Comment on acp-2022-302

Abstract. Secondary organic aerosol (SOA) makes a sizable contribution to fine-particulate-matter (PM2.5) pollution, especially during high-PM episodes. Past studies of SOA evolution at the episode scale mainly rely on measurements of bulk SOA mass, with few studies probing individual SOA molecular tracers. In this study, we continuously monitored (at a bi-hourly resolution) SOA tracers specific to a few common volatile organic compound (VOC) precursors at a suburban site in Hong Kong for a 4-month period from the end of August to December 2020. The SOA molecules include tracers for SOA derived from biomass burning (BB) emissions, monoaromatics, naphthalene/methylnaphthalenes, and three biogenic VOCs (isoprene, monoterpene, and sesquiterpene). Generally, the SOA tracers showed regional characteristics for both anthropogenic and biogenic SOA as well as for the BB-derived SOA. This work focused on the seasonal variation and evolution characteristics of SOA tracers during 11 city-wide PM2.5 episodes, which are defined as periods with PM2.5 concentrations exceeding 35 µg m−3 at 3 or more of the 15 general air quality monitoring stations cross the city. Mass increment ratios (MIR), calculated as the ratio of the mass concentration prior to an episode to that during an episode, were examined for individual species during each episode. During most episodes, the SOA tracer concentrations were enhanced (i.e. MIR >1), and the maximum MIR values were in the range of 5.5–11.0 for SOA tracers of different precursors. Episodes on summer and fall days showed notably larger MIR values than those falling on winter days, indicating the higher importance of SOA to the formation of summer/fall PM2.5 episodes. Simultaneous monitoring of six tracers for isoprene SOA revealed the dominance of the low-NOx pathway in forming isoprene SOA in our study region. The multiple monoterpene SOA products suggested fresher SOA in winter, evidenced by the increased presence of the early-generation products. Thus, the current study has shown by example the precursor-specific SOA chemical evolution characteristics during PM2.5 episodes in different seasons. This study also suggests the necessity to apply high-time-resolution organic marker measurement at multiple sites in order to fully capture the spatial heterogeneity of haze pollution at the city scale.

For source apportionment by tracer method of secondary organic aerosol (SOA), the ratios of aerosol tracer to total SOA mass ( f SOA ) were determined during the oxidation of toluene, naphthalene, α-pinene, and isoprene by a series of laboratory experiments. Seven anthropogenic SOA tracers maintaining an aromatic ring structure, including 4-nitrophthalic acid and 3,5-dinitrosalicylic, were newly investigated as a chamber study together with 21 traditional aerosol tracers of anthropogenic and biogenic SOA. Experiments of the OH-initiated oxidation of anthropogenic VOCs were conducted as a function of the initial VOC/NO x ratio. No significant dependence on the VOC/NO x ratio was observed for the f SOA of 2,3-dihydroxy-4-oxopentanoic acid from toluene and phthalic acid from naphthalene, whereas the f SOA of nitroaromatic compounds such as 5-nitrosalicylic acid, 3,5-dinitrosalicylic acid, and 4-nitrophthalic acid increased with decreasing VOC/NO x ratio. Among seven newly evaluated anthropogenic SOA tracers, we concluded that 3,5-dinitronsalicylic can be used as a toluene SOA tracer, whereas 4-nitrophthalic acid can be used as a naphthalene SOA tracer. Results of kinetic calculations suggest that naphthalene is a major source of 5-nitrosalicylic acid under urban and rural conditions of previous observation studies. The ozonolysis and NO 3 -initiated oxidation of biogenic VOCs were investigated in addition to OH-initiated oxidation of biogenic VOCs. As for biogenic SOA tracers such as pinic acid and 2-methyltetrols, the f SOA value measured for the NO 3 -intiated reaction was lower than that of the OH-initiated oxidation and the f SOA value measured for the ozonolysis was not necessarily close to that of the OH-initiated oxidation. These results suggest that daytime and nighttime biogenic SOA formation events are interpreted by using different sets of the f SOA values. • Ratios of SOA tracer to aerosol mass were measured for aerosol source analysis. • Twenty-eight SOA tracers including new ones formed from four VOCs were measured. • Anthropogenic SOA tracers were studied as a function of initial VOC/NO x ratio. • Biogenic SOA tracers were studied by changing the oxidant of SOA formation.

