An Efficient Gaussian-Plume Multiple-Source Air Quality Algorithm

The information presented in this paper is directed to air pollution scientists with an interest in applying air quality simulation models. RAM is the three letter designation for this efficient Gaussian-plume multiple-source air quality algorithm. RAM is a method of estimating short-term dispersion using the Gaussian steady-state model. This algorithm can be used for estimating air quality concentrations of relatively stable pollutants for averaging times from an hour to a day in urban areas from point and area sources. The algorithm is applicable for locations with level or gently rolling terrain where a single wind vector for each hour is a good approximation to the flow over the source area considered. Calculations are performed for each hour. Hourly meteorological data required are wind direction, wind speed, stability class, and mixing height. Emission information required of point sources consists of source coordinates, emission rate, physical height, stack gas volume flow and stack gas temperature. Emission information required of area sources consists of south-west corner coordinates, source area, total area emission rate and effective area source height. Computation time is kept to a minimum by the manner in which concentrations from area sources are estimated using a narrow plume hypothesis and using the area source squares as given rather than breaking down all sources to an area of uniform elements. Options are available to the user to allow use of three different types of receptor locations: 1 ) those whose coordinates are input by the user, 2) those whose coordinates are determined by thé model and are downwind óf significant point and area sources where maxima are likely to occur, and 3) those whose coordinates are determined by the model to give good area coverage of a specific portion of the region. Computation time is also decreased by keeping the number of receptors to a minimum.     

Why air quality in the Alps remains a matter of concern. The impact of organic pollutants in the alpine area

In the middle of Europe, the Alps form a geographical and meteorological trap for atmospheric pollutants including volatile and semi-volatile organic compounds emitted in the surrounding lowlands. This is due to their barrier effects, high precipitation rates, and low ambient temperatures. Also the pollutants emitted in the cities inside the Alps spread in the region depending on orographic and meteorological conditions. Although a number of studies on the distribution and effect of pollutants in the Alps has been published, comprehensive information on potential hazards, and ways to improve this sensible environment are lacking. This opinion paper is the result of a discussion during the Winterseminar of the AlpsBioCluster project in Munich. It summarizes the current literature and presents some case studies on local pollution sources in the Alps, and the possibility of using biomonitoring techniques to assess critical pollution loads and distributions.     

The Limitations of Air Quality Standards

This paper describes a diffusion model designed to permit calculation of seasonal average concentrations of an air pollutant, in particular, sulfur dioxide. The calculations can encompass multiple sources and multiple receptors. For each receptor location the model sums the effect of all sources over a wide range of meteorological conditions. Input data include source pollutant emissions, source configuration and location, receptor location, and meteorological data expressed as a joint frequency distribution of wind direction, wind speed, stability. To determine the model’s accuracy, concentration estimates for St. Louis, Mo., are compared with measured SO₂ concentrations. The overall correlation with observed data is satisfactory. A computer program to handle the numerous calculations was written in Fortran IV language for use on an IBM 1130 computer.     

Mapping air quality zones for coastal urban centers

This study presents a new method that incorporates modern air dispersion models allowing local terrain and land–sea breeze effects to be considered along with political and natural boundaries for more accurate mapping of air quality zones (AQZs) for coastal urban centers. This method uses local coastal wind patterns and key urban air pollution sources in each zone to more accurately calculate air pollutant concentration statistics. The new approach distributes virtual air pollution sources within each small grid cell of an area of interest and analyzes a puff dispersion model for a full year’s worth of 1-hr prognostic weather data. The difference of wind patterns in coastal and inland areas creates significantly different skewness (S) and kurtosis (K) statistics for the annually averaged pollutant concentrations at ground level receptor points for each grid cell. Plotting the S-K data highlights grouping of sources predominantly impacted by coastal winds versus inland winds. The application of the new method is demonstrated through a case study for the nation of Kuwait by developing new AQZs to support local air management programs. The zone boundaries established by the S-K method were validated by comparing MM5 and WRF prognostic meteorological weather data used in the air dispersion modeling, a support vector machine classifier was trained to compare results with the graphical classification method, and final zones were compared with data collected from Earth observation satellites to confirm locations of high-exposure-risk areas. The resulting AQZs are more accurate and support efficient management strategies for air quality compliance targets effected by local coastal microclimates.

Implications: A novel method to determine air quality zones in coastal urban areas is introduced using skewness (S) and kurtosis (K) statistics calculated from grid concentrations results of air dispersion models. The method identifies land–sea breeze effects that can be used to manage local air quality in areas of similar microclimates.     

