Atmos. Chem. Phys., 12, 9703–9718, 2012www.atmos-chem-phys.net/12/9703/2012/
doi:10.5194/acp-12-9703-2012© Author(s) 2012. CC Attribution 3.0 License.

Atmospheric
Chemistry
and Physics

How have both cultivation and warming influenced annual global
isoprene and monoterpene emissions since the preindustrial era?
K. Tanaka1 , H.-J. Kim1 , K. Saito1 , H. G. Takahashi1,2 , M. Watanabe3 , T. Yokohata4 , M. Kimoto3 , K. Takata1,5 , andT. Yasunari1,6
1 Research Institute for Global Change, Japan Agency for Marine-Earth Science and Technology, Yokohama, Japan
2 Department of Geography, Tokyo Metropolitan University, Hachioji, Japan
3 Atmospheric and Ocean Research Institute, The University of Tokyo, Kashiwa, Japan
4 National Institute for Environmental Studies, Tsukuba, Japan
5 National Institute of Polar Research, Tokyo, Japan
6 Hydrospheric Atmospheric Research Center, Nagoya University, Nagoya, Japan

Correspondence to: K. Tanaka (ktanaka@jamstec.go.jp)
Received: 21 May 2012 – Published in Atmos. Chem. Phys. Discuss.: 5 July 2012
Revised: 19 September 2012 – Accepted: 2 October 2012 – Published: 25 October 2012

Abstract. To examine the influence of both crop cultivation and surface air temperatures (SATs) on annual global
isoprene and monoterpene emissions, which can lead to theformation of secondary organic aerosols (SOAs), we simulated, on a monthly basis, the annual emissions of volatileorganic compounds (VOCs) during the period 1854–2000.
The model estimates were based on historical climate datasuch as SATs, and downward solar radiation (DSR) reproduced with an atmospheric-ocean circulation model, as well
as a time series of the global distribution of cropland (totest the hypothesis that conversion of forests into croplands
lowers emissions). The simulations demonstrated that global
SAT, DSR, the combination of SAT and DSR, and the expansion of cropland all affected emissions. The effect ofcropland expansion (i.e., forest conversion) on annual emissions during this period was larger for isoprene (∼ 7 % reduction on a global scale) than for monoterpenes (∼ 2 % reduction), mainly because of the reduction in broadleaf evergreen forests (BEFs) in Southeast Asia, which have the highest and most constant emissions of isoprene and where bothtemperature and radiation are high all year round. The reduction in the Amazon region and in parts of Africa, which
are other primary sources of annual global isoprene emissions, but where the conversion of BEF to cropland has beenmuch smaller than in Southeast Asia, was less remarkable,
probably because the broadleaf deciduous forests and C4
grasslands in these areas have lower and seasonal emissions;hence, their conversion has less effect. On the other hand,the difference in the emission factors (ε) between cropland
and the other vegetation types was much lower for monoterpenes than for isoprene, although the ε for cropland was generally the lowest for both compounds. Thus, the expansionof cropland also contributed to the reduction in monoterpene
emissions to some degree, but had less effect. A ∼ 5 % increase in emissions due to rising SAT was more than offset by the decrease in isoprene emissions and a concurrent∼ 2 % reduction caused by a decrease in DSR. Overall, annual global isoprene emissions in 2000 were lower than in1854 by 13 TgC yr−1 , whereas annual global monoterpene
emissions were higher by 2.3 TgC yr−1 .

1Introduction

Monoterpene secondary organic aerosols (SOAs) are themost important organic aerosol components on a global scale(Chung and Seinfeld, 2002; Engelhart et al., 2008). SOAs act
as cloud condensation nuclei (Novakov and Penner, 1993)
and directly scatter or absorb solar radiation (Andreae andCrutzen, 1997; Chung and Seinfeld, 2002). The photooxidation of isoprene generates SOAs (Jang et al., 2002). However, previous estimates of isoprene-related SOA levels arebeing reconsidered (Claeys et al., 2004; Henze and Seinfeld, 2006; Paulot et al., 2009), as an organic aerosol that

Published by Copernicus Publications on behalf of the European Geosciences Union.

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K. Tanaka et al.: Isoprene and monoterpene emissions since the preindustrial era

has been found in several forested areas is strongly indicative of an isoprene precursor (Matsunaga et al., 2003; Ionet al., 2005; Kourtchev et al., 2005). Vegetation is thought
to contribute to about 90 % of global emissions of volatileorganic compounds (VOCs) (Kuhn et al., 2004), and Guenther et al. (1995) estimated that the annual global VOC flux
is 1150 TgC, composed of 44 % isoprene, 11 % monoterpenes, 22.5 % other reactive VOCs, and 22.5 % other VOCs.
That study also showed that the contribution to VOCs fromvegetation should not be ignored when considering carbon
cycles. The estimation of VOC emissions from vegetation,
especially isoprene and monoterpene emissions, is essential
for understanding global tropospheric chemistry and regional
photochemical oxidant formation, for balancing the global
carbon cycle, and for understanding the production of organic acids (Fehsenfeld et al., 1992).
Vegetation is influenced by climate changes, and muchvegetation has been rapidly replaced with croplands since
the preindustrial era (Ramankutty and Foley, 1999; Hurttet al., 2006). Global warming has occurred over the past
150 yr; for example, Folland et al. (2001) reported that annual global surface temperature increased by 0.61 ± 0.16 ◦ C
between 1861 and 2000, based on SAT data. Because isoprene and monoterpene emissions increase with temperature (e.g., Guenther et al., 1993), the warming likely accelerates emissions on a global scale. At higher temperatures,the woody parts of vegetation are more likely to release diverse mixtures of terpenoids, including both isoprene andmonoterpenes (Owen et al., 2001; Keeling and Bohlmann,2006). Grasses and cereals are not generally major isopreneemitters, although they emit oxygenated biogenic VOCs
(BVOCs) (König et al., 1995; Kirstine et al., 1998; Davison et al., 2008). Hence, the conversion of forested areas tocropland is predicted to decrease BVOC emissions in certain
geographical areas (Laothawornkitkul et al., 2009). The two
effects offset each other, and the changes in VOC emissions
likely depend on the balance between vegetation type, crop
type, temperature, and region. Thus, the observed changes in
global VOC emissions may have influenced spatial and temporal SOA composition since the preindustrial era (1850s)(Tsigaridis et al., 2006).
Lathière et al. (2005) estimated global annual isoprene
and monoterpene emissions from the terrestrial biosphere between the preindustrial era and present day, using static mode
simulation; annual values were found to be 409 TgC and
127 TgC for the preindustrial era, and 402 TgC and 131 TgC
for the present day, respectively. Lathière et al. (2010) also
estimated global annual isoprene emissions from the terrestrial biosphere during the 20th century with a dynamic vegetation model that considered the negative effect of an increase in leaf area under rising atmospheric CO2 , and foundthat anthropogenic cropland expansion contributed the most
(15 %) to the reduction in isoprene emissions that occurredby 2002, while climate changes and rising CO2 caused a 7 %increase and a 21 % reduction, respectively. Thus, the auAtmos. Chem. Phys., 12, 9703–9718, 2012thors estimated that the present day annual global isopreneemissions would decrease and that monoterpene emissions
would increase in the current era compared to the preindustrial era and to the early 20th century, and they demonstrated
the influences of climate change and cropland expansion on
both types of emissions (Lathière et al., 2005). The authors
also demonstrated the influence of ambient CO2 on isopreneemissions (Lathière et al., 2010).
In the present study, we estimated the annual global isoprene and monoterpene emissions from the preindustrial era
to the present. We used the Model of Emissions of Gases
and Aerosols from Nature (MEGAN) (Guenther et al., 2006),
which is based on historical climate data reproduced with theatmospheric-ocean circulation Model for Interdisciplinary
Research on Climate (MIROC5), version 5 (Watanabe et al.,2010), and the expansion of cropland since the preindustrial era (Hurtt et al., 2006). We focused on how the expansion of cropland, and climate factors such as air temperature and solar radiation, influenced the annual global isoprene and monoterpene emissions from the preindustrial era
to the present. Simulations also considered historical emissions from areas including and excluding large expansionsof cropland and how each vegetation type in each area contributed to both annual emissions from 1854 to 2000.

