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 Comparative Validation of the RAM and Modified SAI Models for Short Term SO2 Concentrations in Detroit

The RAM model provided by the U.S. EPA has been applied to the metropolitan Detroit area for SO₂ concentrations and is compared to concentrations predicted by a numerical model and to field data obtained by the 14 station air sampling network maintained by the Wayne County Air Pollution Control Division. Great care was taken to develop the emission inventory. Based upon examination of the temporal and spatial correspondence of the respective model predictions and observed concentrations, the correlation coefficients for the 24-hour averaged data, the correlation coefficients for over 700 3-hour averaged observations, and the cumulative frequency distributions of the model output and observations, it is concluded that the numerical model provides a superior predictive tool to evaluate cause and effect relations, but that the RAM model, at far lower cost, predicts the correct magnitude of the worst events. Hence RAM might well be used in the Detroit Area for statistically based regulatory decisions.     

Analysis of air quality within a street canyon using statistical and dispersion modelling techniques

The dispersion model, ADMS-Urban, alongside the statistical modelling technique, generalized additive modelling, have been used to predict hourly NO_x and nitrogen dioxide (NO₂) concentrations at a busy street canyon location and the results compared with measurements. Generalized additive models (GAMs) were constructed for NO₂ and NO_x concentrations using input data required to run ADMS-Urban. Bivariate polar plots have been produced from the wind flow (speed and direction) and pollution data (measured and predicted concentrations) to provide further information regarding the complex wind-pollutant interactions in an urban street canyon. The predictions made with the GAMs show excellent agreement with measured concentrations at this location, reproducing both the magnitude of NO_x and NO₂ concentrations and also the wind speed-wind direction dependence of pollutant sources within the canyon. However, the predictions made with ADMS-Urban under-estimated the measured NO_x by 11% and NO₂ by 21% and there are clear differences in the bivariate polar plots. Several sensitivity tests were carried out with ADMS-Urban in an attempt to produce predictions in closer agreement to those measured at Gillygate. Increasing the primary NO₂ fraction in ADMS-Urban (from 10% to 20%) had a considerable effect on the predictions made with this model, increasing NO₂ predictions by ∼20%. However, the bivariate plots still showed major differences to those of the measurements. This work illustrates that generalized additive modelling is a useful tool for investigating complex wind-pollutant interactions within a street canyon.     

Industrial Zoning as a Means of Controlling Area Source Air Pollution

The simple ATDL urban dispersion model Is based on the formula Xo(g/m³) = CO(g/m²s)/U(m/s). The diurnal variation of the stability factor C, which can be thought of as the width of the urban area divided by the vertical dispersion of the pollution cloud, has not before been satisfactorily estimated. Using observed diurnal variations of CO concentrations and traffic frequencies reported by DeMarrais of the EPA for many stations in the states of Maryland, New Jersey, and Colorado, and using wind data from these states, hourly values of C - XoU/Q were calculated. The ratio of C to the daily average C is found to equal about 2.5 at 4 a.m., drops to about 0.5 by 8 a.m., and remains at 0.5 until about 6 p.m.., when it starts to climb slowly again. Application of this new stability factor to independent CO data from Los Angeles yields correlations between measured and predicted concentrations of about 0.7.     

An Urban Diffusion Simulation Model For Carbon Monoxide

A relatively simple Gaussian-type diffusion simulation model for calculating urban carbon monoxide (CO) concentrations as a function of local meteorology and the distribution of traffic is described. The model can be used in two ways: (1) in the synoptic mode, in which hourly concentrations at one or many receptor points are calculated from historical or forecast traffic and meteorological data; and (2) in the climatological mode, in which concentration frequency distributions are calculated on the basis of long-term sequences of input data. For model evaluation purposes, an extensive field study involving meteorological and air-quality measurements was conducted during November-December 1970 in San Jose, Calif., which has an automated network to provide traffic data throughout the central business district. Model refinements made on the basis of the data from this experimental program include the addition of a street-canyon submodel to compensate for the important aerodynamic effects of buildings on CO concentrations at streetside receptors. The magnitude of these effects was underscored by the concentrations measured on opposite sides of the street in San Jose, which frequently differed by a factor of two or more. Evaluation of the revised model has shown that calculated and observed concentration frequency distributions for street-canyon sites are in good agreement. Hour-average predictions are well correlated with observations (correlation coefficient of about 0.6 to 0.7), and about 80 percent of the calculated values are within 3 ppm of the observed hour-average concentrations, which ranged as high as 16 ppm.     