The CCMS air pollution model intercomparison study

Four air pollution transport models were tested and compared in an area of ~ 400 × 400 km². Three models were Eulcrian grid models, the fourth a Lagrangian trajectory model. The data base (emissions and meteorological observations) were essentially the same for all models. Differences in model output could only be a result of the different (numerical) structure of the models and of the differences in processing of the meteorological data. It turned out that the latter was the major source of differences in model results. Generally there was a satisfactory correlation between model results and observed concentrations. Mainly due to the negligence of transport of pollutants into the modelling region, predicted concentrations were considerably lower than the observed.     

Surface Air Pollutant Concentration Frequency Distributions: Implications for Urban Modeling

With the development of ambient air quality standards (AAQS), the need arises to describe the characteristics of regional surface air-pollutant concentration frequency distributions. In the evaluation of land use plans, numerous agencies will be concerned with evaluating the effectiveness of emission zoning and/or control actions. On a regional basis, one means of performing this assessment lies in determining the changes in the pollutant frequency distributions resulting from control actions.

This study presents new data concerning the surface air-pollutant concentration frequency distributions observed for area sources and continuous point sources, and compares these distributions with those of the pertinent meteorological variables describing the transport and diffusion of the pollutant. The observed surface air pollutant frequency distributions are compared to those corresponding to simple modeling concepts from either an urban area source or a continuous point source. For an urban source and a relatively inert pollutant like CO, we found that the observed frequency distribution for CO surface air concentration parallels the approximately log-normal frequency distribution of the reciprocal of the wind speed. We show that the constant relating these two well-correlated frequency distributions can be determined either experimentally or with a numerical simulation model of air pollution. The usefulness of numerical models in air pollution is discussed.     

A model study for ambient air quality analysis using routine meteorological observations

In the present study, more realistic and easily adaptable input parameters have been used with a view to investigating the long-range air quality analysis for the dispersion of air pollutants emitted from an area source with a multiple box model. The model formulation has been discussed at length for the ground level sources when convective conditions prevail. The routine meteorological observations have been used for the computation of sensible surface heat flux, friction velocity and mixing depth. A radiation model provides the estimates of the sensible surface heat flux. Based on the similarity theory, an iterative procedure has been adopted for the estimation of friction velocity which provides a coupling of radiation computation and the surface layer of the planetary boundary layer through surface heat flux expression. The important parameters—wind speed and eddy diffusivity profiles—have been derived and have been used to obtain the concentration patterns as hourly averages. The procedure could be easily adopted where observed meteorological parameters may be used for studying the dispersal of pollutants from the ground level sources.     

Simulating Urban-Scale Air Pollutants and Their Predicting Capabilities over the Seoul Metropolitan Area

Abstract

Urban-scale air pollutants for sulfur dioxide, nitrogen dioxide, particulate matter with aerodynamic diameter >10 μm, and ozone (O₃) were simulated over the Seoul metropolitan area, Korea, during the period of July 2-11, 2002, and their predicting capabilities were discussed. The Air Pollution Model (TAPM) and the highly disaggregated anthropogenic and the biogenic gridded emissions (1 km × 1 km) recently prepared by the Korean Ministry of Environment were applied. Wind fields with observational nudging in the prognostic meteorological model TAPM are optionally adopted to comparatively examine the meteorological impact on the prediction capabilities of urban-scale air pollutants. The result shows that the simulated concentrations of secondary air pollutant largely agree with observed levels with an index of agreement (IOA) of >0.6, whereas IOAs of ～0.4 are found for most primary pollutants in the major cities, reflecting the quality of emission data in the urban area. The observationally nudged wind fields with higher IOAs have little effect on the prediction for both primary and secondary air pollutants, implying that the detailed wind field does not consistently improve the urban air pollution model performance if emissions are not well specified. However, the robust highest concentrations are better described toward observations by imposing observational nudging, suggesting the importance of wind fields for the predictions of extreme concentrations such as robust highest concentrations, maximum levels, and >90th percentiles of concentrations for both primary and secondary urban-scale air pollutants.     

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.     

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.     

Sensitivity Analysis of Dispersion Models for Point and Area Sources

The body of information presented in this paper is directed to air quality managers in industry and government contemplating modeling emissions from complex sources under the bubble concept.

Point and area source algorithms of PAL, RAM, and ISC-ST were analyzed to show the effect of various input assumptions on model output. Several important parameters were varied individually; receptor grid spacing, emission release height, area source size and source type. Each of these parameters was varied over a range of values while all other modeling parameters, both physical and meteorological, were held constant. The outputs of each model are plotted for easy comparison.

