Atmospheric Environment 45 (2011) 2795e2802
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Atmospheric Environment
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Technical note
A novel approach for the characterization of transport and optical properties
of aerosol particles near sources e Part I: Measurement of particle
backscatter coefficient maps with a scanning UV lidar
Andreas Behrendt a, *, Sandip Pal a,1, Volker Wulfmeyer a, Álvaro M. Valdebenito B. b, 2,
Gerhard Lammel b, c, 3
a
b
c
Institute of Physics and Meteorology, University of Hohenheim, Garbenstrasse 30, Stuttgart 70599, Germany
Max Planck Institute for Meteorology, Hamburg, Germany
Research Centre for Toxic Compounds in the Environment, Masaryk University, Brno, Czech Republic
a r t i c l e i n f o
a b s t r a c t
Article history:
Received 14 January 2010
Received in revised form
21 February 2011
Accepted 23 February 2011
The physical and chemical properties of aerosols emitted from a livestock farm were determined by
a novel approach which combines high-resolution lidar measurements (0.33 s, 30 m) with simulations of
a microphysicsechemistryetransport model. This first of two companion papers describes the scanning
lidar measurements of optical particle properties. The lidar system employed laser radiation at a wavelength of 355 nm with a power of 9 W and a pulse repetition rate of 30 Hz. The laser beam was expanded
before transmission to the atmosphere so that it became eye-safe at distances >270 m to the lidar. The
elastic backscatter signal was detected with a resolution of 0.033 s and 3 m. A receiving telescope with
a primary-mirror diameter of 40 cm was used. For this system, we developed a novel method for twodimensional retrievals of the particle backscatter coefficient. With this set up and approach, the lidar was
able to identify the aerosol plume up to a range of w2.5 km from the source, a farm in northern Germany,
in daytime. The measurements confirm that the optical particle properties of the emission plume vary
largely with distance from the source and that the maximum particle backscatter coefficient is found
away from the source. Within a close-to-horizontal scan (elevation angle of 2.3 ), we found a mean
particle backscatter coefficient of 1.5$105 m1 sr1 inside the plume between 1.5 and 2.0 km distance
from the source. Subtraction of the mean particle backscatter coefficient of the background aerosol
present in this case (4.1$106 m1 sr1) yields a particle backscatter coefficient of the livestock aerosols of
1.1$105 m1 sr1. The limited extend of the plume is revealed with the scanning lidar: Scans with
a slightly higher elevation angle of 4.8 did not pick up the plume.
Ó 2011 Elsevier Ltd. All rights reserved.
Keywords:
Livestock aerosols
Aerosoleoptical properties
Scanning lidar
1. Introduction
The impact of livestock facilities on the environment, especially
in areas with dense animal populations, can become significant
(e.g., Denby et al., 2008). Livestock farm emissions are partly
particulate matter and partly gaseous. The emitted gases, like, e.g.,
ammonia, are partly aerosol precursors, so that the farm emissions
contribute directly and indirectly to the aerosol load in the environment (Lammel et al., 2004, 2005). The emissions pose a hazard
* Corresponding author. Tel.: þ49 711 459 22851; fax: þ49 711 459 22461.
E-mail address: [email protected] (A. Behrendt).
1
Present address: Laboratoire des Sciences du Climat et de l’Environnement
(LSCE), Gif-Sur-Yvette, France.
2
Present address: Norwegian Meteorological Institute, Oslo, Norway.
3
Present address: Max Planck Institute for Chemistry, Mainz, Germany.
1352-2310/$ e see front matter Ó 2011 Elsevier Ltd. All rights reserved.
doi:10.1016/j.atmosenv.2011.02.061
to the health of the inhabitants surrounding the sources and to the
farmers working at the facilities (e.g., Cambra-López et al., 2010).
Furthermore, aerosol particles from livestock farm emissions
contribute to the effect of aerosols on anthropogenic climate
change. The uncertainty of this contribution is still large (IPCC,
2007). The experimental quantification of the aerosol emission
from livestock facilities is a prerequisite to characterise the potential impact of these particles. Little is known, about their optical
properties which, however, is an important aspect for assessing
their climate impact. A complicating fact in this context is that
livestock aerosol properties are undergoing rapid changes close to
their sources that affect the composition of particles far away from
the source (Lammel et al., 2005).