Simulating Urban-Scale Air Pollutants and Their Predicting Capabilities over the Seoul Metropolitan Area

Abstract

Urban-scale air pollutants for sulfur dioxide, nitrogen dioxide, particulate matter with aerodynamic diameter >10 μm, and ozone (O₃) were simulated over the Seoul metropolitan area, Korea, during the period of July 2-11, 2002, and their predicting capabilities were discussed. The Air Pollution Model (TAPM) and the highly disaggregated anthropogenic and the biogenic gridded emissions (1 km × 1 km) recently prepared by the Korean Ministry of Environment were applied. Wind fields with observational nudging in the prognostic meteorological model TAPM are optionally adopted to comparatively examine the meteorological impact on the prediction capabilities of urban-scale air pollutants. The result shows that the simulated concentrations of secondary air pollutant largely agree with observed levels with an index of agreement (IOA) of >0.6, whereas IOAs of ～0.4 are found for most primary pollutants in the major cities, reflecting the quality of emission data in the urban area. The observationally nudged wind fields with higher IOAs have little effect on the prediction for both primary and secondary air pollutants, implying that the detailed wind field does not consistently improve the urban air pollution model performance if emissions are not well specified. However, the robust highest concentrations are better described toward observations by imposing observational nudging, suggesting the importance of wind fields for the predictions of extreme concentrations such as robust highest concentrations, maximum levels, and >90th percentiles of concentrations for both primary and secondary urban-scale air pollutants.     

Adsorption Characteristics of Activated Carbon and XAD4 Resin for the Removal of Hazardous Organic Solvents

A comparative study has been conducted on adsorption/desorption of six hazardous organic vapors on synthetic resin (XAD4) and activated carbon, using a differential reactor involving the expansion of a quartz spring. While both sorbents can effectively remove the organic vapors, it was observed that at low concentrations activated carbon adsorbed more organic vapor than synthetic resin. At higher, industrial concentrations, the resins adsorbed more vapor as demonstrated by the slopes of the equilibrium isotherms. The resin also showed much higher desorptlon.

The effective Intraparticle diffusion coefficients (D_e) were observed to be strongly dependent on solute concentration. Pore diffusion dominated the adsorption/desorption of the six organic vapors on XAD4 resin. For the carbon system, pore diffusion dominated the adsorption but surface diffusion contributed to the desorptlon process. This is believed to be due to higher Interaction of the adsorbates with activated carbon.     

Equilibrium partitioning of PCB congeners in the water column: Field measurements from the Hudson River

The environmental behavior of hydrophobic organic compounds in water is driven by partitioning between dissolved and sorbed phases. Partitioning behavior of a compound is often based on empirical relationships to other properties of the chemical, such as water solubility and octanol-water partition coefficients, but actual partitioning in the environment may differ significantly from such predictions. We conducted intensive studies of the distribution of PCBs in the fresh water portion of the Hudson River, using sensitive capillary-column gas chromatography methods to calibrate and resolve quantitations for 90 PCB congeners in 48 samples at 10 locations. A linear equilibrium model of PCB congener partitioning, when corrected for temperature and suspended-matter organic carbon content, provides a good representation of phase distribution. When particulate-phase concentrations are predicted from dissolved concentrations with a two-phase model, the predictions are unbiased for the majority of samples and the average percent difference between observed and predicted particulate concentrations is ±43 percent. Estimated in situ partition coefficients show systematic differences from partition coefficients predicted from octanol-water partitioning. Partitioning to colloids appears to be a significant component of total concentration for mono- and dichlorobiphenyls, but not for more highly chlorinated congeners.The colloidal fraction may still cause significant overestimation of the bioavailable fraction for more hydrophobic congeners when a two-component model is used.     

