**2. Emission fluxes of monoterpenes**

## **2.1. Chemical structure of terpenes**

Monoterpenes are organic compounds of biogenic origin whose structure may be divided into isoprene units. The more volatile mono- (C10) and sesquiterpenes (C15) are emitted in large quantities from the vegetation. The chemists always regard terpenes as alkenes (e.g. βpinene, camphene), cycloalkenes (e.g. α-pinene, Δ3-carene), and dienes (e.g. β-phellandrene, α-terpinene) or as a combination of these classes (e.g. limonene, ocimene). Figure 1 shows the chemical structure of monoterpenes. Of the 14 most commonly occurring monoterpenes (α-pinene, β-pinene, Δ(3)-carene, d-limonene, camphene, myrcene, α-terpinene, βphellandrene, sabinene, ρ-cymene, ocimene, α-thujene, terpinolene, and γ-terpinene), the first six are usually found to be most abundant.

Production of Secondary Organic Aerosol from Multiphase Monoterpenes 365

Natural sources of VOC emissions to the atmosphere also include marine and fresh water, soil and sediments, microbial decomposition of organic material, geological hydrocarbon reservoirs, plant foliage and woody material. In addition, there are human influenced natural sources from harvesting or burning plant material. We have estimated emissions o f VOC only from oceans and plant foliage. VOC emissions from other sources are very uncertain but probably represent less than a few percent of total global emissions

Estimated monoterpene emissions are dominated by α-pinene (35~70% of total) and βpinene (15~40%). Secondary compounds of significance are *d-*limonene (5~20%) and βmyrcene (2~20%). Monoterpene emissions in this region are largely controlled by *Liquidambar styraci*y*ua*, the southern pine group which includes *Pinus taeda, echinata, elliotti, palustris, virginiana*, and to a lesser extent species in the *Acer* (maple), *Magnolia, and Carya*  (hickory) genera. The Pacific Coast forests and sparse coniferous forests of the Nevada Great Basin also emit primarily α-pinene. However, in eastern Montana, the western Dakotas, the Rocky Mountain Front Range of Colorado and Wyoming, the Columbia Plateau of Eastern Oregon and Washington, the Sierra Nevada Range of California, and parts of the western Great Basin, β-pinene and Δ3-carene emissions equal or exceed those of α-pinene, due to the abundance of *Pinus contorta, monticola, ponderosa*, and their subspecies. These regions and hourly summer total monoterpene flux from forests at 30oC are illustrated in Figure 2. The regions dominated by coniferous forests have the highest monoterpene flux estimates. The northern coniferous and Alaskan forests are interesting in that less than 25% of estimated monoterpene emissions are accounted for by α-pinene. The west coast, interior west, and the southern pine regions of the Piedmont and coastal southeast also have estimated fluxes which exceed 200 μg carbon m-2 h-1. α- pinene composes over half of the emissions from these regions except for parts of the western US. Northern mixed, midwestern, Appalachian, and Ozarks forests have a higher hardwood component and have emission rates of approximately 150 μg carbon m-2 h-1. The great plains and agricultural midwest have sparsely scattered woodlands and low emission rates (100μg carbon m-2 h-1). These rates are rather low in comparison to those of isoprene which can exceed 10,000μg carbon m-2 h-1 from oak forests under these conditions (Geron et al., 1994; Guenther et al., 1994). Uncertainties for fluxes of these individual terpenes are difficult to estimate given analytical difficulties and gaps in knowledge of basal emission factors (EFs) and environmental/physiological controls. Current models (Guenther et al., 1994) assume ±50% uncertainty in basal EFs and roughly ±40% uncertainty in biomass and landuse accuracy (Lamb et al., 1987). An assessment of the uncertainty in monoterpene composition (MC) indicates that ±30-50% is a reasonable estimate for the six major compounds, and likely more for the eight minor compounds. This results in estimates of roughly ±150-200% for uncertainty in fluxes of individual compounds at 30oC. Canopy environment models and temperature correction algorithms can add 50-100% uncertainty to model estimates. The estimates shown here can be adjusted to ambient temperature using the exponential

(Zimmerman, 1979; Lamb et al, 1987; Janson, 1992; Eichstaedter et al., 1992).

**2.3. Emission fluxes** 

**Figure 1.** The chemical structures and names of monoterpenes

## **2.2. Biogenic sources**

The biogenic volatile organic compounds (BVOCs) emitted from plants are a myriad of hydrocarbons and oxygenated and other organic compounds. These emissions occur during various stages of plant growth, plant injury and plant decay, and they are a significant source of volatile organic compounds (VOCs) in the atmosphere. Globally, emissions from BVOCs account for approximately 86% of the total of VOCs emitted while anthropogenic VOCs make up the rest (Guenther et al., 1995). BVOC emissions from trees and woody shrubs have been extensively studied (Scholes et al., 2003). The dominant compounds emitted under unperturbed conditions are isoprene, monoterpenes, sesquiterpenes and methanol. There are episodic emissions of C6 aldehydes, esters and alcohols associated with plant injuries, and episodic emissions of ethanol and acetaldehyde associated with waterlogging (Scholes et al., 2003).

