In 2006, we began a three-year project funded by the NASA Integrated Decisions Support program to develop a three-dimensional air quality system (3D-AQS). The focus of 3D-AQS is on the integration of aerosol-related NASA Earth Science Data into key air quality decision support systems used for air quality management, forecasting, and public health tracking. These will include the U.S. Environmental Protection Agency (EPA)'s Air Quality System/AirQuest and AIRNow, Infusing satellite Data into Environmental Applications (IDEA) product, U.S. Air Quality weblog (Smog Blog) and the Regional East Atmospheric Lidar Mesonet (REALM). The project will result in greater accessibility of satellite and lidar datasets that, when used in conjunction with the ground-based particulate matter monitors, will enable monitoring across horizontal and vertical dimensions. Monitoring in multiple dimensions will enhance the air quality community's ability to monitor and forecast the geospatial extent and transboundary transport of air pollutants, particularly fine particulate matter. This paper describes the concept of this multisensor system and gives current examples of the types of products that will result from it.

MODIS aerosol optical depth (AOD) product provides a quantitative measure of columnar aerosol abundance over both land and ocean. The satellite-derived AOD has shown to correlate with surfaced-measured PM2.5 (particulate matter particulate matter with aerodynamic diameter < 2.5 μm) concentration. The timely MODIS AOD product from direct broadcasting facilitates near real-time (1-2 hours after satellite overpass) monitoring of PM distribution and movement over the continental US the Infusing Satellite into Environmental Application (IDEA) (http://idea.ssec.wisc.edu). Many questions, however, are raised in regard to correlation between AOD and PM2.5. In this paper, we characterize the correlation between MODIS AOD and surface-measured PM2.5 in different conditions and introduce mean absolute error as a second measure to help assess satellite derived AOD for air quality application.

High resolution (5x5 km2 horizontal resolution) retrievals of aerosol optical depth (AOD) from the MODerate Resolution Imaging Spectroradiometer (MODIS) instruments aboard NASA's Aqua and Terra satellite platforms have been examined. These data products have been compared to coincident, hourly measurements of ground-based PM-2.5 routinely obtained by the San Joaquin Valley Air Pollution Control District (SJV APCD) and California Air Resources Board (CARB) and to airborne light detection and ranging (lidar) aerosol scattering measurements obtained by NASA in July 2003 in San Joaquin Valley (SJV). Comparison of MODIS AOD to ground based PM-2.5 measurement shows significant improvement for the higher resolution MODIS AOD. Lidar aerosol scattering measurements correspond well to MODIS AOD during a variety of atmospheric conditions, and throughout the SJV. Future lidar measurements are proposed to establish a high resolution vertical link between satellite and ground-based measurements during the winter. With the data from these two episodes, we plan to characterize the horizontal, vertical, and temporal distribution of PM-2.5 in SJV and evaluate the need for future intensive ground-based measurement and modeling studies in SJV.

Knowledge of the concentration and distribution of atmospheric aerosols using both airborne lidar and satellite instruments is a field of active research. An aircraft based aerosol lidar has been used to study the distribution of atmospheric aerosols in the California Central Valley and eastern US coast. Concurrently, satellite aerosol retrievals, from the MODIS (Moderate Resolution Imaging Spectroradiometer) instrument aboard the Terra and Aqua satellites, were take over the Central Valley. The MODIS Level 2 aerosol data product provides retrieved ambient aerosol optical properties (e.g., optical depth (AOD) and size distribution) globally over ocean and land at a spatial resolution of 10 km. The Central Valley topography was overlaid with MODIS AOD (5x5 km² resolution) and the aerosol scattering vertical profiles from a lidar flight. Backward air parcel trajectories for the lidar data show that air from the Pacific and northern part of the Central Valley converge confining the aerosols to the lower valley region and below the mixed layer. Below an altitude of 1 km, the lidar aerosol and MODIS AOD exhibit good agreement. Both data sets indicate a high presence of aerosols near Bakersfield and the Tehachapi Mountains. These and other results to be presented indicate that the majority of the aerosols are below the mixed layer such that the MODIS AOD should correspond well with surface measurements. Lidar measurements will help interpret satellite AOD retrievals so that one day they can be used on a routine basis for prediction of boundary layer aerosol pollution events.