So far only a few studies on aerosols originating from livestock
buildings exist. Some research efforts have been performed to
investigate the aerosol emissions of livestock farming using point
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A. Behrendt et al. / Atmospheric Environment 45 (2011) 2795e2802
measurements around the facilities. Takai et al. (1998) made field
surveys of indoor dust concentrations and dust emissions from
various farms with cattle and poultry. Lammel et al. (2004) investigated the constituents of the aerosols emitted from a livestock
facility in southern Germany with ground measurements collected
downwind and upwind of the farm. Some studies exist on the
yearly or monthly amount of emission (e.g. Costa and Guarino,
2009). But no study allowed yet for volume integrated mass
budgeting because of the limitations the experimental studies
based on point measurements have: (1) they cannot adequately
provide the spatial and temporal distribution of plumes, (2) they
cannot resolve the transport processes under different environmental conditions, (3) emissions from the farms are not continuous
and thus measurements at certain times give erroneous results in
case of varying emission rates. As a result, our knowledge is still
insufficient to describe the spatial extent and the transformation
during the transport of livestock aerosols in order to assess their
significance.
This problem calls for the application of remote sensing techniques: Lidar can determine the range-resolved distributions of
optical properties of atmospheric aerosols with high temporal and
spatial resolution up to a range of several kilometers (see, e.g.,
Weitkamp, 2005 for an overview of the lidar technique). In order to
investigate the spatial distribution of aerosol particles, scanning
lidars can be applied (e.g., Piironen and Eloranta (1995), Mayor and
Spuler, 2004).
While lidar has been used for a large number of other atmospheric studies, only a few lidar studies on livestock aerosols have
been reported to date. Hartung et al. (1998) characterised the
aerosol emission from a farm by tilling and reported an increase of
the backscatter signal intensity in one profile. The transformations
of aerosol properties during transport could not be addressed,
partly because of the restrictions for operation of their non-eyesafe lidar. Prueger et al. (2008) investigated the dispersion of
particulate matter outside an animal husbandry by means of eddy
covariance on towers and supported their findings with scanning
elastic lidar measurements that detected the transport of the
plume. Both studies did not quantify optical properties of the
aerosols.
In this study, we employ the scanning aerosol lidar system of the
University of Hohenheim (UHOH) that emits laser pulses with
a wavelength of 355 nm with 30 Hz and 9 W average power. The use
of the frequency-tripled ND:YAG laser radiation compared to the
frequency-doubled or fundamental Nd:YAG laser radiation has two
main advantages: (1) eye-safety for higher laser power and (2) the
possibility to calibrate the lidar measurements with the strong
molecular backscatter signal in the UV and to derive therefore the
particle backscatter coefficient at the laser wavelength with the
method based on Fernald (1984). Larger laser light intensity is also
uncritical for the eye at wavelengths around 1.5 mm. To reach this
wavelength range, however, special lasers have to be developed as
transmitters for aerosol lidar (Spuler and Mayor, 2007; PetrovaMayor et al., 2008). Furthermore, the Rayleigh backscatter cross
section is a factor of (1500/355)4 ¼ 319 weaker at 1.5 mm compared
to 355 nm which is a disadvantage for calibrating the data. At the
time of this experiment, the UHOH lidar detected only the elastic
backscatter signal. Later, rotational Raman channels were added
(Radlach et al., 2008) to the system that allow the independent
measurement of the particle backscatter coefficient and the particle
extinction coefficient (Behrendt et al., 2002) as well as temperature
measurements (Behrendt, 2005; Groenemeijer et al., 2009;
Radlach, 2009; Behrendt et al., 2010).