Distribution characteristics of secondary organic aerosol tracers in PM2.5 in Jinzhong

Molecular markers of biomass burning, fungal spores and biogenic SOA in the Taklimakan desert aerosols

Hourly measurements of organic molecular markers in urban Shanghai, China: Observation of enhanced formation of secondary organic aerosol during particulate matter episodic periods

Abstract. In order to investigate the variability of the secondary organic aerosol (SOA) distributions and budget and provide a measure for the robustness of the conclusions on human induced changes of SOA, a global 3-dimensional chemistry transport model describing both the gas and the particulate phase chemistry of the troposphere has been applied. The response of the global budget of SOA to temperature and moisture changes as well as to biogenic emission changes over a decade (1984-1993) has been evaluated. The considered emissions of biogenic non-methane volatile organic compounds (VOC) are driven by temperature, light and vegetation. They vary between 756 and 810 Tg Cy-1 and are therefore about 5.5 times higher than the anthropogenic VOC emissions. All secondary aerosols (sulphuric, nitrates and organics) are computed on-line together with the aerosol associated water. Over the studied decade, the computed natural variations (8%) in the chemical SOA production from biogenic VOC oxidation equal the chemical SOA production from anthropogenic VOC oxidation. Maximum values are calculated for 1990 (warmer and drier) and minimum values for 1986 (colder and wetter). The SOA computed variability results from a 7% increase in biogenic VOC emissions from 1986 to 1990 combined with 8.5% and 6% increases in the wet and dry deposition of SOA and leads to about 11.5% increase in the SOA burden of biogenic origin. The present study also demonstrates the importance of the hydrological cycle in determining the built up and fate of SOA in the atmosphere. It also reveals the existence of significant positive and negative feedback mechanisms in the atmosphere responsible for the non linear relationship between emissions of biogenic VOC and SOA burden.

Abstract. The budget of atmospheric secondary organic aerosol (SOA) is very uncertain, with recent estimates suggesting a global source of between 12 and 1820 Tg (SOA) a−1. We used a dataset of aerosol mass spectrometer (AMS) observations from 34 different surface locations to evaluate the GLOMAP global chemical transport model. The standard model simulation (which included SOA from monoterpenes only) underpredicted organic aerosol (OA) observed by the AMS and had little skill reproducing the variability in the dataset. We simulated SOA formation from biogenic (monoterpenes and isoprene), lumped anthropogenic and lumped biomass burning volatile organic compounds (VOCs) and varied the SOA yield from each precursor source to produce the best overall match between model and observations. We assumed that SOA is essentially non-volatile and condenses irreversibly onto existing aerosol. Our best estimate of the SOA source is 140 Tg (SOA) a−1 but with a large uncertainty range which we estimate to be 50–380 Tg (SOA) a−1. We found the minimum in normalised mean error (NME) between model and the AMS dataset when we assumed a large SOA source (100 Tg (SOA) a−1) from sources that spatially matched anthropogenic pollution (which we term antropogenically controlled SOA). We used organic carbon observations compiled by Bahadur et al. (2009) to evaluate our estimated SOA sources. We found that the model with a large anthropogenic SOA source was the most consistent with these observations, however improvement over the model with a large biogenic SOA source (250 Tg (SOA) a−1) was small. We used a dataset of 14C observations from rural locations to evaluate our estimated SOA sources. We estimated a maximum of 10 Tg (SOA) a−1 (10 %) of the anthropogenically controlled SOA source could be from fossil (urban/industrial) sources. We suggest that an additional anthropogenic source is most likely due to an anthropogenic pollution enhancement of SOA formation from biogenic VOCs. Such an anthropogenically controlled SOA source would result in substantial climate forcing. We estimated a global mean aerosol direct effect of −0.26 ± 0.15 Wm−2 and indirect (cloud albedo) effect of −0.6+0.24−0.14 Wm−2 from anthropogenically controlled SOA. The biogenic and biomass SOA sources are not well constrained with this analysis due to the limited number of OA observations in regions and periods strongly impacted by these sources. To further improve the constraints by this method, additional OA observations are needed in the tropics and the Southern Hemisphere.