We are currently developing grating mapping spectrometers (GMS) with very high spectral resolution, very low noise, and very wide field of view. These also would be very compact facilitating deployment in either a leo or geo application. The measurement set could be very comprehensive, addressing air quality, climate change and meteorology, or subsets of these. For this presentation we'll focus on potential applications of these GMS for air quality measurements of the species ozone O₃, formaldehyde HCHO and carbon monoxide CO. We will discuss these applications at various levels of complexity and the commensurate value for application to understanding and forecasting air quality. At lowest complexity we would utilize a single GMS operating in the solar reflective infrared region for column measurements of O₃ and HCHO. A more complex approach would utilize a second and/or third GMS for thermal emissive O₃ measurements that provide improved vertical resolution, and for CO profile. Our major emphasis is the lowest tropospheric air layer 0-2 km. For realistic models of these GMS we'll present retrieval performance as predicted by a linear error analysis. In a polar leo orbit the most complex approach could provide twice daily global mapping with some footprints as small as 1.6 km at nadir. We'll present results from an in house lab demonstration GMS. This demo is a predecessor to an advanced design that we are currently developing with support of the NASA ESTO Instrument Incubator Program (IIP).

Based on AERONET measurements, aerosol absorption properties over 23 AERONET sites are analyzed. The properties include aerosol single scatter albedo (SSA), correlation characteristic of SSA with aerosol optical thickness (AOT), absorption optical thickness and absorption wavelength index. The index is introduced to indicate wavelength-dependence of absorption optical thickness. Among the 23 sites, 8 sites locate over Asia, 3 over Africa, and 12 in USA. Some results are summarized as follows: 1)Total mean absorption optical thickness for the 440nm-wavelength changes between 0.0061 (Howland, USA) and 0.0939 (Beijing, China), and it ranges from 0.0019 (Howland) to 0.0457 (Yulin, China) for the 1020nm wavelength. There are three peaks of absorption optical thicknesses, locating over China, India and north-Africa, respectively. 2)Over all sites except for two sites (Goa-india in India and Dahkla in Africa), correlative coefficients between SSA and AOT are positive, changing from 0.048 to 0.692. This characteristic implies that relative contribution of stronger-absorbing aerosol component to total AOT decreases when the AOT increases. In other hand, correlative coefficients between Angtr&diaero;m index and AOT are usually negative, showing trendily increasing contribution to total AOT from larger particles when the AOT increases. 3)Apart from two sites of Dahkla and Ilorin in Africa, absorption wavelength index is 0.09-1.29 less than Angtr&diaero;m index, the smallness being larger for some sites in USA. Usually, the larger Angtr&diaero;m index is, the stronger the smallness.

We present an intercomparison of retrieved dust parameters obtained from analyzing AIRS and MODIS satellite data. Recent papers have highlighted using AIRS data to retrieve dust top (layer) height, loading and particle size. Different methods have been used, such as assuming a fixed particle size and dust top height before fitting radiance data from selected AIRS channels, or using lookup tables to retrieve dust loading, height and particle size. In this paper we use the combination of dust retrievals from MODIS visible and AIRS thermal infrared channels to provide information on dust top height by forcing the error term (or intercept of the linear regression of dust optical depths retrieved from MODIS and AIRS) to zero. When available, GLAS measurements will be used to validate dust top height. Collocated ship based M-AERI observations, obtained in March 2004 during the AEROSE campaign will also be analyzed to verify this approach.