To allow for volume integrated mass budgeting, our lidar
measurements were combined with in-situ measurements and
large-eddy-simulation modelling within a collaborative project of
UHOH and Max Planck Institute of Meteorology. The field campaign
(hereafter named PLUS1 campaign) was conducted in the framework of the BW-PLUS (Baden-Württemberg Programm Lebensgrundlage Umwelt and ihre Sicherung) programme. This paper, the
first of the two parts, provides a description of the UHOH scanning
lidar system and discusses the technique to derive the particle
backscatter coefficient. In a companion paper (Valdebenito et al.,
2011), results obtained with the UHOH scanning lidar and with
a high-resolution atmosphereemicrophysicsechemistry model are
combined.
This paper is organised as follows: Technical details of the
UHOH scanning lidar system are presented in Section 2. A
description of the lidar data analysis technique is given in Section
3. An overview of the lidar results of the PLUS1 campaign is given
in Section 4. The combination of the lidar measurements with
results of a large-eddy-simulation aerosol-optical-property model
are outlined in Section 5. A summary and an outlook are given in
Section 6.
2. Set-up of the scanning lidar
Fig. 1 shows a scheme of the scanning lidar of University of
Hohenheim. The whole system is mounted in a truck so that it can
be transported for field deployments. A flash-lamp-pumped
frequency-tripled Nd:YAG laser (GCR5-30 of Spectra-Physics) with
a pulse repetition rate of 30 Hz and a pulse energy of w300 mJ at
a wavelength of 355 nm is used as laser transmitter. The pulse
length is 5 ns. The radiation at 355 nm is separated from radiation
at 1064 and 532 nm (primary and secondary Nd:YAG laser radiation) with a beam splitter and transmitted after 6-fold beam
expansion with a diameter of 6.5 cm to the atmosphere. By the
expansion, the beam divergence is reduced to <1 mrad full width
at half maximum. The expansion reduces the energy density to
such a low level that the output mirror coatings are protected and
eye-safety according to the standards of DIN (Deutsches Institut
für Normung, the German Institute for Standardization) is met for
ranges larger than 270 m from the lidar taking the inhomogeneous
energy distribution within the beam profile into account.
Using three mirrors, the laser beam of the UHOH lidar is
reflected to the center of the receiving telescope and then upwards
to the scanner mirrors which reflect both the laser beam to the
atmosphere and the light backscattered from the atmosphere to the
receiving telescope. The light transmitted to the atmosphere is
linearly polarized but no polarization sensitive optical components
are installed in the receiver.
The beam-steering scanner mirrors are moved independently
by two servomotors that are controlled with a LabView programme. With the use of sliding contacts, uni-directional non-stop
scanning motion can be performed. The coating of the scanner
mirrors shows more than 95% reflectivity within the wavelength
range of 350e1500 nm.
After being collected by the telescope (RitcheyeChrétiene
Cassegrain configuration, 40 cm primary-mirror diameter, 10 cm
secondary-mirror diameter, f/10 focal-length ratio), the backscattered light is focussed on a field stop diaphragm and is then
collimated with a lens. The background light is reduced with an
interference filter (bandwidth of 8 nm FWHM). The received signal
is then focused and detected with a photomultiplier tube (PMT),
Hamamatsu R7400- U02 which shows a noise-free gain of the order
of 105. The amplified signal is then sent to a 14-bit analogue-todigital converter (Compu-Scope 14100) which has a sampling rate
of 50 MSamples/s resulting in a range resolution of 3 m of the lidar
raw data. A detailed description of the data acquisition software can
be found in Pal (2009).
A. Behrendt et al. / Atmospheric Environment 45 (2011) 2795e2802
2797
Fig. 1. Set-up of the scanning lidar system of University of Hohenheim. BSU: beam-steering unit (scanner), BS: Beam Splitter, BE: beam expander, PD: Photo-Diode, IF: interference
filter, L: lenses, PMT: photomultiplier tube.
