Minimum turbulence assumptions and u* and L estimation for dispersion models during low-wind stable conditions

The U.S. Environmental Protection Agency (EPA) short-distance dispersion model, AERMOD, has been shown to overpredict by a factor of as much as 10 when compared with observed concentrations from continuous releases at the Oak Ridge, TN (OR), and Idaho Falls, ID (IF), field experiments during stable periods when wind speeds often dropped below 1 m/sec. Some of this overprediction tendency can be reduced by revising AERMOD's meteorological preprocessor's parameterizations of the friction velocity, u _* , during low-wind stable conditions, thus increasing the calculated σ _v and σ _w and hence the lateral and vertical dispersion rates. Observations show that as the mean wind speed approaches zero at night, there is always significant σ _v and σ _w over time periods of 15 to 60 min, while standard Monin–Obukhov Similarity Theory (MOST) predicts that σ _v and σ _w will approach zero. This paper focuses on the u _* estimation methods and the minimum turbulence (σ _v and σ _w ) assumptions in AERMOD (beta option 4) and two widely used U.S. operational dispersion models, AERMOD (v12345) and SCICHEM. The U.S. EPA has provided results of its tests with the OR and IF data, with its base AERMOD version and its December 2012 modified versions, which assume adjustments to the low-wind u _* and increases in the minimum σ _v parameterization. SCICHEM has relatively small mean bias for both data sets. The revised AERMOD shows much less mean bias, agreeing more with SCICHEM.

Implications:

Suggestions are made for improvements to dispersion models such as AERMOD to correct overpredictions during light-wind stable conditions. Methods for estimating u_*, L, and the minimum turbulence parameters (σ_v and σ_w) are reviewed and compared. SCICHEM and the current operational version and an optional beta version (December 2012) of AERMOD are evaluated with tracer data from low-wind stable field experiments in Idaho Falls and Oak Ridge. It is seen that the operational version of AERMOD overpredicts by a factor of 2 to 10, while the optional beta version of AERMOD and SCICHEM have much less bias.     

An analytical model for the transport,dispersion and elimination of air pollutants emitted from a point source

The solution of the complete transport diffusion equation with a first order reaction term is obtained for a continuous source. A deposition velocity boundary condition is met at the ground and, optionally, a similar leakage velocity boundary condition can be met at the base of a superjacent layer. The identification of a preliminary transformation of the dependent variable that eliminates the transport and sink terms permits particularly simple analytic solutions to be obtained by means of conventional Laplace transform, Green's function methods. Prior solutions are compared with these results. A linearisation of the solution without an overlying layer provides a simple extension of the conventional Gaussian plume result that permits account to be taken of pollutant settling velocity, of absorption at the ground and of a first order reaction. The accuracy of this linearisation is assessed. Examples of the application of the methods to calculation of the distribution of particulates and of the formation of nitrogen dioxide in a plume are given.     

Simulation of short-range diffusion experiment in low-wind convective conditions

A previously obtained analytical solution to model the short-range dispersion of pollutants in low winds from surface releases has been used to simulate diffusion tests conducted during winter in weakly convective conditions at the Indian Institute of Technology (IIT) Delhi. The turbulence parameterization based on friction velocity has been tested to simulate diffusion experiment. Such a parameterization in this study is considered justifiable on two counts: (1) prevailing meteorological and dispersion conditions have been generally of weakly unstable type as indicated by values of Monin–Obukhov length and bulk Richardson number, (2) uncertainties associated with the application of convective velocity based similarity parameterization to simulation of diffusion experiment at IIT Delhi, resulting in significant underprediction in most of the cases (Atmos. Environ. 30 (1996a) 1137). With this parameterization, the model simulations have improved considerably and compare reasonably well with the observations. Further, the results from a simple Gaussian model have been included for comparison. This study is in continuation of the work done earlier to simulate near-source dispersion in weak winds.     

