Near-field dispersion modeling for regulatory applications

This paper evaluates the application of dispersion models to estimate near-field pollutant concentrations in two case studies. The Industrial Source Complex Short-Term Model (ISCST3) was evaluated with hexavalent chromium measurements collected within 100 m of two facilities in Barrio Logan, San Diego, CA. ISCST3 provided reasonable estimates for higher pollutant concentrations but underestimated lower concentrations. To understand the observed distribution of concentrations in Barrio Logan, a recently conducted tracer experiment was analyzed. The tracer, sulfur hexafluoride, was released at ambient temperature from an urban facility at the University of California at Riverside, and concentrations were measured within 20 m of the source. Modeling results indicated that Industrial Source Complex-Plume Rise Model Enhancement and American Meteorological Society/U.S. Environmental Protection Agency Regulatory Model-Plume Rise Model Enhancement overestimated high concentrations and underestimated low concentrations. A diagnostic study with a simple Gaussian dispersion model that incorporated site-specific meteorology was used to evaluate model results. This study found that incorporating lateral meandering for nonbuoyant urban plumes in Gaussian dispersion models could improve concentration estimates even when downwash is not considered. Incorporating a meandering component in ISCST3 resulted in improvements in estimating hexavalent chromium concentrations in Barrio Logan. Credible near-source concentration estimates depend on accurate characterization of emissions, onsite micrometeorology, and a method to account for lateral meandering in the near field.     

Inverse modeling to estimate LNAPL plume release timing

Methodologies are presented for dating releases of light nonaqueous phase liquids (LNAPLs) using an inverse modeling approach with simple analytical models. Models for LNAPL plume migration are presented to predict LNAPL plume velocity in the unsaturated and saturated zones as a function of basic soil and fluid properties. A relative mobility factor is introduced for LNAPL movement at the water table that depends primarily on the van Genuchten n parameter (related to the breadth of the soil pore size distribution) and the magnitude of water table fluctuations. Estimated LNAPL plume velocities compare reasonably with more rigorous numerical models, which may be used in cases where data availability warrant the greater effort entailed.Two methods of estimating release timing and its uncertainty are investigated. A direct estimation method is described that determines travel time for a single observed travel distance based on estimated soil and fluid properties. Release date uncertainty may be determined using the first order (FO) or Monte Carlo (MC) methods. The second method for estimating release date involves nonlinear parameter estimation utilizing distance vs. time measurements and other data.A case study is presented for a field site where independent estimates of release timing were obtained from a numerical modeling analysis. Release timing estimates based on direct inversion of the analytical timing model agree well with the numerical analysis. Results for a second field site indicate that release date confidence limits estimated by the FO method, assuming log-normally distributed travel times, are close to values determined by the MC method, which makes no assumption regarding the form of the travel time probability distribution.Results for a hypothetical problem indicate that LNAPL velocity and travel time may be accurately estimated if sufficient data on travel distance vs. time are available. Incorporating prior information on relevant soil and fluid properties into the objective function reduces the uncertainty in release date if prior estimates are accurate. However, biased prior estimates may lead to over- or underestimation of release date uncertainty. Simultaneous estimation of soil and fluid properties and release date is possible if prior information is available to condition the parameter estimates.     

Pore-scale modeling of dispersion in disordered porous media

We employ a direct pore-level model of incompressible flow that uses the modified moving particle semi-implicit (MMPS) method. The model is capable of simulating both unsteady- and steady-state flow directly in microtomography images of naturally-occurring porous media. We further develop this model to simulate solute transport in disordered porous media. The governing equations of flow and transport at the pore level, i.e., Navier-Stokes and convection-diffusion, are solved directly in the pore space mapped by microtomography techniques. Three naturally-occurring sandstones are studied in this work. We verify the accuracy of the model by comparing the computed longitudinal dispersion coefficients against the experimental data for a wide range of Peclet numbers, i.e., 5×10(-2)相似文献   

室内空气中挥发性有机物的释放特征分析

房屋装修后1周、1个月、3个月、6个月、12个月采集其室内空气样品进行甲醛、苯系物浓度的测定,分析释放规律;另选某处新居于装修后24 h、1周、1个月且密闭状态下采集室内空气中总挥发性有机化合物(TVOC)样品分析研究.结果表明,房屋装修后12个月内甲醛浓度随时间呈非线性递减,多项式回归方程为:y=0.277 13-0.199 72x+0.079 74x2-0.011 67x3+0.000 525 61x4,其中y为甲醛质量浓度,mg/m3;x为时间,月;各苯系物浓度也随时间呈逐渐下降趋势,且通过SPSS13.0软件进行Spearman相关性分析,发现各苯系物间显著相关;装修后不同时间段室内空气中TVOC组分发生变化,随着房屋封闭时间延长,TVOC浓度超标严重;TVOC组分的增多或减少是由于室内装修材料TVOC释放的增强或减弱,以及门窗缝隙所带来的微弱通风造成,无二次污染物的生成.     

