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Journal of Environmental Science & Health Part A

ISSN: 1093-4529 (Print) 1532-4117 (Online) Journal homepage: https://www.tandfonline.com/loi/lesa20

Biogenic vocs emissions and its impact on ozone formation in major cities of China

Min Shao , Meiping Zhao , Yuanhang Zhang , Lxin Peng & Jinlong Li

To cite this article: Min Shao , Meiping Zhao , Yuanhang Zhang , Lxin Peng & Jinlong Li (2000) Biogenic vocs emissions and its impact on ozone formation in major cities of China, Journal of Environmental Science & Health Part A, 35:10, 1941-1950, DOI: 10.1080/10934520009377089

To link to this article: https://doi.org/10.1080/10934520009377089

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J. ENVIRON. SCI. HEALTH, A35(10), 1941-1950 (2000)

BIOGENIC VOCS EMISSIONS AND ITS IMPACT ON OZONE FORMATION IN MAJOR CITIES OF CHINA

Key Wordy: Isoprene, monoterpene, biogenic emission, dependence, ozone

Min Shao*1, Meiping Zhao2, Yuanhang Zhang1, Lxin Peng1, Jinlong Li3

1 State Key Laboratory of Environmental Simulation and Pollution Control, Center for Environmental Sciences; 2 Department of Chemistry;3 Department of Technical

Physics; Peking University, Beijing 100871, P. R. China

ABSTRACT

A measurement campaign was performed in two large cities in China, Beijing

and Guangzhou, to investigate biogenic emissions of volatile organic compounds

(VOCs) using a GC-FID system and the enclosure chamber technique. Four typical

types of trees, namely pine, cypress, poplar and Chinese-scholar tree were studied.

The influences of temperature and light intensity on VOC emissions were analyzed

using algorithms derived from what is currently understood about VOC emission

mechanisms. Biogenic VOC emission fluxes in these two cities were estimated. A

2-D air quality model was developed to assess the role of biogenic VOC emissions in

the ground-level ozone formation in Beijing and Guangzhou.

INTRODUCTION

Within last decade, due to rapid economic development, urban air quality in

China has increasingly worsened. The air pollution is shifting from the problems

Corresponding author; email: [email protected]

1941

Copyright © 2000 by Marcel Dekker, Inc. www.dekker.com

1942 SHAOETAL.

associated with coal-burning to photochemical smog, caused by vehicle emissions in

both Beijing and Guangzhou (Zhang et al., 1998). As the ambient O3 concentration

has dramatically increased, the photochemical smog is becoming a serious air

pollution problem in the city and the surrounding areas. Being one of the major

precursors of atmospheric O3, volatile organic compounds (VOCs) data are essential

for knowing the chemical processes of smog formation. Studies on Biogenic volatile

organic compounds (VOCs), which are much more active in the air than those from

anthropogenic sources, are urgently required for understanding the trends of

atmospheric oxidation potential.

Mechanisms of VOCs emissions from plants have recently been studied

intensively (Sharkey, 1996; Lichtenthaler et al., 1997). Algorithms quantifying the

influence of temperature and light intensity on VOC emission rates were developed

( Guenhter et al., 1993; Schuh et al., 1997) and were employed to estimate VOC

emissions in many regions worldwide (Guenther et al., 1995; Ciccioli et al., 1997). In

China, a measurement campaign has been performed since 1991 to investigate VOC

emissions from the four main genetic types of trees, which are pine (Pinus

Tabulaeformis), cypress (patycladus orientalis), poplar (Populus sp.) and

Chinese-scholar tree (Sophora japonicd). The VOC composition of the emissions

from these trees, the emission rates and the influence of temperature and light were

investigated. By using a two dimensional air quality model, the roles of biogenic

VOC emissions in ground-level ozone formation in Beijing and Guangzhou were

studied.

MATERIALS AND METHODS

VOCs emitted from trees were analyzed using Varian-3400 gas chromatography

with flame ionization detector (GC-FID, fused silicon capillary column: DB-1, 60 m

x 0.3.15 mm i.d.). A chamber enclosure technique was used for sampling, by

wrapping one to several branches or whole plants, depending on the size of the tree.