2

Materials and methods

To estimate emissions for isoprene and monoterpenes (classified by eight components: myrcene, sabinene, limonene,
3-carene, ocimene, β-pinene, α-pinene, and other monoterpenes), we used the MEGAN model (Guenther et al., 2006)
and monthly climatic data including ambient solar radiation
and air temperature at 2 m above the land surface (Watanabe
et al., 2011). The climatic data were reproduced by a historical run from 1850 to 2005 with MIROC5 (Watanabe etal., 2010), which is an atmospheric ocean circulation modelwith the standard resolution of the T85 (256 × 128 regularlongitude/latitude global horizontal grid; approximately 1.4degree resolution) atmosphere and one-degree ocean models. The model considered historical solar irradiance data
(Lean et al., 2005) and surface aerosols emission data, andit reproduced the observed global mean surface air temperature during the 20th century well (Watanabe et al., 2011).
The expansion of cropland is described as the ratio of cropland to each grid (Hurtt et al., 2006). The global distribution of potential vegetation types shown by Ramankutty
and Foley (1999) was consulted, and the vegetation types
were replaced with those of a land-surface model (MATSIRO; Takata et al., 2003) in MIROC5. The level-4 Terra
Moderate-Resolution Imaging Spectroradiometer (MODIS)
global leaf area index (LAI), obtained from March 2000 to
February 2009, was applied to the monthly changes in LAI
of both potential vegetation and cropland in each grid (UnitedStates Geological Survey [USGS], 2010; https://lpdaac.usgs.
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K. Tanaka et al.: Isoprene and monoterpene emissions since the preindustrial era

9705

gov/products/modis products table/mod15a2). The distributions of interannual changes in fraction of cropland, and seasonal changes in LAI of both potential vegetation and cropland were arranged for the T85 Gaussian grids (256 × 128)(approximately 1.4-degree resolution) of climatic data. Interannual and seasonal changes in LAI in each grid were thendescribed with a combination among fractions of both potential vegetation and cropland, and both LAIs. We describe
MEGAN in Sect. 2.1, the values of essential parameters for
isoprene and monoterpene emissions and the algorithm of thecalculation in Sect. 2.2, and the estimation of the influenceof global surface air temperature (SAT), downward solar radiation (DSR), the combination thereof, and the expansionof cropland (or land use change) on both emission types in
Sect. 2.3.

where F is a fraction of foliage, A is relative emission activity, and the subscripts new, gro, mat, and old are new, growing, mature, and old foliages, respectively. The Anew , Agro ,Amat , and Aold values were set at 0.05, 0.6, 1.125, and 1 forisoprene emission, and 2, 1.8, 0.95, and 1 for monoterpene
emission, respectively. The Fnew , Fgro , Fmat , and Fold are estimated based on the current LAI (LAIc ), LAI of the previous
month (LAIp ), and monthly temperature (Tm ), in the following three cases: when LAIc = LAIp , Fnew = 0, Fgro = 0.1,
Fmat = 0.8, and Fold = 0.1; when LAIc < LAIp , Fnew = 0,
Fgro = 0, Fmat = 1 − Fold , and Fold = (LAIp − LAIc )/LAIp ;and when LAIc > LAIp , Fgro = 1−Fnew −Fmat , Fold = 0, andFnew and Fmat are estimated as follows:

2.1

and

A model for emissions of isoprene andmonoterpenes

The emission of VOCs (in this case, isoprene and monoterpenes) is described in MEGAN as follows:
VOC = ε · λLAI · λage · λL · λT ,(1)

where ε is the emission factor of isoprene or monoterpenes
that represents the emission of a compound into the canopy
under standard conditions, and λLAI , λage , λL , and λT areemission activity factors for LAI, age, light (or photosynthetic photon flux density, PPFD), and temperature, respectively. The standard conditions for the MEGAN canopy-scale
emission factors include an LAI of 5 and a canopy with 80 %mature, 10 % growing, and 10 % old foliage; current environmental conditions including a solar angle (degrees fromhorizon to sun) of 60 degrees, a PPFD transmission (ratioof PPFD at the top of the vegetation canopy to PPFD at the
top of the atmosphere) of 0.6, air temperature of 303 K, humidity of 4 g kg−1 , wind speed of 3 m s−1 , and soil moisture of 0.3 m3 m−3 ; average canopy environmental conditions of the prior 24 to 240 h included leaf temperature of
297 K and PPFD of 200 µmol m−2 s−1 for leaves in the sunand 50 µmol m−2 s−1 for leaves in the shade. The original,
right-hand side of Eq. (1) is multiplied by a factor for production or loss of VOCs within the canopy (ρ) and emission activity factors for soil moisture (λSM ) in addition toε, λLAI , λage , λL , and λT . Here, the values for ρ and λSM
were both assumed to be 1. Although the influence of ambient CO2 concentration on VOC emissions has been reported(Laothawornkitkul et al., 2009), it was disregarded.
An emission activity factor for LAI is estimated as follows:
λLAI = 0.49 · LAI/(1 + 0.2 · LAI2 )0.5 .

(2)An emission activity factor for age is estimated as follows:
λage = Fnew Anew + Fgro Agro + Fmat Amat + Fold Aold ,www.atmos-chem-phys.net/12/9703/2012/(3)

Fnew = 1 − LAIp /LAIc at t =≤ ti ,or Fnew = (ti /t) · (1 − LAIp /LAIc ) at t > ti ,Fmat = LAIp /LAIc at t =≤ tm ,or Fmat = LAIp /LAIc + {(t − tm )/t}·(1 − LAIp /LAIc ) at t > tm ,

(4)

(5)

where t is time step (in this case, 30 days), ti is the number ofdays between bud break and the induction of isoprene emission, and tm (or 2.3 ·ti ) is the number of days between bud
break and the initiation of peak isoprene emission. The value
for ti is estimated as follows:ti = 5 + 0.7 · (300 − Tt ) at Ti ≤ 303,or ti = 2.9 at Ti > 303,