Natural sources of VOC emissions to the atmosphere also include marine and fresh water, soil and sediments, microbial decomposition of organic material, geological hydrocarbon reservoirs, plant foliage and woody material. In addition, there are human influenced natural sources from harvesting or burning plant material. We have estimated emissions o f VOC only from oceans and plant foliage. VOC emissions from other sources are very uncertain but probably represent less than a few percent of total global emissions (Zimmerman, 1979; Lamb et al, 1987; Janson, 1992; Eichstaedter et al., 1992).

## **2.3. Emission fluxes**

364 Atmospheric Aerosols – Regional Characteristics – Chemistry and Physics

Monoterpenes are organic compounds of biogenic origin whose structure may be divided into isoprene units. The more volatile mono- (C10) and sesquiterpenes (C15) are emitted in large quantities from the vegetation. The chemists always regard terpenes as alkenes (e.g. βpinene, camphene), cycloalkenes (e.g. α-pinene, Δ3-carene), and dienes (e.g. β-phellandrene, α-terpinene) or as a combination of these classes (e.g. limonene, ocimene). Figure 1 shows the chemical structure of monoterpenes. Of the 14 most commonly occurring monoterpenes (α-pinene, β-pinene, Δ(3)-carene, d-limonene, camphene, myrcene, α-terpinene, βphellandrene, sabinene, ρ-cymene, ocimene, α-thujene, terpinolene, and γ-terpinene), the

The biogenic volatile organic compounds (BVOCs) emitted from plants are a myriad of hydrocarbons and oxygenated and other organic compounds. These emissions occur during various stages of plant growth, plant injury and plant decay, and they are a significant source of volatile organic compounds (VOCs) in the atmosphere. Globally, emissions from BVOCs account for approximately 86% of the total of VOCs emitted while anthropogenic VOCs make up the rest (Guenther et al., 1995). BVOC emissions from trees and woody shrubs have been extensively studied (Scholes et al., 2003). The dominant compounds emitted under unperturbed conditions are isoprene, monoterpenes, sesquiterpenes and methanol. There are episodic emissions of C6 aldehydes, esters and alcohols associated with plant injuries, and episodic emissions of ethanol and acetaldehyde associated with

**2. Emission fluxes of monoterpenes** 

first six are usually found to be most abundant.

**Figure 1.** The chemical structures and names of monoterpenes

**2.2. Biogenic sources** 

waterlogging (Scholes et al., 2003).

**2.1. Chemical structure of terpenes** 

Estimated monoterpene emissions are dominated by α-pinene (35~70% of total) and βpinene (15~40%). Secondary compounds of significance are *d-*limonene (5~20%) and βmyrcene (2~20%). Monoterpene emissions in this region are largely controlled by *Liquidambar styraci*y*ua*, the southern pine group which includes *Pinus taeda, echinata, elliotti, palustris, virginiana*, and to a lesser extent species in the *Acer* (maple), *Magnolia, and Carya*  (hickory) genera. The Pacific Coast forests and sparse coniferous forests of the Nevada Great Basin also emit primarily α-pinene. However, in eastern Montana, the western Dakotas, the Rocky Mountain Front Range of Colorado and Wyoming, the Columbia Plateau of Eastern Oregon and Washington, the Sierra Nevada Range of California, and parts of the western Great Basin, β-pinene and Δ3-carene emissions equal or exceed those of α-pinene, due to the abundance of *Pinus contorta, monticola, ponderosa*, and their subspecies. These regions and hourly summer total monoterpene flux from forests at 30oC are illustrated in Figure 2. The regions dominated by coniferous forests have the highest monoterpene flux estimates. The northern coniferous and Alaskan forests are interesting in that less than 25% of estimated monoterpene emissions are accounted for by α-pinene. The west coast, interior west, and the southern pine regions of the Piedmont and coastal southeast also have estimated fluxes which exceed 200 μg carbon m-2 h-1. α- pinene composes over half of the emissions from these regions except for parts of the western US. Northern mixed, midwestern, Appalachian, and Ozarks forests have a higher hardwood component and have emission rates of approximately 150 μg carbon m-2 h-1. The great plains and agricultural midwest have sparsely scattered woodlands and low emission rates (100μg carbon m-2 h-1). These rates are rather low in comparison to those of isoprene which can exceed 10,000μg carbon m-2 h-1 from oak forests under these conditions (Geron et al., 1994; Guenther et al., 1994). Uncertainties for fluxes of these individual terpenes are difficult to estimate given analytical difficulties and gaps in knowledge of basal emission factors (EFs) and environmental/physiological controls. Current models (Guenther et al., 1994) assume ±50% uncertainty in basal EFs and roughly ±40% uncertainty in biomass and landuse accuracy (Lamb et al., 1987). An assessment of the uncertainty in monoterpene composition (MC) indicates that ±30-50% is a reasonable estimate for the six major compounds, and likely more for the eight minor compounds. This results in estimates of roughly ±150-200% for uncertainty in fluxes of individual compounds at 30oC. Canopy environment models and temperature correction algorithms can add 50-100% uncertainty to model estimates. The estimates shown here can be adjusted to ambient temperature using the exponential equations previously published (Guenther et al., 1993). However, the trees species composition and resulting flux estimates can vary significantly within these regions.

