lidar observations of aerosols in the upper hunter

ACARP C12027 MINING PM10 & NO2 EMISSIONS

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Section 3

Lidar Observations of Aerosols in the Upper HunterJohn Holdsworth and Matthew Pickett

TABLE OF CONTENTS:

1 INTRODUCTION ..............................................................................................771.1 PURPOSE ..................................................................................................................... 771.2 BACKGROUND ............................................................................................................. 77

1.2.1 Aerosols and the Boundary Layer..........................................................................771.2.2 LIDAR Measurements of Aerosols.........................................................................78

1.3 PROJECT ORGANISATION & TIMEFRAME....................................................................... 78

2 EQUIPMENT ............................................................................................................... 792.1 INTRODUCTION ........................................................................................................... 792.2 LIDAR HARDWARE CONSTRUCTION ............................................................................ 792.3 LIDAR SOFTWARE DEVELOPMENT .............................................................................. 81

3 EXPERIMENT ...................................................................................................813.1 FIELD SETUP ............................................................................................................... 813.2 METHOD ..................................................................................................................... 82

3.2.1 Energy Monitor Calibration.............................................................................. 82823.3 LIDAR OPERATIONS ................................................................................................... 84

4 DATA ANALYSIS METHODS ........................................................................844.1 INTRODUCTION ........................................................................................................... 844.2 THEORETICAL BACKGROUND....................................................................................... 85

4.2.1 The LIDAR Equation............................................................................................854.2.2 Calculated Aerosol Properties for Cheshunt Park LIDAR.......................................86

4.3 ANALYSIS OF CHESHUNT PARK LIDAR DATA .............................................................. 884.3.1 Initial Data Processing.........................................................................................884.3.2 Retrieval of Vertical Structural Properties of the Boundary Layer...........................91

5 RESULTS ............................................................................................................915.1 SUMMARY OF MEASUREMENTS.................................................................................... 915.2 LIDAR OBSERVATIONS 16 OCTOBER 2003 ................................................................... 93

5.2.1 LIDAR Observations ............................................................................................935.2.2 Simultaneous In Situ PM Measurements by Grimm 16 October 2003 .......................94

5.3 LIDAR OBSERVATIONS 17 OCTOBER 2003 ................................................................... 955.3.1 LIDAR Observations ............................................................................................955.3.2 Simultaneous In Situ PM Measurements by Grimm 17 October 2003 .......................95

5.4 LIDAR OBSERVATIONS 18 OCTOBER 2003 ................................................................... 965.4.1 LIDAR Observations ............................................................................................965.4.2 Simultaneous In Situ PM Measurements by Grimm 18 October 2003 .......................96

5.5 LIDAR OBSERVATIONS 19 OCTOBER 2003 ................................................................... 975.5.1 LIDAR Observations ............................................................................................975.5.2 Simultaneous In Situ PM Measurements by Grimm 19 October 2003 .......................975.5.3 LIDAR Observations – 19/10/04, a.m. ...................................................................985.5.4 LIDAR Observations of a Dragline Dust Plume .....................................................98

5.6 LIDAR OBSERVATIONS 20 OCTOBER 2003 ................................................................... 995.7 LIDAR OBSERVATIONS 24 OCTOBER 2003 ................................................................... 995.8 LIDAR OBSERVATIONS 25/10/03.................................................................................100


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5.9 LIDAR OBSERVATIONS 15/12/03.................................................................................1015.10 LIDAR OBSERVATIONS 16/12/03.............................................................................1025.11 LIDAR OBSERVATIONS 17/12/03.............................................................................1035.12 LIDAR OBSERVATIONS 18/12/03.............................................................................104

6 CONCLUSION .................................................................................................104

7 ACKNOWLEDGEMENTS .............................................................................105

8 LIST OF ACRONYMS & DEFINITIONS ....................................................106

REFERENCES.........................................................................................................106

APPENDIX 3.A. SUMMARY OF LIDAR FIELDNOTES.................................107

APPENDIX 3.B. ENERGY MONITOR RESULTS ............................................108


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1 INTRODUCTION

1.1 PURPOSE

Open-cut coal miners have an interest in monitoring and mitigating dust emissions from mines forhealth and amenity reasons. Knowledge about the structures and temperature inversions within thelower atmosphere (the ‘boundary layer’) is desired as an operational tool for reducing noise andaerosol impacts from activities such as blasting. The purpose of this project therefore, is todemonstrate the capabilities of laser technology for providing RADAR-like signals of the verticalstructure of the lower atmosphere. This is done by using laser backscatter from aerosols and dustparticles as a tracer. The laser technology is known as Light Detection And Ranging (LIDAR).For providing high-resolution backscatter information from small particles in the atmosphereLIDAR is the best method known to science.

To accomplish the Hunter Valley LIDAR Technology Demonstration Project, the following majortasks were undertaken:

• Construction of a LIDAR apparatus;

• Field campaign, Cheshunt Park (adjacent to Lemington and Narama mines); and

• Data analysis and reporting.

The operation of the Hunter Valley LIDAR near working coal-mines, acquiring aerosolinformation simultaneously with in situ instruments more commonly used for air qualitymonitoring such as High Volume Samplers and DustTraks, represents a novel experiment for theregion. In fact, this may be the first time LIDAR has been used alongside in situ instruments at amine site anywhere in Australia. The results will provide miners with a new view of the verticalstructure of the local atmosphere, which should lead to a better understanding of:

• Dispersion of aerosols and dust in the local atmosphere; and

• Propagation of sound waves in the atmospheric boundary layer.

