Nonturbulent dispersion processes in complex terrain

Mass divergence influences on plume dispersion modify classic Gaussian calculations by as much as a factor of two in complex terrain. The Gaussian plume was derived in flux form to include this process.     

Using CALINE dispersion to assess vehicular PM2.5 emissions

This paper explores the range of CALINE4's PM_2.5 modeling capabilities by comparing previously collected PM_2.5 data with CALINE4 predicted values. Two sampling sites, a suburban site located at an intersection in Sacramento, CA, and an urban site located in London, were used. Predicted concentrations are graphed against observed concentrations and evaluated against the criterion that 75% of the points fall within the factor-of-two prediction envelope. For the suburban site, data estimated by CALINE4 produced results that fell within the acceptable factor-of-two percentage envelope. A reverse dispersion test was also conducted for the suburban site using observed and calculated emission factors, and although it showed correlations between the observed values and CALINE4 predicted values, it could not conclusively prove that the model is accurate at predicting PM_2.5 concentrations. Although the results suggest that CALINE4 PM_2.5 predictions may be reasonably close to observed values, the number of observations used to verify the model was small and consequently, findings from the suburban site should be considered exploratory. For the urban site, a much larger data set was evaluated; however, the CALINE4 results for this site did not fall 75% within the factor-of-two envelope. Several factors, including street canyon effects, likely contributed to an inaccuracy of the emission factors used in CALINE4, and therefore, to the overall CALINE4 predictions. In summary, CALINE4 does not appear to perform well in densely populated areas and differences in topography may be a decisive factor in determining when CALINE4 may be applicable to modeling PM_2.5. For critical transportation projects requiring PM_2.5 analysis, use of CALINE4 may not be optimal because of its inability to produce reasonable estimates for highly trafficked areas. Additional data sets for CALINE4 analysis, particularly in urban environments, are required to fully understand CALINE4's PM_2.5 modeling capabilities.     

A complex terrain dispersion model for regulatory applications

This paper demonstrates the development of a model designed to estimate concentrations associated with a source situated in complex terrain. The model is designed to provide estimates of concentration distributions and is thus primarily suitable for regulatory applications. The model assumes that the concentration at a receptor is a combination of concentrations caused by two asymptotic states: the plume remains horizontal, and the plume climbs over the hill. The factor that weights the two states is a function of the fractional mass of the plume above the dividing streamline height. The model has been evaluated against data from four complex terrain sites. The evaluation shows that the model performs at least as well as CTDMPLUS (Perry, S.G., 1992. CTDMPLUS, a dispersion model for sources near complex topography. Part I: technical formations. Journal of Applied Meteorology 31, 633–645), a more comprehensive model designed for complex terrain applications.     

Performance evaluation of four grid-based dispersion models in complex terrain

Four numerical grid-based dispersion models (Mathew/ADPIC, SMOG, Hybrid, and 2DFLOW) were adapted to the Geysers-Calistoga geothermal area in northern California. The models were operated using five intensive meteorological and tracer diffusion data sets collected during the 1981 ASCOT field experiment at the Geysers (three nocturnal drainage and two daytime valley stagnation episodes). The 2DFLOW and Hybrid Models were found to perform best for drainage and limited-mixing conditions, respectively. These two models were subsequently evaluated using data from five 1980 ASCOT drainage experiments. The Hybrid Model was also tested using data from nine limited-mixing and downwash tracer experiments performed at the Geysers prior to the ASCOT program. Overall, the 2DFLOW Model performed best for drainage flow conditions, whereas the Hybrid Model performed best for valley stagnation (limited-mixing) and moderate crossridge wind conditions. To aid new source review studies at the Geysers, a series of source-receptor transfer matrices were generated for several different meteorological regimes under a variety of emission scenarios using the Hybrid Model. These matrices supply ready estimates of cumulative hydrogen sulfide impacts from various geothermal sources in the region.     

