Observations and Model Simulations of Carbon Monoxide Emission Factors from a California Highway

ABSTRACT

A series of twelve intensively monitored 1-hr CO dispersion studies were conducted near Davis, CA, in winter 1996. The experimental equipment included twelve CO sampling ports at elevations up to 50 m, three sonic anemometers, a tethersonde station, aircraft measurements of wind and temperature profile aloft, and a variety of conventional meteorological equipment. The study was designed to explore the role of vehicular exhaust buoyancy during worst-case meteorological conditions, such as low winds oriented in near-parallel alignment with the road during a surface-based nocturnal inversion. From the study, field estimates of the CO emission factor (EF) from a California vehicle fleet were computed using two different methods. The analysis suggests that the CT-EMFAC/ EMFAC (EMission FACtor) models currently used to conduct federal conformity modeling significantly overpredict CO emissions for high-speed, free-flowing traffic on California highways.     

Carbon Monoxide Exposures to Los Angeles Area Commuters

Carbon monoxide exposures to commuters were simulated in a 5-day study in Los Angeles County. Exposures were determined by measuring CO in three vehicles as they traveled typical commuter routes. The data collected during this study include measurements of vehicle speed and CO measurements in the interior and exterior of the three vehicles during the morning and evening peak traffic periods. In addition, hourly averaged CO measurements were taken from eight south coastal Air Quality Management District fixed-site monitoring stations and six California Department of Transportation vans in the proximity of the commuter routes. These data were used to investigate the relationship of CO exposures to meteorological parameters, fixed-site monitors, and traffic conditions.

The average ratio of interior CO concentrations to exterior CO concentrations was 0.92. Concentrations inside and outside the vehicles remained about the same even when the vehicles were driven with vents closed and windows up. Smoking was not permitted in the vehicles during the study. The average ratio of the hour average CO concentrations in the vehicles to fixed-site measurements was 3.9. However, this ratio decreases with increasing ambient CO levels. Although CO levels in the vehicles frequently exceeded 40 ppm and sometimes exceeded 60 ppm, the hour average CO concentrations did not exceed 35 ppm. Slow moving congested traffic is associated with higher CO levels in the vehicles than a high volume of traffic moving at a steady speed.     

Meteorological conditions during the 1985 southern California nitrogen species methods comparison study

The purpose of this paper is to present a summary of meteorological conditions which occurred during the Nitrogen Species Methods Comparison Study, conducted in Claremont, California, between 11 and 18 September 1985. This information is intended as an introduction for subsequent articles which describe the results of the study.In southern California, September is noted for hot weather, stagnant air, and high concentrations of photochemical air pollution. During mid-September 1985, however, meteorological conditions were unusually favorable for the dispersion of pollutants, with an abnormally strong upper level trough over southern California at the beginning and again at the end of the intercomparison study period. These troughs were accompanied by much cooler and less stable air than would be desirable for a nitrogen species study. Only the four-day period of 12–15 September could be categorized as somewhat typical of September weather.     

Methodological trends in the design of recent microenvironmental studies of personal CO exposure

This paper describes the designs of three recent microenvironmental studies of personal exposure to carbon monoxide (CO) from motor vehicle exhaust. These studies were conducted sequentially, first in four California cities (Los Angeles, Mountain View, Palo Alto, and San Francisco), then in Honolulu, and, most recently, in metropolitan Washington, D.C. Though study purposes differed, each study faced common methodological issues related to personal exposure monitors (PEMs), quality assurance and data collection procedures, and the selection of microenvironments for study.Two major objectives of the California cities study were to determine the CO concentrations typically found in commercial settings and to define and classify microenvironments applicable to such settings: The Honolulu study measured merchant exposure to CO in shopping centers attached to semienclosed parking garages during business hours and commuter exposure to CO in vehicles (passenger cars and buses) on congested roadways during peak periods. The intent of the Washington study was to develop a model of commuter exposure to motor vehicle exhaust using CO as an indicator pollutant.Certain trends are discernible from reviewing the three studies. There are clearly trends in PEM development that have expanded instrument capabilities and automated data collection and storage. There are also trends towards more rigorous quality assurance procedures and more standardized protocols for collecting exposure data. Further, one can see a trend towards more elaborate indicators for identifying microenvironments for study. Finally, there is a trend towards using personal monitors in public policy review and evaluation.     