Production of Secondary Organic Aerosol from Multiphase Monoterpenes 367

as defensive compounds; young leaves are most at risk from pests and pathogens so they have the highest concentrations of defensive compounds (Lerdau et al. 1994). The manner in which monoterpenes and several of the oxygenated hydrocarbons (e.g., methyl chavicol) are stored within leaves and wood leads to a large effect of tissue damage upon flux rate. These compounds are stored in specialized ducts, canals, or cavities. When herbivores partially consume tissue and expose these cavities to the atmosphere, flux rates increase by several orders of magnitude. This increase stems from the change in the resistance term in Fick's

**Figure 3.** Variation of monoterpene emissions as function of temperature. The line represents the best

Due to natural variability and analytical difficulties, monoterpene emission rates and composition are subject to considerable uncertainty. For instance, in one study 20 monoterpenes were identified using vegetation enclosures, but only eight were found in ambient air in the proximity of similar vegetation (Khalil and Rasmussen, 1992). Rough handling of vegetation during enclosure sampling has been suspected to result in artificially high emission rates (Juuti et al., 1990; Guenther et al., 1994). Summertime *Pinus taeda*  monoterpene emissions were found to be 5~20 times higher following "grabbing" of foliage

fit to the data points. The emission rates are expressed per unit dry biomass weight.

**2.5. Temporal and spatial distribution** 

law of diffusion describing the gas flux (Lerdau 1991).

**Figure 2.** Regions and regional average total monoterpene flux (μg carbon m-2 h-1). The numbers indicate region number follow by the average regional flux at 30oC.

## **2.4. Emission factors**

The best-known environmental control on biogenic hydrocarbon emissions is temperature. For compounds such as monoterpenes that are released from resin ducts or glands, temperature is the dominant control factor (Figure 3). The increasing vapor pressure of these compounds with temperature explains the temperature response of emissions. In contrast, isoprene and some plant monoterpene emissions do not come from preexisting pools. In these cases the temperature response of emission is caused by the impact of temperature on the underlying metabolism (Monson et al. 1994). This effect can be described by calculating an activation energy.

Some monoterpene emissions are also dependent upon light. The light dependence is often similar to that of photosynthesis. Water and nitrogen content affect hydrocarbon emission primarily through their influences on enzyme activity of leaves. Another critical factor controlling hydrocarbon fluxes from leaves is the leaf developmental state. Monoterpeneemitting foliage shows its highest emission rates when the leaves are youngest (Lerdau 1993). This high emission rate from young leaves results from the role monoterpenes serve as defensive compounds; young leaves are most at risk from pests and pathogens so they have the highest concentrations of defensive compounds (Lerdau et al. 1994). The manner in which monoterpenes and several of the oxygenated hydrocarbons (e.g., methyl chavicol) are stored within leaves and wood leads to a large effect of tissue damage upon flux rate. These compounds are stored in specialized ducts, canals, or cavities. When herbivores partially consume tissue and expose these cavities to the atmosphere, flux rates increase by several orders of magnitude. This increase stems from the change in the resistance term in Fick's law of diffusion describing the gas flux (Lerdau 1991).

**Figure 3.** Variation of monoterpene emissions as function of temperature. The line represents the best fit to the data points. The emission rates are expressed per unit dry biomass weight.

### **2.5. Temporal and spatial distribution**

366 Atmospheric Aerosols – Regional Characteristics – Chemistry and Physics

equations previously published (Guenther et al., 1993). However, the trees species

composition and resulting flux estimates can vary significantly within these regions.

**Figure 2.** Regions and regional average total monoterpene flux (μg carbon m-2 h-1). The numbers

The best-known environmental control on biogenic hydrocarbon emissions is temperature. For compounds such as monoterpenes that are released from resin ducts or glands, temperature is the dominant control factor (Figure 3). The increasing vapor pressure of these compounds with temperature explains the temperature response of emissions. In contrast, isoprene and some plant monoterpene emissions do not come from preexisting pools. In these cases the temperature response of emission is caused by the impact of temperature on the underlying metabolism (Monson et al. 1994). This effect can be described by calculating

Some monoterpene emissions are also dependent upon light. The light dependence is often similar to that of photosynthesis. Water and nitrogen content affect hydrocarbon emission primarily through their influences on enzyme activity of leaves. Another critical factor controlling hydrocarbon fluxes from leaves is the leaf developmental state. Monoterpeneemitting foliage shows its highest emission rates when the leaves are youngest (Lerdau 1993). This high emission rate from young leaves results from the role monoterpenes serve

indicate region number follow by the average regional flux at 30oC.

**2.4. Emission factors** 

an activation energy.

Due to natural variability and analytical difficulties, monoterpene emission rates and composition are subject to considerable uncertainty. For instance, in one study 20 monoterpenes were identified using vegetation enclosures, but only eight were found in ambient air in the proximity of similar vegetation (Khalil and Rasmussen, 1992). Rough handling of vegetation during enclosure sampling has been suspected to result in artificially high emission rates (Juuti et al., 1990; Guenther et al., 1994). Summertime *Pinus taeda*  monoterpene emissions were found to be 5~20 times higher following "grabbing" of foliage

