Evaluation of results of a numerical simulation of dispersion in an idealised urban area for emergency response modelling

WinMISKAM is evaluated from an emergency response perspective. Comparisons are made between ground level concentrations observed during selected Mock Urban Setting Test (MUST) field trials and predictions generated by the model. The model was driven by 5 min averaged on-site meteorological data, and used minimum grid spacing of 0.5 m in both the horizontal and vertical. The code was found to perform well, with 46% of all predictions (paired in time and space) and 83% of arc maxima predictions within a factor of two of observed concentrations. The model was found to perform better for neutral cases than stable cases with 27% of stable case predictions and 57% of neutral case predictions within a factor of two when compared in time and space.     

Three-dimensional modeling of air flow and pollutant dispersion in an urban street canyon with thermal effects

Effects of excess ground and building temperatures on airflow and dispersion of pollutants in an urban street canyon with an aspect ratio of 0.8 and a length-to-width ratio of 3 were investigated numerically. Three-dimensional governing equations of mass, momentum, energy, and species were modeled using the RNG k-epsilon turbulence model and Boussinesq approximation, which were solved using the finite volume method. Vehicle emissions were estimated from the measured traffic flow rates and modeled as banded line sources, with a street length and bandwidths equal to typical vehicle widths. Both measurements and simulations reveal that pollutant concentrations typically follow the traffic flow rate; they decline as the height increases and are higher on the leeward side than on the windward side. Three-dimensional simulations reveal that the vortex line, joining the centers of cross-sectional vortexes of the street canyon, meanders between street buildings and shifts toward the windward side when heating strength is increased. Thermal boundary layers are very thin. Entrainment of outside air increases, and pollutant concentration decreases with increasing heating condition. Also, traffic-produced turbulence enhances the turbulent kinetic energy and the mixing of temperature and admixtures in the canyon. Factors affecting the inaccuracy of the simulations are addressed.     

A simple urban dispersion model tested with tracer data from Oklahoma City and Manhattan

A simple urban dispersion model is tested that is based on the Gaussian plume model and modifications to the Briggs urban dispersion curves. An initial dispersion coefficient (σ_o) of 40 m is assumed to apply in built-up downtown areas, and the stability is assumed to be slightly unstable during the day and slightly stable during the night. Observations from tracer experiments during the Joint Urban 2003 (JU2003) field study in Oklahoma City and the Madison Square Garden 2005 (MSG05) field study in Manhattan are used for model testing. The tracer SF₆ was released during JU2003 near ground level in the downtown area and concentrations were observed at over 100 locations within 4 km from the source. Six perfluorocarbon tracer (PFT) gases were released near ground level during MSG05 and sampled by about 20 samplers at the surface and on building roofs. The evaluations compare concentrations normalized by source release rate, C/Q, for each sampler location and each tracer release, where data were used only if both the observed and predicted concentrations exceeded threshold levels. At JU2003, for all samplers and release times, the fractional mean bias (FB) is about 0.2 during the day (20% mean underprediction) and 0.0 during the night. About 45 –50% of the predictions are within a factor of two (FAC2) of the observations day and night at JU2003. The maximum observed C/Q is about two times the maximum predicted C/Q both day and night. At MSG05, for all PFTs, surface samplers, and release times, FB is 0.14 and FAC2 is about 45%. The overall 60 min-averaged maximum C/Q is underpredicted by about 40% for the surface samplers and is overpredicted by about 25% for the building-roof samplers.     

Sulfur processing in the marine atmospheric boundary layer: A review and critical assessment of modeling uncertainties

Sulfur is an extremely motile and vital element in the Earth's biogeochemical environment, one whose active redox chemistry maintains small reservoirs in the atmosphere and biosphere yet large fluxes through both. Essential for life, intimately linked to the climate state, and an important component of air quality, sulfur and its transport and processing in the atmosphere have been the subject of active research for several decades. This review article describes the current state of our understanding of the atmospheric sulfur cycle, focusing on the marine atmospheric boundary layer, with the aim of identifying the largest roots of uncertainty that most inhibit accurate simulation of sulfur cycling in the atmosphere. An overview of the emissions by phytoplankton and shipping, dispersion and entrainment in the marine boundary layer, and chemical processing by aerosols, clouds, and dry deposition is presented. Analysis of 20 contemporary modeling studies suggests that the greatest ambiguity in global sulfur cycling derives from (in descending order) wet deposition of aerosol sulfate, dry deposition of sulfur dioxide to the Earth's surface, and the heterogeneous oxidation of SO₂ in aerosols and clouds.     