Results indicate that it would be inappropriate to make certain assumptions regarding source characteristics without knowing the behavior of each model. The graphs show how the model predictions can vary for different input parameters when applied to point and area sources. The paper presents general rules of thumb for evaluating model results for many applications such as the bubble concept, emissions banking, offsets, and new source reviews. The results serve as a guide in selecting and using models for both point and area sources.     

Investigation of respirable suspended particulate trend and relevant environmental factors in Hong Kong downtown areas

As the addressing of high demand of good air quality in urban area, a study on air pollutant dispersion and distribution resulting from vehicular exhaust emission is strongly required. In particular, vehicular exhaust emission has become a major air pollution source in metropolitan city like Hong Kong, which is characterized with the heavy, dense traffic flow and the limited land resources. Respirable suspended particulate (RSP) is one of main pollutants resulted from vehicular exhaust emission in urban area. Hence, in this study, we focus on analyzing the variation of RSP levels including diurnal, monthly and annual patterns at selected roadsides in Hong Kong during the period of 1998--2005. Furthermore, the relationships between RSP level and the relevant meteorological factors such as temperature, rainfall and wind conditions in Hong Kong territory have been discussed as well.     

The Influence of Annual Meteorological Variations On Regional Air Pollution Modeling: A Case Study of Allegheny County,Pennsylvania

The influence of year-to-year meteorological variations on the prediction of annual average ground-level pollutant concentrations has been examined via case studies of Allegheny County, Pa. Twenty-two stability wind roses representing different averaging intervals of from one to seven years were employed in the Air Quality Display Model to predict annual average SO₂ concentrations in two multiple source sub-basins, and from two single point sources representing industrial and utility boiler stacks. Effects of annual meteorological variations were manifested by changes in the magnitude of peak concentrations, the location of peak concentrations, and the geographic distribution of pollutants. For fixed rates of emission, the peak annual average SO₂ ground-level concentration varied by an average of up to 33% of highest values for point sources and 17% for sub-basin complexes. In both cases, there was relatively little change in the location of peak concentration, though occasional directional shifts were noted. In contrast, marked variations were noted in the geographic area exposed to annual average concentrations in excess of several selected values. To aid in regional planning, several methods were formulated which considerably reduced the uncertainty in predicting peak annual concentration for varying degrees of historical data on regional stability wind rose. These methods are-especially applicable to analysis of control strategies directed at attaining annual ambient air quality standards which nominally must never be exceeded.     

Seasonal source-receptor relationships in a petrochemical industrial district over northern Taiwan

This study investigated the relationships between meteorological data, pollution sources, and receptors over northern Taiwan. During the intensive sampling period in summer 1992, the weather was controlled predominantly by a Pacific subtropical high and by Typhoon Mark. During the other intensive sampling period in winter 1993, while a cold frontal system approached Taiwan, the northeasterly winds prevailed most of the time. The local circulation such as land-sea breeze only developed under weak synoptic environment. Particle concentrations and element composition in winter were higher than in summer. This can be attributed to the high convection of air mass, which leads to the vertical dispersion of pollutants in summer. In addition to the subtropical high pressure, typhoons are frequently accompanied with high-wind speeds and unstable weather conditions that also dilute and eliminate the pollutants. In winter, the prevailing northeasterlies might carry pollutants from Midland China. Furthermore, the anticyclone system develops a stagnant condition that easily leads to pollutant accumulation. In this case, the wind direction affected the source contribution of the receptor and the PM10 displays a higher correlation with coarse and fine particulate than meteorological parameters in summer. In addition, the mixing height shows a high correlation with PM10 in winter.     

A Multivariable Model for Atmospheric Dispersion Predictions

In conjunction with a 15-month air quality survey of Jacksonville, Fia., a mathematical model has been developed to describe the dispersion of atmospheric pollutants. The source inventory used with the model was compiled, in part, from the data obtained from the sampling of all major sources within the area. The major sources were considered separately from the one-mile square area sources which accounted for the remainder of the emissions. Meteorological data was recorded continuously in the city including vertical temperature observations to 750 ft. The model was compiled in FORTRAN and can be used for both gaseous and particulate pollutants, by utilizing proper decay rates. The variant nature of meteorological parameters and emission rates are considered. The ground level concentrations of several pollutants which were determined for 24 hr periods at 11 sites and continuously at two other sites were used to check the model. A limited tracer study was carried out in conjunction with the project.     

