- Concept for modelling of chemicals
- Landscape and Climate parameters
- Chemical emissions to different environmental compartments
- Physico-chemical properties of pollutants
- Modelling applications
- POPs (PCBs and PCDD/Fs)
- insecticides (Lindane).
- perfluorinated compounds (PFOS and PFOA)
- pyrethroid insecticides
- household used chemicals including pharmaceuticals.
The availability of pan-continental datasets allows the development of spatially explicit GIS based models for assessment of fate and distribution of pollutants into different environmental media e.g. atmosphere, soil, freshwater and sea. In principle, spatial models predict chemical concentration at a given location when the emissions to different media at continental scale are known. This is a typical "direct" formulation of fate problem aiming to answer the question "where do pollutants go?"
Vice versa, when the emissions of chemicals are unknown, but their concentrations are widely spread monitored, then the "inverse" modelling approach answers the question "where do pollutants come from?" by back tracing of emissions from measured concentrations and identifing possible sources of contamination discharges.
Both approaches are used in our modeling-based assessment of pollutant fate and impacts at continental and regional scales.
Persistent Organic Pollutants (POPs) resist to degradation through chemical, biological, and photolytic processes. Thus, POPs persist in the environment, are capable of long-range transport, bioaccumulate in human and animal tissue, biomagnify in food chains, and have potential significant impacts on human health and the ecosystems. POPs are often halogenated and characterised by low water but high lipid solubility, leading to their bioaccumulation in fatty tissues. They are also semi-volatile, enabling them to move long distances in the atmosphere before deposition occurs.
POPs are used currently or in the past as pesticides, herbicides and insecticides. Others are applied in industrial processes and in the production of goods such as solvents, polyvinyl chloride, and pharmaceuticals. Though there are a few natural sources of POPs actually most POPs are created by human activities, either intentionally or as byproducts.
Large scale screening modelling
The basic idea of MAPPE is to generate maps of chemical emissions and maps of environmental removal rates. Then, eventually to combine them using map algebra in order to obtain estimates of chemical mass and fluxes in different media.
Continental scale datasets
The model input consisits of data at European continental scale:
Data are available at the following link. Follow "Read more" to see a short description to each dataset.
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The atmospheric parameters dataset contains information about: air temperature, OH concentration, Aerosol concentration in air, Organic carbon content in aerosol, 10 m height wind velocity, Atmospheric mixing height, Precipitation, Duration of the wet period, Atmospheric Source-receptor relations and Atmospheric Source-receptor time of travel. The different data subsets vary in time scales and spatial resolution.
Soil and vegetation
The soil and vegetation dataset contains information about: top soil organic carbon content, soil texture, runoff, evapotranspiration, infiltration, erosion rate, Leaf Area Index (LAI). The different data subsets vary in time scales and spatial resolution.
The surface water dataset contains information about: river discharge, river slop, river water velocity, water depth, suspended sediment concentration, and surface water residence time. The different data subsets vary in time scales and spatial resolution.
Ocean and seas
The ocean and seas dataset contains information about: mixing depth, seawater velocity, seawater temperature, total suspended matter, wind speed at 10m height over ocean surface, and chlorophyll. The different data subsets vary in time scales and spatial resolution.
MAPPE, based on 'direct' modelling approach, has been used to assess at continental scale the fate of:
The environmental fate of other chemicals have been investigated using 'inverse' modelling approaches as applied to:
More details could be found in the 'publication' section.