The tidal hydrodynamics modeling of the Topolobampo coastal lagoon system and the implications for pollutant dispersion

The tidal hydrodynamics of the Topolobampo coastal lagoon system (Mexico) has been investigated through a modified two dimensional non-linear hydrodynamic finite difference model. The advective and diffusive process acting over a hypothetical pollutant released into the coastal lagoon have also been simulated. Maxima tidal currents (0.85 m/s) were predicted within the main channel, in agree with direct measurements. The direction of the observed fastest currents (SW), also agree quite well with the direction of the strongest tidal current predicted in this investigation, which occur during the ebb when the water of the coastal lagoon is discharged into the Gulf of California. Residual currents (0.01-0.05 m/s) were also predicted. The hypothetical pollutant released within the Topolobampo Harbor would spread to both Ohuira and Topolobampo sections, reaching the inlet after approximately 12 days.     

A semi-empirical box modeling approach for predicting the carbon monoxide concentrations at an urban traffic intersection

Emissions generated roadside and at intersections are observed to be affected when there is a sudden change in the traffic flow pattern or increase in the vehicular population, particularly, during peak hours and during special events. The vehicles that queue up at traffic intersections spend a longer amount of time in idle driving mode generating more pollutant emissions per unit time. Other driving patterns (i.e., acceleration, deceleration and cruising) are also observed at intersections, affecting the emission pattern and therefore the resulting pollutant concentrations. The emission rate is not only affected by the increase in the vehicular population but also by the constantly changing traffic flow patterns and vehicles’ driving modes. The nature of the vehicle flows also affects the rate and nature of the dispersion of pollutants in the vicinity of the road, influencing the pollutant concentration. It is, therefore, too complex to simulate the effect of such dynamics on the resulting emission rates using conventional deterministic causal models.In view of this, a simple semi-empirical box model based on the ‘traffic flow rate’, is demonstrated in the present study for estimating the hourly average carbon monoxide (CO) concentrations on a 1-week data at one of the busiest traffic intersections in Delhi. The index of agreement for a whole week, was found to be 0.84, suggesting that the semi-empirical model is 84% error free. A value of 0.87 was found for weekdays and 0.75 for weekend days. The correlation coefficient for the whole week was found to be 0.75, with 0.78 for the weekdays and 0.62 for the weekend days. The RMSE and RRMSE were found to be 1.87% and 41% for a whole week, with 1.81% and 39.93% for the weekdays and 2.0% and 43.47% for the weekend days, respectively. Specific vehicle emission rates are optimized in this study for individual vehicle category, which may be useful in assessing their impacts on the air quality when there is a significant change in a specific vehicular population and the traffic pattern.     

Coupling of the Weather Research and Forecasting Model with AERMOD for pollutant dispersion modeling. A case study for PM10 dispersion over Pune,India

The prediction of spatial variation of the concentration of a pollutant governed by various sources and sinks is a complex problem. Gaussian air pollutant dispersion models such as AERMOD of the United States Environmental Protection Agency (USEPA) can be used for this purpose. AERMOD requires steady and horizontally homogeneous hourly surface and upper air meteorological observations. However, observations with such frequency are not easily available for most locations in India. To overcome this limitation, the planetary boundary layer and surface layer parameters required by AERMOD were computed using the Weather Research and Forecasting (WRF) Model (version 2.1.1) developed by the National Center for Atmospheric Research (NCAR). We have developed a preprocessor for offline coupling of WRF with AERMOD. Using this system, the dispersion of respirable particulate matter (RSPM/PM10) over Pune, India has been simulated. Data from the emissions inventory development and field-monitoring campaign (13–17 April 2005) conducted under the Pune Air Quality Management Program of the Ministry of Environment and Forests (MoEF), India and USEPA, have been used to drive and validate AERMOD. Comparison between the simulated and observed temperature and wind fields shows that WRF is capable of generating reliable meteorological inputs for AERMOD. The comparison of observed and simulated concentrations of PM10 shows that the model generally underestimates the concentrations over the city. However, data from this single case study would not be sufficient to conclude on suitability of regionally averaged meteorological parameters for driving Gaussian models like AERMOD and additional simulations with different WRF parameterizations along with an improved pollutant source data will be required for enhancing the reliability of the WRF–AERMOD modeling system.     

