2008, Peters, D.H.W., Gabriel, A., Entzian, G.

This study examines the longitude-dependent decadal changes and trends of ozone for the boreal winter months during the period of 1960–2000. These changes are caused primarily by changes in the planetary wave structure in the upper troposphere and lower stratosphere. The decadal changes and trends over 4 decades of geopotential perturbations, defined as a deviation from the zonal mean, are estimated by linear regression with time. The decadal changes in longitude-dependent ozone were calculated with a simple transport model of ozone based on the known planetary wave structure changes and prescribed zonal mean ozone gradients. For December of the 1960s and 1980s a statistically significant Rossby wave track appeared over the North Atlantic and Europe with an anticyclonic disturbance over the Eastern North Atlantic and Western Europe, flanked by cyclonic disturbances. In the 1970s and 1990s statistically significant cyclonic disturbances appeared over the Eastern North Atlantic and Europe, surrounded by anticyclonic anomalies over Northern Africa, Central Asia and Greenland. Similar patterns have been found for January. The Rossby wave track over the North Atlantic and Europe is stronger in the 1980s than in the 1960s. For February, the variability of the regression patterns is higher. For January we found a strong alteration in the modelled decadal changes in total ozone over Central and Northern Europe, showing a decrease of about 15 DU in the 1960s and 1980s and an increase of about 10 DU in the 1970s and 1990s. Over Central Europe the positive geopotential height trend (increase of 2.3 m/yr) over 40 years is of the same order (about 100 m) as the increase in the 1980s alone. This is important to recognize because it implies a total ozone decrease over Europe of the order of 14 DU for the 1960–2000 period, for January, if we use the standard change regression relation that about a 10-m geopotential height increase at 300 hPa is related to about a 1.4-DU total ozone decrease.

2021, Zhao, Qi, Guo, Yuming, Ye, Tingting, Gasparrini, Antonio, Tong, Shilu, Overcenco, Ala, Urban, Aleš, Schneider, Alexandra, Entezari, Alireza, Vicedo-Cabrera, Ana Maria, Zanobetti, Antonella, Analitis, Antonis, Zeka, Ariana, Tobias, Aurelio, Nunes, Baltazar, Alahmad, Barrak, Armstrong, Ben, Forsberg, Bertil, Pan, Shih-Chun, Íñiguez, Carmen, Ameling, Caroline, De la Cruz Valencia, César, Åström, Christofer, Houthuijs, Danny, Dung, Do Van, Royé, Dominic, Indermitte, Ene, Lavigne, Eric, Mayvaneh, Fatemeh, Acquaotta, Fiorella, de'Donato, Francesca, Di Ruscio, Francesco, Sera, Francesco, Carrasco-Escobar, Gabriel, Kan, Haidong, Orru, Hans, Kim, Ho, Holobaca, Iulian-Horia, Kyselý, Jan, Madureira, Joana, Schwartz, Joel, Jaakkola, Jouni J. K., Katsouyanni, Klea, Hurtado Diaz, Magali, Ragettli, Martina S., Hashizume, Masahiro, Pascal, Mathilde, de Sousa Zanotti Stagliorio Coélho, Micheline, Valdés Ortega, Nicolás, Ryti, Niilo, Scovronick, Noah, Michelozzi, Paola, Matus Correa, Patricia, Goodman, Patrick, Nascimento Saldiva, Paulo Hilario, Abrutzky, Rosana, Osorio, Samuel, Rao, Shilpa, Fratianni, Simona, Dang, Tran Ngoc, Colistro, Valentina, Huber, Veronika, Lee, Whanhee, Seposo, Xerxes, Honda, Yasushi, Guo, Yue Leon, Bell, Michelle L., Li, Shanshan

Background: Exposure to cold or hot temperatures is associated with premature deaths. We aimed to evaluate the global, regional, and national mortality burden associated with non-optimal ambient temperatures. Methods: In this modelling study, we collected time-series data on mortality and ambient temperatures from 750 locations in 43 countries and five meta-predictors at a grid size of 0·5° × 0·5° across the globe. A three-stage analysis strategy was used. First, the temperature–mortality association was fitted for each location by use of a time-series regression. Second, a multivariate meta-regression model was built between location-specific estimates and meta-predictors. Finally, the grid-specific temperature–mortality association between 2000 and 2019 was predicted by use of the fitted meta-regression and the grid-specific meta-predictors. Excess deaths due to non-optimal temperatures, the ratio between annual excess deaths and all deaths of a year (the excess death ratio), and the death rate per 100 000 residents were then calculated for each grid across the world. Grids were divided according to regional groupings of the UN Statistics Division. Findings: Globally, 5 083 173 deaths (95% empirical CI [eCI] 4 087 967–5 965 520) were associated with non-optimal temperatures per year, accounting for 9·43% (95% eCI 7·58–11·07) of all deaths (8·52% [6·19–10·47] were cold-related and 0·91% [0·56–1·36] were heat-related). There were 74 temperature-related excess deaths per 100 000 residents (95% eCI 60–87). The mortality burden varied geographically. Of all excess deaths, 2 617 322 (51·49%) occurred in Asia. Eastern Europe had the highest heat-related excess death rate and Sub-Saharan Africa had the highest cold-related excess death rate. From 2000–03 to 2016–19, the global cold-related excess death ratio changed by −0·51 percentage points (95% eCI −0·61 to −0·42) and the global heat-related excess death ratio increased by 0·21 percentage points (0·13–0·31), leading to a net reduction in the overall ratio. The largest decline in overall excess death ratio occurred in South-eastern Asia, whereas excess death ratio fluctuated in Southern Asia and Europe. Interpretation: Non-optimal temperatures are associated with a substantial mortality burden, which varies spatiotemporally. Our findings will benefit international, national, and local communities in developing preparedness and prevention strategies to reduce weather-related impacts immediately and under climate change scenarios. Funding: Australian Research Council and the Australian National Health and Medical Research Council. © 2021 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license