A simple model for the dispersion of pollutants from a road tunnel portal

The dispersion of pollutants from a roadway tunnel portal is mainly determined by the interaction between the ambient wind and the jet stream from the tunnel portal. In principal, Eulerian microscale models by solving the conservation equations for mass, momentum, and energy, are thus able to simulate effects such as buoyancy etc. properly. However, for engineering applications such models need too much CPU time, and are not easy to handle by non-scientific personnel. Only a few dispersion models, applicable for regulatory purposes, have so far appeared in the literature. These models are either empirical models not always applicable for different sites, or they do not capture important physical effects like buoyancy phenomena. Here, a rather simple model is presented, which takes into account most of the important processes considered to govern the dispersion of a jet stream from portals. These are the exit velocity, the buoyancy, the influence of ambient wind direction fluctuations on the position of the jet stream, and traffic induced turbulence. Although the model contains some heuristic elements, it was successfully tested against tracer experiments taken near a motorway tunnel portal in Austria. The model requires relatively little CPU time. Current limitations of the model include the neglect of terrain, building, and vehicle effects on the dispersion, and the neglect of the horizontal dispersion arising from entrainment of ambient air in the jet stream. The latter could lead to an underestimation of plume spreads for higher wind speeds. The validation of the model will be the focus of future research. The experimental data set is also available for the scientific community.     

An analytical diffusion model for long distance transport of air pollutants

A steady-state two-dimensional diffusion model suitable for predicting ambient air pollutant concentrations averaged over a long time period (e.g., month, season or year) and resulting from the transport of pollutants for distances greater than about 100 km from the source is described. Analytical solutions are derived for the primary pollutant emitted from a point source and for secondary pollutant formed from it. Depletion effects, whether due to wet or dry deposition or chemical conversion to another species, are accounted for in these models as first order processes. Thus, solutions for multiple point sources may be superimposed.In this model the time-averaging of the random trajectories of pollutant-contaminated air parcels is represented by horizontal diffusion in a steady, two-dimensional flow field of the time-averaged wind. The resulting concentration isopleths for a point source show significant dispersion both upwind and cross wind of the source with respect to the mean wind field.The analytical theory for the dispersion of a primary pollutant is compared with the numerical predictions of a plume trajectory model for the case of steady emission from a point source. Good overall agreement between the two models is achieved whether or not depletion by wet and dry deposition is included.The theory for the dispersion of a secondary pollutant is compared with measurements of the annual average sulfate concentration in the U.S. Calculations are carried out using SO₂ emissions from electric power plants in the United States as a source inventory. Using optimum values of the dispersion parameters, the correlation coefficient of observed and calculated ambient concentrations is 0.87 for the eastern United States and 0.69 for the western region. The optimum dispersion parameters used are comparable to values quoted in the literature.The horizontal length scale characterizing the sulphate concentration distribution from a single source is about 500 km, being noticeably larger than that characterizing the primary (sulfur dioxide) distribution. Using optimum dispersion parameters, a point source of 33 kg s⁻¹ of sulfur dioxide would give rise to a maximum annual average sulfate concentration of 1 μ m⁻³.A calculation of annual average SO₂ concentrations in the United States is carried out using previously derived optimal values of the parameters from the sulfate calculation. The resulting isopleths are similar to measured values in the eastern U.S.     

developing a practical dispersion model for an air quality region

A series of computer models have been developed to predict air quality in the New York/New Jersey/Connecticut Air Quality Region. Efforts have been directed at models which have a shorter time scale than climatological models, and which are capable of providing better recommendations for effective abatement and planning, but use input data presently available.

The basic dispersion model for these investigations is a steady-state,nondivergent Gaussian-type model. A modified inventory of SO₂ sources,based on published data for the New York/New Jersey/Connecticut Air Quality Region, was prepared for use with the model. The basic model has been subjected to various internal sensitivity analyses, in which was isolated the variation produced in the pollutant concentration by a given change in each of the factors that contribute, e.g., wind speed, wind direction,mixing depth, stability conditions, source strengths, and grid size for the area sources.

To date, validation tests of the model have been made against the July and August 1969 data for the ten telemetering stations of the New York City Aerometric Network. Hourly as well as averaged concentrations were considered. Various sets of meteorological data from the network stations and the three area airports, were compared and tested. Additional tests, particularly for the winter season, are needed to substantiate the preliminary conclusions suggested by the results to date.

