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CAREAIR: A Computer Aided Modeling Toolbox to Generate and Analyze Emission Data in High Temporal and Spatial
Richard K Laing1, Burkhard Wickert1, Rainer Friedrich1
1a Institute of Energy Economics and the Rational Use of Energy , University of Stuttgart , Stuttgart, Germany.
High-resolution emission data is crucial for air quality strategies. The CAREAIR software tool provides a flexible modeling toolbox for calculating emissions from various sources, aiding environmental research.
Area of Science:
- Environmental Science
- Atmospheric Chemistry
- Computational Modeling
Background:
- Accurate emission data at high temporal and spatial resolutions is essential for evaluating air quality improvement strategies.
- Existing measurement capabilities are insufficient to capture all emission sources and pollutant species.
- Computer-aided modeling is necessary for generating comprehensive emission datasets.
Purpose of the Study:
- Introduce CAREAIR, a novel software tool, to the international community focused on emission inventories and air quality.
- Present CAREAIR as a flexible modeling toolbox for developing emission models.
- Demonstrate the utility of CAREAIR in various air quality research projects.
Main Methods:
- CAREAIR is a flexible modeling toolbox, not a single model.
- It utilizes a database with data and formulas for manipulation via flexible operators.
- Emission calculations are performed by combining multiple data manipulation operators.
Main Results:
- CAREAIR enables the implementation of models for calculating emissions of various pollutants with high spatial and temporal resolution.
- The toolbox's flexibility allows it to meet diverse project demands.
- Successful applications in Germany, Europe, and Nigeria demonstrate its appropriateness.
Conclusions:
- CAREAIR is an effective and adaptable instrument for developing emission models.
- It supports the creation of detailed emission inventories necessary for air quality management.
- The toolbox facilitates research and strategy development in air quality improvement.
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