3. Lidar data analysis of backscatter coefficient maps
with IðrÞ ¼ PðrÞ,r 2 for the range-corrected backscatter signal
measured with the lidar,
3.1. Technique to determine the backscatter coefficient
The elastic-backscatter signal at 355 nm allows for measurements of the backscatter coefficient by analytical inversion of the
lidar equation (Fernald, 1984). In practice, the backscatter signals
P(r) are measured at discrete ranges r and the backscatter coefficient can be calculated stepwise with step length Dr (equal to the
range resolution of the data) via
bðr DrÞ ¼
bðrÞ ¼ bmol ðrÞ þ bpar ðrÞ
(2)
for the total backscatter coefficient, the sum of the molecular
and the particle backscatter coefficients. Spar and Smol are
the extinction-to-backscatter ratios for particle backscattering
and molecular scattering, respectively. Smol is constant with range,
i.e.,
Iðr DrÞ exp Spar Smol ðbmol ðr DrÞ þ bmol ðrÞÞDr
IðrÞ
Spar IðrÞ þ Iðr DrÞ exp Spar Smol ðbmol ðr DrÞ þ bmol ðrÞÞDr Dr
bðrÞ
(1)
Smol ðrÞ ¼
A. Behrendt et al. / Atmospheric Environment 45 (2011) 2795e2802
amol ðrÞ
8p
¼
bmol ðrÞ
3
(3)
with amol(r) for the molecular extinction coefficient.
Calibration of the lidar is accomplished by using the backscatter
signals in the far range of each radial profile and stepwise backward
integration. At the initialization range rini, the total backscatter
coefficient
bðrini Þ ¼ bmol ðrini Þ þ bpar ðrini Þ
(4)
is prescribed. The initialization in the far range and backward
integration down to the lidar has the advantage that the impact of
initialization errors at rini on bpar(r) decrease quickly with
decreasing r because I(r) grows exponentially due to a combination
of geometric effects, extinction, and increasing number density.
The radial profile of bmol(r) is calculated with
bmol ðrÞ ¼
spRay;p
NðrÞ
4p
(5)
with molecular number density N(r), total Rayleigh scattering cross
section s, and the Rayleigh phase function in backward direction
PRay,p. s and PRay,p were calculated for the laser wavelength of
355 nm with the formulae given by Bucholtz (1995). The molecular
number density N(r) was determined from pressure and temperature profiles. Pressure and temperature were measured at the
ground. The pressure profile was calculated with the hydrostatic
equation. For the temperature profile, the profile of a standard
atmosphere was scaled with the ground temperature.
For the particle extinction-to-backscatter ratio, the so called
lidar ratio,
Spar ðrÞ ¼
apar ðrÞ
bpar ðrÞ
(6)
a constant value of 39 sr was used, a typical value at 355 nm for
continental atmospheric-boundary-layer (ABL) aerosols (Pappalardo et al., 2005). The selected value is within the range of values
simulated with the atmosphereemicrophysicsechemistry model
(Valdebenito et al., 2011). We like to point out that the lidar ratio
can be measured together with the temperature field with high
temporal resolution by the detection of rotational Raman signals
(Behrendt et al., 2002; Behrendt, 2005) which makes assumptions
on the lidar ratio and temperature profile obsolete. Such an
extension was added to the UV lidar of UHOH (Radlach et al., 2008)
after the PLUS1 campaign.
Before the Fernald method is applied to the measured lidar
signals, the signal background is subtracted, erroneous profiles
with saturation effects (from trees, cloud boundaries etc.) are
deleted, and the raw data are averaged in time and in range to
increase the signal-to-noise ratio.
The application of the inversion technique of Fernald (1984) is
straightforward for vertically pointing lidar; the initialisation can
be made in the free troposphere or even the stratosphere where
one height rini with low aerosol content and thus small bpar(rini) is
usually found so that initialisation uncertainties are small. The
uncertainties of the lidar inversion technique were discussed, e.g.,
in Sasano and Nakane (1984), Sasano et al. (1985), Bissonnette
(1986), Matsumoto and Takeuchi (1994), Kovalev (1995), and
Ackermann (1998). Note that once the particle backscatter coefficient has been calculated with the Fernald method, the particle
extinction coefficient follows from Eq. (6).
