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.     

工业点源大气污染扩散空间信息系统

开发了一个基于高斯扩散的大气污染扩散空间信息系统,用于模拟工业点源污染对区域大气质量的影响。该工业点源污染模型包括工业点源数据库、扩散参数、气象条件和大气质量评价4个主要数据库。用该模型计算上海市主要工业区的SO2排放,结果表明,该模型为模拟SO2污染扩散提供了一个有效便捷的方法。     

Monte Carlo simulation of buoyant dispersion

Transport and diffusion of dust and nonbuoyant smoke are simulated in a realistic manner by the particle model originally developed by Ohmstede and Stenmark (1980, 1981). However, many pollutants are buoyant, such as burning trash, oil, or other flammable or explosive material. The resultant buoyant cloud is taken into account by a new simple algorithm included in the particle model. For the model discussed in this paper, a particle represents a small parcel of air plus pollutant. The method uses the difference in temperature between an individual particle and the ambient atmosphere to generate a vertical acceleration. It also considers entrainment and ingestion of unheated material on, or loss of heat by contact with, the ground during initial release and subsequent ground contact. A series of computer runs suggests that the particle model with the new buoyancy algorithm realistically simulates transport and diffusion of buoyant material.     

Predictive modelling of dispersion controlled reactive plumes at the laboratory-scale

A model-based interpretation of laboratory-scale experimental data is presented. Hydrolysis experiments carried out using thin glass tanks filled with glass beads to construct a hypothetical and inert, homogeneous porous medium were analysed using a 2D numerical model. A new empirical formula, based upon results for non-reactive (tracer) experiments is used to calculate transversal dispersivity values for a range of grain sizes and any flow velocities. Combined with effective diffusion coefficients calculated from Stokes-Einstein type equations, plume lengths arising from mixing between two solutes can be predicted accurately using numerical modelling techniques. Moreover, pH and ion concentration profiles lateral to the direction of flow of the mixing species can be determined at any given point downstream, without the need for result fitting. In our case, this approach does not lead to overpredictions of lateral mixing, as previously reported when using parameters derived from non-reactive tracer experiments to describe reactive solute transport. The theory is based on the assumption of medium homogeneity.     

Development of a livestock odor dispersion model: part II. Evaluation and validation

A livestock odor dispersion model (LODM) was developed to predict odor concentration and odor frequency using routine hourly meteorological data input. The odor concentrations predicted by the LODM were compared with the results obtained from other commercial models (Industrial Source Complex Short-Term model, version 3, CALPUFF) to evaluate its appropriateness. Two sets of field odor plume measurement data were used to validate the model. The model-predicted mean odor concentrations and odor frequencies were compared with those measured. Results show that this model has good performance for predicting odor concentrations and odor frequencies.     

Airflow dispersion in unsaturated soil

Dispersion data is abundant for water flow in the saturated zone but is lacking for airflow in unsaturated soil. However, for remediation processes such as soil vapour extraction, characterization of airflow dispersion is necessary for improved modelling and prediction capabilities. Accordingly, gas-phase tracer experiments were conducted in five soils ranging from uniform sand to clay at air-dried and wetted conditions. The disturbed soils were placed in one-dimensional stainless steel columns, with sulfur hexafluoride used as the inert tracer. The tested interstitial velocities were typical of those present in the vicinity of a soil vapour extraction well, while wetting varied according to the water-holding capacity of the soils. Results gave dispersivities that varied between 0.42 and 2.6 cm, which are typical of values in the literature. In air-dried soils, dispersion was found to increase with the pore size variability of the soil. For wetted soils, particle shape was an important factor at low water contents, while at high water contents, the proportion of macroporous space filled with water was important. The relative importance of diffusion decreased with increasing interstitial velocity and water content and was, in general, found to be minor compared to mechanical mixing across all conditions studied.     

Transverse vertical dispersion in groundwater and the capillary fringe

Transverse dispersion is the most relevant process in mass transfer of contaminants across the capillary fringe (both directions), dilution of contaminants, and mixing of electron acceptors and electron donors in biodegrading groundwater plumes. This paper gives an overview on literature values of transverse vertical dispersivities alpha(tv) measured at different flow velocities and compares them to results from well-controlled laboratory-tank experiments on mass transfer of trichloroethene (TCE) across the capillary fringe. The measured values of transverse vertical dispersion in the capillary fringe region were larger than in fully saturated media, which is credited to enhanced tortuosity of the flow paths due to entrapped air within the capillary fringe. In all cases, the values observed for alpha(tv) were < 1 mm. The new measurements and the literature values indicate that alpha(tv) apparently declines with increasing flow velocity. The latter is attributed to incomplete diffusive mixing at the pore scale (pore throats). A simple conceptual model, based on the mean square displacement and the pore size accounting for only partial diffusive mixing at increasing flow velocities, shows very good agreement with measured and published data.     

