Sustainable Transport and Urban Inequality: A Mixed Methods Study of Selective Siting and Procedural Justice in Berlin

Katja Salomo, Sarah George, Vanessa Rösner and Viktoria Scheidler

No m5rvd_v1, SocArXiv from Center for Open Science

Abstract: Urban sustainability policies are widely promoted as key instruments for mitigating climate change and improving urban quality of life. At the same time, concerns have grown that such interventions may reproduce socio spatial inequalities through selec-tive siting, uneven benefits, and exclusionary planning processes. This paper examines both the distribution and lived experience of sustainable transport measures, combining a citywide spatial analysis with a qualitative neighborhood case study. Using 1 km × 1 km grid level data for Berlin, we analyze the socio economic correlates of multiple transport sustainability measures, including ride sharing stations, EV charging points, cycling infrastructure, traffic calming measures, and low traffic zones. Spatially Lagged X (SLX) models reveal policy specific patterns: infrastructure ena-bling alternative modes of transport tends to cluster in and around more affluent but also, in some cases, more diverse neighborhoods, while grids with higher child poverty are systematically less likely to feature traffic calmed street space. Low traffic zones are more prevalent in affluent areas, too. Complementary focus group discussions conducted during the implementation of a low-traffic zone show that residents from diverse and poorer neighborhoods as well as small business owners frequently interpret such street space interventions through the lens of gentrification and displacement. Participants describe feelings of alienation and criticize unclear communication and tokenistic participation. Our findings suggest that gentrification concerns may become a significant barrier to public support for urban sustainability transitions.

Date: 2026-10-23
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Persistent link: https://EconPapers.repec.org/RePEc:osf:socarx:m5rvd_v1

DOI: 10.31235/osf.io/m5rvd_v1

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