(6)

where Ti is the average ambient air temperature (K) of thepreceding time step interval, and Tm was used in place of Ti
in the study.
An emission activity factor of light is estimated after
Sakulyanontvittaya et al. (2008), as follows:
λL = sin(a) · b2.46 · {1 + 0.0005 · (Pm − 400)}φ − 0.9φ 2 c
LDF at sin(a) > 0,or λL = 0 at sin(a) < 0,(7)
where a is solar angle in degrees (in this case, the monthly
average value of solar angle only in the daytime), Pm isthe monthly average (original daily average) above canopy
PPFD (µmol m−2 s−1 ), LDF is a light-dependence fractionthat varies depending on the compound under consideration,and φ is the above canopy PPFD transmission, which is estimated as follows:
φ=Pac / [sin(a) {3000+99· cos(2π(DOY − 10)/365)}] , (8)where Pac is the above canopy PPFD (here, Pm ), and DOY
is the day of year.
An emission activity factor of temperature is estimated asfollows:
λT =Eopt · CT2 · exp(CT1 ·x)/ CT2 −CT1 · {1 − exp(CT2 · x)}
for isoprene, and(9)Atmos. Chem. Phys., 12, 9703–9718, 2012

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K. Tanaka et al.: Isoprene and monoterpene emissions since the preindustrial era

λT = exp {β · (Tm − 303)} for monoterpenes,(10)

where Eopt = 1.75 · exp {0.08 · (Td − 297)}, x = [1/Topt −1/Th ], Topt = 313 + {0.6 · (T240 − 297)}, CT1 (= 80) andCT2 (= 200) are empirical coefficients, Td is the daily average temperature (K), Th is the hourly average temperature(K), T240 is the average air temperature over the past 240 h(K), and β is a temperature dependence (K−1 ), the valueof which was set at 0.1. Equation (9) considers that leaves
exposed to a past higher temperature release more isoprene
than those exposed to a lower past temperature. The influence
was disregarded, however, because monthly average ambient
temperature at 2 m above the land surface (Tm ) was used inplace of Td , Th , and T240 .
2.2

The parameters for and calculation of isoprene andmonoterpene emissions

Figure 1 shows the distribution of current potential vegetation. Here, ten vegetation types including continental ice(Ice), broadleaf evergreen forest (BEF), broadleaf deciduous forest and woodland (BDFW), mixed coniferous andbroadleaf deciduous forest and woodland (MCBDF), coniferous forest and woodland (CFW), high-latitude deciduous forest and woodland (HLDFW), wooded C4 grassland(WC4G), shrubs and bare ground (SBG), tundra (Tundra),
and C3 grassland (C3G) were classified. The C4 vegetation fraction during 1986–1995 and SAT (surface air temperature) during September 1957–August 2002 were determined according to Takata et al. (2003), with reference alsoto Ramankutty and Foley (1999), as shown below. The C4
vegetation fraction and SAT data set were from the International Satellite Land Surface Climatology Project, Initiative
II (ISLSCP II; http://daac.ornl.gov/ISLSCP II/islscpii.shtml)
and ECMWF (European Centre for Medium-Range Weather
Forecasts) 40 Year Re-analysis (ERA-40) Data (Uppala etal., 2005), respectively.
(1) Ice was converted from other areas, such as Antarctica and most parts of Greenland, where Ramankutty andFoley (1999) did not conduct classification; (2) BEF from
Tropical Evergreen Forest/Woodland; (3) BDFW from Tropical Deciduous Forest/Woodland; (4) MCBDF from Temperate Broadleaf Evergreen Forest/Woodland, Temperate
Needleleaf Evergreen Forest/Woodland, Temperate Deciduous Forest/Woodland, and Evergreen/Deciduous Mixed Forest (E/DMF) at the lowest monthly SAT of ≥ − 3◦ ; (5) CFW
from Boreal Evergreen Forest/Woodland, and E/DMF at thelowest monthly SAT of < − 3◦ and with ≥ 4 months atmonthly SAT of ≥ 10◦ ; (6) HLDFW from Boreal Deciduous Forest/Woodland, and E/DMF at the lowest monthly
SAT of < − 3◦ and with < 4 months at monthly SAT of≥ 10◦ ; (7) WC4G from Savanna and Dense Shrub (DS) witha C4 vegetation fraction of > 20 %; (8) SBG from OpenShrubland and Desert; (9) Tundra from Tundra and Polar
Atmos. Chem. Phys., 12, 9703–9718, 2012

Fig. 1. Global distribution map of potential vegetation: continental
ice (Ice), broadleaf evergreen forest (BEF), broadleaf deciduous forest and woodland (BDFW), mixed coniferous and broadleaf deciduous forest and woodland (MCBDF), coniferous forest and woodland(CFW), high latitude deciduous forest and woodland (HLDFW),
wooded C4 grassland (WC4G), shrubs and bare ground (SBG), tundra (Tundra), and C3 grassland (C3G). The vegetation types anddistribution are based on Takata et al. (2003) and Ramankutty andFoley (1999), respectively.

Desert/Rock/Ice; (10) C3G from Grassland/Steppe, and Savanna and DS with a C4 vegetation fraction of ≤ 20 %.
The values of ε and LDF for isoprene or monoterpenes
are shown in Table 1. They were set based on Guenther etal. (2006) and Sakulyanontvittaya et al. (2008), respectively.
The values were the highest for isoprene in BEF and BDFW,
which correspond to tree species extending to low latitudes.
The values were the highest for most monoterpenes in CFW
and HLDFW, which correspond to tree species extending
to high latitudes, or in SBG for limonene and ocimene, respectively. The value for cropland was the lowest for isoprene and most monoterpenes. The values of LDF indicate
the higher dependency on land type for isoprene emission
and the smaller dependency on land type for monoterpenes,
excluding ocimene.
VOC levels (e.g., isoprene, myrcene, sabinene, limonene)
were calculated for both vegetation type and cultivation ina grid, using LAIc (current month), LAIp (previous month),monthly DSR (Sm ; W m−2 ), a, and Tm . Monthly above
canopy PPFD (Pm ; µmol m−2 s−1 ) was calculated as kSm ,where k (µmol J−1 ) is an empirical coefficient and the value
was set at 2.3. The monthly average value of a was estimatedamong positive values of hourly values for a during daytime,after the values were calculated hourly with both the latitude
and longitude of a grid and time. The values were summed
according to the fraction of cropland α and potential vegetation (1 − α). The estimations for eight components (i.e.,
myrcene, sabinene, limonene, 3-carene, ocimene, β-pinene,
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K. Tanaka et al.: Isoprene and monoterpene emissions since the preindustrial era

9707

Table 1. The values of emission factors (ε) and light-dependence fraction (LDF) for isoprene or monoterpenes. The italic values correspondto the maximum values of ε, while the bold values correspond to the minimum vales of ε excluding continental ice.
Surface typeεIsoprene
mgC m−2 h−1

Monoterpenes
×10−3 mgC m−2 h−1
Myrcenesabinenelimonene

3-careneocimeneβ−pinene

α−pineneothermonoterpenes

Total

Continental ice (Ice)

0

0

0

0

0

0

0

0

0

0

Broadleaf evergreen forest
(BEF)

11.12

19.5

12.62

35.91

4.41

118.59

35.82

31.85

137.56396.26

Broadleaf deciduous forest
and woodland (BDFW)

11.12

19.5

12.62

35.91

4.41

118.59

35.82

31.85

137.56396.26

Mixed coniferous andbroadleaf deciduous forest
and woodland (MCBDF)

