From environmental measurement to human health.
Two research contributions exploring how scientific data can inform environmental decisions and help anticipate health risks.
Estimating actual company greenhouse-gas emissions.
Combining atmospheric observations, physical models and economic information to estimate emissions attributable to individual companies.
Atmospheric observations
Satellite and ground measurements, gas concentrations and weather data.
Physical modelling
Solar forcing, meteorology, atmospheric transport, chemistry and dispersion.
Sources & sinks
Company emissions and natural carbon uptake by land, vegetation and oceans.
Economic modelling
Company activity, production, incentives, economic assumptions and strategic interactions.
Company emissions
Inverse modelling and data reconciliation to estimate emissions attributable to companies.
Company-level greenhouse-gas emissions estimates
Model-derived estimates of emissions attributable to individual companies, combining atmospheric observations, physical modelling and economic information.
Forecasting the health effects of air pollution.
Translating air-quality forecasts into population exposure estimates, potential health impacts and preventive information.
Pollution forecasts
Predict pollutant concentrations across locations and future time periods.
Population exposure
Combine pollution forecasts with population distributions and geographical information.
Health impacts
Apply epidemiological relationships to estimate potential health risks.
Preventive alerts
Communicate predicted risks to support exposure reduction and public-health decisions.
Anticipated health risks
Air-quality forecasts translated into population exposure estimates, potential health impacts and preventive information.
Environmental intelligence becomes meaningful when it supports better decisions.
This research reflect an interest in environmental measurement, scientific modelling, economics and human wellbeing.