Application of air pollution dispersion modeling for source-contribution assessment and model performance evaluation at integrated industrial estate-Pantnagar

Source-contribution assessment of ambient NO₂ concentration was performed at Pantnagar, India through simulation of two urban mathematical dispersive models namely Gaussian Finite Line Source Model (GFLSM) and Industrial Source Complex Model (ISCST-3) and model performances were evaluated. Principal approaches were development of comprehensive emission inventory, monitoring of traffic density and regional air quality and conclusively simulation of urban dispersive models. Initially, 18 industries were found responsible for emission of 39.11 kg/h of NO₂ through 43 elevated stacks. Further, vehicular emission potential in terms of NO₂ was computed as 7.1 kg/h. Air quality monitoring delineates an annual average NO₂ concentration of 32.6 μg/m³. Finally, GFLSM and ISCST-3 were simulated in conjunction with developed emission inventories and existing meteorological conditions. Models simulation indicated that contribution of NO₂ from industrial and vehicular source was in a range of 45-70% and 9-39%, respectively. Further, statistical analysis revealed satisfactory model performance with an aggregate accuracy of 61.9%.     

PM10 dispersion modeling for Treasure Valley, Idaho

The recorded exceedances of the 24-hr PM10 National Ambient Air Quality Standard (NAAQS) in Treasure Valley, Idaho, have been associated with prolonged stagnation periods during the winter. A comprehensive modeling study of PM10 impact in Treasure Valley was performed to support the State Implementation Plan (SIP). The study included base-year and short-term episodic conditions. The ISCST3 (Industrial Source Complex Short Term 3) model, using the base-year meteorology and gridded emissions of mobile sources, point sources, and wood burning as input, generally agreed well with measurements in both temporal patterns and annual averages. The WYNDvalley model was evaluated using monitoring data and was used to simulate the PM10 impact for episodic exceedances during stagnant winter conditions. An emission inventory was prepared for a base year (1995) and then extrapolated to the years 2000, 2005, 2010, and 2015 in order to determine air quality planning requirements. According to the simulations using base-year emissions and meteorology, exceedances are not expected. However, exceedances at some stations could be expected using projected emissions and episodic meteorology. Results from emission control strategies we developed indicate that mobile-source emissions have the most significant impact; reduction of 25% would be needed to eliminate the simulated exceedances in all projected years.     

Crop loss assessment for California: modeling losses with different ozone standard scenarios

Crop yield losses were estimated for ambient O3 concentrations and for a series of potential O3 air quality standards for California, including the current statewide 1-h oxidant (O3) standard of 0.10 ppm (196 microg m(-3)), 12-h growing season averages, and other models. A model for statewide losses was developed using hourly O3 data for all sites in the State, county crop productivity data, and available O3 concentration-yield loss equations to determine potential yield losses for each crop in each county in California for 1984. Losses were based on comparison to an estimated background filtered air concentration of 0.025 or 0.027 ppm, for 12 or 7 h, respectively. Potential losses due to ambient air in 1984 were estimated at 19% to 25% for dry beans, cotton, grapes, lemons, onions, and oranges. Losses of 5% to 9% were estimated for alfalfa and sweet corn. Losses of 4% or less were estimated for barley, field corn, lettuce, grain sorghum, rice, corn silage, spinach, strawberries, sugar beets, fresh tomatoes, processing tomatoes, and wheat. Implementation of either a modified rollback to meet the current 1 h California O3 standard (0.10 ppm) or a three-month, 12-h growing season average of 0.045 ppm was necessary to produce large reductions in potential crop losses.     

A Test Reference Year (TRY) approach to gas dispersion in the atmosphere

For environmental analysis such as the dispersion of pollutants in the atmosphere, it is essential to have meteorological data that are relevant for a long period. In this paper, we explore the possibility of using an environmental Test Reference Year (TRY), i.e., a set of real, contemporaneous and hourly meteorological variables, 'extracted' from a hourly series of at least 10 years, for modelling pollutant dispersion in the atmosphere. The classical approach, based on a statistical data set, implies the loss of important information such as the real correlation between the different meteorological variables, and this implies crude approximation in the simulation results. We compare the simulation results with the long hourly 10 years data set (which can be considered a 'brute force' approach, since it requires a huge amount of data and time processing, but it is here considered the most severe benchmark) and with the statistical data set commonly used. It is shown that the results obtained using the TRY have a good agreement with the ones obtained with the simulation of the 10 years and they are also much better than those obtained using the statistical data set.     

