Gaseous plume detection in the LWIR (thermal infrared) region of the spectrum (7-14 μm) with the use of hyper-spectral imaging sensors is a rapidly advancing technology.1-2 There are many industrial pollutants that have unique or strong absorption/emission signatures in the mid-wave infrared (MWIR) region of the spectrum. The C-H vibrational frequency modes of hydrocarbons are clustered in the 3-4 micron region. Until recently the use of the MWIR region has been hampered, in part, by a lack of detailed and quantitative characterization of the phenomenology influencing the at-sensor radiance.3 The goal of this paper is to increase understanding of this phenomenology and thus the utility of the MWIR spectral region for industrial pollution monitoring applications.

We conducted experiments with side-by-side active and passive sensors in the 8-12 micron region in order to study similarities and differences in the spectral signatures detected by the two sensors. The active instrument was a frequency-agile CO2 lidar system operating on 44 wavelengths and at a total pulse repetition rate of 5 kHz. The passive system was an Aerospace Corp. dispersive imaging spectrometer with 128 spectral channels from 750-1250 cm-l. The sensors viewed both natural scenes and man-made objects typical of industrial scenes at ranges of 1-3 km along horizontal paths. Scenes were viewed under various ambient conditions in order to evaluate the effects of radiance contrast for the passive images at different times of a day. Both imaging and 'staring' experiments were conducted on the background scenes with a significant level of 'clutter'. Preliminary analysis shows that reflectance data (from an active sensor) does not necessarily have a simple relationship to passive data, which is influenced by ground emissivity, atmospheric radiance, and temperature differences.

The sensitivity of imaging, hyperspectral, passive remote sensors in the long-wavelength infrared (LWIR) spectral region is currently limited by the ability to achieve an accurate, time-invariant, pixel-to-pixel calibration of the elements composing the Focal Plane Array (FPA). Pursuing conventional techniques to improve the accuracy of the calibration will always be limited by the trade-off between the time required to collect calibration data of improved precision and the drift in the pixel response that occurs on a timescale comparable to the calibration time. This paper will present the results from a study of a method to circumvent these problems. Improvements in detection capability can be realized by applying a quick, repetitive dither of the field of view (FOV) of the imager (by a small angular amount), so that radiance/spectral differences between individual target areas can be measured by a single FPA pixel. By performing this difference measurement repetitively both residual differences in the pixel-to-pixel calibration and 1/f detector drift noise can effectively be eliminated. In addition, variations in the atmosphere and target scene caused by the motion of the sensor platform will cause signal drifts that this technique would be able to remove. This method allows improvements in sensitivity that could potentially scale as the square root of the observation time.

The authors report examples of the use of a scanning tunable CO 2 laser lidar system in the 9-11 ym region to construct images of vegetation and rocks at ranges of up to 5 km from the instrument. Range information is combined with horizontal and vertical distances to yield an image with three spatial dimensions simultaneous with the classification of target type. Reflectance spectra in this region are sufficiently distinct to discriminate between several tree species, between trees and scrub vegetation, and between natural and artificial targets. Lidar sensing of vegetation offers some complementary characteristics to passive remote sensing. In the thermal infrared (8-12 μm), lidar interrogation of natural targets is essentially a pure reflectance measurement, unaffected by topographical shading and spatial variations in temperature. Differential measurements using CO2 lasers have been known for some time to be useful in discriminating between vegetation types, tree species, and rock types. The authors have investigated the utility of a scanning CO2 DIAL system in constructing vegetation maps for broad areas

Laser speckle can influence lidar measurements from a diffuse hard target. Atmospheric optical turbulence will also affect the lidar return signal. We present a numerical simulation that models the propagation of a lidar beam and accounts for both reflective speckle and atmospheric turbulence effects. Our simulation is based on implementing a Huygens-Fresnel approximation to laser propagation. A series of phase screens, with the appropriate atmospheric statistical characteristics, are used to simulate the effect of atmospheric turbulence. A single random phase screen is used to simulate scattering of the entire beam from a rough surface. We compare the output of our numerical model with separate CO(2) lidar measurements of atmospheric turbulence and reflective speckle. We also compare the output of our model with separate analytical predictions for atmospheric turbulence and reflective speckle. Good agreement was found between the model and the experimental data. Good agreement was also found with analytical predictions. Finally, we present results of a simulation of the combined effects on a finite-aperture lidar system that are qualitatively consistent with previous experimental observations of increasing rms noise with increasing turbulence level.

