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- ItemProjections of global warming-induced impacts on winter storm losses in the German private household sector(Dordrecht [u.a.] : Springer, 2013) Held, H.; Gerstengarbe, F.-W.; Pardowitz, T.; Pinto, J.G.; Ulbrich, U.; Born, K.; Donat, M.G.; Karremann, M.K.; Leckebusch, G.C.; Ludwig, P.; Nissen, K.M.; Österle, H.; Prahl, B.F.; Werner, P.C.; Befort, D.J.; Burghoff, O.We present projections of winter storm-induced insured losses in the German residential building sector for the 21st century. With this aim, two structurally most independent downscaling methods and one hybrid downscaling method are applied to a 3-member ensemble of ECHAM5/MPI-OM1 A1B scenario simulations. One method uses dynamical downscaling of intense winter storm events in the global model, and a transfer function to relate regional wind speeds to losses. The second method is based on a reshuffling of present day weather situations and sequences taking into account the change of their frequencies according to the linear temperature trends of the global runs. The third method uses statistical-dynamical downscaling, considering frequency changes of the occurrence of storm-prone weather patterns, and translation into loss by using empirical statistical distributions. The A1B scenario ensemble was downscaled by all three methods until 2070, and by the (statistical-) dynamical methods until 2100. Furthermore, all methods assume a constant statistical relationship between meteorology and insured losses and no developments other than climate change, such as in constructions or claims management. The study utilizes data provided by the German Insurance Association encompassing 24 years and with district-scale resolution. Compared to 1971-2000, the downscaling methods indicate an increase of 10-year return values (i.e. loss ratios per return period) of 6-35 % for 2011-2040, of 20-30 % for 2041-2070, and of 40-55 % for 2071-2100, respectively. Convolving various sources of uncertainty in one confidence statement (data-, loss model-, storm realization-, and Pareto fit-uncertainty), the return-level confidence interval for a return period of 15 years expands by more than a factor of two. Finally, we suggest how practitioners can deal with alternative scenarios or possible natural excursions of observed losses.
- ItemEditorial: Recurrence Analysis of Complex Systems Dynamics(Lausanne : Frontiers Media, 2020) beim Graben, Peter; Hutt, Axel; Marwan, Norbert; Uhl, Christian; Webber Jr., Charles L.[No abstract available]
- 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.