Observation of boundary layer aerosols using a continuously operated, portable lidar system

Observation of boundary layer aerosols using a continuously operated, portable lidar system

ARTICLE IN PRESS Atmospheric Environment 38 (2004) 3885–3892 Observation of boundary layer aerosols using a continuously operated, portable lidar sy...

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Atmospheric Environment 38 (2004) 3885–3892

Observation of boundary layer aerosols using a continuously operated, portable lidar system Nofel Lagrosasa,*, Yotsumi Yoshiia, Hiroaki Kuzea, Nobuo Takeuchia, Suekazu Naitob, Akihiro Sonec, Hirofumi Kanc a

Center for Environmental Remote Sensing, Chiba University, 1-33 Yayoi-cho, Inage-ku, Chiba 263-8522, Japan b Chiba Prefectural Environmental Research Center, 1-88 Iwasaki-nishi, Ichihara 290-0046, Japan c Hamamatsu Photonics K.K., 5000 Hirakuchi, Hamakita 434-8601, Japan Received 22 September 2003; accepted 22 February 2004

Abstract A compact, continuously operated lidar system has been developed and applied for unattended, continuous monitoring of troposphere. We demonstrate the effectiveness of the automatic procedure that routinely optimizes the lidar alignment in a definite interval. On the basis of the data taken from December 2002 to June 2003, oscillatory behavior of the aerosol layer height, vertical motion of the aerosol layer, and speed of raindrops are discussed. A good correlation is found between the lidar signal backscattered inside the boundary layer and the data of suspended particulate matter simultaneously measured at the ground level. r 2004 Elsevier Ltd. All rights reserved. Keywords: Portable lidar; Automatic alignment; Buoyancy oscillation; Raindrop speed; SPM concentration

1. Introduction The rise of human and industrial activities has led to the increased production of aerosols released to the atmosphere. In the lower troposphere, they cause visibility degradation, especially when these aerosols are located in the boundary layer. This is commonly experienced during the dust events (Husar et al., 2001; Sugimoto et al., 2003). In addition, highly concentrated aerosols, also known as suspended particulate matters (SPM), give rise to health problems. It has been shown in previous works of Abbey et al. (1999), Samet et al. (2000), and Pope et al. (2002) that exposure to fine particles, especially particulate matter smaller than 2.5 mm (PM 2.5), can result in serious respiratory disorders. Therefore, it is important to study the optical properties and dynamics of aerosols so that pollution *Corresponding author. E-mail address: [email protected] (N. Lagrosas).

transport and local atmospheric variation can be elucidated. The easiest way to investigate the temporal variation of aerosol vertical profile is to have an unattended yet continuously operated optical sensor with a short time resolution. A micro-pulse lidar (MPL) (Spinhirne, 1993) is a good candidate for this type of detection and profiling of atmospheric aerosols and clouds. The relatively high average output of these commercial lasers (second harmonics of a Nd:YLF laser, about 10 mJ/pulse at 2.5 kHz repetition rate) enables the detection of clouds and aerosols up to the stratosphere. A number of literatures have reported on the applications of MPL to environment studies (Chen et al., 2001; Parikh and Parikh, 2002; Campbell et al., 2003; Mahesh et al., 2003; Shibata et al., 2003). Optical and climaterelated characteristics of the lower atmosphere are also observed with MPL. For example, Chen et al. (2001) observed the seasonal change of the mixing layer height. The temporal evolution of the boundary layer height

1352-2310/$ - see front matter r 2004 Elsevier Ltd. All rights reserved. doi:10.1016/j.atmosenv.2004.02.060