compared to normal experiments when rough handling was minimized (Kim et al., 1995). However, there was no effect of rough handling in the late fall. It was concluded that a film of monoterpene compounds was present on the outer surface of the foliage during summer months, but not at other times of the year. Sampling of monoterpenes from *Picea marianna*  seed cones in situ versus ex situ was found to drastically affect both the emission rate as well as the monoterpene composition (Turgeon et al., 1998). Temporal and spatial factors can affect MC of a given tree species. Emissions and needle oil concentrations of Δ3-carene were lower relative to other monoterpenes in the summer but were substantially higher in the spring and fall (Janson, 1993; Lerdau et al., 1995). It was concluded that the high springtime emissions ofΔ3-carene from *Pinus ponderosa* were due to the MC of the oleoresin in that species (Flyckt, 1979). *Picea sitchensis* (Bong.) basal emission rate (in μg carbon g-1 h-1 at leaf temperature =30oC, referred to as emission factor or EF) and MC were found to change somewhat with the season (Street et al., 1996). Conversely, the oil composition of *Picea glauca*  leaves and twigs remained nearly constant from summer through winter, while the oil composition of buds changed significantly during fall and winter (von Rudloff, 1972). However, it seems more typical that foliage MC remains fairly stable during most of the growing season (Hall and Langenheim, 1986; Winer et al., 1992; Street et al., 1997b; Bertin et al., 1997). This is confirmed by measurements in ambient air (Roberts et al., 1985). Diurnal variation has not been examined extensively, but was found to be negligible in *Juniperus scopulorum* (Adams and Hagerman, 1976). Likewise, little diurnal variation was found in the monoterpene composition of ambient (near canopy) air near forests in Colorado (Roberts et al., 1985), where nighttime versus daytime relative abundance of β-pinene, α-pinene, Δ3 carene, camphene, and *d*-limonene changed by 0~4%, although nighttime total monoterpene concentration was over a factor of 2 greater due to lower dispersion. Greater seasonal and diurnal variability in light-dependent emissions of ocimene, linalool, and 1,8-cineole was found relative to the more temperature-dependent emissions of α-pinene and *d*-limonene, which varied little temporally from *Pinus pinea* (Staudt et al., 1997). Tree age effects have also been found for MC within this species (Adams and Hagerman, 1976) as well as for *Eucalyptus* (Street et al., 1997a) and *Picea sitchensis* (Street et al., 1996). Basal EFs were also found to decrease with tree age in these latter three studies and in *Pinus elliotti* (Kim et al., 1995). An increase in basal EFs and changes in MC of emissions following wetting of foliage have been noted (Janson, 1993; Lamb et al., 1984). Humidity has also been found to increase monoterpene emission rates at the leaf (Guenther et al., 1991) and canopy (Schade et al., 1999) levels.

Production of Secondary Organic Aerosol from Multiphase Monoterpenes 369

present in high concentrations in near surface air and are climatically active in the global

Gas-phase monoterpenes readily react with the major atmospheric oxidants such as ozone (O3), hydroxyl radical (OH), and nitrate radical (NO3). During the day, their concentrations are controlled by OH and O3, and at night they are controlled by NO3, with monoterpene lifetimes on the order of a few hours in both cased. Regardless of the initial oxidant, gasphase oxidation of monoterpenes results in a wide variety of polyfunctional carboxylic acids, ketones, aldehydes, peroxides, and alcohols (Kavouras et al., 1998; Yu et al., 1999; Claeys et al., 2007; Presto et al., 2005; Gao et al., 2004; Dalton et al., 2005; Glasius et al., 1999; Hakola et al., 1994; Jaoui et al., 2005; Leungsakul et al., 2005 ). Many of these species have sufficiently low vapor pressure to partition into pre-existing particulate matter. In addition, monoterpenes can partition into aqueous particles or cloud droplets by wet deposition and undergo oxidation via aqueous chemistry, with droplets subsequently drying out into

SOAs are formed by chemical reactions from the condensation and gas/particle partitioning of semivolatile products of hydrocarbon oxidation by OH, O3 and NO3. It is currently believed that approximately 85-90% of SOAs are produced by oxidation of biogenic emissions, which corresponds to 12.2 Tg SOA/yr and 1150 TgC/yr (Kanakidou et al., 2005; Stavrakou et al.,2009; Tsigaridis et al., 2007). Some authors suggest that 91% of SOAs are considered to be caused by O3 and OH oxidation (Chung et al., 2002), while others consider that ozonolysis dominates in SOA production compared to OH and NOx oxidation (Kanakidou et al., 2005). 78% of SOAs are specifically products of monoterpene oxidation (Chung et al., 2002). Monoterpenes *α*-pinene and b-pinene are expected to be the major

A number of laboratory experiments have been carried out to study SOA formation by oxidation of monoterpenes (e.g. α-pinene, β-pinene, d-limonene, Δ3-carene, sabinene) with NOx, O3 and OH (Lee et al., 2004; Jonsson et al., 2008; Northcross and Jang, 2007; Czoschke et al., 2003; Spittler et al., 2003; Colville et al., 2004; Seinfeld et al., 2001). The formation of SOA in the presence of NOx has been studied for several monoterpenes: α-pinene, β-pinene, limonene, Δ3-carene, myrcene, β-ocimene, sabinene, α-terpinene, α-terpinolene (Pandis et al., 1991; Hoffmann et al., 1997; Griffin et al., 1999; Klinedinst and Currie, 1999; Presto et al., 2005; Lee et al., 2006; Zhang et al., 2006). The complexity of the dependence of NOx concentration on monoterpene SOA yields was first noted by Pandis et al. (1991) who found that the SOA yield from the photooxidation of α-pinene increased with increasing VOC/NOx ratio and maximized at 8% for 10–20 ppbC:ppb NOx. The SOA yield was found to decrease for VOC/NOx ratios greater than 20. More recently, Presto et al. (2005) showed that SOA yields from ozonolysis of α-pinene are lower under high- NOx (<15 ppbC:ppb NOx) than low-NOx conditions. The reduction of the SOA yields was attributed to the formation of higher volatility products under high NOx, including evidence of nitrate-

sources of SOAs (Kleindienst et al., 2007; Yu et al., 1999).

atmosphere.

organic particles.

