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Studies have investigated the effects of heat and temperature variability (TV) on mortality. However, few assessed whether TV modifies the heat-mortality association. Data on daily temperature and mortality in the warm season were collected from 717 locations across 36 countries. TV was calculated as the standard deviation of the average of the same and previous days' minimum and maximum temperatures. We used location-specific quasi-Poisson regression models with an interaction term between the cross-basis term for mean temperature and quartiles of TV to obtain heat-mortality associations under each quartile of TV, and then pooled estimates at the country, regional, and global levels. Results show the increased risk in heat-related mortality with increments in TV, accounting for 0.70% (95% confidence interval [CI]: -0.33 to 1.69), 1.34% (95% CI: -0.14 to 2.73), 1.99% (95% CI: 0.29-3.57), and 2.73% (95% CI: 0.76-4.50) of total deaths for Q1-Q4 (first quartile-fourth quartile) of TV. The modification effects of TV varied geographically. Central Europe had the highest attributable fractions (AFs), corresponding to 7.68% (95% CI: 5.25-9.89) of total deaths for Q4 of TV, while the lowest AFs were observed in North America, with the values for Q4 of 1.74% (95% CI: -0.09 to 3.39). TV had a significant modification effect on the heat-mortality association, causing a higher heat-related mortality burden with increments of TV. Implementing targeted strategies against heat exposure and fluctuant temperatures simultaneously would benefit public health., This study was supported by the Australian Research Council (DP210102076) and the Australian National Health and Medical Research Council (APP2000581). Y.W and B.W. were supported by the China Scholarship Council (nos. 202006010044 and 202006010043); S.L. was supported by an Emerging Leader Fellowship of the Australian National Health and Medical Research Council (no. APP2009866); Y.G. was supported by Career Development Fellowship (no. APP1163693) and Leader Fellowship (no. APP2008813) of the Australian National Health and Medical Research Council; J.K. and A.U. were supported by the Czech Science Foundation (project no. 20–28560S); N.S. was supported by the National Institute of Environmental Health Sciences-funded HERCULES Center (no. P30ES019776); Y.H. was supported by the Environment Research and Technology Development Fund (JPMEERF15S11412) of the Environmental Restoration and Conservation Agency; M.d.S.Z.S.C. and P.H.N.S. were supported by the São Paulo Research Foundation (FAPESP); H.O. and E.I. were supported by the Estonian Ministry of Education and Research (IUT34–17); J.M. was supported by a fellowship of Fundação para a Ciência e a Tecnlogia (SFRH/BPD/115112/2016); A.G. and F.S. were supported by the Medical Research Council UK (grant ID MR/R013349/1), the Natural Environment Research Council UK (grant ID NE/R009384/1), and the EU’s Horizon 2020 project, Exhaustion (grant ID 820655); A.S. and F.d.D. were supported by the EU’s Horizon 2020 project, Exhaustion (grant ID 820655); V.H. was supported by the Spanish Ministry of Economy, Industry and Competitiveness (grant ID PCIN-2017–046); and A.T. by MCIN/AEI/10.13039/501100011033 (grant CEX2018-000794-S). Statistics South Africa kindly provided the mortality data, but had no other role in the study.

Minimum mortality temperature (MMT) is an important indicator to assess the temperature-mortality association, indicating long-term adaptation to local climate. Limited evidence about the geographical variability of the MMT is available at a global scale.

Climate change affects human health; however, there have been no large-scale, systematic efforts to quantify the heat-related human health impacts that have already occurred due to climate change. Here, we use empirical data from 732 locations in 43 countries to estimate the mortality burdens associated with the additional heat exposure that has resulted from recent human-induced warming, during the period 1991–2018. Across all study countries, we find that 37.0% (range 20.5–76.3%) of warm-season heat-related deaths can be attributed to anthropogenic climate change and that increased mortality is evident on every continent. Burdens varied geographically but were of the order of dozens to hundreds of deaths per year in many locations. Our findings support the urgent need for more ambitious mitigation and adaptation strategies to minimize the public health impacts of climate change., We thank the participants of the ISIMIP Health workshop in Barcelona in November 2018 where this work was discussed for the first time. This study was supported by the Medical Research Council UK (grant no. MR/M022625/1), the Natural Environment Research Council UK (grant no. NE/R009384/1) and the European Union’s Horizon 2020 Project Exhaustion (grant no. 820655). N.S. was supported by the NIEHS-funded HERCULES Center (P30ES019776). Y.H. was supported by the Environment Research and Technology Development Fund of the Environmental Restoration and Conservation Agency, Japan (JPMEERF15S11412). J.J.J.K.J. was supported by Academy of Finland (grant no. 310372). V.H. was supported by the Spanish Ministry of Economy, Industry and Competitiveness (grant no. PCIN-2017-046) and the German Federal Ministry of Education and Research (grant no. 01LS1201A2). J.K. and A.U. were supported by the Czech Science Foundation (grant no. 20-28560S). J.M. was supported by the Fundação para a Ciência e a Tecnologia (FCT) (SFRH/BPD/115112/2016). S.R. and F.d.R. were supported by European Union’s Horizon 2020 Project EXHAUSTION (grant no. 820655). M.H. was supported by the Japan Science and Technology Agency as part of SICORP, grant no. JPMJSC20E4. Y.G. was supported by the Career Development Fellowship of the Australian National Health and Medical Research Council (APP1163693). S.L. was support by the Early Career Fellowship of the Australian National Health and Medical Research Council (APP1109193). Y.L.L.G. was supported by the Taiwan Ministry of Science and Technology (MOST110-2918-I-002-007) as a visiting academic at the University of Sydney.