1.2 BACKGROUND

1.2.1 Aerosols and the Boundary LayerSmall particles suspended in the atmosphere, or “aerosols”, vary greatly in size, composition andconcentration. Number concentrations range from 10 million per cubic centimetre for gaseousclusters and ions, up to 0.001 per cubic centimetre for ice crystals, rock fragments and ashyresidues from burning processes; for example, refer to Schaefer and Day (1981). Some key pointsfrom Schaefer and Day (ibid.) are:

n There are always greater numbers of smaller (invisible) particles than visible;

n In clean air typically there is approximately 300 particles per cubic centimetre with the ratio ofvisible to invisible particles, 1:3; and

n In polluted air the number concentration can be as high as 100,000 particles per c.c. with theratio of visible-to-invisible particles 1:300 (approx. 3000 visible particles per c.c.).

Some definitions for monitored aerosols that are used worldwide and well known to this country’svarious industries that must report to state environment protection authorities, including the miningindustry, are:


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n PM2.5: “Particulate Matter 2.5” - particles less than 2⋅5 µm in diameter, sometimes referred toas “fine particles”.

n PM10: “Particulate Matter 10” is used to describe mass concentrations of particles withdiameters less than 10 microns; note that a fine woollen fibre is approximately 20 microns indiameter. Units are typically reported in micrograms per cubic metre (µg/m3) to provide easeof comparison with the common 24-hour target for PM10 of 50 µg/m3.

n TSP: “Total Suspended Particulates” – the total mass of particulate matter measured in units ofµg/m3. The TSP in an important measure for predicting the dust deposition that could occurfrom the atmosphere.

The lowest layer of the atmosphere is known as the “boundary layer” or “mixing layer” and ischaracterised by turbulence and convection due to friction and heating by contact of the atmospherewith the ground. The boundary layer varies in thickness depending on the geographical location(e.g. polar regions vs. the equator), season, time of day and land surface type. The boundary layervaries in thickness from several metres (e.g. in almost still air at night), up to a depth of 2-3kilometres in strong convective conditions in summer.

Often the top of the boundary layer is capped by a temperature inversion and very commonly,aerosols become trapped in higher concentrations underneath. The height detection of thesetrapped aerosols can be used to provide a tracer to clearly demarcate the vertical structure both atthe top and within the boundary layer.

1.2.2 LIDAR Measurements of AerosolsLIght Detection And Ranging (LIDAR) is the optical version of radar. LIDAR uses a laser beamrather than radio wave energy to probe targets. Radar is good for the detection of larger particlessuch as rain droplets (e.g., weather radar), or large objects such as aircraft. However the longerradio wavelengths used by radar means that it is not capable of detecting particles smaller than halfa wavelength (a few millimetres). LIDAR uses a laser that operates in the ultra-violet, visible orinfrared parts of the electromagnetic spectrum. The short wavelengths, = 1 micrometre, of lasersrelative to radio waves means that LIDAR easily detects small particles, such as the constituents ofclouds and plumes of pollutants, background aerosols, and even air molecules.

There are many LIDAR applications for atmospheric studies, some use continuous laser beams andothers use pulsed lasers. In a simple and typical arrangement a pulsed laser and telescope aresituated side-by-side. A short pulse of laser light is fired from the laser. The laser pulse propagatesthrough the atmosphere and scatters in all directions from air molecules and particles. Some of thelight is scattered backwards to the propagation direction and collected by the receiver telescope.The time-of-flight of the pulse is used to calculate the range to target via the constant speed oflight.

The range resolution of a LIDAR is a function of the sampling rate of the digitiser used forconversion of the detector electrical response and the pulse length of the laser pulse. A digitisersampling rate of 100MHz yields a range measurement resolution of 1.5 metres. The typical ~8nslaser pulse duration, corresponds to a spatial length of 2.4m and, as an aerosol may scatter from theleading edge or trailing edge of the pulse, provides a range resolution limit of 4.8m. This goodrange resolution enables the acquisition of an accurate range (or height)-profile of the measuredsignal.

1.3 PROJECT ORGANISATION & TIMEFRAME

This project was divided into three main phases: (1) LIDAR development phase; and (2) Fieldcampaign; and (3) Data analysis and reporting. The development phase was begun by CAR(Melbourne) with some assistance from Itec Engineering, and continued through to mid-2003. The


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University of Newcastle (UoN) and Sinclair Knight Merz (SKM) then transported the LIDARcomponents to UoN, where work on some components was completed. The LIDAR hardwaresystem was built and new software developed. The LIDAR was transported to the field siteCheshunt Park, where, following final system tests, the field campaign was begun. The fieldcampaign began in October 2003 measurements were obtained on several occasions untilDecember 2003.

2 EQUIPMENT

2.1 INTRODUCTION

The LIDAR hardware was assembled from primary components made available from CSIRODivision of Atmospheric Research. CSIRO had provided the Blue Sky Nd:YAG laser, aNewtonian telescope, detector, detector electronics and power supply as well as an aircraft rack.These components were separate and had not been integrated into a working system.

2.2 LIDAR HARDWARE CONSTRUCTION

The component pieces may be formed into a system as per the schematic in Figure 2.1. The laserradiation backscattered from the atmosphere and collected by the telescope includes the:

• Elastically scattered light from molecular and atomic species present in the atmosphere dueto Rayleigh scattering.

• The signal of principal interest, the Mie scattered signal from aerosols.

• A small amount of Raman scattered light.

