Real‐Time Estimation of Pollution Emissions and Dispersion from Highway Traffic

Traffic‐related air pollution is a serious problem with significant health impacts in both urban and suburban environments. Despite an increased realization of the negative impacts of air pollution, assessing individuals' exposure to traffic‐related air pollution remains a challenge. Obtaining high‐resolution estimates are difficult due to the spatial and temporal variability of emissions, the dependence on local atmospheric conditions, and the lack of monitoring infrastructure. This presents a significant hurdle to identifying pollution concentration hot spots and understanding the emission sources responsible for these hot spots, which in turn makes it difficult to reduce the uncertainty of health risk estimates for communities and to develop policies that mitigate these risks. We present a novel air pollution estimation method that models the highway traffic state, highway traffic‐induced air pollution emissions, and pollution dispersion, and describe a prototype implementation for the San Francisco Bay Area. Our model is based on the availability of real‐time traffic estimates on highways, which we obtain using a traffic dynamics model and an estimation algorithm that augments real‐time data from both fixed sensors and probe vehicles. These traffic estimates combined with local weather conditions are used as inputs to an emission model that estimates pollutant levels for multiple gases and particulates in real‐time. Finally, a dispersion model is used to assess the spread of these pollutants away from the highway source. Maps generated using the output of the dispersion model allow users to easily analyze the evolution of individual pollutants over time, and provides transportation engineers and public health officials with valuable information that can be used to minimize health risks.     

The importance of source configuration in quantifying footprints of regional atmospheric sulphur deposition

An atmospheric transport-chemistry model is applied to investigate the effects of source configuration in simulating regional sulphur deposition footprints from elevated point sources. Dry and wet depositions of sulphur are calculated for each of the 69 largest point sources in the UK. Deposition contributions for each point source are calculated for 2003, as well as for a 2010 emissions scenario. The 2010 emissions scenario has been chosen to simulate the Gothenburg protocol emission scenario. Point source location is found to be a major driver of the dry/wet deposition ratio for each deposition footprint, with increased precipitation scavenging of SO_x in hill areas resulting in a larger fraction of the emitted sulphur being deposited within the UK for sources located near these areas. This reduces exported transboundary pollution, but, associated with the occurrence of sensitive soils in hill areas, increases the domestic threat of soil acidification. The simulation of plume rise using individual stack parameters for each point source demonstrates a high sensitivity of SO₂ surface concentration to effective source height. This emphasises the importance of using site-specific information for each major stack, which is rarely included in regional atmospheric pollution models, due to the difficulty in obtaining the required input data. The simulations quantify how the fraction of emitted SO_x exported from the UK increases with source magnitude, effective source height and easterly location. The modelled reduction in SO_x emissions, between 2003 and 2010 resulted in a smaller fraction being exported, with the result that the reductions in SO_x deposition to the UK are less than proportionate to the emission reduction. This non-linearity is associated with a relatively larger fraction of the SO₂ being converted to sulphate aerosol for the 2010 scenario, in the presence of ammonia. The effect results in less-than-proportional UK benefits of reducing in SO₂ emissions, together with greater-than-proportional benefits in reducing export of UK SO₂ emissions.     

Impact and uncertainty of a traffic management intervention: population exposure to polycyclic aromatic hydrocarbons