A reevaluation of carbon monoxide: past trends,future concentrations,and implications for conformity "hot-spot" policies

Control of CO is one of the great air-quality management success stories of the past 20 years. This paper evaluates whether past progress will continue into the future and whether changes in microscale CO concentrations are comparable to reductions observed at the regional scale. Neighborhood and microscale CO concentrations were evaluated at six northern and southern California monitoring sites. The study also included a review of CO emission, concentration, and exposure trends and on-road motor vehicle-based CO emission control programs for California and the United States. Consistent with California and national trends, CO concentrations declined at each of the six study locations from 1988 through 1998. Microscale concentrations declined at the same rate as did neighborhood-scale concentrations. Rollback analyses demonstrated that microscale concentrations will continue to decline through at least 2010-2020. Within a few years, microscale violations of the CO National Ambient Air Quality Standards (NAAQS) will be unlikely in California except under extraordinary circumstances.     

Improvements to lawn and garden equipment emissions estimates for Baltimore, Maryland

Lawn and garden equipment are a significant source of emissions of volatile organic compounds (VOCs) and other pollutants in suburban and urban areas. Emission estimates for this source category are typically prepared using default equipment populations and activity data contained in emissions models such as the U.S. Environmental Protection Agency's (EPA) NONROAD model or the California Air Resources Board's (CARB) OFFROAD model. Although such default data may represent national or state averages, these data are unlikely to reflect regional or local differences in equipment usage patterns because of variations in climate, lot sizes, and other variables. To assess potential errors in lawn and garden equipment emission estimates produced by the NONROAD model and to demonstrate methods that can be used by local planning agencies to improve those emission estimates, this study used bottom-up data collection techniques in the Baltimore metropolitan area to develop local equipment population, activity, and temporal data for lawn and garden equipment in the area. Results of this study show that emission estimates of VOCs, particulate matter (PM), carbon monoxide (CO), carbon dioxide (CO2), and nitrogen oxides (NO(x)) for the Baltimore area that are based on local data collected through surveys of residential and commercial lawn and garden equipment users are 24-56% lower than estimates produced using NONROAD default data, largely because of a difference in equipment populations for high-usage commercial applications. Survey-derived emission estimates of PM and VOCs are 24 and 26% lower than NONROAD default estimates, respectively, whereas survey-derived emission estimates for CO, CO2, and NO(x) are more than 40% lower than NONROAD default estimates. In addition, study results show that the temporal allocation factors applied to residential lawn and garden equipment in the NONROAD model underestimated weekend activity levels by 30% compared with survey-derived temporal profiles.     

The Effect of California’s Wintertime Oxygenated Fuels Program on Ambient Carbon Monoxide Concentrations

Abstract

The U.S. Environmental Protection Agency (EPA) mandated the use of oxygenated gasoline beginning in the winter of 1992 to reduce the unhealthful carbon monoxide concentrations in many urban areas. The California Air Resources Board (CARB), weighing the potential effects of the program on other pollutants, implemented a modified version of the federal wintertime oxygenated fuels program. In California, the number of violations of the carbon monoxide air quality standard during the three winters associated with the program was dramatically lower than during any winter prior to the program. Because meteorological conditions during the program were very favorable for dispersion of pollutants, any analysis of the impacts of the program must account for the influence of variable meteorological conditions. Analyses of ambient pollutant concentrations suggest that most of the air quality improvement was due to increased atmospheric dispersion. The analyses presented here account for the large influence of meteorology on ambient concentrations and indicate that California’s modified oxygenated fuels program was responsible for an approximately 5–10% reduction in mean ambient carbon monoxide concentrations, depending on the statistical approach used.     

A Statistical Analysis of the Los Angeles Ambient Carbon Monoxide Data 1955–1972

This paper presents a statistical analysis of some aspects of the ambient carbon monoxide data from 1955 to 1972 recorded at seven appropriately distributed locations in the Los Angeles Basin. Using modern time series methods and graphical techniques, an overall trend analysis of the movement of CO is given. Of special interest is a detailed study of the effect on the observed concentration level of CO due to (i) a change in the method of calibration of the measuring instrument In April 1968 and (ii) various control measures introduced since 1966. Also presented is an analysis of the seasonal variation of CO and the diurnal variation in weekdays and weekends. A major purpose of this study is to assess the influence of meteorological variables on the concentration level of the pollutant. Appropriate mathematical models are developed which relate CO to inversion base height, maximum mixing height, wind speed and direction, and traffic pattern. In addition, an analysis of the meteorological conditions during the days in which hourly concentration level of CO exceeded the Federal Air Quality Standard is given.     

