Kim Y.J. (Ed.) Advanced Environmental Monitoring

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7 Aircraft Measurements of Long-Range 101

Fig. 7.7 Divided air-pollution regions in Northeast Asia (a) and HYSPRIT backward trajectory

(b) for the measurement period

I II III

100

120

140

I II III

Air Pollution Regions

Concentration (ppb)

Air Pollution Regions

Fig. 7.8 Box-plots of air pollutant concentrations in relation to regional distributions (see Fig.

7.6a) for 2005

102 S.-N. Oh et al.

Particle Number

1 10 100 1000 10000

500

1000

1500

2000

2500

3000

Particle Number

Concentration (ea/cm

)

Concentration (ea/cm

)

1 10 100 1000

10000

500

1000

1500

2000

2500

3000

Yellow Sea

Inland

Yellow Sea

Inland

East Sea

Altitude (m)

Fig. 7.9 Vertical distributions of particle number over the Yellow Sea and East Sea obtained by

aircraft and inland of Korea at Tea-An on April 21(a) and October 21(b), 2005

markedly with a northerly and northwesterly flow in association with the passage

of a cold front.

Park (1998) showed that the Shandong peninsula had a high density of SO

emission, with an annual emission amount per 10,000 km

in 1996 of more than

0.1 Mt. This region is located just 300–500 km west of the Taean region in Korea.

Therefore, favorable meteorological conditions could lead to the transport of sulfur

compounds from the Shandong region to the west coast of Korea within a day.

7.3.2 Aerosol and Ozone

Ozone concentration decreased markedly with altitude from 52–63 ppb to 32–

41 ppb on April 18, but aerosol number concentration showed a significant

increasing trend.

The concentrations of fine particles of the atmosphere over inland and ocean areas

measured at the Taean background site showed no variation of altitudinal concentra-

tions during the period April 15–21 but wide variation during October 15–22, as

shown in Fig. 7.9. The overall mean mass concentration was 13.0 µg/m

However, the amount of ammonia gas over open oceans should decrease due to

deposition. Thus, gaseous nitric acid produced during transport over the oceans

should deposit onto large particles. Nitrate is known to exist in a coarse mode in

aerosols in relatively clean air (Jordan et al. 2003; Shimohara et al. 2001; Song and

Carmichael 2001) because gaseous nitric acid quickly deposits on pre-existing

large particles. Only fine liquid particles of sulfuric acid, also formed during the

transport, can absorb ammonia gas and undergo neutralization (Hatakeyama et al.

2004). These facts help to explain the situation observed over the western Pacific

region close to the Asian continent.

7 Aircraft Measurements of Long-Range 103

7.3.3 Flux of Air Pollutants

Studies on the flux of air pollutant transport in the atmospheric boundary layer using

aircraft measurements has been introduced by Lelieved et al. (1989). The flux estima-

tion of air pollutant transport in the region of the Korean peninsula has been con-

ducted by Kim et al. (1997) and Han et al. (2006) using aircraft data gathered from

1997 to 2004. Their results indicated that the influx of SO

was approximately five

times higher than the outflux when considering yearly flux variation, and that there

was a decreasing long-term trend since 1998. NO

outflux averaged 0.095 ton/km/h

and was three times higher than the SO

outflux. The influx and outflux of O

showed

an even distribution on a yearly basis, except for 2002 (influx of 5.45 ton/km/h).

It is important to understand the degree to which the net flux of air pollution

transport varies in the region of the Korean peninsula, including the west ocean area

as influenced by influx from China and outflux to the Korea region.

In this study, the flux amount (F) at the aircraft flight level was calculated using

the following similarity relationship:

FCHLU=

−

10 sinQ

(1)

where F is the transport flux (ton/h/km), C the concentration (ppbv) of air pol-

lutants, H the height of the atmospheric boundary layer (m), L the horizontal flight

distant (km), U the mean wind speed (km/h) in the boundary layer, and Q the angle

between the aircraft flight and mean wind directions.

Table 7.3 Influx and outflux calculations of air pollution transport in the boundary layer over the

west Korean ocean region during the aircraft measurement period

Sampling

time Longitude

Concentration (ppb) F (ton/h/km)