During sampling, necessary environmental parameters, such as ambient temperature

and light intensity, were also measured. A 1.5 m3 polyethylene polymer bag was used

as the enclosure chamber. Air samples were compressed by a grease-free pump into 4

VOCs EMISSIONS AND OZONE FORMATION 1943

L stainless steel canisters to a pressure of about 2 bar. The canisters were then

connected to sample loading loop of GC-FID, which was kept in a cold trap at

temperature of-80 °C. Air samples were injected under their own pressure into the

loop to be pre-concentrated. Then the frozen samples were programmatically heated

at a speed of 6 °C/min until the temperature reached 200 °C. Under the experimental

conditions, C4-C10 VOCs were sufficiently separated and quantified.

By measuring the concentration differences after a period of time in the

enclosure chamber, the emission rates of VOCs were calculated by:

VmxAxAt K)

where Ovoc is emission rate of the VOC species (ug cm'2 hr'1); ACvoc is

concentration difference (ppb) in chamber during a time period of At (hour); V is the

volume of enclosure chamber (m3), Vm is molar volume (Vm =24 L/mol); A is leaf

area (one side) of enclosed plant (cm2) and M is molecular weight of VOC species.

RESULTS AND DISCUSSION

VOCs Composition and Emission Rate

VOCs emitted from pine, cypress, poplar and Chinese-scholar tree include

isoprene, monoterpene as well as some alkanes and alkenes. The predominant VOCs

species emitted from coniferous species, like pine and cypress, were monoterpenes,

while 90% of the total VOCs released from deciduous trees as poplar and

Chinese-scholar, was isoprene (Table 1). The composition of VOCs from these trees

did not change significantly with the season except for Chinese-scholar tree. It is very

interesting that from the measurements Chinese-scholar trees emitted considerable

amounts of monoterpenes while in blossom, but the monoterpenes emissions were

below detection limits during the non-blossoming stage.

Chinese-scholar is quite a rare species, emitting different VOCs during different

season. It is well known that production of isoprene and monoterpene in plants, are

all compounds-specific enzyme involved processes (Sharkey, 1996). Plants release

different VOCs because they have different internal enzymes. Therefore, the

blossoming of Chinese-scholar trees might also be a process that activates enzymes

1944 SHAOETAL.

TABLE 1 VOCs Species from Emission of Various Trees

( in Parentheses, its Percentage Lower than 1% of Emissions) Tree VOCs species _ _ Pine a-terpiene, a-pinene, d-Iimonene, A3-carene,

isoprene Cypress a-terpiene, a-pinene, d-limonene, A3-carene Poplar isoprene (a-pinene) Chinesescholar tree Non-blossoming: isoprene (n-pentene, n-pentane,

n-nonane) Blossoming: isoprene, a-terpiene, a-pinene, d-limonene, A3-carene

for monoterpene production. Detailed studies are needed for more a complete

understanding of biogenic VOCs emission mechanisms of Chinese-scholar trees.

Not only were the compositions of the VOCs emissions from the four types of

trees different, but also the absolute emission rates differed greatly as well. Table 2

lists emission rates of typical VOCs at constant temperatures and light intensities (25

°C, 300 lux, hereafter set as standard condition). The standard emission rates given in

Table 2 did not show systematic seasonal variation in our measurements.

Chinese-scholar tree had a relatively wider range of standard emission rates for

isoprene because of the blossoming.

Influence of Temperature and Light Intensity

Temperature and light intensity are believed to be the most important factors for

short term biogenic VOCs emissions (Schuh et al., 1997). For conifers, the influence

of light on monoterpene emissions, from pine and cypress, was neglected, so that

only temperature dependence following the pool evaporation process was considered:

CT (2) î T • Ts

where O,erpene is the emission rates of VOC (ug cm" 2 hr"1) at leaf temperature T (K),

and Osterpene is Standardemission rate); Cy/R is an empirical constant.

Figure 1 shows the measurement results for pine which fit the above algorithm.