The Rayleigh and Mie signals are discriminated from the Raman and general ambient light by aninterference filter placed before the silicon avalanche photodiode detector. The photocurrentgenerated is pre-amplified, amplified and coupled to an oscilloscope for digital storage and passageto the PC.

The raw data collected are stored on a PC for later analysis as well as the parameters of the system.

Figure 2-1: Schematic of a LIDAR system showing functional components.

Beam expander

Telescope

Data recording, storage andtransfer

Filter and lens

Detection

Si APD and power supply

Pulse detection

Laser

Amplifier


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The telescope was mounted on a roller bearing pivoting bracket with micrometer adjustment thatgimbals about the secondary mirror for axial alignment. The bracket was supported by the mainhousing frame and this frame was mounted upon a support plate resting on three point mounts. Abubble was mounted so that the whole frame would be levelled. This ensured that the laser wasdirected vertically to meet the stringent laser safety requirement.

The laser was mounted to a sub assembly that incorporated the laser, the energy monitorphotodiode, the trigger photodiode and the beam expander as shown in Figure 2-2. The twodimensions of horizontal adjustment as well as two dimensions of angular adjustment on the beamexpander assembly, X,Y, and θ,φ , are necessary to align the optical axis of the beam expander tothe optical axis of the laser. The laser sub-assembly has the ability to free stand for laboratoryadjustments and is mounted to the LIDAR frame with taper pins so that the assembly may beremoved and replaced without major readjustment. The laser sub-assembly incorporated theenergy monitor and trigger photodiodes within the laser safety shroud that is interlocked to complywith the laser safety standards.

(a) (b)

Figure 2-2: (a)Telescope mounted within frame showing gimbal mount brackets

(b) Laser subassembly mounted to rack.


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The completed system had the mount for the detector machined and mounted within the supportcollar for the telescope. The laser power supply was found to be a source of electromagneticinterference and positioned to one side of the unit as opposed to being incorporated within theaircraft rack as originally anticipated.

Figure 2-3: Non-operating LIDAR system viewed from above with components marked

Control of the LIDAR system was via computer which set the laser firing rate, gain of the detectorand recorded laser pulse energy of each shot. Details of the software to control the system areoutline in the following section.

2.3 LIDAR SOFTWARE DEVELOPMENT

A new software package was designed, written and tested for this LIDAR project. The productcomprises a user-friendly interface that enables the user to set up the LIDAR hardware includingfiring the laser. The data from a sequence of several thousand shots is averaged and stored to diskin an ASCII (text) format able to be easily read by other software packages (e.g., Microsoft “Excel”spreadsheet), for further examination and analysis.

The package used to develop the LIDAR control and data acquisition software was the NationalInstruments LabView package. LabView provided an efficient and powerful method of developinga user-friendly program, in a relatively short time, which was capable of communicating with theLIDAR hardware components. In particular, LabView eased what can be the difficult task ofcommunicating with low-level devices via a typical modern desktop PC and operating system.

3 EXPERIMENT

3.1 FIELD SETUP

The Upper Hunter Region, NSW, is an ideal location for this kind of study. There are a number ofactive open-cut mining operations adjacent to the site, several in the development stage and someareas undergoing remediation. A satellite image of the mining areas is shown in Figure 3.1.

Video camera

Power supply and amplifier

Laserpowersupply

Beamexpandingtelescope

Alignmentbubble

Receivingtelescope

Detector


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Figure 3.1. Satellite image of the Cheshunt Park region in the Upper Hunter Valley showinglocations of the LIDAR station and surrounding mines.

The LIDAR and in-situ instruments are located from GPS measurement to be at:

n Easting 314,822 m; Northing 6,402,502 m; and

n Lat. 32.49917998o; Long. 151.0289291o.

There is ancillary meteorological equipment located at the Cheshunt Weather Station,

n AMG: E 314,660; N 6,398,330.

3.2 METHOD

The following sub-sections outline the methods used to set up and operate the LIDAR.

3.2.1 Energy Monitor CalibrationThe laser pulse energy varies from shot to shot and over time depending on environmentalconditions and how the laser is being used. Therefore it was necessary to record the laser pulseenergies to enable the removal of the effects of laser energy variations from the atmosphericbackscatter. To do this an Energy MONitor (EMON) recorded a voltage signal for each Ultra lasershot that was fired. For example, a typical field sequence was 2400 laser shots fired at a rate of 20Hz – the EMON would record an “energy” value for each of these shots as well as a voltage offset.

The EMON was calibrated on 11-12/10/03 by simultaneous measurements of the Ultra laser pulseenergies with the EMON and a laser-pulse energy integrating device (Scientech). It is considered


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outside the scope of this report, which endeavours to demonstrate the LIDAR technology only, toprovide a complete description of the EMON calibration. However, we provide the results of thecalibration in the following sequence of figures:

n Figure 3-1. Best initial calibration tests for EMON vs. Scientech;

n Figure 3-2. Calibration Using Final Two Calibration Runs Calibration result using only tests7 and 8; and

n Figure 3-3. Final determined EMON reading vs. pulse energy relationship from calibrationtests.

Figure 3-1. Initial EMON calibration data

Figure 3-2. Calibration Using Final Two Calibration Runs


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Figure 3-3. Final Determined EMON Calibration

The EMON calibration equation used to create Figure 3-3 is,

Es = {EMON + 1⋅536} × 6.781 (mJ/shot), (3.1)

and the final EMON energy values used for scaling the LIDAR data are provided in Appendix B.

