Identifying optimal locations for minimal CO2 emissions
The Oulu region in Northern Finland established a project to create a model that identifies optimal locations for retail units with minimal CO2 emissions.
Projects such as this are helping the EU to become a smart, sustainable and inclusive economy by 2020, as set out in the EU 2020 growth strategy. The EU is facing some tough challenges, including an ageing population, an insufficiently qualified workforce, the need for greater innovation, striking a balance between economic growth and environmental degradation, and ensuring secure, clean energy supplies. Regional policy projects across the EU are playing an active role in dealing with these and many other challenges, by undertaking projects designed to generate employment, raise educational achievement, develop renewable energy sources, boost productivity and give all citizens access to opportunities. The projects and the regions play a pivotal role in this, as they generate real results that contribute to achieving the strategy’s key goals.
The project, which was implemented by the Department of Geography at the University of Oulu, used geographical information methods and numerical analysis to assess existing and planned store locations in terms of CO2 emissions from private cars.
A different angle on reducing CO2 from transport
According to the International Energy Agency (IEA), the transport sector produced 23% of total carbon dioxide emissions in 2007, with road transport making up almost three quarters of this portion. It is unsurprising then that policy-makers are increasingly concerned with reducing emissions from road transport. This project works from the perspective that these emissions can be reduced through planning and controlling land use.
In 2008, nearly 200 regionally significant retail trade projects were pending in various locations around Finland. Of these, 13 were focused in the Oulu region. The project team used road network data and population information, consisting of different socio-economic variables, to calculate theoretical CO2 emissions associated with different types of roads, thereby helping to identify the best location for these planned units.
One of the methods used in the project is known as origin-destination (OD) analysis. This essentially involves calculating the network distances between a set of origins (households in the area with at least one car) and a set of destinations (both existing retail units and the whole study area) along the least-cost route.
Using this OD analysis and applying GIS (geographical information system) tools, the team concluded that locating large retail units close to a city centre appears to be an optimal solution to reduce CO2 emissions from traffic.
Project manager, Heidi Määttä-Juntunen says, “As a whole, I see that the project had, and still has, a positive impact, since it introduced a new way to examine the locations of facilities and contributed to the discourse on how to minimise traffic emissions. There are a lot of viewpoints to consider in the planning process, but I see that the methods we used can provide the background information on the emissions effects for the city planners.”