In this final entry, I will be delving into a research paper that addresses uneven noise pollution in Berlin, Germany from the angle of environmental justice. In Western European cities, noise pollution is recognised as a key source of environmental stress in relation to human health (Lakes et al., 2014). 

As the capital of Germany, Berlin has a population of around 3,400,000 inhabitants situated within 800 kilometres square, with residential areas being most densely populated in the central districts (Lakes et al., 2014). Lower-income neighbourhoods are mainly situated within earlier West Berlin inner-city regions and post-war high-rise housing estates while inhabitants with perceived higher socio-economic status are condensed in gentrified inner-city neighbourhoods and formerly high-income neighbourhoods (Lakes et al., 2014). 

As one of the greenest cities in Europe, Berlin is still greatly affected by noise pollution due to its densely built areas (Lakes et al., 2014). To address this multi-layered noise problem in Berlin, an environmental justice index – with a focus on distributional justice – was adopted to uncover the relationships between environmental burdens (different sources of noise pollution), environmental benefits (e.g. vegetation) and socio-economic inequality in its residential areas. 

 

Traffic noise data, which included road, air, railway and subway traffic, were acquired from strategic noise maps to better understand the spatiality of the environmental burden associated with noise. High-quality satellite imagery was then utilised to map out spatial variations in neighbourhood vegetation and its subsequent environmental benefits. A stakeholder workshop involving various educational and research institutions, which specialised in environmental justice concerns, was then conducted. Finally, socio-economic data  (e.g. unemployment rate) from the Berlin Senate Department of Urban Development’s social development indicator (SenStadt, 2010), was sieved out to analyse the socio-economic status across different urban neighbourhoods and subsequently integrated into the final environmental justice index.

In doing so, the proposed environmental justice index was able to identify 22 planning units (5% of all the planning units sampled) in central Berlin which reflected low levels of environmental quality and perceived socio-economic status. These urban neighbourhoods were categorised as residential areas with high levels of environmental injustice (Lakes et al., 2014).

In identifying these ‘hotspots’ and ‘coldspots’ of environmental justice, the environmental justice index was then able to identify residential areas which suffered the most from the double burden of unhealthy neighbourhood living environments and socio-economic deprivation (Lakes et al., 2014). This will help government officials and other stakeholders to engage in more well-informed environmental decision-making strategies.

Moving forward, such environmental justice indexes can be supplemented with elements of procedural justice through the use of citizen science, which will not only empower marginalised socio-economic groups but allow policymakers to better understand the nuances of environmental and social issues. 

 

References:

Lakes, T., Brückner, M., & Krämer, A. (2014). Development of an environmental justice index to determine socio-economic disparities of noise pollution and green space in residential areas in Berlin. Journal of Environmental Planning and Management, 57(4), 538-556.

SenStadt. (2010). Monitoring soziale Stadtentwicklung (2010). Fortschreibung für den Zeitraum 2008–2009. Berlin: Senat für Stadtentwicklung.