), but in modelling of non-infected 539 poplar, more than half of the formation and growth is due to HOM originating from isoprene (Fig. 8g), while HOM formed 540 from monoterpenes account for a large fraction of the predicted formation and growth in non-infested birch stands (Fig. 9l). 541 The concentration ratio of isoprene-to-monoterpene carbon is very high in non-infected oak and poplar stands and in 559 oak stands which are no longer exposed to herbivory (Figs. 6b, 7d, 8d), and it is therefore questionable whether particles will 560 be formed at all in the atmospheric boundary layer from these stands when they are not experiencing stress. Biotic stress gre atly 561 reduces R in all three cases. R is most significantly decreased to a minimum 10:00-16:00 median value of 0.004 in simulations 562 of gypsy moth infested oak stands (Fig. 6b), but the period with low R values is rather short. For example, R < 1 during only 563 moth infested oak stand (Fig. 12e). R is predicted to be close to 1, though never below 1, in simulations of both oak powdery 566 mildew infected oak stands and rust infected poplar stands. The duration where R is e.g. less than 22.5 is 39 days in a sever ely 567 mildew infected oak stand, 31 days in a moderately mildew infected oak stand, and 27 days in a severely rust infected poplar 568 stand (Fig. 12e). For comparison, R is never predicted to be less than 22.5 in a moderately infected poplar stand (Fig. 8d). 569 Even if new particles are not formed from oak powdery mildew or poplar rust infected stands in the boundary layer, then both 570 the potential to form new particles in the upper troposphere (Figs. 7f,g, 8f,h) and the potential to grow already existing particles, 571 which are formed in nearby stands and horizontally transported to the infected stands (Figs. 7g,h, 8g), are still predicted to be 572 greater than in our simulations of the correspondingly non-infected stands. R is not relevant in the case of mountain birch, 573 since this tree species does not emit isoprene constitutively, nor in response to herbivory stress by autumnal moth larvae (Yli - formed particles. (l) daily maxima diameter of the growing particle mode. "Moderately" and "severely" refer to 30 % and 80 618 %, respectively, of the leaf area that has been consumed by the end of the feeding period. 619 620

Estimating the reliability of our results 621
Since aerosol processes are very sensitive to changes in environmental conditions -conditions which can vary greatly, both 622 interannually, but also from day to day, we investigated the influence of a wide range of realistic and relevant environmental 623 conditions (Table D1 in Appendix D) on our model predictions (Figs. 10-11, D1-2 in Appendix D). Nine different sensitivity 624 tests (ST1-9) were conducted for all plant species and infections, where only one parameter was changed at a time (Table D1). 625 For these simulations, the default values listed in Table 2 were used, while the default maximum daily temperature at 626 Hohenpeissenberg and SMEAR I were assigned to 25 ºC and 20 ºC, respectively, and the default LAI for oak/poplar and birch 627 was assumed to be 5 m 2 m -2 and 2 m 2 m -2 , respectively. All aerosol parameters (formation and growth rates, diameter, number 628 of particles) show a similar response to changes in the considered environmental parameters, thus only the impact on the 629 number of newly formed particles (Figs. 10-11) and the rate at which new small particles grow (Figs. D1-2) is displayed. 630 As is also observed in nature, certain conditions suppress or prevent the formation of new particles, such as for 631 example a high condensation sink (Fig. 11d,i, (Figs. 10a-d,m-p, 11a-e,p-t). This is emphasised in very 642 severely infested mountain birch stands (e.g. 80 % defoliation), where the number of produced particles is always less than i n 643 its corresponding non-infested stand (Figs. 10m-p, 11p-t). 644 Sensitivity tests were also carried out in order to assess whether the simplifications made in the model are valid: (1) 645 As mentioned earlier (Sec. 2.4), we did not incorporate a full canopy environment in the model -an approach which has also 646 been taken by other investigators (e.g. Simpson et al., 1999Simpson et al., , 2012Bergström et al., 2014). In ST2 (Table D1,  μmol m -2 s -1 would still produce more new particles than its correspondingly non-infected stand at theoretically clear sky 651 conditions (Fig. 10b,f,j,n). A highly autumnal moth stressed mountain birch stand (80 % defoliation) would possibly produce 652 slightly more particles than a non-infested stand, if a full canopy environment would be considered. For example, the number 653 of produced particles is slightly higher in a birch stand experiencing a stress level of 80 % under 1000 μmol m -2 s -1 than a non-654 infested stand under 400 μmol m -2 s -1 (Fig. 10n). However, the LAI of mountain birch stands is usually rather low (Heiskanen,655 2006), making the difference in light environment between a non-infested and a highly defoliated stand small. Since mildew 656 and rust do not decrease the leaf area of their host, a different treatment of the light environment would not influence the 657 relative atmospheric importance of fungally infected oak and poplar vs their correspondingly non-infected stands (Fig. 10f,j). 