Modelling environmental risk

Investigation of the Benzene Concentration and Distribution in Tehran Using Geographic Information System Modelling

Introduction and purpose: Air pollution has been recognized as the most important environmental risk factor worldwide. Benzene which is one of the four pollutants attributed to BTEX (Benzene, Toluene, Ethylbenzene, and Xylene) has been proven to be a carcinogenic component. These pollutants can be easily absorbed and taken into the body via inhalation. With this background in mind, the present ...

Environmental health risk detection with GeogDetector

Human health is affected by many environmental factors. Geographical detector is software based on spatial variation analysis of the geographical strata of variables to assess the environmental risks to human health: the risk detector indicates where the risk areas are; the factor detector identifies which factors are responsible for the risk; the ecological detector discloses the relative impo...

Statmap-a 3-dimensional model for oil spill risk assessment

Stochastic oil spill models have traditionally focussed on the production of statistics for oil on the sea surface and along shorelines. Environmental risk analyses of potential spills therefore have tended to neglect potential risks to organisms in the water column. StatMap fills this void, supplying in addition statistics on the spatial distribution of hydrocarbon concentrations in the water ...

Probabilistic runoff volume forecasting in risk-based optimization for RTC of urban drainage systems

Modelling Uncertainty and Variability in Environmental Systems

Scientists from different disciplines now routinely work together on complex, multi-interactive, geochemical and biochemical environmental processes and it has become necessary to define a common language that can be understood by all the relevant scientific community. This in turn will aid the transfer of expertise between scientists from different disciplines. This paper attempts to relate di...

Modelling bryophytes distribution pattern using environmental parameters of Iran in Geographical Information Systems (GIS): a case study of three genera Tortula, Grimmia and Bryum (Bryophyta)

In the present study, a modelling approach based on Geographical Information Systems (GIS) analysis is presented with the aim of identifying the influence of environmental parameters on three genera, namely, Tortula, Grimmia and Bryum as representatives of Iranian bryoflora. By using ArcGIS Desktop, we produced a model for environmental variables include altitude, precipitation, temperature and...