In urban areas, road traffic is a major source of carcinogenic polycyclic aromatic hydrocarbons (PAH), thus any changes in traffic patterns are expected to affect PAH concentrations in ambient air. Exposure to PAH and other traffic-related air pollutants has often been quantified in a deterministic manner that disregards the various sources of uncertainty in the modelling systems used. In this study, we developed a generic method for handling uncertainty in population exposure models. The method was applied to quantify the uncertainty in population exposure to benzo[a]pyrene (BaP) before and after the implementation of a traffic management intervention. This intervention would affect the movement of vehicles in the studied area and consequently alter traffic emissions, pollutant concentrations and population exposure. Several models, including an emission calculator, a dispersion model and a Geographic Information System were used to quantify the impact of the traffic management intervention. We established four exposure zones defined by distance of residence postcode centroids from major road or intersection. A stochastic method was used to quantify the uncertainty in the population exposure model. The method characterises uncertainty using probability measures and propagates it applying Monte Carlo analysis. The overall model predicted that the traffic management scheme would lead to a minor reduction in mean population exposure to BaP in the studied area. However, the uncertainty associated with the exposure estimates was much larger than this reduction. The proposed method is generic and provides realistic estimates of population exposure to traffic-related pollutants, as well as characterises the uncertainty in these estimates. This method can be used within a decision support tool to evaluate the impact of alternative traffic management policies.     

Transient dispersion of dust by wind from nonpoint sources

This study is concerned with unsteady dispersion of particulates from a nonpoint source such as a storage pile and has been solved analytically. The effects of the particle sizes, the heights of the emission source, wind velocity, and the ground conditions on the downwind particle concentration distribution and deposition are presented using the dust puff model. Results indicate that a significant amount of particle deposition can occur even at locations far away from the emission source. The effect of the height of emission source on the downwind particle concentration is only significant near the emission source.     

Three‐dimensional analytical model of atmospheric dispersion of pollutant in a stable boundary layer

A three‐dimensional atmospheric dispersion model of a heavy admixture emitted from an elevated continuous point source is presented. Appropriate boundary conditions have been employed to model the effects of various removal mechanisms like deposition, settling and leakage of pollutants. This model takes care of variation of mixing layer height with heat flux, geostrophic drag by terrain and several meteorological parameters. A realistic form of variable eddy diffusivity is used in this model for a stable atmospheric condition. It has been found that the effect of settling of large particles is to reduce pollutant concentration always far away (horizontally as well as vertically) from the source. Whereas, in the lower part of the boundary layer near the source its effect is to increase concentration for small values of settling velocity and to decrease for larger values. The present model, being three dimensional in nature, is more suitable to assess the impact of point source emission.     

Particle dispersion and deposition in ventilated rooms: Testing and evaluation of different Eulerian and Lagrangian models

Indoor particle dispersion in a three-dimensional ventilated room is simulated by a Lagrangian discrete random walk (DRW) model and two Eulerian models: drift flux model and mixture model. The simulated results are compared with the published measured data to check the performance of the three models for indoor particle dispersion simulation. The deposition velocity of the particles is also computed and compared with published data. The turbulent airflow is modeled with the renormalization group (RNG) k−ε and a zero equation turbulence model. Comparison of the calculated air velocities with measurement shows that both the two turbulence models can simulate the airflow well for the presented case. For the Lagrangian DRW model, a post-process program is used to state the particle trajectories and transfer the results to particle concentration distribution. For Eulerian models, the effect of particle deposition towards wall surfaces is incorporated with a semi-empirical particle deposition model. The comparison shows that both the Lagrangian DRW model and drift flux model yield satisfactory predictions, while the predicted results by the mixture model are not satisfied. The deposition velocity obtained by the three models match the experimental data well.     

Measuring and modelling the airborne particulate matter mass concentration field in the street environment: model overview and evaluation.

This paper discusses the outline structure and preliminary evaluation of an emission-dispersion model for predicting the temporal and spatial distribution of vehicle-derived airborne particulate matter mass concentration in street canyons. The model is called Street Level Air Quality (SLAQ). SLAQ is semi-empirical, in that it uses not only results from field and wind tunnel experiments but also theory and models derived from multiple runs of numerical routines in order to simulate the basic physical processes within the street canyon. A combination of a plume model, for the direct contribution of vehicle exhaust, and a box model for the recirculating part of the pollutants in the street, is used to predict concentration for receptors within the canyon. Emission rates of vehicle-derived particulate matter are calculated within SLAQ, which serve as input to the dispersion module. Exhaust emission rates are scaled element by element along the street for each of the lanes according to the direction of traffic flow to account for modal operation of vehicles near signalised intersections. This refinement allows SLAQ to account for non-uniformity in along-canyon emission rates and to model a street that has several intersections along its length. Thermal turbulence due to environmental surface sensible heat and vehicle-generated heat is accounted for in the model. Other features of SLAQ include correction for the urban heat island effect, dry deposition, wet deposition, particle settling and estimation of wind direction standard deviation, when this latter data is not available. SLAQ has been evaluated in a street in Loughborough, Leicestershire, United Kingdom and correlation coefficient of 0.8 between the modelled and measured concentrations has been obtained.     