658 (2) In ST3 (Table D1,  maximum temperatures throughout the growing season is assumed to be rather narrow (Fig. 4), this effect does not greatly 665 impact our results (Sec. 3.1), but it means that the number of particles produced at high temperatures ( Fig. 10c,g,k,o), and the 666 growth rate at which they are produced (Fig. D1c,g,k,o), are overestimated for both non-infected and stressed forests. 667 (3) The concentrations of ozone and OH were unaltered between simulations of non-infected forests and forests under 668 varying degrees of infection (Sec. 2.6), though in reality, the atmospheric oxidation capacity is controlled by changes in the 669 concentration of atmospheric trace gases, including VOCs. The total emission of VOCs from oak and poplar stands is greatly 670 dominated by isoprene, but the emission of isoprene decreases as a function of biotic stress severity (Figs. 5a, 7a, 8a). In 671 contrast, the emission of LOX, methyl salicylate, methanol, monoterpenes and sesquiterpenes increases as the level of stress 672 increases (Figs. 5c,e,g, 7a,b, 8a,b). The oxidation of isoprene, LOX, methyl salicylate and methanol is primarily driven by 673 reactions with OH, and also monoterpenes react with OH, which all leads to reductions in the concentration of OH (Table 3), 674 though e.g. ozonolysis of monoterpenes also produce OH, which thus counters part of the reduction. When considerin g the 675 reaction rates and emission rates of the considered VOCs in simulations of oak and poplar stands, the concentration of OH is 676 mainly controlled by changes in the emission of isoprene. Thus, we expect that the concentration of OH will increase as the 677 degree of stress increases, but even a strong shift in the concentration of OH, will not change the conclusion about the relative counted by an increase in the formation of oxidised organic compounds from oxidation of methyl salicylate at high levels of 684 OH, leading totally to higher predicted particle number concentrations (Fig. 11g). Considering the emissions from biotically 685 stressed and non-infested mountain birch, we estimate that the concentration of OH should stay largely the same, or potentially 686 decrease slightly at higher levels of infestation, which will enhance the oxidation of monoterpenes by ozone, which will lead 687 to a larger production of HOM and thereby a slightly higher predicted number of new particles (Fig. 11q). In the atmosphere, 688 the production of sulfuric acid is limited by the availability of OH, and it is therefore possible that the effects of changes in the 689 concentration of OH (Fig. 11b,q) and sulfuric acid (Fig. 11c,r), in herbivory stressed stands, on the absolute number of 690 predicted new particles, will cancel out or even lead to a stronger particle production than predicted. In case of oak powder y 691 mildew infected oak, the two effects will enhance each other and result in an even higher number of predicted particles. In 692 clean, low NOX environments, which we aimed to simulate, the concentration of ozone is largely unaffected by the ambient 693 concentration of isoprene (e.g. Jenkin et al., 2015). However, isoprene forms ozone progressively with an increased availability 694 of NO X (e.g. Jenkin and Clemitshaw, 2000). Higher ozone levels support enhanced formation of HOM, and thus aerosol 695 processes, but the production of HOM is also known to decrease as a function of increased NOX concentration (e.g. Ehn  this effect might cause our predicted aerosol processes (Sec. 3.1) to be overestimated, but since the ratio of isoprene -to-709 monoterpenes carbon concentration is much higher in non-infected oak and poplar stands than in the correspondingly stressed 710 stands (Figs. 6b, 7d, 8d), the overestimation is expected to be more pronounced in the non-infected stands (McFiggans et al., 711 2019). The difference in the atmospheric importance of non-infected and biotically stressed oak and poplar stands thereby 712 widens (Fig. 11e,j,o). 