3.3 LIDAR OPERATIONS

The LIDAR field operations for this project comprised the following steps:

(1) Check on all LIDAR optical components and electronic connections including those for lasersafety;

(2) Check for any aircraft movements;

(3) Remove hatch and power up;

(4) Data acquisition of the “optical zero” by placement of telescope cover; and

(5) Removal of telescope cover, then step-by-step acquisition of laser shot sequences withsimultaneous (manual) recording of field notes; i.e., LIDAR settings and meteorologicalconditions for assistance for later analysis of data.

4 DATA ANALYSIS METHODS

4.1 INTRODUCTION

Once a LIDAR is operational, typically large volumes of data are acquired very rapidly and thismeans a significant part of any LIDAR study involves data management, pre-processing of data,and finally, analysis and reporting. The analysis of data for a series of LIDAR measurements thatcould be undertaken is virtually unlimited, as a brief inspection of the scientific literature shows.


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What we have endeavoured to do for this project is demonstrate that highly valuable informationcan be recovered from a LIDAR dataset even with the most basic data analysis undertaken atrelatively low cost. This was done using simple software procedures developed in-house. Thefollowing sub-sections detail the data processing and basic data analysis undertaken for this project.

4.2 THEORETICAL BACKGROUND

4.2.1 The LIDAR EquationThe instantaneous optical power received from range r, at the aperture of a LIDAR telescope maybe expressed as,

φ(r) = φo (cτ/2) A(r)r-2β(r)T2(ro, r), (4.1)

where φo is the average optical power of the transmitted pulse, A(r) is the effective receiving areaof the telescope objective lens or mirror, c is the speed of light, and τ the pulse duration (theproduct cτ is the pulse length), the inverse range-squared term is due to the spherical geometry ofscattering, β is the volume backscatter coefficient (m2/m3/sr or m-1sr-1), and T(zo,z) is theatmospheric transmittance from the LIDAR (ro) to range r; for example, Collis and Russell (1976).The transmittance T is given by,

T(z) = exp{-∫σ(z’)dz’}. (4.2)

The equations (4.1) and (4.2) omit the effects of multiple scattering, which is negligible for short-range measurements of aerosols in the boundary layer. The integral in (4.2) is computed from theLIDAR level to height z, and σ is the volume extinction coefficient (m2/m3 or m-1). The values of βand σ are dependent on the composition and size distribution of the particles. Further, the β and Tparameters may be separated into components thus:

β(z) = β1(z) + β2(z) + β3(z) +… (4.3)

T(0, z) = T1(0, z).T2(0, z)T3(0, z)… (4.4)

where 1, 2, 3… represent different species with different particle size distributions/compositions.

If information on β and σ is available for some sample height, it is possible to solve the equation(4.1) for a height profile of β or σ; for example, Fernald (1984). However, for vertically-pointingLIDAR measurements of the boundary layer atmosphere, where information is retrieved fromheights of only a few hundred metres above the LIDAR1, a separation of the variables β and σ isnot necessary for a simple retrieval of atmospheric backscatter. The reason for this is that ingeneral the transmittance over short ranges is high (assuming no fog). Thus, complex and costlyanalysis can be avoided simply by retrieving data proportional to the product of β and T2.

A simpler LIDAR equation combines the instrumentation parameters for a specific LIDAR systeminto a system constant C, and describes the backscattered signal voltage (V) as a function of rangefrom the LIDAR. In this case we assume a vertically-pointing LIDAR so substitute height (z) for r.the LIDAR equation may be expressed as,

V(z) = E.C.z-2β(z)T2(zo, z) + Vo, (4.5)

where E is the energy of the transmitted laser pulse and Vo is a signal voltage offset. 1 Short-range LIDAR retrievals of backscatter depend on the laser beam lying sufficiently within the field ofview of the telescope.


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4.2.2 Calculated Aerosol Properties for Cheshunt Park LIDARAs a stand-alone instrument LIDAR has good ranging and detection capabilities, and thereforeproduces detailed vertical structure information, but the retrieval of absolute values of the physicaland chemical properties of the atmosphere can only be achieved with independent measurements.The need for independent measurements is due to the required separation of β and σ described inthe previous section.

Ideally, particles size distributions are measured in situ and simultaneously with the LIDARmeasurements. The atmospheric optical properties of these particles are calculated using theRayleigh and Mie scattering theories (e.g., Van de Hulst, 1981; Wiscombe, 1980). The LIDARmeasurements can be calibrated to some extent using these calculated (expected) scatteringproperties.

Time constraints project prevent us from undertaking a complete analysis of the relationshipsbetween the LIDAR measurements and the in situ particles data from Cheshunt Park (DustTrak,HVS etc.), so some previously calculated results are presented in this section, which provide orderof magnitude results for the optical properties. Based on this information we then estimate theorder of magnitude of β and σ for the Cheshunt Park aerosols.

Pickett (1999) calculated optical properties of boundary layer and free troposphere aerosols inclean (marine) air, for the laser wavelength 532 nm (frequency doubled Nd:YAG laser). TheseMie calculations assumed spherical particles and used code developed by S.Banks (CSIRODivision of Atmospheric Research). The calculations were based on measured particle sizedistributions measured by aircraft-borne instruments over the Southern Ocean (refer to Pickett,1999), and partitioned into the following particle size and composition groups: ammonium sulfates,common salt (NaCl), and water droplets. These measured particles were measured by instrumentsfor two size ranges (radii): 0.06–0.056 µm; and 1–23.5 µm. Most of the particles were in thesmaller size range, and most of the mass, small water droplets and probably some dryer saltparticles, was in the larger size range. Some key points from those calculations are provided inTable 4-1, for a number of ambient (measured) relative humidities. The measured numbers ofparticles in each case (N), in the boundary layer or above it (“free troposphere”), are also provided.

