This paper demonstrates the importance of accounting for the uncertainties associated with input data when using air dispersion models in environmental impact assessment (EIA) studies. EIA studies are developed at the project stage, prior to the construction and operation of the particular facility under assessment. As such, dispersion models are applied with expected an
Uncertainty is virtually unavoidable in environmental impact assessments (EIAs). From the literature...
Uncertainty analysis assesses the uncertainty in numerical model outputs that arises from ambiguity ...
In a lot of last years industrial licensing procedures in Germany, the yet unanswered question of cl...
Numerous numerical models are developed to predict long range transport of hazardous air pollution i...
AbstractThe objectives of paper are the application of uncertainty and sensitivity analysis methods ...
Abstract: The atmospheric dispersion modelling of pollutants is based on models, but also on data an...
The objectives of this paper are the application of uncertainty and sensitivity analysis methods in ...
Atmospheric dispersion modelling can be used to estimate the environmental impact of releases to air...
Regarding air quality, odours have been repeatedly ranked as the number one reason for public compla...
Air quality is far from being a new concern but remains an issue demanding increasing attention. The...
For an Environmental Impact Statement (EIS) to effectively contribute to decision-making, it must in...
International audienceDuring the pre-release and early phase of an accidental release of radionuclid...
In the framework of the European project CONFIDENCE, Work Package 1 (WP1) focused on the uncertainti...
Air being an important part of the environment is always required to be in a satisfactory condition ...
The validation and reliability of atmospheric dispersion models are important concerns for both mode...
Uncertainty is virtually unavoidable in environmental impact assessments (EIAs). From the literature...
Uncertainty analysis assesses the uncertainty in numerical model outputs that arises from ambiguity ...
In a lot of last years industrial licensing procedures in Germany, the yet unanswered question of cl...
Numerous numerical models are developed to predict long range transport of hazardous air pollution i...
AbstractThe objectives of paper are the application of uncertainty and sensitivity analysis methods ...
Abstract: The atmospheric dispersion modelling of pollutants is based on models, but also on data an...
The objectives of this paper are the application of uncertainty and sensitivity analysis methods in ...
Atmospheric dispersion modelling can be used to estimate the environmental impact of releases to air...
Regarding air quality, odours have been repeatedly ranked as the number one reason for public compla...
Air quality is far from being a new concern but remains an issue demanding increasing attention. The...
For an Environmental Impact Statement (EIS) to effectively contribute to decision-making, it must in...
International audienceDuring the pre-release and early phase of an accidental release of radionuclid...
In the framework of the European project CONFIDENCE, Work Package 1 (WP1) focused on the uncertainti...
Air being an important part of the environment is always required to be in a satisfactory condition ...
The validation and reliability of atmospheric dispersion models are important concerns for both mode...
Uncertainty is virtually unavoidable in environmental impact assessments (EIAs). From the literature...
Uncertainty analysis assesses the uncertainty in numerical model outputs that arises from ambiguity ...
In a lot of last years industrial licensing procedures in Germany, the yet unanswered question of cl...