The measurement sensitivity of CO2 differential absorption LIDAR (DIAL) can be affected by a number of different processes. Two of these processes are atmospheric optical turbulence and reflective speckle. Atmospheric optical turbulence affects the beam distribution of energy and phase on target. The effects of this phenomenon include beam spreading, beam wander and scintillation which can result in increased shot-to-shot signal noise. In addition, reflective speckle alone has been shown to have a major impact on the sensitivity of CO2 DIAL. We have previously developed a Huygens-Fresnel wave optics propagation code to separately simulate the effects of these two processes. However, in real DIAL systems it is a combination of these phenomena, the interaction of atmospheric optical turbulence and reflective speckle, that influences the results. In this work, we briefly review a description of our model including the limitations along with a brief summary of previous simulations of individual effects. The performance of our modified code with respect to experimental measurements affected by atmospheric optical turbulence and reflective speckle is examined. The results of computer simulations are directly compared with lidar measurements and show good agreement. In addition, simulation studies have been performed to demonstrate the utility and limitations of our model. Examples presented include assessing the effects for different array sizes on model limitations and effects of varying propagation step sizes on intensity enhancements and intensity probability distributions in the receiver plane.

Issues related to the development of direct detection, long-range CO2 DIAL systems for chemical detection and identification are presented and discussed including : data handling and display techniques for large, multi-lambda data sets, turbulence effects, slant path propagation, and speckle averaging. Data examples from various field campaigns and CO2 lidar platforms are used to illustrate the issues.

A combined experimental and computational approach utilizing tunable CO(2) lasers and chemometric analysis was employed to detect chemicals and their concentrations in the field under controlled release conditions. We collected absorption spectra for four organic gases in the laboratory by lasing 40 lines of the laser in the 9.3-10.8-mum range. The ability to predict properly the chemicals and their respective concentrations depends on the nature of the target, the atmospheric conditions, and the round-trip distance. In 39 of the 45 field experiments, the identities of the released chemicals were identified correctly without predictions of false positives or false negatives.

A combined experimental and computational approach utilizing CO2 infrared gas lasers and chemometric multivariate analysis was employed to detect chemicals and their concentrations in the open atmosphere under controlled release conditions. Absorption spectra of four organic gases were collected in the laboratory by lasing 40 lines of a Synrad 15 W CO2 laser in the 9.3 to 10.8 micron range. Several chemometric calibration models were constructed based on this IR data using the Partial Least Squares computational technique. The chemometric models were used to analyze in near real time the field DIAL data acquired over this exact wavelength range at round trip distances of 7 and 13 km. It will be shown that the ability to predict the chemicals and their respective concentrations depends on a variety of factors. In 39 of the 45 experiments, the identities of the released chemicals were correctly identified without predictions of false positives or false negatives. Under the best field conditions, we achieved predictions of absolute concentrations within 30% of the actual values.

The ambient atmosphere between the laser transmitter and the target can affect CO2 differential absorption lidar (DIAL) measurement sensitivity through a number of different processes. In this work, we will address two of the sources of atmospheric interference with CO2 DIAL measurements: effects due to beam propagation through atmospheric turbulence and extinction due to absorption by atmospheric gases. Measurements of atmospheric extinction under different atmospheric conditions are presented and compared to a standard atmospheric transmission model (FASCODE). We have also investigated the effects of atmospheric turbulence on system performance. Measurements of the effective beam size after propagation are compared to model predictions using simultaneous measurements of atmospheric turbulence as input to the model. These results are also discussed in the context of the overall effect of beam propagation through atmospheric turbulence on the sensitivity of DIAL measurements.

Reflection of laser light from a diffuse surface exhibits a complex interference pattern known as laser speckle. Measurement of the reflected intensity from remote targets, common to `hard-target' differential absorption lidar, requires consideration of the statistical properties of the reflected light. We have explored the effects of laser speckle on the noise statistics for CO2 DIAL. For an ensemble of independent speckle patterns it is predicted that the variance for the measured intensity is inversely proportional to the number of speckle measured. We have used a rotating drum target to obtain a large number of independent speckle and have measured the predicted decrease in the variance after correlations due to system drifts were removed. Measurements have been made using both circular and linear polarized light. These measurements show a slight improvement in return signal statistics when circular polarization is used. We have conducted experiments at close range to isolate speckle phenomena from other phenomena, such as atmospheric turbulence and platform motion thus allowing us to gain a greater understanding of speckle issues. We have also studied how to remove correlation in the data caused by albedo inhomogenuties producing a more statistically independent ensemble of speckle patterns. We find that some types of correlation are difficult to remove from the data.