N. Lagrosas et al. / Atmospheric Environment 38 (2004) 3885–3892

and boundary layer aerosol can also be studied (Parikh and Parikh, 2002). However, in this type of monitoring device, the same telescope is employed for both transmitting and receiving the laser beam, and a very small portion of the transmitted light reflected inside the telescope often damages the detector. In the case of a conventional and compact lidar system, on the contrary, this problem is nonexistent, since the laser head is usually placed at the side of the telescope. In this paper, we describe a portable automated lidar (PAL) system based on this type of conventional approach, where two prisms are used to deliver the laser beam to the telescope axis. The continuous operation of a PAL system provides a picture of the daily dynamics of the local atmosphere over the observation site. Therefore, it is considered as a reliable tool for atmospheric sensing. However, in contrast to the MPL system, the optical alignment of the PAL system imposes potentially significant problems if the lidar is left unattended. This is due to the thermal expansion/contraction of some parts of the system as ambient temperature changes. Since the two prisms guide the laser beam to the telescope axis, any disturbance of the prism orientation creates a misalignment. Thus, continuous monitoring and optimization of the alignment is necessary to acquire reliable data. The prevention of misalignment could be achieved by placing the lidar in a temperature-controlled environment or by using temperature-insensitive materials. From a practical point of view, however, the former is not cost efficient and the latter does not necessarily assure good alignment if not all parts of the lidar system, especially the laser and the telescope, are made of temperature-insensitive materials. Moreover, if these methods were employed, it would be impossible to automatically recover the good alignment when the lidar system is mechanically disturbed, e.g., by an earthquake. When misalignment occurs between the laser beam and the telescope axis, the overlap function in the lidar equation does not saturate to unity even at large ranges. Several papers treated this subject in detail. Wandinger and Ansmann (2002) presented two methods (direct and iteration) to determine experimentally the overlap function of a Raman lidar. The direct method calculated the overlap function directly from the lidar equation. The iteration method relied on the Klett’s solution and the Raman lidar solution. Chourdakis et al. (2002) examined the dependence of the overlapping function on the optical configuration of a noncoaxial lidar system. Sassen and Dodd (1982) presented a theoretical approach that dealt with optical axes alignment. Dho et al. (1997) used polynomial regression to find out the geometrical form factor in the lidar equation. In most of these studies, determination of the overlap function requires a clear atmosphere; moreover, align-

ment adjustments were not implemented during data acquisition. The purpose of this paper is twofold. First, we describe the instrumental aspects of the automatic alignment procedure of the PAL system during data acquisition. Second, we show the results of observations of boundary layer aerosols and clouds from our operation of the system from December 2002 to June 2003. The location of our operation site is Ichihara city (35.52 N, 140.07 E, about 40 km southeast of Tokyo), an industrial area south of Chiba city, along the east coast of the Tokyo bay.

2. Lidar system 2.1. Basic instrumentation The basic specifications of the PAL system are summarized in Table 1. Inside the Nd:YAG laser system, a diode laser of 1.7 W output power pumps a Nd:YAG crystal. This generates a 600 mW cw laser power that is Q-switched by an acoustic-optical modulator (AOM) operated at 1.4 kHz, giving pulsed output with 100 mJ/pulse at the fundamental wavelength of 1064 nm. A potassium titanyl phosphate (KTP) crystal inside the cavity doubles this frequency, resulting in a typical output of 15 mJ pulse1 at 532 nm wavelength. The laser head is placed on an aluminum plate attached to the upper side of the cylinder of a 20 cm diameter Cassegrainian telescope. The output is expanded 25 times to 25 mm in diameter, and is bent by two prisms so that the emitted beam spatially coincides with the optical axis of the telescope. In order to reduce background noise due to the skylight during daytime, a narrow fieldof-view angle of 0.2 mrad is used. The backscattered

Table 1 Specification of the PAL system Transmitter Laser Wavelength Laser pulse width Repetition rate Laser pulse energy Laser beam divergence AOM carrier frequency

LD-pumped Q-switch Nd:YAG 532 nm 50 ns 1.4 kHz 15 mJ 50 mrad 80 MHz

Receiver Telescope diameter Telescope type Field of view Detector Model Quantum efficiency

20 cm Cassegrain 0.2 mrad PMT HPK-R1924P 10–25%

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signal is collected by the telescope, detected by a photomultiplier tube in photon-counting mode using a scaler (Stanford Research SR430), accumulated for 20 s, and stored in a personal computer (PC). To stabilize the alignment between the laser and telescope axes, a step motor controls the two-axis Gimbal mount holding the first (upper) prism. By varying the orientation of the prism attached to the mirror holder, the alignment of the laser beam is adjusted.


the alignment is finished, the PC continues to gather data. Fig. 1 shows the typical behavior of lidar data as alignment is checked in the vertical direction. The graph shows that during the scanning process, the lidar peaks tend to move to higher altitudes (B250 m) as good alignment is nearing completion. It also shows that a one-step change of the actuator creates a substantial difference in the intensity and shape of the signal backscattered from the atmosphere.