6.44

47.56

24.79

61.59

21.35

60.97

58.32

115.59192.79582.97

Coniferous forest andwoodland (CFW)

1.76

75.71

36.97

87.26

38.38

3.44

80.91

199.32248.12770.12High latitudedeciduous forest andwoodland (HLDFW)

0.62

75.71

36.97

87.26

38.38

3.44

80.91

199.32248.12770.12

Wooded C4 grassland(WC4G)

0.44

4.94

7.06

36.62

15.18

12.62

19.32

50.47

139.5

285.71

Shrubs and bare ground
(SBG)

9.44

18.44

15.26

153.44

5.38

90.88

39.71

45.18

280.85649.15

Tundra

0.44

4.94

7.06

36.62

15.18

12.62

19.32

50.47

139.5

285.71C3 grassland (C3G)

0.44

4.94

7.06

36.62

15.18

12.62

19.32

50.47

139.5

285.71

Cropland

0.08

4.94

7.06

36.62

15.18

12.62

19.32

50.47

139.5

285.71

LDF value

0.9999

0.05

0.1

0.05

0.05

0.8

0.1

0.1

0.1

–

α-pinene, and other monoterpenes) were summed to get avalue for total monoterpene emissions. Total isoprene andmonoterpene emissions on a global scale were calculated
while considering the land surface area of grids and excluding both sea and lake surfaces. Variables such as VOC emissions, λL and λT , are shown as 10-yr running means; for example, the values in 1854 and 2000 were averaged among
those from 1850 to 1859 and from 1996 to 2005, respectively.
We estimated both isoprene and monoterpene emissions
in the 11 regions shown in Fig. 2. The A1–A8 regions included parts of Europe, Africa, East Asia, India, Southeast
Asia, Oceania, North America, and South America, respectively. These regions had the largest expansion of cultivation since 1850, as shown in the results. On the other hand,minimal expansion was estimated for regions A9, A10, andA11, which are regions that include latitudes from 90◦ N
to ∼ 21◦ N, from ∼ 21◦ N to ∼ 21◦ S, and from ∼ 21◦ S to90◦ S, excluding the areas in the A1–A8 regions, respectively(Fig. 2). Figure 2 shows the area of each region; region A2 isthe largest and A5 is the smallest in A1–A8.

www.atmos-chem-phys.net/12/9703/2012/

A9 (3.154)

A3

A1(1.471)(1.553)A4(0.569)A2(1.933)

A5(0.447)

A6(0.811)

Area (×107 km2)

A7

(1.248)A10 (1.091)
A8(1.083)

A11(1.519)

Fig. 2. Targeted areas and related surface (in 107 km2 ). A1–A8 are
Fig. 2 with relatively intensive expansion of cropland (Fig. 4), whileareas
A9–A11 are regions with minimal expansion of cropland. Annual
global isoprene and monoterpene emissions in each area are shownin Figs. 8 and 9.

Atmos. Chem. Phys., 12, 9703–9718, 2012

K. Tanaka et al.: Isoprene and monoterpene emissions since the preindustrial era

a)

b)

289

19 0

DSR(W m- 2 )SAT (K)

9708

288

287
18 5 018 9 019 3 019 7 0

2 010

18 5

18 0
18 5 018 9 0Year

19 3 019 7 0

2 010

Year

Fig. 3Fig. 3. Global mean surface air temperature (SAT) (a) and downward solar radiation (DSR) above the land surface (b). Thinlines and thick solid lines are temporal and ten-year runningmeans. These were reconstructed by a historical run for the period 1850–2005 with MIROC5 (Watanabe et al., 2010), which is anatmospheric-ocean circulation model, and was used as input data
for estimation of global isoprene and monoterpene emissions.

2.3

Estimation of the influence of both cultivation andclimate on emissions

Both isoprene and monoterpene emissions were calculated with the expansion of cropland in 1850 and climate
from 1850 to 2005, and described as 10-yr running means(VOCveg1850 (y)). The value of VOCveg1850 (y) was comparedto the value for VOC(y) calculated with the changes in both
expansion of cropland and climate, to estimate the influenceof expansion of cropland on both types of emissions. Here, yis the year from 1854 to 2000 (see Sect. 2.2). The influenceof the expansion of cultivated land on the emissions was estimated as VOC(y)/VOCveg1850 (y) − 1. The influence of climate was estimated as VOCveg1850 (y)/VOCveg1850 (1854) −1. The influence of changes in temperature (SAT) and light
conditions (DSR) were estimated as λT (y)/λT (1854) − 1 and
λL (y)/λL (1854)−1 for isoprene and monoterpene emissions,
respectively. Here, the λL (y) values for monoterpenes are
given as the weighted-average, weighted by emission factors(ε) of both potential vegetation type and cropland and the areas at all grids for eight species (Table 1), whose values weredifferent as the emissions for most monoterpene species react
very little to changes in light conditions while the ocimene
emissions react strongly, as mentioned above.

3
3.1

Results
Climate change and cultivation from 1850 to 2005

Figure 3 shows the interannual variation in both global mean
SAT and DSR at 2 m above the land surface. These values
were reproduced by a historical run from 1850 to 2005 with
MIROC5 (Watanabe et al., 2010). The SAT gradually increased from the 1850s to the 2000s with some fluctuation; inparticular, the periods of global warming observed from the
1890s to the 1950s and from the 1970s to the 2000s were remarkable. Tatebe et al. (2012) found that the anomalies were
Atmos. Chem. Phys., 12, 9703–9718, 2012

similar to those observed in SAT data from 1948 to 2006
and were reanalyzed by the National Centers for Environmental Prediction/National Center for Atmospheric Research(NCEP/NCAR) (Kalnay, 1996). In particular, the magnitudeof the reanalyzed interannual SAT was near that of the 10yr running mean of reconstructed interannual SAT. The DSR
gradually decreased until the 1950s, fell again sharply fromthe 1960s to the 1980s, and then increased slightly from themid-1980s.
Figure 4a and b show the fraction of cropland in 1850 andin 2000, respectively. In 1850, extensive cultivation was already found in regions A1, A3, A4, and A7 (shown in Fig. 2).
Figure 4c shows the difference in the fraction of cropland between 2000 and 1850. By 1850, cultivation was already extensive in Europe but more extensive in the Ukraine (region
A1) and extended eastward into Russia by 2000 (Fig. 4b).
Cultivation in 1850 was minimal in western regions of Africa(region A2), but expanded due to a change in distribution of
WC4G-type vegetation (yellow area of Fig. 1). Cultivation
was initially concentrated around the Yellow River basin inregion A3, but over time extended northeastward and southward. Region A4 (Indian subcontinent) was already cultivated in 1850, and by 2000 was much further developed.
Very little cultivation was evident in 1850 in region A5; however, by 2000 there appeared to be a strongly concentrated
area of cultivation in the Indochina Peninsula, the Malay
Peninsula, the island of Sumatra, the Kalimantan/Borneo Islands, and the Philippines. Croplands also expanded aroundboth the east and west coasts of Australia, in particular along
the east coast by 2000 in region A6. Cropland was initiallyconcentrated in the eastern portions of the North American continent in 1850 (region A7), but migrated westward
into the Midwestern United States, the Prairie Provinces ofCanada, and Mexico by 2000. Cultivation also expanded insouthern Brazil and in parts of Argentina (region A8) from1850. Generally, the expansion of cultivation was related topopulation increases in countries such as China, India, Indonesia, the United States, and Brazil. In contrast, a change
from cropland into other forms of vegetation was found insome areas of both A1 and A7 (Fig. 4c). Cropland expansion of more than 10 % (or 0.1) was found only minimally inregions A9–A11.
Figure 5 shows the increase in cultivation and changes invegetation types in A1 through A11 during the period from1850–2005 as the ratio of each vegetation area to each targeted land surface area. Cropland increased from 11.5 % to24.4 %, coinciding with a decrease in both C3G and MCBDF
vegetation during the period 1850–1960 in region A1, subsequently decreased gradually until 1980, and then decreased
more rapidly in the 1980s until it reached a value of 20.6 %(Fig. 5a). As shown in Fig. 5b, cropland area in region A2 increased from 2.4 % to 10.1 %, mainly due to the replacementof WC4G. Region A3 exhibited a steep increase in croplandafter 1980 with cultivation in both MCBDF and SGB lands(Fig. 5c). In region A4, cropland increased from 19.5 % towww.atmos-chem-phys.net/12/9703/2012/