Contribution of trace metals from atmospheric deposition to stormwater runoff in a small impervious urban catchment

The contribution of atmospheric deposition to emissions of trace metals in stormwater runoff was investigated by quantifying wet and dry deposition fluxes and stormwater discharges within a small, highly impervious urban catchment in Los Angeles. At the beginning of the dry season in spring 2003, dry deposition measurements of chromium, copper, lead, nickel, and zinc were made monthly for 1 year. Stormwater runoff and wet deposition samples also were collected, and loading estimates of total annual deposition (wet+dry) were compared with annual stormwater loads. Wet deposition contributed 1-10% of the total deposition inside the catchment, indicating the dominance of dry deposition in semi-arid regions such as Los Angeles. Based on the ratio of total deposition to stormwater, atmospheric deposition potentially accounted for as much as 57-100% of the total trace metal loads in stormwater within the study area. Despite potential bias attributable to processes that were not quantified in this study (e.g., resuspension out of the catchment or sequestration within the catchment), these results demonstrate atmospheric deposition represents an important source of trace metals in stormwater to waterbodies near urban centers.     

Simulating impacts of wind farms on local hydrometeorology

Wind power is one of the fastest growing energy sources in the world, most of the growth being in large wind farms that are often located on agricultural land near residential communities. This study explores the possible impacts of such wind farms on local hydrometeorology using a mesoscale model equipped with a rotor parameterization based on data from a commercial wind turbine. Results show that wind farms significantly affect near-surface air temperature and humidity as well as surface sensible and latent heat fluxes. The signs of the impacts, i.e., increase or decrease, depend on the static stability and total water mixing ratio lapse rates of the atmosphere. The magnitudes of these impacts are not only constrained by the hub-height wind speed but also depend to some extent on the size of the wind farms. Wind farms also affect the hydrometeorology of an area up to 18-23 km downwind. More work is required to conclusively estimate the length-scale of wind farm wakes. This study is one of the first few to provide realistic estimates of possible impacts of wind farms. The model developed and used in this study can help in assessing and addressing the environmental impacts of wind farms thereby ensuring the long-term sustainability of wind power.     

Numerical modeling of passive scalar dispersion in an urban canopy layer

A turbulent dispersion model describing the dispersion of a passive scalar from a localized source released in a built-up environment (urban area) is presented. The proposed model simulates both the flow field in the urban complex using the ensemble-averaged, three-dimensional Navier-Stokes equations with a standard k-ε turbulence closure model and the turbulent diffusion using transport equations for the mean concentration and concentration variance of the scalar. Two models for the scalar dissipation rate, required to close the transport equation for concentration variance, are investigated. Results of a detailed comparison of the flow and turbulent dispersion between a comprehensive water channel experiment and the model predictions are presented. The water channel experiment is unique in the sense that it includes data obtained from the dispersion of both continuous and nearly instantaneous releases of a tracer from a point source located within a regular array of building-like obstacles, and this data include measurements of both the mean concentration and concentration variance.     

