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- ItemLearning from urban form to predict building heights(San Francisco, California, US : PLOS, 2020) Milojevic-DupontI, Nikola; Hans, Nicolai; Kaack, Lynn H.; Zumwald, Marius; Andrieux, François; de Barros Soares, Daniel; Lohrey, Steffen; PichlerI, Peter-Paul; Creutzig, FelixUnderstanding cities as complex systems, sustainable urban planning depends on reliable high-resolution data, for example of the building stock to upscale region-wide retrofit policies. For some cities and regions, these data exist in detailed 3D models based on real-world measurements. However, they are still expensive to build and maintain, a significant challenge, especially for small and medium-sized cities that are home to the majority of the European population. New methods are needed to estimate relevant building stock characteristics reliably and cost-effectively. Here, we present a machine learning based method for predicting building heights, which is based only on open-access geospatial data on urban form, such as building footprints and street networks. The method allows to predict building heights for regions where no dedicated 3D models exist currently. We train our model using building data from four European countries (France, Italy, the Netherlands, and Germany) and find that the morphology of the urban fabric surrounding a given building is highly predictive of the height of the building. A test on the German state of Brandenburg shows that our model predicts building heights with an average error well below the typical floor height (about 2.5 m), without having access to training data from Germany. Furthermore, we show that even a small amount of local height data obtained by citizens substantially improves the prediction accuracy. Our results illustrate the possibility of predicting missing data on urban infrastructure; they also underline the value of open government data and volunteered geographic information for scientific applications, such as contextual but scalable strategies to mitigate climate change.
- ItemAmbient carbon monoxide and daily mortality: a global time-series study in 337 cities(Amsterdam : Elsevier, 2021) Chen, Kai; Breitner, Susanne; Wolf, Kathrin; Stafoggia, Massimo; Sera, Francesco; Vicedo-Cabrera, Ana M.; Guo, Yuming; Tong, Shilu; Lavigne, Eric; Matus, Patricia; Valdés, Nicolás; Kan, Haidong; Jaakkola, Jouni J. K.; Ryti, Niilo R. I.; Huber, Veronika; Scortichini, Matteo; Hashizume, Masahiro; Honda, Yasushi; Nunes, Baltazar; Madureira, Joana; Holobâcă, Iulian Horia; Fratianni, Simona; Kim, Ho; Lee, Whanhee; Tobias, Aurelio; Íñiguez, Carmen; Forsberg, Bertil; Åström, Christofer; Ragettli, Martina S.; Guo, Yue-Liang Leon; Chen, Bing-Yu; Li, Shanshan; Milojevic, Ai; Zanobetti, Antonella; Schwartz, Joel; Bell, Michelle L.; Gasparrini, Antonio; Schneider, AlexandraBackground Epidemiological evidence on short-term association between ambient carbon monoxide (CO) and mortality is inconclusive and limited to single cities, regions, or countries. Generalisation of results from previous studies is hindered by potential publication bias and different modelling approaches. We therefore assessed the association between short-term exposure to ambient CO and daily mortality in a multicity, multicountry setting. Methods We collected daily data on air pollution, meteorology, and total mortality from 337 cities in 18 countries or regions, covering various periods from 1979 to 2016. All included cities had at least 2 years of both CO and mortality data. We estimated city-specific associations using confounder-adjusted generalised additive models with a quasi-Poisson distribution, and then pooled the estimates, accounting for their statistical uncertainty, using a random-effects multilevel meta-analytical model. We also assessed the overall shape of the exposure–response curve and evaluated the possibility of a threshold below which health is not affected. Findings Overall, a 1 mg/m3 increase in the average CO concentration of the previous day was associated with a 0·91% (95% CI 0·32–1·50) increase in daily total mortality. The pooled exposure–response curve showed a continuously elevated mortality risk with increasing CO concentrations, suggesting no threshold. The exposure–response curve was steeper at daily CO levels lower than 1 mg/m3, indicating greater risk of mortality per increment in CO exposure, and persisted at daily concentrations as low as 0·6 mg/m3 or less. The association remained similar after adjustment for ozone but was attenuated after adjustment for particulate matter or sulphur dioxide, or even reduced to null after adjustment for nitrogen dioxide. Interpretation This international study is by far the largest epidemiological investigation on short-term CO-related mortality. We found significant associations between ambient CO and daily mortality, even at levels well below current air quality guidelines. Further studies are warranted to disentangle its independent effect from other traffic-related pollutants.