For low-elevation measurements, the initialization cannot be
performed in high altitudes like for vertical measurements. A
calibration point above the ABL would be at such large range that
the lidar backscatter signal would show too low signal-to-noise
ratio to be analyzed. Inside the ABL, the aerosol load is usually not
low and thus the initialization uncertainty would be significant if
the initialization point is set here without supporting the selected
values for bpar(rini) by additional information.
Sasano (1996) described an approach to derive the particle
backscatter coefficient from scanning lidar measurements with an
iterative approach. The Fernald algorithm is first initialized with the
pure-molecular backscatter coefficient at the boundaries of a box
and radial profiles bpar(r) are calculated. The resulting particle
backscatter coefficient field is horizontally averaged to one vertical
profile. These values are used for initialization at the box boundaries in the next step. This approach has the disadvantage that
aerosol sources within the scanned volume are not taken into
account and horizontally homogeneously distributed aerosol has to
be assumed.
We have developed a different approach. Our calculation of the
particle backscatter coefficient from the detected radial lidar
signals makes use of measurements of bpar(r) in the vicinity of the
initialization range from previous radial profiles with a step-wise
method as illustrated in Fig. 2. The retrieval starts with radial
profiles of high elevation angle. If the initialisation is performed at
fixed range rini from the lidar, the initialisation range rini reaches
lower and lower altitudes during the range-height-indicator (RHI)
scan. As long as the calibration point is above the ABL and bpar(rini)
is low, the initialisation can be performed similar to vertical
profiling, e.g., with bðrini Þzbmol ðrini Þ if bpar ðrini Þ << bmol ðrini Þ. For
radial profiles of lower elevation angle, the initialisation range
reaches the aerosol-loaded regions within the ABL. For these
profiles, bpar obtained at the same height with the previously
analyzed radial profile is used for the initialisation. The same
approach is applied on the opposite side of the RHI scan. When
preparing this publication, we found that a similar calibration
method has been described by Machol et al. (2009) in parallel to us
who used a few elevation angles (typically just 4 at 2, 6, 20, 90 ) to
extend the aerosol backscatter profile to close to the ground by
assuming a horizontally homogeneous atmosphere.
As can be seen in Fig. 2, that the closer q is to the horizon, the
larger becomes the distance between the initialization point and
the point where the initialization value is taken from. This can be
a problem, if scanning data with large-elevation-angle steps Dq are
Elevation angle, °
4.0
Height AGL,
km
2798
120
110
100
90
80
70
60
130
3.0
50
140
40
150
2.0
30
160
1.0
0.0
20
170
180
10
0.0
1.0
2.0
3.0
0
4.0
Distance, km
Fig. 2. Initialisation scheme applied to obtain the field of particle backscatter coefficient bpar in the area marked with the bold black line. In this examples, the initialisation is performed at constant range rini ¼ 3.5 km from the lidar. The lidar is located at
distance ¼ 0 and height above ground level (AGL) ¼ 0. The retrieval starts with highelevation-angle profiles. For those radial profiles for which the initialisation point at rini
(open circles) is above the ABL (grey area) and bpar(rini) << bmol(rini), the initialisation
can be made with b(rini) z bmol(rini). For low-elevation-angle scans for which the
initialisation range of 3.5 km lies inside the ABL (open circles with arrows), the particle
backscatter coefficient bpar at the same height of the previous profile is used (filled
circles). For clarity, a low angular resolution of the elevation angle of 5 is used in this
sketch.
A. Behrendt et al. / Atmospheric Environment 45 (2011) 2795e2802
used. Then, as alternative to our scheme, the initialization is
sometimes better performed with the previous bpar profile at fixed
distance Dr to rini. Whether the scheme of Fig. 2 is advantageous or
this alternative scheme can be decided by comparing Dr with
Dx ¼ rini cosðqÞ rini
sinðqÞ
tanðq DqÞ
(7)
with the minus (plus) sign for q smaller (larger) than 90 . As long as
Dx < Dr, the scheme of Fig. 2 is advantageous because of the smaller
distance of the initialization point to the point from which the
initialization value is taken from.
