Recent Assignment and Accomplishment
A Complementary Tool to Established Protocols for Analysing Beach Litter
The project Deep Dive is a system for beach litter analysis and data collection in the Arctic. To solve the problem of beach litter, decisionmakers need to understand the sources and causes of litter. Most beach litter monitoring protocols do not provide this information., and the Deep Dive method is designed to fill this gap.
The Deep Dive method has been created as a complementary tool to established protocols for analysing beach litter, such as the OSPAR and Ocean Conservancy Protocol Ocean, that give useful information at a global and regional level, but have some limitations in guiding preventive measures at a local level. Deep Dive method will provide a better understanding of the sources of- and reasons behind litter ending up on Arctic shores. This portal will assist your beach litter Deep Dive. Additionally, it will promote dialogue with stakeholders to identify possible intervention points to prevent litter from entering the oceans.
While the next sections will give you some tips and provide useful links on the process as a whole, the main focus of the webpage is related to the specific litter categories typically found on Arctic beaches that give useful information about the sources of- and reasons behind items ending up as litter. The interactive tools developed for analysing beach litter will guide you through your Deep Dive.
May 9, 2023
A Unique Citizen Science PlastRiskToolbox
Recently we have launched a beta version of 'PlastRiskToolbox' project. The 'PlastRiskToolbox' is a methodology developed by a group of elite scientists to assess the quality of microplastic and microplastic environmental concentration and toxicity data.
I am responsible for converting their mathematical concept into an online version with python as the core technology. The toolbox will allow existing datasets and scientific publications to be evaluated against a defined set of criteria to ensure that only those of sufficient quality are selected for use in the risk assessment of microplastic and microplastic pollution. Although developed to facilitate risk assessment in Norway, the toolbox can be applied to data generated for any geographical region, including global risk assessment.
May 9, 2023
The Global Tailings Portal Dashboard
It’s another exciting project The Global Tailings Portal is based on charts and the Django stack is the core technology. This is a kind of unique free, searchable database with detailed information on more than 1,800 mine tailings dams around the world. It enables users to sort data about tailings dams by location, company, dam type, height, volume, and risk, among other factors. The data was submitted by more than 100 of the world’s largest mining companies, in response to requests from institutional investors. Previously, very little information about mine tailings dams was publicly available. The portal is designed to be used by governments, scientists, the finance community, the mining industry, media, and civil society.
This current “beta” version of the portal is still undergoing testing, development, and verification.
May 9, 2023
WebGIS Application for Arctic Window
This is incredible to see how the open-source software stack plays a vital role in arctic data communication in the Arctic Passion project. We recently lunch a beta version Arctic Window module which is based on a map-based application that provides a unique window and facilitates communication between the different piolet services.
The Pilot Services of the project mainly provide information in areas of societal and economic relevance that are presently inadequately served: food security, emergency preparedness, wildfire and pollution risk reduction, environmental change information, and infrastructure, transport, and safe shipping.
Since the Arctic Window of this module is in its juvenile stage but an exciting part, it’s all the data and its visualizations are available to the public domain. Soon we will see some more exciting data on the platform which is more dynamic and near-real-time such as sea ice, temperature data etc will solve the bigger hidden problem of the Arctic.
May 9, 2023