Abstract. Secondary organic aerosol (SOA) plays a significant role in atmospheric chemistry. However, little is known about the vertical profiles of SOA in the urban boundary layer (UBL). This knowledge gap constrains the SOA simulation in chemical transport models. Here, the aerosol samples were synchronously collected at 8, 120, and 260 m based on a 325 m meteorological tower in Beijing from 15 August to 10 September 2015. Strict emission controls were implemented during this period for the 2015 China Victory Day parade. Here, we observed that the total concentration of biogenic SOA tracers increased with height. The fraction of SOA from isoprene oxidation increased with height, whereas the fractions of SOA from monoterpenes and sesquiterpenes decreased, and 2,3-dihydroxy-4-oxopentanoic acid (DHOPA), a tracer of anthropogenic SOA from toluene oxidation, also increased with height. The complicated vertical profiles of SOA tracers highlighted the need to characterize SOA within the UBL. The mass concentration of estimated secondary organic carbon (SOC) ranged from 341 to 673 ng C m−3. The increase in the estimated SOC fractions from isoprene and toluene with height was found to be more related to regional transport, whereas the decrease in the estimated SOC from monoterpenes and sesquiterpene with height was more subject to local emissions. Emission controls during the parade reduced SOC by 4 %–35 %, with toluene SOC decreasing more than the other SOC. This study demonstrates that vertical distributions of SOA within the UBL are complex, and the vertical profiles of SOA concentrations and sources should be considered in field and modeling studies in the future.

Abstract. The largest global source of secondary organic aerosol (SOA) in the atmosphere is derived from the oxidation of biogenic emissions. Plant stressors associated with a changing environment can alter both the quantity and composition of the compounds that are emitted. Alterations to the biogenic volatile organic compound (BVOC) profile could impact the characteristics of the SOA formed from those emissions. This study investigated the impacts of one global change stressor, increased herbivory, on the composition of SOA derived from real plant emissions. Herbivory was simulated via application of methyl jasmonate (MeJA), a proxy compound. Experiments were repeated under pre- and post-treatment conditions for six different coniferous plant types. Volatile organic compounds (VOCs) emitted from the plants were oxidized to form SOA via dark ozone-initiated chemistry. The SOA chemical composition was measured using a Aerodyne high-resolution time-of-flight aerosol mass spectrometer (HR-AMS). The aerosol mass spectra of pre-treatment biogenic SOA from all plant types tended to be similar with correlations usually greater than or equal to 0.90. The presence of a stressor produced characteristic differences in the SOA mass spectra. Specifically, the following m/z were identified as a possible biogenic stress AMS marker with the corresponding HR ion(s) shown in parentheses: m/z 31 (CH3O+), m/z 58 (C2H2O2+, C3H6O+), m/z 29 (C2H5+), m/z 57 (C3H5O+), m/z 59 (C2H3O2+, C3H7O+), m/z 71 (C3H3O2+, C4H7O+), and m/z 83 (C5H7O+). The first aerosol mass spectrum of SOA generated from the oxidation of the plant stress hormone, MeJA, is also presented. Elemental analysis results demonstrated an O : C range of baseline biogenic SOA between 0.3 and 0.47. The O : C of standard MeJA SOA was 0.52. Results presented here could be used to help identify a biogenic plant stress marker in ambient data sets collected in forest environments.