Potential geographic distribution of atmospheric nitrogen deposition from intensive livestock production in North Carolina, USA

To examine the consequences of increased spatial aggregation of livestock production facilities, we estimated the annual production of nitrogen in livestock waste in North Carolina, USA, and analyzed the potential distribution of atmospheric nitrogen deposition from confined animal feeding operations ("CAFO") lagoons. North Carolina is a national center for industrial livestock production. Livestock is increasingly being raised in CAFOs, where waste is frequently held, essentially untreated, in open-air lagoons. Reduced nitrogen in lagoons is volatilized as ammonia (NH(3)), transported atmospherically, and deposited to other ecosystems. The Albemarle-Pamlico Sound, NC, is representative of nitrogen-sensitive coastal waters, and is a major component of the second largest estuarine complex in the U.S. We used GIS to model the area of water in the Sound within deposition range of CAFOs. We also evaluated the number of lagoons within deposition range of each 1 km(2) grid cell of the state. We considered multiple scenarios of atmospheric transport by varying distance and directionality. Modeled nitrogen deposition rates were particularly elevated for the Coastal Plain. This pattern matches empirical data, suggesting that observed regional patterns of reduced nitrogen deposition can be largely explained by two factors: limited atmospheric transport distance, and spatial aggregation of CAFOs. Under our medium-distance scenario, a small portion (roughly 22%) of livestock production facilities contributes disproportionately to atmospheric deposition of nitrogen to the Albemarle-Pamlico Sound. Furthermore, we estimated that between 14-37% of the state receives 50% of the state's atmospheric nitrogen deposition from CAFO lagoons. The estimated total emission from livestock is 134,000 t NH(3) yr(-1), 73% of which originates from the Coastal Plain. Stronger waste management and emission standards for CAFOs, particularly those on the Coastal Plain nearest to sensitive water bodies, may help mitigate negative impacts on aquatic ecosystems.     

Dust concentrations around coal stockpiles

One of the sources of airborne dust from operations at coal terminals is wind erosion of the stockpiles. The condition of the stockpile, whether it is being worked (a live stockpile) or at rest (dead storage), is of prime importance. A further important set of variables is formed by the meteorological conditions.To predict the dust concentration in the air around future coal terminals due to wind erosion, we have used a computer program developed some time ago for describing the dispersion of heavy gases in the atmosphere, adapting the program to take into account the fall-out of particles as a function of their size. The input of the program comprises the geometry of the stockpile area, the atmospheric conditions and the source strength of the stockpile.To provide data on the source strength as a function of atmospheric conditions, measurements were performed near a number of existing stockpiles in various countries and regions. Dust concentrations in the air around the stockpiles were determined with a high volume air sampler. The dust collected on the filters was analysed and the particle size distribution determined. The results obtained were compared with predictions from the computer program for various input conditions. In this way the source strength was derived. When this source strength is inserted into the computer program, predictions for a projected coal terminal can be made. The results of the calculations predict the dust concentrations in the surrounding area under various conditions. Some typical results are presented.     

Towards quantification of uncertainty in predicting water quality failures in integrated catchment model studies

This paper describes the development and application of a method for estimating uncertainty in the prediction of sewer flow quantity and quality and how this may impact on the prediction of water quality failures in integrated catchment modelling (ICM) studies. The method is generic and readily adaptable for use with different flow quality prediction models that are used in ICM studies. Use is made of the elicitation concept, whereby expert knowledge combined with a limited amount of data are translated into probability distributions describing the level of uncertainty of various input and model variables. This type of approach can be used even if little or no site specific data is available. Integrated catchment modelling studies often use complex deterministic models. To apply the results of elicitation in a case study, a computational reduction method has been developed in order to determine levels of uncertainty in model outputs with a reasonably practical level of computational effort. This approach was applied to determine the level of uncertainty in the number of water quality failures predicted by an ICM study, due to uncertainty associated with input and model parameters of the urban drainage model component of the ICM. For a small case study catchment in the UK, it was shown that the predicted number of water quality failures in the receiving water could vary by around 45% of the number predicted without consideration of model uncertainty for dissolved oxygen and around 32% for unionised ammonia. It was concluded that the potential overall levels of uncertainty in the ICM outputs could be significant. Any solutions designed using modelling approaches that do not consider uncertainty associated with model input and model parameters may be significantly over-dimensioned or under-dimensioned. With changing external inputs, such as rainfall and river flows due to climate change, better accounting for uncertainty is required.     