Odor emission rate estimation of indoor industrial sources using a modified inverse modeling method

Odor emission rates are commonly measured in the laboratory or occasionally estimated with inverse modeling techniques. A modified inverse modeling approach is used to estimate source emission rates inside of a postdigestion centrifuge building of a water reclamation plant. Conventionally, inverse modeling methods divide an indoor environment in zones on the basis of structural design and estimate source emission rates using models that assume homogeneous distribution of agent concentrations within a zone and experimentally determined link functions to simulate airflows among zones. The modified approach segregates zones as a function of agent distribution rather than building design and identifies near and far fields. Near-field agent concentrations do not satisfy the assumption of homogeneous odor concentrations; far-field concentrations satisfy this assumption and are the only ones used to estimate emission rates. The predictive ability of the modified inverse modeling approach was validated with measured emission rate values; the difference between corresponding estimated and measured odor emission rates is not statistically significant. Similarly, the difference between measured and estimated hydrogen sulfide emission rates is also not statistically significant. The modified inverse modeling approach is easy to perform because it uses odor and odorant field measurements instead of complex chamber emission rate measurements.     

Study of expiratory droplet dispersion and transport using a new Eulerian modeling approach

Understanding of droplet nuclei dispersion and transport characteristics can provide more engineering strategies to control transmission of airborne diseases. Droplet dispersion in a room under the conventional well-mixed and displacement ventilation is simulated. Two droplet nuclei sizes, 0.01 and 10 μm, are selected as they represent very fine and coarse droplets. The flow field is modeled using k–ε RNG model. A new Eulerian drift-flux methodology is employed to model droplet phase. Under the conventional ventilation scheme, both fine and coarse droplets are homogeneously dispersed within approximately 50 s. Droplet nuclei exhibit distinctive dispersion behavior, particularly for low airflow microenvironment. After 270 s of droplet emission, gravitational settling influences the dispersion for 10 μm droplets, and concentration gradient can still be observed for displacement ventilation.     

Particulate matter emission rates from beef cattle feedlots in Kansas-reverse dispersion modeling

Open beef cattle feedlots emit various air pollutants, including particulate matter (PM) with equivalent aerodynamic diameter of 10 microm or less (PM10); however limited research has quantified PM10 emission rates from feedlots. This research was conducted to determine emission rates of PM10 from large cattle feedlots in Kansas. Concentrations of PM10 at the downwind and upwind edges of two large cattle feedlots (KS1 and KS2) in Kansas were measured with tapered element oscillating microbalance (TEOM) PM10 monitors from January 2007 to December 2008. Weather conditions at the feedlots were also monitored. From measured PM10 concentrations and weather conditions, PM10 emission rates were determined using reverse modeling with the American Meteorological Society/U.S. Environmental Protection Agency Regulatory Model (AERMOD). The two feedlots differed significantly in median PM10 emission flux (1.60 g/m2-day for KS1 vs. 1.10 g/m2-day for KS2) but not in PM10 emission factor (27 kg/1000 head-day for KS1 and 30 kg/1000 head-day KS2). These emission factors were smaller than published U.S. Environmental Protection Agency (EPA) emission factor for cattle feedlots.     

Estimating micrometeorological inputs for modeling dispersion in urban areas during stable conditions

We examine the performance of three methods to estimate the surface friction velocity and the Monin–Obukhov (MO) length in stable conditions. Estimates from these methods are compared with measurements made at two urban sites: the Wilmington site located in the middle of an urban area, and the VTMX site located on a sloping, smooth area in Salt Lake City. The first method uses the mean wind at a single height (Single U or SU), the second uses the wind speed at a single level and the temperature difference between two levels (U delta T or UDT), and the third method uses two levels of wind speed and temperature (delta U delta T or DUDT). The performance of the SU and UDT methods in estimating u_* are comparable. The SU method yields better estimates of the MO length than the UDT method does. The DUDT method performs poorly in estimating both u_* and L. The major conclusions of this study are that (1) measurements of mean winds and temperatures at one or two levels at an urban location can provide adequate estimates of micrometeorological variables required in modeling dispersion in the stable boundary layer, and (2) methods based on using differences in temperatures and velocities between two levels can provide unreliable estimates of these variables because these differences can be overwhelmed by inevitable uncertainties in the measurement of mean variables.     