Air-vegetation transfer of PCDD/PCDFs: an assessment of field data and implications for modeling

This study was designed to evaluate soil and air (gas and particle) transfer of polychlorinated dibenzo-p-dioxins and dibenzofurans (PCDD/Fs) to vegetation in residential and industrial areas. In a first part, soil-vegetation transfer was assessed. The levels of PCDD/Fs in 120 soil and 120 herbage samples collected from 1996 to 2002 in an industrial area of Montcada (Barcelona, Spain), near a municipal solid waste incinerator (MSWI), were determined. Some additional individual samples were also evaluated. It was concluded that high soil concentrations, which are not at steady state with the air layer above it, show a tendency for PCDD/Fs to escape via volatilization. In a second part of the study, air-vegetation transfer was examined. PCDD/F concentrations from 24 herbage samples were used, while PCDD/F concentrations were also measured in seven high-volume air samples and seven passive air-vapor samples. Scavenging coefficients (m3 air "sampled"/g grass d.m.) ranged from 1.9 to 11.3 m3/g. A good trend with K(OA) was observed for PCDDs (R=0.82), while it was lower for PCDFs (R=0.55). The current results corroborate that PCDD/F concentrations in vegetation are associated with atmospheric deposition. For the highest substituted PCDD/F congeners, the air-particle uptake from plants is the principal pathway. In regions impacted by combustion emission sources, PCDD/F gas-particle partitioning is influenced by a higher concentration of particles in the air. Particles and associated particle-bound PCDD/Fs would sorb to leaf surfaces, and are subject to removal via wash off. However, in areas where emissions to air are not very notable, vapor absorption would be the principal source of vegetation pollution. The results of this investigation can have a potential interest in risk assessment studies and environmental fate models.     

Numerical modeling on air quality in an urban environment with changes of the aspect ratio and wind direction

Due to heavy traffic emissions within an urban environment, air quality during the last decade becomes worse year by year and hazard to public health. In the present work, numerical modeling of flow and dispersion of gaseous emissions from vehicle exhaust in a street canyon were investigated under changes of the aspect ratio and wind direction. The three-dimensional flow and dispersion of gaseous pollutants were modeled using a computational fluid dynamics (CFD) model which was numerically solved using Reynolds-averaged Navier–Stokes (RANS) equations. The diffusion flow field in the atmospheric boundary layer within the street canyon was studied for different aspect ratios (W/H?=?1/2, 3/4, and 1) and wind directions (θ?=?90°, 112.5°, 135°, and 157.5°). The numerical models were validated against wind tunnel results to optimize the turbulence model. The numerical results agreed well with the wind tunnel results. The simulation demonstrated that the minimum concentration at the human respiration height within the street canyon was on the windward side for aspect ratios W/H?=?1/2 and 1 and wind directions θ?=?112.5°, 135°, and 157.5°. The pollutant concentration level decreases as the wind direction and aspect ratio increase. The wind velocity and turbulence intensity increase as the aspect ratio and wind direction increase.     

An air quality data analysis system for interrelating effects, standards, and needed source reductions: Part 13--Applying the EPA Proposed Guidelines for Carcinogen Risk Assessment to a set of asbestos lung cancer mortality data

The Clean Air Act Amendments of 1990 (CAAA-90) list 189 hazardous air pollutants (HAPs) for which "safe" ambient concentrations are to be determined. The primary purpose of this paper is to develop two mathematical models, lognormal and logarithmic, that effectively express excess lung cancer mortality as a function of asbestos concentration for an example set of data and also to suggest using these two models for additional HAPs. The secondary purpose of this paper is to calculate a "safe" asbestos concentration by first assuming a default linear extrapolation (to one excess death per million people, as specified for carcinogenic HAPs). The resulting "safe" concentration is an impossible-to-achieve 1/1000 of present background asbestos concentrations. A letter to the editor and a response in this Journal issue use additional asbestos data that suggest that the "safe" concentration should be about 730 times higher than first calculated here and that a default nonlinear extrapolation should be used instead, with the "safe" concentration proportional to the desired mortality level raised to the 0.39 power. These results suggest that the most important problem in setting a "safe" concentration for each carcinogenic HAP is to determine the correct nonlinear extrapolation to use for each HAP.     