Carbonyl emissions from vehicular exhausts sources in Hong Kong

Vehicular emission (VE) is one of the important anthropogenic sources for airborne carbonyls in urban area. Six types of VE-dominated samples were collected at representative locations in Hong Kong where polluted by a particular fueled type of vehicles, including (i) a gas refilling taxis station (liquefied petroleum gas [LPG] emission); (ii) a light-duty passenger car park (gasoline emission); (iii) a minibus station (diesel emission); (iv) a single-deck-bus depot (diesel emission); (v) a double-deck-bus depot (diesel emission); and (vi) a whole-food market entrance for light- and heavy-duty vehicles (diesel emission). A total of 15 carbonyls in the samples were quantified. Formaldehyde was the most abundant carbonyl among the VE-dominated samples, and its contribution to the total quantified amount on a molar basis ranged from 54.8% to 60.8%. Acetaldehyde and acetone were the next two abundant carbonyls. The carbonyls were quantified at three roadside locations in Hong Kong. The highest concentrations of formaldehyde and acetaldehyde, 22.7 +/- 8.4 and 6.0 +/- 2.8 microg/m3, respectively, were determined in the samples collected at a main transportation gate for goods between Hong Kong and Mainland China. The total quantified carbonyl concentration, 37.9 +/- 9.3 microg/m3, was the highest at an entrance of a cross-harbor tunnel in downtown area. The theoretical carbonyls compositions of the three roadside locations were estimated according to the VE-dominated sample profiles and the statistics on vehicle numbers and types during the sampling period. The measured compositions of formaldehyde were much higher than the theoretical compositions in summer, demonstrating that photochemical reactions significantly contributed to the formaldehyde production in the roadsides.     

Performance of a time-dependent dispersion model in elevated terrain

A study was conducted to evaluate the ability of the TVA quasi-steady model (QSM) to simulate plume dispersion over high terrain. QSM is a time-dependent, plume-segment model. The modeling results are compared with measured data obtained from a field study conducted at the Tennessee Valley Authority's (TVA) Widows Creek Steam Plant. Also, the results obtained using a steady-state Gaussian model are compared to give an indication of the advantages of a time-dependent method compared to a steady-state method.Although the results from both models agree well with the measured values, QSM, which provides better temporal and spatial resolution, more successfully modeled inversion-breakup and plume-impingement conditions.     

Trends in vehicular emissions in China's mega cities from 1995 to 2005

Multiyear inventories of vehicular emissions in Beijing, Shanghai and Guangzhou from 1995 through 2005 have been developed in this paper to study the vehicle emissions trends in China's mega cities during the past decade. The results show that the vehicular emissions of CO, HC, NO_x and PM₁₀ have begun to slow their growth rates and perhaps even to decline in recent years due to the implementation of measures to control vehicular emissions in these cities. However, vehicular CO₂ emissions have substantially increased and still continue to grow due to little fuel economy improvement. Passenger cars and large vehicles (including heavy duty trucks and buses) are the major sources of vehicular CO₂ and CO emissions while large vehicles were responsible for nearly 70% and 80% of the vehicular NO_x and PM₁₀ emissions in these mega cities. Motorcycles are also important contributors to vehicular emissions in Guangzhou and Shanghai.     

Characteristics of real-world vehicular emissions in Chinese cities

On-board emission measurements were performed on 49 light-duty gasoline vehicles in seven cities of China. Vehicle-specific power mode distribution and emission characteristics were analyzed based on the data collected. The results of our study show that there were significant differences in different types of roads. The emission factors and fuel consumption rates on arterial roads and residential roads were approximately 1.4-2 times those on freeways. The carbon monoxide, hydrocarbon, and nitrogen oxides emission factors of Euro II vehicles were on average 86.2, 88.2, and 64.5% lower than those of carburetor vehicles, respectively. The new vehicle emission standards implemented in China had played an important role in reducing individual vehicle emissions. More comprehensive measures need to be considered to reduce the total amount of emissions from vehicles.     

A complex terrain dispersion model for regulatory applications at the Westvaco luke mill