K. Tanaka et al.: Isoprene and monoterpene emissions since the preindustrial era

9709

in Fig. 5f, the cropland in region A6 increased clearly fromabout 1910 with a coinciding decline in SBG and WC4G. In
region A7, cultivation increased constantly along with a decline in both C3G and MCBDF during the period 1850–1940,
after which the rate of cropland expansion slowed (Fig. 5g).
As shown in Fig. 5h, cropland in region A8 constantly increased along with a decrease in WC4G, SBG, and BDFW
after ∼ 1900, while the decrease in BEF in this region was
relatively lower than these three vegetation types. Regions
A9 through A11 exhibited only small changes (<∼ 1 %)in cultivation (Fig. 5i, k); region A11, which has the thirdlargest area, was 90.1 % ice cover without VOC emissions(Table 1).
Overall, region A5 featured decreases in both BEF and
BDFW with the highest emission factors (ε) of isoprene (Table 1). The decrease in BDFW was also obvious in region
A4. However, the decrease in both CFW and HLDFW, withthe highest emission factors (ε) of monoterpenes (Table 1),
were relatively small in higher latitudes such as A1, A3, andA7. In these areas, both C3G, which had the lowest ε, andMCBDF, which had a relatively high ε for monoterpenes,
were replaced the most with cropland. Thus, compared toisoprene, the expansion of cropland had a lesser impact onthe ε values of monoterpenes (Table 1).
3.2

3.2.1

Fig. 4. Global map of fraction of cropland in 1850 (a) and 2000 (b),and the difference between 2000 and 1850 (c). The results are basedon Hurtt et al. (2006). Targeted areas (A1–A11) are shown in (c).

33.1 %, with the steeper increase from 1930 to 1960, but
the increase rate slowed after about 1960 (Fig. 5d). Region
A5 initially exhibited BEF vegetation of 76.3 % and BDFW
vegetation of 10.9 %, respectively, but large portions of bothwere replaced with cropland by 2005 (Fig. 5e). As shown
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Annual isoprene and monoterpene emissions andthe influence of both climate and cultivation during
the period 1854–2000
Global scale

Global annual isoprene and monoterpene emissions during
the entire study period are shown in Fig. 6a and b. In the
figure, red solid lines denote cropland expansion. The valuesof isoprene and monoterpene were 573 and 69.3 TgC yr−1 ,respectively, in 1854, and 540 and 69.5 TgC yr−1 , respectively, in the 1990s. The 1990s values are withinpresent estimated and published annual global isoprene andmonoterpene emissions: 410–601 TgC yr−1 for isoprene and
33–480 TgC yr−1 for monoterpenes, according to Laothawornkitkul et al. (2009). Arneth et al. (2008) reported that
estimates of global terrestrial isoprene emissions are similar while estimates for global monoterpenes emissions vary.
Both emissions increased with a steep rise in SAT during the mid-1990s to 2000, and the values were 560 and
71.6 TgC yr−1 , respectively, in 2000. The maximum andminimum values for isoprene and monoterpene emissions
were 600 (1927) and 530 TgC yr−1 (1965), and 71.6 (1998)
and 67.3 TgC yr−1 (1890), respectively. Lathière et al. (2005)
estimated annual isoprene and monoterpene emissions forthe 1850s and 1990s at 409 and 402 TgC yr−1 , and 127 and
131 TgC yr−1 , respectively. Our estimates are higher for isoprene emissions and lower for monoterpene emissions. However, all of these analyses indicate that annual emissions ofisoprene and monoterpenes decreased and increased in the
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9710

K. Tanaka et al.: Isoprene and monoterpene emissions since the preindustrial era

(%)

a)

c)

d) A4 (India)

A3 (East Asia)

50

50

50

40

40

40

40

30

30

30

30

20

20

20

20

10

10

10

10

0
18 5 0e)(%)b) A2 (Africa)

A1 (Europe)50

18 9 019 3 019 7 00
18 5 02 010

f)

A5 (Southeast Asia)

18 9 019 3 019 7 00
18 5 02 010

18 9 019 3 019 7 02 010g) A7 (North America)

A6 (Oceania)0
18 5 0

50

50

50

4
70

40

40

40

3
60

30

30

30

20

20

20

20

10

10

10

10

0
18 5 019 3 019 7 02 010h) A8 (South America)

5
80

~
~

18 9 0~~18 9 019 3 019 7 00
18 5 02 010

18 9 019 3 019 7 00
18 5 02 010

18 9 019 3 019 7 02 010

018 5 018 9 019 3 019 7 0

2 010

Year

(%)

i)

j)

A9 (90 o N － ~21 o N)

A10 (~21 o N － ~21 o S)k)

A11 (~21 o S － 90 o S)

50

50

50
10

40

40

4
90

30

30

3
80

20

20

20

10

10

10

~
~

0
18 5 018 9 019 3 019 7 02 010

018 5 0Year

18 9 019 3 019 7 0

Year

2 010

0
18 5 0~~18 9 019 3 019 7 01. Ice2. BEF
3. BDFW
4 MCBDF
5. CFW
6. HLDFW
7. WC4G
8. SBG
9. Tundra
10. C3G
11. Cropland

2 010

Year

Fig. 5

Fig. 5. Interannual changes in the ratio of vegetation area in regions A1 through A11 during the period from 1850–2005.