Emission and Fate Assessment of Methyl Tertiary Butyl Ether in the Boston Area Airshed Using a Simple Multimedia Box Model: Comparison with Urban Air Measurements

Abstract

Expected urban air concentrations of the gasoline additive methyl tertiary butyl ether (MTBE) were calculated using volatile emissions estimates and screening transport models, and these predictions were compared with Boston, MA, area urban air measurements. The total volatile flux of MTBE into the Boston primary metropolitan statistical area (PMSA) airshed was calculated based on estimated automobile nontailpipe emissions and the Universal Quasi-Chemical Functional-Group Activity Coefficient computed abundance of MTBE in gasoline vapor. The fate of MTBE in the Boston PMSA was assessed using both the European Union System for the Evaluation of Substances, which is a steady-state multimedia box model, and a simple airshed box model. Both models were parameterized based on the meteorological conditions observed during air sampling in the Boston area. Measured average urban air concentrations of 0.1 and 1 [H9262]g/m³ MTBE during February and September of 2000, respectively, were comparable to corresponding model predictions of 0.3 and 1 μg/m³ and could be essentially explained from estimated temperature-dependent volatile emissions rates, observed average wind speed (the airshed flushing rate), and reaction with ambient tropospheric hydroxyl radical (.OH), within model uncertainty. These findings support the proposition that one can estimate gasoline component source fluxes and use simple multimedia models to screen the potential impact of future proposed gasoline additives on urban airsheds.     

PM2.5 concentrations in London for 2008–A modeling analysis of contributions from road traffic

We report on the analysis of contributions from road traffic emissions to fine particulate matter (PM_2.5) concentrations within London for 2008 with the OSCAR Air Quality Assessment System. A spatiotemporal evaluation of the OSCAR system has been conducted with measurements from the London air quality network (LAQN). For the predicted and measured hourly time series of concentrations at 18 sites in London, the medians of correlation, mean absolute error, index of agreement, and factor of two (FAC2) of all stations were 0.80, 4.1 μg/m³, 0.86, and 74%, respectively. Spatial evaluation of modeled and observed annual mean concentrations also showed a fairly good agreement, with all the values falling within the FAC2 range. According to model predictions, the urban increment (including the contributions from urban traffic and other urban sources) was evaluated to be on the average 18%, 33%, 39%, and 43% of the total PM_2.5 in suburban environments, in the urban background, near roads, and near busy roads, respectively. However, the highest values of the urban traffic increment can be around 50% of the total PM_2.5 concentrations near motorways and major roads. The total concentrations (including regional background, and the contributions from urban traffic and other urban sources) can therefore be almost three times the regional background. The total urban increment close to busy roads was around 7–8 μg/m³, in which the estimated traffic contribution is more than 2 μg/m³. On the average, urban traffic contributes approximately 1 μg/m³ of PM_2.5 to the urban background across London. According to modeling, approximately two-thirds of the traffic increment originated from exhaust emissions and most of the rest was due to brake and tire wear.

Implications: The urban increment and traffic contribution to the total PM_2.5 are significant and spatially heterogeneous across London. The highly heterogeneous distribution of PM_2.5 hence requires detailed modeling studies to be carried out at high spatial resolution, which can be particularly important for exposure and health impact assessment. This type of information can be used to quantify health impacts resulting from specific sources of PM_2.5 such as traffic emissions, to aid city and national decision makers when formulating pollution control strategies.     

