Application of Airborne Lidar in Particulate Air Quality Problem Delineation,Monitoring Network Design and Control Strategy Development

Airborne lidar (light detection and ranging) data were collected during two field programs in 1989 in the border metropolitan area comprising El Paso (U.S.) and Ciudad Juarez (Mexico). These data were utilized to provide estimates of suspended particulate distributions in the presence of historical data with limited spatial and temporal density in the U.S. and almost no historical data in Mexico. The resulting information was used to help ascertain the magnitude and spatial extent of the particulate air quality problem and to help determine the number and disposition of recommended permanent particulate monitors in the area. The results support the hypothesis that, given a few representative measurements for calibration, airborne lidar might be used in specific situations to develop detailed concentration patterns and to provide useful estimates of pollutant flux, when combined with appropriate measurements of wind velocity profiles. Such information, in turn, should be useful for the development of control strategies for potential alleviation of particulate air quality problems.     

Remote monitoring of air pollutant emissions from point sources by a mobile lidar/sodar system

This paper describes remote monitoring of air pollutant emissions by a mobile lidar (light detection and ranging)/ sodar (sound detection and ranging) system. First, measurements are carried out in the flue gas plume of a public power plant. The investigations focus mainly on quantifying SO2 emissions, but the uncertainties of such measurements are also emphasized. Furthermore, an example providing valuable data sets for the development and validation of plume dispersion models is outlined with measurements of the dilution of SO2 along the plume axis. Series of repeated determinations of SO2 emissions show a large variation in the obtained flux values, with moderate margins of error. Incomplete recording of the plume within the individual lidar scans, induced by strong looping movements of the flue gas plume, predominantly causes the variations of flux values. Therefore, the highest flux values determined are considered to be the most exact. This is verified by a comparison of measured fluxes with in situ measurements made by the plant operators. The results further indicate that lidar measurements illustrate the location and dimension of aerosol plumes better than the location and dimension of the plumes of gaseous compounds. The wind direction affecting the plume at any moment can be determined faster by lidar than by sodar because the latter requires much longer time intervals of signal averaging. Measurements show higher concentrations of SO2 compared with results from a Gaussian plume model for periods of less than 5 min after dispersion. The findings emphasize the suitability of remote sensing for detecting emissions and for investigating the propagation and dilution of air pollutant plumes.     

Modeling effects of traffic and landscape characteristics on ambient nitrogen dioxide levels in Connecticut

An integrated exposure model was developed that estimates nitrogen dioxide (NO(2)) concentration at residences using geographic information systems (GIS) and variables derived within residential buffers representing traffic volume and landscape characteristics including land use, population density and elevation. Multiple measurements of NO(2) taken outside of 985 residences in Connecticut were used to develop the model. A second set of 120 outdoor NO(2) measurements as well as cross-validation were used to validate the model. The model suggests that approximately 67% of the variation in NO(2) levels can be explained by: traffic and land use primarily within 2 km of a residence; population density; elevation; and time of year. Potential benefits of this model for health effects research include improved spatial estimations of traffic-related pollutant exposure and reduced need for extensive pollutant measurements. The model, which could be calibrated and applied in areas other than Connecticut, has importance as a tool for exposure estimation in epidemiological studies of traffic-related air pollution.     

The Estimation of Personal Exposures to Air Pollutants for a Community-Based Study of Health Effects in Asthmatics—Design and Results of Air Monitoring

In order to provide reliable pollutant and meteorological exposure estimates for an epidemiological study of asthmatics residing in two Houston neighborhoods, a dedicated three-tier air monitoring system was established. This consisted of fixed site ambient air monitoring at the center of each study area, a mobile van performing simultaneous indoor and outdoor measurements at selected residences of study participants, and a limited amount of direct personal monitoring for half of the participants. Monitored pollutants Included all criteria pollutant gases, as well as aeroallergens, aldehydes, TSP, and IP. Laboratory analyses provided concentrations of sulfate, nitrate, and trace elements. Continuous measurements of several meteorological parameters also were obtained. Intensive quality assurance and data validation efforts resulted in a high percentage of valid data for most pollutants. Ozone was the only measured pollutant that exceeded the NAAQS during the six-month (May to October) study period. The monitoring scheme allowed important pollutant concentration differences to be detected between day and night, between Indoors and outdoors, and among various indoor environments. The use of these monitoring data in combination with personal activity and household characteristics data to generate estimates of personal exposures for the epidemiological analysis will be described in a subsequent paper.     