713 It is well known that the potential for foliage to emit VOCs depends on the age of the foliage: emerging and growing 714 foliage usually emits isoprene at reduced rates (e.g. Guenther et al., 1991Guenther et al., , 2012Goldstein et al., 1998;Petron et al., 2001) and 715 monoterpenes at enhanced rates (e.g. Guenther et al., 1991Guenther et al., , 2012 in herbivory stressed and non-infested oak forests insignificantly (Fig. B2). However, it would decrease the ratio of isoprene-721 to-monoterpenes carbon so significantly in gypsy moth infested oak stands, that the possible suppression of aerosol processes infected poplar stand would need to decline by 99.8 %, and from a rust infected poplar stand by at least 79 %, in order to attain 730 R≤1 (Fig. B4a). In order to reach R≤22.5, the upper limit at which new particle formation has been observed in the atmosphere 731 (Yu et al., 2014), the emission of isoprene from a non-infected poplar stand would need to decrease by ~95 %, whereas heavily 732 rust infected poplar forest would already be below this limit without considering an age dependent reduction of the emission 733 potential (Fig B4a).  height (a, e, i, m), light (b, f, j, n), temperature (c, g, k, o) and leaf area index (d, h, l, p) for non-infected 741 and infected oak (a-d, gypsy moth, e-h, powdery mildew), poplar (i-l) and birch (m-p) stands . Light (b, f, j, n) and temperature 742  ozone (a, f, k, p), OH (b, g, l, q) and sulfuric acid (c, h, m, r)

Implications and remaining issues to be explored 765
Our simulation results (Figs. 5-9) illustrate that biotic plant stresses are capable of substantially perturbing both the number 766 and size of atmospheric aerosol particles throughout a significant fraction of the year (summarised in Fig. 12). Considering 767 that we calculated daily new particle growth, our results point to the direction that induced plant emissions will subsequently 768 lead to more efficient CCN production in the atmosphere (Fig. 12), which will moreover affect cloud properties, such as cloud 769 albedo and lifetime (Twomey, 1977;Albrecht, 1989;Gryspeerdt et al., 2014;Rosenfeld et al., 2014). The amplitude of the 770 enhancement, however, depends strongly on the specific stressor and tree species which are attacked. 771 Naturally, both the duration of stress (Fig. 12e) and the predicted number (Fig. 12d) and size (Fig. 12c) of new 772 particles depend highly on our assumptions about e.g. when the fungi start to attack their host, how fast the fungi spread, 773 whether the larval eggs hatch simultaneously with budburst, how fast larval development occurs, and when senescence onsets 774 -all which depend strongly on environmental conditions. It is furthermore probable that emissions are also induced from 775 fungally infected leaves during senescence, which was not simulated here. The duration of stress can, thus, be significantly 776 longer than what is summarised in Fig. 12e, whereby also the post-defoliation period, in case of herbivory infestations, will be 777 shorter, and the atmospheric importance of the stresses stronger. 778 We have also shown that it can be more important to account for biotic plant stresses in models for local and regional 779 predictions of new particle formation and growth during the time of infestation/infection than significant variations in those recorded damage symptoms on trees growing in European forests (ICP Forests, 2020). To put that number in perspective, ~87 787 % of all investigated broadleaved trees (>50000) are yearly reported to have damage symptoms in European forests (ICP 788 Forests, 2020). Considering the duration of stress, and the predicted increase in the number and size of atmospheric aerosol 789 particles in response to fungal infections, together with the fact that especially oak powdery mildew is one of the most common 790 plant diseases, with e.g. ~9 % of pedunculate and sessile oak reported to be infected by powdery mildew in Europe yearly (ICP 791 Forests, 2020), our findings call for initiatives to account for fungal stress emission responses in numerical models in a robust 792 manner. Though larvae are present every summer, the population density of both gypsy and autumnal moths is cyclic, with 8- reported to not be defoliated at all or that less than 10 % of the trees' foliage have been defoliated by herbivores (ICP Forests, 802 2020). Since European gypsy moth is one of the major defoliating insects feeding on pedunculate oak 803 (https://www.cabi.org/isc/datasheet/31807#tohostsOrSpeciesAffected, last accessed 11th of June, 2021), it must be reasonable 804 to assume that a significant fraction of the reported defoliation is caused by feeding by gypsy moth larvae, and thus it is l ikely 805 that accounting for stress emissions in response to feeding