Polluting fuels and inefficient stove technologies are still a leading cause of premature deaths worldwide, particularly in low-income and middle-income countries. Previous studies of global household air pollution (HAP) have neither considered the estimation of PM_2·5 at national level nor the corresponding attributable mortality burden. Additionally, the effects of climate and ambient air pollution on the global estimation of HAP-PM_2·5 exposure for different urban and rural settings remain largely unknown. In this study, we include climatic effects to estimate the HAP-PM_2·5 exposure from different fuel types and stove technologies in rural and urban settings separately and the related attributable global mortality burden. Bayesian hierarchical models were developed to estimate an annual average HAP-PM_2·5 personal exposure and HAP-PM_2·5 indoor concentration (including both outdoor and indoor sources). Model variables were selected from sample data in 282 peer-reviewed studies drawn and updated from the WHO Global HAP dataset. The PM_2·5 exposure coefficients from the developed model were applied to the external datasets to predict the HAP-PM_2·5 exposure globally (personal exposure in 62 countries and indoor concentration in 69 countries). Attributable mortality rate was estimated using a comparative risk assessment approach. Using weighted averages, the national level 24 h average HAP-PM_2·5 exposure due to polluting and clean fuels and related death rate per 100 000 population were estimated. In 2020, household use of polluting solid fuels for cooking and heating led to a national-level average personal exposure of 151 μg/m³ (95% CI 133-169), with rural households having an average of 171 μg/m³ (153-189) and urban households an average of 92 μg/m³ (77-106). Use of clean fuels gave rise to a national-level average personal exposure of 69 μg/m³ (62-76), with a rural average of 76 μg/m³ (69-83) and an urban average of 49 μg/m³ (46-53). Personal exposure-attributable premature mortality (per 100 000 population) from the use of polluting solid fuels at national level was on average 78 (95% CI 69-87), with a rural average of 82 (73-90) and an urban average of 66 (57-75). The average attributable premature mortality (per 100 000 population) from the use of clean fuels at the national level is 62 (54-70), with a rural average of 66 (58-74) and an urban average of 52 (47-57). The estimated HAP-PM_2·5 indoor concentration shows that the use of polluting solid fuels resulted in a national-level average of 412 μg/m³ (95% CI 353-471), with a rural average of 514 μg/m³ (446-582) and an urban average of 149 μg/m³ (126-173). The use of clean fuels (gas and electricity) led to an average PM_2·5 indoor concentration of 135 μg/m³ (117-153), with a rural average of 174 μg/m³ (154-195) and an urban average of 71 μg/m³ (63-80). Using time-weighted HAP-PM_2·5 indoor concentrations, the attributable premature death rate (per 100 000 population) from the use of polluting solid fuels at the national level is on average 78 (95% CI 72-84), the rural average being 84 (78-91) and the urban average 60 (54-66). From the use of clean fuels, the average attributable premature death rate (per 100 000 population) at the national level is 59 (53-64), the rural average being 68 (62-74) and the urban average 45 (41-50). A shift from polluting to clean fuels can reduce the average PM_2·5 personal exposure by 53% and thereby lower the death rate. For all fuel types, the estimated average HAP-PM_2·5 personal exposure and indoor concentrations exceed the WHO's Interim Target-1 average annual threshold. Policy interventions are urgently needed to greatly increase the use of clean fuels and stove technologies by 2030 to achieve the goal of affordable clean energy access, as set by the UN in 2015, and address health inequities in urban-rural settings. Wellcome Trust, The Lancet Countdown, the Engineering and Physical Sciences Research Council, and the Natural Environment Research Council.

Many natural and man-made lineaments form networks that can be analysed through entropy and energy considerations. Here we report the results of a detailed study of the variations in trends and lengths of 1554 named streets and 6004 street segments, forming a part of the evolving street network of the city of Dundee in East Scotland. Based on changes in the scaling exponents (ranging from 0.24 to 3.89), the streets can be divided into 21 populations. For comparison, we analysed 221 active crustal fractures in Iceland that (a) are of similar lengths as the streets of Dundee; (b) are composed of segments; and (c) form evolving networks. The streets and fractures follow power-law size distributions (validated through various statistical tests) that can be partly explained in terms of the energies needed for their formation. The entropies of the 21 street populations and 9 fracture populations show strong linear correlations with (1) the scaling exponents (R² = 0.845–0.947 for streets, R² = 0.859 for fractures) and with (2) the length ranges, that is, the differences between the longest and shortest streets/fractures, (R² = 0.845–0.906 for streets, R² = 0.927 for fractures).

Geographical location and landforms of various types have strong effects on the developments of many cities and associated street networks. This study presents new results of landform effects, in particular the geometry of shorelines, on the grid street networks (a total of 10,442 streets) of three Brazilian coastal cities. The results are compared with the street networks of three coastal cities in Britain (a total of 22,002 streets) that have evolved through a more natural “bottom-up” process. Gibbs/Shannon entropy (a measure of dispersion) generally has a positive linear correlation with length ranges and the average lengths of the street, and for the power-law tails in particular. The geometry of the adjacent shorelines has great effect on the spatial orientation of streets in the Brazilian cities but less so for the networks of the British cities. More specifically, the more curved the shoreline, the greater is the dispersion in the street orientation and the greater the associated entropy. The results also show that the length-entropies of the outer parts of the Brazilian cities are generally lower than those of the inner parts, whereas the entropies of outer parts of the British cities are higher than those of the inner parts, indicating dispersion during street-network growth in the British cities.

With wind power providing an increasing amount of electricity worldwide, the quantification of its spatio-temporal variations and the related uncertainty is crucial for energy planners and policy-makers. Here, we propose a methodological framework which (1) uses machine learning to reconstruct a spatio-temporal field of wind speed on a regular grid from spatially irregularly distributed measurements and (2) transforms the wind speed to wind power estimates. Estimates of both model and prediction uncertainties, and of their propagation after transforming wind speed to power, are provided without any assumptions on data distributions. The methodology is applied to study hourly wind power potential on a grid of $$250\times 250$$250×250 m $$^{2}$$2 for turbines of 100 m hub height in Switzerland, generating the first dataset of its type for the country. We show that the average annual power generation per turbine is 4.4 GWh. Results suggest that around 12,000 wind turbines could be installed on all 19,617 km $$^{2}$$2 of available area in Switzerland resulting in a maximum technical wind potential of 53 TWh. To achieve the Swiss expansion goals of wind power for 2050, around 1000 turbines would be sufficient, corresponding to only 8% of the maximum estimated potential.

To establish a universal procedure to determine and predict the durability of components of PEM fuel cells in practical applications, it is desirable to assess the extent to which accelerated stress tests amplify cell degradation compared to lifetime tests. Experimental data from performance evaluation tests and open circuit voltage accelerated stress tests were compared to verify the ability for this type of accelerated test to provide a true measure of cell life. The performance evaluation tests involved 184 h total operation, including performance tests at 80 to 120°C and 35 to 100% RH as well as a stability test for 64 hours at 95°C/83% RH, 400 mA/cm² and 0.5 atm backpressure. The OCV ASTs involve operation at 90°C/30% RH and OCV for 100 h. Diagnostic tests conducted on the cells included hydrogen crossover, fluoride emission, catalyst electrochemical surface area, post-test membrane SEM and TEM evaluation, and defect identification in membranes. In general, the ASTs resulted in accelerated decay modes. The relationship between the deterioration during the performance tests and the ASTs was found to be a function of the Pt/C and PtCo/C electrode catalysts and different electrode ionomer types (1100 EW Nafion and 825 EW 3M) used.