A data set for studying transport and dispersion in complex terrain was collected at the Westvaco Corporation's Luke Mill, located in the Potomac River valley in western Maryland. Meteorological analyses indicate very strong channeling of winds and the presence of strong inversions and wind shears in a shallow layer at the height of the surrounding mountaintops (300 m above the valley floor). Wind velocities observed near the valley floor are unrepresentative of wind velocities at plume height. Observed turbulence intensities at plume height are about twice as large as those observed over flat terrain. Standard stability classification schemes generally underestimate plume dispersion at this site. When high 3-h and 24-h average SO₂ concentrations are observed, winds are usually light and an inversion is present. These instances of relatively high concentrations are often associated with periods when the wind shifts direction 180° from up-valley to down-valley or vice versa, and the nearly stagnant polluted air mass blows against the mountainsides.A dispersion model was developed that is Gaussian in form but uses observed meteorological data to the maximum extent possible. For example, observed turbulence intensities at plume height are used to estimate dispersion. Plume impaction on terrain is calculated if the plume height is below a critical height dependent on the Hill Froude number. Evaluation of the model with the full 2-y data set shows that it can estimate the second highest 3-h and 24-h average concentrations (of regulatory significance) with a mean bias of less than 7%.     

Estimation of vehicular emissions by capturing traffic variations

Increase in traffic volumes and changes in travel-related characteristics increase vehicular emissions significantly. It is difficult, however, to accurately estimate emissions with current practice because of the reliance on travel forecasting models that are based on steady state hourly averages and, thus, are incapable of capturing the effects of traffic variations in the transportation network. This paper proposes an intermediate model component that can provide better estimates of link speeds by considering a set of Emission Specific Characteristics (ESC) for each link. The intermediate model is developed using multiple linear regression; it is then calibrated, validated, and evaluated using a microscopic traffic simulation model. The improved link speed data can then be used to provide better estimates of emissions. The evaluation results show that the proposed emission estimation method performs better than current practice and is capable of estimating time-dependent emissions if traffic sensor data are available as model input.     

Shared- and distributed-memory parallelization of a Lagrangian atmospheric dispersion model

This paper describes parallelization of a 3-D Lagrangian stochastic atmospheric dispersion model using both distributed- and shared-memory methods. Shared-memory parallelism is implemented through the use of OpenMP compiler directives. Distributed-memory parallelism relies on the MPI message-passing library. One or both (using MPI for inter-node and OpenMP for intra-node communication) of the parallel modes can be used depending upon the requirements of the problem and the computational platform available. The distributed-memory version achieves a nearly linear decrease in execution time as the number of processors is increased. As the number of particles per processor is lowered, performance is limited by the decrease in work per processor and by the need to produce one set of output files. The shared-memory version achieves a speedup factor of ∼1.4 running on machines with four processors.     

Monte Carlo simulation of nitrogen oxides dispersion from a vehicular exhaust plume and its sensitivity studies

The pollutant dispersion behavior from the vehicular exhaust plume has a direct impact on human health, particularly to the drivers, bicyclists, motorcyclists, pedestrians, people working nearby and vehicle passengers. A two-dimensional pollutant dispersion numerical model was developed based on the joint-scalar probability density function (PDF) approach coupled with a k–ε turbulence model to simulate the initial dispersion process of nitrogen oxides, temperature and flow velocity distributions from a vehicular exhaust plume. A Monte Carlo algorithm was used to solve the PDF transport equations in order to obtain the dispersion distribution of nitrogen oxides concentration. The model was then validated by a series of sensitivity experimental studies in order to assess the effects of vehicular exhaust tailpipe velocities, wind speeds and chemistry on the initial dispersion of NO and NO₂ mass concentrations from the vehicular exhaust plume. The results show that the mass concentrations of nitrogen oxides decrease along the centerline of the vehicular exhaust plume in the downstream distance. The dispersion process can be enhanced when the vehicular exhaust tailpipe velocity is much larger than the wind speed. The oxidation reaction of NO plays an important role when the wind speed is large and the vehicular exhaust exit velocity is small, which leads to chemical reduction of NO, and the formation and accumulation of NO₂ in the exhaust plume. It is also found that the effect of vehicular exhaust-induced turbulence in the vicinity of the exhaust tailpipe exit is more dominant than the effect of wind turbulence, while the wind turbulence gradually shows a significant role for the dispersion of nitrogen oxides along with the development of exhaust plume. The range of dispersion of nitrogen oxides in the radial direction is increased along with the development of vehicular exhaust plume.     