Dissociation of sulfur hexafluoride tracer gas in the presence of an indoor combustion source

As an odorless, nontoxic, and inert compound, sulfur hexafluoride (SF6) is one of the most widely used tracer gases in indoor air quality studies in both controlled and uncontrolled environments. This compound may be subject to reactions with water vapor under elevated temperature to form acidic inorganic compounds such as HF and H2SO4. Thus, in the presence of unvented combustion sources such as kerosene heaters, natural gas heaters, gas log fireplaces, candles, and lamps, the SF6 dissociation may interfere with measurements of the emissions from these sources. Tests were conducted in a research house with a vent-free natural gas heater to investigate these potential interferences. It was observed that the heater operation caused about a 5% reduction of SF6 concentration, which can be an error source for the ventilation rate measurement and consequently the estimated pollutant emission rates. Further analysis indicates that this error can be much greater than the observed 5% under certain test conditions because it is a function of the ventilation flow rate. Reducing the tracer gas concentration has no effect on this error. A simple theoretical model is proposed to estimate the magnitude of this error. The second type of interference comes from the primary and secondary products of the SF6 dissociation, mainly H2SO4, SO2, HF, and fine particulate matter (PM). In the presence of approximately 5 ppm SF6, the total airborne concentrations of these species increased by a factor of 4-10. The tests were performed at relatively high SF6 concentrations, which is necessary to determine the interferences quantitatively. The second type of interference can be significantly reduced if the SF6 concentration is kept at a low ppb level.     

A new Lagrangian particle model for the simulation of dense gas dispersion

A Lagrangian stochastic model (MicroSpray), able to simulate the airborne dispersion in complex terrain and in presence of obstacles, was modified to simulate the dispersion of dense gas clouds. This is accomplished by taking into account the following processes: negative buoyancy, gravity spreading and the particle's reflection at the bottom computational boundary. Elevated and ground level sources, continuous and instantaneous emissions, time varying sources, plumes with initial momentum (horizontal, vertical or oblique in any direction), plumes without initial momentum are considered. MicroSpray is part of the model system MSS, which also includes the diagnostic MicroSwift model for the reconstruction of the 3-D wind field in presence of obstacles and orography. To evaluate the MSS ability to simulate the dispersion of heavy gases, its simulation performances are compared in detail to two field experiments (Thorney Island and Kit Fox) and to a chlorine railway accident (Macdona). Then, a comprehensive analysis considering several experiments of the Modelers Data Archive is presented. The statistical analysis on the overall available data reveals that the performance of the new MicroSpray version for dense gas releases is generally reliable. For instance, the agreement between concentration predictions and observations is within a factor of two in the 72% up to 99% of the occurrences for the case studies considered. The values of other performance measures, such as correlation coefficient, geometric mean bias and geometric variance, mostly set in the ranges indicated as good-model performances in the specialized literature.     

Integrated catchment modeling for nutrient reduction: scenarios showing impacts, potential, and cost of measures

A hydrological-based model (HBV-NP) was applied to a catchment (1900 km2) in the southern part of Sweden. Careful characterization of the present load situation and the potential for improved treatment or reduced soil leaching were analyzed. Several scenarios were modeled to find strategies to reach the Swedish environmental goals of reducing anthropogenic nitrogen load by 30% and phosphorus load by 20%. It was stated that the goals could be reached by different approaches that would affect different polluters and social sectors. However, no single measure was enough by itself. Instead, a combination of measures was necessary to achieve the goals. The nitrogen goal was the most difficult to attain. In order to be cost-effective, these measures should be applied to areas contributing the most to the net loading of the sea. This strategy could reduce the costs by 70%-80% when compared with implementing the measures in the entire catchment. Integrated catchment models may thus be helpful tools for reducing costs in environmental control programs.     

Wind direction bias in generating wind roses and conducting sector-based air dispersion modeling

Certain widely used wind rose programs and air dispersion models use an overly simple data-transfer algorithm that induces a directional bias in their output products. The purpose of this paper is to provide a revised algorithm that corrects the directional bias that occurs from the aliasing that occurs when the sector widths used to report wind direction data are on the same order of magnitude, but not equal, to the sector widths used in the wind direction summaries. The directional bias issue arises when output products in 16 direction sectors (22.5 degrees each) are produced from wind direction data reported in terms of 36 sectors (10 degrees each). The result directional bias affects the results of simulations of air and surface concentrations using widely applied air dispersion models. Datasets or models with the directional bias discussed here give consistent positive biases (approximately 30%) for cardinal direction sectors (north, south, east, and west) and consistent negative biases for all of the other sectors (around -10%). Data summary and air dispersion programs providing outputs in direction sectors that do not match the observational sectors need to be checked for this bias. A revised data-transfer algorithm is provided that corrects the directional bias that can occur in transferring wind direction data between different sector widths.     