For the assessment of climatic impact of aerosols, the knowledge of both the temporal and spatial distributions of aerosol is essential. Laser radar, more popularly known as Lidar, has becoming one of the most powerful techniques for active detection of aerosols in the atmosphere. Lidar can provide vertically resolved of extinction and backscatter coefficients, and thereby the height of the planetary boundary layer or the nighttime residual layer. As the long-term changes in the structure and dynamics of the lower and middle troposphere is now becoming a priority, a pulsed Nd:YAG Lidar system is applied for measuring the vertical distribution of aerosol properties in the metropolitan Taipei. Two years (2004-2005) of aerosol optical depth (AOD) measured by Lidar, Cimel Sunphotometer and MODerate resolution Imaging Spectroradiometer (MODIS) were compared. The AOD shows strong seasonal variation with maximum values (AOD_Lidar > 1, AOD_Cimel > 1 and AOD_MODIS > 0.39) occurred in April. AOD_MODIS shows significant underestimation. AOD_Lidar has good correlation with AOD_Cimel, but the Lidar measurement is biased toward lower values as presented by the 0.725 slope in the linear regression. This bias is mostly caused by the Lidar blind distance at the lowest part of the atmosphere. The R-squared of AOD_Cimel and surface PM_2.5 concentration is about 0.44. This reflects the fact that the atmospheric boundary layer is often not well-mixed, so aerosols there cannot represent the total AOD value. Particles in the free troposphere also need to be concerned. Further comparison of our Lidar data with the CALIPSO measurements is intended.

East Asian dust sources are mostly located in remote areas where the geographical characteristics are not well understood. This imposes difficulties in the modeling of atmospheric mineral dust. Satellite remote sensing is a viable way of deriving temporal dynamics and spatial distributions of dust emission over large areas. Although the present-day satellites provide only column-integrated aerosol properties, it is possible to retrieve from them the dust emission strength, which is also a column denomination. In this study, dust emission over East Asia is estimated using aerosol optical depth retrieved from MODIS sensors with the aide of a regional meteorological and dust model. Differences of daily AOD and meteorological data are applied to the mass conservation equation to estimate net emission of dust over specified desert areas. The derived emission is then compared with the old data set used in the model for dust simulation in East Asia. The area of study covers northern and western China as well as Mongolia. Asian dust events identified during the period January 2003 to December 2004 are selected for emission retrieval and for modeling comparisons. The results show that the patterns of emission coefficient retrieved from Aqua-MODIS AOD data are consistent with spatial characteristics of land cover over Northern China and Mongolia.

The data assimilation of 2000-2004 carbon monoxide (CO) retrievals by the MOPITT (Measurements Of Pollution In The Troposphere) instrument onboard the NASA Terra satellite provide an opportunity for the first time to study the transport and sources of pollution including their year-to-year variations. Based on the different representations of assimilated CO in the chemistry transport model (CTM) space and at the MOPITT retrieval grid this study advocates for direct mapping of CO-sensitive radiances or characterized CO retrievals by the chemical data assimilation schemes. The comprehensive CO forecast provides a great deal of information on the vertical scales that cannot be constrained by the measured radiances. It also provides comprehensive a priori specifications for the inverse problems especially for the vertical levels and geographical regions where the radiometer begins to misplace its high sensitivity to the CO loading. Evaluation of the multi-year MOPITT retrievals and assimilated CO against in situ CO statistics showed how the data assimilation helps to diminish a priori effects in the reprocessed CO retrievals. Data analysis of the multi-year data reveal substantial inter-annual variations of CO loading in the free troposphere and call for the unbiased tracer assimilation schemes in the CTM with optimized CO surface emissions.

Dust is known to aggravate respiratory diseases. This is an issue in the desert southwestern United States, where windblown dust events are common. The Public Health Applications in Remote Sensing (PHAiRS) project aims to address this problem by using remote-sensing products to assist in public health decision support. As part of PHAiRS, a model for simulating desert dust cycles, the Dust Regional Atmospheric Modeling (DREAM) system is employed to forecast dust events in the southwestern US. Thus far, DREAM has been validated in the southwestern US only in the lower part of the atmosphere by comparison with measurement and analysis products from surface synoptic, surface Meteorological Aerodrome Report (METAR), and upper-air radiosonde. This study examines the validity of the DREAM algorithm dust load prediction in the desert southwestern United States by comparison with satellite-based MODIS level 2 and MODIS Deep Blue aerosol products, and ground-based observations from the AERONET network of sunphotometers. Results indicate that there are difficulties obtaining MODIS L2 aerosol optical thickness (AOT) data in the desert southwest due to low AOT algorithm performance over areas with high surface reflectances. MODIS Deep Blue aerosol products show improvement, but the temporal and vertical resolution of MODIS data limit its utility for DREAM evaluation. AERONET AOT data show low correlation to DREAM dust load predictions. The potential contribution of space- or ground-based lidar to the PHAiRS project is also examined.