1990s, respectively, compared to 1850. Lathière et al. (2010)
also estimated annual isoprene emissions during the 20th
century while considering cropland expansion and estimatedthe values to be 607 and 464 TgC yr−1 in 1901 and 2002. We
estimated the annual isoprene emission to be 572 TgC yr−1
in 1901. The difference between the 1901 and 2002 values islarger in their estimates than in ours.
Both annual emissions were estimated with cropland expansion from 1850 fluctuating with changes in SAT and DSR(Fig. 3), mainly SAT, during the period from 1854 to 2000
(Fig. 6a and b). The values were estimated to be 604 and73.2 TgC yr−1 for isoprene and monoterpenes, respectively,
in 2000. Although the changes were similar to the annual
emissions estimated by changes in cropland expansion, thedifferences between the annual emissions with and withoutchanges in cropland expansion gradually become larger, indicating the influence of cropland expansion. The influence ofcropland expansion induced a reduction of global emissions
by 56.3 and 1.6 TgC yr−1 for isoprene and monoterpenes, respectively, in 2000, and the influences were larger for global
isoprene emissions than for global monoterpenes emissions.
Figure 6c and d shows the influence of climate, land use(cultivation expansion), SAT, and DSR on global isoprene
and monoterpene emissions, respectively. The fluctuations
correspond to the annual emissions shown in Fig. 6a and b.
Atmos. Chem. Phys., 12, 9703–9718, 2012

Changes in land use induced a gradual reduction in annual
emissions; the minimum values appeared in 2000, and were
−7.2 % for isoprene and −2.2 % for monoterpenes. The influences were always larger for isoprene emissions than formonoterpene emissions during the period under study. The
influence of SAT on both types of emissions changed withlarge fluctuations, peaks around the 1920s and the 1950s,
and the maximum influence appeared in 1999. The maximum
values were 10.0 % for isoprene and 7.7 % for monoterpenes,
respectively. The influence of a gradual decrease in DSR on
isoprene emissions was evident as a 2.2 % reduction in emissions by 2000. In contrast, monoterpene emissions were minimally influenced by changes in DSR.
Figure 7a and b shows the distribution of estimated annual global emissions for isoprene and monoterpenes, respectively, in 2000. Estimated isoprene emissions were concentrated in low latitudes with BEF and BDFW, in particular in BEF (or tropical rain forests), and also in MCBDF(Fig. 1). On the other hand, estimated monoterpene emissions occurred in high latitudes with CFW, HLDFW and
WC4G, as well as in low latitudes. Figure 7c and d shows thedifference in estimated annual global emissions for isoprene
and monoterpenes between 2000 and 1854. Isoprene emissions were lower in 2000 than in 1854 in northeast India,
Southeast Asia, and in parts of Central America and South
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K. Tanaka et al.: Isoprene and monoterpene emissions since the preindustrial eraa) Iso. emissionb) Mon. emission
75

Veg1850
Change(Tg C y - 1 )(Tg C y - 1 )

650

600

550

500
18 5 0

19 0 019 5 0Yearc)

19 5 02000

19 5 0

2000

Year

10

Clima teLanduse
SAT
DSR
AL L

5

(%)

5

(%)

19 0 0d)

Clima t e
Landuse
SAT
DSR
AL L

10

70

65
18 5 02000

Veg1850
Change

0
-5

0
-5

-10
18 5 0

19 0 019 5 02000-10
18 5 0

19 0 0Year

Year

Fig. 6. Interannual changes in estimated annual global isoprene (a)and monoterpene (b) emissions during the period 1854–2000. The
red and blue lines in (a) and (b) are the emissions estimated withtemporal distribution of vegetation and with constant vegetation distribution in 1850, respectively. The impacts of surface air temperature (SAT; red lines), downward solar radiation (DSR; blue lines),
the combination of both SAT and DSR (or climate; gray lines), theextent of cropland (or land use; green thick lines), and the combination thereof (black lines) on annual global isoprene (c) andmonoterpene emissions (d). The estimate of the influence is detailed in Sect. 2.3. The results in (a–d) are shown as 10-yr runningmeans, e.g., results in 1854 correspond to average values from 1850
to 1859.

Fig. 6

America, while they were larger in the Amazon. Monoterpene emissions were lower in 2000 than in 1854 in eastern
China and in parts of Indochina, India, central North America, and Europe, while they were larger in the Amazon andin parts of North America and Africa. The distribution of thedifference between the two types of emissions changed fromyear to year, compared to those in 1854 (not shown).
3.2.2

Contribution of isoprene and monoterpene
emissions from each area to the global emissions

Figure 8 shows how regions A1 through A11 contributed to
global emissions during the study period. Isoprene emissions
were largest in the following order: low latitudes of region
A10 with minimal expansion of cultivation, an area of SouthAmerica in region A8, an area of Africa in region A2, andan area of Southeast Asia in region A5, all of which are distributed in lower latitudes. Monoterpene emissions were thelargest in the following order: region A2, region A8, region
A10, and an area of North America in region A7. Annual isoprene emissions were much larger in these four areas than in
any other areas, because both BEF and BDF with the highest ε are distributed in the areas with high temperature andsolar radiation all year round (Fig. 7a). Although CFW and
HLDFW with the higher ε of monoterpenes are distributed
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9711

in high latitudes with high temperature during a few months
in the summer season, the annual emissions were larger inlower latitudes, as in regions A2, A8, and A10, due to theirhigh year-round temperatures. However, the differences (e.g.,
between A10 and A7) were relatively small, compared tothose between the annual isoprene emissions from different
regions.
The fluctuation in isoprene emissions in region A8 overthe study period was similar to that in region A10, with relatively less change in land use, and the two areas contributed
to the global annual emissions the most, which indicates thatthe emissions were dependent on climate changes rather thanon the expansion of cropland. These areas had lower emissions with lower SAT from around 1950 to the 1960s (Fig. 3)
than in 1854. The annual emissions in region A5 were similar to those in region A2 from 1850 to the 1890s, but they
decreased obviously starting around 1930, and the differencein annual emissions between regions A5 and A2 were thelargest at the end of the time series. The influence of expansion of cropland on the annual emissions was the highest in
region A5; region A5 likely contributed significantly to thedecreases in the annual emissions since the 1950s (Fig. 6a).
The annual emissions also decreased with time in regions
A4, A3, and A1, although the expansion of cropland had alesser influence. Region A1 had slight increases in isopreneemissions by reforestation (Fig. 5) in the 1990s. The time series for annual monoterpene emissions were similar among
regions A2 and A8, both of which had relatively large expansions of cropland, and region A10, which had minimal
expansion of cropland.
Figure 9 shows how each vegetation type contributed to
global annual emissions. Cropland minimally emitted isoprene according to the lowest emission factors (ε) (Table 1).
Simulations showed that loss of both BEF and BDFW withthe highest ε effectively decreased the annual isoprene emissions in region A5. A slight decrease due to BEF loss appeared in region A2. In region A8, a decrease caused by
BDFW loss was more obvious than that caused by BEF loss.
Decreases in regions A3 and A4 appeared because of the lossof MCBDF and BDFW, respectively. As previously mentioned, the decrease caused by the loss of MCBDF appearedin the 1980s in region A1, but then reforestation increased
the annual emissions around the 1990s.
On the other hand, annual monoterpene emissions fromcropland increased with its expansion, and offset the decreases due to other vegetation types to some degree. Thus,
the replacement of natural vegetation with cropland decreased the annual emissions of monoterpenes to a lesser
extent than it did for isoprene. In region A1, reforestation
also increased the annual monoterpene emissions around the1990s, as it did for isoprene, but the contributions to both annual global emissions was quite small, as shown by Lathièreet al. (2006). In regions A2 and A8, WC4G played an important role increasing the annual monoterpene emissions, but
not isoprene emissions.
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9712

K. Tanaka et al.: Isoprene and monoterpene emissions since the preindustrial era

Fig. 7. Distribution of estimated annual global emissions (gC m−2 yr−1 ) in 2000, and the differences between 2000 and 1854 for isoprene(a and c) and monoterpenes (b and d), respectively.