**3.1. Chamber experiments** 

### **3. Secondary organic aerosol formation**

Most of monoterpenes are photochemically reactive in the atmosphere because of their alkenyl bonds and other properties of their structure (Seinfeld and Pandis, 1998). Two key products of the photochemical reactions of these compounds in the atmosphere are gasphase oxidants (including ozone) and secondary organic aerosols. These gas-phase oxidants and secondary organic aerosol can have significant effects on human health when present in high concentrations in near surface air and are climatically active in the global atmosphere.

Gas-phase monoterpenes readily react with the major atmospheric oxidants such as ozone (O3), hydroxyl radical (OH), and nitrate radical (NO3). During the day, their concentrations are controlled by OH and O3, and at night they are controlled by NO3, with monoterpene lifetimes on the order of a few hours in both cased. Regardless of the initial oxidant, gasphase oxidation of monoterpenes results in a wide variety of polyfunctional carboxylic acids, ketones, aldehydes, peroxides, and alcohols (Kavouras et al., 1998; Yu et al., 1999; Claeys et al., 2007; Presto et al., 2005; Gao et al., 2004; Dalton et al., 2005; Glasius et al., 1999; Hakola et al., 1994; Jaoui et al., 2005; Leungsakul et al., 2005 ). Many of these species have sufficiently low vapor pressure to partition into pre-existing particulate matter. In addition, monoterpenes can partition into aqueous particles or cloud droplets by wet deposition and undergo oxidation via aqueous chemistry, with droplets subsequently drying out into organic particles.

SOAs are formed by chemical reactions from the condensation and gas/particle partitioning of semivolatile products of hydrocarbon oxidation by OH, O3 and NO3. It is currently believed that approximately 85-90% of SOAs are produced by oxidation of biogenic emissions, which corresponds to 12.2 Tg SOA/yr and 1150 TgC/yr (Kanakidou et al., 2005; Stavrakou et al.,2009; Tsigaridis et al., 2007). Some authors suggest that 91% of SOAs are considered to be caused by O3 and OH oxidation (Chung et al., 2002), while others consider that ozonolysis dominates in SOA production compared to OH and NOx oxidation (Kanakidou et al., 2005). 78% of SOAs are specifically products of monoterpene oxidation (Chung et al., 2002). Monoterpenes *α*-pinene and b-pinene are expected to be the major sources of SOAs (Kleindienst et al., 2007; Yu et al., 1999).

## **3.1. Chamber experiments**

368 Atmospheric Aerosols – Regional Characteristics – Chemistry and Physics

1999) levels.

**3. Secondary organic aerosol formation** 

Most of monoterpenes are photochemically reactive in the atmosphere because of their alkenyl bonds and other properties of their structure (Seinfeld and Pandis, 1998). Two key products of the photochemical reactions of these compounds in the atmosphere are gasphase oxidants (including ozone) and secondary organic aerosols. These gas-phase oxidants and secondary organic aerosol can have significant effects on human health when

compared to normal experiments when rough handling was minimized (Kim et al., 1995). However, there was no effect of rough handling in the late fall. It was concluded that a film of monoterpene compounds was present on the outer surface of the foliage during summer months, but not at other times of the year. Sampling of monoterpenes from *Picea marianna*  seed cones in situ versus ex situ was found to drastically affect both the emission rate as well as the monoterpene composition (Turgeon et al., 1998). Temporal and spatial factors can affect MC of a given tree species. Emissions and needle oil concentrations of Δ3-carene were lower relative to other monoterpenes in the summer but were substantially higher in the spring and fall (Janson, 1993; Lerdau et al., 1995). It was concluded that the high springtime emissions ofΔ3-carene from *Pinus ponderosa* were due to the MC of the oleoresin in that species (Flyckt, 1979). *Picea sitchensis* (Bong.) basal emission rate (in μg carbon g-1 h-1 at leaf temperature =30oC, referred to as emission factor or EF) and MC were found to change somewhat with the season (Street et al., 1996). Conversely, the oil composition of *Picea glauca*  leaves and twigs remained nearly constant from summer through winter, while the oil composition of buds changed significantly during fall and winter (von Rudloff, 1972). However, it seems more typical that foliage MC remains fairly stable during most of the growing season (Hall and Langenheim, 1986; Winer et al., 1992; Street et al., 1997b; Bertin et al., 1997). This is confirmed by measurements in ambient air (Roberts et al., 1985). Diurnal variation has not been examined extensively, but was found to be negligible in *Juniperus scopulorum* (Adams and Hagerman, 1976). Likewise, little diurnal variation was found in the monoterpene composition of ambient (near canopy) air near forests in Colorado (Roberts et al., 1985), where nighttime versus daytime relative abundance of β-pinene, α-pinene, Δ3 carene, camphene, and *d*-limonene changed by 0~4%, although nighttime total monoterpene concentration was over a factor of 2 greater due to lower dispersion. Greater seasonal and diurnal variability in light-dependent emissions of ocimene, linalool, and 1,8-cineole was found relative to the more temperature-dependent emissions of α-pinene and *d*-limonene, which varied little temporally from *Pinus pinea* (Staudt et al., 1997). Tree age effects have also been found for MC within this species (Adams and Hagerman, 1976) as well as for *Eucalyptus* (Street et al., 1997a) and *Picea sitchensis* (Street et al., 1996). Basal EFs were also found to decrease with tree age in these latter three studies and in *Pinus elliotti* (Kim et al., 1995). An increase in basal EFs and changes in MC of emissions following wetting of foliage have been noted (Janson, 1993; Lamb et al., 1984). Humidity has also been found to increase monoterpene emission rates at the leaf (Guenther et al., 1991) and canopy (Schade et al.,