Measurement and three-dimensional modeling of airflow and pollutant dispersion in an undersea traffic tunnel

Airflow and pollutant dispersion in a cross-harbor traffic tunnel were experimentally and numerically studied. Concentrations of the gaseous pollutants CO, NOx, and total hydrocarbons (THC) at three axial locations in the tunnel, together with traffic flow rate, traffic speed, and types of vehicle were measured. Three-dimensional (3D) turbulent flow and dispersion of air pollutants in the tunnel were modeled and solved numerically using the finite volume method. Traffic emissions were modeled accordingly as banded line sources along the tunnel floor. The results reveal that cross-sectional concentrations are nonuniformly distributed and that concentrations rise with downstream distance. The piston effect of vehicles alone can provide 9-23% dilution of air pollutants in the tunnel, compounded to a 23-74% dilution effect according to the ventilation condition.     

Assimilating concentration observations for transport and dispersion modeling in a meandering wind field

Assimilating concentration data into an atmospheric transport and dispersion model can provide information to improve downwind concentration forecasts. The forecast model is typically a one-way coupled set of equations: the meteorological equations impact the concentration, but the concentration does not generally affect the meteorological field. Thus, indirect methods of using concentration data to influence the meteorological variables are required. The problem studied here involves a simple wind field forcing Gaussian dispersion. Two methods of assimilating concentration data to infer the wind direction are demonstrated. The first method is Lagrangian in nature and treats the puff as an entity using feature extraction coupled with nudging. The second method is an Eulerian field approach akin to traditional variational approaches, but minimizes the error by using a genetic algorithm (GA) to directly optimize the match between observations and predictions. Both methods show success at inferring the wind field. The GA-variational method, however, is more accurate but requires more computational time. Dynamic assimilation of a continuous release modeled by a Gaussian plume is also demonstrated using the genetic algorithm approach.     

Use of an indoor air quality model (IAQM) to estimate indoor ozone levels

Currently, outdoor ozone levels in many U.S. cities exceed the primary health-based national ambient air quality standard. While outdoor ozone levels are an important measure of the severity of those exceedances, people typically spend more than 80 percent of their time indoors, where ozone levels are lower. Indoor ozone levels range from 10 to 80 percent of outdoor levels, with many people receiving a substantial portion of their ozone exposure while indoors. This paper uses an indoor air quality model (IAQM) to estimate indoor ozone levels by microenvironment type (home, office, and vehicle) and configuration (windows open, windows closed, older construction, weatherized, and air conditioned). The formulation of IAQM is discussed, along with specification of model parameters for ozone. The multicompartment version of IAQM is described, with a single-compartment version used for the analyses. IAQM-calculated ozone indoor-outdoor ratios compare well with research-reported values. Results indicate that ozone peak-concentration indoor-outdoor ratios range as follows: home--0.65 (windows open), 0.36 (air conditioned), 0.23 (typical construction, windows closed), and 0.05 (energy-efficient construction, windows closed); office--0.82 (heating, ventilation and air conditioning systems supplying 100 percent outdoor air), 0.60 (typical HVAC), and 0.32 (energy-efficient HVAC); and vehicle--0.41 (85 mph), 0.33 (55 mph), and 0.21 (10 mph). Analysis results are presented to characterize IAQM's sensitivity to assumed model parameters.     

基于神经网络的活性污泥系统建模及其控制

针对松江污水厂污水处理活性污泥系统，采用神经网络技术进行建模试验研究，在对实际运行数据剔除异常数据后，将样本数据随机分成训练样本、检验样本和测试样本。用试凑法确定合理的神经网络隐层节点数，用检验样本实时监控训练过程从而避免“过训练”现象，用多次改变网络初始连接权值求得全局极小点，从而建立了泛化能力较好的基于神经网络的活性污泥系统数学模型。利用建立的神经网络模型，对活性污泥系统运行情况的仿真与控制进行了分析研究。示例研究表明：神经网络技术能较好地应用于活性污泥系统的建模与控制，有很好的理论与实践意义。