Cooling cities through urban green infrastructure: a health impact assessment of European cities.

BACKGROUND: High ambient temperatures are associated with many health effects, including premature mortality. The combination of global warming due to climate change and the expansion of the global built environment mean that the intensification of urban heat islands (UHIs) is expected, accompanied by adverse effects on population health. Urban green infrastructure can reduce local temperatures. We aimed to estimate the mortality burden that could be attributed to UHIs and the mortality burden that would be prevented by increasing urban tree coverage in 93 European cities. METHODS: We did a quantitative health impact assessment for summer (June 1-Aug 31), 2015, of the effect of UHIs on all-cause mortality for adults aged 20 years or older in 93 European cities. We also estimated the temperature reductions that would result from increasing tree coverage to 30% for each city and estimated the number of deaths that could be potentially prevented as a result. We did all analyses at a high-resolution grid-cell level (250 × 250 m). We propagated uncertainties in input analyses by using Monte Carlo simulations to obtain point estimates and 95% CIs. We also did sensitivity analyses to test the robustness of our estimates. FINDINGS: The population-weighted mean city temperature increase due to UHI effects was 1·5°C (SD 0·5; range 0·5-3·0). Overall, 6700 (95% CI 5254-8162) premature deaths could be attributable to the effects of UHIs (corresponding to around 4·33% [95% CI 3·37-5·28] of all summer deaths). We estimated that increasing tree coverage to 30% would cool cities by a mean of 0·4°C (SD 0·2; range 0·0-1·3). We also estimated that 2644 (95% CI 2444-2824) premature deaths could be prevented by increasing city tree coverage to 30%, corresponding to 1·84% (1·69-1·97) of all summer deaths. INTERPRETATION: Our results showed the deleterious effects of UHIs on mortality and highlighted the health benefits of increasing tree coverage to cool urban environments, which would also result in more sustainable and climate-resilient cities. FUNDING: GoGreenRoutes, Spanish Ministry of Science and Innovation, Institute for Global Health, UK Medical Research Council, European Union's Horizon 2020 Project Exhaustion.

Author Correction: A rasterized building footprint dataset for the United States.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

A rasterized building footprint dataset for the United States.

Microsoft released a U.S.-wide vector building dataset in 2018. Although the vector building layers provide relatively accurate geometries, their use in large-extent geospatial analysis comes at a high computational cost. We used High-Performance Computing (HPC) to develop an algorithm that calculates six summary values for each cell in a raster representation of each U.S. state, excluding Alaska and Hawaii: (1) total footprint coverage, (2) number of unique buildings intersecting each cell, (3) number of building centroids falling inside each cell, and area of the (4) average, (5) smallest, and (6) largest area of buildings that intersect each cell. These values are represented as raster layers with 30 m cell size covering the 48 conterminous states. We also identify errors in the original building dataset. We evaluate precision and recall in the data for three large U.S. urban areas. Precision is high and comparable to results reported by Microsoft while recall is high for buildings with footprints larger than 200 m2 but lower for progressively smaller buildings.