Because of the remaining initialization uncertainties, though
reduced by our approach, we decided to select a value of rini in the
far range, i.e., typically Dr ¼ 500 m (corresponding to 17 range bins)
away from the region of interest. The large number of integration
steps when calculating bpar assures small dependence of the results
on the uncertainty of b(rini). We use data with Dq ¼ 0.16 . From
Eq. (7), we see that the approach of Fig. 2 is then advantageous
down to close the horizon.
3.2. Measurement example
An RHI scan of the particle backscatter coefficient obtained by
applying the technique described in the previous section is shown
in Fig. 3. The scan started just above the horizon with 5 elevation
and extended to 175 elevation. The scan speed was 0.5 s1 to
provide high angular resolution so that the scan required approximately 6 min to be completed. For the initialization range rini,
a value of 3.5 km was chosen. The raw data were averaged over 10
range bins and 10 laser shots resulting in a range resolution of 30 m
and an elevation angle resolution of 0.16 . With rini ¼ 3.5 km, q ¼ 5 ,
and Dq ¼ 0.16 , we get Dx ¼ 109 m with Eq. (7) which fulfils the
condition Dx < Dr for Dr ¼ 500 m.
2799
The bpar field shows the typical aerosol-loaded ABL by higher
values of bpar between 2.5 and 6.0$106 sr1 m1 at altitudes up to
about 1.2 km above ground. The ABL top is not constant but shows
variations like expected for a convective boundary layer in the early
afternoon (see, e.g., Pal et al., 2010, for details on ABL studies with
high-resolution backscatter lidar). Above 1.2 km altitude, substantially lower values of bpar < 7$107 sr1 m1 are found in the free
troposphere. No clouds were present during this measurement. The
vertical particle-backscatter-coefficient profile is shown in the right
panel of Fig. 3. The RHI scan shown in Fig. 3 is just one example of
12 consecutive scans (not shown here).
4. Particle backscatter coefficient mapping
of livestock aerosols
The PLUS1 campaign took place from 11 to 21 September 2005 in
close vicinity of a livestock farm (5219.440 N; 7 8.80 E; 56 m above
sea level) in Mettingen, northern Germany. The ground distance
between the farm and lidar was 480 m with the farm situated at an
azimuth angle of 193.5 (measured from the geographical north)
from the lidar position. The livestock facility hosted 1800 pigs and
was actively ventilated from two chimneys separated by about 30 m
from each other with output of 9 2 m3s1. The primary particle
emission for PM10 was expected to be in the order of 100 gh1
(IIASA, 2001). The outlet of the farm chimney was just w5 m higher
than a horizontal lidar beam. There were no other animal facilities
(or other known sources of significant aerosol emissions) in the
vicinity. The terrain was flat which was preferred because the results
are easier to interpret. For the analysis, episodes of dry and sunny
weather were selected. A detailed description on the synoptic
weather situation and local meteorological conditions during the
PLUS1 campaign are given in Lammel et al. (2007) and in Pal (2009).
Fig. 4 shows a series of 6 consecutive plane-polar-indicator (PPI)
scans that picked up a cross section of the livestock aerosol plume
Fig. 3. An example RHI measurement with the scanning UHOH lidar. Left panel: hemispherical bpar map in a north-south orientation (PLUS1 campaign, 1415e1420 UTC, 20
September 2005, angular resolution in elevation ¼ 0.16 , range resolution ¼ 30 m). Right panel: Profile of bpar of this scan in vertical direction. The grey area shows the near-range
where non-total overlap between laser beam and field of view of the receiving telescope hinders measurements of the particle backscatter coefficient.
2800
A. Behrendt et al. / Atmospheric Environment 45 (2011) 2795e2802
Fig. 4. Sequence of consecutive PPI scans at an elevation angle of 2.3 above horizon showing the particale backscatter coefficient bpar of the aerosol plume originating from the
livestock facility (around 1625 UTC, 20 September 2005). Azimuth angles of 180 e210 are covered by each scan within 15 s. The total measurement time of these six maps was
106 s; the interval between consecutive scans was about 3 s. The lidar was located at the origin of the image, the farm (white square with black outline) downwind of the lidar. The
surface wind direction is shown in scan a (red arrow). Range rings each 200 m and azimuth sectors each 10 are marked.