Iso. emissiona)Mon. emission

b)
14

16 0

A10
14 0

A2

12

A8

A8

10 0

A2

80

A5

(Tg C y - 1 )(Tg C y - 1 )

12 0

10

A10
8

A7
A3
A5

6

60

A1

A9
4

40
20
0
18 5 0

A6

A7

A4
A3

A4
2

A6
A9

19 0 019 5 0

A1
A11
2000

A11
0
18 5 0

19 0 0Year

19 5 0

2000

Year

8
Fig.Fig.
8. Interannualchanges in estimated annual isoprene (a) andmonoterpene (b) emissions during the period 1854–2000 in regions
A1 through A11. The results are shown as 10-yr running means.

4Discussion

We demonstrated the effects of the expansion of croplandand climate change on annual global isoprene and monoterpene emissions during the period 1854–2000. The expansionof cropland had a greater effect on isoprene emissions thanon monoterpene emissions (Fig. 6). The expansion of cropland contributed to the annual global emissions of monoterpenes to some degree but contributed only minimally to isoAtmos. Chem. Phys., 12, 9703–9718, 2012prene emissions (Fig. 9). The annual global emissions increased for monoterpenes mainly due to global warming, andthey decreased for isoprene in the 1990s due to a decline
in cropland, compared to those in the preindustrial era. Thechanges for both compounds between the preindustrial era
and the present were consistent with those demonstrated using a static mode simulation by Lathière et al. (2005).
DSR gradually decreased over the entire period, except for
a rapid decline from the 1950s to the 1980s and a small increase in the 1990s, while SAT increased overall but withlarger fluctuations (Fig. 3). The decline reconstructed by
MIROC5 could describe the significant reductions in solar
radiation during the past 50 yr, reported by a number of studies according to a review by Stanhill and Cohen (2001). The
possible causes are an increase in anthropogenic aerosols,
other air pollution, and clouds. In addition, the reduction canbe attributed to changes in optical properties caused by anincrease in atmospheric water vapor due to global warming.
The decrease in DSR decreased the annual global isopreneemissions by 2 %, while it had little impact on monoterpene
emissions. The influence of DSR was the smallest of thethree factors considered (Fig. 6). Considering the increasein the ratio of the diffused to direct radiation and the consequent increase in infiltration of solar radiation into regionswith deep canopy (e.g., Mercado et al., 2009), the influences
may become smaller.

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K. Tanaka et al.: Isoprene and monoterpene emissions since the preindustrial era
a)Iso. emission
160b)Mon. emission
14

A1 A2 A3 A4 A5 A6 A7 A8 A9 A10 A11

140

9713

A1 A2 A3 A4 A5 A6 A7 A8 A9 A10 A11

12

120

(Tg C y-1)

(Tg C y-1)

10
100
80
60

1. Ice2. BEF
3. BDFW
4. MCBDF
5. CFW
6. HLDFW
7. WC4G
8. SBG
9. Tundra
10. C3G
11. Cropland

8

6

4

40

2000

1850

1850

1850

1850

1850

1850

1850

1850

1850

1850

Year

1850

2000

1850

1850

1850

1850

1850

1850

1850

1850

0

1850

0

1850

2

1850

20

Year

Fig. 9Fig. 9. Interannual changes in contributions of each vegetation type to estimated annual isoprene (a) and monoterpene (b) emissions during
the period 1854–2000 in regions A1 through A11. The results are shown as 10-yr running means.

We disregarded the influences of ambient CO2 , soil moisture, and other factors on global emissions, and the contributions to both annual global emissions from BEF in Southeast Asia with low latitudes such as in the Amazon were thelargest. These findings are further discussed in Sects. 4.1 and
4.2, respectively. We demonstrated that the influence of cropland on annual global isoprene emissions was the largest inSoutheast Asia. The expansion of oil palm plantations withhigh emissions has occurred on the largest scale in Southeast
Asia. However, the influences of this were not considered in
the present study. In Sect. 4.3, we discuss how the expansionof this crop in Southeast Asia may influence the estimate ofannual global isoprene emissions.
4.1

Effects of ambient CO2 , soil moisture, and otherfactors neglected in the study

Our estimate did not consider the influence of ambient
CO2 and soil moisture on either isoprene or monoterpene
emissions. According to a review by Laothawornkitkul etal. (2009), elevated CO2 levels either increase (Sharkey etal., 1991; Staudt et al., 2001), decrease (Sharkey et al., 1991;
Loreto et al., 2001; Rosenstiel et al., 2003; Possell et al.,
2004; Vuorinen et al., 2004; Wilkinson et al., 2008), or haveno significant effects (Penuelas and Llusia, 1997; Constable et al., 1999; Buckley, 2001; Centritto et al., 2004) on
BVOC production and emissions at the whole plant, shoot,and leaf levels. Laothawornkitkul et al. (2009) stated thatthese contradictory results may be caused by the various factors assessed in each study, including plant species, age, experimental duration, and CO2 concentration, as well as bylimitations in experimental design and implementation. On
balance, increasing CO2 likely causes a decrease in isopreneemissions from the leaf surface. On the other hand, the decrease might be offset by increases in emissions as a resultof increasing vegetation productivity and leaf area growthcaused by elevated CO2 levels (Possell et al., 2005; Arneth
et al., 2007). Heald et al. (2009) incorporated an empirical model of the observed response of isoprene emissions
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to both ambient CO2 in the long-term growth environmentand short-term changes in intercellular CO2 concentration
into the MEGAN embedded within Community Land Model(CLM). They showed that CO2 inhibition has little impact on
predictions of present day global isoprene emission. Lathièreet al. (2010) estimated annual global isoprene emissions from1901 to 2002 while considering the suppressive effect of isoprene emissions by rising CO2 and CO2 fertilization of terrestrial vegetation, and reported that the rising atmospheric
CO2 caused a 21 % reduction during that period.
Müller et al. (2008) estimated global isoprene emissions
from 1995 to 2006 with the MEGAN model, including the effect of isoprene emissions caused by decreased soil moisture.
Müller’s results indicated that isoprene emissions were about
30 % less than the standard MEGAN estimate (Guenther etal., 2006), mainly because including soil moisture decreased
emissions by more than 20 %. Moderate drought may decrease, enhance, or have no effect on isoprene and monoterpene emissions, although severe and long-lasting water stresssignificantly reduces BVOC emissions (Laothawornkitkul etal., 2009). Vegetation classified here as BEF corresponds totropical or seasonal tropical forests with a dry season and awet season. The evergreen vegetation is likely to have deeproots (e.g., Canadell et al., 1996; Nepstad et al., 1994), andthe consequent large water capacity may maintain leaves all
year round (Tanaka et al., 2004). Thus, the emissions from
BEF could be minimally reduced by soil moisture even ina dry period. On the other hand, the emissions from SBG
and BDFW, with high ε for both isoprene and monoterpenes
around BEF, can be significantly reduced by soil moisturestress during dry periods (Table 1, Fig. 1). Therefore, bothof our estimated global emissions may be overestimated because we disregarded the effects of CO2 and soil moisture,even though our findings were within the ranges of the published annual global emissions.
We used monthly instead of hourly data for SAT and DSR
for our estimates of emissions. Because the monthly SAT
value includes lower air temperatures at nighttime, when

