The clean energy transition and large-scale deindustrialization have caused major changes in the industrial landscape of many high-income economies. This paper investigates how closures of large industrial facilities in Germany affect surrounding communities. By exploiting quasi-random variation in the timing of facility shutdowns, I analyze the neighborhood-level effects of these closures using data at the 1km x 1km grid cell level. I find that shutdowns of industrial sites lead to significant improvements in environmental amenities as represented by air quality. These environmental benefits, however, do not capitalize into increasing housing prices. Instead, housing values fall by up to 5% following facility shutdowns -a result that contrasts with existing evidence for the US context. Neighborhoods affected by industrial closures also experience substantial local downturns with average household income dropping by 4% in the most affected neighborhoods. The resulting total annual income loss attributable to facility shutdowns amounts to e0.7 -e1.9 billion. Using a simplified model of neighborhood choice, I further show that neighborhoods surrounding a closed industrial site become less amenable over time. These findings have important implications for place-based policies in the context of significant structural change. Additionally, using the newly assembled granular data, I reveal biases originating from the ecological fallacy in previous assessments of environmental inequality in Germany and show that there exists significant inequality in the exposure to fine particulate matter across the income distribution.