A number of laboratory experiments have been carried out to study SOA formation by oxidation of monoterpenes (e.g. α-pinene, β-pinene, d-limonene, Δ3-carene, sabinene) with NOx, O3 and OH (Lee et al., 2004; Jonsson et al., 2008; Northcross and Jang, 2007; Czoschke et al., 2003; Spittler et al., 2003; Colville et al., 2004; Seinfeld et al., 2001). The formation of SOA in the presence of NOx has been studied for several monoterpenes: α-pinene, β-pinene, limonene, Δ3-carene, myrcene, β-ocimene, sabinene, α-terpinene, α-terpinolene (Pandis et al., 1991; Hoffmann et al., 1997; Griffin et al., 1999; Klinedinst and Currie, 1999; Presto et al., 2005; Lee et al., 2006; Zhang et al., 2006). The complexity of the dependence of NOx concentration on monoterpene SOA yields was first noted by Pandis et al. (1991) who found that the SOA yield from the photooxidation of α-pinene increased with increasing VOC/NOx ratio and maximized at 8% for 10–20 ppbC:ppb NOx. The SOA yield was found to decrease for VOC/NOx ratios greater than 20. More recently, Presto et al. (2005) showed that SOA yields from ozonolysis of α-pinene are lower under high- NOx (<15 ppbC:ppb NOx) than low-NOx conditions. The reduction of the SOA yields was attributed to the formation of higher volatility products under high NOx, including evidence of nitrate-

containing organic species. The NOx dependence becomes increasingly complex when the monoterpene consists of two double bonds with differing reactivity, as is the case for limonene. Zhang et al. (2006) indicated that two competing effects contribute to the NOx dependence of the SOA yield: reactive uptake by the aerosol and gas-phase oxidation. In the presence of ozone and at low NOx, heterogeneous ozonolysis of the exo double bond generates condensed-phase secondary generation oxidation products. However, at high NOx, gas-phase oxidation of the double bond becomes the dominant process for aerosol product generation.The yield dependence on NOx is complicated when oxidation by ozone or hydroxyl radicals takes place in the presence of NOx. The primary reason is thought to be that under high NOx conditions, organo-peroxy radicals (RO2) react with NO and NO2 instead of with peroxy radicals (RO2 or HO2). A number of different critical values (VOC/NOx) have been suggested (e.g. 10–15:1, Pandis et al., 1991, 8:1, Presto et al., 2005, 3– 10:1, Lane et al., 2008) for the point of 50:50 branching between the two reaction paths. As the OH/O3 ratio also depends on the VOC/NOx ratio, it is difficult to separate changes in yield due to changes in concentrations of OH and O3 from changes in product distribution due to the presence of NOx (Presto et al., 2005). However, the approach adopted by Lane et al. (2008) is to identify product yields for each fundamental pathway (i.e., high-NOx dominated by RO2 + NO, low-NOx by RO2 +HO2) and then to assume that SOA yields can be calculated by a linear combination of the "pure" mass yields scaled by the strength of each reaction pathway. Clearly, anthropogenic processes that perturb these branching ratios from their background values will influence overall SOA formation.

Production of Secondary Organic Aerosol from Multiphase Monoterpenes 371

primary aerosols, it will be difficult to assess the relative importance of the SOA. Measurements made during the Amazonian Aerosol Characterization Experiment 2008 (AMAZE-08), under near pristine conditions, show that the submicrometer aerosol is mostly composed of BSOA, while supermicron particles consist mainly of primary organic matter (Pöschl et al., 2010). While the submicrometer fraction was found to account for more than 99% of the ca. 200 cm-3 particles observed, approximately 70% of the ca. 2μg m-3 total particle mass was made up by the supermicron particles. The ongoing development of the Amazon is resulting in an enhanced anthropogenic influence on regional atmospheric composition. Changes in anthropogenic pollutants (particularly NOx and SO2) can alter the SOA formation potential (Kroll et al., 2005; Ng et al., 2007) and the relative roles of different oxidation pathways. It is typically assumed that more SOA is formed from monoterpenes under low-NOx conditions, such as prevail in the Amazon. Therefore a change in the amount of NOx due to anthropogenic emissions would lead to a change in the amount of SOA. The magnitude and the sign of this change depend on the