Undiscovered gas leaks, known as fugitive emissions, in chemical plants and refinery operations can impact regional air quality and present a loss of product for industry. Surveying a facility for potential gas leaks can be a daunting task. Industrial leak detection and repair programs can be expensive to administer. An efficient, accurate and cost effective method for detecting and quantifying gas leaks would both save industries money by identifying production losses and improve regional air quality. Specialized thermal video systems have proven effective in rapidly locating gas leaks. These systems, however, do not have the spectral resolution for compound identification. Passive FTIR spectrometers can be used for gas compound identification, but using these systems for facility surveys is problematic due to their small field of view. A hybrid approach has been developed that utilizes the thermal video system to locate gas plumes using real time visualization of the leaks, coupled with the high spectral resolution FTIR spectrometer for compound identification and quantification. The prototype hybrid video/spectrometer system uses a sterling cooled thermal camera, operating in the MWIR (3-5 μm) with an additional notch filter set at around 3.4 μm, which allows for the visualization of gas compounds that absorb in this narrow spectral range, such as alkane hydrocarbons. This camera is positioned alongside of a portable, high speed passive FTIR spectrometer, which has a spectral range of 2 - 25 μm and operates at 4 cm^-1 resolution. This system uses a 10 cm telescope foreoptic with an onboard blackbody for calibration. The two units are optically aligned using a turning mirror on the spectrometer's telescope with the video camera's output.

Wavelength Modulation Spectroscopy (WMS) utilizes low frequency modulation of the probe, followed by synchronous detection at the modulation frequency or at one of the harmonics. WMS provides a particularly useful tool for resolving highly disparate overlapping lines, because the high-order derivative-like structure of higher harmonics results in an enhancement of features, not possible with conventional ("direct") absorption spectroscopy. An important question, not yet systematically addressed in the literature is, "Given that in any measurement seeking to resolve overlapping spectra there is always a minimum harmonic detection order, how does one determine this order?" To address this issue, a Rayleigh-like criterion is defined and used to determine when two lines are barely resolved. Shannon's information theoretical principles are then used to calculate the information obtained when overlapping spectra are barely resolved at a particular harmonic. The results obtained allow one to predict the minimal harmonic detection order that should be used to resolve overlapping lines.

In this paper, a particular equipment, one-channel optical-fiber-based methane gas real-time monitoring system, will be demonstrated. The system is designed especially for the mining complexes and residential area. A long-distance silica fiber link with a self-design optical gas sensor head have been employed in conjunction with a wavelength-tunable InGaAsP DFB laser diode at 1.64μm (around R(6) absorption peak of methane)1 to realize highly sensitive remote interrogation of CH4. By wavelength modulation with the DFB laser diode and a self-design processing circuit, sensitivities of less than 0.1 % (volume) have been achieved with the response time of less than 5 seconds.

Agricultural operations produce a variety of particulates and gases that influence ambient air quality. Lidar (LIght Detection And Ranging) technology provides a means to derive quantitative information of particulate spatial distribution and optical/physical properties over remote distances. A three-wavelength scanning lidar system built at the Space Dynamic Laboratory (SDL) is used to extract optical parameters of particulate matter and to convert these optical properties to physical parameters of particles. This particulate emission includes background aerosols, emissions from the agricultural feeding operations, and fugitive dust from the road. Aerosol optical parameters are retrieved using the widely accepted solution proposed by Klett. The inversion algorithm takes advantage of measurements taken simultaneously at three lidar wavelengths (355, 532, and 1064 nm) and allows us to estimate the particle size distribution. A bimodal lognormal particle size distribution is assumed and mode radius, width of the distribution, and total number density are estimated, minimizing the difference between calculated and measured extinction coefficients at the three lidar wavelengths. The results of these retrievals are then compared with simultaneous point measurements at the feeding operation site, taken with standard equipment including optical particle counters, portable PM₁₀ and PM_2.5 ambient air samplers, multistage impactors, and an aerosol mass spectrometer.