H (m) L (km) U SO

′05.04.15 124°30′ 1.18 2.3

500 111 −2.14 −0.01 −0.35 −0.38

′05.04.16 124°10′ 3.5 3.1 56 800 111 8.48 0.24 0.15 2.96

′05.04.16 125°30′ 1.8 2.5 58 800 111 8.48 0.13 0.12 3.03

′05.04.16 127° 0.6 2.8 52 800 111 8.48 0.04 0.14 2.72

′05.04.17 124°10′ 1.2 2.5 63 800 111 5.08 0.05 0.07 1.98

′05.04.17 125°30′ 1.2 2.5 62 800 111 5.08 0.05 0.07 1.94

′05.04.17 127° 2.3 3.9 67 800 111 5.08 0.1 0.11 2.1

′05.04.18 124°30′ 12 12.6 88 1,500 111 8.45 1.57 1.14 8.62

Average

in 0.31 0.26 3.33

out 0.01 0.35 0.38

′05.10.16 124°10′ 4.8 3 50 1,200 111 −1.51 −0.09 −0.04 −0.7

′05.10.16 125°30′ 2.7 2.1 45 1,200 111 −1.51 −0.05 −0.03 −0.64

′05.10.16 127° 2.5 5.4 45 1,200 111 −1.51 −0.05 −0.07 −0.64

′05.10.17 124°30′ 17.7 5.8 85.7 1,000 111 −1.6 −0.29 −0.06 −1.057

′05.10.19 125° 1.7 1.8 44.8 1,500 111 0.4 0.01 0.008 0.208

Average

in 0.01 0.008 0.208

out 0.12 0.05 0.76

104 S.-N. Oh et al.

The results indicate that influxes were larger than outfluxes in April but smaller

in October, as shown in Table 7.3 The larger outflux than influx of October sug-

gests emission from the Korean region. The outflux of NO

was on average 0.35

and 0.05 ton/km/h in April and October, respectively. The average influx of O

was

3.33 ton/km/h and 0.21 ton/km/h during the measurement periods in April and

October, respectively. The influx of the three gases into the Korean peninsula was

extremely large on April 18, when the wind in the boundary layer blew strongly

from a northwesterly direction.

7.4 Conclusions

Observations of the long-range transport of the trace gases SO

and O

in the

atmospheric boundary layer were conducted over the ocean area “transport corri-

dor” between the Korean peninsula and China using measurements obtained by

aircraft during April 15–22 and October 15–25, 2005. The objectives of gathering

measurements by aircraft were to study the spatial distribution of pollution in the

ocean atmosphere between Korea and China, and to improve our understanding of

acidic deposition in the Korean area in relation to processes affecting the transport

of long-range trans-boundary air pollutants from China.

Aircraft measurements of gas concentrations (ppbv) for SO

, NO

and O

were

2.58, 4.24 and 54 in April and 6.63, 3.74 and 48.8 in October, respectively. Changes

in concentration of the three gases with respect to altitude were only investigated on

April 18 and October 17, 2005. The highest concentrations of the three gases were

recorded around an altitude of 500 m on April 18 and at 800 m on October 17, 2005.

The highest concentrations of SO

at these altitudes were greater than 20 ppb, while the

concentration of NO

was higher than 10 ppb for both flight days. The results suggest

that the high concentrations at low altitude were the result of the transport of air pollu-

tion emission from China, while the high concentration at 500 m was due to strong

wind from the west. The concentrations of O

were greater than 80 ppb (and up to

110 ppb on April 18) at these altitudes on both observation days. The lower concentra-

tions of these species at higher altitudes were related to the highest water mixing ratio.

Lower concentrations of SO

and NO

were measured at an altitude of 1,000 m.

Ozone concentration decreased markedly with altitude from 52–63 ppb to

32–41 ppb on April 18, whereas aerosol number concentration showed a significant

increasing trend.

The concentrations of fine particle in the atmosphere over inland and ocean

areas measured at the Taean background site showed no variation with respect to

altitude during the period April 15–21, but exhibited wide variation during October

15–22, as shown in Fig. 7.9. The overall mean mass concentration was 13.0 µg/m

Flux analysis indicated that influxes of air pollution were larger than outfluxes in

April but smaller in October. The larger outflux than influx suggests emission from

the Korean region. The influx of the three gases into the Korean peninsula was

extremely large in spring, when the wind in the boundary layer blew strongly from

a northwesterly direction. Correlations between O

and NO

showed interesting

7 Aircraft Measurements of Long-Range 105

changes that were related to the distance from the emission source. O

and NO

showed a negative correlation, which indicates that the pollutants in the air masses

are very clean. During the process of transport, most of the acidic sulfates and

acidic gases were mixed with regional air pollutants such as chlorides and nitrates

existing in the metropolitan Seoul area.

The pathway of the air mass based on backward trajectory analysis indicated

that air pollution transport was affected predominantly by a northwesterly flow at

ground level. The high concentration of SO

was measured when the most of the

air flow passed through region III of central China in April and region II of southern

China in October. Flux analysis revealed that the influx was greater than the outflux

in April but smaller in October for the west ocean of Korea.

Acknowledgements The research described in this paper was conducted with financial

support from the Long Range Trans-boundary Air-Pollution project of the Korea

Ministry of Environment, Korea in 2005.

