Keywords
heterogeneous networks, space time models, calibration, particulate matter, wastewater, heavy metals, bio lters
Start Date
1-7-2006 12:00 AM
Abstract
Statistical sensitivity analysis is shown to be a useful technique for assessing both multivariate environmental computer models and environmental statistical spatio-temporal models in the perspective of risk assessment. Methods are reviewed and extended to cover with two applications which are reported as case studies. The first, related to waste water bio litters for heavy metals, is aimed at assessing the input in influence on both environmental and economical variables. The second, related to spatio-temporal models for air quality monitoring networks, is intended to study the in influence of each station to the model performance.
Sensitivity Analysis for Environmental Models and Monitoring Networks
Statistical sensitivity analysis is shown to be a useful technique for assessing both multivariate environmental computer models and environmental statistical spatio-temporal models in the perspective of risk assessment. Methods are reviewed and extended to cover with two applications which are reported as case studies. The first, related to waste water bio litters for heavy metals, is aimed at assessing the input in influence on both environmental and economical variables. The second, related to spatio-temporal models for air quality monitoring networks, is intended to study the in influence of each station to the model performance.