Many regions of the world are now facing more frequent and unprecedentedly large wildfires. However, the association between wildfire-related PMFor this time series study, data on daily counts of deaths for all causes, cardiovascular causes, and respiratory causes were collected from 749 cities in 43 countries and regions during 2000-16. Daily concentrations of wildfire-related PM65·6 million all-cause deaths, 15·1 million cardiovascular deaths, and 6·8 million respiratory deaths were included in our analyses. The pooled RRs of mortality associated with each 10 μg/mShort-term exposure to wildfire-related PMAustralian Research Council, Australian National HealthMedical Research Council.

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.

Objective To evaluate the short term associations between nitrogen dioxide (NO2) and total, cardiovascular, and respiratory mortality across multiple countries/regions worldwide, using a uniform analytical protocol. Design Two stage, time series approach, with overdispersed generalised linear models and multilevel meta-analysis. Setting 398 cities in 22 low to high income countries/regions. Main outcome measures Daily deaths from total (62.8 million), cardiovascular (19.7 million), and respiratory (5.5 million) causes between 1973 and 2018. Results On average, a 10 μg/m3 increase in NO2 concentration on lag 1 day (previous day) was associated with 0.46% (95% confidence interval 0.36% to 0.57%), 0.37% (0.22% to 0.51%), and 0.47% (0.21% to 0.72%) increases in total, cardiovascular, and respiratory mortality, respectively. These associations remained robust after adjusting for co-pollutants (particulate matter with aerodynamic diameter ≤10 μm or ≤2.5 μm (PM10 and PM2.5, respectively), ozone, sulfur dioxide, and carbon monoxide). The pooled concentration-response curves for all three causes were almost linear without discernible thresholds. The proportion of deaths attributable to NO2 concentration above the counterfactual zero level was 1.23% (95% confidence interval 0.96% to 1.51%) across the 398 cities. Conclusions This multilocation study provides key evidence on the independent and linear associations between short term exposure to NO2 and increased risk of total, cardiovascular, and respiratory mortality, suggesting that health benefits would be achieved by tightening the guidelines and regulatory limits of NO2., HaK was supported by the National Natural Science Foundation of China (92043301, 82030103, and 91843302) and China Medical Board Collaborating Program (16-250). AG and FS were supported by the Medical Research Council, UK (MR/M022625/1), the Natural Environment Research Council, UK (NE/R009384/1), and the European Union’s Horizon 2020 Project Exhaustion (820655). VH was supported by the Spanish Ministry of Science and Innovation (PCIN-2017-046), and the German Federal Ministry of Education and Research (01LS1201A2). YH and MH were supported by the Environment Research and Technology Development Fund (JPMEERF15S11412) of the Environmental Restoration and Conservation Agency, Japan. JK and AU were supported by the Czech Science Foundation (18-22125S). ST was supported by the Shanghai Municipal Science and Technology Commission (18411951600). Y-LLG was supported by a Career Development Fellowship of the Australian National Health and Medical Research Council (APP1163693). SL was supported by an Early Career Fellowship of the Australian National Health and Medical Research Council (APP1109193). JJKJJ and NR were supported by the Academy of Finland (310372). The funders had no role in considering the study design or in the collection, analysis, interpretation of data, writing of the report, or decision to submit the article for publication.