Considerable insight into the relative importance of model components has been acquired from the sensitivity studies. Furthermore the validation results lend support to the belief that a reasonably simple, practical dispersion model can be developed for the region.     

连云港市大气污染物时间序列的长程相关性分析

运用R/S分析(Rescaled Range Analysis)方法对连云港市3个大气环境定位监测点近10年来的SO2、NOx和TSP序列数据进行了时间序列的长程相关性分析.结果表明,连云港市SO2、NOx和TSP月均值序列的Hurst指数在0.500～1.000,表现出明显的长程相关性,并且这种相关性程度的强弱随着城市功能区的不同而表现出一定的差异.研究结果对于认识连云港市城市大气环境质量变化过程和科学制定环保决策具有重要意义.     

大同盆地复杂地形下近场大气污染物扩散模型选取研究

基于大同盆地地形和气象站数据对山区复杂地形下的近地面风场特征进行分析,发现大同盆地内特殊的地形构造所形成的气流通道对其主导风向存在明显影响.在不开展实地气象观测、仅引用周边气象站数据的条件下,CALPUFF模拟的电厂处西南、东北风向风频分别为40.5％、14.9％,AERMOD模拟的电厂处西南、东北风向风频分别为19....     

Comparison among air pollutants, meteorological conditions and some chemical parameters in the transplanted lichen Usnea amblyoclada

The response of Usnea amblyoclada (Müll. Arg.) Zahlbr. to real concentrations of atmospheric pollutants measured by two automatic monitoring stations, was studied in Córdoba City, Argentina. The influence of different weather conditions on the biomonitor's response was also assessed. The concentration of chlorophyll a, chlorophyll b, hydroperoxy-conjugated dienes, and malondialdehyde were quantified in lichen thalli collected from a clean area and in transplanted thalli after 1 month of exposure in an urban area, from April to October, 1996. The dry weight/fresh weight, chlorophyll b/chlorophyll a and phaeophytin a/chlorophyll a ratios were also calculated. Data sets were evaluated by two-way analysis of variance and correlation analysis. It was observed that hydroperoxy-conjugated dienes, malondialdehyde, chlorophylls, and pigment degradation increase during winter-time, when higher levels of suspended particles, non-methane hydrocarbons, hydrogen sulfide and ozone were also measured. These findings would be connected mainly with meteorological conditions, as most pollutants did not exceed prescribed threshold levels.     

Analysis of air quality data near roadways using a dispersion model

We used a dispersion model to analyze measurements made during a field study conducted by the U.S. EPA in July–August 2006, to estimate the impact of traffic emissions on air quality at distances of tens of meters from an eight-lane highway located in Raleigh, NC. The air quality measurements consisted of long path optical measurements of NO at distances of 7 and 17 m from the edge of the highway. Sonic anemometers were used to measure wind speed and turbulent velocities at 6 and 20 m from the highway. Traffic flow rates were monitored using traffic surveillance cameras. The dispersion model [Venkatram, A., 2004. On estimating emissions through horizontal fluxes. Atmospheric Environment 38, 2439–2446] explained over 60% of the variance of the observed path averaged NO concentrations, and over 90% of the observed concentrations were within a factor of two of the model estimates.Sensitivity tests conducted with the model indicated that the traffic flow rate made the largest contribution to the variance of the observed NO concentrations. The meteorological variable that had the largest impact on the near road NO concentrations was the standard deviation of the vertical velocity fluctuations, σ_w. Wind speed had a relatively minor effect on concentrations. Furthermore, as long as the wind direction was within ±45° from the normal to the road, wind direction had little impact on near road concentrations. The measurements did not allow us to draw conclusions on the impact of traffic-induced turbulence on dispersion. The analysis of air quality and meteorological observations resulted in plausible estimates of on-road emission factors for NO.     

Evaluating the use of occupational standards for controlling toxic air pollutants

Currently, the U.S. Environmental Protection Agency has established air standards for relatively few chemicals. As a result, state agencies are faced with controlling air contaminants for a large number of chemicals posing potential public health threats. Use of occupational standards as a basis for deriving ambient air guidelines is a method used by states to control air toxics. This standard development approach is reviewed by considering the differences in the health basis and numerical values which often occur among the occupational standards set by OSHA, NIOSH and ACGIH. This study indicated that careful selection should be made of the most appropriate occupational standard to use to protect public health. A comparison is made of chemicals regulated by various state air toxic programs using occupational standards lowered by a safety factor to concentrations established by the U.S. EPA. It was found that the air guidelines vary, but the degree of stringency can be comparable.     