Assessment of a regulatory model's performance relative to large spatial heterogeneity in observed ozone in Houston,Texas

In Houston, some of the highest measured 8-hr ozone (O₃) peaks are characterized by sudden increases in observed concentrations of at least 40 ppb in 1 hr, or 60 ppb in 2 hr. Measurements show that these large hourly changes appear at only a few monitors and span a narrow geographic area, suggesting a spatially heterogeneous field of O₃ concentrations. This study assessed whether a regulatory air quality model (AQM) can simulate this observed behavior. The AQM did not reproduce the magnitude or location of some of the highest observed hourly O₃ changes, and it also failed to capture the limited spatial extent. On days with measured large hourly changes in O₃ concentrations, the AQM predicted high O₃ over large regions of Houston, resulting in overpredictions at several monitors. This analysis shows that the model can make high O₃, but on these days the predicted spatial field suggests that the model had a different cause. Some observed large hourly changes in O₃ concentrations have been linked to random releases of industrial volatile organic compounds (VOCs). In the AQM emission inventory, there are several emission events when an industrial point source increases VOC emissions in excess of 10,000 mol/hr. One instance increased predicted downwind O₃ concentrations up to 25 ppb. These results show that the modeling system is responsive to a large VOC release, but the timing and location of the release, and meteorological conditions, are critical requirements. Attainment of the O₃ standard requires the use of observational data and AQM predictions. If the large observed hourly changes are indicative of a separate cause of high O₃, then the model may not include that cause, which might result in regulators enacting control strategies that could be ineffective.

Implications To show the attainment of the O₃ standard, the U.S. Environmental Protection Agency (EPA) requires the use of observations and model predictions under the assumption that simulations are capable of reproducing observed phenomena. The regulatory model is unable to reproduce observed behavior measured in the observational database. If the large observed hourly changes were indicative of a separate cause of high O₃, then the model would not include that cause. Inaccurate model predictions may prompt air quality regulators to enact control strategies that are effective in the modeling system, but prove ineffective in the real world.     

Turbulent Diffusion Behind Vehicles: Effect of Traffic Speed on Pollutant Concentrations

Recent theoretical and experimental investigations Indicate that turbulent diffusion behind moving vehicles Is Influenced by the speed of the vehicle. Vertical wake induced turbulent diffusion, explicitly treated in the numerical ROADWAY model, is proportional to the square of the wind speed relative to the moving vehicle. Hence, the model predictions of turbulent mixing and pollutant concentrations on and downwind of a roadway are dependent upon the traffic speed. It Is expected from theoretical considerations that the effect of vehicle speed on pollutant concentrations will be more significant during stable atmospheric conditions, because in neutral and unstable conditions the vehicle-wake turbulence is quickly masked by the ambient turbulence. In this study, experimental data are utilized to evaluate the theoretical predictions of the effects of traffic speed on the ambient pollutant concentrations. The effects of vehicle speed upon ambient concentrations are investigated through wind tunnel experiments and field studies that used dual tracers. Consistent with predictions of the ROADWAY model, data obtained near the Long Island Expressway indicate that the influence of traffic speed on the ambient pollutant concentrations Is not significant during unstable and neutral conditions. The Long Island experiment did not provide sufficient field data to assess the model predictions of the traffic speed effect during stable atmospheric conditions.     

Adherence of Sulfur Dioxide Concentrations in the Vicinity of a Steam Plant to Plume Dispersion Models

Air monitoring data for a calendar year at one of the TVA power plants has been used to evaluate the appropriateness of the Sutton, the Bosanquet and Pearson, and the USPHS-TVA atmospheric dispersion models to predict ground level concentrations of sulfur dioxide from emission and meterological data. Aerometric data included one half hourly average sulfur dioxide concentrations, recorded by four Thomas autometers, and the necessary meterological parameters for the solving of atmospheric dispersion models. Based on these meterological parameters and observed plume rise data, over 4000 one half hourly average maximum and minimum expected ground line sulfur dioxide concentrations were predicted for each of the above dispersion models by the use of computer techniques. The plant is a line source; however, an empirical correction was applied to emission data to reduce them to emissions for an equivalent point source. The predicted sulfur dioxide levels for each of the dispersion models were compared to the measured levels throughout the year. Three different sets of diffusion coefficients were applied to the Sutton model and successful predictions, according to a criterion utilizing an acceptable range of concentration, varied from 66 to 93%. The Bosanquet and Pearson model produced successful predictions 90% of the time, while the USPHS-TVA model was successful 94% of the time.Unsuccessful predictions were primarily overestimates.     