Table 4-1 Calculated Aerosol Properties for Wavelength 532 nm

Location of Particles RH (%) β (sr-1 m-1) σ (m-1) N (cm-3)Boundary layer 60 6.02E-07 1.23E-05 28.6Boundary layer 70 6.13E-07 1.27E-05 28.6Boundary layer 80 6.33E-07 1.32E-05 28.6Boundary layer 90 6.93E-07 1.48E-05 28.6Boundary layer 95 7.98E-07 1.86E-05 28.6Free troposphere 50 8.90E-08 1.73E-06 8.39Free troposphere dry 1.31E-07 1.32E-06 8.39

The primary differences between the results provided in Table 4-1 and the particles measured byLIDAR at Cheshunt Park are, obviously, the source of the particles (marine versus inlandenvironment), and secondly, wavelength (Cheshunt Park, 1.064 µm). Determination of the likelyvalues of β and σ for the particles observed by LIDAR at Cheshunt Park is outlined in thefollowing paragraphs, using the information provided above as a guide.

Apart from moist aerosols being composed of significant amounts of water, (a typical fog droplet is10 µm in radius), a previous ACARP (Bridgman et al., 2002), found that aerosols measured in theHunter Valley comprise, by mass, the substances provided in dot form below:

n PM10: Soil and sea-salt (NaCl); and


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n PM2.5: Ammonium sulfate, elemental carbon, soil and sea-salt.

In Bridgman et al. (ibid.) the “soil” component was determined from Principal ComponentsAnalysis and comprised a group of elements, with the key elements from this group beingaluminium, iron and silicon.

We have carried out Mie calculations for this project for the same particle size distributions used toproduce the values shown in Table 4-1, but using refractive indices to reflect the substances thatmay exist in the inland environment at Cheshunt Park, based on the Bridgman et al. (ibid.)information. The chosen substances and refractive indices are provided in Table 4-2 below(primary reference CRC, 1978; secondary reference, Pickett, 1999).

Sensitivity tests show the change in wavelength from 532 nm to 1064 nm produces only a smalland negligible difference in the results; refer to the comparison in Table 4-2 for water droplets.Any differences in scattering due to wavelength have been smoothed out by the particle sizedistributions.

Table 4-2 Calculated Aerosol Properties for Wavelength 1.064 µm

Substance Refractive Index(Real2, Complex3)

β (sr-1 m-1) σ (m-1) N (cm-3)

Water, 532 nm 1.3337, 1.5 x 10-9 6.99E-07 1.31E-05 26.1Water, 1064 nm 1.32, 1.5 x 10-9 6.76E-07 1.31E-05 26.1Glass, SiO2 (‘heavy flint’) 1.56, 10-6 1.43E-06 1.33E-05 26.1Aluminium oxide, hydrated 1.583, 10-5 1.93E-06 1.34E-05 26.1Iron oxide, hydrated (est.) 2.73, 10-4 2.11E-06 1.36E-05 26.1

Inspection of Table 4-2 and with row 1 of Table 4-1, shows that the more soil-like aerosols (glass,aluminium and iron oxides), scatter and absorb light more strongly than the marine aerosols.Therefore the soil-like aerosols have higher values for backscatter and extinction. The opticalproperties of these inland aerosols may have been underestimated due to the relatively low particleconcentration (26 cm-3) used for the calculations.

The conclusion of this section is that the absolute values of the volume scattering coefficients inrelatively clean air4 expected to be observed by the 1.064 µm-wavelength LIDAR will beapproximately:

n β 1.0 x 10-6 sr-1 m-1; and

n σ 1.9 x 10-5 m-1 (humid conditions) down to 1.2 x 10-5 m-1 (dryer conditions).

Although molecular backscatter would have been detected by this LIDAR, the molecularbackscatter in the boundary layer for the LIDAR wavelength has not been calculated for thisproject. The variation in molecular backscatter with height is negligible for the relatively thinatmospheric depths examined for this project. The lack of detailed information on molecular

2 Most of these refractive indices are for the sodium emission wavelength, 589 nm. Sensitivity tests usingrefractive indices for glass obtained from CRC (1978), indicate that the effect of change in wavelength to1.064 µm is at most, an error of -2%; i.e., negligible for the Mie scattering calculations.3 There is less information on complex refractive indices. Estimates here are based on increasing that forammonium sulfates and salt (10-7) by an order of magnitude in each case.4 An indication of clean air at the Cheshunt Park site may be provided by the periods when the DustTrak wasshowing approximately less than 5 µg/m3.


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backscatter has not detracted from providing detailed information on the vertical structure of theboundary layer.

4.3 ANALYSIS OF CHESHUNT PARK LIDAR DATA

4.3.1 Initial Data ProcessingThe data analysis is described step-by-step using plots of the data for each step. First, an exampleof a raw (unprocessed) LIDAR signal and its corresponding “zero” signal (telescope cover on), isprovided in Figure 4-1. The plot shows the traces observed by the LIDAR operator on theCathode Ray Oscilloscope (CRO) display, after targeting the appropriate time-base and signallevel. The traces show signal voltages versus time. Time zero relates to the time when a laserpulse is fired. Inspection of this plot shows that a single LIDAR signal is acquired over a very shorttime period, in this case only 45 µS.