2.2. Alignment procedure A computer program was made to control the acquisition of the data and the automatic alignment. The alignment is checked and optimized every 15 min. During the alignment procedure, the PC commands the controller to move the actuator for vertical motion backwards by 10 units, and then forward by 1 unit step and integrate the signal for 1 s until it has moved a total of 20 units in the same direction. Here, 1 unit motion of the actuator (equivalent to its resolution) corresponds to a change of 50 mrad in the tilt angle of the laser beam. The backward movement is required to take into account the hysteresis effect (backlash) of the actuator. Each integrated signal is stored during the forward motion. Note that in this procedure of lidar integration, we make use of the overlap region of the A-scope, i.e. the region where the overlap between the laser beam and the telescope field-of-view is substantial but not yet complete. The vertical actuator then is moved back to the peak signal position and the same procedure is applied to the actuator for the horizontal motion. It takes around 100 s to complete the whole process. After

Intensity (a.u.)




0 0.0






Height (km) Fig. 1. Vertical behavior of lidar A-scope signals as the lidar alignment is adjusted. The largest profile corresponds to the optimal alignment, while the other (smaller) profiles are observed for actuator steps (50 mrad for each step) away from the best position.

3. Operation conditions The PAL system is placed at the Chiba Prefectural Environmental Research Center (CERC) in Ichihara city for the purpose of comparing the lidar data with the ground base data (see below). Since the CERC is located in an industrial area, it is plausible that a significant part of the aerosol particles observed by the PAL system originates from anthropogenic sources such as automobile and industrial emissions. The system is installed indoors at about 4.5 m high from the ground level. The laser beam, pointed toward the north sky with an elevation angle of 38o, is positioned so that it does not hit the cornice of the roof of the building. The horizontal distance between the lidar location and the seashore (east coast of the Tokyo bay) is about 2 km in the laser beam direction. The alignment correction mechanism was added in the middle of December 2002, and since then has been continuously operated. In terms of eye-safety consideration, the PAL system is not eye safe at the exit of laser beam, whereas the MPL system satisfies the eye-safety conditions. This is due to the fact that the laser beam of PAL is expanded up to only 25 mm, while that of MPL is expanded up to 200 mm in diameter. Near the beam expander the laser’s energy density per pulse is 18 times the standard maximum permissible exposure (ANSI Z136.1-1986), which is 1.16  107 J cm2. Nevertheless, at a distance of 340 m along the laser path, the beam is already considered eye-safe. Under this range the observation region of our lidar is over the industrial area, and the laser beam obstructs no aviation traffic. In Section 4.5 below, we will discuss the observed relationship between the lidar backscatter signal and the SPM concentration. The SPM data were monitored at Iwasaki-nishi station (just 70 m away from the lidar site) and is available through the website (http://www.soramame.nies.go.jp) provided by the Ministry of Environment, Japan. The website displays data of SPM monitored using one of the following methods: b-ray absorption technique, piezo-electric balance method, or optical scattering method. At Iwasaki-nishi, the b-ray absorption method (van Elzakker and van der Muelen, 1989) is employed.

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4. Results and discussion

4.2. Oscillation in aerosol height

4.1. Effect of automatic alignment

The PAL system acquires data every 20 s. This short period ensures the reliable observation of the relatively rapid phenomena related to atmospheric dynamics. Fig. 3 shows the occurrence of oscillatory behavior in the aerosol concentration. It is known that such type of waves is often triggered by the air flow over orographic locations, shear instability, frontal acceleration or geostrophic adjustment (Hertzog et al., 2001). The lidar data in Fig. 3 (1 April 2003) shows an aerosol layer with a top height of about 2.1 km, and a bottom height of 1.7 km. On 1 April 2003, the great Tokyo metropolitan area (where the observation site is located) was at the eastern edge of a high pressure zone centered at the Japan sea (1020 hPa), and there was a stationary front southward, along the 30 N latitude line (Fig. 4). At the ground level, the wind speed was in a range of 5–9 m s1 (east wind), the sea level pressure was 1015 hPa, and the relative humidity was about 40%. The relative humidity was gradually increasing toward the next day, when light rainfall started around noon. Stull (1988) pointed out that thermal waves are often found in the pre- or post-frontal zones with vertical motion amplitude that ranged from 1–4 m s1. Hooke and Jones (1986) analyzed similar undulations observed by an acoustic echo sounder in terms of the Brunt– Vaisala (BV) oscillation. Since high mountains are not present near the lidar site, it is likely that the observed oscillation is due to thermal or convection waves, presumably associated with the prefrontal conditions. The period of oscillation as calculated by performing a Fourier transform analysis of the data is 10.75 min, giving an oscillation frequency, N ¼ 2pf , of 9.7  103 s1. In general, the frequency of BV oscillation has a direct proportionality to the magnitude of the wind speed (Wallace and Hobbes, 1977). However, here