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Han J.S., Ahn J.Y., Hong Y.D., Konh B.J., Lee S. J., and Sun W.Y. 2006, The vertical distribution

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of Asian air pollutant to North America, Geophys. Res. Lett., 26, 26711–26714.

Jordan C.E., Dibb J.E., Anderson B.E., and Fuelberg H.F. (2003), Uptake of nitrate and

sulfate on dust aerosols during TRACE-P, J. Geophys. Res., 108(D20), 8817, DOI

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Kim B.G., Cha J.S., Han J.S., Park I.S., Kim J.S., Na J.G., Choi D.L., Ahn J.Y., and Kang C.G.

(1997), Aircraft measurement of SO

, NO

over Yellow Sea Area, Journal of Korea Air

Pollution Research Association., 13(5), 361–369.

Kim B.G., Han J.S., and Park S.U. (2001), Transport of SO

and aerosol over the Yellow sea,

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Lelieved J., Janson F.W., and Dop H.V. (1989), Assessment of pollutant fluxes across the frontiers

of the Federal Republic of Germany on the basis of aircraft measurement, Atmos. Environ., 23,

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Nunnermacker L.J., Weinstein-Lloyd J., Kleinman L., Daum P.H., Lee Y.N., Springston S.R.,

Klotz P., Newman L., Neuroth G., and Hyde P. (2004), Ground-based and aircraft measure-

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Chapter 8

Optical Remote Sensing for Characterizing

the Spatial Distribution of Stack Emissions

Michel Grutter

, Roberto Basaldud

, Edgar Flores

, and Roland Harig

Abstract In this contribution, optical methods based on passive FTIR (Fourier

Transform Infrared) and DOAS (Differential Optical Absorption Spectroscopy)

techniques have been used to characterize the dispersion of gas emissions from

industrial sources. Portable, zenith-looking, passive-DOAS instruments measured

the horizontal distribution of an SO

plume from a power plant in a coastal town

of Mexico. The column density of this gas was measured while making traversals

across the plume with a car and a boat downwind from the emission source. The cross

sections measured at different distances from the source are used to characterize

the horizontal dispersion and to estimate emission ﬂ uxes. In addition, a Scanning

Infrared Gas Imaging System (SIGIS) was used to acquire passive IR spectra at

4 cm

−1

resolution in a two-dimensional array, from which a false-color image is

produced representing the degree of correlation of a speciﬁ c gaseous pollutant.

The 24-h, real-time animations of the SO

plume help us to understand dispersion

phenomena in various atmospheric conditions. The wealth of information retrieved

from these optical remote sensors provides an alterative method for evaluating the

results from plume dispersion models.

Keywords: Industrial emissions, optical remote sensing, passive DOAS, passive

FTIR, plume dispersion

8.1 Introduction

The dispersion of atmospheric pollutants from stacks is often characterized by

mathematical models which predict the ground-level concentrations from

meteorological, topographical and emission data. Tall stacks do not eliminate the

Centro de Ciencias de la Atmósfera, Universidad Nacional Autónoma de México, 05410

México D.F. México

Institut für Messtechnik, Technische Universität Hamburg-Harburg, 21079 Hamburg, Germany

107

Y.J. Kim and U. Platt (eds.), Advanced Environmental Monitoring,

107–118.

108 M. Grutter et al.

pollution to the atmosphere, but they do aid in reducing ground-level concentrations

and their potentially harmful or damaging effects (Schnelle and Partha 2000).

The tall stack, however, may not always provide the best solution when the

atmospheric conditions do not favor long range dispersion. The most widely used

models for regulatory purposes are the deterministic Gaussian plume models. The

performance of such models is commonly evaluated by experimentally determining

the concentration of a pollutant at a number of receptor points and comparing the

measurements with the model output. This task can be expensive, time consuming

and the results may not represent the general performance of the model over the total

area of interest.

In this contribution, we demonstrate how measurements, based on optical

remote sensing, are used to characterize the spatial distribution of stack emissions.

The plume’s structure is determined by two methods based on the radiative

absorption and emission of the polluting gases. The first technique measures the

amount of absorption of solar UV by molecules like SO

and NO

. The radiation is

spectroscopically analyzed so that the column concentration of these gases can be

monitored while moving along a path perpendicular to the propagation of the plume.

This measurement is a cross-section of the horizontal distribution of the plume at

a specific distance from the source. The second technique uses a spectroscopic

analysis of the natural thermal radiation from the plume and surroundings. These

thermal emissions are analyzed with a passive infrared sensor and used to identify

the characteristic emission/absorption properties of specific constituents in the

plume. A two-dimensional image of the vertical distribution of the plume is

constructed by scanning the area around the emission source.