emitted by the farm. During these measurements, wind was from
northenortheast with a speed of <3 ms1. The temperature at the
ground was 17 C. Relative humidity at ground was 45%. The solar
elevation angle was 15 . The measurements were made at a fixed
elevation angle of 2.3 with a scan speed of 2 s1. As an azimuth
angle sector of 30 was covered, the measurement time of each
scan was 15 s. The data were collected with the maximum temporal
and spatial resolution (0.033 s and 3 m) and afterwards averaged
over 10 profiles and 10 range bins before calculating the particle
backscatter coefficient fields resulting in a range resolution of 30 m
and an azimuth angle resolution of 0.66 .
Since these PPI scans took place inside the ABL, the initialisation
value bpar(rini) could not be obtained during the same scan with the
technique described in Section 3.1. Instead, first an RHI scan was
performed in the direction of the planned PPI scans determining
bpar(rini) for the elevation angle of the PPI scans. This value for used
for all scans. For the initialization range rini, a value of 3.5 km was
chosen.
The particle backscatter coefficient within the aerosol plume at
a distance of 250 m to the farm (730 m distance from the lidar) was
5.4$106 m1 sr1 which was approximately 30% higher than the
background aerosol present around the plume. From the source to
A. Behrendt et al. / Atmospheric Environment 45 (2011) 2795e2802
a distance of about 2.5 km (3.0 km distance to the lidar), bpar within
the plume was increasing up to values more than three times larger
than the background bpar for which we find a mean value of
4.1$106 m1 sr1. The increase in size of the plume with distance
shows the effect of dispersion. The values of bpar of the aerosols
distributed in the region of 1.0e1.5 km distance to the farm
(1.5e2.0 km distance to the lidar) were the largest within the
plume with a mean of 1.5$105 m1 sr1. Subtraction of the background results in a mean bpar of the livestock-aerosol plume of
1.1$105 m1 sr1. With the elevation angle of 2.3 , the height of the
lidar beam above the chimney height of the farm is 24 m, 54 m, and
74 m at 250 m, 1.0 km, and 1.5 km distance from the farm.
All the 22 consecutive scans of this period (6 of which are shown
in Fig. 4) show in a similar way the influence of the turbulent flow
on the plume emitted by the farm. The average of the 22 PPI scans,
i.e., over 15 min, is discussed by Valdebenito et al. (2011).
The farm plume was only picked up with the sequence of scans;
all other scans were made with higher elevation angle (see, Lammel
et al., 2007 for a detailed description on the different scans performed). Before and after the scans shown in Fig. 4, PPI scans with
4.8 elevation angle were made. In these data, there was no
significant increase of bpar related to the livestock aerosol plume.
We conclude that the plume stayed below this elevation angle
within a range of 3 km from the lidar.
Prueger et al. (2008) found that the vertical extent of the aerosol
plume emitted from a livestock facility was 30e40 m in the near
region at about 200 m distance to the farm. Our results concerning
the plume extension and maximum height are similar. They are
also in agreement with the results obtained by Holmén et al.
(2001a,b) who investigated an aerosol plume caused by tilling
under light wind (<6 ms1) conditions. Of course, the dispersion of
an aerosol plume depends critically on the ABL characteristics
present in each case.
5. Combination of lidar measurements and large-eddysimulation aerosol-optical-property model
The high-resolution lidar measurements obtained with the
scanning UV lidar have been combined with high-resolution
atmosphereemicrophysicsechemistry model simulations to
analyse the aerosol transformation during transport on a small
spatial and temporal scale (Valdebenito et al., 2011). In-situ point
measurements served for the characterisation of physical and
chemical properties of the aerosols surrounding the source. On the
basis of these measurements, the large-eddy-simulation aerosoloptical-property (LESeAOP) model calculated three-dimensional
discretised aerosol mass and number size distributions. The output
of an operational weather forecast model provided the meteorological variables for the LESeAOP initialisation. From the calculated
aerosol distributions, the particle backscatter coefficients bpar(x, y,
z, t) for each time step t and grid point (x, y, z) were computed using
the complex refractive index for different aerosol types and Miescattering look-up tables.