Particulate air quality model predictions using prognostic vs. diagnostic meteorology in central California

Comparisons were made between three sets of meteorological fields used to support air quality predictions for the California Regional Particulate Air Quality Study (CRPAQS) winter episode from December 15, 2000 to January 6, 2001. The first set of fields was interpolated from observations using an objective analysis method. The second set of fields was generated using the WRF prognostic model without data assimilation. The third set of fields was generated using the WRF prognostic model with the four-dimensional data assimilation (FDDA) technique. The UCD/CIT air quality model was applied with each set of meteorological fields to predict the concentrations of airborne particulate matter and gaseous species in central California. The results show that the WRF model without data assimilation over-predicts surface wind speed by ～30% on average and consequently yields under-predictions for all PM and gaseous species except sulfate (S(VI)) and ozone(O₃). The WRF model with FDDA improves the agreement between predicted and observed wind and temperature values and consequently yields improved predictions for all PM and gaseous species. Overall, diagnostic meteorological fields produced more accurate air quality predictions than either version of the WRF prognostic fields during this episode. Population-weighted average PM_2.5 exposure is 40% higher using diagnostic meteorological fields compared to prognostic meteorological fields created without data assimilation. These results suggest diagnostic meteorological fields based on a dense measurement network are the preferred choice for air quality model studies during stagnant periods in locations with complex topography.     

Trends in passenger exposure to carbon monoxide inside a vehicle on an arterial highway of the San Francisco Peninsula over 30 years: A longitudinal study

This paper describes a long-term trend study of passenger exposure to carbon monoxide (CO) inside a vehicle traveling on an arterial highway in northern California. CO exposure was measured during four field surveys on State Route #82 (El Camino Real) on the San Francisco Peninsula in 1980–1981, 1991–1992, 2001–2002, and 2010–2011. Each field survey took at least 12 months. Fifty trips from each survey—for a total of 200 trips—were matched by date, day of the week, and starting time of the day to facilitate comparisons over three decades. The mean net CO concentration of each trip was obtained by subtracting the background CO level from the average CO concentration for the entire trip. The mean net CO concentration (0.5 ppm) for 2010–2011 was only 5.2% of that (9.7 ppm) for 1980–1981. For the 50 trips, the average travel time for the 1980–1981 period (39.6 min) was only 8.3% higher than during the 2010–2011 period (36.3 min). The estimated round-trip distance on the highway was held constant at 11.8 miles. The reduction in the mean net CO concentration was attributed to more stringent CO emission standards on new vehicles sold in California since 1980. The state’s cold-temperature CO standard implemented in 1996 appeared to reduce high CO concentrations that were observed during the late fall and winter of 1980–1981. In addition, the observed standard deviation in concentration fell from 3.1 ppm in 1980–1981 to 0.2 ppm in 2010–2011, and the range of the 50 mean net CO concentrations narrowed from 14.9 ppm in 1980–1981 to 1.1 ppm in 2010–2011, but the relative variability, as indicated by the geometric standard deviation, remained the same. These results have important scientific implications for regulatory policies designed to control air pollution from motor vehicles.

Implications: Many developing countries launched or expanded their mobile source emission control programs in the 1990s, yet many of them do not have adequate inspection and maintenance (I/M) programs. The El Camino Real study shows the long-term public health benefits of more stringent motor vehicle emission standards for carbon monoxide (CO) on new cars and of an I/M program (Smog Check) on the existing fleet in California. The study provides a protocol for conducting standardized field surveys of in-vehicle exposure on a periodic basis. Such surveys would enable developing countries to assess the progress of their mobile source emission control programs.     

Near-road air pollutant concentrations of CO and PM2.5: A comparison of MOBILE6.2/CALINE4 and generalized additive models