The next step is to subtract the zero signal from the LIDAR signal. Also, the resultant signal offsetis subtracted by using a portion of the signal known to produce no backscatter (in this case asection of the end of the profile received from “above” the cloud). The time data was thenconverted to ranges given that each signal byte is obtained in a period equivalent to cτ/2. Theresult is shown in Figure 4-2. With the benefit of the field notes for this shot sequence indicatingaltocumulus clouds overhead (19/10/04 15:08), this plot shows:

n Measured aerosol backscatter from near ground level up to a height of approximately 400metres;

n Laser backscatter detected from a cloud with a cloud-base height approximately 3,680 metres.

This result demonstrates the powerful capabilities of LIDAR – good range-resolution and rangingcapability – and good sensitivity. No other type of instrument could retrieve this amount of detailfrom a cloud of small cloud particles, (with particle radii probably of the order 10–100 µm), at thisrange.

Figure 4-1 Raw LIDAR and “Zero” Signals


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Figure 4-2 LIDAR Signal with “Zero” Signal Removed

A larger scale view of the LIDAR signal up to a height of 1000 metres is provided in Figure 4-3.This plot shows a small noise spike up to a height of approximately 40 metres, a near-field 5 signalgrowing from heights 50 to just under 100 metres as the laser beam is gradually enveloped by thetelescope field of view, then a complete and strong backscatter signal from boundary layer aerosolsreceived from 100-400 metres.

Figure 4-3. Larger Scale View of Heights 0-1000 metres from Figure 4-2

The third step in the analysis is to perform a range-squared correction. The result for the range-corrected profile is provided in Figure 4-4.

5 The “near-field” is defined here as the region from which the large, close-range atmospheric backscatter isreceived by the LIDAR, in this case comprising backscatter from aerosols and air molecules.


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Figure 4-4 LIDAR Signal Voltage vs. Time, “Zero” Signal Removed

The noisy signal in this plot from ranges approximately 2000 metres and onwards, provides someindication of the problems faced for analysis of LIDAR signals from distant targets. This is aproblem for analysis of cloud signals, but is not a problem for this project, which has focussed onshort-range backscatter from boundary layer aerosols. A larger scale plot of the same figure for theranges 0-1000 metres is provided in Figure 4-5.

Figure 4-5. Logarithmic Larger-Scale View of Heights 0-1000 metres from Figure 4-4

The logarithmic plot shows that noise, (both electrical and numerical), could be a significantproblem for analysis. This is especially the case for heights above approximately 400 metres. Thenext step forward is to analyse the relationships between consecutive signals. There aremathematical procedures available to do this, but the simplest (and cheapest) method is to use thein-built pattern recognition capabilities of the human eye-and-brain. The LIDAR results can be


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presented as contour plots of height versus time-of-shot, with the strength of the received signalcolour-coded for the eye. This is more than ample to provide information on variations inatmospheric backscatter. Such contour plots will be provided later in the Results section.

4.3.2 Retrieval of Vertical Structural Properties of the Boundary LayerIn this section we provide some brief and final notes on the data used for the results, (presented inthe next section as contour plots), are in the following dot points:

n The LIDAR results have accounted for the average laser shot energy in each burst of lasershots. That is, the (range-corrected) LIDAR signals have been divided by the calibrated shotenergies, accounting for the large laser energy variations as shown in Appendix B.

n The effects of multiple scattering have been assumed to be negligible. This is not anunreasonable assumption considering the following points:

n The aerosols were measured at short ranges and the field of view of the LIDAR isrelatively narrow;

n The optical depths of the boundary layer aerosols are small therefore the effects ofmultiple scattering would have been small.

5 RESULTS

5.1 SUMMARY OF MEASUREMENTS

A summary of the LIDAR measurements obtained from the Cheshunt Park field site is provided inTable 5-1. The initial measurements were more sporadic because initially in the field morehardware and software improvements were being made improve the LIDAR signal quality andefficiency and quality of data acquisition. A full summary of the field notes is provided in theappendix.

Although a goal of this project was not to obtain LIDAR measurements of clouds, cloudobservations of clouds are a feature of the field notes for three reasons. First, fog and clouds wereoften observed in the boundary layer so measurements of clouds/fogs/mists could not be avoided.Secondly, the strong and clear backscatter signals from boundary layer clouds and higher altitudeclouds assist with the co-alignment of the laser beam and telescope field of view; and finally, thecloud signals provided a good quality-check on the data.

Table 5-1 Summary of LIDAR Measurements

Data Set Date-TimeFrom: (EST)

Date-Time To:(EST)

ShotSeq. # Some Field Observations / Comments

031011a 11/10/03 17:22 11/10/03 20:55 5 First LIDAR shots.031011b 11/10/03 21:31 11/10/03 22:55 16 First confirmed atmospheric signals –

backscatter from stratocumulus cloud ataltitude 3000 metres

031011c 11/10/03 23:01 11/10/03 23:54 5 Possible backscatter from boundary layeraerosols approx. 1000 metres deep incloud-free air

031012a 12/10/03 09:06 12/10/03 09:22 2 Backscatter from cloud-free air031012b 12/10/03 10:34 12/10/03 14:23 20 Stratocumulus and cumulus clouds031012c 12/10/03 14:34 12/10/03 17:09 46 Cumulus clouds and cloud-free sky, ops.

were ceased ~17:00 due rain.16:40: “v. clean air”, Grimm 3 µg/m3;DustTrak 3-4 µg/m3.22:00. “Very clear air, some thin layers


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Data Set Date-TimeFrom: (EST)

Date-Time To:(EST)

ShotSeq. # Some Field Observations / Comments

Sc, DustTraks 4-8 µg/m3; Grimm 12-16µg/m3.”