Current BVOC emission and air quality models aggregate all monoterpene (C10H16) compounds, assuming that their fate in the atmosphere is similar. However, studies have shown that individual monoterpene compounds may react quite differently (Hoffmann et al., 1997; Atkinson et al., 1992; Atkinson, 1990; Yokouchi and Ambe, 1985). Reaction rates with O3, OH, and NO3 radicals can vary by an order of magnitude between these compounds. Aerosol yields can likewise vary significantly. Monoterpenes with exocyclic double bonds, such as b-pinene and sabinene, tend to form more aerosols following ozonolysis compared to those with endocyclic double bonds, such as α-pinene and Δ3 carene (Hatakeyama et al., 1989). Those with two double bonds can react to produce even higher aerosol yields, depending on the vapor pressure of the reaction products. Open-chain monoterpenes, such as myrcene, linalool, and ocimene (Hoffmann et al., 1997), tend to produce lower aerosol yields under most circumstances. It was recently concluded that it is not possible to use generalized descriptions of terpene chemistry in models (Hallquist et al., 1999). Aerosol forming potentials of terpenes discussed here could be partially explained by their structural characteristics (Griffin et al., 1999). It was concluded that most biogenic hydrocarbons would have to be accounted for individually when modeling atmospheric

predominant VOC species.

**3.3. Modeling** 

aerosol formation.

**Author details** 

*Center for Research on Urban Environment,* 

*South China Institute of Environmental Sciences (SCIES), Ministry of Environmental Protection (MEP), Guangzhou, China* 

Shexia Ma

## **3.2. Field studies**

The high abundant vegetation in Amazonia make this region a global hotspot for the emission of various biogenic volatile organic compounds (e.g. Keller et al., 2009). Previously it was thought that the vast emissions of VOC in the Amazon area would deplete the oxidative potential of the atmosphere (Lelieveld et al., 2002) and thus constrain the BSOA production. However, there have been strong indications that HOx chemistry remains substantially more vigorous under low-NOx conditions than standard mechanisms predict (Thornton et al., 2002). This was confirmed by a more recent study by Lelieveld et al. (2008) showing that the oxidative potential in the pristine rainforest is maintained through the recycling of OH via organic peroxy radical reactions under low NOx conditions. Most attempts to estimate Amazonian BSOA production (e.g. Penner et al., 2001; Kanakidou et al., 2005) with global models have considered only monoterpenes as precursors. More recent efforts (e.g. Heald et al., 2008) have included isoprene, which has been shown to be a significant SOA precursor (Claeys et al., 2004), but still omit some potentially significant precursors such as the highly reactive sesquiterpenes which have very high BSOA yields. Both observational and modelling studies have concluded that 80% of the aerosol mass in the Amazon forest is of biogenic origin (Artaxo et al., 1990; Artaxo and Hansson, 1995; Heald et al., 2008; Chen et al., 2009) either due to primary or secondary sources (Kanakidou et al., 2005), however there is a large uncertainty in this number. One has to keep in mind that unless we have an accurate knowledge of the emissions of primary aerosols, it will be difficult to assess the relative importance of the SOA. Measurements made during the Amazonian Aerosol Characterization Experiment 2008 (AMAZE-08), under near pristine conditions, show that the submicrometer aerosol is mostly composed of BSOA, while supermicron particles consist mainly of primary organic matter (Pöschl et al., 2010). While the submicrometer fraction was found to account for more than 99% of the ca. 200 cm-3 particles observed, approximately 70% of the ca. 2μg m-3 total particle mass was made up by the supermicron particles. The ongoing development of the Amazon is resulting in an enhanced anthropogenic influence on regional atmospheric composition. Changes in anthropogenic pollutants (particularly NOx and SO2) can alter the SOA formation potential (Kroll et al., 2005; Ng et al., 2007) and the relative roles of different oxidation pathways. It is typically assumed that more SOA is formed from monoterpenes under low-NOx conditions, such as prevail in the Amazon. Therefore a change in the amount of NOx due to anthropogenic emissions would lead to a change in the amount of SOA. The magnitude and the sign of this change depend on the predominant VOC species.

### **3.3. Modeling**

370 Atmospheric Aerosols – Regional Characteristics – Chemistry and Physics

from their background values will influence overall SOA formation.

The high abundant vegetation in Amazonia make this region a global hotspot for the emission of various biogenic volatile organic compounds (e.g. Keller et al., 2009). Previously it was thought that the vast emissions of VOC in the Amazon area would deplete the oxidative potential of the atmosphere (Lelieveld et al., 2002) and thus constrain the BSOA production. However, there have been strong indications that HOx chemistry remains substantially more vigorous under low-NOx conditions than standard mechanisms predict (Thornton et al., 2002). This was confirmed by a more recent study by Lelieveld et al. (2008) showing that the oxidative potential in the pristine rainforest is maintained through the recycling of OH via organic peroxy radical reactions under low NOx conditions. Most attempts to estimate Amazonian BSOA production (e.g. Penner et al., 2001; Kanakidou et al., 2005) with global models have considered only monoterpenes as precursors. More recent efforts (e.g. Heald et al., 2008) have included isoprene, which has been shown to be a significant SOA precursor (Claeys et al., 2004), but still omit some potentially significant precursors such as the highly reactive sesquiterpenes which have very high BSOA yields. Both observational and modelling studies have concluded that 80% of the aerosol mass in the Amazon forest is of biogenic origin (Artaxo et al., 1990; Artaxo and Hansson, 1995; Heald et al., 2008; Chen et al., 2009) either due to primary or secondary sources (Kanakidou et al., 2005), however there is a large uncertainty in this number. One has to keep in mind that unless we have an accurate knowledge of the emissions of