The contribution of vehicular traffic to air pollutant concentrations is often difficult to establish. This paper utilizes both time-series and simulation models to estimate vehicle contributions to pollutant levels near roadways. The time-series model used generalized additive models (GAMs) and fitted pollutant observations to traffic counts and meteorological variables. A one year period (2004) was analyzed on a seasonal basis using hourly measurements of carbon monoxide (CO) and particulate matter less than 2.5 μm in diameter (PM_2.5) monitored near a major highway in Detroit, Michigan, along with hourly traffic counts and local meteorological data. Traffic counts showed statistically significant and approximately linear relationships with CO concentrations in fall, and piecewise linear relationships in spring, summer and winter. The same period was simulated using emission and dispersion models (Motor Vehicle Emissions Factor Model/MOBILE6.2; California Line Source Dispersion Model/CALINE4). CO emissions derived from the GAM were similar, on average, to those estimated by MOBILE6.2. The same analyses for PM_2.5 showed that GAM emission estimates were much higher (by 4–5 times) than the dispersion model results, and that the traffic-PM_2.5 relationship varied seasonally. This analysis suggests that the simulation model performed reasonably well for CO, but it significantly underestimated PM_2.5 concentrations, a likely result of underestimating PM_2.5 emission factors. Comparisons between statistical and simulation models can help identify model deficiencies and improve estimates of vehicle emissions and near-road air quality.     

An Analysis of Michigan and California CO Remote Sensing Measurements

Abstract

Remote sensing measurements of CO emissions from on-road vehicles were made in California in 1991 and in Michigan in 1992. It was determined that both fleets had a small linear increase in the high emitter frequency (vehicles emitting more than 4% CO) as a function of vehicle age for 1986 and newer model vehicles. Although high emitting vehicles were only a small minority of the fleet, they had a dominant impact on the mean CO and total CO emitted by the fleet. In Michigan, the highest emitting 5% of passenger cars generated 45% of the CO from cars. In California, the highest emitting 5% of passenger cars generated 38% of the CO from cars. There was a high correlation between the mean CO emitted by each model year of vehicle and the frequency of high emitting vehicles within the model year for both the Michigan and California fleets. The frequency of high emitters within any model year had no obvious relation to that model year’s certification standards. The high emitter frequencies for vehicles less than nine years old were very similar for the California and Michigan fleets. An increase in the high emitter frequency in the ten-year-old and older Michigan passenger car fleet (relative to the California passenger car fleet), suggests, but does not conclusively demonstrate, that the rate of high emitters in Michigan and California is reduced by the inspection and maintenance (I/M) programs.     

Analysis of the Trend and Seasonal Cycle of Carbon Monoxide Concentrations in an Urban Area (4 pp)

Background, Aim and Scope Air quality is an field of major concern in large cities. This problem has led administrations to introduce plans and regulations to reduce pollutant emissions. The analysis of variations in the concentration of pollutants is useful when evaluating the effectiveness of these plans. However, such an analysis cannot be undertaken using standard statistical techniques, due to the fact that concentrations of atmospheric pollutants often exhibit a lack of normality and are autocorrelated. On the other hand, if long-term trends of any pollutant’s emissions are to be detected, meteorological effects must be removed from the time series analysed, due to their strong masking effects. Materials and Methods The application of statistical methods to analyse temporal variations is illustrated using monthly carbon monoxide (CO) concentrations observed at an urban site. The sampling site is located at a street intersection in central Valencia (Spain) with a high traffic density. Valencia is the third largest city in Spain. It is a typical Mediterranean city in terms of its urban structure and climatology. The sampling site started operation in January 1994 and monitored CO ground level concentrations until February 2002. Its geographic coordinates are W0°22′52″ N39°28′05″ and its altitude is 11 m. Two nonparametric trend tests are applied. One of these is robust against serial correlation with regards to the false rejection rate, when observations have a strong persistence or when the sample size per month is small. A nonparametric analysis of the homogeneity of trends between seasons is also discussed. A multiple linear regression model is used with the transformed data, including the effect of meteorological variables. The method of generalized least squares is applied to estimate the model parameters to take into account the serial dependence of the residuals of this model. This study also assesses temporal changes using the Kolmogorov-Zurbenko (KZ) filter. The KZ filter has been shown to be an effective way to remove the influence of meteorological conditions on O₃ and PM to examine underlying trends. Results The nonparametric tests indicate a decreasing, significant trend in the sampled site. The application of the linear model yields a significant decrease every twelve months of 15.8% for the average monthly CO concentration. The 95% confidence interval for the trend ranges from 13.9% to 17.7%. The seasonal cycle also provides significant results. There are no differences in trends throughout the months. The percentage of CO variance explained by the linear model is 90.3%. The KZ filter separates out long, short-term and seasonal variations in the CO series. The estimated, significant, long-term trend every year results in 10.3% with this method. The 95% confidence interval ranges from 8.8% to 11.9%. This approach explains 89.9% of the CO temporal variations. Discussion The differences between the linear model and KZ filter trend estimations are due to the fact that the KZ filter performs the analysis on the smoothed data rather than the original data. In the KZ filter trend estimation, the effect of meteorological conditions has been removed. The CO short-term componentis attributable to weather and short-term fluctuations in emissions. There is a significant seasonal cycle. This component is a result of changes in the traffic, the yearly meteorological cycle and the interactions between these two factors. There are peaks during the autumn and winter months, which have more traffic density in the sampled site. There is a minimum during the month of August, reflecting the very low level of vehicle emissions which is a direct consequence of the holiday period. Conclusions The significant, decreasing trend implies to a certain extent that the urban environment in the area is improving. This trend results from changes in overall emissions, pollutant transport, climate, policy and economics. It is also due to the effect of introducing reformulated gasoline. The additives enable vehicles to burn fuel with a higher air/fuel ratio, thereby lowering the emission of CO. The KZ filter has been the most effective method to separate the CO series components and to obtain an estimate of the long-term trend due to changes in emissions, removing the effect of meteorological conditions. Recommendations and Perspectives Air quality managers and policy-makers must understand the link between climate and pollutants to select optimal pollutant reduction strategies and avoid exceeding emission directives. This paper analyses eight years of ambient CO data at a site with a high traffic density, and provides results that are useful for decision-making. The assessment of long-term changes in air pollutants to evaluate reduction strategies has to be done while taking into account meteorological variability     