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isoprene emissions do not occur, the use of monthly data
might reduce estimated isoprene emissions, but it would haveminimal influence on monoterpene estimates. Lathière etal. (2010) used photosynthetically active radiation with a 1 hinterval, based on monthly data and a scheme proposed by
dePury and Farquhar (1997), to estimate isoprene emissions.
But they did not consider the influence of diurnal patterns on
the estimates, and neither did we. Müller et al. (2008) also
examined how the differences between air temperature andleaf temperature influence estimated isoprene emissions, andshowed that leaves are about 1 or 2 K warmer than their environment in most forested areas, resulting in emission enhancements of about 10 %.
4.2

Contributions of isoprene and monoterpene
emissions in region A5 (Southeast Asia) and inlow latitudes to the annual global-scale emissions

Our estimates demonstrated that region A5 may have madethe greatest contribution to annual global isoprene emissions, in particular from BEF (Fig. 9). The data also suggest that this region may have contributed to the annual
global monoterpene emissions with constant emissions all
year round. These results are consistent with many previous reports (e.g., Guenther et al., 1995, 2006; Müller et al.,2008). However, measurements of BVOC emissions from
BEF at the canopy scale in Southeast Asia have only been
done by Langford et al. (2010), while a relatively larger number of measurements have been done in Amazon forests (e.g.,Helmig et al., 1998; Rinne et al., 2002; Greenberg et al.,
2004; Karl et al., 2007; Kuhn et al., 2007; Müller et al., 2008)
and in Africa (Greenberg et al., 1999; Serça et al., 2001).
Langford et al. (2010) measured BVOC emissions over a
tropical rainforest in Malaysian Borneo and found that theemission rates for isoprene and monoterpenes were 4 and 1.8
times lower, respectively, than the default value for tropicalforests in the MEGAN model used here, so our estimatedemissions for region A5 may be underestimates. On the other
hand, the estimated emissions in the abovementioned studies
on Amazon forests varied widely. Greenberg et al. (2004)
suggested that the different results might be attributable tothe species composition of each ecoregion. Thus, the differences among ecoregions in Southeast Asia may be as large
as in the Amazon. Langford et al. (2010) argued the need formore direct canopy-scale flux measurements of VOCs fromthe world’s tropical forests.
4.3

Decrease in annual isoprene emissions in Southeast
Asia and the expansion of oil palm

The simulated isoprene emissions also demonstrated thatthe influence of land use changes on annual isoprene emissions during the study period were remarkable, in particularin Southeast Asia (Figs. 7–9) and that the effective reduction by the expansion of cropland from BEF, BDFW, andAtmos. Chem. Phys., 12, 9703–9718, 2012

other vegetation was −15.7 % between 1854 and 2000. In
the area (4.47 × 106 km2 ; see Fig. 2), an expansion of palm
oil cultivation has occurred since the early 1980s; by 2006,
the planted area had reached around 6.2 × 104 km2 (BPS,2008) and 4.2 × 104 km2 (MOPB, 2008) in Indonesia andMalaysia, respectively. Oil palm is one of highest isopreneemitters (Owen and Penuelas, 2005; Wilkinson et al., 2006;
Geron et al., 2006; Misztal et al., 2011), and the total area
occupied 2.3 % of the area of region A5. Moreover, the expansion likely continues at the expense of natural forest. The
influence of expanded palm oil cultivation on isoprene emission, however, was not considered in the present study. Misztal et al. (2011) measured BVOC emissions, including isoprene from a 15-yr-old palm oil plantation in Malaysian Borneo, with an eddy correlation system, compared the measurements to those from a nearby rainforest measured by Langford et al. (2010) with the same system, and suggested thatthe isoprene concentrations from the oil palm site were 4 to
8 times greater than the values from the rainforest. Thus, the
9.6 % loss of BEF areas in region A5 during the period from1854 to 2000 was likely offset or exceeded by subsequent
positive effect of substitution with oil palm. Nonetheless, theestimated influences are appropriate before the 1990s, whenoil plantations expanded exponentially. The influence will
become increasingly important with further expansion after
the 2000s. The LAI of an oil palm plantation changes withage, being 2.14 for 5- to 9-yr-old palms and 2.37 for 15-yrold palms in the Malay Peninsula (Awal et al., 2010). Trees
aged 9 to 15 yr are the most productive (Sheil et al., 2009),
which implies that isoprene may be emitted the most during those years. Trees become too tall to harvest the fruits
after 25 to 30 yr, and some long-established plantations in
Malaysia have already been replaced for the third time (Basiron, 2007), indicating that the isoprene emissions should
weaken during the replacement. Palms mature so rapidly thatthe fruit can be harvested as soon as 2 to 3 yr after planting(Basiron, 2007). Thus, such changes in the characteristics ofoil palm with age and plantation management will be essential for estimating isoprene emissions with the expansion ofcropland area in Southeast Asia.

5

Conclusions

We estimated annual global isoprene and monoterpene emissions since the beginning of the industrial age (1850s) with
the MEGAN model (Guenther et al., 2006), based on SAT
and DSR reconstructed by a historical run with MIROC5,
and temporal expansion of cropland. We investigated theinfluences of SAT, DSR, and cropland expansion on bothannual emissions. The expansion of cropland had a lesser
effect on annual global monoterpene emissions (∼ 2 % reduction) than on isoprene emissions (∼ 7 % reduction), because the cropland also contributed substantially to the emission of the former but not the latter. A gradual decrease in
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K. Tanaka et al.: Isoprene and monoterpene emissions since the preindustrial era
SDR decreased isoprene emissions by 2 % between 1854 and2000, but only slightly decreased monoterpene emissions because most monoterpenes (except ocimene) react minimallyto solar radiation. The gradual rise in SAT with large fluctuations increased isoprene and monoterpene emissions by 9 %and 7 %, respectively, between 1854 and 2000. The changes
in both emissions depended on the balance between the increase caused by increasing temperature and the reduction
caused by the expansion of cultivation, and annual global isoprene and monoterpene emissions decreased and increased in
2000, respectively. The influence of cultivation changes onannual global isoprene emissions were most remarkable inSoutheast Asia, because of the replacement of BEF, which
has the most constant and highest emissions, with cropland,
which has the lowest emissions. On the other hand, since oilpalm plantations with very high emissions have expanded
since the 1980s in this area, we discussed the possible influence of oil palm plantations on the estimated influence ofland use changes. Specifically, we suggested that the expansion of oil palm cultivation will likely offset or exceed the decline in emissions caused by loss of broad-leaved evergreen
forest (or tropical rainforest) in the 2000s.

Acknowledgements. This research was supported by the Environment Research and Technology Development Fund (A-0902) of
the Ministry of the Environment, Japan. We are grateful to Takashi
Sakamoto of the University of Tokyo, and Hiroaki Tatebe andYoshiki Komuro of Japan Agency for Marine-Earth Science andTechnology for their helpful comments on a historical climate
data reproduced by MIROC5. We also thank Sou Matsunaga of
Hokkaido University, Akira Tani of University of Shizuoka, Takuya
Saito of National Institute for Environment Studies, and Motonori
Okumura of Kyoto University for helpful suggestions.
Edited by: A. B. Guenther

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