Holistic air pollution control

This system feeds of modern numerical weather prediction (NWP) data and combines Mesocscale meteorological models and urban feature modeling (anthropogenic heat fluxes, redistribution of eddies, urban mixing height, building impact on wind etc.,) with micro climate CFD modelling to deliver relaible urban scale meterological data.

This module seamlessly combines nested grid models with stack, street canyon & CFD models to make the modeling system comprehensive, handling any resolution. All 14 Air pollutants are modeled effectively. This includes the major pollutants like PM2.5/10, Ozone, NOX etc., as well as air Toxins such as Xylene and some Polycyclic aromatic hydrocardons.

This system manages execution of guided Monte-Carlo simulations accounting for input/output uncertainties across multiple model variants for emissions, metrological and air quality. Active AI objects at grid level constantly calibrate model outputs against available measurements to ensure the credibility of estimates within confidence levels.

This System provides all the tools required to solve more policy oriented problems, such as estimating the costs required to achieve a desired level of air quality. This helps design the most cost-effectivce abatement strategies in different areas of the same region ( urban vs rural) using cost-curves, cost-benefit analysis based on precise source receptor matrixes.