Nonmethane Organic Compound to Nitrogen Oxide Ratios and Organic Composition in Cities and Rural Areas

The observed ranges in nonmethane organic compound (NMOC) concentrations, NMOC composition and nitrogen oxides (NO_X) concentrations have been evaluated for urban and nonurban areas at ground level and aloft of the contiguous United States. The ranges in NMOC to NO_X ratios also are considered. The NMOC composition consistently shifts towards less reactive compounds, especially the alkanes, in air parcels over nonurban areas compared to the NMOC composition near ground level within urban areas. The values for the NMOC to NO_X ratios, 1.2 to 4.2, in air aloft over nonurban areas are lower than in air at ground level urban sites, ≥8, and much lower than in air at ground level nonurban sites, ≥20.

The layers of air aloft over a number of nonurban areas of the United States tend to accumulate NO_X emissions from the tall stacks of large fossil fuel power plants located at nonurban sites. During the night into the morning hours, the air aloft is isolated from any fresh NMOC emissions predominately coming from near surface sources. Conversely, during this extended period of restricted vertical mixing, air near the surface accumulates NMOC emissions while this air is isolated from the major NO_X sources emitting aloft. These differences in the distribution of NMOC and NO_X sources appear to account for the much larger NMOC to NO_X ratios reported near ground level compared to aloft over nonurban areas.

Two types of experimental results are consistent with these conclusions: (1) observed increases in surface rural NO_X concentrations during the morning hours during which the mixing depth increases to reach the altitude at which NO_X from the stacks of fossil fuel power plants is being transported downwind; (2) high correlations of total nitrate at rural locations with Se, which is a tracer for coal-fired power plant NO_X emissions.

The implications of these conclusions from the standpoint of air quality strategies are suggested by use of appropriate scenarios applied to both urban and regional scale photochemical air quality models. The predictions from urban model scenarios with NMOC to NO_X ratios up to 20 are that NO_X control will result in the need for the control of more NMOC emissions than necessary in the absence of NO_X control, in order to meet the O₃ standard. On a regional scale, control of NO_X emissions from fossil fuel power plants has little overall effect regionally but does result on a more local scale in both small decreases and increases in O₃ concentrations compared to the baseline scenario without NO_X control. The regional modeling results obtained to date suggest that NO_X control may be effective in reducing O₃ concentrations only for a very limited set of conditions in rural areas.     

An urban trajectory model for sulfur in Asian megacities: model concepts and preliminary application

This paper explores the adaptation of a regional Lagrangian approach for making long-term simulations of SO₂ and sulfate ambient concentrations at the resolution needed for health effects risk assessment in Asian megacities and their surroundings. A Lagrangian trajectory model (UR-BAT) is described which simulates transport and diffusion of sulfur within and near urban areas, originating from area and major point sources. The long-range contribution is accounted for by the ATMOS model, simulating all Asian sources. The model has been applied to Beijing and Bombay, by using preliminary emission figures, and the results have been compared with available monitoring data. The computed concentrations in different cities are in the correct range, indicating the potential use of the model in an integrated assessment framework such as RAINS-Asia.     