Lidar-assisted measurement of PM10 emissions from agricultural tilling in California's San Joaquin Valley – Part I: lidar

Vertical profiling with point samplers is an accepted method for quantifying the fluxes of PM₁₀ from non-point fugitive dust sources, but is limited by uncertainty in estimates of the actual height of the dust plume, especially for plumes that exceed the highest sampling height. Agricultural land preparation operations in the San Joaquin Valley were monitored using upwind–downwind vertical PM₁₀ profiles and data collected during the first successful experiment to include light detection and ranging (lidar), in 1998, were analyzed to provide modeling criteria for the 1996 and 1997 data. A series of six comprehensive PM₁₀ tests with concurrent lidar data was examined to: (a) develop a framework for analyzing upwind–downwind point PM₁₀ concentration profiles of land preparation operations (disking, listing, root cutting, and ripping) and (b) identify conditions under which the field sampling strategies affect the reproducibility of PM₁₀ concentration measurements. Lidar data were used to verify that the plume heights and shapes extrapolated from the point sampler vertical profiles adequately described the plumes. The shortcomings of the vertical profiling technique and lidar methods are discussed in the light of developing efficient robust methods for accurate PM₁₀ emissions quantification from complex non-point sources.     

Near-field dispersion modeling for regulatory applications

This paper evaluates the application of dispersion models to estimate near-field pollutant concentrations in two case studies. The Industrial Source Complex Short-Term Model (ISCST3) was evaluated with hexavalent chromium measurements collected within 100 m of two facilities in Barrio Logan, San Diego, CA. ISCST3 provided reasonable estimates for higher pollutant concentrations but underestimated lower concentrations. To understand the observed distribution of concentrations in Barrio Logan, a recently conducted tracer experiment was analyzed. The tracer, sulfur hexafluoride, was released at ambient temperature from an urban facility at the University of California at Riverside, and concentrations were measured within 20 m of the source. Modeling results indicated that Industrial Source Complex-Plume Rise Model Enhancement and American Meteorological Society/U.S. Environmental Protection Agency Regulatory Model-Plume Rise Model Enhancement overestimated high concentrations and underestimated low concentrations. A diagnostic study with a simple Gaussian dispersion model that incorporated site-specific meteorology was used to evaluate model results. This study found that incorporating lateral meandering for nonbuoyant urban plumes in Gaussian dispersion models could improve concentration estimates even when downwash is not considered. Incorporating a meandering component in ISCST3 resulted in improvements in estimating hexavalent chromium concentrations in Barrio Logan. Credible near-source concentration estimates depend on accurate characterization of emissions, onsite micrometeorology, and a method to account for lateral meandering in the near field.     

Lidar and satellite retrieval of dust aerosols over the Azores during SOFIA/ASTEX