031013a 13/10/03 15:32 13/10/03 18:33 24 Rain overnight, unable to operate a.m.due rain. Meas. are of broken cld &cloud-free. 17:50: Grimm 8 µg/m3;DustTraks 4-5 µg/m3. First Energy-Monitor readings. Bad signals .

031013b 13/10/03 18:40 13/10/03 19:05 8 Nocturnal thin cloud. Do not use fileTek00026.

031015a 15/10/03 00:32 15/10/03 01:11 4 Nocturnal boundary layer. Bad signals .031015b 15/10/03 05:48 15/10/03 08:02 16 Light fog. Clear (cloud-free). Bad

signals .031015c 15/10/03 09:05 15/10/03 10:53 10 Clear. Zero signal obtained.031015d 15/10/03 11:26 15/10/03 11:50 5 –031015e 15/10/03 12:37 15/10/03 22:04 61 Nocturnal layer study, JH031016a 16/10/03 04:07 16/10/03 13:39 90 Nocturnal layer study, JH031017a 17/10/03 00:58 17/10/03 03:30 25 Nocturnal layer study, low cloud031017b 17/10/03 04:44 17/10/03 11:10 46 Nocturnal layer study, overcast a.m.031017c 17/10/03 11:17 17/10/03 17:56 40 Nocturnal layer study, JH031017d 17/10/03 18:04 17/10/03 22:06 28 Clouds then clear031018a 18/10/03 05:32 18/10/03 08:46 26 Haze, low overcast031018b 18/10/03 08:50 18/10/03 11:47 25 Clouds dissipating then clear031018c 18/10/03 12:04 18/10/03 21:03 43 Clear031019a 19/10/03 04:19 19/10/03 08:03 30 Dissipation nocturnal fog031019b 19/10/03 08:07 19/10/03 11:16 22 Clear sky, steady north breeze031019c 19/10/03 13:45 19/10/03 15:53 10 Clear, scattered cumulus031019d 19/10/03 16:04 19/10/03 17:07 9 Overcast, N wind031019e 19/10/03 17:14 19/10/03 19:43 26 Dragline plume031020a 20/10/03 03:34 20/10/03 07:13 24 Nocturnal observations, clouds031020b 20/10/03 07:25 20/10/03 10:45 26 Morning, clear, energy monitor test031024a 24/10/03 04:40 24/10/03 06:44 25 –031024b 24/10/03 06:51 24/10/03 11:00 33 –031024c 24/10/03 11:03 24/10/03 18:05 20 –031025a 25/10/03 04:07 25/10/03 06:36 33 –031025b 25/10/03 06:41 25/10/03 07:40 11 –031025c 25/10/03 07:56 25/10/03 08:33 16 Minimum range tests (telescope steering)031029a 29/10/03 10:27 29/10/03 11:30 14 “August Wind” type conditions031215 15/12/03 5:06 15/12/03 15:22 130 Rising clouds031216 16/12/03 4:09 16/12/03 21:37 172 Rising clouds031217 17/12/03 3:59 17/12/03 22:07 217 Clear skies031218 18/12/03 3:59 18/12/03 11:03 99 Clear skies, breeze from SE


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5.2 LIDAR OBSERVATIONS 16 OCTOBER 2003

5.2.1 LIDAR Observations

Figure 5-1. LIDAR observations – ground level to approx. height 1350 metres

The time sequence of the range data sets clearly displays the changing of aerosol backscatter withdiurnal patterns. The early morning time period shows the presence of an inversion layer <200mvertical height and aerosol backscatter growing rapidly. As the sun rises, convective upwellinglofts the aerosols into a larger volume and backscatter decreases. The vertical height of the cappinginversion appears to be ~550m at 7:30am local time. As the morning progresses the cappinginversion appears to continue rising to 1150m-1300m as evidenced by cloud ingress atop thecapping inversion. Figure 5-2 is a closer look at the structures <500m during the time period.

As the opportunity presented to compare the LIDAR data with independent measurements ofaerosols acquired 10m away at ground level, the data from the Grimm is plotted as a comparison.


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Figure 5-2. LIDAR observations – ground level to height 500 metres

5.2.2 Simultaneous In Situ PM Measurements by Grimm 16 October 2003

Figure 5-3. Grimm measurements for PM10 and PM2.5

There is a correlation with the Grimm data and the aerosol backscatter signal as recorded byLIDAR. This is confirmation of the diurnal atmospheric processes of nocturnal layers trappingaerosols adjacent to the ground. As the sun rises the energy deposited in the atmosphere initiallycauses the local temperature to drop. Mists form when the temperature is close to the dew point forthe appropriate humidity and densification of the stagnant layer gives rise to the increase in aerosolmeasurement. As the sun continues to rise, the mists evaporate locally cooling the atmosphere but


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beginning convective uplift. The radiant energy begins to heat the ground and the convectivemixing of the layer begins. The top of the convective mixed layer moves to higher elevation.







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These data reflect that a wind change has brought clean air in over the LIDAR site. The Grimmspike at 17:00 hours reflects an aerosol spike that did not extend >100m into the atmosphere.


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These data reflect a measurement of the dust plume from an operating dragline at a range of ~3kmthat was observed by the operator on site to have drifted directly over the LIDAR position at 18:00hours. These data are a reflection of the background clean air levels and the highest loftedparticulate levels extending from ground level, where the Grimm is stationed to some 350mvertically as determined by the LIDAR trace. An expanded trace is shown in Section 5.5.4.