Integrated river flow modelling: A case study

The paper presents a holistic approach to river flow modelling in which catchment rainfall-runoff, sewer hydrodynamic and river hydrodynamic models are linked together and applied to the Bradford catchment (UK). The catchment features steep gradients, flashy supercritical flow in combination with dry bed condition and is highly urbanised. Given this complexity and the paucity of data, a holistic approach was found essential, although its application proved challenging.

Most important uncertainties inherent in each sub-model were assessed individually as well as propagation effects through the integrated model. The relative contribution of uncertainty sources to the total uncertainty in river flow predictions was quantified using the concept of variance decomposition. The results show that uncertainties in model structure and rainfall input in the rainfall-runoff model were significant. However, within the river hydrodynamic model, uncertainties propagated from the rainfall-runoff model were less apparent due to additional uncertainty arising from the urban drainage system.     

Analysis of a combined cooling, heating, and power system model under different operating strategies with input and model data uncertainty

Combined cooling, heating, and power (CCHP) system models have been used by many researchers to compare their performance with conventional systems. However, decisions based on the results of computer simulations need to take into account the uncertainty of these results to get insight into the level of confidence in the predictions. This paper presents an analysis of a CCHP system model under different operating strategies with input and model data uncertainty. However, the uncertainties that underlie the variation in input parameters such as the thermal load, natural gas prices and electricity prices are not readily available. Additionally, engine performance uncertainty can be difficult to characterize because of the nonlinearity of engine efficiency curves. This paper presents practical and novel approaches to estimating the uncertainty in these and other input parameters. A case study using a small office building located in Atlanta, GA, is described to illustrate the importance of the use of uncertainty and sensitivity analysis in CCHP system performance predictions, and how the primary energy consumption, operational cost, and carbon dioxide emissions are affected by the uncertainty associated with the model input parameters.     

Intercomparison study of atmospheric mercury models: 2. Modelling results vs. long-term observations and comparison of country deposition budgets

Five regional scale models with a horizontal domain covering the European continent and its surrounding seas, two hemispheric and one global scale model participated in the atmospheric Hg modelling intercomparison study. The models were compared between each other and with available measurements from 11 monitoring stations of the EMEP measurement network. Because only a very limited number of long-term measurement records of Hg were available, significant attention was given to the intercomparison of modelling results. Monthly and annually averaged values of Hg concentrations and depositions as well as items of the Hg deposition budgets for individual European countries were compared. The models demonstrated good agreement (within +/-20%) between annual modelled and observed values of gaseous elemental Hg. Modelled values of Hg wet deposition in Western and Central Europe agreed with the observations within +/-45%. The probability to predict wet depositions within a factor of 2 with regard to measurements was 50-70% for all the models. The scattering of modelling results for dry depositions of Hg was more significant (up to +/-50% at the annual scale and even higher for monthly data). Contribution of dry deposition to the total Hg deposition was estimated at 20-30% with elevated dry deposition fluxes during summer time. The participating models agree in their predictions of transboundary pollution for individual countries within +/-60% at the monthly scale and within +/-30% at the annual scale. For the cases investigated, all the models predict that the major part of national anthropogenic Hg emissions is transported outside the country territory.     

Evaluation of calibration efficacy under different levels of uncertainty

This paper examines how calibration performs under different levels of uncertainty in model input data. It specifically assesses the efficacy of Bayesian calibration to enhance the reliability of EnergyPlus model predictions. A Bayesian approach can be used to update uncertain values of parameters, given measured energy-use data, and to quantify the associated uncertainty. We assess the efficacy of Bayesian calibration under a controlled virtual-reality setup, which enables rigorous validation of the accuracy of calibration results in terms of both calibrated parameter values and model predictions. Case studies demonstrate the performance of Bayesian calibration of base models developed from audit data with differing levels of detail in building design, usage, and operation.     