The synergy between active (airborne lidar) and passive (Meteosat) sensors is achieved with the help of a numerical transport model (TM2z) to derive optical properties of Saharan dust during a long range transport over the Azores. Measurements were taken in June 1992 during the surface of the ocean, fluxes and interaction with the atmosphere campaign, which took place during the Atlantic stratocumulus transition experiment. The dust source is identified to be in north Morocco from a TM2z back-trajectory analysis. Lidar observations over the Azores show that the dust is maintained in multiple thin layers (few hundred meters) up to 5 km altitude after a 4-day transport. Horizontal gradients are less marked, with a typical scale of variation of about 5 km. Lidar inversions yield dust optical thicknesses from 0.1 to 0.16 mainly due to two layers centered at 1.3 and 3.7 km. Since the weather was extremely cloudy over this region, the dust plume was not observable on the coincident Meteosat image. We thus processed the image taken two days earlier that clearly shows a dust plume between Azores and Spain. The Meteosat inversion was constrained by using the airborne lidar measurements in the marine boundary layer. The retrieved dust optical thicknesses are in good agreement with that retrieved from the lidar. Coherence of both lidar and radiometry measurements suggests that such a combined analysis is promising for retrieving the optical thickness of elevated dust layers as well as their spatial extent outside the source region even under cloudy conditions.     

Lidar Applications in Air Pollution Research and Control

The fundamental capabilities and limitations of the lidar (laser radar) in observing particulate concentrations in the atmosphere are discussed. The advantages of the lidar technique stem from its ability to obtain measurements remotely and at a high density in space and time. The quantitative application of the technique is limited by the accuracies with which: (1) the separate effects upon the return signal of back-scatter and attenuation may be identified; and (2) the optical parameters may be related to the characteristics of the aerosol. The main areas of utility for lidar in air pollution research and control are: (1) to observe the structure and height of mixing layers; (2) to measure the transport and diffusion of plumes or clouds of particulates; and (3) to remotely determine smoke-plume opacity. These applications are briefly reviewed and exemplified.     

A statistical assessment of saturation and mobile sampling strategies to estimate long-term average concentrations across urban areas

The objectives of this study were: (1) to quantify the errors associated with saturation air quality monitoring in estimating the long-term (i.e., annual and 5 yr) mean at a given site from four 2-week measurements, once per season; and (2) to develop a sampling strategy to guide the deployment of mobile air quality facilities for characterizing intraurban gradients of air pollutants, that is, to determine how often a given location should be visited to obtain relatively accurate estimates of the mean air pollutant concentrations. Computer simulations were conducted by randomly sampling ambient monitoring data collected in six Canadian cities at a variety of settings (e.g., population-based sites, near-roadway sites). The 5-yr (1998-2002) dataset consisted of hourly measurements of nitric oxide (NO), nitrogen dioxide (NO2), oxides of nitrogen (NOx), sulfur dioxide (SO2), coarse particulate matter (PM10), fine particulate matter (PM2.5), and CO. The strategy of randomly selecting one 2-week measurement per season to determine the annual or long-term average concentration yields estimates within 30% of the true value 95% of the time for NO2, PM10 and NOx. Larger errors, up to 50%, are expected for NO, SO2, PM2.5, and CO. Combining concentrations from 85 random 1-hr visits per season provides annual and 5-yr average estimates within 30% of the true value with good confidence. Overall, the magnitude of error in the estimates was strongly correlated with the variability of the pollutant. A better estimation can be expected for pollutants known to be less temporally variable and/or over geographic areas where concentrations are less variable. By using multiple sites located in different settings, the relationships determined for estimation error versus number of measurement periods used to determine long-term average are expected to realistically portray the true distribution. Thus, the results should be a good indication of the potential errors one could expect in a variety of different cities, particularly in more northern latitudes.     