In recent years, the Indian capital city of Delhi has been impacted by very high levels of air pollution, especially during winters. Comprehensive knowledge of the composition and sources of the organic aerosol (OA), which constitutes a substantial fraction of total particulate mass (PM) in Delhi, is central to formulating effective public health policies. Previous source apportionment studies in Delhi identified key sources of primary OA (POA) and showed that secondary OA (SOA) played a major role, but were unable to resolve specific SOA sources. We address the latter through the first field deployment of an extractive electrospray ionization time-of-flight mass spectrometer (EESI-TOF) in Delhi, together with a high-resolution aerosol mass spectrometer (AMS). Measurements were conducted during the winter of 2018/2019, and positive matrix factorization (PMF) was used separately on AMS and EESI-TOF datasets to apportion the sources of OA. AMS PMF analysis yielded three primary and two secondary factors which were attributed to hydrocarbon-like OA (HOA), biomass burning OA (BBOA-1 and 2), more oxidized oxygenated OA (MO-OOA), and less oxidized oxygenated OA (LO-OOA). On average, 40 % of the total OA mass was apportioned to the secondary factors. The SOA contribution to total OA mass varied greatly between daytime (76.8 %, 10:00–16:00 local time (LT)) and nighttime (31.0 %, 21:00–04:00 local time). The higher chemical resolution of EESI-TOF data allowed identification of individual SOA sources. The EESI-TOF PMF analysis in total yielded six factors, two of which were primary factors (primary biomass burning and cooking-related OA). The remaining four factors were predominantly of secondary origin: aromatic SOA, biogenic SOA, aged biomass burning SOA, and mixed urban SOA. Due to the uncertainties in the EESI-TOF ion sensitivities, mass concentrations of EESI-TOF SOA dominated factors were related to the total AMS SOA (i.e., MO-OOA + LO-OOA) by multi-linear regression (MLR). Aromatic SOA was the major SOA component during the day-time, with 55.2 % contribution to total SOA mass (42.4 % contribution to total OA). Its contribution to total SOA, however, decreased to 25.4 % (7.9 % of total OA) during night-time. This factor was attributed to the oxidation of light aromatic compounds emitted mostly from traffic. Biogenic SOA accounted for 18.4 % of total SOA mass (14.2 % of total OA) during day-time and 36.1 % of total SOA mass (11.2 % of total OA) during night-time. Aged biomass burning and mixed urban SOA accounted for 15.2 % and 11.0 % of total SOA mass ( 11.7 % and 8.5 % of total OA mass) during day-time respectively and 15.4 % and 22.9 % of total SOA mass (4.8 % and 7.1 % of total OA mass) during night-time, respectively. A simple dilution/partitioning model was applied on all EESI-TOF factors to estimate the fraction of observed day-time concentrations resulting from local photochemical production (SOA) or emissions (POA). Aromatic SOA, aged biomass burning, and mixed urban SOA were all found to be dominated by local photochemical production, likely from the oxidation of locally emitted VOCs. In contrast, biogenic SOA was related to the oxidation of diffuse regional emissions of isoprene and monoterpenes. The findings of this study show that in Delhi, the night-time high concentrations are caused by POA emissions led by traffic and biomass burning, and the daytime OA is dominated by SOA, with aromatic SOA accounting for the largest fraction. Because aromatic SOA is possibly more toxic than biogenic SOA and primary OA, its dominance during the day-time suggests an increased OA toxicity and health-related consequences for the general public.