Preliminary on-road measurement of the effect of oxygenated fuel on CO emissions near Las Vegas, Nevada

A preliminary measurement of an oxygenated fuel effect for in-use vehicles travelling at freeway speed was conducted near Las Vegas, NV, in January 1991 and May 1992. The experimental design was based on two principal factors: (1) the large volume of traffic that visits Las Vegas from Southern California on three-day holiday weekends and (2) the fact that, at the time of the study, the Las Vegas area used oxygenated fuels in the winter and Southern California did not. Measurements were conducted at carefully selected sites 20 km southwest of Las Vegas near Sloan, NV, and were accomplished with the Fuel Efficiency Automoblie Test (FEAT) remote sensor developed at the University of Denver. The January 1991 measurements were made during the Las Vegas oxyfuel season, while the May 1992 control measurements were made outside the oxyfuel season. Over 24,500 individual CO concentrations were measured; registration data from over 5,500 of these vehicles were obtained from the license plate numbers. After corrections for differences in velocity and mean age, the Las Vegas outbound (oxyfuel) CO emissions on Monday morning of the January holiday weekend showed a difference of -18% +/- 11% compared to the inbound (non-oxyfuel) CO emissions on Friday evening preceding the holiday weekend.     

Assessment of the nested grid model estimates for driving regional visibility models in the southwestern United States

The Nested Grid Model (NGM) is a primitive-equation meteorological model that is routinely exercised over North America for forecasting purposes by the National Meteorological Center. While prognostic meteorological models are being increasingly used to drive air quality models, their use in conducting annual simulations requires significant resources. NGM estimates of wind fields and other meteorological variables provide an attractive alternative since they are typically archived and readily available for an entire year. Preliminary evaluation of NGM winds during the summer of 1992 for application to the region surrounding the Grand Canyon National Park showed serious shortcomings. The NGM winds along the borders between California, Arizona and Mexico tend to be northwesterly with a speed of about 6 m/sec, while the observed flow is predominantly southerly at about 2-5 m/sec. The mesoscale effect of a thermal low pressure area over the highly heated Southern California and western Arizona deserts does not appear to be represented by the NGM because of its coarse resolution and the use of sparse observations in that region. Tracer simulations and statistical evaluation against special high resolution observations of winds in the southwest United States clearly demonstrate the northwest bias in NGM winds and its adverse effect on predictions of an air quality model. The "enhanced" NGM winds, in which selected wind observations are incorporated in the NGM winds using a diagnostic meteorological model provide additional confirmation on the primary cause of the northwest bias. This study has demonstrated that in situations where limited resources prevent the use of prognostic meteorological models, previously archived coarse resolution wind fields in which additional observations are incorporated to correct known biases provide an attractive option.     