Fig. 2 shows the vertical and horizontal alignment positions from the last week of December 2002 to June 2003. On 15 January 2003 the alignment positions were reset to zero. Throughout this period of operation, we find a correlation between the alignment positions (horizontal and vertical) and the ambient temperature. This behavior suggests that changes in the room temperature affect the optical alignment of the system. It is found that the vertical positioning is more sensitive to temperature changes than the horizontal one. The larger sensitivity of the vertical position occurs since the prisms bend the optical path vertically. As the ambient temperature increased from January to June, the alignment positions have shifted by 20 units (1 mrad). The theory of the lidar overlapping function (Kuze et al., 1998) is employed to evaluate the actual amount of temperature distortion. For that purpose, the A-scopes observed during the adjustment procedure are compared with the theoretically calculated profiles. The result shows that the typical value of angulartilting deviation is from 100 to 200 mrad, and is ascribable to the thermal, linear distortion of the telescope outer cylinder and/or the laser base plate (on which the laser is attached) of the order of 0.02 to 0.03 mm. This turns out to be reasonable if one considers the thermal expansion coefficient of aluminum (2.2  105 K1) and the change in the ambient temperature of the order of 5 K.

30 20

Vertical Horizontal


10 0 –10 –20 –30 01/01/03



Date Fig. 2. Variations of optimum alignment positions from December 2002 to June 2003. Positions were reset to zero on 15 January 2003.

Fig. 3. Atmospheric oscillations observed in the lidar signal on 1 April 2003, having periods of 10.75 min.





80 60




20 1.0 Fig. 4. The weather map of Japan on 1 April 2003 at 9:00 a.m. showing low pressures in the eastern and western regions and high pressure existing northward.

we analyze the present data by neglecting the horizontal movement of the air parcel, since no wind data is available around 2 km altitude. According to Hooke and Jones (1986), the BV frequency, N, is related to the density r of the  oscillating air 1=2parcel as given by the equation N ¼ ðg=rÞð@[email protected]Þ ; where g is the gravitational acceleration and z is the height. Assuming that @[email protected]=dz; the difference between the top and the bottom densities can be approximated using the equation   rtop N2 ¼ exp  ðztop  zbottom Þ ¼ 0:992: ð1Þ rbottom g This indicates that only a slight change in the parcel density in a height range ztop  zbottom ¼ 0:4 km could explain such an oscillatory behavior. The vertical motion amplitude is computed using the equation, v ¼ NA; where A(E0.2 km) is the amplitude of the wave. The resulting value is v ¼ 1:9 m s1, a value that is within the range 1–4 m s1 as mentioned above. 4.3. Falling raindrops Fig. 5 shows the time-height diagram observed by the PAL system on 23 April 2003, indicating downwardmoving liquid water in the lower troposphere. A light rain shower took place from 22:00 to 24:00. Ground measurements showed that the precipitation from 22:00 to 23:00 (o0.5 mm) was less than that from 23:00 to 24:00 (0.5 mm). The relative humidity values from 22:00 to 23:00 and from 23:00 to 24:00 were 86% and 91%, respectively. Ground temperature ranged from 16.5 C to 16.1 C. The recorded streaks lead to the average vertical speed of the water droplets of 4.2 m s1, with the assumption that the atmosphere is horizontally homogeneous. Edwards et al. (2001) simulated the dynamics of falling raindrops considering the effects of both mist and air drag. Given a droplet speed, n; and assuming that the mist drag is small compared to the air drag, the raindrop

Signal Intensity (a.u.)