Dispersion of odorous gases in the atmosphere - Part I: Modeling approaches to the phenomenon

The study of odor dispersion, particularly its modeling, is an important decision tool for estimating the impact of human activities on the environment and its populations. In this sense, software to model the dispersion of odorous gases was developed and is presented. It is based on the theory established by H?gstr?m on the odor dispersion of puff emissions. This theory is applied to Gaussian models and takes the frequency of values for odor intensity over any time period into account. Such a model is able to consider the instantaneous characteristics of odor perception by human beings. Nine approaches that explore several solutions within the Gaussian domain for the atmospheric dispersion problem are proposed in software named ODODIS (ODOr DISpersion Software). This software was developed to test the different solutions. Four of these solutions are based on the punctual (or point source) emission or classic equation; two are based on the instantaneous punctual emission equation; and the other three, on the prolonged punctual emission equation (puff models). Measuring units used for the input data may be g s(-1) or OU (Odor Units). The software developed here satisfies the need to obtain instantaneous data of either a passive or an odorous gas at a specific point of an area. The simulation time varies depending on the purpose of the analysis. Mean concentration values may be obtained by integrating the instantaneous results generated by the model.     

Modelling of volatile organic compounds emission from dry building materials

A numerical and an analytical model were developed to predict the volatile organic compound (VOC) emission rate from dry building materials. Both models consider the mass diffusion process within the material and the mass convection and diffusion processes in the boundary layer. All the parameters, the mass diffusion coefficient of the material, the material/air partition coefficient, and the mass transfer coefficient of the air can be either found in the literature or calculated using known principles.

The predictions of the models were validated at two levels: with experimental results from the specially designed test and with predictions made by a CFD model. The results indicated that there was generally good agreement between the model predictions, the experimental results, and the CFD results. The analytical and numerical models then were used to investigate the impact of air velocity on emission rates from dry building materials. Results showed that the impact of air velocity on the VOC emission rate increased as the VOC diffusion coefficient of the material increased. For the material with a diffusion coefficient >10⁻¹⁰ m²/s, the VOC emission rate increased as the velocity increased; air velocity had significant effect on the VOC emission. For the material with a VOC diffusion coefficient <10⁻¹⁰ m²/s, the VOC emission rate increased as the velocity increased only in the short-term; <24 h. In the medium to long-term time range, the VOC emission rate decreased slightly as the air velocity increased; velocity did not have much impact on these materials. Furthermore, the study also found that the VOC concentration distribution within the material; the VOC emission rate and the VOC concentration in the air were linearly proportional to the initial concentration. However, the normalized emitted mass was not a function of the initial concentration: it was a function of the properties of the VOC and the material.     

Approximate methods for uncertainty analysis of water distribution systems

Monte Carlo simulation (MCS) has been commonly applied for uncertainty analysis of model predictions. However, when modelling a water distribution system under unsteady conditions, the computational demand of MCS is quite high even for a reasonably sized system. The aim of this study is to evaluate alternative approximation schemes and examine their ability to predict model prediction uncertainty with less computational effort. Here, MCS is compared with a point estimation method, the first-order second-moment (FOSM) method, and a quasi-MCS method, Latin hypercube sampling (LHS). Hydraulic and water quality simulations are performed using EPANET and the evaluated model outputs are nodal pressure, water age and chlorine concentration. Six input parameters, pipe diameter and roughness coefficient, nodal spatial and temporal demands and bulk and wall decay coefficients, are considered. To examine the effect of the magnitude of input uncertainty on model output, three uncertainty levels are evaluated. The study is performed for a real system with 116 pipes and 90 nodes. Results demonstrate that LHS provides very good estimates of the predicted output range for steady and unsteady conditions compared with MCS, while FOSM did well for steady conditions but poorly for some periods in the extended-period simulation for chlorine concentration.