Three years (2003-2005) of aerosol optical depths (AOD) measured with CIMEL sunphotometer were compared to the surface concentrations of PM₁₀ and PM_2.5 in Northern (i.e. Taipei) and Southern (i.e. Tainan) Taiwan. The correlation between AOD and PM10 is higher in Taipei than in Tainan. Additional chemical compositions of PM₁₀ and PM_2.5 in these two sites, including ionic component, sea salt, OC/EC and crustal components, were also examined to find their relationship with the AOD. These analyses indicate that aerosols in Taipei are mainly composed of fine aerosols, whereas in Tainan more crustal material and OC exist in the coarse mode, which partially explain the higher correlation of PM₁₀ and AOD in Taipei. Closure calculations are carried out by combining data from lidar, sunphotometer, nephelometer, aethalomter, SMPS and APS size spectrometers, as well as chemical analyses of aerosols from PM₁₀ and PM_2.5 samplers and MOUDI impactor to investigate their consistency. The observed surface single scattering albedo was also compared to that retrieved by CIMEL sunphotometer, with additional discussion on the possible explanation to the discrepancies of the comparisons. Then, lidar measurement is applied to relate aerosols at the surface to those aloft.

Analyses and assessment on the influence of sanddust activities in the Hexi Corridor on the PM₁₀ concentration in Lanzhou city from 2001 to 2005 lead to the following conclusions of this paper. Lanzhou PM₁₀ concentrations (LPC) possess a double-peak annual distributive character with one peak in December and the other in next March both in the same winter half-year, however, the number of the sanddust activities in the corridor shows a single-peak annual variation with the peak in April (9.8 times/month). It is known from comparing the distributions of the both that the peak value of the number of Hexi sanddust activities (HSA) corresponds to the sub-peak of LPCs in spring, and it is held that the winter particular boundary layer condition is mainly responsible for the peak of LPC in December. The number of spring HSA is positively/significantly correlated with the LPC in the same time period, i.e. the frequent period of HSA corresponds to the sub-peak period of LPCs. The quantitative analyses of sanddust indices indicate that 15.7 %, 37.8%, and 49.5% of the annual, march, April LPCs are associated with the impact of HSAs, respectively, and 8%, 12.7%, 19.8% of the annual, march, April LPCs arise from the PM₁₀ particles transfer of HSAs. The HSAs lead to the multiplication of the LPC in successive impacting day, but the impacting extent is different in different time periods.

The University of Maryland Baltimore County (UMBC) airborne Visible-Near Infrared (VNIR) hyperspectral sensor is a grating spectrometer that collects data in the 380 to 985 nm spectral range with spectral resolution as high as 1.15 nm. This imager is a push-broom type sensor utilizing a two dimensional charge coupled device (CCD, 480×640) camera to collect the spectral information along a single line on the ground perpendicular to the aircraft flight line. The UMBC sensor can provide measurements for a variety of studies, including land development and land use, cultivated and natural vegetation and forestry, and water turbidity and coastal environments. Due to the sensor's wealth of spectral bands, high signal-to-noise, and narrow band widths, a number of atmospheric constituents can be also detected that can be incorporated into atmospheric correction models to benefit the retrievals of surface properties. We present a detailed description of the sensor as well as preliminary results of its calibration in this paper. Related on-going research and some potential applications of this sensor are summarized.

Aerosol particles are important components of the earth-atmosphere system, which change the radiance balance of earth-atmosphere system by the two processes of absorption and scattering, also distort the signal of earth observation satellite. For understanding the atmospheric attenuating effect of aerosols to satellite signals, a portable Mie Lidar system is developed, which is mainly used for measuring the optical properties of aerosol. At the same time, a radiative transfer model is introduced for implementing atmospheric correction of satellite signal. The aerosol data from lidar measurement are fed into radiative transfer code, instead of the model transcendental value. The primary results are shown in this paper. Furthermore, long-term atmospheric and aerosol data could be obtained by consecutive lidar observations. Also these data will be used for emending the existing atmospheric model and make it more compliant for China area application.