by gypsy moth larval is important for realistic predictions of ne w 806 particle formation and growth. It is also likely that the reported defoliation which is not caused by gypsy moth larvae, but other 807 herbivores, also impacts SOA formation, though to which direction and with which amplitude is currently unknown. When 808 the larval density of autumnal moth in Fennoscandinavia is low, the level of defoliation usually remains less than 15 % (Bylund 809 1995), but during outbreak years, large areas (in the order of several thousands of square kilometres) can become either 810 completely or severely defoliated (e.g., Ruohomäki et al., 2000;Tenow 1975;Nikula 1993). Thus, considering the scale of 811 autumnal moth infestation combined with our findings about both the order of the increase in atmospheric new particle 812 formation and growth caused by autumnal moth infestations, and also the absolute number and size of newly formed particles, 813 it could seem that the importance of accounting for autumnal moth infestation in models to predict SOA formation is minor. 814 It should, however, be emphasised that in our simulations we did not accounted for delayed defense responses, which mountain 815 birches are known to possess (e.g., Kaitaniemi et al., 1998;Ruuhola et al., 2007), and which possibly cause elevated total 816 particle concentrations for few years after larval infestation (Ylivinkka et al., 2020). Also, we did not take multiple co-occurring 817 stresses into account, which are often the rule in nature and which generally enhances the already induced emission response differences between the averaged parameter in a stressed and stress-free forest stand of the same plant species type. Differences 832 and averages are considered based on the complete growing season, the period with stress, when the ratio of isoprene-to-833 monoterpenes carbon concentration is less than 1 or less than 22.5. Be aware that R is always zero in simulations of birch. I n 834 cases where R does not reach less than 1 or less than 22.5 in the atmosphere surrounding a non-infected forest stand, but it 835 does in the case of the corresponding stressed stand, it is assumed that the atmospheric parameter in the non-infected stand is 836 zero and hence the difference is given as the value of the stressed stand. The concentration differences of OxOrg, fo rmation 837 rates and number concentrations are calculated based on an average, for the period of interest, of the median values during 838 10:00-16:00 local time. "Severe" and "moderate" refer to that 80 % or 30 % of the total leaf area has been consumed or infec ted 839 by the end of the feeding/infection period, respectively. Southern Germany has been used as border conditions for simulations 840 of oak and poplar, while SMEAR I, Finnish Lapland, has been used for modelling of birch. 841 842 Unsurprisingly, we found that the predicted atmospheric importance of biotic plant stress highly depends on the specific 846 individual stressor and tree species which are attacked. Thus, the amount of newly formed particles was predicted to be up to 847 about one order of magnitude higher in a gypsy moth infested oak stand than in a non-infested oak stand. In comparison, the 848 number of new particles was simulated to be up to about a factor of 3, 4 and 5 higher in autumnal moth, oak powdery mildew 849 and poplar rust infected mountain birch, pedunculate oak a nd balsam poplar stands, respectively. We furthermore predicted 850 that the new particles will grow up to about 46, 28, 26 and 8 nm larger in an oak gypsy moth, poplar rust, autumnal moth and 851 oak powdery mildew infected stand, respectively, compared to their corresponding non-infected stands within one day. To our 852 knowledge, this study is the first to investigate the atmospheric impact of biotic plant stresses throughout a full growing s eason. 853 Our modelling results generally indicate that all the investigated plant stresses are capable of substantially perturbing 854 both the number and size of atmospheric aerosol particles, and it is thus likely that the induced emissions will subsequently 855 lead to more efficient CCN production in the atmosphere. We also showed that it can be more important to account for biotic 856 plant stresses in models for local and regional predictions of new particle formation and growth during the time of  Figure D2. Impact of changed boundary conditions on the growth rate of small particles in non-infected and biotically stressed 1851 forest stands. The subplots correspond to those in Fig. 11, except the subplots here display growth rate, and not number of 1852 particles. Thus we refer to Fig. 11 for further explanations. 1853