Application of an integrated Weather Research and Forecasting (WRF)/CALPUFF modeling tool for source apportionment of atmospheric pollutants for air quality management: A case study in the urban area of Benxi,China

In this study, the authors endeavored to develop an effective framework for improving local urban air quality on meso-micro scales in cities in China that are experiencing rapid urbanization. Within this framework, the integrated Weather Research and Forecasting (WRF)/CALPUFF modeling system was applied to simulate the concentration distributions of typical pollutants (particulate matter with an aerodynamic diameter <10 μm [PM₁₀], sulfur dioxide [SO₂], and nitrogen oxides [NO_x]) in the urban area of Benxi. Statistical analyses were performed to verify the credibility of this simulation, including the meteorological fields and concentration fields. The sources were then categorized using two different classification methods (the district-based and type-based methods), and the contributions to the pollutant concentrations from each source category were computed to provide a basis for appropriate control measures. The statistical indexes showed that CALMET had sufficient ability to predict the meteorological conditions, such as the wind fields and temperatures, which provided meteorological data for the subsequent CALPUFF run. The simulated concentrations from CALPUFF showed considerable agreement with the observed values but were generally underestimated. The spatial-temporal concentration pattern revealed that the maximum concentrations tended to appear in the urban centers and during the winter. In terms of their contributions to pollutant concentrations, the districts of Xihu, Pingshan, and Mingshan all affected the urban air quality to different degrees. According to the type-based classification, which categorized the pollution sources as belonging to the Bengang Group, large point sources, small point sources, and area sources, the source apportionment showed that the Bengang Group, the large point sources, and the area sources had considerable impacts on urban air quality. Finally, combined with the industrial characteristics, detailed control measures were proposed with which local policy makers could improve the urban air quality in Benxi. In summary, the results of this study showed that this framework has credibility for effectively improving urban air quality, based on the source apportionment of atmospheric pollutants.

Implications: The authors endeavored to build up an effective framework based on the integrated WRF/CALPUFF to improve the air quality in many cities on meso-micro scales in China. Via this framework, the integrated modeling tool is accurately used to study the characteristics of meteorological fields, concentration fields, and source apportionments of pollutants in target area. The impacts of classified sources on air quality together with the industrial characteristics can provide more effective control measures for improving air quality.

Through the case study, the technical framework developed in this study, particularly the source apportionment, could provide important data and technical support for policy makers to assess air pollution on the scale of a city in China or even the world.     

Implications for emergency response to the severe odor incident occurred in source water: Potential odorants and control strategy

Environmental Science and Pollution Research - Sudden odor incidents occurring in the source water have been a severe problem for water suppliers. In order to apply emergency control measures...     

A biochar-based medium in the biofiltration system: Removal efficiency,microorganism propagation,and the medium penetration modeling

Biofiltration is a method of biological treatment belonging to cleaner technologies because it does not produce secondary air pollutants, but helps to integrate natural processes in microorganisms for decomposing volatile air pollutants and solving odor problems. The birch wood biochar has been chosen as a principal material for biofilter bed medium. The experiments were conducted at the temperatures of 24, 28, and 32 °C, while the concentration of acetone, xylene, and ammonium reached 300 mg/m³ and the flow rate was 100 m³/hr. Before passing through the stage of the experimental research into the packing material inside biofilters, microorganisms were introduced. Four strains of microorganisms (including micromycetes Aspergillus versicolor BF-4 and Cladosporium herbarum 7KA, as well as yeast Exophiala sp. BF1 and bacterium Bacillus subtilis B20) were selected. At the inlet loading rate of 120 g/m³/hr, the highest elimination capacity of xylene in the biochar-based biofilter with the inoculated medium was 103 g/m³/hr, whereas that of ammonia was 102 g/m³/hr and that of acetone was 97 g/m³/hr, respectively. The maximum removal efficiency reached 86%, 85%, and 81%, respectively. The temperature condition (though characterized by some rapid changes) can hardly have a considerable influence on the biological effect (i.e., microbiological activity) of biofiltration; however, it can cause the changes in physical properties (e.g., solubility) of the investigated compounds.