Near-Field Dispersion Modeling for Regulatory Applications

Abstract

This paper evaluates the application of dispersion models to estimate near-field pollutant concentrations in two case studies. The Industrial Source Complex Short-Term Model (ISCST3) was evaluated with hexavalent chromium measurements collected within 100 m of two facilities in Barrio Logan, San Diego, CA. ISCST3 provided reasonable estimates for higher pollutant concentrations but underestimated lower concentrations. To understand the observed distribution of concentrations in Barrio Logan, a recently conducted tracer experiment was analyzed. The tracer, sulfur hexafluoride, was released at ambient temperature from an urban facility at the University of California at Riverside, and concentrations were measured within 20 m of the source. Modeling results indicated that Industrial Source Complex–Plume Rise Model Enhancement and American Meteorological Society/U.S. Environmental Protection Agency Regulatory Model–Plume Rise Model Enhancement overestimated high concentrations and underestimated low concentrations. A diagnostic study with a simple Gaussian dispersion model that incorporated site-specific meteorology was used to evaluate model results. This study found that incorporating lateral meandering for nonbuoyant urban plumes in Gaussian dispersion models could improve concentration estimates even when downwash is not considered. Incorporating a meandering component in ISCST3 resulted in improvements in estimating hexavalent chromium concentrations in Barrio Logan. Credible near-source concentration estimates depend on accurate characterization of emissions, onsite micrometeorology, and a method to account for lateral meandering in the near field.     

Note on a Method to Estimate Missing Air Pollution Data

An iterative regression procedure is presented to estimate missing air pollution measurements when the data are measured at two or more sampling stations in the same vicinity. The procedure utilizes the measurements taken at other stations, on neighboring days, and of other pollutants.

The procedure is applied to a set of Philadelphia pollution data with from five to seventeen per cent of the observations missing. The method is tested by comparing the known observed pollutant values, with their estimates given by the procedure. Correlations between the observations and their estimates are uniformly high, ranging from 0.87 to 0.91. These correlations compare favorably with those estimates given by a simple linear interpolation. The magnitude of the correlations suggests that estimates given by this iterative regression procedure may be used where missing observations pccur without fear of undesirable effects on subsequent work. Therefore, this procedure may be a valuable tool in handling the problem of missing observations in air pollution data.     

Numerical Evaluation of the Effect of Traffic Pollution on Indoor Air Quality of a Naturally Ventilated Building

Abstract

A computational fluid dynamics technique was used to evaluate the effect of traffic pollution on indoor air quality of a naturally ventilated building for various ventilation control strategies. The transport of street-level nonreactive pollutants emitted from motor vehicles through the indoor environment was simulated using the large eddy simulation (LES) of the turbulent flows and the pollutant transport equations. The numerical model developed herein was verified by available wind-tunnel measurements. Good agreement with the measured velocity and concentration data was found. Twelve sets of numerical scenario simulations for various roof- and side-vent openness and outdoor wind speeds were carried out. The effects of the air change rate, the indoor airflow pattern, and the external pollutant dispersion on indoor air quality were investigated. The control strategies of ventilation rates and paths for reducing incoming vehicle pollutants and maintaining a desirable air change rate are proposed to reduce the impact of outdoor traffic pollution during traffic rush hours. It was concluded that the windward side vent is a significant factor contributing to air change rate and indoor air quality. Air intakes on the leeward side of the building can effectively reduce the peak and average indoor concentration of traffic pollutants, but the corresponding air change rate is relatively low. Using the leeward cross-flow ventilation with the windward roof vent can effectively lower incoming vehicle pollutants and maintain a desirable air change rate during traffic rush hours.     

Numerical evaluation of the effect of traffic pollution on indoor air quality of a naturally ventilated building

A computational fluid dynamics technique was used to evaluate the effect of traffic pollution on indoor air quality of a naturally ventilated building for various ventilation control strategies. The transport of street-level nonreactive pollutants emitted from motor vehicles through the indoor environment was simulated using the large eddy simulation (LES) of the turbulent flows and the pollutant transport equations. The numerical model developed herein was verified by available wind-tunnel measurements. Good agreement with the measured velocity and concentration data was found. Twelve sets of numerical scenario simulations for various roof- and side-vent openness and outdoor wind speeds were carried out. The effects of the air change rate, the indoor airflow pattern, and the external pollutant dispersion on indoor air quality were investigated. The control strategies of ventilation rates and paths for reducing incoming vehicle pollutants and maintaining a desirable air change rate are proposed to reduce the impact of outdoor traffic pollution during traffic rush hours. It was concluded that the windward side vent is a significant factor contributing to air change rate and indoor air quality. Air intakes on the leeward side of the building can effectively reduce the peak and average indoor concentration of traffic pollutants, but the corresponding air change rate is relatively low. Using the leeward cross-flow ventilation with the windward roof vent can effectively lower incoming vehicle pollutants and maintain a desirable air change rate during traffic rush hours.     