Remote Sensing Data and a Potential Model of Vehicle Exhaust Emissions

In June 1991, General Motors Research and Development Center (GMR&D) participated in a remote sensing study conducted by the California Air Resources Board and the U. S. Environmental Protection Agency. During this study, the GMR&D remote sensor was used to measure the carbon monoxide (CO) and hydrocarbon (HC) emissions from approximately 15,000 vehicles. The vehicle type (passenger car, light-duty truck, or medium/heavy-duty truck), manufacturer, and model year were identified for each vehicle by acquiring registration data from the state of California. Analyses were performed separately for each vehicle type and for passenger cars by separate model years. The data indicate that the passenger cars with the highest 10% of CO emissions generated approximately 58% of the total CO from all cars. Similarly, the 10% highest HC-emitting cars generated 65% of the total HC from cars. It was found that for each model year of vehicle, the distribution of emission concentrations followed a logarithmic relationship. The logarithmic functions that describe these relationships can be used to estimate the fraction of vehicles that emitted at or above any given concentration of CO or HC. However, these logarithmic functions only describe measured distributions for vehicles emitting more than 1% CO and 0.015% HC.     

Summer Transport Patterns Affecting the Mohave Power Project Emissions

The Mohave Power Project (MPP) is an isolated 1580-MW coal-fired electric generating plant located in Laughlin, NV. Laughlin is a small desert gambling town situated in the lower Colorado River Valley near the junction of three states: Nevada, California, and Arizona. The location of the MPP is approximately 115 km southwest of the western end of the Grand Canyon National Park and about 240 km southwest from the Grand Canyon Village. This paper describes the summer transport patterns of the MPP emittants using illustrated examples from the Project MOHAVE (Measurements of Haze and Visual Effects) 1992 summer intensive study. The intensive study lasted 50 days from mid-July through August and encompassed the major meteorological patterns associated with southwestern U.S. summer meteorology. The MPP emittants were transported toward the Grand Canyon (north to the northeast) during more than 80% of the total hours. Airflow was from the south most of the time due to a combination of the semi-permanent thermal low, differential heating between the Gulf of California and lower Colorado River Valley, and upslope heating of the southern and western slopes of the nearby Colorado Plateau.     

Persistence Factors for Mobile Source (Roadway) Carbon Monoxide Modeling

A critical step in the modeling of the carbon monoxide (CO) impacts of mobile sources is predicting an 8-hour CO concentration given a modeled "worst-case" 1-hour concentration. Often, this is done by a multiplicative persistence factor. A meteorological persistence factor (MPF) accounts for the variability over 8 hours of wind speed, wind direction, stability class, and temperature. A vehicular persistence factor (VPF) reflects the lower traffic volumes during the off-peak hours.

Hourly meteorological data for ten years for four cities in Florida were obtained from the National Climatic Data Center. The CALINE3 model was used to obtain hourly CO concentrations, which were combined to derive MPFs for each city. Similarly, VPFs were derived from hourly vehicle counts from one busy roadway in each city. The mean VPF multiplied by the second highest MPF was defined as the worst-case total persistence factor (TPF). These worst-case TPFs increased significantly as more hours of nighttime were included in the 8- hour averaging time, but were fairly consistent from city to city. In general, the results suggest worst-case TPFs in the range of 0.4 to 0.5, lower than has been recommended by EPA in the past.     

Assessment of the Nested Grid Model Estimates for Driving Regional Visibility Models in the Southwestern United States

ABSTRACT

The Nested Grid Model (NGM) is a primitive-equation meteorological model that is routinely exercised over North America for forecasting purposes by the National Meteorological Center. While prognostic meteorological models are being increasingly used to drive air quality models, their use in conducting annual simulations requires significant resources. NGM estimates of wind fields and other meteorological variables provide an attractive alternative since they are typically archived and readily available for an entire year. Preliminary evaluation of NGM winds during the summer of 1992 for application to the region surrounding the Grand Canyon National Park showed serious shortcomings. The NGM winds along the borders between California, Arizona and Mexico tend to be northwesterly with a speed of about 6 m/sec, while the observed flow is predominantly southerly at about 2-5 m/sec. The mesoscale effect of a thermal low pressure area over the highly heated Southern California and western Arizona deserts does not appear to be represented by the NGM because of its coarse resolution and the use of sparse observations in that region. Tracer simulations and statistical evaluation against special high resolution observations of winds in the southwest United States clearly demonstrate the northwest bias in NGM winds and its adverse effect on predictions of an air quality model. The “enhanced” NGM winds, in which selected wind observations are incorporated in the NGM winds using a diagnostic meteorological model provide additional confirmation on the primary cause of the northwest bias. This study has demonstrated that in situations where limited resources prevent the use of prognostic meteorological models, previously archived coarse resolution wind fields in which additional observations are incorporated to correct known biases provide an attractive option.