Rüttenauer Tobias
University of Kaiserslautern, Erwin-Schrödinger-Str. 57, D-67663 Kaiserslautern, Germany.
Soc Sci Res. 2018 Feb;70:198-211. doi: 10.1016/j.ssresearch.2017.11.009. Epub 2017 Dec 7.
This study investigates the presence of environmental inequality in Germany and analyses its spatial pattern on a very fine grained level. Using the 2011 German census and pollution measures of the E-PRTR, the study relies on nearly 100,000 one squared km census cells over Germany. SLX and community-fixed SLX models incorporate spatial spillover-effects into the analysis to account for the spatial distribution of socio-demographic characteristics. Results reveal that the share of minorities within a census cell indeed positively correlates with the exposure to industrial pollution. Furthermore, spatial spillover effects are highly relevant: the characteristics of the neighbouring spatial units matter in predicting the amount of pollution. Especially within urban areas, clusters of high minority neighbourhoods are affected by high levels of environmental pollution. This highlights the importance of spatial clustering processes in environmental inequality research.
本研究调查了德国环境不平等的存在情况,并在非常精细的层面上分析其空间格局。该研究利用2011年德国人口普查数据和欧洲污染物排放与转移登记处(E-PRTR)的污染测量数据,基于德国近10万个一平方公里的人口普查单元展开。空间滞后模型(SLX)和社区固定效应空间滞后模型将空间溢出效应纳入分析,以考量社会人口特征的空间分布。结果显示,人口普查单元内少数群体的比例确实与工业污染暴露呈正相关。此外,空间溢出效应高度相关:相邻空间单元的特征在预测污染量方面至关重要。特别是在城市地区,少数群体聚居的社区集群受到高水平环境污染的影响。这凸显了空间集聚过程在环境不平等研究中的重要性。