Numerical investigation of pollutant transport characteristics inside deep urban street canyons

A validated LES model was employed to simulate the street canyons of aspect ratio (AR) 3, 5, and 10. Three, five, and eight vertically aligned primary recirculations were found for the three cases, respectively, which showed decreasing strength with decreasing height. The ground-level wind speeds were found to be very small, making it extremely difficult for the ground-level pollutants to disperse. Local maxima of turbulence intensities were found at the interfaces between the primary recirculations and the shear layer. The pollutant trajectory followed the primary recirculations. High pollutant concentration and variance were found near the buildings where wind flowed upward. Large gradients of pollutant concentration and variance were also observed at the interfaces between the primary recirculations and the shear layer. Detailed analyses of concentration budget showed that the advection terms were responsible for pollutant redistribution within primary recirculations, while the turbulent transport terms were responsible for pollutant penetration between primary recirculations as well as pollutant removal from the street canyon.     

The effects of roadside structures on the transport and dispersion of ultrafine particles from highways

Understanding local-scale transport and dispersion of pollutants emitted from traffic sources is important for urban planning and air quality assessments. Predicting pollutant concentration patterns in complex environments depends on accurate representations of local features (e.g., noise barriers, trees, buildings) affecting near-field air flows. This study examined the effects of roadside barriers on the flow patterns and dispersion of pollutants from a high-traffic highway in Raleigh, North Carolina, USA. The effects of the structures were analyzed using the Quick Urban & Industrial Complex (QUIC) model, an empirically based diagnostic tool which simulates fine-scale wind field and dispersion patterns around obstacles. Model simulations were compared with the spatial distributions of ultrafine particles (UFP) from vehicular emissions measured using a passenger van equipped with a Differential Mobility Analyzer/Condensation Particle Counter. The field site allowed for an evaluation of pollutant concentrations in open terrain, with a noise barrier present near the road, and with a noise barrier and vegetation present near the road.Results indicated that air pollutant concentrations near the road were generally higher in open terrain situations with no barriers present; however, concentrations for this case decreased faster with distance than when roadside barriers were present. The presence of a noise barrier and vegetation resulted in the lowest downwind pollutant concentrations, indicating that the plume under this condition was relatively uniform and vertically well-mixed. Comparison of the QUIC model with the mobile UFP measurements indicated that QUIC reasonably represented pollutant transport and dispersion for each of the study configurations.     

The influence of atmospheric stability on pollutant transport by slope winds

The results of a field investigation into pollutant transport by slope flows are presented. During the study, ozone levels were monitored for eight days at three locations along a mountain slope extending above the Los Angeles Air Basin. In addition, tracer tests were conducted during two afternoons during the study period. The tests were conducted on days with widely varying atmospheric stability and indicate the effect of a strongly stable capping layer on pollutant transport by upslope flows. The experimental results indicated at least two mechanisms for the return of polluted air to the valley below. Under weakly stable conditions, the often noted return of pollutants via night-time downslope winds was observed. In addition, under more strongly stable conditions, a daytime recirculation mechanism consistent with that described by Vergeiner (1982) was observed. The tests also indicated that the slope flow layer depth and speed decreased with increasing atmospheric stability. In addition, the rate of transport and dilution of pollutants in a slope flow appears to be influenced by the entrainment and growth of the boundary layer, limiting the applicability of models that neglect these processes.     