The two measurement techniques were implemented in Manzanillo, a coastal

town with 138,000 inhabitants (INEGI 2005), located on the Pacific coast of

Mexico, in the State of Colima (19.03 N, 104.19 W). A large, oil-fired power

plant, with a maximum capacity of producing 1,900 MW of electricity, is located

approximately 3 km south of the town center. The oil used in this plant has a high

content of sulphur (3–4%) such that the plume produced during combustion is

high in SO

. In the following sections, the measurement techniques will be

described and selected results will be presented.

8.2 Passive DOAS

The Differential Optical Absorption Spectrometer (DOAS) is a widely used

technique for the continuous measurement of atmospheric gases (Platt 1994; Platt

et al. 1979). In its configuration for active sensing, where the light traveling along

an open path is provided by a synthetic radiation source, low detection limits for

the ambient concentrations of various gases (O

, SO

, HCHO, NO

, several

hydrocarbons, aromatic compounds, etc.) can be achieved. This technique is based

on the spectral analysis of the differential absorption by molecules in the ultraviolet

and visible part of the spectrum. The broader extinction of UV light due to other

8 Optical Remote Sensing for Characterizing 109

processes such as dispersion by fine particles is cancelled when processed and thus

not taken into account.

In the passive sensing configuration, as is in the case when dispersed light from

the sun (i.e. from a blue sky) is used as the radiation source, the spectral analysis

is based on the differential absorption of a particular gas or group of gases. The

total amount of molecules in an atmospheric column is determined between the

altitude where the radiation is dispersed and the position of the observer. These

techniques have been used to identify and quantify atmospheric gases both in

industrial (Lohberger et al. 2004) and volcanic (Bobrowski et al. 2003; Lee et al.

2005) plumes.

The scheme used for making passive DOAS measurements in this study is

presented in Fig. 8.1. The dispersed solar UV light is collected with a narrow

field-of-view (<20 mrad) telescope that was built in-house. This consists of a

concave lens (f = 100 mm), a bandpass optical filter (240–400 nm) and a 200-µm

diameter optical fiber. The light is analyzed with a hand-held spectrometer (Ocean

Optics, model S2000), at a resolution of 0.44 nm between 280 and 420 nm. This

devise uses a UV holographic grating, a 2048 element CCD detector and has no

moving parts; hence, it is appropriate for this type of application. The spectra are

recorded using an interface based on LabView that couples each acquisition with a

longitude-latitude fix from a GPS receiver. User defined parameters along with dark

and background spectra are entered prior to each measurement along a trajectory.

The spectra are evaluated following these general steps:

●

Reference spectra of the target gases are generated for each spectrometer

through the convolution of a high-resolution reference spectrum from the

literature or a spectral library. For this purpose the instrumental line shape (ILS),

determined by measuring the emission line from a low-pressure mercury lamp,

is used to produce a reference spectrum with the true resolution of the

spectrometer.

●

A dark spectrum is subtracted from the measured spectrum (blue trace in Fig. 8.2)

to correct the baseline offset.

Fig. 8.1 Schematic diagram of the portable passive DOAS instrument used for measuring column

gas concentrations on a moving platform

110 M. Grutter et al.

●

A differential absorption spectrum (upper orange trace in Fig. 8.2) is created

from the background spectrum measured outside the gas plume and by applying

a high-pass filter.

●

The resulting spectrum is fitted to the reference spectrum (lower trace) using the

software DOASIS (Kraus 2003).

●

is analyzed by fitting the reference (Vandaele et al. 1994) in the region

306–317 nm and taking into account the interference of O

absorptions. NO

(Harder et al. 1997) is evaluated in the 350–390 nm region.

Figure 8.3 presents the results from traversals of a plume over the ocean made

from a small boat that sailed across the Manzanillo Bay. Fig. 8.3a is a map of the

region with the red dot marking the power plant location. The trajectory of the boat

is drawn on the map as a thick black line starting close to the location marked by

the green star and moving in the direction marked by the arrows. The positions of

the plume crossings are shown on the boat trajectory in false colors whose scale is

given in the same figure. The wind rose in Fig. 8.3b shows that winds were

predominately from the southeast, coinciding with the positions where the plume

was detected.

Figure 8.3c is a plot of the SO

column concentration along the trajectory of the

boat. The first large peak in this plot represents the first pass below the plume at

2.5 km (in a straight line) downwind of the source. The SO

profile reveals that the

width of the plume at this distance was 1,250 m, which can be interpreted as its

horizontal dispersion profile. The second and forth passes, approximately 5 km

from the emission source, have widths of 1,500 m. The third pass and furthest from

the source (10 km) had an approximate width of 2,800 m.

Fig. 8.2 Measured spectrum (blue trace) from solar dispersed light in the direction of the zenith

and across a plume. The orange traces are differential absorptions of SO

from the measurement

(upper) and from the reference (lower) spectra