The LESeAOP model used within our project yielded a detailed
description of the particle size distribution and aerosol composition, which allowed for estimating the absolute value of the particle
backscattering coefficient. The UHOH lidar provided measurements
of the particle backscatter coefficient in radial coordinates, i.e.,
bpar(r, 4, q ,t) at a certain range r from the lidar and time t for
a scanner elevation q and azimuth direction 4. After interpolation of
the different coordinates, the common deliverable of both the lidar
and the LESeAOP model was the field of the particle backscatter
coefficient (bpar) which allowed for a direct intercomparison.
The model, once evaluated with the lidar measurements by
intercomparison, can be used to predict the optical properties and
2801
transport processes of the aerosols emitted from the agricultural
source. It is noteworthy, that this approach can also be applied to
other faint aerosol sources. In the future, the lidar measurements of
bpar could be assimilated by developing an aerosol forward operator, i.e. be used to initialise or to constrain the aerosol model like
performed previously for lidar water vapor measurements (e.g.,
Wulfmeyer et al., 2006, Grzeschik et al., 2008) in state-of-the-art
mesoscale weather forecast models.
6. Summary and conclusions
A new mobile eye-safe scanning aerosol lidar at 355 nm has
been developed at UHOH to derive information on spatial distribution and optical property of aerosol particles in the lower
troposphere. The lidar system was operated with an average
power of 9 W in combination with a 40-cm scanner with a scan
speed of up to 10 s1. A two-dimensional retrieval technique was
developed for determining particle backscatter coefficient maps
with resolutions in the order of a few meters. It is based on an
initialization scheme which makes use of the particle backscatter
coefficient of previous radial profiles in the vicinity of the initialization point.
With this approach, the determination of the particle backscatter coefficient of a plume from a livestock farm was realised for
the first time. Consecutive lidar scans allow for investigating the
aerosol emissions and transport processes. With a PPI scan of 2.3
elevation, the aerosol plume emitted by the livestock facility was
picked up which means that the plume was detected in w20 m AGL
at a distance of 120 m to the source and w80 m at a distance of
1.5 km. The measurements showed a particle backscatter coefficient bpar of the plume of 5.4$106 m1 sr1 at 250 m distance to the
source which was approximately 30% higher than the backgroundaerosol bpar. Larger values of 1.5$105 m1 sr1 in the mean were
found between 1.0 and 1.5 km distance to the source. Scans with
higher elevation (4.8 ) did not show signs of the plume.
Our results encourage future lidar application to other livestock
facilities or other faint aerosol sources. The results promise new
information useful in the context of emission mitigation and air
quality control near livestock confinements. We believe that it will
be beneficial if future research activities include the following: (1)
Simultaneous RHI and PPI volume scans with very high speed so
that a four-dimensional distribution of the optical property of
aerosol particles can be achieved, (2) deployment of scanning
rotational Raman lidar and scanning water vapor DIAL (Behrendt
et al., 2009) providing independent particle extinction coefficient
and backscatter coefficient fields together with temperature and
humidity fields. This will help to understand in detail the effects of
meteorological variables on aerosol optical properties and transformation (e.g., Wulfmeyer and Feingold, 2000), (3) to perform
four-dimensional variational data assimilation of the lidar derived
particle-backscatter-coefficient maps in a high-resolution atmosphereemicrophysicsechemistry model for better prediction of the
aerosol emission.
Acknowledgements
This project work was conducted in the framework of the BWPLUS programme, funded by the Ministry of the Environment and
Transport of the state of Baden-Württemberg, Germany. We thank
Marcus Radlach (UHOH) for his help during the development of the
lidar system as well as during the PLUS1 campaign. We highly
appreciate the support of GKSS Research Centre, Germany, for
donating the mobile platform and our colleagues at NCAR, USA, for
building the scanner. Finally, we would like to thank three anonymous reviewers for their helpful comments and suggestions.
2802
A. Behrendt et al. / Atmospheric Environment 45 (2011) 2795e2802
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