Affiliation:
1. Faculty of Electrical Engineering, Mathematics & Computer Science Delft University of Technology Delft Netherlands
2. School of Mathematical Sciences University of Southampton Southampton UK
Abstract
AbstractRecycling centers sort and process collected waste in the interest of the environment, but also lead to damaging climate effects via released emissions and pollutants in their operation. Consequently, governments are closing such centers to fulfill climate and carbon neutrality goals. However, such closures risk populations being forced to travel further to facilities that collect waste, and can cause an unfair burden on the remaining open centers, thereby reducing participation in recycling. Using a facility location optimization model and mobility survey data within the state of Bavaria in Germany, we show how selective closures of these centers can still lead to high levels of recycling access. Our analysis ensures that even when 20% of facilities are closed smartly, the median travel distance by residents to their assigned recycling center increases by only 450 m. Additionally, we find Bavaria suffers from disparity in recycling patterns in rural and urban regions, both in terms of motivation to recycle and the locations of the facilities. We promote a policy that favors retention of recycling centers in rural regions by reserving 75% of open facilities to be in rural areas, while selectively closing facilities in urban regions, to remove these regional differences. Success of recycling campaigns depends on public perception of closures of such facilities and also on their ease of access. As policymakers gradually implement further closures, such data‐driven strategies can assist in being more transparent to the public thereby increasing the willingness to participate in such recycling programs.
Funder
Bayerisches Staatsministerium für Wissenschaft und Kunst
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