Comprehensive primary particulate organic characterization of vehicular exhaust emissions in France

A study to characterize primary particulate matter (PM_2.5 and PM₁₀) from the French vehicular fleet was conducted during winter 2008, in a tunnel in Marseille, France. The carbonaceous fraction represents 70% of the aerosol mass and elemental carbon fraction (EC) represent 60% of the carbonaceous fraction. The organic carbon OC was characterized in term of its water soluble fraction, functionalization rate and HULIS content. Seventy trace organic compounds including alkanes, polycyclic aromatic hydrocarbons (PAH), petroleum biomarkers and carboxylic acids were also quantified, in order to determine an organic emission profile for chemical mass balance modeling studies. Such source profiles were still missing in Europe and particularly in France. The profile obtained in this study is consistent with profiles determined in tunnel or dynamometer studies performed in other countries during the last ten years. These results suggest that organic compounds profiles from vehicular exhaust emissions are not significantly influenced by the geographic area and are thus suitable for use in aerosol source apportionment modeling applied across extensive regions. The chemical profile determined here is very similar to those obtained for diesel emissions with high concentrations of EC relative to OC (EC/OC = 1.8) and low concentrations of the higher molecular weight PAH. These results are consistent with the high proportion of diesel vehicles in the French fleet (49%).     

MM5 simulations for air quality modeling: An application to a coastal area with complex terrain

A series of modifications were implemented in MM5 simulation in order to account for wind along the Santa Clarita valley, a north–south running valley located in the north of Los Angeles. Due to high range mountains in the north and the east of the Los Angeles Air Basin, sea breeze entering Los Angeles exits into two directions. One branch moves toward the eastern part of the basin and the other to the north toward the Santa Clarita valley. However, the northward flow has not been examined thoroughly nor simulated successfully in the previous studies. In the present study, we proposed four modifications to trigger the flow separation. They were (1) increasing drag over the ocean, (2) increasing soil moisture content, (3) selective observational nudging, and (4) one-way nesting for the innermost domain. The Control run overpredicted near-surface wind speed over the ocean and sensible heat flux, in an urbanized area, which justifies the above 1st and 2nd modification. The Modified run provided an improvement in near-surface temperature, sensible heat flux and wind fields including southeasterly flow along the Santa Clarita valley. The improved MM5 wind field triggered a transport to the Santa Clarita valley generating a plume elongated from an urban center to the north, which did not exist in MM5 Control run. In all, the modified MM5 fields yielded better agreement in both CO and O₃ simulations especially in the Santa Clarita area.     

Case study of plume dispersion over elevated terrain

A study was conducted to evaluate the ability of a steady-state Gaussian model to simulate plume dispersion over elevated terrain. MULTIMAX, a multisource model equivalent to the Environmental Protection Agency's CRSTER model, was used in the study.The effects of using different combinations of onsite and offsite meteorological data with six different terrain treatment techniques were investigated. The modeling results are compared with measured data obtained during an intensive field study conducted at the Tennessee Valley Authority's Widows Creek Steam Plant. Although the model initially failed to simulate the various dispersion conditions, the results improved significantly after modifications were made to the model and the meteorological preprocessor program.     

Simulating industrial emissions using atmospheric dispersion modeling system: model performance and source emission factors

In this paper, the Gaussian Atmospheric Dispersion Modeling System (ADMS4) was coupled with field observations of surface meteorology and concentrations of several air quality indicators (nitrogen oxides (NOx), carbon monoxide (CO), fine particulate matter (PM10) and sulfur dioxide (SO2)) to test the applicability of source emission factors set by the European Environment Agency (EEA) and the United States Environmental Protection Agency (USEPA) at an industrial complex. Best emission factors and data groupings based on receptor location, type of terrain and wind speed, were relied upon to examine model performance using statistical analyses of simulated and observed data. The model performance was deemed satisfactory for several scenarios when receptors were located at downwind sites with index of agreement 'd' values reaching 0.58, fractional bias 'FB' and geometric mean bias 'MG' values approaching 0 and 1, respectively, and normalized mean square error 'NMSE' values as low as 2.17. However, median ratios of predicted to observed concentrations 'Cp/Co' at variable downstream distances were 0.01, 0.36, 0.76 and 0.19 for NOx, CO, PM10 and SO2, respectively, and the fraction of predictions within a factor of two of observations 'FAC2' values were lower than 0.5, indicating that the model could not adequately replicate all observed variations in emittant concentrations. Also, the model was found to be significantly sensitive to the input emission factor bringing into light the deficiency in regulatory compliance modeling which often uses internationally reported emission factors without testing their applicability.