<strong class="journal-contentHeaderColor">Abstract.</strong> Secondary organic aerosols (SOA) are an important component of atmospheric fine particulate matter (PM_2.5) in China, and elsewhere, with contributions from anthropogenic and biogenic volatile organic compounds (AVOC and BVOC) and semi- (SVOC) and intermediate volatility organic compounds (IVOC). Policy makers need to know which SOA precursors are important but accurate simulation of SOA magnitude and contributions remains uncertain. We reviewed SOA modelling studies in the past decade that have reported the relative contributions of different precursors to SOA concentration and the findings have many inconsistencies due to differing emission inventory methodologies/assumptions, air quality model (AQM) algorithms, and other aspects of study methodologies. We investigated the role of different AQM SOA algorithms by applying two commonly used models, CAMx and CMAQ, with consistent emission inventories to simulate SOA concentrations and contributions for July and November 2018 in China. Both models have a volatility basis set (VBS) SOA algorithm but with different parameters and treatments of SOA photochemical aging. BSOA (SOA produced from BVOC) is found to be more important over southern China whereas SOA generated from anthropogenic precursors is more prevalent in the North China Plain (NCP), Yangtze River Delta (YRD), Sichuan Basin and Central China. Both models indicate negligible SOA formation from SVOC emissions as compared to other precursors. In July when BVOC emissions are abundant, SOA is predominantly contributed by BSOA (except for NCP), followed by IVOC-SOA (i.e. SOA produced from IVOC) and ASOA (i.e. SOA produced from anthropogenic VOC). In contrast in November, IVOC becomes the leading SOA contributor for all selected regions except PRD, illustrating the important contribution of IVOC emissions to SOA formation. Therefore, future control policies should aim at reducing IVOC emissions as well as traditional VOC emissions. While both models generally agree in terms of the spatial distributions and seasonal variations of different SOA components, CMAQ tends to predict higher BSOA while CAMx generates higher ASOA concentrations. As a result, CMAQ results suggest that BSOA concentration is always higher than ASOA in November while CAMx emphasizes the importance of ASOA. Utilizing a conceptual model, we found that different treatment of SOA aging between the two models is a major cause of differences in simulated ASOA concentrations. The step-wise SOA aging scheme implemented in CAMx (based on gas-phase reactions with OH radical and similar to other models) exhibits a strong enhancement effect on simulated ASOA concentrations and this effect increases with the ambient OA concentrations. The CMAQ VBS implements a different SOA aging scheme that represents particle-phase oligomerization and has smaller impacts, or no impact, on total OA. A brief literature survey shows that different structure and/or parameters of the SOA aging schemes are being used in current models, which could greatly affect model simulations of OA in ways that are difficult to anticipate. Our results indicate that large uncertainties still exist in the simulation of SOA in current air quality models due to the aging schemes as well as uncertainties of the emission inventory. More sophisticated measurement data and/or chamber experiments are needed to better characterize SOA aging and constrain model parameterizations.

Modeling of secondary organic aerosols (SOA) based on two commonly used air quality models in China: Consistent S/IVOCs contribution but large differences in SOA aging

Secondary organic aerosols (SOA) produced in the atmosphere from sequential oxidation of biogenic or anthropogenic volatile organic compounds (VOC) represent a significant part of the atmospheric organic aerosol. Aerosol particles can act as cloud condensation nuclei or can be scavenged by cloud droplets, where organic carbon undergo chemical and biological transformations. Due to its high complexity, a nontargeted analysis by FT-ICR MS (Fourier-transform ion cyclotron resonance mass spectrometry) has been used to characterize the dissolved organic matter at a molecular level. SOA compounds have been detected in six aqueous samples collected in 2017 at the Puy de Dome station (PUY, France). SOA tracers, produced by VOC oxidation in environmental chambers or in ambient air and characterized in previous studies by mass spectrometry, were searched by FT-ICR MS in cloudwaters. Results clearly indicate the presence of oxidation products of isoprene, α- and β-pinene, and other monoterpenes and sesquiterpenes. I...