Coal particle dispersion monitoring system

A monitoring system for coal panicle dispersion at coal storage yards is necessary to meet environmental standards for the operation of coal fired power plants. We have developed a system having three functions as follows:

• 1.(1) To measure coal particle concentrations at the first connecting part of belt conveyors.
• 2.(2) To predict occurrence of coal particle dispersion during stacking.
• 3.(3) To moisten the coal at the second connecting part of belt conveyors when coal particle dispersion occurs.

The generation of coal dispersion is determined by whether or not the hygroscopic moisture is greater than the critical hygroscopic moisture value for each coal type. Coal particle concentrations are measured using dust meters. In this report, the dust meter readings were related to emission rate of coal particle and dustiness index of coarse dust defined by ASTM D547-41 in order to predict occurrence of coal particle dispersion using dust meters.The adaptability of the system to real coal handling facilities was examined by a model which consisted of belt conveyors, a stacker, connecting parts and the monitoring system. As a result of these experiments, it was demonstrated that coal particle dispersion can be suppressed by means of wetting coal in response to dust meter readings.     

On the influence of the urban roughness sublayer on turbulence and dispersion

The concept of the urban roughness sublayer is discussed and this lowest atmospheric layer over a rough surface is shown to have a non-negligible vertical extension over typical urban surfaces. The existing knowledge on the turbulence and flow structure within an urban roughness sublayer is reviewed, focusing on the height dependence of turbulent fluxes and a scaling approach for turbulence statistics, such as velocity variances, in the above-roof part of the roughness sublayer. Finally, the implication of this turbulence and flow structure upon dispersion characteristics is investigated. The most prominent difference of explicitly taking into account the roughness sublayer in a dispersion simulation (as compared to assuming a `constant flux layer') is a clearly enhanced ground level concentration far downwind from the source. For the example of a tracer release experiment over a (sub) urban surface (Copenhagen) it is shown that introducing the roughness sublayer clearly improves the model performance.     

Development of a livestock odor dispersion model: part I. Model theory and development

A livestock odor dispersion model (LODM) was developed to predict mean odor concentration, odor frequency, instantaneous odor concentration, and peak odor concentration from livestock operations. This model is based on the Gaussian fluctuating plume model and has the ability to consider the instantaneous concentration fluctuations and the differences between odor and traditional air pollutants. It can predict odor frequency from the routine hourly meteorological data input and deal with different types of sources and multiple sources. Also, the relationship between odor intensity and odor concentration was incorporated into the model.     

Transverse dispersion of non-reactive tracers in porous media: a new nonlinear relationship to predict dispersion coefficients

Assessing the potential of natural attenuation in groundwater relies on the ability to predict and quantify the processes that occur in contaminant plumes. Transverse dispersion is a significant mass transfer mechanism for mixing of electron acceptors and donors and thus may control the lengths of steady state plumes. Laboratory experiments were carried out using a 2-dimensional acrylic glass tank filled with glass beads, quartz sand and field site material as porous media. Flow velocities and grain sizes were varied in order to cover a large range of Peclet numbers including typical field scenarios. The laboratory study was extended by a comprehensive literature search to compare the new results with earlier work. As a result we propose a new empirical relationship for prediction of transverse dispersion coefficients (Dt) which is based on the Peclet number (Pe). This new relationship indicates a nonlinear dependency on the flow velocity (nu a) and grain size (d), namely a relative decrease of the dispersion coefficient with increasing flow velocity in relatively fast flowing water: Dt/Daq=Dp/Daq+0.28(Pe)0.72 (with Pe=nu a d/Daq; Daq and Dp denote the aqueous and pore diffusion coefficients, resp.).     

Modeling of dispersion near roadways based on the vehicle-induced turbulence concept

A mathematical model is developed for dispersion near roadways by incorporating vehicle-induced turbulence (VIT) into Gaussian dispersion modeling using computational fluid dynamics (CFD). The model is based on the Gaussian plume equation in which roadway is regarded as a series of point sources. The Gaussian dispersion parameters are modified by simulation of the roadway using CFD in order to evaluate turbulent kinetic energy (TKE) as a measure of VIT. The model was evaluated against experimental carbon monoxide concentrations downwind of two major freeways reported in the literature. Good agreements were achieved between model results and the literature data. A significant difference was observed between the model results with and without considering VIT. The difference is rather high for data very close to the freeways. This model, after evaluation with additional data, may be used as a framework for predicting dispersion and deposition from any roadway for different traffic (vehicle type and speed) conditions.     