Implications: The birch biochar can be successfully used in the biofiltration system for propagation of inoculated microorganisms, biodegrading acetone, xylene, and ammonia. At the inlet loading rate of 120 g/m³/hr, the highest elimination capacity of xylene was 103 g/m³/hr, that of ammonia was 102 g/m³/hr, and that of acetone was 97 g/m³/hr, respectively. The morphological structure of biochar can be affected by the aggressive air contaminants, causing the change in the medium specific surface area, which is one of the factors controlling the biofilter performance. Although biological effects in biofiltration are typically considered to be more important than physical effects, the former may be more important for compounds with high Henry’s Law coefficient values, and the biofilter design should thus provide conditions for better compound absorption.     

Application of the top specified boundary layer (TSBL) approximation to initial characterization of an inland aquifer mineralization: 1. Direct contact between fresh and saltwater

This paper presents a basic study in generalized terms that originates from two needs: (1) to understand the major mechanisms involved in the mineralization of groundwater of the Great Bend Prairie aquifer of Kansas by saltwater originating from a deeper Permian bedrock formation, and (2) to develop simple, robust tools that can readily be used for local assessment and management activities in the salt-affected region. A simplified basic conceptual model is adopted, incorporating two horizontal layers of porous medium which come into contact at a specific location within the model domain. The top layer is saturated with freshwater, and the bottom layer is saturated with saltwater. The paper considers various stages of approximation which can be useful for simplified simulation of the build-up of the transition zone (TZ) between the freshwater and the saltwater. The hierarchy of approximate approaches leads to the development of the top specified boundary layer (TSBL) method, which is the major tool used in this study for initial characterization of the development of the TZ. It is shown that the thickness of the TZ is mainly determined by the characteristic dispersivity. The build-up of the TZ is completed after a time period equal to the time needed to advect a fluid particle along the whole extent of the TZ. Potential applications and the effects of natural recharge and pumpage on salinity transport in the domain are discussed and evaluated in the context of demonstrating the practicality of the TSBL approach.     

Remanence of lead pollution in an urban river system: a multi-scale temporal and spatial study in the Seine River basin,France

Total lead (Pb) concentration and Pb isotopic ratio (²⁰⁶Pb/²⁰7Pb) were determined in 140 samples from the Seine River basin (France), covering a period of time from 1945 to 2011 and including bed sediments (bulk and size fractionated samples), suspended particulate matter (SPM), sediment cores, and combined sewer overflow (CSO) particulate matter to constrain the spatial and temporal variability of the lead sources at the scale of the contaminated Seine River basin. A focus on the Orge River subcatchment, which exhibits a contrasted land-use pattern, allows documenting the relation between hydrodynamics, urbanization, and contamination sources. The study reveals that the Pb contamination due to leaded gasoline that peaked in the 1980s has a very limited impact in the river nowadays. In the upstream Seine River, the isotopic ratio analysis suggests a pervasive contamination which origin (coal combustion and/or gasoline lead) should be clarified. The current SPM contamination trend follows the urbanization/industrialization spatial trend. Downstream of Paris, the lead from historical use originating from the Rio Tinto mine, Spain (²⁰⁶Pb/²⁰⁷Pb?=?1.1634?±?0.0001) is the major Pb source. The analysis of the bed sediments (bulk and grain size fractionated) highlights the diversity of the anthropogenic lead sources in relation with the diversity of the human activities that occurred in this basin over the years. The “urban” source, defined by waste waters including the CSO samples (²⁰⁶Pb/²⁰⁷Pb?=?1.157?±?0.003), results of a thorough mixing of leaded gasoline with “historical” lead over the years. Finally, a contamination mixing scheme related to hydrodynamics is proposed.     