Diurnal evolution of organic aerosol over boreal and tropical forests The first research question of this thesis is: how do local surface forcings and large-scale meteorological forcings shape the evolution of organic aerosol over the boreal and tropical forest? This question is dealt with in Chapters 3 and 4 in case studies for the boreal and tropical forest, respectively. To answer this question a modeling tool (MXLCH-SOA) is developed, which represents land surface conditions and dynamical and chemical processes that influence the evolution of organic aerosol (OA) in a balanced way. The novelty of our approach is that it combines the dynamics of a convective boundary layer (BL) with a reduced gas-phase chemistry mechanism and a module for gas/particle-partitioning of semi-volatile organic species. The principles and governing equations of this modeling tool are described in Chapter 2 and in the subsequent chapters the simplified chemical reaction schemes are presented to calculate secondary organic aerosol (SOA) formation from terpenes (Chapter 3 and 4) and from isoprene (Chapter 4). Despite its simplicity, MXLCH-SOA is able to satisfactorily reproduce the main observed characteristics of dynamics, gas-phase chemistry and gas/particle partitioning for the two studied forest ecosystems and it enables us to explain the temporal variability of the concentrations of organic aerosol and its precursors as a function of the various processes. In short, the results show that the diurnal evolution of organic aerosol in a boreal and a tropical forest is the net result of land surface conditions, boundary layer dynamics, chemical transformations and gas/particle partitioning. In the case study for the boreal forest, the entrainment term of the background OA dominates the OA tendency, while in the tropical forest case it is the interplay of several local and large scale processes that shape the diurnal evolution of OA. A sensitivity analysis for the boreal forest case further shows that the OA concentration is sensitive to both volatile organic compound (VOC) emissions and the partitioning of the surface energy budget into a latent and a sensible heat flux. We have identified two regimes, based on which of the two studied land surface drivers dominates: one in which OA is mainly driven by SOA formation from the emitted VOCs and another in which dilution due to entrainment, as driven by the surface energy fluxes, determines the OA concentration. A background OA to fresh SOA ratio is introduced to facilitate the interpretation of this analysis and is used to quantify the contributions of both fresh and background components to the total OA concentration. One main difference between the two case studies is that in the boreal forest entrainment appears to dominate the diurnal cycle, which leads to a decreasing OA concentration during the day, while in the tropical forest the formation of SOA from both isoprene and terpenes leads to increasing OA concentrations during day time. The MXLCH-SOA framework therefore shows the need to represent all these biochemical and physical processes simultaneously in order to understand the diurnal evolution of OA. As the boundary layer dynamics-chemistry system is not a closed system, it is necessary to further study the influence of external forcings on the diurnal evolution of OA, besides the surface forcings. Two types of large-scale meteorological forcings and their effects on OA evolution through their impact on BL dynamics have been studied: subsidence due to the presence of a high pressure system and advection of relatively cool air. In Chapter 3 a theoretical sensitivity analysis is given of OA evolution to subsidence, which is applied to the tropical forest case study in Chapter 4. Subsidence has a rather counter-intuitive effect on OA concentrations: even though it suppresses the growth of the BL and consequently decreases the mixing volume for chemical species, it leads to decreased OA concentrations. The reason for this is that entrainment is strongly enhanced in case of subsidence due to thermodynamic effects, which results in a stronger dilution of OA. This knowledge is applied in the case study for the tropical forest in Chapter 4, since results from a large-scale model show subsiding air motions over the measurement site and surroundings at Borneo. In addition to subsidence, the advection of cool air is needed to reproduce the observed boundary layer dynamics at Borneo: only if subsidence and advection of relatively cool air are accounted for, the observed low BL height can be reconciled with the large observed surface sensible and latent heat flux. This cool air suppresses BL growth and entrainment. Consequently, the aerosol is trapped in a shallower layer, which leads to an increased concentration compared to the case without advection of cooler air. In conclusion, the large-scale meteorological forcings subsidence and advection of cool air have opposing effects on the diurnal evolution of OA, even though both suppress BL growth. These findings show the utility of our method in identifying effects that should be accounted for in large-scale chemistry transport models. The second research question is whether recently discovered pathways of isoprene chemistry are the key to closing the gap between measured and modeled organic aerosol concentrations in tropical forests and other high isoprene environments. To address this issue, several mechanisms which may affect SOA formation from isoprene are implemented in MXLCH-SOA