AIR-EIA was funded under INFO2000
by the European Commssion (PUB-1221).

AIR-EIA:

air pollution and environmental impact assessment:
the multimedia information source

Analytical Methods

There are several groups of analytical tools in the domain of Environmental Impact Assessment and Air Quality Management:

  • Specific tools to support EIA, usually based on checklists and data management with limited analytical or modeling capabilities; rule based expert system that can guide through an entire EIA process are one prototypical example.

  • Simulation models for the individual impact categories; in the air pollution domain, these are models that translate emission scenarios into ambient air pollutant concentrations or immissions, typically dispersion models.

  • Generic data analysis tools, including a range of statistical tools such as time series analysis including advanced methods such as neural networks, genetic algorithms, or machine learning approaches that attempt to derive forecasts from the analysis of historical observation data.


Environmental Impact Assessment: an introduction

Member States shall adopt all measures necessary to ensure that, before consent is given, projects likely to have significant effects on the environment by virtue, inter alia, of their nature, size or location are made subject to a requirement for development consent and an assessment with regard to their effects (97/11/EC).

A short summary of the Austrian EIA legislation described by Umweltverträglichkaeitsprüfungsgesetz BGBl 1993/697 idF BGBl 1996/773 is based on:

Bergthaler, W., Weber, K., and Wimmer, J. (1998)
Die Umweltverträglichkeitsprüfung. Praxishandbuch für Juristen und Sachverständige. 633 pp., Manz, Wien.

An on-line PowerPoint based slide show provides an overview of
Environmental Impact Assessment, its history, p hilosophy, and the basic methodology of the process.

EIA home page

Environmental Impact Assessment:
Background and State of the Art

From: Fedra, K., Winkelbauer, L. and Pantulu. V.R. (1991)
Expert Systems for Environmental Screening.
  An Application in the Lower Mekong Basin.   RR-91-19. International Institute for Applied Systems Analysis. A-236l Laxenburg, Austria. 169p.

Human activities, such as those that relate to large scale water resources development projects, construction, agriculture, energy, industry and development projects, considerably affect the natural environment. These effects or impacts occur during the construction phase, the operational life time of a project, and in many cases, as with waste disposal sites, may continue long after closure of a plant or site or the completion of a development activity. Consumption of natural resources, including space, water, air and biota, and the generation of wastes including the dissipation of energy and noise, usually lead to a degradation of the natural, and above all, the human environment.

more .....

  Air Quality Simulation Models

An essential tool for environmental impact assessment in any domain, and certainly for air quality impacts, are simulation models. They provide the capability to forecast the effects of any emission source that may be part of a project subject to an environmental impact assessment.

Numerous air quality models have been developed and are described in the scientific literature, many of them available in the public domain, as well as a number of complete modeling systems that combine the basic models with monitoring data, GIS, and various assessment functions. Fir an example of an integrated system for air quality assessment and management combining monitoring and modeling, visit the AirWare System home page !


Model inventory


  Generic Tools: GIS, data analysis

The various EIA methods draw on a broad range of tools, including many general purpose data processing and analytical methods.

The most important ones among them are:

  • geographical information systems (GIS), for the capture, management, display, and analysis of georeferenced data; basic methods include overlay and buffer analysis.

  • statistical analysis, with basic tools such as time series analysis, histograms, regression, analysis of variance, cluster analysis, etc.


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