Extreme learning machines: a new approach for modeling dissolved oxygen (DO) concentration with and without water quality variables as predictors

In this paper, several extreme learning machine (ELM) models, including standard extreme learning machine with sigmoid activation function (S-ELM), extreme learning machine with radial basis activation function (R-ELM), online sequential extreme learning machine (OS-ELM), and optimally pruned extreme learning machine (OP-ELM), are newly applied for predicting dissolved oxygen concentration with and without water quality variables as predictors. Firstly, using data from eight United States Geological Survey (USGS) stations located in different rivers basins, USA, the S-ELM, R-ELM, OS-ELM, and OP-ELM were compared against the measured dissolved oxygen (DO) using four water quality variables, water temperature, specific conductance, turbidity, and pH, as predictors. For each station, we used data measured at an hourly time step for a period of 4 years. The dataset was divided into a training set (70%) and a validation set (30%). We selected several combinations of the water quality variables as inputs for each ELM model and six different scenarios were compared. Secondly, an attempt was made to predict DO concentration without water quality variables. To achieve this goal, we used the year numbers, 2008, 2009, etc., month numbers from (1) to (12), day numbers from (1) to (31) and hour numbers from (00:00) to (24:00) as predictors. Thirdly, the best ELM models were trained using validation dataset and tested with the training dataset. The performances of the four ELM models were evaluated using four statistical indices: the coefficient of correlation (R), the Nash-Sutcliffe efficiency (NSE), the root mean squared error (RMSE), and the mean absolute error (MAE). Results obtained from the eight stations indicated that: (i) the best results were obtained by the S-ELM, R-ELM, OS-ELM, and OP-ELM models having four water quality variables as predictors; (ii) out of eight stations, the OP-ELM performed better than the other three ELM models at seven stations while the R-ELM performed the best at one station. The OS-ELM models performed the worst and provided the lowest accuracy; (iii) for predicting DO without water quality variables, the R-ELM performed the best at seven stations followed by the S-ELM in the second place and the OP-ELM performed the worst with low accuracy; (iv) for the final application where training ELM models with validation dataset and testing with training dataset, the OP-ELM provided the best accuracy using water quality variables and the R-ELM performed the best at all eight stations without water quality variables. Fourthly, and finally, we compared the results obtained from different ELM models with those obtained using multiple linear regression (MLR) and multilayer perceptron neural network (MLPNN). Results obtained using MLPNN and MLR models reveal that: (i) using water quality variables as predictors, the MLR performed the worst and provided the lowest accuracy in all stations; (ii) MLPNN was ranked in the second place at two stations, in the third place at four stations, and finally, in the fourth place at two stations, (iii) for predicting DO without water quality variables, MLPNN is ranked in the second place at five stations, and ranked in the third, fourth, and fifth places in the remaining three stations, while MLR was ranked in the last place with very low accuracy at all stations. Overall, the results suggest that the ELM is more effective than the MLPNN and MLR for modelling DO concentration in river ecosystems.     

Shifted power-law relationship between NO2 concentration and the distance from a highway: A new dispersion model based on the wind profile model

In this paper, a shifted power-law model, based on the wind profile model, had been supposed to simulate concentration gradient of nitrogen dioxide (NO₂) with distance from a highway. Field experiments were performed for NO₂ gradients from a highway in Shanghai by using passive samplers. The shifted power-law model was fitted well with experimental results of field experiments both in this study and in the literature. The results not only verified the validity of shifted power-law relationship between NO₂ concentration and the distance from a highway, but also partially demonstrated that there were some significant similarities between wind profile and air pollutants concentration profile near highway. With known concentration of chosen reference point and appropriate value of the parameter k, the model could be practically applied for predicting the NO₂ distributions near a highway. The methods of determining the parameter k were also discussed for further detailed studies.     

A new method for testing the sensitivity of active biomonitoring: an example of its application to a terrestrial moss

For the first time, the concepts of limit of detection and limit of quantification, commonly used in analytical chemistry, are applied to the field of active biomonitoring with terrestrial mosses, using the controls as blanks so that the limits indicate the error associated with the transplant technique. The application of these concepts to data corresponding to Hg concentrations in the surroundings of a chlor-alkali plant and a power plant, makes interpretation of the results easier by providing better spatial and temporal coherence. This procedure may allow improvement in the standardization of active biomonitoring techniques as it is applicable to all kinds of biomonitors. One disadvantage of the application of the limit of detection and limit of quantification is that they only take into account the alpha error, or risk of false positives, and do not take into account the beta error, or risk of false negatives.