Height (km)

N. Lagrosas et al. / Atmospheric Environment 38 (2004) 3885–3892

0 22.0





Time Fig. 5. PAL data during a slight rain condition (23 April 2003). Near the ground, increase in precipitation from 23:00 to 24:00 causes higher signals as compared to the signals from 22:00 to 23:00. Falling raindrops are recorded as streaks in the lidar signal.

radius can be estimated by the equation: sffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi "  3  #   3 1 8es 8es r ¼ s7 s2  4 v  2 ; 3g 3g where    1=3 2 rd 2=3 g2 s¼ 3 ra 3Z



is the falling rate measured in s1. The other parameters in Eqs. (2) and (3) are as follows: g(=9.8 ms2) is the acceleration due to gravity, rd(=1 g cm3) is the water density; ra(=0.856  103 g cm3) is the air density at 2– 3 km above the ground; and e ¼ rm =4rd ; where rm(=106 g cm3) is the mist density. If we assume that the kinematic viscosity of air, Z; to be 0.206 cm2 s1, the radius r is calculated to be roughly 0.5 mm. This radius is a typical value for droplets with a terminal speed of 4 m s1 (Rogers and Yau, 1989). 4.4. Updraft and downdraft observations Upward and downward movements of aerosols are regularly detected, as shown in Fig. 6. The frequency of the downdraft and updraft occurrence is summarized in Fig. 7, as analyzed visually from the 90 day data (January–March 2003). In the ordinate, a count indicates the occurrence in a 1 h time bin. The upward motions of the aerosols were detected with a greater frequency during afternoon to evening. The maximum number of occurrence takes place from 16:00 to 18:00 local time, as shown in Fig. 7(a). The upward motion can be attributed to the solar heating of the ground that peaks in the afternoon. The heating causes temperature increase, resulting in atmospheric convection. During this time interval, the air lifts the particulates from the

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By observing the streaks formed by the updrafts and downdrafts, the average vertical speed can be estimated. For example, the estimated average speed of the updraft in Fig. 6(a) is around 1.25 m s1. When the data were acquired, the ground temperature, wind direction, wind speed and relative humidity were 11.3 C, ENE, 1.5 m s1 and 34%, respectively. From Fig. 6(b), the downward process has an average speed of 0.93 m s1. The ground temperature, wind direction, wind speed and relative humidity were 2.3 C, ENE, 1.9 m s1 and 82%, respectively. 4.5. Correlation with the SPM data

Fig. 6. Downdraft and updraft movements on the same day (14 March 2003). Updrafts are formed during daytime (a), while downdrafts are often formed in the early morning (b). The horizontal bands in the graphs are due to minor digitizing errors.

100 (a) Updraft



0 0:00 100








(b) Downdraft


0 0:00


Fig. 8 shows the SPM concentration recorded by the b-ray detector from the last week of December 2002 to June 2003. In this time period, the SPM concentration gradually increased. The PAL can detect these particulates when their sizes are of the same order of, or larger than the laser wavelength (532 nm). The constituents of the SPM are solid and liquid particles with different sizes and shapes. The sources of these include dust from paved or unpaved road, soil, maritime sea salt (coarse particle) or exhaust from automobile combustions and industrial processes (fine particles). Anthropogenic gases such as sulfurous compounds (e.g., SO2) and nitrogen compounds (e.g., NOx) can also produce SPM when they dissolve in water to form less volatile substances via particle-to-gas conversion. Particle growth is expected to occur when the relative humidity increases (Wallacw and Hobbes, 1977). The discussion that follows is the relationship between observed particle growth due to relative humidity and lidar data from 28 February to 2 March 2003. Fig. 9(a) shows the ground-measured SPM data, relative

Local Time

ground to the atmosphere. The downward events, on the other hand, are rather dominant during nighttime. Fig. 7(b) shows that the peak occurrence is from 6:00 to 8:00. The downward motion of the aerosols is due to the cooling of the ground surface. Before daybreak, when the temperature is at its lowest, air loses kinetic energy and thus particles settle to the ground. The number of observed updrafts is less than that of the observed downdrafts. The reason for this asymmetry is the relatively cooler temperature of the grounds during the months of January to March.


SPM Concentration Concentration (mgm -3 )

Fig. 7. Number of updraft and downdraft occurrence from January to March 2003. A count indicates the occurrence in a 1 h time bin. (a) Updraft occurrence shows a peak count at around 16:00 and 18:00. (b) Downdraft occurrence shows a peak occurrence at 6:00.