Preliminary scoping exercises indicate that remote-sensing lidar can play a useful role in missions that involve determining regional weather patterns and atmospheric transport conditions. Both meteorological modeling and local atmospheric sensing should be employed. Satellite-based remote sensing systems, using an incoherent Doppler wind-sensor, seem feasible.

The need for an instrument capable of measuring water-vapor fluxes over mixed canopy and large areas has long been recognized. Such a device would greatly enhance the study of evapotranspiration processes and has great practical value for water management. To address this problem, a scanning water Raman lidar has been designed and constructed. Analytical methods have also been developed to take advantage of the type of information that this lidar can generate. The lidar is able to measure the absolute water content and calculate the evaporative flux quickly over relatively large areas. This capability provides new opportunities for the study of microscale atmospheric processes. The variogram data indicate that the spatial sampling size must be of the order of 10 m if fluxes and scalars are to be properly represented. Examples of data are presented.

The exchange of mass and energy is a turbulent process that often occurs in coherent periods of time and in discrete regions of space. Prior to the development of volume imaging lidars, the study of coherent structures in the atmosphere was limited, for the most part, to time-series analysis of point-instrument data. This paper describes the use of the Los Alamos National Laboratories scanning Raman lidar to observe both temporal and spatial coherent structures, such as plume and ramp-like features, that developed over a Green Ash orchard. Most of the ramp structures identified from lidar data were between 20 and 30 m in size and had transit lifetimes of between 20 and 30 s. The validity of these results was confirmed by comparison with previously collected point-instrument data. An analysis of the multi-dimensional lidar images was also able to relate discrete spatial features, such as plumes to ramp patterns, found at the base of plumes in both the temporal and spatial domains. A further finding supports the concept that ramp development is a function of shear-scale and roughness length. The lidar represents a new tool to gain a deeper understanding of the mechanisms underlying the turbulent exchange process.

A continuously-tunable, narrow-linewidth, flashlamp-pumped, Q-switched Cr: LiSAF laser has been developed (energy: 30 mJ, pulsewidth: 40 ns, linewidth:<2 GHz) and was used successfully for the DIAL(differential absorption lidar) measurements of atmospheric water vapor. Application to LIF lidar for the remote detection of metal oxide fluorescence was also demonstrated using the frequency doubled output of the laser transmitter.

When static electric fields (F less-than-or-equal-to 90 kV/cm) were applied to the H- photodetachment interaction region, new structure and lowered thresholds for production of neutral hydrogen were observed. Relative partial cross sections were measured by detection of excited states of the fragment neutral hydrogen atom H(N = 4, 5, or 6) resulting from laser interaction with relativistic H- ions. Downward shifts in the onset of excited hydrogen production are observed to increase with field strength, and agree with a recent hyperspherical coordinate interpretation of Zhou and Lin [Phys. Rev. Lett. 69, 3294 (1992)]. Field-induced window-type resonance structure is observed both below and above the zero-field threshold (ZFT) energy. Quenching of high-lying autoionizing states was also monitored, providing evidence of field-induced tunneling by resonances lying just below the associated ZFT.

Two techniques are described by which the flux of water vapor can be derived from concentration measurements made by a Raman-Lidar. Monin-Obukhov similarity theory and dissipation techniques are used as the basis for these methods. The resulting fluxes are compared to fluxes from standard point instruments. The techniques described are appropriate for measuring the flux of any scalar quantity using Lidar measurements in the inner region of the boundary layer.

Over the last two decades, Mexico City, like many large industrial and populous urban areas, has developed a serious air pollution problem, especially during the winter months when there are frequent temperature inversions and weak winds. The deteriorating air quality is the result of several factors. The basin within which Mexico City lies in Mexico's center of political, administrative and economic activity, generating 34 percent of the gross domestic product and 42 percent of the industrial revenue, and supporting a population which is rapidly approaching the 20 million mark. The basin is surrounded by mountains on three sides which end up preventing rapid dispersal of pollutants. Emissions from the transportation fleet (more than 3 million vehicles) are one of the primary pollution sources, and most are uncontrolled. Catalytic converters are just now working their way into the fleet. The Mexico City Air Quality Research Initiative in an international collaboration project between the Los Alamos National Laboratory and the Mexican Petroleum Institute are dedicated to the investigation of the air quality problem in Mexico City. The main objective of the project is to identify and assess the cost and benefits of major options being proposed to improve the air quality. The project is organized into three main activity areas: (1) modeling and simulation; (2) characterization and measurements; and (3) strategic evaluation.