From CAMS data to an air quality report: context beyond a short monitoring campaign
Why historical air quality matters, what CAMS represents, and how I built a platform to simplify scientific data requests, processing and reporting.
Read articleWe support project teams with environmental assessment, predictive modelling and technical review. Our focus is the link between project activities, sensitive receptors and practical mitigation.
EIA · AERMOD · CALPUFF · WRF
Good modelling begins with the right question and suitable data. We document inputs and assumptions, evaluate scenarios and explain what the results mean for your project.
Clear input data, documented assumptions and methods that can be reviewed.
Findings translated into mitigation options, study conclusions and technical responses.
Maps shown are illustrative visuals from the supplied ENVI image library.
Understand the project, identify sensitive receptors and agree the scope and input requirements.
Review the data, select suitable methods and evaluate project scenarios and mitigation options.
Explain the findings and limitations, prepare technical deliverables and support the review process.
A project description, location and current project stage are a good starting point. Layouts, source data and previous studies help us define the scope and identify data gaps.
Yes. We can review model inputs, assumptions and results, update scenarios and prepare technical responses to review comments.
Our services focus on studies, assessment and modelling. When measured data are required, we review data supplied by the project team or its appointed measurement specialist.
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