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The Pollutants in the Urban Environment (PUrE) framework is designed to deal with real life scenarios. This project utilised models and data from the development of the Ecological Impact Assessment (EIA) framework to demonstrate that PUrE provides a robust modelling and decision framework for dealing with pollutants in urban areas.
Particulate matter contains a mixture of pollutants, but the effects have primarily been studied by size rather than by composition. Therefore, research on particles could be significantly improved by applying an updated and integrated approach.
For PUrE, the upper size of particles will be limited to those that can be readily transported via air dispersion or suspension in flowing water. This will involve a more thorough characterisation of the particles (e.g. chemical, physical, biological properties, etc.), mapping of sources and movements, and an integrated assessment of the associated human and ecological health effects/risks.
The Forest Research component will determine the composition and bioavailability of particulate contaminants and assess their associated risk to ecological health. There are two primary components:
Quantification of particulates in ecological receptors
This will use indicator vegetation species planted along a particulate gradient. The species selected will include those common in urban greening.
The vegetation tissue compartments will be analysed for their metal content, both before and after washing, to assess the amount of particulate adhered to the tissue surface and that transported within the plant.
In addition, a range of primary plant consumers will be used to assess the food-chain transport of particulate pollution. These will be related to air sampling data collected from the study sites.
Validation of models
The use of vegetation to mitigate particulate pollution has been recognised for a number of years. Models have been developed to predict the potential dry deposition of particles to urban tree planting.
This component of the project will validate and, if necessary, refine these models using air sampling data from an urban greenspace in London.
The results of this work will test existing models and refine those being developed during the development of the EIA framework and will provide a dataset for inclusion in the databases supporting the software.
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