Open-path tunable diode laser absorption spectroscopy for acquisition of fugitive emission flux data

Air pollutant emission from unconfined sources is an increasingly important environmental issue. The U.S. Environmental Protection Agency (EPA) has developed a ground-based optical remote-sensing method that enables direct measurement of fugitive emission flux from large area sources. Open-path Fourier transform infrared spectroscopy (OP-FTIR) has been the primary technique for acquisition of pollutant concentration data used in this emission measurement method. For a number of environmentally important compounds, such as ammonia and methane, open-path tunable diode laser absorption spectroscopy (OP-TDLAS) is shown to be a viable alternative to Fourier transform spectroscopy for pollutant concentration measurements. Near-IR diode laser spectroscopy systems offer significant operational and cost advantages over Fourier transform instruments enabling more efficient implementation of the measurement strategy. This article reviews the EPA's fugitive emission measurement method and describes its multipath tunable diode laser instrument. Validation testing of the system is discussed. OP-TDLAS versus OP-FTIR correlation testing results for ammonia (R2 = 0.980) and methane (R2 = 0.991) are reported. Two example applications of tunable diode laser-based fugitive emission measurements are presented.     

A Statistical Assessment of Saturation and Mobile Sampling Strategies to Estimate Long-Term Average Concentrations across Urban Areast

Abstract

The objectives of this study were: (1) to quantify the errors associated with saturation air quality monitoring in estimating the long-term (i.e., annual and 5 yr) mean at a given site from four 2-week measurements, once per season; and (2) to develop a sampling strategy to guide the deployment of mobile air quality facilities for characterizing intraurban gradients of air pollutants, that is, to determine how often a given location should be visited to obtain relatively accurate estimates of the mean air pollutant concentrations. Computer simulations were conducted by randomly sampling ambient monitoring data collected in six Canadian cities at a variety of settings (e.g., population-based sites, near-roadway sites). The 5-yr (1998–2002) dataset consisted of hourly measurements of nitric oxide (NO), nitrogen dioxide (NO₂), oxides of nitrogen (NO_x), sulfur dioxide (SO₂), coarse particulate matter (PM₁₀), fine particulate matter (PM_2.5)_, and CO. The strategy of randomly selecting one 2-week measurement per season to determine the annual or long-term average concentration yields estimates within 30% of the true value 95% of the time for NO₂, PM₁₀ and NO_x. Larger errors, up to 50%, are expected for NO, SO₂, PM_2.5, and CO. Combining concentrations from 85 random 1-hr visits per season provides annual and 5-yr average estimates within 30% of the true value with good confidence. Overall, the magnitude of error in the estimates was strongly correlated with the variability of the pollutant. A better estimation can be expected for pollutants known to be less temporally variable and/or over geographic areas where concentrations are less variable. By using multiple sites located in different settings, the relationships determined for estimation error versus number of measurement periods used to determine long-term average are expected to realistically portray the true distribution. Thus, the results should be a good indication of the potential errors one could expect in a variety of different cities, particularly in more northern latitudes.     

Application of a Three-Layer Photochemical Box Model in an Athens Street Canyon

ABSTRACT

The aim of this paper is to show that a photochemical box model could describe the air pollution diurnal profiles within a typical street canyon in the city of Athens. As sophisticated three-dimensional dispersion models are computationally expensive and they cannot serve to simulate pollution levels in the scale of an urban street canyon, a suitably modified three-layer photochemical box model was applied. A street canyon of Athens with heavy traffic was chosen to apply the aforementioned model. The model was used to calculate pollutant concentrations during two days with meteorological conditions favoring pollutant accumulation. Road traffic emissions were calculated based on existing traffic load measurements. Meteorological data, as well as various pollutant concentrations, in order to compare with the model results, were provided by available measurements. The calculated concentrations were found to be in good agreement with measured concentration levels and show that, when traffic load and traffic composition data are available, this model can be used to predict pollution episodes. It is noteworthy that high concentrations persisted, even after additional traffic restriction measures were taken on the second day because of the high pollution levels.