**3.2. Field studies** 

containing organic species. The NOx dependence becomes increasingly complex when the monoterpene consists of two double bonds with differing reactivity, as is the case for limonene. Zhang et al. (2006) indicated that two competing effects contribute to the NOx dependence of the SOA yield: reactive uptake by the aerosol and gas-phase oxidation. In the presence of ozone and at low NOx, heterogeneous ozonolysis of the exo double bond generates condensed-phase secondary generation oxidation products. However, at high NOx, gas-phase oxidation of the double bond becomes the dominant process for aerosol product generation.The yield dependence on NOx is complicated when oxidation by ozone or hydroxyl radicals takes place in the presence of NOx. The primary reason is thought to be that under high NOx conditions, organo-peroxy radicals (RO2) react with NO and NO2 instead of with peroxy radicals (RO2 or HO2). A number of different critical values (VOC/NOx) have been suggested (e.g. 10–15:1, Pandis et al., 1991, 8:1, Presto et al., 2005, 3– 10:1, Lane et al., 2008) for the point of 50:50 branching between the two reaction paths. As the OH/O3 ratio also depends on the VOC/NOx ratio, it is difficult to separate changes in yield due to changes in concentrations of OH and O3 from changes in product distribution due to the presence of NOx (Presto et al., 2005). However, the approach adopted by Lane et al. (2008) is to identify product yields for each fundamental pathway (i.e., high-NOx dominated by RO2 + NO, low-NOx by RO2 +HO2) and then to assume that SOA yields can be calculated by a linear combination of the "pure" mass yields scaled by the strength of each reaction pathway. Clearly, anthropogenic processes that perturb these branching ratios

Current BVOC emission and air quality models aggregate all monoterpene (C10H16) compounds, assuming that their fate in the atmosphere is similar. However, studies have shown that individual monoterpene compounds may react quite differently (Hoffmann et al., 1997; Atkinson et al., 1992; Atkinson, 1990; Yokouchi and Ambe, 1985). Reaction rates with O3, OH, and NO3 radicals can vary by an order of magnitude between these compounds. Aerosol yields can likewise vary significantly. Monoterpenes with exocyclic double bonds, such as b-pinene and sabinene, tend to form more aerosols following ozonolysis compared to those with endocyclic double bonds, such as α-pinene and Δ3 carene (Hatakeyama et al., 1989). Those with two double bonds can react to produce even higher aerosol yields, depending on the vapor pressure of the reaction products. Open-chain monoterpenes, such as myrcene, linalool, and ocimene (Hoffmann et al., 1997), tend to produce lower aerosol yields under most circumstances. It was recently concluded that it is not possible to use generalized descriptions of terpene chemistry in models (Hallquist et al., 1999). Aerosol forming potentials of terpenes discussed here could be partially explained by their structural characteristics (Griffin et al., 1999). It was concluded that most biogenic hydrocarbons would have to be accounted for individually when modeling atmospheric aerosol formation.

## **Author details**

Shexia Ma *Center for Research on Urban Environment, South China Institute of Environmental Sciences (SCIES), Ministry of Environmental Protection (MEP), Guangzhou, China* 

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**Chapter 14** 

© 2012 Chung, licensee InTech. This is an open access chapter distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use,

distribution, and reproduction in any medium, provided the original work is properly cited.

© 2012 Chung, licensee InTech. This is a paper distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Aerosol direct forcing can be, and has been, estimated purely from observations alone, but the estimation has been done predominantly by a radiation model. A variety of radiation

**Aerosol Direct Radiative Forcing: A Review** 

Aerosols affect climate in multiple ways. Aerosol absorbs or scatters radiation in the atmosphere (so-called direct effect). Aerosols, except dust, interfere mainly with solar radiation. Some aerosols act as cloud condensation nuclei (CCN), thus affecting cloud albedo and lifetime (so-called indirect effect). Dark color aerosols can be deposited on sea ice, snow packs and glaciers, thus darkening the snow and ice surfaces, and enhancing the absorption of sunlight (so-called surface darkening effect). Some of the aerosols can absorb sunlight efficiently and heat the atmosphere. This heating can burn cloud (so-called semi-

direct effect). Here, I offer an overview of the aerosol direct effect on solar radiation.

τa AAOD Absorption Aerosol Optical Depth; = (1−SSA)×AOD

The effect of aerosols on climate is normally quantified in terms of aerosol radiative forcing. Aerosol radiative forcing is defined as the effect of anthropogenic aerosols on the radiative fluxes at the top of the atmosphere (TOA) and at the surface and on the absorption of radiation within the atmosphere. The effect of the total (anthropogenic + natural) aerosols is called aerosol radiative effect or total aerosol forcing. In this chapter, I discuss various parameters that affect aerosol direct radiative effect or aerosol direct radiative forcing.

Chul Eddy Chung

**1. Introduction** 

http://dx.doi.org/10.5772/50248

Additional information is available at the end of the chapter

τ AOD Aerosol Optical Depth

 SSA Single Scattering Albedo ASY Asymmetry parameter

**Table 1.** Summary of acronyms and symbols.

α AE Ångström Exponent for Extinction β AAE Absorption Ångström Exponent