Predicting size-resolved particle behavior in multizone buildings

We compare model predictions to measurements of SF₆ and environmental tobacco smoke particle concentrations in a three-room chamber experiment. To make predictions of multi-room aerosol transport and fate, we linked a multizone airflow model (COMIS) with an indoor aerosol dynamics model (MIAQ4). The linked models provide improved simulation capabilities for predicting aerosol concentrations and exposures in buildings. In this application, we found that the multizone air flow model was vital for predicting the inter-room airflows due to temperature differences between the rooms and when air-sampling pumps were operating during the experiment. Model predictions agree well with measurements, as shown by several comparison metrics. However, predictions of airborne ETS concentrations are slightly lower than measurements. This is mostly attributable to under-stating the source release amount, which we specified independently from literature estimates. Model predictions of ETS particle-size distributions agree with measurements; size bins with the peak concentrations are slightly over-predicted initially, but agree thereafter.     

Overestimation of urban nitrogen dioxide by passive diffusion tubes: a comparative exposure and model study

A detailed comparative trial of passive diffusion tubes (PDT) for measurement of NO₂ in urban air has been undertaken in Edinburgh, UK. Acrylic, foil-wrapped and quartz tubes were exposed in parallel for 1-week and 4-week periods at three urban sites equipped with continuous analysers for NO, NO_x and O₃. Standard acrylic PDTs significantly overestimated NO₂ concentrations relative to chemiluminescence analysers, by an average of 27% over all sites for 1-week exposures. No significant difference was observed between standard and foil-wrapped acrylic tubes (both UV blocking). The mean ratio between quartz (UV transmitting) tubes and chemiluminescence analysers was 1.06. Quartz PDT data suggest a tendency for in situ photolysis to offset (but in a non-quantifiable way) the effect of chemical overestimation. The 4-week exposures yielded systematically lower NO₂ concentration than average NO₂ from four sequential 1-week exposures over the same period. The reduction in the apparent NO₂ sampling rate with time mostlikely arises from in situ photolysis of trapped NO₂. Hourly NO₂, NO and O₃ data for 20 1-week exposures were used as input to a numerical model of diffusion tube operation incorporating chemical reaction between co-diffusing NO and O₃ within the tube. The mean calculated overestimation of 22% for NO₂ from the PDT model simulations is close to the average difference between acrylic PDT and analyser NO₂ concentrations (24% for the same exposure periods), showing that within-tube chemistry can account for observed discrepancies in NO₂ measurement between the two techniques. Overestimation by PDT generally increased as average NO₂/NO_x ratios decreased. Accurate quantitative correction of PDT measurements is not possible. Nevertheless, PDT NO₂ concentrations were correlated with both analyser NO₂ and NO_x suggesting that acrylic PDTs retain a qualitative measure of NO₂ and NO_x variation at a particular urban location.     

Harbour of Ravenna: The contribution of harbour traffic to air quality

Ravenna is one of the main Italian ports and has assumed a leadership position in Italy for some products and markets. The commercial harbour and the adjacent industrial area are very important for the economic system of Ravenna but, at the same time, they are highly critical areas.In particular, on average 8000 ships per year pass through the harbour of Ravenna, influencing air quality in harbour environment.The paper originates from a study about the contribution of different sources of air pollution in Ravenna and its aim is to evaluate the maritime traffic contribution to the air quality in the port area and to determine the suitability of an urban air quality model to support the air quality management in Ravenna. NO_x and PM are selected as modelled pollutants.The study is made up of two parts. The first deals with the evaluation of annual emission of PM₁₀ and NO_x coming from ships through a standard European methodology while in the second we simulated the diffusion of these pollutants in the whole area. In order to evaluate the capability of the model to treat maritime traffic emissions, we compared hour-by-hour simulated concentrations with data collected by a fixed monitoring station located near the Candiano Canal.NO_x concentrations obtained by short- and long-term simulations show a good match with the values measured by the fixed monitoring station, located in the centre of harbour area, and these results are also supported by FA2 performance index.Instead the omission of the secondary particulate and the contribution of other sources of particulate matter in the port area are probably the most important causes of the PM₁₀ underestimation.The worse results obtained according to the performance indexes indicate the need to consider the formation and transport of secondary particulate matter in order to obtain more reliable predictions.