An experimental verification of a theoretical model for the dispersion of a stack plume heavier than air

Experiments were carried out in a windtunnel to test the theoretical model for the dispersion of a stack plume heavier than air developed by Ooms et al. (1974, First Int. Symp. on Loss Prevention and Safety Promotion in the Process Industries, The Hague). Particular attention was paid to the initial conditions which have to be supplied in order to make model calculations possible. A good agreement between experimental results and model predictions was found for the plume path and the density distribution along the plume axis. The velocity distribution inside the plume was less well predicted.     

An autonomic station for measuring air pollutants in remote areas

An automatic station for measuring tropospheric ozone in remote sites is described. The electrical power is generated by a photovoltaics generator system. A modern end-to-end remote data acquisition system comprising intermediate storage, preprocessing and communication of measured data (mean half hourly data on ozone concentration, wind velocity and wind direction, temperature, pressure) via the ARGOS satellite enables a quasi on-line observation of sensor signals to be made in remote areas at reasonable costs.     

修订版大气导则与现行大气导则推荐模式实例对比验证分析

介绍了现行大气导则推荐预测模式的不足及修订版大气导则推荐模式AERMOD与ADMS的特点,并分析了不同推荐模式的功能及适用范围.以美国环境保护署两个试验场(Clifty Creek(简单地形)和Epri Bowline(建筑物下洗))的数据资料为基础,分别用修订版大气导则推荐模式AERMOD与ADMS及现行大气导则推荐模式计算小时浓度、日均浓度及年均浓度,并采用统计法(最大值比较法、高端值比较法、相对偏差比较法)和图形法(Q-Q对比图)进行模式比较分析.结果表明,在简单地形下,3种预测模式小时浓度预测精度接近,修订版大气导则推荐模式在可靠性上要优于现行大气导则推荐模式;在考虑建筑物下洗的复杂条件下,AERMOD、ADMS模式的预测结果普遍比现行大气导则推荐模式要好;现行大气导则推荐模式无法应用于计算建筑物下洗的模拟条件.     

Prediction of atmospheric dispersion of pollutants in an airport environment

In this article we discuss the development of a methodology to predict atmospheric turbulent dispersion of pollutants generated from air traffic in an airport. It is based on the Lagrangian stochastic model (LSM), developed by Das and Durbin [2005. A Lagrangian stochastic model for dispersion in stratified turbulence, Physics of Fluids 17, 025109]. The approach is via the backward trajectory formulation of the model. The sources and receptors in an airport type problem are modeled as spheres and procedures have been derived for concentration calculation by both forward and backward trajectory methods. Some tests are performed to highlight certain features of the method. The turbulence statistics that are required as input are provided in terms of similarity profiles. The airport domain is partitioned to make the required search algorithms efficient. Pollutant concentration profiles are calculated over a range of meteorological data.     

Neural modelling of the spatial distribution of air pollutants

In this paper, a new method to calculate the average spatial distribution of air pollutants based on diffusive sampling measurements and artificial neural networks evaluation is presented. Most established methods like interpolation algorithms are inflexible or limited in considering important distribution parameters such as emission sources or land use. Of special interest are air quality measurements since they provide a direct view on the actual pollutant level. With diffusive samplers, the average concentration of many gaseous species over a large area can be determined simultaneously. During a project in Cyprus, NO₂ diffusive samplers were exposed at 270 sites in six month-long campaigns throughout one year providing the database for the model described in this paper. A multilayer perceptron was trained with the NO₂ measurement data and distribution parameters like population density and meteorological parameters using a 1 × 1 km grid covering Cyprus. The best fit could be achieved with an emissions inventory including previously simulated concentration plumes and population density data as input nodes for the neural network, resulting in realistic maps of the annual average distribution of NO₂ in Cyprus.