0.20 0.15 0.10 0.05 0.00 01/01/03



Date Fig. 8. Ground SPM concentration measured at Iwasaki-nishi station from the last week of December to the end of June 2003. From March 2003, increase in daily SPM concentration is evident.





SPM Concentration

Relative Humidity

60 0.1



20 _20


4.0 3.0

Height (km)




SPM Concentration (mgm 3 )

Rel. Hum. (%) Temp. ( C)

N. Lagrosas et al. / Atmospheric Environment 38 (2004) 3885–3892





2.0 1.0 0.0 02/28





Fig. 9. (a) Ground-measured values of temperature, relative humidity and SPM concentration from 28 February to 2 March 2003. (b) Lidar data from 28 February to 2 March 2003: (a)–(e) indicate the time periods listed in Table 2.

Table 2 Correlation coefficient between atmospheric backscattering and SPM concentration and the corresponding height of maximum correlation Case


Period (h)

Correlation coefficient

Height of max. correlation (km)

a b c d e

28 February 06:00–18:00 28 February 18:00–1 March 06:00 1 March 06:00–18:00 1 March 18:00–2 March 06:00 2 March 06:00–18:00

12 12 12 12 12

0.55 0.81 0.94 0.83 0.85

0.24 0.15 0.21 0.13 0.22

humidity and temperature. During these days, the observed maximum SPM concentration was 0.183 mg m3. Precipitation ranging from 0 to 17.5 mm h1 occurred from 16:00 JST on 1 March to 03:00 JST on 2 March. Maximum precipitation took place from 23:00 to 24:00 JST on 1 March. It is noted that under precipitation conditions, the PAL data provide no clue whether the observed matters are aerosols or cloud/ mist particles. Thus, the quantity derived from lidar data may be different from the definition of SPM monitored by ground base measurement. To correlate the lidar data with the SPM concentration, the lidar data (backscattered intensities) are corrected to include the overlapping function and averaged for 1 h in accordance with the SPM data interval. Correlation in a 12 h interval is then studied at every 14.8 m in a height range (vertical step) between 0 and 2 km. For each height range, a value of the correlation coefficient is produced. The maximum correlation coefficient at some height is taken as the result for that particular time bin (12 h). Fig. 9(b) shows the time-height indication of the PAL data for the same 3-day period. During this period, the ground measurements indicated weak correlation be-

tween humidity and temperature. Table 2 shows the resulting correlation coefficients and correlation heights for the 3 days, divided into five cases of a–e, each case lasting for 12 h (also shown in Fig. 9(b)). On 28 February 2003, the increase of the correlation coefficient from daytime to nighttime (from cases a to b) suggests that SPM was in the process of building up due to the onset of the nocturnal boundary layer as seen in sections a and b of Fig. 9(b). On 1 March (cases b and c), the upsurge of humidity in the middle of the day indicates strengthening of particle growth. This causes the intensified lidar return signal and higher correlation coefficient. The precipitation that occurred in the late afternoon effectively lowered the nighttime correlation (case d) between the SPM and lidar data. Higher daytime correlation coefficient on 2 March (case e) is presumably due to the active mixing of the local atmosphere. Generally, the presence of solar influx during daytime creates aerosol mixing and thus, vertical transport takes place. When the lidar and SPM data are correlated during daytime, high correlation value is expected at higher altitude within the boundary layer. The low temperature and wind speed during nighttime prevent


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vertical motion of SPM. This is the reason why correlation height is lower at nighttime.

5. Conclusions The operation of the portable automated lidar (PAL) has proven that the conventional configuration of the lidar transmitter/receiver system can be used to continuously monitor the lower atmospheric profiles when appropriate mechanism of alignment optimization is additionally incorporated. The mechanism, in principle, can be applied to many types of lidars so that they give continuous information on the atmosphere. Lidars with sufficiently narrow field-of-views require automatic alignment since the lidar A-scope signal is susceptible to the slight change in the laser beam deflection from the optical axis of the telescope. Such a continuously operated system can also detect atmospheric oscillations as long as the integration time is shorter than the period of the oscillation. This paper has also demonstrated the application of the PAL data to studies in the fields of meteorology and atmospheric dynamics. In particular, the combination of the PAL data with the ground-measured SPM concentration can be used to explain dynamic behavior of the aerosol particles. In the future, it is hoped that the multiwavelength operation, desirably including the polarization-measurement capability, brings about more detailed information on the urban air pollution.

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