and discussed in Chapter 4. The hydroxyl radical (OH), the main oxidant of isoprene, is thought to be regenerated in the oxidation of isoprene. We find that for the tropical forest case study, we cannot reconcile the modeled concentrations of VOCs, OH and OA with their observed concentrations and fluxes both for cases with and without OH recycling. Therefore, we conclude that the issue of recycling of the OH radical in the oxidation of isoprene has to be solved before its effect on SOA formation can be determined. The formation of SOA from isoprene involves multiple generations of oxidation and due to this complex chemistry there is no single mechanism which can explain SOA formation from isoprene under all conditions. To gain understanding in this issue, we have implemented different pathways through which isoprene SOA is known to form, although we do not explicitly account for the detailed isoprene oxidation chain. A central aspect of this branching approach is whether the isoprene peroxy radical chemistry follows the low- or the high-NOx pathway. We find that the latter channel dominates in our case study. For SOA formed through the high-NOx channel, we further account for the effect of the NO2/NO ratio on SOA yields. In the presented case study this has little effect as this ratio is low, it but could be more important in regions with slower photochemistry or higher emissions of anthropogenic pollution. In the low-NOx regime, isoprene epoxides (IEPOX) are important intermediate gas-phase species in the formation of isoprene SOA. Even though the low-NOx pathway is only a minor one here, the amount of IEPOX SOA formed is likely substantial, although a better understanding of the exact mechanisms for its formation is needed to confirm this. However, as in previous studies we systematically underestimate the organic aerosol concentration in a tropical forest even though we incorporate the state-of-the-art knowledge on isoprene SOA formation in MXLCH-SOA. Nevertheless, we advocate accounting for NOx regime specific chemical pathways when modeling isoprene SOA formation. As this field is rapidly evolving in terms of the development of new measurement techniques and the discovery of chemical mechanisms, we strongly recommend the intensive use of our modeling system to gain further understanding of the diurnal variability of OA and for testing new hypotheses under atmospheric conditions. Satellite observations of cloud droplet concentration over the boreal forest The final objective of this thesis is to understand how aerosols and meteorological factors influence cloud droplet concentration over the boreal forest. This is a first step in translating the process understanding such as addressed in the previous chapters to larger spatio-temporal scales. Since this objective considers different temporal and spatial scales, a different method is applied in Chapter 5 than in the foregoing chapters. Observations of cloud properties by the MODIS instrument onboard the Terra satellite are combined with a model that contains the microphysics and thermodynamics of a single-layered water cloud to obtain a seasonal cycle of cloud droplet number concentrations, averaged over 9 years of data. This seasonal cycle in cloud droplet concentration is compared with aerosol concentrations at the surface and meteorological fields from ECMWF reanalysis. We find that the cloud droplet number concentration is related to the potential temperature gradient in the boundary layer, a measure for the strength of convection, while it shows no clear relationship with the cloud active aerosol concentration at the surface. From this we conclude that the convective transport of the aerosols from the surface to cloud base is the limiting factor for their activation as cloud droplets. However, convection will also influence the formation of clouds from a thermodynamic perspective. Therefore, it is likely that convection, as driven by land surface conditions, regulates both transport of aerosols to cloud base and the height of the cloud base, defined as the height at which water vapor reaches its saturation pressure. To ultimately understand the effect of the boreal forest on cloud properties, the effects of aerosols and thermodynamics should be studied simultaneously.

Secondary organic aerosol (SOA) is a significant component of fine particulate matter, and it has increased during past drought periods in the U.S. Here, we use the Community Multiscale Air Quality (CMAQ) model to characterize the complex effects of drought on SOA through a case study comparing a drought period (June 2011) and a wet period (June 2013) over the southeast U.S. The model simulates a 68% (1.7 μg/m3) higher SOA concentration at the surface during drought and attributes 98% of this increase to biogenic SOA. Through model sensitivity simulations, the SOA increase associated with drought is attributed to 54% from accelerated gas-phase reactions oxidizing volatile organic compounds (VOCs) to SOA, 45% from higher emissions of biogenic VOCs, 18% from enhanced acid-catalyzed production of isoprene SOA in aerosol water due to changing sulfate, 3% from enhanced in-cloud aqueous phase chemistry. Because the higher SOA levels overwhelm the reduced precipitation, there is an increase in wet deposition flux in the drought month which offsets 20% of the total SOA increase. If anthropogenic emissions are held constant, anthropogenic SOA is 51% higher during drought, highlighting the importance of meteorological impacts on chemistry.