The CT/R value for a-terpinene was 19980 ± 8500. The value for Cypress

VOCs EMISSIONS AND OZONE FORMATION 1945

TABLE 2 The Emission Rates of VOCs Emitted from Typical Types of Trees

Types

Typical compounds

'ï'voc (Hg/cm2-hr)

Pine

Monoterpenes

0.14-0.34 i

Cypress

Monoterpenes

>.7xl0'4-28.2xl0'4

Poplar

Isoprene

0.10-0.14

Chinesescholar tree

Isoprene

0.016-0.11

2.5 2.0 1.5 1.0

S 0.5 0.0 -0.5 -1.0 -1.5

0.00330 0.00335 0.00340 0.00345 0.00350

l/T (IC1)

FIGURE 1 Temperature dependence of a-terpinene emission rates from pine.

-

- lnE = -19980/T + 68. 686 r2 = 0.9294

1 i 1

monoterpene emission rates obtained from the fitting was 18750 ± 7400. This was

generally in agreement with the results reported by Goldan et al. (1995).

The isoprene emission rates, of the two deciduous trees, were both temperature

and light sensitive. Guenther et al. (1993) developed an algorithm to describe

biogenic isoprene emissions:

<b iso prene = «5 isoprene • C L a • I

exp R

T - Ts

\ + a 2 • I2 1 + exp - T2

R

T - T M T - 7 \

(3)

where Ojs o p r e n e is the isoprene emission rate at leaf temperature T (K) and light

intensity 1 (lux). OSjSOprene is the standard emission rate; CL, a and CTI and Cj2 are

empirical constants; TM is optimal enzyme temperature. Since the leaf temperature T

1946 SHAOETAL.

is normally much lower than TM, which is generally around 318 K, the denominator

of the temperature term can be set as 1.

The fit for poplar isoprene emission rates obtained the parameters CL, a and CTi.

The result of the fit is shown in Figure 2, when leaf temperature T was 302+2 K.

It is noteworthy that isoprene emission rates of pine showed a very similar

diurnal variation as the monoterpenes (Figure 3). The plot showed that monoterpene

emission rates were nearly constant at the same temperature, whether during the day

or at night, but the nocturnal isoprene emission rate was nearly 1/3 of the daytime

emissions, under similar temperatures. This result suggested that the algorithm (3)

cannot explain isoprene emissions from pines. The algorithm of Schuh et al. (1997)

was proved as a tool to describe the behavior. The algorithm assumed that biogenic

VOC emissions were due to two independent processes: pool evaporation and

biosynthesis related activities.

In field measurements, it was difficult to investigate the influence of temperature

and light intensity on VOCs emission rates independently. To make an estimate with

reasonable precision of the VOC flux on a city scale, we adopted algorithm (2) to

describe monoterpene emissions from pine and cypress trees, and used algorithm (3)

to simulate isoprene emissions form poplar and Chinesescholar trees.

Emission Flux Estimate

The seasonal variations of both isoprene and monoterpene emissions were

assumed here to be due to temperature and light intensity changes. In our estimation,

an annual mean temperature was chosen to be 11.5 °C. Effective isoprene emission

time in a year was estimated to be 2100 hours, because nocturnal and winter

emissions were under the detection limits. Isoprene emissions from pine were

excluded, because the total amount was negligible at the city scale. Monoterpene

emissions from Chinese-scholar trees were not taken into account because its quantity

was unavailable.

Based on the data and assumptions above, the isoprene and monoterpene

emission flux in Beijing was calculated and listed in Table 3.

By integrating the data of forest area information into VOCs emission rates, the

flux of biogenic VOCs in Beijing was estimated. The VOCs emissions from

VOCs EMISSIONS AND OZONE FORMATION 1947

~ 0.150 JZ

% 0.140

0.130

cd S 0.120 o "3 0.110

CO

w 0.100

-Emission rate (measured) Emission rate (modeled))

250 300 350 400

Light intensity (Lux)

450

FIGURE 2 Isoprene emission rates from poplar fit to algorithm of Guenther et al. (1993).

0.500

0.400 cd j a u f 0.300 c N co g

CD

•- 3- 0.200

0.100

0.000

-a-terpinene •isoorene (xlOO)

b-pinene temperature

35.0

25.0

5.0

-5.0

15.0 £ cd

eu

eu

- v v <b-

Time (measured in May 8-9, 1993)

FIGURE 3 Diurnal variation of isoprene and selected monoterpene emission rates of oil pine.

