Find out about the projects that applied below
Earthwatch are bringing stakeholders together on the issue of plastic pollution, mapping the pathways from source to sea and inspiring action to address this urgent challenge. We have recently conducted two large studies, on which we are basing our research into solutions. The first looks at “Microplastics: The risks to business”, and the second on “Plastic Rivers: reducing the plastic pollution on our doorstep”. We are looking to collaborate with business, other NGOs, policy makers and the public to develop innovative and impactful projects.
We are encouraging individuals to make a plastic pledge to reduce their plastic footprint from the “Top Ten” worst offenders, to track their success and tell us what they have done with #PlasticRivers. We have an action map, a series of infographics and pledge sheet to help them choose their pledges.
Project Location: UK, with hopes to expand in the future
Centre for Ecology and Hydrology
At the Centre for Ecology and Hydrology we are carrying out scientific research to understand the sources, accumulation and ecological effects of microplastics in soils and freshwaters. This research allows us to identify and communicate where microplastics come from (for example degradation of plastic litter) and the implications of such microplastic pollution, enabling people to make informed and effective choices about their day-to-day use and disposal of plastics. Additionally, we provide this evidence to regulators to guide policy decisions on use and management of plastics to ultimately reduce input to the environment. We also run the UK Microplastics knowledge exchange network.
Project location: International
Website: www.ceh.ac.uk and www.ukmicroplasticsnetwork.co.uk
King's College London
We focus on land based movement of litter in an urban environment; trying to discover the pathways which litter takes from land to sea. We would like to collaborate with others who not only share an interest in litter, but have skills in machine learning to model the data we collect and generate accurate projections.