Modeling the ETEX plume dispersion with the Canadian emergency response model

The CANadian Emergency Response Model (CANERM) was used to simulate the dispersion resulting from the ETEX release of 23 October 1994. Dispersion simulations were done using three different data sets as meteorological input: the ECMWF/ETEX Data Set, data from the CMC Global Data Assimilation System, and results from a diagnostic execution of the Global Environmental Multiscale (GEM) model. Comparisons of the dispersion simulations are made with observed surface concentration data provided by the Joint Research Centre (JRC) of the European Commission. It is found that CANERM can simulate fairly well the main features of the cloud dispersion. The spatial and temporal evolution of the simulated cloud appear quite plausible, but a tendency to overestimate surface concentrations is apparent. The simulations provide a credible explanation for the two peaks observed at station NL01; the first peak appears to be associated with the passage of the head portion of the plume, while the second seems to be associated with the tail part. Verification scores indicate that the simulations using the ECMWF/ETEX data set and CMC global data are of equivalent quality. However, the simulations obtained using the GEM diagnostic fields are significantly better.     

Unsteady characteristics of the dispersion process in the vicinity of a pig barn. Wind tunnel experiments and comparison with field data

Two complementary methods, field experiments and physical modelling in a wind tunnel, have been used to investigate the dispersion of tracer-gas released from the ventilation system of a pig barn, under near-neutral stability conditions. In both cases, concentration fluctuations were measured and the deduced statistical results were compared. The choice of data processing applied to the time series of concentration was motivated by special issues in the assessment of odour annoyances: “where, how often, how long and how strong does it smell?” These features were described by the mean concentration distribution, the intermittency factor, the persistence and the 90-percentile. The good agreement between field and wind tunnel data confirmed the ability to replicate in wind tunnel the unsteady properties of a dispersion process, if the unsteady turbulent behaviour of the atmospheric boundary layer was properly modelled.A parametrical study of the influence on the dispersion process of the ratio between the exhaust velocity from the stack and the wind speed was then performed in wind tunnel. The fundamental outcome was that the near-field dispersion process under neutral stability conditions, despite the strong influence of the building wake, was for the most part driven by the meandering behaviour of the plume and not so much by the diffusion process.This study was also focused on the influence of the averaging time on the statistical results. The scatter generated by using dimensionless averaging times 200<T_a^*<400 (used during field experiments) instead of T_a^*→∞ (averaging time to ensure reproducible statistic results) was quantified in the wind tunnel. A degree of representativity of the results obtained from short-term samples, compared to fully converged statistical results was therefore assessed.     

Pathways and products of the degradation of PCBs by the sodium dispersion method

Nine polychlorinated biphenyl (PCB) congeners (2-chlorobiphenyl, 3-chlorobiphenyl, 4-chlorobiphenyl, 2,3,4-trichlorobiphenyl, 2,2',5,5'-tetrachlorobiphenyl, 2,3',4,4',5-pentachlorobiphenyl, 3,3',4,4',5-pentachlorobiphenyl, 2,2',4,4',5,5'-hexachlorobiphenyl, and decachlorobiphenyl) were dechlorinated by the sodium dispersion method (SD) at low temperature (60 degrees C). The dechlorination of 4-chlorobiphenyl was the fastest among the three monochlorobiphenyls. As for the other six congeners, we investigated the major dechlorination pathways. Although reaction selectivity was not very sensitive to the position of the chlorine substituent, the chlorines at the para position were slightly easier to dechlorinate than those at the ortho or meta positions. The decomposition rate increased with the total numbers of chlorine substituents. A chlorine situated between two other chlorines showed a high reactivity. When the numbers of chlorines on each of the phenyl rings were different, the reactions occurred on the more substituted ring. In the degradation of 4-chlorobiphenyl at elevated temperature (160 degrees C), we investigated the structures of the polymerized products and whether all the organic chlorinated compounds degraded finally or not. As for the dimers, p-quarterphenyl (QP) and m,p-QP were detected but not o-QP, m-QP, o,p-QP, o,m-QP, or the mono- to tetra-chlorinated QPs. Compounds with a molecular weight of 534.4183 or 758.6713 were detected. They were considered to have C40H54 or C56H86 as their molecular formula. The compounds were most probably the polymerized products resulting from coupling of hexadecane or two hexadecanes and two phenylcyclohexadienes. It was thought the dechlorination and the polymerization were the main reactions. All of many detected compounds were hydrocarbons without chlorines, and no peaks originating from organic chlorinated compounds were observed by mass spectroscopic (MS) methods.