TABLE 3 Isoprene and Monoterpene Emission Flux in Beijing

Species Pine Cypress Poplar Chinesescholar Compounds Forest area * (106 m2) Emission flux (Ton/Year)

monoterpene monoterpene isoprene isoprene 163 163 492 492

5100 51 1500 3000

* The specified forest areas for individual tree species are not available, it was assumed that pine and cypress has the same sharing in area of conifer, poplar and Chinese-scholar tree has the same sharing in area of deciduous forest.

1948 SHAOETAL.

VOCs Emissions in Sources

Beijing Guangzhou

Industries

2.91 6.11

Beijing TABLE 4

and Guangzhou Area Vehicular source emissions 0.42 0.44

5.07 7.88

Cities (104 ton Biogenic emission 4.97 12.15

C/year) Total

13.37 26.60

TABLE 5 The Influence of VOCs Emission on Urban Ozone Concentration

Beijing

Guangzhou

Biogenic sources

1* 0 1 1 0 1

Manmade sources

1 1 0 1 1 0

Ozone concentration (daily average,

ppb) 44.6 37.0 8.6 63.1 30.9 41.4

Change of ozone

concentration (%)

Current -17.0 -80.7 Current -51.0 -34.4

* 1 means 100% of current emissions.

anthropogenic sources were investigated in the UNDP CPR96/305 project. The same

procedure was implemented for Guangzhou city (Table 4). For use in the air quality

model, isoprene and monoterpene data were summed up. Both were considered as

double-bond molecules in the CBM-IV chemical mechanisms.

The Role of Biogenic VOCs in Ozone Formation

A 2-D Eulerian air quality model was developed to simulate the ozone formation

in Beijing (Peng, 1999). This model has two dimensions at horizontal level, and

vertically ranged from the ground to the mixing layer height. It adopts the CBM-IV

mechanism for chemical reactions. The inputs of the model were the wind field, the

diffusion coefficient, the mixing layer and the source inventory.

To assess the influence of VOCs emissions in urban ozone formation, two

scenarios were set for both Beijing and Guangzhou, in which biogenic VOCs and

anthropogenic VOCs were assumed to be zero. From the model run, the

corresponding ground-level ozone reductions were obtained (Table 5).

VOCs EMISSIONS AND OZONE FORMATION 1949

The 2-D air quality model showed that ground-level ozone concentrations were

sensitive to VOCs in both cities. The results in Table 5 demonstrated that

anthropogenic VOCs emissions played key role in the control ozone concentrations in

Beijing. But in Guangzhou, biogenic VOCs emissions were more important than

manmade sources in ozone formation, indicating that ozone abatement in Guangzhou

would be a very hard task.

CONCLUSION

The isoprene and monoterpene emissions from the four main tree species were

investigated. The deciduous trees Poplar and Chinese-scholar trees were found to be

big isoprene emitters, and light intensity was the most important environmental

parameter affecting the emission rate. The Chinese-scholar tree emits monoterpene

during the vegetative stage of blossoming. Further studies are required to examine the

detailed plant physiology of this process and determine the methodology to quantify

the monoterpene emission rates, if the emissions are locally important.

The monoterpene emission from conifers can be modeled following a pool

evaporation process and hence only leaf temperatures are dependent. Isoprene

emissions of oil pine are quantitatively less important though, it has been revealed

that both light intensity and temperature may have influence on its emissions from the

two independent processes: pool evaporation and processes in parallel with

biosynthetic activities.

Biogenic VOCs emission fluxes in Beijing and Guangzhou were estimated.

Together with investigations of other VOC emission sources, a 2-D air quality model

was employed to simulate ground-level ozone concentrations in both cities. It is

revealed that in Guangzhou biogenic sources contribute slightly less than

anthropogentic emissions, but have a more important role in ozone formation. The

ground-level ozone concentration in Beijing was mainly controlled by VOCs from

manmade sources.

ACKNOWLEDGEMENTS

This research work was partly supported by UNDP project CPR/96/305. The

1950 SHAO ET AL.

authors would like to express gratefulness to Dr. Juergen Wildt for the valuable

discussion about biogenic emission mechanisms.

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