Summary Background Many regions of the world are now facing more frequent and unprecedentedly large wildfires. However, the association between wildfire-related PM2·5 and mortality has not been well characterised. We aimed to comprehensively assess the association between short-term exposure to wildfire-related PM2·5 and mortality across various regions of the world. Methods For this time series study, data on daily counts of deaths for all causes, cardiovascular causes, and respiratory causes were collected from 749 cities in 43 countries and regions during 2000–16. Daily concentrations of wildfire-related PM2·5 were estimated using the three-dimensional chemical transport model GEOS-Chem at a 0·25° × 0·25° resolution. The association between wildfire-related PM2·5 exposure and mortality was examined using a quasi-Poisson time series model in each city considering both the current-day and lag effects, and the effect estimates were then pooled using a random-effects meta-analysis. Based on these pooled effect estimates, the population attributable fraction and relative risk (RR) of annual mortality due to acute wildfire-related PM2·5 exposure was calculated. Findings 65·6 million all-cause deaths, 15·1 million cardiovascular deaths, and 6·8 million respiratory deaths were included in our analyses. The pooled RRs of mortality associated with each 10 μg/m3 increase in the 3-day moving average (lag 0–2 days) of wildfire-related PM2·5 exposure were 1·019 (95% CI 1·016–1·022) for all-cause mortality, 1·017 (1·012–1·021) for cardiovascular mortality, and 1·019 (1·013–1·025) for respiratory mortality. Overall, 0·62% (95% CI 0·48–0·75) of all-cause deaths, 0·55% (0·43–0·67) of cardiovascular deaths, and 0·64% (0·50–0·78) of respiratory deaths were annually attributable to the acute impacts of wildfire-related PM2·5 exposure during the study period., Australian Research Council, Australian National Health & Medical Research Council.

The glacier system covering Europe's highest mountain, Elbrus, has exhibited an accelerated retreat since 1980. Some studies have related this retreat to a significant summer temperature increasing trend. Relief- and aspect-related parameters for the glacierized area have an important impact on glacier changes. In this paper, the changes in glacier area are identified, quantified and correlated with relief parameters for the period 1985–2007. Spatial analysis was performed using the GLAM-CD (Glacier Mapper – Change Detector) algorithm. The input data for this algorithm were Landsat 5 images, the Aster Global Digital Elevation and the glacier outlines from the GLIMS project (Global Land Ice Measurements from Space). Regression analyses between glacier area losses and relief-related parameters indicate a significant positive relation with the altitude and a significant negative relation with the glacier surface area. In this context, we used a correlated component regression to model these relations. The model explains >50% of the total variation.

This study proposes a new method designed to assess quantitative changes in mountain glaciers. The Glacier Mapper–Change Detector method has a four-step algorithm: i image ratioing on two time-comparable satellite images; ii digitization of glacier outlines from ratio images using a threshold value; iii change detection using the position of glacier outlines at two different moments in time; and iv derivation of the future evolution model by using relief-related parameters of glacier changes. The method was calibrated and verified for the Elbrus Greater Caucasus glacier over the period 1985–2007 using Landsat TM images. The Glacier Mapper–Change Detector results indicated altitude as the most important relief control for glacial retreat. The most probable future glacial area losses modelled reflect the 1985–2007 glacial retreat patterns.

Characterizing climatic changes in the high-altitude mountain regions helps scientists and policy makers understand the effects of such changes on water resources, economic development, and the health of ecosystems. This paper proposes a change-point analysis to determine the time and magnitude of summer temperature changes in the summit areas of Romanian Carpathians between 1961 and 2007. Due to their altitude, massiveness, and position, Romanian Carpathians are an important barrier for different types of air masses between Western and Southeastern Europe. The results show that the change in summer temperatures occurred shortly after 1980. The average magnitude of this change is consistent with changes occurring in other parts of Southern Europe in the same time period although the magnitude of changes at individual weather stations may differ substantially. We aided our analysis by a statistical method based on regression models with serially correlated ARMA errors.

Air temperature variability and trends in Romania were analysed using monthly, seasonal, and annual datasets. Temperature data of winter wheat season were also analysed. The Mann-Kendall test, Sen’s slope estimate, the sequential version of the Mann-Kendall test, the Pettitt test and spatial and temporal hierarchical cluster analyses were used. First, the datasets were checked for changing points. The 106-year period was divided into two long periods of 100 years each to verify the importance of a very short interval in changing of general trends; after that it was divided into three shorter periods of 35–36 years each. The main conclusions are as follows: the 6 years making up the difference between the two long periods are very important in the context of the recent global warming; the three shorter periods analysis indicate some fluctuations rather than continuous warming. The latest short period is the most relevant for global warming. Spatial hierarchical cluster analysis indicated the existence of two distinctive groups. One of them, which includes stations in the south-east part of the country, seems to be influenced by the Black Sea surface temperature. Temporal hierarchical cluster analysis reveals that annual data series have the closest relation with the summer data series. Further, the impact of temperature changes on winter wheat phenology was determined using a phenology simulation performed with the model from the Decision Support System for Agrotechnology Transfer v. 4.0.2.0 platform. Earlier occurrences of anthesis and maturity were noticed for several regions in the country.