Simulating urban-scale air pollutants and their predicting capabilities over the Seoul metropolitan area

Urban-scale air pollutants for sulfur dioxide, nitrogen dioxide, particulate matter with aerodynamic diameter > or = 10 microm, and ozone (O3) were simulated over the Seoul metropolitan area, Korea, during the period of July 2-11, 2002, and their predicting capabilities were discussed. The Air Pollution Model (TAPM) and the highly disaggregated anthropogenic and the biogenic gridded emissions (1 km x 1 km) recently prepared by the Korean Ministry of Environment were applied. Wind fields with observational nudging in the prognostic meteorological model TAPM are optionally adopted to comparatively examine the meteorological impact on the prediction capabilities of urban-scale air pollutants. The result shows that the simulated concentrations of secondary air pollutant largely agree with observed levels with an index of agreement (IOA) of >0.6, whereas IOAs of approximately 0.4 are found for most primary pollutants in the major cities, reflecting the quality of emission data in the urban area. The observationally nudged wind fields with higher IOAs have little effect on the prediction for both primary and secondary air pollutants, implying that the detailed wind field does not consistently improve the urban air pollution model performance if emissions are not well specified. However, the robust highest concentrations are better described toward observations by imposing observational nudging, suggesting the importance of wind fields for the predictions of extreme concentrations such as robust highest concentrations, maximum levels, and >90th percentiles of concentrations for both primary and secondary urban-scale air pollutants.     

Assessing sensitivity of source term estimation

Source term estimation algorithms compute unknown atmospheric transport and dispersion modeling variables from concentration observations made by sensors in the field. Insufficient spatial and temporal resolution in the meteorological data as well as inherent uncertainty in the wind field data make source term estimation and the prediction of subsequent transport and dispersion extremely difficult. This work addresses the question: how many sensors are necessary in order to successfully estimate the source term and meteorological variables required for atmospheric transport and dispersion modeling?The source term estimation system presented here uses a robust optimization technique – a genetic algorithm (GA) – to find the combination of source location, source height, source strength, surface wind direction, surface wind speed, and time of release that produces a concentration field that best matches the sensor observations. The approach is validated using the Gaussian puff as the dispersion model in identical twin numerical experiments. The limits of the system are tested by incorporating additive and multiplicative noise into the synthetic data. The minimum requirements for data quantity and quality are determined by an extensive grid sensitivity analysis. Finally, a metric is developed for quantifying the minimum number of sensors necessary to accurately estimate the source term and to obtain the relevant wind information.     

基于遗传算法的大气污染总量控制新方法

提出一种利用遗传算法进行大气污染总量控制的新方法,并以柳州市SO2总量控制为例说明这种方法的具体运用.遗传算法具备自适应全局搜索寻优特点,从控制点浓度推算源强分布,该源强分布满足总量控制的根本要求.该方法的具体实现是:将区域内各污染源的排放量编码为染色体,让染色体群体在模拟的进化环境下按生物进化规律进行优胜劣汰的自然选择,经过若干代的进化,最终得到的最优个体即代表最佳的源强分布.研究结果表明,这种方法是有效的和可行的.     

Estimation of the exchange of sulphur pollution over the Balkan region in 1995–2000

The Bulgarian dispersion model 'Eulerian Model for Air Pollution' (EMAP) is used to estimate the sulphur pollution over the Balkan region for the period 1995–2000. A subdomain of the European Monitoring and Evaluation Programme (EMEP) grid is chosen containing 12 countries. The computational grid in this domain has a space step of 25 km, twice as fine as the EMEP grid. The former operational DWD 'Europa-Model' is used as meteorological driver. The source input is the official EMEP emission data. Monthly calculations are made having the last moment fields from the previous month as initial conditions for the next one. The boundary conditions are set to zero, so the influence of other European sources is not accounted for in this study. According to the EMEP methodology, multiple runs are made setting every time the sources of various countries to zero. The impact of every country in the pollution of all others is estimated.     

Root growth responses of Anagallis arvensis L., primulaceae to air pollution

The root growth response to air pollution in populations of Anagallis arvensis growing about 0.5, 2, 6, 12 and 20 km leeward from a power plant complex varied with the level of pollution, age of the stand and meteorological conditions. The roots were more affected by the pollutants at a young stage and the loss in net primary productivity was proportional to the pollution level. The populations up to 2 km from the source of pollution completed their life cycle quickly. The coal consumption rate at the power plant, relative humidity, wind direction and other environmental factors were found to influence the degree of growth response to air pollution.