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5.5.3 LIDAR Observations – 19/10/04, a.m.

Figure 5-10. LIDAR observations 19/10/03 ~0430-1100EST to 500 metres

5.5.4 LIDAR Observations of a Dragline Dust Plume


A more detailed look at the dragline dust plume shows detection below the 100m overlap region.Because of the very high aerosol load, multiple scattering events are taking place and deflectinglight back into the telescope. In the region of vertical height between initial and full overlap, thescatter is collected more efficiently than would otherwise be possible. The magnitude of thebackscatter is very high due to this aerosol load.

Rainfall was observed to reach ground level at the end of this measurement sequence – note theapparent suppression of the plume beginning approximately 19.1 hours.


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Figure 5-12. LIDAR observations 20/10/2003 0430-1030 to 2500 metres




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5.8 LIDAR OBSERVATIONS 25/10/03



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Figure 5-16. LIDAR observations 15/12/03 ~0630-1600 to ~1250 metres



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Figure 5-18. LIDAR observations 16/12/03 0430-0900EST to ~1250 metres

Figure 5-19. LIDAR observations 16/12/03 ~0900-1600EST to ~1250 metres


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Figure 5-20. LIDAR observations 16/12/03 2000-2124EST to 600 metres




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Figure 5-22. LIDAR observations 17/12/03 1400-2200EST to 300 metres




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6 CONCLUSIONIn defining an objective for this project it was stated that:

The vertical structure of the atmosphere has a critical impact on air pollutiondispersion from ground-based sources. A windy, stormy atmosphere is unstable andallows rapid dispersion. A dominant high pressure system creates weak winds andstrong stability, minimising dispersion and potentially creating air pollution episodes.In the Hunter Region, an understanding of the vertical structure of the atmosphereand how it changes with time will allow better modelling and forecasting of pollutiondispersion from mining, industrial and urban sources.

Currently our understanding of the vertical structure of the atmosphere, not only in the HunterValley but in Australia and the world in general, is limited. Primarily this is because, in general,vertical measurements of the vertical structure of the atmosphere are rare due to the high cost ofmeasurement. This project, which included simultaneous LIDAR and in situ (particulate matter)measurements, has provided rare and highly valuable observations of the changing structure of theboundary layer atmosphere at an inland site in the Hunter Valley. The simultaneous remotesensing-and-in situ observations included some acquired during one fortunate occasion when theLIDAR observed a dust plume from a mine dragline machine. Some of these LIDAR observationsmay represent a world-first for a mine site.

The key conclusions of the LIDAR project are:

n The LIDAR system is able to elucidate atmospheric structure above 100 metres including fordusty inland sites. With further engineering effort the minimum height could be lowered.

n In general, the aerosol load in the Hunter Valley atmosphere was found to be quite low duringthe observations period. In fact on some occasions the air was very clean. This meant thedetermination of convective mixed layer height was difficult in an absolute sense, sometimes.Secondary indicators such as cloud formation atop the layer, serve as a guide.

n Lofted anthropogenic plumes due to dragline activity were observed only when prevailingwind direction allowed.

n When the meteorological conditions are appropriate, textbook diurnal variation in boundarylayer height with time is observed.

7 ACKNOWLEDGEMENTSn CSIRO Atmospheric Research (hardware design, hardware and advice)

n University of Newcastle

n Sinclair Knight Merz (financial support for M. Pickett – software, fieldwork, data analysis,reporting)

n Itec Engineering (advice on hardware design)


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8 LIST OF ACRONYMS & DEFINITIONSACARP Australian Coal Association Research ProgramAGL Above Ground LevelASL Above Sea LevelNSW EPA Environment Protection Authority (NSW)USEPA Environmental Protection Agency (United States)PM Particulate MatterPM2⋅5 Particulate Matter 2⋅5, particle diameters less than 2⋅5 µmPM10 Particulate Matter 10, particle diameters less than 10 µmTSP Total Suspended Particulates

9 REFERENCES1. Bridgman, H., M. Pickett and D. Cohen, Modelling Fine-Particulate Dispersion Over Short

Time Spans from Open Cut Mining Activity , Australian Coal Association Research ProjectC10035, University of Newcastle & Australian Nuclear Science and Technology Organisation,July 2002.

2. Collis R.T.H. and P.B. Russell, Lidar measurements of particles and gases by elasticbackscattering and differential absorption in Topics in Applied Physics: Laser Monitoring ofthe Atmosphere. Springer, New York, 1976.

3. CRC (Chemical Rubber Company), Handbook of Chemistry and Physics, 58th Edition, CRCPress, 1977-1978.

4. Fernald, F.G., Analysis of atmospheric lidar observations: some comments. Appl. Opt. 5, 652-653, (1984).

5. Pickett, M.C., Lidar and Infrared Radiometer Studies of Stratocumulus Clouds, PhD Thesis,Victoria University of Technology, 1999.

6. Schaefer & Day, A Field Guide To The Atmosphere, Houghton Mifflin, Boston (1981)

7. Van de Hulst, H.C., Light Scattering by Small Particles. Dover, New York, 1981.

8. Wiscombe, W.J. Improved Mie scattering algorithms. Appl. Opt. 19, 1505-1509, 1980.


APPENDIX 3.A. SUMMARY OF LIDAR FIELDNOTES


APPENDIX 3.B. ENERGY MONITOR RESULTS


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lidar observations of aerosols in the upper hunter

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