A Practical Numerical Algorithm to Compute Steady-State Ground Level Concentration by a K-Model

A numerical algorithm to compute steady-state ground level concentration from elevated sources by means of a K-model which takes into account the spatial variability of wind and diffusivity and neglects horizontal diffusion is discussed. The boundary value problem to be treated, also for a point source, is always reduced to a two dimensional one and it is solved on an optimized grid. In this way the proposed method is made computationally comparable with the classical Gaussian plume model

Abatement of Air Pollutants and Cogeneration: Search for an Optimal Solution

In this paper atmospheric diffusion modelling and nonlinear optimization techniques are used for the analysis of minimum cost alternatives of air pollution control strategies. Two cases are considered: a) control of air pollution from a large point source and b) reduction of existing pollution levels in an urban area utilizing the heat cogenerated by a thermal power plant for district heating. As to a) a program has been built to compute the minimum cost function for the chosen abatement techniques (including stack height) under the constraint of keeping the ground level concentration of N pollutants (gaseous or particulates) at specified values. Cost functions for stack height and abatement techniques are input to the program. As an example, results are presented for the control of two different pollutants controlled by two abatement techniques plus stack height. As to b) an interactive program has been developed to identify minimum cost network for heat conveyance necessary to supply a set of residential areas to achieve a given reduction of pollution in the urban area. Results are presented for the city of Vienna

An Analysis of Finite Difference and Galerkin Techniques Applied to the Simulation of Advection and Diffusion of Air Pollutants from a Line Source

A finite difference and a Galerkin type scheme are compared with reference to a very accurate solution describing time dependent advection and diffusion of air pollutants from a line source in an atmosphere vertically stratified and limited by an inversion layer. The accurate solution was achieved by applying the finite difference scheme on a very refined grid with a very small time step. Grid size and time step were defined according to stability and accuracy criteria discussed in the text. It is found that for the problem considered, the two methods can be considered equally accurate. However, the Galerkin method gives larger areas of small errors close to the source, This was assumed to be partly due to the different way the source term is taken into account by the two methods. An improvement of the accuracy of the finite difference scheme was achieved by approximating, at every step, the contribution of the source term by a Gaussian puff moving and diffusing with velocity and diffusivity of the source location, instead of utilizing a stepwise function for the numerical approximation of the delta function representing the source term

Statistical Analysis of Winter Sulphur Dioxide Concentration Data in Vienna

The paper describes two nonlinear regression models, applied to winter daily SO2 concentration data and to the corresponding meteorological data from the metropolitan area of Vienna. The first model accounts for the role of wind speed and temperature (a proxy for emissions due to residential heating) on average SO2 concentration in the area. The second regression has an additional wind direction input and tries to point out the contribution by the industrial emissions (located primarily near the south-eastern border of the area) to concentration in the most polluted subarea. Both models offer a satisfactory fitting performance (e.g., correlations around 0.85 between observed and regression values). However, since model validation is a critical point for regressions, sensitivity tests of model fitting performance are carried out by using various data sets for the estimation of regression coefficients. One of such tests points out that there is an "optimal length" of the data set to be used, namely neither a too short set nor a set including "too past" data offer a satisfactory fitting quality

Real-Time Forecasting of Air Pollution Episodes in the Venetian Region. Part I: The Advection-Diffusion Model. Part II: The Kalman Predictor

The object of this overall research, which has an expected duration of two years is to set up a scheme for predicting ground-level pollutant concentrations for real-time control purposes (i.e. the action to be taken at the emission sources in the presence of forthcoming high pollutant events). The forecasting scheme is described, together with its application to sulphur dioxide pollution in the Venetian lagoon area. The scheme is based on a complex mathematical model to be run on a computer and receiving at the beginning of each interval of time all the information (about the meteorological and emission situation) required for the prediction. The type of control action which should be taken on the basis of such a forecast is the object of this part of the research

Validation and Physical Parametrization of a Gaussian Climatological Model Applied to a Complex Site

Seasonal sulphur-dioxide concentrations have been simulated in a topographically complex-coastal site, by means of a Gaussian type model. The model diffusion equation has been parametrized on the basis of the results from a series of field experiments conducted in the area to characterize the dynamic and thermodynamic properties of the local atmosphere. The validity of the adopted model formulation and physical parametrization has been discussed by comparing simulated and measured concentration values separately for unstable, neutral and stable situations, and by testing the model sensitivity with respect to changes in the parameters used. The analysis has shown that definition of the model physical parameters as indicated by the field experiments leads to a very satisfactory agreement between the calculated and measured concentrations. Therefore the model can be considered a suitable tool to implement air quality strategies in the area on a climatological basis. The study has been applied to the complex coastal sites of La Spezia, Italy, for the period March 1975 - February 1977

Acid rain in Europe : A framework to assist decision making.

The ratification of the Geneva Convention on Transboundary Air Pollution in March of 1983 showed that nations of Eastern and Western Europe were determined to control the problem of acid rain. In the same year, IIASA offered its analytical skills to the international community to help solve the problem. It did so by entering into official cooperation with the UN Economic Commission of Europe (ECE) which is responsible for implementing the convention. As part of this cooperation IIASA is developing a computer model which can be used by decision makers to evaluate policies for controlling the impact of acid rain in Europe. In addition, we hope that our work will help identify gaps in understanding the acid rain problem and stimulate the research necessary to overcome these gaps. This paper describes the status of the acid rain model after approximately one year's work. It also presents some examples of how the model is used and the type of information it provides

Integrated Analysis of Acidification in Europe.

This paper presents the interim status of the RAINS model developed at IIASA. The principle purpose of the model is to provide a tool to assist decision-makers in their evaluation of strategies to control acidification of Europe's environment. Model design emphasizes user comprehension and ease of use. The overall framework of RAINS consists of three linked compartments: "Pollutant Generation," "Atmospheric Processes" and "Environmental Impact." Each of these compartments can be filled by different substitutable submodels. The four submodels currently available are "Sulfur Emissions," EMEP Sulfur Transport," Forest Soil Acidity" and "Lake Acidity." Submodels which deal with NOx emissions and deposition and other environmental impacts will be added to the model. To operate the model, a user must select (1) an energy pathway, (2) a pollution control strategy and (3) an environmental impact indicator. This information is inputed to RAINS and yields a "scenario" which is a consistent set of energy pathway, sulfur emissions, forest soil acidity and lake acidity. In an iterative fashion, a model user can quickly evaluate the consequences of many different alternatives to control acidification in Europe

Atmospheric Diffusion Modeling and Optimal Air Quality Control Strategies

Atmospheric diffusion models are used in a rapidly increasing number of studies for controlling and/or managing air quality. In general these studies try to find the least-cost control strategy by solving the following mathematical program: select x (1) thatminimizes γ(x) (2) subjectto C(x,q)<cx (